A comparison of methods for calculating general practice level socioeconomic deprivation

• Published in: International journal of health geographics Vol. 5; no. 1; p. 29
• Main Authors: Strong, Mark, Maheswaran, Ravi, Pearson, Tim
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 04.07.2006; BioMed Central; BMC
• Subjects: Cause of Death; Family Practice - economics; Health Status Indicators; Humans; Poverty; Poverty Areas; Socioeconomic Factors; United Kingdom
• ISSN: 1476-072X; 1476-072X
• DOI: 10.1186/1476-072X-5-29

A measure of the socioeconomic deprivation experienced by the registered patient population of a general practice is of interest because it can be used to explore the association between deprivation and a wide range of other variables measured at practice level. If patient level geographical data are available a population weighted mean area-based deprivation score can be calculated for each practice. In the absence of these data, an area-based deprivation score linked to the practice postcode can be used as an estimate of the socioeconomic deprivation of the practice population. This study explores the correlation between Index of Multiple Deprivation 2004 (IMD) scores linked to general practice postcodes (main surgery address alone and main surgery plus any branch surgeries), practice population weighted mean IMD scores, and practice level mortality (aged 1 to 75 years, all causes) for 38 practices in Rotherham UK. Population weighted deprivation scores correlated with practice postcode based scores (main surgery only, Pearson r = 0.74, 95% CI 0.54 to 0.85; main plus branch surgeries, r = 0.79, 95% CI 0.63 to 0.89). All cause mortality aged 1 to 75 correlated with deprivation (main surgery postcode based measure, r = 0.50, 95% CI 0.22 to 0.71; main plus branch surgery based score, r = 0.55, 95% CI 0.28 to 0.74); population weighted measure, r = 0.66, 95% CI 0.43 to 0.81). Practice postcode linked IMD scores provide a valid proxy for a population weighted measure in the absence of patient level data. However, by using them, the strength of association between mortality and deprivation may be underestimated.