Skip to main content Accessibility help


  • Access
  • Cited by 1


      • Send article to Kindle

        To send this article to your Kindle, first ensure is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about sending to your Kindle. Find out more about sending to your Kindle.

        Note you can select to send to either the or variations. ‘’ emails are free but can only be sent to your device when it is connected to wi-fi. ‘’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

        Find out more about the Kindle Personal Document Service.

        Effect of multi-micronutrient-fortified rice on cognitive performance depends on premix composition and cognitive function tested: results of an effectiveness study in Cambodian schoolchildren
        Available formats

        Send article to Dropbox

        To send this article to your Dropbox account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Dropbox.

        Effect of multi-micronutrient-fortified rice on cognitive performance depends on premix composition and cognitive function tested: results of an effectiveness study in Cambodian schoolchildren
        Available formats

        Send article to Google Drive

        To send this article to your Google Drive account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Google Drive.

        Effect of multi-micronutrient-fortified rice on cognitive performance depends on premix composition and cognitive function tested: results of an effectiveness study in Cambodian schoolchildren
        Available formats
Export citation



Even though current policy is strongly focused on the crucial first ‘1000 days’, it might be still possible to enhance cognitive function during the pre-adolescent and adolescent years by improving micronutrient status. In Cambodia, nutritional status is poor. Provision of rice fortified with micronutrients through a school meal programme (SMP) could be a cost-effective strategy to help improve health and school performance. The present study aimed to evaluate the effect of three different micronutrient-fortified rice formulations on cognitive function in Cambodian children.


Sixteen Cambodian schools receiving SMP.


The FORISCA-UltraRice®+NutriRice® study was a randomized, double-blind, placebo-controlled trial. Four groups of four schools were randomly allocated to receive normal rice, UltraRice®Original, UltraRice®New or NutriRice®. Within each school, 132 children were randomly selected. Data on cognitive performance (picture completion, block design and Raven’s coloured progressive matrices (RCPM)), anthropometry, parasite infestation and micronutrient status were collected before the intervention and after 6 months.


Cognitive data were available for 1796 children aged 6–16 years.


All cognitive scores improved after 6 months (P<0·001). Block design score improvement was significantly higher in children consuming UltraRice®Original (P=0·03) compared with the other fortified rice groups and placebo. No difference among groups was found on RCPM or picture completion scores. Stunting, parasite infestation and inflammation negatively affected the impact of the intervention.


Combined with other interventions, using SMP to distribute fortified rice to schoolchildren may be a cost-effective way to increase cognitive performance and thereby improve school performance and educational achievements.

In South-East Asia, micronutrient deficiencies remain highly prevalent( 1 ). In addition to the most vulnerable groups (i.e. pregnant and lactating women, young children), the prevalence of micronutrient deficiencies is also high among school-aged children. Over 30 % of school-aged children in South-East Asia are affected by Zn deficiency, while 20 % of school-aged children are deficient in Fe or vitamin A( 2 ). During the primary school years, anaemia and deficiencies of Fe, Zn, iodine, vitamin A, vitamin B12, vitamin B6 or folic acid can impair concentration and cognitive function( 2 5 ) and reduce school attendance by increasing morbidity( 6 ). Therefore, micronutrient deficiencies are detrimental to optimal schooling, while at the same time education is recognized as a prime opportunity to break the cycle of poverty and undernutrition( 7 , 8 ).

Although the ‘1000-day window’ concept rightly highlights that micronutrient deficiencies in fetal life or early childhood can permanently damage cognitive function and development( 9 ), it is important to realize that it might still possible to improve cognition among children of primary-school age by improving micronutrient status. Several studies have clearly shown a beneficial impact of micronutrient supplementation or food fortification on morbidity and cognitive performance( 5 , 10 13 ), with multiple micronutrients appearing to be more efficient than single or double micronutrient interventions( 14 ). However, the overall evidence remains equivocal( 15 , 16 ). In South-East Asia, a region where refined rice typically provides 70 % of the dietary energy intake, rice fortification could be a cost-effective strategy to reduce micronutrient deficiencies and anaemia( 17 22 ) and therefore possibly improve cognitive performance in school-aged children.

The school meal programme (SMP) of the UN World Food Programme (WFP) reached almost 26 million children worldwide in 2011( 23 ). The primary objective of the WFP SMP is to increase school enrolment and attendance; however, it can also serve to improve child nutritional status at the same time( 23 ). Fortification of the school meal with micronutrients could help reduce the prevalence of micronutrient deficiency at very little additional cost. For example, depending on technologies, to fortify rice in school meals would add only $US 0·50–2·00 per child per year( 24 ).

In Cambodia, malnutrition among children under 5 years of age is highly prevalent, with 40 % stunting and 11 % wasting prevalence( 25 ). Unfortunately, data on the nutritional status of primary-school-aged children are scarce in Cambodia. The WFP distributes school meals to more than 500 000 school-aged children in rural Cambodia( 23 ). The standard school meal, eaten as breakfast, consists of rice cooked with chick peas, served with canned tomato sauce with fish. Rice is the main component of the programme and is also the main vehicle in many other food-based social safety net programmes in Cambodia as well as in Asia. Therefore, evidence for the effectiveness of rice fortification would be of immediate importance to these programmes as well as for the development of national fortification guidelines in the whole region. The FORISCA project (Fortified Rice for School children in Cambodia) aimed to assess the effect of fortifying the rice in the WFP SMP with multiple micronutrients on micronutrient status and functional outcomes. The present paper reports on the effects of consuming rice fortified with multiple micronutrients, using three different fortification formulations, on cognitive performance based on specific cognitive functions in Cambodian children of primary-school age.

Participants and methods

Study site

The study was conducted in Cambodia, in sixteen primary schools from Kampong Speu province, around 60 km south-west of the capital Phnom Penh. Kampong Speu province can be characterized as rural, with most families involved in rice farming. In 2010, prevalence of stunting and underweight in pre-school children in Kampong Speu province was 44 and 9 %, respectively( 25 ) and in 2005 more than 60 % of pre-school children in the province were anaemic( 26 ). Representative data on schoolchildren were not available.

