Literature
首页医源资料库在线期刊美国临床营养学杂志2005年82卷第2期

Anthropometric indicators of body composition in young adults: relation to size at birth and serial measurements of body mass index in childhood in the New De

来源:《美国临床营养学杂志》
摘要:HarshpalSSachdev,CarolineHDFall,CliveOsmond,RamakrishnanLakshmy,SushantKDeyBiswas,SamanthaDLeary,KolliSrinathReddy,DavidJPBarkerandSantoshKBhargava1FromtheDepartmentofPediatrics,SunderLalJainHospital,Delhi,India(SKB)。theDepartmentofPediatrics,MaulanaAz......

点击显示 收起

Harshpal S Sachdev, Caroline HD Fall, Clive Osmond, Ramakrishnan Lakshmy, Sushant K Dey Biswas, Samantha D Leary, Kolli Srinath Reddy, David JP Barker and Santosh K Bhargava

1 From the Department of Pediatrics, Sunder Lal Jain Hospital, Delhi, India (SKB); the Department of Pediatrics, Maulana Azad Medical College, New Delhi, India (HSS); the Medical Research Council Epidemiology Resource Centre, University of Southampton, Southampton General Hospital, Southampton, United Kingdom (CHDF, CO, SDL, and DJPB); the Department of Cardiology, All India Institute of Medical Sciences, New Delhi, India (RL and KSR); and the Indian Council of Medical Research, New Delhi, India (SKDB)

2 The original cohort study was funded by the US National Center for Health Statistics and the Indian Council of Medical Research. The current study was supported by the British Heart Foundation and the Medical Research Council UK.

3 Reprints not available. Address correspondence to HS Sachdev, E-6/12 Vasant Vihar, New Delhi 110 057, India. E-mail: hpssachdev{at}hotmail.com.


ABSTRACT  
Background: South Asians have a muscle-thin but adipose body phenotype and high rates of obesity-related disease. Adult body composition may be predictable in early life.

Objective: Anthropometric indexes of adult body composition were examined in relation to birth size and body mass index (BMI) during childhood.

Design: A population-based cohort of 1526 men and women aged 26–32 y in Delhi, India, who were measured sequentially from birth until 21 y of age were followed up. Adult weight, height, skinfold thicknesses, and waist and hip circumferences were measured. BMI and indexes of adiposity (sum of skinfold thicknesses), central adiposity (waist-hip ratio), and lean mass (residual values after adjustment of BMI for skinfold thicknesses and height) were derived.

Results: Mean birth weight was 2851 g. As children, many subjects were underweight-for-age (>2 SDs below the National Center for Health Statistics mean; 53% at 2 y), but as adults, 47% were overweight, 11% were obese, and 51% were centrally obese (according to World Health Organization criteria). Birth weight was positively related to adult lean mass (P < 0.001) and, in women only, to adiposity (P = 0.006) but was unrelated to central adiposity. BMI from birth to age 21 y was increasingly strongly positively correlated with all outcomes. BMI and BMI gain in infancy and early childhood were correlated more strongly with adult lean mass than with adiposity or central adiposity. Higher BMI and greater BMI gain in late childhood and adolescence were associated with increased adult adiposity and central adiposity.

Conclusions: Birth weight and BMI gain during infancy and early childhood predict adult lean mass more strongly than adult adiposity. Greater BMI gain in late childhood and adolescence predicts increased adult adiposity.

Key Words: Body composition • lean mass • obesity • developmental origins of adult disease • birth weight • childhood growth • nutritional transition • India


INTRODUCTION  
Obesity is a strong risk factor for hypertension, type 2 diabetes, dyslipidemia, and ischemic heart disease (IHD). Although its harmful effects on health are thought to arise from an excess of body fat (adipose tissue), obesity is generally defined by using the body mass index (BMI; weight/height2), which does not distinguish between lean and fat components of body weight (1). Body composition can vary widely at any given BMI, as highlighted recently by the debate concerning the appropriateness of BMI definitions of obesity in different ethnic groups (2, 3). South Asians have a low mean BMI, but this low BMI masks several adverse features of their body composition. South Asians have a lower muscle mass and a higher percentage body fat and are more centrally obese than are whites of comparable ages and BMIs (4–9). These characteristics are thought to partly explain South Asians' high risk of developing type 2 diabetes and IHD (4, 9–12).

Considerable interest currently exists in the associations between growth in early life (fetal life, infancy, childhood, and adolescence) and the later development of obesity and obesity-related disease. Higher weight or BMI, or accelerated gain in weight or BMI, during childhood and adolescence is associated with a higher adult BMI (13, 14) and with an increased risk of adult hypertension (15), type 2 diabetes (16–18), and IHD (19–22). Paradoxically, however, although higher birth weight predicts higher adult BMI (14, 23, 24), it is associated with a lower risk of type 2 diabetes and IHD (18, 22, 25–29), an exception being high birth weight caused by maternal diabetes, which is associated with an increased risk of later type 2 diabetes (29, 30). Higher weight or BMI in infancy is also associated with higher adult BMI (14) but a lower risk of type 2 diabetes and IHD (18, 22, 25–27). One possible explanation for these discrepancies is that weight gain at different periods of early life may have differential effects on the acquisition of fat and lean mass. There is good evidence, for example, that higher birth weight is associated more strongly with increased adult lean body mass than with adult adiposity (31–37).

