J Yang1, F Wang1, X Han1, J Yuan1, P Yao1, Y Liang1, S Wei2, X M Zhang1, H Guo1, H D Yang3, M A He1. 1. Department of Occupational and Environmental Health/State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China. 2. Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China. 3. Department of Cardiovascular Medicine, Dongfeng General Hospital, Shiyan 442000, China.
Abstract
Objective: To explore the relationship between anthropometric indices and the incident risk of hypertension, compare novel anthropometric indices with traditional indices in hypertension prediction and establish hypertension prediction models among elderly Chinese. Methods: A total of 27 009 retirees from the Dongfeng Motor Corporation were recruited at baseline in 2008 and the first follow-up was conducted in 2013. After the exclusion of participants less than 60 years old, participants with hypertension, coronary heart disease, stroke, cancer, and those with missing data, a total of 6 784 elderly participants were enrolled in this study. A multivariate logistic regression model was used to analyze the relationship between traditional anthropometric indices, body mass index (BMI), waist circumference (WC), waist-to-height ratio (WHtR), novel anthropometric indices, visceral adiposity index (VAI), body shape index (ABSI), body roundness index (BRI), and the incident risk of hypertension. Meanwhile, a multivariate logistic regression model was used to establish hypertension prediction models. Receiver operating characteristic (ROC) curve was applied to compare the prediction ability of different models. Results: A total of 1 787 incident cases of hypertension were identified, with the incidence of hypertension about 27.59%. Significant positive associations were detected between BMI, WC, WHtR, VAI, BRI and the incident risk of hypertension after adjusting for potential confounders (all P values<0.05). In men, the OR (95%CI) (upper tertile vs lower tertile) was 1.45 (1.22-1.73) for VAI, and 1.86 (1.55-2.23) for BRI. In women, the OR (95% CI) (upper tertile vs lower tertile) was 1.55 (1.22-1.96) for VAI, and 1.60 (1.27-2.01) for BRI. For ABSI, no significant association was observed in either men (OR (95%CI): 1.07 (0.90-1.28)) or women (OR (95%CI): 1.03 (0.82-1.29), both P values >0.05). The basic hypertension prediction model included age, drinking (only in men), education status (only in men), systolic blood pressure (SBP), diastolic blood pressure (DBP), and fasting blood glucose levels. Based on the basic prediction model, BMI (in men: AUC=0.697) and BRI (only in men: AUC=0.696) improved area under ROC curve (AUC) significantly (P<0.05). BMI was the strongest predictor in both men (AUC=0.697) and women (AUC=0.685) in the extended model. Conclusion: Significant positive associations were detected between BMI, WC, WHtR, VAI, BRI and the incident risk of hypertension among elderly Chinese. BMI was the strongest predictor in hypertension prediction model compared with other anthropometric indices.
Objective: To explore the relationship between anthropometric indices and the incident risk of hypertension, compare novel anthropometric indices with traditional indices in hypertension prediction and establish hypertension prediction models among elderly Chinese. Methods: A total of 27 009 retirees from the Dongfeng Motor Corporation were recruited at baseline in 2008 and the first follow-up was conducted in 2013. After the exclusion of participants less than 60 years old, participants with hypertension, coronary heart disease, stroke, cancer, and those with missing data, a total of 6 784 elderly participants were enrolled in this study. A multivariate logistic regression model was used to analyze the relationship between traditional anthropometric indices, body mass index (BMI), waist circumference (WC), waist-to-height ratio (WHtR), novel anthropometric indices, visceral adiposity index (VAI), body shape index (ABSI), body roundness index (BRI), and the incident risk of hypertension. Meanwhile, a multivariate logistic regression model was used to establish hypertension prediction models. Receiver operating characteristic (ROC) curve was applied to compare the prediction ability of different models. Results: A total of 1 787 incident cases of hypertension were identified, with the incidence of hypertension about 27.59%. Significant positive associations were detected between BMI, WC, WHtR, VAI, BRI and the incident risk of hypertension after adjusting for potential confounders (all P values<0.05). In men, the OR (95%CI) (upper tertile vs lower tertile) was 1.45 (1.22-1.73) for VAI, and 1.86 (1.55-2.23) for BRI. In women, the OR (95% CI) (upper tertile vs lower tertile) was 1.55 (1.22-1.96) for VAI, and 1.60 (1.27-2.01) for BRI. For ABSI, no significant association was observed in either men (OR (95%CI): 1.07 (0.90-1.28)) or women (OR (95%CI): 1.03 (0.82-1.29), both P values >0.05). The basic hypertension prediction model included age, drinking (only in men), education status (only in men), systolic blood pressure (SBP), diastolic blood pressure (DBP), and fasting blood glucose levels. Based on the basic prediction model, BMI (in men: AUC=0.697) and BRI (only in men: AUC=0.696) improved area under ROC curve (AUC) significantly (P<0.05). BMI was the strongest predictor in both men (AUC=0.697) and women (AUC=0.685) in the extended model. Conclusion: Significant positive associations were detected between BMI, WC, WHtR, VAI, BRI and the incident risk of hypertension among elderly Chinese. BMI was the strongest predictor in hypertension prediction model compared with other anthropometric indices.
Entities:
Keywords:
Aged; Anthropometric indices; Cohort studies; Hypertension; Prediction model