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Nutritional supplementation during the preschool years influences body size and composition of Guatemalan adolescents(¹,²)


*Centro de Inuestigaciones en Salud Públics, Instituto Nacional de Salud Pública, 62508 Cuernacaca, Morelos, Mexico, †Department of International Health, The Rollins School of Public Health of Emory University, Atlanta, CA 30322, ‡Division of Nutrition and Health, Instituto de Nutritión de Centro America y Panama, Guatemala City, Guatemala, and §Division of Nutritional Sciences Cornell University, Ithaca, NY 14853-6301

¹ Presented in the symposium on Nutrition in Early Childhood and its long-term Functional Significance, FASEB, April 6, 1992, Anaheim, CA. Published as a supplement to The Journal of Nutrition. Guest editors for this supplemental publication were Reynaldo Martorell, The Rollins School of Public Health of Emory University, Atlanta, GA, and Nevin Scrimshaw, The United Nations University, Boston, MA.

² Data analyses were supported by NIH Grant HD22440 and by grant 9202716-000 from the Pew C heritable Trusts.

³ To whom correspondence should be addressed: Centro de Investigaciones en Salud Pública, Instituto Nacional de Salud Pública, 62508 Cuernavaca, Morelos, Mexico.

Materials and methods
Literature cited


ABSTRACT Effects of supplementary feeding during early childhood on body size and composition at adolescence are examined in a population with marked growth failure in the first 3 y of life. The data came from a supplementation trial conducted in rural Guatemala from 1969 to 1977 and a 1988-89 follow-up study of the same subjects at adolescence. Two pairs of villages participated in the trial. One village from each pair received a high protein-energy supplement (Atole), which significantly improved dietary intakes, whereas the other village of the pair received a low-energy, no-protein supplement (Fresco), which did not impact appreciably on dietary intakes. Children from Atole villages grew better during the preschool period than children from Fresco villages. At adolescence, subjects from Atole villages were taller, weighed more and had greater fat-free masses than subjects from Fresco villages. Differences in height at adolescence were slightly reduced in magnitude relative to differences at 3 y of age. However, differences in weight were increased in adolescence relative to 3 y of age. J. Nutr. 125: 1068S-1077S,1995.


• growth
• height
• adolescence
• rural Guatemala

In a review of controlled supplementation trials, clear effects of supplementary feeding on growth were found in populations with evidence of growth retardation when the dietary intakes of young children were truly improved (Habicht and Butz 1979, Rivera 1988). On the other hand, the long-term effects of community-based supplementation programs during early childhood on the growth and body composition at adolescence or adulthood have not been studied.

This article examines effects of supplementary feeding during early childhood on body size and composition at adolescence in a population where effects of supplementation on growth rates were observed during the first 3 y of life but not from 3 to 7 y of age Martorell et al. 1982, Schroeder et al. 1995). It remains to be shown whether these improvements in growth persist into adolescence.

Tanner (1986) has described human growth as a target-seeking function. In his view, children have their own natural growth trajectories; when deviations occur, restoring forces develop to return children to their original growth curves. Growth after 3 y of age in rural Guatemala is not significantly constrained (Martorell et al. 1995b) and thus, it may be possible for the differences in size in favor of supplemented children observed at 3 y of age to be reduced through faster growth subsequently in nonsupplemented children. In addition, nonsupplemented children may have a greater potential for growth than supplemented children because of delayed maturation. Martorell et al. (1979) found that nonsupplemented children were less mature at 3 y of age than supplemented children in this population. Less mature children, in turn, may have a more prolonged subsequent growth period that could compensate for some of the growth failure incurred in early childhood.

The hypothesis tested in the present study is that effects of supplementation on growth at 3 y of age persist into adolescence and that differences in attained growth at: adolescence between supplemented and nonsupplemented groups are of similar magnitude as observed at 3 y of age. The data used in the analysis were collected during a supplementation trial of rural Guatemalan children conducted from 1969 to 1977 and from a follow-up study of the same subjects at adolescence. Results are presented for length and weight at 3 y of age and for height, weight and fat free mass (FFM) at adolescence and young adulthood.

Materials and methods

Design and sample

Design of the supplementation trial (1969-1977). A controlled supplementation trial was conducted in rural Guatemala between 1969 and 1977 by the Institute of Nutrition of Central America and Panama (INCAP). Detailed descriptions of the sample, methods, and quality control have been published elsewhere (Martorell et al. 1995a). A brief summary of the intervention follows.

