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In which neighborhoods are older adult populations expanding?: Sociodemographic and built environment characteristics across neighborhood trajectory classes of older adult populations in four U.S. cities over 30 Years.

ABSTRACT: OBJECTIVES:We sought to examine characteristics of neighborhoods with changing older adult populations. METHODS:We used 30 years (1980-2011) of data from four U.S. cities (n=392 neighborhoods; Birmingham, AL; Chicago, IL; Minneapolis, MN; Oakland, CA) and finite mixture modeling to identify trajectory classes: neighborhoods with "stable", declining, or increasing older adult populations (?65 years). We then compared mean baseline and change in their characteristics. RESULTS:Neighborhoods with increasing (vs. "stable") percentage of older adult populations had lower initial poverty and greater increases in education and income, with lower increases in road connectivity, population density, and housing prices/debt over time. The same was true for neighborhoods with declining older adult populations, with the exception of having higher increases in housing prices/debt. We observed few significant differences in neighborhood amenities or parks across classes. CONCLUSIONS:Our results emphasize the need to consider built and social environments when planning communities for older adults.

SUBMITTER: Rummo PE

PROVIDER: S-EPMC5072399 | biostudies-literature | 2016 Jan-Dec

REPOSITORIES: biostudies-literature

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In which neighborhoods are older adult populations expanding?: Sociodemographic and built environment characteristics across neighborhood trajectory classes of older adult populations in four U.S. cities over 30 Years.

Rummo Pasquale E PE Hirsch Jana A JA Howard Annie Green AG Gordon-Larsen Penny P

Gerontology & geriatric medicine 20160101

<h4>Objectives</h4>We sought to examine characteristics of neighborhoods with changing older adult populations.<h4>Methods</h4>We used 30 years (1980-2011) of data from four U.S. cities (n=392 neighborhoods; Birmingham, AL; Chicago, IL; Minneapolis, MN; Oakland, CA) and finite mixture modeling to identify trajectory classes: neighborhoods with "stable", declining, or increasing older adult populations (≥65 years). We then compared mean baseline and change in their characteristics.<h4>Results</h4 ...[more]

PMID: 27774501

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Project description:BackgroundIn the background of an aging population, the risk of cognitive impairment in the older population is prominent. Exposure to complex neighborhood built environments may be beneficial to the cognitive health of older adults, and the purpose of this study was to systematically review the scientific evidence on the effects of neighborhood built environments on cognitive function in older adults.MethodsKeywords and references were searched in Web of Science, Pubmed, PsycINFO, and MEDLINE. Studies examining the relationship between the built environment and cognitive function in older adults were included. The neighborhood built environment as an independent variable was classified according to seven aspects: density, design, diversity, destination accessibility, public transportation distance, blue/green space, and built environment quality. The cognitive function as the dependent variable was classified according to overall cognitive function, domain-specific cognitive function, and incidence of dementia. The quality of the included literature was assessed using the National Institutes of Health's Observational Cohort and Cross-Sectional Study Quality Assessment Tool.ResultsA total of 56 studies were included that met the inclusion criteria, including 31 cross-sectional studies, 23 longitudinal studies, 1 cross-sectional study design combined with a case-control design, and 1 longitudinal study design combined with a case-control design. Most of the studies reviewed indicate that the built environment factors that were positively associated with cognitive function in older adults were population density, street connectivity, walkability, number of public transportation stops around the residence, land use mix, neighborhood resources, green space, and quality of the neighborhood built environment. Built environment factors that were negatively associated with cognitive function in older adults were street integration, distance from residence to main road. The relationship between residential density, destination accessibility, and blue space with cognitive function in older adults needs to be further explored.ConclusionPreliminary evidence suggests an association between the neighborhood built environment and cognitive function in older adults. The causal relationship between the built environment and cognitive function can be further explored in the future using standardized and combined subjective and objective assessment methods, and longitudinal or quasi-experimental study designs. For public health interventions on the cognitive health of older adults, it is recommended that relevant authorities include the neighborhood built environment in their intervention programs.

Project description:Investments in neighborhood built environments could increase physical activity and overall health. Disproportionate distribution of these changes in advantaged neighborhoods could inflate health disparities. Little information exists on where changes are occurring. This paper aims to 1) identify changes in the built environment in neighborhoods and 2) investigate associations between high levels of change and sociodemographic characteristics. Using Geographic Information Systems, neighborhood land-use, local destinations (for walking, social engagement, and physical activity), and sociodemographics were characterized in 2000 and 2010 for seven U.S. cities. Linear and change on change models estimated associations of built environment changes with baseline (2000) and change (2010-2000) in sociodemographics. Spatial patterns were assessed using Global Moran's I to measure overall clustering of change and Local Moran's I to identify statistically significant clusters of high increases surrounded by high increases (HH). Sociodemographic characteristics were compared between HH cluster and other tracts using Analysis of Variance (ANOVA). We observed small land-use changes but increases in the destination types. Greater increases in destinations were associated with higher percentage non-Hispanic whites, percentage households with no vehicle, and median household income. Associations were present for both baseline sociodemographics and changes over time. Greater increases in destinations were associated with lower baseline percentage over 65 but higher increases in percentage over 65 between 2000 and 2010. Global Moran's indicated changes were spatially clustered. HH cluster tracts started with a higher percentage non-Hispanic whites and higher percentage of households without vehicles. Between 2000 and 2010, HH cluster tracts experienced increases in percent non-Hispanic white, greater increases in median household income, and larger decreases in percent of households without a vehicle. Changes in the built environment are occurring in neighborhoods across a diverse set of U.S. metropolitan areas, but are patterned such that they may lead to increased health disparities over time.

Project description: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. Highlights • Strong, inverse cross-sectional relationships between the built environment, residential property values (a proxy for individual socioeconomic status), and measured BMI were observed.• Measures of the built environment and residential property values showed modest and inconsistent associations with 1- and 2-year BMI change.• There was suggestive evidence that age may moderate the association between urban density and 1- and 2-year BMI change while education may moderate the association between residential property values and 2-year BMI change.

Dataset Information

In which neighborhoods are older adult populations expanding?: Sociodemographic and built environment characteristics across neighborhood trajectory classes of older adult populations in four U.S. cities over 30 Years.

Publications

In which neighborhoods are older adult populations expanding?: Sociodemographic and built environment characteristics across neighborhood trajectory classes of older adult populations in four U.S. cities over 30 Years.

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