Division of International Health (Public Health), Graduate School of Medical and Dental Sciences, Niigata University, Niigata, Japan; Institute for Research Administration, Niigata University, Niigata, Japan.
Department of Global Health, School of Tropical Medicine and Global Health, Nagasaki University, Nagasaki, Japan.
Environ Res. 2024 Dec 15;263(Pt 1):120065. doi: 10.1016/j.envres.2024.120065. Epub 2024 Sep 26.
Ambient temperature and humidity are established environmental stressors with regard to influenza infections; however, mapping disease burden is difficult owing to the complexities of the underlying associations and differences in vulnerable population distributions. In this study, we aimed to quantify the burden of influenza attributable to non-optimal ambient temperature and absolute humidity in Japan considering geographical differences in vulnerability.
The exposure-lag-response relationships between influenza incidence, ambient temperature, and absolute humidity in all 47 Japanese prefectures for 2000-2019 were quantified using a distributed lag non-linear model for each prefecture; the estimates from all the prefectures were then pooled using a multivariate mixed-effects meta-regression model to derive nationwide average associations. Association between prefecture-specific indicators and the risk were also examined. Attributable risks were estimated for non-optimal ambient temperature and absolute humidity according to the exposure-lag-response relationships obtained before.
A total of 25,596,525 influenza cases were reported during the study period. Cold and dry conditions significantly increased influenza incidence risk. Compared with the minimum incidence weekly mean ambient temperature (29.8 °C) and the minimum incidence weekly mean absolute humidity (20.2 g/m), the cumulative relative risks (RRs) of influenza in cold (2.5 °C) and dry (3.6 g/m) conditions were 2.79 (95% confidence interval [CI]: 1.78-4.37) and 3.20 (95% CI: 2.37-4.31), respectively. The higher RRs for cold and dry conditions were associated with geographical and climatic indicators corresponding to the central and northern prefectures; demographic, socioeconomic, and health resources indicators showed no clear trends. Finally, 27.25% (95% empirical CI [eCI]: 5.54-36.35) and 32.35% (95% eCI: 22.39-37.87) of all cases were attributable to non-optimal ambient temperature and absolute humidity (6,976,300 [95% eCI: 1,420,068-9,306,128] and 8,280,981 [95% eCI: 8,280,981-9,693,532] cases), respectively.
These findings could help identify the most vulnerable populations in Japan and design adaptation policies to reduce the attributable burden of influenza due to climate variability.
环境温度和湿度是与流感感染有关的既定环境应激源；然而，由于潜在关联的复杂性和脆弱人群分布的差异，映射疾病负担是困难的。在这项研究中，我们旨在考虑到脆弱性的地域差异，量化日本因非最佳环境温度和绝对湿度导致的流感负担。
使用分布式滞后非线性模型对 2000-2019 年日本所有 47 个县的流感发病率、环境温度和绝对湿度之间的暴露-滞后-反应关系进行量化；然后使用多变量混合效应荟萃回归模型对所有县的估计值进行汇总，以得出全国平均关联。还检查了特定于县的指标与风险之间的关联。根据之前获得的暴露-滞后-反应关系，估算非最佳环境温度和绝对湿度的归因风险。
在研究期间共报告了 25596525 例流感病例。寒冷和干燥的条件显著增加了流感发病率的风险。与最低发病率每周平均环境温度（29.8°C）和最低发病率每周平均绝对湿度（20.2g/m）相比，寒冷（2.5°C）和干燥（3.6g/m）条件下的流感累积相对风险（RR）分别为 2.79（95%置信区间[CI]：1.78-4.37）和 3.20（95% CI：2.37-4.31）。寒冷和干燥条件下较高的 RR 与对应于中部和北部县的地理和气候指标有关；人口统计学、社会经济和卫生资源指标没有明显趋势。最后，27.25%（95%经验置信区间[eCI]：5.54-36.35）和 32.35%（95% eCI：22.39-37.87）的所有病例归因于非最佳环境温度和绝对湿度（6976300 [95% eCI：1420068-9306128]和 8280981 [95% eCI：8280981-9693532]例）。
这些发现可以帮助确定日本最脆弱的人群，并制定适应政策以减少因气候变异性导致的流感归因负担。
