Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.
Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, QC, Canada.
Int J Epidemiol. 2023 Apr 19;52(2):489-500. doi: 10.1093/ije/dyac117.
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.
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).
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).
Our study provides robust evidence that specific neighbourhood socioeconomic improvement exposures are important for determining mortality risks.
由于存在残留混杂和邻里社会暴露的不精确规范的风险,使用区域社会经济指标进行因果推断具有挑战性。通过使用多链接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。
我们使用来自加拿大社区健康调查的数据,该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)居住在低社会经济地位(SES)地区的 25-69 岁个体,在 5 年内进行邻里社会经济改善的随访。我们记录了 2016 年之前的过早死亡(75 岁之前死亡)。我们使用 Cox 比例风险模型估计邻里社会经济改善暴露的保护作用。稳定的逆处理概率加权(IPTW)用于解释基线健康、社会和行为特征引起的混杂。针对三种暴露情况分别进行了分析:任何改善、通过居住迁移(即迁居者)的改善或原地改善(非迁居者)。
总体而言,研究队列中有 36.9%的人经历了邻里社会经济的改善,无论是通过居住迁移还是原地改善。在暴露组之间,基线健康状况、人口统计学特征和个体 SES 存在差异。IPTW 生存模型显示,社会经济改善对过早死亡风险具有适度的保护作用(HR=0.86;95%CI 0.63,1.18)。原地改善(HR=0.67;95%CI 0.48,0.93)的效果强于居住迁移改善(HR=1.07;95%CI 0.67,1.51)。
我们的研究提供了有力的证据表明,特定的邻里社会经济改善暴露对于确定死亡风险很重要。