Skip to content

Associations between Neighborhood Built Environment, Residential Property Values, and Adult BMI Change: The Seattle Obesity Study III

Buszkiewicz, James H.; Rose, Chelsea M.; Ko, Linda K.; Mou, Jin; Moudon, Anne Vernez; Hurvitz, Philip M.; Cook, Andrea J.; Drewnowski, Adam. (2022). Associations between Neighborhood Built Environment, Residential Property Values, and Adult BMI Change: The Seattle Obesity Study III. SSM-Population Health, 19.

View Publication

Abstract

Objective: To examine associations between neighborhood built environment (BE) variables, residential property values, and longitudinal 1-and 2-year changes in body mass index (BMI). Methods: The Seattle Obesity Study III was a prospective cohort study of adults with geocoded residential addresses, conducted in King, Pierce, and Yakima Counties in Washington State. Measured heights and weights were obtained at baseline (n = 879), year 1 (n = 727), and year 2 (n = 679). Tax parcel residential property values served as proxies for individual socioeconomic status. Residential unit and road intersection density were captured using Euclidean-based SmartMaps at 800 m buffers. Counts of supermarket (0 versus. 1+) and fast-food restaurant availability (0, 1-3, 4+) were measured using network based SmartMaps at 1600 m buffers. Density measures and residential property values were categorized into tertiles. Linear mixed-effects models tested whether baseline BE variables and property values were associated with differential changes in BMI at year 1 or year 2, adjusting for age, gender, race/ethnicity, education, home ownership, and county of residence. These associations were then tested for potential disparities by age group, gender, race/ethnicity, and education. Results: Road intersection density, access to food sources, and residential property values were inversely associated with BMI at baseline. At year 1, participants in the 3rd tertile of density metrics and with 4+ fast-food restaurants nearby showed less BMI gain compared to those in the 1st tertile or with 0 restaurants. At year 2, higher residential property values were predictive of lower BMI gain. There was evidence of differential associations by age group, gender, and education but not race/ethnicity. Conclusion: Inverse associations between BE metrics and residential property values at baseline demonstrated mixed associations with 1-and 2-year BMI change. More work is needed to understand how individual-level sociodemographic factors moderate associations between the BE, property values, and BMI change.

Keywords

Body-mass Index; Physical-activity; Food Environment; Socioeconomic-status; Weight-gain; Health; Quality

Differences in Weight Gain Following Residential Relocation in the Moving to Health (M2H) Study

Cruz, Maricela; Drewnowski, Adam; Bobb, Jennifer F.; Hurvitz, Philip M.; Moudon, Anne Vernez; Cook, Andrea; Mooney, Stephen J.; Buszkiewicz, James H.; Lozano, Paula; Rosenberg, Dori E.; Kapos, Flavia; Theis, Mary Kay; Anau, Jane; Arterburn, David. (2022). Differences in Weight Gain Following Residential Relocation in the Moving to Health (M2H) Study. Epidemiology, 33(5), 747-755.

View Publication

Abstract

Background: Neighborhoods may play an important role in shaping long-term weight trajectory and obesity risk. Studying the impact of moving to another neighborhood may be the most efficient way to determine the impact of the built environment on health. We explored whether residential moves were associated with changes in body weight. Methods: Kaiser Permanente Washington electronic health records were used to identify 21,502 members aged 18-64 who moved within King County, WA between 2005 and 2017. We linked body weight measures to environment measures, including population, residential, and street intersection densities (800 m and 1,600 m Euclidian buffers) and access to supermarkets and fast foods (1,600 m and 5,000 m network distances). We used linear mixed models to estimate associations between postmove changes in environment and changes in body weight. Results: In general, moving from high-density to moderate- or low-density neighborhoods was associated with greater weight gain postmove. For example, those moving from high to low residential density neighborhoods (within 1,600 m) gained an average of 4.5 (95% confidence interval [CI] = 3.0, 5.9) lbs 3 years after moving, whereas those moving from low to high-density neighborhoods gained an average of 1.3 (95% CI = -0.2, 2.9) lbs. Also, those moving from neighborhoods without fast-food access (within 1600m) to other neighborhoods without fast-food access gained less weight (average 1.6 lbs [95% CI = 0.9, 2.4]) than those moving from and to neighborhoods with fast-food access (average 2.8 lbs [95% CI = 2.5, 3.2]). Conclusions: Moving to higher-density neighborhoods may be associated with reductions in adult weight gain.

Keywords

Body-mass Index; Neighborhood Socioeconomic-status; New-york-city; Built Environment; Physical-activity; Food Environment; Urban Sprawl; Risk-factors; Obesity; Walking; Electronic Medical Records; Fast Foods; Population Density; Residential Density; Residential Moves; Supermarkets

Hedonic, Residual, and Matching Methods for Residential Land Valuation

Bourassa, Steven C.; Hoesli, Martin. (2022). Hedonic, Residual, and Matching Methods for Residential Land Valuation. Journal Of Housing Economics, 58.

