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Rice: Importance for Global Nutrition

Affiliations.

• 1 USDA, ARS, Beltsville Human Nutrition Research Center.
• 2 USDA, ARS, Adaptive Cropping Systems Laboratory.
• PMID: 31619630
• DOI: 10.3177/jnsv.65.S2

Rice, a staple food for more than half of the world's population, is grown in >100 countries with 90% of the total global production from Asia. Although there are more than 110,000 cultivated varieties of rice that vary in quality and nutritional content, after post-harvest processing, rice can be categorized as either white or brown. Regional and cultural preferences as well as need for stability during storage and transport are the final determinants of market availability and final consumption. In addition to calories, rice is a good source of magnesium, phosphorus, manganese, selenium, iron, folic acid, thiamin and niacin; but it is low in fiber and fat. Although brown rice is promoted as being "healthier" because of bioactive compounds, including minerals and vitamins not present in white rice after polishing, white rice is more widely consumed than brown. This is for several reasons, including cooking ease, palatability, and shelf life. Polished rice has a higher glycemic load and may impact glucose homeostasis but when combined with other foods, it can be considered part of a "healthy" plate. With the projected increase in the global population, rice will remain a staple. However, it will be important to encourage intake of the whole grain (brown rice) and to identify ways to harness the phytonutrients that are lost during milling. Furthermore, as the world faces environmental challenges, changing demographics and consumer demands, farmers, healthcare providers, food manufacturers and nutritionists must work collaboratively to assure adequate supply, nutritional integrity and sustainability of rice production systems globally.

Keywords: global nutrition; health; rice.

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Fortification of rice with vitamins and minerals for addressing micronutrient malnutrition

Rice fortification with vitamins and minerals has the potential to increase the nutrition in rice‐consuming countries where micronutrient deficiencies exist. Globally, 490 million metric tonnes of rice are consumed annually. It is the dominant staple food crop of around three billion people.

To determine the benefits and harms of rice fortification with vitamins and minerals (iron, vitamin A, zinc or folic acid) on micronutrient status and health‐related outcomes in the general population.

Search methods

We searched CENTRAL, MEDLINE, Embase, CINAHL, and 16 other databases all up to 10 December 2018. We searched ClinicalTrials.gov, and World Health Organization International Clinical Trials Registry Platform (ICTRP) on 10 December 2018.

Selection criteria

We included randomised and quasi‐randomised trials (with either individual or cluster randomisation) and controlled before‐and‐after studies. Participants were populations older than two years of age (including pregnant women) from any country. The intervention was rice fortified with at least one micronutrient or a combination of several micronutrients (iron, folic acid, zinc, vitamin A or other vitamins and minerals) compared with unfortified rice or no intervention.

Data collection and analysis

We used standard methodological procedures expected by Cochrane. Two review authors independently screened studies and extracted data.

Main results

We included 17 studies (10,483 participants) and identified two ongoing studies. Twelve included studies were randomised‐controlled trials (RCTs), with 2238 participants after adjusting for clustering in two cluster‐RCTs, and five were non‐randomised studies (NRS) with four controlled before‐and‐after studies and one cross‐sectional study with a control (8245 participants). Four studies were conducted in India, three in Thailand, two in the Philippines, two in Brazil, one each in Bangladesh, Burundi, Cambodia, Indonesia, Mexico and the USA. Two studies involved non‐pregnant, non‐lactating women and 10 involved pre‐school or school‐age children.

All 17 studies reported fortification with iron. Of these, six studies fortified rice with iron only; 11 studies had other micronutrients added (iron, zinc and vitamin A, and folic acid). One study had one arm each with vitamin A alone and carotenoid alone. Elemental iron content ranged from 0.2 to 112.8 mg/100 g uncooked rice given for a period varying from two weeks to 48 months.

Thirteen studies did not clearly describe either sequence generation or allocation concealment. Eleven studies had a low attrition rate. There was no indication of selective reporting in the studies. We considered two RCTs at low overall risk of bias and 10 at high overall risk of bias. One RCT was at high or unclear risk of bias for most of the domains. All controlled before‐and‐after studies had a high risk or unclear risk of bias in most domains. The included studies were funded by Government, private and non‐governmental organisations, along with other academic institutions. The source of funding does not appear to have altered the results. We used the NRS in the qualitative synthesis but we excluded them from the quantitative analysis and review conclusions since they provided mostly contextual information and limited quantitative information.

Rice fortified with iron alone or in combination with other micronutrients versus unfortified rice (no micronutrients added)

Fortification of rice with iron (alone or in combination with other micronutrients) may make little or no difference in the risk of having anaemia (risk ratio (RR) 0.72, 95% confidence interval (CI) 0.54 to 0.97; I 2 = 74%; 7 studies, 1634 participants; low‐certainty evidence) and may reduce the risk of iron deficiency (RR 0.66, 95% CI 0.51 to 0.84; 8 studies, 1733 participants; low‐certainty evidence). Rice fortification may increase mean haemoglobin (mean difference (MD) 1.83, 95% CI 0.66 to 3.00; I 2 = 54%; 11 studies, 2163 participants; low‐certainty evidence) and it may make little or no difference to vitamin A deficiency (with vitamin A as one of the micronutrients in the fortification arm) (RR 0.68, 95% CI 0.36 to 1.29; I 2 = 37%; 4 studies, 927 participants; low‐certainty evidence). One study reported that fortification of rice (with folic acid as one of the micronutrients) may improve serum or plasma folate (nmol/L) (MD 4.30, 95% CI 2.00 to 6.60; 215 participants; low‐certainty evidence). One study reported that fortification of rice with iron alone or with other micronutrients may slightly increase hookworm infection (RR 1.78, 95% CI 1.18 to 2.70; 785 participants; low‐certainty evidence). We are uncertain about the effect of fortified rice on diarrhoea (RR 3.52, 95% CI 0.18 to 67.39; 1 study, 258 participants; very low‐certainty evidence).

Rice fortified with vitamin A alone or in combination with other micronutrients versus unfortified rice (no micronutrients added)

One study had one arm providing fortified rice with vitamin A only versus unfortified rice. Fortification of rice with vitamin A (in combination with other micronutrients) may increase mean haemoglobin (MD 10.00, 95% CI 8.79 to 11.21; 1 study, 74 participants; low‐certainty evidence). Rice fortified with vitamin A may slightly improve serum retinol concentration (MD 0.17, 95% CI 0.13 to 0.21; 1 study, 74 participants; low‐certainty evidence).

No studies contributed data to the comparisons of rice fortification versus no intervention. The studies involving folic acid and zinc also involved iron in the fortification arms and hence we reported them as part of the first comparison.

Authors' conclusions

Fortification of rice with iron alone or in combination with other micronutrients may make little or no difference in the risk of having anaemia or presenting iron deficiency and we are uncertain about an increase in mean haemoglobin concentrations in the general population older than 2 years of age. Fortification of rice with iron and other micronutrients such as vitamin A or folic acid may make little or no difference in the risk of having vitamin A deficiency or on the serum folate concentration. There is limited evidence on any adverse effects of rice fortification.

Plain language summary

What is the aim of this review?

The aim of this Cochrane Review was to assess whether rice fortification with one or more vitamins and minerals in the general population aged two years or older improves nutritional status.

Key messages

Fortification of rice with iron alone or in combination with other micronutrients may make little or no difference in the risk of having anaemia but probably reduces the risk of iron deficiency and increases mean haemoglobin concentrations in population aged two years or above. If vitamin A is added, it may reduce the risk of having vitamin A deficiency and when folic acid is added, fortified rice may slightly increase serum folate concentrations.

What was studied in this review?

Micronutrient malnutrition compromises the health and well‐being of populations in many low‐ and middle‐income countries. Fortification is the addition of nutrients to foods to improve their nutritional quality. Rice is widely consumed as a staple food and is suitable for adopting as a food vehicle for fortification. This review addresses the benefits and harms of rice fortification with vitamins and minerals on micronutrient status along with health‐related outcomes, among participants aged two years and above, in addition to outcomes relevant to deficiencies in iron, vitamin A, zinc and folate.

What are the main results of the review?

We identified 17 studies (involving 10,483 participants) from Bangladesh, Brazil, Burundi, Cambodia, India, Indonesia, Mexico, Philippines, Thailand and USA. Twelve were randomised studies (2238 participants); 10 involved children, and two studies involved non‐pregnant non‐lactating women. In addition to iron, some studies had vitamin A, zinc or folic acid as fortifying agents, alone or in combination. Five non‐randomised studies (8245 participants), were assessed to augment the information on implementation and impact of fortification. The included studies were funded by government, private and non‐governmental organisations, along with other academic institutions. The source of funding does not appear to have altered the results.

We are uncertain about whether rice fortification with iron and other micronutrients reduces the risk of having anaemia although this intervention may increase mean haemoglobin concentrations (a biomarker of anaemia). We are uncertain if fortification of rice with iron alone or in combination with other micronutrients as compared to without any fortification, reduces the risk of iron deficiency.

Furthermore, consumption of vitamin A in the fortified rice, may make little difference on haemoglobin and serum retinol concentrations (a biomarker of vitamin A nutrition). We do not know whether fortification of rice has any adverse effects, in the mid‐ or long‐term, as the evidence was very limited. We found that the overall certainty of the evidence ranged from very low to low. Also, all studies used iron to fortify rice, so the effect of isolated nutrients may be hidden. There was no significant publication bias across the studies.

How up‐to‐date is this review?

The review authors searched for studies that had been published up to 10 December 2018.

Summary of findings

Summary of findings for the main comparison.

1 Downgraded 2 levels: one for serious limitations in study design or execution (risk of bias) and one for indirectness. The baseline characteristics were not similar in all groups and the method of randomisation was unclear in half of the studies. Also studies used different cut‐off levels of haemoglobin to define anaemia. Hardinsyah 2016 ; Parker 2015 (C) ; Perignon 2016 (C) ; Radhika 2011 used WHO cut‐off levels, Hotz 2008 used CDC criteria and Angeles‐Agdeppa 2008 and Thankachan 2012 did not name the criteria they used. 2 Downgraded 2 levels: one for serious limitations in study design or execution (risk of bias) and one for indirectness as most of the studies, except one ( Hotz 2008 ), were conducted in children. There was negligible inconsistency among the studies. 3 Downgraded 2 levels: one for serious limitations in study design or execution (risk of bias) and one for indirectness. Most of the included studies (except Hotz 2008 ; Losso 2017 ) were carried out among children. Losso 2017 was carried out in USA, which is a different study setting as compared to all other studies included. 4 Downgraded 2 levels: one for serious risk of bias and one for inconsistency. Findings from the studies crossed line of no effect except one study ( Thankachan 2012 ), which showed clear benefit due to fortification. 5 Downgraded 2 levels for risk of bias being serious in the included study ( Hardinsyah 2016 ), having selection bias, reporting bias and presence of other bias. 6 Downgraded 2 levels: one for inconsistency and one for indirectness. Only one study in children assessed this adverse effect of hookworm infection in an endemic setting to soil‐transmitted helminth infections among participating children ( Perignon 2016 (C) ). 7 Downgraded 3 levels: one for inconsistency, one for indirectness and one for imprecision. Only one study in children reported on this outcome and assessed it through asking participating children about symptoms and signs during the previous week ( Thankachan 2012 ). Wide confidence intervals.

Summary of findings 2

1 Downgraded by 2 levels: one level for risk of bias and one level for indirectness. The only study was carried out in India with a small sample size (250 children aged 5‐8 years) attending a school with a subsidised lunch feeding programme ( Hussain 2014 ).

Description of the condition

Adequate vitamin and mineral nutrition is required for optimal growth and development of children and for the maintenance of adequate health and nutrition of adult populations. Vitamin and mineral deficiencies may result in conditions such as anaemia, blindness, birth defects, retarded growth, diminished mental development and other poor health outcomes ( Howson 1998 ; Oakley 2004 ; Darnton‐Hill 2005 ; A2Z Project 2008 ). Micronutrient deficiencies have also long been demonstrated to increase the risk of morbidity and, in some cases, mortality, especially from infection ( Bhaskaram 2002 ; Singhal 2002 ; Black 2003 ). They also significantly and negatively impact on socioeconomic development at the individual, community and national levels ( Darnton‐Hill 2005 ). Iron, vitamin A, iodine and zinc deficiencies constitute the world’s most common micronutrient deficiencies ( WHO 2009b ).

The World Health Organization (WHO) estimates that approximately 1.6 billion people are anaemic worldwide with half being women and children under five years of age ( WHO 2015a ). It is estimated that in 2016, 41.7% of children, 40% of pregnant women and 32.5% of non‐pregnant women had anaemia ( Stevens 2013 ; WHO 2015a ; WHO 2019 ). Although anaemia can be caused by multiple factors, iron deficiency is estimated to account for up to 50% at least of the anaemia burden, making it the single most widespread nutritional deficiency in the world ( Graham 2001 ; Rastogi 2002 ; Stoltzfus 2011 ). Other conditions such as parasitic infections, inherited haemoglobin disorders, or nutritional deficiencies such as of folate or vitamin B 12 can also cause anaemia ( WHO 2017 ). Thus, low haemoglobin concentrations are indicators of both poor nutrition and poor health ( WHO 2011a ). Before birth and during the first years of life, iron deficiency affects growth, neurodevelopment and cognitive performance ( Lozoff 2006 ; Carter 2010 ), and may increase susceptibility to infections ( Scrimshaw 2010 ). In adults, iron deficiency and anaemia cause the loss of healthy and productive lives due to their effects on work and physical capacity ( Haas 1996 ). Pregnant women with iron deficiency are at higher risk of suboptimal pregnancy outcomes, including complications at delivery, low birthweight infants and preterm births ( Peña‐Rosas 2015 ).

Vitamin A deficiency causes xerophthalmia, which leads to night blindness and weakens the immune system, thereby increasing the risk of childhood morbidity and mortality ( Sommer 1996 ). Vitamin A deficiency may increase the risk of morbidity and mortality during infancy, pregnancy and in the postpartum period ( Sommer 1996 ; West 1999 ). It is estimated that vitamin A deficiency results in 18 million disability‐adjusted life years (DALYs) lost, a measure of overall disease burden that is expressed as the number of years lost due to ill‐health, disability or early death ( WHO 2002 ). Vitamin A deficiency occurs mostly after prolonged deprivation of this vitamin ( WHO/FAO 2004 ), and is a significant public health problem in many low‐ and middle‐income countries, most seriously affecting young children, women of reproductive age and pregnant women. According to recent estimates, 190 million preschool‐age children (under five years of age) and 19.1 million pregnant women have inadequate concentrations of retinol. Roughly 45% of all preschool‐age children and pregnant women with vitamin A deficiency live in the WHO regions of South‐East Asia, while Africa accounts for another 30% of cases ( WHO 2009b ). An analysis of trends of vitamin A deficiency showed a decline in the overall prevalence from 39% to 29% from 1991 to 2013, but Africa and South Asia had the least decline ( Stevens 2015 ). Vitamin A deficiency alone is responsible for almost 6% of child deaths under the age of five years in Africa and 8% in South‐East Asia ( WHO 2009a ). It was estimated that in 2013, 1.7% of all deaths in children younger than five years were attributable to vitamin A deficiency ( Stevens 2015 ).

Zinc deficiency is considered to be associated with morbidity and mortality in low‐ and middle‐income countries. Severe zinc deficiency in children may cause short stature, impaired immune function and other disorders, and is a significant cause of respiratory infections, malaria and diarrhoeal disease ( WHO 2002 ). Adequate zinc nutrition is essential for human health because of zinc’s critical structural and functional roles in multiple enzyme systems that are involved in gene expression, cell division and growth, and immunologic and reproductive functions ( Hess 2009 ). Although there is very limited national‐ or first administrative‐level survey data on the prevalence of zinc deficiency, it has been estimated that zinc deficiency is responsible for approximately 4% of child mortality and DALYs ( Black 2008 ). An estimated 17.3% of the global population is at risk of inadequate zinc intake. The regional estimated prevalence of inadequate zinc intake ranged from 7.5% in high‐income regions to 30% in South Asia. These country‐specific prevalences of inadequate zinc intake were calculated based on the estimated absorbable zinc content of the national food supply ( Wessells 2012 ).

Inadequate intake is a leading cause of folate deficiency and insufficiency in the population although increased requirements from pregnancy or neoplastic diseases, malabsorptive conditions, use of antifolate drugs or other metabolic inhibitors can also cause folate deficiency ( Bailey 2015 ). Inadequate periconceptional folate status and folic acid intake are associated with congenital malformations including neural tube defects ( IOM 2003 ). Folic acid is a synthetic form of folate used in supplements and fortified foods (like wheat and maize flour) to reduce the occurrence of neural tube defects (NTDs). These defects include spina bifida (or cleft spine), where there is an opening in one or more of the bones (vertebrae) of the spinal column and anencephaly where the head (cephalic) end of the neural tube fails to close. It has been demonstrated through controlled studies that the risk of neural tube defects can be substantially reduced (risk ratio (RR) 0.31, 95% confidence interval (CI) 0.17 to 0.58; 5 studies, 6708 births; high‐certainty evidence) with daily folic acid supplementation, alone or in combination with other vitamins and minerals ( De‐Regil 2015 ). The effectiveness of mandatory folic acid fortification in wheat flour programmes has also been documented by a decline in the prevalence of neural tube defects, in the USA, Canada, Costa Rica, Chile and South Africa ( Berry 2010 ). In general, populations from lower socioeconomic status do not consume sufficient high‐folate‐content foods, and although their diets may be adequate in folate intake to preventing clinical deficiency (i.e. megaloblastic anaemia), they may be insufficient to reach red blood cell folate concentrations associated with optimal health and fetal development (i.e. greatest NTD risk reduction) in women of reproductive age, that is concentrations above 400 ng/mL (906 nmol/L) ( WHO 2015b ).

Other vitamins and minerals

In addition to iron, vitamin A, zinc and folate deficiencies, those of iodine, calcium, vitamin B 12 and vitamin D impair health and development. For example, iodine deficiency is a major threat to the health and development of populations worldwide, particularly in preschool children and pregnant women, resulting in goitre, stillbirth and miscarriage, hypothyroidism, and impaired growth ( Andersson 2012 ). Vitamin D deficiency (defined as low concentrations of serum 25‐hydroxyvitamin D) may be a common health problem worldwide ( Bandeira 2006 ; Palacios 2014 ). A recent review found an important proportion of infants, children, adolescents, adults and older persons living in different countries with low serum vitamin D concentrations ( Palacios 2014 ). These low concentrations were seen in all age groups, but in particular in girls and women from the Middle East. Vitamin D deficiency and/or perturbations of vitamin D metabolism; very low chronic calcium intake or a combination of both vitamin D deficiency and low chronic calcium intake, can cause nutritional rickets. Rickets is mostly associated with very low calcium intake in older children while in adolescents, the studies suggest that nutritional rickets is more associated with vitamin D deficiency ( Munns 2016 ).

Intervention strategies for micronutrient malnutrition

Current recommended intervention strategies for the prevention and treatment of micronutrient deficiencies include either one or a combination of supplementation, food‐based approaches such as dietary diversification, mass food fortification or point‐of‐use food fortification; other public health control measures include deworming, health and nutrition education ( Howson 1998 ; Zimmermann 2007 ; WHO 2011c ). These strategies can be delivered through at least four platforms, the health systems, agriculture, market‐based, and social protection programmes ( Olney 2012 ). Supplementation is still the most widely practiced intervention to control iron ( WHO 2011b ; WHO 2011d ; WHO 2016 ) and vitamin A deficiencies in high‐risk populations ( WHO 2011e ).

Some adverse effects observed with high‐dose supplements, as well as active participation from users, may affect compliance and the long‐term sustainability of such programmes. Supplementation programmes ( Baltussen 2004 ; Alderman 2007 ), usually face logistical and human‐resource constraints, such as bad road networks and generally fragile institutions, which may hinder their effectiveness, especially in low‐ and middle‐income countries where the intervention is needed most ( Zimmermann 2007 ). In such cases, mass fortification of staple foods becomes an important option to combat vitamin and mineral deficiencies. There are fewer concerns related to mass food fortification and it can be a complementary intervention to supplementation for efforts to reduce vitamin and mineral deficiencies.

Meeting the recommended dietary intakes ( WHO/FAO 2004 ), through the daily diet is desirable but not always possible for many populations. Poor dietary diversity and dependence on cereal‐based diets, which are common in low‐ and middle‐income countries, are major contributing factors to the high prevalence of micronutrient deficiencies ( Welch 1999 ). Cereals, in addition to being poor sources of vitamins and minerals, also contain high quantities of other dietary compounds, such as phytates, which decrease the absorption of certain micronutrients, often called 'anti‐nutrients' ( Graham 2001 ). For instance, iron and zinc absorption is significantly inhibited by phytic acid, present in cereals and other grains; polyphenols, contained in red wine and chocolate; or calcium, abundant in dairy products ( Gibson 1998 ; Hurrell 2010 ; Kim 2011 ). On this basis, dietary bioavailability of iron has been estimated to be in the range of 14% to 18% for mixed diets and 5% to 12% for vegetarian diets.

Cereals, however, are overwhelmingly the major source of food supplies for direct human consumption. In 2014, around 2.5 billion tonnes of cereals were produced with roughly 1.1 billion tonnes (43%) used as food; around 900 million tonnes (35%) used as animal feed and the remaining 500 million tonnes were diverted to industrial usage or seed, or were wasted ( FAO 2016 ). While rice is produced in vast areas of the world, the physical requirements for growing this crop are limited to certain zones. Rice is the primary staple for more than half the world’s population. Production and consumption is greatest in Asia ( Muthayya 2014 ), and in recent years, it has also become an important staple in Africa ( FAO 2012 ). About 741 million tonnes of rice (paddy) were harvested in 2014 ( FAOSTAT 2016 ). The milled equivalent of rice produced is 490 million tonnes ( FAO 2016 ).

Description of the intervention

Fortification is “the addition of one or more essential nutrients to a food, whether or not it is normally contained in the food, for the purpose of preventing or correcting a demonstrated deficiency of one or more nutrients in the general population or specific population groups" ( Codex Alimentarius 1994 ). This process usually takes place during food processing by the food industry at a central level so that it reaches the intended population en masse and does not require the active participation of end users. While there are some different definitions for enrichment, for the purposes of this review, we used enrichment and fortification interchangeably.

Results of a study in Vietnamese school children showed that iron‐fortified rice noodles are efficacious in reducing anaemia and improving haemoglobin and iron status indicators ( Huong 2006 ). In places where rice is a staple food, iron fortification has been shown to reduce the prevalence of iron‐deficiency anaemia from 100% to 33% among preschool age children ( Angeles‐Agdeppa 2008 ), particularly when there is strong political support and intensive social marketing activities as well as efforts to keep the cost affordable (Angeles‐Agdeppa 2011). Zinc fortification of cereals can boost total zinc consumed daily and absorbed zinc in infants, young children and adults ( Brown 2007 ). Although less frequent, fortification of wheat and maize flours with vitamin A has the technological and biological potential to palliate this deficiency ( Klemm 2010 ). Perhaps the most well known area of micronutrient fortification is that of folic acid, in both wheat and maize flours, and its effect on the prevention of birth defects ( WHA 2010 ). Well conducted studies from several countries have documented decreases of 26% to 42% in the occurrence of neural tube defect (NTD)‐affected births after implementation of national regulations mandating wheat flour fortification with folic acid ( WHO 2009b ). Food fortification brings together the benefit of energy, fat and protein, and the complementary roles of vitamins and minerals to enhance the stability and bioavailability of vitamins and minerals used to fortify foods ( Best 2011 ). In addition, this strategy has a dual advantage of reaching a wider and larger proportion of the population than supplementation without requiring radical changes in food consumption patterns ( Howson 1998 ).

Food fortification practices vary nationally. The choice of nutrients (in this context also known as fortificants) varies according to their bioavailability. In the case of iron, for instance, many compounds such as ferrous sulphate, ferrous fumarate, ferric pyrophosphate and electrolytic iron powder can be used in food fortification ( WHO/FAO 2006 ). However, many cereal foods are fortified with low‐cost iron powders with absorption of iron lower than 2% ( Hurrell 2010 ). For vitamin A fortification, retinyl palmitate and acetate are frequently used while the synthetic form of folic acid is used to improve folate status.

A concern expressed by a few people about food fortification is related to the possible toxicity of excessive vitamins and minerals among all groups, particularly those that are not at risk of deficiencies ( Garcia‐Casal 2019 ). This is especially so with iron excess ( Gordeuk 1987 ), which may affect the risk of colonic adenomas and cancer ( Muthunayagam 2009 ), and a potentially more pathogenic gut microbiota that is associated with higher gut inflammation ( Zimmermann 2010 ). Excess and chronic vitamin A intake during pregnancy has been shown to increase the risk of teratogenicity ( Rothman 1995 ), and hip fracture ( Penniston 2003 ). A hypothetical association between the prolonged consumption of folic acid‐enriched cereals and the increase in the incidence of colorectal cancer in the USA and Canada ( Mason 2007 ), has been challenged with other studies where such an association has not been demonstrated ( EFSA 2009 ). Another concern may relate to the possibility of over‐consumption of rice given the potential benefits of additional vitamins and minerals. As a public health intervention, the use of a vehicle would imply not encouraging the population to consume greater amounts of the 'fortified' rice. Higher consumption of white rice is associated with a significantly increased risk of type 2 diabetes, especially in Asian (Chinese and Japanese) populations ( Hu 2012 ).

Micronutrient deficiencies of public health significance are all widespread in most high rice‐consuming countries ( Juliano 1993 ; MIcronutrient Initiative/UNICEF 2004 ), and rice fortification has the potential to fill an obvious gap in current nutrition programmes and help aid vulnerable populations that are currently out of reach. A fundamental requirement in the adoption of food fortification as a public health intervention is the selection of the most appropriate and suitable food that will serve as a vehicle for the extra nutrients. It needs to be eaten in large amounts by the target population and be affordable and available all year round ( Dexter 1998 ; WHO/FAO 2006 ). Although almost all foods can be fortified, cereals are widely grown, produced and consumed in low‐ and middle‐income countries ( Welch 1999 ), making them important vehicles for fortification. Improving the micronutrient content of cereals or their subproducts could provide a sustainable solution to the worldwide problem of micronutrient deficiencies, particularly in populations where there is a marked social characterisation of eating habits ( Prättälä 2012 ), and where the fortified foods will be reaching those in need of the vitamins and minerals. Poor children and their mothers systematically lag behind the better‐off in terms of mortality, morbidity and undernutrition. Evaluations of the equity impact of health programmes and nutrition interventions are scarce. There are, however, some results suggesting that innovative approaches can effectively promote equity through, for example, employing appropriate delivery channels; removing financial barriers; and monitoring implementation, coverage and impact with an equity lens. Mandatory fortification of staple foods being consumed by the most vulnerable segments of the populations would potentially provide vitamins and minerals to those in a vulnerable situation ( WHO 2010 ), although it is clear that tackling inequities requires the involvement of various programmes and stakeholders, both within and outside the health sector, that can help address social determinants ( WHO 2010 ).

How the intervention might work

Rice is a globally produced, milled and traded staple food with an annual production and consumption worldwide of about 490 million tonnes. It is the dominant staple food crop of around three billion people worldwide, providing up to 50% to 60% of their daily energy and protein intake ( IRRI 2010 ). Rice is cultivated in almost all parts of the world as it can grow in a wide range of soil and environmental conditions ( Juliano 1993 ). It is estimated that 90% of the world's rice is produced in Asia ( Juliano 1993 ; Muthayya 2014 ). China and India consume 50% of the world's rice and per capita consumption is highest in Asia ( Muthayya 2014 ). High consumption has been reported in Latin America and Caribbean countries as well as in sub‐Saharan Africa ( Muthayya 2014 ). With its popularity, reach and quantum of consumption, rice far exceeds the requirements for adoption as a vehicle for food fortification for the purposes of a population‐level intervention.

Globally, the main rice processing method is milling. The process is aimed at producing a maximum yield of unbroken milled rice compared to flour or meal in other cereals ( Dexter 1998 ). The process involves cleaning the paddy or rough rice (un‐hulled rice grain) and de‐hulling (removing hull, germ and bran layers) to produce brown rice ( Dexter 1998 ). Brown rice consists of an average weight of 6% to 7% bran, 90% endosperm and 2% to 3% embryo ( Saunders 1979 ). Further milling to remove the bran layer yields white rice. On average, paddy rice produces 25% hulls, 10% bran, and 65% white rice ( Chen 1998 ). In some countries the milled white rice is coated with talc and glucose to improve its appearance ( Dexter 1998 ). The various forms of rice are presented in Table 3 . Milled white rice is low in vitamins and minerals as these vitamins (B vitamins) and minerals (iron) are found predominately in the germ and bran layers ( Dexter 1998 ). Parboiling is one of the ways by which nutrients in the rice grain can be partially preserved. The parboiling process of soaking the rough rice, applying heat, drying and milling results in the transfer of nutrients to the inner endosperm layer from the bran before milling ( Dexter 1998 ). Parboiling is expensive and the end product, referred to as ‘golden colour rice’, may not be readily acceptable to consumers ( Dexter 1998 ). The different types rice are depicted in Table 3 .

Adapted from Dexter 1998 .

Previous attempts to fortify rice by simply adding a micronutrient powder to the rice that adheres to the grains by electrostatic forces (dusting) have proven unsuccessful ( Leon Guerrero 2009 ), due to the typical washing and cooking methods employed in most developing countries, which results in the rinsing away of the enrichment. Three more sophisticated methods have been developed to overcome this problem ( A2Z Project 2008 ). Coating involves spraying of the surface of ordinary rice grains in several layers with a vitamin and mineral mix to form a protective coating that will not easily rinse off the surface when washed ( Kyritsia 2011 ). The grains (fortified premix) contain high concentrations of vitamin and mineral fortificants and must be blended with natural rice (that is commonly 1 part fortified premix to 199 parts untreated milled rice) to produce fortified rice. The extrusion technology is a totally different concept in rice fortification. In hot extrusion, a dough made of rice flour, vitamin and mineral mix and water is passed through a single or twin screw extruder and shaped into partially precooked grain‐like structures resembling rice grains; that is then blended with natural polished rice at a ratio of about 1:200 to produce fortified rice. This process involves relatively high temperatures (70 to 110 °C) obtained by preconditioning or heat transfer through steam‐heated barrel jackets, or both. The cold extrusion follows a similar process at low temperature (below 70 °C) that does not primarily utilise any additional heat and produces uncooked, opaque fortified premix grains with a slightly softer consistency. This is then blended with natural polished rice at a ratio of about 1:200 to produce fortified rice.