Four rural Ladino (i.e., Spanish speaking, mixed Spanish-Indian ancestry) villages located in eastern Guatemala were selected for the study. The villages were selected to be as similar as possible in nutrition, health and demographic characteristics. Two villages were randomly allocated to receive a high-protein (11.5 g per 180 mL or 1 cup serving), high-energy (682 kJ/163 kcal per 180 mL) drink called Atole. The remaining two villages were assigned to receive a low-energy (247 kJ/59 kcal per 180 mL), nonprotein supplement called Fresco. The two drinks contained similar concentrations of vitamins and minerals. A preventive and curative health program was offered in all four villages. The supplements were distributed centrally in supplementary feeding centers and were available daily, on a voluntary basis, to all members of the community. Subjects were free to consume as much as desired and the amounts ingested by children 0-7 y were measured and recorded at each session to the nearest 10 mL.

Design of the follow-up study (1988-89). A follow-up study of the children who participated in the supplementation trial was conducted between 1988 and 1989. At this time, the subjects were between 11 and 27 y of age, of which 2169 were known or believed to be alive. Of these, 1574 (73%) were studied at follow-up (Martorell et al. 1995a).

Sample. The sample for the current analyses consists of 460 children (245 males and 215 females) who were exposed to supplementary feeding in the study villages from birth to 3 y of age (born between March 1969 and February 1974), had anthropometric measurements at 3 y of age (±7 d) and had anthropometric measurements at follow-up, when they were between 14 and 20 y of age (for convenience, this range in age is referred to hereafter as adolescence).

Data utilized

Data from the supplementation trial. Anthropometric measurements at 36 mo, home diet, duration of breastfeeding, diarrhea, maternal height, maternal education and socioeconomic status were used in the present analyses.

Anthropometric measurements at 36 mo. Weight, measured to the nearest 0.01 kg, using a beam balance scale, and recumbent length, measured to the nearest millimeter on a standard measuring table were used in the analyses.

Home diet. Energy intake from the home diet (excluding breastfeeding) was estimated by the 24-h recall method using surveys every 3 mo between 15 and 36 mo of age. The average daily energy intake (kilocalories/day) from the diet between 15 and 36 mo was obtained using all the recalls available during that period. The average was used in the analyses.

Diarrhea. Information about the occurrence and duration of diarrhea, as defined by the mother, was collected every two weeks during home visits. The percentage of time with diarrhea between 0 and 36 mo of age was used in the analyses. This variable was derived by dividing the number of days with diarrhea by the number of days for which information about morbidity was available, multiplied by 100.

Maternal height. Maternal height was measured every 3 mo during pregnancy and lactation starting in 1971. The median value of the repeated measures was used in the analyses.

Socioeconomic status. A socioeconomic score (SES) was generated from factor analysis using information about living conditions of the family in 1975. After initial testing, the model was restricted to one factor. Only variables with factor loadings ³0.5 were retained. These were house characteristics (type of floor, an overall assessment of the quality of the house construction, type of excrete disposal, the location of the kitchen and facilities for cooking) and possession of household items (radio, TV, record player, bicycle, motorcycle, car, sewing machine and refrigerator). The variance explained by this model was 46%. Standardized factor scores were used in the analyses.

Data from the follow-up study. Anthropometric measurements and maturation were used in the analyses.

Anthropometric measurements. A battery of anthropometric measurements were obtained on the sample (Martorell et al. 1995a). Only height, weight and estimated FFM were used as outcomes in the present analyses. Sex-specific prediction equations for FFM were developed in an urban group specifically selected to match the subjects of the follow-up study on age, anthropometric measurements and ethnic origin. The prediction equation for males included weight, bicristal diameter and arm-fat area as independent variables; the equation for females included weight, height, and waist circumference (Conlisk et al. 1992).

Maturation. The methods of assessing maturation in this study are given by Pickett et al. (1995). Lefthandwrist X-rays of adolescents up to the age of 18 y, excluding pregnant women, were obtained by field workers who were trained by a radiologist. X-rays in older subjects were not obtained because the probability of finding anyone who had not reached skeletal maturity was very small. All X-rays were read and graded by a single person using the TW-2 (RUS) method (Tanner et al. 1983) in which skeletal maturity is assigned the value of 18.0 y in males and 16.0 y in females. The variable "maturation", which was used in the analyses, was given the hand-wrist X-ray rating value (bone age) if chronological age was <17.9 in males. All males ³18 y were given a value of 18.0 for maturation. In females, bone age was used if chronological age was <15.9 y. Between chronological ages 16.0 and 17.9, bone age was used if skeletal maturity had not occurred, while 16.0 was assigned when skeletal maturity had occurred. All females ³18 y were given a value of 16.0 for maturation. Haas et al. (1995) also use this variable as a covariate but refer to it as skeletal age (SA). A nonlinear association between maturation and growth at adolescence was found in males; therefore, a quadratic term was used in the models for males.

