Effects and interaction of air pollution and meteorological factors on pertussis incidence in P.R.China

Abstract

Background: Previous studies on the risk of pertussis exposure to atmospheric pollutants are still inconclusive. Methods: Air pollutant, meteorological data and epidemiological distribution of pertussis cases in China during 2004–2018 were concluded in this study. A distributed lag nonlinear model (DLNM) for a maximum lag of 15 months was developed to evaluate the lag effects of monthly air pollutants and meteorological factors on pertussis incidence. Then a generalized additive model (GAM) was constructed to explore the interaction effect among air pollutants, meteorological factors and pertussis incidence and the stratified effect of selected variables. Results: A total of 74,249 cases of pertussis were included during 2004–2018 in China. Long-term exposure to NO2 was positively associated with the risk of pertussis at 32–94 µg/m3. Interaction and stratified analyses showed that there were certain correlations between 4 air pollutants (PM2.5, SO2, NO2, and O3) and 3 meteorological factors (temperature, sunlight and wind speed). In the high PM2.5 environment, a unit increment in NO2 contributed to a 2.52% (95% CI: 2.13%-2.92%) increase in pertussis incidence risk, while in a low PM2.5 environment, a unit increment of NO2 contributed to a 2.16% (95% CI: 1.64%-2.69%) increase in pertussis incidence risk. Conclusions: Our study indicated that air pollutants and meteorological factors have delayed effects on the occurrence of pertussis in China, and the effect of NO2 can be modified by PM2.5, SO2, and O3. In the prevention and control of pertussis, the additive effect of different factors on pertussis and the variability of weather should be considered.

Keywords

• Air pollution
• Meteorological factors
• Pertussis
• Distributed lag nonlinear models
• Generalized additive model