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Spatiotemporal and demographic variation in the association between temperature variability and hospitalizations in Brazil during 2000–2015: A nationwide time-series study
journal contributionposted on 2018-11-01, 00:00 authored by Q Zhao, M S Z S Coelho, S Li, P H N Saldiva, K Hu, M J Abramson, Rachel HuxleyRachel Huxley, Y Guo
© 2018 Elsevier Ltd Background: Extreme temperature events are known to be adversely associated with a range of health outcomes, but little is known about the effect of less extreme, but more frequent fluctuation in temperature. We examined the spatiotemporal and demographic variation in the effect of temperature variability (TV) on nationwide hospitalizations in Brazil during 2000–2015. Methods: Data on daily hospitalizations and weather variables were collected from 1814 cities, comprising 78.4% of Brazilian population. TV was defined as the standard deviation of daily minimum and maximum temperatures during exposure days. City-specific TV effect was estimated using a quasi-Poisson regression model, and then pooled at the national and regional level using meta-analysis. Stratified analyses were performed by sex, 10 age-groups, and 11 cause categories. Meta-regression was applied to city-year-specific estimates to examine the temporal change. Results: The estimate of TV effect peaked on 0–1 days’ exposure, contributing to 3.5% [95% confidence interval (CI): 3.1–3.8%] of hospitalizations nationwide, equalling 221 (95%CI: 200–242) cases per 100,000 population annually. The effect estimate varied across 11 cause categories, which was strongest for respiratory admissions. Males, particular those 10–49 year old were more affected than females but there was no sex difference for the attributable hospitalization rate. The attributable rate for the under-fives was twice as high as for the elderly, and five times higher than in adults. The majority of the most affected cities were located in the central west and the inland of northeast. The risk of hospitalization related to TV showed a significant increase over the 16-year period at the national level. Conclusions: In Brazil, the effect of TV on hospitalization is acute, and varies by spatial, sex, age, and cause category. Given there is no evidence regarding TV adaptation, hospitalization burden associated with TV is likely to further increase and warrants consideration when developing future public health policies in the context of climate change.