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American Journal of Epidemiology Advance Access originally published online on October 3, 2006
American Journal of Epidemiology 2006 164(12):1160-1170; doi:10.1093/aje/kwj328
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American Journal of Epidemiology Copyright © 2006 by the Johns Hopkins Bloomberg School of Public Health All rights reserved; printed in U.S.A.

ORIGINAL CONTRIBUTIONS

Exposure to a Nutrition Supplementation Intervention in Early Childhood and Risk Factors for Cardiovascular Disease in Adulthood: Evidence from Guatemala

Aryeh D. Stein1, Meng Wang1, Manuel Ramirez-Zea2, Rafael Flores1, Ruben Grajeda2, Paul Melgar2, Usha Ramakrishnan1 and Reynaldo Martorell1

1 Rollins School of Public Health, Emory University, Atlanta, GA
2 Institute of Nutrition of Central America and Panama (INCAP), Guatemala City, Guatemala

Reprint requests to Dr. Aryeh D. Stein, Hubert Department of Global Health, Rollins School of Public Health, Emory University, 1518 Clifton Road NE, Atlanta, GA 30322 (e-mail: Aryeh.Stein{at}emory.edu).

Received for publication November 14, 2005. Accepted for publication May 1, 2006.


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 References
 
To study the role of nutrition in the association of birth size and childhood growth with development of cardiovascular disease, the authors in 2002–2004 surveyed 665 men and 790 women aged 25–42 years who had been exposed as children to a community-randomized nutrition supplementation intervention in four villages in eastern Guatemala. Exposure was associated with a lower fasting glucose level (7.0 mg/dl, 95% confidence interval (CI): 0.5, 13.5) for exposure at ages 36–72 months; lower systolic blood pressure (3.0 mmHg, 95% CI: 0.4, 5.6) for exposure at ages 24–60 months; and a lower triglyceride level (sex-adjusted; 22.2 mg/dl, 95% CI: 0.4, 44.1) and higher high density lipoprotein cholesterol level (males only; 4.7 mg/dl, 95% CI: 1.5, 7.9) for exposure prior to age 36 months. Improved nutrition at any age prior to 7 years was not associated with diastolic blood pressure, total or low density lipoprotein cholesterol level, or prevalence of the metabolic syndrome. Interventions designed to address nutrient deficiencies and ameliorate stunting that are targeted at pregnant women and young children are unlikely to increase cardiovascular disease risk later in life and may instead lower the risk.

cardiovascular diseases; dietary supplements; intervention studies; nutrition

Abbreviations: CI, confidence interval; GEE, generalized estimating equations; INCAP, Institute of Nutrition of Central America and Panama


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 References
 
Adverse circumstances during birth and in early childhood are associated with increased risk of development of a range of chronic diseases and their underlying risk factors (1–4). In this literature, size at birth, usually expressed as birth weight, is taken to represent underlying causal factors in pregnancy. Postnatal growth, particularly growth failure over the first 2–3 years of life followed by above-average increases in weight (but not height), has also been related to the development of later risk for type 2 diabetes (5–7).

Protein and energy supplementation during pregnancy has modest effects on birth weight in nonfamine settings (8, 9). Severe undernutrition in late gestation causes approximately a 300-g decrease in birth weight (10). Food supplementation during the first 3 years of postnatal life improves the growth of chronically undernourished children (11, 12).

Follow-up studies of the Dutch famine of World War II suggest modest adverse effects of late-gestation exposure on glucose metabolism at age 50 years (13) but no association between famine exposure and blood pressure (14). Offspring of women whose diets were assessed late in gestation presented inconsistent patterns of associations of intake of meat, fish, protein, fat, and carbohydrate with blood pressure and glucose/insulin metabolism at age 40 years (15–17). Premature infants randomized to receive expressed breast milk showed an improved lipid profile at ages 13–16 years relative to infants randomized to receive formula (18). Full-term infants randomized to receive low-sodium formula from birth to age 6 months showed lower blood pressures at age 15 years than did infants randomized to receive normal-sodium formula (19).

