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Biomedical subjects

Tony Blakely

Publications and source records attributed to Tony Blakely.

At least 19 recordsLinked to original sources
PubMed2006

Are socially disadvantaged neighbourhoods deprived of health-related community resources?

BACKGROUND: Recent work in a number of countries has identified growing geographical inequalities in health between deprived and non-deprived neighbourhoods. The health gaps observed cannot be entirely explained by differences in the characteristics of individuals living in those neighbourhoods, which has led to a concerted international public health research effort to determine what contextual features of neighbourhoods matter. This article reports on access to potentially health-promoting community resources across all neighbourhoods in New Zealand. Prevailing international opinion is that access to community resources is worse in deprived neighbourhoods. METHODS: Geographical Information Systems were used to calculate geographical access to 16 types of community resources (including recreational amenities, and shopping, educational and health facilities) in 38,350 small census areas across the country. The distribution of these access measures by neighbourhood socioeconomic deprivation was determined. RESULTS: For 15 out of 16 measures of community resources, access was clearly better in more deprived neighbourhoods. For example, the travel time to large supermarkets was approximately 80% greater in the least deprived quintile of neighbourhoods compared with the most deprived quintile. CONCLUSIONS: These results challenge the widely held, but largely untested, view that areas of high social disadvantage have poorer access to community resources. Poor locational access to community resources among deprived neighbourhoods in New Zealand does not appear to be an explanation of poorer health in these neighbourhoods. If anything, a pro-equity distribution of community resources may be preventing even wider disparities in neighbourhood inequalities in health.

Community Networks↗
PubMed2006

Mortality among lifelong nonsmokers exposed to secondhand smoke at home: cohort data and sensitivity analyses.

Evidence is growing that secondhand smoke can cause death from several diseases. The association between household exposure to secondhand smoke and disease-specific mortality was examined in two New Zealand cohorts of lifelong nonsmokers ("never smokers") aged 45-77 years. Individual census records from 1981 and 1996 were anonymously and probabilistically linked with mortality records from the 3 years that followed each census. Age- and ethnicity-standardized mortality rates were compared for never smokers with and without home exposure to secondhand smoke (based on the reported smoking behavior of other household members). Relative risk estimates adjusted for age, ethnicity, marital status, and socioeconomic position showed a significantly greater mortality risk for never smokers living in households with smokers, with excess mortality attributed to tobacco-related diseases, particularly ischemic heart disease and cerebrovascular disease, but not lung cancer. Adjusted relative risk estimates for all cardiovascular diseases were 1.19 (95% confidence interval: 1.04, 1.38) for men and 1.01 (95% confidence interval: 0.88, 1.16) for women from the 1981-1984 cohort, and 1.25 (95% confidence interval: 1.06, 1.47) for men and 1.35 (95% confidence interval: 1.11, 1.64) for women from the 1996-1999 cohort. Passive smokers also had nonsignificantly increased mortality from respiratory disease. Sensitivity analyses indicate that these findings are not due to misclassification bias.

Aged↗
PubMed2006

What potential has tobacco control for reducing health inequalities? The New Zealand situation.

In this Commentary, we aim to synthesize recent epidemiological data on tobacco and health inequalities for New Zealand and present it in new ways. We also aim to describe both existing and potential tobacco control responses for addressing these inequalities. In New Zealand smoking prevalence is higher amongst Māori and Pacific peoples (compared to those of "New Zealand European" ethnicity) and amongst those with low socioeconomic position (SEP). Consequently the smoking-related mortality burden is higher among these populations. Regarding the gap in mortality between low and high socioeconomic groups, 21% and 11% of this gap for men and women was estimated to be due to smoking in 1996-99. Regarding the gap in mortality between Māori and non-Māori/non-Pacific, 5% and 8% of this gap for men and women was estimated to be due to smoking. The estimates from both these studies are probably moderate underestimates due to misclassification bias of smoking status. Despite the modest relative contribution of smoking to these gaps, the absolute number of smoking-attributable deaths is sizable and amenable to policy and health sector responses. There is some evidence, from New Zealand and elsewhere, for interventions that reduce smoking by low-income populations and indigenous peoples. These include tobacco taxation, thematically appropriate mass media campaigns, and appropriate smoking cessation support services. But there are as yet untried interventions with major potential. A key one is for a tighter regulatory framework that could rapidly shift the nicotine market towards pharmaceutical-grade nicotine (or smokeless tobacco products) and away from smoked tobacco.

