Using the NILS to analyse socio-economic & demographic determinants of antibiotic prescribing patterns

Johnston, F. & Rosato, M. (2011) British Society for Population Studies Annual Conference, University of York, UK, 7 - 9 September 2011 [NILS]

Other information:
Abstract:

The Northern Ireland Longitudinal Study (NILS) is a large scale, representative data-linkage study consisting of approximately 500,000 people (28% of the population). The NILS follows major life events using information from sources including the 2001 Census, vital events data (e.g. births, deaths) from the General Register Office and demographic data derived from health card registration data. The NILS is an innovative research resource which also allows for the opportunity to link to distinct Health and Social Care administrative datasets. For this analysis, the NILS database was linked to the Enhanced Prescribing Database, an electronic record of drugs prescribed in Northern Ireland. This linkage required specific ethical approval and only an anonymised dataset was made available to researchers. The aim of this project is to examine for individual and area level characteristics influencing variation in antibiotic usage to inform the management of antibiotic prescribing and consumption in Northern Ireland. A multinomial logistic regression modelling framework was used to examine the relative risks of receiving an antibiotic prescription in relation to both (a) individual level demographic and socio-economic characteristics; and (b) area level attributes such as urban/rural classifications and deprivation measures. Preliminary results show clear emerging patterns in relation to the prescribing of antibiotics: women; those not married; those living in deprived circumstances; and those from a Catholic community background all show significantly increased risks of being prescribed more antibiotic drugs when compared with their associated reference groups.

Available online: Link
Download output document: Presentation slides (PDF 182KB)
Output from project: 042

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