Summary
The objective was to study the relationship between body mass index (BMI) and body fat per cent (BF%) in different population groups of Asians. The study design was a literature overview with ...special attention to recent Asian data. Specific information is provided on Indonesians (Malays and Chinese ancestry), Singaporean Chinese, Malays and Indians, and Hong Kong Chinese. The BMI was calculated from weight and height and the BF% was determined by deuterium oxide dilution, a chemical‐for‐compartment model, or dual‐energy X‐ray absorptiometry. All Asian populations studied had a higher BF% at a lower BMI compared to Caucasians. Generally, for the same BMI their BF% was 3–5% points higher compared to Caucasians. For the same BF% their BMI was 3–4 units lower compared to Caucasians. The high BF% at low BMI can be partly explained by differences in body build, i.e. differences in trunk‐to‐leg‐length ratio and differences in slenderness. Differences in muscularity may also contribute to the different BF%/BMI relationship. Hence, the relationship between BF% and BMI is ethnic‐specific. For comparisons of obesity prevalence between ethnic groups, universal BMI cut‐off points are not appropriate.
Summary
The aim of this study was to investigate the relationship between body mass index (BMI) and body fat percentage (BF%) in Singaporean Chinese, Malays and Indians, and to determine the risk for ...selected comorbidities at various BMI categories and abdominal fat distributions, as assessed by waist circumference (WC). The study was a cross‐sectional (population) design. In total, 4723 subjects participated in the National Health Survey of 1998 in which the risks were investigated. A selected subsample of 291 subjects participated in a detailed body composition study, where weight, height and WC were measured, as were blood pressure, total and high‐density lipoprotein (HDL) cholesterol, serum triglycerides and fasting glucose. In the subsample, BF% was determined by means of a chemical four‐compartment model. At any given BF% the BMI of Singaporeans was about 3 kg m−2 lower than that of Caucasians. There were slight differences in the BF%/BMI relationship between the three ethnic groups. For all the ethnic groups, it was found that at low categories of BMI (between 22 and 24 kg m−2) and WC (between 75 and 80 cm for women and between 80 and 85 cm for men), the absolute risks for having at least one of the aforementioned risk factors were high, ranging from 41 to 81%. At these same categories the relative risks were significantly higher compared to the reference category, odds ratios ranging from 1.97–4.38. These categories of BMI and WC were all far below the cut‐off values of BMI and WC as currently recommended by the World Health Organization (WHO). The data from the current study, which includes evidence that not only risk factors, but also BF% are elevated at low BMI values, presents a strong case for lowering the BMI cut‐off value for overweight and obesity among Singaporeans, from 25 kg m−2 and 30 kg m−2 to 23 kg m−2 and 27 kg m−2, respectively.
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.
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.
Cross-sectional study.
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.
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.
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.
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.
Quantitative ultrasound (QUS) is used to measure bone quality and is known to be safe, radiation free and relatively inexpensive compared with dual-energy X-ray absorptiometry (DXA) that is ...considered the gold standard for bone status assessments. However, there is no consensus regarding the validity of QUS for measuring bone status. The aim of this study was to compare QUS and DXA in assessing bone status in Thai children.
A total of 181 Thai children (90 boys and 91 girls) aged 6 to 12 years were recruited. Bone status was measured by two different techniques in terms of the speed of sound (SOS) using QUS and bone mineral density (BMD) using DXA. Calcium intake was assessed by 24 h diet recall. Pearson's correlation, κ-statistic and Bland and Altman analysis were used to assess the agreement between the methods.
There was no correlation between the two different techniques. Mean difference (s.d.) of the Z-scores of BMD and SOS was -0.61 (1.27) that was different from zero (P<0.05). Tertiles of Z-scores of BMD and QUS showed low agreement (κ 0.022, P=0.677) and the limits of agreement in Bland and Altman statistics were wide.
Although QUS is easy and convenient to use, the SOS measurements at the radius seem not appropriate for assessing bone quality status.
Bioelectrical impedance analysis enables a rapid and safe assessment of body water. When it is assumed that the hydration factor of the fat-free mass is constant and is not different in the obese ...state, then fat-free mass and thus body fat can be assessed with bioelectrical impedance. However, several factors limit the valid application of bioelectrical impedance analysis in the severely obese state. One is the assumption of a constant hydration factor. Furthermore, body geometry is different in the obese state and body water distribution may also be different. All these factors have an effect on the validity of the method in the severely obese state, for which the amount of body fat generally will be underestimated with use of prediction formulas developed in normal-weight subjects. I discuss these limiting factors and provide some theoretical background.
To compare the relationship between body mass index (BMI) and body fat percentage (BF%) in children of different ethnic background.
