Disability-related inequalities in the prevalence of loneliness across the lifespan: trends from Australia, 2003 to 2020.

BACKGROUND: Experiencing loneliness can be distressing and increasing evidence indicates that being lonely is associated with poor physical and mental health outcomes. Cross-sectional studies have demonstrated that people with disability have increased risk of experiencing loneliness compared to people without disability. However, we do not know if these inequalities have changed over time. This study investigated the prevalence of loneliness for people with disability in Australia annually from 2003 to 2020 to examine whether disability-related inequalities in loneliness have changed over time, and disaggregated results for subgroups of people with disability by age group, sex, and disability group. METHODS: We used annual data (2003-2020) from the Household, Income and Labour Dynamics in Australia Survey. Loneliness was measured by a single question assessing the subjective experience of loneliness. For each wave, we calculated population-weighted age-standardised estimates of the proportion of people experiencing loneliness for people with and without disability. We then calculated the absolute and relative inequalities in loneliness between people with and without disability for each wave. Analyses were stratified by 10-year age groups, sex, and disability group (sensory or speech, physical, intellectual or learning, psychological, brain injury or stroke, other). RESULTS: From 2003 to 2020, the prevalence of loneliness was greater for people with disability, such that people with disability were 1.5 to 1.9 times more likely to experience loneliness than people without disability. While the prevalence of loneliness decreased for people without disability between 2003 and 2020, the prevalence of loneliness did not decrease for people with disability during this period. Inequalities in loneliness were more substantial for people with intellectual or learning disabilities, psychological disability, and brain injury or stroke. CONCLUSION: This study confirms that people with disability have increased risk of loneliness compared to people without disability. We add to the existing evidence by demonstrating that disability-related inequalities in loneliness have persisted for two decades in Australia without improvement. Our findings indicate that addressing inequalities in loneliness for people with disability is a critical public health concern given that loneliness is associated with a wide range of poor health outcomes.

Disability-related inequalities in health and well-being are mediated by barriers to participation faced by people with disability. A causal mediation analysis.

Large inequalities in health and well-being exist between people with and without disability, in part due to poor socio-economic circumstances, and potentially also related to societal factors including issues associated with accessibility and participation. To better understand the contribution of societal factors, we used a unique longitudinal survey of disability in Great Britain to quantify the extent to which barriers to participation contribute to poorer health and well-being. We used data from 2354 individuals who participated in three waves of the Life Opportunities Survey between 2009 and 2014 and compared five health and well-being outcomes (self-rated health, anxiousness, life satisfaction, life worth, happiness) between adults who acquired an impairment and those who remained disability-free. Causal mediation analysis was conducted to quantify how much of the effect of disability acquisition on each outcome was explained by barriers to participation in employment, economic life, transport, community, leisure and civic activities, social contact, and accessibility. People who recently acquired a disability had poorer health and well-being compared to people with no disability. Barriers to participation explained 15% of inequalities in self-rated health, 28% for anxiousness, 32% for life satisfaction, 37% for life worth, and 70% for happiness. A substantial proportion of the inequalities in health and well-being experienced by people with recently acquired disability were socially produced, driven by barriers to participation in different life domains. Furthermore, there was evidence that barriers to participation mediated the effect of well-being measured to a greater extent than the more clinically aligned measures, self-reported health and anxiousness. These findings highlight modifiable factors amenable to public health interventions that could lead to substantial improvements in health and well-being for people with disability.

Use of health services by preschool-aged children who are developmentally vulnerable and socioeconomically disadvantaged: testing the inverse care law.

