Incidence of cardiovascular risk factors by education level 2000-2005 : the Australian diabetes, obesity and lifestyle (AusDiab) cohort study

Lower socioeconomic status (SES) is associated with a higher prevalence of major risk factors for cardiovascular disease (CVD). However, few longitudinal studies have examined the association between SES and CVD risk factors over time. We aimed to determine whether SES, using education as a proxy, is associated with the onset of CVD risk factors over 5 years in an Australian adult cohort study.

Participants in the Australian Diabetes, Obesity and Lifestyle study (AusDiab) study aged 25 years and over who attended both baseline and 5-year follow-up examinations (n=5 967) were categorised according to educational attainment. Cardiovascular risk factor data at both time points were ascertained through questionnaire and physical measurement.

Women with lower education had a greater risk of progressing from normal weight to overweight or obesity than those with higher education (age-adjusted OR 1.57, 95% CI 1.06-2.31). Both men and women with lower education were more likely to develop diabetes (age-adjusted OR from higher education 1.75, 95% CI 1.14-2.71 and 3.01, 95% CI 1.26-7.20, respectively). A lower level of education was associated with a greater number of risk factors accumulated over time in women (OR of progressing from having two or less risk factors at baseline to three or more at follow up, 2.04, 95% 1.32-3.14).

In this Australian population-based study, lower educational attainment was associated with an increased risk of developing both individual and total CVD risk factors over a 5-year period. These findings suggest that SES inequalities in CVD will persist into the future.

Validation of de-identified record linkage to ascertain hospital admissions in a cohort study

Background Cohort studies can provide valuable evidence of cause and effect relationships but are subject to loss of participants over time, limiting the validity of findings. Computerised record linkage offers a passive and ongoing method of obtaining health outcomes from existing routinely collected data sources. However, the quality of record linkage is reliant upon the availability and accuracy of common identifying variables. We sought to develop and validate a method for linking a cohort study to a state-wide hospital admissions dataset with limited availability of unique identifying variables.

Methods A sample of 2000 participants from a cohort study (n = 41 514) was linked to a state-wide hospitalisations dataset in Victoria, Australia using the national health insurance (Medicare) number and demographic data as identifying variables. Availability of the health insurance number was limited in both datasets; therefore linkage was undertaken both with and without use of this number and agreement tested between both algorithms. Sensitivity was calculated for a sub-sample of 101 participants with a hospital admission confirmed by medical record review.

Results Of the 2000 study participants, 85% were found to have a record in the hospitalisations dataset when the national health insurance number and sex were used as linkage variables and 92% when demographic details only were used. When agreement between the two methods was tested the disagreement fraction was 9%, mainly due to "false positive" links when demographic details only were used. A final algorithm that used multiple combinations of identifying variables resulted in a match proportion of 87%. Sensitivity of this final linkage was 95%.

Conclusions High quality record linkage of cohort data with a hospitalisations dataset that has limited identifiers can be achieved using combinations of a national health insurance number and demographic data as identifying variables.

Best practice for prevention and treatment of cardiovascular disease through an equity lens : a review

Background Despite declining rates of cardiovascular disease (CVD) mortality in developed countries, lower socioeconomic groups continue to experience a greater burden of the disease. There are now many evidence-based treatments and prevention strategies for the management of CVD and it is essential that their impact on the more disadvantaged group is understood if socioeconomic inequalities in CVD are to be reduced.

Aims To determine whether key interventions for CVD prevention and treatment are effective among lower socioeconomic groups, to describe barriers to their effectiveness and the potential or actual impact of these interventions on the socioeconomic gradient in CVD.

Methods Interventions were selected from four stages of the CVD continuum. These included smoking reduction strategies, absolute risk assessment, cardiac rehabilitation, secondary prevention medications, and heart failure self-management programmes. Electronic searches were conducted using terms for each intervention combined with terms for socioeconomic status (SES).

Results Only limited evidence was found for the effectiveness of the selected interventions among lower SES groups and there was little exploration of socioeconomic-related barriers to their uptake. Some broad themes and key messages were identified. In the majority of findings examined, it was clear that the underlying material, social and environmental factors associated with disadvantage are a significant barrier to the effectiveness of interventions.

Conclusion Opportunities to reduce socioeconomic inequalities occur at all stages of the CVD continuum. Despite this, current treatment and prevention strategies may be contributing to the widening socioeconomic-CVD gradient. Further research into the impact of best-practice interventions for CVD upon lower SES groups is required.

