Neighborhood built and food environment in relation to glycemic control in people with type 2 diabetes in the moving to health study.

OBJECTIVE: To examine whether built environment and food metrics are associated with glycemic control in people with type 2 diabetes. RESEARCH DESIGN AND METHODS: We included 14,985 patients with type 2 diabetes using electronic health records from Kaiser Permanente Washington. Patient addresses were geocoded with ArcGIS using King County and Esri reference data. Built environment exposures estimated from geocoded locations included residential unit density, transit threshold residential unit density, park access, and having supermarkets and fast food restaurants within 1600-m Euclidean buffers. Linear mixed effects models compared mean changes of HbA1c from baseline at 1, 3 (primary) and 5 years by each built environment variable. RESULTS: Patients (mean age = 59.4 SD = 13.2, 49.5% female, 16.6% Asian, 9.8% Black, 5.5% Latino/Hispanic, 57.1% White, 20% insulin dependent, mean BMI = 32.7±7.7) had an average of 6 HbA1c measures available. Participants in the 1st tertile of residential density (lowest) had a greater decline in HbA1c (-0.42, -0.43, and -0.44 in years 1, 3, and 5 respectively) than those in the 3rd tertile (HbA1c = -0.37 at 1- and 3-years and -0.36 at 5-years; all p-values <0.05). Having any supermarkets within 1600 m of home was associated with a greater decrease in HbA1c at 1-year and 3-years compared to having none (all p-values <0.05). CONCLUSIONS: Lower residential density and better proximity to supermarkets may benefit HbA1c control in people with people with type 2 diabetes. However, effects were small and indicate limited clinical significance.

Gentrification Yields Racial And Ethnic Disparities In Exposure To Contextual Determinants Of Health.

This article examines racial and ethnic disparities in the relationship between gentrification and exposure to contextual determinants of health. In our study, we focused on changes in selected contextual determinants of health (health care access, social deprivation, air pollution, and walkability) and life expectancy during the period 2006-21 among residents of gentrifying census tracts in six large US cities that have experienced different gentrification patterns and have different levels of segregation: Chicago, Illinois; Los Angeles, California; New York, New York; Philadelphia, Pennsylvania; San Francisco, California; and Seattle, Washington. We found that gentrification was associated with overall improvements in the likelihood of living in Medically Underserved Areas across racial and ethnic groups, but it was also associated with increased social deprivation and reduced life expectancy among Black people, Hispanic people, and people of another or undetermined race or ethnicity. In contrast, we found that gentrification was related to better (or unchanged) contextual determinants of health for Asian people and White people. Our findings can inform policies that target communities identified to be particularly at risk for worsening contextual determinants of health as a result of gentrification.

Individualized orthotic alignment and footwear for balance and mobility in children with bilateral spastic cerebral palsy: A randomized trial.

AIM: To examine whether designed-to-be-rigid ankle-foot orthoses and footwear combinations with individualized alignment and footwear designs (AFO-FC/IAFD) would be more effective than designed-to-be-rigid AFO with non-individualized alignment and footwear designs (AFO-FC/NAFD) in children with cerebral palsy (CP). METHOD: Nineteen children with bilateral spastic CP were randomized to AFO-FC/NAFD (n = 10) or AFO-FC/IAFD (n = 9) groups. Fifteen were male, average age 6 years 11 months (range 4 years 2 months-9 years 11 months), classified in Gross Motor Function Classification System levels II (n = 15) and III (n = 4). The Pediatric Balance Scale (PBS), Gait Outcomes Assessment List (GOAL), Patient-Reported Outcomes Measurement Information System (PROMIS), and Orthotic and Prosthetic Users' Survey (OPUS) measures of satisfaction were collected at baseline and after 3 months' wear. RESULTS: Compared with the AFO-FC/NAFD group, those with AFO-FC/IAFD demonstrated greater change in PBS total scores (mean 12.8 [standard deviation 10.5] vs 3.5 [5.8]; p = 0.03) and GOAL total scores (3.5 [5.8] vs -0.44 [5.5]; p = 0.03). There were no significant changes in OPUS or PROMIS scores. INTERPRETATION: After 3 months, individualized orthosis alignment and footwear designs had a greater positive effect on balance and parent-reported mobility than a non-individualized approach. No effect was documented for the PROMIS and OPUS. Results may inform orthotic management for ambulatory children with bilateral spastic CP. WHAT THIS PAPER ADDS: Balance and parent-reported mobility increased more over time for the ankle-foot orthoses and footwear combinations with individualized alignment and footwear designs (AFO-FC/IAFD) group. Changes in balance over time suggest a therapeutic effect of the AFO-FC/IAFD approach.

