Abstract：
OBJECTIVE: From 2010 to 2022, the Victorian Department of Health operated a heat health alert system. We explored whether changes to morbidity occurred during or directly after these alerts, and how this differed for certain population groups.
METHODS: We used a space-time-stratified case-crossover design and conditional logistic regression to examine the associations between heat health alerts and heat-related and all-cause emergency department (ED) presentations and hospital admissions at the state-wide level, with models created for the whole population and subgroups. Data were included for the warm season (November-March) from 2014 to 2021.
RESULTS: Increases occurred in heat-related ED presentations (OR 1.73, 95% CI: 1.53-1.96) and heat-related hospital admissions (OR 1.23, 95% CI: 1.16-1.30) on days on or after heat health alerts. Effect sizes were largest for those 65 years and older, Aboriginal and Torres Strait Islander people, and those living in the most disadvantaged areas.
CONCLUSIONS: We confirm that increases in morbidity occurred in Victoria during heat health alerts and describe which population groups are more likely to require healthcare in a hospital.
CONCLUSIONS: These findings can inform responses before and during periods of extreme heat, data-driven adaptation strategies, and the development of heat health surveillance systems.
METHODS: We used a space-time-stratified case-crossover design and conditional logistic regression to examine the associations between heat health alerts and heat-related and all-cause emergency department (ED) presentations and hospital admissions at the state-wide level, with models created for the whole population and subgroups. Data were included for the warm season (November-March) from 2014 to 2021.
RESULTS: Increases occurred in heat-related ED presentations (OR 1.73, 95% CI: 1.53-1.96) and heat-related hospital admissions (OR 1.23, 95% CI: 1.16-1.30) on days on or after heat health alerts. Effect sizes were largest for those 65 years and older, Aboriginal and Torres Strait Islander people, and those living in the most disadvantaged areas.
CONCLUSIONS: We confirm that increases in morbidity occurred in Victoria during heat health alerts and describe which population groups are more likely to require healthcare in a hospital.
CONCLUSIONS: These findings can inform responses before and during periods of extreme heat, data-driven adaptation strategies, and the development of heat health surveillance systems.
摘要：
目标：从2010年到2022年，维多利亚州卫生部运行了热健康警报系统。我们探讨了发病率的变化是否发生在这些警报期间或之后，以及这对某些人群有什么不同。
方法：我们使用时空分层病例交叉设计和条件逻辑回归来检查热量健康警报与热量相关和全因急诊科（ED）报告之间的关联。为整个群体和子群体创建模型。数据包括2014年至2021年的温暖季节（11月至3月）。
结果：在高温健康警报当天或之后，与热相关的ED报告（OR1.73，95％CI：1.53-1.96）和与热相关的住院（OR1.23，95％CI：1.16-1.30）增加。65岁及以上的患者的效果最大，原住民和托雷斯海峡岛民，以及那些生活在最不利地区的人。
结论：我们确认在高温健康警报期间，维多利亚州的发病率增加，并描述了哪些人群更可能需要医院的医疗保健。
结论：这些发现可以为极端高温之前和期间的反应提供信息，数据驱动的适应战略，以及热健康监测系统的开发。
方法：我们使用时空分层病例交叉设计和条件逻辑回归来检查热量健康警报与热量相关和全因急诊科（ED）报告之间的关联。为整个群体和子群体创建模型。数据包括2014年至2021年的温暖季节（11月至3月）。
结果：在高温健康警报当天或之后，与热相关的ED报告（OR1.73，95％CI：1.53-1.96）和与热相关的住院（OR1.23，95％CI：1.16-1.30）增加。65岁及以上的患者的效果最大，原住民和托雷斯海峡岛民，以及那些生活在最不利地区的人。
结论：我们确认在高温健康警报期间，维多利亚州的发病率增加，并描述了哪些人群更可能需要医院的医疗保健。
结论：这些发现可以为极端高温之前和期间的反应提供信息，数据驱动的适应战略，以及热健康监测系统的开发。
