Ost Katarina, Berrang-Ford Lea, Bishop-Williams Katherine, Charette Margot, Harper Sherilee L, Lwasa Shuaib, Namanya Didacus B, Huang Yi, Katz Aaron B, Ebi Kristie
School of Epidemiology and Public Health, University of Ottawa, Ottawa, Canada.
Priestley International Centre for Climate, University of Leeds, Leeds, UK.
Malar J. 2022 Mar 22;21(1):98. doi: 10.1186/s12936-022-04118-5.
There is concern in the international community regarding the influence of climate change on weather variables and seasonality that, in part, determine the rates of malaria. This study examined the role of sociodemographic variables in modifying the association between temperature and malaria in Kanungu District (Southwest Uganda).
Hospital admissions data from Bwindi Community Hospital were combined with meteorological satellite data from 2011 to 2014. Descriptive statistics were used to describe the distribution of malaria admissions by age, sex, and ethnicity (i.e. Bakiga and Indigenous Batwa). To examine how sociodemographic variables modified the association between temperature and malaria admissions, this study used negative binomial regression stratified by age, sex, and ethnicity, and negative binomial regression models that examined interactions between temperature and age, sex, and ethnicity.
Malaria admission incidence was 1.99 times greater among Batwa than Bakiga in hot temperature quartiles compared to cooler temperature quartiles, and that 6-12 year old children had a higher magnitude of association of malaria admissions with temperature compared to the reference category of 0-5 years old (IRR = 2.07 (1.40, 3.07)).
Results indicate that socio-demographic variables may modify the association between temperature and malaria. In some cases, such as age, the weather-malaria association in sub-populations with the highest incidence of malaria in standard models differed from those most sensitive to temperature as found in these stratified models.
The effect modification approach used herein can be used to improve understanding of how changes in weather resulting from climate change might shift social gradients in health.
国际社会关注气候变化对天气变量和季节性的影响，而这些因素在一定程度上决定了疟疾的发病率。本研究调查了社会人口统计学变量在乌干达西南部卡农古区温度与疟疾关联中的调节作用。
将布温迪社区医院的住院数据与2011年至2014年的气象卫星数据相结合。使用描述性统计来描述按年龄、性别和种族（即巴基加族和原住民巴特瓦族）划分的疟疾住院分布情况。为了研究社会人口统计学变量如何调节温度与疟疾住院之间的关联，本研究采用了按年龄、性别和种族分层的负二项回归，以及研究温度与年龄、性别和种族之间相互作用的负二项回归模型。
与较凉爽温度四分位数相比，在炎热温度四分位数中，巴特瓦族的疟疾住院发病率比巴基加族高1.99倍，并且与0至5岁参考类别相比，6至12岁儿童的疟疾住院与温度的关联程度更高（发病率比值比=2.07（1.40，3.07））。
结果表明，社会人口统计学变量可能会调节温度与疟疾之间的关联。在某些情况下，如年龄，标准模型中疟疾发病率最高的亚人群中的天气-疟疾关联与这些分层模型中对温度最敏感的亚人群中的关联不同。
本文采用的效应修正方法可用于增进对气候变化导致的天气变化如何改变健康方面的社会梯度的理解。
