Receiver operating characteristics curve analysis of body fat & body mass index in dyslipidaemic Asian Indians

Anoop Misra, R. M. Pandey, S. Sinha, R. Guleria, V. Sridhar, Vikas Dudeja

Research output: Contribution to journalArticle

26 Citations (Scopus)

Abstract

Background & objectives: Optimal limit of body mass index (BMI) for Asian Indians remains to be defined. In this study, we describe the anthropometric and lipid profiles and determine the appropriate cut-offs of BMI for defining obesity in dyslipidaemic patients. Methods: Correlations were carried out between lipid profile and anthropometric variables in 217 dyslipidaemic Asian Indians and the data were compared to those of 123 healthy historical controls. Receiver operating characteristics (ROC) curve analysis was carried out to determine the appropriate cut-offs of BMI for defining obesity taking the percentage of body fat (% BF) as the standard. Results: Dyslipidaemic patients had high waist-hip ratio (W-HR) and percentage of BF. The prevalence of obesity as measured by percentage of BF was significantly (P<0.05) higher as compared to obesity defined by the BMI cut-off. W-HR was the most important independent predictor (odds ratio: 2.8; 95% CI: 1.02-7.83) of atherogenic dyslipidaemia on multivariate logistic regression analysis. On ROC curve analysis the suggested appropriate cut-offs of BMI were; males 24.0 kg/m2 (sensitivity, 74.7%, and specificity, 79.7%), and females 23.0 kg/m2 (sensitivity, 85.7% and specificity, 62.5%). According to the suggested lower limits of BMI, an additional 15 per cent dyslipidaemic patients will be diagnosed as obese. Interpretation & conclusion: The observations in dyslipidaemic Asian Indians suggest high prevalence rates of generalized and abdominal obesity, and that high values of W-HR alone predisposes to atherogenic dyslipidaemia. Further, obesity may be optimally defined by a lower cut-off of BMI. The revised criteria for the BMI-based diagnosis of obesity will lead to a more rational management of dyslipidaemia in Asian Indians.

Original languageEnglish (US)
Pages (from-to)170-179
Number of pages10
JournalIndian Journal of Medical Research
Volume117
Issue numberAPR.
StatePublished - Apr 1 2003
Externally publishedYes

Fingerprint

ROC Curve
Adipose Tissue
Body Mass Index
Fats
Lipids
Correlation methods
Obesity
Regression analysis
Waist-Hip Ratio
Logistics
Dyslipidemias
Sensitivity and Specificity
Abdominal Obesity
Logistic Models
Odds Ratio
Regression Analysis

Keywords

  • Asian Indian
  • Hyperlipidaemia
  • Obesity
  • Percentage body fat
  • Receiver operating characteristics (ROC) curve
  • Skinfolds
  • Waist-hip ratio

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)

Cite this

Receiver operating characteristics curve analysis of body fat & body mass index in dyslipidaemic Asian Indians. / Misra, Anoop; Pandey, R. M.; Sinha, S.; Guleria, R.; Sridhar, V.; Dudeja, Vikas.

In: Indian Journal of Medical Research, Vol. 117, No. APR., 01.04.2003, p. 170-179.

Research output: Contribution to journalArticle

Misra, Anoop ; Pandey, R. M. ; Sinha, S. ; Guleria, R. ; Sridhar, V. ; Dudeja, Vikas. / Receiver operating characteristics curve analysis of body fat & body mass index in dyslipidaemic Asian Indians. In: Indian Journal of Medical Research. 2003 ; Vol. 117, No. APR. pp. 170-179.
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AB - Background & objectives: Optimal limit of body mass index (BMI) for Asian Indians remains to be defined. In this study, we describe the anthropometric and lipid profiles and determine the appropriate cut-offs of BMI for defining obesity in dyslipidaemic patients. Methods: Correlations were carried out between lipid profile and anthropometric variables in 217 dyslipidaemic Asian Indians and the data were compared to those of 123 healthy historical controls. Receiver operating characteristics (ROC) curve analysis was carried out to determine the appropriate cut-offs of BMI for defining obesity taking the percentage of body fat (% BF) as the standard. Results: Dyslipidaemic patients had high waist-hip ratio (W-HR) and percentage of BF. The prevalence of obesity as measured by percentage of BF was significantly (P<0.05) higher as compared to obesity defined by the BMI cut-off. W-HR was the most important independent predictor (odds ratio: 2.8; 95% CI: 1.02-7.83) of atherogenic dyslipidaemia on multivariate logistic regression analysis. On ROC curve analysis the suggested appropriate cut-offs of BMI were; males 24.0 kg/m2 (sensitivity, 74.7%, and specificity, 79.7%), and females 23.0 kg/m2 (sensitivity, 85.7% and specificity, 62.5%). According to the suggested lower limits of BMI, an additional 15 per cent dyslipidaemic patients will be diagnosed as obese. Interpretation & conclusion: The observations in dyslipidaemic Asian Indians suggest high prevalence rates of generalized and abdominal obesity, and that high values of W-HR alone predisposes to atherogenic dyslipidaemia. Further, obesity may be optimally defined by a lower cut-off of BMI. The revised criteria for the BMI-based diagnosis of obesity will lead to a more rational management of dyslipidaemia in Asian Indians.

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