These studies (which were largely observational) point to periods of sensitivity of the developing infant to its own and its maternal diet but do not address questions of specificity of timing of such exposures. Prospective randomized studies of child nutrition can provide high-quality evidence in this regard. The present analysis was conducted to examine associations between the timing of exposure to an improved nutrition supplement available to pregnant women and young children and the distribution of risk factors for cardiovascular disease in adults currently aged 25–42 years.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 References
 
The INCAP Longitudinal Study
The Institute of Nutrition of Central America and Panama (INCAP) conducted a study of growth and development between 1969 and 1977 in four villages of mixed Spanish-Amerindian descent located 40–110 km east of Guatemala City, Guatemala. As described in detail elsewhere (20), villages were randomized within pairs defined on the basis of population size. Village residents were offered either atole, a dietary supplement made from maize, dry skim milk, and sugar (protein, 6.4 g/100 ml; energy, 3.80 MJ (900 kcal)/liter), or fresco, which contained no protein or fat and provided 1.35 MJ (330 kcal)/liter of energy, all from sugar. Both supplements were fortified with micronutrients in equal concentrations by volume. Supplement was available twice daily in a central location in each village. Supplement intake to the nearest 10 ml was recorded for all pregnant and lactating women and their offspring up to the age of 7 years. Anecdotal evidence suggests little consumption of either supplement by persons outside of these target groups. INCAP established and maintained medical services for each village.

The 2002–2004 follow-up
Between 2002 and 2004, persons studied as children in 1969–1977 were resurveyed (21, 22). Of the 2,393 persons in the 1969–1977 sample, 1,856 (77 percent) were determined to be alive and living in Guatemala, 11 percent had died (the large majority from infectious diseases in early childhood), and 8 percent had migrated abroad; nothing could be learned about the remaining 4 percent. Of the 1,856 persons who were still living in Guatemala, 1,113 lived in their original villages, 154 lived in nearby villages, 419 lived in or near Guatemala City, and 170 lived elsewhere. Of these 1,856 persons, 1,570 (85 percent) completed at least one instrument during the 2002–2004 data collection. Although these persons were known to be living in Guatemala, location information was insufficient to make contact with 202 (11 percent) of them, with most being concentrated among out-migrants from the villages. Overt refusal to participate was uncommon, with only 84 persons (5 percent of the persons contacted) declining to participate. Data collection occurred at INCAP facilities in the study villages, at INCAP headquarters in Guatemala City, or at the respondents' homes. All data collection followed protocols approved by the institutional review boards of Emory University (Atlanta, Georgia) and INCAP, and all participants gave written informed consent.

Measurements
Trained field workers measured weight, height, and waist circumference. Weight was measured using a digital scale (model 1582; Tanita Corporation, Tokyo, Japan) with a precision of 100 g while subjects were dressed in their normal underclothes with no shoes. Height was measured to the nearest 0.1 cm, with the participants standing barefoot with their backs to a stadiometer (GPM Anthropological Instruments, Zurich, Switzerland). Waist circumference was measured to the nearest 0.1 cm at the umbilicus, using a plastic inextensible measuring tape. All measurements were taken twice, and the two values were averaged. If the difference exceeded 0.5 kg for body weight, 1.0 cm for height, or 1.5 cm for waist circumference, a third measurement was taken and the average of the two closest measurements was used.

Physicians obtained all clinical measurements. Blood pressure was measured using a digital sphygmomanometer (OMRON, model UA-767; A & D Medical, Milpitas, California) that was periodically checked for precision and accuracy. Participants were instructed to refrain from use of tobacco products, alcohol, or caffeine in the 30 minutes preceding measurement. Participants sat quietly, with the left arm resting on a flat surface (at the level of the heart), for at least 5 minutes before the first measurement. A standard cuff was used for all subjects. Three measurements were taken at 3- to 5-minute intervals; readings from the second and third measurements were averaged. When the second and third measurements (of either systolic or diastolic pressure) did not coincide within 10 mmHg, a fourth measurement was taken and the two closest readings were averaged. Measurements obtained using this method are highly concordant (concordance correlation coefficients > 0.90) with simultaneous measurements obtained by auscultation (23).