We recently reported data from a cohort of young adults who were born in Delhi, India, and whose weight and height were measured at birth and throughout infancy, childhood, and adolescence (38). Lower BMI in infancy and accelerated BMI gain from 2 y onward were associated with an increased risk of adult type 2 diabetes and impaired glucose tolerance. Here we describe the relation of the early growth of this cohort with their adult body composition.


SUBJECTS AND METHODS  
The methodology of the Delhi birth cohort study has been described (38). In brief, the cohort was established between 1969 and 1972 to study pregnancy outcomes and child growth. All families living in a 12-km2 area of South Delhi were identified, and 20755 married women of reproductive age were followed up bimonthly to record menstrual dates. A total of 9169 pregnancies, resulting in 8181 live births (8030 singletons and 151 from twin pairs), were recorded. Trained personnel recorded the weight and length or height of the babies within 72 h of birth, at ages 6 and 12 mo (±7 days), and every 6 mo (±15 days) thereafter up to the age of 14–21 y. At recruitment, 60% of the families had an income >50 rupees per month (national average = 28 rupees), and only 15% of parents were illiterate (national average = 66%). Nevertheless, 43% of families lived in only one room. Hindus were the majority religious group (84%), followed by Sikhs (12%), Christians (2%), Muslims (1%), and Jains (1%).

Current study
From August 1998 to August 2002, we retraced 2584 (32%) of the initial cohort. They were visited at home by a social worker who explained the study, obtained consent, and administered a questionnaire. Ethical approval for the study was granted by the All India Institute of Medical Sciences, and informed consent was obtained from each subject.

Questionnaire data
Education was recorded as 1 of 7 categories ranging from "no schooling" (category 1) to "professional degree" (eg, Master of Science degree, PhD, or medical qualification) and occupation as 1 of 6 categories ranging from "unemployed" (category 1) and "unskilled manual labor" (category 2) to "professional." Housewives were categorized according to their husbands' occupations. Information on material possessions was recorded as an indicator of socioeconomic status. Subjects were given a score of 1 for each of the following household items: electricity, fan, bicycle, radio, motorized 2-wheeled vehicle, gas stove, television, cable television, electric mixer, electric grinder, electric air cooler, washing machine, car, air conditioner, computer, television antenna, and telephone. Alcohol consumption was recorded as the frequency of intake and volume of spirits, beer, and wine consumed per week. These data were converted into units of alcohol (1 unit = 25 mL spirits, 282 mL beer, or 125 mL wine) and were categorized as none, <7 units/wk, 7–14 units/wk, and >14 units/wk. Tobacco consumption was recorded as whether the subjects smoked (cigarettes, bidis, cigars, or hookah), chewed (raw tobacco or with pan), or inhaled (snuff). Subjects were categorized simply as current tobacco users or as nonusers. A score was derived as a summary estimate of daily physical activity. Work-related activity was classified on a 6-point scale ranging from "almost entirely sedentary" to "heavy physical work." Additional time spent per day in domestic activities (eg, sweeping, washing clothes, and cooking) and leisure activities (eg, jogging, swimming, and yoga) was recorded. Distances walked and cycled each day, with and without a load, were recorded and converted into approximate periods of time spent in these activities. These were then multiplied by metabolic constants, which were derived from the relative energy expenditure of activities (39), and were summed to derive a score.

Clinic investigations
After the home visit, the subjects were asked to attend a clinic after fasting overnight. Their weight, height, waist and hip circumferences, midupper arm circumference, and skinfold thicknesses (triceps and subscapular) were measured by using standardized techniques. The upper measurable limit for skinfold thickness was 40 mm. BMI was calculated as weight/height2 (in kg/m2). Subjects were categorized as obese if their BMI was 30 (40). Two definitions of overweight were used: the standard World Health Organization (WHO) cutoff of 25 (40) and that recently recommended for Asians of 23 (2). Central obesity was defined by using WHO criteria: waist-hip ratio > 0.90 (males) or > 0.85 (females) (41).

Two indexes of adiposity were derived from the skinfold-thickness measurements: 1) the sum of subscapular and triceps skinfold thicknesses, and 2) percentage body fat (42, 43). Three indexes of lean mass were derived: 1) arm muscle area, which was derived from midupper arm circumference and triceps skinfold thickness and was corrected for arm bone area (44); 2) lean body mass, which was derived as body weight minus fat mass and was adjusted for height, where fat mass = weight x percentage body fat; and 3) the residual value from a linear regression predicting BMI from the sum of skinfold thicknesses and height, adjusted for age and sex (designated the "lean residual"). The adjustments for height in these calculations were intended to derive proxies for lean tissue other than bone. Height adjustment was included in the derivation of the lean residual from BMI, even though BMI is often uncorrelated with height, because in Delhi there was a positive association between BMI and height (r = 0.09, P = 0.007 in men and r = 0.10, P = 0.009 in women).

