在许多研究中,线性方法用于计算空气质量改善的健康效益,但是空气污染物与疾病之间的关系可能是复杂和非线性的。此外,以前的研究使用参考数字作为疾病的平均数量可能会高估健康益处。因此,非线性模型估计和参考数的重置非常重要。冠心病(CHD)的住院数据,气象数据,收集了淄博市2015-2019年的大气污染物数据。广义加性模型(GAM)用于探索空气污染物与冠心病住院之间的关系。并评估不同参考数字设置下对健康益处的影响。在研究期间,淄博市共报告了21,105例冠心病住院病例。GAM的结果表明,O3与冠心病住院患者之间存在对数线性暴露-反应关系,RR(相对风险)为1.0143(95%CI:1.0047~1.0239)。PM10,PM2.5,SO2和CHD入院之间存在对数非线性暴露-响应关系。随着污染物浓度的增加,入院风险呈现先升高后降低的趋势。与作为参考数字的平均住院人数相比,由GAM模型预测的住院人数计算的健康益处较低。以世界卫生组织的空气质量准则为参考,O3,PM10和PM2.5的归因分数为1.97%(95%CI:0.63〜3.40%),11.82%(95%CI:8.60~15.24%),和11.82%(95%CI:8.79~15.04%),分别。在量化改善空气质量带来的健康益处时,首先,应根据空气污染物与结果之间的暴露-响应关系确定相应的计算方法。然后,将平均住院人数作为参考数字可能会高估空气质量改善带来的健康益处。
In many studies, linear methods were used to calculate health benefits of air quality improvement, but the relationship between air pollutants and diseases may be complex and nonlinear. In addition, previous studies using reference number as average number of diseases may overestimate the health benefits. Therefore, the nonlinear model estimation and resetting of the reference number were very important. Hospital admission data for coronary heart disease (CHD), meteorological data, and air pollutant data of Zibo City from 2015 to 2019 were collected. The generalized additive model (GAM) was used to explore the association between air pollutants and hospital admission for CHD, and to evaluate the effects on health benefits under different reference number settings. A total of 21,105 hospitalized cases for CHD were reported in Zibo during the
study period. The results of the GAM showed there was a log-linear exposure-response relationship between O3 and hospital admissions for CHD, with RR (relative risk) of 1.0143 (95% CI: 1.0047 ~ 1.0239). There were log-nonlinear exposure-response relationships between PM10, PM2.5, SO2, and hospital admissions for CHD. With the increase of pollutants concentrations, the risk for hospital admission showed a trend of increasing first and then decreasing. Compared with the average hospital admissions as the reference number, health benefits calculated by hospital admissions predicted by the GAM model yielded lower. Using the World Health Organization air quality guidelines as reference, attributable fractions of O3, PM10, and PM2.5 were 1.97% (95% CI: 0.63 ~ 3.40%), 11.82% (95% CI: 8.60 ~ 15.24%), and 11.82% (95% CI: 8.79 ~ 15.04%), respectively. When quantifying health benefits brought by improving air quality, corresponding calculation methods should first be determined according to the exposure-response relationships between air pollutants and outcomes. Then, applying the average hospital admissions as reference number may overestimate health benefits resulting from improved air quality.