The impact of temperature on mortality across different climate zones

  • Thomas LongdenEmail author


There are numerous studies that have estimated the number of deaths attributable to heat and cold using city-level or provincial-level data. However, none of these studies have assessed temperature-mortality relationships using meteorological climate zones and data that covers an entire population/country. This analysis uses a national data set of death records to create time-series data for different regional aggregations. Temperature-mortality relationships are estimated using this data set of 1,717,224 deaths, which covers the whole of Australia between 2006 and 2017. This paper finds that the majority of deaths related to temperature in Australia are caused by heat. It also finds that the reference temperature used to separate impacts into heat-/cold-related mortality has a notable impact on the magnitude of these estimates. Previous studies (using the same methodology) found that most of the temperature-related mortality burden in Australia was attributed to cold temperatures. This led to studies that associated this with a net benefit from climate change. This analysis indicates that studies that found net benefits from climate change need to be re-assessed, especially for Australia and warmer climate zones.



The author thanks Associate Professor Antonio Gasparrini and co-authors for making their R code available online (via The author thanks Mahbub Hakim for research assistance (i.e. assisting with matching weather stations to local government areas). The Cause of Death Unit Record File (COD URF) was provided by the Australian Coordinating Registry for the COD URF on behalf of Australian Registries of Births, Deaths and Marriages, Australian Coroners and the National Coronial Information System.


This research was funded by the Lord Mayor’s Charitable Foundation and a UTS Business School Research Grant.

Compliance with ethical standards

This project was conducted under CHERE’s programme ethics approval from the UTS Human Research Ethics Committee (UTS HREC reference no. 2015000135).

Conflict of interest

The author declares that he has no conflict of interest.

Supplementary material

10584_2019_2519_MOESM1_ESM.docx (1.3 mb)
ESM 1 (1.30 mb DOCX)


