Prospective associations between changes in physical activity and sedentary time and subsequent lean muscle mass in older English adults: the EPIC-Norfolk cohort study.

BACKGROUND: The longitudinal associations between physical behaviours and lean muscle mass indices need to be better understood to aid healthy ageing intervention development. METHODS: We assessed physical behaviours (total physical activity, moderate-to-vigorous physical activity (MVPA), light physical activity, total sedentary time and prolonged sedentary bout time) for 7 days using hip-worn accelerometers. We also assessed domain-specific physical behaviours (walking, cycling, gardening and housework time) with self-report questionnaires at baseline (2006-2011) and follow-up (2012-2016) in the European Prospective Investigation into Cancer (EPIC)-Norfolk study. We assessed body composition using dual-energy X-ray absorptiometry (DEXA) at follow-up in 1535 participants (≥ 60 years at baseline). From this, we derived appendicular lean muscle mass (ALM) indices (% relative ALM = (ALM/total body weight)*100), body mass index (BMI)-scaled ALM (ALM/BMI, kg/kg/m2) and height-scaled ALM (ALM/height2, kg/m2)). We evaluated the prospective associations of both baseline and change in physical behaviours with follow-up muscle mass indices using multivariable linear regression. RESULTS: Over 5.5 years (SD 14.8) follow-up, higher baseline accelerometer-measured physical activity and lower sedentary time were associated with higher subsequent relative ALM and BMI-scaled ALM, but not height-scaled ALM (e.g. 0.02% higher subsequent relative ALM per minute/day of baseline MVPA for men). Greater increases in physical activity and greater declines in sedentary time variables were associated with higher subsequent relative ALM and BMI-scaled ALM, but not height-scaled ALM (e.g. 0.001 kg/kg/m2 subsequent BMI-scaled ALM and 0.04% subsequent relative ALM per min/day/year increases in LPA over follow-up; 0.001 kg/kg/m2 subsequent BMI-scaled ALM and -0.03% subsequent relative ALM per min/day/year less of total sedentary time over follow-up). Greater increases in women's cycling and gardening over follow-up were associated with greater subsequent relative ALM (cycling 0.9% per hour/week/year; gardening 0.2% per hour/week/year) and BMI-scaled ALM (cycling 0.03 kg/kg/m2 per hour/week/year; gardening 0.004 kg/kg/m2 per hour/week/year). CONCLUSION: Physical behaviours across all intensities, and in women more specifically cycling and gardening, may help prevent age-related declines in muscle mass.

Associations between residential greenspace exposure and mortality in 4 645 581 adults living in London, UK: a longitudinal study.

BACKGROUND: Urban greenspaces could reduce non-communicable disease (NCD) risk. The links between greenspaces and NCD-related mortality remain unclear. We aimed to estimate associations between residential greenspace quantity and access and all-cause mortality, cardiovascular disease mortality, cancer mortality, respiratory mortality, and type 2 diabetes mortality. METHODS: We linked 2011 UK Census data of London-dwelling adults (aged ≥18 years) to data from the UK death registry and the Greenspace Information for Greater London resource. We calculated percentage greenspace area, access point density (access points per km2), and distance in metres to the nearest access point for each respondent's residential neighbourhood (defined as 1000 m street network buffers) for greenspaces overall and by park type using a geographic information system. We estimated associations using Cox proportional hazards models, adjusted for a range of confounders. FINDINGS: Data were available for 4 645 581 individuals between March 27, 2011, and Dec 31, 2019. Respondents were followed up for a mean of 8·4 years (SD 1·4). All-cause mortality did not differ with overall greenspace coverage (hazard ratio [HR] 1·0004, 95% CI 0·9996-1·0012), increased with increasing access point density (1·0076, 1·0031-1·0120), and decreased slightly with increasing distance to the nearest access point (HR 0·9993, 0·9987-0·9998). A 1 percentage point (pp) increase in pocket park (areas for rest and recreation under 0·4 hectares) coverage was associated with a decrease in all-cause mortality risk (0·9441, 0·9213-0·9675), and an increase of ten pocket park access points per km2 was associated with a decreased respiratory mortality risk (0·9164, 0·8457-0·9931). Other associations were observed, but the estimated effects were small (eg, all-cause mortality risk for increases of 1 pp in regional park area were 0·9913, 0·9861-0·9966 and increases of ten small open space access points per km2 were 1·0247, 1·0151-1·0344). INTERPRETATION: Increasing the quantity of, and access to, pocket parks might help mitigate mortality risk. More research is needed to elucidate the mechanisms that could explain these associations. FUNDING: Health Data Research UK (HDRUK).

