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Diurnal temperature range and hospital admission due to cardiovascular and respiratory diseases in Dezful, a city with hot climate and high DTR fluctuation in Iran: an ecological time-series study.

Hamidreza AghababaeianRahim SharafkhaniMaryam KiarsiShahzad MehranfarAhmad MoosaviLadan Araghi AhvaziOmid Aboubakri
Published in: Environmental geochemistry and health (2023)
The results of previous studies have indicated the effects of temperature changes on health status. The present study was conducted to investigate the effects of diurnal temperature range (DTR) and hospital admission on cardiovascular and respiratory diseases in Dezful, in Iran. In this ecological time-series study, data related to hospital admissions based on ICD-10, meteorological, and climatological data were gathered over a period of six years from 2014 to 2019. A distributed lag nonlinear model combined with a quasi-Poisson regression was then used to assess the impact of DTR on cardiovascular and respiratory hospital admissions. Potential confounders, including wind speed, air pollution, seasonality, time trend, weekends and holidays, days of week, and humidity were controlled. In extreme low DTRs, the cumulative effects of cardiovascular admissions significantly increased in total, and in warm and cold seasons (Lag 0-21 , P ≤ 0.05). In addition, in extreme high DTRs, the cumulative effects of cardiovascular significantly decreased in total (Lag 0-13 and Lag 0-21 , P ≤ 0.05), and in warm (Lag 0-21 , P ≤ 0.05) and cold seasons (Lag 0-21 , P ≤ 0.05). Moreover, respiratory admissions significantly decreased in total (Lag 0-21 , P ≤ 0.05) and in warm season (Lag 0-21 , P ≤ 0.05).Our result indicates that extreme low DTRs could increase the risk of daily cardiovascular admissions, and extreme high DTRs may cause a protective effect on daily respiratory and cardiovascular admissions in some regions with high fluctuations in DTR.
Keyphrases
  • climate change
  • air pollution
  • healthcare
  • emergency department
  • electronic health record
  • cystic fibrosis
  • chronic obstructive pulmonary disease
  • particulate matter
  • big data