Wei Liao1, Xiaotian Liu1, Ning Kang1, Yu Song2, Yinghao Yuchi1, Ze Hu1, Jian Hou1, Chongjian Wang1, Yuqian Li3,4. 1. Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, People's Republic of China. 2. Department of Occupational and Environmental Health Sciences, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People's Republic of China. 3. Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, People's Republic of China. liyuqian@zzu.edu.cn. 4. Department of Clinical Pharmacology, School of Pharmaceutical Science, Zhengzhou University, Zhengzhou, Henan, People's Republic of China. liyuqian@zzu.edu.cn.
Abstract
PURPOSE: This study aimed to investigate the associations between overall lifestyles and HRQoL, as well as the variations in age, sex, education level, and income. METHODS: A total of 23,402 participants from the Henan rural cohort were included. The healthy lifestyle score (HLS) consists of five lifestyle factors: smoking, alcohol drinking, physical activity, diet, and body mass index. HRQoL was assessed by the EQ-5D-5L questionnaire. The general linear model and Tobit regression model were utilized to assess the associations of HLS with visual analogue score (VAS) and utility index. RESULTS: Compared with participants with an HLS of 0-2, the corresponding regression coefficients (β) and 95% confidence intervals (CI) of participants with an HLS of 3, 4, and 5 for VAS score were 1.09 (0.59, 1.59), 1.92 (1.38, 2.46), and 2.60 (1.83, 3.37); the corresponding β and 95% CI for utility index were 0.02 (0.01, 0.03), 0.05 (0.03, 0.06), and 0.06 (0.04, 0.07). Notably, these positive associations were greater among the elderly, female, and those with lower education level and average monthly income (p for interaction < 0.05). For instance, the corresponding β and 95% CI of individuals with an HLS of 5 for utility index in average monthly income < 500 RMB, 500-999 RMB, and ≥ 1000 RMB groups were 0.08 (0.05, 0.11), 0.06 (0.03, 0.09), and 0.02 (- 0.00, 0.05). CONCLUSION: Engaging in healthier lifestyle habits was associated with a higher level of HRQoL, especially in the elderly, females, and those with low education level and average monthly income.
PURPOSE: This study aimed to investigate the associations between overall lifestyles and HRQoL, as well as the variations in age, sex, education level, and income. METHODS: A total of 23,402 participants from the Henan rural cohort were included. The healthy lifestyle score (HLS) consists of five lifestyle factors: smoking, alcohol drinking, physical activity, diet, and body mass index. HRQoL was assessed by the EQ-5D-5L questionnaire. The general linear model and Tobit regression model were utilized to assess the associations of HLS with visual analogue score (VAS) and utility index. RESULTS: Compared with participants with an HLS of 0-2, the corresponding regression coefficients (β) and 95% confidence intervals (CI) of participants with an HLS of 3, 4, and 5 for VAS score were 1.09 (0.59, 1.59), 1.92 (1.38, 2.46), and 2.60 (1.83, 3.37); the corresponding β and 95% CI for utility index were 0.02 (0.01, 0.03), 0.05 (0.03, 0.06), and 0.06 (0.04, 0.07). Notably, these positive associations were greater among the elderly, female, and those with lower education level and average monthly income (p for interaction < 0.05). For instance, the corresponding β and 95% CI of individuals with an HLS of 5 for utility index in average monthly income < 500 RMB, 500-999 RMB, and ≥ 1000 RMB groups were 0.08 (0.05, 0.11), 0.06 (0.03, 0.09), and 0.02 (- 0.00, 0.05). CONCLUSION: Engaging in healthier lifestyle habits was associated with a higher level of HRQoL, especially in the elderly, females, and those with low education level and average monthly income.
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