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Department of Nutrition and Food Science, University of the Basque Country, Vitoria, Spain; * University School of Health Sciences, University of Zaragoza, Zaragoza, Spain; Endocrinology Unit, Military Hospital of Zaragoza, Spain; ** Facultad de Ciencias de la Actividad Física y del Deporte, Universidad Politécnica de Madrid, Madrid, Spain; and Departamento de Pediatría, Universidad de Zaragoza, Zaragoza, Spain
2 To whom correspondence should be addressed. E-mail: lmoreno{at}unizar.es.
ABSTRACT
Size at birth and early postnatal growth are determinants of adult height and BMI. The aim of this study was to evaluate the effect of birth weight on body composition and fat distribution in a group of Spanish adolescents. Current body composition was assessed by both skinfold thickness and dual X-ray absorptiometry in 234 adolescents born at term (140 girls and 94 boys), now aged 13-18 y and living in the city of Zaragoza. Relative fat distribution was estimated using the ratio of the subscapular to triceps skinfolds (S:T). Birth weight and gestational age were assessed by a questionnaire. Birth weight was inversely associated with the S:T ratio (P < 0.05) in boys and directly associated with bone mass (P < 0.01) and fat-free mass (P < 0.05) in girls. This association was independent of factors such as age, Tanner stage, gestational age, socioeconomic status, physical activity, and height. In conclusion, our data support the hypothesis that impaired fetal growth, measured by birth weight, may be related to central fat distribution in boys and decreased bone and fat-free mass in girls.
KEY WORDS: • birth weight • body composition • adolescence
Several authors have proposed that there are critical periods during childhood that influence the development of obesity, including gestation and early infancy, the period of adiposity rebound, and adolescence (1–3). "Programming" is the process by which factors acting during early life may have a long-term effect on health. It may represent a further potentially important mechanism that could contribute to the development of obesity (4,5). For example, the greater propensity to higher BMI seen in children and adults who were heavier at birth suggests that fetal life is a critical window for programming later body fatness (6).
BMI is frequently used as a marker of adult obesity. In children and younger adults, it is correlated with body fatness. High weight at birth has been associated with higher BMI in adulthood (2). However, low weight at birth has also been identified as a risk factor for adult obesity, and was associated with a greater risk of development of cardiovascular disease, noninsulin-dependent diabetes and the insulin resistance syndrome in adult life (7,8). This paradox could be due to the fact that BMI reflects fat mass (FM)3 and also fat-free mass (FFM).
In this context, poor fetal growth, as measured by low birth weight, could program a smaller proportion of lean tissue mass later in life (9). The discrepancies cited in the literature in relation to the effect of higher birth weight on later body weight and BMI can be attributed to differences in lean rather than in FM (10). Another possibility is that lower birth weight could be associated with abdominal FM distribution, which is responsible for the increase in the metabolic risk of cardiovascular diseases (11–13).
The discrepancies in the literature could also be due to the different age periods or sex groups examined. Thus, low birth weight has been associated with a higher waist:hip ratio in adult women (14) and with a higher subscapular:triceps (S:T) ratio in adolescent girls (15).
In this study, we investigated male and female adolescents using a more objective measurement of body composition, dual energy X-ray absorptiometry (DXA), which provides a direct and accurate means of measuring lean body mass and FM in adolescents to determine the effect of birth weight on body composition and adipose tissue distribution. Possible gender-related differences in this programming effect were also analyzed.
MATERIAL AND METHODS
Subjects. Subjects included in this analysis belonged to the AVENA Zaragoza Study population. The AVENA (Alimentación y Valoración del Estado Nutricional en Adolescentes) study was designed to evaluate the nutritional status, dietary and leisure time habits, and physical activity and fitness of Spanish adolescents to identify risk factors for chronic diseases in adulthood. The overall methodology of this multicenter, cross-sectional survey from 5 Spanish cities (Santander, Granada, Murcia, Zaragoza, and Madrid) was described previously (16,17). In the city of Zaragoza, we studied 348 adolescents aged 13.0–17.9 y (198 girls and 146 boys). The adolescents were from 19 school classes belonging to 14 public and private schools and represented the socioeconomic distribution of the population in this area; 15 school classes from 11 schools agreed to go to the Military Hospital of Zaragoza for measurement of their body composition by DXA. DXA measurements were performed in 280 adolescents between January 2000 and March 2002. For the purpose of this analysis, we identified 234 subjects who were born at >35 wk of gestation (94.1%) and whose data for socioeconomic status (SES), physical activity (data not available, n = 15), and gestational age (missing data, n = 18) were available. The percentage of adolescents born preterm was 5.9%. Written informed consent was obtained from parents or guardians and subjects, and the study protocol was approved by the Review Committee for Research Involving Human Subjects of the Hospital Clínico Universitario "Lozano Blesa" (Zaragoza, Spain).
