Association between neighborhood availability of physical activity facilities and cognitive performance in older adults.

The existing evidence on the contextual influence of the availability of local facilities for physical activity on the cognitive health of elderly residents is sparse. This study examined the association between neighborhood physical activity facilities and cognitive health in older individuals. A cohort study of community-dwelling older adults was performed using baseline data and follow-up data from the Taiwan Biobank. Cognitive health was measured in 32,396 individuals aged 60-70 years using the Mini-Mental State Examination (MMSE) with follow-up information on 8025 participants. The district was used as the proxy for local neighborhood. To determine neighborhood physical activity facilities, school campuses, parks, activity centers, gyms, swimming pools, and stadiums were included. Multilevel linear regression models were applied to examine the associations of neighborhood physical activity facilities with baseline MMSE and MMSE decline during follow-up, with adjustment for individual factors and neighborhood socioeconomic characteristics. Multilevel analyses revealed that there was a neighborhood-level effect on cognitive health among older adults. After adjusting for compositional and neighborhood socioeconomic characteristics, baseline MMSE was higher in individuals living in the middle- (beta = 0.12, p-value = 0.140) and high-density facility (beta = 0.22, p-value = 0.025) groups than in the low-density group (p-value for trend-test = 0.031). MMSE decline during follow-up was slower in the middle- (beta = 0.15, p-value = 0.114) and high-density facility (beta = 0.27, p-value = 0.052) groups than in the low-density group (p-value for trend-test = 0.032). Greater neighborhood availability of physical activity facilities was associated with better cognitive health among older residents. These findings have implications for designing communities and developing strategies to support cognitive health of an aging population.

Investigating how researcher-defined buffers and self-drawn neighbourhoods capture adolescent availability to physical activity facilities and greenspaces: An exploratory study.

BACKGROUND: Modifying the environment is considered an effective population-level approach for increasing healthy behaviours, but associations remain ambiguous. This exploratory study aims to compare researcher-defined buffers and self-drawn neighbourhoods (SDN) to objectively measured availability of physical activity (PA) facilities and greenspaces in adolescents. METHODS: Seven consecutive days of GPS data were collected in an adolescent sample of 14-18 year olds (n = 69). Using Points of Interest and greenspace data, availability of PA opportunities within activity spaces were determined. We compared 30 different definitions of researcher-defined neighbourhoods and SDNs to objectively measured availability. RESULTS: Findings showed low agreement for all researcher-defined buffers in measuring the availability of PA facilities in activity spaces. However, results were less clear for greenspace. SDNs also demonstrate low agreement for capturing availability to the PA environment. CONCLUSION: This exploratory study highlights the inadequacy of researcher-defined buffers and SDNs to define availability to environmental features.

Distance to sports facilities and low frequency of exercise and obesity: a cross-sectional study.

BACKGROUND: Little research has investigated the associations between proximity to physical activity facilities and behavior-related health and the majority have focused on proximity from home address. We add to the literature by examining proximity of these facilities to work and home address and including a wide range of physical activity facilities. We assess the associations for proximity of physical activity facilities from home and work address with self-reported frequency of exercise and obesity. METHODS: Our analytical sample of 7358 participants was from the 2018 wave of the Swedish Longitudinal Occupational Survey of Health. We used logistic binomial regression adjusting for age, sex, education, civil status, individual socioeconomic status, neighborhood socioeconomic status, number of children under 12 years of age, work strain, and chronic disease. RESULTS: Longer distance from home to paid outdoor and paid indoor physical activity facilities was associated with low frequency of exercise (fully adjusted Relative Risk for both 1.01, 95% CI 1.01-1.02). Associations of any or free outdoor facility with low frequency of exercise were not robust. Findings also indicated associations between long distance from workplace to any and paid outdoor facility and low frequency of exercise. Results for obesity were in the similar direction, however, these were not statistically significant. CONCLUSION: Increased distance of paid outdoor and paid indoor physical activity facilities from home and of paid outdoor facilities from work was associated with low frequency of exercise. Longitudinal and larger studies are needed to confirm our findings, particularly regarding obesity.

The association between spatial access to physical activity facilities within home and workplace neighborhoods and time spent on physical activities: evidence from Guangzhou, China.

BACKGROUND: Urban residents from the developing world have increasingly adopted a sedentary lifestyle and spend less time on physical activities (PA). Previous studies on the association between PA facilities and individuals' PA levels are based on the assumption that individuals have opportunities to use PA facilities within neighborhoods all day long, ignoring the fact that their willingness and opportunities to use nearby facilities depend on how much discretionary time (any time when people have a choice what to do) they have. Further, scant attention has been paid to the influence of PA facilities within both residential and workplace neighborhoods in the dense urban context. To address the above research gaps, this study investigated the links between the spatial access to PA facilities within home/workplace neighborhoods and time spent on PA among working adults, focusing on whether results were different when different measures of accessibility were used and whether participants' discretionary time over a week affected their time spent on PA. METHOD: This study used data from a questionnaire survey (n = 1002) in Guangzhou between June and July 2017 and point of interest (POI) data from online mapping resources. Outcome variables included the amount of time spent on physical activity/moderate and vigorous intensity physical activity (PA/MVPA) over the past week. Home/workplace neighborhoods were measured as different distance buffers (500 m circular buffers, 1000 m circular buffers, and 1080 m network buffers) around each respondent's home/workplace. Spatial access to PA facilities was measured using two indicators: the counts of PA facilities and proximity to PA facilities within home/workplace neighborhoods. The amount of discretionary time was calculated based on activity log data of working day/weekend day from the Guangzhou questionnaire survey, and regression models were used to examine relationships between the spatial access of PA facilities, the time spent on PA/MVPA, and the amount of discretionary time, adjusted for covariates. Associations were stratified by gender, age, education, and income. RESULTS: Using different measures of accessibility (the counts of and proximity to PA facilities) generated different results. Specifically, participants spent more time on PA/MVPA when they lived in neighborhoods with more PA facilities and spent more time on MVPA when worked in closer proximity to PA facilities. A larger amount of discretionary time was associated with more time spent on PA/MVPA, but it did not strengthen the relationship between access to PA facilities and PA/MVPA time. In addition, relationships between access to PA facilities and PA levels varied by gender, age, education, and income. CONCLUSION: This study contributes to the knowledge of PA-promoting environments by considering both the home and workplace contexts and by taking into account the temporal attributes of contextual influences. Policymakers and urban planners are advised to take into account the workplace context and the temporal variability of neighborhood influences when allocating public PA facilities and public spaces.