Cross-sectional observational study.
The study was performed in ...three different locations, Singapore, Beijing and Wageningen (The Netherlands).
In each centre 25 boys and 25 girls, aged 7-12 y, were selected. They were matched on age, sex and body height.
Body weight and body height was measured following standardized procedures. The body mass index (BMI) was calculated as weight/height squared (kg/m(2)). Body fat was measured by densitometry in Beijing and Wageningen and by dual energy X-ray absorptiometry (DXA) in Singapore. The DXA measurements in Singapore were validated against densitometry.
There were no significant differences in BF% or BMI within each gender group across the three study sites. However, after controlling for (non-significant) differences in age and BF%, the Singapore children had a lower (mean+/-s.e.) BMI (15.6+/-0.3) than the Beijing 17.6+/-0.3) and Wageningen (16.9+/-0.3) children. For the same BMI, age and sex the Singapore children had a significant higher BF% (24.6+/-0.7) than the Beijing (19.2+/-0.8) and Wageningen (20.3+/-0.7) children.
The study strongly suggests that the relationship between BF% and BMI (or weight and height) is different among children of different ethnic background. Consequently growth charts and BMI cut-off points for underweight, overweight and obesity in children may have to be ethnic-specific.
The objective of the study was to test the hypothesis that differences in the relationship between percent body fat (%BF) and body mass index (BMI) between populations can be explained (in part) by ...differences in body build.
Cross-sectional, comparative study.
120 age, gender and BMI matched Singapore Chinese, Beijing Chinese and Dutch (Wageningen) Caucasians.
From body weight and body height, BMI was calculated. Relative sitting height (sitting height/height) was used as a measure of relative leg length. Body fat was determined using densitometry (underwater weighing) in Beijing and Wageningen and using a three-compartment model based on densitometry and hydrometry in Singapore. Wrist and knee widths were measured as indicators for frame size and skeletal mass was calculated based on height, wrist and knee width. In addition, a slenderness index (height/sum of wrist and knee width) was calculated.
For the same BMI, Singapore Chinese had the highest %BF followed by Beijing Chinese and the Dutch Caucasians. Singaporean Chinese had a more slender frame than Beijing Chinese and Dutch Caucasians. Predicted %BF from BMI, using a Caucasian prediction formula, was not different from measured %BF in Wageningen and in Beijing, but in Singapore the formula underpredicted %BF by 4.0 +/- 0.8% (mean +/- s.e.m.) compared to Wageningen. The difference between measured and predicted %BF (bias) was related to the level of %BF and with measures of body build, especially slenderness. Correction for differences in %BF, slenderness and relative sitting height, decreased the differences between measured and predicted values compared to the Dutch group from 1.4 +/- 0.8 (not statistically significant, NS) to -0.2 +/- 0.5 (NS) in Beijing and from 4.0 +/- 0.8 (P < 0.05) to 0.3 +/- 0.5 (NS) in Singapore (all values mean +/- s.e.m.).
The study results confirm the hypothesis that differences in body build are at least partly responsible for a different relationship between BMI and %BF among different (ethnic) groups.
To test the impact of body build factors on the validity of impedance-based body composition predictions across (ethnic) population groups and to study the suitability of segmental impedance ...measurements.
Cross-sectional observational study.
Ministry of Health and School of Physical Education, Nanyang Technological University, Singapore.
A total of 291 female and male Chinese, Malays and Indian Singaporeans, aged 18-69, body mass index (BMI) 16.0-40.2 kg/ m2.
Anthropometric parameters were measured in addition to impedance (100 kHz) of the total body, arms and legs. Impedance indexes were calculated as height2/impedance. Arm length (span) and leg length (sitting height), wrist and knee width were measured from which body build indices were calculated. Total body water (TBW) was measured using deuterium oxide dilution. Extra cellular water (ECW) was measured using bromide dilution. Body fat percentage was determined using a chemical four-compartment model.
The bias of TBW predicted from total body impedance index (bias: measured minus predicted TBW) was different among the three ethnic groups, TBW being significantly underestimated in Indians compared to Chinese and Malays. This bias was found to be dependent on body water distribution (ECW/TBW) and parameters of body build, mainly relative (to height) arm length. After correcting for differences in body water distribution and body build parameters the differences in bias across the ethnic groups disappeared. The impedance index using total body impedance was better correlated with TBW than the impedance index of arm or leg impedance, even after corrections for body build parameters.
The study shows that ethnic-specific bias of impedance-based prediction formulas for body composition is due mainly to differences in body build among the ethnic groups. This means that the use of 'general' prediction equations across different (ethnic) population groups without prior testing of their validity should be avoided. Total body impedance has higher predictive value than segmental impedance.
PDF
