How differing methods of ascribing ethnicity and socio-economic status affect risk estimates for hospitalisation with infectious disease

Abstract

Significant ethnic and socio-economic disparities exist in infectious diseases (IDs) rates in New Zealand, so accurate measures of these characteristics are required. This study compared methods of ascribing ethnicity and socio-economic status. Children in the Growing Up in New Zealand longitudinal cohort were ascribed to self-prioritised, total response and single-combined ethnic groups. Socio-economic status was measured using household income, and both census-derived and survey-derived deprivation indices. Rates of ID hospitalisation were compared using linked administrative data. Self-prioritised ethnicity was simplest to use. Total response accounted for mixed ethnicity and allowed overlap between groups. Single combined ethnicity required aggregation of small groups to maintain power but offered greater detail. Regardless of the method used, Māori and Pacific children, and children in the most socio-economically deprived households had a greater risk of ID hospitalisation. Risk differences between self-prioritised and total response methods were not significant for Māori and Pacific children but single-combined ethnicity revealed a diversity of risk within these groups. Household income was affected by non-random missing data. The census derived deprivation index offered a high level of completeness with some risk of multicollinearity and concerns regarding the ecological fallacy. The survey-derived index required extra questions but was acceptable to participants and provided individualised data. Based on these results, the use of single-combined ethnicity and an individualised survey-derived index of deprivation are recommended where sample size and data structure allow it.

Citation

Hobbs, M. R., Atatoa Carr, P., Fa'alili-Fidow, J., Pillai, A., Morton, S. M. B., & Grant, C. C. (2019). How differing methods of ascribing ethnicity and socio-economic status affect risk estimates for hospitalisation with infectious disease. Epidemiology and Infection, 147. https://doi.org/10.1017/S0950268818002935

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Cambridge University Press (CUP)

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