Journal Article↗
PubMed2006

What is the contribution of smoking and socioeconomic position to ethnic inequalities in mortality in New Zealand?

BACKGROUND: Mortality rates for Māori are twice those for non-Māori in New Zealand. We have assessed the contribution of tobacco smoking and socioeconomic position to these inequalities in 45-74-year-old census respondents during 1981-84 and 1996-99 (2.3 and 2.7 million person-years, respectively). METHODS: We used linked census and mortality cohort datasets with measures of socioeconomic position (household income, highest educational qualification, car access, labour-force status, and neighbourhood deprivation) and smoking (never, ex, current). We used direct standardisation to adjust for smoking and Poisson regression to adjust for socioeconomic position. FINDINGS: The apparent contribution of smoking to mortality differences between Māori and non-Māori non-Pacific people was greatest for women in 1996-99 (8% reduction in standardised rate difference); it had increased from 3% in 1981-84. The corresponding reductions in men were 5% in 1996-99 and -1% in 1981-84. The apparent contribution of socioeconomic factors to mortality differences between Māori and non-Māori non-Pacific was greatest for men (39% in 1981-84 and 37% in 1996-99) and increased over time for women (from 23% in 1981-84 to 32% in 1996-99). INTERPRETATION: Although small, the contribution of smoking to ethnic inequalities in mortality increased over time and might grow more during the next two decades if differences in smoking between ethnic groups continue to increase. Better measurement of socioeconomic position (eg, lifecourse measures, asset wealth) might increase the proportion of ethnic inequalities attributable to socioeconomic position, perhaps to about half. Action to redress socioeconomic gaps and control of tobacco use will both be important in reducing ethnic inequalities in health.

Aged↗
PubMed2006

Trends in absolute socioeconomic inequalities in mortality in Sweden and New Zealand. A 20-year gender perspective.

BACKGROUND: Both trends in socioeconomic inequalities in mortality, and cross-country comparisons, may give more information about the causes of health inequalities. We analysed trends in socioeconomic differentials by mortality from early 1980s to late 1990s, comparing Sweden with New Zealand. METHODS: The New Zealand Census Mortality Study (NZCMS) consisting of over 2 million individuals and the Swedish Survey of Living Conditions (ULF) comprising over 100, 000 individuals were used for analyses. Education and household income were used as measures of socioeconomic position (SEP). The slope index of inequality (SII) was calculated to estimate absolute inequalities in mortality. Analyses were based on 3-5 year follow-up and limited to individuals aged 25-77 years. Age standardised mortality rates were calculated using the European population standard. RESULTS: Absolute inequalities in mortality on average over the 1980s and 1990s for both men and women by education were similar in Sweden and New Zealand, but by income were greater in Sweden. Comparing trends in absolute inequalities over the 1980s and 1990s, men's absolute inequalities by education decreased by 66% in Sweden and by 17% in New Zealand (p for trend <0.01 in both countries). Women's absolute inequalities by education decreased by 19% in Sweden (p = 0.03) and by 8% in New Zealand (p = 0.53). Men's absolute inequalities by income decreased by 51% in Sweden (p for trend = 0.06), but increased by 16% in New Zealand (p = 0.13). Women's absolute inequalities by income increased in both countries: 12% in Sweden (p = 0.03) and 21% in New Zealand (p = 0.04). CONCLUSION: Trends in socioeconomic inequalities in mortality were clearly most favourable for men in Sweden. Trends also seemed to be more favourable for men than women in New Zealand. Assuming the trends in male inequalities in Sweden were not a statistical chance finding, it is not clear what the substantive reason(s) was for the pronounced decrease. Further gender comparisons are required.