Study design and selection of participants

The study period was November 2012 to June 2013, with a rolling recruitment of 1 month and a 6-month intervention period. The study was a double-blind, cluster-randomized, placebo-controlled feeding trial, conducted in sixteen schools selected from all primary schools participating in the SMP of WFP (n 18) in Kampong Speu province that gave daily breakfast at school, but did not give take-home rations. The sixteen schools were randomly allocated to receive: (i) placebo (normal rice); (ii) UltraRice®Original; (iii) UltraRice®New; or (iv) NutriRice®. To ensure blinding, the intervention groups were coded with letters (A–H) and two schools were allocated to each intervention letter code. Randomization of schools was done by a researcher not involved in the study implementation (M.A.D.) and codes were known only to the researcher and the head of the logistics department of WFP, responsible for the distribution of rice to the schools. Codes were broken only after data collection was completed and all biochemical data analysis had been done. Before the study commenced, all parents of children of the selected schools were invited to attend a meeting at which objectives and procedures of the study were explained, as well as their right to refuse to participate in or to continue the study. Only children for whom written informed parental consent was obtained were eligible for randomization. In each school, 132 children were randomly selected from lists provided by the school director, with stratification by grade and gender, giving a total number of 2112 eligible children. Age of each child was calculated using the birth date provided by the registration book at school, itself based on the birth certificate. Exclusion criteria were age <6 years and severe anaemia (Hb concentration <70 g/l( 27 )). Severely anaemic children received appropriate treatment.


The meal was composed of rice (115 g uncooked) and yellow split peas (15 g uncooked) cooked together with a sauce made from canned fish (15 g), vegetable oil fortified with vitamin A and vitamin D (5 g), and iodized salt (3 g). Fortified rice kernels were produced from fortified rice flour by extrusion. NutriRice® (NR) was produced by hot extrusion by DSM and Buhler Food (Wuxi, China). Both types of UltraRice® were custom-made for the project, with UltraRice®Original (URO) produced using cold extrusion techniques by Maple Grove Gluten Free Foods, Ltd (Chino, CA, USA) and UltraRice®New (URN) using warm extrusion techniques by the Food Technology department of Kansas State University (Manhattan, KS, USA). Kernels were blended at a ratio of 1:99 with local normal rice to produce fortified rice. The same rice was used for the placebo intervention. The micronutrient composition of the URO, URN and NR is provided in Table 1. The meal was cooked in the school kitchen and served as breakfast at the beginning of the school day. The school meal was distributed for at least 6 months during school days (6 d/week, except during national holidays). An earlier study had shown that fortified rice (URO and NR) were highly accepted by Cambodian school-aged children( 28 ). Children were dewormed using mebendazole after baseline and endline sample collection. Cognitive performance, anthropometry, parasite infestation and micronutrient status were evaluated at baseline and after 6 months of intervention.

Table 1 Micronutrient composition of uncooked rice, per 100 g of blended rice

URO, UltraRice®Original; URN, UltraRice®New; NR, NutriRice®.

Data collection

Blood samples and anthropometric measurements were collected and cognitive tests performed at schools, after breakfast between 07.30 and 10.00 hours.

Cognitive tests

Cognitive tools generally suffer from intercultural variability( 15 , 29 ); to avoid bias linked to translation into Khmer language, tests not involving oral items and with predominantly pictorial content were chosen for the present study( 30 ). Three tests were performed to assess cognitive performance: (i) Raven’s coloured progressive matrices (RCPM), a common non-verbal test of overall intellectual ability in children aged ≥5 years( 31 33 ); and two standardized tests from the Wechsler Intelligence Scale for Children (WISC III) widely used to evaluate the intelligence of children aged 6–16 years( 34 ), namely (ii) block design and (iii) picture completion. RCPM and WISC III tests were previously used in Vietnamese schoolchildren in nutritional intervention trials( 35 ). RCPM consists of selecting the correct piece (choice of six different patterns) that completes an illustrated pattern. The block design test requires constructing a design with blocks to match a given design on a picture. The picture completion test consists of identifying the missing detail in a picture. Higher scores indicate better performance. Fluid intelligence underlies reasoning functions, whereas crystallized intelligence is related to experience, education and culture as it requires acquired skills and knowledge( 13 ). Block design and RCPM tests are associated with fluid intelligence( 36 38 ) while picture completion is related to crystallized intelligence( 39 ).

Each child was tested individually. The cognitive tests were administered by a team of twenty-five students from the Psychology department of Royal University of Phnom Penh. The team was specifically trained during a one-week workshop prior to the start of the intervention to ensure standardization of procedures and scoring.

Anthropometric measurements

Weight and height were measured without footwear and wearing minimal clothing, using standardized procedures( 40 ). Weight was measured once to the nearest 100 g (model 881 U scale; Seca, Hamburg, Germany). The accuracy of the scales was checked every day using a set of two calibration weights. Height was measured twice to the nearest 0·1 cm on a wooden stadiometer and mean values were used. When differences between two measures of height for the same child exceeded 0·5 cm, measurements were repeated. Height-for-age Z-score (HAZ) and BMI-for-age Z-score (BAZ) were calculated according to the WHO 2006 reference( 41 ). Stunting and severe stunting were defined as HAZ<−2 and HAZ<−3, respectively. Thinness and severe thinness were defined as BAZ<−2 and BAZ<−3, respectively. Overweight was defined as 1<BAZ≤2 and obesity as BAZ>2. Anthropometric measurements were performed by three teams who were trained and standardized before baseline and again before endline( 40 ).

Blood and urine sample collection and Hb concentration measurements

Five millilitres of venous blood were collected by experienced phlebotomists into a Vacuette® (Greiner Bio-One, Kremsmünster, Austria) trace-element-free vacutainer without anticoagulant. Urine was taken in a sterile container. Urine and blood samples were stored immediately at 4 °C in an icebox containing ice-packs and transported to the laboratory within a maximum of 5 h after the first sample was obtained. Blood samples were centrifuged at 2700 g for 10 min at room temperature. Serum and urine were then aliquoted into Eppendorf tubes and stored at −30 °C. Hb concentration was measured on-site in whole blood immediately after blood taking, using a HemoCue® R 301+ System and HemoCue controls (Hemotrol low, medium and high; HemoCue AB, Ängelholm, Sweden).

Parasite infestation

Plastic containers and instructions for stool sample collection were given to the child on the day of data collection and requested to be returned to the school the following day. Stool samples were then stored in a cool box, transferred to the National Malaria Center (CNM, Phnom Penh, Cambodia) and stored at 4 °C until analysis. Quantitative parasite eggs counts were performed by CNM using the Kato–Katz method( 42 ).