AIM: The inverse care law suggests that those with the greatest need for services are least likely to receive them. Our aim of this study was to test the inverse care law in relation to the use of health services by children aged 4-5 years in Australia who were developmentally vulnerable and socioeconomically disadvantaged. METHOD: Cross-sectional data were collected from the Longitudinal Study of Australian Children birth cohort when the children were aged 4-5 years. Children were grouped according to the combination of developmental vulnerability (yes, no) and socioeconomic disadvantage (lower, higher), resulting in four groups (reference group: developmentally vulnerable and disadvantaged). Multivariate regression was used to examine the impact of the combination of developmental vulnerability and disadvantage on health service use, adjusting for other sociodemographic characteristics. RESULTS: 3967 (90%) of children had data on developmental vulnerability at 4-5 years. A third of children (32.6%) were classified as developmentally vulnerable, and 10%-25% of these children had used health services. Non-disadvantaged children who were developmentally vulnerable (middle need) had 1.4-2.0 times greater odds of using primary healthcare, specialist and hospital services; and non-disadvantaged children who were not developmentally vulnerable (lowest need) had 1.6-1.8 times greater odds of using primary healthcare services, compared with children who were developmentally vulnerable and disadvantaged (highest need). CONCLUSION: We found some evidence of the inverse care law. Equity in service delivery remains a challenge that is critically important to tackle in ensuring a healthy start for children.

The effect of gender on mental health service use: an examination of mediation through material, social and health-related pathways.

PURPOSE: We aimed to understand how much of the gender difference in mental health service use could be due to the joint mediation of employment, behavioural and material factors, social support and mental health need. METHODS: We used data from employed individuals aged 18-65 years who participated in the 2015-2017 waves of the Household, Income and Labour Dynamics in Australia survey. The exposure (male, female) and confounders were measured in 2015, mediators in 2016 and the outcome-whether a person had seen a mental health professional in the previous year-was measured in 2017. We estimated natural mediation effects using weighted counterfactual predictions from a logistic regression model. RESULTS: Men were less likely to see a mental health care provider than women. The total causal effect on the risk difference scale was - 0.045 (95% CI - 0.056, - 0,034). The counterfactual of men taking the mediator values of women explained 28% (95% CI 1.7%, 54%) of the total effect, with the natural direct effect estimated to represent an absolute risk difference of - 0.033 (95% CI - 0.048, - 0.018) and the natural indirect effect - 0.012 (95% CI - 0.022, - 0.0027). CONCLUSION: Gendered differences in the use of mental health services could be reduced by addressing inequalities in health, employment, material and behavioural factors, and social support.

Gendered Working Environments as a Determinant of Mental Health Inequalities: A Protocol for a Systematic Review.

Both gender and employment are critical and intersecting social determinants of mental and physical health. This paper describes the protocol used to conduct a systematic literature review of the relationship between "gendered working environments" and mental health. Gendered working environments (GWE) are conceptualised as involving: (1) differences in selection into work, and more specifically, occupations; (2) variation in employment arrangements and working hours; (3) disparities in psychosocial exposures at work, and; (4) differences in selection out of work. Methods/design: The review will adhere to a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) search procedure. Key words will be identified that are specific to each of the four domains of GWE. The databases used for the search will be Scopus, Pubmed, Proquest, and Web of Science. Keywords will be adapted for the specific requirements of each electronic database. Inclusion criteria are: Using a validated scale to measure mental health (outcome); including exposures related to the four domains of GWE; reporting estimates for both men and women; and use of a cohort, case-control, or cross-sectional design. Studies will be excluded if they were published more than 10 years ago, are not in English or do not present extractable data on the relationship between GWE and mental health. Discussion: The proposed review will provide evidence about the numerous and complex ways in which employment and gender intersect (and are reinforced) to influence mental health over the life course.

Neighborhood Disadvantage and Body Mass Index: A Study of Residential Relocation.

Natural experiments, such as longitudinal observational studies that follow-up residents as they relocate, provide a strong basis to infer causation between the neighborhood environment and health. In this study, we examined whether changes in the level of neighborhood disadvantage were associated with changes in body mass index (BMI) after residential relocation. This analysis included data from 928 residents who relocated between 2007 and 2013, across 4 waves of the How Areas in Brisbane Influence Health and Activity (HABITAT) study in Brisbane, Australia. Neighborhood disadvantage was measured using a census-derived composite index. For individual-level data, participants self-reported their height, weight, education, occupation, and household income. Data were analyzed using multilevel, hybrid linear models. Women residing in less disadvantaged neighborhoods had a lower BMI, but there was no association among men. Neighborhood disadvantage was not associated with within-individual changes in BMI among men or women when moving to a new neighborhood. Despite a growing body of literature suggesting an association between neighborhood disadvantage and BMI, we found this association may not be causal among middle-aged and older adults. Observing associations between neighborhood socioeconomic disadvantage and BMI over the life course, including the impact of residential relocation at younger ages, remains a priority for future research.

