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High-mortality days during the winter season: comparing meteorological conditions across 5 US cities

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Abstract

While the relationship between weather and human health has been studied from various perspectives, this study examines an alternative method of analysis by examining weather conditions on specific high-mortality days during the winter season. These high-mortality days, by definition, represent days with dramatic increases in mortality and the days with the highest mortality. By focusing solely on high-mortality days, this research examines the relationship between weather variables and mortality through a synoptic climatology, environment-to circulation approach. The atmospheric conditions during high-mortality days were compared to the days prior and the days not classified as high-mortality days. Similar patterns emerged across all five locations despite the spatial and temporal variability. Southern locations had a stronger relationship with temperature changes while northern locations showed a greater relationship to atmospheric pressure. Overall, all high-mortality days were associated with warmer temperatures, decreased pressure, and a greater likelihood of precipitation when compared to the previous subset of days. While the atmospheric conditions were consistent across all locations, the importance of the lag effect should not be overlooked as a contributing factor to mortality during the winter season. Through a variety of diverse, methodological approaches, future studies may build upon these results and explore in more detail the complex relationship between weather situations and the impact of short-term changes in weather and health outcomes.

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Acknowledgments

We would like to thank Tom Schmidlin and Debarchana Ghosh for their insight and assistance with this research, and the helpful comments of the anonymous reviewers in improving our manuscript.

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Correspondence to Michael J. Allen.

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Allen, M.J., Sheridan, S.C. High-mortality days during the winter season: comparing meteorological conditions across 5 US cities. Int J Biometeorol 58, 217–225 (2014). https://doi.org/10.1007/s00484-013-0640-4

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  • DOI: https://doi.org/10.1007/s00484-013-0640-4

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