The total health gains and cost savings of eradicating cold housing in Australia.

BACKGROUND: Cold indoor temperature (<18 °C) is associated with hypertension-related and respiratory disease, depression, and anxiety. We estimate total health, health expenditure and income impacts of permanently lifting the temperature in living areas of the home to 18 °C in cold homes in South-eastern Australia (N = 17 million). METHODS: A proportional multistate lifetable model was used to estimate health adjusted life years (HALYs), health expenditure and income earnings, over the remainder of the lifespan of the population alive in 2021 (3% discount rate). Multiple data were integrated including the prevalence of cold housing (5.87%; mean temperature 15 °C), the effect of temperature to hypertension-related, respiratory disease, depression and anxiety. FINDINGS: Eradicating cold housing was predicted to lead to 89,600 (95% UI 47,700 to 177,000) lifetime HALYs gained over the population's remaining lifespan, nearly half of which occurred from 2021 to 2040. Respiratory disease (32.4%) and mental illness (60.6%) made large contributions to HALYs gained, but also had large uncertainty (95% UI 30.0%-42.9% and 45.1%-64.6%, respectively) due to uncertain estimates of their magnitude of causal association with cold housing. Health gains per capita were 6.1 times greater (95% UI 4.7 to 8.1) among the most compared to least deprived quintile. From 2021 to 2040, health expenditure decreased by AUD$0.87 billion (0.35-1.98) and income earnings increased by AUD$4.35 billion (1.89-9.81). INTERPRETATION: Eliminating cold housing would lead to substantial health gains, reductions in health inequalities, savings in health expenditure, and productivity gains. Next steps require research to reduce uncertainty about the magnitude of causal associations of cold with mental and respiratory health.

Housing and health: an updated glossary.

Recent crises have underscored the importance that housing has in sustaining good health and, equally, its potential to harm health. Considering this and building on Howden-Chapman's early glossary of housing and health and the WHO Housing and Health Guidelines, this paper introduces a range of housing and health-related terms, reflecting almost 20 years of development in the field. It defines key concepts currently used in research, policy and practice to describe housing in relation to health and health inequalities. Definitions are organised by three overarching aspects of housing: affordability (including housing affordability stress (HAS) and fuel poverty), suitability (including condition, accessibility and sustainable housing) and security (including precarious housing and homelessness). Each of these inter-related aspects of housing can be either protective of, or detrimental to, health. This glossary broadens our understanding of the relationship between housing and health to further promote interdisciplinarity and strengthen the nexus between these fields.

Environmental Noise Exposure and Mental Health: Evidence From a Population-Based Longitudinal Study.

INTRODUCTION: Exposure to environmental noise from within homes has been associated with poor mental health. Existing evidence rests on cross-sectional studies prone to residual confounding, reverse causation, and small sample sizes, failing to adequately consider the causal nature of this relationship. Furthermore, few studies have examined the sociodemographic distribution of noise exposure at a country level. METHODS: The study, conducted in 2021, examined the impact of environmental noise from road traffic, airplanes, trains, and industry on mental health and psychological distress as reported by 31,387 respondents using a 19-year longitudinal data set in Australia (2001‒2019). To improve the capacity to make causal inference and reduce bias from measurement error, reverse causation, and unobserved confounders, analyses used instrumental variables, fixed-effects models, and an aggregated area-level measure of noise exposure. Utilizing the large-scale national data set, sociospatial distributions of noise exposure were described. RESULTS: Private and public rental tenants, lone parents, residents of socioeconomically disadvantaged areas, and those with long-term health conditions were more likely to report residential noise exposure. This exposure to noise was consistently associated with poorer mental health (self-reported noise: ß= -0.58; 95% CI= -0.76, -0.39; area-level noise: ß= -0.43; 95% CI= -0.61, -0.26), with the relationship strongest for traffic noise (ß= -0.79; 95% CI= -1.07, -0.51). Notably, when noise exposure decreased over time, there was an increase in mental health (ß= 0.43; 95% CI= 0.14, 0.72). CONCLUSIONS: The study provides strong evidence of a negative mental health effect of perceived residential noise, and the results have implications for healthy home design and urban planning. These findings should be validated with further studies that measure noise intensity and housing quality.