Laboratory analyses

Ferritin, soluble transferrin receptor, retinol-binding protein, C-reactive protein and α1-acid glycoprotein serum concentrations

Serum samples were sent on dry ice to the VitMin laboratory (Willstaett, Germany) for determination of ferritin (FER), soluble transferrin receptor (TfR), retinol-binding protein (RBP), C-reactive protein (CRP) and α1-acid glycoprotein (AGP) concentrations. All of these proteins were measured by a sandwich ELISA technique( 43 ). Inflammation was defined as an elevated CRP (>5 mg/l) and/or elevated AGP (>1 g/l), allowing differentiation between incubation phase (high CRP), convalescence phase (both AGP and CRP elevated) and late convalescence phase (elevated AGP only)( 44 ). Anaemia was defined as Hb below cut-offs depending on age and gender: 115 g/l for participants aged <12 years, 120 g/l for adolescents aged 12–15 years and girls aged ≥15 years, and 130 g/l for boys aged ≥15 years; severe anaemia was defined as Hb<70 g/l; depleted Fe stores were defined as inflammation-corrected FER<15 μg/l( 27 ). Correction factors for FER were 0·77, 0·53 and 0·75 for participants in incubation, early convalescence and late convalescence phases, respectively, after Thurnham et al.( 44 ). Tissue Fe deficiency was defined as TfR>8·3 mg/l( 43 ). Low FER and high TfR concentrations are both considered indicators of Fe deficiency( 27 ), so Fe deficiency was defined as depleted Fe stores (low FER) and/or tissue Fe deficiency (high TfR). Body Fe was calculated according to the formula of Cook et al.( 45 ): body Fe (mg/kg)=[2(log (TfR/FER) × 22·8229)]/0·1207, using FER corrected for inflammation. Body Fe was considered low when <4 mg/kg( 46 ). Vitamin A status was measured using RBP concentration, which reflects serum retinol concentration as RBP occurs in a 1:1:1 complex with retinol and transthyretin( 47 ). RBP concentrations were corrected in participants with inflammation by the factor of 1·15, 1·32 and 1·12, respectively, for incubation, early convalescence and late convalescence( 48 ). Vitamin A deficiency was defined as corrected RBP<0·7 μmol/l( 47 ) and marginal vitamin A deficiency as corrected RBP value ≥0·7 and <1·05 μmol/l( 49 ).

Serum zinc concentration

Serum samples were sent on dry ice to the National Institute of Nutrition (Hanoi, Vietnam). Serum Zn was measured by flame atomic absorption spectrophotometry, using trace-element-free procedures. Considering that none of the children were fasting due to the school breakfast, Zn deficiency was defined as serum Zn concentration <0·65 mg/l for participants aged <10 years; for participants aged ≥10 years, the cut-off used was 0·66 mg/l for girls and 0·70 mg/l for boys( 50 ). Severe Zn deficiency was defined as serum Zn concentration <0·5 mg/l( 51 ).

Urinary iodine concentration

Urine samples were sent on dry ice to the National Institute of Nutrition (Hanoi, Vietnam). Urinary iodine was measured using an ammonium persulfate method at the Thai Nguyen Provincial Hospital, Vietnam, which is one of the three reference laboratories for iodine determination in Vietnam( 52 ). Iodine deficiency and iodine status above requirements were defined as urinary iodine concentration <50 µg/l and >200 µg/l, respectively( 53 ).

Rice sample analysis

Analysis of the fortified kernels for Fe, Zn, vitamin A, vitamin B6, vitamin B12, folic acid and niacin was conducted after production by Silliker Laboratories (Chicago, IL, USA) using standard methods. The final composition of blended fortified rice was calculated taking account of a mixing ratio of 1:100. The composition of the fortified rice kernels is given in Table 1.

Data management and statistical analysis

Data entry, including quality checks and validation by double entry of questionnaires, was performed with EpiData version 3·1 (EpiData Association, Odense, Denmark). Data management and analyses were performed using the statistical software package IBM SPSS Statistics version 20.0. Normality of data was checked before analysis with the Kolmogorov–Smirnoff test. In addition, absolute values of skewness and kurtosis of the distribution curves of <2 and <7, respectively, were used to indicate that the distribution of continuous variables was close to normal( 54 ). Baseline characteristics were compared between intervention groups using ANOVA for continuous variables and the Pearson χ 2 test for categorical variables.

Primary analysis

Generalized linear mixed models including intervention group, visit (baseline, endline), intervention group×visit, age, gender and clustering (school within group) as fixed factors were used to assess the impact of intervention on the raw scores of the cognitive tests compared with the placebo group. A P value of <0·05 was considered significant and a P value between 0·1 and 0·05 as a tendency.

Secondary analysis

Low Fe status, helminth infection and stunting were identified earlier as risk factors for low cognitive scores in children participating in the FORISCA study( 55 ). Inflammation was shown to significantly affect the effect of the FORISCA intervention on micronutrient status( 56 ). To assess if these covariates had an impact on the effect of the intervention on cognitive scores in the present study, interactions of body Fe <4 mg/kg, helminth infection, stunting and inflammation were included as fixed factors in the previous generalized mixed models.


Baseline characteristics

In total, cognition data were available for 1933 children at baseline and 1796 children at endline (Fig. 1). Biochemical, physiological and anthropometric characteristics of the 1933 children at baseline are presented in Table 2.

Fig. 1 Design of the FORISCA-UltraRice®+NutriRice® study conducted among Cambodian schoolchildren aged 6–16 years, November 2012–June 2013 (FORISCA, Fortified Rice for School children in Cambodia; WFP, World Food Programme; SMP, school meal programme; URO, UltraRice®Original; URN, UltraRice®New; NR, NutriRice®)

Table 2 Baseline characteristics of Cambodian schoolchildren aged 6–16 years (n 1933), FORISCA-UltraRice®+NutriRice® study, November 2012–June 2013

FORISCA, Fortified Rice for School children in Cambodia; HAZ, height-for-age Z-score; BAZ, BMI-for-age Z-score; CRP, C-reactive protein; AGP, α1-acid glycoprotein; FER, ferritin; TfR, soluble transferrin receptor; UIC, urinary iodine concentration; RBP, retinol-binding protein.

* Hb<115 g/l for participants aged <12 years; 120 g/l for teenagers aged 12–15 years and girls aged ≥15 years; 130 g/l for boys aged ≥15 years.

FER corrected for inflammation <15 mg/l.

Serum Zn<0·65 mg/l for participants aged <10 years; for participants aged ≥10 years, cut-off is 0·66 mg/l for girls and 0·70 mg/l for boys.

§ Serum Zn<0·5 mg/l.

