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采用 11 种不同建模方法在妇女健康倡议记忆研究(WHIMS)中比较空气污染暴露与健康效应关联。

Comparison of Air Pollution Exposures and Health Effects Associations Using 11 Different Modeling Approaches in the Women's Health Initiative Memory Study (WHIMS).

机构信息

Department of Epidemiology, Milken Institute School of Public Health, Washington, District of Columbia, USA.

Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.

出版信息

Environ Health Perspect. 2024 Jan;132(1):17003. doi: 10.1289/EHP12995. Epub 2024 Jan 16.

Abstract

BACKGROUND

Many approaches to quantifying air pollution exposures have been developed. However, the impact of choice of approach on air pollution estimates and health-effects associations remains unclear.

OBJECTIVES

Our objective is to compare particulate matter with aerodynamic diameter () concentrations and resulting health effects associations using multiple estimation approaches previously used in epidemiologic analyses.

METHODS

We assigned annual exposure estimates from 1999 to 2004 derived from 11 different approaches to Women's Health Initiative Memory Study (WHIMS) participant addresses within the contiguous US. Approaches included geostatistical interpolation approaches, land-use regression or spatiotemporal models, satellite-derived approaches, air dispersion and chemical transport models, and hybrid models. We used descriptive statistics and plots to assess relative and absolute agreement among exposure estimates and examined the impact of approach on associations between and death due to natural causes, cardiovascular disease (CVD) mortality, and incident CVD events, adjusting for individual-level covariates and climate-based region.

RESULTS

With a few exceptions, relative agreement of approach-specific exposure estimates was high for concentrations across the contiguous US. Agreement among approach-specific exposure estimates was stronger near monitors, in certain regions of the country, and in 2004 vs. 1999. Collectively, our results suggest but do not quantify lower agreement at local spatial scales for . There was no evidence of large differences in health effects associations with among estimation approaches in analyses adjusted for climate region.

CONCLUSIONS

Different estimation approaches produced similar spatial patterns of concentrations across the contiguous US and in areas with dense monitoring data, and effects associations were similar among estimation approaches. estimates and effects associations may differ more in samples drawn from smaller areas or areas without substantial monitoring data, or in analyses with finer adjustment for participant location. Our results can inform decisions about estimation approach in epidemiologic studies, as investigators balance concerns about bias, efficiency, and resource allocation. Future work is needed to understand whether these conclusions also apply in the context of other air pollutants of interest. https://doi.org/10.1289/EHP12995.

摘要

背景

已经开发出许多量化空气污染暴露的方法。然而,选择方法对空气污染估计和健康效应关联的影响仍不清楚。

目的

我们的目的是比较使用先前在流行病学分析中使用的多种估计方法得出的颗粒物浓度和由此产生的健康效应关联。

方法

我们将 1999 年至 2004 年期间的年度 暴露估计值分配给美国大陆的妇女健康倡议记忆研究(WHIMS)参与者地址,这些估计值来自 11 种不同的方法。这些方法包括地质统计学插值方法、土地利用回归或时空模型、卫星衍生方法、空气扩散和化学输送模型以及混合模型。我们使用描述性统计和图形来评估暴露估计值之间的相对和绝对一致性,并研究方法对 与自然原因导致的死亡、心血管疾病(CVD)死亡率和心血管疾病事件之间关联的影响,同时调整个体水平协变量和气候区域。

结果

除了少数例外,对于整个美国大陆的 浓度,特定方法的 暴露估计值之间的相对一致性较高。特定方法的暴露估计值之间的一致性在靠近监测站、在美国某些地区以及在 2004 年与 1999 年之间更强。总的来说,我们的结果表明,但无法量化局部空间尺度上 的低一致性。在调整气候区域的分析中,不同估计方法对 健康效应关联的影响没有明显差异。

结论

不同的估计方法在整个美国大陆和监测数据密集的地区产生了相似的 浓度空间模式,并且在估计方法之间, 效应关联相似。在从较小区域或没有大量监测数据的区域抽取的样本中,或在更精细地调整参与者位置的分析中, 估计值和 效应关联可能会有更大的差异。我们的结果可以为流行病学研究中的 估计方法决策提供信息,因为研究人员在权衡对偏倚、效率和资源分配的关注。未来需要进一步研究,以了解这些结论是否也适用于其他感兴趣的空气污染物的情况。https://doi.org/10.1289/EHP12995.

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5834/10790222/9f148ee8dd6d/ehp12995_f1.jpg

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