Impact of COVID-19 shocks, precarity and mediating resources on the mental health of residents of share housing in Victoria, Australia: an analysis of data from a two-wave survey.

OBJECTIVES: COVID-19 lockdown measures have challenged people's mental health, especially among economically vulnerable households. The objective of this study was to investigate the impact of exposure to COVID-19 shocks (defined as job loss, living cost pressures and changing housing conditions throughout the lockdown period) and double precarity (defined as precarity in housing and employment) on mental health outcomes for members of share households as well as the mediating effects of a range of resources. DESIGN: We conducted a two-wave survey of occupants of share housing in June and October 2020 during a prolonged period of population lockdown. Research design involved fixed effects ordered logit regression models to assess the mental health consequences of baseline precarity and COVID-related shocks. SETTING: Victoria, Australia. PARTICIPANTS: We surveyed 293 occupants of share houses (mean age 34 SD 11.5, 56% female). Members of share houses (where individuals are unrelated adults and not in a romantic relationship) are more likely to be young, casually employed, visa-holders and low-income. OUTCOME MEASURES: We measured household composition, housing and employment precarity, access to government support, household crowding, social networks and COVID-19 shocks. We used a self-reported measure of mental health. RESULTS: Those exposed to COVID-19 shocks reported a 2.7 times higher odds of mental health deterioration (OR 2.7, 95% CI 1.53 to 4.85). People exposed to double precarity (precarity in both housing and employment) reported 2.4 times higher odds of mental health deterioration (OR 2.4, 95% CI 0.99 to 5.69). Housing inadequacy and lack of access to sufficient government payments explained 14.7% and 7% of the total effect of double precarity on mental health, respectively. CONCLUSIONS: Results indicate that residents of group households characterised by pre-existing precarity were vulnerable to negative mental health effects during lockdown. Access to sufficient government payments and adequate housing buffered this negative effect.

How much of the effect of disability acquisition on mental health is mediated through employment and income? A causal mediation analysis quantifying interventional indirect effects using data from four waves of an Australian cohort study.

OBJECTIVES: There is evidence that disability acquisition causes a decline in mental health, but few studies have examined the causal mechanisms through which the effect operates. This study used a novel approach to mediation analysis to quantify interventional indirect effects (IIEs) through employment and income. DESIGN AND SETTING: We used four waves of longitudinal data (2011-2014) from the Household, Income and Labour Dynamics in Australia Survey, a nationally representative survey of Australian households. PARTICIPANTS: Working aged individuals who acquired a disability (n=233) were compared with those who remained disability-free in all four waves (n=5419). PRIMARY OUTCOME MEASURE: Self-reported mental health was measured using the Mental Health Inventory subscale of the Short Form 36 general health questionnaire, which measures symptoms of depression, anxiety and psychological well-being. STATISTICAL ANALYSIS: We conducted a causal mediation analysis quantifying IIEs of disability acquisition on mental health operating through two distinct mediators: employment status and income. We used multiple imputation with 50 imputed datasets to account for missing data. RESULTS: The total causal effect of disability acquisition on mental health was estimated to be a 4.8-point decline in mental health score (estimated mean difference: -4.8, 95% CI -7.0 to -2.7). The IIE through employment was estimated to be a 0.5-point difference (-0.5, 95% CI -1.0 to 0.0), accounting for 10.6% of the total effect, whereas there was no evidence that income explained any of the effects. CONCLUSIONS: This study estimated that disability-related mental health inequalities could be reduced by 10.6% if employment rates were the same for people with disability as those without disability. The results suggest that employment is implicated in the relationship between disability acquisition and mental health and that more research is needed to understand the influence of other aspects of employment and other socioeconomic characteristics.

Mapping home internet activity during COVID-19 lockdown to identify occupation related inequalities.