Associations between change in physical activity and sedentary time and health-related quality of life in older english adults: the EPIC-Norfolk cohort study.

BACKGROUND: No previous studies have examined the associations between changes in objectively-measured physical behaviours with follow-up QoL in older adults. Based on cross-sectional evidence, it is biologically plausible that such associations exist. If so, this bolsters the case for the commissioning of activity interventions and for including QoL as an outcome in trials of such interventions. METHODS: We assessed physical behaviours (total physical activity, moderate-to-vigorous physical activity (MVPA), light physical activity, total sedentary time and prolonged sedentary bout time) for 7 days using hip-worn accelerometers at baseline (2006-2011) and follow-up (2012-2016) and health-related quality-of-life (QoL) using EQ-5D questionnaires at follow-up in 1433 participants (≥ 60 years) of the EPIC (European Prospective Investigation into Cancer)-Norfolk study. The EQ-5D summary score was used, with 0 as the worst to 1 as best perceived quality-of-life. We evaluated the prospective associations of baseline physical behaviours with follow-up QoL, and of changes in behaviours with follow-up QoL using multi-level regression. RESULTS: On average, MVPA decreased by 4.0 min/day/year (SD 8.3) for men and 4.0 min/day/year for women (SD 12.0) between baseline and follow-up. Total sedentary time increased by an average 5.5 min/day/yr (SD 16.0) for men and 6.4 min/day/yr (SD 15.0) for women between baseline and follow-up. Mean (SD) follow-up time was 5.8 (1.8) years. We found that higher baseline MVPA and lower sedentary time was associated with higher subsequent QoL (e.g. 1 h/day greater baseline MVPA was associated with 0.02 higher EQ-5D score, 95% CI 0.06, 0.36). More pronounced declines in activity were associated with worse Hr-QoL (0.005 (95% CI 0.003, 0.008) lower EQ-5D per min/day/yr decrease in MVPA). Increases in sedentary behaviours were also associated with poorer QoL (0.002 lower EQ-5D, 95% CI -0.003, -0.0007 per hour/day/yr increase in total sedentary time). CONCLUSIONS: Promotion of physical activity and limiting sedentary time among older adults may improve quality-of-life, and therefore this relationship ought to be included in future cost effectiveness analyses so that greater commissioning of activity interventions can be considered.

Effects of the onset of the COVID-19 pandemic restrictions on park crime in London, England: An interrupted time series analysis.

Introduction: Park crimes may have increased during the COVID-19 pandemic as a result of lockdowns that limited the number of capable guardians in public spaces. Despite this, the impacts of the lockdowns on park crimes remain unknown. To help us understand the societal impacts of policies implemented during this period, we assessed how the onset of the COVID-19 restrictions impacted urban park crime levels in London, England. Methods: We identified crimes that occurred in publicly accessible parks and gardens in the Greater London Authority (England, UK) between March 1, 2019 and February 28, 2021 by overlaying open-access crime data with greenspace data supplied by the Greater Information for Greater London service. Using interrupted time series analyses, we estimated seasonality-adjusted associations between the onset of COVID-19 restrictions and park crimes. Results: Overall (1565.7, 95% confidence intervals [CI] 1021.9 to 2109.5) and antisocial behaviour crimes (1772.7, 95% CI 823.6-2721.7) increased in London parks during the first full month of COVID-19 restrictions (April 2020). There were no notable trends in park crimes in London prior to the onset of restrictions, but overall and antisocial behaviour crimes decreased after the onset of restrictions at a rate of 156.4 (95% CI -220.25 to -92.51) and 164.7 (95% CI -280.68 to -48.74) crimes/months, respectively. Conclusions: Overall park crimes increased during the first full month of the COVID-19 restrictions, largely driven by an increase in antisocial behaviours. Additional research is needed to identify the specific misdemeanours that accounted for this rise in antisocial behaviours and to investigate their downstream impacts (e.g. increases in policing costs or decreases in perceived park safety).

Bidirectional associations of accelerometer-assessed physical activity and sedentary time with physical function among older English adults: the EPIC-Norfolk cohort study.