Underemployment and its impacts on mental health among those with disabilities: evidence from the HILDA cohort.

BACKGROUND: Underemployment (defined as when a person in paid employment works for fewer hours than their desired full working capacity) is increasingly recognised as a component of employment precarity. This paper sought to investigate the effects of underemployment on the mental health of people with disabilities. METHODS: Using 14 waves of the Household, Income and Labour Dynamics in Australia survey, we used fixed-effects models to assess whether the presence of a disability modified the association between underemployment and mental health. Both disability and underemployment were assessed as time-varying factors. Measures of effect measure modification were presented on the additive scale. RESULTS: The experience of underemployment was associated with a significantly greater decline in mental health when a person reported a disability (mean difference -1.38, 95% CI -2.20 to -0.57) compared with when they did not report a disability (mean difference -0.49, 95% CI -0.84 to -0.14). The combined effect of being underemployed and having a disability was nearly one point greater than the summed independent risks of having a disability and being underemployed (-0.89, 95% CI -1.75 to -0.03). CONCLUSION: People with disabilities are more likely to experience underemployment and more likely to have their mental health adversely affected by it. There is a need for more research and policy attention on how to ameliorate the effects of underemployment on the mental health of persons with disabilities.

Young maternal age at first birth and mental health later in life: Does the association vary by birth cohort?

BACKGROUND: It is well established that maternal age at childbirth has implications for women's mental health in the short term, however there has been little research regarding longer term implications and whether this association has changed over time. We investigated longer term mental health consequences for young mothers in Australia and contrasted the effects between three birth cohorts. METHODS: Using thirteen waves of data from 4262 women aged 40 years or above participating in the Household, Income and Labour Dynamics in Australia Survey, we compared the mental health of women who had their first child aged 15-19 years, 20-24 years, and 25 years and older. Mental health was measured using the mental health component summary score of the SF-36. We used random-effects linear regression models to generate estimates of the association between age at first birth and mental health, adjusted for early life socioeconomic characteristics (country of birth, parents' employment status and occupation) and later life socioeconomic characteristics (education, employment, income, housing tenure, relationship status and social support). We examined whether the association changed over time, testing for effect modification across three successive birth cohorts. RESULTS: In models adjusted for early life and later life socioeconomic characteristics, there was strong evidence of an association between teenage births and poor mental health, with mental health scores on average 2.76 to 3.96 points lower for mothers aged younger than 20 years than for mothers aged 25 years and older (Late Baby Boom (born 1936-1945): -3.96, 95% CI -5.38, -2.54; Early Baby Boom (born 1946-1955): -3.01, 95% CI -4.32, -1.69; Lucky Few (born 1956-1965): -2.76, 95% CI -4.34, -1.18), and evidence of an association for mothers aged 20-24 years compared to mothers aged 25 years and older in the most recent birth cohort only (-1.09, 95% CI -2.01, -0.17). There was some indication (though weak) that the association increased in more recent cohorts. CONCLUSION: This study highlights that young mothers, and particularly teenage mothers, are a vulnerable group at high risk of poor mental health outcomes compared to mothers aged 25 years and above, and there was some suggestion (though weak) that the health disparities increased over time.

Housing tenure and affordability and mental health following disability acquisition in adulthood.

