METHODS: Taking the Sichuan Basin (SCB), an economically imbalanced area with high humidity and four distinctive seasons, as an example, we used a novel multi-stage strategy to investigate the two issues. First, distributed lag nonlinear models were independently constructed to obtain the county-level associations between daily temperature and cardiorespiratory mortality. Then, an estimation-error-based spatial scan statistic was used to detect the association-clustered regions. Third, multivariate meta-regression incorporating the identified clustered regions and socioeconomic and natural factors was used to obtain stable county-specific associations, based on which the heat- and cold-attributable deaths were mapped and their inequalities were evaluated using concentration indices and Lorenz curves.
RESULTS: On average, a U-shaped temperature-mortality association was examined. A significantly association-clustered region was detected (P = 0.017), in which heat and cold temperatures presented significantly stronger associations than those in the non-clustered region, particularly for heat temperatures. The cold-attributable deaths (3.5%) were substantially more than the heat-attributable deaths (0.5%). Both presented severe inequalities over counties. Significant temperature-attributable inequalities were also found over per-capital public budget, urbanization rate, employment rate and per-capital GDP. The directions of inequalities over GDP and urbanization rate were opposite between heat and cold temperatures.
CONCLUSIONS: Our analysis provided the first evidence about the clustering of temperature-mortality associations and the inequality of cold- and heat-attributable burdens. Significantly association-clustered regions and heavy temperature-attributable inequalities were found in the SCB. Rural people bore heavier cold-attributable but less heat-attributable mortality risk than urban people, suggesting that different policies should be designed to reduce the temperature-attributable inequalities for heat and cold temperatures and different regions. This novel strategy can provide an interesting new perspective in the association between environmental exposure and human health.
方法:以四川盆地(SCB)为例,一个高湿度和四个独特季节的经济不平衡地区,作为一个例子,我们采用了一种新颖的多阶段策略来研究这两个问题。首先,独立构建分布滞后非线性模型,以获得县级每日温度与心肺死亡率之间的关联。然后,使用基于估计误差的空间扫描统计量来检测关联聚类区域.第三,结合已识别的聚集区域以及社会经济和自然因素的多元元回归用于获得稳定的特定县关联。在此基础上绘制了热死亡和冷死亡的地图,并使用浓度指数和洛伦兹曲线评估了它们的不平等。
结果:平均而言,研究了U型温度-死亡率相关性.检测到一个显著的关联聚类区域(P=0.017),其中高温和低温比非集群区域表现出明显更强的关联,特别是加热温度。因冷死亡(3.5%)明显高于因热死亡(0.5%)。两者都在县之间表现出严重的不平等。在每资本公共预算中也发现了显著的温度归因不平等,城镇化率,就业率和人均国内生产总值。在高温和低温之间,GDP和城市化率的不平等方向相反。
结论:我们的分析提供了关于温度-死亡率关联的聚类以及冷热负担不平等的第一个证据。在SCB中发现了显着的关联聚集区域和严重的温度归因不等式。农村人口比城市人口承受更重的冷归因死亡风险,但热归因死亡风险较小,建议应设计不同的政策,以减少热和冷温度以及不同地区的温度可归因于的不平等。这种新策略可以为环境暴露与人类健康之间的关联提供有趣的新视角。