  1. ABS (2012) 1270.0.55.006 - Australian Statistical Geography Standard (ASGS): correspondences, July 2011 Accessed 24 July 2018
  2. ABS (2013) 2033.0.55.001 - Census of population and housing: Socio-Economic Indexes for Areas (SEIFA), Australia, 2011. Accessed 24 July 2018
  3. Ackerman F, Stanton EA (2008) A comment on “Economy-wide estimates of the implications of climate change: human health”. Ecol Econ 66:8–13. CrossRefGoogle Scholar
  4. Ackerman F, Stanton EA, Hope C, Alberth S (2009) Did the Stern Review underestimate US and global climate damages? Energy Policy 37:2717–2721. CrossRefGoogle Scholar
  5. Barnett AG, Hajat S, Gasparrini A, Rocklöv J (2012) Cold and heat waves in the United States. Environ Res 112:218–224. CrossRefGoogle Scholar
  6. Barreca A, Clay K, Deschênes O, Greenstone M, Shapiro JS (2015) Convergence in adaptation to climate change: evidence from high temperatures and mortality, 1900-2004. Am Econ Rev 105:247–251CrossRefGoogle Scholar
  7. Barreca A, Clay K, Deschenes O, Greenstone M, Shapiro JS (2016) Adapting to climate change: the remarkable decline in the US temperature-mortality relationship over the twentieth century. J Polit Econ 124:105–159. CrossRefGoogle Scholar
  8. Basu R, Malig B (2011) High ambient temperature and mortality in California: exploring the roles of age, disease, and mortality displacement. Environ Res 111:1286–1292CrossRefGoogle Scholar
  9. Basu R, Pearson D, Malig B, Broadwin R, Green R (2012) The effect of high ambient temperature on emergency room visits. Epidemiology 813–820Google Scholar
  10. Bobb JF, Peng RD, Bell ML, Dominici F (2014) Heat-related mortality and adaptation to heat in the United States. Environ Health Perspect 122:811–816. CrossRefGoogle Scholar
  11. BOM (2016) Climate classifications—thermal climate zone classification (temperature/humidity zones). Accessed 24 July 2018 2018
  12. Cui Y et al (2016) Heat or cold: which one exerts greater deleterious effects on health in a basin climate city? Impact of ambient temperature on mortality in Chengdu, China. Int J Environ Res Public Health 13:1225CrossRefGoogle Scholar
  13. Dang TN et al (2016) Characterizing the relationship between temperature and mortality in tropical and subtropical cities: a distributed lag non-linear model analysis in Hue, Viet Nam, 2009–2013. Glob Health Action 9Google Scholar
  14. Egondi T, Kyobutungi C, Kovats S, Muindi K, Ettarh R, Rocklöv J (2012) Time-series analysis of weather and mortality patterns in Nairobi’s informal settlements. Glob Health Action 5:19065CrossRefGoogle Scholar
  15. European Commission (2008) Impact assessment: document accompanying the package of implementation measures for the EU’s objectives on climate change and renewable energy for 2020. Commission Staff Working Paper,Google Scholar
  16. Garnaut R (2008) The Garnaut climate change review. Cambridge, CambridgeGoogle Scholar
  17. Gasparrini A et al (2015) Mortality risk attributable to high and low ambient temperature: a multicountry observational study. Lancet 386:369–375CrossRefGoogle Scholar
  18. Gasparrini A et al (2017) Projections of temperature-related excess mortality under climate change scenarios. Lancet Planetary Health 1:e360–e367. CrossRefGoogle Scholar
  19. Gosling SN, McGregor GR, Páldy A (2007) Climate change and heat-related mortality in six cities. Part 1: model construction and validation. Int J Biometeorol 51:525–540CrossRefGoogle Scholar
  20. Gosling SN, Lowe JA, McGregor GR, Pelling M, Malamud BD (2009a) Associations between elevated atmospheric temperature and human mortality: a critical review of the literature. Clim Chang 92:299–341CrossRefGoogle Scholar
  21. Gosling SN, McGregor GR, Lowe JA (2009b) Climate change and heat-related mortality in six cities. Part 2: climate model evaluation and projected impacts from changes in the mean and variability of temperature with climate change. Int J Biometeorol 53:31–51. CrossRefGoogle Scholar
  22. Guo Y, Li S, Li Liu D, Chen D, Williams G, Tong S (2016) Projecting future temperature-related mortality in three largest Australian cities. Environ Pollut 208:66–73CrossRefGoogle Scholar
  23. Herold N, Ekström M, Kala J, Goldie J, Evans JP (2018) Australian climate extremes in the 21st century according to a regional climate model ensemble: implications for health and agriculture. Weather Clim Extremes 20:54–68. CrossRefGoogle Scholar
  24. Jegasothy E, McGuire R, Nairn J, Fawcett R, Scalley B (2017) Extreme climatic conditions and health service utilisation across rural and metropolitan New South Wales. Int J Biometeorol 61:1359–1370CrossRefGoogle Scholar
  25. King AD, Karoly DJ, Henley BJ (2017) Australian climate extremes at 1.5 °C and 2 °C of global warming. Nat Clim Chang 7:–412.
  26. Langlois N, Herbst J, Mason K, Nairn J, Byard RW (2013) Using the excess heat factor (EHF) to predict the risk of heat related deaths. J Forensic Legal Med 20:408–411CrossRefGoogle Scholar
