OBJECTIVES: To assess differences in statin prescribing across Australia by geographic area. DESIGN, SETTING AND PARTICIPANTS: A cross-sectional study using Pharmaceutical Benefits Scheme data on statin prescribing by rurality, gender and patient postcode for the period May to December 2002. Participants were the Australian population, stratified by gender, quintile of index of relative socioeconomic disadvantage and rural, remote and metropolitan areas classification. RESULTS: Statin prescribing (scripts per 1000 population per month) was higher in urban areas (women, 51.915; men, 51.892) than in rural (women, 48.311; men, 48.098) or remote (women, 39.679; men, 34.145) areas. In urban areas, weighted least squares regression analysis showed a significant negative linear association between statin prescribing and socioeconomic status for both women (weighted least squares slope, -3.358; standard error (SE) 0.057; P < 0.0001) and men (slope, -0.507; SE 0.056; P < 0.0001). A similar association occurred in rural areas: women (slope, -4.075; SE 0.122; P < 0.0001) and men (slope, -3.455; SE 0.117; P < 0.0001), but not in remote areas where there was a positive linear association (slope, 3.120; SE 0.451; P < 0.0001) and men (slope, 3.098; SE 0.346; P < 0.0001). CONCLUSION: Our results suggest differences in statin prescribing in Australia across geographic location, adjusting for age, gender and socioeconomic status. IMPLICATIONS: These findings suggest that health inequalities due to geography should be addressed.
OBJECTIVES: To assess differences in statin prescribing across Australia by geographic area. DESIGN, SETTING AND PARTICIPANTS: A cross-sectional study using Pharmaceutical Benefits Scheme data on statin prescribing by rurality, gender and patient postcode for the period May to December 2002. Participants were the Australian population, stratified by gender, quintile of index of relative socioeconomic disadvantage and rural, remote and metropolitan areas classification. RESULTS: Statin prescribing (scripts per 1000 population per month) was higher in urban areas (women, 51.915; men, 51.892) than in rural (women, 48.311; men, 48.098) or remote (women, 39.679; men, 34.145) areas. In urban areas, weighted least squares regression analysis showed a significant negative linear association between statin prescribing and socioeconomic status for both women (weighted least squares slope, -3.358; standard error (SE) 0.057; P < 0.0001) and men (slope, -0.507; SE 0.056; P < 0.0001). A similar association occurred in rural areas: women (slope, -4.075; SE 0.122; P < 0.0001) and men (slope, -3.455; SE 0.117; P < 0.0001), but not in remote areas where there was a positive linear association (slope, 3.120; SE 0.451; P < 0.0001) and men (slope, 3.098; SE 0.346; P < 0.0001). CONCLUSION: Our results suggest differences in statin prescribing in Australia across geographic location, adjusting for age, gender and socioeconomic status. IMPLICATIONS: These findings suggest that health inequalities due to geography should be addressed.