Associations among Neighborhood Socioeconomic Deprivation, Physical Activity Facilities, and Physical Activity in Youth during the Transition from Childhood to Adolescence.

BACKGROUND: This study aims to examine the longitudinal association of neighborhood socioeconomic deprivation (SED) with physical activity in youth during the transition from elementary to middle school, and to determine if access to physical activity facilities moderates this relationship. METHODS: Data were obtained from the Transitions and Activity Changes in Kids (TRACK) study, which was a multilevel, longitudinal study designed to identify the factors that influence changes in physical activity as youth transition from elementary to middle school. The analytic sample for the current study included 660 youth with complete data in grades 5 (baseline) and 7 (follow-up). A repeated measures multilevel framework was employed to examine the relationship between SED and physical activity over time and the potential moderating role of elements of the built environment. RESULTS: Decreases in physical activity varied by the degree of neighborhood SED with youth residing in the most deprived neighborhoods experiencing the greatest declines in physical activity. Access to supportive physical activity facilities did not moderate this relationship. CONCLUSION: Future research studies are needed to better understand how neighborhood SED influences youth physical activity over time.

Neighbourhood typologies and associations with body mass index and obesity: A cross-sectional study.

Little research has investigated associations between a combined measure of the food and physical activity (PA) environment, BMI (body-mass-index) and obesity. Cross-sectional data (n=22,889, age 18-86years) from the Yorkshire Health Study were used [2010-2013]. BMI was calculated using self-reported height and weight; obesity=BMI≥30. Neighbourhood was defined as a 2km radial buffer. Food outlets and PA facilities were sourced from Ordnance Survey Points of Interest (PoI) and categorised into 'fast-food', 'large supermarkets', 'convenience and other food retail outlets' and 'physical activity facilities'. Parks were sourced from Open Street Map. Latent class analysis was conducted on these five environmental variables and availability was defined by quartiles of exposure. Linear and logistic regressions were then conducted for BMI and obesity respectively for different neighbourhood types. Models adjusted for age, gender, ethnicity, area-level deprivation, and rural/urban classification. A five-class solution demonstrated best fit and was interpretable. Neighbourhood typologies were defined as; 'low availability', 'moderate availability', 'moderate PA, limited food', 'saturated' and 'moderate PA, ample food'. Compared to low availability, one typology demonstrated lower BMI (saturated, b=-0.50, [95% CI=-0.76, -0.23]), while three showed higher BMI (moderate availability, b=0.49 [0.27, 0.72]; moderate PA, limited food, b=0.30 [0.01, 0.59]; moderate PA, ample food, b=0.32 [0.08, 0.57]). Furthermore, compared to the low availability, saturated neighbourhoods showed lower odds of obesity (OR=0.86 [0.75, 0.99]) while moderate availability showed greater odds of obesity (OR=1.18 [1.05, 1.32]). This study supports population-level approaches to tackling obesity however neighbourhoods contained features that were health-promoting and -constraining.

Associations between access to recreational physical activity facilities and body mass index in Scottish adults.

BACKGROUND: The aim of this country-wide study was to link individual health and behavioural data with area-level spatial data to examine whether the body mass index (BMI) of adults was associated with access to recreational physical activity (PA) facilities by different modes of transport (bus, car, walking, cycling) and the extent to which any associations were mediated by PA participation. METHODS: Data on individual objectively-measured BMI, PA (number of days of (a) ≥20 min of moderate-to-vigorous PA, and (b) ≥15 min of sport or exercise, in previous 4 weeks), and socio-demographic characteristics were obtained from a nationally representative sample of 6365 adults. The number of accessible PA facilities per 1,000 individuals in each small area (data zones) was obtained by mapping a representative list of all fixed PA facilities throughout mainland Scotland. A novel transport network was developed for the whole country, and routes on foot, by bike, by car and by bus from the weighted population centroid of each data zone to each facility were calculated. Separate multilevel models were fitted to examine associations between BMI and each of the 24 measures of accessibility of PA facilities and BMI, adjusting for age, gender, longstanding illness, car availability, social class, dietary quality and urban/rural classification. RESULTS: We found associations (p < 0.05) between BMI and 7 of the 24 accessibility measures, with mean BMI decreasing with increasing accessibility of facilities-for example, an estimated decrease of 0.015 BMI units per additional facility within a 20-min walk (p = 0.02). None of these accessibility measures were found to be associated with PA participation. CONCLUSIONS: Our national study has shown that some measures of the accessibility of PA facilities by different modes of transport (particularly by walking and cycling) were associated with BMI; but PA participation, as measured here, did not appear to play a part in this relationship. Understanding the multi-factorial environmental influences upon obesity is key to developing effective interventions to reduce it.