Socioeconomic status. In accordance with the recommendations of the Spanish Society of Epidemiology, the SES was assessed according to the educational level and type of occupation of the father. Using this information, adolescents were classified into the following 5 categories: low, medium-low, medium, medium-high, and high SES (18).
Neonatal data. Birth weight and gestational age at birth were obtained from the health booklets in which these data were recorded. Other health indicators were added during infancy and childhood. Birth weight was expressed as the SD from expected weight (Z-score), calculated with the use of appropriate centiles previously described for the population of this city and according to sex and gestational age (19). Gestational age was coded as 1 (from 35 to 40 wk of gestation) or 2 (>40 wk of gestation).
Anthropometric measures and Tanner staging. Height (cm) was measured with a stadiometer to the nearest 0.1 cm (SECA, Vogel & Halke). Body weight was measured at the time of the DXA scans, without shoes and with light clothing to the nearest 0.05 kg using a beam balance (SECA, Vogel & Halke). BMI was calculated from the ratio of weight/height2. Skinfold thicknesses (SFT) were measured in triplicate with the use of a skinfold caliper (Holtain) at the triceps, biceps, subscapular, and suprailiac sites on the left side (20) and the mean value was obtained. Measurements were done by the same investigator who was trained in the techniques involved, following the method previously described (21–23). For all of the SFT measurements, intraobserver technical errors of measurements were <1 mm and the reliability was >95% (17). SFT measurements were used to estimate FM (and hence FFM) using the equations of Slaughter et al. (24,25). To describe the central subcutaneous body fat distribution, the S:T ratio was calculated (26,27). Pubertal status was determined by physical examination and classified according to the method of Tanner (28).
Body composition. DXA measurements were performed after anthropometric study. A DXA scanner (Lunar DPX-L scanner) with DPX-L software (Lunar ) was used to estimate FM, bone free lean tissue mass (FFM) and bone mass (BM). All DXA scans, which were completed with the same device and software, were performed by the same technician who had been fully trained in the operation of the scanner, the positioning of subjects, and the analysis of results according to manufacturer's guidelines and adhering to accepted methodology (29,30). The percentage of FM by DXA was calculated as [(FM/(FM + FFM + bone mineral content) x 100].
Physical activity. The physical activity index (PAI) was calculated by means of 4 quantitative variables, expressed in metabolic equivalents: 1) activities done during the summer period and recorded in the summer questionnaires; 2) daily physical activity for week days during the school period; and 3) Saturday and 4) Sunday physical activities, considering the academic period. By factorial analysis of principal components, a single factor (PAI) was identified with an autovalue > 1 (2.23) that accounted for 55.9% of the variance. The adolescents also answered another questionnaire about the practice of regular physical activity (yes/no). The 2 physical activity estimates were compared; PAI sensitivity was calculated and then a cut-off point, expressed as the maximum value of the Youden's index, classifying the adolescents as sedentary or active, was obtained.
Statistical analysis.
Statistical analyses were performed with the "Statistical Package for the Social Sciences (SPSS)" software 12.0. Regression analysis was used to assess associations between FFM, FM, BM, or subcutaneous fat distribution and the Z-score for birth weight; multiple regression analysis was used to adjust for age, Tanner stage, gestational age, SES, and physical activity level. The Tanner stage categorical variable was transformed into 4 dummy variables to perform the regression analysis. The association between birth weight Z-score and body composition was also adjusted for variation in body size by adjusting for height squared (31). We also tested the interaction between sex and birth weight Z-score The simplest models assessed body composition results relative to Z-score birth weight in all subjects; there were significant interactions between sex and Z-score for FFM, FM, BM, and the S:T skinfold thickness. Given the sex interactions in these models, the results are presented stratified by sex. The interaction results are also presented. Overweight and obesity percentages were calculated using the criteria proposed by Cole et al. (32). Results were expressed as means ± SEM. A P-value 
0.05 was defined as significant.