A whole-blood sample was obtained by finger-prick after an overnight fast. Plasma glucose and lipid profiles were determined with an enzymatic/peroxidase dry chemistry method (LDX System; Cholestech Corporation, Hayward, California). In this population, this instrument provides estimates of lipid concentrations that agree closely (concordance correlation coefficients: total cholesterol, 0.90; high density lipoprotein cholesterol, 0.69; triglycerides, 0.97) with estimates derived from samples analyzed in a reference laboratory (24). Persons who had consumed food during the 5 hours and 8 hours prior to blood drawing were excluded from analysis of glucose levels and triglyceride levels, respectively.

Variable specification
We derived a score for 1975 household socioeconomic status, using an approach described elsewhere (25). We classified current residence as urban or rural on the basis of local classifications and access to municipal services. We calculated body mass index as weight (kg) divided by the square of height (m). Fasting glucose values were categorized using American Diabetes Association criteria (26). Blood pressures were categorized according to the classification given by the US National High Blood Pressure Education Program (27). Low density lipoprotein cholesterol concentration was calculated using Friedewald's equation (28). Blood lipid cutoff values were defined according to the Third Report of the US National Cholesterol Education Program (29). The metabolic syndrome was defined on the basis of American Heart Association criteria (30); this information was considered missing if any of the required elements was missing.

Model specification
We used an intent-to-treat analysis in which persons were considered exposed to the randomly assigned supplement regardless of actual intakes. The original INCAP Longitudinal Study included all children in the villages under the age of 7 years at study launch, pregnant women, and newborns. Children were followed through age 7 years or study closeout. Supplementation was provided from March 1969 through February 1977. Thus, children were exposed to the supplement at a range of ages—prenatally through supplement intake by the mother; during the first year or two of life (through maternal supplement intake transmitted in breast milk and through the child's own consumption); or later in childhood. Older cohort members were exposed to supplement at ages above 7 years, but attendance at the supplementation center was not recorded for these persons.

We defined participants as having been exposed to the intervention within specified age ranges if the whole of the eligible age range fell during the period of supplementation. Thus, for example, participants were considered to have been exposed from birth through age 36 months if they had been born between March 1969 and February 1974 (persons born prior to study launch would not have been exposed from birth, and births taking place after February 1974 would not have had 3 full years of exposure to intervention prior to study closeout). Other age groupings, devised to represent potential critical age ranges in child development, were created in a similar fashion (see figure 1). The age specifications overlap, with a large overlap in the persons classified as having been exposed across adjacent age groups. The age-specific models are not wholly independent of each other, but examination of the pattern across age specifications provides clues as to potential critical exposure periods.


Figure 1
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  		FIGURE 1 Exposure to nutritional supplementation at specified ages in an intervention study conducted between 1969 and 1977 in four villages in Guatemala, by year and quarter of birth.

 
Of primary interest was the incremental effect of exposure to atole in specified age ranges, over and above baseline differences among villages or secular trends. To estimate this effect, we included three dummy variables to control for fixed effects of village of birth and treatment assignment (coded 1 for atole, 0 for fresco), a variable characterizing age-specific exposure to the intervention (coded as 1 if the participant had been exposed to the intervention for the whole of the relevant age interval and 0 otherwise), and a multiplicative term for interaction between the exposure variable and treatment type. All analyses focused on the estimate of this interaction term. Note that the use of three indicators for the village fixed effects yields results identical to those from an alternate formulation of the underlying village fixed effects that considers the villages within their randomly allocated treatment groups (atole vs. fresco), a dummy variable to denote whether the village is large or small (the two strata used to define the pairs for randomization), and the interaction between treatment and size.

Statistical analysis
We developed a standard set of models, using multiple linear regression to assess associations with continuous variables (glucose, blood pressure, lipids) and multiple logistic regression to assess associations with binary variables (hypertension, diabetes, metabolic syndrome). The base model included a term for year of birth (as a continuous variable) to control for the age-dependence of many of the parameters and for unmeasured time-varying changes within exposure groups. We then added baseline covariates (1975 household socioeconomic status; maternal educational attainment; paternal educational attainment; maternal height; and maternal age at the time of birth of the index child, dichotomized as ≤40 years or >40 years). Birth order was not an independent predictor of any outcome variable, and its inclusion as a covariate did not alter any estimates. In a third model, we added urbanicity of the offspring's current residence (rural or urban), educational attainment, and anthropometric measures (body mass index, waist:hip ratio, height). Model 2, which included only factors present at baseline, was our preferred model. In practice, estimates for model 3 did not differ from those of model 2, and hence we do not present the results for model 3. Each model included all persons with the outcome variable of interest.

