Comparison of obesity-related parameters as predictors of high brachial-ankle pulse wave velocity in middle-aged and elderly people in China: A multicenter cross-sectional community-based study

Abstract Background The association between obesity-related parameters and occurrence of high brachial-ankle pulse wave velocity (baPWV) in Chinese middle-aged (40–59 years) and elderly people (≥ 60 years) is unknown, especially when body composition indicators are compared. Methods A total of 3219 middle-aged and elderly subjects who were recruited from 6 community health service centers located in Hefei, Bengbu, and Chuzhou (Anhui province, Eastern China) met the inclusion criteria and had valid data. An e-health promotion system was used to collect basic health data, and baPWV and the body composition of each subject were measured. Partial correlation and binary logistic regression analyses were performed to identify associations between obesity-related parameters and high baPWV, and receiver operating characteristic (ROC) curves were analyzed to determine the optimal cutoff values and predictive capacity of high baPWV. Results Partial correlation coefficients (adjusted for age and mean arterial pressure) for waist-to-height ratio (WHtR) (0.101 and 0.192) and waist circumference (WC) (0.101 and 0.172) were highest in women. The partial correlation coefficient for fat tissue index (0.158) was highest in middle-aged men. WHtR combined covariates explained the largest proportion of the variance for dependent variables in model 1, model 2 (women), and model 3 (women). R2 ranged from 0.088 to 0.216 in Model 1. The predictive capacities of these parameters were lower in men. The area under the ROC curve was higher for WHtR (0.647–0.739) than other parameters in elderly women, with optimal cutoff values of 0.52. Conclusions WHtR and WC may be useful for community-based screening of women as a secondary preventative measure for high baPWV. These 2 parameters can be used in conjunction with others (eg, body composition index) to predict the risk of high baPWV based on region, age, and sex.