Mean age at enrolment was 9·7 years old, with participants’ age ranging from 6 years to 16 years. Due to late school enrolment and repeating of class, 44 % of the participants were aged ≥10 years, which is adolescent according to the WHO definition( 57 ), but in the present paper all participants are referred to as children. Stunting was highly prevalent in the children participating in the FORISCA study (43 %), whereas 26 % were classified as ‘thin’. Fe stores were adequate (FER>15 μg/l) in most children (99 %), whereas, paradoxically, tissue Fe deficiency was highly prevalent (48 % of participants with TfR>8·3 mg/l). Accordingly, half of the children were classified as Fe deficient, but this was almost exclusively related to high TfR. Almost all children were Zn deficient (>90 %) while less than 1 % of the children were vitamin A deficient. Prevalence of anaemia was 17 %.

Primary analysis

All cognitive scores improved over the 6-month intervention (visit (baseline, endline) effect: P<0·001; Table 3). On average, the scores increased by 7 (54 %), 3 (20 %) and 3 (38 %) points for the block design, RCPM and picture completion test, respectively (results not shown). The intervention had a significant overall impact on block design score increase (effect of interaction between intervention group and visit, P=0·003; Table 3). Improvement in block design scores was significantly higher compared with the placebo group only in children consuming URO (β=1·17; 95 % CI 0·12, 2·22; P=0·03). No significant difference in RCPM scores or picture completion scores was found between the intervention groups.

Table 3 Cognition outcomes and effect sizes after 6 months of intervention for Cambodian schoolchildren aged 6–16 years (n 1796), FORISCA-UltraRice®+NutriRice® study, November 2012–June 2013

FORISCA, Fortified Rice for School children in Cambodia; RCPM, Raven’s coloured progressive matrices; URO, UltraRice®Original; URN, UltraRice®New; NR, NutriRice®.

* Results from generalized mixed models including intervention group, visit (baseline, endline), intervention group×visit, age, gender and clustering (school within group) as fixed factors.

Effect of intervention group on the difference in scores between baseline and endline.

Secondary analysis

For block design scores, only stunting had an influence on the impact of the intervention (P=0·006 for overall interaction; Table 4), while intestinal parasite infection, inflammation and low body Fe did not. The increase in block design scores over time was higher in non-stunted children receiving NR compared with stunted children receiving NR (difference in scores=−0·69, P=0·05).

Table 4 Effects of risk factors for low cognitive scores on the 6-month intervention among Cambodian schoolchildren aged 6–16 years (n 1796), FORISCA-UltraRice®+NutriRice® study, November 2012–June 2013

FORISCA, Fortified Rice for School children in Cambodia; URO, UltraRice®Original; URN, UltraRice®New; NR, NutriRice®; RCPM, Raven’s coloured progressive matrices.

Results from generalized mixed models including age, gender, clustering (school within group), intervention group, visit (baseline, endline), intervention group×visit, and each risk factor (stunting, parasite infection, inflammation or low body Fe)×intervention group×visit, as fixed factors.

* β coefficient of the interaction intervention group×visit×risk factor (stunting, parasite infection, inflammation or low body Fe).

Difference in improvement of scores between baseline and endline in stunted children compared with non-stunted children (or in children with parasites compared with children without parasites, or in children with inflammation compared with children without inflammation, or in children with low body Fe compared with children with normal body Fe).

Significance of the difference of improvement in scores.

For RCPM scores, parasite infection had a negative effect on the intervention (P=0·045 for overall interaction). Among children receiving URO, RCPM scores increased more in children without parasites than in children with parasites (difference in scores=−0·08, P=0·010). Low body Fe, stunting and inflammation did not affect the impact of the intervention regarding RCPM scores.

For picture completion scores, both stunting and low body Fe had a strong effect on the impact of the intervention (P<0·001 and P=0·001, respectively). In children receiving URN, those with low body Fe increased less in their picture completion scores compared with children with body Fe ≥4 mg/kg (difference in scores=0·51, P=0·001). Similarly, the scores of stunted children increased less compared with non-stunted children receiving URO (difference in scores=−0·51, P=0·015).


To our knowledge, the present paper is the first reporting modest but significant effects of a micronutrient-fortified rice provided in an SMP on cognitive function in primary-school children. Beneficial effects of URO on micronutrient status and anaemia were reported in small populations (n 210) of Mexican women( 20 ), Indian school-aged children( 18 ) and Thai school-aged children( 58 ). No effect of NR was found on Indian children’s cognitive function, but the sample size was considerably smaller than in the present study( 19 ). Duration of these studies was comparable to the FORISCA study, with meals containing URO or NR being served 5–6 d/week for 5 to 8 months.

Perhaps surprisingly, the present study found an effect of only URO on cognitive performance, and not of the two other types of fortified rice.

URO was fortified with Zn, which is involved in neurotransmission pathways( 59 ). Moreover, Zn, as a component of Zn-dependent enzymes, plays an important role in neuronal genesis and migration, making adolescents particularly sensitive to Zn deficiency due to rapid brain growth, similar to early childhood( 5 , 59 , 60 ). Even though data are lacking about long-term effects of Zn treatment on cognitive performance, there is some evidence that Zn supplementation may improve neuropsychological functions( 5 ) especially reasoning( 61 ). For example, Zn supplementation had beneficial effects on cognitive scores of Indian adolescent girls, by reducing reaction time, improving memory and RCPM scores( 62 ). However, a recent meta-analysis found no effect of Zn on cognitive functioning, but reported that there is a lack of high-quality trials( 63 ). Zn composition was close between the different formulas of fortified rice and the FORISCA intervention improved Zn status and reduced Zn deficiency and severe Zn deficiency in all intervention groups (K Kuong, P Tor, M Fiorentino et al., unpublished results). Plus, negative cases of interactions between Zn and Fe in fortification or supplementation trials were reported( 64 ). Therefore, we may not attribute cognitive improvement to Zn in URO.

URO contained the highest concentration of Fe, which is known to be important in brain development also during pre-adolescence and adolescence. Fe plays a role in neurotransmission, especially in the dopamine pathway, which serves in memory, learning, attention, motor control and emotional affect modulation( 65 , 66 ). Increasing Fe intake in Fe-deficient and/or anaemic children using fortification or supplementation has been shown to improve schooling or cognitive outcomes like learning, memory, concentration or school achievement( 11 , 12 , 67 71 ). URO did not improve Fe stores and was not fortified with vitamin A, but it was the only fortified rice that improved cognitive performance, which is tempting to link to the improved tissue Fe status observed only in children receiving URO (decrease of TfR concentrations, P=0·088, as reported elsewhere( 56 )).

