Association between Heat Exposure and Hospitalization for Diabetes in Brazil during 2000–2015: A Nationwide Case-Crossover Study

Xu, Rongbin; Zhao, Qi; Coelho, Micheline S.Z.S.; Saldiva, Paulo Hilário Nascimento; Zoungas, Sophia; Huxley, Rachel R.; Abramson, Michael J.; Lee, Hyewon; Li, Shanshan

doi:10.1289/ehp5688

Cited by 52 publications

(35 citation statements)

References 46 publications

(47 reference statements)

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“…These changes may compromise the body’s ability to regulate temperature leading to a range of health outcomes, including heat exhaustion, heatstroke, and hyperthermia [ 6 ]. Exposure to extreme heat events can worsen cardiovascular and respiratory diseases, as well as other chronic conditions, such as cerebrovascular disease, diabetes, and kidney disease [ 7 , 8 ]. The mechanisms by which heat exacerbates respiratory disease are not well understood.…”

Section: Introductionmentioning

confidence: 99%

Synergistic health effects of air pollution, temperature, and pollen exposure: a systematic review of epidemiological evidence

et al. 2020

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Background Exposure to heat, air pollution, and pollen are associated with health outcomes, including cardiovascular and respiratory disease. Studies assessing the health impacts of climate change have considered increased exposure to these risk factors separately, though they may be increasing simultaneously for some populations and may act synergistically on health. Our objective is to systematically review epidemiological evidence for interactive effects of multiple exposures to heat, air pollution, and pollen on human health. Methods We systematically searched electronic literature databases (last search, April 29, 2019) for studies reporting quantitative measurements of associations between at least two of the exposures and mortality from any cause and cardiovascular and respiratory morbidity and mortality specifically. Following the Navigation Guide systematic review methodology, we evaluated the risk of bias of individual studies and the overall quality and strength of evidence. Results We found 56 studies that met the inclusion criteria. Of these, six measured air pollution, heat, and pollen; 39 measured air pollution and heat; 10 measured air pollution and pollen; and one measured heat and pollen. Nearly all studies were at risk of bias from exposure assessment error. However, consistent exposure-response across studies led us to conclude that there is overall moderate quality and sufficient evidence for synergistic effects of heat and air pollution. We concluded that there is overall low quality and limited evidence for synergistic effects from simultaneous exposure to (1) air pollution, pollen, and heat; and (2) air pollution and pollen. With only one study, we were unable to assess the evidence for synergistic effects of heat and pollen. Conclusions If synergistic effects between heat and air pollution are confirmed with additional research, the health impacts from climate change-driven increases in air pollution and heat exposure may be larger than previously estimated in studies that consider these risk factors individually.

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Section: Introductionmentioning

confidence: 99%

Synergistic health effects of air pollution, temperature, and pollen exposure: a systematic review of epidemiological evidence

et al. 2020

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“…Authors' contributions: XS made search strategy and wrote the article; LJ analyzed data, assessed risk of bias and wrote the article; DZ wrote the article; XW searched articles and assessed risk of bias; YM and YH selected studies and extracted data, XL and JT selected studies; YM and DZ wrote the protocol and registered at the PROSPERO; WH, AS and YF checked data and results of RoB assessment; YZ made some suggestions for improvement of this article. Basagaña et al 2011Campbell et al 2019Green et al 2010He et al 2019Kim et al 2015Liu et al 2018Méndez-Lázaro et al 2016Ostro et al 2010Xu et al 2019Stafoggia et al 2006Bai et al 2016Basu et al 2012Calkins et al 2016Gasparrini et al 2015Isaksen et al 2015Li et al 2017Li et al 2014bLi et al 2014aOgbomo et al 2016Åström et al 2015Pudpong and Hajat. 2011Seposo et al 2017Sherbakov et al 2018Chen et al 2017Vaneckova et al 2013Wang et al 2012Wang et al 2014Wilson et al 2013Winquist et al 2016Yang et al 2016Ma et al 2020 Overall analysis of extreme temperatures on diabetes Figure 3 Overall analysis of extreme temperatures on diabetes Figure 4 Overall analysis of extreme temperatures on diabetes Figure 5 Impact of heat exposures on diabetes mortality and morbidity Figure 7 Impact of heat exposures on diabetes mortality and morbidity…”

Section: Declarationsmentioning

confidence: 99%

Impact of short-term exposure to extreme temperatures on diabetes mellitus morbidity and mortality? A systematic review and meta-analysis

