Unhealthy behaviours in urban Illinois communities affected by eviction: A descriptive analysis

Hazekamp, Corey; Yousuf, Sana; Khare, Manorama M.; MacDowell, Martin

doi:10.1111/hsc.13312

Cited by 6 publications

(4 citation statements)

References 34 publications

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“…In addition, cost-driven moves may necessitate compromises (eg, working more hours, reducing certain expenses, or moving to lower-quality housing or a less desirable neighborhood) that further diminish opportunities for health promotion and social connection, ultimately limiting both general health and physical activity . Although previous research has found an ecological association between neighborhood eviction rates and lower participation in leisure-time exercise, our study is the first, to our knowledge, to find an association between cost-driven moves and diminished physical activity at the individual level.…”

Section: Discussionmentioning

confidence: 61%

Association of Cost-Driven Residential Moves With Health-Related Outcomes Among California Renters

et al. 2023

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ImportanceUnaffordable housing is associated with adverse health-related outcomes, but little is known about the associations between moving due to unaffordable housing and health-related outcomes.ObjectiveTo characterize the association of recent cost-driven residential moves with health-related outcomes.Design, Setting, and ParticipantsThis cross-sectional study involved a weighted multivariable regression analysis of California Health Interview Survey data from January 1, 2011, to December 31, 2017. A population-based sample of 52 646 adult renters and other nonhomeowners in California were included. Data were analyzed from March 2, 2021, to January 6, 2023.ExposureCost-driven moves in the past 3 years relative to no move and to non–cost-driven moves.Main Outcomes and MeasuresFive outcomes were assessed: psychological distress (low, moderate, or severe, as categorized by the 6-item Kessler Psychological Distress Scale), emergency department [ED] visits in the past year (any vs none), preventive care visits in the past year (any vs none), general health (poor or fair vs good, very good, or excellent), and walking for leisure in the past 7 days (in minutes).ResultsAmong 52 646 adult renters and other nonhomeowners, 50.3% were female, 85.2% were younger than 60 years, 45.3% were Hispanic, and 55.1% had income lower than 200% of the federal poverty level. Overall, 8.9% of renters reported making a recent cost-driven move, with higher prevalence among Hispanic (9.9%) and non-Hispanic Black (11.3%) renters compared with non-Hispanic White renters (7.2%). In multivariable models, compared with not moving, cost-driven moving was associated with a 4.2 (95% CI, 2.6-5.7) percentage point higher probability of experiencing moderate psychological distress; a 3.2 (95% CI, 1.9-4.5) percentage point higher probability of experiencing severe psychological distress; a 2.5 (95% CI, 0-4.9) percentage point higher probability of ED visits; a 5.1 (95% CI, 1.6-8.6) percentage point lower probability of having preventive care visits; a 3.7 (95% CI, 1.2-6.2) percentage point lower probability of having good, very good, or excellent general health; and 16.8 (95% CI, 6.9-26.6) fewer minutes of walking for leisure. General health, psychological distress, and walking for leisure were also worse with cost-driven moves relative to non–cost-driven moves, with a 3.2 (95% CI, 1.7-4.7) percentage point higher probability of experiencing moderate psychological distress; a 2.5 (95% CI, 1.2-3.9) percentage point higher probability of experiencing severe psychological distress; a 4.6 (95% CI, 2.1-7.2) percentage point lower probability of having good, very good, or excellent general health; and 13.0 (95% CI, 4.0-21.9) fewer minutes of walking for leisure. However, the incidence of preventive care and ED visits did not differ between those who made cost-driven vs non–cost-driven moves.Conclusions and RelevanceIn this study, cost-driven moves were associated with adverse health-related outcomes relative to not moving and to non–cost-driven moves. These findings suggest that policies to improve housing affordability, prevent displacement, and increase access to health care for groups vulnerable to cost-driven moves may have the potential to improve population health equity, especially during the current national housing affordability crisis.

