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Heat-related morbidity in Brisbane, Australia : spatial variation and area-level predictors

机译:澳大利亚布里斯班与热有关的发病率:空间变异和面积水平预测因子

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摘要

Background: Extreme heat is a leading weather-related cause of illness and death in many locations across the globe, including subtropical Australia. The possibility of increasingly frequent and severe heat waves warrants continued efforts to reduce this health burden, which could be accomplished by targeting intervention measures toward the most vulnerable communities.\ud\udObjectives: We sought to quantify spatial variability in heat-related morbidity in Brisbane, Australia, to highlight regions of the city with the greatest risk. We also aimed to find area-level social and environmental determinants of high risk within Brisbane.\ud\udMethods: We used a series of hierarchical Bayesian models to examine city-wide and intracity associations between temperature and morbidity using a 2007–2011 time series of geographically referenced hospital admissions data. The models accounted for long-term time trends, seasonality, and day of week and holiday effects.\ud\udResults: On average, a 10°C increase in daily maximum temperature during the summer was associated with a 7.2% increase in hospital admissions (95% CI: 4.7, 9.8%) on the following day. Positive statistically significant relationships between admissions and temperature were found for 16 of the city’s 158 areas; negative relationships were found for 5 areas. High-risk areas were associated with a lack of high income earners and higher population density.\ud\udConclusions: Geographically targeted public health strategies for extreme heat may be effective in Brisbane, because morbidity risk was found to be spatially variable. Emergency responders, health officials, and city planners could focus on short- and long-term intervention measures that reach communities in the city with lower incomes and higher population densities, including reduction of urban heat island effects.
机译:背景:极热是全球许多地方(包括亚热带澳大利亚)与天气有关的主要疾病和死亡原因。越来越频繁和严重的热浪的发生,需要继续努力减轻这种健康负担,这可以通过针对最脆弱的社区采取干预措施来实现。\ ud \ ud目标:我们试图量化布里斯班与热相关的发病率的空间变异性,以突出显示该城市中风险最大的地区。 \ ud \ ud方法:我们使用一系列分层贝叶斯模型,使用2007-2011年时间序列,研究了城市范围内和城市内部温度与发病率之间的关联。地理参考的医院入院数据。该模型考虑了长期趋势,季节性以及星期几和节假日的影响。\ ud \ ud结果:平均而言,夏季每天最高温度升高10°C会使住院人数增加7.2% (95%CI:4.7,9.8%)。在该市158个地区中,有16个地区的入场人数与气温之间存在统计学上的正相关关系;在5个方面发现了负面关系。高风险地区与缺乏高收入者和较高的人口密度有关。结论:在布里斯班,针对地理条件的极端高温公共卫生策略可能有效,因为发现发病风险在空间上是可变的。应急人员,卫生官员和城市规划人员可以将重点放在短期和长期干预措施上,这些措施将覆盖城市中收入较低,人口密度较高的社区,包括减少城市热岛效应。

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