At baseline in all groups, Fe deficiency was uncommon, which could possibly have limited the impact of the fortified rice formulas on cognitive performance. The high prevalence of high TfR concentrations, suggesting functional Fe deficiency with the absence of depleted Fe stores, may appear surprising, as the Fe depletion process usually consists of depletion of Fe stores before tissue Fe decrease and erythropoiesis impairment. However, such discrepancy between adequate Fe stores and tissue Fe deficiency has been reported in several other studies, and attributed among other factors to malaria or haemoglobinopathies( 56 , 72 75 ). Therefore, we may hypothesize that external Fe provided to children with replete Fe stores but functional Fe deficiency was first used for filling tissues and for functions, such as cognitive functions, before building Fe stores in the URO group. A slight decrease of Hb was also observed at midline in this group (P=0·068)( 56 ), thus these physiological functions were probably non-erythropoietic functions. Although URO contained the highest Fe content, the difference compared with the two other types of fortified rice was relatively small, and other micronutrients might have contributed to the observed difference in impact on cognition.

No cognitive improvement, but a significant increase of FER and TfR, respectively indicating improvement of Fe stores and decline of Fe status, was observed between baseline and endline only in children receiving URN and NR (P<0·001 for all). The additional vitamin A in these two groups improved vitamin A status of the children (P<0·001)( 56 ) and may have helped to build Fe stores, as was already observed in adolescents supplemented with multiple micronutrients( 76 ) or children consuming vitamin A-fortified food( 77 ). At the same time, tissue Fe decreased in children receiving URN and NR, an effect that could perhaps be attributed to the vitamin A in the rice premix in these two groups also. Vitamin A might have led to higher erythropoietin concentrations, pushing erythropoiesis as reported elsewhere( 78 ). Vitamin A is known to help in mobilizing Fe for physiological functions, especially erythropoiesis, as was observed in anaemic children receiving vitamin A supplementation( 78 , 79 ) and in animal models( 80 ). Interestingly, a slight increase of Hb concentrations was observed in children receiving URN between baseline and midline (P=0·048). Oppositely to what was observed in the URO group, external Fe was apparently first used for building stores and erythropoiesis before physiological functions. One may assume that vitamin A provided in URN and NR groups has increased Fe storage to the detriment of tissue uptake of Fe for other functions such as cognitive improvement on one hand, and stimulated erythropoiesis using Fe from tissues rather than from stores, on the other hand.

Moreover, it is likely that interactions with other micronutrients present in the URN and NR, but not in the URO, also played a role in modifying the effect on cognitive outcomes. URN had the lowest concentrations of Zn and Fe but the highest of vitamins (A, B6, B12, thiamin, folic acid and niacin). Even though vitamins B12, B6 and folic acid are known to play a role in cognitive performance by being involved in methylation in the central nervous system( 81 , 82 ), URN and NR, fortified with these vitamins, did not improve cognition performance in the present study, while URO, not fortified with these vitamins, did improve cognition performance. Therefore, we could hypothesize that improvement in cognition performance in the present study is more likely to be related to the additional Fe and Zn provided through URO, and not to additional B-vitamins. However, these results should be interpreted with caution. Another hypothesis to explain our discrepant results about Fe status and cognitive performance between fortified rice formulas may be that vitamins A, B12 and niacin in URN and NR helped to build Fe stores and pushed erythropoiesis( 83 ) to the detriment of tissue Fe uptake for cognitive development. Little is known about the role micronutrients on the physiological pathways of Fe distribution between Fe storage, erythropoiesis and other physiological functions. No data about vitamin B12 and niacin deficiencies were collected during the study, hence the prevalence and potential impact of vitamin B12 and niacin deficiencies on the intervention are not known. Apart from Zn and Fe negative interactions, other contradictory benefits of different micronutrients on cognitive improvement are not well documented to our knowledge.

Therefore, the possible effect of Fe alone and the interaction between Fe and other micronutrients remain unclear. The results also raise questions on which indicator should be used for assessing functional Fe deficiency.

In an overview of randomized controlled trials of multiple micronutrient supplementation in school-aged children, Eilander et al. noticed a potential beneficial effect on fluid intelligence and school performance, but not on crystallized intelligence( 13 ), which is consistent with fortified rice having an impact on block design scores but not on picture completion scores in children participating in the FORISCA study. The block design test measures perceptual reasoning and executive functions, both of which are associated with frontal lobe functions( 39 , 84 ). The development of the full range of executive functions is suggested to occur in late childhood and adolescence as myelination of the frontal lobes proceeds( 31 ), with peaks at 7, 9 and 12 years of age( 66 , 85 ). There is some evidence that Fe is a key nutrient in the development of these executive functions( 66 ).

Although the impact of URO on RCPM scores did not reach significance, it was significantly lower in children with intestinal parasite infection than in those without parasites. Hence, while being a risk factor for poor cognitive scores in itself, parasite infestation also limited the impact of fortified rice on RCPM scores. Earlier we reported that fortified rice also increased parasite infestation in children participating in the FORISCA study( 86 ), highlighting the complex interaction between nutrition and infection.

Albeit no significant impact of fortified rice on RCPM and picture completion scores was observed in the general sample, low body Fe diminished the increase of these scores over the intervention period regardless of intervention type, indicating that children participating in the FORISCA study with low Fe status benefited less from fortified rice with respect to cognition scores, in comparison to children with adequate Fe status. Even if increased Fe intake during the intervention had an overall beneficial effect on block design scores, this suggests that the amount of bioavailable Fe in the fortified rice may not be sufficient to reverse the negative effect of Fe deficiency on cognition scores.

Inflammation also had a negative effect on RCPM score improvement. Interestingly, this is in parallel with the observed effects of fortified rice on Fe status of children participating in the FORISCA study, which emerged stronger after removing children with inflammation from the analysis( 56 ). This suggests that the acute-phase response may disturb the response to fortified foods and therefore the impact on functional outcomes such as cognitive performance.

Strengths and limitations of the study

One of the strengths of the present study was its design as an effectiveness trial. We assessed the impact of the introduction of fortified rice within an existing programme, with minimal interference in the programme’s daily logistics. Hence, the results obtained provide a realistic indication of what can be expected from the introduction of multi-micronutrient-fortified rice on cognitive performance in Cambodian school-aged children. Another strength of the study is the sample size, with >2000 children being followed over the study period.

