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.

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.].

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.

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.

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.

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.

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.

Physical Activity Measurement in Children Who Use Mobility Assistive Devices: Accelerometry and Global Positioning System.

PURPOSE: To explore the usefulness of combining accelerometry, global positioning systems, and geographic information systems, to describe the time spent in different locations and physical activity (PA) duration/count levels by location for 4 children with cerebral palsy (CP) who use assistive devices (AD). METHODS: A descriptive multiple-case study. RESULTS: Combining the 3 instruments was useful in describing and differentiating duration by location, and amount and location of PA across differing functional levels and AD. For example, the child classified with a Gross Motor Function Classification System (GMFCS) level II exhibited large amounts of PA in community settings. In contrast, the child classified with a GMFCS level V had small amounts of PA and spent most measured time at home. CONCLUSIONS: Combined accelerometry, global positioning system, and geographic information system have potential to capture time spent and amount/intensity of PA relative to locations within daily environments for children with CP who use AD.

Motorcycle taxi programme increases safe riding behaviours among its drivers in Kampala, Uganda.

BACKGROUND: SafeBoda is a motorcycle taxi company that provides road safety training and helmets to its drivers in Kampala, Uganda. We sought to determine whether SafeBoda drivers are more likely to engage in safe riding behaviours than regular drivers (motorcycle taxi drivers not part of SafeBoda). METHODS : We measured riding behaviours in SafeBoda and regular drivers through: (1) computer-assisted personal interview (CAPI), where 400 drivers were asked about their riding behaviours (eg, helmet and mobile phone use) and (2) roadside observation, where riding behaviours were observed in 3000 boda-boda drivers and their passengers along major roads in Kampala. RESULTS: Across the two cross-sectional studies, a higher proportion of SafeBoda drivers than regular drivers engaged in safe riding behaviours. For instance, helmet use among SafeBoda compared with regular drivers was 21% points higher (95% CI 0.15 to 0.27; p<0.001) based on the CAPI and 45% points higher (95% CI 0.43 to 0.47; p<0.001) based on roadside observation. Furthermore, compared with regular drivers, SafeBoda drivers were more likely to report having a driver's license (66.3% vs 33.5 %; p<0.001) and a reflective jacket (99.5% vs 50.5 %; p<0.001) and were less likely to report driving towards oncoming traffic (4% vs 45.7 %; p<0.001) in the past 30 days. CONCLUSION: The SafeBoda programme is associated with increased safe riding behaviours among motorcycle taxi drivers in Kampala. Therefore, the promotion and expansion of such programmes may lead to a reduction in morbidity and mortality due to road injuries.

Probabilistic walking models using built environment and sociodemographic predictors.

BACKGROUND: Individual sociodemographic and home neighborhood built environment (BE) factors influence the probability of engaging in health-enhancing levels of walking or moderate-to-vigorous physical activity (MVPA). Methods are needed to parsimoniously model the associations. METHODS: Participants included 2392 adults drawn from a community-based twin registry living in the Seattle region. Objective BE measures from four domains (regional context, neighborhood composition, destinations, transportation) were taken for neighborhood sizes of 833 and 1666 road network meters from home. Hosmer and Lemeshow's methods served to fit logistic regression models of walking and MVPA outcomes using sociodemographic and BE predictors. Backward elimination identified variables included in final models, and comparison of receiver operating characteristic (ROC) curves determined model fit improvements. RESULTS: Built environment variables associated with physical activity were reduced from 86 to 5 or fewer. Sociodemographic and BE variables from all four BE domains were associated with activity outcomes but differed by activity type and neighborhood size. For the study population, ROC comparisons indicated that adding BE variables to a base model of sociodemographic factors did not improve the ability to predict walking or MVPA. CONCLUSIONS: Using sociodemographic and built environment factors, the proposed approach can guide the estimation of activity prediction models for different activity types, neighborhood sizes, and discrete BE characteristics. Variables associated with walking and MVPA are population and neighborhood BE-specific.

Capturing fine-scale travel behaviors: a comparative analysis between personal activity location measurement system (PALMS) and travel diary.

BACKGROUND: Device-collected data from GPS and accelerometers for identifying active travel behaviors have dramatically changed research methods in transportation planning and public health. Automated algorithms have helped researchers to process large datasets with likely fewer errors than found in other collection methods (e.g., self-report travel diary). In this study, we compared travel modes identified by a commonly used automated algorithm (PALMS) that integrates GPS and accelerometer data with those obtained from travel diary estimates. METHODS: Sixty participants, who made 2100 trips during seven consecutive days of data collection, were selected from among the baseline sample of a project examining the travel behavior impact of a new light rail system in the greater Seattle, WA (USA) area. GPS point level analyses were first conducted to compare trip/place and travel mode detection results using contingency tables. Trip level analyses were then performed to investigate the effect of proportions of time overlap between travel logs and device-collected data on agreement rates. Global performance (with all subjects' data combined) and subject-level performance of the algorithm were compared at the trip level. RESULTS: At the GPS point level, the overall agreement rate of travel mode detection was 77.4% between PALMS and the travel diary. The agreement rate for vehicular trip detection (84.5%) was higher than for bicycling (53.5%) and walking (58.2%). At the trip level, the global performance and subject-level performance of the PALMS algorithm were 46.4% and 42.4%, respectively. Vehicular trip detection showed highest agreement rates in all analyses. Study participants' primary travel mode and car ownership were significantly related to the subject-level mode agreement rates. CONCLUSIONS: The PALMS algorithm showed moderate identification power at the GPS point level. However, trip level analyses found lower agreement rates between PALMS and travel diary data, especially for active transportation. Testing different PALMS parameter settings may serve to improve the detection of active travel and help expand PALMS's applicability in geographically different urbanized areas with a variety of travel modes.

