| Objective:To evaluate the effects of the atmospheric pollutants(PM2.5,PM10,NO2,SO2,CO)and temperature on the daily outpatient visits of cardiovascular diseases,we collect main air pollutants,meteorological and cardiovascular diseases data in Shijiazhuang city.In addition,the effects of the atmospheric pollutants on the daily outpatient visit of cardiovascular diseases in different seasons were assessed.Provide a scientific basis for taking effective preventive measures and protecting the residents'health.Methods:The outpatient visits of cardiovascular disease from the First Hospital of Hebei Medical University and the First Hospital of Shijiazhuang City from January 1,2014 to December 31,2016 was collected.The daily atmospheric pollutant monitoring concentrations and daily maximum temperature,minimum temperature,average temperature,maximum humidity,minimum humidity,average relative humidity,daily average wind speed,hours of sunshine and other meteorological data were collected during the same period.The Generalized Additive Model?GAM?was applied to evaluate the impact of atmospheric pollutants with the lag effects of 0 to 7days in a single day and the cumulative effects?lag01 to lag07?on the daily outpatient visits of cardiovascular diseases,using the smooth spline to control the long-term trend and seasonal trend of time,the"day of the week effect",meteorological factors and other confounding factors.Then determine the strongest effect period that was used in the two-pollutant model,seasonal effects,sensitivity analysis.In order to visually describe the effect of temperature on the daily outpatient visits of cardiovascular diseases,this study constructed a penalized distribution lag nonlinear model?Penalized dlnm?by establishing temperature“cross-basic”function and incorporating it into the GAM model.Analysis of effects of temperature on the daily cardiovascular outpatient visits and the lag effects of temperature,quantitative description and evaluating the effect of temperature on cardiovascular diseases.Results:1?January 1,2014 to December 31,2016,the average concentrations of atmospheric pollutants PM2.5,PM10,NO2,SO2 and CO were 104.93?g/m3,175.45?g/m3,53.90?g/m3,50.59?g/m3,1.49mg/m3,respectively.The distribution of atmospheric pollutants had certain seasonality.The spearman rank correlation analysis indicated that there was a strong significantly positive correlation between the five air pollutants.In particular,there is a strongest correlation between PM2.5.5 and PM10?r=0.97,P<0.01?.The correlation coefficients of PM2.5 and NO2,SO2,CO were 0.76?0.63?0.87?P<0.01?,respectively.The correlation coefficients of PM10 and NO2,SO2,CO were 0.78,0.60,0.84?P<0.01?,respectively.The correlations coefficient between NO2 and SO2,CO were 0.75 and 0.85?P<0.01?.The correlation coefficient between SO2 and CO was 0.72?P<0.01?.At the same time,it can be seen that there is a negative correlation between the five pollutants and temperature,wind speed and sunshine hours?P<0.01?,and with the pressure showed a positive correlation?P<0.01?;NO2 and SO2 were negatively correlated with relative humidity?P<0.01?;PM2.5,PM10 and CO showed positively correlated with relative humidity?P<0.01?.2?The results of the GAM model analysis showed that the effects of five air pollutants on the daily outpatient visits of cardiovascular disease were the strongest in the current day,and the best lag period of the single-day effect is lag0,and the daily average concentration of PM2.5,PM10,SO2,and NO2 increased by 10?g/m3,the number of outpatients increased by 0.42%,0.26%,0.92%,and 1.84%,respectively;for every 0.1mg/m3increase in daily CO concentration,the number of outpatients increased by0.44%.The cumulative effect was strongest at lag06.The daily average concentration of PM2.5,PM10,SO2,and NO2 increased by 10?g/m3,and the number of outpatients was increased by 0.61%,0.37%,1.35%,and 2.89%;for every 0.1 mg/m3 increase in daily average CO concentration,the number of cardiovascular disease increased by 0.82%.A subgroup analysis of the seasons revealed that the effects of atmospheric pollutants in the cold season were stronger than warm.The daily average concentrations of PM2.5,PM10,SO2,and NO2 increased by 10?g/m3,and the number of outpatients was increased by0.80%,0.65%,1.52%,and 4.71%,respectively.The daily average concentration of CO increased by 0.1 mg/m3,the outpatient visits of cardiovascular diseases were increased by0.82%.The impact of atmospheric pollutants on cardiovascular disease was statistically significant in the cold season.The two-pollutant models showed that the effect of SO2 on the daily outpatient visits of cardiovascular disease lost statistical significance after adjusting other pollutants.PM10 was only statistically significant when adjusting SO2.Other pollutants were still statistically significant and may be independent risk factors.3?The results of the penalized distributed lag nonlinear model analysis showed that low temperature had a great influence on the daily outpatient visits of cardiovascular diseases,and the relative risk will change with the temperature.The effect of temperature on the daily outpatient visits of cardiovascular diseases was nonlinear.The day did not show risk effects,and even show“protective”effects,but the risk effects of low temperature will last for a relatively long time?nearly two weeks?,while it was the“protective”effect at relatively high temperature.There was a certain risk effect after fifteen lag days,but there was no statistical significance.The relative risk values at-4°C?1st?and 0°C?10th?were 0.89?95%CI:0.80-0.99?and 0.91?95%CI:0.84-0.99?,respectively,showing protection effects;the relative risk values were 1.07?95%CI:1.03-1.12?,1.05?95%CI:1.01-1.09?at lag 5 days and there was a risk effect.The relative risk values were 1.03?95%CI:1.00-1.07?,1.03?95%CI:1.00,1.06?when the lag was 10days and the risk effect was reduced.The risk effects exhibited increase first and then weaken by the lag time.The temperature had no significant effect on cardiovascular diseases at the cumulative lag of 5 days?lag0-5?.After the cumulative lag of 10 days?lag0-10?,-4°C and 0°C showed risk effects.The relative risk values were 1.81?95%CI:1.11-2.94?and 1.53?95%CI:1.00-2.34?when the cumulative lag is 27 days.The risk effects were stronger when the temperature was relatively low.No risk effects were observed at relatively high temperatures of 27.7°C and 30.7°C.Conclusion:1?In 2014-2016,the atmospheric pollutants showed seasonal changes in Shijiazhuang,which were characterized by“winter heavy and summer light”with a certain cyclical and seasonal fluctuations trend.2?The increase of atmospheric pollutant concentrations had a positive correlation with the increase of outpatient visits and had lag effects.The harmful effects of atmospheric pollutants had obvious seasonality,showing that the effect of the cold season is higher than that of the warm season.The effect of gaseous pollutants was higher than particulate matter and the effect of NO2 was the strongest.In two pollutants model,it is found that NO2,PM2.5,CO may have independent risk effects,while SO2 and PM100 may not have independent risk effects.3?The effects of ambient temperature on the daily outpatient visits of cardiovascular diseases were non-linear and the risk effects were greater when the temperature was low.In addition,there was a fifteen days lag effect.While no harmful effects were found at higher temperatures. |
PDF Full Text Request