The effects of hot and cold temperatures on hospital admissions for respiratory diseases in Campo Grande, MS, Brazil
Abstract
Introduction: It examined the relationship between temperatures and hospital admissions for respiratory diseases in the city of Campo Grande, Brazil, during 2008-2014. Methods: We used a distributed lag of the nonlinear model (DLNM) to examine the nonlinear effects of temperature on admissions hospital for respiratory diseases by age group. Results: Nonlinear temperature effects were found in hospitalization for respiratory diseases by age group. Both hot and cold effects can last longer - a statistically significant relationship between the extreme temperatures and hospital admissions in all age groups in the gap. The heat had a greater impact on the elderly, while those aged 5-60 years were more sensitive to cold temperatures. The greatest risk of cumulative effects of heat was observed among those over 65 years at lag 0-25 (HR 1.509, 95% CI: 1.209 to 1.883), while those aged 65 years were at greater risk of exposure the extreme temperatures of cold lagged 0-25 (RR 1.482, 95% CI: 1.231 to 1.785). Conclusions: This study provides useful data for policy managers' decisions to better manage the health impacts of hot and cold temperatures.
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