One limitation of the study was the intervention’s short duration of only 6 months; this amount of time may not have been enough to improve cognitive performance to its full potential. An intervention exceeding 6 months may have shown a larger impact on cognitive outcomes. Also, the present study was an effectiveness study, not an efficacy study. Hence, quantities of rice consumed every day were not controlled. Moreover, it was not possible to ensure that micronutrient status at baseline would be the same between randomized groups. The prevalence of low Fe stores was very low, and larger impact on cognitive function may have been observed in a population with a higher prevalence. Although the schools were randomly allocated to the different intervention groups, groups still differed with respect to thinness, Fe status, iodine status, micronutrient deficiencies and parasite infestation. Groups did not differ with respect to gender, age and stunting. As the sample size is large, and the statistical modelling robust, no attempts were made to correct or amend for this; instead the validity of each analysis was carefully checked. In addition, the pre–post comparison model of the study design further aids the clear interpretation of the data. Another limitation of the FORISCA study is that levels of Fe and Zn used in the present study are below the current recommended levels for fortified rice, which might have reduced the effectiveness( 87 ).


The WFP SMP is known to be an incentive for school attendance and enrolment, and could enhance learning by reducing hunger and increasing concentration( 23 ). However, only selected cognitive functions may still be improved with nutritional interventions at school age, which stresses the importance to pursue efforts for prevention of malnutrition over the life cycle, especially before and during pregnancy and early childhood, together with school interventions in order to prevent irreversible cognitive damages. The current study illustrates that fortification of school meals with multiple micronutrients can improve cognitive performance and thus promote schooling further. However, the improvements in cognitive performance were modest and impact was modified by several external factors such as stunting, intestinal parasite infestation, low body Fe and inflammation. This strengthens the case for combining health interventions, such as deworming combined with provision of micronutrients. However, micronutrients used in rice fortification should be carefully selected and appropriately dosed, taking the initial nutritional and infection status of the target population also into account.


Acknowledgements: The authors are most grateful to the children participating in the FORISCA study and their parents. Additional appreciation goes to colleagues who were involved in data collection, biochemical analyses and distribution of meals. The authors thank school teachers and directors, local authorities and education authorities for their cooperation. Financial support: This work was funded by the UN WFP–DSM consortium; the US Department of Agriculture/Foreign Agricultural Service (USDA/FAS); and the Institut de Recherche pour le Développement (IRD). DSM had no role in the design, analysis or writing of this article. Conflict of interest: No author has conflict of interest. Authorship: M.F. participated in the data collection, performed the statistical analysis and wrote the manuscript. M.Pe. and M.Pa. participated in the research design, data collection and the manuscript review. K.K., K.B., S.S., C.C. and J.B. participated in the research design and data collection. R.d.G. participated in the statistical analysis and the manuscript review. M.A.D. was responsible for group allocation and reviewed the manuscript. F.T.W. supervised the general research, participated in the statistical analysis and reviewed the manuscript. All authors read and approved the final manuscript. Ethics of human subject participation: This study was conducted according to the guidelines laid down in the Declaration of Helsinki and was approved by the National Ethic Committee for Health Research (NECHR) of the Ministry of Health (Phnom Penh, Cambodia) and the Research Ethics Committee (REC) of PATH (Program for Appropriate Technology in Health, Seattle, USA). Written informed consent was obtained from parents of all involved children. The trial was registered at (identifier: NCT01706419).


