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3 Program in International and Community Nutrition and Department of Nutrition, University of California, Davis, CA 95616; 4 Instituto de Investigación Nutricional, La Molina, Lima, Perú; and 5 USDA-Agricultural Research Service, Western Human Nutrition Research Center, Davis, CA 95616
* To whom correspondence should be addressed. E-mail: khbrown{at}ucdavis.edu.
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ABSTRACT |
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 TOP ABSTRACT IntroductionMethodsResultsDiscussionLITERATURE CITED |
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Introduction |
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TOPABSTRACTIntroductionMethodsResultsDiscussionLITERATURE CITED |
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An estimated 42% of the population of Peru is at risk of inadequate zinc intake, based on estimates of per capita absorbable zinc in the national food supply (9). The prevalence of stunting, defined as length-for-age Z-score (LAZ) < –2 SD with respect to international reference data, among children < 5 y in Peru is 25% (10). A study of 313 infants aged 6–12 mo in peri-urban communities on the north coast of Peru revealed that 
40% of infants had low plasma zinc concentrations (<9.9 µmol/L) (11). Based on this information, there is reason to think that young Peruvian children are at risk of zinc deficiency.
The objectives of this study were to examine the effects of zinc supplementation or zinc fortification of a complementary food on growth, morbidity, dietary intake, appetite, body composition, and hormonal regulators of energy balance among young Peruvian children at risk of stunting. The effects of the interventions on the children's growth, morbidity, and plasma zinc concentrations have been reported previously (12). Briefly, there were no significant effects on anthropometric or morbidity outcomes, and plasma zinc concentration increased significantly only in the zinc supplement group compared with the control group. This article presents the results of the following outcomes: 1) dietary energy intake; 2) reported appetite; and 3) body composition. We hypothesized that children receiving additional zinc, either via a liquid supplement or fortified complementary food, would have a greater increase in energy intake, lower prevalence of poor appetite, and greater increase in FFM than children not receiving additional zinc.
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Methods |
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TOPABSTRACTIntroductionMethodsResultsDiscussionLITERATURE CITED |
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600,000, which is located on the Pacific coast 400 km north of Lima. Children 5–7 mo old were identified during a census and invited to attend screening examinations at local community health centers. Informed consent was obtained from the caregivers to measure the children's weight, length, and hemoglobin concentration. Children were selected if they met the following inclusion criteria: LAZ < –0.5, weight-for-length Z-score > –3, hemoglobin > 80 g/L, no congenital or chronic conditions affecting growth, no use of infant formula (providing >1 mg zinc/d, 
5 times per week), no twin enrolled in the study, and planning to live in the study community during the next 7 mo. A project supervisor visited the home of eligible children whose families were interested in participating in the intervention trial within 2 d of the screening exam to explain the study procedures, review the consent form, and obtain written, informed consent. The protocol was approved by the Institutional Review Boards of the Instituto de Investigación Nutricional, Lima, Perú and the University of California, Davis.
Interventions.
Children were randomly assigned to 1 of 3 groups: 1) iron-fortified, wheat-based porridge without added zinc, and liquid multivitamin supplement with zinc (ZnSuppl); 2) the same porridge with added zinc and the liquid multivitamin supplement without zinc (ZnFort); or 3) both the porridge and the liquid multivitamin supplement without zinc (control). The porridge fed to children in all groups was prepared primarily from wheat flour that was fortified with ferrous sulfate to provide 30 mg iron/kg flour dry weight. The porridge fed to children in the ZnFort group was also fortified with zinc sulfate (150 mg Zn/kg dry weight) to provide an additional 3 mg/d of zinc, assuming an average porridge consumption of 20 g/d dry weight, as was observed in a previous study in Peru (13). In addition to wheat flour, the porridge contained milk powder, palm oil, sugar, soy protein, and vanilla flavoring, with an energy content of 400 kcal/100 g (1675 kJ/100 g) dry weight. The liquid multivitamin supplement was made from a commercially available, fruit-flavored children's supplement (Supradyn, Productos Roche) diluted with distilled water. The liquid supplement with added zinc (zinc sulfate) provided 3 mg of zinc per daily dose. The daily dose of supplement (with or without added zinc) contained the following vitamin amounts: vitamin A (225 µg retinol equivalents), thiamin (0.5 mg), riboflavin (0.38 mg), pantothenic acid (2.5 mg), vitamin B-6 (0.5 mg), vitamin C (20 mg), ergocalciferol (5.6 µg), 
-tocopherol acetate (3.8 mg), biotin (50 µg), and niacin (3.8 mg). Details of the distribution and compliance monitoring have been reported previously (12).
