On the validity of area-based income measures to proxy household income

<p/> <p>Background</p> <p>This paper assesses the agreement between household-level income data and an area-based income measure, and whether or not discrepancies create meaningful differences when applied in regression equations estimating total household prescription drug e...

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Main Authors: Hanley Gillian E, Morgan Steve
Format: Article
Language:English
Published: BMC 2008-04-01
Series:BMC Health Services Research
Online Access:http://www.biomedcentral.com/1472-6963/8/79
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spelling doaj-8c080093324745f48b600b38612893262020-11-25T00:38:54ZengBMCBMC Health Services Research1472-69632008-04-01817910.1186/1472-6963-8-79On the validity of area-based income measures to proxy household incomeHanley Gillian EMorgan Steve<p/> <p>Background</p> <p>This paper assesses the agreement between household-level income data and an area-based income measure, and whether or not discrepancies create meaningful differences when applied in regression equations estimating total household prescription drug expenditures.</p> <p>Methods</p> <p>Using administrative data files for the population of BC, Canada, we calculate income deciles from both area-based census data and Canada Revenue Agency validated household-level data. These deciles are then compared for misclassification. Spearman's correlation, kappa coefficients and weighted kappa coefficients are all calculated. We then assess the validity of using the area-based income measure as a proxy for household income in regression equations explaining socio-economic inequalities in total prescription drug expenditures.</p> <p>Results</p> <p>The variability between household-level income and area-based income is large. Only 37% of households are classified by area-based measures to be within one decile of the classification based on household-level incomes. Statistical evidence of the disagreement between income measures also indicates substantial misclassification, with Spearman's correlations, kappa coefficients and weighted kappa coefficients all indicating little agreement. The regression results show that the size of the coefficients changes considerably when area-based measures are used instead of household-level measures, and that use of area-based measures smooths out important variation across the income distribution.</p> <p>Conclusion</p> <p>These results suggest that, in some contexts, the choice of area-based versus household-level income can drive conclusions in an important way. Access to reliable household-level income/socio-economic data such as the tax-validated data used in this study would unambiguously improve health research and therefore the evidence on which health and social policy would ideally rest.</p> http://www.biomedcentral.com/1472-6963/8/79
collection DOAJ
language English
format Article
sources DOAJ
author Hanley Gillian E
Morgan Steve
spellingShingle Hanley Gillian E
Morgan Steve
On the validity of area-based income measures to proxy household income
BMC Health Services Research
author_facet Hanley Gillian E
Morgan Steve
author_sort Hanley Gillian E
title On the validity of area-based income measures to proxy household income
title_short On the validity of area-based income measures to proxy household income
title_full On the validity of area-based income measures to proxy household income
title_fullStr On the validity of area-based income measures to proxy household income
title_full_unstemmed On the validity of area-based income measures to proxy household income
title_sort on the validity of area-based income measures to proxy household income
publisher BMC
series BMC Health Services Research
issn 1472-6963
publishDate 2008-04-01
description <p/> <p>Background</p> <p>This paper assesses the agreement between household-level income data and an area-based income measure, and whether or not discrepancies create meaningful differences when applied in regression equations estimating total household prescription drug expenditures.</p> <p>Methods</p> <p>Using administrative data files for the population of BC, Canada, we calculate income deciles from both area-based census data and Canada Revenue Agency validated household-level data. These deciles are then compared for misclassification. Spearman's correlation, kappa coefficients and weighted kappa coefficients are all calculated. We then assess the validity of using the area-based income measure as a proxy for household income in regression equations explaining socio-economic inequalities in total prescription drug expenditures.</p> <p>Results</p> <p>The variability between household-level income and area-based income is large. Only 37% of households are classified by area-based measures to be within one decile of the classification based on household-level incomes. Statistical evidence of the disagreement between income measures also indicates substantial misclassification, with Spearman's correlations, kappa coefficients and weighted kappa coefficients all indicating little agreement. The regression results show that the size of the coefficients changes considerably when area-based measures are used instead of household-level measures, and that use of area-based measures smooths out important variation across the income distribution.</p> <p>Conclusion</p> <p>These results suggest that, in some contexts, the choice of area-based versus household-level income can drive conclusions in an important way. Access to reliable household-level income/socio-economic data such as the tax-validated data used in this study would unambiguously improve health research and therefore the evidence on which health and social policy would ideally rest.</p>
url http://www.biomedcentral.com/1472-6963/8/79
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