高血压日入院人数与空气污染物浓度相关性研究

  目的  比较空气污染与疾病关系研究中广义相加模型中泊松分布、类泊松分布、负二项分布对研究结果造成的差异，为空气污染物与疾病的相关研究提供方法参考。  方法  收集福棠儿童医学研究中心病案首页（FUTURE）数据库中河南省郑州市儿童医院2016年1月1日 — 2019年12月31日呼吸系统疾病住院病例的病案首页数据及郑州市同一时期的空气污染和气象数据，采用广义相加模型的泊松分布、类泊松分布、负二项分布方法分析臭氧（O₃）与儿童呼吸系统疾病的关系。  结果  对日住院病例数进行Kolmogorov-Smirnov拟合优度检验结果显示，日住院病例数不服从泊松分布（D = 0.203，P < 0.001），但服从负二项分布（D = 0.055，P = 0.079）；基于泊松分布、类泊松分布和负二项分布的广义相加模型分析滞后0～3 d的平均效应结果显示，O₃对儿童呼吸系统住院病例数的RR（95 % CI）值分别为1.0039（1.0015～1.0064）、1.0041（1.0001～1.0081）和1.0041（1.0000～1.0081）。  结论  广义相加模型中以病例数作为结局变量，当出现过度离散时首选负二项分布可减少假阳性错误且能更好地进行模型拟合优度的比较。

Research on adaption to air pollution in Chinese cities: evidence from social media-based health sensing

  Objective  To compare differences among the results of utilizing Poisson distribution, quasi-Poisson distribution, and negative binomial distribution in the generalized additive model (GAM) analysis on the association of ambient air ozone (O₃) with respiratory diseases in children for providing references to researches on the relationship between air pollutants and diseases.   Methods  The data on 117 502 children with respiratory diseases hospitalized in Zhengzhou Children′s Hospital, Henan province during 2016 through 2019 were extracted from the FUTang Updating Medical Records (FUTURE) database; daily data of meteorological monitoring and atmospheric pollution in Zhengzhou city during the same period were also collected. Poisson distribution, quasi-Poisson distribution, and negative binomial distribution of generalized additive model were used to analyze the relationship between daily ambient air O₃ concentration and number of child hospitalization due to respiratory diseases.   Results  The results of Kolmogorov-Smirnov goodness of fit test revealed that the distribution of daily hospitalization of children with respiratory diseases was consistent with negative binomial distribution (D = 0.055, P = 0.079), but not with Poisson distribution (D = 0.203, P < 0.001). The results of the GAM analysis with Poisson distribution, quasi-Poisson distribution, and negative binomial distribution showed that a 10 μg/m³ increase in ambient O₃ was significantly related to an increment in the number of child hospitalization due to respiratory diseases averagely at lag day 0 – lag day 3, with the relative risks (RRs) (95% confidence interval, 95% CI) of 1.0039 (1.0015 – 1.0064), 1.0041 (1.0001 – 1.0081), and 1.0041 (1.0000 – 1.0081), respectively.   Conclusion  The study results suggest that negative binomial distribution should be adopted first when conducting a GAM analysis involving an overdispersed dependent variable for reducing false positive error.