To develop healthy ageing interventions, longitudinal associations between objectively assessed physical behaviours and physical function need to be better understood. We assessed associations between accelerometer-assessed total physical activity (PA), moderate-to-vigorous physical activity (MVPA), light physical activity (LPA), sedentary time and prolonged sedentary bout time, and clinically assessed physical function (grip strength, usual walking speed (UWS), chair stand speed) at two time-points in 3188 participants (≥ 60 years) of the EPIC-Norfolk study. Bidirectional associations were assessed using multivariable linear regression. Over an average of 6.1 years, baseline physical behaviours (greater total PA, MVPA and LPA, and less sedentary time) were associated with better subsequent walking and chair stand speed. Better baseline physical function was associated with better follow-up physical behaviours. There were no bidirectional associations between changes in physical behaviours and grip strength. Improvements in UWS were associated with improvements in all physical behaviours. Improvements in chair stand speed were associated with improvements in total PA, MVPA, and sedentary bout time. Improvements in physical behaviours were associated with improvements in UWS (3.1 cm/s/yr per 100 cpm/yr  total PA, 3.6 cm/s/yr per hr/day/yr MVPA, 2.5 cm/s/yr per hr/day/yr LPA, - 2.9 cm/s/yr per hour/day/yr sedentary time, and - 1.6 cm/s/yr per hr/day/yr prolonged sedentary bout time). Only improvements in total PA, MVPA and sedentary bout time were associated with improvements in chair stand speed. In conclusion, we found bidirectional associations between changes in some physical behaviours and physical function and between baseline physical behaviours and subsequent physical function, highlighting the importance of considering the full range of physical behaviours to promote healthy ageing. Supplementary Information: The online version contains supplementary material available at 10.1007/s10433-022-00733-y.

Rethinking walkability and developing a conceptual definition of active living environments to guide research and practice.

BACKGROUND: Walkability is a popular term used to describe aspects of the built and social environment that have important population-level impacts on physical activity, energy balance, and health. Although the term is widely used by researchers, practitioners, and the general public, and multiple operational definitions and walkability measurement tools exist, there are is no agreed-upon conceptual definition of walkability. METHOD: To address this gap, researchers from Memorial University of Newfoundland hosted "The Future of Walkability Measures Workshop" in association with researchers from the Canadian Urban Environmental Health Research Consortium (CANUE) in November 2017. During the workshop, trainees, researchers, and practitioners worked together in small groups to iteratively develop and reach consensus about a conceptual definition and name for walkability. The objective of this paper was to discuss and propose a conceptual definition of walkability and related concepts. RESULTS: In discussions during the workshop, it became clear that the term walkability leads to a narrow conception of the environmental features associated with health as it inherently focuses on walking. As a result, we suggest that the term Active Living Environments, as has been previously proposed in the literature, are more appropriate. We define Active Living Environments (ALEs) as the emergent natural, built, and social properties of neighbourhoods that promote physical activity and health and allow for equitable access to health-enhancing resources. CONCLUSIONS: We believe that this broader conceptualization allows for a more comprehensive understanding of how built, natural, and social environments can contribute to improved health for all members of the population.

Effectiveness of Minimal Contact Interventions: An RCT.

INTRODUCTION: Around 23% of adults worldwide are insufficiently active. Wearable devices paired with virtual coaching software could increase physical activity. The effectiveness of 3 minimal contact interventions (paper-based physical activity diaries, activity trackers, and activity trackers coupled with virtual coaching) in increasing physical activity energy expenditure and cardiorespiratory fitness were compared over 12 weeks among inactive adults. METHODS: This was an open label, parallel-group RCT. Inactive adults (aged ≥18 years, N=488) were randomized to no intervention (Control; n=121), paper-based diary (Diary; n=124), activity tracker (Activity Band; n=122), or activity tracker plus virtual coaching (Activity Band PLUS; n=121) groups. Coprimary outcomes included 12-week changes in physical activity energy expenditure and fitness (May 2012-January 2014). Analyses were conducted in 2019-2020. RESULTS: There were no differences between groups overall (physical activity energy expenditure: p=0.114, fitness: p=0.417). However, there was a greater increase in physical activity energy expenditure (4.21 kJ/kg/day, 95% CI=0.42, 8.00) in the Activity Band PLUS group than in the Diary group. There were also greater decreases in BMI and body fat percentage in the Activity Band PLUS group than in the Control group (BMI= -0.24 kg/m2, 95% CI= -0.45, -0.03; body fat= -0.48%, 95% CI= -0.88, -0.08) and in theActivity Band PLUS group than in the Diary group (BMI= -0.30 kg/m2, 95% CI= -0.50, -0.09; body fat= -0.57%, 95% CI= -0.97, -0.17). CONCLUSIONS: Coupling activity trackers with virtual coaching may facilitate increases in physical activity energy expenditure compared with a traditional paper‒based physical activity diary intervention and improve some secondary outcomes compared with a traditional paper‒based physical activity diary intervention or no intervention. TRIAL REGISTRATION: This study is registered at www.clinicaltrials.gov ISRCTN31844443.

