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Age differences in the impact of nutritional supplementation on growths(¹,²)

DIRK G. SCHROEDER,*³ REYNALDO MARTORELL,* JUAN A. RIVERA,† MARIE T. RUEL‡ AND JEAN-PIERRE HABICHT§

*Department of International Health, the Rollins School of Public Health of Emory University Atlanta, CA 30322, †Centro de Investigaciones en Salud Pública, Instituto Nacional de Salud Pública, 62508 Cuernavaca, Morelos, México, ‡Divison of Nutrition and Health, Institute of Nutrition of Central America and Panama, Guatemala City, Guatemala and §Dioision of Nutritional Sciences, Cornell University, Ithaca, NY 14853-6301

¹ Presented in the symposium on Nutrition, Growth, and Development, FASEB, March 28 to April 1, 1993, New Orleans, Louisiana. 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 Supported by NIH grant HD-22440 and by a grant from the Pew Charitable Trusts.

³ To whom correspondence should be addressed: Department of International Health, The Rollins School of Public Health of Emory University, 1518 Clifton Rd., N.E., Atlanta, Georgia 30322.

Materials and methods
Results
Discussion
Literature cited

Supplementary feeding programs to improve nutritional status in children who are malnourished or at high risk of malnutrition are in wide use in developing countries. The ability of these programs to demonstrate an impact on growth, however, has been inconsistent (Beacon and Ghassemi 1982). This failure has been attributed to the use of inappropriate indicators in measuring impact as well as poor targeting of the intervention (Rivera et al. 1991).

A child's age often is used as a means of targeting interventions because it is a rough measure of nutritional needs, vulnerability (i.e., to infections, inappropriate care, etc.) and growth potential. A more precise understanding of the ages at which infants and children benefit most from nutritional supplementation may aid in the improved effectiveness of such interventions (Beaton 1993).

Very few published analyses have investigated agespecific responsiveness to supplementation (Burger 1992, Gopalan et al.1973, Lutter et al. 1990, Martorell et al. 1980, Rivera et al. 1991). In one of these reports (Gopalan et al. 1973), results were presented by age of the child, but lack of detailed information on supplement intake makes interpretation difficult. The study by Lutter et al. (1990) restricted analyses to children <3 y of age. Using the same dataset employed in the current analysis, Burger (1992) examined the impact of supplement on growth by 3 mo age intervals (e.g., 0-3, 3-6, etc) but restricted the analysis to chil dren <2 y of age. Examination of older children is of interest because a large number of on-going programs target children <5 y of age. The paper by Rivera et al. (1991) analyzed the same data set used in the current study, but focused on the impact of supplementation on the recovery from wasting (i.e., low weight-for-height).

An analysis with similar objectives to the current paper based on the same study was published previously but used only a subset of cases (Martorell and Klein 1980). Additional covariates, such as a well-constructed proxy for socioeconomic status, are now available. The current analysis will examine the research question using a variety of approaches not employed in the previous work.

The objective of the current paper is to examine the age-specific impact of nutritional supplementation on length and weight during the first 7 y of life.

Materials and methods

Study population and research design. The data for these analyses are derived from a supplementation trial conducted in Eastern Guatemala between 1969 and 1977. The overall objective of the study was to test the impact of food supplementation on physical growth and mental development in young children. Details of the study design, sample, and methods have been published elsewhere (Martorell et al. 1995a).

Briefly, four rural villages of similar ethnicity and development were randomized to receive either a high energy, high-protein gruel-like beverage (Atole) or a low-energy, no-protein drink (Fresco). Atole contained 163 kcal (682 kJ) and 11.5 g of protein per cup (180 mL) whereas Fresco contained only 59 kcal (247 kJ) per cup. Both supplements were fortified with vitamins and minerals in equal amounts (Martorell et al. 1995a).

Supplements were offered ad libitum in the morning and afternoon at fixed locales in each village on a daily basis. Consumption by pregnant and lactating mothers and children <7 y of age was recorded to the nearest 10 mL. Before 3 mo of age, infants consumed very little supplement; median intakes were about 2 kcal/d for Atole and Fresco children combined. Thereafter, consumption of the supplements in terms of volume was greater for children in the Atole villages until 4 y of age, but greater for children in the Fresco communities between 5 and 7 y of age (Schroeder et al. 1992). With Atole containing three times the energy of Fresco, however, children in the Atole villages consumed greater amounts of energy at all ages.

In addition to the supplementation, all participants were offered free obstetric and medical care, including free medication and vaccination services.

Children were weighed and measured at birth, 15 d of life, and within ±7 days of age 3, 6, 9, 12, 15, 18, 21, 24, 30, 36, 42, 48, 60, 72 and 84 mot Weights (to the nearest 10 g) were obtained using a beam scale with children dressed in a light shift, the weight of which was later subtracted. Supine lengths were measured to the nearest 0.1 cm using a standard treasuring table; no standing heights were taken on children. The reliability between measurements was 95% for weight and 99% for length (Habicht et al. 1979).

