WIT Press


A Retrospective Case-control Study Investigating The Association Between Pollutant Exposures And Childhood Asthma

Price

Free (open access)

Paper DOI

10.2495/AIR120411

Volume

157

Pages

10

Page Range

469 - 478

Published

2012

Size

387 kb

Author(s)

J. Lai, S. Julious, S. Mason & J. Freeman

Abstract

Objective: to investigate possible associations between daily counts of schoolage asthma-medical contacts (and controls) and daily measures of pollution in Scotland. Study design: retrospective case-control study. Methods: daily counts and daily measures were obtained from 01/01/1999 to 31/12/2004. Autoregressive models using a Poisson distribution were undertaken on three groups: cases (school age-asthmatics), controls (cases and controls were matched by age, gender, primary care practice) and on the excess of daily counts for cases over controls. Twenty-one pollutant measures were investigated. These included minimum, mean and maximum daily measures of NO, NO2, NOD, PM10, O3, CO, SO2. Exposures were delayed by seven days to investigate any lagged effects with daily counts. Covariates include day of the week, bank holiday and season. The effects of each pollutant exposure were investigated using an F-test. Results: five pollutant exposures were associated with the daily counts for cases; six exposures were associated with daily counts for controls and eight exposures were associated with the daily excess of cases over controls. NO2 Mean was the most statistically significant exposure for cases and the excess whilst SO2 Maximum was the most statistically significant exposure for controls. Estimates were most significant after a delay (from exposure) of five (cases), four (controls) and current (excess) day(s) (lagged effect). Keywords: asthma, child, medical contact, pollutants, autoregression. 1 Introduction The prevalence of asthma (a chronic condition that affects the airways [1]) has increased substantially over the past five decades (1955–2004) [2]. The

Keywords

asthma, child, medical contact, pollutants, autoregression.