Open AccessThe impact of geographic unit of analysis on socioeconomic inequalities in cancer survival and distant summary stage – a population‐based study
Author(s) -
Tervonen Hanna E.,
Morrell Stephen,
Aranda Sanchia,
Roder David,
You Hui,
Niyonsenga Theo,
Walton Richard,
Baker Deborah,
Currow David
Publication year - 2017
Publication title -
australian and new zealand journal of public health
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.946
H-Index - 76
eISSN - 1753-6405
pISSN - 1326-0200
DOI - 10.1111/1753-6405.12608
Subject(s) - socioeconomic status , demography , disadvantage , population , medicine , logistic regression , environmental health , sociology , political science , law
Objective: When using area‐level disadvantage measures, size of geographic unit can have major effects on recorded socioeconomic cancer disparities. This study examined the extent of changes in recorded socioeconomic inequalities in cancer survival and distant stage when the measure of socioeconomic disadvantage was based on smaller Census Collection Districts (CDs) instead of Statistical Local Areas (SLAs). Methods: Population‐based New South Wales Cancer Registry data were used to identify cases diagnosed with primary invasive cancer in 2000–2008 (n=264,236). Logistic regression and competing risk regression modelling were performed to examine socioeconomic differences in odds of distant stage and hazard of cancer death for all sites combined and separately for breast, prostate, colorectal and lung cancers. Results: For all sites collectively, associations between socioeconomic disadvantage and cancer survival and distant stage were stronger when the CD‐based socioeconomic disadvantage measure was used compared with the SLA‐based measure. The CD‐based measure showed a more consistent socioeconomic gradient with a linear upward trend of risk of cancer death/distant stage with increasing socioeconomic disadvantage. Site‐specific analyses provided similar findings for the risk of death but less consistent results for the likelihood of distant stage. Conclusions: The use of socioeconomic disadvantage measure based on the smallest available spatial unit should be encouraged in the future. Implications for public health: Disadvantage measures based on small spatial units can more accurately identify socioeconomic cancer disparities to inform priority settings in service planning.