Housing Crowding Research Articles

Social inequalities in health within the City of Milan (Lombardy Region, Northern Italy): An ecological assessment.

to document existing geographical inequalities in health in the city of Milan (Lombardy Region, Northern Italy), examining the association between area socioeconomic disadvantage and health outcomes, with the aim to suggest policy action to tackle them. the analysis used an ecological framework; multiple health indicators were considered in the analysis; socioeconomic disadvantage was measured through indicators such as low education, unemployment, immigration status, and housing crowding. For each municipal statistical area, Bayesian Relative Risks of the outcomes (using the Besag-Yorkand-Mollié model) were plotted on the city map. To evaluate the association between social determinants and health outcomes, Spearman correlation coefficients were estimated. residents in the City of Milan aged between 30 and 75 years who were residing in Milan as of 01.01.2019, grouped in 88 statistical areas. all-cause mortality, type-2 diabetes mellitus, hypertension, neoplasms, respiratory diseases, metabolic syndrome, antidepressants use, polypharmacy, and multimorbidity. the results consistently demonstrated a significant association between socioeconomic disadvantage and various health outcomes, with low education exhibiting the strongest correlations. Neoplasms displayed an inverse social gradient, while the relationship with antidepressant use varied. these findings provide valuable insights into the distribution of health inequalities in Milan and contribute to the existing literature on the social determinants of health. The study highlights the need for targeted interventions to address disparities and promote equitable health outcomes. The results can serve to inform the development of effective public health strategies and policies aimed at reducing health inequalities in the city.

Tokyo's COVID-19: An urban perspective on factors influencing infection rates in a global city

This research investigates the relationship between COVID-19 and urban factors in Tokyo. To understand the spread dynamics of COVID-19, the study examined 53 urban variables (including population density, socio-economic status, housing conditions, transportation, and land use) in 53 municipalities of Tokyo prefecture. Using spatial models, the study analysed the patterns and predictors of COVID-19 infection rates. The findings revealed that COVID-19 cases were concentrated in central Tokyo, with clustering levels decreasing after the outbreaks. COVID-19 infection rates were higher in areas with a greater density of retail stores, restaurants, health facilities, workers in those sectors, public transit use, and telecommuting. However, household crowding was negatively associated. The study also found that telecommuting rate and housing crowding were the strongest predictors of COVID-19 infection rates in Tokyo, according to the regression model with time-fixed effects, which had the best validation and stability. This study's results could be useful for researchers and policymakers, particularly because Japan and Tokyo have unique circumstances, as there was no mandatory lockdown during the pandemic.

Respiratory health and its determinants among Nunavimmiut: results from the Qanuilirpitaa? 2017 Nunavik Health Survey

ObjectivesRespiratory diseases are the leading cause of hospitalization in Nunavik (northern Québec, Canada) and contribute to disparities in life expectancy with the rest of Canada. As part of Qanuilirpitaa? 2017, a cross-sectional population-based health survey, we sought to describe the prevalence of respiratory health indicators, including the first estimate of airway obstruction based on spirometry in an Inuit population, and explore their associated characteristics.MethodsWe analyzed data from 1296 participants aged 16 years and older, using multivariate logistic regression to assess characteristics associated with spirometry-determined airway obstruction and self-reported respiratory symptoms, i.e., wheezing in the last year and chronic cough during at least 3 months.ResultsIn this relatively young population (83% aged 16 to 54), the prevalences of wheezing, chronic cough, and airway obstruction were, respectively, 27% (95% CI 24–30), 21% (18–23), and 17% (14–20). These estimates are prone to biases due to the relatively low participation rate (about 37%). The most consistent associations were with smoking (≥ 15 pack-years; odds ratio [OR] 3.13, 3.39, and 2.86 for the three indicators, respectively) and food security (OR 0.55 with wheezing and OR 0.26 with chronic cough), as defined in the Household Food Security Survey Module. Wheezing was also associated with allergic sensitization to dogs (2.60) and obesity (2.18). Chronic cough was associated with respiratory infections during childhood (2.12), housing in need of major repairs (1.72), and housing crowding (1.50), and was negatively associated with participation to traditional activities (0.62) and going on the land (0.64). Airway obstruction was associated with being underweight (3.84) and post-secondary education (0.40). Among young adults and women, wheezing was also associated with any inhalation of solvents for recreational purposes during their lifetime (2.62 and 1.56, respectively), while airway obstruction was associated with regular marijuana use (2.22 and 1.84, respectively).ConclusionSmoking and food insecurity are both highly prevalent and strongly associated with respiratory symptoms in Nunavik. Together with essential smoking prevention and cessation programs, our findings suggest that solving food security and housing crises, improving socioeconomic conditions, and promoting traditional lifestyle may improve respiratory health in Nunavik.