Missing data on covariates (20 percent for maternal height, 8 percent for socioeconomic status, 7 percent for paternal schooling, 2 percent for maternal schooling) were handled by adding a dummy variable to the model, coded as 1 if the information was missing and 0 otherwise, and recoding the missing value to the sex-specific mean (for continuous variables) or median (for categorical variables). We tested for systematic bias due to the inclusion of persons with one or more missing values by running all analyses with a data set that included only complete records. As would be expected given the low prevalence of missing data, differences between the full and restricted models were trivial.

In our population, 84 percent of participants had one or more siblings in the study; thus, within-family correlation could have been substantial, which would have biased the standard errors derived from ordinary least squares and hence might have resulted in incorrect inferences. We used the generalized estimating equations (GEE) approach (31) with an exchangeable working matrix to adjust for correlation among persons clustered within families, since the model controls for unmeasured family factors shared by siblings, including parental genetic influences, which might play a role in predicting health outcomes. To examine the robustness of our inference, we tested alternative approaches to the calculation of standard errors. We implemented a cell mean approach (32) by calculating the mean (frequency for categorical variables) of each study variable within each of the 64 village-birth year clusters and then conducting ordinary least-squares analysis on these 64 observations. In effect, this approach reduces the data set to an ecologic analysis and compensates for the reduced number of degrees of freedom by utilizing population means as the units of analysis. We also implemented a block bootstrapping method (33) by drawing 200 bootstrap samples, each of which contained ordinary least-squares results from 64 bootstrapped village-birth year samples, and using these to derive the sampling distribution of the standard error. Both methods yielded results very similar to those obtained from the GEE approach, and only the GEE-based results are presented.

All analyses were implemented in SAS, version 9.1 (SAS Institute, Inc., Cary, North Carolina). The SAS procedure GENMOD was used to fit models. Analyses were initially carried out for men and women separately. We tested for heterogeneity by sex through examination of the statistical significance of the coefficient of the third-order term (sex x atole x exposure cohort). Few differences significant at p < 0.10 were observed. We also conducted pooled analyses with adjustment for sex.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
DISCUSSION
 References
 
Study participants were 25–42 years old at interview. Almost three quarters lived in rural areas; most migrants lived in Guatemala City. Anthropometry was performed in 1,271 persons, blood pressure was measured in 1,420, and fasting blood samples for determination of lipid and glucose levels were obtained from 1,051 and 1,165 persons, respectively.

Selected characteristics of the study population, described in detail elsewhere (34), are summarized in table 1. In tables 2–5, we present the estimates for exposure to atole at defined age intervals. Adjustment for parameters measured at follow-up did not affect the point estimates substantially. Since our preferred model was model 2, we focused on this specification.


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  		TABLE 1 Selected characteristics of persons exposed to a nutrition supplementation intervention in four villages in Guatemala between 1969 and 1977 and followed up in 2002–2004, by sex

 

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  		TABLE 2 Estimates of the effect of exposure to atole at specified ages on fasting glucose levels (mg/dl) among persons exposed to a nutrition supplementation intervention in 1969–1977 in four Guatemalan villages who were followed up in 2002–2004{dagger}

 

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  		TABLE 3 Estimates of the effect of exposure to atole at specified ages on blood pressure (mmHg) among persons exposed to a nutrition supplementation intervention in 1969–1977 in four Guatemalan villages who were followed up in 2002–2004{dagger}

 

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  		TABLE 4 Estimates of the effect of exposure to atole at specified ages on serum lipid levels (all in mg/dl) among persons exposed to a nutrition supplementation intervention in 1969–1977 in four Guatemalan villages who were followed up in 2002–2004{dagger}

 

