Modeling the relation between socioeconomic status and mortality in a mixture of majority and minority ethnic groups

Does mortality vary between Asian subgroups in New Zealand: an application of hierarchical Bayesian modelling

The aim of this paper was to see whether all-cause and cause-specific mortality rates vary between Asian ethnic subgroups, and whether overseas born Asian subgroup mortality rate ratios varied by nativity and duration of residence. We used hierarchical Bayesian methods to allow for sparse data in the analysis of linked census-mortality data for 25-75 year old New Zealanders. We found directly standardised posterior all-cause and cardiovascular mortality rates were highest for the Indian ethnic group, significantly so when compared with those of Chinese ethnicity. In contrast, cancer mortality rates were lowest for ethnic Indians. Asian overseas born subgroups have about 70% of the mortality rate of their New Zealand born Asian counterparts, a result that showed little variation by Asian subgroup or cause of death. Within the overseas born population, all-cause mortality rates for migrants living 0-9 years in New Zealand were about 60% of the mortality rate of those living more than 25 years in New Zealand regardless of ethnicity. The corresponding figure for cardiovascular mortality rates was 50%. However, while Chinese cancer mortality rates increased with duration of residence, Indian and Other Asian cancer mortality rates did not. Future research on the mechanisms of worsening of health with increased time spent in the host country is required to improve the understanding of the process, and would assist the policy-makers and health planners.

Migration and Pacific mortality: estimating migration effects on Pacific mortality rates using Bayesian models

Pacific people living in New Zealand have higher mortality rates than New Zealand residents of European/Other ethnicity. The aim of this paper is to see whether Pacific mortality rates vary by natality and duration of residence. We used linked census-mortality information for 25- to 74-year-olds in the 2001 census followed for up to three years. Hierarchical Bayesian modeling provided a means of handling sparse data. Posterior mortality rates were directly age-standardized. We found little evidence of mortality differences between the overseas-born and the New Zealand-born for all-cause, cancer, and cardiovascular disease (CVD) mortality. However, we found evidence for lower all-cause (and possibly cancer and CVD) mortality rates for Pacific migrants resident in New Zealand for less than 25 years relative to those resident for more than 25 years. This result may arise from a combination of processes operating over time, including health selection effects from variations in New Zealand's immigration policy, the location of Pacific migrants within the social, political, and cultural environment of the host community, and health impacts of the host culture. We could not determine the relative importance of these processes, but identifying the (modifiable) drivers of the inferred long-term decline in health of the overseas-born Pacific population relative to more-recent Pacific migrants is important to Pacific communities and from a national health and policy perspective.

Do ethnic and socio-economic inequalities in mortality vary by region in New Zealand? An application of hierarchical Bayesian modelling

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.