Adult↗
PubMed2006

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.

Age Factors↗
PubMed2006

Patterns of disparity: ethnic and socio-economic trends in breast cancer mortality in New Zealand.

OBJECTIVE: To test whether trends in breast cancer mortality varied by ethnicity and socio-economic position during the 1980s and '90s in New Zealand. METHODS: Four cohorts of the entire New Zealand population for 1981-84; 86-89; 91-94 and 96-99 allowed direct determination of socio-economic trends in breast cancer mortality. For ethnicity, unlinked routine census and mortality data were used with adjustment factors for undercounting of Māori and Pacific deaths. RESULTS: Māori and non-Māori non-Pacific mortality rates changed little until mid-1990s with Māori experiencing 25% higher mortality. In 1996-99, Māori rates increased notably to become 68% higher than non-Māori non-Pacific (SRR 1.68; 95% CI: 1.49-1.90). Pacific women experienced an approximate three-fold increase in breast cancer mortality over time. There appeared to be reducing mortality among higher income and education groups but trends within socio-economic groups were not statistically significant. Nevertheless, by 1996-99, there was a significant 22% excess mortality (SRR 1.22; 95% CI: 1.01-1.49) for low compared with high-income groups. CONCLUSIONS: Widening ethnic, and probably, socio-economic disparities in breast cancer mortality are likely due to both underlying incidence and differential survival trends. Disparities are likely to increase once the full differential mortality benefits of screening impact on the population.

Adolescent↗
PubMed2006

No association of neighbourhood volunteerism with mortality in New Zealand: a national multilevel cohort study.

BACKGROUND: The association of social capital with health and mortality is contentious, and empirical findings are inconsistent. This study tests the association of neighbourhood-level volunteerism with mortality. METHODS: Cohort study of 1996 New Zealand census respondents aged 25-74 years (4.75 million person years) using multilevel Poisson regression analyses. Neighbourhood (average population 2,034) measures included indices of social capital (volunteering activities for all census respondents) and deprivation. RESULTS: Adjusting for just age and marital status, the mortality rate ratios for people living in the quintile of neighbourhoods with the lowest compared with highest volunteerism were 1.16 (95% confidence interval 1.08-1.24) and 1.09 (1.01-1.18), for males and females, respectively. Adjusting for potential individual-level and neighbourhood-level socioeconomic confounders reduced the rate ratios to 0.94 (0.88-1.01) and 0.92 (0.85-1.01), respectively. There was no significant association with any cause of death, including suicide [rate ratios 0.89 (0.64-1.22) and 0.57 (0.31-1.05), respectively]. Restricting the analyses to only those census respondents living at their census night address for five or more years, and therefore 'exposed' to that level of volunteerism for a longer period, did not substantially alter findings. CONCLUSIONS: This study, one of the largest multilevel studies yet, found no statistically significant independent association of a structural measure of neighbourhood social capital with mortality-including suicide. Assuming social features of neighbourhoods are important determinants of health, future research should examine other features (e.g. social fragmentation) and other outcomes (e.g. behaviour).

Adult↗
PubMed2006

Trends in colorectal cancer mortality by ethnicity and socio-economic position in New Zealand, 1981-99: one country, many stories.

BACKGROUND: Ethnicity and socio-economic position are important determinants of colorectal cancer (CRC) mortality. In this paper, we determine trends in colorectal cancer mortality by ethnicity and socio-economic position in New Zealand. METHODS: Cohort studies of the entire New Zealand population for 1981-84, 1986-89, 1991-94 and 1996-99 (linking Census and mortality datasets) allowed direct determination of trends in CRC mortality by income and education. For ethnicity, we used routine unlinked Census and mortality data, but with correction factors applied for undercounting of Mâori and Pacific deaths. RESULTS: ETHNICITY: CRC mortality trends varied markedly. There were small (10-20%) decreases among non-Mâori non-Pacific people, a 50% increase among Mâori, and up to 10-fold increase among Pacific people. By 1996-99, all three ethnic groups had similar CRC mortality. SOCIO-ECONOMIC POSITION: For females, differences in CRC mortality by education and income increased over time e.g. poor females had a 40% higher CRC mortality than rich females in 1996-99, compared with no difference in 1981-84 (p for trend 0.04). In men, increases in inequality were seen by income but not education. CONCLUSION: The observed ethnic trends probably reflect differential trends in exposure to etiological risk factors. Social inequalities in colorectal cancer mortality appear to be increasing.

