Hu Peng, Zheng Murui, Huang Jun, Fan Huan-Ying, Fan Chun-Jiang, Ruan Hui-Hong, Yuan Yue-Shuang, Zhao Wenjing, Wang Harry H X, Deng Hai, Liu Xudong
School of Public Health, Guangdong Pharmaceutical University, Guangzhou, China.
Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China.
Front Med (Lausanne). 2022 Aug 30;9:920760. doi: 10.3389/fmed.2022.920760. eCollection 2022.
Limited evidence was available on the association of the integrated effect of multidimensional lifestyle factors with mortality among Chinese populations. This cohort study was to examine the effect of combined lifestyle factors on the risk of mortality by highlighting the number of healthy lifestyles and their overall effects.
A total of 11,395 participants from the Guangzhou Heart Study (GZHS) were followed up until 1 January 2020. Individual causes of death were obtained from the platform of the National Death Registry of China. The healthy lifestyle index (HLI) was established from seven dimensions of lifestyle, and lifestyle patterns were extracted from eight dimensions of lifestyle using principal component analysis (PCA). Hazard ratios (HRs) and 95% confidence intervals (95% CIs) were estimated using the Cox proportional hazard regression model.
During 35,837 person-years of follow-up, 184 deaths (1.61%) were observed, including 64 from cardiovascular disease. After adjustment for confounders, HLI was associated with a 50% (HR: 0.50, 95% CI: 0.25-0.99) reduced risk of all-cause mortality when comparing the high (6-7 lifestyle factors) with low (0-2 lifestyle factors) categories. Three lifestyle patterns were defined and labeled as pattern I, II, and III. Lifestyle pattern II with higher factor loadings of non-smoking and low-level alcohol drinking was associated with a decreased risk of all-cause mortality (HR: 0.63, 95% CI: 0.43-0.92, = 0.023) when comparing the high with low tertiles of pattern score, after adjustment for confounders. Every 1-unit increment of pattern II score was associated with a decreased risk (HR: 0.97, 95% CI: 0.95-0.99) of all-cause mortality. The other two patterns were not associated with all-cause mortality, and the association of cardiovascular mortality risk was observed with neither HLI nor any lifestyle pattern.
The results suggest that the more dimensions of the healthy lifestyle the lower the risk of death, and adherence to the lifestyle pattern characterized with heavier loading of non-smoking and low-level alcohol drinking reduces the risk of all-cause mortality. The findings highlight the need to consider multi-dimensional lifestyles rather than one when developing health promotion strategies.
关于多维生活方式因素的综合效应与中国人群死亡率之间的关联,现有证据有限。这项队列研究旨在通过强调健康生活方式的数量及其总体影响,来检验综合生活方式因素对死亡风险的影响。
对来自广州心脏研究(GZHS)的11395名参与者进行随访,直至2020年1月1日。从中国国家死亡登记平台获取个体死亡原因。从生活方式的七个维度建立健康生活方式指数(HLI),并使用主成分分析(PCA)从生活方式的八个维度提取生活方式模式。使用Cox比例风险回归模型估计风险比(HRs)和95%置信区间(95% CIs)。
在35837人年的随访期间,观察到184例死亡(1.61%),其中64例死于心血管疾病。在调整混杂因素后,与低(0 - 2种生活方式因素)类别相比,高(6 - 7种生活方式因素)类别时,HLI与全因死亡率风险降低50%(HR:0.50,95% CI:0.25 - 0.99)相关。定义了三种生活方式模式,并标记为模式I、II和III。在调整混杂因素后,与模式得分低三分位数相比,模式得分高三分位数时,具有较高非吸烟和低水平饮酒因素负荷的生活方式模式II与全因死亡率风险降低相关(HR:0.63,95% CI:0.43 - 0.92,P = 0.023)。模式II得分每增加1个单位,与全因死亡率风险降低(HR:0.97,95% CI:0.95 - 0.99)相关。其他两种模式与全因死亡率无关,并且未观察到HLI和任何生活方式模式与心血管死亡率风险之间的关联。
结果表明,健康生活方式的维度越多,死亡风险越低,坚持以较重的非吸烟和低水平饮酒为特征的生活方式模式可降低全因死亡率风险。这些发现凸显了在制定健康促进策略时,需要考虑多维生活方式而非单一生活方式的必要性。