Rice is a highly culturally‐sensitive commodity ( Hariyadi 2011 ). Growing, selecting and cooking of rice grains are subject to regional, national and even local preferences. It is estimated that a large proportion of key vitamins and minerals are lost during milling ( DSM/Buhler 2010 ). Additionally, rinsing and washing are common cooking methods which can potentially dissolve added or restored nutrients. There are many different ways of cooking rice. These are 1) soaking, and boiling with excess water; 2) boiling in excess water; 3) boiling without excess water; 4) rinsing and boiling without excess water; and 5) frying and boiling without excess water. The use of these cooking preparations could have different retentions of micronutrients in fortified rice kernels as some vitamins are sensitive to heat and others are water‐soluble ( WHO/FAO 2006 ). Cultural preferences for specific types of rice characteristics may represent a barrier to mass fortification in some settings. A technical challenge is to produce fortified rice that resembles natural rice and resists normal meal preparation and cooking processes.

A study conducted as far back as 1948 in the Philippines demonstrated the effects of rice fortification in the prevention of beriberi ( Salcedo 1950 ). In Brazil, a bioavailability study with vitamin A‐fortified rice showed an improvement in children's retinol levels ( Flores 1994 ). Another study among young children from 6 to 24 months of age in Brazil found that rice fortified with micronized iron pyrophosphate was more effective than iron drops in decreasing anaemia from 100% to 62%, and iron deficiency from 69% to 25%, and improving iron status ( Beinner 2010 ). In a study in India, fortified rice in school‐age children attending school showed a reduction of iron‐deficiency anaemia from 78% at baseline to 25% in the iron group ( Moretti 2006a ). In another setting, the feeding of rice fortified with microencapsulated, micronized iron pyrophosphate to improve the iron status of women in Mexico showed significant increases in plasma ferritin concentrations and estimated body iron stores as well as a significant decrease in plasma transferrin receptor concentrations. Fortified rice reduced the prevalence of anaemia by 80% and iron deficiency by 29% in Mexican women working in a factory ( Hotz 2008 ).

This review attempts to evaluate, based on existing research, the effectiveness of rice fortification as a public health intervention. The World Health Organization and Centers for Disease Control and Prevention (WHO/CDC) logic model for micronutrient interventions in public health depicts the programme theory and plausible relationships between inputs and expected improvements in Sustainable Development Goals and can be adapted to different contexts ( WHO/CDC 2016 ). The effectiveness of rice fortification in public health depends on several factors related to policies and legislation regulations; production and supply of the fortified rice; the development of delivery systems for the fortified rice; the development and implementation of external and internal food quality control systems; and the development and implementation of strategies for information, education and communication for behaviour change among consumers. A generic logic model for micronutrient interventions that depicts these processes and outcomes is presented in Figure 1 .

WHO/CDC logic model for micronutrients interventions in public health (with permission from WHO)

The high consumption of polished rice as a staple food in many settings has been associated with an increased risk of diabetes and other chronic diseases although the results of the studies have been conflicting. One systematic review and meta‐analysis has been published with respect to polished rice and diabetes studies ( Hu 2012 ), and another has been published with respect to rice and the incidence of chronic diseases including diabetes ( Saneei 2017 ). The earlier meta‐analysis included four prospective cohort studies and found that higher white rice consumption was associated with increased risk of developing type‐2 diabetes in comparison with lower intake levels (relative risk 1.27 (95% CI 1.04 to 1.54; Hu 2012 ). This association was stronger for Asian (Chinese and Japanese) populations, although the dose‐response relations indicated that even for Western populations with typically low intake levels, white rice consumption may still modestly increase risk of diabetes. A more recent meta‐analysis ( Saneei 2017 ), did not show an increased risk of diabetes with higher rice consumption due to an additional study from Spain ( Soriguer 2013 ), which showed that a negative association was found between white rice intake and the six‐year incidence of diabetes. No disaggregation of the estimates was done in Saneei 2017 for origin of population but both Hu 2012 and Saneei 2017 showed an increased risk of diabetes or chronic diseases among women who consumed more rice. Rice fortification policies may have to take into account the possible increased risk of diabetes and other diseases with rice consumption and identify fortification levels targeting existing rice consumption levels as has been done for salt iodisation and salt reduction policies ( WHO 2014 ). Additionally, the fortification of this staple food may affect acceptability of the fortified rice and thus potentially change dietary patterns ( Khanh 2014 ).

Why it is important to do this review

Vitamin and mineral deficiencies are important public health concerns worldwide. Among the options to address these deficiencies, mass fortification represents an appealing intervention as it takes advantage of the existing market and delivery systems, does not require the active participation of vulnerable populations to increase food intake or diversify the diet, and has few safety concerns. Rice represents a suitable vehicle for fortification as it is considered a staple food in most of the world, especially in regions where micronutrient deficiencies are most evident.

Wheat and maize flour fortification with iron alone, or in combination with folic acid and other micronutrients, has been implemented in more than 50 countries ( CDC 2008 ; WHO 2009b ) and is showing promising results in reducing anaemia and neural tube defects ( Centeno Tablante 2019 ; Garcia‐Casal 2018 ). Based on this experience, an increasing number of countries across the world are rapidly adopting fortification of rice as a means to fight malnutrition. Mandatory fortification of rice has been adopted in some countries, such as the Philippines, Costa Rica, Papua New Guinea and Nicaragua ( GAIN 2010 ). Fortified rice is sold in China using a multi‐micronutrient formula and in Japan enriched rice has been on the market since 1981. The USA has a mandatory food standard for 'enriched rice', prescribing levels of thiamin, niacin, riboflavin, folic acid and iron to be added to rice for enrichment. Although this requirement only applies in order for rice to be labelled as 'enriched' ( FDA 2001 ), 70% of the rice eaten in the USA is enriched or fortified ( American Rice Inc 2004 ; A2Z Project 2008 ). In India, Brazil and Colombia, fortified rice is currently being distributed through public safety net programmes ( Tsang 2016 ).

Despite this interest, to date there has been no systematic assessment of the benefits and harms of this intervention to inform policymaking and assist countries in the design and implementation of appropriate food‐fortification programmes, except for one systematic review carried out on interventions among children between 6 to 59 months ( Hijar 2015 ). Rice fortification was concluded to be effective for correcting and improving iron deficiency in children aged under five years of age.

Criteria for considering studies for this review

Types of studies.

We included randomised controlled trials (RCTs). Such studies provide information on whether fortified rice is effective and can actually achieve changes in health and vitamin and mineral status for those receiving the intervention.

Food fortification is, however, an intervention that aims at reaching the entire population of a country or large sections of the population and is frequently delivered through the food system. Therefore we have also included data from other study designs.

In summary, we aimed to include the following study designs.

• RCTs, with randomisation at either the individual or cluster level
• Quasi‐RCTs (where allocation of treatment has been made, for example, by alternate allocation, date of birth, or alphabetical order)
• Non‐randomised controlled trials
• cohort studies (prospective and retrospective);
• controlled before‐and‐after studies with at least two control and two intervention sites;
• interrupted time series with at least three measure points both before and after the intervention.

We analysed results from controlled non‐randomised and observational study designs separately from randomised and quasi‐randomised study designs.

We did not consider before‐and‐after studies without a control group for inclusion in this review. Results from these studies are presented in a table but are not included in a meta‐analysis and do not directly inform the conclusions of the review. Such studies provide information on the implementation, feasibility and other contextual factors relating to the interventions under review. We did not include cross‐over trials.

Types of participants

General population older than two years of age (including pregnant women) from any country. We excluded studies of interventions targeted toward participants with a critical illness or severe co‐morbidities.

Types of interventions

Interventions in the review were those in which rice had been fortified with at least one micronutrient or a combination of several micronutrients (iron, folic acid, zinc, vitamin A or other vitamins and minerals) irrespective of the method of fortification technology used. Fortified rice, for the purposes of this review, refers to the addition of a micronutrient premix to ordinary rice using any rice fortification technologies, such as hot extrusion, cold extrusion, coating or dusting ( A2Z Project 2008 ). We included studies with co‐interventions, that is, fortified rice with education, if the comparison group also received the education component in addition to the unfortified rice.

Comparisons include the following.

Rice fortified with iron alone or in combination with other micronutrients versus no intervention

Rice fortified with vitamin a alone or in combination with other micronutrients versus no intervention, rice fortified with zinc alone or in combination with other micronutrients versus unfortified rice (no micronutrients added), rice fortified with zinc alone or in combination with other micronutrients versus no intervention, rice fortified with folic acid alone or in combination with other micronutrients versus unfortified rice (no micronutrients added), rice fortified with folic acid alone or in combination with other micronutrients versus no intervention.

If studies examined the effects of two or more nutrients along with iron, we included them in the first comparison only to avoid duplication. If the studies had micronutrients in their fortification arms without iron, we included them in the further comparisons.

We excluded studies comparing rice fortification with other forms of micronutrient interventions (i.e. supplementation or dietary diversification) or the fortification of other food vehicles. We also excluded in‐vitro studies and those examining the effect of bio‐fortified rice (nutrient‐dense staple crops of rice using conventional breeding practices and modern biotechnology).

Types of outcome measures

Primary outcomes.

The primary outcomes across all populations in this review were the presence of anaemia, iron deficiency, haemoglobin concentrations and adverse effects.

• Anaemia (defined as haemoglobin (Hb) below the WHO cut‐off, adjusted for altitude as appropriate ( WHO 2011a ), or as defined by the study authors)
• Iron deficiency (as defined by study authors, based on a biomarker of iron status)

Haemoglobin concentration (g/L)

• Vitamin A deficiency (as defined by study authors, by using a biomarker; only for vitamin A‐fortified rice as intervention)
• Serum or plasma folate (nmol/L) (only for folic acid‐fortified rice as intervention)
• Any adverse effects (as defined by study authors)

Additional primary outcomes of interest differed by participant group, as listed below.

Children (2 to 11.9 years of age)

• Diarrhoea (as defined by study authors)
• Respiratory infections (as defined by study authors)
• All‐cause death

Pregnant women

• Congenital anomalies (neural tube defect, cleft lip, cleft palate, congenital cardiovascular defects and others as defined by study authors; only for folic acid‐fortified rice as intervention)
• Miscarriage

Secondary outcomes

Secondary outcomes included the following.

• Serum or plasma retinol (µmol/L) (only for vitamin A‐fortified rice as intervention)

Serum or plasma zinc (µmol/L)

• Anthropometric measures (height‐for‐age Z‐score and weight‐for‐height Z‐score for children, body mass index (BMI) for adults)

Risk of iron overload (defined by serum ferritin higher than 150 µg/L in women and higher than 200 µg/L in men)

• Clinical malaria (as defined by study authors)
• Severe malaria (as defined by study authors)
• Night blindness (defined as the reported inability to see after dusk by people who typically report having normal vision during the day; only for vitamin A‐fortified rice as intervention)

For those studies that delivered the intervention at the first administrative level or higher (i.e. non‐randomised studies) we examined the same variables at an ecological level (for example prevalence of anaemia or congenital anomalies rates).

Search methods for identification of studies

Electronic searches.

We searched the following international and regional sources.

International databases

• Cochrane Central Register of Controlled Trials (CENTRAL; Issue 7 2012 to Issue 12 2018) via Cochrane Register of Studies Online (CRSO)
• MEDLINE (OVID; 1948 to 10 December 2018)
• Embase (OVID; 1980 to 10 December 2018)
• CINAHL EBSCOhost (1937 to 10 December 2018)
• Web of Science (ISI) SCI, SSCI, CPCI‐exp & CPCI‐SSH (until 10 December 2018)
• POPLINE (www.popline.org/; 10 December 2018)
• AGRICOLA (Ebsco; 10 December 2018)
• ClinicalTrials.gov (searched 10 December 2018)
• WHO International Clinical Trials Registry Platform (ICTRP; apps.who.int/trialsearch; searched 10 December 2018)
• BIOSIS (ISI; 2012 to 10 December 2018)

Regional databases

• IBECS (ibecs.isciii.es; searched 10 December 2018)
• SciELO (Scientific Electronic Library Online; www.scielo.br; searched 10 December 2018)
• African Index Medicus (AIM; www.globalhealthlibrary.net/php/index.php?lang=en; searched 10 December 2018)
• Index Medicus for the Eastern Mediterranean Region (IMEMR; www.globalhealthlibrary.net/php/index.php?lang=en; searched 10 December 2018)
• LILACS (Latin American and Caribbean Health Sciences Literature; lilacs.bvsalud.org/en; searched 10 December 2018)
• PAHO (Pan American Health Library; www1.paho.org/english/DD/IKM/LI/library.htm; searched 10 December 2018)
• WHOLIS (WHO Library; dosei.who.int/; searched 10 December 2018)
• WPRIM (Western Pacific Region Index Medicus; www.wprim.org/; searched 10 December 2018)
• Index Medicus for the South‐East Asia Region (IMSEAR; imsear.hellis.org; searched 10 December 2018)
• IndMED, Indian medical journals; medind.nic.in/imvw/; searched to 10 December 2018)
• Native Health Research Database; hslic‐nhd.health.unm.edu; searched to 10 December 2018)

For these sources, we searched WorldCat, Networked Digital Library of Theses and Dissertations, DART‐Europe E‐theses Portal, Australasian Digital Theses Program, Theses Canada Portal and ProQuest‐Desertations and Theses.

We handsearched the five journals with the highest number of included studies in the last 12 months to capture any article that may not have been indexed in the databases at the time of the search. As rice fortification technologies are relatively novel we limited the search, from 1960 to present, for all databases, although some had no time restrictions.

We contacted Cochrane Public Health's Information Specialist to search the Cochrane Public Health Group Specialised Register. The search used keyword and controlled vocabulary (when available), using the search terms set out in the Appendices and adapting them as appropriate for each database (see Appendix 1 ).

We did not apply any language restrictions. If we identified articles written in a language other than English, we commissioned their translation into English. If this was not possible, we sought advice from Cochrane Public Health. We stored these articles in the 'Awaiting assessment' section of the review until a translation is available.

Searching other resources

For assistance in identifying ongoing or unpublished studies, we contacted the Department of Nutrition for Health and Development and WHO regional offices, the nutrition section of the United Nations Children's Fund (UNICEF), the World Food Programme (WFP), the US Centers for Disease Control and Prevention (CDC), US Agency for International Development (USAID) micronutrient programme, Nutrition International, the Global Alliance for Improved Nutrition (GAIN), Hellen Keller International (HKI), Sight and Life Foundation, PATH, the Wright Group, premix producers DSM and BASF, Food Fortification Initiative (FFI) and the Rice Fortification Resource Group (March 2019).

Selection of studies

Two review authors (JPP, PM) independently screened the titles and abstracts of articles retrieved by each search to assess initial eligibility. After the initial screening, we then retrieved full copies of all eligible papers and screened them for eligibility as determined by the inclusion and exclusion criteria listed above. When we were unable to reject a title or abstract with certainty, we obtained the full text of the article for further evaluation. If we could not obtain full articles, we attempted to contact the study authors to obtain further details of  the study. Failing this, we classified studies as 'awaiting assessment' until further information is published or made available to us. We resolved disagreements at any stage of the eligibility assessment process through discussion and consultation with two other review authors (SN, LMR), where necessary.

Data extraction and management

Two review authors independently extracted data in duplicate using customised data extraction forms based on those from Cochrane Handbook ( Higgins 2019 ), Cochrane Public Health ( Cochrane PHG 2010 ), and Cochrane Effective Practice and Organisation of Care ( EPOC 2017 ).

All review authors were involved in piloting the form using a subset of articles in order to enhance consistency amongst review authors; based on this, we modified the form as necessary. We collected information on study design, study setting, participants (number and characteristics) and provided a full description of the interventions examined. We extracted details of outcomes measured (including a description of how and when outcomes were measured) and results.

Two review authors (JPP, LMR) designed the form, so that we were able to record results for our prespecified outcomes as well as for other non‐specified outcomes, although we did not use such outcomes to underpin any of our conclusions. We also extracted additional items relating to study recruitment and the implementation of the intervention, including number of sites for an intervention, whether recruitment was similar at different sites, levels of compliance and use of rice in different sites within studies, resources required for implementation, and whether studies had conducted a process evaluation. We also recorded whether or not studies included specific strategies to address diversity or disadvantage. We used the PROGRESS (place of residence, race/ethnicity, occupation, gender, religion, education, socioeconomic status, capital) checklist to collect information on whether or not studies had reported data by sociodemographic characteristics known to be important from an equity perspective ( Ueffing 2011 ).

Two review authors (JPP, JAS) entered data into Review Manager 5 software and checked for accuracy ( Review Manager 2014 ).

Assessment of risk of bias in included studies

We used the EPOC 'RIsk of bias' tool for studies with a separate control group to assess the risk of bias of all studies at study level for primary outcomes ( EPOC 2017 ). This tool includes five domains of bias: selection, performance, attrition, detection and reporting; as well as an 'other bias' category to capture other potential threats to validity.

Two review authors independently assessed risk of bias in duplicate (JPP, PM) for each study and resolved any disagreement by discussion or by involving an additional review author (SN).

Assessing risk of bias in randomised trials and quasi‐randomised trials

1. sequence generation (checking for possible selection bias).

We assessed studies as:

• low risk of bias if there is a random component in the sequence generation process (e.g. random number table; computer random number generator);
• high risk of bias if a non‐random approach has been used (e.g. odd or even date of birth; hospital or clinic record number). Non‐randomised studies should be scored 'high';
• unclear risk of bias if not specified in the paper.

2. Allocation concealment (checking for possible selection bias)

• low risk of bias if participants and investigators enrolling participants could not foresee assignment because an appropriate method was used to conceal allocation (e.g. telephone or central randomisation; consecutively numbered sealed opaque envelopes). We gave this rating to studies where the unit of allocation was by institution and allocation was performed on all units at the start of the study;
• high risk of bias if participants of investigators enrolling participants could possibly foresee assignments and potentially introduce selection bias (e.g. open random allocation; unsealed or non‐opaque envelopes);
• unclear.   

3. Similarity of baseline outcome measurements (checking for confounding, a potential consequence of selection bias)

• low risk of bias if outcomes were measured prior to the intervention, and no important differences were present across intervention groups;
• high risk of bias if important differences in outcomes between groups were present prior to intervention and were not adjusted for in the analysis;
• unclear risk of bias if there was no baseline measure of outcome (note: if 'high' or 'unclear' but there is sufficient information to do an adjusted analysis, the assessment should be 'low').

4. Similarity of baseline characteristics (checking for confounding, a potential consequence of selection bias)

• low risk of bias if baseline characteristics are reported and similar across intervention groups;
• high risk of bias if baseline characteristics are not reported or if there are differences across groups;
• unclear risk of bias if it is not clear (e.g. characteristics mentioned in text but no data presented).

5. Incomplete outcome data (checking for possible attrition bias through withdrawals, dropouts and protocol deviations)

We assessed outcomes in each included study as:

• low risk of bias due to incomplete outcome data, which could be either that there were no missing outcome data or the missing outcome data were unlikely to bias the results based on the following considerations: study authors provided transparent documentation of participant flow throughout the study, the proportion of missing data was similar in the intervention and control groups, the reasons for missing data were provided and balanced across the intervention and control groups, the reasons for missing data were not likely to bias the results (e.g. moving house).
• high risk of bias if missing outcome data was likely to bias the results. Studies will also receive this rating if an 'as‐treated' (per protocol) analysis is performed with substantial differences between the intervention received and that assigned at randomisation, or if potentially inappropriate methods for imputation have been used;
• unclear risk of bias.

6. Blinding (checking for possible performance and detection bias)

We assessed the risk of performance bias associated with blinding as:

• low, high or unclear risk of bias for participants;
• low, high or unclear risk of bias for personnel.

We assessed the risk of detection bias associated with blinding as:

• low, high or unclear risk of bias for outcome assessors.

Whilst assessed separately, we combined the results in a single evaluation of risk of bias associated with blinding as follows:

• low risk of bias if there was blinding of participants and key study personnel and it was unlikely to have been broken, or the outcomes are objective. This rating will also be given to studies where either participants and key study personnel were not blinded but outcome assessment was blinded and the non‐blinding of others was unlikely to introduce bias;
• high risk of bias if there was no blinding or incomplete blinding or if there was blinding that was likely to have been broken and the outcome or outcome assessment was likely to be influenced by a lack of blinding;

7. Contamination (checking for possible performance bias)

• low risk of bias if allocation was by community, institution or practice and it is unlikely that the control group received the intervention;
• high risk of bias if it is likely that the control group received the intervention;
• unclear risk of bias if it is possible that contamination occurred but the risk of this happening is not clear.

8. Selective reporting bias

• low risk of bias if it is clear, either by availability of the study protocol or otherwise, that all prespecified outcomes that are of interest in the review have been reported;
• high risk of bias if it is clear that not all of the study's prespecified outcomes have been reported, or reported outcomes were not prespecified (unless justification for reporting is provided), or outcomes of interest are reported incompletely and cannot be used, or where one or more of the primary outcomes is reported using measurements or analysis methods that were not prespecified, or finally if the study report fails to include an important outcome that would be expected to have been reported;

9. Other sources of bias

Other possible sources of bias were described for each included study and a rating of low, high or unclear risk of bias was given for this item.

In addition to the above criteria, we also assessed cluster‐RCTs with the following criteria:

1. Recruitment bias

• low risk of bias if individuals were recruited to the study before the clusters were randomised;
• high risk of bias if individuals were recruited to the study after the clusters were randomised;

2. Baseline imbalance

• low risk of bias if baseline characteristics were reported and were similar across clusters or if study authors used stratified or pair‐matched randomisation of clusters;
• high risk of bias if baseline characteristics were not reported or if there were differences across clusters;
• Unclear risk of bias.

3. Loss of clusters

• low risk of bias if no complete clusters were lost or omitted from the analysis;
• high risk of bias if complete clusters were lost or omitted from the analysis;

4. Incorrect analysis

• low risk of bias if study authors appropriately accounted for clusters in the analysis or provided enough information for review authors to account for clusters in the meta‐analysis;
• High risk of bias if study authors did not appropriately account for clusters in the analysis or did not provide enough information for review authors to account for clusters in the meta‐analysis;

5. Compatibility with individual RCTs

• low risk of bias if effects of the intervention were likely not altered by the unit of randomisation;
• high risk of bias if effects of the intervention were likely altered by the unit of randomisation;

Overall risk of bias

For all included studies, we summarised the overall risk of bias by primary outcome within each study at the study level. Studies at high risk of bias were those with high or unclear risk of bias in the following domains: allocation concealment, similarity of baseline outcome measurements, and incomplete outcome data. We judged the overall risk of bias of each study as 'low' if we had assessed all three domains at low risk; and 'high' when we had assessed one or more of the domains at either high or unclear risk. Judgements took into account the likely magnitude and direction of bias and whether it was likely to impact on the findings of the study.  

Measures of treatment effect

For dichotomous outcomes we have presented proportions, and for two‐group comparisons we have presented results as average risk ratio (RR) with 95% confidence interval (CI). We have reported results for continuous outcomes as the mean difference (MD) with 95% CI if studies measured outcomes in the same way. Where some studies reported endpoint data and others reported changes from baseline data (with errors), we combined these in the meta‐analysis if the outcomes had been reported using the same scale. We used standardised mean difference (SMD) with 95% CI to combine studies that measured the same outcome (for example haemoglobin) but used different methods.

For studies with multiple arms reporting a continuous variable as an outcome, we calculated the weighted average for single pair‐wise results in the meta analysis.

Unit of analysis issues

Cluster‐randomised trials.

We combined results from both cluster‐randomised and individually randomised studies if there was little heterogeneity between the studies. We labelled cluster‐randomised trials with a 'C'. If the authors of cluster‐randomised trials had conducted their analyses at a different level to that of allocation, and they had not appropriately accounted for the cluster design in their analyses, we calculated studies' effective sample sizes to account for the effect of clustering in the data. We utilised the intra‐cluster correlation coefficient (ICC) derived from the study (if available) or from another source (for example using the ICCs derived from other, similar studies) ( Adams 2004 ; Gulliford 1999 ), and then calculated the design effect with the formula provided in the Cochrane Handbook for Systematic Reviews of Interventions ( Higgins 2011 ). We reported this and undertook sensitivity analysis to investigate the effect of variations in ICC.

We made an adjustment in the number of participants for design effect for both the continuous outcome of haemoglobin concentrations and dichotomous outcomes of anaemia, iron deficiency and vitamin A deficiency in two studies ( Parker 2015 (C) ; Perignon 2016 (C) . We used the design effect calculated for anaemia for calculating the total number of participants in iron deficiency, vitamin A deficiency and haemoglobin concentration. We used the mean and standard deviations of haemoglobin concentration in the analysis without making any changes. The details of adjustments for design effect in each of the studies are provided in Characteristics of included studies .

Studies with more than two treatment groups

If we identified studies with more than two intervention groups (multi‐arm studies), where possible we combined groups to create a single pair‐wise comparison or used the methods set out in the Cochrane Handbook for Systematic Reviews of Interventions to avoid double counting study participants ( Higgins 2011 ). If two or more study arms shared the control group, we divided the control group over the number of relevant subgroup categories to avoid double counting the participants (for dichotomous data, we divided the events and the total population while for continuous data we assumed the same mean and standard deviation but divided the total population). The details are described in the Characteristics of included studies tables.

Dealing with missing data

We noted missing outcome data and levels of attrition for included studies on the data extraction form. We explored the impact of including studies with high levels of missing data in the overall assessment of treatment effect by using sensitivity analysis. The denominator for each outcome in each study was the number randomised minus any participants whose outcomes we knew to be missing. For missing summary data, we contacted lead study authors for clarification or, if possible, we estimated missing summary data using other statistical information (for example confidence intervals, standard errors) provided in the primary paper and imputed the standard deviation either from other studies in the same systematic review or from studies in another systematic review.

Assessment of heterogeneity

We examined forest plots from a meta‐analysis to visually determine the level of heterogeneity (in terms of the size or direction of treatment effect) between studies. We used Tau², I² statistic ( Higgins 2003 ) and Chi² statistic to quantify the level of heterogeneity among the studies in each analysis ( Deeks 2017 ). We regarded substantial or considerable heterogeneity as Tau² greater than 0 and either I² statistic greater than 30% or a low P value (< 0.10) in the Chi² test. We noted this in the text and explored it using prespecified subgroup analyses mentioned below. Caution was taken in the interpretation of those results with high levels of unexplained heterogeneity.

Assessment of reporting biases

Where we suspected reporting bias (see 'Selective reporting bias' above) we attempted to contact study authors asking them to provide missing outcome data. Where this was not possible, and we thought that the missing data would introduce serious bias, we explored the impact of including such studies in the overall assessment of results by a sensitivity analysis.

We did not anticipate that there would be sufficient studies contributing data for any particular outcome for us to examine possible publication bias; if more than 10 studies reporting the same outcome of interest were available, we planned to generate funnel plots in Review Manager 2014 and visually examine them for asymmetry. Where we pooled studies in a meta‐analysis we ordered studies in terms of weight so that a visual examination of forest plots might allow us to assess whether the results from smaller and larger studies were similar or if there were any apparent differences according to study size.

Data synthesis

We carried out a meta‐analysis to provide an overall estimate of treatment effect when more than one study examined the same intervention, provided that studies used similar methods and measured the same outcome in similar ways in similar populations. We used a random‐effects model meta‐analysis for combining data as we anticipated that there might be natural heterogeneity between studies attributable to the difference. We used narrative synthesis, guided by the data extraction form in terms of the ways in which studies were grouped and summarised, to describe the outcomes, explore intervention processes, and describe the impact of interventions by sociodemographic characteristics known to be important from an equity perspective based on the PROGRESS framework, where this information was available.

We did not combine results from randomised and non‐randomised trials together in a meta‐analysis, and we have not presented pooled estimates for non‐randomised studies with different types of study design. We have reported the results of the controlled before‐and‐after studies in narrative form.

Assessing the certainty of evidence

For the assessment across studies, we used MECIR (Methodological Expectations of Cochrane Intervention Reviews) conduct standards ( MECIR 2018 ), and we employed the GRADE approach to interpret findings ( Langendam 2013 ). The GRADE profiler ( GRADEpro GDT 2015 ) allowed us to import data from Review Manager 2014 to create 'Summary of findings' tables. For each of the outcomes, two review authors (JPP, MNGC) assessed the certainty of evidence of included studies independently, using the GRADE approach ( Balshem 2011 ). We have listed the primary outcomes for each comparison with estimates of relative effects along with the number of participants and studies contributing data for those outcomes. These tables provide outcome‐specific information concerning the overall certainty of evidence from studies included in the comparison, the magnitude of effect of the interventions examined, and the sum of available data on the outcomes we considered. We included only primary outcomes in the 'Summary of findings' tables. We prepared 'Summary of findings' tables for the comparisons including rice fortified with iron alone versus unfortified rice, vitamin A alone or in combination with other micronutrients versus unfortified rice, zinc alone or in combination with other micronutrients versus unfortified rice, and folic acid alone or in combination with other micronutrients versus unfortified rice. The outcomes included in these were anaemia, iron deficiency, haemoglobin concentration, vitamin A deficiency, diarrhoea, respiratory infections, all‐cause death, and any adverse effects (see Table 1 ; Table 2 ).

For assessments of the overall certainty of evidence for each outcome that included pooled data from included studies from RCTs only, we downgraded the evidence from 'high certainty' by one level for serious (or by two for very serious) study limitations (risk of bias), indirectness of evidence (due to the use of different cut‐offs, for example), serious inconsistency, imprecision of effect estimates or potential publication bias. Data from observational studies started at low certainty. This assessment was limited only to the studies included in this review and as we did not consider there was a serious risk of publication bias, we did not downgrade in this domain.

