Cityscape最新文献

For more than a decade, the U.S. Department of Housing and Urban Development (HUD) and the National Center for Health Statistics (NCHS) have partnered to link NCHS national health survey data with HUD administrative records on persons participating in federal public and assisted housing programs. This study used 2015-18 National Health Interview Survey (NHIS)-HUD linked data to examine women 18-44 years old with children and renting their home who were receiving HUD assistance (n=852) and a comparison population of women of the same age with children, who were low-income renters but did not link to HUD records at the time of their NHIS interview (n=894). The population of HUD-assisted women differed from the comparison group on key sociodemographic characteristics and health indicators. HUD-assisted women were more likely to report their health as fair or poor and to being a current smoker. HUD-assisted women also were less likely to be uninsured and more likely to have a regular source of care. The findings in this article are exploratory but demonstrate how the NCHS-HUD-linked data can be a resource for researchers and policymakers in further examining housing status as an important social determinant of health.

An increasing number of American renters within major metropolitan housing markets rely on online platforms such as Craigslist to find rental units. Landlords that advertise rentals on these websites have been found to tailor the language used in their listings in reference to surrounding neighborhood demographics to influence prospective tenants' rental searches. This work investigates the underexplored subject of move-in fees, referring to upfront costs to secure a lease, such as security deposits, application charges, and advanced rent payments that can affect whether a prospective renter can afford an advertised unit. This study advances a framework for how housing researchers can assess variations in landlord discourse within online housing marketplaces using text analysis methods and web scraping. It then illustrates how the resulting measures about move-in fees have distinct variations in prevalence along sociodemographic, spatial, and policy measures through a series of descriptive analyses, with subsequent conclusions toward policy implications designed to assist low-income renters with overcoming financial barriers in securing rental housing.

Research on rental housing markets in the United States has traditionally relied on national or local housing surveys. Those sources lack temporal and spatial specificity, limiting their use for tracking short-term changes in local markets. As rental housing ads have transitioned to digital spaces, a growing body of literature has utilized web scraping to analyze listing practices and variations in rental market dynamics. Those studies have primarily relied on one platform, Craigslist, as a source of data. Despite Craigslist's popularity, the authors contend that rental listings from various websites, rather than from individual ones, provide a more comprehensive picture. Using a mixed-methods approach to study listings across various platforms in five metropolitan areas, this article demonstrates considerable variation in both the types of rental units advertised and the features provided across those platforms. The article begins with an account of the birth and consolidation of online rental platforms and emergent characteristics of several selected websites, including the criteria for posting, search parameters, search results priority, and first-page search results. Visualizations are used to compare features such as the 40th percentile of rent, rent distribution, and bedroom size based on scraped data from six online platforms (Padmapper, Forrent.com, Trulia, Zillow, Craigslist, and GoSection8), 2020 Fair Market Rents, and 2019 American Community Survey data. The analyses indicate that online listing platforms target different audiences and offer distinct information on units within those market segments, resulting in markedly different estimates of local rental costs and unit size distribution depending on the platform.

The number of highly destructive disasters is increasing in regions of the United States where the Hispanic population is growing fastest. Up-to-date studies of disaster preparedness are needed that include housing measures and other factors that may account for differences in disaster preparedness between Hispanics and other racial and ethnic groups. This study fills this gap in the literature by using data from the 2017 American Housing Survey, which includes a topical module on disaster planning along with the core measures of housing and neighborhood characteristics, including housing tenure. The results reveal that Hispanics are generally less prepared than non-Hispanic Whites regarding resource- and action-based measures, with a few exceptions. Hispanics, Blacks, and Asians are significantly more likely than Whites to have at least 3 gallons of water per person, and Hispanics and Blacks are significantly more likely than Whites and Asians to have flood insurance. The findings show that housing and residential characteristics are consistently significant in predicting preparedness-controlling for other relevant variables-although they do not attenuate the disadvantages that Hispanics and Blacks face in their disaster preparedness relative to Whites. Future research would benefit from further exploration of the linkage between racial and ethnic inequalities in housing and neighborhood characteristics and household disaster preparedness.