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Effects of Environmental and Socioeconomic Inequalities on Health Outcomes: A Multi-Region Time-Series Study

Iara da Silva (), Caroline Fernanda Hei Wikuats, Elizabeth Mie Hashimoto and Leila Droprinchinski Martins
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Iara da Silva: Graduate Program in Environmental Engineering, Campus Londrina, Federal University of Technology—Paraná, Av. Dos Pioneiros, 3131, Londrina 86036-370, Paraná, Brazil
Caroline Fernanda Hei Wikuats: Graduate Program in Environmental Engineering, Campus Londrina, Federal University of Technology—Paraná, Av. Dos Pioneiros, 3131, Londrina 86036-370, Paraná, Brazil
Elizabeth Mie Hashimoto: Graduate Program in Environmental Engineering, Campus Londrina, Federal University of Technology—Paraná, Av. Dos Pioneiros, 3131, Londrina 86036-370, Paraná, Brazil
Leila Droprinchinski Martins: Graduate Program in Environmental Engineering, Campus Londrina, Federal University of Technology—Paraná, Av. Dos Pioneiros, 3131, Londrina 86036-370, Paraná, Brazil

IJERPH, 2022, vol. 19, issue 24, 1-22

Abstract: The gradual increase in temperatures and changes in relative humidity, added to the aging and socioeconomic conditions of the population, may represent problems for public health, given that future projections predict even more noticeable changes in the climate and the age pyramid, which require analyses at an appropriate spatial scale. To our knowledge, an analysis of the synergic effects of several climatic and socioeconomic conditions on hospital admissions and deaths by cardiorespiratory and mental disorders has not yet been performed in Brazil. Statistical analyses were performed using public time series (1996–2015) of daily health and meteorological data from 16 metropolitan regions (in a subtropical climate zone in South America). Health data were stratified into six groups according to gender and age ranges (40–59; 60–79; and ≥80 years old) for each region. For the regression analysis, two distributions (Poisson and binomial negative) were tested with and without zero adjustments for the complete series and percentiles. Finally, the relative risks were calculated, and the effects based on exposure–response curves were evaluated and compared among regions. The negative binomial distribution fit the data best. High temperatures and low relative humidity were the most relevant risk factors for hospitalizations for cardiovascular diseases (lag = 0), while minimum temperatures were important for respiratory diseases (lag = 2 or 3 days). Temperature extremes, both high and low, were the most important risk factors for mental illnesses at lag 0. Groups with people over 60 years old presented higher risks for cardiovascular and respiratory diseases, while this was observed for the adult group (40-59 years old) in relation to mental disorders. In general, no major differences were found in the results between men and women. However, regions with higher urbanization levels presented risks, mainly for respiratory diseases, while the same was observed for cardiovascular diseases for regions with lower levels of urbanization. The Municipal Human Development Index is an important factor for the occurrence of diseases and deaths for all regions, depending on the evaluated group, representing high risks for health outcomes (the value for hospitalization for cardiovascular diseases was 1.6713 for the female adult group in the metropolitan region Palmas, and the value for hospitalization for respiratory diseases was 1.7274 for the female adult group in the metropolitan region Campo Mourão). In general, less developed regions have less access to adequate health care and better living conditions.

Keywords: temperature extremes; socioeconomic conditions; climate and health; regression analysis; relative risk (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
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