Socioeconomic level and associations between heat exposure and all-cause and cause-specific hospitalization in 1,814 Brazilian cities: A nationwide case-crossover study

Autoři: Rongbin Xu aff001;  Qi Zhao aff002;  Micheline S. Z. S. Coelho aff003;  Paulo H. N. Saldiva aff003;  Michael J. Abramson aff002;  Shanshan Li aff002;  Yuming Guo aff001
Působiště autorů: School of Public Health and Management, Binzhou Medical University, Yantai, China aff001;  School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia aff002;  Institute of Advanced Studies, University of São Paulo, São Paulo, Brazil aff003
Vyšlo v časopise: Socioeconomic level and associations between heat exposure and all-cause and cause-specific hospitalization in 1,814 Brazilian cities: A nationwide case-crossover study. PLoS Med 17(10): e32767. doi:10.1371/journal.pmed.1003369
Kategorie: Research Article



Heat exposure, which will increase with global warming, has been linked to increased risk of a range of types of cause-specific hospitalizations. However, little is known about socioeconomic disparities in vulnerability to heat. We aimed to evaluate whether there were socioeconomic disparities in vulnerability to heat-related all-cause and cause-specific hospitalization among Brazilian cities.

Methods and findings

We collected daily hospitalization and weather data in the hot season (city-specific 4 adjacent hottest months each year) during 2000–2015 from 1,814 Brazilian cities covering 78.4% of the Brazilian population. A time-stratified case-crossover design modeled by quasi-Poisson regression and a distributed lag model was used to estimate city-specific heat–hospitalization association. Then meta-analysis was used to synthesize city-specific estimates according to different socioeconomic quartiles or levels. We included 49 million hospitalizations (58.5% female; median [interquartile range] age: 33.3 [19.8–55.7] years). For cities of lower middle income (LMI), upper middle income (UMI), and high income (HI) according to the World Bank’s classification, every 5°C increase in daily mean temperature during the hot season was associated with a 5.1% (95% CI 4.4%–5.7%, P < 0.001), 3.7% (3.3%–4.0%, P < 0.001), and 2.6% (1.7%–3.4%, P < 0.001) increase in all-cause hospitalization, respectively. The inter-city socioeconomic disparities in the association were strongest for children and adolescents (0–19 years) (increased all-cause hospitalization risk with every 5°C increase [95% CI]: 9.9% [8.7%–11.1%], P < 0.001, in LMI cities versus 5.2% [4.1%–6.3%], P < 0.001, in HI cities). The disparities were particularly evident for hospitalization due to certain diseases, including ischemic heart disease (increase in cause-specific hospitalization risk with every 5°C increase [95% CI]: 5.6% [−0.2% to 11.8%], P = 0.060, in LMI cities versus 0.5% [−2.1% to 3.1%], P = 0.717, in HI cities), asthma (3.7% [0.3%–7.1%], P = 0.031, versus −6.4% [−12.1% to −0.3%], P = 0.041), pneumonia (8.0% [5.6%–10.4%], P < 0.001, versus 3.8% [1.1%–6.5%], P = 0.005), renal diseases (9.6% [6.2%–13.1%], P < 0.001, versus 4.9% [1.8%–8.0%], P = 0.002), mental health conditions (17.2% [8.4%–26.8%], P < 0.001, versus 5.5% [−1.4% to 13.0%], P = 0.121), and neoplasms (3.1% [0.7%–5.5%], P = 0.011, versus −0.1% [−2.1% to 2.0%], P = 0.939). The disparities were similar when stratifying the cities by other socioeconomic indicators (urbanization rate, literacy rate, and household income). The main limitations were lack of data on personal exposure to temperature, and that our city-level analysis did not assess intra-city or individual-level socioeconomic disparities and could not exclude confounding effects of some unmeasured variables.


Less developed cities displayed stronger associations between heat exposure and all-cause hospitalizations and certain types of cause-specific hospitalizations in Brazil. This may exacerbate the existing geographical health and socioeconomic inequalities under a changing climate.

