In South-East Asia, micronutrient deficiencies remain highly prevalent( Reference Black, Victora and Walker 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( Reference Best, Neufingerl and van Geel 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( Reference Best, Neufingerl and van Geel 2 – Reference Bhatnagar and Taneja 5 ) and reduce school attendance by increasing morbidity( Reference Black 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( Reference Atinmo, Mirmiran and Oyewole 7 , Reference Lockwood and Collier 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( Reference Beard 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( Reference Bhatnagar and Taneja 5 , Reference Shrestha 10 – Reference Eilander, Gera and Sachdev 13 ), with multiple micronutrients appearing to be more efficient than single or double micronutrient interventions( Reference Allen, Peerson and Olney 14 ). However, the overall evidence remains equivocal( Reference Khor and Misra 15 , Reference Best, Neufingerl and Del Rosso 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( Reference Moretti, Zimmermann and Muthayya 17 – Reference Nogueira Arcanjo, Santos and Arcanjo 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( Reference Alavi, Bugusu and Cramer 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.
Intervention
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( Reference Khanh Van, Burja and Thuy Nga 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.
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( Reference Khor and Misra 15 , Reference Greenfield 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( Reference Van de Vijver and Tanzer 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( Reference Isaacs and Oates 31 – Reference Aiken 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( Reference Hughes and Bryan 34 ), namely (ii) block design and (iii) picture completion. RCPM and WISC III tests were previously used in Vietnamese schoolchildren in nutritional intervention trials( Reference Nga, Winichagoon and Dijkhuizen 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( Reference Eilander, Gera and Sachdev 13 ). Block design and RCPM tests are associated with fluid intelligence( Reference DeThorne and Schaefer 36 – Reference Gray, Chabris and Braver 38 ) while picture completion is related to crystallized intelligence( Reference Pennington 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( Reference Cogill 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( Reference de Onis, Onyango and Borghi 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( Reference Cogill 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( Reference Ash, Orihel and Savioli 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( Reference Erhardt, Estes and Pfeiffer 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)( Reference Thurnham, McCabe and Haldar 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.( Reference Thurnham, McCabe and Haldar 44 ). Tissue Fe deficiency was defined as TfR>8·3 mg/l( Reference Erhardt, Estes and Pfeiffer 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.( Reference Cook, Flowers and Skikne 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( Reference Milman 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( Reference de Pee and Dary 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( Reference Thurnham, McCabe and Northrop-Clewes 48 ). Vitamin A deficiency was defined as corrected RBP<0·7 μmol/l( Reference de Pee and Dary 47 ) and marginal vitamin A deficiency as corrected RBP value ≥0·7 and <1·05 μmol/l( Reference Gibson 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( Reference Brown, Rivera and Bhutta 50 ). Severe Zn deficiency was defined as serum Zn concentration <0·5 mg/l( Reference Sazawal, Black and Bhan 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( Reference Pino, Fang and Braverman 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( Reference Kim 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( Reference Perignon, Fiorentino and Kuong 55 ). Inflammation was shown to significantly affect the effect of the FORISCA intervention on micronutrient status( Reference Perignon, Fiorentino and Kuong 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.
Results
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.
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®)
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.
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).
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).
Discussion
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( Reference Hotz, Porcayo and Onofre 20 ), Indian school-aged children( Reference Radhika, Nair and Kumar 18 ) and Thai school-aged children( Reference Pinkaew, Winichagoon and Hurrell 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( Reference Thankachan, Rah and Thomas 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( Reference Golub, Keen and Gershwin 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( Reference Bhatnagar and Taneja 5 , Reference Golub, Keen and Gershwin 59 , Reference Levenson and Morris 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( Reference Bhatnagar and Taneja 5 ) especially reasoning( Reference Black 61 ). For example, Zn supplementation had beneficial effects on cognitive scores of Indian adolescent girls, by reducing reaction time, improving memory and RCPM scores( Reference Kawade 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( Reference Warthon-Medina, Moran and Stammers 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( Reference Olivares, Pizarro and Ruz 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( Reference Murray-Kolb and Beard 65 , Reference Bryan, Osendarp and Hughes 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( Reference Pollitt, Soemantri and Yunis 11 , Reference Bruner, Joffe and Duggan 12 , Reference Lynn and Harland 67 – Reference Soemantri, Pollitt and Kim 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( Reference Perignon, Fiorentino and Kuong 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( Reference Perignon, Fiorentino and Kuong 56 , Reference Fiorentino, Bastard and Sembène 72 – Reference Schulze, Christian and Wu 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)( Reference Perignon, Fiorentino and Kuong 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)( Reference Perignon, Fiorentino and Kuong 56 ) and may have helped to build Fe stores, as was already observed in adolescents supplemented with multiple micronutrients( Reference Angeles-Agdeppa, Schultink and Sastroamidjojo 76 ) or children consuming vitamin A-fortified food( Reference Mejia and Chew 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( Reference Zimmermann, Biebinger and Rohner 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( Reference Zimmermann, Biebinger and Rohner 78 , Reference Cusick, Tielsch and Ramsan 79 ) and in animal models( Reference da Cunha, Siqueira and Trindade 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( Reference Alpert and Fava 81 , Reference Bottiglieri 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( Reference Munoz, Villar and Garcia-Erce 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( Reference Eilander, Gera and Sachdev 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( Reference Pennington 39 , Reference Brown, Brockmole and Gow 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( Reference Isaacs and Oates 31 ), with peaks at 7, 9 and 12 years of age( Reference Bryan, Osendarp and Hughes 66 , Reference Giedd, Blumenthal and Jeffries 85 ). There is some evidence that Fe is a key nutrient in the development of these executive functions( Reference Bryan, Osendarp and Hughes 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( Reference de Gier, Mpabanzi and Vereecken 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( Reference Perignon, Fiorentino and Kuong 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( Reference Pee 87 ).
Conclusion
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
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 ClinicalTrials.gov (identifier: NCT01706419).
