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PurposeWhen 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.MethodsWe 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).ResultsWe 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.ConclusionsBoth 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.

The growing trend towards young adults staying in the parental home has garnered much recent scholarly interest. However, less is known about which young adults are living at home, and the impacts this has over young adults’ lives. Using The Household, Income and Labour Dynamics in Australia (HILDA) dataset, this study examines the profiles of co-residing young adults and how these have changed over the first two decades of the 21 st century. It then analyses the associations between co-residence and young adults’ mental health, applying a propensity score modelling approach to determine differences in mental health between young adults living at home and their counterparts living independently. Results indicate that rates of co-residence have increased over the 2000s, most steeply amongst those residing outside of major cities (by 46%), older adults (by 36%), females (by 28%), and low-income groups (by 10%). Findings show a significant negative association between co-residence and mental health (a 4-point difference on the 100-point scale, 95% CI -5.93, -2.14). However, the greatest differential in mental health between co-resident and independent young adults is observed amongst those for whom rates of co-residence have increased most dramatically, i.e., females and older adults (a 6-point difference in mental health) and residents of regional and rural areas (a 5-point difference in mental health). We situate this discussion in the context of intensifying housing market constraints, considering how the transformation of the Australian housing system into a vehicle for wealth accumulation has generated barriers to residential independence.

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.

Local destinations have previously been shown to be associated with higher levels of both physical activity and walking, but little is known about how the distribution of destinations is related to activity. Kernel density estimation is a spatial analysis technique that accounts for the location of features relative to each other. Using kernel density estimation, this study sought to investigate whether individuals who live near destinations (shops and service facilities) that are more intensely distributed rather than dispersed: 1) have higher odds of being sufficiently active; 2) engage in more frequent walking for transport and recreation. The sample consisted of 2349 residents of 50 urban areas in metropolitan Melbourne, Australia. Destinations within these areas were geocoded and kernel density estimates of destination intensity were created using kernels of 400m (meters), 800m and 1200m. Using multilevel logistic regression, the association between destination intensity (classified in quintiles Q1(least)-Q5(most)) and likelihood of: 1) being sufficiently active (compared to insufficiently active); 2) walking≥4/week (at least 4 times per week, compared to walking less), was estimated in models that were adjusted for potential confounders. For all kernel distances, there was a significantly greater likelihood of walking≥4/week, among respondents living in areas of greatest destinations intensity compared to areas with least destination intensity: 400m (Q4 OR 1.41 95%CI 1.02-1.96; Q5 OR 1.49 95%CI 1.06-2.09), 800m (Q4 OR 1.55, 95%CI 1.09-2.21; Q5, OR 1.71, 95%CI 1.18-2.48) and 1200m (Q4, OR 1.7, 95%CI 1.18-2.45; Q5, OR 1.86 95%CI 1.28-2.71). There was also evidence of associations between destination intensity and sufficient physical activity, however these associations were markedly attenuated when walking was included in the models. This study, conducted within urban Melbourne, found that those who lived in areas of greater destination intensity walked more frequently, and showed higher odds of being sufficiently physically active-an effect that was largely explained by levels of walking. The results suggest that increasing the intensity of destinations in areas where they are more dispersed; and or planning neighborhoods with greater destination intensity, may increase residents' likelihood of being sufficiently active for health.

PurposeUnaffordable 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.MethodsWe 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.ResultsUnaffordable 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.ConclusionsIn conclusion, the negative mental health effect of unaffordable housing is largely mediated through increased financial hardship.

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. 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. 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. 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 -value=0.05). 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.

ObjectivesCOVID-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.DesignWe 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.SettingVictoria, Australia.ParticipantsWe 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 measuresWe 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.ResultsThose 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.ConclusionsResults 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.

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.

Asthma is related to triggers within the home. Although it is recognised that triggers likely occur due to characteristics of housing, these characteristics have not been comprehensively reviewed, and there is a paucity of housing-focused interventions to reduce asthma and asthma symptoms. Following five steps identified by Arksey and O’Malley, we conducted a scoping review of published evidence on the associations between asthma and housing characteristics. We searched three electronic databases (PubMed, Scopus, Web of Science), identifying 33 studies that met our inclusion criteria. Through an iterative approach, we identified nine housing characteristics relevant to asthma onset or exacerbation, categorised as relating to the surrounding environment (location), the house itself (dwelling), or to conditions inside the home (occupancy). We conceptualise these three levels through a housing typologies framework. This facilitates the mapping of housing characteristics, and visualises how they can cluster and overlap to exacerbate asthma or asthma symptoms. Of the three levels in our framework, associations between asthma and locational features were evidenced most clearly in the literature reviewed. Within this category, environmental pollutants (and particularly air pollutants) were identified as a potentially important risk factor for asthma. Studies concerning associations between dwelling features and occupancy features and asthma reported inconsistent results, highlighting the need for greater research in these areas. Interpreting housing-related asthma triggers through this framework paves the way for the identification and targeting of typologies of housing that might adversely affect asthma, thus addressing multiple characteristics in tandem rather than as isolated elements.

Climate change is shifting the experience of energy hardship. Here we examine the effect of the intensity, frequency, and duration of temperature extremes on energy hardship, and how this risk is shaped by individual, housing and neighbourhood resiliencies across Australia, using nationally representative data (269,500 observations) on energy hardship linked to temperature records between 2005 and 2021. Findings suggest that the risk of energy hardship increases with more intense extreme heat and cold, with greater risks for older individuals, lone-person or single-parent households, and rental tenants. These vulnerabilities can be offset by quality housing and renewable energy installations. Energy hardship risks under moderate and high emissions global warming scenarios are projected to increase by 0.1%−2.6% and 0.6%−3.3% respectively in the long run. Energy hardship will remain a concern despite raising temperatures, especially for colder regions less prepared for heat and populations with individual vulnerabilities and lacking housing and neighbourhood adaptations. In Australia, the energy burden increases with extreme heat, and single-parent or lone-person households, residents living in poor-quality houses, and colder regions are at greater risk, according to an analysis of 269,500 observations of energy expense and temperature records from 2005 to 2021.