1. Black, RE, Victora, CG, Walker, SP et al. (2013) Maternal and child undernutrition and overweight in low-income and middle-income countries. Lancet 382, 427451.
2. Best, C, Neufingerl, N, van Geel, L et al. (2010) The nutritional status of school-aged children: why should we care? Food Nutr Bull 31, 400417.
3. McCann, JC & Ames, BN (2007) An overview of evidence for a causal relation between iron deficiency during development and deficits in cognitive or behavioral function. Am J Clin Nutr 85, 931945.
4. Morley, R (1998) Nutrition and cognitive development. Nutrition 14, 752754.
5. Bhatnagar, S & Taneja, S (2001) Zinc and cognitive development. Br J Nutr 85, Suppl. 2, S139S145.
6. Black, R (2003) Micronutrient deficiency: an underlying cause of morbidity and mortality. Bull World Health Organ 81, 79.
7. Atinmo, T, Mirmiran, P, Oyewole, OE et al. (2009) Breaking the poverty/malnutrition cycle in Africa and the Middle East. Nutr Rev 67, Suppl. 1, S40S46.
8. Lockwood, M & Collier, P (1988) Maternal Education and the Vicious Cycle of High Fertility and Malnutrition: An Analytic Survey. New York: World Bank.
9. Beard, J (2003) Iron deficiency alters brain development and functioning. J Nutr 133, 5 Suppl. 1, 1468S1472S.
10. Shrestha, R (1994) Effect of Iodine and Iron Supplementation on Physical, Psychomotor and Mental Development in Primary School Children in Malawi. Wageningen: Wageningen Agricultural University.
11. Pollitt, E, Soemantri, A, Yunis, F et al. (1985) Cognitive effects of iron-deficiency anaemia. Lancet 325, 158.
12. Bruner, AB, Joffe, A, Duggan, AK et al. (1996) Randomised study of cognitive effects of iron supplementation in non-anaemic iron-deficient adolescent girls. Lancet 348, 992996.
13. Eilander, A, Gera, T, Sachdev, HS et al. (2010) Multiple micronutrient supplementation for improving cognitive performance in children: systematic review of randomized controlled trials. Am J Clin Nutr 91, 115130.
14. Allen, LH, Peerson, JM & Olney, DK (2009) Provision of multiple rather than two or fewer micronutrients more effectively improves growth and other outcomes in micronutrient-deficient children and adults. J Nutr 139, 10221030.
15. Khor, GL & Misra, S (2012) Micronutrient interventions on cognitive performance of children aged 5–15 years in developing countries. Asia Pac J Clin Nutr 21, 476486.
16. Best, C, Neufingerl, N, Del Rosso, JM et al. (2011) Can multi-micronutrient food fortification improve the micronutrient status, growth, health, and cognition of schoolchildren? A systematic review. Nutr Rev 69, 186204.
17. Moretti, D, Zimmermann, MB, Muthayya, S et al. (2006) Extruded rice fortified with micronized ground ferric pyrophosphate reduces iron deficiency in Indian schoolchildren: a double-blind randomized controlled trial. Am J Clin Nutr 84, 822829.
18. Radhika, MS, Nair, KM, Kumar, RH et al. (2011) Micronized ferric pyrophosphate supplied through extruded rice kernels improves body iron stores in children: a double-blind, randomized, placebo-controlled midday meal feeding trial in Indian schoolchildren. Am J Clin Nutr 94, 12021210.
19. Thankachan, P, Rah, JH, Thomas, T et al. (2012) Multiple micronutrient-fortified rice affects physical performance and plasma vitamin B-12 and homocysteine concentrations of Indian school children. J Nutr 142, 846852.
20. Hotz, C, Porcayo, M, Onofre, G et al. (2008) Efficacy of iron-fortified Ultra Rice in improving the iron status of women in Mexico. Food Nutr Bull 29, 140149.
21. Beinner, MA, Velasquez-Melendez, G, Pessoa, MC et al. (2010) Iron-fortified rice is as efficacious as supplemental iron drops in infants and young children. J Nutr 140, 4953.
22. Nogueira Arcanjo, FP, Santos, PR, Arcanjo, CP et al. (2012) Use of iron-fortified rice reduces anemia in infants. J Trop Pediatr 58, 475480.
23. World Food Programme (2013) State of School Feeding Worldwide 2013. Rome: WPF.
24. Alavi, S, Bugusu, B, Cramer, G et al. (2008) Rice Fortification in Developing Countries: A Critical Review of the Technical and Economic Feasibility. Washington, DC: Institute of Food Technologists.
25. World Health Organization (2012) WHO Global Database on Child Growth and Malnutrition. (accessed April 2014).
26. World Health Organization (2007) Vitamin and Mineral Nutrition Information System (VMNIS). WHO Global Database on Anaemia. (accessed April 2014).
27. World Health Organization (2007) Assessing the Iron Status of Populations: Including Literature Reviews. Report of a Joint World Health Organization/Centers for Disease Control and Prevention Technical Consultation on the Assessment of Iron Status at the Population Level. Geneva: WHO.
28. Khanh Van, T, Burja, K, Thuy Nga, T et al. (2014) Organoleptic qualities and acceptability of fortified rice in two Southeast Asian countries. Ann N Y Acad Sci 1324, 4854.
29. Greenfield, PM (1997) You can’t take it with you: why ability assessments don’t cross cultures. Am Psychol 52, 11151124.
30. Van de Vijver, F & Tanzer, N (1997) Bias and equivalence in cross-cultural assessment. Eur Rev Appl Psychol 47, 263279.
31. Isaacs, E & Oates, J (2008) Nutrition and cognition: assessing cognitive abilities in children and young people. Eur J Nutr 47, Suppl. 3, 424.
32. Kaplan, RM & Saccuzzo, DP (2009) Psychological Testing: Principles, Applications, and Issues. Belmont, CA: Wadsworth Cengage Learning.
33. Aiken, LR (2004) Assessment of Intellectual Functioning. Berlin/Heidelberg: Springer Science & Business Media.
34. Hughes, D & Bryan, J (2003) The assessment of cognitive performance in children: considerations for detecting nutritional influences. Nutr Rev 61, 413422.
35. Nga, TT, Winichagoon, P, Dijkhuizen, MA et al. (2011) Decreased parasite load and improved cognitive outcomes caused by deworming and consumption of multi-micronutrient fortified biscuits in rural Vietnamese schoolchildren. Am J Trop Med Hyg 85, 333340.
36. DeThorne, LS & Schaefer, BA (2004) A guide to child nonverbal IQ measures. Am J Speech Lang Pathol 13, 275290.
37. Wesley, LV (2006) Artificial Intelligence: New Research. New York: Nova Science Publishers.
38. Gray, JR, Chabris, CF & Braver, TS (2003) Neural mechanisms of general fluid intelligence. Nat Neurosci 6, 316322.
39. Pennington, BF (2008) Diagnosing Learning Disorders: A Neuropsychological Framework. New York: Guilford Press.
40. Cogill, B (2003) Anthropometric Indicators Measurement Guide. Washington, DC: Food and Nutrition Technical Assistance, FHI 360.
41. de Onis, M, Onyango, AW, Borghi, E et al. (2007) Development of a WHO growth reference for school-aged children and adolescents. Bull World Health Organ 85, 660667.
42. Ash, L, Orihel, T & Savioli, L (1994) Bench Aids for the Diagnosis of Intestinal Parasites. Geneva: WHO.
43. Erhardt, JG, Estes, JE, Pfeiffer, CM et al. (2004) Combined measurement of ferritin, soluble transferrin receptor, retinol binding. J Nutr 134, 31273132.
44. Thurnham, DI, McCabe, LD, Haldar, S et al. (2010) Adjusting plasma ferritin concentrations to remove the effects of subclinical inflammation in the assessment of iron deficiency: a meta-analysis. Am J Clin Nutr 92, 546555.
