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Influence of Indoor Temperature Exposure on Emergency Department Visits Due to Infectious and Non-Infectious Respiratory Diseases for Older People

Author

Listed:
  • Chien-Cheng Jung

    (Department of Public Health, China Medical University, Taichung City 406060, Taiwan)

  • Nai-Tzu Chen

    (Research Center of Environmental Trace Toxic Substances, National Cheng Kung University, Tainan City 70403, Taiwan)

  • Ying-Fang Hsia

    (Big Data Center, China Medical University Hospital, Taichung City 404332, Taiwan)

  • Nai-Yun Hsu

    (Department of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, Tainan City 70403, Taiwan)

  • Huey-Jen Su

    (Department of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, Tainan City 70403, Taiwan)

Abstract

Previous studies have demonstrated that outdoor temperature exposure was an important risk factor for respiratory diseases. However, no study investigates the effect of indoor temperature exposure on respiratory diseases and further assesses cumulative effect. The objective of this study is to study the cumulative effect of indoor temperature exposure on emergency department visits due to infectious (IRD) and non-infectious (NIRD) respiratory diseases among older adults. Subjects were collected from the Longitudinal Health Insurance Database in Taiwan. The cumulative degree hours (CDHs) was used to assess the cumulative effect of indoor temperature exposure. A distributed lag nonlinear model with quasi-Poisson function was used to analyze the association between CDHs and emergency department visits due to IRD and NIRD. For IRD, there was a significant risk at 27, 28, 29, 30, and 31 °C when the CDHs exceeded 69, 40, 14, 5, and 1 during the cooling season (May to October), respectively, and at 19, 20, 21, 22, and 23 °C when the CDHs exceeded 8, 1, 1, 35, and 62 during the heating season (November to April), respectively. For NIRD, there was a significant risk at 19, 20, 21, 22, and 23 °C when the CDHs exceeded 1, 1, 16, 36, and 52 during the heating season, respectively; the CDHs at 1 was only associated with the NIRD at 31 °C during the cooling season. Our data also indicated that the CDHs was lower among men than women. We conclude that the cumulative effects of indoor temperature exposure should be considered to reduce IRD risk in both cooling and heating seasons and NIRD risk in heating season and the cumulative effect on different gender.

Suggested Citation

  • Chien-Cheng Jung & Nai-Tzu Chen & Ying-Fang Hsia & Nai-Yun Hsu & Huey-Jen Su, 2021. "Influence of Indoor Temperature Exposure on Emergency Department Visits Due to Infectious and Non-Infectious Respiratory Diseases for Older People," IJERPH, MDPI, vol. 18(10), pages 1-11, May.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:10:p:5273-:d:555403
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    References listed on IDEAS

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    1. Satman, A & Yalcinkaya, N, 1999. "Heating and cooling degree-hours for Turkey," Energy, Elsevier, vol. 24(10), pages 833-840.
    2. Papakostas, K. & Kyriakis, N., 2005. "Heating and cooling degree-hours for Athens and Thessaloniki, Greece," Renewable Energy, Elsevier, vol. 30(12), pages 1873-1880.
    3. Chia-Tsung Yeh & Ya-Yun Cheng & Tsai-Yun Liu, 2020. "Spatial Characteristics of Urban Green Spaces and Human Health: An Exploratory Analysis of Canonical Correlation," IJERPH, MDPI, vol. 17(9), pages 1-14, May.
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