Vaneckova Pavla, Beggs Paul J, de Dear Richard J, McCracken Kevin W J
Department of Physical Geography, Macquarie University, Sydney, NSW, Australia.
Environ Res. 2008 Nov;108(3):361-9. doi: 10.1016/j.envres.2008.07.015. Epub 2008 Sep 5.
Studies of heat-related mortality have been predominantly based on analyses of underlying cause of death as the single indicator of a population's vulnerability to high temperatures. Examination of both underlying and associated causes of death could provide a more comprehensive understanding of the population at risk. This study analyzes the impact of high temperatures on mortality in Sydney, Australia, during the warmer six months (October-March) between 1993 and 2004, using the underlying and associated cause of death due to all-cause, circulatory, and respiratory disease. Some mortality datasets were also divided into two age groups, 0-64 and 65+. A generalized linear model assuming negative binomial distribution was constructed for the daily mortality counts using daily maximum temperature and hourly maximum concentrations of ozone (O3) and particulate matter (PM10) as covariates. With the air pollution terms in a model, the change in mortality was estimated to be between 4.5% and 12.1% for a 10 degrees C increase in maximum daily temperature, depending on mortality dataset. When air pollutants were removed from a model, the above mortality percentages changed by -1.1% to 0.9%. When both underlying and associated causes of death were considered, the effect remained the same or became lower. Maximum temperature has been found to have a significant effect on mortality in Sydney, with PM10 and O3 confounding the association.
与高温相关的死亡率研究主要基于对潜在死因的分析,将其作为衡量人群对高温脆弱性的单一指标。同时考察潜在死因和相关死因,可能会让人对高危人群有更全面的了解。本研究分析了1993年至2004年澳大利亚悉尼较为温暖的六个月(10月至次年3月)期间高温对死亡率的影响,使用了全因、循环系统和呼吸系统疾病的潜在死因及相关死因。部分死亡率数据集还被分为两个年龄组,即0 - 64岁和65岁及以上。以每日最高气温、臭氧(O3)和颗粒物(PM10)的每小时最高浓度作为协变量,针对每日死亡人数构建了一个假定负二项分布的广义线性模型。在模型中纳入空气污染因素后,根据死亡率数据集的不同,估计每日最高气温每升高10摄氏度,死亡率的变化在4.5%至12.1%之间。当从模型中去除空气污染物时,上述死亡率百分比的变化为 -1.1%至0.9%。当同时考虑潜在死因和相关死因时,这种影响保持不变或变小。研究发现,最高气温对悉尼的死亡率有显著影响,PM10和O3混淆了这种关联。