Dietary assessment. Dietary intakes were assessed by direct observation in the children's homes, using 12-h weighed food records and recall of any foods consumed during the previous 12-h period. One or 2 d of dietary information were obtained both prior to the intervention and 2–3 mo after the start of the intervention. During the 12-h observation period, all food items, recipe ingredients, prepared recipes, and beverages (including water) served to the child and any uneaten portions were weighed using electronic balances with 1-g precision (MyWeigh6000, MyWeigh). Foods consumed were converted to nutrients using the Peruvian Food Composition database (14). Additional sources of nutrient data included food labels, the USDA database (15), the International Minilist (16), and the Nutrient Data System for Research (17).
Breast milk intake was estimated by the test-weighing procedure. Children were weighed using an electronic infant balance with 5-g precision (Seca Baby Scale Model 231) before and after each feeding during 12 h of observation. The 12-h intake of breast milk was calculated by summing the differences in body weights of each feeding episode and correcting for insensible losses, as described previously (18). The mean insensible loss of all subjects (0.0352 g·kg–1·min–1) was used to estimate the weight of insensible losses for each child during the feeding episode and the calculated insensible loss was added to the 12-h intakes. The corrected 12-h intakes were used to estimate breast milk intake over a 24-h period using a regression equation developed in a previous study of Peruvian infants (19): 24-h intake (g) = [1.36 x 12-h intake (g)] + 177.
Reported appetite. For morbidity assessments, field workers visited the subjects' homes 2–3 d/wk and inquired about symptoms of illness. Caregivers were asked if the child's appetite was: 1) usual; 2) somewhat diminished; or 3) very diminished on that day and each day since the previous visit. The percentage of days with diminished appetite was calculated dividing the number of days with reported appetite "somewhat diminished" or "very diminished" by the number of days of assessment for each child. Data on appetite were collected for 1 mo prior to the start of the intervention to obtain baseline information and for the 6-mo duration of the intervention period.
Anthropometry. Anthropometric assessments were completed at baseline and 3 and 6 mo. Weight was measured using an infant balance with 15-g precision (Seca Model 345) and recumbent length was measured to 0.01 cm using a digital infantometer (447 Infantronic Digital Infantometer, Quickmedical). The same person performed all measurements. MUAC was measured to the nearest 0.1 cm using a flexible, nonstretch tape on the right arm at baseline and 6 mo among the subgroup of children in the body composition study. Anthropometric Z-scores for weight and length were calculated using EpiInfo software (version 3) with CDC 2000 reference data (20). MUAC Z-scores were based on WHO 1997 reference data (21).
Body composition. Body composition was assessed in a subset of children at baseline and 6 mo using deuterium dilution. We determined the children participating in the body composition studies according to geographic area prior to enrollment. A baseline urine sample of at least 10 mL was obtained in a disposable urine collection bag. A preweighed 0.8-g dose of deuterium oxide tracer (2H2O) was transferred quantitatively from a vial to a syringe and administered orally. Two hours after administering the dose, a new urine collection bag was placed on the children and the next urine sample was discarded to avoid collection of a nonequilibrated sample. A 3rd urine collection bag was then placed on the children and this sample was saved for analysis. The average length of time from dosing to the sample collected for analysis was 3.6 ± 0.9 h (2.3–9.1 h range). The children were allowed to breast-feed during this time and the amount of breast milk consumed was measured by test-weighing, as described above. Consumption of other fluids, such as water and juice, was also allowed and these were weighed before and after consumption using a portable balance with 0.1-g precision (MyWeigh MX200).
