Dataset Information

Comparison of various anthropometric and body fat indices in identifying cardiometabolic disturbances in Chinese men and women.

ABSTRACT:

Background

Although many adiposity indices may be used to predict obesity-related health risks, uncertainty remains over which of them performs best.

Objective

This study compared the predictive capability of direct and indirect adiposity measures in identifying people at higher risk of metabolic abnormalities.

Methods

This population-based cross-sectional study recruited 2780 women and 1160 men. Body weight and height, waist circumference (WC), and hip circumference (HC) were measured and body mass index (BMI), waist-to-hip ratio (WHR), and waist-to-height ratio (WHtR) were calculated. Body fat (and percentage of fat) over the whole body and the trunk were determined by bioelectrical impedance analysis (BIA). Blood pressure, fasting lipid profiles, and glucose and urine acid levels were assessed.

Results

In women, the ROC and the multivariate logistic regression analyses both showed that WHtR consistently had the best performance in identifying hypertension, dyslipidemia, hyperuricemia, diabetes/IFG, and metabolic syndrome (MetS). In men, the ROC analysis showed that WHtR was the best predictor of hypertension, WHtR and WC were equally good predictors of dyslipidemia and MetS, and WHtR was the second-best predictor of hyperuricemia and diabetes/IFG. The multivariate logistic regression also found WHtR to be superior in discriminating between MetS, diabetes/IFG, and dyslipidemia while BMI performed better in predicting hypertension and hyperuricemia in men. The BIA-derived indices were the second-worst predictors for all of the endpoints, and HC was the worst.

Conclusion

WHtR was the best predictor of various metabolic abnormalities. BMI may be used as an alternative measure of obesity for identifying hypertension in both sexes.

SUBMITTER: Zhang ZQ

PROVIDER: S-EPMC3741370 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Publications

Comparison of various anthropometric and body fat indices in identifying cardiometabolic disturbances in Chinese men and women.

Zhang Zhe-qing ZQ Deng Juan J He Li-ping LP Ling Wen-hua WH Su Yi-xiang YX Chen Yu-ming YM

PloS one 20130812 8

<h4>Background</h4>Although many adiposity indices may be used to predict obesity-related health risks, uncertainty remains over which of them performs best.<h4>Objective</h4>This study compared the predictive capability of direct and indirect adiposity measures in identifying people at higher risk of metabolic abnormalities.<h4>Methods</h4>This population-based cross-sectional study recruited 2780 women and 1160 men. Body weight and height, waist circumference (WC), and hip circumference (HC) w ...[more]

PMID: 23951031

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Project description:ObjectivesWe aim to compare the efficacies of the bioelectrical indices (percentage of body fat, PBF; visceral fat area, VFA) with the conventional anthropometric measures (body mass index, BMI; waist-hip ratio, WHR) for predicting type 2 diabetes (T2D) risk by sex and to determine the sex-specific optimal adiposity indices to predict the T2D risk.DesignCross-sectional design.SettingTianjin First Central Hospital and Tianjin Union Medical Center, Tianjin, China.ParticipantsA total of 9,332 adults (41.35% men) undergoing physical examination.Primary and secondary outcome measuresT2D was defined using the WHO's criteria: fasting blood glucose (FBG) ≥7.0 mmol/L and/or previous diagnosis of T2D. Height, weight, waist, hip, PBF, VFA, and fasting plasma glucose were measured.ResultsAll studied adiposity indices were associated with T2D among both males and females, and the observed associations differed by sex. The standardized aORs of BMI, WHR, PBF and VFA for T2D were 1.60 (95% CI 1.42-1.81), 1.43 (95% CI 1.25-1.64), 1.42 (95% CI 1.23-1.62) and 1.53 (95% CI 1.35-1.75) for females, and 1.47 (95% CI 1.31-1.66), 1.40 (95% CI 1.25-1.58), 1.54 (95% CI 1.36-1.74) and 1.47 (95% CI 1.31-1.65) for males, respectively. The AUCs of VFA, WHR and BMI were 0.743, 0.742 and 0.717 in women, respectively, whereas none of the indices had AUC larger than 0.70 in men. The AUCs were not significantly different between VFA and WHR, while both demonstrate larger AUCs than BMI and PBF in females (all p < 0.05). The optimal cutoff values of VFA, WHR, and BMI for T2D in women were 103.55 cm2, 0.905, and 24.15 kg/m2, respectively.ConclusionAlthough BMI, WHR, and PBF and VFA as measured by bioelectrical impedance analysis (BIA) were all positively associated with T2D, their efficacy for predicting the risk of T2D differed by sex. VFA, WHR and BMI could be used as biomarkers to predict T2D risk in women, however none of the study indicators demonstrated favorable efficacy of predicting T2D risk in men.

