Dataset Information

Associations between neighborhood built environment and cognition vary by apolipoprotein E genotype: Multi-Ethnic Study of Atherosclerosis.

ABSTRACT: We examined whether neighborhood built environment (BE) and cognition associations in older adults vary by apolipoprotein E (APOE) genotype, a genetic risk factor for Alzheimer's disease (AD). We conducted a cross-sectional analysis of 4091 participants. Neighborhood characteristics included social and walking destination density (SDD, WDD), intersection density, and proportion of land dedicated to retail. Individuals were categorized as APOE ?2 (lower AD risk), APOE ?4 (higher AD risk), or APOE ?3 carriers. Among APOE ?2 carriers, greater proportion of land dedicated to retail was associated with better global cognition, and greater SDD, WDD, intersection density, and proportion of land dedicated to retail was associated with better processing speed. These associations were not observed in APOE ?3 or ?4 carriers. APOE ?2 carriers may be more susceptible to the potentially beneficial effects of denser neighborhood BEs on cognition; however, longitudinal studies are needed.

SUBMITTER: Besser L

PROVIDER: S-EPMC6901106 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

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Associations between neighborhood built environment and cognition vary by apolipoprotein E genotype: Multi-Ethnic Study of Atherosclerosis.

Besser Lilah L Galvin James E JE Rodriguez Daniel D Seeman Teresa T Kukull Walter W Rapp Stephen R SR Smith Jennifer J

Health & place 20191129

We examined whether neighborhood built environment (BE) and cognition associations in older adults vary by apolipoprotein E (APOE) genotype, a genetic risk factor for Alzheimer's disease (AD). We conducted a cross-sectional analysis of 4091 participants. Neighborhood characteristics included social and walking destination density (SDD, WDD), intersection density, and proportion of land dedicated to retail. Individuals were categorized as APOE ε2 (lower AD risk), APOE ε4 (higher AD risk), or APOE ...[more]

PMID: 31797769

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Project description:BackgroundTransport walking has drawn growing interest due to its potential to increase levels of physical activities and reduce reliance on vehicles. While existing studies have compared built environment-health associations between Euclidean buffers and network buffers, no studies have systematically quantified the extent of bias in health effect estimates when exposures are measured in different buffers. Further, prior studies have done the comparisons focusing on only one or two geographic regions, limiting generalizability and restricting ability to test whether direction or magnitude of bias are different by context. This study aimed to quantify the degree of bias in associations between built environment exposures and transport walking when exposures were operationalized using Euclidean buffers rather than network buffers in diverse contexts.MethodsWe performed a simulations study to systematically evaluate the degree of bias in associations between built environment exposures in Euclidean buffers and network buffers and transport walking, assuming network buffers more accurately captured true exposures. Additionally, we used empirical data from a multi-ethnic, multi-site cohort to compare associations between built environment amenities and walking for transport where built environment exposures were derived using Euclidean buffers versus network buffers.ResultsSimulation results found that the bias induced by using Euclidean buffer models was consistently negative across the six study sites (ranging from -80% to -20%), suggesting built environment exposures measured using Euclidean buffers underestimate health effects on transport walking. Percent bias was uniformly smaller for the larger 5 km scale than the 1 km and 0.25 km spatial scales, independent of site or built environment categories. Empirical findings aligned with the simulation results: built environment-health associations were stronger for built environment exposures operationalized using network buffers than using Euclidean buffers.ConclusionThis study is the first to quantify the extent of bias in the magnitude of the associations between built environment exposures and transport walking when the former are measured in Euclidean buffers vs. network buffers, informing future research to carefully conceptualize appropriate distance-based buffer metrics in order to better approximate real geographic contexts. It also helps contextualize existing research in the field that used Euclidean buffers when that were the only option. Further, this study provides an example of the uncertain geographic context problem.

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

Associations between neighborhood built environment and cognition vary by apolipoprotein E genotype: Multi-Ethnic Study of Atherosclerosis.

Publications

Associations between neighborhood built environment and cognition vary by apolipoprotein E genotype: Multi-Ethnic Study of Atherosclerosis.

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