During the COVID-19 pandemic, evidence has accumulated that movement restrictions enacted to combat virus spread produce disparate consequences along socioeconomic lines. We investigate the hypothesis that people engaged in financially secure employment are better able to adhere to mobility restrictions, due to occupational factors that link the capacity for flexible work arrangements to income security. We use high-resolution spatial data on household internet traffic as a surrogate for adaptation to home-based work, together with the geographical clustering of occupation types, to investigate the relationship between occupational factors and increased internet traffic during work hours under lockdown in two Australian cities. By testing our hypothesis based on the observed trends, and exploring demographic factors associated with divergences from our hypothesis, we are left with a picture of unequal impact dominated by two major influences: the types of occupations in which people are engaged, and the composition of households and families. During lockdown, increased internet traffic was correlated with income security and, when school activity was conducted remotely, to the proportion of families with children. Our findings suggest that response planning and provision of social and economic support for residents within lockdown areas should explicitly account for income security and household structure. Overall, the results we present contribute to the emerging picture of the impacts of COVID-19 on human behaviour, and will help policy makers to understand the balance between public health and social impact in making decisions about mitigation policies.

Alcohol and tobacco consumption: What is the role of economic security?

AIMS: To better understand the longstanding inequalities concerning alcohol and tobacco use, we aimed to quantify the effect of household economic security on alcohol and tobacco consumption and expenditure. DESIGN: Longitudinal analysis using data from the Household, Income and Labour Dynamics in Australia survey (2001-2018). SETTING: Australia PARTICIPANTS: A nationally representative cohort of 24 134 adults aged 25-64 years (187 378 observations). MEASUREMENTS: Tobacco and alcohol use (Yes/No), frequency of use of each per week, household expenditure on each per week, household weekly income (Consumer Price Index [CPI]-adjusted), employment security (based on conditions of employment) and housing affordability (housing costs relative to household income). FINDINGS: At baseline, one-quarter of the sample used tobacco and 87% used alcohol. Annual increases in household income were associated with the increased use of both tobacco and alcohol for people in households in the lowest 40% of the national income distribution (OR = 1.13, 95% CI = 1.03-1.23 and OR = 1.12, 95% CI = 1.04-1.20, respectively) with no similar income effect observed for higher-income households. In relation to smoking, the odds of a resident's tobacco use increased when their household was unemployed (OR = 1.32, 95% CI = 1.07-1.62). In relation to alcohol, the odds of use decreased when households were insecurely employed or unemployed, or housing costs were unaffordable (OR = 0.87, 95% CI = 0.77-0.98, OR = 0.66, 95% CI = 0.55-0.80 and OR = 0.84, 95% CI = 0.75-0.93, respectively). This was also reflected in the reduced odds of risky drinking (defined in accordance with Australian guidelines) when housing became unaffordable or households became unemployed (OR = 0.90, 95% CI = 0.81-0.99; OR = 0.82, 95% CI = 0.69-0.98, respectively). CONCLUSIONS: In Australia, smoking and drinking appear to exhibit different socio-behavioural characteristics and household unemployment appears to be a strong determinant of smoking.

Mental health and prolonged exposure to unaffordable housing: a longitudinal analysis.

PURPOSE: When housing is insufficient, or poor quality, or unaffordable there are well established health effects. Despite the pervasiveness of housing affordability problems (widely referred to as Housing Affordability Stress-HAS), little quantitative work has analysed long-term mental health effects. We examine the mental health effects of (prolonged and intermittent) patterns of exposure to housing affordability problems. METHODS: We analysed a large, nationally representative longitudinal population sample of individuals, following them over five-year periods to assess the relative mental health effects of different patterns of exposure to housing affordability problems. To maximise the number of observations and the robustness of findings, we used 15 years (2002-2016) of data, across three pooled exposure windows. Longitudinal regression analysis with Mundlak adjustment was used to estimate the association between prolonged (constant over a 5-year period) and intermittent exposure to HAS, and mental health (as measured using the SF-36 MCS). RESULTS: We found that, on average, both prolonged and intermittent exposure were associated with lower mental health (Beta = - 1.338 (95% CI - 2.178-0.488) and Beta = - 0.516 (95% CI - 0.868-0.164), respectively). When we additionally adjusted for baseline mental health, thereby accounting for initial mental health status, coefficients were attenuated but remained significant. CONCLUSIONS: Both prolonged and intermittent exposure to HAS negatively impact mental health, irrespective of baseline mental health. Interventions that target affordable housing would benefit population mental health. Mental health interventions should be designed with people's housing context in mind.

Does the effect of disability acquisition on mental health differ by employment characteristics? A longitudinal fixed-effects analysis.