RESULTS
The descriptive data, anthropometric variables, and body composition measurements of the 234 study subjects are shown in Table 1. The birth weight of the boys was 3283.8 ± 33.8 g and that of the girls was 3300.4 ± 53.8 g; there were no differences between the sexes
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The ratio of S:T skinfold thickness was inversely associated with the Z-score in the 3 regression models, i.e., unadjusted, adjusted by sex (P = 0.003), and adjusted by sex, Tanner stage, age, gestational age, physical activity, SES and height squared (Table 2). There were nonsignificant associations between Z-score and FFM and FM obtained by DXA or by SFT measurements. Bone mass was significantly associated with birth weight Z-score. This association remained significant after adjustment for sex (P = 0.028), but was not significant when adjusted for other factors that might affect the results (Table 2).
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When the influence of birth weight Z-score on body composition was observed separately in boys and girls, the birth weight Z-score was strongly and positively correlated with height in girls in all models, not only in the unadjusted model and that adjusted for pubertal stage (P = 0.001), but also in the other models with the potentially confounding factors mentioned. Therefore, weight was moderately associated with birth weight Z-score and remained significant after adjustment for Tanner stage (P = 0.032). However, this association was not significant after adjustment for age, SES, gestational age, and physical activity (P = 0.077). In male adolescents, birth weight Z-score was not correlated with any of these anthropometric measurements (Table 3).
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In male adolescents, birth weight Z-score was not associated with any of the body composition measurements. However, after adjustment for the above-mentioned factors, birth weight Z-score was inversely associated with the S:T skinfold thickness ratio. There was a similar trend in girls (P = 0.061) and after adjustments, the weak association remained nonsignificant (Table 4).
DISCUSSION
The fetal period is considered to be one of the critical periods for the development of obesity (1,4,33). Low weight at birth has been associated with the development of non-insulin-dependent diabetes (34,35) and with a central pattern of fat distribution, which is a component of the insulin resistance syndrome in adults (8). These observations led to the hypothesis that non-insulin-dependent diabetes and cardiovascular disease could be programmed by events in fetal life that lead to persisting changes in body composition and metabolic function (36,37).
Our study was not designed to compare different methods for assessing body composition. However, it is interesting to point out that the results for FM produced by DXA were higher than those obtained with the use of SFT equations as previously reported by others (38,39), and that the body FM percentage in Spanish adolescents seems to be elevated as we reported previously (40). Nevertheless, the results of the regression analysis were not affected by the method used.
In the present study we report gender-related differences in the programming effect of birth weight for gestational age in body size and composition in the adolescents. In girls, the data showed that a higher birth weight was associated with greater weight, height, FFM, and BM, but not with greater FM or BMI. These associations were independent of age, pubertal stage, gestational age, physical activity, SES, and height and were observed when FFM was measured either by SFT equations or by DXA scanning. On the other hand, one of the difficulties in comparing body composition measurements in children and adolescents, particularly when the groups differ in weight or height, is that of expressing the data in an appropriate manner. In this study, the body composition measurements were normalized for body size as proposed by Van Itallie et al. (31) adjusting them for height squared.
Although high birth weight tended to be associated with higher body weight, this was largely attributable to the fact that girls with a high birth weight Z-score were taller and had greater FFM, but not FM or percentage of body fat than adolescents with low birth weight. Previous studies suggesting an increased risk of obesity in individuals with high birth weight used weight or BMI as a measure of adiposity rather than body composition measures (41,42). Our data are in agreement with other more recent studies, indicating that the association of birth weight with later body weight could in fact be related to the programming of greater lean tissue mass rather than of FM (10,35). The association of birth weight with FFM was independent of height, which suggests that a high birth weight programs body composition rather than simply predisposing to greater body size.
On the other hand, the results clearly showed that birth weight bears a positive association with adolescent BM in girls, even after adjusting for height. A recent cohort study showed that birth weight and weight at 1 y were independent determinants of BM in the 7th decade in both sexes (43). In another study, a relation between birth weight and adult BM and muscle mass was found in both sexes (44). However, there have been no previously published reports of the differences in programming effect of birth size with bone and muscle mass in male and female adolescents measured by DXA. An early study showed the association between birth weight Z-score and lean body mass in adolescence after adjusting for sex (35).
Birth weight Z-score was inversely associated with relative truncal subcutaneous fat distribution relative to arm fat deposition in male adolescents in this sample, but not with whole-body FM, percentage of body fat or with the sum of skinfolds, which is an indicator of subcutaneous fatness per se. Low birth weights were associated with a central or truncal pattern of subcutaneous fat distribution relative to arm deposition measured by an increased S:T skinfold ratio and this relation was independent of known variables that might interfere such as SES, age, height, physical activity, Tanner stage, or gestational age. Previous studies showed a significant association between low birth weight, with increased central (39,45) or abdominal (46) fat distribution in children and adults (3,27,47), but the results were inconsistent for adolescents. An earlier study performed in adolescent girls showed a higher S:T ratio (15); in another case-control study of adolescents, however, the body fat distribution of low-birth-weight adolescent girls and boys and normal-birth-weight adolescent controls did not differ (48).