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Section: Discussionmentioning

confidence: 61%

Association of Cost-Driven Residential Moves With Health-Related Outcomes Among California Renters

et al. 2023

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“…Six studies investigating the association between population-level eviction or foreclosure rates and weight produced mixed results. Hazekamp et al found that the prevalence of obesity, as well as other unhealthy behavior indicators (i.e., binge drinking, current smoking status, lack of leisure-time physical activity, and short sleep), was associated with census-level eviction rates in urban Illinois communities [ 87 ]. Another cross-sectional study found that foreclosures in 75 of the top 100 most populous metropolitan areas in the United States were independently associated with obesity prevalence [ 89 ].…”

Section: Resultsmentioning

confidence: 99%

Housing instability and cardiometabolic health in the United States: a narrative review of the literature

Faulkner

Thorndike

2023

BMC Public Health

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Housing instability is variably defined but generally encompasses difficulty paying rent, living in poor or overcrowded conditions, moving frequently, or spending the majority of household income on housing costs. While there is strong evidence that people experiencing homelessness (i.e., lack of regular housing) are at increased risk for cardiovascular disease, obesity, and diabetes, less is known about housing instability and health. We synthesized evidence from 42 original research studies conducted in the United States examining the association of housing instability and cardiometabolic health conditions of overweight/obesity, hypertension, diabetes, and cardiovascular disease. The included studies varied widely in their definitions and methods of measuring housing instability, but all exposure variables were related to housing cost burden, frequency of moves, living in poor or overcrowded conditions, or experiencing eviction or foreclosure, measured at either the individual household level or at a population level. We also included studies examining the impact of receipt of government rental assistance, which serves as a marker of housing instability given that its purpose is to provide affordable housing for low-income households. Overall, we found mixed but generally adverse associations between housing instability and cardiometabolic health, including higher prevalence of overweight/obesity, hypertension, diabetes, and cardiovascular disease; worse hypertension and diabetes control; and higher acute health care utilization among those with diabetes and cardiovascular disease. We propose a conceptual framework for pathways linking housing instability and cardiometabolic disease that could be targeted in future research and housing policies or programs.

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“…1 b and d). Housing insecurity and unaffordability can lead to stress and despair, as well as alter metabolism and increase the risk of unhealthy behaviors such as smoking and inactivity (Chambers and Fuster 2012 ; Hazekamp et al 2021 ). Little is known about how policy interventions, such as supply-side housing subsidy programs aimed at increasing affordable housing, affect eviction dynamics in communities across the United States (Preston and Reina 2021 ).…”

Section: Discussionmentioning

confidence: 99%

Spatial machine learning for predicting physical inactivity prevalence from socioecological determinants in Chicago, Illinois, USA

Lotfata

Georganos

2023

J Geogr Syst

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The increase in physical inactivity prevalence in the USA has been associated with neighborhood characteristics. While several studies have found an association between neighborhood and health, the relative importance of each component related to physical inactivity or how this value varies geographically (i.e., across different neighborhoods) remains unexplored. This study ranks the contribution of seven socioecological neighborhood factors to physical inactivity prevalence in Chicago, Illinois, using machine learning models at the census tract level, and evaluates their predictive capabilities. First, we use geographical random forest (GRF), a recently proposed nonlinear machine learning regression method that assesses each predictive factor’s spatial variation and contribution to physical inactivity prevalence. Then, we compare the predictive performance of GRF to geographically weighted artificial neural networks, another recently proposed spatial machine learning algorithm. Our results suggest that poverty is the most important determinant in the Chicago tracts, while on the other hand, green space is the least important determinant in the rise of physical inactivity prevalence. As a result, interventions can be designed and implemented based on specific local circumstances rather than broad concepts that apply to Chicago and other large cities. Supplementary Information The online version contains supplementary material available at 10.1007/s10109-023-00415-y.

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Unhealthy behaviours in urban Illinois communities affected by eviction: A descriptive analysis

Cited by 6 publications

References 34 publications

Association of Cost-Driven Residential Moves With Health-Related Outcomes Among California Renters

Association of Cost-Driven Residential Moves With Health-Related Outcomes Among California Renters

Housing instability and cardiometabolic health in the United States: a narrative review of the literature

Spatial machine learning for predicting physical inactivity prevalence from socioecological determinants in Chicago, Illinois, USA

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