Zealand Census-Mortality Research Articles

Socio-economic inequalities in mortality for Asian people: New Zealand Census-Mortality Study, 1996–2004

This study examines the association of socio-economic factors with mortality for the Asian population, and compares with those of the European/Other group. Conversely, it examines differences in mortality rates between the European/Other and Asian groups by levels of these socio-economic factors. Asian and European/Other 25–74 year olds on census night 1996 and 2001 were followed up for 3 years by record linkage with mortality data. Socio-economic position was measured using household income, highest educational qualification and a measure of neighbourhood deprivation. Poisson regression modelling was used to estimate the effect socio-economic variables and ethnicity on mortality rates. Asians with no qualifications had mortality rates 72% higher than those Asians with post-school qualifications whereas the corresponding figure for European/Others was 29%. Asian people living in areas of high deprivation had mortality rates 56% higher than those living in areas of low deprivation, with a similar result for the European/Other group. However, while there was no income-mortality gradient among Asian people, there was a significant effect of household income for the European/Other group where mortality rates decreased by 6% for each unit increase in income decile. Consequently, the protective effect on mortality from being Asian compared to European/Other) is more marked at higher levels of education or lower levels of income. Education is an important determinant of mortality among Asian people, but not income, perhaps reflecting the importance of education as a predictor of health status following migration, and sacrifices in income that migrants are prepared to make.

New Zealand’s Integrated Data Infrastructure (IDI): Value to date and future opportunities

ABSTRACT
 ObjectivesStatistics New Zealand, the official statistics agency of the New Zealand (NZ) Government, has developed an Integrated Data Infrastructure (IDI). We aimed to review the value of the IDI to date from a research perspective and to consider the opportunities it provides.
 ApproachWe considered recent projects in which we have been involved: the New Zealand Census-Mortality and CancerTrends studies (NZCMS/CT), a Suicide Mortality Review Committee (SuMRC) feasibility trial, and a study on cardiovascular disease costs in NZ. We also considered IDI-related work published by other agencies and the views expressed at IDI meetings involving health and social sector personnel.
 ResultsSince 1993 in NZ, it has been possible to link all official health datasets using the National Health Index (NHI) number. However it was much more difficult to link health data with data from other sources. Studies often involved much ad hoc data linkage, with different versions of the same data being stored in multiple sites resulting in data integrity and security issues. The IDI provides one place to securely link the various data sources then make the anonymised data available for research for public good.
 The IDI provides the following advantages:
 
 Administrative data sources are available in one place nationally rather than many data silos.
 Health data can be linked with other administrative data eg, tax, education, crime, migration, welfare, housing, population census. 
 It facilitates collaboration between agencies and the sharing of code and associated documentation.
 Increased use of these data means there is more feedback to the source government agencies around data collection standards and data quality issues. 
 It allows for nationally-standardised processes for ensuring that only responsible and capable researchers with appropriate research questions have access to the relevant anonymised data.
 Perhaps the greatest long-term research potential is with the repeated measures data, allowing analyses with greater potential causal inference than previously available.
 All the above reduce the cost of doing research as well as assisting government departments with evaluation and costing studies.
 
 ConclusionsNZ is making good progress with integration of administrative data from the health and social sectors. The IDI is a valuable tool for advancing research that provides government departments and academic researchers with new insights into complex social issues such as crime and vulnerable children. It allows government to target limited resources to those areas where the greatest long-term benefit might be made.

O3-2.2 Linkage of census with mortality and cancer data in New Zealand. [part of symposium ref number 2353, "linkage of data in the study of ethnic inequalities ..."

<h3>Introduction</h3> Ethnicity is difficult to collect in a standard way between health and census datasets, meaning routinely calculated rates are prone to numerator-denominator bias. <h3>Methods</h3> Census and mortality data have been routinely linked in the New Zealand Census-Mortality Study, creating time series data from 1981. More recently, the Cancer trends study has linked cancer registrations. The proportion of eligible mortality / cancer records linked to a census record is now over 80%. Weighting is used to adjust for any linkage bias. <h3>Results</h3> Previously calculated mortality rates for Māori and Pacific people were shown to be underestimated by a quarter due to numerator-denominator bias. Corrected trends in mortality rates since 1981 demonstrate little if any improvement in Māori mortality rates during the 1980s–90s, concurrent with major reforms that impacted more on Māori than non-Māori (eg, unemployment rates among Māori reached 25% in 1992, compared with 7% among Europeans). Other analyses demonstrate that CVD is the major cause of death giving rise to ethnic inequalities in mortality, but as CVD rates fall for all ethnic groups inequalities in mortality are “relocating” to cancer. Inequalities in cancer incidence are less prominent than inequalities in cancer mortality, but nevertheless there are curious findings, such as: higher (and faster rising) breast cancer incidence among Māori, despite a more favourable risk factor profile; and particularly high endometrial and thyroid cancer incidence among Pacific women. There has also been a tremendous reduction in cervical cancer inequalities. <h3>Conclusion</h3> This linkage has allowed accurate research on trends that was hitherto impossible.

