title: Do ethnic and socio-economic inequalities in mortality vary by region in New Zealand? An application of hierarchical Bayesian modelling.
abstract: We hypothesised that ethnic and socio-economic inequality in mortality might vary by region in New Zealand. Linked 2001-2004 census-mortality data were stratified by region (District Health Boards or DHBs), sex, age and ethnic groups, and income quintiles. To accommodate data sparseness, and to achieve accurate estimates of DHB-specific mortality rates and rate ratios by ethnicity and income, we used hierarchical Bayesian methods. To aid presentation of results, we used posterior mortality rates from the models to calculate directly standardised rates and rate ratios, with credible intervals. Māori-European/Other mortality rate ratios were often similar across DHBs, but Waitemata and Canterbury DHBs (both predominantly urban areas with low Māori population) had significantly lower rate ratios. In contrast, Bay of Plenty and Waikato DHBs (heterogeneous by both ethnicity and socio-economic position) had significantly higher rate ratios. There was little variation in mortality inequalities by income across DHBs. Examining the underlying rates for ethnic and income groups separately, there were significant variations across DHBs, but these were often correlated such that the ethnic or income rate ratio was similar across DHBs. The application of hierarchical Bayesian allowed more definitive conclusions than routine empirical methods when comparing small populations such as social groups across regions. The range of hierarchical Bayesian estimates of Māori mortality and Māori:European rate ratios across regions was considerably narrower than empirical standardisation estimates.
authors.affiliation: University of Otago, Department of Public Health, Newtown, Wellington, New Zealand. ken.richardson@otago.ac.nz
authors.forename: Ken
authors.initials: K
authors.lastname: Richardson
authors.forename: Tony
authors.initials: T
authors.lastname: Blakely
authors.forename: Jim
authors.initials: J
authors.lastname: Young
authors.forename: Patrick
authors.initials: P
authors.lastname: Graham
authors.forename: Martin
authors.initials: M
authors.lastname: Tobias
mesh_terms: D001499:Bayes Theorem; D019352:Censuses; D005006:Ethnicity / Q000706:statistics & numerical data*; D005260:Female; D054624:Health Status Disparities; D006801:Humans; D007182:Income / Q000706:statistics & numerical data*; D008297:Male; D008875:Middle Aged; D009026:Mortality / Q000208:ethnology*; D009520:New Zealand / Q000453:epidemiology; D016012:Poisson Distribution; D012044:Regression Analysis; D017678:Sex Distribution; D012959:Socioeconomic Factors