Neighborhood greenspace and neighborhood income associated with white matter grade worsening: Cardiovascular Health Study.

INTRODUCTION: We examined whether a combined measure of neighborhood greenspace and neighborhood median income was associated with white matter hyperintensity (WMH) and ventricle size changes. METHODS: The sample included 1260 cognitively normal ≥ 65-year-olds with two magnetic resonance images (MRI; ≈ 5 years apart). WMH and ventricular size were graded from 0 (least) to 9 (most) abnormal (worsening = increase of ≥1 grade from initial to follow-up MRI scans). The four-category neighborhood greenspace-income measure was based on median neighborhood greenspace and income values at initial MRI. Multivariable logistic regression tested associations between neighborhood greenspace-income and MRI measures (worsening vs. not). RESULTS: White matter grade worsening was more likely for those in lower greenspace-lower income neighborhoods than higher greenspace-higher income neighborhoods (odds ratio = 1.73; 95% confidence interval = 1.19-2.51). DISCUSSION: The combination of lower neighborhood income and lower greenspace may be a risk factor for worsening white matter grade on MRI. However, findings need to be replicated in more diverse cohorts. HIGHLIGHTS: Population-based cohort of older adults (≥ 65 years) with greenspace and MRI dataCombined measure of neighborhood greenspace and neighborhood income at initial MRIMRI outcomes included white matter hyperintensities (WMH) and ventricular sizeLongitudinal change in MRI outcomes measured approximately 5 years apartWorsening WMH over time more likely for lower greenspace-lower income neighborhoods.

Association of Perceived Neighborhood Environments With Cognitive Function in Older Adults.

The current study examined the associations between perceptions of the social and physical neighborhood environments and cognitive function in older adults. This cross-sectional study analyzed 821 adults aged ≥65 years from the Adult Changes in Thought study. Perceived neighborhood attributes were measured by the Physical Activity Neighborhood Environment Scale. Cognitive function was assessed using the Cognitive Ability Screening Instrument. The associations were tested using multivariate linear regression. One point greater perceived access to public transit was associated with 0.56 points greater cognitive function score (95% confidence interval [CI] [0.25, 0.88]), and an additional one point of perceived sidewalk coverage was related to 0.22 points higher cognitive function score (95% CI [0.00, 0.45]) after controlling for sociodemographic factors. The perception of neighborhood attributes alongside physical infrastructure may play an important role in supporting older adults' cognitive function. [Journal of Gerontological Nursing, 49(8), 35-41.].

Cross-Sectional Study of Location-Based Built Environments, Physical Activity, Dietary Intake, and Body Mass Index in Adult Twins.

We examined relationships between walkability and health behaviors between and within identical twin pairs, considering both home (neighborhood) walkability and each twin's measured activity space. Continuous activity and location data (via accelerometry and GPS) were obtained in 79 pairs over 2 weeks. Walkability was estimated using Walk Score® (WS); home WS refers to neighborhood walkability, and GPS WS refers to the mean of individual WSs matched to every GPS point collected by each participant. GPS WS was assessed within (WHN) and out of the neighborhood (OHN), using 1-mile Euclidean (air1mi) and network (net1mi) buffers. Outcomes included walking and moderate-to-vigorous physical activity (MVPA) bouts, dietary energy density (DED), and BMI. Home WS was associated with WHN GPS WS (b = 0.71, SE = 0.03, p < 0.001 for air1mi; b = 0.79, SE = 0.03, p < 0.001 for net1mi), and OHN GPS WS (b = 0.18, SE = 0.04, p < 0.001 for air1mi; b = 0.22, SE = 0.04, p < 0.001 for net1mi). Quasi-causal relationships (within-twin) were observed for home and GPS WS with walking (ps < 0.01), but not MVPA, DED, or BMI. Results support previous literature that neighborhood walkability has a positive influence on walking.

Time-Varying Food Retail and Incident Disease in the Cardiovascular Health Study.

