Joint modeling of time series measures and recurrent events and analysis of the effects of air quality on respiratory symptoms

Exposure to ambient pollutants at concentrations above defined standards is a risk factor for respiratory symptoms, especially in sensitive children. Many studies have been undertaken to monitor air quality and to assess its association with respiratory symptoms. We propose a joint mixed-effects regression model of time series measures and recurrent events to analyze the air quality and respiratory symptom data from the Yale Mothers and Infants Health Study. Three mothers' symptoms (runny nose, cough, and sore throat) and three infants' symptoms (runny nose, cough, and general sickness) were investigated, To alleviate the computational complexity, a two-stage maximum likelihood-based estimation procedure is introduced to estimate the parameters, and simulation studies are conducted to assess the validity of this estimation procedure. Our analysis reveals differences in the etiology of respiratory symptoms between mothers and infants. Most notably, coarse particles of mass between 2.5 and 10 μ in diameter increased the risks of mothers' runny nose and cough symptoms but had no significant effect on any of the three infants' symptoms. The sulfate level was negatively associated with the risk of infants' runny nose and cough symptoms but had no significant effect on any of the three mothers' symptoms. High level of humidity is negatively associated with the mothers' cough incidence but had no significant association with any of the three infants' symptoms. Such differences reveal not only the sensitivity of the mothers and infants to the air quality, but also call for further understanding of the differences. It is possible that actions taken to overcome humidity by mothers may inadvertently affect their infants.