Systolic and diastolic blood pressures were recorded by using an automated device (Omron 711; Omron Healthcare Europe, Hoosddorp, Netherlands) while the subjects were seated and after they had rested for 5 min. As described previously (38), plasma glucose and insulin concentrations were measured while the subjects were fasting and 120 min after a standard 75-g oral anhydrous glucose load. Plasma glucose, triacylglycerol, and cholesterol concentrations were analyzed by standard enzymatic methods by using Randox kits (Randox Laboratories Limited, Crumlin, United Kingdom) on a Beckman autoanalyzer (Beckman Instruments Inc, Brea, CA). HDL cholesterol was estimated by using the same method as for cholesterol measurement, after precipitation with phosphotungstate. Aliquots of plasma were stored at –70°C for up to 8 mo and were analyzed for insulin concentrations in batches by radioimmunoassay (Coat-a-Count insulin kit; Diagnostic Products Corporation, Los Angeles, CA). The method had intraassay and interassay CVs of <5% and <7.5%, respectively. Insulin resistance was calculated by homeostasis model assessment. Biochemical measurements were made in the biochemistry laboratory of the Department of Cardiology, All India Institute of Medical Sciences, New Delhi.

Statistical analyses
Variables with skewed distributions were log-transformed. Data were analyzed by using partial correlation coefficients and multiple linear regression. As previously described (38), we used all recorded data (not just the data for subjects recruited for this study) to derive SD scores for height and BMI for each subject at age 6 mo and at birthdays from age 1 to 21 y. The SD score is the number of SDs by which an observation differs from the mean for the cohort. Interpolated values were used if a measurement had been made within 6 mo (up to 1 y), 1 y (age of 2 y), 1.5 y (age of 3 y), and 2 y (all older ages). Back transformation provided estimates of the measurements at these ages. To measure the change in BMI in a time interval during childhood (for example between the ages of 2 and 5 y), we regressed the value at the end of the interval (age 5 y) on the value at the beginning of the interval (age 2 y) and at all preceding time points (birth, 6 mo, and 1 y) and expressed the residual as an SD score. This produces uncorrelated variables describing BMI change at specific time points in childhood, which we refer to as conditional SD scores. We calculated the age at adiposity rebound as the birthday between 2 and 9 y at which the lowest estimate of BMI occurred.


RESULTS  
Of the 2584 men and women traced, 1583 agreed to participate. Of these, 57 were excluded (24 were pregnant, 2 left after recruitment, and 31 were unreliably linked to earlier data), leaving 1526 (59% of those traced, and 19% of the original cohort). Compared with the original cohort, among the recruited subjects, 7% more of the subjects were male, maternal literacy was 6% higher, mean birth weight was 32 g heavier, and birth length was 2 mm longer. Height and BMI in childhood and adolescence were 0.1 SD lower.

The characteristics of the 886 men and 640 women studied are shown in Table 1.


View this table:
TABLE 1. Characteristics of the study cohort

 
At all ages from birth to adolescence, the subjects studied were short, light, and thin by international standards. For example, at 2 y, their mean SD scores for height, weight, and BMI relative to National Center for Health Statistics (NCHS) standards (45) were –1.54, –2.01, and –0.78 in boys and –1.55, –2.27, and –0.85 in girls. Percentages of children >2 SDs below the NCHS median for height, weight, and BMI at 2 y were 33%, 50%, and 12% (boys) and 30%, 57%, and 13% (girls). When they were reexamined as adults, most subjects were married, graduates (Bachelor's degree or higher), and in nonmanual employment (Table 1). Few women drank alcohol or used tobacco. Approximately 1 in 10 subjects was obese by the WHO definition (BMI 30). Almost one-half of the subjects were overweight by the WHO definition (BMI 25), and nearly two-thirds were overweight by the Asian cutoff (BMI 23). Sixty-five percent of the men and 31% of the women were centrally obese.

To select the most appropriate indexes of body composition for the analysis, we correlated BMI, height, and the direct and derived measures of adiposity, central adiposity, and lean mass with the cardiovascular risk factor variables (Table 2). Skinfold thicknesses, percentage body fat, waist circumference, and waist-hip ratio were positively correlated with all the risk factors except HDL cholesterol, for which the correlation was negative. The subscapular-triceps ratio showed weak and mainly nonsignificant correlations with the risk factors. The indexes of lean mass were also positively correlated with the risk factors (negatively with HDL cholesterol), especially insulin resistance and blood pressure, although these correlations were less strong than those for the measures of adiposity. For subsequent analyses, we limited the outcome variables to BMI and 4 other body-composition variables: sum of skinfold thicknesses and waist-hip ratio as the measures of general and central adiposity, respectively, that were most strongly correlated with the risk factors; the lean residual as the measure of lean mass least correlated with the risk factors; and height as the measure of skeletal size. Waist-hip ratio was selected in preference to waist circumference because it was uncorrelated with height. The correlations of each of these 4 variables with the risk factors, adjusted for the other 3, were weaker than but generally in the same direction as those described above (bottom of Table 2).