Correlates of change in accelerometer-assessed total sedentary time and prolonged sedentary bouts among older English adults: results from five-year follow-up in the EPIC-Norfolk cohort.

BACKGROUND: Development of effective strategies to reduce sedentary time among older adults necessitates understanding of its determinants but longitudinal studies of this utilising objective measures are scarce. METHODS: Among 1536 older adults (≥60 years) in the EPIC-Norfolk study, sedentary time was assessed for seven days at two time-points using accelerometers. We assessed associations of change in total and prolonged bouts of sedentary time (≥ 30 minutes) with change in demographic and behavioural factors using multi-level regression. RESULTS: Over follow-up (5.3±1.9 years), greater increases in total sedentary time were associated with older age, being male, higher rate of increase in BMI, lower rate of increase in gardening (0.5 min/day/yr greater sedentary time per hour/week/yr less gardening, 95% CI 0.1, 1.0), a lower rate of increase in walking (0.2 min/day/yr greater sedentary time per hour/week/yr less walking, 95% CI 0.1, 0.3) and a higher rate of increase in television viewing. Correlates of change in prolonged sedentary bouts were similar. CONCLUSION: Individuals in specific sub-groups (older, male, higher BMI) and who differentially participate in certain behaviours (less gardening, less walking and more television viewing) but not others increase their sedentary time at a higher rate than others; utilising this information could inform successful intervention content and targeting.

Cross-sectional and prospective associations between active living environments and accelerometer-assessed physical activity in the EPIC-Norfolk cohort.

The environments in which young and middle-aged adults live may influence their physical activity (PA) behaviours. These associations are less clear among older adults. We estimated cross-sectional and prospective associations of population density, junction density, and land use mix and perceived active living environments with accelerometer-assessed PA in a cohort of older adults. Adults living in more dense and mixed neighbourhoods had less optimal activity profiles at baseline and less optimal changes in activity. Better perceptions were associated with more overall PA at baseline. Interventions for older adults may wish to target individuals living in more dense and mixed neighbourhoods.

Effects of Mobile Health App Interventions on Sedentary Time, Physical Activity, and Fitness in Older Adults: Systematic Review and Meta-Analysis.

BACKGROUND: High sedentary time, low physical activity (PA), and low physical fitness place older adults at increased risk of chronic diseases, functional decline, and premature mortality. Mobile health (mHealth) apps, apps that run on mobile platforms, may help promote active living. OBJECTIVE: We aimed to quantify the effect of mHealth app interventions on sedentary time, PA, and fitness in older adults. METHODS: We systematically searched five electronic databases for trials investigating the effects of mHealth app interventions on sedentary time, PA, and fitness among community-dwelling older adults aged 55 years and older. We calculated pooled standardized mean differences (SMDs) in these outcomes between the intervention and control groups after the intervention period. We performed a Cochrane risk of bias assessment and Grading of Recommendations, Assessment, Development, and Evaluation certainty assessment. RESULTS: Overall, six trials (486 participants, 66.7% [324/486] women; age mean 68 [SD 6] years) were included (five of these trials were included in the meta-analysis). mHealth app interventions may be associated with decreases in sedentary time (SMD=-0.49; 95% CI -1.02 to 0.03), increases in PA (506 steps/day; 95% CI -80 to 1092), and increases in fitness (SMD=0.31; 95% CI -0.09 to 0.70) in trials of 3 months or shorter and with increases in PA (753 steps/day; 95% CI -147 to 1652) in trials of 6 months or longer. Risk of bias was low for all but one study. The quality of evidence was moderate for PA and sedentary time and low for fitness. CONCLUSIONS: mHealth app interventions have the potential to promote changes in sedentary time and PA over the short term, but the results did not achieve statistical significance, possibly because studies were underpowered by small participant numbers. We highlight a need for larger trials with longer follow-up to clarify if apps deliver sustained clinically important effects.

Do older English adults exhibit day-to-day compensation in sedentary time and in prolonged sedentary bouts? An EPIC-Norfolk cohort analysis.

