医学
社会经济地位
危险系数
人口学
四分位数
比例危险模型
队列研究
置信区间
队列
人口
人体测量学
入射(几何)
老年学
环境卫生
内科学
物理
社会学
光学
作者
Lola Neufcourt,Marie Zins,Lisa F. Berkman,Olivier Grimaud
标识
DOI:10.1097/hjh.0000000000002959
摘要
Reducing hypertension represents a critical point of intervention to lower the burden of cardiovascular disease worldwide. Although the relationship between lower socioeconomic status and higher rates of hypertension is well documented, most of the evidence comes from prevalence studies involving young adult population.To investigate the independent association of wealth, education and income with incident hypertension among older adults living in the United States.This cohort study included 16 587 individuals aged 50 years and older, free of hypertension and cardiovascular disease at baseline from the Health and Retirement Study over the period 1992-2014. We used Cox proportional hazards models to examine longitudinal associations between wealth, education, and income at baseline and self-reported diagnosis of incident hypertension.During a median follow-up of 7.8 years, 6817 participants declared an occurrence of hypertension (incidence rate: 45.3 [95% confidence interval (CI) = 44.2-46.4] per 1000 person-years). Overall, those in low as compared with high socioeconomic status groups had a higher risk of developing hypertension in late life. In particular, adjusted hazard ratios [95% CI] across decreasing wealth quartiles were 1.0 (reference), 0.97 [0.88-1.08], 1.17 [1.05-1.30], and 1.20 [1.07-1.35] in men, and 1.0 (reference), 1.28 [1.17-1.41], 1.21 [1.09-1.33], and 1.28 [1.16-1.42] in women. In multivariate analyses, wealth remained strongly associated with incident hypertension among women after accounting for other socioeconomic, behavioral and anthropometric risk factors.Socioeconomic status, especially wealth, is a strong independent predictor of incident hypertension in older adults. Our findings support population-based interventions tailored to those in disadvantaged socioeconomic groups to reduce the risk of hypertension.
科研通智能强力驱动
Strongly Powered by AbleSci AI