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OP52 Long-term exposure to air pollution and hospital admissions in Scotland: A 16-years register-based cohort study (2002–2017)
  1. Mary Abed Al Ahad1,
  2. Urška Demšar1,
  3. Frank Sullivan2,
  4. Hill Kulu1
  1. 1School of Geography and Sustainable Development, University of St Andrews, St Andrews, UK
  2. 2School of Medicine, University of St Andrews, St Andrews, UK

Abstract

Background Despite the well-documented research on the impact of air pollution on health, limitations in data, study designs, health outcomes selection, spatial considerations, and assessments of long-term exposures exist. In this study, we assessed the association of 16-years exposure to air pollution with all-cause and cause-specific hospital admissions in Scotland.

Methods We followed a ‘Scottish Longitudinal Study (SLS)’ cohort of 202,237 individuals aged 17+ for 16 years (2002–2017; N=2,810,414 observations). The SLS dataset was linked to yearly concentrations of four pollutants (NO2, SO2, and particulate-matter PM10 and PM2.5) at 1-Km spatial resolution using the individual’s residential postcode. Multilevel mixed-effects negative binomial regression was used to examine the association between air pollution and all-cause, cardiovascular, respiratory, infectious, mental/behavioural disorders, and other-causes hospital admissions. We accounted in our models for the spatial autocorrelation (SA) of air pollution between neighbouring postcodes by computing Local-Geary’s C0–1 score, a novel local neighbourhood-similarity measure.

Results Higher rates of all-cause, cardiovascular, infectious, mental/behavioural disorders, and other-causes hospital admissions were observed with increasing concentrations of NO2, PM10, and PM2.5 pollutants. Hospital admissions for respiratory diseases were associated with higher exposure to all the four pollutants including SO2. For example, the incidence-rate for respiratory hospital admissions increased by 12.5% (95%CI=9.7%-15.5%), 6.8% (95%CI=5.1%-8.5%), 2.2% (95%CI=0.5%-4.0%), and 1.9% (95%CI=1.5%-2.4%) per 1 µg/m3 increase in average cumulative exposure to PM2.5, PM10, SO2 and NO2 pollutants, respectively. Accounting for SA reduced the association magnitude between SO2 and hospital admission outcomes.

Conclusion By linking large register-based longitudinal data to air pollution at a fine spatial resolution over a period of 16 years and controlling for SA, this study highlights the harmful effect of air pollution on health manifested in higher rates of hospital admissions for various disease outcomes. Thus, interventions on air pollution through stricter environmental regulations could help ease the hospital-care burden.

  • Air pollution
  • hospital admissions
  • spatial autocorrelation

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