Urine samples were processed at the USDA Western Human Nutrition Research Center in Davis, CA. The samples were vacuum distilled to obtain pure water and 2H2O concentrations were measured in duplicate by infrared spectrometry (Miran-IFF, Foxboro). The 2H2O concentration of the baseline predose urine was subtracted from the 2H2O concentration of the final postdose urine to obtain 2H2O enrichment. Total body water (TBW) was calculated using the following formula:
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Corrections were made for the molecular weight of 2H2O relative to water (900), the nonaqueous hydrogen exchange (0.96) (22), and the estimated fractionation of the isotope (0.944) (23). Water intake consumed during the equilibration period was subtracted (water used to rinse the 2H2O vial and water from breast milk and other foods or fluids). FFM was calculated by dividing TBW by the proportion of water in FFM, as obtained from age- and sex-specific reference data (24). Fat mass (FM) was calculated by difference, and the percentage of body weight as FM was calculated (percent FM). Fifty percent of urine samples were reanalyzed and the average 2H2O concentrations were used, except for 1 sample for which the reanalyzed sample was used, because the original value for FM was implausible (negative). The average CV between the original and reanalyzed samples for deuterium enrichment (postdose minus predose deuterium concentration) was ± 5.2%.
Sample sizes.
For the outcome of change in energy intake, we estimated a sample size of 93 per group as sufficient to detect an effect size 0.5 SD, corresponding to 100 kcal/d according to a previous study in Peruvian infants (25), with a probability of type-I error of 0.05 and a power of 80%, accounting for 15% attrition. For the outcome of change in FFM, a sample size of 47 per group was predicted to be sufficient to detect an effect size 0.7 SD, corresponding to 0.4 kg, as observed in 1 previous study of zinc supplementation in infants (26).
Statistical analysis. A dietitian (J. E. Arsenault) checked dietary data forms on-site for accuracy of coding and calculations and consistency among data collectors. Any errors were corrected prior to computer entry. The data files were then reviewed to verify that all food items were entered and weights were accurate. Statistical analyses were performed using SAS (version 8.0, SAS Institute). We used ANOVA to assess baseline group-wise differences. Post hoc tests included Tukey's test and Kruskal-Wallis test (for variables that were not normally distributed). For proportions, group-wise comparisons were made using chi-square analysis. To evaluate changes over time in energy intake and body composition measures, irrespective of group assignment, repeated measures ANOVA (PROC MIXED) was used. Group means for changes in energy intake and body composition variables were compared by using ANCOVA with the following covariates: the baseline value of the respective outcome variable, age, sex, and initial body weight. The energy intake model also included as a covariate the number of days between diet studies. For the model with prevalence of diminished appetite as the dependent variable, diminished appetite during the 30-d preintervention period was also included as a covariate. In addition, we tested interactions of variables representing baseline stunting and dietary zinc intake with treatment group for significance. Differences were considered significant at P < 0.05. Values in the text are means ± SD. The proportion of children with zinc intakes less than the recommended amounts was estimated using the estimated average requirement (EAR) cut-point method (27).
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Results |
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TOPABSTRACTIntroductionMethodsResultsDiscussionLITERATURE CITED |
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1–3 wk before randomization to treatment group and the age of the children at the time of the first diet study was 6.9 ± 0.9 mo. Nearly all of the children (95%) were breast-feeding and 6% were exclusively breast-feeding. The children subsequently assigned to the zinc supplement group had 10–13% greater mean initial total daily energy intake than the other 2 groups (P < 0.01). Overall, total energy intakes were 91% of estimated requirements for age and 98% of requirements per kilogram body weight (28,29). Major sources of energy at baseline were: breast milk (68% of total energy intake), cow's milk (11%), grains (7%), meat (beef, organs, poultry, or fish) (3%), and vegetables (3%). The majority of children (91%) had daily zinc intakes less than the IZiNCG EAR of 3 mg/d at baseline (9). Overall, 80% of total zinc intake at baseline was from animal sources, namely breast milk (33% of total zinc intake), cow's milk (28%), and meat (21%). The mean phytate:zinc molar ratio was 3. Change in energy intake. Overall, mean total energy intake increased from 561 to 641 kcal/d (2347 to 2682 kJ/d) from baseline to the 3-mo follow-up assessment (P < 0.0001). Energy intake from breast milk decreased from 380 to 316 kcal/d (1590 to 1322 kJ/d) (P < 0.0001) and non-breast milk energy intake increased from 180 to 325 kcal/d (753 to 1360 kJ/d) (P < 0.0001). The mean number of days between diet studies was not different among study groups. Nevertheless, the number of days was included as a covariate in all models of dietary changes, because the time interval ranged from 49 to 125 d. The group with the highest baseline energy intake had the lowest increase in intake at follow-up and vice versa; and, after controlling for baseline energy intakes, groups did not differ in the changes in total energy intake, breast milk, or non-breast milk energy intake (Table 2). Major sources of energy intake at follow-up were: breast milk (49%), grains (26%), cow's milk (8%), vegetables (4%), and meat (4%). The high intake of grains is attributed to consumption of the wheat-based porridge (supplied by the project), which contributed 15% of the total energy intakes.