Klíčová slova:

Asthma – Brazil – Cities – Economic analysis – Morbidity – Seasons – Socioeconomic aspects of health – Urbanization


1. Watts N, Amann M, Ayeb-Karlsson S, Belesova K, Bouley T, Boykoff M, et al. The Lancet Countdown on health and climate change: from 25 years of inaction to a global transformation for public health. Lancet. 2018;391(10120):581–630. doi: 10.1016/S0140-6736(17)32464-9

2. Benmarhnia T, Deguen S, Kaufman JS, Smargiassi A. Review article: vulnerability to heat-related mortality: a systematic review, meta-analysis, and meta-regression analysis. Epidemiology. 2015;26(6):781–93. doi: 10.1097/EDE.0000000000000375 26332052

3. Chen K, Zhou L, Chen X, Ma Z, Liu Y, Huang L, et al. Urbanization level and vulnerability to heat-related mortality in Jiangsu Province, China. Environ Health Perspect. 2016;124(12):1863–9. doi: 10.1289/EHP204 27152420

4. Hu K, Guo Y, Hochrainer-Stigler S, Liu W, See L, Yang X, et al. Evidence for urban–rural disparity in temperature–mortality relationships in Zhejiang Province, China. Environ Health Perspect. 2019;127(3):37001. doi: 10.1289/EHP3556 30822387

5. Zanobetti A, O’Neill MS, Gronlund CJ, Schwartz JD. Susceptibility to mortality in weather extremes effect modification by personal and small-area characteristics. Epidemiology. 2013;24(6):809–19. doi: 10.1097/01.ede.0000434432.06765.91 24045717

6. Kovach MM, Konrad CE II, Fuhrmann CM. Area-level risk factors for heat-related illness in rural and urban locations across North Carolina, USA. Appl Geogr. 2015;60:175–83. doi: 10.1016/j.apgeog.2015.03.012

7. Harlan SL, Declet-Barreto JH, Stefanov WL, Petitti DB. Neighborhood effects on heat deaths: social and environmental predictors of vulnerability in Maricopa County, Arizona. Environ Health Perspect. 2012;121(2):197–204. doi: 10.1289/ehp.1104625 23164621

8. Berko J, Ingram DD, Saha S, Parker JD. Deaths attributed to heat, cold, and other weather events in the United States, 2006–2010. Natl Health Stat Report. 2014;(76):1–15.

9. Madrigano J, Jack D, Anderson GB, Bell ML, Kinney PL. Temperature, ozone, and mortality in urban and non-urban counties in the northeastern United States. Environ Health. 2015;14:3. doi: 10.1186/1476-069X-14-3 25567355

10. Vicedo-Cabrera AM, Gasparrini A, Armstrong B, Sera F, Guo Y, Hashizume M, et al. How urban characteristics affect vulnerability to heat and cold: a multi-country analysis. Int J Epidemiol. 2019; 48(4):1101–12. doi: 10.1093/ije/dyz008 30815699

11. Burkart K, Schneider A, Breitner S, Khan MH, Krämer A, Endlicher W. The effect of atmospheric thermal conditions and urban thermal pollution on all-cause and cardiovascular mortality in Bangladesh. Environ Pollut. 2011;159(8–9):2035–43. doi: 10.1016/j.envpol.2011.02.005 21377776

12. Hajat S, Kosatky T. Heat-related mortality: a review and exploration of heterogeneity. J Epidemiol Community Health. 2010;64(9):753–60. doi: 10.1136/jech.2009.087999 19692725

13. Zhang YQ, Yu CH, Bao JZ, Li XD. Impact of temperature on mortality in Hubei, China: a multi-county time series analysis. Sci Rep. 2017;7:45093. doi: 10.1038/srep45093 28327609

14. Bennett JE, Blangiardo M, Fecht D, Elliott P, Ezzati M. Vulnerability to the mortality effects of warm temperature in the districts of England and Wales. Nat Clim Chang. 2014;4(4):269. doi: 10.1038/nclimate2123

15. Hattis D, Ogneva-Himmelberger Y, Ratick S. The spatial variability of heat-related mortality in Massachusetts. Appl Geogr. 2012;33:45–52. doi: 10.1016/j.apgeog.2011.07.008

16. Yu WW, Vaneckova P, Mengersen K, Pan XC, Tong SL. Is the association between temperature and mortality modified by age, gender and socio-economic status? Sci Total Environ. 2010;408(17):3513–8. doi: 10.1016/j.scitotenv.2010.04.058 20569969

17. Phung D, Guo YM, Nguyen HTL, Rutherford S, Baum S, Chu C. High temperature and risk of hospitalizations, and effect modifying potential of socio-economic conditions: a multi-province study in the tropical Mekong Delta Region. Environ Int. 2016;92–93:77–86. doi: 10.1016/j.envint.2015.11.003 26562560

18. Hondula DM, Barnett AG. Heat-related morbidity in Brisbane, Australia: spatial variation and area-level predictors. Environ Health Perspect. 2014;122(8):831–6. doi: 10.1289/ehp.1307496 24787277

19. Phung D, Chu C, Tran DN, Huang CR. Spatial variation of heat-related morbidity: a hierarchical Bayesian analysis in multiple districts of the Mekong Delta Region. Sci Total Environ. 2018;637:1559–65. doi: 10.1016/j.scitotenv.2018.05.131 29801249