INTRODUCTION: Natural experiments can strengthen evidence linking neighborhood food retail presence to dietary intake patterns and cardiometabolic health outcomes, yet sample size and follow-up duration are typically not extensive. To complement natural experiment evidence, longitudinal data were used to estimate the impacts of neighborhood food retail presence on incident disease. METHODS: The Cardiovascular Health Study recruited adults aged 65+ years in 1989-1993. Analyses conducted in 2021-2022 included those in good baseline health, with addresses updated annually through the year of death (restricted to 91% who died during >2 decades of cohort follow-up). Baseline and annually updated presence of 2 combined food retail categories (supermarkets/produce markets and convenience/snack focused) was characterized using establishment-level data for 1-km and 5-km Euclidean buffers. Cox proportional hazards models estimated associations with time to each incident outcome (cardiovascular disease, diabetes), adjusting for individual and area-based confounders. RESULTS: Among 2,939 participants, 36% with baseline supermarket/produce market presence within 1 km had excess incident cardiovascular disease (hazard ratio=1.12; 95% CI=1.01, 1.24); the association was attenuated and no longer statistically significant after adjustment for sociodemographic characteristics. Adjusted associations were robustly null for time-varying supermarket/produce market or convenience/fast food retail presence across analyses with outcomes of cardiovascular disease or diabetes incidence. CONCLUSIONS: Food environment changes continue to be studied to provide an evidence base for policy decisions, and null findings in this longitudinal analysis add literature that casts doubt on the sufficiency of strategies targeting food retail presence alone of an elderly cohort for curtailing incident events of clinical importance.

The Availability and Price of Healthy Food in Seattle by Neighborhood Sociodemographic Characteristics.

INTRODUCTION: Unequal access to healthy food in the local food retail environment contributes to diet quality disparities. We assessed whether in-store availability and prices of healthy foods differ by neighborhood-level income and racial and ethnic composition in a representative sample of food stores in Seattle, Washington. METHODS: We developed and validated an in-store survey tool and surveyed 134 stores. We measured availability and prices of 19 items. For each store, we calculated a healthy food availability score (range, 0-25), and mean prices within each category. Using census tract data, we identified the median household income and proportions of Black and Hispanic residents for each store's neighborhood and grouped them by tertiles of these neighborhood characteristics across Seattle census tracts. We used Wald tests to compare mean availability scores and prices between tertiles and applied postestimation weights to reflect store-type distributions within each tertile. RESULTS: Neighborhoods with lower income and a larger proportion of Black residents had lower healthy food availability scores compared with neighborhoods with higher income (8.06 [95% CI, 7.04-9.07] vs 12.40 [95% CI, 10.63-14.17], P < .001) and fewer Black residents (8.88 [95% CI, 7.79-9.98] vs 12.32 [95% CI, 10.51-14.14], P = .003). Availability did not differ by Hispanic population proportions. Mean prices of grains, eggs, and meat were lower in neighborhoods with larger proportions of Black residents. CONCLUSION: We found systematic differences in healthy food availability based on neighborhood-level income and racial composition. In-store assessments of the food retail environment can inform local, tailored strategies to improve healthy food access.

Associations between neighborhood built environment, residential property values, and adult BMI change: The Seattle Obesity Study III.

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.

Geographic ecological momentary assessment methods to examine spatio-temporal exposures associated with marijuana use among young adults: A pilot study.

BACKGROUND: This study demonstrates the use of geographic ecological momentary assessment (GEMA) methods among young adult marijuana users. METHOD: Participants were 14 current marijuana users ages 21-27 living in Greater Seattle, Washington. They completed brief surveys four times per day for 14 consecutive days, including measures of marijuana use and desire to use. They also carried a GPS data logger that tracked their spatial movements over time. RESULTS: Participants completed 80.1% of possible EMA surveys. Using the GPS data, we calculated daily number of exposures to (i.e., within 100-m of) marijuana retail outlets (mean = 3.9 times per day; SD = 4.4) and time spent per day in high poverty census tracts (mean = 7.3 h per day in high poverty census tracts; SD = 5.1). CONCLUSIONS: GEMA may be a promising approach for studying the role spatio-temporal factors play in marijuana use and related factors.

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

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.

Addressing patient's unmet social needs: disparities in access to social services in the United States from 1990 to 2014, a national times series study.