Acquiring a disability in adulthood is associated with a reduction in mental health and access to secure and affordable housing is associated with better mental health. We hypothesised that the association between acquisition of disability and mental health is modified by housing tenure and affordability. We used twelve annual waves of data (2001-2012) (1913 participants, 13,037 observations) from the Household, Income and Labour Dynamics in Australia survey. Eligible participants reported at least two consecutive waves of disability preceded by two consecutive waves without disability. Effect measure modification, on the additive scale, was tested in three fixed-effects linear regression models (which remove time-invariant confounding) which included a cross-product term between disability and prior housing circumstances: housing tenure by disability; housing affordability by disability and, in a sub-sample (896 participants 5913 observations) with housing costs, tenure/affordability by disability. The outcome was the continuous mental component summary (MCS) of SF-36. Models adjusted for time-varying confounders. There was statistical evidence that prior housing modified the effect of disability acquisition on mental health. Our findings suggested that those in affordable housing had a -1.7 point deterioration in MCS (95% CI -2.1, -1.3) following disability acquisition and those in unaffordable housing had a -4.2 point reduction (95% CI -5.2, -1.4). Among people with housing costs, the largest declines in MCS were for people with unaffordable mortgages (-5.3, 95% CI -8.8, -1.9) and private renters in unaffordable housing (-4.0, 95% CI -6.3, -1.6), compared to a -1.4 reduction (95% CI -2.1, -0.7) for mortgagors in affordable housing. In sum, we used causally-robust fixed-effects regression and showed that deterioration in mental health following disability acquisition is modified by prior housing circumstance with the largest negative associations found for those in unaffordable housing. Future research should test whether providing secure, affordable housing when people acquire a disability prevents deterioration in mental health.

Inequalities in socio-economic characteristics and health and wellbeing of men with and without disabilities: a cross-sectional analysis of the baseline wave of the Australian Longitudinal Study on Male Health.

BACKGROUND: Internationally, men with disabilities have higher rates of social and economic disadvantage and poorer health and wellbeing than men without disabilities. No single study has provided comprehensive, population-level information about the magnitude of such differences among adult men using a well-validated instrument to measure disability. METHODS: We analysed baseline data from Ten to Men - an Australian longitudinal study of male health. Ten to Men used a stratified multi-stage cluster random sample design to recruit a national sample of males aged 10 to 55 years residing in private dwellings. Data were collected between October 2013 and July 2014 from 15,988 males. This analysis was restricted to 18-55 year old participants with data available on age and disability (n = 13,569). We compared the demographic, socio-economic characteristics and health and wellbeing of men with and without disabilities using chi squared tests for proportions and t tests for continuous variables. Linear regression adjusted for age was used to assess the association between disability status and health and wellbeing, which were measured using the SF-12 mental and physical health component scores and the Personal Wellbeing Index. RESULTS: Men with disabilities were older and more likely to be born in Australia, speak English at home, be Aboriginal and Torres Strait Islander and were less likely to be married or de facto, or to live in urban areas. They were less likely to have completed secondary school, be employed and live in affordable housing, and were more likely to live on low incomes, in more socio-economically disadvantaged areas, and in rental accommodation and to experience shortages of money. Among employed men, those with disabilities were less likely to be in high skilled jobs, worked less hours on average, and were more likely to report that they would prefer to work more. Men with disabilities had lower levels of social support and community participation and poorer mental and physical health and overall wellbeing. CONCLUSION: Adult men with disabilities experience marked social and economic disadvantage and poorer health and wellbeing. Improving the health and wellbeing of disabled men should be a priority for public health researchers and policy-makers.

Socioeconomic position in young adulthood is associated with BMI in Australian families.

BACKGROUND: Low socioeconomic position (SEP) is associated with increased cardiovascular (CV) disease risk, but the relative importance of SEP in childhood and adulthood, and of changes in SEP between these two life stages, remains unclear. Studies of families may help clarify these issues. We aimed to assess whether SEP in young adulthood, or change in SEP from childhood to young adulthood, was associated with five continuously measured CV risk factors. METHODS: We used data from 286 adult Australian families from the Victorian Family Heart Study (VFHS), in which some offspring have left home (n = 364) and some remained at home (n = 199). SEP (defined as the Index of Relative Socioeconomic Disadvantage) was matched to addresses. We fitted variance components models to test whether young adult SEP and/or change in SEP was associated with systolic blood pressure, diastolic blood pressure, body mass index (BMI), total cholesterol or high-density lipoprotein cholesterol, after adjustment for parental SEP and within-family correlation. RESULTS: An increase in SEP of 100 SEIFA units from childhood to adulthood was associated with a lower BMI (ß = -0.49 kg/m(2), P < 0.01) only. CONCLUSIONS: These results suggest that a change in SEP in young adulthood is an important predictor of BMI, independent of childhood SEP.