PURPOSE: Longitudinal studies have suggested a causal relationship between disability acquisition and mental health, but there is substantial heterogeneity in the magnitude of the effect. Previous studies have provided evidence that socioeconomic characteristics can buffer the effect but have not examined the role of employment characteristics. METHODS: We used data from 17 annual waves of the Household, Income and Labour Dynamics in Australia Survey to compare the mental health of working age individuals before and after disability acquisition, using the Mental Health Inventory, a subscale of the SF-36 health questionnaire. Linear fixed-effects regression models were used to estimate the effect of disability acquisition on mental health. We tested for effect modification by two characteristics of people's employment prior to disability acquisition: occupational skill level and contract type. Multiple imputation using chained equations was used to handle missing data. RESULTS: Disability acquisition was associated with a substantial decline in mental health score (estimated mean difference: - 4.3, 95% CI - 5.0, - 3.5). There was evidence of effect modification by occupational skill level, with the largest effects seen for those in low-skilled jobs (- 6.1, 95% CI - 7.6, - 4.5), but not for contract type. CONCLUSIONS: The findings highlight the need for social and health policies that focus on increasing employment rates, improving the sustainability of employment, and providing employment services and education and training opportunities for people who acquire a disability, particularly for people in low-skilled occupations, to reduce the mental health inequalities experienced by people with disabilities.

Do financial hardship and social support mediate the effect of unaffordable housing on mental health?

PURPOSE: Unaffordable housing has a negative impact on mental health; however, little is known about the causal pathways through which it transmits this effect. We examine the role of financial hardship and social support as mediators of this relationship. METHODS: We identified households where housing costs changed from affordable to unaffordable across two waves of the Household, Income and Labour Dynamics in Australia (HILDA) Survey (2014-2015). The sequential causal mediation analysis was used to decompose the total effect of unaffordable housing on mental health into the portion attributable to financial hardship and social support [natural indirect effect (NIE)] and the portion not occurring through measured pathways [natural direct effect (NDE)]. Mental health was measured using the Mental Health Inventory (MHI) and Kessler psychological distress (KPD) scale. Baseline covariates included age, sex, household income, financial hardship, social support, marital status and employment status. Bootstrapping with 1000 replications was used to calculate 95% confidence intervals (CIs). Multiple imputations using chained equations were applied to account for missing data. RESULTS: Unaffordable housing led to a change in mean mental health score on the MHI scale (- 1.3, 95% CI: - 2.1, - 0.6) and KPDS scale (0.9, 95% CI: 0.4, 1.4). Financial hardship accounted for 54% of the total effect on MHI scale and 53% on KPD scale. Collectively, financial hardship and social support explained 68% of the total effect on MHI scale and 67% on KPD scale, respectively. CONCLUSIONS: In conclusion, the negative mental health effect of unaffordable housing is largely mediated through increased financial hardship.

How Does Household Residential Instability Influence Child Health Outcomes? A Quantile Analysis.

At the core of housing and welfare research is a premise that stable residential environments are important to children's health and development. The relationship between housing stability and health outcomes for children is, however, complex; stable housing situations are sometimes associated with poorer health outcomes, and some children may be more or less resilient to residential instability. The Longitudinal Study of Australian Children (LSAC) dataset enables us to longitudinally follow the housing and health of more than 10,000 children and their families. We employ a quantile analysis technique, a currently underutilized tool for testing associations across the distribution of an outcome, to test whether exposure to housing instability has a differential impact on children's health dependent on their initial health status. Our findings suggest that the health outcomes of residential instability are highly dependent on children's initial health status.

Better transport accessibility, better health: a health economic impact assessment study for Melbourne, Australia.