Adult↗
PubMed2005

The contribution of causes of death to socioeconomic inequalities in child mortality: New Zealand 1981-1999.

BACKGROUND: Socioeconomic inequalities in all-cause child mortality exist in New Zealand; however the inequalities in cause-specific mortality have not been examined. This study examines child mortality inequality by household income between 1981 and 1999, by cause of death. METHODS: Data was used from a record linkage study of census and mortality records of all New Zealand children aged 0-14 years on census night 1981, 1986, 1991, 1996 followed up for 3 years for specific causes of mortality between ages 1-14 years. All cohorts were combined to calculate mortality rates, rate ratios, and rates differences for each cause of death. RESULTS: Socioeconomic differences in child mortality (low income compared to high income) were observed for injury (non road traffic) (RR 1.87, 1.35 to 2.58), road traffic injury (RR 1.36, 1.01 to 1.82), and 'other' causes of death (RR 1.81, 1.32 to 2.47). 'Other' and non-road traffic injury deaths together contributed 70% of the total gap in child mortality between the rich and the poor. CONCLUSIONS: Socioeconomic differences existed across most broad causes of child death. The major contributors to mortality inequality are diverse, suggesting that the similar distal causes of inequality (e.g. poverty) play out through a myriad of proximal causes. Fortunately there appears to be some scope for policymakers to modify some of the proximal and distal causes of these inequalities.

Accidents, Traffic↗
PubMed2005

Shifting dollars, saving lives: what might happen to mortality rates, and socio-economic inequalities in mortality rates, if income was redistributed?

Personal or household income predicts mortality risk, with each additional dollar of income conferring a slightly smaller decrease in the mortality risk. Regardless of whether levels of income inequality in a society impact on mortality rates over and above this individual-level association (i.e., the 'income inequality hypothesis'), the current consensus is that narrowing income distributions will probably improve overall health status and reduce socio-economic inequalities in health. Our objective was to quantify this impact in a national population using 1.3 million 25-59-year-old respondents to the New Zealand 1996 census followed-up for mortality over 3 years. We modelled 10-40% shifts of everyone's income to the mean income (equivalent to 10-40% reductions in the Gini coefficient). The strength of the income-mortality association was modelled using rate ratios from Poisson regression of mortality on the logarithm of equivalised household income, adjusted for confounders of age, marital status, education, car access, and neighbourhood socio-economic deprivation. Overall mortality reduced by 4-13% following 10-40% shifts in everyone's income, respectively. Inequalities in mortality reduced by 12-38% following 10-40% shifts in everyone's income. Sensitivity analyses suggested that halving the strength of the income-mortality association (i.e., assuming our multivariable estimate still overestimated the causal income-mortality association) would result in 2-6% reductions in overall mortality and 6-19% reductions in inequalities in mortality in this New Zealand setting. Many commentators have noted the non-linear association of income with mortality predicts that narrowing the income distribution will both reduce overall mortality rates and reduce inequalities in mortality. Quantifying such reductions can only be done with considerable uncertainty. Nevertheless, we tentatively suggest that the gains in overall mortality will be modest (although still potentially worthwhile from a policy perspective) and the reductions in inequalities in mortality will be more substantial.

Adult↗
PubMed2005

The contribution of smoking to inequalities in mortality by education varies over time and by sex: two national cohort studies, 1981-84 and 1996-99.