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Body composition.
Overall, mean TBW increased from 3.97 to 4.74 kg and FFM increased from 4.95 to 6.00 kg during the 6-mo study period (P < 0.0001). FM increased from 2.66 to 2.93 kg (P < 0.0001) and percent FM decreased from 34.7 to 32.6% (P = 0.0002). TBW, FFM, FM, and percent FM did not differ among groups at baseline and there were no significant main effects of treatment group on the change in any of these variables from baseline to 6 mo (Table 3). However, there were 2 significant group-wise interactions in the model predicting the change in FFM, one with an indicator variable for low initial LAZ using a cutoff at the median value of –1.1 (P = 0.01) and another with the percentage of dietary zinc from animal sources (P = 0.02) (Table 4). Specifically, among children with initial LAZ < –1.1, the ZnSuppl group had a greater increase in FFM (1.36 kg) than the ZnFort group (0.95 kg; P = 0.02) or the control group (0.95 kg; P = 0.04) (Fig. 2). There were no significant group-wise differences among children with an initial LAZ –1.1. For the interaction of treatment group and percent zinc from animal sources, the slope for the ZnSuppl group was negative and differed from the slope of 0 for the control group (P = 0.01). In other words, children at the low end of the distribution of percent animal source zinc had greater increase in FFM if they were in the ZnSuppl group than if they were in the control group.
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Discussion |
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TOPABSTRACTIntroductionMethodsResultsDiscussionLITERATURE CITED |
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Although we did not find an overall effect of supplemental zinc on FFM accrual, 2 other studies, both conducted in children with a high risk of zinc deficiency, have reported an association between zinc supplementation and increased TBW (26,30). In young Jamaican children recovering from malnutrition, Golden et al. (30) found that the increase in the children's TBW during hospitalization, as assessed by tritium dilution, was positively related to the concentration of supplemental zinc in the soy-based rehabilitation formula. Likewise, in a study of preterm Chilean infants, Diaz-Gomez et al. (26) found that infants who were fed a zinc-fortified formula (10 mg zinc/L) had greater TBW, as assessed by bioelectrical impedance, after 3 and 6 mo compared with infants who received the usual formula (5 mg zinc/L). These study populations, malnourished or preterm infants, were perhaps more likely to respond to zinc supplementation than those in our study population due to an increased physiological need for zinc.
The overall increase of 1 kg FFM among the study children during this period of infancy was somewhat less than reported in a study of U.S. children who gained 1.7 kg FFM from 6 to 12 mo of age (24). Additionally, the percent FM of the Peruvian children (33–35%) was greater at both time points than reported in the U.S. children (27–31%). Most of the children in our study were breast-feeding. In the U.S. cohort, breast-fed children had higher FM at 3 mo and 6 mo (boys only) than non-breast-fed children, but not thereafter up to 24 mo of age (31). It is possible that the higher proportion of breast-fed children in our study compared with the U.S. cohort may account for differences in body composition in these 2 study populations. Our results also differ from a previous study of Peruvian children 6–60 mo of age, which reported higher TBW and lower estimates of FM than those in U.S. children (32). A large proportion of the children in that previous study had a high weight-for-height Z-score, which the authors attributed to greater hydration of FFM, not to high FM. They reasoned that the greater hydration of FFM may have been due to prior malnutrition, which has been associated with high extracellular water in fat-free tissue. The children in our study were similar to those in the previous Peruvian study in terms of the distributions of LAZ and weight-for-height Z-scores; however, the different ages of the children may account for some of the differences in body composition between the 2 studies. Protein intakes were adequate for FFM accrual at baseline (Table 1). At the 6-mo follow-up, the overall protein intake was 2.3 ± 0.9 g·kg–1·d–1 and treatment groups did not differ (data not shown).