Associations between individual socioeconomic position, neighbourhood disadvantage and transport mode: baseline results from the HABITAT multilevel study.

BACKGROUND: Understanding how different socioeconomic indicators are associated with transport modes provide insight into which interventions might contribute to reducing socioeconomic inequalities in health. The purpose of this study was to examine associations between neighbourhood-level socioeconomic disadvantage, individual-level socioeconomic position (SEP), and usual transport mode. METHODS: This investigation included 11,036 residents from 200 neighbourhoods in Brisbane, Australia. Respondents self-reported their usual transport mode (car or motorbike, public transport, walking or cycling). Indicators for individual-level SEP were education, occupation and household income; and neighbourhood disadvantage was measured using a census-derived index. Data were analysed using multilevel multinomial logistic regression. High SEP respondents and residents of the most advantaged neighbourhoods who used a private motor vehicle as their usual form of transport was the reference category. RESULTS: Compared with driving a motor vehicle, the odds of using public transport were higher for white collar employees (OR 1.68, 95% CrI 1.41-2.01), members of lower income households (OR 1.71 95% CrI 1.25-2.30) and residents of more disadvantaged neighbourhoods (OR 1.93, 95% CrI 1.46-2.54); and lower for respondents with a certificate-level education (OR 0.60, 95% CrI 0.49-0.74) and blue collar workers (OR 0.63, 95% CrI 0.50-0.81). The odds of walking for transport were higher for the least educated (OR 1.58, 95% CrI 1.18-2.11), those not in the labour force (OR 1.94, 95% CrI 1.38-2.72), members of lower income households (OR 2.10, 95% CrI 1.23-3.64) and residents of more disadvantaged neighbourhoods (OR 2.73, 95% CrI 1.46-5.24). The odds of cycling were lower among less educated groups (OR 0.31, 95% CrI 0.19-0.48). CONCLUSIONS: The relationships between socioeconomic characteristics and transport modes are complex, and provide challenges for those attempting to encourage active forms of transportation. Further work is required exploring the individual-level and neighbourhood-level mechanisms behind choice of transport mode, and what factors might influence individuals from different socioeconomic backgrounds to change to more active transport modes.

Perceived fairness of pay among people with and without disabilities: a propensity score matched analysis of working Australians.

OBJECTIVES: Equity and fairness at work are associated with a range of organizational and health outcomes. Past research suggests that workers with disabilities experience inequity in the workplace. It is difficult to conclude whether the presence of disability is the reason for perceived unfair treatment due to the possible confounding of effect estimates by other demographic or socioeconomic factors. METHODS: The data source was the Household, Income, and Labor Dynamics in Australia (HILDA) survey (2001-2012). Propensity for disability was calculated from logistic models including gender, age, education, country of birth, and father's occupational skill level as predictors. We then used nearest neighbor (on propensity score) matched analysis to match workers with disabilities to workers without disability. RESULTS: Results suggest that disability is independently associated with lower fairness of pay after controlling for confounding factors in the propensity score matched analysis; although results do suggest less than half a standard deviation difference, indicating small effects. Similar results were apparent in standard multivariable regression models and alternative propensity score analyses (stratification, covariate adjustment using the propensity score, and inverse probability of treatment weighting). CONCLUSIONS: Whilst neither multivariable regression nor propensity scores adjust for unmeasured confounding, and there remains the potential for other biases, similar results for the two methodological approaches to confounder adjustment provide some confidence of an independent association of disability with perceived unfairness of pay. Based on this, we suggest that the disparity in the perceived fairness of pay between people with and without disabilities may be explained by worse treatment of people with disabilities in the workplace.

Intersections between disability, type of impairment, gender and socio-economic disadvantage in a nationally representative sample of 33,101 working-aged Australians.