Subgroup analysis and investigation of heterogeneity

Where possible we conducted subgroup analysis to explore heterogeneity according to the following subgroups.

• Micronutrient content: single nutrient versus two or more nutrients
• Rice fortification method: hot extrusion versus cold extrusion versus coating versus dusting
• Cooking method most commonly used in study setting (as reported): soaking, and boiling with excess water versus boiling in excess water versus boiling without excess water versus rinsing and boiling without excess water versus frying and boiling without excess water versus unknown/unreported
• Public health significance of anaemia at baseline in the target group: not a problem (lower than 5%) versus mild and moderate (5% to 39.9%) versus severe (40% and more) versus mixed/unknown/unreported
• Malaria endemicity at the time that the study was conducted: some malaria risk setting versus malaria‐free area versus unknown/unreported malaria setting.

We examined differences between subgroups by visual inspection of the CIs; non‐overlapping CIs suggesting a statistically significant difference in treatment effect between the subgroups. We also used the approach of Borenstein 2008 to formally investigate differences between two or more subgroups. We conducted analyses in RevMan 5 ( Review Manager 2014 ). We limited this analysis to those outcomes for which three or more studies contributed data.

Sensitivity analysis

We carried out sensitivity analysis to examine the effects of removing studies at high risk of bias (those with high or unclear risk of bias for allocation concealment, similarity of baseline outcome measurements, incomplete outcome data) from the meta‐analysis. For cluster‐randomised trials, we carried out sensitivity analysis using a range of ICC on overall effect estimate and have reported these effects.

Description of studies

Results of the search.

Our search strategy identified 28,730 references (22,147 references after removing duplicates) for possible inclusion. We screened a total of 58 full‐text articles for potential inclusion for the analyses. We included 17 studies (28 records). We excluded 22 studies (28 records) with reasons and identified two ongoing or unpublished studies ( NCT02714075 ; NCT03056625 ). All 17 included studies were reported in English. We have summarised the study selection process in Figure 2 . Of the 17 studies, 12 RCTs contributed to the meta‐analysis.

PRISMA study flow diagram

Included studies

We have presented the details of included studies, including participants, interventions, outcomes, source of funding, and results of contact with the study authors, in the Characteristics of included studies . We have given a summary of the general characteristics of the included studies in Table 4 . Twelve studies were reported from Asian countries ( Angeles‐Agdeppa 2008 ; Ara 2019 ; Gershoff 1977 ; Hardinsyah 2016 ; Hussain 2014 ; Moretti 2006b ; Perignon 2016 (C) ; Pinkaew 2013 ; Pinkaew 2014 ; Radhika 2011 ; Salcedo 1950 ; Thankachan 2012 ), two from Brazil ( Della Lucia 2016 ; Nogueira Arcanjo 2013 ), one from Mexico ( Hotz 2008 ), one from the USA (Louisiana; Losso 2017 ) and one study from Burundi ( Parker 2015 (C) ). The PROGRESS‐Plus framework characteristics are given in Table 5 . Each of the 17 included studies had different levels of micronutrient concentrations per 100 grams of uncooked rice, and we have given details of the micronutrient fortification profile in Table 6 .

a One international unit (IU) vitamin A is equivalent to 0.0003 mg of retinol, 0.0006 mg of beta‐carotene and 0.0012 mg of other pro‐vitamin A carotenoids.

Study designs

Out of the 17 included studies (28 records), twelve were RCTs ( Angeles‐Agdeppa 2008 ; Hardinsyah 2016 ; Hotz 2008 ; Hussain 2014 ; Losso 2017 ; Moretti 2006b ; Parker 2015 (C) ; Perignon 2016 (C) ; Pinkaew 2013 ; Pinkaew 2014 ; Radhika 2011 ; Thankachan 2012 ), two of which were cluster‐randomised trials ( Parker 2015 (C) ; Perignon 2016 (C) . For distinguishing them from individual randomised trials, their names are denoted with '(C)'. Five studies were controlled before‐and‐after studies ( Ara 2019 ; Della Lucia 2016 ; Gershoff 1977 ; Nogueira Arcanjo 2013 ; Salcedo 1950 ).

Overall, eight RCTs had 2‐arms ( Hardinsyah 2016 ; Hotz 2008 ; Losso 2017 ; Moretti 2006b ; Parker 2015 (C) ; Pinkaew 2013 ; Pinkaew 2014 ; Radhika 2011 ), two studies had three arms ( Angeles‐Agdeppa 2008 ; Thankachan 2012 ), and one study had five arms (including a placebo and traditional feeding intervention) as a part of the FORISCA‐UltraRice+NutriRice study ( Perignon 2016 (C) ). One RCT had six arms with five fortification groups in addition to control group ( Hussain 2014 ). The studies had various types of randomisation procedures, sequence generation, allocation concealment, blinding as described in Characteristics of included studies .

One before‐and‐after study had five arms ( Gershoff 1977 ) and four had two arms ( Ara 2019 ; Della Lucia 2016 ; Nogueira Arcanjo 2013 ; Salcedo 1950 ).

Twelve studies were carried out in Asia, four in the Americas and one in Africa. The studies in Asia were carried out in Bangladesh ( Ara 2019 ), Cambodia ( Perignon 2016 (C) ), India ( Hussain 2014 ; Moretti 2006b ; Radhika 2011 ; Thankachan 2012 ), Indonesia ( Hardinsyah 2016 ), Philippines ( Angeles‐Agdeppa 2008 ; Salcedo 1950 ) and Thailand ( Gershoff 1977 ; Pinkaew 2013 ; Pinkaew 2014 ). The four studies in the Americas were conducted in Brazil ( Della Lucia 2016 ; Nogueira Arcanjo 2013 ), Mexico ( Hotz 2008 ) and in the USA ( Losso 2017 ). The study in Africa was conducted in Burundi ( Parker 2015 (C) ). The Indian studies had school children in an urban area ( Thankachan 2012 ), urban slum ( Moretti 2006b ), and rural school setting ( Radhika 2011 ). The Mexican study ( Hotz 2008 ), recruited women from six factories without any specific mention of ethnicity or race. The studies from the Philippines had urban school children in Manila ( Angeles‐Agdeppa 2008 ), and children from a welfare institution and military personnel ( Salcedo 1950 ). The study in Burundi was conducted among rural school age children from Muyinga Province ( Parker 2015 (C) ). The study in Cambodia was among rural school children in Kampung Speu ( Perignon 2016 (C) ), while the Indonesian study included teenage girls from a boarding school in the area of Medan ( Hardinsyah 2016 ).

Malaria endemicity

One study reported that it was conducted in a malaria‐endemic area ( Parker 2015 (C) ). Four studies reported to be from non‐endemic areas for malaria ( Angeles‐Agdeppa 2008 ; Moretti 2006b ; Perignon 2016 (C) ; Thankachan 2012 ). Other studies did not report on endemicity for malaria ( Ara 2019 ; Della Lucia 2016 ; Gershoff 1977 ; Hardinsyah 2016 ; Hotz 2008 ; Hussain 2014 ; Losso 2017 ; Nogueira Arcanjo 2013 ; Pinkaew 2013 ; Pinkaew 2014 ; Radhika 2011 ; Salcedo 1950 ).

Participants

The 17 included studies had a total of 10,483 participants. The controlled before‐and‐after studies were conducted in children aged two to six years of age ( Della Lucia 2016 ; Nogueira Arcanjo 2013 ), 18 months to nine years of age ( Gershoff 1977 ), and one was among women aged between 15 and 49 years ( Ara 2019 ). One controlled before‐and‐after study was on infants to adults as it was prompted by clinical beriberi which cut across ages ( Salcedo 1950 ). Among the RCTs, two were conducted among non‐pregnant, non‐lactating women 18 to 49 years of age ( Hotz 2008 ; Losso 2017 ). All other included studies were carried out among preschool and school age children. RCTs involved children aged between 5 to 18 years of age ( Angeles‐Agdeppa 2008 ; Hardinsyah 2016 ; Hussain 2014 ; Moretti 2006b ; Parker 2015 (C) ; Perignon 2016 (C) ; Pinkaew 2013 ; Pinkaew 2014 ; Radhika 2011 ; Thankachan 2012 ). There were no studies reporting data exclusively on adolescents beyond the age of 12 years, adult men or pregnant women.

Anaemia prevalence

The baseline prevalence of anaemia ranged from 5% to 62% in the studies in children ( Angeles‐Agdeppa 2008 ; Hussain 2014 ; Moretti 2006b ; Nogueira Arcanjo 2013 ; Parker 2015 (C) ; Perignon 2016 (C) ; Pinkaew 2014 ; Radhika 2011 ; Thankachan 2012 ), and around 21% (intervention: 21.4 %; control: 20.4%) in one study among women ( Hotz 2008 ), while the other study on women included women with iron deficiency as determined by serum ferritin or serum iron value, or both ( Losso 2017 ). The study done on teenagers ( Hardinsyah 2016 ), had a baseline anaemia level of 34%. Two studies from India had an anaemia prevalence of around 40% and above ( Radhika 2011 ; Thankachan 2012 ). A third study from India reported iron‐deficiency anaemia of around 30% suggesting a much higher anaemia rate ( Moretti 2006b ). The two studies that included only anaemic children reported 38% ( Parker 2015 (C) ), and 45% ( Angeles‐Agdeppa 2008 ), during screening. Three studies had an anaemia prevalence between 10% to 18% ( Perignon 2016 (C) ; Pinkaew 2013 ; Pinkaew 2014 ). The controlled before‐and‐after study Ara 2019 had a baseline level of anaemia of 42%.

In total, five studies reported on stunting at baseline ranging from 12% to 40% ( Angeles‐Agdeppa 2008 ; Perignon 2016 (C) ; Pinkaew 2014 ; Radhika 2011 ; Thankachan 2012 ), one study reported less than 10% stunting in both intervention and control arms ( Hussain 2014 ). Two studies reported the height‐for‐age Z‐score ( Moretti 2006b ; Pinkaew 2013 ) as −1.3 and −0.8 respectively. One study ( Perignon 2016 (C) ), reported both: 40% stunting; −1.75 Z‐score). None of the studies restricted inclusion of participants or analysed their data based on stunting status.

Thirteen studies had preschool or school‐going children as participants ( Angeles‐Agdeppa 2008 ; Della Lucia 2016 ; Gershoff 1977 ; Hardinsyah 2016 ; Hussain 2014 ; Moretti 2006b ; Nogueira Arcanjo 2013 ; Parker 2015 (C) ; Perignon 2016 (C) ; Pinkaew 2013 ; Pinkaew 2014 ; Radhika 2011 ; Thankachan 2012 ). One study had women factory workers ( Hotz 2008 ), and another did not mention the occupation of the participants ( Losso 2017 ). The Ara 2019 study had mostly housewives (> 70% in each of the groups) followed by unskilled workers (˜7.82% to 11.26%).

Gender allocation was reported in all but three studies ( Hussain 2014 ; Moretti 2006b ; Salcedo 1950 ). All the three studies among adults included all women ( Ara 2019 ; Hotz 2008 ; Losso 2017 ). There were no differences in gender between treatment groups at baseline in any study. Six studies had more female participants ( Della Lucia 2016 ; Parker 2015 (C) ; Pinkaew 2013 ; Pinkaew 2014 ; Radhika 2011 ; Thankachan 2012 ). One study was carried out among teenage girls ( Hardinsyah 2016 ). Two studies had more male participants ( Angeles‐Agdeppa 2008 ; Perignon 2016 (C) ). One before‐and‐after study had roughly equal numbers ( Gershoff 1977 ), while one had more women ( Nogueira Arcanjo 2013 ).

Religion/culture

No specific mention was made about the religion of the study population in 12 studies ( Angeles‐Agdeppa 2008 ; Ara 2019 ; Della Lucia 2016 ; Gershoff 1977 ; Hotz 2008 ; Hussain 2014 ; Losso 2017 ; Moretti 2006b ; Nogueira Arcanjo 2013 ; Perignon 2016 (C) ; Radhika 2011 ; Salcedo 1950 ). However one of these studies ( Losso 2017 ), had mixed ethnic background participants. One study from India ( Thankachan 2012 ), reported that the majority of the study participants were Hindus (74% in fortification groups and 65% in control groups). Two studies from Thailand had a predominantly Muslim population ( Pinkaew 2013 ; Pinkaew 2014 ). The study from Indonesia had Javanese and Bataknese ethnic participants predominantly ( Hardinsyah 2016 ).

Socioeconomic status

The studies were conducted mostly among those with low‐socioeconomic status. Three studies from India ( Moretti 2006b ; Radhika 2011 ; Thankachan 2012 ), and two studies from Thailand ( Pinkaew 2013 ; Pinkaew 2014 ), were carried out among children from low socioeconomic backgrounds. One study from India was in an urban area ( Thankachan 2012 ), urban slum ( Moretti 2006b ), and rural area ( Radhika 2011 ). Other studies did not specify the socioeconomic status of their participants.

Twelve studies ( Angeles‐Agdeppa 2008 ; Della Lucia 2016 ; Hardinsyah 2016 ; Hussain 2014 ; Moretti 2006b ; Nogueira Arcanjo 2013 ; Parker 2015 (C) ; Perignon 2016 (C) ; Pinkaew 2013 ; Pinkaew 2014 ; Radhika 2011 ; Thankachan 2012 ), reported studies on pre‐school and school‐going children. One community‐based study ( Salcedo 1950 ), and two other studies ( Hotz 2008 ; Losso 2017 ), were on women whose educational status was not reported. One study included pre‐school children attending a day‐care centre ( Gershoff 1977 ). In Ara 2019 , nearly 25% of the study population did not have any education, the remaining participants all had primary school education and above.

Social capital

The studies did not report issues related to inequity, access to food or any particular instances of preferences of certain social classes. However, the included studies were carried out in predominantly lower socioeconomic settings.

Interventions

Micronutrient content.

All studies fortified rice with iron and some studies added various additional combinations of micronutrients. Seven studies ( Hardinsyah 2016 ; Hussain 2014 ; Parker 2015 (C) ; Perignon 2016 (C) ; Pinkaew 2013 ; Pinkaew 2014 ; Thankachan 2012 ), and four controlled before‐and‐after studies fortified with multiple micronutrients ( Ara 2019 ; Della Lucia 2016 ; Gershoff 1977 ; Salcedo 1950 ). Among them, six studies ( Hardinsyah 2016 ; Parker 2015 (C) ; Perignon 2016 (C) ; Pinkaew 2013 ; Pinkaew 2014 ; Thankachan 2012 ), compared the effectiveness of multiple‐micronutrient‐fortified rice with that of unfortified rice. One RCT reported different micronutrients and their effects on each arm, compared with the control arm, which received unfortified rice ( Hussain 2014 ), in which out of five intervention arms, one arm each received iron alone, beta carotene, retinyl palmitate, iron plus retinyl palmitate and iron plus beta carotene. Five studies ( Angeles‐Agdeppa 2008 ; Hotz 2008 ; Losso 2017 ; Moretti 2006b ; Radhika 2011 ), and one controlled before‐and‐after study ( Nogueira Arcanjo 2013 ), included iron alone for rice fortification (with various quantities of iron and its compounds).

For the RCTs with multiple micronutrients, two studies ( Pinkaew 2013 ; Pinkaew 2014 ), reported rice fortified with three micronutrients (iron, zinc and vitamin A); one study ( Parker 2015 (C) ), with four micronutrients (iron, zinc, thiamine and folic acid) and two ( Hardinsyah 2016 ; Perignon 2016 (C) ), with four or more micronutrients. All the multiple micronutrient studies had an arm with at least iron and zinc. One study ( Gershoff 1977 ), reported the field effect of consumption of rice fortified with lysine, threonine, thiamin, riboflavin, vitamin A and iron. One study ( Thankachan 2012 ), compared the effectiveness of high iron (12.5 mg/100 g natural rice) with that of low iron (6.25 mg/100 g of natural rice) fortification, along with vitamin A, thiamine, niacin, vitamin B 6 , vitamin B 12 , folate, iron and zinc and no fortification of rice. Another study ( Angeles‐Agdeppa 2008 ) compared the effectiveness of ferrous sulphate‐fortified rice and micronized dispersible ferric pyrophosphate‐fortified rice with that of unfortified rice, wherein each of the three arms received in 160 g (1 cup) of cooked rice, ferrous sulphate (ExFeSO4), micronized ferric pyrophosphate (ExFeP80) or no added fortificant (control).

In all the included studies, the amount of elemental iron per 100 g of rice ranged from 0.2 mg to 112.8 mg. Vitamin A was a fortificant in three studies. The amount of vitamin A per 100 g of rice ranged from 0.15 mg ( Ara 2019 ) to 2.1 mg ( Pinkaew 2013 ; Pinkaew 2014 ). The amount of zinc per 100 g of rice ranged from 2 mg ( Perignon 2016 (C) ) to 18 mg ( Pinkaew 2013 ; Pinkaew 2014 ). One study carried out among women had ferrous sulphate 18 mg/100 g of fortified rice for the intervention arm and unfortified rice for the control arm ( Losso 2017 ). Fortification details per 100 g of uncooked rice are given in Table 6 .

Rice fortification method

One study reported using extrusion as a fortification method without indicating the temperature ( Angeles‐Agdeppa 2008 ). Seven studies used hot‐extrusion process only ( Ara 2019 ; Hardinsyah 2016 ; Moretti 2006b ; Parker 2015 (C) ; Pinkaew 2013 ; Pinkaew 2014 ; Thankachan 2012 ), and three studies reported a cold extrusion process only ( Della Lucia 2016 ; Hotz 2008 ; Radhika 2011 ). One study included 2 arms with hot extrusion and one arm with cold extrusion ( Perignon 2016 (C) ). Three studies reported using coating in the fortification ( Gershoff 1977 ; Losso 2017 ; Salcedo 1950 ), and two studies did not report the method ( Hussain 2014 ; Nogueira Arcanjo 2013 ).

Iron compounds

The included studies used three types of iron compounds. The before‐and‐after study ( Gershoff 1977 ) used ferric phosphate tetrahydrate. One study ( Angeles‐Agdeppa 2008 ), used ferrous sulphate as one of two iron fortificants. Nine studies that were part of the meta‐analysis used ferric pyrophosphate. Micronized iron reduces the particle size to promote absorption. Two studies used a micronized ferric pyrophosphate, which had a particle size of 0.3 μm and was encapsulated ( Angeles‐Agdeppa 2008 ; Hotz 2008 ). One study, which used cold extrusion, reported a particle size of 3.1 μm ( Radhika 2011 ). Five studies described the iron used as micronized ground ferric pyrophosphate ( Moretti 2006b ; Perignon 2016 (C) ; Pinkaew 2013 ; Pinkaew 2014 ; Thankachan 2012 ), and three of these specified the particle size as 2.5 μm ( Moretti 2006b ; Pinkaew 2013 ; Pinkaew 2014 ). One study described the iron compound as ferric pyrophosphate without any reference to micronization or particle size ( Parker 2015 (C) ). Other studies had micronized ground ferric pyrophosphate with 4 mg iron ( Hussain 2014 ), 10 mg iron ( Pinkaew 2014 ), 11.8 mg per 100 g ( Parker 2015 (C) ); 10.6 mg per 11 g rice for cold‐extruded and 7.5 mg per 100 g rice for hot‐extruded ( Perignon 2016 (C) ), 20 mg iron ( Moretti 2006b ; Hotz 2008 ), 0.8% by weight ( Gershoff 1977 ). One study on women reported ferrous sulphate as the iron compound used ( Losso 2017 ). Two studies did not specify the iron compound ( Ara 2019 ; Hardinsyah 2016 ).

Cooking methods

In three studies, rice was washed prior to cooking ( Angeles‐Agdeppa 2008 ; Moretti 2006b ; Radhika 2011 ). However, the manner of cooking was not described in sufficient detail to categorise based on the protocol for this review. In ( Moretti 2006b ), in addition to rice being washed in preparation for cooking, rice portions were cooked with seasoning ingredients in household pressure cookers for 8 min after reaching peak pressure, after which pressure was released. Test servings contained 35 g cooked rice.

One study used the absorption method of cooking rice ( Perignon 2016 (C) ; author correspondence). Lunch menus were prepared in rotating order and usually consisted of rice together with chicken or fish and occasionally with vegetables. The schools also provided free milk (200 mL) daily to all children. Weekly iron supplementation, which had been given to the children by health officers or village health volunteers before the intervention, was not provided during the intervention. This was to improve the chance of showing an improvement in iron status even though it was not the primary outcome measure ( Pinkaew 2014 ). In Burundi, parent committees performed all the cooking ( Parker 2015 (C) ). The other studies did not describe the manner of cooking rice.

All but one study ( Parker 2015 (C) ), described the accompanying dishes or menu. The study on female teenagers ( Hardinsyah 2016 ), reported the cooking methods as pouring one sack of fortified rice into a plastic bucket to wash the rice, and steaming for about one hour until the rice was cooked well. One study ( Losso 2017 ), was done as a pilot among women from the Baton Rouge area (Louisiana (LA), USA), wherein they tested the iron retention of fortified rice by several methods of cooking; however there was no description of the type cooking used for the clinical study. Similarly, Ara 2019 did not specify the method of cooking.  

Comparisons

Twelve studies (2201 participants) made this comparison.

No studies contributed data to this comparison.

One study (74 participants) made this comparison, having a vitamin A‐only arm versus a control arm.

Of the 12 RCTs included in the meta‐analysis, seven reported on anaemia ( Angeles‐Agdeppa 2008 ; Hardinsyah 2016 ; Hotz 2008 ; Parker 2015 (C) ; Perignon 2016 (C) ; Radhika 2011 ; Thankachan 2012 ). Five out of the twelve RCTs used WHO thresholds to define anaemia based on serum haemoglobin concentrations (Hb) ( Hardinsyah 2016 ; Moretti 2006b ; Parker 2015 (C) ; Perignon 2016 (C) ; Radhika 2011 ), three used a cut‐off level but did not mention the cut‐off criteria ( Angeles‐Agdeppa 2008 , Pinkaew 2013 Thankachan 2012 ), one RCT ( Hotz 2008 ), used CDC 1989 criteria and three RCTs did not report the cut‐off used to define anaemia ( Hussain 2014 ; Losso 2017 ; Pinkaew 2014 ). Among the included non‐randomised studies, three mentioned Hb cut‐off to define anaemia, but did not specify the criteria ( Ara 2019 ; Della Lucia 2016 ; Gershoff 1977 ), one used WHO criteria ( Nogueira Arcanjo 2013 ), and one study did not report a Hb cut‐off ( Salcedo 1950 ). The details of the cut‐off used in each included study are given in Table 7 . We used data from these studies in the meta‐analysis irrespective of the criteria used by them to define anaemia. Three studies reported iron‐deficiency anaemia ( Moretti 2006b ; Radhika 2011 ; Thankachan 2012 ); however we did not use these data in quantitative synthesis.

Nine studies reported iron deficiency ( Angeles‐Agdeppa 2008 ; Hardinsyah 2016 ; Hotz 2008 ; Hussain 2014 ; Moretti 2006b ; Perignon 2016 (C) ; Pinkaew 2013 ; Radhika 2011 ; Thankachan 2012 ); we included eight in the meta‐analysis. We did not include data from Hussain 2014 because the subgroup‐specific details were not available for further analysis.

To evaluate iron deficiency, seven studies used plasma ferritin concentrations (Angeles‐Agdeppa 2008; Hotz 2008; Hussain 2014 ; Losso 2017; Moretti 2006a; Radhika 2011; Thankachan 2012), four studies used serum transferrin receptor concentrations ( Hotz 2008 ; Losso 2017 ; Moretti 2006b Thankachan 2012 ), wherein two studies (Moretti 2006a; Thankachan 2012 ), used and reported both these parameters.

Eleven studies reported mean haemoglobin concentrations ( Angeles‐Agdeppa 2008 ; Hardinsyah 2016 ; Hotz 2008 ; Hussain 2014 ; Losso 2017 ; Moretti 2006b ; Parker 2015 (C) ; Perignon 2016 (C) ; Pinkaew 2013 ; Radhika 2011 ; Thankachan 2012 ), four studies evaluated vitamin A deficiency ( Hardinsyah 2016 ; Perignon 2016 (C) ; Pinkaew 2014 ; Thankachan 2012 ), and one study reported plasma folate concentration ( Hardinsyah 2016 ). One study reported the level of diarrhoea ( Thankachan 2012 ). No studies compared the groups for respiratory infections (as measured by study authors) or all‐cause death in their outcomes. One study reported on hookworm infection ( Perignon 2016 (C) ). One study reported abdominal pain ( Thankachan 2012 ). No studies reported congenital anomalies or miscarriage (no studies were carried out among pregnant women). Five studies reported serum retinol ( Angeles‐Agdeppa 2008 ; Hardinsyah 2016 ; Pinkaew 2013 ; Pinkaew 2014 ; Thankachan 2012 ), three studies reported plasma zinc concentration ( Hardinsyah 2016 ; Pinkaew 2014 ; Thankachan 2012 ).

One study ( Moretti 2006b ), reported anthropometric measurements (weight‐for‐age, height‐for‐age, weight‐for‐height in terms of Z‐score) whereas Angeles‐Agdeppa 2008 reported prevalence of wasting and stunting. No studies compared the risk of iron overload (defined by serum ferritin higher than 150 µg/L in women and higher than 200 µg/L in men), clinical and severe malaria, night blindness (defined as the inability to see after dusk by people who typically report having normal vision during the day; only for vitamin A fortified rice as an intervention), across the groups

The controlled before‐and‐after studies reported biochemical outcomes relevant to iron, vitamin A, zinc and folate in addition to clinical outcomes such as beriberi ( Della Lucia 2016 ; Gershoff 1977 ; Nogueira Arcanjo 2013 ; Salcedo 1950 ). In Ara 2019 , they included anaemia, mean haemoglobin (g/L), zinc deficiency (< 10.1 mmol/L), mean serum zinc (mmol/L), morbidity (last two weeks), diarrhoea, fever and inflammation (CRP >10.0 mg/L) as the outcomes. Gershoff 1977 study reported the effect of consumption of rice fortified with multiple vitamins, however they did not report the total number of outcomes in the entire study population, hence their report did not reach the stage of meta‐analysis.

Sources of funding

Most included studies were funded by one or more agencies from the government sector, private sector, academic organisations, or non‐government organisations. One study did not report the source of financial support ( Losso 2017 ).

Angeles‐Agdeppa 2008 stated its source of funding was The International Life Sciences Institute Center for Health Promotion of Japan (ILSI CHP, Japan), and the ILSI CHP, Atlanta, USA. Taiyo Kagaku, Japan donated the necessary fortificant used in this study.

DSM Nutritional Products (India) provided fortified rice for Thankachan 2012 . Another study, Gershoff 1977 , reported that they were supported in part by the United States Agency for International Development and the Fund for Research and Teaching, Department of Nutrition, Harvard School of Public Health. Also, that Ajinomoto Company, Tokyo, Japan supplied the rice fortification grains.

Two RCTs ( Pinkaew 2013 ; Pinkaew 2014 ), were supported by Medicor Foundation (Triesen, Liechtenstein), the Royal Thai Government Scholarship. Also, Pinkaew 2014 study was supported by the International Atomic Energy Agency (Vienna, Austria). The Micronutrient Initiative, Ottawa, Canada, along with the Swiss Federal Institute of Technology, Zurich, Switzerland, and St John’s Academy of Health Sciences, Bangalore, India supported Moretti 2006b and Dr. Paul Lohmann (GmbH, Emmerthal, Germany) provided the iron and zinc compounds, and DSM Nutritional Products Ltd. (Basel, Switzerland) provided the vitamin A compound for Moretti 2006b ; Pinkaew 2013 ; and Pinkaew 2014 . Radhika 2011 was funded by the Department of Biotechnology, New Delhi, India. The Program for Appropriate Technology in Health (PATH), Seattle, USA provided the Ultra Rice premix for them. United States Department of Agriculture (USDA) and the Open Road Alliance funded one study ( Parker 2015 (C) ). USDA, the World Food Programme‐DSM Consortium, and the Institut de Recherce pour le Development (IRD) supported Perignon 2016 (C) .

A subcontract grant from PATH through an original grant from Bill & Melinda Gates Foundation provided the funding for Hotz 2008 . The Food and Nutrition Society of Indonesia supported Hardinsyah 2016 . Williams‐Waterman Fund Committee of the Research Corporation, New York City funded Salcedo 1950 , and Hoffmann‐LaRoche, Inc., Nutley, New Jersey, USA donated the premix that they used. Della Lucia 2016 had financial support from O Programa Institucional de Bolsas de Iniciação Científica e Tecnológica da (PROBIC/FAPEMIG), PIBIC/CNPq and FAPEMIG and PATH donated the fortified rice. The United Nations World Food Programme (Grant # 1209) funded the study conducted in Bangladesh by Ara 2019

Excluded studies

We excluded 28 articles from 22 studies after assessing the full‐text articles. The details of excluded studies along with the reasons for exclusion are given in Characteristics of excluded studies .

See Figure 2 for reasons for excluding the articles. Nine studies were related to a different type of intervention or rice was not the medium of intervention ( Arsenault 2010 ; Bagni 2009 ; Barboza 2011 ; Castro 2017 ; Finkelstein 2013 ; Graham 2007 ; Haskell 2005 ; Sridevi 2013 ; Vitolol 1998 ), six studies with participants outside the age range of interest ( Beinner 2010 ; Ma 2016 ; Nogueira Arcanjo 2012 ; Pham 2012 ; Skau 2015 ; Walter 1993 ); five studies with different type of study design ( Ando 2012 ; Angeles‐Agdeppa 2011 ; Florentino 1998 ; Huo 2014 ; Kagawa 2017 ), and two studies had insufficient information ( Hyun 2015 ; Pham Van 2013 ).

We have provided details of two ongoing studies in Characteristics of ongoing studies table.