BACKGROUND: Physical inactivity is a global public health problem, partly due to urbanization and increased use of passive modes of transport such as private motor vehicles. Improving accessibility to public transport could be an effective policy for Governments to promote equity and efficiency within transportation systems, increase population levels of physical activity and reduce the negative externalities of motor vehicle use. Quantitative estimates of the health impacts of improvements to public transport accessibility may be useful for resource allocation and priority-setting, however few studies have been published to inform this decision-making. This paper aims to estimate the physical activity, obesity, injury, health and healthcare cost-saving outcomes of scenario-based improvements to public transport accessibility in Melbourne, Australia. METHODS: Baseline and two hypothetical future scenario estimates of improved public transport accessibility for Melbourne, Australia, were derived using a spatial planning and decision tool designed to simulate accessibility performance (the Spatial Network Analysis for Multimodal Urban Transport Systems (SNAMUTS)). Public transport related physical activity was quantified by strata of age group and sex from Melbourne travel survey data (VISTA survey) and used with the SNAMUTS Composite Index to estimate input data for health impact modelling for the Melbourne population aged 20-74 years. A proportional multi-state, multiple cohort lifetable Markov model quantified the potential health gains and healthcare cost-savings from estimated changes in physical activity, body weight and injuries related to walking to access/egress public transport under two scenarios: (S1) public transport accessibility under current policy directions, and (S2) multi-directional, high-frequency network improvements. RESULTS: Multi-directional, high-frequency improvements to the public transport network (S2) resulted in significantly greater health and economic gains than current policy directions (S1) in relation to physical activity (mean 6.4 more MET minutes/week), body weight (mean 0.05 kg differential), health-adjusted life years gained (absolute difference of 4878 HALYs gained) and healthcare cost-savings (absolute difference of AUD43M), as compared to business as usual under both scenarios (n = 2,832,241 adults, over the lifecourse). CONCLUSIONS: Based on our conservative analyses, improving accessibility to public transport will improve population health by facilitating physical activity and lead to healthcare cost savings compared with business-as-usual. These wider health benefits should be better considered in transport planning and policy decisions.

Daily Walking among Commuters: A Cross-Sectional Study of Associations with Residential, Work, and Regional Accessibility in Melbourne, Australia (2012-2014).

BACKGROUND: Most research on walking for transport has focused on the walkability of residential neighborhoods, overlooking the contribution of places of work/study and the ease with which destinations outside the immediate neighborhood can be accessed, referred to as regional accessibility. OBJECTIVES: We aimed to examine if local accessibility/walkability around place of work/study and regional accessibility are independently and interactively associated with walking. METHODS: A sample of 4,913 adult commuters was derived from a household travel survey in Melbourne, Australia (2012-2014). Local accessibility was measured as the availability of destinations within an 800-m pedestrian network from homes and places of work/education using a local living index [LLI; 0-3 (low), 4-6, 7-9, and 10-12 (high) destinations]. Regional accessibility was estimated using employment opportunity, commute travel time by mode, and public transport accessibility. Every individual's potential minutes of walking for each level of exposure (observed and counter to fact) were predicted using multivariable regression models including confounders and interaction terms. For each contrast of exposure levels of interest, the corresponding within-individual differences in predicted walking were averaged across individuals to estimate marginal effects. RESULTS: High LLI at home and work/education was associated with more minutes walking than low LLI by 3.9 [95% confidence interval (CI): 2.3, 5.5] and 8.3 (95% CI: 7.3, 9.3) min, respectively, in mutually adjusted models. Across regional accessibility measures, an independent association with walking and an interactive association with LLI at work/education was observed. To take one example, the regional accessibility measure of "Jobs within 30 min by public transport" was associated with 4.3 (95% CI: 2.9, 5.7) more mins walking for high (≥30,000 jobs) compared with low (<4,000 jobs) accessibility in adjusted models. The estimated difference for high vs. low LLI (work/education) (among those with low regional accessibility) was 3.6 min (95% CI: 2.3, 4.8), while the difference for high vs. low regional accessibility (among those with low LLI) was negligible (-0.01; 95% CI: -1.2, 1.2). However, the combined effect estimate for high LLI and high regional accessibility, compared with low on both, was 12.8 min (95% CI: 11.1, 14.5), or 9.3 (95% CI: 6.7, 11.8) min/d walking more than expected based on the separate effect estimates. CONCLUSIONS: High local living (work/education) and regional accessibility, regardless of the regional accessibility measure used, are positively associated with physical activity. High exposure to both is associated with greater benefit than exposure to one or the other alone. https://doi.org/10.1289/EHP3395.

The 'double precarity' of employment insecurity and unaffordable housing and its impact on mental health.