Racial and Neighborhood-Level Disparities in COVID-19 Incidence among Patients on Hemodialysis in New York City.

The coronavirus disease 2019 (COVID-19) pandemic has disproportionately affected socially disadvantaged populations. Whether disparities in COVID-19 incidence related to race/ethnicity and socioeconomic factors exist in the hemodialysis population is unknown. Our study involved patients receiving in-center hemodialysis in New York City. We used a validated index of neighborhood social vulnerability, the Social Vulnerability Index (SVI), which comprises 15 census tract-level indicators organized into four themes: socioeconomic status, household composition and disability, minority status and language, and housing type and transportation. We examined the association of race/ethnicity and the SVI with symptomatic COVID-19 between March 1, 2020 and August 3, 2020. COVID-19 cases were ascertained using PCR testing. We performed multivariable logistic regression to adjust for demographics, individual-level social factors, dialysis-related medical history, and dialysis facility factors. Of the 1378 patients on hemodialysis in the study, 247 (17.9%) developed symptomatic COVID-19. In adjusted analyses, non-Hispanic Black and Hispanic patients had significantly increased odds of COVID-19 compared with non-Hispanic White patients. Census tract-level overall SVI, modeled continuously or in quintiles, was not associated with COVID-19 in unadjusted or adjusted analyses. Among non-Hispanic White patients, the socioeconomic status SVI theme, the minority status and language SVI theme, and housing crowding were significantly associated with COVID-19 in unadjusted analyses. Among patients on hemodialysis in New York City, there were substantial racial/ethnic disparities in COVID-19 incidence not explained by neighborhood-level social vulnerability. Neighborhood-level socioeconomic status, minority status and language, and housing crowding were positively associated with acquiring COVID-19 among non-Hispanic Whites. Our findings suggest that socially vulnerable patients on dialysis face disparate COVID-19-related exposures, requiring targeted risk-mitigation strategies.

Association between household overcrowding and depressive mood among Chinese residents

Background: Recent household overcrowding has strongly affected households’ mental health in China. The possible association of household overcrowding and depressive mood is not fully demonstrated in unique Chinese economic context. Objectives: The aim of this study was to examine the association of household overcrowding and depressive mood among Chinese adults and to evaluate whether the association varies across socio-demographic characteristics. Methods: The relationship between household overcrowding and individual's depressive mood was examined using ordered logistic regression models. Stratified analysis was used to evaluate whether the association varies across socio-demographic characteristics. Results: Ordered logistic regression models showed that the odds ratio for depressive mood among residents enduring housing overcrowding, as compared with residents without household overcrowding were 1.12 (95% confidence interval [CI]: 1.02–1.22), after controlling for important confounders. We secondarily examined the association across subgroups. Stratified analysis revealed that household overcrowding significantly affected depressive mood for the low household income subgroups, whereas has no significant effect on depressive mood for the high household income. Limitations: CFPS does not investigate the depression of people under 16, making it impossible for us to study the impacts of housing crowding on Chinese children's depression. Secondly, we did not adjust for other potential confounders, such as lifetime history of depression or depressive mood, medication use and anxiety disorders/symptoms. Conclusions: This finding indicates that household overcrowding is harmful to residents’ mental health, and appropriate protective measures should be taken to reduce the adverse effects of household overcrowding on residents’ mental health.