INTRODUCTION: Compensatory behaviours may be one of the reasons for the limited success of sedentary time interventions in older adults, but this possibility remains unexplored. Activity compensation is the idea that if we change activity levels at one time we compensate for them at a later time to maintain a set point. We aimed to assess, among adults aged ≥60 years, whether sedentary time and time spent in prolonged sedentary bouts (≥30 mins) on one day were associated with sedentary time and time spent in prolonged sedentary bouts (≥30 mins) on the following day. We also sought to determine whether these associations varied by sociodemographic and comorbid factors. METHODS: Sedentary time was assessed for seven days using hip-worn accelerometers (ActiGraph GT1M) for 3459 adults who participated in the EPIC-Norfolk Study between 2004 and 2011. We assessed day-to-day associations in total and prolonged bouts of sedentary time using multi-level regressions. We included interaction terms to determine whether associations varied by age, sex, smoking, body mass index, social class, retirement, education and comorbid factors (stroke, diabetes, myocardial infarction and cancer). RESULTS: Participants (mean age = 70.3, SD = 6.8 years) accumulated 540 sedentary mins/day (SD = 80.1). On any given day, every 60 minutes spent in sedentary time was associated with 9.9 extra sedentary minutes on the following day (95% CI 9.0, 10.2). This association was greater in non-retired compared to retired participants (non-retired 2.57 extra minutes, p = 0.024) and in current compared to former and never-smokers (5.26 extra mins for current vs former; 5.52 extra mins for current vs never, p = 0.023 and 0.017, respectively). On any given day, every 60 minutes spent in prolonged bouts was associated with 7.8 extra minutes in these bouts the following day (95% CI 7.6, 8.4). This association was greater in older individuals (0.18 extra minutes/year of age, 95% CI 0.061, 0.29), and for retired versus non-retired (retired 2.74 extra minutes, 95% CI 0.21, 5.74). CONCLUSION: Older adults did not display day-to-day compensation. Instead, individuals demonstrate a large stable component of day-to-day time spent sedentary and in prolonged bouts with a small but important capacity for positive variation. Therefore older adults appear to be largely habitual in their sedentary behaviour. Strategies to augment these patterns may be possible, given they may differ by age, smoking, and working status.

Driving status, travel modes and accelerometer-assessed physical activity in younger, middle-aged and older adults: a prospective study of 90 810 UK Biobank participants.

BACKGROUND: Associations between driving and physical-activity (PA) intensities are unclear, particularly among older adults. We estimated prospective associations of travel modes with total PA, sedentary time (ST), light-intensity PA (LPA), and moderate-to-vigorous intensity PA (MVPA) among adults aged 39-70 years. METHODS: We studied 90 810 UK Biobank participants (56.1 ± 7.8 years). Driving status, specific travel modes (non-work travel; commuting to/from work) and covariates were assessed by questionnaire (2006-10). PA was assessed over 7 days by wrist-worn accelerometers (2013-15). We estimated associations using overall and age-stratified multivariable linear-regression models. RESULTS: Drivers accumulated 1.4% more total PA (95% confidence interval: 0.9, 1.9), 11.2 min/day less ST (-12.9, -9.5), 12.2 min/day more LPA (11.0, 13.3) and 0.9 min/day less MVPA (-1.6, -0.2) than non-drivers. Compared with car/motor-vehicle users, cyclists and walkers had the most optimal activity profiles followed by mixed-mode users (e.g. for non-work travel, cyclists: 10.7% more total PA, 9.0, 12.4; 20.5 min/day less ST, -26.0, -15.0; 14.5 min/day more MVPA, 12.0, 17.2; walkers: 4.2% more total PA, 3.5, 5.0; 7.5 min/day less ST -10.2, -4.9; 10.1 min/day more MVPA, 8.9, 11.3; mixed-mode users: 2.3% more total PA, 1.9, 2.7; 3.4 min/day less ST -4.8, -2.1; 4.9 min/day more MVPA, 4.3, 5.5). Some associations varied by age (p interaction < 0.05), but these differences appeared small. CONCLUSIONS: Assessing specific travel modes rather than driving status alone may better capture variations in activity. Walking, cycling and, to a lesser degree, mixed-mode use are associated with more optimal activity profiles in adults of all ages.

Descriptive epidemiology of changes in objectively measured sedentary behaviour and physical activity: six-year follow-up of the EPIC-Norfolk cohort.