View this table:
TABLE 2. Correlation coefficients between adult anthropometric variables and cardiovascular disease risk factors1

 
Adult body composition in relation to age and adult lifestyle factors
BMI rose with increasing age (P < 0.001) and socioeconomic status (measured by each of the 3 indicators: education, occupation, and material possessions; P < 0.001 for all). It rose from 20.5 in those with fewer than 6 household possessions to 26.7 in those who owned 15 or 16 possessions. It was inversely related to physical activity (P = 0.01) and was higher in non-tobacco-users (men, P = 0.04; few women smoked) and in women of higher parity (P = 0.001 adjusted for age). Like BMI, the sum of skinfold thicknesses increased with age (P < 0.001), was inversely related to physical activity (P = 0.004), and was higher in men who were non-tobacco-users (P = 0.001) and in women of higher parity (P < 0.001). Waist-hip ratio rose with increasing alcohol consumption (men, P = 0.006; few women drank alcohol) and was inversely related to physical activity score (P = 0.001). The lean residual decreased with age (P < 0.001). All body-composition variables were strongly positively related to socioeconomic status as measured by occupation, education, and household possessions (P < 0.01 for all), except that waist-hip ratio and lean residual were not related to education status (P = 0.09 and P = 0.3 respectively). In further analyses, associations of early life variables with adult outcomes were adjusted for age, sex, socioeconomic status (all 3 measures), tobacco use, alcohol consumption, physical activity, and (in women) parity.

Adult body composition in relation to size at birth
In the sexes combined, higher birth weight was associated with higher adult lean residual and taller adult height (Table 3) . In women, but not men, it was associated with higher adult BMI and sum of skinfold thicknesses (P values for the interaction between sex and birth weight were 0.006 for BMI and 0.01 for sum of skinfold thicknesses). Longer birth length was strongly associated with taller adult height. It was also associated with higher adult sum of skinfold thicknesses and lean residual and with higher BMI in women but not men (P for sex interaction 0.04). Ponderal index at birth was positively related to adult lean residual but to none of the other adult body-composition outcomes. None of the birth measurements was related to adult waist-hip ratio. Although it was not one of the selected variables, we examined adult subscapular-triceps ratio in relation to size at birth, because this has been reported frequently in the literature (24). The ratio was negatively associated with birth weight (P < 0.001), length (P = 0.02), and ponderal index (P = 0.01). There were no significant interactions between birth size and sex. Means fell from 1.48 and 1.00 in men and women, respectively, who weighed 2500 g at birth to 1.38 and 0.95 in those who weighed >3250 g.


View this table:
TABLE 3. Adult body mass index, sum of skinfold thicknesses, waist-hip ratio, lean residual, and height according to birth weight, birth length, ponderal index at birth, and body mass index at ages 6 mo and 12 y1

 
Adult body composition in relation to BMI during infancy, childhood, and adolescence
Correlations between adult BMI and BMI measured during infancy, childhood, and adolescence were positive and strengthened progressively with increasing age (6 mo: 0.19; 1 y: 0.21; 2 y: 0.24; 5 y: 0.32; 8 y: 0.47; 11 y: 0.58; 14 y: 0.65). The correlations between BMI from birth to 21 y and all the adult body-composition outcomes are shown in Figure 1. Like adult BMI, all outcomes except height were positively correlated with BMI measured at earlier ages and correlations strengthened with increasing age. In males, BMI during infancy, childhood, and adolescence was more strongly correlated with adult lean residual than with adult sum of skinfold thicknesses (Figure 1). The differences between correlations with lean residual and the sum of skinfold thicknesses were significant (P < 0.05) for BMI at birth, 6 mo, 1 and 2 y, 5–13 y, and 16–18 y. In females, whereas BMI in early childhood was more strongly correlated with adult lean residual than with adult sum of skinfold thicknesses, differences between correlations were significant only at 2, 5, and 6 y, and BMI during adolescence was correlated more strongly with adult sum of skinfold thicknesses than with adult lean mass (statistically significant from 15 y onward).


View larger version (27K):
FIGURE 1.. Correlations between BMI in early life and adult body-composition outcomes. The graphs show the adjusted correlation coefficients and 95% CIs at the age of 6 mo and at every birthday, with the points connected for ease of reading. The number of subjects at any age was always >600 (men) or >500 (women) up to the age of 17 y; thereafter, the minimum numbers at any age were 243 (men) and 178 (women). All analyses were adjusted for age, education, occupation, number of household possessions, tobacco use, alcohol consumption, physical activity, and (in women) parity. Differences between the lines were tested by using inverse hyperbolic tangent transformation and by assuming normality. There were significant interactions (P < 0.05) between sex and the difference in correlations with adult lean residual and adult sum of skinfold thicknesses for BMI measurements at 6 mo, 1 y, and 6–12 y.

 
The associations of changes in BMI SD scores during infancy, childhood, and adolescence with adult body composition were examined in the sexes combined by using conditional SD scores at birth–6 mo, 6 mo–1 y, and 1–2, 2–5, 5–8, 8–11, and 11–14 y (after the age of 14 y, the numbers available decreased rapidly). The analysis was limited to 957 men and women with values at all these time points. All the conditional SD scores were included in regression models simultaneously, together with age, sex, BMI at birth, and the adult lifestyle variables (Figure 2). Higher BMI at birth and increases in BMI during every period of growth were associated with significantly higher adult BMI and lean residual. There were steep increases in the strength of these associations between birth and 6 mo and between 2 and 8 y. In contrast, conditional BMI SD scores up to the age of 2 y predicted adult sum of skinfold thicknesses only weakly. There was a steep increase in the strength of the associations between 2 and 8 y, and this was sustained throughout adolescence. There was a similar pattern for waist-hip ratio.


