School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, 3004, Australia.
Department of Public Health Environments and Society, London School of Hygiene and Tropical Medicine, London, UK.
BMJ. 2023 Oct 4;383:e075081. doi: 10.1136/bmj-2023-075081.
To evaluate lag-response associations and effect modifications of exposure to floods with risks of all cause, cardiovascular, and respiratory mortality on a global scale.
Time series study.
761 communities in 35 countries or territories with at least one flood event during the study period.
Multi-Country Multi-City Collaborative Research Network database, Australian Cause of Death Unit Record File, New Zealand Integrated Data Infrastructure, and the International Network for the Demographic Evaluation of Populations and their Health Network database.
The main outcome was daily counts of deaths. An estimation for the lag-response association between flood and daily mortality risk was modelled, and the relative risks over the lag period were cumulated to calculate overall effects. Attributable fractions of mortality due to floods were further calculated. A quasi-Poisson model with a distributed lag non-linear function was used to examine how daily death risk was associated with flooded days in each community, and then the community specific associations were pooled using random effects multivariate meta-analyses. Flooded days were defined as days from the start date to the end date of flood events.
A total of 47.6 million all cause deaths, 11.1 million cardiovascular deaths, and 4.9 million respiratory deaths were analysed. Over the 761 communities, mortality risks increased and persisted for up to 60 days (50 days for cardiovascular mortality) after a flooded day. The cumulative relative risks for all cause, cardiovascular, and respiratory mortality were 1.021 (95% confidence interval 1.006 to 1.036), 1.026 (1.005 to 1.047), and 1.049 (1.008 to 1.092), respectively. The associations varied across countries or territories and regions. The flood-mortality associations appeared to be modified by climate type and were stronger in low income countries and in populations with a low human development index or high proportion of older people. In communities impacted by flood, up to 0.10% of all cause deaths, 0.18% of cardiovascular deaths, and 0.41% of respiratory deaths were attributed to floods.
This study found that the risks of all cause, cardiovascular, and respiratory mortality increased for up to 60 days after exposure to flood and the associations could vary by local climate type, socioeconomic status, and older age.
在全球范围内评估暴露于洪水与全因、心血管和呼吸死亡率风险之间的滞后反应关联和效应修饰作用。
时间序列研究。
研究期间至少发生过一次洪水事件的 35 个国家或地区的 761 个社区。
多国家多城市合作研究网络数据库、澳大利亚死因单位记录文件、新西兰综合数据基础设施以及人口及其健康国际网络数据库。
主要观察指标为每日死亡人数。对洪水与每日死亡率风险之间的滞后反应关系进行了估计，并对滞后期内的相对风险进行了累积，以计算总体效应。进一步计算了因洪水而导致的死亡的归因分数。采用具有分布式滞后非线性函数的拟泊松模型，以检验每个社区中每日死亡风险与洪水日之间的关系，然后使用随机效应多元荟萃分析汇总社区特异性关联。洪水日的定义为洪水事件的开始日期至结束日期之间的天数。
共分析了 4760 万例全因死亡、1110 万例心血管死亡和 490 万例呼吸死亡。在 761 个社区中，暴露于洪水后的 60 天内（心血管死亡率为 50 天），死亡率风险增加并持续存在。全因、心血管和呼吸死亡率的累积相对风险分别为 1.021（95%置信区间 1.006 至 1.036）、1.026（1.005 至 1.047）和 1.049（1.008 至 1.092）。这些关联因国家或地区以及区域而异。洪水与死亡率之间的关联似乎受到气候类型的影响，在低收入国家和人类发展指数较低或老年人比例较高的人群中，关联更强。在受洪水影响的社区中，高达 0.10%的全因死亡、0.18%的心血管死亡和 0.41%的呼吸死亡归因于洪水。
本研究发现，暴露于洪水后，全因、心血管和呼吸死亡率的风险增加了长达 60 天，并且这种关联可能因当地气候类型、社会经济地位和老年人口比例而有所不同。