View Publication

Abstract

• Our first method involves a hedonic model estimated for sales of vacant lots. • Another method depreciates improvements, obtaining land value as a residual. • Our third approach matches the sales of vacant and subsequently developed lots. • This allows us to estimate a hedonic model of land leverage (the ratio of land to total property value) for improved properties. • We conclude that the third approach is the most promising of the three methods. Accurate estimates of land values on a property-by-property basis are an important requirement for the effective implementation of land-based property taxes. We compare hedonic, residual, and matching techniques for mass appraisal of residential land values, using data from Maricopa County, Arizona. The first method involves a hedonic valuation model estimated for transactions of vacant lots. The second approach subtracts the depreciated cost of improvements from the value of improved properties to obtain land value as a residual. The third approach matches the sales of vacant lots with subsequent sales of the same properties once they have been developed. For each pair, we use a land price index to inflate the land price to the time of the improved property transaction and then calculate land leverage (the ratio of land to total property value). A hedonic model is estimated and used to predict land leverage for all improved properties. We conclude that the matching approach is the most promising of the methods considered. [ABSTRACT FROM AUTHOR]; Copyright of Journal of Housing Economics is the property of Academic Press Inc. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Keywords

Hedonic Method; Land Leverage; Land Valuation; Matching Approach; Residual Approach

Housing Cost Burden and Life Satisfaction

Acolin, Arthur; Reina, Vincent. (2022). Housing Cost Burden and Life Satisfaction. Journal Of Housing & The Built Environment, 37(4), 1789-1815.

View Publication

Abstract

The share of income that households spent on their housing has been increasing over time in a wide range of countries, particularly among lower income households. In theory, the share of income spent on housing can reflect variations in household preferences for housing consumption but for low-income household, high burdens are likely more reflective of constraints and force these households to face tradeoffs between housing and non-housing consumption that negatively affect their overall life satisfaction. This paper uses data from the 2018 European Union Statistics on Income and Living Conditions (EU-SILC) for 14 countries. We find that, controlling for household sociodemographic characteristics, households spending more than 30 percent of their income and those spending more than 50 percent of their income on housing report significantly lower levels of life satisfaction. The estimated relationship is largest for this latter heavily cost burdened group. The negative relationship between housing cost burden and reported life satisfaction is found across countries but varies in magnitude, suggesting that stronger welfare systems may mediate the negative impacts of housing cost burdens, although further research is needed to confirm both this relationship and the precise mechanisms driving it.

Keywords

Life Satisfaction; Income; Housing; Poor Communities; Subjective Well-being (psychology); Living Conditions; European Countries; Housing Cost; Subjective Wellbeing; Economic Hardship; Homeownership; Affordability; Determinants; Cost Analysis; Housing Costs; Households; Consumption; Low Income Groups; Expenditures; Welfare; Sociodemographics

Measuring the Housing Sector’s Contribution to GDP in Emerging Market Countries

Acolin, Arthur;hoek-smit, Marja;green, Richard K. (2022). Measuring the Housing Sector’s Contribution to GDP in Emerging Market Countries. International Journal Of Housing Markets And Analysis, 15(5), 977-994.

View Publication

Abstract

Purpose > This paper aims to document the economic importance of the housing sector, as measured by its contribution to gross domestic product (GDP), which is not fully recognized. In response to the joint economic and health crises caused by the COVID-19 pandemic, there is an opportunity for emerging market countries to develop and implement inclusive housing strategies that stimulate the economy and improve community health outcomes. However, so far housing does not feature prominently in the recovery plans of many emerging market countries. Design/methodology/approach > This paper uses national account data and informal housing estimates for 11 emerging market economies to estimate the contribution of housing investments and housing services to the GDP of these countries. Findings > This paper finds that the combined contribution of housing investments and housing services represents between 6.9% and 18.5% of GDP, averaging 13.1% in the countries with information about both. This puts the housing sector roughly on par with other key sectors such as manufacturing. In addition, if the informal housing sector is undercounted in the official national account figures used in this analysis by 50% or 100%, for example, then the true averages of housing investments and housing services’ contribution to GDP would increase to 14.3% or 16.1% of GDP, respectively. Research limitations/implications > Further efforts to improve data collection about housing investments and consumption, particularly imputed rent for owner occupiers and informal activity require national government to conduct regular household and housing surveys. Researcher can help make these surveys more robust and leverage new data sources such as scraped housing price and rent data to complement traditional surveys. Better data are needed in order to capture housing contribution to the economy. Practical implications > The size of the housing sector and its impact in terms of employment and community resilience indicate the potential of inclusive housing investments to both serve short-term economic stimulus and increase long-term community resilience. Originality/value > The role of housing in the economy is often limited to housing investment, despite the importance of housing services and well-documented methodologies to include them. This analysis highlights the importance of housing to the economy of emerging market countries (in addition to all the non-GDP related impact of housing on welfare) and indicate data limitation that need to be addressed to further strengthen the case for focusing on housing as part of economic recovery plans.

