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Associations between various anthropometric indices and hypertension and hyperlipidaemia: a cross-sectional study in
Chuyao Feng1, Cihang Lu1, Kang Chen2
1Department of Endocrinology and Metabolism, Institute of Endocrinology, National Health Commission Key Laboratory of Diagnosis and Treatment of Thyroid Diseases, The First Hospital of China Medical University, Liaoning Province, Shenyang, 110001, People's Republic of China.
Background:
This study aims to explore the association and determine the distinguished potential of anthropometric adiposity indices in screening for hypertension and hyperlipidaemia in the Chinese population.
Methods:
A recent nationwide cross-sectional study, called the Thyroid Disorders, Iodine State, and Diabetes Epidemiological Survey (TIDE 2015-2017), provided the newest data on the relationships between anthropometric adiposity indices and hypertension and hyperlipidaemia and included 65,231 subjects. The area under the curve (AUC) was used to assess the feasibility of using these indices to distinguish hypertension and hyperlipidaemia. After age stratification, a restricted cubic spline (RCS) fitted for generalized linear regression was used to visualize the relationships of the body mass index (BMI), waist circumference (WC), the waist-to-height ratio (WHtR), the body roundness index (BRI), and the "a body shape index" (ABSI) with hypertension and hyperlipidaemia.
Results:
The results showed that there were significant differences in the BMI, WC, the WHtR, the BRI, and the ABSI among the different age groups (P < 0.0001). After adjusting for sex, age, education, income, smoking status, urban or rural residence, and ethnicity in model, The WHtR and BRI had greater discriminatory power in identifying hypertension (AUC = 0.665, 95% confidence interval (CI) 0.660-0.671 for both), hypercholesterolaemia (AUC = 0.629, 95% CI 0.624-0.634 for both), and high low-density lipoprotein cholesterol (LDL-C; AUC = 0.659, 95% CI 0.653-0.664 for both) status in the overall population. When distinguishing hypertriglyceridaemia among the general population, the BMI (AUC = 0.711, 95% CI 0.706-0.716) and WC (AUC = 0.715, 95% CI 0.710-0.720) had greater discriminatory ability than the other anthropometric indices did. The BMI (AUC = 0.631, 95% CI 0.625-0.637) had the highest power for low high-density lipoprotein cholesterol (HDL-C) status in the general population.
Conclusions:
Several anthropometric indices show significant correlation with hypertension and hyperlipidaemia. The WHtR and BRI were better in distinguishing hypertension, hypercholesterolaemia and high LDL-C status, while the BMI was better in hypertriglyceridaemia and low HDL-C status. The use of combined indices, such as the BMI, WC, the WHtR and the BRI, can be included in an individual's medical history and can be used as tools for cardiovascular health screening, which may yield superior results for public health.
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