Assessing the Impact of Individual Characteristics and Neighborhood Socioeconomic Status During the COVID-19 Pandemic in the Provinces of Milan and Lodi.

Social inequalities in health are known to be influenced by the socioeconomic status of the territory in which people live. In the context of the ongoing coronavirus disease 2019 (COVID-19) pandemic, this study is aimed at assessing the role of 5 area-level indicators in shaping the risk of contagion in the provinces of Milan and Lodi (Lombardy, Italy), namely: educational disadvantage, unemployment, housing crowding, mobility, and population density. The study area includes the municipalities at the origin of the first Italian epidemic outbreak. Data on COVID-19 patients from the Integrated Datawarehouse for COVID Analysis in Milan were used and matched with aggregate-level data from the National Institute of Statistics Italy (Istat). Multilevel logistic regression models were used to estimate the association between the census block-level predictors and COVID-19 infection, independently of age, sex, country of birth, and preexisting health conditions. All the variables were significantly associated with the outcome, with different effects before and after the lockdown and according to the province of residence. This suggests a pattern of socioeconomic inequalities in the outbreak, which should be taken into account in the eventuality of future epidemics to contain their spread and its related disparities.

Pandemic Injustice: Spatial and Social Distributions of COVID-19 in the US Epicenter

We examine the uneven social and spatial distributions of COVID-19 and their relationships with indicators of social vulnerability in the U.S. epicenter, New York City (NYC). As of July 17th, 2020, NYC, despite having only 2.5% of the U.S. population, has [Formula: see text]6% of all confirmed cases, and [Formula: see text]16% of all deaths, making it a key learning ground for the social dynamics of the disease. Our analysis focuses on the multiple potential social, economic, and demographic drivers of disproportionate impacts in COVID-19 cases and deaths, as well as population rates of testing. Findings show that immediate impacts of COVID-19 largely fall along lines of race and class. Indicators of poverty, race, disability, language isolation, rent burden, unemployment, lack of health insurance, and housing crowding all significantly drive spatial patterns in prevalence of COVID-19 testing, confirmed cases, death rates, and severity. Income in particular has a consistent negative relationship with rates of death and disease severity. The largest differences in social vulnerability indicators are also driven by populations of people of color, poverty, housing crowding, and rates of disability. Results highlight the need for targeted responses to address injustice of COVID-19 cases and deaths, importance of recovery strategies that account for differential vulnerability, and provide an analytical approach for advancing research to examine potential similar injustice of COVID-19 in other U.S. cities. Significance Statement Communities around the world have variable success in mitigating the social impacts of COVID-19, with many urban areas being hit particularly hard. Analysis of social vulnerability to COVID-19 in the NYC, the U.S. national epicenter, shows strongly disproportionate impacts of the pandemic on low income populations and communities of color. Results highlight the class and racial inequities of the coronavirus pandemic in NYC, and the need to unpack the drivers of social vulnerability. To that aim, we provide a replicable framework for examining patterns of uneven social vulnerability to COVID-19- using publicly available data which can be readily applied in other study regions, especially within the U.S.A. This study is important to inform public and policy debate over strategies for short- and long-term responses that address the injustice of disproportionate impacts of COVID-19. Although similar studies examining social vulnerability and equity dimensions of the COVID-19 outbreak in cities across the U.S. have been conducted (Cordes and Castro 2020,Kim and Bostwick 2002,Gaynor and Wilson 2020; Wang et al. 2020; Choi and Unwin 2020), this study provides a more comprehensive analysis in NYC that extends previous contributions to use the highest resolution spatial units for data aggregation (ZCTAs). We also include mortality and severity rates as key indicators and provide a replicable framework that draws from the Centers for Disease Control and Prevention’s Social Vulnerability indicators for communities in NYC.

Racial Disparities in Frontline Workers and Housing Crowding During COVID-19: Evidence from Geolocation Data

We document that racial disparities in COVID-19 in New York City stem from patterns of commuting and housing crowding. During the initial wave of the pandemic, out- of-home activity related to commuting is strongly associated with COVID-19 cases at the ZIP Code level and hospitalization at an individual level. After layoffs of essential workers decreased commuting, case growth continued through household crowding. A larger share of individuals in crowded housing or commuting to essential work are Black, Hispanic, and lower-income. As a result, structural inequalities, rather than population density, help determine the cross-section of COVID-19 risk exposure in urban areas.