BACKGROUND: People with disabilities are socio-economically disadvantaged and have poorer health than people without disabilities; however, little is known about the way in which disadvantage is patterned by gender and type of impairment. OBJECTIVES: 1. To describe whether socio-economic circumstances vary according to type of impairment (sensory and speech, intellectual, physical, psychological and acquired brain injury). 2. To compare levels of socio-economic disadvantage for women and men with the same impairment type. METHODS: We used a large population-based disability-focused survey of Australians, analyzing data from 33,101 participants aged 25-64. Indicators of socio-economic disadvantage included education, income, employment, housing vulnerability, and multiple disadvantage. Stratified by impairment type, we estimated: the population weighted prevalence of socio-economic disadvantage; the relative odds of disadvantage compared to people without disabilities; and the relative odds of disadvantage between women and men. RESULTS: With few exceptions, people with disabilities fared worse for every indicator compared to people without disability; those with intellectual and psychological impairments and acquired brain injuries were most disadvantaged. While overall women with disabilities were more disadvantaged than men, the magnitude of the relative differences was lower than the same comparisons between women and men without disabilities, and there were few differences between women and men with the same impairment types. CONCLUSIONS: Crude comparisons between people with and without disabilities obscure how disadvantage is patterned according to impairment type and gender. The results emphasize the need to unpack how gender and disability intersect to shape socio-economic disadvantage.

Inequalities in social capital and health between people with and without disabilities.

The poor mental and physical health of people with disabilities has been well documented and there is evidence to suggest that inequalities in health between people with and without disabilities may be at least partly explained by the socioeconomic disadvantage (e.g. low education, unemployment) experienced by people with disabilities. Although there are fewer studies documenting inequalities in social capital, the evidence suggests that people with disabilities are also disadvantaged in this regard. We drew on Bourdieu's conceptualisation of social capital as the resources that flow to individuals from their membership of social networks. Using data from the General Social Survey 2010 of 15,028 adults living in private dwellings across non-remote areas of Australia, we measured social capital across three domains: informal networks (contact with family and friends); formal networks (group membership and contacts in influential organisations) and social support (financial, practical and emotional). We compared levels of social capital and self-rated health for people with and without disabilities and for people with different types of impairments (sensory and speech, physical, psychological and intellectual). Further, we assessed whether differences in levels of social capital contributed to inequalities in health between people with and without disabilities. We found that people with disabilities were worse off than people without disabilities in regard to informal and formal networks, social support and self-rated health status, and that inequalities were greatest for people with intellectual and psychological impairments. Differences in social capital did not explain the association between disability and health. These findings underscore the importance of developing social policies which promote the inclusion of people with disabilities, according to the varying needs of people with different impairments types. Given the changing policy environment, ongoing monitoring of the living circumstances of people with disabilities, including disaggregation of data by impairment type, is critical.

Income inequality and Neisseria gonorrhoeae notifications in females: a country-level analysis.

UNLABELLED: Background Patterns of population susceptibility to sexually transmissible infections may be influenced by various social determinants of health, however these receive relatively little attention. Income inequality is one such determinant that has been linked to a number of poor health outcomes. The objective of this analysis was to determine whether there is an association between income inequality and Neisseria gonorrhoeae notification rates when measured at the country level. METHODS: Gini coefficients, gonorrhoea notification rates among women, per capita gross domestic product and approximate size of female population were obtained for 11 countries of the OECD. Linear regression was used to measure the association between income inequality and gonorrhoea notification rates, using generalised estimation equations (GEE) to control for the non-independence of repeat measures from particular countries. RESULTS: A total of 36 observations from 11 countries were included. Gini coefficients ranged from 0.21 to 0.38 and gonorrhoea notifications from 0.7 to 153 per 100000 females. Significant associations were found between country-level income inequality and gonorrhoea notification rates among women (b=17.79 (95% CI: 10.64, 24.94, P<0.01). CONCLUSIONS: Significant associations were found, highlighting the importance of acknowledging and accounting for social determinants of sexual health and suggesting that further research in this arena may be fruitful.

Time trends in socio-economic inequalities for women and men with disabilities in Australia: evidence of persisting inequalities.

