Neighbourhood socioeconomics status predicts non-cardiovascular mortality in cardiac patients with access to universal health care.

Neighbourhood socioeconomics status predicts non-cardiovascular mortality in cardiac patients with access to universal health care.
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DOI:
10.1371/journal.pone.0004120
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发表时间:
2009
期刊:
影响因子:
3.7
通讯作者:
Hill JS
Hill JS
中科院分区:
综合性期刊3区
文献类型:
--
作者:
Heslop CL;Miller GE;Hill JS

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虽然加拿大的医疗保健系统为所有居民提供基本服务,但有证据表明,疾病结果的社会经济梯度仍然存在。我们研究的主要目的是调查心血管疾病或其他原因导致的死亡率是否因社区社会经济梯度而异,这些患者进入医疗保健系统进行心血管疾病管理。对485例有冠状动脉疾病(CAD)血管造影证据和社区社会经济状况信息的患者进行了13.3年的随访。生存分析在调整潜在混杂风险因素后完成。心血管死亡64例,非心血管慢性病死亡66例。未观察到心血管死亡率的社会经济差异。然而,较低的邻里就业,教育和家庭收入中位数确实预测了非心血管慢性疾病死亡率的风险增加。社区社会经济地位每下降五分之一,非心血管死亡风险就会上升21- 30%。社区教育、就业和收入每减少1个五分位数,非心血管疾病死亡率的协变量调整风险比(95%置信区间)分别为1.21(1.02-1.42)、1.21(1.01-1.46)和1.30(1.06-1.60)。这些模式主要归因于癌症死亡率。社区收入中位数和就业率每下降五分之一,估计癌症死亡风险分别上升42%和62%。虽然只收集了基线临床信息,患者水平的社会经济学数据不可用,我们的研究结果表明,环境社会经济因素对CAD患者的生存有显着影响。尽管有公共卫生保健服务,但居住在社会经济地位较低的社区的CAD患者对非心血管慢性疾病死亡率的脆弱性增加,特别是在癌症领域。这些发现促进了进一步的研究,探索邻里对健康的影响机制,以及改善这些机制的方法。
Although the Canadian health care system provides essential services to all residents, evidence suggests that socioeconomic gradients in disease outcomes still persist. The main objective of our study was to investigate whether mortality, from cardiovascular disease or other causes, varies by neighbourhood socioeconomic gradients in patients accessing the healthcare system for cardiovascular disease management. A cohort of 485 patients with angiographic evidence of coronary artery disease (CAD) and neighbourhood socioeconomic status information was followed for 13.3 years. Survival analyses were completed with adjustment for potentially confounding risk factors. There were 64 cases of cardiovascular mortality and 66 deaths from non-cardiovascular chronic diseases. No socioeconomic differentials in cardiovascular mortality were observed. However, lower neighbourhood employment, education, and median family income did predict an increased risk of mortality from non-cardiovascular chronic diseases. For each quintile decrease in neighbourhood socioeconomic status, non-cardiovascular mortality risk rose by 21–30%. Covariate-adjusted hazard ratios (95% confidence interval) for non-cardiovascular mortality were 1.21 (1.02–1.42), 1.21 (1.01–1.46), and 1.30 (1.06–1.60), for each quintile decrease in neighbourhood education, employment, and income, respectively. These patterns were primarily attributable to mortality from cancer. Estimated risks for mortality from cancer rose by 42% and 62% for each one quintile decrease in neighbourhood median income and employment rate, respectively. Although only baseline clinical information was collected and patient-level socioeconomic data were not available, our results suggest that environmental socioeconomic factors have a significant impact on CAD patient survival. Despite public health care access, CAD patients who reside in lower-socioeconomic neighbourhoods show increased vulnerability to non-cardiovascular chronic disease mortality, particularly in the domain of cancer. These findings prompt further research exploring mechanisms of neighbourhood effects on health, and ways they may be ameliorated.
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