In our study, low birth weight was not associated with an increased waist:hip ratio or waist circumference. The S:T skinfold ratio and waist:hip ratio reflect different aspects of body fat distribution; as previous studies have shown, the waist:hip ratio can be a poor indicator of body fat distribution at younger ages (49). This relation between low birth weight and high waist:hip ratio was described in only a few studies performed in adults (3,14).
In boys, there were no associations between size at birth and body composition measurements. The lack of effect of fetal growth on lean tissue in adolescent males could be associated with the possible amplification of the programming effect of later body composition with age and may be most marked after puberty. Thus, despite the lack of differences in the age and Tanner stage of the males and females adolescents examined, multiple body composition changes take place during adolescence, and the pattern of these changes is influenced more by gender and pubertal development stage than by age (50). In this sense, a possible explanation of sex-related differences in the programming effect of birth weight on body composition of this adolescent sample could simply be a reflection of their stage of maturation because the majority of the girls were already in a slow linear growth period, whereas a high proportion of the boys were in a fast growing period. Other studies showed that fetal growth measured by birth size for gestational age appears to be associated with the timing of maturation. Thus, several authors observed a more rapid progression of pubertal maturation in girls born small for gestational age (51,52). Further studies might help to verify the suggested trends in other populations with a high number of male and female adolescents in varying pubertal maturation stages.
An early study showed the association between birth weight Z-score and lean body mass in adolescence after adjusting for sex (35). Differences in study designs make it difficult to compare the results of this study with others. In most of previous studies, adolescents were at varying stages of sexual maturation, and the data were not adjusted. On the other hand, birth weights were not corrected with the appropriate centiles according to sex and gestational age.
The mechanisms underlying the association between birth size for gestational age status with body composition and future propensity to adult diseases are unknown. Genetics and environmental conditions during intrauterine life partially explain this association. Several fetal gene effects (e.g., insulin gene variable number tandem repeat polymorphism and others) are more evident in the absence of maternal-uterine growth restraint (53). Environmental factors, including nutrition, are supposed to influence the expression of genes such as insulin-like growth factor, leptin, and glucocorticoids that involve hormonal and metabolic regulation and, thus, fetal growth and later disease risk (54). There are several plausible hypotheses to explain the relation between smaller birth weight for gestational age and lower proportion of lean body mass or more central subcutaneous fat distribution later in life. For example, genetically determined insulin resistance could result in impaired insulin-mediated growth of fetal muscle, and the continuation of this pattern of body composition would lead to less muscle mass later in life (37). On the other hand, as previously suggested, intrauterine factors could program later body composition independently of maternal and genetic influences (55). In this sense, fetal adaptation to undernutrition and to other intrauterine suboptimal conditions may alter fetal physiology, endocrine response, and metabolism, resulting in increased protein breakdown and decreased protein accretion, which could compromise fetal muscle and bone growth (36,56). Thus, intrauterine growth retardation may be associated with a relative greater deficit in fetal lean mass rather than in fat mass and, later, could lead to the birth of infants that are small for their gestational age (57). One manifestation of this metabolic programming might be the allocation of cells during critical early periods to different body compartments (fat, muscle, and bone) (44). Permanent readjustments in homeostatic systems may ultimately be detrimental to health in later life and make these individuals more vulnerable to the additional effects of lifestyle.
In summary, this study suggests that in adolescents born at term, genetic and/or intrauterine environmental factors that influence fetal growth and are reflected in birth weight have long-term consequences for bone and muscle mass in girls and for subcutaneous fat distribution in boys.
FOOTNOTES
1 The AVENA-Study was supported by the Spanish Ministry of Health (FIS 00/0015) and grants from Panrico S.A., Madaus S.A., and Procter & Gamble S.A. This study was also supported by Instituto de Salud Carlos III (Spain), RCESP (C03/09). 
3 Abbreviations used: BM, bone mass; DXA, dual energy X-ray absorptiometry; FFM, fat-free mass; FM, fat mass; PAI, physical activity index; SES, socioeconomic status; SFT, skinfold thickness; S:T, ratio of the subscapular to triceps skinfolds.
Manuscript received 13 May 2005. Initial review completed 6 July 2005. Revision accepted 28 September 2005.
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