Asthma and Chronic Obstructive Pulmonary Disease (COPD) are two of the most common chronic respiratory diseases causing a major burden of ill health to populations across the world. Respiratory medication prescribing can be used as an indicator of air pollution effect on asthma and COPD, capturing patients with any severity of disease from mild to severe. In contrast, the traditional indicators of asthma exacerbation, such as hospital admissions and emergency room visits, only capture events of patients who suffer severe symptoms. In this study, I aimed to develop statistical models for assessing the spatiotemporal patterns of salbutamol prescribing in relation to air quality, in a primary health care setting. Salbutamol represents 93% of short-acting β2-agonists, which are prescribed for quick-relief of symptoms and acute exacerbations to individuals that suffer from asthma or COPD. I analysed salbutamol medication (approximately 67 billion Average-Daily-Quantities) prescribed by 64 GP practices in Newcastle and North Tyneside Primary Care Trusts, Northeast England, in 2002-2006. I used a mixed-effects model suitable for data that are not independent in time or space. My study found ambient Particulate Matter (PM10) concentrations to have a significant relationship to salbutamol prescribing in primary care. An increase of 10μg/m3 in ambient PM10 concentrations was associated with an increase of 1% in salbutamol prescribing. Income deprivation and average age of patients registered per practice also had a significant relationship with salbutamol prescribing. The findings showed that the variation of salbutamol prescribing was subject not only to health needs caused by deprivation and air quality, but also random effects that were practice specific, such as facilities within the practice or experience and prescribing pattern of practitioners. Overall, the findings demonstrated that respiratory prescribing in primary care can be used as indicator of air pollution effect on asthma and COPD, increasing the scope of its use for health surveillance in the future.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:566895 |
| Date | January 2011 |
| Creators | Sofianopoulou, Eleni |
| Publisher | University of Newcastle Upon Tyne |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://hdl.handle.net/10443/1335 |
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