The impact of heatwaves on emergency department visits in Brisbane, Australia: a time series study

Toloo, Ghasem Sam; Yu, Weiwei; Aitken, Peter; FitzGerald, Gerry; Tong, Shilu

doi:10.1186/cc13826

Cited by 38 publications

(49 citation statements)

References 38 publications

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“…These studies have found a 'U shaped' distribution of mortality or health service demand, as related to ambient temperature of the day. 5,15,23,24 The findings of this current study build on these studies in demonstrating a clear dose-response relationship for heatwave and health service demand. Note: The error bars represent the 95% CI for the rate ratio.…”

Section: Discussionsupporting

confidence: 63%

Responding to heatwave intensity: Excess Heat Factor is a superior predictor of health service utilisation and a trigger for heatwave plans

Scalley

Spicer

Jian

et al. 2015

Australian and New Zealand Journal of Public Health

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Objective: To determine which measures of heatwave have the greatest predictive power for increases in health service utilisation in Perth, Western Australia. Methods:Three heatwave formulas were compared, using Poisson or zero-inflated Poisson regression, against the number of presentations to emergency departments from all causes, and the number of inpatient admissions from heat-related causes. The period from July 2006 to June 2013 was included. A series of standardised thresholds were calculated to allow comparison between formulas, in the absence of a gold standard definition of heatwaves.Results: Of the three heatwave formulas, Excess Heat Factor (EHF) produced the most clear dose-response relationship with Emergency Department presentations. The EHF generally predicted periods that resulted in a similar or higher rate of health service utilisation, as compared to the two other formulas, for the thresholds examined. Conclusions:The EHF formula, which considers a period of acclimatisation as well as the maximum and minimum temperature, best predicted periods of greatest health service demand. The strength of the dose-response relationship reinforces the validity of the measure as a predictor of hazardous heatwave intensity. Implications:The findings suggest that the EHF formula is well suited for use as a means of activating heatwave plans and identifies the required level of response to extreme heatwave events as well as moderate heatwave events that produce excess health service demand.

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Section: Discussionsupporting

confidence: 63%

Responding to heatwave intensity: Excess Heat Factor is a superior predictor of health service utilisation and a trigger for heatwave plans

Scalley

Spicer

Jian

et al. 2015

Australian and New Zealand Journal of Public Health

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“…The importance of SES in the evaluation of effects of HW was highlighted in several studies of vulnerability to HW (11, 28). Overall, populations with lower SES, poor accessibility to services, and older or younger age groups have higher vulnerability to HWs.…”

Section: Discussionmentioning

confidence: 99%

Variation in Population Vulnerability to Heat Wave in Western Australia

Xiao

Spicer

Jian

et al. 2017

Front. Public Health

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Heat waves (HWs) have killed more people in Australia than all other natural hazards combined. Climate change is expected to increase the frequency, duration, and intensity of HWs and leads to a doubling of heat-related deaths over the next 40 years. Despite being a significant public health issue, HWs do not attract the same level of attention from researchers, policy makers, and emergency management agencies compared to other natural hazards. The purpose of the study was to identify risk factors that might lead to population vulnerability to HW in Western Australia (WA). HW vulnerability and resilience among the population of the state of WA were investigated by using time series analysis. The health impacts of HWs were assessed by comparing the associations between hospital emergency department (ED) presentations, hospital admissions and mortality data, and intensities of HW. Risk factors including age, gender, socioeconomic status (SES), remoteness, and geographical locations were examined to determine whether certain population groups were more at risk of adverse health impacts due to extreme heat. We found that hospital admissions due to heat-related conditions and kidney diseases, and overall ED attendances, were sensitive indicators of HW. Children aged 14 years or less and those aged 60 years or over were identified as the most vulnerable populations to HWs as shown in ED attendance data. Females had more ED attendances and hospital admissions due to kidney diseases; while males had more heat-related hospital admissions than females. There were significant dose–response relationships between HW intensity and SES, remoteness, and health service usage. The more disadvantaged and remotely located the population, the higher the health service usage during HWs. Our study also found that some population groups and locations were resilient to extreme heat. We produced a mapping tool, which indicated geographic areas throughout WA with various vulnerability and resilience levels to HW. The findings from this study will allow local government, community service organizations, and agencies in health, housing, and education to better identify and understand the degree of vulnerability to HW throughout the state, better target preparatory strategies, and allocate limited resources to those most in need.

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“…In the USA, Basu et al found that increased temperatures had same-day effects on ED visits and age seemed to modify some of these impacts [ 10 ]. In Australia, Toloo et al found emergency departments significantly increased on heatwave days and the RRs in different age groups ranged between 3.0 ~ 9.2 when two or more successive days with daily maximum temperature was ≥34°C [ 28 ]. In Shanghai, Sun et al found heat wave with intensity above the 90 th percentile had 2.62% and 0.95% increases in ED visits for a duration of at least 2 days and 3 days respectively [ 25 ].…”

Section: Discussionmentioning

confidence: 99%

Effect of ambient temperature on emergency department visits in Shanghai, China: a time series study

et al. 2014

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BackgroundMany studies have examined the association between ambient temperature and mortality. However, less evidence is available on the temperature effects on gender- and age-specific emergency department visits, especially in developing countries. In this study, we examined the short-term effects of daily ambient temperature on emergency department visits (ED visits) in Shanghai.MethodsDaily ED visits and daily ambient temperatures between January 2006 and December 2011 were analyzed. After controlling for secular and seasonal trends, weather, air pollution and other confounding factors, a Poisson generalized additive model (GAM) was used to examine the associations between ambient temperature and gender- and age-specific ED visits. A moving average lag model was used to evaluate the lag effects of temperature on ED visits.ResultsLow temperature was associated with an overall 2.76% (95% confidence interval (CI): 1.73 to 3.80) increase in ED visits per 1°C decrease in temperature at Lag1 day, 2.03% (95% CI: 1.04 to 3.03) and 2.45% (95% CI: 1.40 to 3.52) for males and females. High temperature resulted in an overall 1.78% (95% CI: 1.05 to 2.51) increase in ED visits per 1°C increase in temperature on the same day, 1.81% (95% CI: 1.08 to 2.54) among males and 1.75% (95% CI: 1.03 to 2.49) among females. The cold effect appeared to be more acute among younger people aged <45 years, whereas the effects were consistent on individuals aged ≥65 years. In contrast, the effects of high temperature were relatively consistent over all age groups.ConclusionsThese findings suggest a significant association between ambient temperature and ED visits in Shanghai. Both cold and hot temperatures increased the relative risk of ED visits. This knowledge has the potential to advance prevention efforts targeting weather-sensitive conditions.Electronic supplementary materialThe online version of this article (doi:10.1186/1476-069X-13-100) contains supplementary material, which is available to authorized users.

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The impact of heatwaves on emergency department visits in Brisbane, Australia: a time series study

Cited by 38 publications

References 38 publications

Responding to heatwave intensity: Excess Heat Factor is a superior predictor of health service utilisation and a trigger for heatwave plans

Responding to heatwave intensity: Excess Heat Factor is a superior predictor of health service utilisation and a trigger for heatwave plans

Variation in Population Vulnerability to Heat Wave in Western Australia

Effect of ambient temperature on emergency department visits in Shanghai, China: a time series study

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