20. Urban A, Davidkovova H, Kysely J. Heat- and cold-stress effects on cardiovascular mortality and morbidity among urban and rural populations in the Czech Republic. Int J Biometeorol. 2014;58(6):1057–68. doi: 10.1007/s00484-013-0693-4 23793998

21. Song X, Wang S, Hu Y, Yue M, Zhang T, Liu Y, et al. Impact of ambient temperature on morbidity and mortality: an overview of reviews. Sci Total Environ. 2017;586:241–54. doi: 10.1016/j.scitotenv.2017.01.212 28187945

22. Zhao Q, Li S, Coelho M, Saldiva PHN, Hu K, Abramson MJ, et al. Assessment of intraseasonal variation in hospitalization associated with heat exposure in Brazil. JAMA Netw Open. 2019;2(2):e187901. doi: 10.1001/jamanetworkopen.2018.7901 30735233

23. Zhao Q, Li S, Coelho M, Saldiva PHN, Hu K, Arblaster JM, et al. Geographic, demographic, and temporal variations in the association between heat exposure and hospitalization in Brazil: a nationwide study between 2000 and 2015. Environ Health Perspect. 2019;127(1):17001. doi: 10.1289/EHP3889 30620212

24. Zhao Q, Coelho MSZS, Li S, Saldiva PHN, Abramson MJ, Huxley RR, et al. Trends in hospital admission rates and associated direct healthcare costs in Brazil: a nationwide retrospective study between 2000 and 2015. The Innovation. 2020;1(1):100013. doi: 10.1016/j.xinn.2020.04.013

25. Xavier AC, King CW, Scanlon BR. Daily gridded meteorological variables in Brazil (1980–2013). Int J Climatol. 2016;36(6):2644–59.

26. Guo Y. Hourly associations between heat and ambulance calls. Environ Pollut. 2017;220:1424–8. doi: 10.1016/j.envpol.2016.10.091 27825842

27. Guo Y, Barnett Adrian G, Pan X, Yu W, Tong S. The impact of temperature on mortality in Tianjin, China: a case-crossover design with a distributed lag nonlinear model. Environ Health Perspect. 2011;119(12):1719–25. doi: 10.1289/ehp.1103598 21827978

28. Gasparrini A. Distributed lag linear and non-linear models in R: the package dlnm. J Stat Softw. 2011;43(8):1–20. 22003319

29. Gasparrini A, Armstrong B. Reducing and meta-analysing estimates from distributed lag non-linear models. BMC Med Res Methodol. 2013;13:1. doi: 10.1186/1471-2288-13-1 23297754

30. Romero-Lankao P, Qin H, Dickinson K. Urban vulnerability to temperature-related hazards: a meta-analysis and meta-knowledge approach. Glob Environ Change. 2012;22(3):670–83. doi: 10.1016/j.gloenvcha.2012.04.002

31. Gronlund CJ. Racial and socioeconomic disparities in heat-related health effects and their mechanisms: a review. Curr Epidemiol Rep. 2014;1(3):165–73. doi: 10.1007/s40471-014-0014-4 25512891

32. Malta DC, Bernal RT, de Souza MF, Szwarcwald CL, Lima MG, Barros MB. Social inequalities in the prevalence of self-reported chronic non-communicable diseases in Brazil: national health survey 2013. Int J Equity Health. 2016;15(1):153. doi: 10.1186/s12939-016-0427-4 27852264

33. Medina-Ramon M, Schwartz J. Temperature, temperature extremes, and mortality: a study of acclimatisation and effect modification in 50 US cities. Occup Environ Med. 2007;64(12):827–33. doi: 10.1136/oem.2007.033175 17600037

34. Hajat S, O’Connor M, Kosatsky T. Health effects of hot weather: from awareness of risk factors to effective health protection. Lancet. 2010;375(9717):856–63. doi: 10.1016/S0140-6736(09)61711-6 20153519

35. Forrester S. Residential cooling load impacts on brazil’s electricity demand [thesis]. Ann Arbor (MI): University of Michigan; 2019 [cited 2020 Sep 8]. Available from:

36. Sampson NR, Gronlund CJ, Buxton MA, Catalano L, White-Newsome JL, Conlon KC, et al. Staying cool in a changing climate: reaching vulnerable populations during heat events. Glob Environ Change. 2013;23(2):475–84. doi: 10.1016/j.gloenvcha.2012.12.011 29375195

37. Tan J, Zheng Y, Tang X, Guo C, Li L, Song G, et al. The urban heat island and its impact on heat waves and human health in Shanghai. Int J Biometeorol. 2010;54(1):75–84. doi: 10.1007/s00484-009-0256-x 19727842

