Effects of early life exposure to particulates on respiratory health through childhood and adolescence: ALSPAC

Asthma and wheezing illness are major causes of impaired quality of life, use of primary care, consumption of prescribed drugs and hospital admission in children. There is increasing evidence that air pollutants may be important in both causing asthma and related conditions such as childhood wheeze, as well as exacerbating these conditions once they have occurred. There is also evidence that exposures to air pollutants in early life, including of the fetus before birth, may be important. We aim to investigate the long-term effects of exposure to fine particulate air pollution (PM2.5) in the prenatal period and early infancy on allergy, respiratory symptoms, doctor-diagnosed asthma and lung function of children through to adolescence. The research takes advantage of the wealth of existing information from the Avon Longitudinal Study of Parents and Children (ALSPAC), one of the largest and best characterised birth cohort studies in the world. Data are available from the antenatal period, with detailed measurement and capture of health data through childhood to age 15+ years. We will supplement these data with estimated exposures to PM2.5 at place of residence during the critical period of lung development from the fetal period until the end of the first year of life. These exposures will reflect both local sources (mainly traffic-related pollution) and long-distance transport of pollutants. Detailed modelling of these exposures will be carried out, together with monitoring in the study area in order to help validate the estimates obtained. Daily estimates of exposure to PM2.5 will then be made, taking account of place of residence and (where relevant) school. Associations between exposures to PM2.5 and the health outcomes will be analysed taking account of other variables that might confound this association including individual socio-economic variables, lifestyle and personal characteristics, as well as other environmental variables such as environmental tobacco smoke and ambient temperature. Results of the research will inform policy on regulation of air pollutants for the protection of public health.

Asthma and wheezing illness are important causes of impaired quality of life, use of primary care, consumption of prescribed drugs and hospital admission in children. There is increasing evidence that air pollutants may be important in the aetiology as well as exacerbation of asthma and related conditions, including exposures to air pollutants in early life. We aim to investigate the long-term effects of exposure to fine particulate air pollution (PM2.5) in the prenatal period and early infancy on sensitisation to aeroallergens, respiratory symptoms, doctor-diagnosed asthma and lung function of children through to adolescence. The research takes advantage of the wealth of existing information from the Avon Longitudinal Study of Parents and Children (ALSPAC), one of the largest and best characterised birth cohort studies in the world. Data are available from the ante-natal period, with detailed measurement and capture of health data through childhood to age 15+ years. We will supplement these data with estimated spatial (largely traffic-related) and temporal exposures to PM2.5 at place of residence during the critical period of lung development from the fetal period until the end of the first year of life. Exposure modelling will be done using a combination of local and trans-boundary (inter-regional) dispersion modelling, based on real-time (hourly) meteorological data, and detailed emissions inventories for all major sources (including road traffic and point industrial emissions). Extensive model validation will be carried out in the study area via purpose-designed monitoring. Daily estimates of exposure to PM2.5 will then be made, taking account of place of residence and (where relevant) school. Associations between exposures and the health outcomes will be analysed in a frequentist setting using logistic and multinomial logistic regression and by hierarchical Bayesian modelling techniques. We will control for potential confounding by individual socio-economic variables, lifestyle and personal characteristics, as well as other environmental variables such as environmental tobacco smoke and ambient temperature. We will include use of measurement error models to improve estimation. Results of the research will inform policy on regulation of air pollutants for the protection of public health.