  27. Lee M, Nordio F, Zanobetti A, Kinney P, Vautard R, Schwartz J (2014) Acclimatization across space and time in the effects of temperature on mortality: a time-series analysis. Environ Health 13:89CrossRefGoogle Scholar
  28. Lee W, Kim H, Hwang S, Zanobetti A, Schwartz JD, Chung Y (2017) Monte Carlo simulation-based estimation for the minimum mortality temperature in temperature-mortality association study. BMC Med Res Methodol 17:137CrossRefGoogle Scholar
  29. Lo YTE et al (2019) Increasing mitigation ambition to meet the Paris Agreement’s temperature goal avoids substantial heat-related mortality in U.S. cities. Sci Adv 5:eaau4373. CrossRefGoogle Scholar
  30. Lomborg B (2016) An overheated climate alarm: the White House launches a scary campaign about deadly heat. Guess what: cold kills more peopleGoogle Scholar
  31. Longden T (2018) Measuring temperature-related mortality using endogenously determined thresholds. Clim Chang 150:343–375. CrossRefGoogle Scholar
  32. Longden T (2019) Temperature-related mortality and climate change in Australia. Lancet Planetary Health 3:e121CrossRefGoogle Scholar
  33. Markandya A, Sampedro J, Smith SJ, Van Dingenen R, Pizarro-Irizar C, Arto I, González-Eguino M (2018) Health co-benefits from air pollution and mitigation costs of the Paris Agreement: a modelling study. Lancet Planetary Health 2:e126–e133CrossRefGoogle Scholar
  34. Martens WJ (1998) Climate change, thermal stress and mortality changes. Soc Sci Med 46:331–344CrossRefGoogle Scholar
  35. Muscatello DJ, Newall AT, Dwyer DE, MacIntyre CR (2013) Mortality attributable to seasonal and pandemic influenza, Australia, 2003 to 2009, using a novel time series smoothing approach. PLoS One 8:e64734CrossRefGoogle Scholar
  36. Nairn JR, Fawcett RJ (2014) The excess heat factor: a metric for heatwave intensity and its use in classifying heatwave severity. Int J Environ Res Public Health 12:227–253CrossRefGoogle Scholar
  37. Nairn J, Fawcett R (2015) The Excess heat factor: a metric for heatwave intensity and its use in classifying heatwave severity. Int J Environ Res Public Health 12:227CrossRefGoogle Scholar
  38. Nairn JR, Fawcett RG, Day KA (2013) Defining heatwaves: heatwave defined as a heat-impact event servicing all community and business sectors in Australia. Centre for Australian Weather and Climate ResearchGoogle Scholar
  39. Nordhaus WD (1993) Optimal greenhouse-gas reductions and tax policy in the “DICE” model. Am Econ Rev 83:313–317Google Scholar
  40. Nordio F, Zanobetti A, Colicino E, Kloog I, Schwartz J (2015) Changing patterns of the temperature–mortality association by time and location in the US, and implications for climate change. Environ Int 81:80–86. CrossRefGoogle Scholar
  41. Scalley BD, Spicer T, Jian L, Xiao J, Nairn J, Robertson A, Weeramanthri T (2015) Responding to heatwave intensity: excess heat factor is a superior predictor of health service utilisation and a trigger for heatwave plans. Aust N Z J Public Health 39:582–587CrossRefGoogle Scholar
  42. Schwartz J (2000) Harvesting and long term exposure effects in the relation between air pollution and mortality. Am J Epidemiol 151:440–448CrossRefGoogle Scholar
  43. Sim G, Kim H, Zanobetti A, Schwartz J, Chung Y (2018) Non-parametric Bayesian multivariate metaregression: an application in environmental epidemiology. Journal of the Royal Statistical Society: Series C (Applied Statistics)Google Scholar
  44. Stern N (2006) Stern review report on the economics of climate changeGoogle Scholar
  45. Tol RSJ (2002a) Estimates of the damage costs of climate change. Part I: benchmark estimates. Environ Resour Econ 21:47–73. CrossRefGoogle Scholar
  46. Tol RSJ (2002b) Estimates of the damage costs of climate change, part II. Dyn Estimates Environ Resour Econ 21:135–160. CrossRefGoogle Scholar
  47. Tol RSJ (2013) The economic impact of climate change in the 20th and 21st centuries. Clim Chang 117:795–808. CrossRefGoogle Scholar
  48. Vicedo-Cabrera AM et al (2018) Temperature-related mortality impacts under and beyond Paris Agreement climate change scenarios. Clim Chang 150:391–402. CrossRefGoogle Scholar
  49. Xiao J et al (2017) Variation in population vulnerability to heat wave in Western Australia. Front Public Health:5.
  50. Yu W, Mengersen K, Wang X, Ye X, Guo Y, Pan X, Tong S (2012) Daily average temperature and mortality among the elderly: a meta-analysis and systematic review of epidemiological evidence. Int J Biometeorol 56:569–581. CrossRefGoogle Scholar
  51. Zanobetti A, Wand M, Schwartz J, Ryan L (2000) Generalized additive distributed lag models: quantifying mortality displacement. Biostatistics 1:279–292CrossRefGoogle Scholar

Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Centre for Health Economics Research and EvaluationUniversity of Technology SydneyUltimoAustralia

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