Conceptual Model

The variables included in the regression models were based on a conceptual model of the determinants of growth. From evidence in the literature and from previous analyses of the data, the direct determinants of growth during the first 3 y of age are dietary intake (Habicht and Butz 1979) and morbidity, particularly diarrhea (River and Martorell 1988). Two variables representing dietary intake initially were considered: breastfeeding duration and home energy intake. However, breastfeeding duration was dropped from the analyses because of the large number of missing values. Previous analyses in this population showed that maternal height was an important determinant of children's growth. It is probably an indicator of both the genetic potential for growth and of the socioeconomic condition of the family. Maturation was included in all models for adolescents. Socioeconomic status of the family and maternal education were selected for analysis but the latter was dropped because of high rates of missing values. Socioeconomic status operates through dietary intake and morbidity. Because dietary intake and diarrhea, which are direct determinants of growth, were included in the model, incorporation of socioeconomic status may be redundant and should therefore be justified. One important reason for including the three variables in the model is that measures of dietary intake are imprecise (the reliability of the 24-h dietary recall method is low and breast-milk intake was not measured). Also, diarrhea was the only indicator of morbidity used. Therefore, socioeconomic status may capture some of the variability in growth that would be lost because of imperfect measurement of dietary intake and morbidity.

Analysis methodology

Full rather than reduced models (i.e., models in which only those variables found to be statistically significant are retained) were used to decrease biases in the regression coefficients as a result of omitting relevant variables (Johnston 1984). The precision of estimation of the full models was very similar to that observed in the reduced models.

Unadjusted differences in attained growth between supplement groups (Atole and Fresco) were analyzed by test. Analysis of variance (ANOVA) and ordinary least squares (OLS) regression analysis were used to control for potential confounding variables and to compute adjusted means. The conceptual model described above guided the choice of variables. The outcome variables analyzed were: length (centimeters) and weight kilograms) at 3 y of age and height (centimeters), weight (kilograms) and FFM (kilograms) at adolescence. The independent variables included: supplement type (Atole = 1; Fresco = 0), maternal height (centimeters), percent of time with diarrhea between 0 and 3 y of age, SES and home diet (kilocalories). The variable "home diet" was dichotomized using the sex-specific median: diet was considered low (0) if the energy intake from the diet was lower than the median and high (1) if the energy intake was greater than or at the median. The reasons for dichotomizing were that the relationship between energy intake and attained growth is not linear and because of imprecision in the measurement of home diet (Habicht et al. 1995). Maturation was included in all adolescent models. Also included in some adolescent models were anthropometric measurements at 3 y of age and height at adolescence. The former was used to test if differences in attained growth at adolescence were totally explained by differences at 3 y; the latter was used to test if effects on FFM and weight at adolescence were independent of effects on height.

The analytical approach consisted of: testing the effect of supplementation on length, weight and weight adjusting for length, at 3 y of age; testing the long-term effect of supplementation on height, weight and FFM at adolescence and on weight and FFM adjusting for height:; and testing the effect of supplementation on weight and height at adolescence, controlling for anthropometric measurements at 3 y of age. These last models tested whether the effect of supplementation on adolescents' outcomes still remained when anthropometric measurements at 3 y of age were included in the model.

Data for males and females were analyzed separately, mainly because of differences in patterns of maturation. In females maturation was related linearly to height at adolescence whereas in males the relationship was quadratic.

Atole versus Fresco differences were considered statistically significant at an alpha level <0.05, using two tailed tests in descriptive analyses. Statistical power was inadequate to analyze these data according to the intervention design, which would require the unit of analysis to be the village and not the individual (see Habicht et al. 1995 for the application of this approach to size at 3 y of age). However, the important inferences about the long-term effects of supplementation depend more on major changes in the absolute differences in size between Atole and Fresco subjects than on shifts in statistical significance.

All analyses were done using the SAS version 6.04 for microcomputers.

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