J Glob Health. 2024 Aug 16;14:04127. doi: 10.7189/jogh.14.04127.
The increasing prevalence of depressive symptoms has emerged as a critical public health issue globally, highlighting the need for analyses of the factors contributing to depressive symptoms within the Chinese population and the development of targeted recommendations for improving mental well-being. We aimed to explore the correlation between internet use and depressive symptoms and the role of socioeconomic inequalities in this association.
We included data on 8019 residents aged 18 years and above, which we retrieved from the 2018 and 2020 waves of the China Family Panel Studies. We used latent profile analysis to categorise individuals' internet usage patterns and multiple linear regression to determine their association with depressive symptoms.
Higher socioeconomic status (SES) was associated with fewer depressive symptoms (τ = -0.08; 95% confidence interval (CI) = -0.36, -0.18). Individuals in the high-dependence group presented a greater likelihood of developing depressive symptoms (τ = 0.04; 95% CI = 0.007, 0.66). We observed no significant difference in the interaction effect between individual-level SES and the four patterns of internet usage. However, compared with urban-dwelling respondents, those in rural areas had a stronger association between internet usage patterns and depressive symptoms, especially those in the high-dependence group (τ = -0.07; 95% CI = -1.47, -0.20).
Our findings indicate a significant association between depressive symptoms and internet usage patterns, indicating a need for interventions related to internet use, especially those targeted at reducing the risk of depressive symptoms in individuals of lower SES.
抑郁症状的患病率不断上升,已成为全球一个重大的公共卫生问题,这凸显了分析中国人群中导致抑郁症状的因素并制定有针对性的改善心理健康建议的必要性。我们旨在探讨互联网使用与抑郁症状之间的相关性,以及社会经济不平等在这种关联中的作用。
我们纳入了来自中国家庭追踪调查 2018 年和 2020 年两轮调查的 8019 名 18 岁及以上居民的数据。我们使用潜在剖面分析对个体的互联网使用模式进行分类,并使用多元线性回归确定它们与抑郁症状的关联。
较高的社会经济地位(SES)与较少的抑郁症状相关(τ=-0.08;95%置信区间(CI)=-0.36,-0.18)。高依赖组的个体出现抑郁症状的可能性更大(τ=0.04;95%CI=0.007,0.66)。我们未观察到个体 SES 水平和四种互联网使用模式之间的交互作用有显著差异。然而,与城镇居民相比,农村居民的互联网使用模式与抑郁症状之间的关联更强,尤其是高依赖组(τ=-0.07;95%CI=-1.47,-0.20)。
我们的研究结果表明抑郁症状与互联网使用模式之间存在显著关联,这表明需要进行与互联网使用相关的干预措施,特别是针对降低低 SES 个体抑郁症状风险的干预措施。