Risk of bias in included studies

We used standardised domains to assess the risk of bias of included studies (including individually and cluster‐randomised trials) ( Higgins 2019 ). We assessed the primary outcomes for risk of bias at the study level. We considered additional domains for risk of bias among the cluster‐RCTs. We presented them in the 'Risk of bias' table in the Characteristics of included studies section, and give a summary of the ’Risk of bias’ analyses in Figure 3 and Figure 4 . Among the 12 RCTs contributing to the meta‐analysis, two studies had a low overall risk of bias ( Moretti 2006b ; Radhika 2011 ), having low risk in allocation concealment, differences in baseline outcome measures, and incompleteness of outcome data. We assessed all other RCTS to be at high overall risk of bias. The five controlled before‐and‐after studies had high or unclear risk of bias for most domains ( Ara 2019 ; Della Lucia 2016 ; Gershoff 1977 ; Nogueira Arcanjo 2013 ; Salcedo 1950 ). Two of these studies had a documented difference in baseline outcome measures ( Della Lucia 2016 ; Nogueira Arcanjo 2013 ). Also, Ara 2019 had different baseline and end‐line populations.

'Risk of bias' summary: review authors' judgements about each 'Risk of bias' item for each included study

Four studies were controlled before‐and‐after studies ( Ara 2019 ; Della Lucia 2016 ; Gershoff 1977 ; Nogueira Arcanjo 2013 ), and one was a controlled cross‐sectional study ( Salcedo 1950 )

'Risk of bias' graph: review authors' judgements about each 'Risk of bias' item presented as percentages across all included studies

Sequence generation

We noted three studies adequately describing the sequence generation for the recruitment of study participants in their respective studies ( Hotz 2008 ; Perignon 2016 (C) ; Thankachan 2012 ), and we graded them to be at low risk of bias. We assessed four studies at high risk of bias for not having random sequence generation ( Ara 2019 ; Della Lucia 2016 ; Gershoff 1977 ; Salcedo 1950 ), and 10 studies to be at unclear risk ( Angeles‐Agdeppa 2008 ; Hardinsyah 2016 ; Hussain 2014 ; Losso 2017 ; Moretti 2006b ; Nogueira Arcanjo 2013 ; Parker 2015 (C) ; Pinkaew 2013 ; Pinkaew 2014 ; Radhika 2011 ) ; all four studies at high risk of bias for random sequence generation were before‐and‐after comparison studies.

Allocation concealment

Five studies reported allocation concealment completely in their methods ( Della Lucia 2016 ; Hardinsyah 2016 ; Moretti 2006b ; Perignon 2016 (C) ; Radhika 2011 ), and we assessed them to be at low risk of bias. Six studies did not effectively conceal allocation ( Angeles‐Agdeppa 2008 ; Ara 2019 ; Gershoff 1977 ; Pinkaew 2013 ; Pinkaew 2014 ; Salcedo 1950 ), and we assessed them at high risk of bias, and six studies were at unclear risk ( Hotz 2008 ; Hussain 2014 ; Losso 2017 ; Nogueira Arcanjo 2013 ; Parker 2015 (C) ; Thankachan 2012 ).

Similarity of baseline characteristics

We assessed 13 studies to be at low risk of bias for similarity of baseline characteristics ( Angeles‐Agdeppa 2008 ; Ara 2019 ; Hardinsyah 2016 ; Hotz 2008 ; Hussain 2014 ; Losso 2017 ; Moretti 2006b ; Nogueira Arcanjo 2013 ; Pinkaew 2013 ; Pinkaew 2014 ; Radhika 2011 ; Salcedo 1950 ; Thankachan 2012 ). Two studies were at high risk of bias ( Gershoff 1977 ; Perignon 2016 (C) ), and two studies were at unclear risk ( Della Lucia 2016 ; Parker 2015 (C) ).

Overall, seven studies were at high risk of selection bias ( Angeles‐Agdeppa 2008 ; Ara 2019 ; Gershoff 1977 ; Perignon 2016 (C) ; Pinkaew 2013 ; Pinkaew 2014 ; Salcedo 1950 ) with high risk of bias in any one of the domains of selection bias.

For similarity of baseline outcome measurements, nine studies were at low risk of bias ( Angeles‐Agdeppa 2008 ; Hotz 2008 ; Hussain 2014 ; Losso 2017 ; Moretti 2006b ; Pinkaew 2013 ; Pinkaew 2014 ; Radhika 2011 ; Thankachan 2012 ), seven studies were at high risk of bias ( Ara 2019 ; Della Lucia 2016 ; Gershoff 1977 ; Hardinsyah 2016 ; Nogueira Arcanjo 2013 ; Parker 2015 (C) ; Perignon 2016 (C) ), and we assessed one study as unclear risk of bias ( Salcedo 1950 ).

Eight studies described the blinding process for the participants adequately and we graded them to be at low of bias in blinding the participants ( Angeles‐Agdeppa 2008 ; Hardinsyah 2016 ; Losso 2017 ; Moretti 2006b ; Nogueira Arcanjo 2013 ; Perignon 2016 (C) ; Radhika 2011 ; Thankachan 2012 ), five studies were at low risk of bias in blinding the outcome assessment ( Angeles‐Agdeppa 2008 ; Moretti 2006b ; Nogueira Arcanjo 2013 ; Radhika 2011 ; Thankachan 2012 ), and seven studies were at low risk in terms of contamination ( Ara 2019 ; Hardinsyah 2016 ; Hussain 2014 ; Losso 2017 ; Nogueira Arcanjo 2013 ; Parker 2015 (C) ; Perignon 2016 (C) ). Overall, four studies ( Hardinsyah 2016 ; Losso 2017 ; Nogueira Arcanjo 2013 ; Perignon 2016 (C) ), were at low risk of performance bias and five studies gave an account of blinding the outcome assessors which we assessed to be at low risk of detection bias ( Angeles‐Agdeppa 2008 ; Moretti 2006b ; Nogueira Arcanjo 2013 ; Radhika 2011 ; Thankachan 2012 ).

We assessed 13 studies at unclear risk of blinding. Two studies were at unclear risk of blinding the participants and personnel ( Della Lucia 2016 ; Parker 2015 (C) ), six studies for blinding of outcome assessment ( Della Lucia 2016 ; Hardinsyah 2016 ; Hussain 2014 ; Perignon 2016 (C) ; Pinkaew 2013 ; Pinkaew 2014 ), and nine studies for contamination ( Della Lucia 2016 ; Gershoff 1977 ; Hotz 2008 ; Moretti 2006b ; Pinkaew 2013 ; Pinkaew 2014 ; Radhika 2011 ; Salcedo 1950 ; Thankachan 2012 ).

Ten studies were at high risk of blinding. Seven studies were at high risk of blinding of the participants ( Ara 2019 ; Gershoff 1977 ; Hotz 2008 ; Hussain 2014 ; Pinkaew 2013 ; Pinkaew 2014 ; Salcedo 1950 ), six studies for blinding of outcome assessment ( Ara 2019 ; Gershoff 1977 ; Hotz 2008 ; Losso 2017 ; Parker 2015 (C) ; Salcedo 1950 ), and one study was at high risk of contamination ( Angeles‐Agdeppa 2008 ).

Incomplete outcome data

We assessed 11 studies to be at low risk of bias for completeness of outcome data ( Angeles‐Agdeppa 2008 ; Hardinsyah 2016 ; Hussain 2014 ; Losso 2017 ; Moretti 2006b ; Nogueira Arcanjo 2013 ; Perignon 2016 (C) ; Pinkaew 2013 ; Pinkaew 2014 ; Radhika 2011 ; Thankachan 2012 ), and they reported minimum loss to follow‐up rates among the study participants. Two studies were at high risk of bias ( Hotz 2008 ; Salcedo 1950 ), because of high rates of dropout from the study, and we assessed four studies at unclear risk of bias due to inadequate description of attrition ( Ara 2019 ; Della Lucia 2016 ; Gershoff 1977 ; Parker 2015 (C) ).

Selective reporting

There was no indication of selective reporting by any of the studies from published records, however we did not have access to the study protocols. Ten studies reported all of their pre‐specified outcomes, including the insignificant ones, and we assessed them to be at low risk of bias ( Angeles‐Agdeppa 2008 ; Ara 2019 ; Losso 2017 ; Moretti 2006b ; Parker 2015 (C) ; Perignon 2016 (C) ; Pinkaew 2013 ; Pinkaew 2014 ; Radhika 2011 ; Thankachan 2012 ); one of these studies provided a study registration number for the protocol ( Pinkaew 2014 ). We assessed one study at high risk of reporting bias because the study participants were given rewards for maintaining highest attendance in the schools in which the attendance rate was not steady ( Hardinsyah 2016 ). We assessed six studies to be at unclear risk of bias ( Della Lucia 2016 ; Gershoff 1977 ; Hotz 2008 ; Hussain 2014 ; Nogueira Arcanjo 2013 ; Salcedo 1950 )

Other potential sources of bias

We could not identify other potential sources of bias in the included studies. For some studies, industry provided the fortificants or the rice fortification grains. We assessed three studies to be at low risk of bias ( Angeles‐Agdeppa 2008 ; Parker 2015 (C) ; Perignon 2016 (C) ), one study at high risk of bias ( Hardinsyah 2016 ), and 13 studies at unclear risk of bias ( Ara 2019 ; Della Lucia 2016 ; Gershoff 1977 ; Hotz 2008 ; Hussain 2014 ; Losso 2017 ; Moretti 2006b ; Nogueira Arcanjo 2013 ; Pinkaew 2013 ; Pinkaew 2014 ; Radhika 2011 ; Salcedo 1950 ; Thankachan 2012 ).

We evaluated and determined additional criteria for risk of bias in cluster‐randomised studies (i.e. recruitment bias, baseline imbalance, loss of clusters, incorrect analysis, compatibility with individual RCTs) for two studies ( Parker 2015 (C) ; Perignon 2016 (C) ). Among these criteria, Perignon 2016 (C) was at unclear risk for baseline imbalance because they did not describe clusters and did not report any process of statistical adjustment for clustering. For all remaining criteria, we judged both the studies to be at low risk of bias.

Effects of interventions

See: Table 1 ; Table 2

A summary of the effects of interventions is given in Table 1 and Table 2 .

We included 12 RCTs in the meta‐analysis. All 12 RCTs contained at least one arm with iron and compared with unfortified rice. No RCT had a 'no intervention' arm in their study. Of the 12 RCTs, six RCTs fortified with iron only, five RCTs fortified with iron and other micronutrients and one RCT had several fortified groups including iron only, vitamin A only and multiple micronutrients. Few of the pre‐specified outcome measures in this review were not reported by any of the included studies. We analysed the results using a random‐effects model, since all the included studies had significant heterogeneity. See Data and analyses for a detailed description of pre‐specified outcomes and their results.

We carried out sensitivity analyses for two cluster‐randomised trials ( Parker 2015 (C) ; Perignon 2016 (C) ), with different values of ICC and examined their effect on the effect estimates (RR) for two outcomes: anaemia and mean haemoglobin concentration. We observed that ICC did not change the direction of effects of interventions significantly for any outcome. We have presented the details of these sensitivity analyses in Table 8 . We also carried out sensitivity analysis by excluding the single RCT ( Parker 2015 (C) ), with a high/unclear risk of bias in eight out of 15 domains (including the additional domains for cluster‐RCTs) for two outcomes, anaemia and mean haemoglobin.

No studies looked at fortified rice versus no intervention, and we could not examine comparisons 2 and 4 to 8 because there were no studies looking at vitamin A, folic acid and zinc with other micronutrients that did not also include iron, and there were no studies with a 'no intervention' arm. However we undertook meta‐analysis for vitamin A versus unfortified rice since one study ( Hussain 2014 ), reported an intervention arm with vitamin A only compared with unfortified rice. We included this in comparison 3.

Rice fortified with iron alone or in combination with other micronutrients versus unfortified rice

There were 12 studies (2201 participants) included in this comparison ( Angeles‐Agdeppa 2008 ; Hardinsyah 2016 ; Hotz 2008 ; Hussain 2014 ; Losso 2017 ; Moretti 2006b ; Parker 2015 (C) ; Perignon 2016 (C) ; Pinkaew 2013 ; Pinkaew 2014 ; Radhika 2011 ; Thankachan 2012 ). These studies comprise all the data included in the synthesis of this Review. We included five non‐randomised studies in this comparison ( Ara 2019 ; Della Lucia 2016 ; Gershoff 1977 ; Nogueira Arcanjo 2013 ; Salcedo 1950 ) for qualitative assessment.

Anaemia (defined as haemoglobin (Hb) below the WHO cut‐off, adjusted for altitude as appropriate or as defined by the study authors)

We included seven studies in the analysis ( Angeles‐Agdeppa 2008 ; Hardinsyah 2016 ; Hotz 2008 ; Parker 2015 (C) ; Perignon 2016 (C) ; Radhika 2011 ; Thankachan 2012 ). The studies had a duration of four months ( Hardinsyah 2016 ), six months ( Angeles‐Agdeppa 2008 ; Hotz 2008 ; Parker 2015 (C) ; Perignon 2016 (C) ; Thankachan 2012 ), and eight months ( Radhika 2011 ). The detailed results are presented in Analysis 1.1 . Overall, the children who consumed iron‐fortified rice had similar levels of anaemia to controls at the end of the follow‐up period (RR 0.72, 95% CI 0.54 to 0.97; 7 studies; 1634 participants; low‐certainty evidence). Heterogeneity was high (Tau² = 0.10; Chi² = 23.27, df = 6; P = 0.0007; I 2 = 74%) and the results have to be interpreted with caution. One study ( Angeles‐Agdeppa 2008 ), reported direction of benefit favouring fortification, whereas Hotz 2008 ; Parker 2015 (C) ; Perignon 2016 (C) ; Radhika 2011 and Thankachan 2012 showed ambiguous direction. Exclusion of two studies, which clearly favoured fortification ( Angeles‐Agdeppa 2008 ; Hardinsyah 2016 ), changed the effect such that there was no effect on anaemia (RR 0.92, 95% CI 0.76 to 1.12; 1248 participants) and reduced heterogeneity among studies (Tau² = 0.01; Chi² = 5.08, df = 4; P = 0.28; I 2 = 21%). Exclusion of Parker 2015 (C) revealed a slight reduction in anaemia with fortification of rice (RR 0.66, 95% CI 0.49 to 0.89; I 2 = 61%; 1336 participants) and it reduced the heterogeneity slightly.

Comparison 1 Rice fortified with iron alone or in combination with other micronutrients versus unfortified rice (no micronutrients added)., Outcome 1 Anaemia (defined as haemoglobin (Hb) below the WHO cut‐off, adjusted for altitude as appropriate).

There was no clear evidence of differences between subgroups in terms of reduction of anaemia in any of the following subgroup analyses.

Comparison 1 Rice fortified with iron alone or in combination with other micronutrients versus unfortified rice (no micronutrients added)., Outcome 2 Anaemia (subgroup: by micronutrient content).

Comparison 1 Rice fortified with iron alone or in combination with other micronutrients versus unfortified rice (no micronutrients added)., Outcome 3 Anaemia (subgroup: by rice fortification method).

Comparison 1 Rice fortified with iron alone or in combination with other micronutrients versus unfortified rice (no micronutrients added)., Outcome 4 Anaemia (subgroup: by cooking method most commonly used in trial setting).

Comparison 1 Rice fortified with iron alone or in combination with other micronutrients versus unfortified rice (no micronutrients added)., Outcome 5 Anaemia (subgroup: by public health significance of anaemia at baseline ).

Comparison 1 Rice fortified with iron alone or in combination with other micronutrients versus unfortified rice (no micronutrients added)., Outcome 6 Anaemia (subgroup: by malaria endemicity).

Iron deficiency

We included eight studies in the analysis ( Angeles‐Agdeppa 2008 ; Hardinsyah 2016 ; Hotz 2008 ; Moretti 2006b ; Perignon 2016 (C) ; Pinkaew 2013 ; Radhika 2011 ; Thankachan 2012 ). We did not include data from Hussain 2014 in the meta‐analysis because the subgroup details (for each arm) related to iron deficiency were not available, since the study authors reported data only for overall fortification versus unfortified rice. The intervention in the included studies lasted four months ( Hardinsyah 2016 ), five months ( Pinkaew 2013 ), six months ( Angeles‐Agdeppa 2008 ; Hotz 2008 ; Perignon 2016 (C) ; Thankachan 2012 ), seven months ( Moretti 2006b ) and eight months ( Radhika 2011 ). Details are presented in Analysis 1.7 . Participants consuming rice fortified with iron or in combination with other micronutrients may have slightly lower levels of iron deficiency compared to those consuming unfortified rice (RR 0.66, 95% CI 0.51 to 0.84; 8 studies, 1733 participants; low‐certainty evidence). Heterogeneity was low (Tau² = 0.02; Chi² = 8.60, df = 7; P = 0.28; I 2 = 19%). The pooled estimate favours fortification, in which direction of benefit was positive for fortification in Moretti 2006b and Radhika 2011 . Also Hussain 2014 showed favourable effects towards fortification (48 out of 185 in the fortification arms together and 19 out of 37 in the control arm).

Comparison 1 Rice fortified with iron alone or in combination with other micronutrients versus unfortified rice (no micronutrients added)., Outcome 7 Iron deficiency (as defined by study authors, based on a biomarker of iron status).

There were no significant differences in iron deficiency due to consumption of iron‐fortified rice across the subgroups.

Comparison 1 Rice fortified with iron alone or in combination with other micronutrients versus unfortified rice (no micronutrients added)., Outcome 8 Iron deficiency (subgroup: by micronutrient content).

Comparison 1 Rice fortified with iron alone or in combination with other micronutrients versus unfortified rice (no micronutrients added)., Outcome 9 Iron deficiency (subgroup: by rice fortification method).

Comparison 1 Rice fortified with iron alone or in combination with other micronutrients versus unfortified rice (no micronutrients added)., Outcome 10 Iron deficiency (subgroup: by cooking method most commonly used in trial setting).

Comparison 1 Rice fortified with iron alone or in combination with other micronutrients versus unfortified rice (no micronutrients added)., Outcome 11 Iron deficiency (subgroup: by public health significance of anaemia at baseline ).

Comparison 1 Rice fortified with iron alone or in combination with other micronutrients versus unfortified rice (no micronutrients added)., Outcome 12 Iron deficiency (subgroup: by malaria endemicity).

We included 11 studies in the analysis ( Angeles‐Agdeppa 2008 ; Hardinsyah 2016 ; Hotz 2008 ; Hussain 2014 ; Losso 2017 ; Moretti 2006b ; ; Parker 2015 (C) ; Perignon 2016 (C) ; Pinkaew 2013 ; Radhika 2011 ; Thankachan 2012 ). The duration of the intervention varied between two weeks ( Losso 2017 ), and eight months ( Radhika 2011 ). The other included studies provided the intervention for four months ( Hardinsyah 2016 ), five months ( Pinkaew 2013 ), six months ( Angeles‐Agdeppa 2008 ; Hotz 2008 ; Hussain 2014 ; Perignon 2016 (C) ; Thankachan 2012 ) and seven months ( Moretti 2006b ; Parker 2015 (C) ). Details are presented in Analysis 1.13 . Consuming rice fortified with iron or in combination with other micronutrients may increase haemoglobin concentrations (g/L) in comparison to consuming unfortified rice (MD 1.83, 95% CI 0.66 to 3.00; 11 studies, 2163 participants; low‐certainty evidence). Heterogeneity was substantial (Tau² = 1.58; Chi² = 21.86, df = 10; P = 0.02; I² = 54%) and results should be interpreted with caution. The direction of benefit was towards fortification in three studies ( Angeles‐Agdeppa 2008 ; Hardinsyah 2016 ; Perignon 2016 (C) ). Exclusion of Parker 2015 (C) did not change the direction of the effect or the heterogeneity.

Comparison 1 Rice fortified with iron alone or in combination with other micronutrients versus unfortified rice (no micronutrients added)., Outcome 13 Haemoglobin concentration (g/L).

There were no clear differences between other subgroups, or any obvious asymmetry in the funnel plot ( Figure 5 ).

Funnel plot of comparison 1. Rice fortified with iron alone or in combination with other micronutrients versus unfortified rice (no micronutrients added), outcome 1.13, haemoglobin concentration (g/L)

Comparison 1 Rice fortified with iron alone or in combination with other micronutrients versus unfortified rice (no micronutrients added)., Outcome 14 Haemoglobin concentration (subgroup: by micronutrient content).

Comparison 1 Rice fortified with iron alone or in combination with other micronutrients versus unfortified rice (no micronutrients added)., Outcome 15 Haemoglobin concentration (subgroup: by rice fortification method).

Comparison 1 Rice fortified with iron alone or in combination with other micronutrients versus unfortified rice (no micronutrients added)., Outcome 16 Haemoglobin concentration (subgroup: by cooking method most commonly used in trial setting).

Comparison 1 Rice fortified with iron alone or in combination with other micronutrients versus unfortified rice (no micronutrients added)., Outcome 17 Haemoglobin concentration (subgroup: by public health significance of anaemia at baseline).

Comparison 1 Rice fortified with iron alone or in combination with other micronutrients versus unfortified rice (no micronutrients added)., Outcome 18 Haemoglobin concentration (subgroup: by malaria endemicity).

Vitamin A deficiency (as defined by the study authors)

Four studies contributed data for vitamin A deficiency ( Hardinsyah 2016 ; Perignon 2016 (C) ; Pinkaew 2014 ; Thankachan 2012 ). Details are provided in Analysis 1.19 . Consumption of fortified rice may make little or no difference to vitamin A deficiency (RR 0.68, 95% CI 0.36 to 1.29; 927 participants; 4 studies, low‐certainty evidence). Heterogeneity was marginally high (Tau² = 0.16; Chi² = 4.77, df = 3; P = 0.19; I² = 37%) and results have to be interpreted with caution. We did not include data from Hussain 2014 in the meta‐analysis, since the study authors reported vitamin A deficiency for the fortified rice group overall versus unfortified rice (37 out of 185 in the fortified arm and 22 out of 37 in the control arm). However their overall estimates had significant decrease in vitamin A deficiency in the fortified arm compared to control arm at the end of the six‐month intervention period.

Comparison 1 Rice fortified with iron alone or in combination with other micronutrients versus unfortified rice (no micronutrients added)., Outcome 19 Vitamin A deficiency (as defined by study authors, by using a biomarker of vitamin A).

There are no significant differences in the risk ratio across the subgroups. The details of subgroup analyses are presented below.

Comparison 1 Rice fortified with iron alone or in combination with other micronutrients versus unfortified rice (no micronutrients added)., Outcome 20 Vitamin A deficiency (subgroup: by micronutrient content).

Comparison 1 Rice fortified with iron alone or in combination with other micronutrients versus unfortified rice (no micronutrients added)., Outcome 21 Vitamin A deficiency (subgroup: by rice fortification method).

Comparison 1 Rice fortified with iron alone or in combination with other micronutrients versus unfortified rice (no micronutrients added)., Outcome 22 Vitamin A deficiency (subgroup: by cooking method most commonly used in trial setting).

Comparison 1 Rice fortified with iron alone or in combination with other micronutrients versus unfortified rice (no micronutrients added)., Outcome 23 Vitamin A deficiency (subgroup: by public health significance of anaemia at baseline ).

Comparison 1 Rice fortified with iron alone or in combination with other micronutrients versus unfortified rice (no micronutrients added)., Outcome 24 Vitamin A deficiency (subgroup: by malaria endemicity).

Serum or plasma folate (nmol/L)

One study reported the level or comparison of serum folate ( Hardinsyah 2016 ). The direction of benefit in this study was slightly towards fortified rice (MD 4.30, 95% CI 2.00 to 6.60; 1 study, 215 participants; low‐certainty evidence). The details are given in Analysis 1.25 .

Comparison 1 Rice fortified with iron alone or in combination with other micronutrients versus unfortified rice (no micronutrients added)., Outcome 25 Serum or plasma folate (nmol/L).

Any adverse effects (hookworm infection risk)

One study ( Perignon 2016 (C) ), reported that children given fortified rice were more likely to have hookworm infection compared to those given unfortified rice (RR 1.78, 95% CI 1.18 to 2.70, 1 study, 785 participants; low‐certainty evidence; Analysis 1.26 ).

Comparison 1 Rice fortified with iron alone or in combination with other micronutrients versus unfortified rice (no micronutrients added)., Outcome 26 Any adverse effects.

Any adverse effects (abdominal pain more than three days)

One study ( Thankachan 2012 ), reported that children given fortified rice were just as likely to have abdominal pain compared to those given unfortified rice (average RR 0.77, 95% CI 0.42 to 1.42; Analysis 1.26 ).

Diarrhoea (as defined by study authors; for studies among children aged 2 to 11.9 years of age)

One study reported the comparison of diarrhoeal episodes across the fortified and unfortified groups ( Thankachan 2012 ). There was no difference in the risk of diarrhoea (average RR 3.52, 95% CI 0.18 to 67.39; 1 study, 258 participants, very low‐certainty evidence; Analysis 1.27 ).

Comparison 1 Rice fortified with iron alone or in combination with other micronutrients versus unfortified rice (no micronutrients added)., Outcome 27 Diarrhoea (as defined by study authors).

Respiratory infections (for studies among children aged 2 to 11.9 years of age)

The included studies mentioned the episodes of respiratory infections in intervention and control groups during the study period, however, none reported the differences across the groups following rice fortification.

All‐cause death (for studies among children aged 2 to 11.9 years of age)

None of the included studies reported deaths.

Congenital anomalies (for studies among pregnant women with folic acid‐fortified rice as intervention)

No studies involved pregnant women.

Miscarriage (for studies among pregnant women)

Serum or plasma retinol (µmol/L)

Five studies reported the outcome of serum retinol (µmol/L) across the iron‐fortified and unfortified groups ( Angeles‐Agdeppa 2008 ; Hardinsyah 2016 ; Hussain 2014 ; Pinkaew 2014 ; Thankachan 2012 ). Details are presented in Analysis 1.28 . Participants consuming rice fortified with iron alone or other micronutrients had a marginally higher plasma retinol compared to those consuming unfortified rice (MD 0.04, 95% CI −0.13 to 0.21; 5 studies; 727 participants). Heterogeneity was high (Tau² = 0.03; Chi² = 60.39, df = 4 P < 0.00001; I 2 = 93%). Two studies favoured fortification ( Angeles‐Agdeppa 2008 ; Hussain 2014 ), and three had ambiguous results ( Hardinsyah 2016 ; Pinkaew 2014 ; Thankachan 2012 ). Heterogeneity was explained by one study ( Hardinsyah 2016 ), and its removal showed a higher mean difference favouring fortification (MD 0.20, 9% CI 0.18 to 0.22). This study had seven micronutrients.

Comparison 1 Rice fortified with iron alone or in combination with other micronutrients versus unfortified rice (no micronutrients added)., Outcome 28 Serum or plasma retinol (µmol/L).

Three studies reported the effectiveness of multiple micronutrient‐fortified rice on the level of serum or plasma zinc among children ( Hardinsyah 2016 ; Pinkaew 2014 ; Thankachan 2012 ). See Analysis 1.29 for details (MD 0.38, 95% CI −0.08 to 0.83; I 2 = 28%; 3 studies, 618 participants).

Comparison 1 Rice fortified with iron alone or in combination with other micronutrients versus unfortified rice (no micronutrients added)., Outcome 29 Serum or plasma zinc (µmol/L).

Anthropometric measures

One study ( Moretti 2006b ), contributed data to the outcome height‐for‐age Z‐score and weight‐for‐height Z‐score. The mean difference for height‐for‐age Z‐score was 0.02 (95% CI −0.32 to 0.36; 1 study, 184 participants; Analysis 1.30 ) and for weight‐for‐height Z‐score mean difference was 0.13 (95% CI −0.19 to 0.45; 1 study, 184 participants; Analysis 1.31 ). For both these outcomes, fortification may or may not make a difference.

Comparison 1 Rice fortified with iron alone or in combination with other micronutrients versus unfortified rice (no micronutrients added)., Outcome 30 Height‐for‐age Z‐score.

Comparison 1 Rice fortified with iron alone or in combination with other micronutrients versus unfortified rice (no micronutrients added)., Outcome 31 Weight‐for‐height Z‐score.

No studies reported the aspects of iron overload.

Clinical and severe malaria

None of the included studies had details on malaria across any of the study groups. Few studies had declared they were conducted in malaria non‐endemic areas.

Night blindness (defined as the inability to see after dusk by people who typically report having normal vision during the day; only for vitamin A‐fortified rice as an intervention)

No studies with vitamin A reported night blindness.

No studies contributed data for this outcome.

Rice fortified with vitamin A alone or in combination with other micronutrients versus unfortified rice

We included one study in this comparison ( Hussain 2014 ).

Anaemia (defined as haemoglobin (Hb) below the WHO cut‐off, adjusted for altitude as appropriate)

One study contributed data for this analysis ( Hussain 2014 ). The study had five intervention arms; we included the retinyl palmitate arm with the fortification arm and the arm without fortification as the control arm for this comparison. The study authors reported a significant increase in the haemoglobin concentration in the vitamin A‐fortified arm compared to the unfortified control arm (MD 10.00, 95% CI 8.79 to 11.21; 1 study, 74 participants; low‐certainty evidence; Analysis 2.1 ).

Comparison 2 Rice fortified with vitamin A alone or in combination with other micronutrients versus unfortified rice (no micronutrients added), Outcome 1 Haemoglobin concentration (g/L).

Vitamin A deficiency (as defined by study authors, by using a biomarker)

We did not include any studies in this meta‐analysis. One study ( Hussain 2014 ), reported vitamin A deficiency; however there were no data on vitamin A deficiency status in the arm fortified with vitamin A only. Their estimates are reported for the fortification arms in total. Details of their findings are in comparison 1.

One study contributed data to this analysis ( Hussain 2014 ). Fortification of rice with vitamin A probably increases the serum retinol concentration compared to unfortified rice (MD 0.17, 95% CI 0.13 to 0.21; 1 study, 74 participants; low‐certainty evidence; Analysis 2.2 ).

Comparison 2 Rice fortified with vitamin A alone or in combination with other micronutrients versus unfortified rice (no micronutrients added), Outcome 2 Serum or plasma retinol (µmol/L).

Any adverse effects (abdominal pain more than 3 days)

Summary of non‐randomised studies.

