A child's growth achievement depends on his genetic endowment and the environment in which he lives; Comparative studies of children of similar racial origin but growing under different environmental conditions have shown differences in their body size and shape. In general higher income families produce offspring with higher mean birth weight. This is largely due to better nutrition and care of mothers during pregnancy and childhood. Children from higher socioeconomic groups are on an average larger in size in terms of weight, height, head circumference, midarm circumference, crown-rump length and leg length. This is largely due to a better home environment including sanitation, nutrition, health and care enjoyed by the better-off children. .Generally urban children are larger than rural children mainly due to economic differences between the two areas. In most countries the secular trend to children getting larger still continues reflecting an improvement of living conditions with time. Unlike body size, body shape is less influenced by the environment and the change in body proportion brought about by environment is not permanent. In developing countries, children from higher socioeconomic families have generally thicker skinfolds. On the average, infants and preschool children of European ancestry have thicker triceps skinfolds compared with Negroes and Asians living in comparable environments. It is possible that this is due to long term adaptation to different climatic conditions.
This study was conducted to determine the mRNA and protein expression levels of peroxisome proliferator-activated receptors (PPARs) in visceral adipose tissue, as well as serum adipokine levels, in Sprague Dawley rats. The rats were fed either a normal (control rats) or excessive (experimental rats) intake of food for 8 or 16 weeks, then sacrificed, at which time visceral and subcutaneous adipose tissues, as well as blood samples, were collected. The mRNA and protein expression levels of PPARs in the visceral adipose tissues were determined using reverse transcription-polymerase chain reaction and Western blotting, respectively. In addition, the levels of adipokines in the serum samples were determined using commercial ELISA kits. The results revealed that at 8 weeks, the mass of subcutaneous adipose tissue was higher than that of the visceral adipose tissue in the experimental rats, but the reverse occurred at 16 weeks. Furthermore, at 16 weeks the experimental rats exhibited an upregulation of PPARγ mRNA and protein expression levels in the visceral adipose tissues, and significant increases in the serum levels of CCL2 and interleukin (IL)-6 were observed, compared with those measured at 8 weeks. In conclusion, this study demonstrated that the PPARγ expression level was likely correlated with serum levels of CCL2 and IL-6, molecules that may facilitate visceral adipose tissue accumulation. In addition, the levels of the two adipokines in the serum may be useful as surrogate biomarkers for the expression levels of PPARγ in accumulated visceral adipose tissues.
Most in vivo body composition methods rely on assumptions that may vary among different population groups as well as within the same population group. The assumptions are based on in vitro body composition (carcass) analyses. The majority of body composition studies were performed on Caucasians and much of the information on validity methods and assumptions were available only for this ethnic group. It is assumed that these assumptions are also valid for other ethnic groups. However, if apparent differences across ethnic groups in body composition 'constants' and body composition 'rules' are not taken into account, biased information on body composition will be the result. This in turn may lead to misclassification of obesity or underweight at an individual as well as a population level. There is a need for more cross-ethnic population studies on body composition. Those studies should be carried out carefully, with adequate methodology and standardization for the obtained information to be valuable.
This study aimed to evaluate changes in maternal adiposity and lipid profile and to correlate these parameters with Deoxyribonucleic acid (DNA) damage and total antioxidant capacity (TAC) levels among pregnant women.
This cross-sectional study compared body fat percentage (BF%) obtained from a four-compartment (4C) model with BF% from hydrometry (using 2H2O), dual-energy X-ray absorptiometry (DXA) and densitometry among the three main ethnic groups (Chinese, Malays and Indians) in Singapore, and determined the suitability of two-compartment (2C) models as surrogate methods for assessing BF% among different ethnic groups. A total of 291 subjects (108 Chinese, seventy-six Malays, 107 Indians) were selected to ensure an adequate representation of age range (18-75 years) and BMI range (16-40 kg/m2) of the general adult population, with almost equal numbers from each gender group. Body weight was measured, together with body height, total body water by 2H2O dilution, densitometry with Bodpod and bone mineral content with Hologic QDR-4500. BF% measurements with a 4C model for the subgroups were: Chinese females 33.5 (sd 7.5), Chinese males 24.4 (sd 6.1), Malay females 37.8 (sd 6.3), Malay males 26.0 (sd 7.6), Indian females 38.2 (sd 7.0), Indian males 28.1 (sd 5.5). Differences between BF% measured by the 4C and 2C models (hydrometry, DXA and densitometry) were found, with underestimation of BF% in all the ethnic-gender groups by DXA of 2.1-4.2 BF% and by densitometry of 0.5-3.2 BF%). On a group level, the differences in BF% between the 4C model and 2H2O were the lowest (0.0-1.4 BF% in the different groups), while differences between the 4C model and DXA were the highest. Differences between the 4C model and 2H2O and between the 4C model and DXA were positively correlated with the 4C model, water fraction (f(water)) of fat-free mass (FFM) and the mineral fraction (f(mineral)) of FFM, and negatively correlated with density of the FFM (D(FFM)), while the difference between 4C model and densitometry correlated with these variables negatively and positively respectively (i.e. the correlations were opposite). The largest contributors to the observed differences were f(water) and D(FFM). When validated against the reference 4C model, 2C models were found to be unsuitable for accurate measurements of BF% at the individual level, owing to the high errors and violation of assumptions of constant hydration of FFM and D(FFM) among the ethnic groups. On a group level, the best 2C model for measuring BF% among Singaporeans was found to be 2H2O.