1 Institute of Island and Coastal Ecosystems, Ocean College, Zhejiang University , Zhoushan, China.
2 Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University , Melbourne, Australia.
Environ Health Perspect. 2019 Mar;127(3):37001. doi: 10.1289/EHP3556.
Temperature-related mortality risks have mostly been studied in urban areas, with limited evidence for urban-rural differences in the temperature impacts on health outcomes.
We investigated whether temperature-mortality relationships vary between urban and rural counties in China.
We collected daily data on 1 km gridded temperature and mortality in 89 counties of Zhejiang Province, China, for 2009 and 2015. We first performed a two-stage analysis to estimate the temperature effects on mortality in urban and rural counties. Second, we performed meta-regression to investigate the modifying effect of the urbanization level. Stratified analyses were performed by all-cause, nonaccidental (stratified by age and sex), cardiopulmonary, cardiovascular, and respiratory mortality. We also calculated the fraction of mortality and number of deaths attributable to nonoptimum temperatures associated with both cold and heat components. The potential sources of the urban-rural differences were explored using meta-regression with county-level characteristics.
Increased mortality risks were associated with low and high temperatures in both rural and urban areas, but rural counties had higher relative risks (RRs), attributable fractions of mortality, and attributable death counts than urban counties. The urban-rural disparity was apparent for cold (first percentile relative to minimum mortality temperature), with an RR of 1.47 [95% confidence interval (CI): 1.32, 1.62] associated with all-cause mortality for urban counties, and 1.98 (95% CI: 1.87, 2.10) for rural counties. Among the potential sources of the urban-rural disparity are age structure, education, GDP, health care services, air conditioners, and occupation types.
Rural residents are more sensitive to both cold and hot temperatures than urban residents in Zhejiang Province, China, particularly the elderly. The findings suggest past studies using exposure-response functions derived from urban areas may underestimate the mortality burden for the population as a whole. The public health agencies aimed at controlling temperature-related mortality should develop area-specific strategies, such as to reduce the urban-rural gaps in access to health care and awareness of risk prevention. Future projections on climate health impacts should consider the urban-rural disparity in mortality risks. https://doi.org/10.1289/EHP3556.
与城市地区相比，有关温度相关死亡风险的研究大多集中在城市地区，有关城市与农村地区之间温度对健康结果影响的差异的证据有限。
我们调查了中国城乡地区的温度-死亡率关系是否存在差异。
我们收集了 2009 年和 2015 年中国浙江省 89 个县的 1 公里网格化温度和死亡率的每日数据。我们首先进行了两阶段分析，以估计城乡地区的温度对死亡率的影响。其次，我们进行了元回归分析，以研究城市化水平的调节作用。分层分析包括全因、非意外（按年龄和性别分层）、心肺、心血管和呼吸死亡。我们还计算了与冷和热成分相关的非最佳温度导致的死亡率和死亡人数的比例。使用县级特征的元回归探索城乡差异的潜在来源。
在农村和城市地区，死亡率的升高都与低温和高温有关，但农村地区的相对风险（RR）、归因死亡率比例和归因死亡人数都高于城市地区。农村地区的城乡差异在寒冷地区（与最低死亡率温度的第一百分位相比）表现明显，城市地区全因死亡率的 RR 为 1.47（95%置信区间[CI]：1.32，1.62），农村地区为 1.98（95% CI：1.87，2.10）。城乡差异的潜在来源包括年龄结构、教育程度、国内生产总值、医疗保健服务、空调和职业类型。
在中国浙江省，与城市居民相比，农村居民对寒冷和炎热天气更为敏感，尤其是老年人。这些发现表明，过去使用源自城市地区的暴露-反应函数进行的研究可能低估了整体人群的死亡率负担。旨在控制与温度相关的死亡率的公共卫生机构应制定针对特定地区的策略，例如减少城乡之间获得医疗保健和风险预防意识的差距。未来有关气候健康影响的预测应考虑死亡率风险的城乡差异。https://doi.org/10.1289/EHP3556.