BACKGROUND: Sedentary time increases and total physical activity decreases with age. The magnitude and correlates of changes in sedentary time, light-intensity physical activity (LPA), moderate-to-vigorous intensity physical activity (MVPA), and overall physical activity remain unclear. We quantified these changes and identified their individual and sociodemographic correlates. METHODS: We used data from 1259 adults (67.8 ± 6.9 years; 41.9% women) who participated in the EPIC-Norfolk Study. Activity was assessed at baseline (2004-2011) and follow-up (2012-2016) for 7 days using accelerometers. Potential correlates of change were specified a priori. We used unadjusted and adjusted sex-stratified linear regressions to identify correlates of change. RESULTS: Only 3.7% of adults met the current MVPA recommendations. Sedentary time increased by 3.0 min/day/year (SD = 12.3). LPA, MVPA, and overall PA decreased by 1.7 min/day/year (SD = 5.4), 3.0 min/day/year (SD = 6.0), and 8.8 cpm/year (SD = 18.8), respectively. Correlates of greater rates of increase in sedentary time included older age and higher BMI in men, and older age, higher BMI, smoking, and urban dwelling in women. Correlates of greater rates of decrease in physical activity included older age, higher BMI, living alone, depression, car use, and/or fair/poor self-rated health in men, and older age, higher BMI, depression, smoking, and/or urban dwelling in women (e.g. depressed women had a 1.0 min/day/year greater rate of decline in MVPA than non-depressed women, 95% CI -1.8, - 0.2). CONCLUSIONS: Most (> 95%) adults are insufficiently active. Sedentary time increases and LPA, MVPA and overall physical activity decreases over time, with more pronounced rates of change observed in specific sub-groups (e.g. among older and depressed adults). To promote active living, the correlates of these changes should be considered in future interventions.

Laboratory-Assessed Markers of Cardiometabolic Health and Associations with GIS-Based Measures of Active-Living Environments.

Active-living-friendly environments have been linked to physical activity, but their relationships with specific markers of cardiometabolic health remain unclear. We estimated the associations between active-living environments and markers of cardiometabolic health, and explored the potential mediating role of physical activity in these associations. We used data collected on 2809 middle-aged adults who participated in the Canadian Health Measures Survey (2007⁻2009; 41.5 years, SD = 15.1). Environments were assessed using an index that combined GIS-derived measures of street connectivity, land use mix, and population density. Body mass index (BMI), systolic blood pressure (SBP), hemoglobin A1c, and cholesterol were assessed in a laboratory setting. Daily step counts and moderate-to-vigorous intensity physical activity (MVPA) were assessed for seven days using accelerometers. Associations were estimated using robust multivariable linear regressions adjusted for sociodemographic factors that were assessed via questionnaire. BMI was 0.79 kg/m² lower (95% confidence interval (CI) -1.31, -0.27) and SBP was 1.65 mmHg lower (95% CI -3.10, -0.20) in participants living in the most active-living-friendly environments compared to the least, independent of daily step counts or MVPA. A 35.4 min/week difference in MPVA (95% CI 24.2, 46.6) was observed between residents of neighborhoods in the highest compared to the lowest active-living-environment quartiles. Cycling to work rates were also the highest in participants living in the highest living-environment quartiles (e.g., Q4 vs. Q1: 10.4% vs. 4.9%). Although active-living environments are associated with lower BMI and SBP, and higher MVPA and cycling rates, neither daily step counts nor MVPA appear to account for environment⁻BMI/SBP relationships. This suggests that other factors not assessed in this study (e.g., food environment or unmeasured features of the social environment) may explain this relationship.

Steps, moderate-to-vigorous physical activity, and cardiometabolic profiles.

