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.
Body fat percent (BF%) was measured in 108 adult Chinese, 76 Malays, and 107 Indians in Singapore by densitometry, deuterium oxide dilution (hydrometry), dual energy x-ray absorptiometry (DXA) and a chemical four-compartment model (BF%4c). The hydration of the fat-free mass (FFM) was calculated. Subjects ranged in age from 18 to 69 years and their body mass index ranged from 16 to 40 kg/m2. BF%4c for the various subgroups were: Chinese females (33.5 +/- 7.5%), Chinese males (24.4 +/- 6.1%), Malay females (37.8 +/- 6.3%), Malay males (26.0 +/- 7.6%), Indian females (38.2 +/- 7.0%) and Indian males (28.1 +/- 5.5%). Biases were found between BF%4c and BF% measured by 2-compartment models (hydrometry, densitometry, DXA), with systematic underestimation by DXA and densitometry. On a group level hydrometry had the lowest bias while DXA gave the highest bias. When validated against BF%4c, 2-compartment models were found to be unsuitable for accurate measures of body fat due to high biases at the individual level and the violation of assumptions of constant hydration of FFM and density FFM among the ethnic groups. On a group level the best 2-compartment model for measuring body fat was found to be hydrometry.
This paper describes body composition and dietary intakes of the three major ethnic groups residing in Singapore and how these are related to cardiovascular risk factors in these groups. When the relationship between body mass index (BMI, kg/m2) and body fat percentage was studied, Singaporeans were found to have higher percentage of body fat compared with Caucasians with the same BMI. At BMIs that are much lower than WHO-recommended cut-off values for obesity, both the absolute and relative risks of developing cardiovascular risk factors are markedly elevated for all three ethnic groups. The excessive fat accumulation and increased risks at lower BMIs signal a need to re-examine cut-off values for obesity among Chinese, Malays, and Indians.
Body fat percentage (BF%) was measured in 298 Singaporean Chinese, Malay and Indian men and women using a chemical four-compartment model consisting of fat, water, protein and mineral (BF%4C). In addition, weight, height, skinfold thickness and segmental impedance (from hand to hand) was measured. Body fat percentage was predicted using prediction equations from the literature (for skinfolds BF%SKFD) and using the manufacturer's software for the hand-held impedance analyser (BF%IMP). The subjects ranged in age from 18-70 years and in body mass index from 16.0 to 40.2 kg/m2. Body fat ranged from 6.5 to 53.3%. The biases for skinfold prediction (BF%4C-BF%SKFD, mean +/- SD) were -0.4+/-3.9, 2.3+/-4.1 and 3.1+/-4.2 in Chinese, Malay and Indian women, respectively, the Chinese being different from the Malays and Indians. The differences were significant from zero (P < 0.05) in the Malays and Indians. For the men, the biases were 0.5+/-3.8, 0.0+/-4.8 and 0.9+/-4.0 in Chinese, Malays and Indians, respectively. These biases were not significantly different from zero and not different among the ethnic groups. The biases for hand-held impedance BF% were -0.7+/-4.5, 1.5+/-4.4 and 0.4+/-3.8 in Chinese, Malay and Indian women. These biases were not significantly different from zero but the bias in the Chinese was significantly different from the biases in the Malays and Indians. In the Chinese, Malay and Indian men, the biases of BF%IMP were 0.7+/-4.6, 1.9+/-4.8 and 2.0+/-4.4, respectively. These biases in Malay and Indian men were significantly different from zero and significantly different from the bias in Chinese men. The biases were correlated with level of body fat and age, and also with relative arm span (arm span/height) for impedance. After correction, the differences in bias among the ethnic groups disappeared. The study shows that the biases in predicted BF% differ between ethnic groups, differences that can be explained by differences in body composition and differences in body build. This information is important and should be taken into account when comparing body composition across ethnic groups using predictive methods.
OBJECTIVE: To study the relationship between body fat percentage and body mass index (BMI) in three different ethnic groups in Singapore (Chinese, Malays and Indians) in order to evaluate the validity of the BMI cut-off points for obesity.
DESIGN: Cross-sectional study.