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  		TABLE 5 Estimates of the effect of exposure to atole at specified ages on prevalence of the metabolic syndrome* among persons exposed to a nutrition supplementation intervention in 1969–1977 in four Guatemalan villages who were followed up in 2002–2004{dagger}

 
Glucose
Exposure to atole was associated with lower fasting glucose levels (table 2). The association was consistent for both men and women but tended to be stronger for women. In women, the effect size increased (in absolute terms) with increasing age at exposure, from –4.0 mg/dl (95 percent confidence interval (CI): –11.1, 3.1) for exposure in the age range of gestation through 24 months to –10.5 mg/dl (95 percent CI: –21.4, 0.3) for exposure in the age range 36–72 months. The latter estimate represents a decrease of 0.4 standard deviations.

Blood pressure
Systolic blood pressures were lower among persons exposed to atole in the age range 24–60 months, with the effect estimate achieving statistical significance in the pooled model (–3.0 mmHg, 95 percent CI: –5.6, –0.4) and for men (–4.2 mmHg, 95 percent CI: –7.9, –0.4) (table 3). The association between atole and diastolic blood pressure was not significant.

Lipids
Exposure to atole was not significantly associated with total or low density lipoprotein cholesterol levels in either sex-specific or sex-pooled models (table 4). There was a positive association between exposure to atole during gestation and the first 36 months of postnatal life and high density lipoprotein cholesterol levels in men (effect size of 0.5 standard deviations), with no association being observed in women. The association between exposure to atole during gestation and through age 24 months and high density lipoprotein cholesterol (increment of 2.7 mg/dl, 95 percent CI: 0.3, 5.0) remained statistically significant in the sex-pooled model. Triglyceride levels were lower among persons exposed to atole throughout gestation and the first 36 months of postnatal life. Across the specific age exposure categories, effect estimates were broadly consistent for men and women.

Metabolic syndrome
Odds ratios were close to null for the metabolic syndrome.


   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
References
 
We analyzed the distribution of established risk factors for cardiovascular disease among persons born into a chronically undernourished population and exposed to a nutrition intervention during childhood. We found few significant associations of the intervention with the distribution of the risk factors; the associations that were observed were consistent with a reduction in risk for cardiovascular disease given exposure to atole. Our results were robust to control for a range of potential covariates and mediating variables and were broadly similar for men and women. Our study is of value to the literature relating early-life exposures to later disease development because of its community-randomized design and prospective follow-up.

In earlier studies in this population, Conlisk et al. (35) observed lower fasting glucose levels among persons born in an atole village (p < 0.05 for women), while Webb et al. (36) found no difference in blood pressure between persons born in the two atole villages as compared with those born in the fresco villages. These previous findings were limited by the younger age at follow-up (data were collected in 1997–1998) and were restricted to persons followed since birth, precluding examination of the role of timing of supplementation. In our population, adult factors were strongly associated with the cardiovascular disease risk factor distribution (37, 38). Our present findings of few strong associations between supplementation and later cardiovascular disease risk are broadly consistent with those earlier reports, yet they suggest the emergence of a protective effect of supplementation on risk of future cardiovascular disease as the cohort matures and risk factors become more established.

In countries undergoing rapid nutritional and epidemiologic transitions, cardiovascular disease is becoming epidemic (39). A large and growing body of literature ascribes adult disease to a mismatch between the developmental trajectory established by the fetus in response to maternal signals and the later environment of the offspring (3). Our study suggests that community-wide food interventions targeted at pregnant women and young children that are of sufficient intensity to reduce the prevalence of stunting (40) have a modest impact on risk of later disease.

Among birth cohort studies in developing countries, this cohort is unique in its intervention design and has one of the longest durations of follow-up (41). In Delhi, India, Bhargava et al. (7) have followed a cohort established in 1969, but no dietary intake data have been published. Among adolescents in Cebu, the Philippines, maternal height and midarm fat area were found to have interactive associations with serum lipid levels (42), while maternal nutritional intake and maternal nutritional status interacted in their effects on blood pressure (43).