View larger version (24K):
FIGURE 2.. Prediction of adult anthropometric variables from BMI changes in early life. The graphs show adjusted regression coefficients for each time period during childhood (indicated on the x axis), with the points connected for ease of reading. The number of subjects included was 957. All analyses were adjusted for age, education, occupation, number of household possessions, tobacco use, alcohol consumption, physical activity, and (in women) parity by using multiple linear regression with the 5 indexes of adult body composition as outcomes and a standard set of x variables included in all models (birth weight and BMI change in the 7 time intervals shown, conditional on BMI up to the start of the interval and expressed as an SD score). m, months.

 
A total of 206 out of 1379 (15%) subjects with known gestational age at birth were born prematurely (<37 wk gestation). There were no significant associations between gestational age and adult body-composition variables. Regression coefficients for the associations between adult sum of skinfold thicknesses and change in BMI between birth and 6 mo and between 1 and 2 y were significantly larger in subjects born prematurely than in those born at term [P = 0.02 for the interaction between the binary variable (preterm vs full-term) and change in BMI, for both time periods]. There were no significant interactions at any age for the lean residual. Similar analyses were carried out in relation to being born small for gestational age. Subjects were divided into those with sex and gestation-adjusted birth weights above and below 2500 g. The regression coefficient for the association between adult lean residual and change in BMI between birth and 6 mo was smaller in the lower birth weight group [P = 0.02 for the interaction between the binary variable (<2500 g vs 2500 g) and BMI change]. There were no significant interactions at any age for the other adult outcomes. These analyses show that the differences in the correlations between BMI gain in infancy and adult lean residual compared with adult sum of skinfold thicknesses were lower in subjects born prematurely or small for gestational age.

Adult body composition in relation to the adiposity rebound
The mean (±SD) age and BMI at adiposity rebound were 6.6 ± 1.7 y and 13.8 ± 0.9, respectively. As reported previously (38), lower BMI at 2 y (P < 0.001) and a low gain in BMI from birth to 2 y (P = 0.003) were associated with earlier adiposity rebound. Earlier rebound predicted an increase in all measurements of adult body composition (P 0.001) except height.

Adult body composition in relation to height during earlier life
Length or height during infancy, childhood, and adolescence were increasingly strongly positively correlated with adult height (Figure 3). There were steep increases in the correlation coefficients during infancy and adolescence. Correlations between earlier height, or changes in height SD score, and adult sum of skinfold thicknesses, lean residual, and waist-hip ratio were weak and generally not significantly different from each other. There was no evidence of increased adiposity or central adiposity in subjects who were short or stunted [<2 SDs shorter than the NCHS reference (45)] at any time during childhood.


View larger version (22K):
FIGURE 3.. Correlations between height in early life and adult body-composition outcomes. The graphs show adjusted correlation coefficients and 95% CIs at the age of 6 mo and at every birthday, with the points connected for ease of reading. The maximum number of subjects was 1496 (at 14 y). The number was never <1200 subjects up to the age of 17 y, and, thereafter, the minimum number was 429 at the age of 21 y. All analyses were adjusted for age, education, occupation, number of household possessions, tobacco use, alcohol consumption, physical activity, and (in women) parity. Differences between the lines were tested by using inverse hyperbolic tangent transformation and by assuming normality.

 

DISCUSSION  
We studied 1526 men and women who grew up in the city of Delhi, India, at a time of rapid nutritional transition. According to international definitions, the subjects were underweight as children but as young adults had a high prevalence of overweight, obesity, and central obesity. Higher birth weight was associated with higher adult lean residual (an index of lean tissue mass) in both sexes and with higher adult BMI and sum of skinfold thicknesses in women. Higher BMI during infancy, childhood, and adolescence was associated with higher adult BMI, lean residual, sum of skinfold thicknesses, and waist-hip ratio. These associations strengthened with increasing age of earlier measurement. BMI and BMI gain during infancy and early childhood were more strongly correlated with adult lean residual than with adult adiposity or with central adiposity. This phenomenon was most prominent in males, in subjects born at full term, and in those who were not born small for gestational age. Higher BMI and greater BMI gain in late childhood and adolescence were strongly associated with adult adiposity and central adiposity.

The subjects came from an original population representing all live births within a defined area. The subjects' families were affluent and well-educated compared with national averages. Only 19% of the original cohort participated, and the subjects are thus likely to be unrepresentative of the original sample. The differences in their mean size at birth and during infancy and childhood, however, although statistically significant, were trivial. Our analysis was based on internal comparisons within the study sample and would be biased only if the associations between early growth and adult body composition differed between those who were and those who were not traced. Adult body composition was assessed only anthropometrically. None of our indexes of adiposity or lean mass was ideal, although all have been used in population studies. We recognize that our findings need to be confirmed with the use of better methods of assessing body composition.

We found expected associations between measures of adult adiposity and cardiovascular disease risk factors. Insulin resistance and blood pressure were also positively related to indexes of lean mass. The most likely explanation is that the latter were inadequately adjusted for body fat, especially nonsubcutaneous fat. The associations may, however, reflect a biological relation; several studies have reported positive associations between muscularity and blood pressure, although the mechanisms are unclear (46, 47). The subscapular-triceps ratio was positively correlated with cardiovascular disease risk factors in other studies (48, 49), but the mainly nonsignificant relations observed in Delhi suggest that this ratio has limited clinical utility at this age in this population.