INTRODUCTION: The socio-economic circumstances and health of people with disabilities has been relatively ignored in public health research, policy and practice in Australia and internationally. This is despite emerging evidence that the socio-economic circumstances that people with disabilities live in contributes to their poorer health. Compared to other developed countries, Australians with disabilities are more likely to live in disadvantaged circumstances, despite being an economically prosperous country; it is therefore likely that the socio-economic disadvantage experienced by Australians with disabilities makes a significant contribution to their health. Despite the importance of this issue Australia does not routinely monitor the socio-economic inequalities for people with disabilities. This paper addresses this gap by describing time trends in socio-economic conditions for Australians with and without disabilities according to the severity of the disability and sex. METHODS: Cross-sectional analyses of the Australian Bureau of Statistics Survey of Disability, Ageing and Carers were carried out at three time points (1998, 2003 and 2009) to estimate the proportions of women and men (aged between 25 and 64 years) who were living on low incomes, had not completed year 12, were not in paid work, living in private rental and experiencing multiple disadvantage (three or more of the indicators). RESULTS: People with disabilities are less likely to have completed year 12, be in paid work and are more likely to be living on low incomes and experiencing multiple disadvantage. These conditions worsened with increasing severity of disability and increased or persisted over time, with most of the increase between 1998 and 2003. While women with milder disabilities tended to fare worse than men, the proportions were similar for those with moderate and severe/profound disabilities. CONCLUSION: People with disabilities experience high levels of socio-economic disadvantage which has increased or persisted over time and these are likely to translate into poorer health outcomes. A large proportion experience multiple forms of disadvantage, reinforcing the need to tackle disadvantage in a coordinated way across sectors.People with disabilities should be a priority population group for public health. Monitoring socio-economic conditions of people with disabilities is critical for informing policy and assessing the impact of disability reforms.

Leave entitlements, time off work and the household financial impacts of quarantine compliance during an H1N1 outbreak.

BACKGROUND: The Australian state of Victoria, with 5.2 million residents, enforced home quarantine during a H1N1 pandemic in 2009. The strategy was targeted at school children. The objective of this study was to investigate the extent to which parents' access to paid sick leave or paid carer's leave was associated with (a) time taken off work to care for quarantined children, (b) household finances, and (c) compliance with quarantine recommendations. METHODS: We conducted an online and telephone survey of households recruited through 33 schools (85% of eligible schools), received 314 responses (27%), and analysed the subsample of 133 households in which all resident parents were employed. RESULTS: In 52% of households, parents took time off work to care for quarantined children. Households in which no resident parent had access to leave appeared to be less likely to take time off work (42% vs 58%, p=0.08) although this difference had only borderline significance. Among parents who did take time off work, those in households without access to leave were more likely to lose pay (73% vs 21%, p<0.001). Of the 26 households in which a parent lost pay due to taking time off work, 42% experienced further financial consequences such as being unable to pay a bill. Access to leave did not predict compliance with quarantine recommendations. CONCLUSIONS: Future pandemic plans should consider the economic costs borne by households and options for compensating quarantined families for income losses.

Area-level socioeconomic status and incidence of abnormal glucose metabolism: the Australian Diabetes, Obesity and Lifestyle (AusDiab) study.

OBJECTIVE: To examine the role of area-level socioeconomic status (SES) on the development of abnormal glucose metabolism (AGM) using national, population-based data. RESEARCH DESIGN AND METHODS: The Australian Diabetes, Obesity and Lifestyle (AusDiab) study is a national, population-based, longitudinal study of adults aged ≥25 years. A sample of 4,572 people provided complete baseline (1999 to 2000) and 5-year follow-up (2004 to 2005) data relevant for these analyses. Incident AGM was assessed using fasting plasma glucose and 2-h plasma glucose from oral glucose tolerance tests, and demographic, socioeconomic, and behavioral data were collected by interview and questionnaire. Area SES was defined using the Index of Relative Socioeconomic Disadvantage. Generalized linear mixed models were used to examine the relationship between area SES and incident AGM, with adjustment for covariates and correction for cluster design effects. RESULTS: Area SES predicted the development of AGM, after adjustment for age, sex, and individual SES. People living in areas with the most disadvantage were significantly more likely to develop AGM, compared with those living in the least deprived areas (odds ratio 1.53; 95% CI 1.07-2.18). Health behaviors (in particular, physical activity) and central adiposity appeared to partially mediate this relationship. CONCLUSIONS: Our findings suggest that characteristics of the physical, social, and economic aspects of local areas influence diabetes risk. Future research should focus on identifying the aspects of local environment that are associated with diabetes risk and how they might be modified.