The Relationship Between Objectively Measured Walking and Risk of Pedestrian-Motor Vehicle Collision.

Safe urban walking environments may improve health by encouraging physical activity, but the relationship between an individual's location and walking pattern and the risk of pedestrian-motor vehicle collision is unknown. We examined associations between individuals' walking bouts and walking risk, measured as mean exposure to the risk of pedestrian-vehicle collision. Walking bouts were ascertained through integrated accelerometry and global positioning system data and from individual travel-diary data obtained from adults in the Travel Assessment and Community Study (King County, Washington) in 2008-2009. Walking patterns were superimposed onto maps of the historical probabilities of pedestrian-vehicle collisions for intersections and midblock segments within Seattle, Washington. Mean risk of pedestrian-vehicle collision in specific walking locations was assessed according to walking exposure (duration, distance, and intensity) and participant demographic characteristics in linear mixed models. Participants typically walked in areas with low pedestrian collision risk when walking for recreation, walking at a faster pace, or taking longer-duration walks. Mean daily walking duration and distance were not associated with collision risk. Males walked in areas with higher collision risk compared with females, while vehicle owners, residents of single-family homes, and parents of young children walked in areas with lower collision risk. These findings may suggest that pedestrians moderate collision risk by using lower-risk routes.

Differences in Behavior, Time, Location, and Built Environment between Objectively Measured Utilitarian and Recreational Walking.

OBJECTIVES: Utilitarian and recreational walking both contribute to physical activity. Yet walking for these two purposes may be different behaviors. We sought to provide operational definitions of utilitarian and recreational walking and to objectively measure their behavioral, spatial, and temporal differences in order to inform transportation and public health policies and interventions. METHODS: Data were collected 2008-2009 from 651 Seattle-King County residents, wearing an accelerometer and a GPS unit, and filling-in a travel diary for 7 days. Walking activity bouts were classified as utilitarian or recreational based on whether walking had a destination or not. Differences between the two walking purposes were analyzed, adjusting for the nested structure of walking activity within participants. RESULTS: Of the 4,905 observed walking bouts, 87.4% were utilitarian and 12.6% recreational walking. Utilitarian walking bouts were 45% shorter in duration (-12.1 min) and 9% faster in speed (+0.3km/h) than recreational walking bouts. Recreational walking occurred more frequently in the home neighborhood and was not associated with recreational land uses. Utilitarian walking occurred in areas having higher residential, employment, and street density, lower residential property value, higher area percentage of mixed-use neighborhood destinations, lower percentage of parks/trails, and lower average topographic slope than recreational walking. CONCLUSION: Utilitarian and recreational walking are substantially different in terms of frequency, speed, duration, location, and related built environment. Policies that promote walking should adopt type-specific strategies. The high occurrence of recreational walking near home highlights the importance of the home neighborhood for this activity.

Obesity, diet quality, physical activity, and the built environment: the need for behavioral pathways.

BACKGROUND: The built environment (BE) is said to influence local obesity rates. Few studies have explored causal pathways between home-neighborhood BE variables and health outcomes such as obesity. Such pathways are likely to involve both physical activity and diet. METHODS: The Seattle Obesity Study (SOS II) was a longitudinal cohort of 440 adult residents of King Co, WA. Home addresses were geocoded. Home-neighborhood BE measures were framed as counts and densities of food sources and physical activity locations. Tax parcel property values were obtained from County tax assessor. Healthy Eating Index (HEI 2010) scores were constructed using data from food frequency questionnaires. Physical activity (PA) was obtained by self-report. Weights and heights were measured at baseline and following 12 months' exposure. Multivariable regressions examined the associations among BE measures at baseline, health behaviors (HEI-2010 and physical activity) at baseline, and health outcome both cross-sectionally and longitudinally. RESULTS: None of the conventional neighborhood BE metrics were associated either with diet quality, or with meeting PA guidelines. Only higher property values did predict better diets and more physical activity. Better diets and more physical activity were associated with lower obesity prevalence at baseline and 12 mo, but did not predict weight change. CONCLUSION: Any links between the BE and health outcomes critically depend on establishing appropriate behavioral pathways. In this study, home-centric BE measures, were not related to physical activity or to diet. Further studies will need to consider a broader range of BE attributes that may be related to diets and health.

Evidence-Based Program Service Deserts: A Geographic Information Systems (GIS) Approach to Identifying Service Gaps for State-Level Implementation Planning.

