The Association Between Posting WeChat Moments and the Risk of Depressive Symptoms Among Middle-Aged and Older Chinese Adults: Prospective National Cohort Study.

IF 3.5 2区医学 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

JMIR Public Health and Surveillance Pub Date : 2025-01-13 DOI:10.2196/62730

Wei Wang, Hui Wang, Xinru Hu, Qian Yu, Fangyi Chen, Xirui Qiu, Xiaoxiao Wang

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引用次数: 0

Abstract

Background: The association between social media usage and the risk of depressive symptoms has attracted increasing attention. WeChat is a popular social media software in China. The impact of using WeChat and posting WeChat moments on the risk of developing depressive symptoms among community-based middle-aged and older adults in China is unknown.

Objective: The objective was to assess the association between using WeChat and posting WeChat moments and the risk of depressive symptoms among middle-aged and older adults in China.

Methods: A prospective national cohort study was designed based on the data obtained from the fourth and fifth waves of the China Health and Retirement Longitudinal Study (CHARLS). The strength of association between using WeChat and posting WeChat moments and the risk of depressive symptoms was estimated by modified Poisson regressions. Depressive symptoms were determined using the 10-item Center for Epidemiologic Studies Depression Scale. Meanwhile, the heterogeneity of the associations was explored through multiple subgroup analyses. Moreover, multiple sensitivity analyses were performed to verify the robustness of the associations between the exposures and depressive symptoms.

Results: A total of 9670 eligible participants were included in the cohort study, and the incidence rate of depressive symptoms was 19.08% (1845/9670, 95% CI 19.07%-19.09%) from the fourth to fifth waves of the CHARLS. Using WeChat (adjusted relative risk [aRR] 0.691, 95% CI 0.582-0.520) and posting WeChat moments (aRR 0.673, 95% CI 0.552-0.821) reduced the risk of depressive symptoms among middle-aged and older Chinese adults. The association between the exposures and depressive symptoms was robust, proved through multiple sensitivity analyses (all P<.05). However, the associations were heterogeneous in certain subgroup catagories, such as solitude, duration of sleep at night, nap after lunch, physical activity, and having multiple chronic conditions.

Conclusions: Using WeChat and especially posting WeChat moments can mitigate the risk of depressive symptoms among community-based middle-aged and older Chinese adults. However, there is likely a need for a longer follow-up period to explore the impact of the exposures on the risk of long-term depressive outcomes.

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中国中老年人群发微信朋友圈与抑郁症状风险的关系：前瞻性国家队列研究

背景：社交媒体使用与抑郁症状风险之间的关系越来越受到关注。b微信是中国流行的社交媒体软件。在中国以社区为基础的中老年人中，使用微信和发布微信朋友圈对患抑郁症状风险的影响尚不清楚。目的：目的是评估中国中老年人使用微信和发布微信朋友圈与抑郁症状风险之间的关系。方法：基于中国健康与退休纵向研究（CHARLS）第四和第五波数据设计前瞻性国家队列研究。使用微信和发布微信时刻与抑郁症状风险之间的关联强度通过修正泊松回归估计。采用10项流行病学研究中心抑郁量表来确定抑郁症状。同时，通过多亚组分析探讨这些关联的异质性。此外，还进行了多重敏感性分析，以验证暴露与抑郁症状之间关联的稳健性。结果：队列研究共纳入9670名符合条件的受试者，CHARLS第四至第五波抑郁症状发生率为19.08% （1845/9670,95% CI 19.07%-19.09%）。使用微信（校正相对危险度[aRR] 0.691, 95% CI 0.582-0.520）和发布微信朋友圈（aRR 0.673, 95% CI 0.552-0.821）降低了中国中老年人群出现抑郁症状的风险。多重敏感性分析证明，接触微信与抑郁症状之间的相关性很强。结论：使用微信，尤其是发布微信朋友圈，可以减轻社区中老年中国成年人抑郁症状的风险。然而，可能需要更长的随访时间来探索暴露对长期抑郁结果风险的影响。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

JMIR Public Health and Surveillance Multiple-

CiteScore

13.70

自引率

2.40%

发文量

136

审稿时长

12 weeks

期刊介绍： JMIR Public Health & Surveillance (JPHS) is a renowned scholarly journal indexed on PubMed. It follows a rigorous peer-review process and covers a wide range of disciplines. The journal distinguishes itself by its unique focus on the intersection of technology and innovation in the field of public health. JPHS delves into diverse topics such as public health informatics, surveillance systems, rapid reports, participatory epidemiology, infodemiology, infoveillance, digital disease detection, digital epidemiology, electronic public health interventions, mass media and social media campaigns, health communication, and emerging population health analysis systems and tools.