Do New Zealand's immigrants have a mortality advantage? Evidence from the New Zealand Census-Mortality Study

Objective. To examine all-cause mortality differentials among New Zealand's (NZ) immigrant population. Unlike other studies that use the total non-migrant population as the reference group, we use NZ-born populations of the same ethnic group for comparison purposes. Our study intends to answer two questions: first, do immigrants have a mortality advantage relative to their NZ-born counterparts of the same ethnicity? Second, does an immigrant mortality advantage, if one exists, decline as duration of residence increases? Design. Data from the New Zealand Census-Mortality Study from 1996–1999 and 2001–2004 were used. The main variable of interest, years of residence in NZ, was classified as living in NZ for less than 5, 5–9, 10–19, 20–34, 35 or more years, and born in NZ. Three main ethnic groups were examined, such as Asian, Pacific, and European/Other. Mortality rates for subgroups within these broad ethnic groups were not calculated. Negative binomial models controlled for socioeconomic and demographic factors to assess the independent effect of duration of residence on mortality. Results. European/Other and Asian immigrants have a mortality advantage relative to their NZ-born counterparts, which declines as length of residence increases. Within strata of duration of residence, there are few differences between European/Other and Asian mortality. Pacific immigrants showed no statistically significant mortality advantage relative to the NZ-born Pacific people, and had higher mortality rates than Europeans/Others or Asians regardless of duration in NZ. Conclusion. Findings from our study are consistent with international literature. Both the healthy migrant effect and acculturation may be responsible for the protective mortality effect among Asians and Europeans/Others that erodes over time. However, our results for the Pacific population suggest some migrant groups come to the host country with a health disadvantage and with no apparent healthy migrant effect.

Changing trends in indigenous inequalities in mortality: lessons from New Zealand.

We describe trends from 1951 to 2006 in inequalities in mortality between the indigenous (Māori) and non-indigenous (non-Māori, mainly European-descended) populations of New Zealand. We relate these trends to the historical context in which they occurred, including major structural adjustment of the economy from the mid 1980s to the mid 1990s, followed by a retreat from neoliberal social and economic policies from the late 1990s onwards. This was accompanied by economic recovery and the introduction of health reforms, including a reorientation of the health system towards primary health care. Abridged period lifetables for Māori and non-Māori from 1951 to 2006 were constructed using standard demographic methods. Absolute [standardized rate difference (SRD)] and relative [standardized rate ratio (SRR)] mortality inequalities for Māori compared with European/Other ethnic groups (aged 1-74 years) were measured using the New Zealand Census-Mortality Study (an ongoing data linkage study that links mortality to census records) from 1981-84 to 2001-04. The SRDs were decomposed into their contributions from major causes of death. Poisson regression modelling was used to estimate the extent of socio-economic mediation of the ethnic mortality inequality over time. Life expectancy gaps and relative inequalities in mortality rates (aged 1-74 years) widened and then narrowed again, in tandem with the trends in social inequalities (allowing for a short lag). Among females, the contribution of cardiovascular disease to absolute mortality inequalities steadily decreased, but was partly offset by an increasing contribution from cancer. Among males, the contribution of CVD increased from the early 1980s to the 1990s, then decreased again. The extent of socio-economic mediation of the ethnic mortality inequality peaked in 1991-94, again more notably among males. Our results are consistent with a causal association between changing economic inequalities and changing health inequalities between ethnic groups. However, causality cannot be established from a historical analysis alone. Three lessons nevertheless emerge from the New Zealand experience: the lag between changes in ethnic social inequality and ethnic health inequality may be short (<5 years); both changes in the distribution of the social determinants of health and an appropriate health system response may be required to address ethnic health inequalities; and timely monitoring of ethnic health inequalities, based on high-quality ethnicity data, may help to sustain political commitment to pro-equity health and social policies.