Several studies have reported higher adult BMI in individuals of higher birth weight (23, 24). In common with other studies (31–37, 50), our data showed that birth weight was more strongly related to the lean than to the fat component of adult BMI. This difference was more marked in males than in females; higher birth weight in females was also associated with increased adiposity. There was a similar sex difference in one study (37), although others reporting data for both sexes showed no sex differences (31, 33, 34, 36); higher birth weight was significantly associated with muscle mass (31) or fat-free mass (33, 34, 36) but not fat mass in both sexes. Our data are consistent with the suggestion that fetal life is a critical period for the development of muscle or visceral mass (26, 35, 51). This may explain the increased risk of insulin resistance and type 2 diabetes in persons of low birth weight (18, 27, 29) despite lower adult BMI.

The positive correlations between adult BMI and BMI in earlier life, which strengthened with increasing age, have also been reported elsewhere (13). A novel finding of our study was the differing associations with fat and lean components of adult body mass depending on the age of BMI measurement in earlier life. Higher BMI gain in infancy and early childhood was associated with a greater increase in adult lean mass than in adult adiposity. Higher BMI gain in late childhood and adolescence was strongly associated with adult adiposity and central adiposity. As previously described in the Delhi cohort (38) and in Europeans (18, 27), lower BMI in infancy and greater BMI gain during childhood and adolescence are associated with an increased risk of adult impaired glucose tolerance and type 2 diabetes. Our data may provide an explanation for these findings. Low adult muscle mass could explain the association between adult glucose intolerance and low BMI in infancy, whereas increased generalized and central adiposity could explain its association with accelerated BMI gain in later childhood and adolescence. Skeletal muscle cells lose their ability to divide in early postnatal life (51, 52). In animals, undernutrition at this time permanently reduces muscle mass, and enhanced nutrition at later ages results in excessive fat deposition (52). We propose that infancy, like fetal life, is a critical period for the development of lean mass. The susceptibility of South Asians to type 2 diabetes and IHD may partly be caused by poor development of lean mass in fetal life and infancy, combined with increased adiposity in later childhood resulting from urban transition. Several other studies have examined adult body composition in relation to weight and BMI gain in infancy (50, 53, 54), but none compared the strength of associations for fat and lean measurements. In Guatemala, Li et al (37) studied anthropometric measurements of adult body composition in relation to birth length and changes in length during the first 2 postnatal years. In both sexes, a greater increase in length between birth and 2 y was associated with stronger effects on adult fat-free mass than on fat mass.

Debate currently exists about optimal infant weight gain. Randomized trials of different infant feeds in preterm and growth-restricted neonates have shown that rapid infant weight gain is associated with increased cardiovascular disease risk factors later in childhood (55), which suggests that rapid weight gain during infancy could be harmful. Our data indicate that associations between early postnatal growth and later body composition may vary according to gestational age at birth and fetal growth rates, and this needs to be investigated further. The findings for full-term infants and those who were not small for gestational age suggest that infancy may be a window of opportunity during which better nutrition and greater BMI gain could increase adult lean mass. Infant weight gain is an important issue in developing countries, where the emphasis is still on eradicating undernutrition and where it is routine practice to encourage weight gain in small infants because of evidence that this increases infant survival (56), prevents stunting (57), and enhances cognitive development (58).

In contrast with the findings in infancy, accelerated BMI gain in later childhood and adolescence was clearly associated with increased adult adiposity and central adiposity. As previously described, it was also associated with an increased risk of impaired glucose tolerance and type 2 diabetes (38). As a population, our subjects had low BMI values in childhood compared with international reference data. Those who went on to develop diabetes had accelerated BMI gain after infancy, becoming "obese relative to themselves," but did not have a high BMI in absolute terms. Efforts to prevent obesity-related disease should start in childhood and should probably target not only children who are frankly overweight or obese but also those who are silently moving up the BMI percentiles. Serial BMI measurements and appropriate local reference standards would be needed to recognize this trajectory. Pediatricians would also need to develop effective ways of preventing children from acquiring excessive adipose tissue without impairing lean mass and skeletal growth.


ACKNOWLEDGMENTS  
We thank the men and women and their families who took part in the study and the field and laboratory staff for their contribution. It is our privilege to acknowledge Shanti Ghosh, Former Professor and Head, Department of Pediatrics, Safdarjang Hospital, New Delhi, and IM Moriyama, former Director at the National Center for Health Statistics, United States, who initiated this study along with Santosh K Bhargava and provided valuable guidance and support throughout its completion up to 1990. We also thank Vinod Kapani for technical input and advice on data analysis. Rajeshwari Verma and Bhaskar Singh provided invaluable assistance in maintaining a liaison with the cohort and in completing the study.

SKB established the original cohort and designed the current study along with CHDF and DJPB. The data were analyzed and interpreted and the manuscript written by HSS, CHDF, and CO. Significant contributions were also made by SDL and SKDB (data collection and analysis), RL (laboratory analyses), and KSR (provision of advice on study design and data interpretation). None of the authors had a financial, commercial, or personal conflict of interest.


