Science Advances · 2020 · 1.4K citations · 43 references
Public HealthEnvironmental SciencesPopulation Health SciencesEnvironmental HealthEpidemiologic MethodsEpidemiologyAir PollutantsAir Pollution EpidemiologyAir QualityEnvironmental Determinants Of HealthEnvironmental EpidemiologyEnvironmental Health EpidemiologyAir Pollution Exposure RiskAir Pollution RiskData AvailabilityEcological StudiesEpidemiology Of Air Pollution Health EffectsLong-term Exposure Effects
Limitations in COVID‑19 data availability and quality, and the fact that publicly available outcome data are only area‑level counts, hinder conclusive studies on the impact of air pollution. The study aims to assess whether long‑term exposure to air pollution increases COVID‑19 severity, including mortality. The authors used an ecological regression analysis, which prevents controlling for individual‑level risk factors. In a preliminary U.S.
Assessing whether long-term exposure to air pollution increases the severity of COVID-19 health outcomes, including death, is an important public health objective. Limitations in COVID-19 data availability and quality remain obstacles to conducting conclusive studies on this topic. At present, publicly available COVID-19 outcome data for representative populations are available only as area-level counts. Therefore, studies of long-term exposure to air pollution and COVID-19 outcomes using these data must use an ecological regression analysis, which precludes controlling for individual-level COVID-19 risk factors. We describe these challenges in the context of one of the first preliminary investigations of this question in the United States, where we found that higher historical PM
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Fitting Linear Mixed-Effects Models Using <b>lme4</b>
Douglas M. Bates, Martin Mächler, Benjamin M. Bolker et al. · Journal of Statistical Software · 2015 · 85.6K citations · Full text
Likelihood Ratio Tests for Model Selection and Non-Nested Hypotheses
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