Temporal changes in temperature-related mortality in relation to the establishment of the heat-health alert system in Victoria, Australia
- PMID: 38709342
- PMCID: PMC11282152
- DOI: 10.1007/s00484-024-02691-9
Temporal changes in temperature-related mortality in relation to the establishment of the heat-health alert system in Victoria, Australia
Abstract
Extreme heat alerts are the most common form of weather forecasting services used in Australia, yet very limited studies have documented their effectiveness in improving health outcomes. This study aimed to examine the temporal changes in temperature-related mortality in relation to the activation of the heat-health alert and response system (HARS) in the State of Victoria, Australia. We examined the relationship between temperatures and mortality using quasi-Poisson regression and the distributed lag non-linear model (dlnm) and compared the temperature-mortality association between the two periods: period 1- prior-HARS (1992-2009) and period 2- post-HARS (2010-2019). Since the HARS heavily weights heatwave effects, we also compared the main effects of heatwave events between the two periods. The heatwaves were defined for three levels, including 3 consecutive days at 97th, 98th, and 99th percentiles. We also controlled the potential confounding effect of seasonality by including a natural cubic B-spline of the day of the year with equally spaced knots and 8 degrees of freedom per year. The exposure-response curve reveals the temperature mortality was reduced in period 2 in comparison with period 1. The relative risk ratios (RRR) of Period 2 over Period 1 were all less than one and gradually decreased from 0.86 (95% CI, 0.72-1.03) to 0.64 (95% CI, 0.33-1.22), and the differences in attributable risk percent increased from 13.2 to 25.3%. The reduction in the risk of heatwave-related deaths decreased by 3.4% (RRp1 1.068, 95% CI, 1.024-1.112 versus RRp2 1.034, 95% CI, 0.986-1.082) and 10% (RRp1 1.16, 95% CI, 1.10-1.22 versus RRp2 1.06, 95% CI, 1.002-1.119) for all groups of people. The study indicated a decrease in heat-related mortality following the operation of HARS in Victoria under extreme heat and high-intensity heatwaves conditions. Further studies could investigate the extent of changes in mortality among populations of differing socio-economic groups during the operation of the heat-health alert system.
Keywords: Australia; Extreme temperature; Heat-action plan; Mortality; Victoria.
© 2024. The Author(s).
Conflict of interest statement
The authors declare no known competing conflict of interest that might influence the content of this article.
Figures




Similar articles
-
Heatwave and mortality in 31 major Chinese cities: Definition, vulnerability and implications.Sci Total Environ. 2019 Feb 1;649:695-702. doi: 10.1016/j.scitotenv.2018.08.332. Epub 2018 Aug 26. Sci Total Environ. 2019. PMID: 30176480
-
Heatwaves and hospitalizations due to hyperthermia in defined climate regions in the conterminous USA.Environ Monit Assess. 2019 Jun 28;191(Suppl 2):394. doi: 10.1007/s10661-019-7412-5. Environ Monit Assess. 2019. PMID: 31254102
-
Heatwaves and diabetes in Brisbane, Australia: a population-based retrospective cohort study.Int J Epidemiol. 2019 Aug 1;48(4):1091-1100. doi: 10.1093/ije/dyz048. Int J Epidemiol. 2019. PMID: 30927429
-
Systematic review of the impact of heatwaves on health service demand in Australia.BMC Health Serv Res. 2022 Jul 28;22(1):960. doi: 10.1186/s12913-022-08341-3. BMC Health Serv Res. 2022. PMID: 35902847 Free PMC article.
-
Heat exposure and cardiovascular health outcomes: a systematic review and meta-analysis.Lancet Planet Health. 2022 Jun;6(6):e484-e495. doi: 10.1016/S2542-5196(22)00117-6. Lancet Planet Health. 2022. PMID: 35709806
Cited by
-
Outpacing climate change: adaptation to heatwaves in Europe.Int J Biometeorol. 2025 May;69(5):989-1002. doi: 10.1007/s00484-025-02872-0. Epub 2025 Feb 19. Int J Biometeorol. 2025. PMID: 39966149 Free PMC article.
-
The graded heat-health risk forecast and early warning with full-season coverage across China: a predicting model development and evaluation study.Lancet Reg Health West Pac. 2025 Jan 11;54:101266. doi: 10.1016/j.lanwpc.2024.101266. eCollection 2025 Jan. Lancet Reg Health West Pac. 2025. PMID: 39877409 Free PMC article.
References
-
- Australian Bureau of Statistics (2021b) Victoria 2021 Census All persons QuickStats. Australian Bureau of Statistics. https://www.abs.gov.au/census/find-census-data/quickstats/2021/2. Accessed 05/01/2024
-
- Australian Bureau of Statistics (2021a) Population: Census. Australian Bureau of Statistics. https://www.abs.gov.au/statistics/people/population/population-census/2021. Accessed 24/08/2022
-
- Australian Bureau of statistics (2019) Data by region. https://dbr.abs.gov.au/. Accessed 06/02/2019
-
- Australian Bureau of Statistics (2006) Victoria 2006 Census All persons QuickStats. Australian Bureau of Statistics. https://abs.gov.au/census/find-census-data/quickstats/2006/2#:~:text=In%.... Accessed 05/01/2024
-
- Baghi H, Noorbaloochi S, Moore JB (2007) Statistical and nonstatistical significance: implications for Health Care Researchers. Qual Manage Healthc 16 (2) - PubMed
MeSH terms
LinkOut - more resources
Full Text Sources