Additional file 1 of Effects of particulate matter on hospital admissions for respiratory diseases: an ecological study based on 12.5 years of time series data in Shanghai
Creators: name: Peng, Wenjia
name: Li, Hao
name: Peng, Li
name: Wang, Ying
name: Wang, Weibing
Publisher: name: figshare
Year: 2022
Subjects: Medicine
Biotechnology
Environmental Sciences not elsewhere classified
Biological Sciences not elsewhere classified
Cancer
Science Policy

description: Additional file 1: Table S I. The annual average concentrations of PMs in Shanghai. Table S II. Spearman correlation coefficients among air pollution variables and meteorological factors. Table S III. The attributable number of respiratory diseases admissions due to exceeding PM2.5 concentrations. Table S IV. The attributable number of respiratory diseases admissions due to exceeding PM10 concentrations. Table S V. The attributable number of respiratory diseases admissions due to exceeding PM2.5 concentrations in males. Table S VI. The attributable number of respiratory diseases admissions due to exceeding PM2.5 concentrations in females. Table S VII. The attributable number of respiratory diseases admissions due to exceeding PM10 concentrations in males. Table S VIII. The attributable number of respiratory diseases admissions due to exceeding PM10 concentrations in females. Table S III. The attributable number of respiratory diseases admissions due to exceeding PM2.5 concentrations in &lt; 45 years. Table S IX. The attributable number of respiratory diseases admissions due to exceeding PM2.5 concentrations in 45 ~ 64 years. Table S X. The attributable number of respiratory diseases admissions due to exceeding PM2.5 concentrations in 65 ~ 74 years. Table S XI. The attributable number of respiratory diseases admissions due to exceeding PM2.5 concentrations in ≥75 years. Table S XII. The attributable number of respiratory diseases admissions due to exceeding PM10 concentrations in &lt; 45 years. Table S XIII. The attributable number of respiratory diseases admissions due to exceeding PM10 concentrations in 45 ~ 64 years. Table S XIV. The attributable number of respiratory diseases admissions due to exceeding PM10 concentrations in 65 ~ 74 years. Table S XV. The attributable number of respiratory diseases admissions due to exceeding PM10 concentrations in ≥75 years. Table S XVI. Percentage change with 95% confidence interval in hospital admissions for respiratory diseases per 10 μg/m3 increase in concentrations of PM2.5 and PM10 using two-pollutant models. Table S XVII. Percentage change with 95% confidence interval in hospital admissions for respiratory diseases associated with a 10 μg/m3 increase in concentrations of PM2.5 and PM10 through changing degrees of freedom for the calendar time. Table S XVIII. Percentage change with 95% confidence interval in hospital admissions for respiratory diseases associated with a 10 μg/m3 increase in concentrations of PM2.5 and PM10 through excluding the data from 2020 due to the coronavirus disease 2019 pandemic. Fig. S I. Percentage change with 95% confidence interval in hospital admissions for respiratory diseases per 10 μg/m3 increase in concentrations of PM2.5 stratified by genders. All the models were adjusted by public holidays, DOW, and calendar day. Fig. S II. Percentage change with 95% confidence interval in hospital admissions for respiratory diseases per 10 μg/m3 increase in concentrations of PM10 stratified by genders. All the models were adjusted with public holidays, DOW, and calendar day. Fig. S III. Percentage change with 95% confidence interval in hospital admissions for respiratory diseases per 10 μg/m3 increase in concentrations of PM2.5 stratified by age groups. All the models were adjusted with public holidays, DOW, and calendar day. Fig. S IV. Percentage change with 95% confidence interval in hospital admissions for respiratory diseases per 10 μg/m3 increase in concentrations of PM10 stratified by age groups. All the models were adjusted with public holidays, DOW, and calendar day. Fig. S V. Percentage change with 95% confidence interval in hospital admissions for respiratory diseases per 10 μg/m3 increase in concentrations of PM2.5 stratified by season. All the models were adjusted with public holidays, DOW, and calendar day. Fig. S VI. Percentage change with 95% confidence interval in hospital admissions for respiratory diseases per 10 μg/m3 increase in concentrations of PM10 stratified by season. All the models were adjusted with public holidays, DOW, and calendar day.