The children in this study were consuming adequate dietary energy per kilogram body weight at baseline, so it was unlikely that we would be able to detect any impact of additional zinc on their dietary energy intakes. The available sample size and SD would have allowed us to detect treatment group-related differences in energy intakes of 88 kcal/d (368 kJ/d). Despite randomization, energy intakes were greater in the zinc supplementation group at baseline. However, baseline energy intakes were included in the statistical models to control for any treatment group differences at baseline and there were no group-wise differences at follow-up.
We also explored the effect of additional zinc on reported appetite, which may occur directly or may be mediated by reduced illness. Umeta et al. (33) found that stunted Ethiopian infants receiving 10 mg/d supplemental zinc for 6 mo had a lower incidence of reported anorexia than infants receiving placebo. However, the infants receiving zinc also had lower incidence of illnesses, so it is unclear if the reduced appetite in zinc-supplemented children was affected by zinc directly or indirectly through reduced illness. In this study, concurrent illnesses, such as fever or diarrhea, were major factors explaining poor appetite, but zinc did not affect the prevalence of these illnesses.
Despite a large percentage of the study population consuming less than the EAR of zinc, the study population as a whole did not respond functionally to additional zinc. This discrepancy could be due to errors in the estimated requirements or incorrect assumptions about absorption of zinc in children. The children in our study were consuming a high percentage (80%) of dietary zinc from animal sources, which may have resulted in sufficient zinc absorption for growth. However, the interaction between percentage of zinc intake from animal sources and treatment group with respect to FFM accrual suggests that zinc supplementation resulted in greater FFM accrual in those children who were consuming a diet low in animal-source zinc vs. a diet with higher amounts of animal-source zinc. Other baseline dietary factors were examined and variables representing high intake of nonanimal source complementary foods, such as grains and vegetables, were also associated with greater increases in FFM if these children were also receiving the zinc supplement (data not shown). Although these analyses are exploratory, this could imply that children who were not absorbing sufficient zinc from their diet benefited from the zinc supplement.
In conclusion, we found that the provision of 3 mg additional zinc daily to Peruvian children did not affect their energy intake or appetite, regardless of the zinc delivery platform. Although FFM accrual did not differ by treatment group when all children were considered, among the subset of children who were mild-to-moderately stunted initially (< –1.1 LAZ), zinc supplementation, but not zinc fortification, induced more FFM accrual. The reason for the overall lack of response to zinc supplementation is that these children were not severely zinc deficient, although some degree of zinc deficiency may have accounted for the effect on FFM gain in the children who were more stunted. Notably, this response occurred only when the additional zinc was provided as a supplement. Although provision of additional zinc in a locally produced complementary food is a potentially sustainable method for long-term delivery of zinc in a community setting, we did not find evidence of any functional benefit of the present dose of zinc when delivered in a fortified porridge. More research is needed on the optimal level of zinc fortification to produce improved health outcomes. Ideally, such studies should be conducted in communities with high rates of zinc deficiency, so that any functional benefits of additional zinc will be detectable.
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ACKNOWLEDGMENTS |
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FOOTNOTES |
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2 Author disclosures: J. E. Arsenault, D. López de Romaña, M. E. Penny, M. D. Van Loan, and K. H. Brown, no conflicts of interest.
6 Abbreviations used: EAR, estimated average requirement; FFM, fat-free mass; FM, fat mass; 2H2O, deuterium oxide; LAZ, length-for-age Z-score; MUAC, mid-upper arm circumference; TBW, total body water; ZnFort, zinc-fortification group; ZnSuppl, zinc-supplement group.
Manuscript received 10 August 2007. Initial review completed 10 September 2007. Revision accepted 3 October 2007.
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