Data Sheet 1_Association between ambient air pollution and outpatient visits of cardiovascular diseases in Zibo, China: a time series analysis.docx

IntroductionFacing Mount Tai in the south and the Yellow River in the north, Zibo District is an important petrochemical base in China. The effect of air pollution on cardiovascular diseases (CVDs) in Zibo was unclear.
MethodsDaily outpatient visits of common CVDs including coronary heart disease (CHD), stroke, and arrhythmia were obtained from 2019 to 2022 in Zibo. Air pollutants contained fine particulate matter (PM2.5), inhalable particulate matter (PM10), nitrogen dioxide (NO2), sulfur dioxide (SO2), ozone (O3), and carbon monoxide (CO). Distributed lag non-linear models (DLNM) including single-pollutant model in single-day (lag0-lag7) and cumulative-days (lag01-lag07), concentration-response curve, subgroup analysis, and double-pollutant model were utilized to examine the relationships of daily air pollutants on CHD, stroke, and arrhythmia. Meteorological factors were incorporated to control confounding.
ResultsIn single-pollutant model, NO2 was positively associated with CHD, stroke and arrhythmia, with the strongest excess risks (ERs) of 4.97% (lag07), 4.71% (lag07) and 2.16% (lag02), respectively. The highest ERs of PM2.5 on CHD, stroke and arrhythmia were 0.85% (lag01), 0.59% (lag0) and 0.84% (lag01), and for PM10, the ERs were 0.37% (lag01), 0.35% (lag0) and 0.39% (lag01). SO2 on CHD was 0.92% (lag6), O3 on stroke was 0.16% (lag6), and CO on CHD, stroke, and arrhythmia were 8.77% (lag07), 5.38% (lag01), 4.30% (lag0). No threshold was found between air pollutants and CVDs. The effects of ambient pollutants on CVDs (NO2&CVDs, PM2.5&stroke, PM10&stroke, CO&stroke, CO&arrhythmia) were greater in cold season than warm season. In double-pollutant model, NO2 was positively associated with CHD and stroke, and CO was also positively related with CHD.
ConclusionAmbient pollutants, especially NO2 and CO were associated with CVDs in Zibo, China. And there were strong relationships between NO2, PM2.5, PM10, CO and CVDs in cold season.