Rees-Punia Erika, Deubler Emily, Patel Alpa V, Diver W Ryan, Hodge James, Islami Farhad, Lee Min Jee, McCullough Marjorie L, Teras Lauren R
Department of Population Science, American Cancer Society, Kennesaw, Georgia.
Department of Surveillance & Health Equity Science, American Cancer Society, Kennesaw, Georgia.
AJPM Focus. 2022 Jul 22;1(1):100013. doi: 10.1016/j.focus.2022.100013. eCollection 2022 Sep.
The role of individual risk factors in the rural‒urban mortality disparity is poorly understood. The purpose of this study was to explore the role of individual-level demographics and health behaviors on the association between rural residence and the risk of mortality.
Cancer Prevention Study-II participants provided updated addresses throughout the study period. Rural‒Urban Commuting Area codes were assigned to participants' geocoded addresses as a time-varying exposure. Cox proportional hazards regression was used to estimate hazard ratios and 95% CIs for mortality associated with Rural‒Urban Commuting Area groups.
After adjustment for age and sex, residents of rural areas/small towns had a small but statistically significant elevated risk of all-cause mortality compared with metropolitan residents (hazard ratio=1.04; 95% CI=1.01, 1.06). Adjustment for additional covariates attenuated the association entirely (hazard ratio=0.99; 95% CI=0.97, 1.01). Individually, adjustment for education (hazard ratio=0.99; 95% CI=0.97, 1.01), alcohol use (hazard ratio=1.01; 95% CI=0.99, 1.04), and moderate-to-vigorous intensity aerobic physical activity (hazard ratio=1.00; 95% CI=0.97, 1.02) eliminated the elevated risk.
The elevated risk of death for rural compared with that for metropolitan residents appeared to be largely explained by individual-level demographics and health behaviors. If replicated in other subpopulations, these results suggest that modifiable factors may play an important role in reducing the rural mortality disparity.
个体风险因素在城乡死亡率差异中所起的作用尚不清楚。本研究的目的是探讨个体层面的人口统计学特征和健康行为在农村居住与死亡风险之间的关联中所起的作用。
癌症预防研究-II的参与者在整个研究期间提供了最新地址。城乡通勤区代码被指定为参与者地理编码地址的时变暴露因素。采用Cox比例风险回归来估计与城乡通勤区组相关的死亡率的风险比和95%置信区间。
在调整年龄和性别后,与大城市居民相比,农村地区/小镇居民的全因死亡率风险略有升高,但具有统计学意义(风险比=1.04;95%置信区间=1.01, 1.06)。对其他协变量进行调整后,这种关联完全减弱(风险比=0.99;95%置信区间=0.97, 1.01)。单独来看,对教育程度(风险比=0.99;95%置信区间=0.97, 1.01)、饮酒情况(风险比=1.01;95%置信区间=0.99, 1.04)和中度至剧烈强度的有氧运动(风险比=1.00;95%置信区间=0.97, 1.02)进行调整后,消除了升高的风险。
与大城市居民相比,农村居民死亡风险升高似乎在很大程度上可由个体层面的人口统计学特征和健康行为来解释。如果在其他亚人群中得到验证,这些结果表明可改变的因素可能在缩小农村死亡率差异方面发挥重要作用。