Twenty-four-hour dietary recalls were conducted every 3 mo between 15 and 36 mo of age and at 42, 48 and 60 mo of age. Unfortunately, few 24-h recalls were done in children <15 mo of age so good information on home diet during the early weaning period is unavailable. An ethnographic study in the four villages found that the foods most frequently consumed by children 3-60 mo of age were: maize (corn) tortilla, black beans, bean soup, bread and coffee; milk products were consumed very rarely (Mejía-Pivaral 1972). Initiation of breastfeeding in these communities was nearly universal with a mean duration of any breastfeeding of ~18 mo (Burger 1992).

Morbidity data were collected during biweekly home visits during which caretakers were asked about their child's illnesses during the previous two weeks. Socioeconomic information such as the physical conditions of the household and parents' schooling was collected during a census conducted between 1974-1975.

Analytic approach. Growth, supplement, illness and home diet data were summarized over ages 3-12 mo and nonoverlapping, yearly intervals thereafter until 84 mot Very little supplement was consumed before 3 mo of age (Burger 1992) so this period was not included in these analyses. Data for the first interval (3-12 mo) were converted to yearly figures for comparability with the other intervals. Only children who were present in the village for the complete interval were included in the analyses of that interval. Because of the longitudinal nature of the study, children may be represented in more than one interval.

Supplement intake data were analyzed in two forms, first as average kilocalories of supplement ingested per day over the interval. Analyses using this variable may be interpreted as defining the potential impact of a certain amount of supplement on growth regardless of age-related variations of recommended dietary intakes and of growth.

In addition, the percent of the recommended dietary allowances that the supplement represented was calculated. Recommended dietary allowances per kilogram body weight for the interval were based on published values (National Research Council 1989). Because children gained weight at less than the expected rate, RDAs calculated from actual weights may underestimate needs if these children have the potential for growth similar to the reference. RDAs therefore also were calculated using expected weights as indicated by the NCHS/WHO reference (World Health Organization 1983). The argument against using expected weights is that as the children age, they deviate further from the growth reference and are less and less likely to consume at the expected levels (Burger 1992) Using both approaches gives an envelope within which lies the correct RDA for these children.

Growth data are analyzed in a variety of forms. Raw weight and length increments were calculated by subtracting the value at the beginning of the interval from that at the end. The percent of median of an internal growth reference that this increment represented also was calculated by dividing the child's weight or length velocity by the median value for the entire sample as was done by Lutter et al. (1990). In addition, percent of median of an external growth velocity reference was calculated using actual growth velocities based on the Fels data set as presented by Baumgartner et al. (1986)

Multivariate regression techniques were used to estimate the impact of supplement intake on growth increment after controlling for potential confounding factors. Parameter estimates of the variables of interest were calculated as follows, impact of: 100 kcal (418 kJ) supplement/day or 10% of RDA from supplement on raw growth increment (in millimeters length or grams weight) or percent of median expected growth

Covariates considered for inclusion in each of the models were: body size, percent of days with diarrhea: illness, socioeconomic status and sex. Home diet (an ergy) was controlled for during all intervals except the first (e.g., 3-12 mo) and last (e.g., 72-84 mo) for which it was not available.

To control for the possibility that larger children would consume supplement or grow differently from smaller children, body size (length or weight) at the measurement period immediately before the start of the interval was included as a covariate. For example for the age interval 12-24 mo, length (or weight) at 5 mo was included in the model. This approach was necessary because body size at the beginning of the interval (e.g.,12 mo) was used to create the dependent variable (i.e., the growth increment); the errors be tween these two variables are thus correlated and the use of both in one model may bias results (Plewis 1985). High correlations between subsequent measurements, >0.90 and >0.80 for most consecutive length and weight measures respectively, further justified this approach.

Though the use of difference scores as dependent variables has been criticized (Bohrnstedt 1969), in eluding a measure of body size before the beginning of the interval avoids the problem of correlated errors, the primary criticism of this approach. An alternate approach that uses the residuals of the late age given the earlier (Bohrnstedt 1969) was used in the previous analysis of these data (Martorell and Klein 1980), but provides less interpretable results (Dalecki and Willits 1991).

Percent of time with diarrhea! illness was calculated by dividing the number of days with diarrhea during the interval by the number of days at risk. For the home diet variable, if more than one 24-h recall was available during the interval, these were averaged. Because 24-h recalls were only done between ages 15 and 60 mo, home diet was not controlled for in the regressions for the age intervals 3-12 and 72-84. A summary socioeconomic status (SES) variable was created using principal components analysis and is based on housing quality and possession variables (Rivera et al. 1995); the variable was standardized with mean = 0 and SD = 1. Sex was included as a covariate because growth rates are slightly different for males versus females. Interactions between the above covariates and the independent supplement variables were tested to determine if the impact of supplement varied at different levels of the covariate; interactions were considered significant at P<0.10.

An indicator variable for supplement type (i.e., Atole or Fresco) was not included in analyses which pool all villages because of the high correlation between this variable and amount of energy from supplement ingested. In analyses not presented, interactions between supplement type and amount of energy from supplement that might indicate that the impact of energy from Atole differed from that from Fresco were not found to be significant.

All analyses were conducted using the PC-SAS statistical package version 6.04.

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