The value of the controlled before‐and‐after studies was mixed. Salcedo 1950 documented a reduction in clinical beriberi. Gershoff 1977 reported on the changes in amino acid intake and weight and length but did not make any formal estimates of change. One of the more recent studies, Nogueira Arcanjo 2013 , comparing iron‐fortified rice versus unfortified rice showed no change in mean haemoglobin but with an increase in anaemia in the unfortified group. The study comparing multiple micronutrient‐fortified rice with unfortified rice compared outcomes relative to baseline values within the fortified group and the unfortified group ( Della Lucia 2016 ). In the fortified group, there was an improvement in folic acid, thiamine and serum zinc, but not for haemoglobin or ferritin. In the unfortified group, there was an improvement in thiamine and ferritin concentrations. The groups were unbalanced with respect to ferritin levels, being significantly higher in the fortified group at baseline.

In Nogueira Arcanjo 2013 , the groups were different in the prevalence of anaemia at baseline: 8.9% (11/120 were anaemic) in the group receiving iron‐fortified rice, and 20.8% (30/144 were anaemic) in the group receiving unfortified rice (P = 0.009). At the end of the study, the groups remained different, 10.5% (13/120) among the participants receiving iron‐fortified rice, and 37.5% (54/144) among those receiving unfortified rice (P < 0.001). There was a statistically significant increase in anaemia prevalence in the control group receiving standard unfortified rice; however, the iron‐fortified rice group did not present a statistically significant change in the number of anaemic children after the intervention. Also, the groups were similar for haemoglobin concentration: 120.6 ± 10.1 g/L in the fortified rice group versus 124.0 ± 41.4 g/L in the unfortified rice group, P = 0.38; but after intervention, there was no significant difference between the groups, P = 0.56. The after intervention period haemoglobin concentrations were 121.4 ± 10.6 g/L in the fortified rice group and 122.9 ± 24.8 g/L. Among only anaemic participants, in the group receiving iron‐fortified rice before intervention, mean haemoglobin value was 101.2 ± 8.5 g/L (n = 11) and 115.6 ± 8.6 after intervention, P = 0.0003; in the control group receiving unfortified rice (n = 30), mean haemoglobin concentrations changed from 108.3 ± 11.1 g/L at baseline to 109.4 ± 11.8 g/L after intervention, P = 0.18. For the standard rice school: baseline mean haemoglobin was 124.0 ± 41.4 g/L, and after intervention 122.9 ± 24.8, P = 0.78. Considering only anaemic participants, there was a significant increase in haemoglobin means before and after intervention, P = 0.003 in the fortified rice school.

In the other controlled before‐and‐after study ( Gershoff 1977 ), the average haemoglobin concentration among those children consuming less than 10% or no fortified rice for all ages (5 to 9 years of age) was 114.6 g/L ± 6.6 (n = 135) in 1971 and changed to 119.8 g/L ± 12.6 (n = 135) in 1975. On the other hand, the average haemoglobin concentration among those children consuming more than 66% of fortified rice for all ages (5 to 9 years) was 117.7 g/L ± 8.8 (n = 61) in 1971 and 122.5 g/L ± 11.8 (n = 61) in 1975. These changes were not significant.

Summary of main results

We have summarised the findings here and in Table 1 and Table 2 . We included 17 studies in this review, 12 of which were RCTs. Two of the RCTs were cluster‐randomised trials. Five studies had a before‐and‐after study design that compared micronutrient‐fortified rice with unfortified rice. All the included studies had unfortified rice in the control arm. There were no studies comparing fortified rice with no intervention arm.

We considered 12 RCTs for the meta‐analysis. Ten RCTs were conducted in children and two were among non‐pregnant and non‐lactating women. All studies included in this review had unfortified rice as the control. All the studies included iron in their intervention arms (one study by Hussain 2014 with multiple arms had one fortification group with vitamin A only). Five studies included rice fortified with iron alone and one study had one arm with iron alone as the intervention. Seven studies used multiple micronutrients (six in children; one in women). Vitamin A, zinc, folate and vitamin B were the additional micronutrients. Four studies fortified with vitamin A, five studies fortified with zinc and three studies fortified with folic acid. The fortification profile of the included studies is shown in Table 6 .

Participants consuming rice fortified with iron alone or in combination with other micronutrients were just as likely to be anaemic as those taking unfortified rice (7 RCTs, low‐certainty evidence); however, fortification of rice may reduce the risk of iron deficiency (8 RCTs, low‐certainty evidence). Considering the low level of certainty, rice fortification may make an improvement in the mean haemoglobin levels (g/L; 11 RCTs). Consumption of fortified rice may make little or no difference to vitamin A deficiency (4 RCTs, low‐certainty evidence), it may improve serum or plasma folate (1 RCT). Two studies reported on three adverse effects of diarrhoea, hookworm infection risk and abdominal pain of more than three days' duration. We are uncertain about the risk of diarrhoea (1 RCT, very low‐certainty evidence). Children given fortified rice may have a higher risk of hookworm infection compared to those given unfortified rice (1 RCT, low‐certainty evidence) and there may not be any difference in terms of abdominal pain of more than three days.

We noted a slight improvement in serum or plasma retinol (µmol/L) concentration among the participants consuming fortified rice (5 RCTs). There is no difference in serum zinc concentration (µmol/L; 3 RCTs), height‐for‐age Z‐score (1 RCT) and weight‐for‐height Z‐score (1 RCT) with fortification.

We included one RCT under the comparison of vitamin A alone or in combination with other micronutrients versus unfortified rice, since all other RCTs that included vitamin A in their fortification arm, also had iron. So they were only included in the first comparison, to avoid duplication.

Participants consuming rice fortified with vitamin A alone tend to have higher mean haemoglobin levels (1 RCT) and serum retinol levels (1 RCT).

The controlled before‐and‐after studies were significant in showing the first evidence of a clinical outcome attributable most likely to rice fortification ( Salcedo 1950 ), and the extent by which dietary content is improved ( Gershoff 1977 ). The limitations of unbalanced groups, most likely due to the absence of random allocation into treatment groups, limits our interpretation of the two studies in Brazil ( Della Lucia 2016 ; Nogueira Arcanjo 2013 ), however both provide a foundation for planning studies on zinc and folate, both of which have very few studies.

Overall completeness and applicability of evidence

The review includes studies on preschool and school‐age children, and non‐pregnant, non‐lactating women. We found no studies for adolescents only (except one study that included adolescent girls), pregnant or lactating women or adult males. All but one study were from low‐ and middle‐income countries, where anaemia prevalence among children aged 6 to 59 months of age ranged between 26% to 59% ( WHO 2015a ). The studies with serum retinol as outcomes were conducted in countries where the prevalence of vitamin A deficiency among preschoolers ranged from 16% to 62% ( WHO 2009a ).

Almost all randomised clinical trials used micronized ferric pyrophosphate and the hot extrusion method, with three studies including either a cold or warm extrusion arm. Of the four vitamins and minerals identified for review, studies were found to have investigated four (iron, vitamin A, folate and zinc). All but one study had haemoglobin data but not all studies reported the mean haemoglobin or anaemia rates. Although three studies included folic acid as one of the fortificants, folate status was reported in only one. Also, most of the included RCTs were conducted in school settings. The certainty of evidence for anaemia and iron deficiency was low. For haemoglobin concentration, it was very low‐certainty evidence. This being a closed and controlled set up, generalising the findings of such studies becomes a challenge for the present systematic review. There could also be an interplay of co‐interventions like other added micronutrients to the same fortified rice, dosage and absorption of iron and consumption of other nutritive items, which would alter the overall estimate of effect.

Another potential aspect of the rice fortification and its effect on malnutrition is the duration of intervention. The included studies had a duration of follow‐up from two weeks to four years. However in the included RCTs, one study had a follow‐up of two weeks, other studies ranged from four months to eight months. Thus there could be a role played by the duration of intervention and follow‐up.

Quality of the evidence

Among the RCTs that contributed to the meta‐analysis, we assessed two studies as having overall low risk of bias and one study as having a high or unclear risk of bias in most of the domains. Excluding this study favoured fortification and altered the conclusion for anaemia (from no effect to a reduction of anaemia) and the conclusion for the multiple micronutrient subgroup in comparison 1 for mean haemoglobin (from no effect to an increased mean difference). Most of these studies inadequately described their randomisation sequence generation. Close to half had an unclear description of allocation concealment and blinding of outcomes. Most of the studies had low attrition rate.

The GRADE assessment of the certainty of evidence was low for anaemia (no effect), iron deficiency (favours fortification), vitamin A deficiency (no effect), serum or plasma folate (one included study favouring fortification), and adverse events (one study reported hookworm infection risk higher with fortification) in the comparison of iron alone or in combination with other micronutrients versus no fortification. The certainty of the evidence was also low for mean haemoglobin (may favour). We rated the outcome diarrhoea (no effect) as very low‐certainty evidence. We mainly downgraded studies due to inconsistency and imprecision in the estimates. In the comparison of vitamin A alone versus no fortification, one RCT contributed data and we graded the certainty of evidence for haemoglobin concentration and serum retinol concentration as low.

Further research is very likely to have an important impact on our confidence in the estimates of effect and is likely to change the results.

Potential biases in the review process

Two review authors independently carried out the review process, with the same data extraction sheet and tools to assess risk of bias in the included studies. Many studies had minimum information regarding the randomisation procedure, allocation concealment and blinding. In the absence of precise details, we considered mutual discussion among review authors as final in this review, since these included subjective components. We also extensively searched grey literature and trials registries, along with contacting agencies involved in carrying out RCTs and subject experts; thus minimising publication bias in this review. Also there was no language limit set in this systematic review for searches as well as obtaining abstracts/full‐text articles. We sought the help of translators to convert non‐English‐language articles to English. This would minimise the language bias in this review.

Agreements and disagreements with other studies or reviews

Our review is the first systematic review and meta‐analysis specific to rice as a vehicle to fortification as a public health intervention. There are systematic reviews and meta‐analyses of micronutrient fortification of staples, condiments and processed foods including all age groups, but these do not include a subgroup analysis specifically for rice ( Das 2013 ; Gera 2012 ). Only two of the 12 studies included in our review were included in Das 2013 and our review did not include infants and young children under two years of age. In Das 2013 , staple foods fortified with iron were found to improve mean haemoglobin and serum ferritin concentrations, and reduce the risk of anaemia. Staple foods fortified with vitamin A improved mean haemoglobin and serum retinol concentrations. Cereals fortified with zinc improved zinc serum levels. Staple foods fortified with iron had no impact on iron indicators among women. The two reviews agreed that fortification with iron improved mean haemoglobin concentrations. Our review showed a reduction of iron deficiency, while Das 2013 showed an improvement in serum ferritin concentrations. There was no agreement between Das 2013 and this review on the impact on anaemia, vitamin A and zinc concentrations or deficiency. The systematic review by Gera 2012 included only apparently healthy individuals and examined the effect of fortified food items on haematological outcomes. They concluded that food items fortified with iron led to improvement in haemoglobin, serum ferritin and iron status and there by reduced the risk of anaemia.

Another systematic review and meta‐analysis evaluated the effect of fortification of staples with zinc on serum zinc levels and zinc deficiency ( Shah 2016 ). Zinc‐fortified staples were compared with food without zinc. None of the studies included in our review were included in Shah 2016 . Shah 2016 showed that fortification of foods with zinc alone, but not in combination with other micronutrients, improved serum zinc levels. Our review did not have a comparison of rice fortified with zinc alone with unfortified rice, but rice fortified with zinc and other micronutrients did not improve zinc levels. In both reviews, the certainty of evidence was low for zinc.

A systematic review of rice fortification included seven studies among children aged 6 to 59 months ( Hijar 2015 ). They did not carry out a meta‐analysis and the search strategy was more limited than that used in our review. The population also included children less than two years, who we excluded from our review. None of the studies in our review were included in the review by Hijar 2015 . They reported that rice fortification was effective in correcting iron deficiency among children aged less than five years. The improvement was not significant for vitamin A‐fortified rice.

Another systematic review of rice fortification with no age restrictions included 12 studies that fortified rice with iron, four studies that fortified with vitamin A and two that included other micronutrients ( De Pee 2017 ). They gave a description of the direction of the effects, but did not perform a meta‐analysis. The review by De Pee 2017 concluded that with the available evidence of efficacy, stability and needs, rice should be fortified with multiple micronutrients including iron, zinc, and vitamins A, B 1 (thiamin), B 3 (niacin) B 6 (pyridoxine), B 9 (folic acid) and B 12 (cobalamin). The meta‐analysis in our review shows evidence of an effect of iron on mean haemoglobin and iron deficiency; of vitamin A fortification on vitamin A deficiency; and of folate fortification on folate deficiency. Another review on issues related to rice fortification in correcting micronutrient deficiency compiled the evidence from available primary studies to conclude that rice fortification is an effective strategy ( Piccoli 2012 ).

Implications for practice

Fortification of rice has been recommended as an effective strategy for reducing micronutrient deficiencies. This review shows that fortification of rice may make no difference on anaemia and there are probable effects on blood haemoglobin concentration (an indicator used in diagnosis of anaemia). However, the review suggests that fortification of rice with iron may reduce iron deficiency. There is some evidence that these effects may be greater in single nutrient fortification than multiple micronutrient fortification. There is also evidence that fortification of rice with iron, vitamin A and other micronutrients may improve serum retinol concentrations, may not reduce the risk of vitamin A deficiency, and it may improve plasma folate. There is no evidence that fortification improves zinc levels.

This review may provide enough evidence supporting the effectiveness of fortification for anaemia and iron status. However, more evidence is needed for other micronutrients. Moreover, more thought may have to be given to the number of micronutrients added as this appears to have some bearing on the effect of fortification of rice.

Implications for research

The certainty of evidence for the outcome of anaemia and iron deficiency was low. The certainty of outcome change in mean haemoglobin was also low. There were considerable differences in the effects of single and multiple nutrient fortification. Single nutrient fortification with iron compound was found to be superior to multiple micronutrient interventions in terms of improvement in iron deficiency and haemoglobin concentration. A similar observation could be made when exploring heterogeneity in serum retinol results, with heterogeneity mainly due to one study with multiple micronutrients. Very few studies reported adverse effects, and a substantial number did not report the manner of cooking or malaria endemicity. There were only a handful of studies that used cold extrusion. We identify the following areas of research.

• More, high‐quality randomised controlled trials (RCTs) with anaemia as a reported outcome. Given that anaemia, rather than iron deficiency or mean haemoglobin is a more common indicator of national nutrition programmes, it is important to have better evidence on this outcome.
• RCTs that directly compare the efficacy or effectiveness of iron‐fortified rice, and iron and other micronutrient‐fortified rice with unfortified rice would inform policymakers on whether the reduced effect of the multiple micronutrient‐fortified rice described in this review happens in a controlled setting with the same population.
• RCTs directly comparing cold extrusion with unfortified rice would increase the evidence base for evaluating the effect of the cold extrusion method.
• RCTs should be encouraged to include the recording of solicited and unsolicited adverse effects and data relevant to rice fortification (e.g. manner of cooking) and iron metabolism (e.g. malaria and other parasitic infections like hookworm infection).
• RCTs with zinc and folate as outcomes would increase the evidence base as very few studies reported these.

Acknowledgements

We would like to thank the editorial staff of Cochrane Public Health, in particular Solange Durao, Anke Rohwer, Reza Yousefi‐Nooraie, Irma Klerings, Hilary Thomson and Newton Opiyo (Cochrane Public Health and Health Systems Network)” for their support throughout the preparation of this review. The review team also acknowledges the external referees, Mark Lawrence and Annhild Mosdøl for their useful input to this work.

We would to thank Joseph Ashong, Sumithra Muthayya, Arnaud Laillou, Christophe Guyondet, Regina Moench‐Pfanner, and Belinda J Burford for their work in the protocol and in the early stages of the review. Joseph Ashong, Sumithra Muthayya, Arnaud Laillou and Christophe Guyondet initially screened independently the records for eligibility in an early search in 2012. The whole process was repeated in 2016 to 2017 for this version of the review with a new review team.

We are grateful for technical support from Dr Lucero Lopez and Dr Ricardo X Martinez for the interpretation of the results from two non‐randomised studies.

Special thanks are due to Joanne Abbott, for her support in designing and running various updates to the search strategy. We would like to thank Mr Thomas Allen and Jose Luis Garnica from the World Health Organization Library Services for their support with the search in Agricola. We also thank all the authors who contributed additional details of their studies.

The World Health Organization retains copyright and all other rights in the manuscript of this review as submitted for publication, including any revisions or updates to the manuscript that they may make from time to time.

Appendix 1. Search strategy for electronic databases

Cochrane Central Register of Controlled Trials (CENTRAL) (CRSO)

#1 MESH DESCRIPTOR Micronutrients EXPLODE ALL TREES

#2 MESH DESCRIPTOR iron compounds

#3 MESH DESCRIPTOR zinc compounds

#4 MESH DESCRIPTOR iron, dietary EXPLODE ALL TREES

#5 ((micronutrient* or micro‐nutrient*)):TI,AB,KY

#6 ((multinutrient* or multi‐nutrient*)):TI,AB,KY

#7 ((multinutrient* or multi‐nutrient* or multi* nutrient* or multimicronutrient*)):TI,AB,KY

#8 ((multivitamin* or multi‐vitamin* or multi* vitamin*)):TI,AB,KY

#9 ( (multimineral* or multi‐mineral* or multi* mineral*)):TI,AB,KY

#10 ((trace adj (element* or mineral* or nutrient*))):TI,AB,KY

#11 ((iron or Fe or ferric* or ferrous* or zinc or Zn or vitamin* or retinol* or folate* or folic* or folacin*)):TI,AB,KY

#12 #1 OR #2 OR #3 OR #4 OR #5 OR #6 OR #7 OR #8 OR #9 OR #10 OR #11

#13 MESH DESCRIPTOR Food, Fortified EXPLODE ALL TREES

#14 (((fortifi* or enrich* or enhanc*) adj2 (food* or rice))):TI,AB,KY

#15 MESH DESCRIPTOR Oryza sativa EXPLODE ALL TREES

#16 #13 OR #14 OR #15

#17 #12 AND #16

#18 11/07/2012 TO 08/11/16

#19 #17 AND #18

MEDLINE and Medline in Process (OVID)

1 exp Micronutrients/ or iron compounds/ or zinc compounds/ or exp iron, dietary/

2 (micronutrient$ or micro‐nutrient$).ti,ab.

3 (multinutrient$ or multi‐nutrient$).ti,ab.

4 (multinutrient$ or multi‐nutrient$ or multi$ nutrient$ or multimicronutrient$).ti,ab.

5 (multivitamin$ or multi‐vitamin$ or multi$ vitamin$).ti,ab.

6 (multimineral$ or multi‐mineral$ or multi$ mineral$).ti,ab.

7 (trace adj (element$ or mineral$ or nutrient$)).ti,ab.

8 (iron or Fe or ferric$ or ferrous$ or zinc or Zn or vitamin$ or retinol$ or folate$ or folic$ or folacin$).ti,ab.

9 or/1‐8

10 exp Food, Fortified/

11 ((fortifi$ or enrich$ or enhanc$) adj2 (food* or rice)).ti,ab.

13 Oryza sativa/

14 or/10‐13

15 9 and 14

16 exp animals/ not humans.sh.

17 15 not 16

18 (201206* or 201207* or 201208* or 201209* or 201210* or 201211* or 201212* or 2013* or 2014* or 2015* or 2016*).ed.

19 17 and 18

Embase (OVID)

16 (animal/ or nonhuman/) not human/

18 (201206* or 201207* or 201208* or 201209* or 201210* or 201211* or 201212* or 2013* or 2014* or 2015* or 2016*).dd.

CINAHL (EBSCO)

June 2012 to Nov 2016 (n=152)

S20 S18 AND S19

S19 EM 20120601‐20151130

S18 S11 AND S16 Limiters ‐ Human

S17 S11 AND S16

S16 S12 OR S13 OR S14 OR S15

S15 Oryza sativa

S14 (MH "Rice")

S13 ((fortifi* or enrich* or enhanc*) N2

(food* or rice))

S12 (MH "Food, Fortified")

S11 S1 OR S2 OR S3 OR S4 OR S5 OR S6 OR

S7 OR S8 OR S9 OR S10

S10 (iron or Fe or ferric* or ferrous* or

zinc or Zn or vitamin* or retinol* or

folate* or folic* or folacin*)

S9 (trace N1 (element* or mineral* or

nutrient*))

S8 (multimineral* or multi‐mineral* or

multi* mineral*)

S7 (multivitamin* or multi‐vitamin* or

multi* vitamin*)

S6 (multinutrient* or multi‐nutrient* or

multi* nutrient* or multimicronutrient*)

S5 (multinutrient* or multi‐nutrient*)

S4 (micronutrient* or micro‐nutrient*)

S3 (MH "Zinc Compounds")

S2 (MH "Iron Compounds+")

S1 (MH "Micronutrients")

BIOSIS & Web of Science (ISI) SCI, SSCI, CPCI‐exp & CPCI‐SSH

2012 to 7/11/16 (n=1)

#10 #9 AND #8

#9 TOPIC: (((fortifi* or enrich* or enhanc*) N2 (food* or rice)))

#8 #7 OR #6 OR #5 OR #4 OR #3 OR #2 OR #1

#7 TOPIC: ((iron or Fe or ferric* or

ferrous* or zinc or Zn or vitamin* or

retinol* or folate* or folic* or

#6 TOPIC: ((trace N (element* or mineral*

or nutrient*)))

#5 TOPIC: ((multimineral* or multi‐

mineral* or "multi* mineral*"))

#4 TOPIC: ((multivitamin* or multi‐

vitamin* or "multi* vitamin*"))

#3 TOPIC: ((multinutrient* or multi‐

nutrient* or "multi* nutrient*" or

multimicronutrient*))

#2 TOPIC: ((multinutrient* or multi‐

#1 TOPIC: ((micronutrient* or micro‐

Popline & SCIELO

(micronutrient* OR micronutrient* OR multinutrient* OR multinutrient* OR multinutrient* OR multinutrient* OR multi* nutrient* OR multimicronutrient* OR multivitamin* OR multivitamin* OR multi* vitamin* OR multimineral* OR multimineral* OR multi* mineral* OR trace element* OR trace mineral* OR trace nutrient* OR iron OR Fe OR ferric* OR ferrous* OR zinc OR Zn OR vitamin* OR retinol* OR folate* OR folic* OR folacin*)

((fortifi* OR enrich* OR enhanc*) AND (food* OR rice))

2012‐2015

IBECS, PAHO, WHOLIS, AFRO and LILACS (BIRME)

(micronutrient$ or micro‐nutrient$) or (multinutrient$ or multi‐nutrient$) or (multinutrient$ or multi‐nutrient$ or multi$ nutrient$ or multimicronutrient$) or (multivitamin$ or multi‐vitamin$ or multi$ vitamin$) or (multimineral$ or multi‐mineral$ or multi$ mineral$) or trace element$ or trace mineral$ or trace nutrient$ or (iron or Fe or ferric$ or ferrous$ or zinc or Zn or vitamin$ or retinol$ or folate$ or folic$ or folacin$) [Words] and ((fortifi$ or enrich$ or enhanc$) and (food$ or rice)) [Words] and 2012 or 2013 or 2014 or 2015 [Country, year publication]

IMSEAR and EMRO (GLOBAL INDEX MEDICUS)

fortification

INMED & Native Health Research database

Rice AND fortify OR fortified OR enrich OR enriched

AGRICOLA (Ebsco)

#1 (ZU "micronutrients") OR (ZU "micronutrients concentration") OR (ZU "micronutrients uptake") OR (ZU "micronutrition") OR (ZU "micronycteris minuta")) OR ((ZU "iron compounds") OR (ZU "iron compounds‐congresses") OR (ZU "iron compounds‐structure") OR (ZU "iron concentration") OR (ZU "iron concretions") OR (ZU "iron consumption") OR (ZU "iron content") OR (ZU "iron contents"))) OR ((ZU "zinc compounds") OR (ZU "zinc contamination") OR (ZU "zinc content") OR (ZU "zinc coordination") OR (ZU "zinc deficiencies") OR (ZU "zinc deficiency") OR (ZU "zinc deficiency diseases") OR (ZU "zinc deficiency diseases‐congresses") OR (ZU "zinc deficiency diseases‐epidemiology") OR (ZU "zinc deficiency diseases‐united states") OR (ZU "zinc deficiency states‐congresses"))) OR ((ZU "dietary iron")) OR TI (multinutrient* OR multi‐nutrient* OR multinutrient * OR “multi‐nutrient*” OR “multi* nutrient*” OR multimicronutrient* OR multivitamin* OR multi‐vitamin* OR multi* vitamin* OR multimineral* or multi‐mineral* or multi* mineral* OR iron or Fe or ferric* or ferrous* or zinc or Zn or vitamin* or retinol* or folate* or folic* or folacin*) OR AB (multinutrient* OR multi‐nutrient* OR multinutrient* OR multi‐nutrient* OR multi* nutrient* OR multimicronutrient* OR multivitamin* OR multi‐vitamin* OR multi* vitamin* OR multimineral* OR multi‐mineral* OR multi* mineral* OR iron OR Fe OR ferric* OR ferrous* OR zinc OR Zn OR vitamin* OR retinol* OR folate* OR folic* OR folacin*)

#2 (fortified food) or (ZU "fortified food") or (ZU "fortified foods") or (ZU "fortified fruit beverages") or (ZU "fortified instant asian noodles") or (ZU "fortified milk") or (ZU "fortified musts") or (ZU "fortified seaweed extract") or (ZU "fortified soy protein powder") or (ZU "fortified vegetables") or (ZU "fortified vitamin juices") or (ZU "fortified water") or (ZU "fortifying agents") OR (ZU "rice") or (ZU "rice ( <i>oryza sativa</i> l.)") or (ZU "rice (<i>oryza sativa</i> l.)") or (ZU "rice (oriza sativa l.)") or (ZU "rice (oryza sativa cv tainung 67) suspension cells") or (ZU "rice (oryza sativa l)") or (ZU "rice (oryza sativa l. var. nipponbare)") or (ZU "rice (oryza sativa l.)") or (ZU "rice (oryza sativa l.) crop") or (ZU "rice (oryza sativa ssp. japonica)") or (ZU "rice (oryza sativa)") or (ZU "rice (oryza sativa) cells") or (ZU "rice (oryzae sativa l.)") or (ZU "rice (oryzae sativa)") or (ZU "rice (orzya sativa)") or (ZU "rice (qryza sativa l.)") or (ZU "rice act1 genes") or (ZU "rice aging") or (ZU "rice agriculture") or (ZU "rice agro‐residues") or (ZU "rice and rice products") or (ZU "rice as feeding stuff") or (ZU "rice as food") or (ZU "rice bibliography") or (ZU "rice blends") or (ZU "rice bran") or (ZU "rice bran protein") or (ZU "rice byproducts") or (ZU "rice cake") or (ZU "rice cake machines") or (ZU "rice cakes") or (ZU "rice cereals") or (ZU "rice consumption") or (ZU "rice cookie") or (ZU "rice cooking") or (ZU "rice council for market development") or (ZU "rice cracker") or (ZU "rice crackers") or (ZU "rice development") or (ZU "rice drink") or (ZU "rice economy") or (ZU "rice enrichment") or (ZU "rice exploitation") OR ((TI (fortifi* or enrich* or enhanc*) OR AB (fortifi* or enrich* or enhanc*)) N2 (TI (food* or rice) OR AB (food* or rice))) OR ((TI (fortifi* or enrich* or enhanc*) OR AB (fortifi* or enrich* or enhanc*) ) AND ((TI (food* or rice) OR AB (food* or rice)))

#3 ZU (rabbit* OR bird* OR chicken* OR soil* OR insect* OR Mice OR rat OR goat* OR sheep OR animal* OR livestock* OR cow*) OR ((ZE "animals") or (ZK "animal breeding and genetics") or (ZK "animal diseases (bacterial)") or (ZK "animal diseases (fungal)") or (ZK "animal diseases (general)") or (ZK "animal diseases (physiological)") or (ZK "animal diseases (viral)") or (ZK "animal disorders and injuries") or (ZK "animal ecology and behavior") or (ZK "animal nutrition") or (ZK "animal physiology and biochemistry") or (ZK "animal production") or (ZK "animal reproduction") or (ZK "animal science") or (ZK "animal structure") or (ZK "animal taxonomy and geography") or (ZK "pests of animals (general)") or (ZK "pests of animals (helminths)") or (ZK "pests of animals (insects and other arthropods)"))

#4 (#1 AND #2) NOT #3

#5 Limited to up to January 2017

Clinicaltrials.gov

"rice AND fortification", "rice AND enrichment","fortified rice" OR "enriched rice".

WHO International Clinical Trials Registry Platform (ICTRP)

"rice AND fortification", "rice AND enrichment","fortified rice" and "enriched rice". Duplicates were removed.

Data and analyses

Comparison 1.

Comparison 2

Characteristics of studies

Characteristics of included studies [ordered by study id].

BMI: body‐mass index; CBA: controlled before‐and‐after study; FFR: fortified rice; Hb: haemoglobin; ICC: intra‐cluster correlation; RCT: randomised controlled trial; SD: standard deviation; UN: United Nations; USAID: United States Agency for International Development; USDA: United States Department of Agriculture; VGD: Vulnerable Group Development; WFP: World Food Programme

Characteristics of excluded studies [ordered by study ID]

FFR: fortified rice; Hb: haemoglobin; RCT: randomised controlled trial

Characteristics of ongoing studies [ordered by study ID]

FFR: fortified rice; Hb: haemoglobin

Differences between protocol and review

We aimed at searching two databases in the protocol that were not available to us at the review stage: BIOSIS and Food Science and Technology Abstracts (FSTA). We also made the following changes from the published protocol ( Ashong 2012 ).