BACKGROUND: The contributions of tobacco smoking to overall mortality and socioeconomic inequalities in mortality vary between populations and over time. We determined how these contributions varied by sex and over time in two national New Zealand cohort studies. METHODS: Poisson regression and modelling were conducted on linked census-mortality cohorts for people aged 45-74 years in 1981-84 and 1996-99 (2.0 and 2.7 million person-years, respectively). RESULTS: Contribution to socioeconomic inequalities in mortality. Adjusting for current and former smoking reduced the all-cause mortality rate ratios for men with nil educational qualifications compared with men with post-school qualifications from 1.34 to 1.29 in 1981-84 and from 1.31 to 1.25 in 1996-99, or 16 and 21% reductions in relative inequalities. Equivalent results for women were 1.42-1.41 in 1981-84 and 1.42-1.37 in 1996-99, or 3 and 11% reductions in relative inequalities. Contribution to overall mortality. Using 1996-99 data, we estimated that if all current smokers quit and became ex-smokers, mortality rates would reduce by 11% for men and 5% for women. If everyone was a never smoker (i.e. a historically smoke-free society), mortality rates would have been 26% lower for men and 25% lower for women. CONCLUSIONS: The contribution of smoking to educational inequalities in mortality was greater for males, and increased over time for both males and females, reflecting the historically differential phasing of the tobacco epidemic by sex and socioeconomic position. Complete cessation of smoking in contemporary New Zealand would reduce both overall mortality and educational inequalities in mortality.

Aged↗
PubMed2005

The smoking-mortality association varies over time and by ethnicity in New Zealand.

BACKGROUND: The strength of the smoking-mortality association may vary over time and by ethnic group. METHODS: Cohort studies of 1.6 million (1981-84) and 1.9 million (1996-99) New Zealanders aged 25-74 years were formed by the linkage of census and mortality data. Comparing current smokers with never smokers, standardized rate ratios (RRs) and rate differences (RDs) were calculated for all-cause and ischaemic heart disease (IHD) mortality. RESULTS: Between 1981-84 and 1996-99 the all-cause mortality RR increased from 1.59 (95% CI 1.53-1.66) to 2.05 (1.97-2.14) for men and from 1.49 (1.42-1.56) to 2.01 (1.91-2.12) for women. All-cause RRs were significantly greater among non-Ma-ori non-Pacific than Ma-ori: 2.22 (2.12-2.33) compared with 1.51 (1.35-1.69) in men and 2.20 (2.09-2.33) compared with 1.45 in women (1.27-1.66), respectively, in 1996-99. This RR heterogeneity remained after adjusting for socio-economic factors and was similar for IHD. The RDs demonstrated less heterogeneity. For example, in 1996-99 the RDs were 627 per 100,000 (452-802) for Ma-ori compared with 464 (427-502) for non-Ma-ori non-Pacific among men, and 368 (228-509) compared with 340 (311-370) among women. CONCLUSIONS: In New Zealand the relative effect of smoking on mortality differs over time and by ethnicity. We expect that such heterogeneity exists in other countries where the background mortality rates vary over time or between social groups. Information on this heterogeneity, including ethnicity-specific data, is needed to accurately determine the mortality burden owing to tobacco. The size of the RR estimates should be interpreted in the context of absolute mortality and effect measures.

Adult↗
PubMed2005

Varying evolution of the New Zealand lung cancer epidemic by ethnicity and socioeconomic position (1981-1999).

AIM: Tobacco use and resultant health effects have been described as an epidemic that progresses through the population. This paper aims to describe and explain trends in lung cancer mortality by ethnicity and socioeconomic position in New Zealand between 1981-1999. METHODS: Cohort studies of the entire New Zealand population for 1981-84, 1986-89, 1991-94, and 1996-99 (linking census and mortality datasets) allowed direct determination of trends in lung mortality by income and education. For ethnicity, we used unlinked census and mortality data--but with correction factors applied for undercounting of Maori and Pacific deaths. RESULTS: Lung cancer mortality decreased in males and increased in females over the time period studied. In males, socioeconomic inequality persisted despite a decline in mortality in all socioeconomic groups. In females, a disproportionate increase in the mortality of lower socioeconomic groups compared to higher socioeconomic groups resulted in an increase in inequality. Divergent trends by ethnic group resulted in an increase in ethnic inequalities between 1981 and 1996 in both males and females. CONCLUSIONS: There are significant and growing ethnic and socioeconomic inequalities in lung cancer mortality in New Zealand. In the current absence of concerted public health action these inequalities will probably widen in future decades.