BACKGROUND: To address patient's unmet social needs and improve health outcomes, health systems have developed programs to refer patients in need to social service agencies. However, the capacity to respond to patient referrals varies tremendously across communities. This study assesses the emergence of disparities in spatial access to social services from 1990 to 2014. METHODS: Social service providers in the lower 48 continental U.S. states were identified annually from 1990 to 2014 from the National Establishment Times Series (NETS) database. The addresses of providers were linked in each year to 2010 US Census tract geometries. Time series analyses of annual counts of services per Km2 were conducted using Generalized Estimating Equations with tracts stratified into tertiles of 1990 population density, quartiles of 1990 poverty rate and quartiles of 1990 to 2010 change in median household income. RESULTS: Throughout the period, social service agencies/Km2 increased across tracts. For high population density tracts, in the top quartile of 1990 poverty rate, compared to tracts that experienced the steepest declines in median household income from 1990 to 2010, tracts that experienced the largest increases in income had more services (+ 1.53/Km2, 95% CI 1.23, 1.83) in 1990 and also experienced the steepest increases in services from 1990 to 2010: a 0.09 services/Km2/year greater increase (95% CI 0.07, 0.11). Similar results were observed for high poverty tracts in the middle third of population density, but not in tracts in the lowest third of population density, where there were very few providers. CONCLUSION: From 1990 to 2014 a spatial mismatch emerged between the availability of social services and the expected need for social services as the population characteristics of neighborhoods changed. High poverty tracts that experienced further economic decline from 1990 to 2010, began the period with the lowest access to services and experienced the smallest increases in access to services. Access was highest and grew the fastest in high poverty tracts that experienced the largest increases in median household income. We theorize that agglomeration benefits and the marketization of welfare may explain the emergence of this spatial mismatch.

Associations of cannabis retail outlet availability and neighborhood disadvantage with cannabis use and related risk factors among young adults in Washington State.

BACKGROUND: This study examined associations of local cannabis retail outlet availability and neighborhood disadvantage with cannabis use and related risk factors among young adults. METHODS: Data were from annual cross-sectional surveys administered from 2015 to 2019 to individuals ages 18-25 residing in Washington State (N = 10,009). As outcomes, this study assessed self-reported cannabis use at different margins/frequencies (any past year, at least monthly, at least weekly, at least daily) and perceived ease of access to cannabis and acceptability of cannabis use in the community. Cannabis retail outlet availability was defined as the presence of at least one retail outlet within a 1-kilometer road network buffer of one's residence. Sensitivity analyses explored four other spatial metrics to define outlet availability (any outlet within 0.5-km, 2-km, and the census tract; and census tract density per 1000 residents). Census tract level disadvantage was a composite of five US census variables. RESULTS: Adjusting for individual- and area-level covariates, living within 1-kilometer of at least one cannabis retail outlet was statistically significantly associated with any past year and at least monthly cannabis use as well as high perceived access to cannabis. Results using a 2-km buffer and census tract-level metrics for retail outlet availability showed similar findings. Neighborhood disadvantage was statistically significantly associated with at least weekly and at least daily cannabis use and with greater perceived acceptability of cannabis use. CONCLUSIONS: Results may have implications for regulatory and prevention strategies to reduce the population burden of cannabis use and related harms.

Sweetened beverage taxes: Economic benefits and costs according to household income.

Taxing sweetened beverages has emerged as an important and effective policy for addressing their overconsumption. However, taxes may place a greater economic burden on people with lower incomes. We assess the degree to which sweetened beverage taxes in three large US cities placed an inequitable burden on populations with lower incomes by assessing spending on beverage taxes by income after taxes have been implemented, as well as any net transfer of funds towards lower income populations once allocation of tax revenue is considered. We find that while lower income populations pay a higher percentage of their income in beverage taxes, there is no difference in absolute spending on beverage taxes per capita, and that there is a sizable net transfer of funds towards programs targeting lower income populations. Thus, when considering both population-level taxes paid and sufficiently targeted allocations of tax revenues, a sweetened beverage tax may have characteristics of an equitable public policy.

Walkability measures to predict the likelihood of walking in a place: A classification and regression tree analysis.