SUBJECTS: Two-hundred and ninety-one subjects, purposively selected to ensure adequate representation of range of age and BMI of the general adult population, with almost equal numbers from each ethnic and gender group.
MEASUREMENTS: Body weight, body height, sitting height, wrist and femoral widths, skinfold thicknesses, total body water by deuterium oxide dilution, densitometry with Bodpod(R) and bone mineral content with Hologic(R) QDR-4500. Body fat percentage was calculated using a four-compartment model.
RESULTS: Compared with body fat percentage (BF%) obtained using the reference method, BF% for the Singaporean Chinese, Malays and Indians were under-predicted by BMI, sex and age when an equation developed in a Caucasian population was used. The mean prediction error ranged from 2.7% to 5.6% body fat. The BMI/BF% relationship was also different among the three Singaporean groups, with Indians having the highest BF% and Chinese the lowest for the same BMI. These differences could be ascribed to differences in body build. It was also found that for the same amount of body fat as Caucasians who have a body mass index (BMI) of 30 kg/m2 (cut-off for obesity as defined by WHO), the BMI cut-off points for obesity would have to be about 27 kg/m2 for Chinese and Malays and 26 kg/m2 for Indians.
CONCLUSIONS: The results show that the relationship between BF% and BMI is different between Singaporeans and Caucasians and also among the three ethnic groups in Singapore. If obesity is regarded as an excess of body fat and not as an excess of weight (increased BMI), the cut-off points for obesity in Singapore based on the BMI would need to be lowered. This would have immense public health implications in terms of policy related to obesity prevention and management.
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.
The National Breastfeeding Survey 2001 was the first comprehensive study on breastfeeding conducted on a national level in Singapore. It aimed to establish the prevalence of breastfeeding among Chinese, Malay and Indian mothers and to identify factors influencing breastfeeding. A total of 2098 mothers were interviewed in this two-phase study, with the first interview conducted 2 months after delivery and the second interview 6 months after birth among mothers who were still breastfeeding at 2 months. Frequency distributions of breastfeeding prevalence and types of breastfeeding practices at different time intervals (from birth to 6 months) were produced. Multivariate logistic regression was carried out to construct a model with predictive information on factors which influence continued breastfeeding till 2 months and 6 months after delivery respectively. The study found that about 94.5% of the mothers attempted breastfeeding. At 1 month, 71.6% were still breastfeeding, 49.6% continued to do so at 2 months, and 29.8% persisted till 4 months. By 6 months, the breastfeeding prevalence rate fell to 21.1%. The results of this study show higher breastfeeding prevalence rates compared to past studies in Singapore. Despite this, exclusive breastfeeding is still not a common practice. Various factors were found to be significant in influencing mothers' decision to breastfeed. Factors such as ethnicity, age, educational attainment, religion and baby's sex are non-modifiable in the short term or at an individual level. However, factors such as awareness of breastfeeding benefits, advice from health professionals and previous breastfeeding experience are potentially modifiable. Efforts aimed at promoting breastfeeding in Singapore need to take these modifiable factors into consideration so as to better tailor health promotion efforts on breastfeeding to women.
OBJECTIVE: To investigate the effect of body mass index (BMI) and body fat distribution as measured by waist-to-hip ratio (WHR) on the cardiovascular risk factor profile of the three major ethnic groups in Singapore (Chinese, Malay and Indian people) and to determine if WHO recommended cut-off values for BMI and WHR are appropriate for the different sub-populations in Singapore.
DESIGN: Cross-sectional population study.
SUBJECTS: A total of 4723 adult subjects (64% Chinese individuals, 21% Malay individuals and 15% Indian individuals) were selected through a multi-staged sampling technique to take part in the National Health Survey in 1998.
MEASUREMENTS: Data on socio-economic status (education level, occupation, housing type) and lifestyle habits (smoking and physical activity), body weight, body height, waist and hip circumferences and blood pressure measured using standardised protocols. Fasting venous blood samples were obtained for determination of serum total cholesterol (TC), high density lipoprotein cholesterol (HDL), low density lipoprotein cholesterol (LDL), triglycerides (TG). Venous blood samples were taken for 2 h oral glucose tolerance test (2 h glu).