The relative benefits of meeting the current moderate-to-vigorous intensity physical activity (MVPA) and active step count recommendations are unknown. Using robust linear regressions, we compared cardiometabolic marker differences (blood pressure, lipid levels, Homeostatic Model Assessment of Insulin Resistance (HOMA-IR), hemoglobin A1C, C-reactive protein (CRP), and body mass index (BMI)) across MVPA (150min/week) and step (10,000 steps/day) thresholds and between step categories (low active: 5000 to 7499, somewhat active: 7500 to 9999, and active: ≥10,000 steps/day vs. inactive: <5000 steps/day) in approximately 6000 Canadian adults (41.5years, SD 14.9). Differences across MVPA and step thresholds were similar but additional benefits were observed for BMI and A1C for the MVPA target (i.e., above vs. below 150min/week MVPA: -1.02kg/m2 (95% Confidence Interval [CI] -1.25 to -0.80) and -0.04% (95% CI -0.06 to -0.02); above vs. below ≥10,000 steps/day: -0.40kg/m2 (95% CI -0.63 to -0.16) and 0.01% (95% CI -0.01 to 0.03)). In terms of steps categories, the greatest incremental improvement was achieved at the somewhat active threshold (e.g., somewhat active vs. inactive: -0.90kg/m2, 95% CI -1.28 to -0.53; low active vs. inactive: -0.36kg/m2, 95% CI -0.73 to 0.02). Additional benefits beyond the 10,000 step/day threshold were limited (e.g., -0.93kg/m2, 95% CI -1.30 to -0.57). Given that most benefits to markers of cardiometabolic health were at the ≥7500 step/day threshold and that there was some additional benefit across the 150min/week MVPA threshold compared to a 10,000 steps/day threshold, we suggest aiming for ≥7500 steps/day and then advancing to a 150min/MVPA goal.

Lexical neutrality in environmental health research: Reflections on the term walkability.

Neighbourhood environments have important implications for human health. In this piece, we reflect on the environments and health literature and argue that precise use of language is critical for acknowledging the complex and multifaceted influence that neighbourhood environments may have on physical activity and physical activity-related outcomes. Specifically, we argue that the term "neighbourhood walkability", commonly used in the neighbourhoods and health literature, constrains recognition of the breadth of influence that neighbourhood environments might have on a variety of physical activity behaviours. The term draws attention to a single type of physical activity and implies that a universal association exists when in fact the literature is quite mixed. To maintain neutrality in this area of research, we suggest that researchers adopt the term "neighbourhood physical activity environments" for collective measures of neighbourhood attributes that they wish to study in relation to physical activity behaviours or physical activity-related health outcomes.

Neighbourhood walkability and home neighbourhood-based physical activity: an observational study of adults with type 2 diabetes.

BACKGROUND: Converging international evidence suggests that diabetes incidence is lower among adults living in more walkable neighbourhoods. The association between walkability and physical activity (PA), the presumed mediator of this relationship, has not been carefully examined in adults with type 2 diabetes. We investigated the associations of walkability with total PA occurring within home neighbourhoods and overall PA, irrespective of location. METHODS: Participants (n = 97; 59.5 ± 10.5 years) were recruited through clinics in Montreal (QC, Canada) and wore a GPS-accelerometer device for 7 days. Total PA was expressed as the total Vector of the Dynamic Body Acceleration. PA location was determined using a Global Positioning System (GPS) device (SIRF IV chip). Walkability (street connectivity, land use mix, population density) was assessed using Geographical Information Systems software. The cross-sectional associations between walkability and location-based PA were estimated using robust linear regressions adjusted for age, body mass index, sex, university education, season, car access, residential self-selection, and wear-time. RESULTS: A one standard deviation (SD) increment in walkability was associated with 10.4 % of a SD increment in neighbourhood-based PA (95 % confidence interval (CI) 1.2, 19.7) - equivalent to 165 more steps/day (95 % 19, 312). Car access emerged as an important predictor of neighbourhood-based PA (Not having car access: 38.6 % of a SD increment in neighbourhood-based PA, 95 % CI 17.9, 59.3). Neither walkability nor car access were conclusively associated with overall PA. CONCLUSIONS: Higher neighbourhood walkability is associated with higher home neighbourhood-based PA but not with higher overall PA. Other factors will need to be leveraged to facilitate meaningful increases in overall PA among adults with type 2 diabetes.

Neighbourhood Walkability and Daily Steps in Adults with Type 2 Diabetes.