We are not aware of any other studies in which persons randomized to receipt of a nutritional supplement in childhood have been followed to adulthood. However, the study population was not individually randomized to receive atole or fresco. As such, with only two pairs of villages being randomized, baseline differences among the villages may not have been fully addressed by randomization. Our specification of potentially critical periods thus represents a major advantage of our approach over that used in previous analyses (35, 36), as we were able to control for village-specific fixed effects. We controlled for a set of variables collected at baseline that potentially related to the later development of cardiovascular disease risk but that in practice made little difference to our effect estimates. Our analysis did not consider the dose of either supplement received, which has previously been shown to be related to factors such as the distance from the home to the feeding center (44). Since these factors may also relate to variables that predict the prevalence of cardiovascular disease risk factors, use of a dose-response model may lead to biased estimates. The estimates we provide should be considered in the light of the estimated supplement coverage in the villages and not as estimates that would be obtained were supplement directly provided to each mother and child under direct observation.

The potential for attrition bias must be considered. We targeted 1,856 persons from the original birth cohort and obtained blood samples for analysis from 1,201 of them (64.7 percent). For village residents, who completed study assessments in several waves, scheduling of the blood drawing proved to be the limiting factor, especially among those who worked outside the village, leaving before dawn each day. For migrants, who completed all study examinations in one session, we were limited by lack of exact addresses. For attrition to have biased our results, those who were not studied would have had to selectively differ with respect to both their exposure to the intervention and their risk of cardiovascular disease. The first has been shown to have occurred (21), and we lack information on the latter. Hence, bias related to attrition is possible.

Our study had only limited power to detect modest effects of the intervention. While this cohort is still quite young and overt diabetes and hypertension are rare, the prevalences of prediabetes and prehypertension are high (34). In the absence of intervention programs, the prevalences of hypertension and diabetes are likely to increase as the cohort ages, resulting in higher statistical power in future waves of data collection. Similar considerations apply to the association between exposure to atole and the metabolic syndrome. However, for the continuous variables, our study had adequate power to detect associations of 0.2 standard deviations or greater.

There was no consistent pattern of associations by age at exposure to the intervention. For glucose, associations were strongest given exposure at older ages, whereas for high density lipoprotein cholesterol and triglycerides, the associations were strongest at younger ages. Where an effect was seen for one age category, neighboring categories showed attenuated associations, and distant categories generally showed no association. Where effects were consistently null, effect sizes were also consistent in strength across the age specifications, suggesting true null effects. There were no situations in which significant associations in opposite directions were observed for men and women. Where sex differences were observed (and these were rare), they most commonly took the form of differences in effect size, not in direction, such that the association was null in one sex group and nonnull in the other. We find the consistency across the sexes encouraging.

Our data provide reassurance that efforts to address nutrient deficiencies and ameliorate stunting through interventions targeted at pregnant women and young children are unlikely to have adverse consequences for the cardiovascular disease risk of the offspring, and may in some cases be beneficial. Our data do not support a strong role for maternal or offspring nutritional intakes as potent triggers for the development or prevention of cardiovascular disease risk factors among adults who grew up in environments characterized by widespread undernutrition and growth failure.


   ACKNOWLEDGMENTS
 
The authors gratefully acknowledge the financial support of the US National Institutes of Health (grants R01 TW-05598 (Principal Investigator, Dr. Reynaldo Martorell) and R01 HD-046125 (Principal Investigator, Dr. Aryeh Stein)) for the present activities and the many organizations (the US National Institutes of Health, the Thrasher Research Fund, the Nestle Foundation) that have funded the work of the INCAP Longitudinal Study since its inception.

The 2002–2004 field work would not have been possible without the dedication and outstanding work of the field team at INCAP and the staff of the data coordination center, directed by Humberto Méndez and Luis Fernando Ramírez. The authors thank Alexis Murphy of the International Food Policy Research Institute (Washington, DC) for data management. They also thank the past investigators and staff of the INCAP Longitudinal Study for establishing and maintaining this invaluable cohort.

Conflict of interest: none declared.


   References
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 References
 

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A. D Stein, P. Melgar, J. Hoddinott, and R. Martorell
Cohort Profile: The Institute of Nutrition of Central America and Panama (INCAP) Nutrition Trial Cohort Study
Int. J. Epidemiol., August 1, 2008; 37(4): 716 - 720.
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