RESULTS: Absolute and relative risks for at least one cardiovascular risk factor (elevated TC, elevated TC/HDL ratio, elevated TG, hypertension and diabetes mellitus) were determined for various categories of BMI and WHR. At low categories of BMI (BMI between 22 and 24 kg/m(2)) and WHR (WHR between 0.80 and 0.85 for women, and between 0.90 and 0.95 for men), the absolute risks are high, ranging from 41 to 81%. At these same categories the relative risks are significantly higher compared to the reference category, ranging from odds ratio of 1.97 to 4.38. These categories of BMI and WHR are all below the cut-off values of BMI and WHR recommended by WHO.
CONCLUSIONS: The results show that, at relatively low BMI and WHR, Singaporean adults experience elevated levels of risks (absolute and relative) for cardiovascular risk factors. These findings, in addition to earlier reported high percentage body fat among Singaporeans at low levels of BMI, confirm the need to revise the WHO cut-off values for the various indices of obesity and fat distribution, viz BMI and WHR, in Singapore.
We have previously reported an interaction between -514C>T polymorphism at the hepatic lipase (HL) gene and dietary fat on high-density lipoprotein-cholesterol (HDL-C) metabolism in a representative sample of white subjects participating in the Framingham Heart Study. Replication of these findings in other populations will provide proof for the relevance and consistency of this marker as a tool for risk assessment and more personalized cardiovascular disease prevention. Therefore, we examined this gene-nutrient interaction in a representative sample of Singaporeans (1324 Chinese, 471 Malays and 375 Asian Indians) whose dietary fat intake was recorded by a validated questionnaire. When no stratification by fat intake was considered, the T allele was associated with higher plasma HDL-C concentrations (P = 0.001), higher triglyceride (TG) concentrations (P = 0.001) and higher HDL-C/TG ratios (P = 0.041). We found a highly significant interaction (P = 0.001) between polymorphism and fat intake in determining TG concentration and the HDL-C/TG ratio (P = 0.001) in the overall sample even after adjustment for potential confounders. Thus, TT subjects showed higher TG concentrations only when fat intake supplied >30% of total energy. This interaction was also found when fat intake was considered as continuous (P = 0.035). Moreover, in the upper tertile of fat intake, TT subjects had 45% more TG than CC individuals (P < 0.01). For HDL-C concentration, the gene-diet interaction was significant (P = 0.015) only in subjects of Indian origin. In conclusion, our results indicate that there are differences in the association of -514C>T polymorphism with plasma lipids according to dietary intake and ethnic background. Specifically, the TT genotype is associated with a more atherogenic lipid profile when subjects consume diets with a fat content > 30%.
In Singapore. there exists differences in risk factors for coronary heart disease among the three main ethnic groups: Chinese, Malays and Indians. This study aimed to investigate if differences in dietary intakes of fat, types of fat, cholesterol, fruits, vegetables and grain foods could explain the differences in serum cholesterol levels between the ethnic groups. A total of 2408 adult subjects (61.0% Chinese, 21.4% Malays and 17.6% Indians) were selected systematically from the subjects who took part in the National Health Survey in 1998. The design of the study was based on a cross-sectional study. A food frequency questionnaire was used to assess intakes of energy, total fat, saturated fat, polyunsaturated fat, monounsaturated fat, cholesterol, fruits, vegetables and cereal-based foods. The Hegsted score was calculated. Serum total cholesterol, low density lipoprotein cholesterol, high density lipoprotein cholesterol were analysed and the ratio of total cholesterol to high density lipoprotein cholesterol was computed. The results showed that on a group level (six sex-ethnic groups), Hegsted score, dietary intakes of fat, satutrated fat, cholesterol, vegetables and grain foods were found to be correlated to serum cholesterol levels. However, selected dietary factors did not explain the differences in serum cholesterol levels between ethnic groups when multivariate regression analysis was performed, with adjustment for age, body mass index, waist-hip ratio, cigarette smoking, occupation, education level and physical activity level. This cross-sectional study shows that while selected dietary factors are correlated to serum cholesterol at a group level, they do not explain the differences in serum cholesterol levels between ethnic groups independently of age, obesity, occupation, educational level and other lifestyle risk factors.