UNASSIGNED: This study aimed to evaluate the effect of ambient temperature on the mortality burden of nonaccidental deaths in Yunnan Province and to further explore its spatial heterogeneity among different regions.
UNASSIGNED: We collected mortality and meteorological data from all 129 counties in Yunnan Province from 2014 to 2020, and 16 prefecture-level cities were analyzed as units. A distributed lagged nonlinear model was used to estimate the effect of temperature exposure on years of life lost (YLL) for nonaccidental deaths in each prefecture-level city. The attributable fraction of YLL due to ambient temperature was calculated. A multivariate meta-analysis was used to obtain an overall aggregated estimate of effects, and spatial heterogeneity among 16 prefecture-level cities was evaluated by adjusting the city-specific geographical characteristics, demographic characteristics, economic factors, and health resources factors.
UNASSIGNED: The temperature-YLL association was nonlinear and followed slide-shaped curves in all regions. The cumulative cold and heat effect estimates along lag 0-21 days on YLL for nonaccidental deaths were 403.16 (95% empirical confidence interval [eCI] 148.14-615.18) and 247.83 (95% eCI 45.73-418.85), respectively. The attributable fraction for nonaccidental mortality due to daily mean temperature was 7.45% (95% eCI 3.73%-10.38%). Cold temperature was responsible for most of the mortality burden (4.61%, 95% eCI 1.70-7.04), whereas the burden due to heat was 2.84% (95% eCI 0.58-4.83). The vulnerable subpopulations include male individuals, people aged <75 years, people with education below junior college level, farmers, nonmarried individuals, and ethnic minorities. In the cause-specific subgroup analysis, the total attributable fraction (%) for mean temperature was 13.97% (95% eCI 6.70-14.02) for heart disease, 11.12% (95% eCI 2.52-16.82) for respiratory disease, 10.85% (95% eCI 6.70-14.02) for cardiovascular disease, and 10.13% (95% eCI 6.03-13.18) for stroke. The attributable risk of cold effect for cardiovascular disease was higher than that for respiratory disease cause of death (9.71% vs 4.54%). Furthermore, we found 48.2% heterogeneity in the effect of mean temperature on YLL after considering the inherent characteristics of the 16 prefecture-level cities, with urbanization rate accounting for the highest proportion of heterogeneity (15.7%) among urban characteristics.
UNASSIGNED: This study suggests that the cold effect dominated the total effect of temperature on mortality burden in Yunnan Province, and its effect was heterogeneous among different regions, which provides a basis for spatial planning and health policy formulation for disease prevention.
■本研究旨在评估环境温度对云南省非意外死亡死亡负担的影响,并进一步探讨其在不同地区之间的空间异质性。
■我们收集了2014-2020年云南省所有129个县的死亡率和气象数据,并以16个地级市为单位进行了分析。使用分布式滞后非线性模型来估计温度暴露对每个地级市非意外死亡的寿命损失(YLL)的影响。计算由于环境温度引起的YLL的可归属分数。多变量荟萃分析用于获得效果的总体汇总估计,通过调整城市特定的地理特征,评估了16个地级市之间的空间异质性,人口特征,经济因素,和卫生资源因素。
■温度-YLL关联是非线性的,并且在所有区域都遵循滑动形曲线。非意外死亡的YLL滞后0-21天的累积冷热效应估计为403.16(95%经验置信区间[eCI]148.14-615.18)和247.83(95%eCI45.73-418.85),分别。每日平均温度导致非意外死亡率的归因分数为7.45%(95%eCI为3.73%-10.38%)。寒冷的温度是造成大部分死亡负担的原因(4.61%,95%eCI1.70-7.04),而热负担为2.84%(95%eCI0.58-4.83)。脆弱的亚群包括男性个体,75岁以下的人,大专以下文化程度的人,农民,未婚个体,和少数民族。在特定原因的亚组分析中,心脏病的平均温度的总归因分数(%)为13.97%(95%eCI6.70-14.02),呼吸系统疾病占11.12%(95%eCI2.52-16.82),心血管疾病的10.85%(95%eCI6.70-14.02),卒中占10.13%(95%eCI6.03-13.18)。心血管疾病的冷效应归因风险高于呼吸系统疾病死亡原因(9.71%vs4.54%)。此外,在考虑了16个地级市的固有特征后,我们发现平均温度对YLL的影响具有48.2%的异质性,城市化率占城市特征异质性比例最高(15.7%)。
■这项研究表明,寒冷效应主导了温度对云南省死亡负担的总影响,其影响在不同地区之间是异质的,为疾病预防的空间规划和卫生政策制定提供了依据。