Assessment of the concordance between individual-level and area-level measures of socio-economic deprivation in a cancer patient cohort in England and Wales

Abstract

ObjectivesMost research on health inequalities uses aggregated deprivation scores assigned to the small area where the patient lives; however, the concordance between aggregate area-level deprivation measures and personal deprivation experienced by individuals living in the area is poorly understood. Our objective was to examine the agreement between individual and ecological deprivation. We tested the concordance between metrics of income, occupation and education at individual and area levels, and assessed the reliability of area-based deprivation measures to predict individual deprivation circumstances.SettingEngland and Wales.ParticipantsA cancer patient cohort of 9547 individuals extracted from the Office for National Statistics Longitudinal Study.OutcomesWe quantified the concordance between measures of income, occupation and education at individual and area level. In addition, we used ROC (receiver operating characteristic) curves and the area under the curve (AUC) to assess the reliability of area-based deprivation measures to predict individual deprivation circumstances.ResultsWe found low concordance between individual-level and area-level indicators of deprivation (Cramer’s V statistics range between 0.07 and 0.20). The most commonly used indicator in health inequalities research, area-based income deprivation, was a poor predictor of individual income status (AUC between 0.56 and 0.59), whereas education and occupation were slightly better predictors (AUC between 0.62 and 0.65). The results were consistent across sexes and across six major cancer types.ConclusionsOur results indicate that ecological deprivation measures capture only part of the relationship between deprivation and health outcomes, especially with respect to income measurement. This has important implications for our understanding of the relationship between deprivation and health, and, as a consequence, healthcare policy. The results have a wide-reaching impact for the way in which we measure and monitor inequalities, and in turn, fund and organise current UK healthcare policy aimed at reducing them.

Association between multimorbidity and socioeconomic deprivation on short-term mortality among patients with diffuse large B-cell or follicular lymphoma in England: a nationwide cohort study

“…21 Furthermore, there is better concordance between area-level and individual-level measures of education when assessing patient health outcomes. 46 The observed deprivation level of a patient in our study is likely to be consistent had they been diagnosed at a different time; this is because deprivation scores have a high concordance between updates (ie, IMD of 2007, 2010 and 2015). 21 Our results are comparable to studies using this area-level measure of deprivation.…”

“…Second, recent research highlights the interest in using individual-level socioeconomic measures for assessing patient health outcomes in addition to arealevel measures of deprivation. 46 However, information on individual-level socioeconomic measures was unavailable, so we used only an area-level measure of socioeconomic status, which encapsulates the multidimensional composition of a patient's deprivation level in addition to the contextual level. 21 Furthermore, there is better concordance between area-level and individual-level measures of education when assessing patient health outcomes.…”

Impact of Socioeconomic Status on Adult Patients with Asthma: A Population-Based Cohort Study from UK Primary Care

“…The Indices of Multiple Deprivation is an area-based measure derived from the postcode of the patient's general practice, which may not accurately reflect the circumstances of the individual patients included in our analysis. 54,55 However, this potential misallocation should manifest in an underestimate of SES disparities due to regression dilution bias, meaning our main conclusions are not affected. Finally, there were a relatively low number of patients from EMGs, which did not facilitate a comparison of whether SES disparities differed by specific ethnicity (eg, Asian, Black).…”

Lung, Breast and Colorectal Cancer Incidence by Socioeconomic Status in Spain: A Population-Based Multilevel Study

“…We highlight the importance of interpreting findings at the population level to minimize ecological fallacy risk. It has recently been shown that, in England and Wales, the average socioeconomic status at the area level correlates poorly with the individual SES in higher heterogeneity areas (i.e., ecological fallacy) [ 37 ]. Moreover, in our study, the SDI was derived for 2011, while cancer incidence is measured for the period 2010–2013.…”