• We removed the subgroup analysis by prevalence of stunting in children under five years in the study site: moderate (number of children whose height‐for‐age Z‐score is between −2.0 and 2.99 standard deviations (SD) below the mean) versus severe stunting (number of children whose height‐for‐age Z‐score is less than −3.0 SD below the mean) versus mixed/unknown/unreported. This information was not available in most studies and not all studies were conducted in children. The most commonly used form of reporting was by mean Z‐score in each group rather than the prevalence.
• We removed the subgroup by iron compound as most studies used micronized pyrophosphate and ferrous sulphate, which have similar bioavailability with differences varying depending on encapsulation, particle size and other factors not captured in these studies.
• Given the different ways that diarrhoea was reported, we changed our protocol definition of three liquid stools in a single day, to any as defined by study authors in order to be able to capture this adverse effect, if present.
• We have included any adverse effects to primary outcomes. They are reported separately.
• We did not consider before‐and‐after studies without a control group for inclusion in this review as planned in protocol.
• We did not include data from non‐randomised studies in the quantitative synthesis and the review conclusions, since these studies provided little information on the comparative effectiveness of rice fortification in improving nutrition. However, we did include them in the qualitative synthesis because of their details on contextual aspects and concepts of fortification. We mentioned their findings under the subheading 'Summary of non‐randomised studies' at the end of the main synthesis.
• We have made the change from the proposed type of participants in the protocol being general population of all age groups (including pregnant women) from any country to general population older than two years of age (including pregnant women) from any country.
• We planned to examine the effects of two or more nutrients (in the same study arm) in multiple comparisons. However, owing to the duplication of findings because most of the studies had iron as one of the micronutrients in the fortification arm, we included multi nutrient studies in comparison 1 only and since one study had vitamin A only in one of the arms, we included it in comparison 2.

Contributions of authors

Protocol development: Joseph Ashong drafted an initial protocol with technical input from Sumithra Muthayya, Arnaud Laillou, Luz Maria De‐Regil and Juan Pablo Pena‐Rosas. Luz Maria De‐Regil, Belinda Burford and Juan Pablo Pena‐Rosas developed the methods of the protocol. All authors provided input and contributed to drafting the final version of the protocol.

Review development: all authors contributed to screening, extraction and assessment of data, as described in the Methods . MNGC, JPP and LMD prepared the GRADE 'Summary of findings' tables. All the review authors wrote and approved the final manuscript.

Juan Pablo Peña‐Rosas is the guarantor for the review.

Disclaimer: Juan Pablo Peña‐Rosas and Maria Nieves Garcia‐Casal are full‐time staff members of the World Health Organization. The review authors alone are responsible for the views expressed in this publication and they do not necessarily represent the official position, decisions, policy or views of the World Health Organization.

Sources of support

Internal sources.

• Centre for Health Innovation and Partnership, NSW Health, North Parramatta, Australia.
• Department of Nutrition for Health and Development, World Health Organization, Switzerland.

External sources

WHO provided partial financial support from the Department of Nutrition for Health and Development for this work for some of the authors of this review.

WHO thanks GAIN for their financial support for conducting systematic reviews on micronutrient interventions. SM received partial financial support from GAIN during the preparation of the protocol.

The National Center for Birth Defects and Developmental Disabilities provided financial support for conducting this systematic review.

WHO thanks Nutrition International for their financial support for conducting systematic reviews on micronutrient interventions.

WHO acknowledges the financial support from the Bill & Melinda Gates Foundation for the development of systematic reviews of the evidence on the effects of nutrition interventions.

Declarations of interest

Juan Pablo Peña‐Rosas (JPP) co‐ordinates the Evidence and Programme Guidance Unit, Department of Nutrition for Health and Development, which received financial resources from the Bill & Melinda Gates Foundation (2013‐2019); US Centers for Disease Control and Prevention (CDC) (2014‐2019); Nutrition International (2014‐2019) and USAID (2014‐2019). Donors do not fund specific guidelines and do not participate in any decision related to the guideline development process including the composition of policy questions, membership of the guideline groups, the conduct and interpretation of systematic reviews, or the formulation of recommendations.

Prasanna Mithra (PM) received partial financial support from the Department of Nutrition for Health and Development, World Health Organization for this work.

B Unnikrishnan (BUK) received partial financial support from the Department of Nutrition for Health and Development, World Health Organization for this work.

Nithin Kumar (NK) received partial financial support from the Department of Nutrition for Health and Development, World Health Organization for this work.

Luz Maria De‐Regil (LMD) was a full‐time staff member of Nutrition International (formerly Micronutrient Initiative), an international not‐for‐profit organisation that delivers nutrition interventions to children, women of reproductive age and pregnant women. Nutrition International supports the implementation of large‐scale research projects on food fortification. None of them met the inclusion criteria of this review. Nutrition International is a partner of the Food Fortification Initiative and receives funds from the Canadian Department of Foreign Affairs. LMD was an Editor for the Cochrane Developmental, Psychosocial and Learning Problems Group.

Sreekumar Nair (SN) received partial financial support from the Department of Nutrition for Health and Development, World Health Organization for this work.

Maria Nieves Garcia‐Casal (MNG) is a scientist in the Evidence and Programme Guidance Unit, Department of Nutrition for Health and Development, which received financial resources from the Bill & Melinda Gates Foundation (2013‐2019); US Centers for Disease Control and Prevention (CDC) (2014‐2019); Nutrition International (2014‐2019) and USAID (2014‐2019). Donors do not fund specific guidelines and do not participate in any decision related to the guideline development process including the composition of policy questions, membership of the guideline groups, the conduct and interpretation of systematic reviews, or the formulation of recommendations.

Juan Antonio Solon (JAS) is president of the Nutrition Center of the Philippines, a non‐profit organisation working towards nutrition security (www.ncp.org.ph). He received partial financial support for this work. His involvement with the review was at the final stage where he helped with the interpretation of the results.

References to studies included in this review

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• Review article
• Open access
• Published: 21 October 2019

Nutritional and functional properties of coloured rice varieties of South India: a review

• Rathna Priya T. S. 1 ,
• Ann Raeboline Lincy Eliazer Nelson 1 ,
• Kavitha Ravichandran 1 &
• Usha Antony 1  

Journal of Ethnic Foods volume  6 , Article number:  11 ( 2019 ) Cite this article

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Rice is a major cereal food crop and staple food in most of the developing countries. India stands second in the production of rice next to China. Though almost 40,000 varieties of rice are said to exist, at present, only a few varieties are cultivated extensively, milled and polished. Even if white rice is consumed by most people around the world, some specialty rice cultivars are also grown. These include the coloured and aromatic rice varieties. The nutritional profile of the specialty rice is high when compared to the white rice varieties. The coloured rice, which usually gets its colour due to the deposition of anthocyanin pigments in the bran layer of the grain, is rich in phytochemicals and antioxidants. Rice bran, a by-product of the rice milling industry is under-utilised, is rich in dietary fibre which finds application in the development of functional foods and various other value-added products. Thus, more focus on specialty rice and its by-products will not only save it from becoming extinct but also lead a step forward towards nutrition security of the country as they are abundant in vitamins, minerals and polyphenols.

Introduction

Rice is a major cereal crop consumed as a staple food by over half of the world’s population. Consumption of rice is very high in developing countries and nations in Asia. Almost 95% of the rice production is done in Asian countries and about half of the world’s population consumes it. The cultivation of rice ranks third in the production of agricultural commodity next to sugarcane and maize. It is the predominant dietary energy source of 17 countries in Asia and the Pacific, 9 countries in North and South America and 8 countries in Africa. India is one of the major centres for rice production. The area for rice cultivation in India comprises about 43,388,000 hectares of land [ 1 ] and rice contributes to 780 and 689 kcal/capita/day of the food supply in Asia and India, respectively. Furthermore, India is one of the largest countries in terms of energy consumption from agriculture and rice comprises a major part of it [ 2 ].

Rice is rich in genetic diversity, with thousands of varieties grown throughout the world and India is home to 6000 varieties, at present. Originally, India had more than 110,000 varieties of rice until 1970, which were lost during the Green Revolution with its emphasis on monoculture and hybrid crops [ 3 ]. Paddy comes in many different colours, including brown, red, purple and even black. The colourful varieties of rice are considered valuable for their health benefits. The unpolished rice with its bran has high nutrient content than milled or polished white rice. However, rice consumers prefer to consume polished white rice, despite the fact that brown rice contains valuable nutrient content [ 4 ]. A detailed analysis on the nutrient content of rice suggests that the nutrition value varies depending upon several factors such as the strain or variety (i.e. white , brown , red and black /purple), nutrient quality of the soil in which rice is cultivated, the degree of milling and the method of preparation before consumption.

Origin and spread of rice

Oryza sativa , the dominant rice species, is a member of the Poaceae family. Historically, rice was cultivated widely in the river valleys of South and Southeast Asia 10,000 years ago [ 5 ] and it is believed to have originated probably in India. Domestication of rice in India is mainly attributed to the Indus valley civilization c. 3000–1500 BC [ 6 ]; however, the evidence of rice cultivation in India has been pushed to 4000 years ahead with the discovery of rice grains and early pottery found in the site of Lahuradewa, Uttar Pradesh, situated in the middle Ganges plains dating to c. 6409 BC [ 7 , 8 ].

Rice is highly adaptable to its environment of growth and this is evident from the fact that it is grown in north-eastern parts of China at latitude 53°N, on the equator in central Sumatra, and at 35°S in New South Wales, Australia. In India, it is grown below sea level in Kerala; most rice-growing areas are present at or near sea level and also, at elevations above 2000 m in Kashmir. Today, rice is cultivated in all parts of the world except Antarctica [ 9 ].

Importance of rice in India

India ranks second in the production of rice in the world next to China, accounting for 22.5% of overall world rice production. Rice is India’s pre-eminent crop and is the staple food of the people of the eastern and southern parts of the country. Apart from being nutritionally rich, rice has greater significance in India and holds great spiritual and ritual importance. As per Indian tradition, rice is revered as a potent symbol of auspiciousness, prosperity and fertility because of its life-sustaining qualities. Several rituals involving rice are performed during different occasions and festivals. In Tamil Nadu, kolam , a kind of geometric pattern, is drawn using rice flour at the threshold of the houses by women before sunrise. Rice also plays a vital role in wedding ceremonies in India. Dhanpan is a ritual wherein the family of bridegroom sends paddy, betel and/or turmeric to the house of the bride [ 10 ]. Rice mixed with turmeric is thrown on the couples during the wedding ceremony as a symbol of prosperity, eternity, continuity and fertility. The father of the bride organises a feast called Bhat (means, boiled rice) for the family and relations of the bridegroom [ 10 ]. The brides throw five handfuls of rice before leaving their parents’ home after the wedding to wish prosperity and wealth and remain with the family members. The bride enters her new home by pushing a glass or a jar full of rice while, rice is the first food offered to the bridegroom by the bride after marriage. In Tamil Nadu, the groom is offered a special variety of rice named Maappillai Samba to improve fertility [ 11 ]. Rice also plays a vital role during the baby shower function, named godh bharai in North India, valaikaapu in Tamil Nadu and seemandham in Kerala; on the event of birth; at the time of giving first solid food to the baby that is 6 or 7 months old; and during puberty in Kerala and Tamil Nadu. Flattened rice made from a variety called Thavala Kannan is given as offering in Kerala.

Rice also plays a prominent role in cultural celebrations of India, such as the festivals are based on sowing of seeds in the paddy field, transplanting the saplings in the fields, removal of weeds from the fields, harvesting of paddy, thrashing of paddy and storage of paddy [ 10 ]. The harvest festivals include Thai Pongal celebrated in the Tamizhian calendar month of Thai (falls in the month of January) in Tamil Nadu; Onam celebrated in the Malayalam month of Chingam (falls in the month of August or September) and Sankranti in Andhra Pradesh and Telangana, Makar Sankranti in Karnataka, Na-Khuwa Bhooj in rural Assam, Nabanna in West Bengal, and Nua khia or Navanna in Odisha; and Bihu in Assam celebrates the harvest of paddy. Thus, rice has not only shaped the history, culture, diet and economy of people but also the growth stage of the rice crop marks the passage of time and season. In India, rice is considered the root of civilization [ 12 ].

Production and market demand for rice varieties

Rice is a fundamental food in many cultural cuisines around the world. According to Ricepedia, more than 90% of production and consumption of rice in the world occur in Asia and the current share in global rice consumption is around 87%. In African countries, per capita consumption continues to increase than production [ 13 ]. The volume of international rice trade has increased almost sixfold, from 7.5 million tonnes annually in the 1960s to an average of 44.2 million tonnes during 2015–2016.

Based on the global market scenario with respect to rice, the production has increased slightly with years. The use of rice as food remains predominant compared to feed and other uses. The supply and utilisation of rice have also increased slightly (Table  1 ).

Similarly, rice is a major cereal crop and is consumed as a staple food by the majority of the population in India. India is one of the major centres for the production of rice. Both the Himalayan red rice and the Assam red rice find their place in international trade. The production of rice, wheat and maize has grown steadily over this period and that of rice is the highest followed by wheat (Table  2 ). In contrast, the production of other grains such as sorghum, pearl millet, finger millet, little millet and coarse cereals have either remained steady or have declined.

Rice is consumed by the rich and poor as well as rural and urban households. The per capita net availability of food grains increased after the Green Revolution, and rice is a part of the balanced diet along with vegetables, pulses, eggs, meat and fruits. The per capita net availability of rice increased to 69.3 kg/year in 2017 from 58.0 kg/year in 1951 [ 15 , 16 ]. Although rice is widely consumed, with years, the expenditure on cereals decreased from 26.3% in 1987–1988 to 12.0% in 2011–2012 and from 15% in 1987–1988 to 7.3% in 2011–2012 in rural and urban households, respectively. This overall dip in the expenditure may be due to the fact that more money is spent on non-food items in both rural and urban households [ 16 ].

Rice varieties

Among the 40,000 varieties of rice cultivated worldwide, only two major species are cultivated widely— Oryza sativa or the Asian rice and Oryza glaberrima or the African rice. The cultivation of Oryza sativa is practised worldwide; however, the cultivation of the Oryza glaberrima is confined to Africa [ 17 ].

Oryza sativa has two major subspecies: the Indica , long-grain rice and the Japonica , round-grain rice. Japonica rice is mainly cultivated and consumed in Australia, China, Taiwan, Korea, the European Union, Japan, Russia, Turkey and the USA. Indica rice varieties are grown widely in Asia [ 17 ]. These varieties also comprise of the fragrant ones which are priced as premium. The principal fragrant varieties are Hom Mali from Thailand and the various types of Basmati exclusively grown on the Himalayan foothills of India (in the states of Haryana and Punjab) and Pakistan (in the state of Punjab) [ 18 ].

The Indian rice varieties cultivated widely are Basmati , Joha , Jyothi , Navara , Ponni , Pusa , Sona Masuri , Jaya , Kalajiri (aromatic), Boli , Palakkad Matta , etc. The coloured variety includes Himalayan red rice; Matta rice, Kattamodon , Kairali , Jyothy , Bhadra , Asha , Rakthashali of Kerala; Red Kavuni , Kaivara Samba , Mappillai Samba , Kuruvi Kar , Poongar of Tamil Nadu, etc.

The shelf life of rice

In general, it is recommended to store rice in the form of paddy rather than as milled rice, since the husk provides protection against insects and helps prevent quality deterioration. Rice can be stored for long periods only if the following three conditions are met and maintained: (1) the moisture levels of grains, 14% or less and that of seeds must be 12% or less; (2) grains must be well protected from insects, birds and rodents; and (3) grains must be protected from rains or imbibing moisture from the atmosphere. In addition to its nutritive and medicinal properties, red rice and black rice possess several other special features and the most common one is their resistance to insects and pests during storage than brown rice. From the cultivation point of view, red rice possesses resistance to drought, flood, submergence, alkalinity, salinity, and resistance to pests and diseases [ 19 ].

Structure of rice grain

The paddy (also, rough rice or rice grain) consists of the hull, an outer protective covering, and the fruit or rice caryopsis (brown or dehusked rice) [ 20 ]. Rice primarily consists of carbohydrates, proteins and small quantities of fat, ash, fibre and moisture. Vitamins and minerals are largely confined to the bran and germ [ 21 ].

The polished white rice, usually consumed, is the highly refined version of raw rice. The processing and milling of raw rice take away significant parts of the grain, namely the bran and the germ. Both bran and germ are rich in dietary fibre as well as nutrients that are beneficial for human health. Further, if white rice undergoes additional polishing, its aleurone layer getsremoved leading to loss of more nutrients, as this layer is rich in vitamin B, proteins, minerals and essential fats.

In this aspect, the coloured rice finds an advantage as a healthier alternative to white rice. Coloured rice varieties and brown rice varieties have the same harvesting process apart from possessing similar nutritional profiles. These varieties are usually either dehulled or partially hulled with the bran and germ intact. Brown rice is found worldwide, while red rice is confined to the Himalayas, Southern Tibet, and Bhutan, as well as parts of North East and South India. After the removal of husk, brown rice still consists of few outer layers—the pericarp, seed-coat and nucellus; the germ or embryo; and the endosperm. The endosperm consists of the aleurone layer, the sub-aleurone layer and the starchy or inner endosperm (Fig.  1 ). The aleurone layer encloses the embryo. Pigments are confined to the pericarp layer [ 20 ].

Structure of rice grain (Copyright: FAO) [ 22 ]. Paddy consists of the husk, bran, aleurone layer, starchy endosperm and embryo. Brown rice is semi-polished, so it retains embryo while white rice is more polished than brown rice, lacking bran, aleurone and embryo. The removal of bran, aleurone and embryo provides aesthetic appeal to rice and improves shelf life; however, it also removes nutrients and minerals found in the grain

The hull (also, husk) constitutes about 20% of the rough rice weight, but values range from 16 to 28%. The aleurone layer varies from one to five cell layers; it is thicker at the dorsal than at the ventral side and thicker in short-grain than in long-grain rice [ 23 ]. The aleurone and embryo cells are rich in protein and lipid bodies [ 24 ].

The different layers of rice contain different quantities of nutrients. The bran layer is rich in dietary fibre, minerals and vitamin B complex while the aleurone layer contains the least. The endosperm of rice is rich in carbohydrate and also contains a reasonable amount of digestible protein, with favourable amino acid profile than other grains [ 25 ].

Rice processing

Processing of rice mainly involves milling of rice which converts paddy into rice by removing the hull and all or part of the bran layer. Milling of rice is a crucial stage and the objective of milling is to remove the husk and bran so as to produce an edible white rice kernel that is free from impurities.

Rabbani and Ali [ 26 ] report that as a result of processing, some essential nutrients like thiamine and vitamin B are lost. The milling process followed by polishing destroys 67% of the vitamin B 3 , 80% of vitamin B 1 , 90% of vitamin B 6 , 50% of manganese and phosphorus, 60% of the iron, and all of the dietary fibre, as well as the essential fatty acids present in the raw unmilled variety.

The rough rice (also, paddy) on milling produces brown rice, milled rice, germ, bran, broken and husk. Each of these has unique properties and can be used in numerous ways. The extent of value addition in rice and rice products depends upon the utilisation pattern of these components directly or as derivatives. For coloured rice varieties, only the first three steps of milling, namely, pre-cleaning, dehusking and separation, are applied and bran and germ are left intact.

Nutritional information

Raw, long-grain white rice is a good source of carbohydrates, calcium, iron, thiamine, pantothenic acid, folate and vitamin E when compared with maize, wheat and potatoes. It does not contain vitamin C, vitamin A, beta-carotene, lutein and zeaxanthin. It is also notably low in dietary fibre.

• Coloured rice

Brown rice retains its bran layer (containing vitamins, minerals and fibre), as this has not been polished more to produce white rice. The coloured rice varieties are either semi-polished or unpolished (Fig.  2 ). Red-coloured rice varieties are known to be rich in iron and zinc, while black rice varieties are especially high in protein, fat and crude fibre. Red and black rice get their colour from anthocyanin pigments, which are known to have free radical scavenging and antioxidant capacities, as well as other health benefits.

Some traditional South Indian rice varieties. a Red Kavuni . b Kaivara Samba . c Kuruvi Kar . d Poongar . e Kattu Yanam . f Koliyal . g Maappillai Samba. h Black Kavuni . Kavuni possesses anti-microbial activity. Kaivara Samba lowers blood sugar levels. Kuruvi Kar is resistant to drought and consumed by the locals for its health benefits. Poongar is consumed by women after puberty and is believed to avert ailments associated with the reproductive system. Kattu Yanam lowers glucose level in blood and also imparts strength. Koliyal is widely consumed as puttu , a specialty dish. Maapillai Samba has a hypocholesterolemic effect and anti-cancer activity and also improves fertility in men. Black Kavuni is resistant to drought and is popular among locals for its health benefits

Brown rice is highly nutritious. It has low calorie and has a high amount of fibre. Furthermore, it is a good source of magnesium, phosphorus, selenium, thiamine, niacin, vitamin B 6 and an excellent source of manganese. Brown rice and rough rice are rich in vitamins and minerals; this is due to the fact that the vitamins are confined to the bran and husk of the paddy. Rice bran and husk contain a higher amount of calcium, zinc and iron (Table  3 ).

Rice is rich in glutamic and aspartic acids but has a lower amount of lysine. The antinutritional factors that are concentrated mainly in the bran are phytate, trypsin inhibitors, oryzacystatin and haemagglutinin-lectin [ 25 ].

The moisture content plays a significant role in determining the shelf life of foods [ 29 ]. Xheng and Lan [ 30 ] report that moisture influences the milling characteristics and the taste of cooked rice. The differences in genetic makeup and the climatic conditions in which they are cultivated determine the moisture content in rice varieties. As seen from Table  4 , the moisture content of the red rice varieties is variable from 9.3 to 12.94%, the moisture content of brown rice and milled rice is lower than other rice varieties.

Protein is the second major component next to starch; it influences the eating quality and the nutritional quality of rice. In India, the dietary supply of rice per person per day is 207.9 g, this provides about 24.1% of the required dietary protein [ 2 ]. Rice has a well-balanced amino acid profile due to the presence of lysine, in superior content to wheat, corn, millet and sorghum and thus makes the rice protein superior to other cereal grains [ 36 ]. The lysine content of rice protein is between 3.5 and 4.0%, making it the highest among cereal proteins. The endosperm protein comprises of 15% albumin (water soluble), globulin (salt soluble), 5–8% prolamin (alcohol soluble), and the rest glutelin (alkali soluble) [ 27 ].

The coloured rice has high protein content than polished white rice due to the presence of bran. The Srilankan and Chinese varieties have higher protein content than the Indian varieties (Table  4 ). Rice bran proteins are rich in albumin than endosperm proteins. The aleurone protein bodies contain 66% albumin, 7% globulin and 27% prolamin and glutelin [ 37 ].

The fat present in rice is a good source of linoleic acid and other essential fatty acids. The rice does not contain cholesterol [ 36 ]. The lipids or fats in rice are mainly confined to the rice bran (20%, dry basis). It is present as lipid bodies in the aleurone layer and bran. The core of the lipid bodies is rich in lipids and the major fatty acids are linoleic, oleic and palmitic acids [ 38 , 39 ]. Starch lipids present in rice is composed of monoacyl lipids (fatty acids and lysophosphatides) complexed with amylose [ 40 ]. The amount of fat present in various fractions of rice and red rice indicate that red rice varieties from Sri Lanka and India have about 1% fat, while the China red rice has almost doubled this value (Table  4 ).

The presence of fibre in the diet increases the bulk of faeces, which has a laxative effect in the gut. The fibre content is 0.5–1.0% for well-milled rice [ 41 ]. Arabinoxylans, along with β-d-glucan, are the major component of soluble dietary fibre in rice. In addition, rhamnose, xylose, mannose, galactose and glucose are also present in soluble dietary fibre. Insoluble dietary fibre is made up of cellulose, hemicellulose, insoluble β-glucan and arabinoxylans. However, the quantity and amount of non-starch polysaccharide depend upon the rice cultivar, the degree of milling and water solubility [ 42 ]. Among the red rice varieties, Chak-hao amubi (Manipur black rice) has a significantly lower content of crude fibre (Table  4 ).

The variation in ash content of different cultivars of rice may be due to genetic factors or the mineral content of the soil [ 43 ]. The zinc and iron content of red rice is two to three times higher than that of white rice [ 44 ]. The most common minerals found in rice include calcium, magnesium, iron and zinc (Table  3 ).

The proximate composition of rice and its fractions are influenced by the kind of rice and degree of milling, as milling completely or partially removes the bran layer, aleurone layer and embryo. Thus, variation occurs in the nutrition content between the rice fractions of the same rice variety. The variations can be found in the amount of fats, fibre and minerals present in the grain.

Phytochemical composition

The non-nutritive plant chemicals that have a protective or disease-preventing property are known as phytochemicals. The phytochemical compounds are mainly accumulated in the pericarp and bran of the rice kernel. They prevent oxidative damage in foods and also have a wide spectrum of beneficial biological activities.

Phytochemicals present in rice can be divided into the following sub-groups namely carotenoids, phenolics, alkaloids, nitrogen and organo-sulphur containing compounds. Phenolic compounds are further sub-grouped as phenolic acids, flavonoids, coumarins and tannins. Anthocyanins, the major pigment responsible for the colour of red and black rice, are a kind of flavonoids. Maapillai Samba , a kind of red rice from Tamil Nadu, has the highest amount of total polyphenolic compounds and anthocyanin content than the varieties from Sri Lanka, China red rice and Manipur black rice (Table  5 ).

The pigmented cereal grains, such as red and purple/black rice, have phytochemical compounds in higher amounts than non-pigmented varieties. The phytochemicals such as cell wall-bound phenolics and flavonoids are gaining more interest as these compounds can be broken down by digestive enzymes and gut microflora, and as a result, they can be easily absorbed into the body [ 45 ].

The coloured rice bran contains anthocyanins that possess inhibition of reductase enzyme and anti-diabetic activities [ 46 ]. The reductase inhibitors possess anti-androgen effects and are used in the treatment of benign prostatic hyperplasia and to lower urinary tract symptoms. β-sitosterol present in Maappillai Samba (Fig.  2 g) has a hypocholesterolemic effect, improves fertility and also heals colon cancer. Furthermore, stigmasterol found in this variety is a precursor in the production of semi-synthetic progesterone [ 11 ].

Garudan Samba contains 9,12-octadecadienoic acid ( Z , Z ) which has the potential to act as hypocholesterolemic, anti-arthritic, hepatoprotective, 5-alpha-reductase inhibitor, anti-histaminic, anti-coronary and anti-androgenic effects. In addition to these compounds, it also contains several other bioactive compounds [ 47 ].

3-Cyclohexene-1-methanol and α, α,4-trimethyl- present in red Kavuni (Fig.  2 a) possess the anti-microbial activity, and also, 3-hydroxy-4 methoxy benzoic acid is used as a precursor for the synthesis of morphine. In addition to these compounds, fatty acid esters and fatty acids such as dodecanoic acid, ethyl ester (lauric acid ester) and octadecanoic acid are present. Among these bioactive compounds, octadecanoic acid and ethyl esters increase low-density lipoprotein (LDL) cholesterol in the human body [ 48 ].

Health benefits

Depending upon the flavours, culinary needs, availability and its potential health benefits, people choose different varieties of rice. Rice has the ability to provide fast and instant energy. Brown rice and red rice are great sources of fibre, B vitamins, calcium , zinc and iron, manganese, selenium, magnesium and other nutrients. The red and black rice variety gets its rich colour from a group of phytochemicals called anthocyanins, which are also found in deep purple or reddish fruits and vegetables.

Diabetes mellitus

Unlike white polished rice, brown rice releases sugars slowly thus helping to stabilise blood sugar in a sustained manner. This trait makes it a better option for people who are suffering from diabetes mellitus. Further, studies in Asia have shown a relationship between the consumption of white rice and risk of type 2 diabetes. Dietary fibres reduce the absorption of carbohydrates by providing an enclosure to the food, hindering the action of hydrolytic enzymes in the small intestine on food, and increasing the viscosity of food in the intestine [ 49 ]. This plays a vital role in reducing the GI of food thereby preventing the risk of diabetes type 2 [ 50 ]. Proanthocyanidins present in red rice provide protection against type 2 diabetes [ 51 ]. Similarly, anthocyanins present in black rice is said to have a hypoglycemic effect [ 52 ].

Brown rice is rich in manganese and selenium, which play a vital role against free radicals, which acts as a major cancer-causing agent. Due to the presence of these elements and high dietary fibre, brown rice is associated with a lowered risk of cancer. Studies have also correlated the use of whole grains like brown rice with lowered levels of colon cancer. This may be related to its high fibre content, as fibre gets attached to carcinogenic substances and toxins helps to eliminate them from the body, and also keep them away from attaching to the cells in the colon. Proanthocyanins, present in red rice, modulate the inflammatory response and protect against some cancers [ 51 ]. Similarly, anthocyanins which are found abundantly in black rice have anti-carcinogenic properties based on epidemiological and in vivo animal and human-based studies [ 53 ].

Cardiovascular disease

Brown rice may help in lowering the risk of metabolic syndrome, while metabolic syndrome itself is a strong predictor of cardiovascular disease. Red rice contains magnesium that prevents the risk of heart attacks [ 54 ]. Various high-fat diet-induced risk factors for cardiovascular disease were ameliorated by anthocyanin-rich extracts from black rice in rat models [ 55 ].

Cholesterol

Brown rice contains naturally occurring bran oil, which helps in reducing LDL forms of cholesterol. Intake of black rice has found to eliminate reactive oxygen species (ROS) such as lipid peroxide and superoxide anion radicals and lower cholesterol levels due to the presence of compounds such as anthocyanins, polyphenolic compounds, flavonoids, phytic acid, vitamin E and γ-oryzanol [ 56 , 57 ]. Modulation of inflammatory responses by proanthocyanidins in red rice provided protection from cardiovascular disease [ 51 ]. Based on these studies, it is evident that whole grains can lower the chances of arterial plaque buildup, thus reducing the chances of developing heart disease.

Hypertension

Both brown and red rice have high magnesium content than white rice. Magnesium is an important mineral that plays a vital role in the regulation of blood pressure and sodium balance in the body [ 54 ].

Rice varieties such as brown, red and black rice are rich in fibre and have the ability to keep healthy bowel function and metabolic function. Anthocyanins present in red rice have properties that can help in weight management [ 54 ].

Rice protein is hypoallergenic; products from other plant sources such as soy and peanut and animal sources like eggs and milk are a good source of proteins, yet they may cause allergy when consumed. Rice protein provides a solution to this problem because it is hypoallergenic. Furthermore, the anthocyanins present in red rice also have the property to reduce allergy [ 54 ].

