Zhang Haisu, Wang Yifan, Li Haomin, Zhu Qiao, Ma Tszshan, Liu Yang, Steenland Kyle
Rollins School of Public Health, Emory University, United States.
Rollins School of Public Health, Emory University, United States.
Environ Int. 2025 Jun;200:109539. doi: 10.1016/j.envint.2025.109539. Epub 2025 May 18.
The associations of PM mass and various adverse health outcomes have been widely investigated. However, fewer studies focused on the potential health impacts of PM components, especially for dementia and Alzheimer's diseases (AD).
We constructed a nationwide population-based open cohort study among Medicare beneficiaries aged 65 or older during 2000-2018. This dataset was linked with the predicted levels of 15 PM components, including 5 major mass contributors (EC, OC, NH, NO, SO) and 10 trace elements (Br, Ca, Cu, Fe, K, Ni, Pb, Si, V, Zn) across contiguous U.S. territory. Data were aggregated by ZIP code, calendar year and individual level demographics. Two mixture analysis methods, weighted quantile sum regression (WQS) and quantile g-computation (qgcomp), were used with quasi-Poisson models to analyze the health effects of the total mixture of PM components on dementia and AD, as well as the relative contribution of individual components.
Exposure to PM components over the previous 5 years was significantly associated with increased risks of both dementia and AD, with stronger associations observed for AD. SO, OC, Cu were identified as major contributors to the combined positive association of the mixture from both WQS and qgcomp models.
We found positive associations between the 15 PM components and the incidence of dementia and AD. Our findings suggest that reducing PM emissions from traffic and fossil fuel combustion could help mitigate the growing burden of dementia and Alzheimer's disease.
细颗粒物（PM）质量与各种不良健康结局之间的关联已得到广泛研究。然而，较少有研究关注PM成分对健康的潜在影响，尤其是对痴呆症和阿尔茨海默病（AD）的影响。
我们在2000年至2018年期间对65岁及以上的医疗保险受益人进行了一项基于全国人口的开放队列研究。该数据集与美国本土15种PM成分的预测水平相关联，包括5种主要质量贡献成分（元素碳、有机碳、铵、氮氧化物、硫氧化物）和10种微量元素（溴、钙、铜、铁、钾、镍、铅、硅、钒、锌）。数据按邮政编码、日历年和个体层面的人口统计学信息进行汇总。两种混合分析方法，加权分位数和回归（WQS）和分位数g计算（qgcomp），与准泊松模型一起用于分析PM成分总混合物对痴呆症和AD的健康影响，以及单个成分的相对贡献。
过去5年接触PM成分与痴呆症和AD的风险增加显著相关，AD的相关性更强。硫氧化物、有机碳、铜被确定为WQS和qgcomp模型中混合物综合正向关联的主要贡献成分。
我们发现15种PM成分与痴呆症和AD的发病率之间存在正相关。我们的研究结果表明，减少交通和化石燃料燃烧产生的PM排放有助于减轻痴呆症和阿尔茨海默病日益增长的负担。