Pediatric Asthma Health Disparities: Race, Hardship, Housing, and Asthma in a National Survey

ObjectiveWe sought to determine if racial disparities in pediatric asthma are explained by material hardship and home ownership. MethodsWe performed a secondary analysis of the 2011 American Housing Survey. A total of 33,201 households with children age 6 to 17 years were surveyed regarding childhood asthma diagnosis and emergency department (ED) visits for asthma (for the youngest child with asthma in the household). Material hardship included poor housing quality, housing crowding, lack of amenities, and no vehicle access. We used logistic regression to determine the association between race, material hardship, and asthma diagnosis or ED visits, adjusting for potential confounders. ResultsNon-Hispanic black heads of household had a higher odds of having a child diagnosed with asthma in the home compared with non-Hispanic white heads of household (odds ratio, 1.72; 95% confidence interval [CI], 1.50–1.96), and a higher odds of ED visits for asthma (odds ratio, 3.02; 95% CI, 2.29–3.99). The race–asthma association was decreased but not eliminated after adjusting for material hardship and home ownership (ED visit adjusted odds ratio [AOR], 2.07; 95% CI, 1.50–2.86). Poor housing quality was independently associated with asthma diagnosis (AOR, 1.45; 95% CI, 1.28–1.66) and ED visits (AOR, 1.59; 95% CI, 1.21–2.10). Home ownership was associated with a lower odds of asthma-related ED visits (AOR, 0.62; 95% CI, 0.46–0.84). ConclusionsObserved racial disparities in pediatric asthma are lessened after controlling for material hardship. Poor housing quality in particular is strongly associated with asthma morbidity. Policy makers could target improving housing quality as a means of potentially reducing asthma disparities.

Co-sleeping in school-aged children with a motor disability: a comparative population-based study.

To determine the prevalence and determinants of co-sleeping in school-aged children with a motor disability compared with the school-aged general population. A questionnaire on demographic characteristics and co-sleeping habits, along with the Sleep Disturbance Scale for Children (SDSC), was sent to parents of children aged between 4 years and 18 years followed in our tertiary paediatric neurorehabilitation clinic, and to school-aged children in a representative sample of state schools. We analysed responses for 245 children with motor disability (142 males, 103 females; mean age 10y 6mo, standard deviation [SD] 3y 10mo, range 4-18y) and 2891 of the general population (1484 males, 1497 females; mean age [SD] 9y 6mo [3y 5mo], range 4-18y) (response rates 37% and 26% respectively). Cerebral palsy was the most common diagnosis among children with motor disability. Weekly co-sleeping was significantly more common in children with motor disability than in the general population (11.8% vs 7.9% respectively, p=0.032). Special care of the child with motor disability at night, mainly addressing epilepsy, was reported as a cause of co-sleeping by two-thirds of parents. Factors associated with co-sleeping in the motor disability group were age, housing crowding, severe visual impairment, and pathological sleep according to the SDSC. Co-sleeping is common among children with motor disability. It is influenced by personal and medical factors, as well as the requirements for special care at night. Therefore, health professionals should explore sleeping arrangements in families of children with motor disability.

The influence of housing characteristics on rural migrants’ living condition in Beijing Fengtai District

The study analyzes the influence of housing characteristics on rural migrants’ living condition in Beijing Fengtai District, China. The researcher will identify rural migrants in Beijing, examine their housing characteristics (housing crowding, housing privacy and housing facility) and the influence on their living condition. Also, some suggestions are given to improve their housing characteristics and living condition. The government should revise the migrant housing policy and hukou management. Also, the rural migrants should try to increase their education level and social skills. For the occupation, the local government should give the rural migrants more job opportunity. These issues are analyzed in relation to local government attitudes toward the rural migrants. The analysis is based on data collected from two types of interviews: rural migrants and management interviews which examine the rural migrants’ housing and managerial aspects of this research, respectively. It is also supported by the utilization of secondary data. The findings of the study indicate that the rural migrants’ housing characteristics (housing crowding, housing privacy and housing facility) highly influence their living condition in Beijing Fengtai District. Therefore, the local government should give some assistance to this group people in the big cities. This paper reports on the findings of a study to seek acknowledged definitions of the terms Project and Project Management. The study was based on a conventional review and analysis of the definitions from a series of texts.