This paper describes who is most likely to experience household employment insecurity and housing affordability stress - double precarity - and estimates the degree to which housing affordability mediates the effect of employment insecurity on mental health. We use a cohort of 24,201 participants in 2016 Household, Income and Labour Dynamics in Australia survey (6.2 repeated measures on average). We estimate the likelihood of onset of household employment insecurity, housing affordability stress and change in housing costs using longitudinal regression analyses for socio-demographic groups. We assess mediation by estimating how much exposure variable coefficients attenuate with inclusion of a mediator in fixed effects regression models. We also apply causal mediation methods to fixed-effects regression models to better account for exposure-mediator interaction and meet strict model assumptions. If people's households become insecurely employed, there are five times greater odds of them also experiencing housing affordability stress (OR 4.99 95%CI 4.21-5.90). Key cohorts within the population are shown to be especially vulnerable to double precarity - notably single parents (OR 2.91, 95%CI 1.94-4.35) and people who live alone (OR 4.42, 95% CI 3.03-6.45) (compared to couples), and people who are recently separated or divorced (OR 2.59, 95%CI 1.81-3.70). Mediation analysis confirms that household employment insecurity has a small, negative effect on mental health (Beta -0.24, 95%CI -0.38-0.11 on a 1 to 100-point scale with 10-point standard deviation). Estimates from casual mediation analyses suggest housing affordability accounts for 20% of the total effect; likely concentrated in the lowest and highest strata of income. Employment and housing insecurity represent a form of double precarity for people in households with a single income. When we consider the impact on mental health, we find evidence of a causal relationship between insecure employment onset and mental health, around one fifth of which is mediated by changing housing cost and onset of affordability stress.

A Longitudinal Study Examining Changes in Street Connectivity, Land Use, and Density of Dwellings and Walking for Transport in Brisbane, Australia.

BACKGROUND: Societies face the challenge of keeping people active as they age. Walkable neighborhoods have been associated with physical activity, but more rigorous analytical approaches are needed. OBJECTIVES: We used longitudinal data from adult residents of Brisbane, Australia (40-65 years of age at baseline) to estimate effects of changes in neighborhood characteristics over a 6-y period on the likelihood of walking for transport. METHODS: Analyses included 2,789-9,747 How Areas Influence Health and Activity (HABITAT) cohort participants from 200 neighborhoods at baseline (2007) who completed up to three follow-up questionnaires (through 2013). Principal components analysis was used to derive a proxy measure of walkability preference. Environmental predictors were changes in street connectivity, residential density, and land use mix within a one-kilometer network buffer. Associations with any walking and minutes of walking were estimated using logistic and linear regression, including random effects models adjusted for time-varying confounders and a measure of walkability preference, and fixed effects models of changes in individuals to eliminate confounding by time-invariant characteristics. RESULTS: Any walking for transport (vs. none) was increased in association with an increase in street connectivity (+10 intersections, fixed effects OR=1.19; 95% confidence interval (CI): 1.07, 1.32), residential density (+5 dwellings/hectare, OR=1.10; 95% CI: 1.05, 1.15), and land-use mix (10% increase, OR=1.12; 95% CI: 1.00, 1.26). Associations with minutes of walking were positive based on random effects models, but null for fixed effects models. The association between land-use mix and any walking appeared to be limited to participants in the highest tertile of increased street connectivity (fixed effects OR=1.17; 95% CI: 0.99, 1.35 for a 1-unit increase in land-use mix; interaction p-value=0.05). CONCLUSIONS: Increases in street connectivity, residential density, and land-use heterogeneity were associated with walking for transport among middle-age residents of Brisbane, Australia. https://doi.org/10.1289/EHP2080.

Do material, psychosocial and behavioural factors mediate the relationship between disability acquisition and mental health? A sequential causal mediation analysis.

