Abstract
The current air quality index (AQI) has been argued for failing to respond to the combined health effects of multiple air pollutants. Thus, it is a challenge to construct a new indicator, air quality health index (AQHI) to comprehensively assess and predict air quality and the health effects caused by air pollution. Here, we have comprehensively considered the relationship between six air pollutants and the total mortality. And we constructed AQHI using the principal component analysis (FCA) by taking into account of the associations between six main air pollutants and YLL in Tianjin, China from 2014 to 2017. Then, we used the K-fold cross-validation method and the method of comparing AQHI with AQI to assess the validity of AQHI, respectively. Two principal components (F1 and F2) were used to construct AQHI; the cumulative contribution rate of variance for them was >70% (53.6% and 16.4%, respectively). With each unit increase of F1, the total daily YLL increased by 18.420 person-years. With each unit increase of F2, the total daily YLL increased by 22.409 person-years. The correlation between the predicted and actual values of total mortality and total YLL of AQHI was 0.742 (P < 0.001) and 0.700 (P < 0.001), respectively. The difference between AQI and AQHI was statistically significant (χ2 = 103.15, P < 0.001). There was a correlation between AQHI and AQI (r = 0.807, P < 0.01), and the grading was also correlated (rs = 0.580, P < 0.01). With an increase of interquartile range (IQR) for AQHI, the daily YLL increased by 32.797 (95% CI: 14.559, 51.034), while for the AQI, the daily YLL increased by 22.367 (95% CI: 6.619, 38.116), which was less than AQHI. These results imply that AQHI can comprehensively consider the impact of various pollutants on disease mortality and YLL, and can comprehensively reflect air quality, which has an important practical significance.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call