Song

Jiang

Zhang

et al. 2021

Environ Sci Pollut Res

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The relationship between diabetes mellitus and short-term exposure to extreme temperatures remains controversial. A systematic review and metaanalysis were performed to assess the association between extreme temperatures and diabetes mellitus morbidity and mortality. PubMed, Embase, the Cochrane Library, Web of Science and the Cumulative Index to Nursing and Allied Health Literature (CINAHL) were searched since inception to January 1, 2019, and updated on November 17, 2020. The results were combined using random effects model and reported as relative risk (RR) with 95% con dence interval (CI). 32 studies met the included criteria. (1) Both heat and cold exposures have impact on diabetes. (2) For heat exposure, the subgroup analysis revealed that the effect on diabetes mortality (RR = 1.139, 95% CI: 1.089-1.192) was higher than morbidity (RR = 1.012, 95% CI: 1.004-1.019). (3) With the increase of de nition threshold, the impact of heat exposure on diabetes rised. (4) A stronger association between heat exposure and diabetes was observed in the elderly (≥ 60 years old) (RR = 1.040, 95% CI: 1.017-1.064). In conclusion, both short-term exposure to heat and cold temperatures have impact on diabetes. The elderly is the vulnerable population of diabetes exposure to heat temperature. Developing de nitions of heatwaves at the regional level are suggested.

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“…The data collection for this timeseries study has been described in detail in our previous publications. 10,13,[15][16][17]…”

Section: Study Setting and Datasetmentioning

confidence: 99%

Socioeconomic inequality in vulnerability to all-cause and cause-specific hospitalisation associated with temperature variability: a time-series study in 1814 Brazilian cities

Zhao

Coelho

et al. 2020

The Lancet Planetary Health

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Background Exposure to temperature variability has been associated with increased risk of mortality and morbidity. We aimed to evaluate whether the association between short-term temperature variability and hospitalisation was affected by local socioeconomic level in Brazil. MethodsIn this time-series study, we collected city-level socioeconomic data, and daily hospitalisation and weather data from 1814 Brazilian cities between Jan 1, 2000, and Dec 31, 2015. All-cause and cause-specific hospitalisation data was from the Hospital Information System of the Unified Health System in Brazil. City-specific daily minimum and maximum temperatures came from a 0•25° × 0•25° Brazilian meteorological dataset. We represented city-specific socioeconomic level using literacy rate, urbanisation rate, average monthly household income per capita (using the 2000 and 2010 Brazilian census), and GDP per capita (using statistics from the Brazilian Institute of Geography and Statistics for 2000-15), and cities were categorised according to the 2015 World Bank standard. We used quasi-Poisson regression to do time-series analyses and obtain city-specific associations between temperature variability and hospitalisation. We pooled city-specific estimates according to different socioeconomic quartiles or levels using random-effect meta-analyses. Meta-regressions adjusting for demographic and climatic characteristics were used to evaluate the modification effect of city-level socioeconomic indicators on the association between temperature variability and hospitalisation. Findings We included a total of 147 959 243 hospitalisations (59•0% female) during the study period. Overall, we estimated that the hospitalisation risk due to every 1°C increase in the temperature variability in the current and previous day (TV 0-1 ) increased by 0•52% (95% CI 0•50−0•55). For lower-middle-income cities, this risk was 0•63% (95% CI 0•58-0•69), for upper-middle-income cities it was 0•50% (0•47-0•53), and for high-income cities it was 0•39% (0•33-0•46). The socioeconomic inequality in vulnerability to TV 0-1 was especially evident for people aged 0-19 years (effect estimate 1•21% [1•11-1•31] for lower-middle income vs 0•52% [0•41-0•63] for high income) and people aged 60 years or older (0•60% [0•50-0•70] vs 0•43% [0•31-0•56]), and for hospitalisation due to infectious diseases (1•62% [1•46-1•78] vs 0•56% [0•30-0•82]), respiratory diseases (1•32% [1•20-1•44] vs 0•55% [0•37-0•74]), and endocrine diseases (1•21% [0•99-1•43] vs 0•32% [0•02-0•62]).Interpretation People living in less developed cities in Brazil were more vulnerable to hospitalisation related to temperature variability. This disparity could exacerbate existing health and socioeconomic inequalities in Brazil, and it suggests that more attention should be paid to less developed areas to mitigate the adverse health effects of shortterm temperature fluctuations.

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Association between Heat Exposure and Hospitalization for Diabetes in Brazil during 2000–2015: A Nationwide Case-Crossover Study

Cited by 52 publications

References 46 publications

Synergistic health effects of air pollution, temperature, and pollen exposure: a systematic review of epidemiological evidence

Synergistic health effects of air pollution, temperature, and pollen exposure: a systematic review of epidemiological evidence

Impact of short-term exposure to extreme temperatures on diabetes mellitus morbidity and mortality? A systematic review and meta-analysis

Socioeconomic inequality in vulnerability to all-cause and cause-specific hospitalisation associated with temperature variability: a time-series study in 1814 Brazilian cities

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