INTRODUCTION: There is evidence that greater neighbourhood walkability (i.e., neighbourhoods with more amenities and well-connected streets) is associated with higher levels of total walking in Europe and in Asia, but it remains unclear if this association holds in the Canadian context and in chronic disease populations. We examined the relationships of different walkability measures to biosensor-assessed total walking (i.e., steps/day) in adults with type 2 diabetes living in Montreal (QC, Canada). MATERIALS AND METHODS: Participants (60.5±10.4 years; 48.1% women) were recruited through McGill University-affiliated clinics (June 2006 to May 2008). Steps/day were assessed once per season for one year with pedometers. Neighbourhood walkability was evaluated through participant reports, in-field audits, Geographic Information Systems (GIS)-derived measures, and the Walk Score®. Relationships between walkability and daily steps were estimated using Bayesian longitudinal hierarchical linear regression models (n = 131). RESULTS: Participants who reported living in the most compared to the least walkable neighbourhoods completed 1345 more steps/day (95% Credible Interval: 718, 1976; Quartiles 4 versus 1). Those living in the most compared to the least walkable neighbourhoods (based on GIS-derived walkability) completed 606 more steps per day (95% CrI: 8, 1203). No statistically significant associations with steps were observed for audit-assessed walkability or the Walk Score®. CONCLUSIONS: Adults with type 2 diabetes who perceived their neighbourhoods as more walkable accumulated more daily steps. This suggests that knowledge of local neighborhood features that enhance walking is a meaningful predictor of higher levels of walking and an important component of neighbourhood walkability.

Neighbourhood walkability, daily steps and utilitarian walking in Canadian adults.

OBJECTIVES: To estimate the associations of neighbourhood walkability (based on Geographic Information System (GIS)-derived measures of street connectivity, land use mix, and population density and the Walk Score) with self-reported utilitarian walking and accelerometer-assessed daily steps in Canadian adults. DESIGN: A cross-sectional analysis of data collected as part of the Canadian Health Measures Survey (2007-2009). SETTING: Home neighbourhoods (500 m polygonal street network buffers around the centroid of the participant's postal code) located in Atlantic Canada, Québec, Ontario, the Prairies and British Columbia. PARTICIPANTS: 5605 individuals participated in the survey. 3727 adults (≥18 years) completed a computer-assisted interview and attended a mobile clinic assessment. Analyses were based on those who had complete exposure, outcome and covariate data (n=2949). MAIN EXPOSURE MEASURES: GIS-derived walkability (based on land use mix, street connectivity and population density); Walk Score. MAIN OUTCOME MEASURES: Self-reported utilitarian walking; accelerometer-assessed daily steps. RESULTS: No important relationship was observed between neighbourhood walkability and daily steps. Participants who reported more utilitarian walking, however, accumulated more steps (<1 h/week: 6613 steps/day, 95% CI 6251 to 6975; 1 to 5 h/week: 6768 steps/day, 95% CI 6420 to 7117; ≥6 h/week: 7391 steps/day, 95% CI 6972 to 7811). There was a positive graded association between walkability and odds of walking ≥1 h/week for utilitarian purposes (eg, Q4 vs Q1 of GIS-derived walkability: OR=1.66, 95% CI 1.31 to 2.11; Q3 vs Q1: OR=1.41, 95% CI 1.14 to 1.76; Q2 vs Q1: OR=1.13, 95% CI 0.91 to 1.39) independent of age, sex, body mass index, married/common law status, annual household income, having children in the household, immigrant status, mood disorder, perceived health, ever smoker and season. CONCLUSIONS: Contrary to expectations, living in more walkable Canadian neighbourhoods was not associated with more total walking. Utilitarian walking and daily steps were, however, correlated and walkability demonstrated a positive graded relationship with utilitarian walking.

Associations between neighbourhood walkability and daily steps in adults: a systematic review and meta-analysis.

BACKGROUND: Higher street connectivity, land use mix and residential density (collectively referred to as neighbourhood walkability) have been linked to higher levels of walking. The objective of our study was to summarize the current body of knowledge on the association between neighbourhood walkability and biosensor-assessed daily steps in adults. METHODS: We conducted a systematic search of PubMed, SCOPUS, and Embase (Ovid) for articles published prior to May 2014 on the association between walkability (based on Geographic Information Systems-derived street connectivity, land use mix, and/or residential density) and daily steps (pedometer or accelerometer-assessed) in adults. The mean differences in daily steps between adults living in high versus low walkable neighbourhoods were pooled across studies using a Bayesian hierarchical model. RESULTS: The search strategy yielded 8,744 unique abstracts. Thirty of these underwent full article review of which six met the inclusion criteria. Four of these studies were conducted in Europe and two were conducted in Asia. A meta-analysis of four of these six studies indicates that participants living in high compared to low walkable neighbourhoods accumulate 766 more steps per day (95 % credible interval 250, 1271). This accounts for approximately 8 % of recommended daily steps. CONCLUSIONS: The results of European and Asian studies support the hypothesis that higher neighbourhood walkability is associated with higher levels of biosensor-assessed walking in adults. More studies on this association are needed in North America.