| 缪佳妮,孙静依,曹星琦,丁博楠,蔡志宇,刘足云.不健康生活方式和抑郁症状在生命历程因素与增龄健康关联中的中介效应研究[J].中华流行病学杂志,2024,45(1):71-77 |
| 不健康生活方式和抑郁症状在生命历程因素与增龄健康关联中的中介效应研究 |
| Mediating effect of unhealthy lifestyle and depressive symptom on association between life course factors and ageing health |
| 收稿日期:2023-07-19 出版日期:2024-01-12 |
| DOI：10.3760/cma.j.cn112338-20230719-00024 |
| 中文关键词: 生活方式 抑郁症状 生命历程 增龄健康 中介分析 |
| 英文关键词: Lifestyle Depressive symptom Life course Ageing health Mediation analysis |
| 基金项目:国家自然科学基金（72374180）；浙江省科协软科学研究课题（2023KXCX-KT011）；温州市高水平建设老年友好型城市研究课题（23PGZX0602）；中央高校基本科研业务费专项资金；浙江省智能预防医学重点实验室（2020E10004）；浙江大学国际合作专项 |
| 作者 | 单位 | E-mail | | 缪佳妮 | 浙江大学医学院附属第二医院和公共卫生学院, 浙江省智能预防医学重点实验室, 杭州 310058 | | | 孙静依 | 浙江大学医学院附属第二医院和公共卫生学院, 浙江省智能预防医学重点实验室, 杭州 310058 | | | 曹星琦 | 浙江大学医学院附属第二医院和公共卫生学院, 浙江省智能预防医学重点实验室, 杭州 310058 | | | 丁博楠 | 浙江大学医学院附属第二医院和公共卫生学院, 浙江省智能预防医学重点实验室, 杭州 310058 | | | 蔡志宇 | 浙江大学医学院附属第二医院和公共卫生学院, 浙江省智能预防医学重点实验室, 杭州 310058 | | | 刘足云 | 浙江大学医学院附属第二医院和公共卫生学院, 浙江省智能预防医学重点实验室, 杭州 310058 | Zuyunliu@zju.edu.cn |
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| 中文摘要: |
| 目的 探讨不健康生活方式和抑郁症状在生命历程因素与增龄健康关联中的中介效应。方法 研究对象包括6 217名来自中国健康与养老追踪调查（CHARLS）队列的≥45岁个体。提取70种生命历程因素，采用主成分分析和层次聚类分析方法确定6个生命历程亚群；根据生命历程因素对增龄健康的贡献度和关联分析结果，确定5个关键因素；根据2015年CHARLS生物标志物数据使用的8种生物标志物计算指标生理失调（PD）评估增龄健康。采用线性回归模型、logistic回归模型和中介分析模型探究生命历程亚群及关键因素、不健康生活方式、抑郁症状与PD的复杂关联。结果 调整实足年龄和性别后，生命历程亚群与PD有统计学关联（β值：0.08~0.17，均P<0.05）。生命历程亚群以及关键因素（成年后逆境经历和较低文化程度）与不健康生活方式有统计学关联（β值：0.04~0.52，均P<0.05）。生命历程亚群以及关键因素（童年创伤、童年期父母健康问题、成年后逆境经历和较低文化程度）与抑郁症状有统计学关联（OR值：1.16~4.76，均P<0.05）。中介效应分析显示，不健康生活方式部分介导了生命历程亚群及关键因素（成年后逆境经历和较低文化程度）与PD的关联（3.1%~3.6%），抑郁症状部分介导了生命历程亚群及关键因素（童年创伤、成年后逆境经历和较低文化程度）与PD的关联（6.0%~16.2%）。结论 不健康生活方式和抑郁症状部分介导了生命历程因素对增龄健康的影响，强调在减少童年创伤和成年逆境的同时应关注这两个可改变因素。 |
| 英文摘要: |
| Objective To explore the mediating effect of unhealthy lifestyle and depressive symptom on the associations between life course factors and aging health. Methods The study included 6 217 participants (aged ≥45 years) from the China Health and Retirement Longitudinal Study (CHARLS). We used principal component analysis (PCA) and hierarchical clustering analysis (HCA) to divide participants into six subgroups based on 70 life course factors. Five key life course factors were identified based on correlation analysis and their contribution to aging health. Physiological dysregulation (PD) was calculated by using eight biomarkers in the 2015 CHARLS biomarker dataset. Linear regression, logistic regression, and mediation models were used to explore the complex associations of life course subgroups, key factors, unhealthy lifestyle, depression symptom with PD. Results Life course subgroups were significantly associated with PD after adjusting chronological age and gender (β: 0.08-0.17, all P<0.05). Life-course subgroups and key factors, including adverse experiences in adulthood and lower education level, were significantly associated with unhealthy lifestyle (β: 0.04-0.52, all P<0.05). Life-course subgroups and key factors, including childhood trauma, parental health in childhood, adverse experiences in adulthood, and lower education level, were significantly associated with depression symptom (OR: 1.16-4.76, all P<0.05). Mediation analysis showed that unhealthy lifestyle had partial mediating effect on the association of life course subgroups and key factors, including adverse experiences in adulthood, and lower education levels, with PD (3.1%-3.6%). Depression symptom had partial mediating effect on the association of life course subgroups and key factors, including childhood trauma, adverse experience in adulthood, and lower education level, with PD (6.0%-16.2%). Conclusions Unhealthy lifestyle and depression symptom has partial mediating effect on the impact of life course factors on aging health. It is important to pay attention to these two modifiable factors while targeting childhood trauma and adverse experience in adulthood. |
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