Vega Sofia L, Childs Marissa L, Aggarwal Sarika, Nethery Rachel C
Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.
Center for the Environment, Harvard University, Boston, Massachusetts.
JAMA Netw Open. 2025 Apr 1;8(4):e257956. doi: 10.1001/jamanetworkopen.2025.7956.
The escalating intensity of wildfires in the western US is increasing exposure to smoke pollution. Previous studies of wildfire smoke and health have primarily focused on mortality and respiratory and cardiovascular events, with limited research on broader health impacts or on the shape of concentration-response curves.
To characterize the associations between exposure to smoke-specific fine particulate matter (PM2.5) and cause-specific hospitalizations among older adults in the western US.
DESIGN, SETTING, AND PARTICIPANTS: This retrospective cohort study used Medicare inpatient claims data from 2006 to 2016 linked with machine learning-derived smoke-specific PM2.5 to assess associations between smoke PM2.5 and hospitalization rates. Participants included Medicare beneficiaries aged 65 years or older who lived in a western US state (ie, Arizona, California, Colorado, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, or Wyoming). Analyses were conducted from October 2023 to February 2025.
Daily county-level smoke-specific PM2.5 concentrations were estimated from machine learning models trained on monitor and satellite data.
Daily county-level rates of unscheduled hospitalization for each of 13 broad cause categories. To characterize the association between each cause of hospitalization and smoke PM2.5, distributed lag models were fitted with hospitalization rates modeled as a function of same-day smoke PM2.5 exposure and exposures on each day of the preceding week, using splines on exposure to allow for nonlinearity.
The study included 10 369 361 individuals (mean [SD] age, 74.7 [7.9] years; 4 862 826 male [46.9%]; 5 506 535 female [53.1%]; 373 252 Black [3.6%]; 420 577 Hispanic [4.1%]; and 8 365 607 White [80.7%]), 57 million person-months of follow-up, and 4.7 million unscheduled hospitalizations. Smoke PM2.5 concentration-response curves for respiratory hospitalizations and cardiovascular hospitalizations were flat at lower concentrations but showed increasing trends at concentrations above 25 μg/m3. On average, daily hospitalizations (per 100 000) increased by 2.40 (95% CI, 0.17 to 4.63) for respiratory concerns when increasing same-day and preceding week smoke PM2.5 concentrations from 0 to 40 μg/m3; hospitalizations for cardiovascular concerns increased by 2.61 (95% CI, -0.09 to 5.30), a difference that was not statistically significant. No associations were observed for other causes of hospitalization.
In this cohort study, exposure to high levels of smoke pollution was associated with an increase in hospitalizations for respiratory diseases. These findings underscore the need for interventions to mitigate the health impacts of wildfire smoke exposure.
美国西部野火强度不断升级，致使人们暴露于烟雾污染中的情况日益增多。先前关于野火烟雾与健康的研究主要聚焦于死亡率以及呼吸道和心血管事件，而对更广泛的健康影响或浓度-反应曲线的形状研究有限。
描述美国西部老年人接触特定烟雾细颗粒物（PM2.5）与特定病因住院之间的关联。
设计、设置和参与者：这项回顾性队列研究使用了2006年至2016年医疗保险住院理赔数据，并与机器学习得出的特定烟雾PM2.5数据相链接，以评估烟雾PM2.5与住院率之间的关联。参与者包括居住在美国西部某州（即亚利桑那州、加利福尼亚州、科罗拉多州、爱达荷州、蒙大拿州、内华达州、新墨西哥州、俄勒冈州、犹他州、华盛顿州或怀俄明州）的65岁及以上医疗保险受益人。分析于2023年10月至2025年2月进行。
根据基于监测和卫星数据训练的机器学习模型估算每日县级特定烟雾PM2.5浓度。
13个广泛病因类别中每类的每日县级非计划住院率。为描述每种住院病因与烟雾PM2.5之间的关联，采用分布滞后模型，将住院率建模为当日烟雾PM2.5暴露量以及前一周每日暴露量的函数，使用暴露量样条以考虑非线性关系。
该研究纳入了10369361名个体（平均[标准差]年龄为74.7[7.9]岁；男性4862826名[46.9%]；女性5506535名[53.1%]；黑人373252名[3.6%]；西班牙裔420577名[4.1%]；白人8365607名[80.7%]），随访5700万人月，发生470万次非计划住院。呼吸道住院和心血管住院的烟雾PM2.5浓度-反应曲线在较低浓度时较为平缓，但在浓度高于25μg/m³时呈上升趋势。当当日和前一周烟雾PM2.5浓度从0增加到40μg/m³时，呼吸道相关的每日住院率（每10万人）平均增加2.40（95%置信区间，0.17至4.63）；心血管相关的住院率增加2.61（95%置信区间，-0.09至5.30），差异无统计学意义。未观察到其他住院病因的关联。
在这项队列研究中，接触高水平烟雾污染与呼吸道疾病住院率增加有关。这些发现强调了采取干预措施以减轻野火烟雾暴露对健康影响的必要性。
