The paradox of low body mass index and high body fat percentage among Chinese, Malays and Indians in Singapore

Deurenberg-Yap, Mabel; Schmidt, Günter; Staveren, W.A. van; Deurenberg, P.

doi:10.1038/sj.ijo.0801353

Cited by 469 publications

(405 citation statements)

References 25 publications

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“…First, BMI does not reflect fatness uniformly in all populations and different ethnic groups 939–41. The previous Omani study indicated that WHR and WC better predict CVD risk than BMI 3233.…”

Section: Discussionmentioning

confidence: 98%

Performance of body mass index in predicting diabetes and hypertension in the Eastern Province of Saudi Arabia

Almajwal

Al-Baghli

Batterham

et al. 2009

Annals of Saudi Medicine

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BACKGROUND AND OBJECTIVES:Body mass index (BMI) is the most widely used measure to define obesity and predict its complications, such as diabetes and hypertension, but its accuracy and usefulness in Saudi subjects is unknown. This study aimed to assess the validity of standard BMI cut-point values in the Saudi population.SUBJECTS AND METHODS:197 681 adults participated in a cross-sectional study to detect diabetes and hypertension in the Saudi Eastern province in 2004/2005, with blood pressure, fasting blood sugar, height and weight measurements taken. Sensitivities, specificities, areas under the curves, predictive values, likelihood ratios, false positive, false negatives and total misclassification ratios were calculated for various BMI values determined from receiver operating characteristic (ROC) curves. The significance of the association between risk factors and BMI was assessed using regression analysis.RESULTS:For the definition of overweight, ROC curve analysis suggested optimal BMI cut-offs of 28.50 to 29.50 in men and 30.50 to 31.50 in women, but the levels of sensitivity and specificity were too low to be of clinical value and the overall misclassification was unacceptably high across all the selected BMI values (>0.80). The relationship between BMI and the presence of diabetes and/or hypertension was not improved when a BMI of 25 was used. Using regression analyses, the odds ratios for hypertension and/or diabetes increased significantly from BMI values as low as 21-23 with no improvement in the diagnostic performance of BMI at these cutoffs.CONCLUSION:In Saudi population, there is an increased risk of diabetes and hypertension relative to BMI, starting at a BMI as low as 21 but overall there is no cutoff BMI level with high predictive value for the development of these chronic diseases, including the WHO definition of obesity at BMI of 30.

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Section: Discussionmentioning

confidence: 98%

Performance of body mass index in predicting diabetes and hypertension in the Eastern Province of Saudi Arabia

Almajwal

Al-Baghli

Batterham

et al. 2009

Annals of Saudi Medicine

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“…The data collected on smoking, physical activity, and diet from the self‐administered questionnaires may be subject to recall bias. Future modifications of the LS7 metrics could make BMI specific for each racial/ethnic group because some studies have demonstrated that Asians are at a higher risk of weight‐related diseases, such as CVDs, at lower BMIs 37, 38, 39, 40…”

Section: Discussionmentioning

confidence: 99%

Life's Simple 7 and Incident Heart Failure: The Multi‐Ethnic Study of Atherosclerosis

Ogunmoroti

Oni

Michos

et al. 2017

JAHA

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BackgroundThe American Heart Association introduced the Life's Simple 7 (LS7) metrics to assess and promote cardiovascular health. We sought to examine the association between the LS7 metrics and incident heart failure (HF) in a multiethnic cohort.Methods and ResultsWe analyzed data from 6506 participants of the Multi‐Ethnic Study of Atherosclerosis free of cardiovascular disease at baseline. The LS7 metrics (smoking, physical activity, body mass index, diet, blood pressure, total cholesterol, and blood glucose) were graded on a scale of 0 to 2, with 2 indicating “ideal” status, 1 “intermediate” status, and 0 “poor” status. Points were summed, thus the LS7 score ranged from 0 to 14. Cox proportional hazard ratios and incidence rates of HF per 1000 person‐years were calculated. During a median follow‐up of 12.2 years, 262 (4%) participants developed HF. Incidence of HF decreased as the number of ideal LS7 metrics increased; 5.9 per 1000 person‐years for participants with 0 to 1 ideal metrics and 0.6 per 1000 person‐years for those with 6 to 7 ideal metrics. Compared with inadequate scores (0–8 points), hazard ratios for HF were 0.57 (0.43–0.76) and 0.31 (0.19–0.49) for average (9–10 points) and optimal (11–14 points) scores, respectively. A similar pattern was observed when the results were stratified by 4 racial/ethnic groups: white, Chinese American, black, and Hispanic.ConclusionsA lower risk of HF with more favorable LS7 status regardless of race/ethnicity suggests that efforts to achieve ideal cardiovascular health may reduce the burden of HF, a major source of morbidity and mortality.

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“…For any given BMI, some populations are fatter and have a more central fat distribution. 20 This has led to the recent adoption of population-specific BMI cutoff points to define obesity in some adult populations. The research on this question in children and adolescents is less advanced, but it seems likely that such population differences are not confined to adulthood.…”

Section: Evidence Base On the Comorbidities Of High Bmi For Agementioning

confidence: 99%

“…The research on this question in children and adolescents is less advanced, but it seems likely that such population differences are not confined to adulthood. 11,14,20 Ultimately, population-specific BMI cutoffs may therefore become necessary for children and adolescents. 11,14,20 Barriers to use of the BMI for age…”

Section: Evidence Base On the Comorbidities Of High Bmi For Agementioning

confidence: 99%

Diagnostic accuracy of the BMI for age in paediatrics

Reilly

2006

Int J Obes

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Must and Anderson,1 in this issue of the journal, have described the basis of body mass index (BMI) for age for the assessment of weight status in children and adolescents. The aims of this short article are to summarise the evidence base on the diagnostic accuracy of BMI, and to expand on what we achieve when defining paediatric obesity on the basis of a high BMI for age. A high BMI for age is not 'obesity' (a high body fat content associated with increased morbidity), per se but a diagnostic test for obesity. Similarly, in adults a BMI>30 kg/m2 is not obesity, but a positive diagnostic test for obesity. It is also widely stated that 'BMI does not predict body fat content accurately'. This is true,2, 3, 4, 5 but should not be used to damn the diagnostic ability of BMI because it is not directly relevant to the issue of diagnosis of obesity. When diagnosing or defining obesity, we do not need to estimate body fat content precisely; rather we simply need to establish with confidence that any child defined as obese has a high body fat content relative to his/her peers. There are two main components to the issue of diagnostic accuracy: how well does a high BMI for age diagnose the fattest children in the population? Are children at high BMI for age at greater risk of morbidity than their peers at lower BMI for age

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The paradox of low body mass index and high body fat percentage among Chinese, Malays and Indians in Singapore

Cited by 469 publications

References 25 publications

Performance of body mass index in predicting diabetes and hypertension in the Eastern Province of Saudi Arabia

Performance of body mass index in predicting diabetes and hypertension in the Eastern Province of Saudi Arabia

Life's Simple 7 and Incident Heart Failure: The Multi‐Ethnic Study of Atherosclerosis

Diagnostic accuracy of the BMI for age in paediatrics

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