Medicinal uses of coloured rice

Among several types of rice, few varieties are used to treat ailments. Every variety of rice is unique in its properties, so the treatment of diseases using rice is not limited to a single variety alone. Many different varieties of rice are employed in treating ailments because of their different properties and characteristics. According to practitioners of Ayurveda, rice creates balance to the humours of the body. Rice enriches elements of the body; strengthens, revitalises and energises the body by removing toxic metabolites; regulates blood pressure; and prevents skin diseases and premature ageing. Rakthasali (a kind of red rice) is efficient in subduing disturbed humours of the body and good for fevers and ulcers; improves eyesight, health, voice and skin health; and increases fertility [ 58 , 59 , 60 , 61 ]. In Ayurveda, Sali , Sashtika and Nivara rice are used to treat bleeding from haemorrhoids (piles); Sali rice is used to treat burns and fractures; Nivara rice is used to treat cervical spondylitis, paralysis, rheumatoid arthritis, neuromuscular disorders, psoriasis, skin lesions, reduce backache, stomach ulcers and snakebite; and Nivara rice is also used in the preparation of weaning food for underweight babies [ 58 , 62 ].

Rice water prepared by soaking rice in water or boiling rice in excess water is used to control diseases. In Ayurvedic preparations, rice varieties such as Mahagandhak ras , Kamdudha ras , Sutsekhar ras , Amritanav ras , Swarnmalti ras , Pradraripu ras , Laghumai ras , Dughdavati , Pradaknasak churna , Pushpnag churna , Sangrahat bhasm and Mukta sukti are used to control ailments such as vaginal and seminal discharges, diarrhoea, constipation and dysentery [ 58 ]. Red rice varieties are known to be used in the treatment of ailments such as diarrhoea, vomiting, fever, haemorrhage, chest pain, wounds and burns [ 63 ]. Matali and Lal Dhan are used for curing blood pressure and fever in Himachal Pradesh. Another red rice variety called Kafalya from the hills of Himachal Pradesh and Uttar Pradesh is used in treating leucorrhoea and complications from abortion [ 64 ]. Kari Kagga and Atikaya from Karnataka are used for coolness and also as a tonic, whereas Neelam Samba of Tamil Nadu is used for lactating mothers [ 65 ]. Kuruvi Kar is resistant to drought and consumed by the locals for its health benefits [ 66 ]. Raktasali is efficient in subduing deranged humours [ 60 , 61 ]. It was also regarded as a good treatment for ailments such as fevers and ulcers. It is also believed that it improves eyesight and voice; acts as diuretic, spermatophytic, cosmetic and tonic; and was also antitoxic [ 59 ].

Traditional food and its importance

Ayurvedic treatises mention red rice as a nutritive food and medicine, so the red rice is eaten as a whole grain. Red rice varieties such as Bhama , Danigora , Karhani , Kalmdani , Ramdi , Muru , Hindmauri and Punaigora of Jharkhand and Chattisgarh are rich in nutrition and provide energy and satiety for a whole day [ 67 , 68 ]. Traditionally, various foods such as pongal , puttu , adai , appam , idli , dosai , idiyappam , adirasam , kozhukattai , modakam , payasam , semiya , uppuma , flaked rice, puffed rice, etc. are prepared and consumed. In Tamil Nadu and Kerala, paddy is parboiled prior to milling. This hydrothermal process facilitates the migration of nutrients such as vitamins and minerals from the bran and the aleurone layer to the endosperm [ 69 ]. Rice takes the place of major cereal consumed in the South Indian diet while it is wheat that holds the position in North Indian diet. Dosai , idli , pongal , appam , semiya , uppuma , kichadi and idiyappam are prepared and consumed for breakfast along with wide varieties of chutney. The specialty dish called puttu made from rice is also prepared and consumed for breakfast. The lunch of South India is a combination of cooked parboiled rice, poriyal , eggs, meat, sambar , dal curry, rasam , pappad , moore (buttermilk) or curd and/or dessert, payasam . The dinner usually consists of idli , dosai , idiappam , cooked rice and curries. Various other dishes are also prepared from rice and include biryani, pulao, fried rice, curd rice, tamarind rice, sambar rice, jeera rice, lemon rice, coconut rice, etc. In Tamil Nadu, appams and idlis are also made using the red rice. Koliyal and Garudan Samba ( Kaadai Kazhuththaan ) of Tamil Nadu are used in the preparation of a specialty dish called puttu [ 47 ]. Flatbread and chapatti are made from red Gunja and glutinous rice is used in making puttu , a South Indian meal [ 70 ]. Several products such as cookies, murruku (a type of South Indian snack), are also made using the various coloured rice varieties.

Rice also plays a major role in festivals celebrated in India. The harvest festivals are celebrated with several delicacies made from freshly harvested paddy. In Tamil Nadu, sarkarai pongal is made from raw rice, green gram, milk and jaggery; in Assam, fried rice balls named ghila pitha are prepared and consumed; in West Bengal, traditional Bengali delicacies are made from freshly harvested rice and jaggery, the most famous one is home-made sweets from rice pitha and karpursal or banapuli , and Basmati rice is also used to make Bengali paish .

Parboiled red rice widely consumed in Kerala includes Thondi , Matta , Paal Thondi , Kuruva , Chitteni and Chettadi . Seeraga Samba is an aromatic rice variety consumed widely in Tamil Nadu and Kerala; it is known as ‘Basmati of South India’ and used in the preparation of biryani. Similarly, Jatu of Kulu valley, Ambemohar of Maharastra, Dubraj of Madhya Pradesh, Joha of Assam, Kamod of Gujarat, Badshah bhog of West Bengal and Odisha, Radhunipagla of West Bengal, Katrini and Kalanamak of Uttar Pradesh and Bihar, Gandha samba of Kerala, Kalajira of Odisha and Chakhao varieties of Manipur are prized for its aroma [ 64 , 67 ].

Today, the spotlight is on the increased production of these traditional varieties, promoting the consumption among the younger generation and production of nutritious and novel value-added products from coloured rice.

Although India is home to traditional red rice varieties and their use has been common among the practitioners of traditional medicine and communities as part of their cultural heritage, their functional effects and health benefits in terms of modern scientific methodology are far and few. Due to the insufficient availability of data, the beneficial properties of these varieties still remain unknown to a majority of the population. So, to leverage their health benefits, extensive research on these native coloured varieties by the stakeholders needs to be promoted so that they are available to consumers as a part of the daily diet or specialty functional foods.

Availability of data and materials

Not applicable

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RP initiated the idea of the article and authored all sections of the article except sections on medicinal uses of coloured rice, traditional food products and value-added products and new products. ARLEN authored sections on medicinal uses of coloured rice, traditional food products and value-added products and new products; co-authored other sections of the article KR co-authored the sections on the importance of rice in India, rice processing, production and demand of rice varieties, origin and spread of rice and value-added products and new products; and provided critical inputs to revise the manuscript. UA co-authored the sections on structure of grain, nutrition, health benefits and traditional food products; and provided critical inputs to revise the manuscript. All the authors read and approved the final manuscript.

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Rathna Priya, T., Eliazer Nelson, A.R.L., Ravichandran, K. et al. Nutritional and functional properties of coloured rice varieties of South India: a review. J. Ethn. Food 6 , 11 (2019). https://doi.org/10.1186/s42779-019-0017-3

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Rice research for food security and sustainable agricultural development in Asia: Achievements and future challenges

• Published: March 1995
• Volume 35 , pages 286–298, ( 1995 )

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• Hossain M. 1 &
• Fischer K. S. 1  

Rice is the major staple food of Asia, and an important source of employment and income in rural areas, particularly in low-income countries. Research has contributed significantly in achieving food security by increasing the yield potential of rice in irrigated systems, reducing the crop maturity period and achieving yield stability by developing resistance against major insects and diseases in the modern high-yielding varieties. Poverty is, however, still extensive in fragile rainfed rice ecosystems where rice yield has remained low, as scientists have yet to develop high-yielding varieties resistant to abiotic stresses and problem soils. Rice production needs to be increased by another 70% over the next 30 years to meet growing food needs. This has to be achieved with less land, less water, and less labor to accommodate the demand for these inputs from the expanding nonagricultural sectors. The challenge to the rice research community is to make further shifts in yield potential of rice for the irrigated systems, to close the yield gaps in the rainfed systems through developing resistance of high yielding varieties to abiotic stresses, and greater understanding of the interactions between genotypes and environment, developing durable resistance against pests and diseases to reduce farmers' dependence on harmful agrochemicals, and to increase efficiency in the use of water, labor and fertilizers. As further intensification of rice cultivation is inevitable, scientists must understand the negative environmental side-effects of increasing rice productivity, to develop appropriate mitigation options.

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Research progress on mirnas and artificial mirnas in insect and disease resistance and breeding in plants.

1. Introduction

2. progress in mirna research on insect resistance and breeding in plants, 2.1. plant endogenous mirnas, 2.2. insect endogenous mirnas, 3. progress in mirna research on disease resistance and breeding in plants, 4. application of artificial mirnas (amirnas) in research on plant resistance, 4.1. application of amirnas for insecticidal effects in plants, 4.2. application of amirnas for disease resistance in plants, 5. prospects and conclusions, 5.1. applications of rnai technology in crop production, 5.2. challenges in the application of mirna technology in crop breeding, 5.3. conclusions, author contributions, conflicts of interest.

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Ma, Z.; Wang, J.; Li, C. Research Progress on miRNAs and Artificial miRNAs in Insect and Disease Resistance and Breeding in Plants. Genes 2024 , 15 , 1200. https://doi.org/10.3390/genes15091200

Ma Z, Wang J, Li C. Research Progress on miRNAs and Artificial miRNAs in Insect and Disease Resistance and Breeding in Plants. Genes . 2024; 15(9):1200. https://doi.org/10.3390/genes15091200

Ma, Zengfeng, Jianyu Wang, and Changyan Li. 2024. "Research Progress on miRNAs and Artificial miRNAs in Insect and Disease Resistance and Breeding in Plants" Genes 15, no. 9: 1200. https://doi.org/10.3390/genes15091200

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• Published: 14 September 2024

OsWRKY70 Plays Opposite Roles in Blast Resistance and Cold Stress Tolerance in Rice

• Jiangdi Li 1 ,
• Yating Chen 1 ,
• Rui Zhang 1 ,
• Rujie Wang 1 ,
• Haiwen Zhang 2 &
• Guiqing Xiao 1  

Rice volume  17 , Article number:  61 ( 2024 ) Cite this article

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The transcription factor WRKYs play pivotal roles in the adapting to adverse environments in plants. Prior research has demonstrated the involvement of OsWRKY70 in resistance against herbivores and its response to abiotic stress. Here, we reported the functional analysis of OsWRKY70 in immunity against fungal diseases and cold tolerance. The results revealed that OsWRKY70 was induced by various Magnaporthe oryzae strains. Knock out mutants of OsWRKY70 , which were generated by the CRISPR/Cas9 system, exhibited enhanced resistance to M. oryzae . This was consistent with fortifying the reactive oxygen species (ROS) burst after inoculation in the mutants, elevated transcript levels of defense-responsive genes ( OsPR1b , OsPBZ1 , OsPOX8.1 and OsPOX22.3 ) and the observation of the sluggish growth of invasive hyphae under fluorescence microscope. RNA sequencing (RNA-seq) and quantitative real-time PCR (qRT-PCR) validations demonstrated that differentially expressed genes were related to plant-pathogen interactions, hormone transduction and MAPK cascades. Notably, OsbHLH6 , a key component of the JA signaling pathway, was down-regulated in the mutants compared to wild type plants. Further investigation confirmed that OsWRKY70 bound to the promoter of OsbHLH6 by semi-in vivo chromatin immunoprecipitation (ChIP). Additionally, the loss-function of OsWRKY70 impaired cold tolerance in rice. The enhanced susceptibility in the mutants characterized by excessive ROS production, elevated ion leakage rate and increased malondialdehyde content, as well as decreased activity of catalase (CAT) and peroxidase (POD) under low temperature stress was, which might be attributed to down-regulation of cold-responsive genes ( OsLti6b and OsICE1 ). In conclusion, our findings indicate that OsWRKY70 negatively contributes to blast resistance but positively regulates cold tolerance in rice, providing a strategy for crop breeding with tolerance to stress.

Introduction

Plant growth and development are greatly affected by biotic and abiotic stresses, including pathogen attacks, insect herbivory, extreme temperatures, high salinity and various other factors. To adapt to adverse environments, plants have evolved intricate regulatory mechanisms at the molecular, physiological, biochemical and metabolic levels (Nejat et al. 2017 ). For example, after perceiving the stimulation, plants promptly and effectively initiate extensive transcriptional reprogramming of gene expression, generating a variety of signaling molecules, including phytohormones, reactive oxygen species (ROS), calcium ions (Ca 2+ ) (Buscaill et al. 2014 ; Ng et al. 2018 ; Chen et al. 2020 ). This stress-responsive reprograming requires the coordinated and precise timing of the involvement of different types of transcription factors (TFs) in both temporal and spatial dimensions (Khan et al. 2018 ). Genetic and molecular studies have elucidated the functional attributes of TF families such as WRKY, AP2/ERF, NAC, MYB and bHLH in plants (Ng et al. 2018 ; Kajla et al. 2023 ).

WRKY TFs are among the largest transcriptional regulatory families in plants. These proteins were divided into three subgroups, namely groups I, II and III, according to the number of WRKY domains and the type of zinc finger structure (Eulgem et al. 2000 ; Rushton et al. 2010 ). Up to now, WRKY TFs have been identified in different plant species, including Arabidopsis thaliana , Glycine max , Gossypium hirsutum , Oryza sativa , Solanum tuberosum , Triticum aestivum , Zea mays (Khoso et al. 2022 ; Song et al. 2023 ; Javed et al. 2023 ). For instance, there are 90 and 128 WRKYs in Arabidopsis thaliana and Oryza sativa , respectively (Tian et al. 2020 ). Some WRKY TFs have been evaluated for their pivotal roles in plant growth and development (Wang et al. 2023a ). For example, AtWRKY10 and AtWRKY41 are involved in seed development and dormancy (Ding et al. 2014 ; Xi et al. 2021 ), while AtWRKY23 promotes lateral root growth in Arabidopsis (Grunewald et al. 2012 ). The functions of OsWRKY11 , OsWRKY36 and OsWRKY53 have been separately demonstrated in the flowering process, plant height and grain size in rice, respectively (Cai et al. 2014 ; Lan et al. 2020 ; Tian et al. 2017 ).

WRKY TFs serve as critical regulators in plant immune response, specifically binding to W-box cis-element (T)(T)TGAC(C/T) in the promoter region of target genes to modulate transcription (Bakshi et al. 2014 ; Viana et al. 2018 ; Saha et al. 2023 ). In Arabidopsis , at least 20 WRKY genes have been identified as playing significant roles in diseases or insect resistance, including AtWRKY28 / 33 / 55 / 70 / 75 (Li et al. 2006 ; Chen et al. 2013 ; Wang et al. 2019 , 2020 ; Zhou et al. 2020 ; Saha et al. 2023 ). In rice, overexpression of OsWRKY67 up-regulates defense-related genes ( PR1a , PR1b , PR4 , PR10a and PR10b ), as well as leads to rapid induction of ROS upon stimulation with chitin and flg22 (Liu et al. 2018 ). The adaptation results from the interplay between WRKYs and a variety of plant hormones. For example, OsWRKY72 directly binds to the promoter of AOS1 , which is the jasmonic acid (JA) biosynthesis enzyme gene, negatively regulates JA synthesis and resistance to Xanthomonas oryzae pv oryzae ( Xoo ) infection (Hou et al. 2019 ). OsWRKY42 is a negative regulator to M. oryzae via repressing JA signaling and OsWRKY45-2 directly activates OsWRKY13 , whose encoding protein in turn transcriptionally suppresses OsWRKY42 / OsWRKY45-2 to regulate blast resistance (Cheng et al. 2015 ). OsNPR1 , a key regulator of salicylic acid (SA)-mediated resistance against fungal, bacterial disease and herbivores (Yuan et al. 2007 ; Feng et al. 2011 ), is downstream of OsWRKY03 (Liu et al. 2005 ). Previous research has documented that WRKY TFs play critical roles in plant immune response as one of the downstream substrates of the mitogen-activated protein kinase (MAPK) cascades. For instance, OsMKK10-2-OsMPK3/OsMPK6-OsWRKY31 module participates in the biosynthesis of secondary metabolite camalexin to regulate defense for rice blast pathogen (Wang et al. 2023c ). OsWRKY53 is downstream of MAPK cascades, meanwhile, it functions as a negative feedback modulator of OsMPK3/OsMPK6 in response to striped stem borer (SSB) (Hu et al. 2015 ). Moreover, OsWRKY53 acts as an early suppressor of induced defenses to mediate the MAPK-regulated OsWRKY24 / 33 / 70 expression, as well as SSB-induced JA, JA-isoleucine (JA-Ile) and ethylene (ET) biosynthesis (Hu et al. 2015 ). Collectively, these studies confirm that WRKY genes might contribute to multiple biotic stresses through complex signaling cascades such as ROS, plant hormones and MAPKs.

In the past decades, WRKYs have gained extensive attention due to their functions in involving tolerance against abiotic stress (Khoso et al. 2022 ; Goyal et al. 2023 ). For example, AtWRKY25/26/33 positively mediates tolerance to heat stress in Arabidopsis (Li et al. 2011 ). OsWRKY10 negatively regulates thermotolerance in rice by modulating ROS homeostasis and hypersensitive response (Chen et al. 2022 ). Overexpression of OsWRKY76 up-regulates peroxidase gene OsPrx71 and lipid metabolism gene OsBURP13/OsRAFTIN1 , thus alleviating the damage of low temperatures in rice (Yokotani et al. 2013 ). Some studies have highlighted the relationship of abiotic stress with WRKY genes by regulating the dehydrate-responsive element binding proteins (DREBs) or C-repeat binding factors (CBFs). In particular, the OsWRKY63-OsWRKY76-OsDREB1B signaling cascade module is involved in the regulation of chilling tolerance (Zhang et al. 2022b ). OsWRKY28 confers salinity tolerance by directly activating OsDREB1B in rice (Zhang et al. 2023 ). Additionally, overexpression of OsWRKY55 reduced drought tolerance, is consistent with accelerated water loss and massive accumulation of ROS (Huang et al. 2021 ).

It has been confirmed that several OsWRKY TFs play multiple roles in the adaptation to both biotic and abiotic stress in rice. For instance, OsWRKY10 is involved in resistance to fungus and thermotolerance (Wang et al. 2023b ; Chen et al. 2022 ). OsWRKY24 positively regulates fungal disease resistance, which has been identified as a potential candidate gene affecting cold sensitivity (Yokotani et al. 2018 ; Wu et al. 2023 ). OsWRKY53 acts as a negative modulator in resistance of bacterial blight, cold and salt tolerance (Xie et al. 2021 ; Tang et al. 2022b ; Yu et al. 2023 ), as well as a positive regulator in blast resistance (Chujo et al. 2007 ). OsWRKY76 plays opposite roles in blast resistance and cold stress tolerance (Yokotani et al. 2013 ). Empirical evidence suggests that the adaption of a variety of stress is associated with the crosstalk between WRKYs and phytohormones. For example, overexpression of OsWRKY13 enhanced rice resistance to M. oryzae and Xoo , which was accompanied by the activation of SA signaling pathways and the suppression of JA signaling pathways (Qiu et al. 2007 ). OsWRKY45-1 and OsWRKY45-2 are involved in JA and SA signaling, whereas they play opposite roles in bacterial disease resistance (Tao et al. 2009 ). In addition, OsWRKY45-1 and OsWRKY45-2 act as negative and positive regulators in abscisic acid (ABA) signaling, respectively, while only the latter negatively regulates the tolerance of salt stress (Tao et al. 2011 ). Furthermore, knock out of OsWRKY53 mutants confer rice cold tolerance at the booting stage by repressing the anther gibberellin content (Tang et al. 2022b ). Therefore, WRKY proteins are potentially important components in plant biotic and abiotic stress responses and are associated with an array of signaling crosstalk.

OsWRKY70 encodes a rice WRKY TF belonging to group I, characterized by the presence of two WRKY domains (Zhang et al. 2015 ; Li et al. 2023 ). The resistance to herbivores of OsWRKY70 in rice has been investigated (Li et al. 2015 ; Ye et al. 2019 ). However, whether and how OsWRKY70 affects rice immunity to fungal disease and its association with abiotic stress have not been reported. Our previous study has demonstrated that OsWRKY70 is induced by cold stress (Li et al. 2023 ). Here, we observed that the transcript level of OsWRKY70 was up-regulated by different strains of M. oryzae . The biological functions of OsWRKY70 were also investigated using knock out mutants of OsWRKY70 . Our findings revealed that the loss-function of OsWRKY70 drastically enhanced resistance against M. oryzae , while attenuating cold tolerance in rice, demonstrating that OsWRKY70 plays opposite roles in immunity and cold stress response.

OsWRKY70 is a Fungal Pathogen-Induced Gene

The previous finding that OsWRKY70 acts as an early regulator of plant response to herbivores (Li et al. 2015 ) inspired us to investigate its potential role in immunity against fungal diseases. We first assessed the expression level of OsWRKY70 by quantitative PCR (qPCR) after spray inoculation with M. oryzae strain 318-2. The results showed that the transcript level of OsWRKY70 was rapidly up-regulated upon infection, achieving a peak of 11.4-fold at 24 h post-inoculation (hpi) (Fig.  1 A). To confirm whether the specific fungal pathogens, strains R01-1 and 110-2 were examined. Obviously, the expression of OsWRKY70 was significantly induced by these strains, resulting in an increase of 9.5-fold and 15.6-fold at 48 hpi, respectively (Fig.  1 B, C). Overall, these results indicate that OsWRKY70 exhibits distinct responses to diverse fungal pathogens.

M. oryzae strains infection induced the expression of OsWRKY70 . ( A-C ) 2-week-old seedlings of NIP plants were inoculated with rice blast by spraying method. The qPCR analysis of OsWRKY70 expression levels at 0, 24 and 48 h post-inoculation with M. oryzae strains 318-2 ( A ), R01-1 ( B ) and 110-2 ( C ). OsActin was used as an internal control gene. The expression level of OsWRKY70 in plants under normal condition was set as 1. Data are the means ± SD of three biological replicates. Asterisks indicate significant differences by the Student’s t-test (* P  < 0.05, ** P  < 0.01)

Generation and Characterization of OsWRKY70 Knock Out Mutants

To elucidate the function of OsWRKY70, two homozygous mutants, designated  oswrky70-7 and oswrky70-10 , were generated by CRISPR/Cas9-mediated genome editing. They exhibited a single base A and T insertion in the target sequence of OsWRKY70 , respectively (Fig.  2 A), resulting in the early termination of translation and thus loss of the conserved WRKY domain (Fig.  2 B). Under field condition, our observations revealed that there was no significant difference between the mutants and wild type in terms of plant height, the tiller count, flag leaf and panicle length (Fig.  2 C, D; Supplemental Table 2 ). Interestingly, the grain length of the mutants was notably greater than that of wild type, while the grain width exhibited a slight increase in oswrky70-10 , resulting in a promotion in 1000-grain weight of mutants as compared to wild type (Fig.  2 E-I). These results suggest that the loss-function of OsWRKY70 affects rice grain shape rather than its growth and development.

Generation of mutants and investigations of agronomic traits. ( A ) Knock out of OsWRKY70 gene by CRISPR/Cas9 technology. Target sequences of single-guide RNA (sgRNA) were listed. The mutation sites were indicated in red. Sequencing results of the OsWRKY70 in the mutants and wild type. ( B ) Schematic diagrams of OsWRKY70 in knock out mutants. ( C, D ) The plant height at seeding stage ( C ) and heading stage ( D ). Scale bar = 2 cm and 1 dm, respectively. ( E , F ) The grain length ( E ) and grain width ( F ). Scale bar = 1 cm, n  = 20. ( G-I ) The Statistical analysis of grain length ( G ), grain width ( H ) and 1000-grain weight ( I ). Data are the means ± SD of three biological replicates. Asterisks indicate significant differences by the Student’s t-test (* P  < 0.05, ** P  < 0.01)

Loss-Function of OsWRKY70 Enhances Resistance Against M. Oryzae

To ascertain the involvement of OsWRKY70 in rice blast resistance, we first performed spray inoculation on 2-week-old seedlings with M. oryzae 318-2. At 5 days post-inoculation (dpi), the mutants exhibited a reduced overall severity blast compared to wild type (Fig.  3 A), as determined by a decrease in the lesion numbers by approximately 47.2% (Fig.  3 B). Next, measurement of fungal growth in planta, as revealed by analyzing the genomic DNA level of the MoPOT2 gene of M. oryzae , indicated that oswrky70-7 and oswrky70-10 supported less fungal growth, resulting in a reduction of 73.3% and 97.0%, respectively, as compared with that in wild type (Fig.  3 C). Additionally, we conducted inoculation to detached leaves and punch-inoculated at 4-week-old seedings with strain 318-2. Consistent with previous findings, the mutants were less susceptible to rice blast than wild type, manifesting as significantly reduced disease lesions and lower fungal biomass (Fig.  3 D-F; Figure S1 ). To further investigate the growth characteristics of M. oryzae spores, we infected rice leaf sheath with GFP-tagged strain RB22. At 24 hpi, we observed that almost no appressoria were formed in the leaf sheath cells of mutants, whereas maturing appressoria were found in those of wild type (Fig.  3 G). At 48 hpi, only a limited number of invasive hyphae with no branch were present in the mutant cells, while numerous invasive hyphae freely spread to adjacent cells in wild type (Fig.  3 H). Collectively, these results demonstrate that OsWRKY70 negatively regulates rice immune response against M. oryzae .

Loss-function of OsWRKY70 enhance resistance to M. oryzae. ( A ) Spray inoculation with M. oryzae spores on seedlings of mutants and wild type. ( B ) Lesion numbers on inoculated leaves at 5 days post-inoculation, n  = 5. ( C ) Blast fungus biomass was determined by qPCR analysis using the ratio of M. oryzae DNA ( MoPOT2 ) to rice DNA ( OsAcitn ) in infected leaves. Data are the means ± SD of three biological replicates. Asterisks indicate significant differences by the Student’s t-test (* P  < 0.05, ** P  < 0.01). ( D ) The detached leaves of mutants and wild type were inoculated with the M. oryzae . Scale bar = 1 cm. ( E ) Lesion length was determined on leaves at 5 days after inoculation, n  = 5. ( F ) Relative fungal biomass in the necrotic regions of the detached leaves was assessed by qPCR of the fungal MoPOT2 and normalized to rice OsActin . Data are the means ± SD of three biological replicates. Asterisks indicate significant differences by the Student’s t-test (* P  < 0.05, ** P  < 0.01). ( G , H ) Fluorescence microscopic observation of M. oryzae strain RB22-GFP infection on leaf sheath at 24 hpi ( G ) and 48 hpi ( H ). Scale bar = 20 μm

ROS Accumulation and Up-Regulated Defense Responsive Genes Enhance Resistance Against M. Oryzae in the Mutants

ROS bursts typically trigger plant defense responses (Li et al. 2021 ). Firstly, we conducted the analysis of ROS in the mutants and wild type after inoculation with M. oryzae by histochemical staining. The results showed that the presence of numerous reddish-brown spots on the leaves of mutants upon staining with 3, 3’-diaminobenzidine (DAB) and a significant increase in the number of blue dots were observed on the mutant leaves by nitro-blue tetrazolium (NBT) staining compared with those of wild type (Fig.  4 A, B). The findings indicate that enhanced accumulation of H 2 O 2 and superoxide anion probably contribute to resistance against rice blast disease. Subsequently, we investigated the expression patterns of defense-related genes. The results revealed that OsPBZ1 , OsPOX8.1 and OsPOX22.3 were dramatically up-regulated in the mutants compared to wild type before inoculation, except for OsPR1b (Fig.  4 C-F). Upon exposure M. oryzae strain 318-2, all four genes were a particularly notable up-regulation in the mutants compared with wild type (Fig.  4 C-F). It suggests that loss-function of OsWRKY70 activate defense response, which might play a pivotal role in response to biotic stress in rice.

ROS accumulation and up-regulated defense responsive genes enhance M. oryzae resistance in rice. ( A , B ) DAB staining ( A ) and NBT staining showed H 2 O 2 and superoxide anion accumulation in leaves from 2-week-old seedings cultivated in normal culture and after inoculation with M. oryzae . ( C-F ) Expression levels of defense-responsive genes OsPBZ1 ( C ), OsPOX8.1 ( D ), OsPOX22.3 ( E ) and OsPR1b ( F ) in the leaves at seeding stage without inoculation and post-inoculation with M. oryzae . OsActin was used as an internal control. The expression level of the tested genes in wild type plants under normal condition was set as 1. Data are the means ± SD of three biological replicates. Asterisks indicate significant differences by the Student’s t-test (* P  < 0.05, ** P  < 0.01)

Transcriptome Analysis of OsWRKY70 Knock Out Mutant and qPCR Analysis

To further elucidate mechanisms underlying OsWRKY7 0-mediated immunity response in rice, we examined gene expression differences between oswrky70-7 (W7) and NIP (N) under normal condition and 48 h post-inoculation with M. oryzae using RNA sequencing (RNA-seq). Sample correlation and principal components analysis (PCA) of all genes showed that the three replicates of each treatment clustered together, suggesting good biological replicability (Supplemental Fig.  2 ). Rice genes whose transcript abundance showed a fold change (FC) ≥ 2 and false discovery rate (FDR) ≤ 0.01 were defined as differentially expressed genes (DEGs). We observed significant clustering differences between W7 and N under normal condition, which identified 2210 DEGs, including 1205 up-regulated and 1005 down-regulated genes. The data revealed that knock out of OsWRKY70 led to different transcript profiles. Additionally, a comparison of W7 and N at 48 hpi revealed 968 DEGs, containing 482 up-regulated genes, as well as 486 down-regulated genes in the mutant (Supplemental Fig.  2 ). However, the differences were not significantly enlarged by biotic stress.