Inequalities in cardiovascular disease mortality : the role of behavioural, physiological and social risk factors

Background While the relationship between socio-economic disadvantage and cardiovascular disease (CVD) is well established, the role that traditional cardiovascular risk factors play in this association remains unclear. The authors examined the association between education attainment and CVD mortality and the extent to which behavioural, social and physiological factors explained this relationship.

Methods Adults (n=38 355) aged 40–69 years living in Melbourne, Australia were recruited in 1990–1994. Subjects with baseline CVD risk factor data ascertained through questionnaire and physical measurement were followed for an average of 9.4 years with CVD deaths verified by review of medical records and autopsy reports.

Results CVD mortality was higher for those with primary education only, compared with those who had completed tertiary education, with an HR of 1.66 (95% CI 1.10 to 2.49) after adjustment for age, country of birth and gender. Those from the lowest educated group had a more adverse cardiovascular risk factor profile compared with the highest educated group, and adjustment for these risk factors reduced the HR to 1.18 (95% CI 0.78 to 1.77). In analysis of individual risk factors, smoking and waist circumference explained most of the difference in CVD mortality between the highest and lowest education groups.

Conclusions Most of the excess CVD mortality in lower socio-economic groups can be explained by known risk factors, particularly smoking and overweight. While targeting cardiovascular risk factors should not divert efforts from addressing the underlying determinants of health inequalities, it is essential that known risk factors are addressed effectively among lower socio-economic groups.

Neighborhood disadvantage, individual-level socioeconomic position, and self-reported chronic arthritis : a cross-sectional multilevel study

Objective To examine the association between individual- and neighborhood-level disadvantage and self-reported arthritis.

Methods We used data from a population-based cross-sectional study conducted in 2007 among 10,757 men and women ages 40–65 years, selected from 200 neighborhoods in Brisbane, Queensland, Australia using a stratified 2-stage cluster design. Data were collected using a mail survey (68.5% response). Neighborhood disadvantage was measured using a census-based composite index, and individual disadvantage was measured using self-reported education, household income, and occupation. Arthritis was indicated by self-report. Data were analyzed using multilevel modeling.

Results The overall rate of self-reported arthritis was 23% (95% confidence interval [95% CI] 22–24). After adjustment for sociodemographic factors, arthritis prevalence was greatest for women (odds ratio [OR] 1.5, 95% CI 1.4–1.7) and in those ages 60–65 years (OR 4.4, 95% CI 3.7–5.2), those with a diploma/associate diploma (OR 1.3, 95% CI 1.1–1.6), those who were permanently unable to work (OR 4.0, 95% CI 3.1–5.3), and those with a household income <$25,999 (OR 2.1, 95% CI 1.7–2.6). Independent of individual-level factors, residents of the most disadvantaged neighborhoods were 42% (OR 1.4, 95% CI 1.2–1.7) more likely than those in the least disadvantaged neighborhoods to self-report arthritis. Cross-level interactions between neighborhood disadvantage and education, occupation, and household income were not significant.

Conclusion Arthritis prevalence is greater in more socially disadvantaged neighborhoods. These are the first multilevel data to examine the relationship between individual- and neighborhood-level disadvantage upon arthritis and have important implications for policy, health promotion, and other intervention strategies designed to reduce the rates of arthritis, indicating that intervention efforts may need to focus on both people and places.

Workplace stress: what is the role of positive mental health?

To examine whether positive mental health (PMH)-a positively focused well-being construct-moderates the job stress-distress relationship.

A framework for evaluating the impact of obesity prevention strategies on socioeconomic inequalities in weight.

We developed a theoretical framework to organize obesity prevention interventions by their likely impact on the socioeconomic gradient of weight. The degree to which an intervention involves individual agency versus structural change influences socioeconomic inequalities in weight. Agentic interventions, such as standalone social marketing, increase socioeconomic inequalities. Structural interventions, such as food procurement policies and restrictions on unhealthy foods in schools, show equal or greater benefit for lower socioeconomic groups. Many obesity prevention interventions belong to the agento-structural types of interventions, and account for the environment in which health behaviors occur, but they require a level of individual agency for behavioral change, including workplace design to encourage exercise and fiscal regulation of unhealthy foods or beverages. Obesity prevention interventions differ in their effectiveness across socioeconomic groups. Limiting further increases in socioeconomic inequalities in obesity requires implementation of structural interventions. Further empirical evaluation, especially of agento-structural type interventions, remains crucial.