BACKGROUND: There is evidence of a causal relationship between disability acquisition and poor mental health; however, the mechanism by which disability affects mental health is poorly understood. This gap in understanding limits the development of effective interventions to improve the mental health of people with disabilities. METHODS: We used four waves of data from the Household, Income and Labour Dynamics in Australia Survey (2011-14) to compare self-reported mental health between individuals who acquired any disability (n=387) and those who remained disability-free (n=7936). We tested three possible pathways from disability acquisition to mental health, examining the effect of material, psychosocial and behavioural mediators. The effect was partitioned into natural direct and indirect effects through the mediators using a sequential causal mediation analysis approach. Multiple imputation using chained equations was used to assess the impact of missing data. RESULTS: Disability acquisition was estimated to cause a five-point decline in mental health [estimated mean difference: -5.3, 95% confidence interval (CI) -6.8, -3.7]. The indirect effect through material factors was estimated to be a 1.7-point difference (-1.7, 95% CI -2.8, -0.6), explaining 32% of the total effect, with a negligible proportion of the effect explained by the addition of psychosocial characteristics (material and psychosocial: -1.7, 95% CI -3.0, -0.5) and a further 5% by behavioural factors (material-psychosocial-behavioural: -2.0, 95% CI -3.4, -0.6). CONCLUSIONS: The finding that the effect of disability acquisition on mental health operates predominantly through material rather than psychosocial and behavioural factors has important implications. The results highlight the need for better social protection, including income support, employment and education opportunities, and affordable housing for people who acquire a disability.

The impact of persistent poor housing conditions on mental health: A longitudinal population-based study.

Living with housing problems increases the risk of mental ill health. Housing problems tend to persist over time but little is known about the mental health consequences of living with persistent housing problems. We investigated if persistence of poor housing affects mental health over and above the effect of current housing conditions. We used data from 13 annual waves of the British Household Panel Survey (1996 to 2008) (81,745 person/year observations from 16,234 individuals) and measured the persistence of housing problems by the number of years in the previous four that a household experienced housing problems. OLS regression models and lagged-change regression models were used to estimate the effects of past and current housing conditions on mental health, as measured by the General Health Questionnaire. Interaction terms tested if tenure type modified the impact of persistent poor housing on mental health. In fully adjusted models, mental health worsened as the persistence of housing problems increased. Adjustment for current housing conditions attenuated, but did not explain, the findings. Tenure type moderated the effects of persistent poor housing on mental health, suggesting that those who own their homes outright and those who live in social housing are most negatively affected. Persistence of poor housing was predictive of worse mental health, irrespective of current housing conditions, which added to the weight of evidence that demonstrates that living in poor quality housing for extended periods of time has negative consequences for mental health.

Disability acquisition and mental health: effect modification by demographic and socioeconomic characteristics using data from an Australian longitudinal study.

OBJECTIVES: There is evidence of a causal relationship between disability acquisition and poor mental health, but the substantial heterogeneity in the magnitude of the effect is poorly understood and may be aetiologically informative. This study aimed to identify demographic and socioeconomic factors that modify the effect of disability acquisition on mental health. DESIGN AND SETTING: The Household, Income and Labour Dynamics in Australia Survey is a nationally representative longitudinal survey of Australian households that has been conducted annually since 2001. Four waves of data were included in this analysis, from 2011 to 2014. PARTICIPANTS: Individuals who acquired a disability (n=387) were compared with those who remained disability-free in all four waves (n=7936). PRIMARY OUTCOME MEASURE: Mental health was measured using the mental health subscale of the Short Form 36 (SF-36) general health questionnaire, which measures symptoms of depression, anxiety and psychological well-being. METHODS: Linear regression models were fitted to estimate the effect of disability acquisition on mental health, testing for effect modification by key demographic and socioeconomic characteristics. To maximise causal inference, we used a propensity score approach with inverse probability of treatment weighting to control for confounding and multiple imputation using chained equations to assess the impact of missing data. RESULTS: On average, disability acquisition was associated with a 5-point decline in mental health score (estimated mean difference: -5.1, 95% CI -7.2 to -3.0). There was strong evidence that income and relationship status modified the effect, with more detrimental effects in the lowest (-12.5, 95% CI -18.5 to -6.5) compared with highest income quintile (-1.1, 95% CI -4.9 to 2.7) and for people not in a relationship (-8.8, 95% CI -12.9 to -4.8) compared with those who were (-3.7, 95% CI -6.1 to -1.4). CONCLUSIONS: Our results suggest that the detrimental effect of disability acquisition on mental health is substantially greater for socioeconomic disadvantaged individuals.