REFERENCES  

  1. Prentice AM, Jebb SA. Beyond body mass index. Obes Rev 2001;2:141–7.
  2. WHO/IASO/IOTF. The Asia Pacific perspective: redefining obesity and its treatment. Sydney, Australia: Health Communications Australia Pty Ltd, 2000;18 (Internet: http://www.iotf.org).
  3. WHO Expert Consultation. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet 2004;363:157–63.
  4. McKeigue PM, Shah B, Marmot MG. Relation of central obesity and insulin resistance with high diabetes prevalence and cardiovascular risk in South Asians. Lancet 1991;337:382–6.
  5. Chowdhury B, Lantz H, Sjostrom L. Computed tomography–determined body composition in relation to cardiovascular risk factors in Indian and matched Swedish males. Metabolism 1996;45:634–44.
  6. Banerji MA, Faridi N, Atluri R, Chaiken RL, Lebovitz HE. Body composition, visceral fat, leptin and insulin resistance in Asian Indian men. J Clin Endocrinol Metab 1999;84:137–44.
  7. Chandalia M, Abate N, Garg A, Stray-Gundersen J, Grundy SM. Relationship between generalized and upper body obesity to insulin resistance in Asian Indian men. J Clin Endocrinol Metab 1999;84:2329–35.
  8. Yajnik CS, Yudkin JS. The Y-Y paradox. Lancet 2004;363:163.
  9. Yajnik CS. Obesity epidemic in India: intrauterine origins? Proc Nutr Soc 2004;63:1–10.
  10. Ramachandran A, Snehalatha C, Kapur A, et al. High prevalence of diabetes and impaired glucose tolerance in India: National Urban Diabetes Survey. Diabetologia 2001;44:1094–101.
  11. Ghaffar A, Reddy KS, Singhi M. Burden of non-communicable diseases in South Asia. BMJ 2004;328:807–10.
  12. Wild S, McKeigue P. Cross-sectional analysis of mortality by country of birth in England and Wales, 1970–1992. BMJ 1997;314:705–10.
  13. Dietz WH. Critical periods in childhood for the development of obesity. Am J Clin Nutr 1994;59:955–9.
  14. Eriksson J, Forsen T, Osmond C, Barker DJP. Obesity from cradle to grave. Int J Obes 2003;27:722–7.
  15. Law CM, Shiell AW, Newsome CA, et al. Fetal, infant, and childhood growth and adult blood pressure: a longitudinal study from birth to 22 years of age. Circulation 2002;105:1088–92.
  16. Vanhala M, Vanhala P, Kumpusalo E, Halonen P, Takala J. Relation between obesity from childhood to adulthood and the metabolic syndrome: population based study. BMJ 1998;317:319.
  17. Srinivasan SR, Myers L, Berenson GS. Predictability of childhood adiposity and insulin for developing insulin resistance syndrome (Syndrome X) in young adulthood; the Bogalusa Heart Study. Diabetes 2002;51:204–9.
  18. Eriksson JG, Forsen T, Tuomilehto J, Osmond C, Barker DJP. Early adiposity rebound in childhood and risk of type 2 diabetes in adult life. Diabetologia 2003;46:190–4.
  19. Must A, Jacques PF, Dallal GE, Bajema CJ, Dietz WH. Long-term morbidity and mortality of overweight adolescents: a follow-up of the Harvard Growth Study 1922 to 1935. N Engl J Med 1992;327:1350–5.
  20. Gunnell DJ, Frankel SJ, Nanchahal K, Peters TJ, Davey Smith G. Childhood obesity and adult cardiovascular mortality: a 57 year follow-up study based on the Boyd Orr cohort. Am J Clin Nutr 1998;67:1111–8.
  21. Dietz WH. Childhood weight affects adult morbidity and mortality. J Nutr 1998;128:411S–4S.
  22. Eriksson JG, Forsen T, Tuomilehto HJ, Barker DJP. Early growth and coronary heart disease in later life: longitudinal study. BMJ 2001;322:949–53.
  23. Oken E, Gillman MW. Fetal origins of obesity. Obes Res 2003;11:496–506.
  24. Rogers I. The influence of birthweight and intrauterine environment on adiposity and fat distribution in later life. Int J Obes Relat Metab Disord 2003;27:755–77.
  25. Osmond C, Barker DJP, Winter PD, Fall CHD, Simmonds SJ. Early growth and death from cardiovascular disease in women. BMJ 1993;307:1519–24.
  26. Barker DJP. The fetal origins of coronary heart disease. BMJ 1995;311:171–4.
  27. Hales CN, Barker DJP, Clark PMS, et al. Fetal and infant growth and impaired glucose tolerance at age 64. BMJ 1991;303:1019–22.
  28. Rich-Edwards JW, Stampfer MJ, Mansin J, et al. Birthweight and risk of cardiovascular disease in a cohort of women followed up since 1976. BMJ 1997;315:396–400.
  29. Rich-Edwards JW, Colditz GA, Stampfer MJ, et al. Birthweight and the risk of type 2 diabetes in adult women. Ann Intern Med 1999;130: 278–84.
  30. McCance DR, Pettit DJ, Hanson RL, Jacobsson LDH, Knowler WC, Bennett PH. Birth weight and non-insulin dependent diabetes: thrifty genotype, thrifty phenotype or surviving small baby genotype? BMJ 1994;308:942–5.
  31. Phillips DIW. Relation of fetal growth to adult muscle mass and glucose tolerance. Diabet Med 1995;12:686–90.