Project description:The body mass index (BMI) and waist circumference (WC) are commonly used anthropometric measures for predicting cardiovascular diseases risk factors, but it is uncertain which specific measure might be the most appropriate predictor of a cluster of cardiometabolic abnormalities (CMA) in Chinese adults. A body shape index (ABSI) and body roundness index (BRI) have been recently developed as alternative anthropometric indices that may better reflect health status. The main aims of this study were to investigate the predictive capacity of ABSI and BRI in identifying various CMA compared to BMI, WC, waist-to-hip ratio (WHpR), and waist-to-height ratio (WHtR), and to determine whether there exists a best single predictor of all CMA.We used data from the 2009 wave of the China Health and Nutrition Survey, and the final analysis included 8126 adults aged 18 to 85 years with available fasting blood samples and anthropometric measurements. Receiver-operating characteristic (ROC) analyses were conducted to assess the best anthropometric indices to predict the risk of hypertension, diabetes, dyslipidemia, hyperuricemia, and metabolic syndrome (MetS). Logistic regression models were fit to evaluate the OR of each CMA according to anthropometric indices.In women, the ROC analysis showed that BRI and WHtR had the best predictive capability in identifying all of CMA (area under the curves [AUCs] ranged from 0.658 to 0.721). In men, BRI and WHtR were better predictor of hypertension, diabetes, and at least 1 CMA (AUC: 0.668, 0.708, and 0.698, respectively), whereas BMI and WC were more sensitive predictor of dyslipidemia, hyperuricemia, and MetS. Furthermore, the ABSI showed the lowest AUCs for each CMA. According to the multivariate logistic regression analysis, BRI and WHtR were superior in discriminating hyperuricemia and at least 1 CMA while BMI performed better in predicting hypertension, diabetes, and MetS in women. In men, WC and BRI were the 2 best predictor of all CMA except MetS, and the ABSI was the worst.Our results showed the novel index BRI could be used as a single suitable anthropometric measure in simultaneously identifying a cluster of CMA compared to BMI and WHtR, especially in Chinese women, whereas the ABSI showed the weakest discriminative power.

Project description:OBJECTIVES:This study aimed to assess the accuracy of body mass index (BMI) percentile, waist circumference (WC) percentile, waist-height ratio, and waist-hip ratio for identifying cardiometabolic risk factors in Chinese children and adolescents stratified by sex and BMI categories. METHODS:We measured anthropometric indices, fasting plasma glucose, lipid profile and blood pressure for 15698 participants aged 6-17 in a national survey between September and December 2013. The predictive accuracy of anthropometric indices for cardiometabolic risk factors was examined using receiver operating characteristic (ROC) analyses. The DeLong test and Z test were used for the comparisons of areas under ROC curves (AUCs). RESULTS:The prevalence of impaired fasting glucose, dyslipidemia, hypertension and cluster of risk factors were 2.9%, 27.3%, 10.5% and 5.7% respectively. The four anthropometric indices showed poor to fair discriminatory ability for cardiometabolic risk factors with the AUCs ranging from 0.53-0.72. Each index performed significantly better AUCs for dyslipidemia (0.59-0.63 vs. 0.56-0.59), hypertension (0.62-0.70 vs. 0.55-0.65) and clustered risk factors (0.70-0.73 vs. 0.60-0.64) in boys than that in girls. BMI percentile performed the best accuracy for hypertension in both sexes; WC percentile had the highest AUC for dyslipidemia and BMI percentile and waist-height ratio performed similarly the best AUCs for clustered risk factors in boys while BMI percentile, WC percentile and waist-height ratio performed similar and better AUCs for dyslipidemia and clustered risk factors in girls; whereas waist-hip ratio was consistently the poorest predictor for them regardless of sex. Though the anthropometric indices were more predictive of dyslipidemia, hypertension and clustered risk factors in overweight/obese group compared to their normal BMI peers, the AUCs in overweight/obese group remained in the poor range below 0.70. CONCLUSIONS:Anthropometric indices are not effective screening tools for pediatric cardiometabolic risk factors, even in overweight/obese children.

Dataset Information

Comparison of various anthropometric and body fat indices in identifying cardiometabolic disturbances in Chinese men and women.

Background

Objective

Methods

Results

Conclusion

Publications

Comparison of various anthropometric and body fat indices in identifying cardiometabolic disturbances in Chinese men and women.

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