45. Cook, JD, Flowers, CH & Skikne, BS (2003) The quantitative assessment of body iron. Blood 101, 33593363.
46. Milman, N (2010) Iron in pregnancy: how do we secure an appropriate iron status in the mother and child? Ann Nutr Metab 59, 5054.
47. de Pee, S & Dary, O (2002) Biochemical indicators of vitamin A deficiency: serum retinol and serum retinol. J Nutr 132, 9 Suppl., 2895S2901S.
48. Thurnham, DI, McCabe, GP, Northrop-Clewes, CA et al. (2003) Effects of subclinical infection on plasma retinol concentrations and assessment. Lancet 362, 20522058.
49. Gibson, RS (1990) Principles of Nutritional Assessment, pp. 378388. New York: Oxford Press.
50. Brown, KH, Rivera, JA, Bhutta, Z et al. (2004) International Zinc Nutrition Consultative Group (IZiNCG) technical document #1. Assessment of the risk of zinc deficiency in populations and options for its control. Food Nutr Bull 25, 1 Suppl. 2, S99S203.
51. Sazawal, S, Black, RE, Bhan, MK et al. (1997) Efficacy of zinc supplementation in reducing the incidence and prevalence of acute diarrhea – a community-based, double-blind, controlled trial. Am J Clin Nutr 66, 413418.
52. Pino, S, Fang, SL & Braverman, LE (1996) Ammonium persulfate: a safe alternative oxidizing reagent for measuring urinary iodine. Clin Chem 42, 239243.
53. World Health Organization/UNICEF/International Council for Control of Iodine Deficiency Disorders (2007) Assessment of Iodine Deficiency Disorders and Monitoring their Elimination. A Guide for Program Managers, 3rd ed. Geneva: WHO.
54. Kim, H-Y (2013) Statistical notes for clinical researchers: assessing normal distribution (2) using skewness and kurtosis. Restor Dent Endod 38, 5254.
55. Perignon, M, Fiorentino, M, Kuong, K et al. (2014) Stunting, poor iron status and parasite infection are significant risk factors for lower cognitive performance in Cambodian school-aged children. PLoS One 9, e112605.
56. Perignon, M, Fiorentino, M, Kuong, K et al. (2016) Impact of multi-micronutrient fortified rice on hemoglobin, iron and vitamin A status of Cambodian schoolchildren: a double-blind cluster-randomized controlled trial. Nutrients 8, E29.
57. World Health Organization (1986) Young People’s Health – A Challenge for Society. Report of a WHO Study Group on Young People and ‘Health for All by the Year 2000’. WHO Technical Report Series no. 731. Geneva: WHO.
58. Pinkaew, S, Winichagoon, P, Hurrell, RF et al. (2013) Extruded rice grains fortified with zinc, iron, and vitamin A increase zinc status of Thai school children when incorporated into a school lunch program. J Nutr 143, 362368.
59. Golub, MS, Keen, CL, Gershwin, ME et al. (1995) Developmental zinc deficiency and behavior. J Nutr 125, 8 Suppl., 2263S2271S.
60. Levenson, CW & Morris, D (2011) Zinc and neurogenesis: making new neurons from development to adulthood. Adv Nutr 2, 96100.
61. Black, MM (2003) The evidence linking zinc deficiency with children’s cognitive and motor functioning. J Nutr 133, 5 Suppl. 1, 1473S1476S.
62. Kawade, R (2012) Zinc status and its association with the health of adolescents: a review of studies in India. Glob Health Action 5, 7353.
63. Warthon-Medina, M, Moran, V, Stammers, A et al. (2015) Zinc intake, status and indices of cognitive function in adults and children: a systematic review and meta-analysis. Eur J Clin Nutr 69, 649661.
64. Olivares, M, Pizarro, F, Ruz, M et al. (2012) Acute inhibition of iron bioavailability by zinc: studies in humans. Biometals 25, 657664.
65. Murray-Kolb, LE & Beard, JL (2007) Iron treatment normalizes cognitive functioning in young women. Am J Clin Nutr 85, 778787.
66. Bryan, J, Osendarp, S, Hughes, D et al. (2004) Nutrients for cognitive development in school-aged children. Nutr Rev 62, 295306.
67. Lynn, R & Harland, EP (1998) A positive effect of iron supplementation on the IQs of iron deficient children. Pers Individ Diff 24, 883885.
68. Saloojee, H & Pettifor, JM (2001) Iron deficiency and impaired child development. BMJ 323, 13771378.
69. Groner, JA, Holtzman, NA, Charney, E et al. (1986) A randomized trial of oral iron on tests of short-term memory and attention span in young pregnant women. J Adolesc Health Care 7, 4448.
70. Seshadri, S & Gopaldas, T (1989) Impact of iron supplementation on cognitive functions in preschool and school-aged children: the Indian experience. Am J Clin Nutr 50, 3 Suppl., 675684.
71. Soemantri, A, Pollitt, E & Kim, I (1985) Iron deficiency anemia and educational achievement. Am J Clin Nutr 42, 12211228.
72. Fiorentino, M, Bastard, G, Sembène, M et al. (2013) Anthropometric and micronutrient status of school-children in an urban West Africa setting: a cross-sectional study in Dakar (Senegal). PLoS One 8, e84328.
73. Grant, FK, Martorell, R, Flores-Ayala, R et al. (2012) Comparison of indicators of iron deficiency in Kenyan children. Am J Clin Nutr 95, 12311237.
74. Aguilar, R, Moraleda, C, Quinto, L et al. (2012) Challenges in the diagnosis of iron deficiency in children exposed to high prevalence of infections. PLoS One 7, e50584.
75. Schulze, KJ, Christian, P, Wu, LS-F et al. (2014) Micronutrient deficiencies are common in 6-to 8-year-old children of rural Nepal, with prevalence estimates modestly affected by inflammation. J Nutr 144, 979987.
76. Angeles-Agdeppa, I, Schultink, W, Sastroamidjojo, S et al. (1997) Weekly micronutrient supplementation to build iron stores in female Indonesian adolescents. Am J Clin Nutr 66, 177183.
77. Mejia, LA & Chew, F (1988) Hematological effect of supplementing anemic children with vitamin A alone and in combination with iron. Am J Clin Nutr 48, 595600.
78. Zimmermann, MB, Biebinger, R, Rohner, F et al. (2006) Vitamin A supplementation in children with poor vitamin A and iron status increases erythropoietin and hemoglobin concentrations without changing total body iron. Am J Clin Nutr 84, 580586.
79. Cusick, SE, Tielsch, JM, Ramsan, M et al. (2005) Short-term effects of vitamin A and antimalarial treatment on erythropoiesis in severely anemic Zanzibari preschool children. Am J Clin Nutr 82, 406412.
80. da Cunha, MS, Siqueira, EM, Trindade, LS et al. (2014) Vitamin A deficiency modulates iron metabolism via ineffective erythropoiesis. J Nutr Biochem 25, 10351044.
81. Alpert, JE & Fava, M (1997) Nutrition and depression: the role of folate. Nutr Rev 55, 145149.
82. Bottiglieri, T (1996) Folate, vitamin B12, and neuropsychiatric disorders. Nutr Rev 54, 382390.
83. Munoz, M, Villar, I & Garcia-Erce, JA (2009) An update on iron physiology. World J Gastroenterol 15, 46174626.
84. Brown, LA, Brockmole, JR, Gow, AJ et al. (2012) Processing speed and visuospatial executive function predict visual working memory ability in older adults. Exp Aging Res 38, 119.
85. Giedd, JN, Blumenthal, J, Jeffries, NO et al. (1999) Brain development during childhood and adolescence: a longitudinal MRI study. Nat Neurosci 2, 861863.
86. de Gier, B, Mpabanzi, L, Vereecken, K et al. (2015) Height, zinc and soil-transmitted helminth infections in schoolchildren: a study in Cuba and Cambodia. Nutrients 7, 30003010.
87. Pee, S (2014) Proposing nutrients and nutrient levels for rice fortification. Ann N Y Acad Sci 1324, 5566.