Keywords

Pandemics; Economic Importance; Investments; Housing; Sanitation; Recovery; International Organizations; Covid-19; Economic Growth; Data Collection; Economic Indicators; Economics; Housing Conditions; Economic Policy; Economic Conditions; Market Economies; Resilience; Low Income Groups; Economic Activity; Consumption; Emerging Markets; Earthquakes; Surveys; Gross Domestic Product--gdp; Coronaviruses; Affordable Housing; Economic Development; Informal Economy; Households; Recovery Plans; Disease Transmission; Africa; South Africa; India

Opportunity and Housing Access

Acolin, Arthur; Wachter, Susan. (2017). Opportunity and Housing Access. Cityscape, 19(1), 135 – 150.

View Publication

Abstract

This article examines the relationship between employment opportunity and housing affordability. Access to locations with high-productivity jobs is increasingly limited by regional housing affordability barriers. Recent articles demonstrate a new regional divergence in access to high-productivity regions accompanied by declines in worker mobility associated with affordability barriers. We update these findings and discuss their long-term implications for economic opportunity and intergenerational welfare. We show that areas, from which lower-income households are increasingly priced out, are also more likely to have higher levels of intergenerational mobility. Access to opportunity also continues to be challenged within metropolitan areas as the gentrification of downtown neighborhoods is accompanied by an increase in concentrated poverty in outlying city neighborhoods and inner ring suburbs. These trends on regional and local scales derive from the increased importance of place in the knowledge-based economy and interact to reinforce growing spatial inequality. We conclude with a discussion of the importance of identifying place-based solutions to counter growing spatial inequality of opportunity.]

Moving to Shared Equity: Locational Outcomes for Households in Shared Equity Homeownership Programs

Ramiller, Alex; Acolin, Arthur; Walter, Rebecca J.; Wang, Ruoniu. (2022). Moving to Shared Equity: Locational Outcomes for Households in Shared Equity Homeownership Programs. Housing Studies, 44586.

View Publication

Abstract

Abstract The impact of U.S. housing policy on household locational outcomes has primarily been studied in the context of rental housing assistance programs, but the impact of alternative homeownership models is less fully explored. In this study, we assess residential trajectories for households that have participated in shared-equity homeownership (SEH) programs such as Community Land Trusts and Limited Equity Housing Cooperatives. We examine changes in neighborhood characteristics that occur when households enter and exit SEH units, and compare those outcomes with similar households that entered traditional homeownership or continued to rent. We find that while entering SEH is associated with decreases in neighborhood opportunity measures, exiting SEH is associated with improvements in key measures including lower concentrations of poverty. We conclude that while entering SEH may entail moving to lower-opportunity neighborhoods, participation in SEH programs increases the long-term economic and socio-spatial mobility of participating households by enabling them to access a broader array of neighborhood contexts in their subsequent move. [ABSTRACT FROM AUTHOR]; Copyright of Housing Studies is the property of Routledge and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Keywords

Community Land Trusts; Geographies Of Opportunity; Locational Outcomes; Residential Mobility; Shared-equity Homeownership

Borrowing Constraints and Homeownership

Acolin, Arthur; Bricker, Jesse; Calem, Paul; Wachter, Susan. (2016). Borrowing Constraints and Homeownership. The American Economic Review, 106(5), 625 – 629.

View Publication

Keywords

Borrowing Constraints, Homeownership, Credit Supply

Racial Disparity in Exposure to Housing Cost Burden in the United States: 1980-2017

Hess, Chris; Colburn, Gregg; Crowder, Kyle; Allen, Ryan. (2022). Racial Disparity in Exposure to Housing Cost Burden in the United States: 1980-2017. Housing Studies, 37(10), 1821-1841.

View Publication

Abstract

This article uses the Panel Study of Income Dynamics to analyse Black–White differences in housing cost burden exposure among renter households in the USA from 1980 to 2017, expanding understanding of this phenomenon in two respects. Specifically, we document how much this racial disparity changed among renters over almost four decades and identify how much factors associated with income or housing costs explain Black–White inequality in exposure to housing cost burden. For White households, the net contribution of household, neighbourhood and metropolitan covariates accounts for much of the change in the probability of housing cost burden over time. For Black households, however, the probability of experiencing housing cost burden continued to rise throughout the period of this study, even after controlling for household, neighbourhood and metropolitan covariates. This suggests that unobserved variables like racial discrimination, social networks or employment quality might explain the increasing disparity in cost burden among for Black and White households in the USA.

Keywords

Housing; Racial Inequality; Households; Neighborhoods; Social Networks; Cost Burden; Housing Cost; Employment Discrimination; Housing Costs; Racial Discrimination; Social Factors; Dynamic Tests; Black White Differences; Tenants; Income Inequality; Race Factors; Social Organization; Cost Analysis; Black People; Racial Differences; Income; Exposure; Inequality; Social Interactions; Employment; United States--us