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Anthropometric indices and their predictive ability on metabolic syndrome in west China

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International Journal of Diabetes in Developing Countries Aims and scope Submit manuscript

Abstract

Aims

To evaluate the relationship between anthropometric indices, including abdominal volume index (AVI), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), conicity index (C index), body mass index (BMI), body roundness index (BRI), body adiposity index (BAI), A body shape index (ABSI) and cardiovascular risk factors, and their abilities to predict metabolic syndrome (MetS) in adults.

Methods

A cross-sectional study of 76,915 participants (30,912 females and 46,003 males) aged between 14 and 100 years was conducted. AVI, WHR, WHtR, BMI, conicity index (C index), BRI, BAI, and ABSI were measured and calculated. Pearson correlation analysis and linear regression analysis were used to examine the relationship between anthropometric indicators and the components of MetS, while binary logistic regression analysis was used to assess the relationship between anthropometric indicators and overall MetS. The receiver operating characteristic curve (ROC) was used to analyze and calculate the area under the curve (AUC). Then, a 95% confidence interval (95% CI) was calculated to evaluate the ability of anthropometric indicators to predict MetS and determine the optimal cutoff value of each anthropometric indicator. The optimal cutoff value was determined by the Youden index.

Results

MetS prevalence was 21.71% in males and 9.5% in females. Participants with MetS were older and had higher values of glucose, triglyceride, low-density lipoprotein cholesterol (LDL-C), total cholesterol (TC), systolic blood pressure (SBP), diastolic blood pressure (DBP) than those without MetS. The high-density lipoprotein cholesterol (HDL-C) values of males and females with MetS were lower than the values found in those without MetS. Mean values of all anthropometric indicators in men and women with MetS were significantly higher than the mean values in those without MetS. After adjusting for age, alcohol consumption, and smoking, anthropometric indexes AVI, WHR, WHtR, C index, BMI, and BRI were all associated with cardiovascular risk factors (p < 0.001). Among men over the age 60 years old, an AVI cutoff of 16.0 predicted MetS with a sensitivity of 74.70% and a specificity of 84.90%. The area under the ROC curve was 0.84 (p < 0.001). Among women over the age of 60 years, an AVI cutoff of 12.8 predicted MetS with a sensitivity of 90.13% and a specificity of 63.72%. The area under the ROC curve was 0.80 (p < 0.001). Among men aged 30–60 years, an AVI cutoff of 16 predicted MetS with a sensitivity of 80.44% and a specificity of 82.36%. The area under the ROC curve was 0.85 (p < 0.001). Among women aged 30–60 years, an AVI cutoff of 12.82 predicted MetS with a sensitivity of 87.72% and a specificity of 83.47%. The area under the ROC curve was 0.90 (p < 0.001). Among men under the age of 30 years, an AVI cutoff of 16.22 predicted MetS with a sensitivity of 87.97% and a specificity of 88.65%. The area under the ROC curve was 0.92 (p < 0.001). Among women under the age of 30 years, an AVI cutoff of 12.79 predicted MetS with a sensitivity of 95.92% and a specificity of 93.79%. The area under the ROC curve was 0.97 (p < 0.001). AVI showed the strongest ability to distinguish MetS across genders and different age groups.

Conclusion

AVI, WHR, WHtR, BMI, C index, and BRI were all associated with cardiovascular risk factors. The anthropometric index is a useful screening tool for MS, its components, and cardiovascular risk factors. Among all the indices examined, AVI can best distinguish MetS.

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Data availability

The data used in this study were collected from the Health Management Center of West China Hospital. The data belongs to West China hospital. Those data are not publicly obtainable.

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Acknowledgements

We give our thanks to the research group members in Health Management Center, West China Hospital, Sichuan University, for their generous support.

Funding

This work was supported by the Sichuan Science and Technology Program (Grant No. 2017RZ0046, Grant No. 2018SZ0087, Grant No. 2018HH0099), a grant from the Sichuan province health department (Grant No. Chuanganyan2012-111), and the Youth Teacher Research Startup Fund of Sichuan University (2016SCU11016).

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Authors and Affiliations

  1. West China Hospital, Sichuan University, No. 37 Guo Xue Xiang, Chengdu, Sichuan, 610041, People’s Republic of China

    Qinqin Wu, Ken Qin, Youjuan Wang & Hu Nie

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  1. Qinqin Wu
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  2. Ken Qin
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Contributions

Qinqin Wu and Hu Nie Designed the study, executed the study, analyzed the results, and contributed to the drafting of the manuscript. Qinqin Wu and Ken Qin Analyzed and interpreted the data in the revised version. Qinqin Wu and Youjuan Wang Contributed to designing the study and discussion of results, and the final manuscript. All authors have read and approved the final manuscript.

Corresponding author

Correspondence to Hu Nie.

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Ethics approval and consent to participate

This study was approved by the Ethics Committee of West China Hospital of Sichuan University. As this is a retrospective research, informed consent was not essential according to the Ethical Guidelines for Epidemiological Research. The study was allowed by the Ethics Committee of West China, Sichuan University.

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The authors declare no competing interests.

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Wu, Q., Qin, K., Wang, Y. et al. Anthropometric indices and their predictive ability on metabolic syndrome in west China. Int J Diabetes Dev Ctries 42, 666–682 (2022). https://doi.org/10.1007/s13410-021-01020-9

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