  32. Kahn HS, Narayan KMV, Williamson DF, Valdez R. Relation of birthweight to lean and fat thigh tissue in young men. Int J Obes 2000;24:667–72.
  33. Weyer C, Pratley RE, Lindsay RS, Tataranni A. Relationship between birthweight and body composition, energy metabolism and sympathetic nervous system activity later in life. Obes Res 2000;8:559–65.
  34. Gale CR, Martyn CN, Kellingray S, Eastell R, Cooper C. Intrauterine programming of adult body composition. J Clin Endocrinol Metab 2001;86:267–72.
  35. Loos RJF, Beunen G, Fagard R, Derom C, Vlietinck R. Birth weight and body composition in young adult men—prospective twin study. Int J Obes 2001;25:1537–45.
  36. Singhal A, Wells J, Cole TJ, Fewtrell M, Lucas A. Programming of lean body mass: a link between birth weight, obesity and cardiovascular disease? Am J Clin Nutr 2003;77:726–30.
  37. Li H, Stein AD, Barnhardt HX, Ramakrishnan U, Martorell R. Associations between prenatal and postnatal growth and adult body size and composition. Am J Clin Nutr 2003;77:1498–505.
  38. Bhargava SK, Sachdev HPS, Fall CHD, et al. Relation of serial changes in childhood body mass index to impaired glucose tolerance in young adulthood. N Engl J Med 2004;350:865–75.
  39. Energy and protein requirements. Report of a Joint FAO/WHO/UNU Expert Consultation. World Health Organ Tech Rep Ser 1985;724.
  40. World Health Organization. Physical status: the use and interpretation of anthropometry. World Health Organ Tech Rep Ser 1995;854:329.
  41. World Health Organization. Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1: diagnosis and classification of diabetes mellitus. Report of a WHO Consultation. Geneva: World Health Organization, WHO/NCD/NCS/99.2, 1999.
  42. Durnin JV, Womersley J. Body fat assessed from total body density and its estimation from skinfold thickness: measurements on 481 men and women aged from 16 to 72 years. Br J Nutr 1974;32:77–97.
  43. Kuriyan R, Petracchi C, Ferro-Luzzi A, Shetty PS, Kurpad AV. Validation of expedient methods for measuring body composition in Indian adults. Indian J Med Res 1998;107:37–45.
  44. Heymsfield SB, McManus C, Smith J, et al. Anthropometric measurement of muscle mass: revised equations for calculating bone-free arm muscle area. Am J Clin Nutr 1982;36:680–90.
  45. National Centre for Health Statistics. Internet: http://www.cdc.gov/nchs/about/major/nhanes/growthcharts/datafiles.htm (accessed 19 August 2004).
  46. Julius S, Majahalme S, Nesbitt S, et al. A "gender blind" relationship of lean body mass and blood pressure in the Tecumseh study. Am J Hypertens 2002;15:258–63.
  47. Vitasalo JT, Komi PV, Karvonen MJ. Muscle strength and body composition as determinants of blood pressure in young men. Eur J Appl Physiol Occupat Physiol 1979;42:165–73.
  48. Peiris AN, Sothmann MS, Hoffmann RG, et al. Adiposity, fat distribution, and cardiovascular risk. Ann Intern Med 1989;110:867–72.
  49. Haffner SM, Stern MP, Hazuda HP, Pugh J, Patterson JK. Do upper-body and centralized adiposity measure different aspects of regional body-fat distribution? Relationship to non-insulin-dependent diabetes mellitus, lipids, and lipoproteins. Diabetes 1987;36:43–51.
  50. Aihie Sayer A, Syddall HE, Dennison E, et al. Birth weight, weight at 1 year of age, and body composition in older men: findings from the Hertfordshire Cohort Study. Am J Clin Nutr 2004;80:199–203.
  51. Widdowson EM, Crabb DE, Milner RDG. Cellular development of some human organs before birth. Arch Dis Child 1972;47:652–5.
  52. McCance RA. Food, growth and time. Lancet 1962;2:621–6.
  53. Ong KKL, Ahmed ML, Emmett PM, et al. Association between postnatal catch-up growth and obesity in childhood: prospective cohort study. BMJ 2000;320:967–71.
  54. Cameron N, Pettifor J, De Wet T, Norris S. The relationship of rapid weight gain in infancy to obesity and skeletal maturity in childhood. Obes Res 2003;11:457–60.
  55. Singhal A, Lucas A. Early origins of cardiovascular disease: is there a unifying hypothesis? Lancet 2004;363:1642–5.
  56. Victora CG, Barros FC, Horta BL, Martorell R. Short-term benefits of catch-up growth for small-for-gestational-age infants. Int J Epidemiol 2001;30:1325–30.
  57. Shrimpton R, Victora CG, de Onis M, Lima RC, Blossner M, Clugston G. Worldwide timing of growth faltering: implications for nutritional interventions. Pediatrics [serial online] 2001;107:E75. Internet: http://pediatrics.aappublications.org/cgi/content/full/107/5/e75 (accessed 26 May 2005).
  58. Dobbing J. Infant nutrition and later achievement. Am J Clin Nutr 1985;41(suppl):477–84.
Received for publication November 1, 2004. Accepted for publication April 11, 2005.


作者: Harshpal S Sachdev
医学百科App—中西医基础知识学习工具
  • 相关内容
  • 近期更新
  • 热文榜
  • 医学百科App—健康测试工具