Does employment status mediate the association between disability status and mental health among young adults? Evidence from the Household, Income and Labour Dynamics in Australia (HILDA) survey.

OBJECTIVE: Young adults with disabilities are less likely to be employed and more likely to have poor mental health than peers without disabilities. Growing evidence shows that social determinants of health may be causally related to mental health outcomes of people with disabilities. We aimed to assess if the disability to mental health association was mediated by employment status among young adults aged 20-35 years. METHODS: Four consecutive years (2016-2019) of data from the Household, Income and Labour Dynamics in Australia survey were used to conduct a causal mediation analysis. We decomposed the total causal effect of disability status on mental health (Short Form-36 Mental Health Inventory-5) into the natural direct effect from disability to mental health and the natural indirect effect representing the pathway through the employment mediator (being employed; being unemployed or wanting to work). RESULTS: 3435 participants (3058 with no disabilities, 377 with disabilities) were included in the analysis. The total causal effect of disability status on mental health was an estimated mean decrease in mental health of 4.84 points (95% CI -7.44 to -2.23). The indirect effect, through employment status, was estimated to be a 0.91-point decline in mental health (95% CI -1.50 to -0.31). CONCLUSIONS: Results suggest disability has an effect on the mental health of young adults; a proportion of this effect appears to operate through employment. The mental health of young adults with disabilities could potentially be improved with interventions to improve employment outcomes among this group, and by supporting individuals with disabilities into suitable employment.

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.

Does the presence and mix of destinations influence walking and physical activity?

BACKGROUND: Local destinations have previously been shown to be associated with higher levels of both physical activity and walking, but little is known about how specific destinations are related to activity. This study examined associations between types and mix of destinations and both walking frequency and physical activity. METHOD: The sample consisted of 2349 residents of 50 urban areas in metropolitan Melbourne, Australia. Using geographic information systems, seven types of destinations were examined within three network buffers (400 meters (m), 800 m and 1200 m) of respondents' homes. Multilevel logistic regression was used to estimate effects of each destination type separately, as well as destination mix (variety) on: 1) likelihood of walking for at least 10 min ≥ 4/week; 2) likelihood of being sufficiently physically active. All models were adjusted for potential confounders. RESULTS: All destination types were positively associated with walking frequency, and physical activity sufficiency at 1200 m. For the 800 m buffer: all destinations except transport stops and sports facilities were significantly associated with physical activity, while all except sports facilities were associated with walking frequency; at 400 m, café/takeaway food stores and transport stops were associated with walking frequency and physical activity sufficiency, and sports facilities were also associated with walking frequency. Strongest associations for both outcomes were observed for community resources and small food stores at both 800 m and 1200 m. For all buffer distances: greater mix was associated with greater walking frequency. Inclusion of walking in physical activity models led to attenuation of associations. CONCLUSIONS: The results of this analysis indicate that there is an association between destinations and both walking frequency and physical activity sufficiency, and that this relationship varies by destination type. It is also clear that greater mix of destinations positively predicts walking frequency and physical activity sufficiency.