Housing and neighborhood quality among undocumented Mexican and Central American immigrants

Extensive research has documented the challenges that undocumented immigrants face in navigating U.S. labor markets, but relatively little has explored the impact of legal status on residential outcomes despite their widespread repercussions for social well-being. Using data from the 1996–2008 panels of the Survey of Income and Program Participation to impute documentation status among Mexican and Central American immigrants, we examine group differences in residential outcomes, including homeownership, housing crowding, satisfaction with neighborhood and housing quality, problems with neighborhood crime/safety, governmental services, and environmental issues, and deficiencies with housing units. Results from our analysis indicate that undocumented householders are far less likely to be homeowners than documented migrants, and also live in more crowded homes, report greater structural deficiencies with their dwellings, and express greater concern about the quality of public services and environmental conditions in their neighborhoods. In comparison to native whites, undocumented migrants’ residential circumstances are lacking, but their residential outcomes tend to be superior to those of native-born blacks. Overall, our results highlight the pervasive impact of legal status on stratifying Mexicans’ and Central Americans’ prospects for successful incorporation, but also underscore the rigidity of the black/nonblack divide structuring American residential contexts.

Housing crowding effects on children’s wellbeing

The degree to which children grow up in crowded housing is a neglected but potentially important aspect of social inequality. Poor living conditions can serve as a mechanism of social stratification, affecting children’s wellbeing and resulting in the intergenerational transmission of social inequality. This paper reports an investigation of housing crowding on children’s academic achievement, behavior, and health in the US and Los Angeles, a city with atypically high levels of crowding. We use data from the Panel Study of Income Dynamics’ Child Development Supplement and the Los Angeles Family and Neighborhood Survey to explore the effect of living in a crowded home on an array of child wellbeing indicators. We find that several dimensions of children’s wellbeing suffer when exposed to crowded living conditions, particularly in Los Angeles, even after controlling for socioeconomic status. The negative effects on children raised in crowded homes can persist throughout life, affecting their future socioeconomic status and adult wellbeing.

Subtenures and Housing Outcomes for Low Income Renters in New York City

New York has devised a variety of policy approaches to improve the housing status of low-income households, including public housing, publicly subsidized private housing, rent vouchers, welfare shelter allowances, rent regulation, and tax incentives to landlords. Little systematic attention has been paid to how these various subtenures compare when judged by the housing outcomes they produce for low-income households in the city. Using data from the 1996 New York City Housing and Vacancy Survey, this article compares New York City’s rental subtenures in terms of the following outcomes: housing quality, crowding, affordability, residential mobility/stability, and various indicators of neighborhood quality. Adjusting for differences in household and housing stock characteristics, we find that the tenant-based Section 8 program seems to produce the best set of overall outcomes for low-income renters in the city.

Where the homeless come from: A study of the prior address distribution of families admitted to public shelters in New York City and Philadelphia

Abstract This study investigates hypotheses regarding the association of census tract variables with the risk for homelessness. We used prior address information reported by families entering emergency shelters in two large U.S. cities to characterize the nature ofthat distribution. Three dense clusters of homeless origins were found in Philadelphia and three in New York City, accounting for 67 percent and 61 percent of shelter admissions and revealing that homeless families’ prior addresses are more highly concentrated than the poverty distribution in both cities. The rate of shelter admission is strongly and positively related to the concentration of poor, African‐American, and female‐headed households with young children in a neighborhood. It is also correlated with fewer youth, elderly, and immigrants. Such areas have higher rates of unemployment and labor force nonpartici‐pation, more housing crowding, more abandonment, higher rates of vacancy, and higher rent‐to‐income ratios than other areas.