Walkability is a popular and ubiquitous term at the intersection of urban planning and public health. As the number of potential walkability measures grows in the literature, there is a need to compare their relative importance for specific research objectives. This study demonstrates a classification and regression tree (CART) model to compare five familiar measures of walkability from the literature for their relative ability to predict whether or not walking occurs in a dataset of objectively measured locations. When analyzed together, the measures had moderate-to-high accuracy (87.8% agreement: 65.6% of true walking GPS-measured points classified as walking and 93.4% of non-walking points as non-walking). On its own, the most well-known composite measure, Walk Score, performed only slightly better than measures of the built environment composed of a single variable (transit ridership, employment density, and residential density).Thus there may be contexts where transparent and longitudinally available measures of urban form are worth a marginal tradeoff in prediction accuracy. This comparison of walkability measures using CART highlights the importance for public health and urban design researchers to think carefully about how and why particular walkability measures are used.

Differential associations of the built environment on weight gain by sex and race/ethnicity but not age.

OBJECTIVE: To explore the built environment (BE) and weight change relationship by age, sex, and racial/ethnic subgroups in adults. METHODS: Weight trajectories were estimated using electronic health records for 115,260 insured Kaiser Permanente Washington members age 18-64 years. Member home addresses were geocoded using ArcGIS. Population, residential, and road intersection densities and counts of area supermarkets and fast food restaurants were measured with SmartMaps (800 and 5000-meter buffers) and categorized into tertiles. Linear mixed-effect models tested whether associations between BE features and weight gain at 1, 3, and 5 years differed by age, sex, and race/ethnicity, adjusting for demographics, baseline weight, and residential property values. RESULTS: Denser urban form and greater availability of supermarkets and fast food restaurants were associated with differential weight change across sex and race/ethnicity. At 5 years, the mean difference in weight change comparing the 3rd versus 1st tertile of residential density was significantly different between males (-0.49 kg, 95% CI: -0.68, -0.30) and females (-0.17 kg, 95% CI: -0.33, -0.01) (P-value for interaction = 0.011). Across race/ethnicity, the mean difference in weight change at 5 years for residential density was significantly different among non-Hispanic (NH) Whites (-0.47 kg, 95% CI: -0.61, -0.32), NH Blacks (-0.86 kg, 95% CI: -1.37, -0.36), Hispanics (0.10 kg, 95% CI: -0.46, 0.65), and NH Asians (0.44 kg, 95% CI: 0.10, 0.78) (P-value for interaction <0.001). These findings were consistent for other BE measures. CONCLUSION: The relationship between the built environment and weight change differs across demographic groups. Careful consideration of demographic differences in associations of BE and weight trajectories is warranted for investigating etiological mechanisms and guiding intervention development.

Matching participant address with public records database in a US national longitudinal cohort study.

BACKGROUND: Epidemiological studies utilize residential histories to assess environmental exposure risk. The validity from using commercially-sourced residential histories within national longitudinal studies remains unclear. Our study assessed predictors of non-agreement between baseline addresses from the commercially-sourced LexisNexis database and participants in the national longitudinal study, REasons for Geographic and Racial Differences in Stroke (REGARDS). Additionally, we assessed differences in stroke risk by neighborhood socioeconomic score (nSES) based on participant reported address compared to nSES from LexisNexis/REGARDS matched baseline address. METHODS: From January 2003-October 2007, REGARDS enrolled 30,239 black and white adults aged 45 and older within the continental United States and collected their baseline address. ArcGIS Desktop 10.5.1 with ESRI 2016 Business Analyst Data was used to geocode baseline addresses from LexisNexis and REGARDS. Logistic regression was used to estimate the likelihood that LexisNexis address matched REGARDS baseline address for each participant. Survival analysis was used to estimate association between nSES and incident stroke. RESULTS: Approximately 91% of REGARDS participants had a LexisNexis address. Of these geocoded addresses, 93% of REGARDS baseline addresses matched LexisNexis addresses. Odds of agreement between LexisNexis and REGARDS was higher for older-aged participants (OR = 1.02 per year, 95% CI: 1.01, 1.02), blacks compared to whites (OR = 1.16, 95% CI: 1.05, 1.29), females compared to males (OR = 1.15, 95% CI: 1.04, 1.26), participants with an income of $34k-74k compared to an income less than $20k (OR = 1.62, 95% CI: 1.39, 1.89). Odds of agreement were lower for residents in Midwest compared to residents in the south (OR = 0.82, 95% CI: 0.73, 0.94). No significant differences in nSES-stroke associations were observed between REGARDS only and LexisNexis/REGARDS matched addresses; however, differences in interactions were observed. CONCLUSION: Agreement between LexisNexis and REGARDS addresses varied by sociodemographic groups, potentially introducing bias in studies reliant on LexisNexis alone for residential address data.

