Background Causal inference using area-level socioeconomic measures is challenging due to risks of residual confounding and imprecise specification of the neighbourhood-level social exposure. By using multi-linked longitudinal data to address these common limitations, our study aimed to identify protective effects of neighbourhood socioeconomic improvement on premature mortality risk. Methods We used data from the Canadian Community Health Survey, linked to health administrative data, including longitudinal residential history. Individuals aged 25–69, living in low-socioeconomic status (SES) areas at survey date (n = 8335), were followed up for neighbourhood socioeconomic improvement within 5 years. We captured premature mortality (death before age 75) until 2016. We estimated protective effects of neighbourhood socioeconomic improvement exposures using Cox proportional hazards models. Stabilized inverse probability of treatment weights (IPTW) were used to account for confounding by baseline health, social and behavioural characteristics. Separate analyses were carried out for three exposure specifications: any improvement, improvement by residential mobility (i.e. movers) or improvement in place (non-movers). Results Overall, 36.9% of the study cohort experienced neighbourhood socioeconomic improvement either by residential mobility or improvement in place. There were noted differences in baseline health status, demographics and individual SES between exposure groups. IPTW survival models showed a modest protective effect on premature mortality risk of socioeconomic improvement overall (HR = 0.86; 95% CI 0.63, 1.18). Effects were stronger for improvement in place (HR = 0.67; 95% CI 0.48, 0.93) than for improvement by residential mobility (HR = 1.07, 95% 0.67, 1.51). Conclusions Our study provides robust evidence that specific neighbourhood socioeconomic improvement exposures are important for determining mortality risks.

中文翻译：

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邻里社会经济改善、居住流动性和过早死亡：基于人口的队列研究和治疗加权分析的逆概率

背景 由于残留混杂的风险和邻里级社会暴露的不精确规范，使用区域级社会经济措施进行因果推断具有挑战性。通过使用多关联的纵向数据来解决这些常见的局限性，我们的研究旨在确定邻里社会经济改善对过早死亡风险的保护作用。方法 我们使用了来自加拿大社区健康调查的数据，这些数据与健康管理数据相关联，包括纵向居住史。在调查日期 (n = 8335) 生活在低社会经济地位 (SES) 地区的 25-69 岁个人在 5 年内接受了邻里社会经济改善情况的随访。我们捕获了 2016 年之前的过早死亡率（75 岁之前死亡）。我们使用 Cox 比例风险模型估计了邻里社会经济改善暴露的保护作用。稳定的治疗权重逆概率 (IPTW) 用于解释基线健康、社会和行为特征的混淆。对三种暴露规格进行了单独分析：任何改善、住宅流动性改善（即搬迁者）或就地改善（非搬迁者）。结果 总体而言，36.9% 的研究队列通过居住流动性或就地改善经历了邻里社会经济改善。暴露组之间的基线健康状况、人口统计和个体 SES 存在显着差异。IPTW 生存模型显示对整体社会经济改善的过早死亡风险具有适度的保护作用（HR = 0.86；95% CI 0.63, 1.18)。就地改善的效果 (HR = 0.67；95% CI 0.48, 0.93) 比居住流动性改善的效果 (HR = 1.07, 95% 0.67, 1.51) 更强。结论 我们的研究提供了强有力的证据，表明特定的邻里社会经济改善暴露对于确定死亡风险很重要。