Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Anhui Province Key Laboratory of Major Autoimmune Disease, China.
Department of Geriatrics, Shandong Daizhuang Hospital, China.
Environ Res. 2022 Nov;214(Pt 4):114143. doi: 10.1016/j.envres.2022.114143. Epub 2022 Aug 22.
In the context of frequent global extreme weather events, there are few studies on the effects of sequential extreme precipitation (EP) and heatwaves (HW) events on schizophrenia. We aimed to quantify the effects of the events on hospitalizations for schizophrenia and compare them with EP and HW alone to explore the amplification effect of successive extremes on health loss.
A time-series Poisson regression model combined with a distributed lag non-linear model was applied to estimate the association between sequential EP and HW events (EP-HW) and schizophrenia hospitalizations. The effects of EP-HW with different intervals and intensities on the admission of schizophrenia were compared. In addition, we calculated the mean attributable fraction (AF) and attributable numbers (AN) per exposure of extreme events to reflect the amplification effect of sequential extreme events on health hazards compared with individual extreme events.
EP-HW increased the risk of hospitalization for schizophrenia, with significant effects lasting from lag0 (RR and 95% CI: 1.150 (1.041-1.271)) to lag11 (1.046 (1.000-1.094)). Significant associations were found in the subgroups of male, female, married people, and those aged≥ 40 years old. Shorter-interval (0-3days) or higher-intensity EP-HW (both precipitation ≥ P97.5 and mean temperature ≥ P97.5) had a longer lag effect compared to EP-HW with longer intervals or lower intensity. We found that the mean AF and AN caused by each exposure to EP-HW (AF: 0.074% (0.015%-0.123%); AN: 4.284 (0.862-7.118)) were higher than those induced by each exposure to HW occurring alone (AF:0.032% (0.004%-0.058%); AN:1.845 (0.220-3.329)).
Sequential extreme precipitation-heatwaves events significantly increase the risk of hospitalizations for schizophrenia, with greater impact and disease burden than independently occurring extremes. The impact of consecutive extremes is supposed to be considered in local sector early warning systems for comprehensive public health decision-making.
在全球极端天气事件频繁发生的背景下，关于连续极端降水（EP）和热浪（HW）事件对精神分裂症影响的研究较少。本研究旨在量化这些事件对精神分裂症住院的影响，并与 EP 和 HW 单独进行比较，以探讨连续极端事件对健康损失的放大效应。
采用时间序列泊松回归模型结合分布式滞后非线性模型，估计连续 EP 和 HW 事件（EP-HW）与精神分裂症住院之间的关联。比较 EP-HW 不同间隔和强度对精神分裂症入院的影响。此外，我们计算了极端事件暴露的平均归因分数（AF）和归因数量（AN），以反映连续极端事件对健康危害的放大效应与单个极端事件相比。
EP-HW 增加了精神分裂症住院的风险，其影响从 lag0（RR 和 95%CI：1.150（1.041-1.271））到 lag11（1.046（1.000-1.094））均有显著效应。在男性、女性、已婚人群和≥40 岁人群的亚组中也发现了显著关联。与间隔较长（0-3 天）或强度较高的 EP-HW（降水均≥P97.5 和平均温度均≥P97.5）相比，间隔较短（0-3 天）或强度较高的 EP-HW 具有更长的滞后效应。我们发现，每次暴露于 EP-HW 引起的平均 AF（AF：0.074%（0.015%-0.123%））和 AN（AN：4.284（0.862-7.118））均高于每次单独暴露于 HW 引起的 AF（AF：0.032%（0.004%-0.058%））和 AN（AN：1.845（0.220-3.329））。
连续极端降水-热浪事件显著增加了精神分裂症住院的风险，其影响和疾病负担大于独立发生的极端事件。在地方部门的综合公共卫生决策中，应考虑连续极端事件的影响。
