Urban density, household overcrowding and the spread of COVID-19 in Australian cities.

The UN-Habitat World Cities Report 2020 highlighted that overcrowded housing, not urban density, is the major contributing factor to the spread of COVID-19. The relatively successful ability of densely populated cities such as Seoul, Singapore, Tokyo and New York City to manage virus spread supports this. We hypothesise that, given the complexity of the interaction between people and place, the relative contribution of density and crowding to the spread of infectious diseases may be contingent on local factors. To directly compare the role of urban density and household overcrowding, we examine each in relation to COVID-19 incidence in the three largest cities in Australia, Sydney, Melbourne and Brisbane, as the pandemic unfolded from July 2021 to January 2022. Using ecological models adjusted for spatial autocorrelation and area-level measures of age and socio-economic factors, we assess the association between population density, overcrowding in homes, and COVID-19 infections in local neighbourhoods. Challenging prevailing assumptions, we find evidence for an effect of both density and overcrowding on COVID-19 infections depending on the city and area within cities; that is, depending on the local context. For example, in the southwestern suburbs of Sydney, the case rate decreases by between 0.4 and 6.4 with every one-unit increase in gross density however the case rate increases by between 0.01 and 9.6 with every one-unit increase in total overcrowding. These findings have important implications for developing pandemic response strategies: public health measures that target either density (e.g., lockdowns and restricted range of travel) or overcrowding (e.g., restricting number of people relative to dwelling, mask-wearing indoors, vaccination prioritisation) must be cognisant of the geographically local contexts in which they are implemented.

Mental illness and increased vulnerability to negative health effects from extreme heat events: a systematic review.

RATIONALE: Across countries, extreme heat events are projected to increase in frequency and intensity because of climate change. Exposure to extreme heat events can have a substantial negative impact on human health, and extant research suggests that individuals with mental illness are particularly vulnerable. To date, there has been no review of evidence regarding this vulnerability to inform response strategies and future research. OBJECTIVE: A systematic review was undertaken to investigate mental illness as an effect modifier of the relationship between heat exposure and morbidity or mortality. METHODS: Six databases (Medline, Embase, Global Health, PsychInfo, CINAHL and Scopus) were searched for studies published between the years 2000 to 2022. Twenty-two observational studies that met the inclusion criteria were investigated through narrative synthesis. The RoBANS tool, ROBIS and GRADE were used to assess the certainty of evidence including the risk of bias. RESULTS: Individuals with mental illness experience worse morbidity and mortality outcomes compared to their counterparts without mental illness in all studies investigating high temperature over a single day. This did not hold for studies examining heatwaves, which reported mixed findings. CONCLUSIONS AND IMPLICATIONS: People with diagnosed mental illness should be targeted for policy and service attention during high temperature days. Further research should investigate specific mental illness and adjust for a wider range of confounding factors.

Housing typologies and asthma: a scoping review.

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.

Green and blue spaces, COVID-19 lockdowns, and mental health: An Australian population-based longitudinal analysis.

Australia experienced some of the world's longest and most stringent lockdowns during the COVID-19 pandemic. While lockdown measures had consequences for mental health, investigation is lacking on the potential for green and blue space coverage within people's local environments to ameliorate the impact of lockdowns with varied lengths using longitudinal cohorts. This study examined the impact of lockdown durations on population mental health and tests the effect modification of neighbourhood green and inland and coastal blue space coverage in metropolitan areas. We merged population-based longitudinal data on more than 11,000 individuals collected over a ten-year period from 2012 to 2021 with national land use data describing green and blue space coverage. We used fixed effect models to estimate the relationship between lockdowns (with different durations and staggered introduction) and mental health, controlling for sociodemographic, health, and geographical confounders, and tested the significance of effect modification of green and blue space. Results show that extended lockdowns led to considerably larger decreases in mental health (COVID-y1: -2.66, 95%CI: -3.43, -1.89; COVID-y2: -2.65, 95%CI: -3.33, -1.97) relative to short lockdowns. The mental health effect of lockdowns was smaller where green spaces and inland and coastal blue spaces were available. Effect modification was statistically significant for green space, with smaller negative mental health effects observed where there was sizeable green space coverage, particularly during long lockdowns (COVID-y1: -2.69, 95%CI: -3.63, -1.76 for coverage <5%; -3.27, 95%CI: -4.70, -1.84 for coverage 5%-10%; -0.60, 95%CI: -2.03, 0.83 for coverage ≥30%; COVID-y2: -2.74, 95%CI: -3.62, -1.87 for coverage <5%, -2.95, 95%CI: -3.98, -1.92 for coverage 5%-10%; -2.08, 95%CI: -3.28, -0.88 for coverage ≥30%). Findings support the consideration of nature exposure to improve people's mental wellbeing and resilience when designing lockdown measures in response to future public health emergencies.

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.