The long term effects of untreated mental health need for individuals, families and society has prompted a number of federal policy statements encouraging the use of evidence-based programs (EBP) in children's healthcare. However, among other challenges of evidence-based practice implementation, states often do not know where to make investments based on population need. In this paper we present the use of a Geographic Information System approach to undertake a mental health needs assessment for Washington State. Our study found that this technology can be beneficially applied to conducting needs assessment for EBP implementation, and we provide recommendations for future applications.

Relation between higher physical activity and public transit use.

OBJECTIVES: We isolated physical activity attributable to transit use to examine issues of substitution between types of physical activity and potential confounding of transit-related walking with other walking. METHODS: Physical activity and transit use data were collected in 2008 to 2009 from 693 Travel Assessment and Community study participants from King County, Washington, equipped with an accelerometer, a portable Global Positioning System, and a 7-day travel log. Physical activity was classified into transit- and non-transit-related walking and nonwalking time. Analyses compared physical activity by type between transit users and nonusers, between less and more frequent transit users, and between transit and nontransit days for transit users. RESULTS: Transit users had more daily overall physical activity and more total walking than did nontransit users but did not differ on either non-transit-related walking or nonwalking physical activity. Most frequent transit users had more walking time than least frequent transit users. Higher physical activity levels for transit users were observed only on transit days, with 14.6 minutes (12.4 minutes when adjusted for demographics) of daily physical activity directly linked with transit use. CONCLUSIONS: Because transit use was directly related to higher physical activity, future research should examine whether substantive increases in transit access and use lead to more physical activity and related health improvements.

Access to supermarkets and fruit and vegetable consumption.

OBJECTIVES: We examined whether supermarket choice, conceptualized as a proxy for underlying personal factors, would better predict access to supermarkets and fruit and vegetable consumption than mere physical proximity. METHODS: The Seattle Obesity Study geocoded respondents' home addresses and locations of their primary supermarkets. Primary supermarkets were stratified into low, medium, and high cost according to the market basket cost of 100 foods. Data on fruit and vegetable consumption were obtained during telephone surveys. Linear regressions examined associations between physical proximity to primary supermarkets, supermarket choice, and fruit and vegetable consumption. Descriptive analyses examined whether supermarket choice outweighed physical proximity among lower-income and vulnerable groups. RESULTS: Only one third of the respondents shopped at their nearest supermarket for their primary food supply. Those who shopped at low-cost supermarkets were more likely to travel beyond their nearest supermarket. Fruit and vegetable consumption was not associated with physical distance but, with supermarket choice, after adjusting for covariates. CONCLUSIONS: Mere physical distance may not be the most salient variable to reflect access to supermarkets, particularly among those who shop by car. Studies on food environments need to focus beyond neighborhood geographic boundaries to capture actual food shopping behaviors.

How far from home? The locations of physical activity in an urban U.S. setting.

UNLABELLED: Little is known about where physical activity (PA) occurs, or whether different demographic groups accumulate PA in different locations. METHOD: Objective data on PA and location from 611 adults over 7days were collected in King County, WA in 2008-2009. The relative amounts of time spent in sedentary-to-low and moderate-to-vigorous PA (MVPA) were quantified at three locations: "home" (<125m from geocoded home locations); "near" home (125-1666m, defining the home neighborhood); and "away" from home (>1666m). Differences in MVPA by demographics and location were examined. The percent of daily time in MVPA was estimated using a mixed model adjusted for location, sex, age, race/ethnicity, employment, education, BMI, and income. RESULTS: Most MVPA time occurred in nonhome locations, and disproportionately "near" home; this location was associated with 16.46% greater time in MVPA, compared to at-home activity (p<0.001), whereas more time spent at "away" locations was associated with 3.74% greater time in MVPA (p<0.001). Location was found to be a predictor of MVPA independent of demographic factors. CONCLUSION: A large proportion of MVPA time is spent at "near" locations, corresponding to the home neighborhood studied in previous PA research. "Away" locations also host time spent in MVPA and should be the focus of future research.

The built environment and utilitarian walking in small U.S. towns.

OBJECTIVES: The role of the built environment on walking in rural United States (U.S.) locations is not well characterized. We examined self-reported and measured built environment correlates of walking for utilitarian purposes among adult residents of small rural towns. METHODS: In 2011-12, we collected telephone survey and geographic data from 2152 adults in 9 small towns from three U.S. regions. We performed mixed-effects logistic regression modeling to examine relationships between built environment measures and utilitarian walking ("any" versus "none"; "high" [≥150min per week] versus "low" [<150min per week]) to retail, employment and public transit destinations. RESULTS: Walking levels were lower than those reported for populations living in larger metropolitan areas. Environmental factors significantly (p<0.05) associated with higher odds of utilitarian walking in both models included self-reported presence of crosswalks and pedestrian signals and availability of park/natural recreational areas in the neighborhood, and also objectively measured manufacturing land use. CONCLUSIONS: Environmental factors associated with utilitarian walking in cities and suburbs were important in small rural towns. Moreover, manufacturing land use was associated with utilitarian walking. Modifying the built environment of small towns could lead to increased walking in a sizeable segment of the U.S. population.