How much does health care contribute to health gain and to health inequality? Trends in amenable mortality in New Zealand 1981–2004

To estimate the contribution of health care to health gain, and to ethnic and socio-economic health inequalities, in New Zealand over the past quarter century. Amenable and all-cause mortality rates by ethnicity and equivalised household income tertile from 1981-84 to 2001-04 were estimated from linked census-mortality datasets (the New Zealand Census-Mortality Study). Amenable mortality (deaths under age 75 from conditions responsive to health care) was defined using a classification recently developed for use in Australia and New Zealand. The contribution of health care to the observed improvement in population health status was estimated by the ratio of the difference in amenable to the difference in all-cause mortality over the observation period. Trends in amenable causes of death were estimated to account for approximately one-third of the fall in mortality over the past quarter century, for the population as a whole and for all income and ethnic groups except Pacific peoples, for whom there was no reduction in amenable mortality. In 2001-04, amenable causes accounted for approximately one quarter of the mortality gap between all ethnic groups compared to the European/Other reference. Our finding provides one indicator of the social impact of health care over this period. More importantly, that Pacific peoples seem to have benefited less than other ethnic groups calls for urgent explanation. Also, our finding that amenable causes account for about one quarter of current mortality disparities, clearly indicates that improvement in access to and quality of health care for disadvantaged groups could substantively reduce health inequalities.

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

Ethnic variation in mortality and whether this variation can be explained by socioeconomic status are of substantive interest to social epidemiologists. The authors consider the analysis of mortality data for a mixture of majority and minority ethnic groups. Such data are likely to be coarsely cross-classified by age and socioeconomic status and yet, even then, in some cells of this cross-classification the observed mortality rate will be an imprecise estimate of the underlying rate. The authors illustrate conventional and Bayesian approaches to analysis with data from the 1996 census used by the New Zealand Census-Mortality Study. A conventional approach is exploratory data analysis first followed by Poisson regression. The authors use spline smoothing within a generalized additive model framework as an exploratory data analysis, following a strategy of adding just enough model structure to gain a sensible picture. A Bayesian approach is modeling first and then a description of posterior estimates using exploratory data analysis techniques. The authors use hierarchical Poisson regression and then illustrate their posterior estimates of the mortality rate using the same spline smoothing as before. The advantage of the hierarchical Bayesian approach is that it assesses uncertainty about a Poisson regression model proposed a priori; the conventional approach assumes that the fitted Poisson regression model is correct. All analyses use software that is available at no cost.

Income and mortality: the shape of the association and confounding New Zealand Census-Mortality Study, 1981-1999.

To determine the shape of the income-mortality association, before and after adjusting for confounding by other socioeconomic variables. Poisson regression analyses were conducted on 11.7 million years of follow-up of 25-59 year old New Zealand census respondents spanning four separate cohort studies (1981-1984, 1986-1989, 1991-1994, and 1996-1999). Mortality among low-income people was approximately two times that among high-income people. Adjustment for potential socioeconomic confounders (marital status, education, car access, and neighbourhood socioeconomic deprivation) halved the strength of the income-mortality association, but did not appreciably change the shape of the association. Further adjustment for labour force status largely removed the income-mortality association. The association of non-transformed income with mortality was non-linear, with a flattening out of the slope at higher incomes. Both the logarithm and rank of income appeared to have a better linear fit with the mortality rate, although the association of mortality with the logarithm of income flattened out notably at low incomes. Much, but not all, of the crude association of income with mortality could be due to confounding. Adjusting income-mortality associations for labour force status (also a proxy for health status) is problematic: on the one hand, it over-adjusts the association as poor health will be on the pathway from income to mortality; on the other hand, it appropriately adjusts for both confounding by labour force status and reverse causation whereby income changes as a result of poor health. Both logarithmic and rank transformations of income have a reasonable linear fit with income.

Anonymous linkage of New Zealand mortality and Census data

BackgroundThe New Zealand Census-Mortality Study (NZCMS) aims to investigate socio-economic mortality gradients in New Zealand, by anonymously linking Census and mortality records. ObjectivesTo describe the record linkage method, and to estimate the magnitude of bias in that linkage by demographic and socio-economic factors. MethodsAnonymous 1991 Census records, and mortality records for decedents aged 0-74 years on Census night and dying in the three-year period 1991-94, were probabilistically linked using Automatch®. Bias in the record linkage was determined by comparing the demographic and socio-economic profile of linked mortality records to unlinked mortality records. Results31,635 of 41,310 (76.6%) mortality records were linked to one of 3,373,896 Census records. The percentage of mortality records linked to a Census record was lowest for 20-24 year old decedents (49.0%) and highest for 65-69 year old decedents (81.0%). By ethnic group, 63.4%, 57.7%, and 78.6% of Maori, Pacific, and decedents of other ethnic groups, respectively, were linked. Controlling for demographic factors, decedents from the most deprived decile of small areas were 8% less likely to be linked than decedents from the least deprived decile, and male decedents from the lowest occupational class were 6% less likely to be linked than decedents from the highest occupational class. ConclusionThe proportion and accuracy of mortality records linked was satisfactorily high. Future estimates of the relative risk of mortality by socio-economic status will be modestly under-estimated by 5-10%.