Adult↗
PubMed2005

The global distribution of risk factors by poverty level.

OBJECTIVE: To estimate the individual-level association of income poverty with being underweight, using tobacco, drinking alcohol, having access only to unsafe water and sanitation, being exposed to indoor air pollution and being obese. METHODS: Using survey data for as many countries as possible, we estimated the relative risk association between income or assets and risk factors at the individual level within 11 medium- and low-income subregions of WHO. WHO and The World Bank data on the prevalence of risk factors and income poverty (defined as living on < US$ 1.00 per day, US$ 1-2.00 per day and > US$ 2.00 per day) were analysed to impute the association between poverty and risk factors for each subregion. The possible effect of poverty reduction on the prevalence of risk factors was estimated using population-attributable risk percentages. FINDINGS: There were strong associations between poverty and malnutrition among children, having access only to unsafe water and sanitation, and being exposed to indoor air pollution within each subregion (relative risks were twofold to threefold greater for those living on < US$ 1.00 per day compared with those living on > US$ 2.00 per day). Associations between poverty and obesity, tobacco use and alcohol use varied across subregions. If everyone living on < US$ 2.00 per day had the risk factor profile of those living on > US$ 2.00 per day, 51% of exposures to unimproved water and sanitation could be avoided as could 37% of malnutrition among children and 38% of exposure to indoor air pollution. The more realistic, but still challenging, Millennium Development Goal of halving the number of people living on < US$ 1.00 per day would achieve much smaller reductions. CONCLUSION: To achieve large gains in global health requires both poverty eradication and public health action. The methods used in this study may be useful for monitoring pro-equity progress towards Millennium Development Goals.

Health Services Accessibility↗
PubMed2005

Bias measuring mortality gradients by occupational class in New Zealand.

BACKGROUND: Socioeconomic differences in mortality in New Zealand have traditionally been measured using occupational class from mortality data (based on usual or last occupation) as the numerator, and class from census data (current occupation on census night) as the denominator. Such analyses are prone to numerator-denominator bias. Record linkage of census and mortality data in the New Zealand Census-Mortality Study (NZCMS) allows analyses of 'linked' data that will avoid numerator-denominator bias, but may be prone to other biases. OBJECTIVES: To determine differences in the assignment of occupational class between census and mortality data; to investigate biases in the observed association of class with mortality using linked census-mortality data; and to compare the class-mortality association using unlinked versus linked census-mortality data. METHODS: Census records for males aged 25-64 years on census night 1991 were anonymously and probabilistically linked to 5,844 out of 8,145 eligible deaths occurring in the second and third years following census night. RESULTS: (by objective) Only 47% of linked deaths had an occupation recorded on census data, compared to 84% on mortality data - a census to mortality ratio of 0.56. Relatively fewer deaths were identified as class 4 on census data (census to mortality ratio of 0.45) compared to other classes (ratios 0.55 to 0.64). Linkage bias: A lower likelihood of 25-44 year old deaths (but not 45-64 year olds) from lower socioeconomic classes being successfully linked to a census record meant that analyses using linked census-mortality data underestimated the class-mortality association. Bias due to exclusion of economically inactive: Analyses on linked-census data (using current occupational class) considerably underestimated the estimated association of usual occupational class with mortality. The strength of the association of class with mortality according to linked census-mortality data (and adjusted for the above two biases) and unlinked data were roughly comparable. CONCLUSION: Differences in the recording of occupational class on census and mortality data in New Zealand mean measuring mortality differences by class is thwart with difficulty. If one assumes that biases for any particular method of analysis are similar over time, or one carefully adjusts where possible for bias, using occupational class to monitor trends in socioeconomic mortality gradients may be valid.

Adult↗