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Browsing Faculty Publications by Author "Environmental Health Perspectives, publisher"

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    Assessing United States county-level exposure for research on tropical cyclones and human health
    (Colorado State University. Libraries, 2020-10-28) Anderson, Brooke G., author; Ferreri, Joshua, author; Al-Hamdan, Mohammad, author; Crosson, William, author; Schumacher, Andrea, author; Guikema, Seth, author; Quiring, Steven, author; Eddelbuettel, Dirk, author; Yan, Meilin, author; Peng, Roger D., author; Environmental Health Perspectives, publisher
    Background: Tropical cyclone epidemiology can be advanced through exposure assessment methods that are comprehensive and consistent across space and time, as these facilitate multiyear, multistorm studies. Further, an understanding of patterns in and between exposure metrics that are based on specific hazards of the storm can help in designing tropical cyclone epidemiological research. Objectives: a) Provide an open-source data set for tropical cyclone exposure assessment for epidemiological research; and b) investigate patterns and agreement between county-level assessments of tropical cyclone exposure based on different storm hazards. Methods: We created an open-source data set with data at the county level on exposure to four tropical cyclone hazards: peak sustained wind, rainfall, flooding, and tornadoes. The data cover all eastern U.S. counties for all land-falling or near-land Atlantic basin storms, covering 1996–2011 for all metrics and up to 1988–2018 for specific metrics. We validated measurements against other data sources and investigated patterns and agreement among binary exposure classifications based on these metrics, as well as compared them to use of distance from the storm’s track, which has been used as a proxy for exposure in some epidemiological studies. Results: Our open-source data set was typically consistent with data from other sources, and we present and discuss areas of disagreement and other caveats. Over the study period and area, tropical cyclones typically brought different hazards to different counties. Therefore, when comparing exposure assessment between different hazard-specific metrics, agreement was usually low, as it also was when comparing exposure assessment based on a distance-based proxy measurement and any of the hazard-specific metrics. Discussion: Our results provide a multihazard data set that can be leveraged for epidemiological research on tropical cyclones, as well as insights that can inform the design and analysis for tropical cyclone epidemiological research.
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    The shape of the concentration–response association between fine particulate matter pollution and human mortality in Beijing, China, and its implications for health impact assessment
    (Colorado State University. Libraries, 2019-06-06) Yan, Meilin, author; Wilson, Ander, author; Bell, Michelle L., author; Peng, Roger D., author; Sun, Qinghua, author; Pu, Weiwei, author; Yin, Xiaomei, author; Li, Tiantian, author; Anderson, Brooke, author; Environmental Health Perspectives, publisher
    Background: Studies found approximately linear short-term associations between particulate matter (PM) and mortality in Western communities. However, in China, where the urban PM levels are typically considerably higher than in Western communities, some studies suggest nonlinearity in this association. Health impact assessments (HIA) of PM in China have generally not incorporated nonlinearity in the concentration–response (C-R) association, which could result in large discrepancies in estimates of excess deaths if the true association is nonlinear. Objectives: We investigated nonlinearity in the C-R associations between with PM with aerodynamic diameter ≤2.5μm (PM2.5) and mortality in Beijing, China, and the sensitivity of HIA to linearity assumptions. Methods: We modeled the C-R association between PM2.5 and cause-specific mortality in Beijing, China (2009–2012), using generalized linear models (GLM). PM2.5 was included through either linear, piecewise-linear, or spline functions to investigate evidence of nonlinearity. To determine the sensitivity of HIA to linearity assumptions, we estimated PM2.5-attributable deaths using both linear- and nonlinear-based C-R associations between PM2.5 and mortality. Results: We found some evidence that, for nonaccidental and circulatory mortality, the shape of the C-R association was relatively flat at lower concentrations of PM2.5, but then had a positive slope at higher concentrations, indicating nonlinearity. Conversely, the shape for respiratory mortality was positive and linear at lower concentrations of PM2.5, but then leveled off at the higher concentrations. Estimates of excess deaths attributable to short-term PM2.5 exposure were, in some cases, very sensitive to the linearity assumption in the association, but in other cases robust to this assumption. Conclusions: Our results demonstrate some evidence of nonlinearity in PM2.5–mortality associations and that an assumption of linearity in this association can influence HIAs, highlighting the importance of understanding potential nonlinearity in the PM2.5–mortality association at the high concentrations of PM2.5 in developing megacities like Beijing. https://doi.org/10.1289/EHP4464