Mortality disparities between geographic regions : results from a risk percentiles model for coronary heart disease

Background: Planning of disease prevention strategies requires information regarding the distribution of absolute risk in the population to allow targeting of people at high disease risk. It is well known that death rates from coronary heart disease (CHD) are higher in remote areas of Australia compared with major cities. Less well understood is the distribution of the absolute risk of CHD death within the different geographic regions. We present a mathematical model of CHD which projects the lifetime risk of death among individuals in different percentiles of CHD risk. We apply this to model the distribution of CHD risk within different geographic regions.

Methods: Using information from the Framingham1, MRFIT2 and AusDiab3 studies, the Australian population was divided into percentiles of CHD risk within age and gender groups by geographic location. Absolute mortality risk was determined at each percentile using current Australian mortality data. Survival curves were generated for each percentile using these risk estimates. Approximate confidence intervals were derived using bootstrap methods.

Conclusions: The difference in life expectancy at age 25 between those in the lowest decile of CHD risk compared to the highest was 5.8 years (95%CI:4.7,6.7) in major cities compared to 8.5 years (95%CI:7.6,9.7) in remote areas. The difference in risk of premature death (before age 75) was 12% (95%CI:10%,14%) in major cities compared to 33% (95%CI:28%,38%) in remote areas.

Explaining educational disparities in adiposity: The role of neighborhood environments.

To examine the extent to which characteristics of the neighborhood built environment explain the association between adiposity and educational qualifications in Australian women.

Socio-economic disparities in Australian adolescents' eating behaviours

Objective: To assess the association between socio-economic position (SEP) and poor eating behaviours in a large representative sample of Australian secondary school students.
Design: Cross-sectional survey of students’ vegetable, fruit, sugar-sweetened beverage and fast-food consumption assessed using validated instruments and collected via a web-based self-report format.
Setting: Secondary schools across all Australian states and territories.
Subjects: Secondary-school students (n 12 188; response rate: 54 %) aged 12–17 years participating in the 2009–10 National Secondary Students’ Diet and Activity (NaSSDA) survey.
Results: Overall, 25% of students reported consuming <1 serving of vegetables/d and 29% reported eating <1 serving of fruit/d. Fourteen per cent of students reported drinking at least 1–2 cups of sugar-sweetened beverages/d while 9% reported eating fast food <3 times/week. After adjusting for other demographic factors, students of lower-SEP areas were more likely to report low intake of vegetables (F (4, 231) = 3.61, P = 0.007) and high frequency of consumption of sugar-sweetened beverages (F (4, 231) =8.41, P < 0.001) and fast food (F (4, 231) = 4.59, P =0.001) compared with students of high-SEP neighbourhoods. A positive SEP association was found for fruit consumption among female students only (F (4, 231) = 4.20, P = 0.003). Those from lower-SEP areas were also more likely to engage in multiple poor eating behaviours (F (4, 231) = 5.80, P, < 0.001).
Conclusions: Results suggest that socio-economic disparities in Australian adolescents’ eating behaviours do exist, with students residing in lower-SEP neighbourhoods faring less well than those from high-SEP neighbourhoods. Reducing social inequalities in eating behaviours among young people should be a key consideration of future preventive strategies.

Disparities in pediatric leukemia early survival in Argentina: a population-based study

To identify disparities-using recursive partitioning (RP)-in early survival for children with leukemias treated in Argentina, and to depict the main characteristics of the most vulnerable groups.

Socio-cultural disparities in GDM burden differ by maternal age at first delivery

Aims : Several socio-cultural and biomedical risk factors for gestational diabetes mellitus (GDM) are modifiable. However, few studies globally have examined socio-cultural associations. To eliminate confounding of increased risk of diabetes in subsequent pregnancies, elucidating socio-cultural associations requires examination only of first pregnancies.

Methods : Data for all women who delivered their first child in Victoria, Australia between 1999 and 2008 were extracted from the Victorian Perinatal Data Collection. Crude and adjusted GDM rates were calculated. Multivariate logistic regression was used to examine odds of GDM within and between socio-cultural groups.

Results : From 1999 to 2008, 269,682 women delivered their first child in Victoria. GDM complicated 11,763 (4.4%) pregnancies and burden increased with maternal age, from 2.1% among women aged below 25 years at delivery to 7.0% among those aged 35 years or more. Among younger women, GDM rates were relatively stable across socioeconomic levels. Amongst older women GDM rates were highest in those living in most deprived areas, with a strong social gradient. Asian-born mothers had highest GDM rates. All migrant groups except women born in North-West Europe had higher odds of GDM than Australian-born non-Indigenous women. In all ethnic groups, these differences were not pronounced among younger mothers, but became increasingly apparent amongst older women.

Conclusions : Socio-cultural disparities in GDM burden differ by maternal age at first delivery. Socio-cultural gradients were not evident among younger women. Health and social programs should seek to reduce the risk amongst all older women to that of the least deprived older mothers.

Regional or educational disparities? a counterfactual exercise

This work investigates the impact of schooling Oil income distribution in statesjregions of Brazil. Using a semi-parametric model, discussed in DiNardo, Fortin & Lemieux (1996), we measure how much income diíferences between the Northeast and Southeast regions- the country's poorest and richest - and between the states of Ceará and São Paulo in those regions - can be explained by differences in schooling leveIs of the resident population. Using data from the National Household Survey (PNAD), we construct counterfactual densities by reweighting the distribution of the poorest region/state by the schooling profile of the richest. We conclude that: (i) more than 50% of the income di:fference is explained by the difference in schooling; (ii) the highest deciles of the income distribution gain more from an increase in schooling, closely approaching the wage distribution of the richest region/state; and (iii) an increase in schooling, holding the wage structure constant, aggravates the wage disparity in the poorest regions/ states.

Growth, disequilibrium and disparities: interpretation of the process of economic development

Includes bibliography

Measuring educational performance and disparities in educational outcomes in an international comparative context

Includes bibliography