Measurement of neighborhood-based physical activity bouts.

This study examined how buffer type (shape), size, and the allocation of activity bouts inside buffers that delineate the neighborhood spatially produce different estimates of neighborhood-based physical activity. A sample of 375 adults wore a global positioning system (GPS) data logger and accelerometer over 2 weeks under free-living conditions. Analytically, the amount of neighborhood physical activity measured objectively varies substantially, not only due to buffer shape and size, but by how GPS-based activity bouts are identified with respect to containment within neighborhood buffers. To move the "neighborhood-effects" literature forward, it is critical to delineate the spatial extent of the neighborhood, given how different ways of measuring GPS-based activity containment will result in different levels of physical activity across different buffer types and sizes.

Does the built environment have independent obesogenic power? Urban form and trajectories of weight gain.

OBJECTIVE: To determine whether selected features of the built environment can predict weight gain in a large longitudinal cohort of adults. METHODS: Weight trajectories over a 5-year period were obtained from electronic health records for 115,260 insured patients aged 18-64 years in the Kaiser Permanente Washington health care system. Home addresses were geocoded using ArcGIS. Built environment variables were population, residential unit, and road intersection densities captured using Euclidean-based SmartMaps at 800-m buffers. Counts of area supermarkets and fast food restaurants were obtained using network-based SmartMaps at 1600, and 5000-m buffers. Property values were a measure of socioeconomic status. Linear mixed effects models tested whether built environment variables at baseline were associated with long-term weight gain, adjusting for sex, age, race/ethnicity, Medicaid insurance, body weight, and residential property values. RESULTS: Built environment variables at baseline were associated with differences in baseline obesity prevalence and body mass index but had limited impact on weight trajectories. Mean weight gain for the full cohort was 0.06 kg at 1 year (95% CI: 0.03, 0.10); 0.64 kg at 3 years (95% CI: 0.59, 0.68), and 0.95 kg at 5 years (95% CI: 0.90, 1.00). In adjusted regression models, the top tertile of density metrics and frequency counts were associated with lower weight gain at 5-years follow-up compared to the bottom tertiles, though the mean differences in weight change for each follow-up year (1, 3, and 5) did not exceed 0.5 kg. CONCLUSIONS: Built environment variables that were associated with higher obesity prevalence at baseline had limited independent obesogenic power with respect to weight gain over time. Residential unit density had the strongest negative association with weight gain. Future work on the influence of built environment variables on health should also examine social context, including residential segregation and residential mobility.

Associations of Household Income with Health-Related Quality of Life Following a Colorectal Cancer Diagnosis Varies With Neighborhood Socioeconomic Status.

BACKGROUND: Existing evidence indicates household income as a predictor of health-related quality of life (HRQoL) following a colorectal cancer diagnosis. This association likely varies with neighborhood socioeconomic status (nSES), but evidence is limited. METHODS: We included data from 1,355 colorectal cancer survivors participating in the population-based Puget Sound Colorectal Cancer Cohort (PSCCC). Survivors reported current annual household income; we measured HRQoL via the Functional Assessment of Cancer Therapy - Colorectal (FACT-C) tool. Using neighborhood data summarized within a 1-km radial buffer of Census block group centroids, we constructed a multidimensional nSES index measure. We employed survivors' geocoded residential addresses to append nSES score for Census block group of residence. With linear generalized estimating equations clustered on survivor location, we evaluated associations of household income with differences in FACT-C mean score, overall and stratified by nSES. We used separate models to explore relationships for wellbeing subscales. RESULTS: We found lower household income to be associated with clinically meaningful differences in overall FACT-C scores [<$30K: -13.6; 95% confidence interval (CI): -16.8 to -10.4] and subscale wellbeing after a recent colorectal cancer diagnosis. Relationships were slightly greater in magnitude for survivors living in lower SES neighborhoods. CONCLUSIONS: Our findings suggest that recently diagnosed lower income colorectal cancer survivors are likely to report lower HRQoL, and modestly more so in lower SES neighborhoods. IMPACT: The findings from this work will aid future investigators' ability to further consider the contexts in which the income of survivors can be leveraged as a means of improving HRQoL.