38. Heaviside C, Macintyre H, Vardoulakis S. The urban heat island: implications for health in a changing environment. Curr Environ Health Rep. 2017;4(3):296–305. doi: 10.1007/s40572-017-0150-3 28695487

39. Xu ZW, Crooks JL, Davies JM, Khan A, Hu WB, Tong SL. The association between ambient temperature and childhood asthma: a systematic review. Int J Biometeorol. 2018;62(3):471–81. doi: 10.1007/s00484-017-1455-5 29022096

40. Bobb JF, Obermeyer Z, Wang Y, Dominici F. Cause-specific risk of hospital admission related to extreme heat in older adults. JAMA. 2014;312(24):2659–67. doi: 10.1001/jama.2014.15715 25536257

41. Kokotailo RA, Hill MD. Coding of stroke and stroke risk factors using International Classification of Diseases, revisions 9 and 10. Stroke. 2005;36(8):1776–81. doi: 10.1161/01.STR.0000174293.17959.a1 16020772

42. Wondmagegn BY, Xiang JJ, Williams S, Pisaniello D, Bi P. What do we know about the healthcare costs of extreme heat exposure? A comprehensive literature review. Sci Total Environ. 2019;657:608–18. doi: 10.1016/j.scitotenv.2018.11.479 30677927

43. Gasparrini A, Guo Y, Hashizume M, Kinney PL, Petkova EP, Lavigne E, et al. Temporal variation in heat-mortality associations: a multicountry study. Environ Health Perspect. 2015;123(11):1200–7. doi: 10.1289/ehp.1409070 25933359

44. Carson C, Hajat S, Armstrong B, Wilkinson P. Declining vulnerability to temperature-related mortality in London over the 20th century. Am J Epidemiol. 2006;164(1):77–84. doi: 10.1093/aje/kwj147 16624968

45. Hosseinpoor AR, Bergen N, Magar V. Monitoring inequality: an emerging priority for health post-2015. Bull World Health Organ. 2015;93(9):591–A. doi: 10.2471/BLT.15.162081 26478619

46. Manhaes MA, Loures-Ribeiro A. Spatial distribution and diversity of bird community in an urban area of Southeast Brazil. Braz Arch Biol Technol. 2005;48(2):285–94. doi: 10.1590/S1516-89132005000200016

47. Cavalcante RM, Rocha CA, De Santiago IS, Da Silva TFA, Cattony CM, Silva MVC, et al. Influence of urbanization on air quality based on the occurrence of particle-associated polycyclic aromatic hydrocarbons in a tropical semiarid area (Fortaleza-CE, Brazil). Air Qual Atmos Health. 2017;10(4):437–45. doi: 10.1007/s11869-016-0434-z

48. Leite Silva A, Márcia Longo R. Influence of urbanization on the original vegetation cover in urban river basin: case study in Campinas/SP, Brazil. 19th EGU General Assembly; 2017 Apr 23–28; Vienna; Austria. 2017 [cited 2020 Sep 8]. Available from:

49. Requia WJ, Roig HL, Koutrakis P, Adams MD. Modeling spatial patterns of traffic emissions across 5570 municipal districts in Brazil. J Clean Prod. 2017;148:845–53. doi: 10.1016/j.jclepro.2017.02.010

50. Gronlund CJ, Berrocal VJ, White-Newsome JL, Conlon KC, O’Neill MS. Vulnerability to extreme heat by socio-demographic characteristics and area green space among the elderly in Michigan, 1990–2007. Environ Res. 2015;136:449–61. doi: 10.1016/j.envres.2014.08.042 25460667

51. Burkart K, Meier F, Schneider A, Breitner S, Canario P, Alcoforado MJ, et al. Modification of heat-related mortality in an elderly urban population by vegetation (urban green) and proximity to water (urban blue): evidence from Lisbon, Portugal. Environ Health Perspect. 2016;124(7):927–34. doi: 10.1289/ehp.1409529 26566198

52. Schinasi LH, Benmarhnia T, De Roos AJ. Modification of the association between high ambient temperature and health by urban microclimate indicators: a systematic review and meta-analysis. Environ Res. 2018;161:168–80. doi: 10.1016/j.envres.2017.11.004 29149680

53. Parry M, Green D, Zhang Y, Hayen A. Does particulate matter modify the short-term association between heat waves and hospital admissions for cardiovascular diseases in Greater Sydney, Australia? Int J Environ Res Public Health. 2019;16(18):3270. doi: 10.3390/ijerph16183270 31492044

54. Patel D, Jian L, Xiao J, Jansz J, Yun G, Robertson A. Joint effect of heatwaves and air quality on emergency department attendances for vulnerable population in Perth, Western Australia, 2006 to 2015. Environ Res. 2019;174:80–7. doi: 10.1016/j.envres.2019.04.013 31054525

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