KEGG classification illuminated the functional roles of these DEGs were mainly enriched into such as plant-pathogen interaction, plant hormone signal transduction, MAPK signal cascade and other metabolic processes (Fig.  5 A, B). Among them, several encoding putative NBS-LRR disease resistance protein genes, LOC_Os11g44960 , LOC_Os11g45050 and LOC_Os11g45180 , as well as the gene LOC_Os07g44130 in phenylpropanoids metabolism were significantly up-regulated in W7 (Fig.  5 C). In addition, OsbHLH6 , OsUGT74H4 and OsWRKY76 were negative regulators of disease resistance involved in JA, SA and MAPK cascade signaling, respectively (Yokotani et al. 2013 ; Meng et al. 2020 ; Wu et al. 2022 ), were also dramatically down-regulated in the mutant after inoculation (Fig.  5 C). The findings indicate that complex regulatory networks are activated in timely manners, which is crucial for rice blast resistance. To further screen candidate downstream target genes associated with the immune response of OsWRKY70, the leaves of 2-week-old mutants and wild type were individually collected for qPCR analysis after inoculation. The results revealed that the expression level of hormone, MAPK signaling and metabolic process genes was consistent with the RNA-seq analysis (Fig.  5 D-I).

Transcriptomic analysis of oswrky70-7 before and after blast inoculation, as well as qPCR analysis to verify some DEGs. ( A , B ) KEGG pathway analysis of the DEGs between the mutant and wild type without inoculation ( A ) and 48 h post-inoculation ( B ) with M. oryzae 318-2. ( C ) Heatmaps showing the part of DEGs related to plant-pathogen interaction, plant hormone signal pathway, MAPK signaling pathway and metabolism. ( D-I) Quantitative PCR analysis of OsWRKY76 ( D ), OsbHLH6 ( E ), LOC_Os11g101710 ( F ), LOC_Os03g09260 ( G ), LOC_Os07g44130 ( H ) and LOC_Os07g35350 ( I ). 2-week-old wild-type mutants and wild type plants were grown in soil under 16 h light/8 h dark conditions and were treated under inoculation for 0 and 48 h. The leaves were collected for RNA extraction. Three biological replicates were performed. Relative expression levels were normalized by the transcript level of the OsActin gene as an internal control and the expression level of each gene of interest in wild type plants under normal condition was set as 1. Data are the means ± SD of three biological replicates. Asterisks indicate significant differences by the Student’s t-test (* P  < 0.05, ** P  < 0.01)

OsWRKY70 Interacts with Promoter of OsbHLH6 in Vitro

Our finding revealed that the expression level of OsbHLH6 was down-regulated in the mutants (Fig.  5 E). To further explore whether OsbHLH6 is the candidate target gene of OsWRKY70 in immune response, we initially analyzed the promoter region of OsbHLH6 and found ten W-box elements (Supplemental Table 3 ; Fig.  6 A). Notably, the candidate fragments encompassed one or two core sequences (TGAC) characteristic of W-box. Then, we conducted a semi-in vivo chromosome immunoprecipitation qPCR (ChIP-qPCR) assay to verify the interaction, which employed the purified recombinant His-OsWRKY70 protein (Fig.  6 B; Supplemental Fig.  3 ) and DNA fragments of rice genomic. The ChIP-qPCR results confirmed a significant approximately 4.0-fold enrichment of the P1 fragment in His-OsWRKY70 compared to the His control, while no enrichment was observed for the P2 fragment (Fig.  6 C). These findings suggest that OsbHLH6 might serve as a downstream target gene for OsWRKY70.

OsWRKY70 interacts the promoter of OsbHLH6 in vitro. ( A ) Schematic of the OsbHLH6 promoter. Black rectangles indicate W-box (TGAC core sequences) cis-elements in the promoter of OsbHLH6 . ( B ) The Western blot with purification of His-OsWRKY70 obtained from recombination of E. coli BL21. (Line 1, eluted His-OsWRKY70; M, protein marker). ( C ) The semi-in vivo ChIP-qPCR assay showed that His-OsWRKY70 enriched the P1 fragment of OsbHLH6 promoter. DNA fragments co-incubated with His was used as a negative control. Relative enrichment is represented as the normalized ratio of the ChIP DNA to the input genomic DNA at the site. P1 and P2 are the fragments of the promoter. Data are the means ± SD of three biological replicates. Asterisks indicate significant differences by the Student’s t-test (* P  < 0.05, ** P  < 0.01)

Loss-Function of OsWRKY70 Impairs Cold Tolerance in Rice

Our previous study that OsWRKY70 was induced by cold stress (Li et al. 2023 ) prompted us to investigate whether OsWRKY70 is involved in cold tolerance. Consequently, 2-week-old seedlings were subjected to 4 °C for 3 days and returned to normal growth conditions for a recovery period of 7 days. The mutants exhibited pronounced leaf curling symptoms after cold stress and a significant proportion of them could not be recovered compared with wild type (Fig.  7 A), demonstrating that OsWRKY70 is a positive regulator of cold tolerance in rice. This observation is consistent with the survival rate of oswrky70-7 and oswrky70-10 , which were 25.3% and 3.3%, compared to 42.7% of wild type (Fig.  7 B). Moreover, higher levels of electrolyte leakage and MDA content were in the mutants than that in wild type (Fig.  7 C, D). We further performed histochemical staining to detect ROS bursts in rice plants. After cold treatment, deeper reddish brown and darker bluish-purple spots in the mutant leaves than that in wild type by DAB and NBT staining (Fig.  8 A, B), reflecting excessive H 2 O 2 and superoxide anion in the mutants, respectively. Subsequently, the activity of two antioxidant enzymes crucial for scavenging ROS was examined. A significant decrease in CAT activity was observed in the oswrky70-7 compared to wild type at 24 h after cold treatment (Fig.  8 C). Especially, oswrky70-10 exhibited approximately 30% decline after 12 h of cold treatment compared to wild type (Fig.  8 C). Similarly, POD activity significantly reduced after exposure to cold for 12 h in the mutants. These results indicate that an imbalance of ROS homeostasis contributes to cellular oxidative membrane damage in OsWRKY70-regulated cold tolerance in rice. To assess the potential downstream genes of OsWRKY70 in response to cold, we detected the expression level of OsLti6b , OsICE1 and OsCOLD1 , which are cold-related genes (Kim et al. 2007 ; Ma et al. 2015 ; Zhang et al. 2017 ). The results revealed that the mutants showed down-regulation of OsLti6b and OsICE1 , while no significant difference in the expression of OsCOLD1 was observed (Fig.  8 E-G), implying that knock out of OsWRKY70 attenuates cold tolerance in rice presumably due to the suppressed expression of OsLti6b and OsICE1 .

Knock out of OsWRKY70 reduced cold tolerance in rice. ( A ) 2-week-old seedlings of the mutants and wild type were subjected to 4 °C for 3 days in a growth chamber and then cold stressed recovered under 25–28 °C for 7 days. ( B ) The survival rate of seedlings after recovery were calculated. ( C ) Ion leakage rate in leaves of the cold-stressed mutants and wild type. ( D ) Content of MDA between mutants and wild type under normal condition and cold treatment. Data are the means ± SD of three biological replicates and each replicate includes at least 15 independent seedlings. Asterisks indicate significant differences by the Student’s t-test (* P  < 0.05, ** P  < 0.01)

ROS burst and the expression levels of cold-related genes in oswrky70 mutants in response to cold. ( A ) H 2 O 2 accumulation checked by DAB staining. ( B ) The accumulation of superoxide anion in leaves detected by NBT staining. ( C , D ) Enzyme Activity of CAT ( C ) and POD ( D ) from seedings of 2-week-old wild type and oswrky70 mutants before and after cold stress treatment. Data are the means ± SD of three biological replicates. Asterisks indicate significant differences by the Student’s t-test (* P  < 0.05, ** P  < 0.01). ( E-G ) The expression levels of cold-related genes OsLti6b ( E ), OsICE1 ( F ) and OsCOLD1 ( G ) from the seedings of 2-week-old wild type mutants and mutants without and with cold treatment. Relative expression levels were normalized by the transcript level of the OsActin gene as an internal control and the expression level of each gene of interest in wild type plants under normal condition was set as 1. Data are the means ± SD of three biological replicates. Asterisks indicate significant differences by the Student’s t-test (* P  < 0.05, ** P  < 0.01)

Transcription factor OsWRKY70, a member of WRKY group I, has been established to function as a transcriptional activator (Li et al. 2015 ; Zhang et al. 2015 ). Phylogenetic analysis revealed that OsWRKY70 shares up to 52.43% and 62.87% amino acids identities with OsWRKY24 and OsWRKY53, respectively (Li et al. 2023 ). Repression of OsWRKY24 (Yokotani et al. 2018 ) and overexpression of OsWRKY53 (Chujo et al. 2007 ) confers blast resistance in rice. Our findings demonstrated that knock out of OsWRKY70 mutants enhanced resistance against M. oryzae (Fig.  3 ; Figure S1 ), implying that OsWRKY70 negatively regulates the fungal immunity in rice. However, it seems paradoxical that the increased transcriptional expression level of OsWRKY70 upon infection (Fig.  1 ). Similarly, this feedback-like has been reported in some rice TFs. For instance, OsbHLH6 and ONAC083 , which are induced by inoculation with M. oryzae , act as negative regulators of disease resistance (Bi et al. 2023 ; Meng et al. 2020 ). Additionally, OsWRKY24, OsWRKY53 and OsWRKY70 may be functionally redundant in grain regulation (Tang et al. 2022a ). Considering that predicted interactions of these proteins (data have no shown), we presume that up-regulated OsWRKY70 might be involved in adjusting the intensity of defense response by cooperating with OsWRKY24 or OsWRKY53 to protect the plant from biotic stress. Therefore, further generation of double and triple mutant plants for these genes will contribute to elucidating the molecular mechanism of blast resistance. Our KEGG analysis revealed that the altered genes are involved in plant-pathogen interactions, hormone signaling transduction, MAPK cascades and so on, indicating that OsWRKY70 is a key component of immunity response (Fig.  5 ). Plant NBS-LRR genes, a class of the resistance (R) genes, encode immune receptors that help defend against pathogens infection (Wang et al. 2023 d ). For instance, rice NBS-LRR protein Pit interacts with OsRac1 and induces the generation of ROS and hypersensitive response to resist the invasion of M. oryzae (Kawano et al. 2014 ). Pi63 encodes a typical NBS-LRR protein, whose expression level is closely related to disease resistance (Xu et al. 2014 ). In our study, LOC_Os11g44960 , LOC_Os11g45050 and LOC_Os11g45180 , which are assumed to encode NBS-LRR proteins, were up-regulated expression in the mutant (Fig.  5 C). It is suggested that these genes might be conferred to the resistance to blast. The activation of the JA signaling pathway improved resistance against disease in rice (Okada et al. 2015 ; Wang et al. 2021 ; Qiu et al. 2022 ). OsbHLH6 , a transcription activator, negatively regulates rice blast resistance, which has been shown to play a pivotal role in modulating the JA and SA signaling pathways (Kiribuchi et al. 2004 ; Meng et al. 2020 ). Knock out of the OsbHLH6 mutant downregulates the expression of OsJAZ family genes, which exhibits severe damage upon exposure to herbivores (Valea et al. 2022 ). In our study, the OsbHLH6 gene transcript significantly decreased in oswrky70-7 and oswrky70-10 mutants before and after inoculation compared to the wild type (Fig.  5 C, E). Given the finding that OsWRKY70 enhances rice herbivore resistance to SSB mediated by JA signaling (Li et al. 2015 ), we hypothesized that OsbHLH6 might be a potential downstream target of OsWRKY70. Then, we analyzed the promoter of OsbHLH6 and further confirmed the binding of OsWRKY70 using a semi-in vivo ChIP assay (Fig.  6 ). Therefore, it would be interesting in our future work to verify the interactions in vivo by ChIP and to generate their double mutant plants for exploring the regulatory relationships. Advanced thinking is that JA and SA signaling crosstalk commonly manifests as a reciprocal antagonism or adaptation (Thaler et al. 2012 ). In our work, the transcript level of OsUGT74H4 was decreased in mutant after infection by RNA-seq analysis (Fig.  5 C). OsUGT74H4 may inactivate SA through glycosylation modification, negatively regulating the resistance of rice to bacterial diseases (Wu et al. 2022 ). Both positive and negative transcriptional regulations of SA biosynthesis are required to fine-tune the SA levels for optimal defense without causing unnecessary fitness costs (Ding et al. 2020 ). Therefore, we suspect that knock out of OsWRKY70 might affect SA content in response to fungal pathogen infection. Phenylpropanoids are considered to be secondary metabolites involved in plant defense responses (Kishi-Kaboshi et al. 2010 ). Previous research has revealed that CYP72A1 , the cytochrome P450 gene, positively regulates the production of ROS and the accumulation of defense-related secondary metabolites in basic immune response (Zhang et al. 2022a ). The Cinnamate-4-hydroxylase (C4H) belongs to the cytochrome monooxygenase, which is the second key enzyme in the phenylpropane metabolic pathway (Yang et al. 2005 ). According to our transcriptome analysis, there were more than 20 DEGs in Phenylpropanoids biosynthesis without and after inoculation (Fig.  5 A). Among them, LOC_Os07g44130 , which encodes putative cytochrome P450, was up-regulated more than 5.5-fold in mutants after infection (Fig.  5 H). Thus, it is also worthy of further study and exploration of issues that OsWRKY70 participates in phenylpropanoids biosynthesis to adapt to biotic stress.

The loss-function of OsWRKY70 mutants reduced tolerance to cold stress (Fig.  7 ), suggesting that OsWRKY70 is a positive regulator of cold tolerance. It has been demonstrated that chilling usually causes excessive ROS accumulation in rice (Marchi et al. 2012 ; Zhang et al. 2022b ; Zhai et al. 2024 ). OsWRKY63 and OsWRKY76 might affect ROS homeostasis in the regulation of cold tolerance (Yokotani et al. 2013 ; Zhang et al. 2022b ). We observed that knock out of OsWRKY70 mutants accumulated a large amount of H 2 O 2 and superoxide anion under cold stress condition (Fig.  8 A, B). This is consistent with the measurement of reduced activities of CAT and POD, as well as increased electrolyte leakage levels and MDA content (Figs.  7 C and D and 8 C and D). Cold tolerance is primarily regulated by cold-responsive (COR) regulon (Wani et al. 2021 ). Our findings revealed that the expression level of OsLti6b and OsICE1 was significantly down-regulated in mutants (Fig.  8 E, F), which has been documented to positively regulate cold tolerance in rice (Kim et al. 2007 ; Nakamura et al. 2011 ; Xia et al. 2021 ). What is more, COR regulon also mediates the expression of AtWRKY 6/ 22 / 30 / 40 / 32 / 187 (Banerjee et al. 2015 ; Wani et al. 2021 ), hinting that there may be feedback or cooperation between OsWRKY70 and COR regulon in chilling stress. Unlike cold-responsive genes, OsCOLD1 is involved in sensing cold to trigger Ca 2+ signaling for chilling tolerance (Ma et al. 2015 ). There were no differences in the transcript level of OsCOLD1 between the mutants and wild type before and after cold treatment (Fig.  8 G), suggesting that OsCOLD1 may be the upstream of OsWRKY70 -mediated signaling. Additionally, the changes in OsCOLD1 protein structure and membrane fluidity in response to low temperature might initiate signaling (Ma et al. 2015 ). Thus, another possibility is that the mutation of OsWRKY70 affects the structure and dynamics of OsCOLD1 to regulate cold tolerance.

We demonstrated that OsWRKY70 functions as a negative regulator of rice against M. oryzae while a positive regulator of cold tolerance in rice (Figs.  3 and 7 ). Previous findings showed that temperature is an important factor affecting the occurrence of rice blast. For instance, cold summers increase the frequency and severity of fungal pathogen disease and bring heavy yield losses in the northern regions of Japan (Hironori et al. 2004 ). The blast lesion area and fungal growth in the inoculated seedlings at a warm temperature, 22 °C, is greater than those at 28 °C (Qiu et al. 2022 ). Additionally, 22 °C compromises basal resistance in rice by reducing JA biosynthesis and signaling (Qiu et al. 2022 ), suggesting that JA are involved in temperature-modulated plant resistance. We found that knock out of OsWRKY70 mutants down-regulated OsbHLH6 expression in response to rice blast (Fig.  5 E). However, the regulatory relationship between OsWRKY70 and OsbHLH6 whether involving temperature-mediated fungal pathogen resistance is yet to be clarified. In addition, more and more evidences imply that WRKY TFs are involved in the MAPK signaling pathway to adapt to biotic stress. For example, OsMKK10-20-OsMPK6 pathway is required for OsWRKY45 -mediated resistance against M. oryzae (Ueno et al. 2013 ). OsWRKY31, which is phosphorylated by OsMPKs, elevates DNA-binding activity and confers enhanced blast resistance in rice (Wang et al. 2023c ). Previously, OsMPK3 and OsMPK6 regulates OsWRKY70 in herbivore resistance (Li et al. 2015 ). OsMPK3, phosphorylated and activated by the calcium-dependent protein kinase CPK18, negatively regulates rice blast resistance (Xie et al. 2014 ). In addition to biotic stress, MAPK cascades have also been confirmed to confer abiotic stress responses, including chilling, salt and drought. For instance, OsICE1 is phosphorylated by OsMPK3, resulting in inhibition of OsICE1 ubiquitination and enhanced resistance to chilling damage (Zhang et al. 2017 ). Furthermore, OsMPK3 has positively modulated salt tolerance by attenuating the accumulation of ROS (Zhang et al. 2018 ). Consequently, further validation of the interaction with OsMPK3 and OsWRKY70 will contribute to aid in elucidating the molecular mechanism in response to fungal pathogen infection and cold stress.

Materials and methods

Plants and pathogens.

The wild type rice Oryza sativa L. japonica ‘Nipponbare’ (NIP) was used to generate knock out of OsWRKY70 mutants in this study. All rice seeds were soaked in culture dishes with water at 37℃ for one day. On the second day, the seeds were rinse for 2–3 times and added a small amount water to promote germination at 37 °C. Then, the seeds with same germination state were planted to the substrate soil. The plants were grown under normal conditions (25–28℃, 14 h light/10 h dark photoperiod, 50–75% relative humidity). For agronomic trait analysis, the tiller count, flag leaf, panicle length, grain length, grain width and 1000-grain weight of these plants were grown in the paddy fields of Hunan Agricultural University, Changsha, China.

Magnaporthe oryzae strains 318-2 from College of Agronomy in Hunan Agricultural University, as well as M. oryzae strains 110-2, R01-1 and GFP-tagged RB22 from Institute of Plant Protection in Chinese Academy of Agricultural Sciences, were cultured on oatmeal agar for 2 weeks at 28 °C and the spores were collected with sterile water containing 0.02% Tween-20. For M. oryzae strains treatment, 2-week-old seedlings of NIP were inoculated using M. strains 318-2, 110-2 and R01-1 for gene expression analysis of OsWRKY70 . The plants were sprayed with spores of M. oryzae strains (2 × 10 5 spores/mL), covered with a plastic box in the dark for 24 h (25–28 °C, approximately 100% relative humidity) and transferred to normal alternation of light and dark (25–28 °C, approximately 100% relative humidity). Leaf samples were collected at 0, 24 and 48 h post-inoculation, frozen in liquid nitrogen and stored at -80 °C until use. Each treatment was performed with three biological replicates. The control plants (0 h) were left blast-free.

Generation of OsWRKY70 Knock Out Mutants

For the construction of knock out of OsWRKY70 vector, the sequence (5’-GGACGAGCAGCAACAGTACT-3’) of OsWRKY70 genomic locus was conducted as the guide RNA through CRISPR Primer Designer v1.1.2. We designed two primers sequences (LP: 5’-TGGCGGGACGAGCAGCAACAGTACT-3’; RP: 5’-AAACAGTACTGTTGCTGCTCGTCCC-3’) to synthesized the sgRNA expression cassette. This sequence was inserted into the pHUN4c12 plasmid, which was linearized using Bsa I enzyme (NEB, USA). The vectors were introduced into Agrobacterium tumefaciens strain EHA105 through electroporation, which were further used to transform the rice callus. After screening with hygromycin and sequence confirmation, two homozygous knockouts oswrky70-7 and oswrky70-10 were obtained and the T3 generation seedlings were used for further analysis in this work. The primers used in the plant vector construction and identification are listed in Table S1 .

Fungal Pathogen Resistance Experiment

For spraying with M. oryzae spores (2 × 10 5 spores/mL), 2-week-old transgenic seedlings were used for pathogen infection. Leaves were collected at 0 and 24 h post-inoculation for expression analysis of defense-related genes. After inoculation for 5 d, the lesions were scanned and leaves were collected for DNA extraction to evaluate the relative fungal growth. The qRT-PCR was measured to analyze and compare the genomic level of M. oryzae POT2 in wild type and the mutant leaves with that of the rice OsActin as an internal control. All of primers were listed in Table S1 .

For detached leaf inoculation, leaves of 4-week-old rice seedlings were cut into pieces (about 5 cm × 1 cm) and float on the distilled water in culture dishes. Apply a drop of the spore suspension (10 µL of 4 × 10 5 spores/mL) to the wound of each leaf and keep the dishes at 25–28℃ for 5 days. (Darkness is not required). The lesions were photographed and measured at 5 d post-inoculation and leaves were collected for detecting relative biomass.

For punch inoculation, 4-week-old seedlings grown in the field were made a wound using a hole punch. 10 µL spore suspension (4 × 10 5 spores/mL) was dropped onto wound. The inoculated region was wrapped with tape to maintain humidity. At 5 d post-inoculation, the lesions were pictured and surveyed. Leaf samples were conducted for measuring relative growth of M. oryzae . Blast inoculation was performed as previously described (Gu et al. 2023 ). M. oryzae strain 318-2 was used for rice blast inoculation. All experiments were independently repeated at least three times.

For leaf sheaths infection, detached sheaths of 4-week-old rice plants were inoculated with GFP-tagged M. oryzae strain RB22 spores (4 × 10 5 spores/mL) and kept on dished with approximately 100% humidity for 24 h and 48 h in the dark. Images of conidial germination, appressorium development and invasive hyphal growth were recorded using a fluorescence microscope (Mshot, China).

Evaluation of Cold Tolerance

For cold stress tolerance assay, 2-week-old knock out of OsWRKY70 mutants and wild type plants were grown under normal condition and then transferred into a growth chamber with the temperature set at 4 °C with a cycle of 14 h light/10 h dark for 3 days, followed by transferring to the growth room with the normal condition for recovery. Plants with green leaves and healthy young leaves after transferring to the normal growth condition were considered as survivals and surviving plants were evaluated at 7 days after recovery from cold treatment. Survival rate was calculated as the ratio of the number of survived plants over the total number of treated plants. Leaf samples at 0 and 24 h were used for determination of malondialdehyde (MDA) content and electric conductivity using the colorimetric method and electrical conductivity meter, respectively (Guan et al. 2012 ). Leaves at 0, 12 and 24 h were measured the enzyme activity catalase (CAT) and Leaves at 0 and 12 h were detected the peroxidase (POD) activity, as previously described (Wang et al. 2022 ). Leaves were collected at 0 and 24 h for expression analysis of cold-related genes. The specific primers were exhibited in Table S1 . Cold treatment in each of the experiments included three biological replicates with at least 15 plants and the experiments were independently repeated three times.

Histochemical Staining Analysis

For fungal pathogen infection, 2-week-old seedlings of wild type and oswrky70 mutants were sprayed with M. oryzae 318-2 spores (2 × 10 5 spores/mL) for detection of ROS burst. Leaf samples were collected at 0 and 24 h post-inoculation to carry out Histochemical Staining. For cold stress treatment, 2-week-old transgenic plants were transferred to a growth chamber with temperature set at 4℃. Leaf samples were collected at 0 and 6 h after treatment. 3, 3’-diaminobenzidine (DAB) and nitro-blue tetrazolium (NBT) staining for H 2 O 2 and superoxide anion accumulation in plants, respectively, were conducted as previously described (Jambunathan 2010 ).

DNA Extraction

Rice leaf genomic DNA was extracted, according to the CTAB method (Semagn et al. 2014 ).

RNA Extraction and Quantitative Real‑Time PCR

Total RNA was extracted using Ultrapure RNA Kit (Cwbio, China). RNA was reverse transcribed to cDNA using HiScript III 1st Strand cDNA Synthesis Kit (Vazyme, China). Quantitative Real‑Time PCR (qRT-PCR) was performed using ChamQ Universal SYBR qPCR Master Mix (Vazyme, China). The reaction was carried out in the CFX Connect Real-Time PCR Detection System (Bio-Rad, USA). Rice OsActin gene was used as an internal standard to normalize. All of primers used for mRNA detection of target genes are shown in Table S1 . Three replicate experiments were performed for each sample. The relative quantitation method (2 −ΔΔCT ) was used to evaluate quantitative variation among replicates.

Expression and Purification of Recombinant Protein

The full-length cDNA of OsWRKY70 was PCR-amplified and cloned into the pCold-TF vector (Takara, Japan). Specific primers used for PCR amplification for this gene are listed in Table S1 . The constructs were transformed into Escherichia coli BL21 (DE3) (Vazyme, China). OsWRKY70 recombinant protein was induced by adding 0.4 mM isopropyl-β-thiogalactopyranoside (IPTG) at 15˚C for 24 h. Cells were collected and the recombinant protein was purified using ProteinIso ® Ni-NTA Resin for His (TransGen, China) according to the manufacturer’s instructions.

Transcriptome Analysis

Libraries for RNA-seq were constructed and sequenced by Biomarker Technologies Co., Ltd (Beijing, China). Briefly, RNAs were quantified by NanoDrop 2000c UV-Vis Spectrophotometer (Thermo Fisher Scientific), agarose gel electrophoresis and Agient2100/LabChip GX. mRNAs were isolated from total RNAs by poly (A) selection, fragmented into short fragments and converted to cDNAs. cDNAs were ligated to adapters and the suitable fragments were selected for PCR amplification as templates. All the RNA-seq libraries were pair-end sequenced on an Illumina NovaSeq6000 platform. mRNA sequencing data analysis were performed as reported (Love et al. 2014 ). Low-quality reads were removed and adapters were trimmed to obtain clean reads, which were mapped to the reference genome (Oryza_sativa.MSU_v7.0.genome.fa). Transcriptome analysis was performed using BMKCloud ( www.biocloud.net ). The expression level of each gene was calculated as the FPKM value (fragments per kilobase of transcript per million mapped reads). For differential gene expression analysis, fold change (FC) ≥ 2 and false discovery rate (FDR) ≤ 0.01 as screening criteria. Fold Change represents the ratio of expression between two samples (groups). False Discovery Rate (FDR) is obtained by correcting for the difference significance p-value (p-value), indicating the significance of the difference.

Semi-Vivo Chromatin Immunoprecipitation Assay

The analysis of ChIP was conducted as previously described (Li et al. 2017 ). Total DNA of Nipponbare and purified His-OsWRKY70 were used for a semi-vivo chromatin immunoprecipitation (semi-vivo ChIP) assay. 2-week-old seedlings were used for total DNA extraction. The total DNA was sheared into 200–800 bp fragments using ultrasonic crusher. The His fusion protein was affinity-purified on Ni-NTA Resin. His-OsWRKY70 and DNA fragments were co-incubated for 2 h. The incubation buffer includes: 50 mM Tris, 1mM EDTA, 100 mM KCl, adjust pH to 7.0 by HCl, 5% Glycerol, 0.1% Triton X-100; add freshly-made 100 mM DTT to reaction solution to make final concentration of DTT at 1 mM. After co-incubation, Ni-NTA Resin was washed three times using incubation buffer. Then 4 µL 5 M NaCl was added into the sample for each 100 µL volume and was incubated for 4 h to break down cross-linked His-OsWRKY70 and DNA fragments. The prepared DNA in ChIP was applied for qRT-PCR using respective primer pairs (Table S1 ) in a ChamQ Universal SYBR qPCR Master Mix with a CFX Connect Real-Time PCR Detection System. PCR reactions were performed in triplicate for each sample and the expression levels were normalized to the input sample for enrichment detection. The fold enrichment was calculated against OsActin No addition of antibodies (NoAbs) served as a negative control.

Data Analysis

For qRT-PCR analyzes, disease assays, agronomic traits assessment and cold tolerance assays significant differences between samples/lines and the corresponding controls were analyzed using two-tailed Student’s t test for pairwise comparisons.

Data Availability

No datasets were generated or analysed during the current study.

Abbreviations

Jasmonic acid

Salicylic acid

Abscisic acid

Reactive oxygen species

Mitogen-activated protein kinase

3, 3’-diaminobenzidine

Nitro-blue tetrazolium

Malondialdehyde

Differentially expressed gene

Kyoto encyclopedia of genes and genomes

Principal component analysis

Polymerase chain reaction

Quantitative real‑time PCR

Chromatin immunoprecipitation

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Acknowledgements

First of all, the authors would like to appreciate to all those who have contributed to this study. The authors are grateful to Pro Yuese Ning and Pro Ruyi Wang (Institute of Plant Protection, Chinese Academy of Agricultural Sciences), Pro Wei Li (College of Plant Protection, Hunan Agricultural University), as well as College of Agronomy in Hunan Agricultural University for providing fungal pathogens and valuable suggestions.

This work was supported by grants from the Natural Science Foundation of China (31701781 and 32171950), the Scientific Research Project of Hunan Provincial Department of Education (22A0163), the Hebei Technology Innovation Center for Green Management of Soil-borne Diseases (Baoding University, Grant No. 2022K04) and the Postgraduate Scientific Research Innovation Project of Hunan Province (CX20230687).

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Jiangdi Li, Yating Chen, Rui Zhang, Rujie Wang, Bin Wu & Guiqing Xiao

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JL, GX, and HZ considered the project and designed the study. JL experimented and measured the data. YC, RZ, RW and BW reviewed and edited the manuscript.

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Li, J., Chen, Y., Zhang, R. et al. OsWRKY70 Plays Opposite Roles in Blast Resistance and Cold Stress Tolerance in Rice. Rice 17 , 61 (2024). https://doi.org/10.1186/s12284-024-00741-9

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DOI : https://doi.org/10.1186/s12284-024-00741-9

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• Blast resistance
• Cold tolerance
• Transcriptional regulation