Alice M. Dalton

Patterns and predictors of changes in active commuting over 12 months

Objective To assess the predictors of uptake and maintenance of walking and cycling, and of switching to the car as the usual mode of travel, for commuting. Methods 655 commuters in Cambridge, UK reported all commuting trips using a seven-day recall instrument in 2009 and 2010. Individual and household characteristics, psychological measures relating to car use and environmental conditions on the route to work were self-reported in 2009. Objective environmental characteristics were assessed using Geographical Information Systems. Associations between uptake and maintenance of commuting behaviours and potential predictors were modelled using multivariable logistic regression. Results Mean within-participant changes in commuting were relatively small (walking: + 3.0 min/week, s.d. = 66.7; cycling: − 5.3 min/week, s.d. = 74.7). Self-reported and objectively-assessed convenience of public transport predicted uptake of walking and cycling respectively, while convenient cycle routes predicted uptake of cycling and a pleasant route predicted maintenance of walking. A lack of free workplace parking predicted uptake of walking and alternatives to the car. Less favourable attitudes towards car use predicted continued use of alternatives to the car. Conclusions Improving the convenience of walking, cycling and public transport and limiting the availability of workplace car parking may promote uptake and maintenance of active commuting.

Development of methods to objectively identify time spent using active and motorised modes of travel to work: how do self-reported measures compare?

BackgroundActive commuting may make an important contribution to population health. Accurate measures of these behaviours are required, but it is unknown how self-reported estimates compare to those derived from objective measures. We sought to develop methods for objectively deriving time spent in specific travel behaviours from a combination of locational and activity data, and to assess the convergent validity of two self-reported estimates.MethodsIn 2010 and 2011, a sub-sample of participants from the Commuting and Health in Cambridge study concurrently completed objective monitoring using combined heart rate and movement sensors and global positioning system devices and reported their past-week commuting in a questionnaire (modes used, and usual time spent walking and cycling per trip) and in a day-by-day diary (all modes and durations). Automated and manual approaches were used to objectively identify total time spent using active and motorised modes. Agreement between self-reported and objectively-derived times was assessed using Lin’s concordance coefficients, Bland-Altman plots and signed-rank tests.ResultsCompared to objective assessments, day-by-day diary estimates of time spent using active modes on the commute were overestimated by a mean of 1.1 minutes/trip (95% limits of agreement (LOA): -7.7 to 9.9, p < 0.001). The magnitude of overestimation was slightly larger, but not significant (p = 0.247), when walking or cycling was used alone (mean: 2.4 minutes/trip, 95% LOA: -6.8 to 11.5). Total time spent on the commute was overestimated by a mean of 1.9 minutes/trip (95% LOA: -15.3 to 19.0, p < 0.001). The mean differences between self-reported usual time and objective estimates were -1.1 minutes/trip (95% LOA: -8.7 to 6.4) for cycling and +2.4 minutes/trip (95% LOA: -10.9 to 15.7) for walking. Mean differences between usual and daily estimates of time were <1 minute/trip for both walking and cycling.ConclusionsWe developed a novel method of combining objective data to identify time spent using active and motorised modes, and total time spent commuting. Compared to objectively-derived times, self-reported times spent active commuting were slightly overestimated with wide LOA, suggesting that they should be used with caution to infer aggregate weekly quantities of activity on the commute at the individual level.

The association between neighbourhood greenspace and type 2 diabetes in a large cross-sectional study

Objective To investigate the relationship between neighbourhood greenspace and type 2 diabetes. Design Cross-sectional. Setting 3 diabetes screening studies conducted in Leicestershire, UK in 2004–2011. The percentage of greenspace in the participants home neighbourhood (3 km radius around home postcode) was obtained from a Land Cover Map. Demographic and biomedical variables were measured at screening. Participants 10 476 individuals (6200 from general population; 4276 from high-risk population) aged 20–75 years (mean 59 years); 47% female; 21% non-white ethnicity. Main outcome measure Screen-detected type 2 diabetes (WHO 2011 criteria). Results Increased neighbourhood greenspace was associated with significantly lower levels of screen-detected type 2 diabetes. The ORs (95% CI) for screen-detected type 2 diabetes were 0.97 (0.80 to 1.17), 0.78 (0.62 to 0.98) and 0.67 (0.49 to 0.93) for increasing quartiles of neighbourhood greenspace compared with the lowest quartile after adjusting for ethnicity, age, sex, area social deprivation score and urban/rural status (Ptrend=0.01). This association remained on further adjustment for body mass index, physical activity, fasting glucose, 2 h glucose and cholesterol (OR (95% CI) for highest vs lowest quartile: 0.53 (0.35 to 0.82); Ptrend=0.01). Conclusions Neighbourhood greenspace was inversely associated with screen-detected type 2 diabetes, highlighting a potential area for targeted screening as well as a possible public health area for diabetes prevention. However, none of the risk factors that we considered appeared to explain this association, and thus further research is required to elicit underlying mechanisms. Trial registration number This study uses data from three studies (NCT00318032, NCT00677937, NCT00941954).

Using spatial equity analysis in the process evaluation of environmental interventions to tackle obesity: the healthy towns programme in England

IntroductionProcess evaluations of environmental public health interventions tend not to consider issues of spatial equity in programme delivery. However, an intervention is unlikely to be effective if it is not accessible to those in need. Methods are required to enable these considerations to be integrated into evaluations. Using the Healthy Towns programme in England, we demonstrate the potential of spatial equity analysis in the evaluation of environmental interventions for diet and physical activity, examining whether the programme was delivered to those in greatest need.MethodsLocations of new physical infrastructure, such as cycle lanes, gyms and allotments, were mapped using a geographic information system. A targeting ratio was computed to indicate how well-located the infrastructure was in relation to those at whom it was specifically aimed, as detailed in the relevant project documentation, as well as to generally disadvantaged populations defined in terms of UK Census data on deprivation, age and ethnicity. Differences in targeting were examined using Kruskal-Wallis and t-tests.ResultsThe 183 separate intervention components identified were generally well located, with estimated targeting ratios above unity for all population groups of need, except for black and ethnic minorities and children aged 5–19 years. There was no evidence that clustering of population groups influenced targeting, or that trade-offs existed when components were specifically targeted at more than one group.ConclusionsThe analysis of spatial equity is a valuable initial stage in assessing the provision of environmental interventions. The Healthy Towns programme can be described as well targeted in that interventions were for the most part located near populations of need.

The association between air pollution and type 2 diabetes in a large cross-sectional study in Leicester: The CHAMPIONS Study

BACKGROUND Observational evidence suggests there is an association between air pollution and type 2 diabetes; however, there is high risk of bias. OBJECTIVE To investigate the association between air pollution and type 2 diabetes, while reducing bias due to exposure assessment, outcome assessment, and confounder assessment. METHODS Data were collected from 10,443 participants in three diabetes screening studies in Leicestershire, UK. Exposure assessment included standard, prevailing estimates of outdoor nitrogen dioxide and particulate matter concentrations in a 1×1km area at the participants home postcode. Three-year exposure was investigated in the primary analysis and one-year exposure in a sensitivity analysis. Outcome assessment included the oral glucose tolerance test for type 2 diabetes. Confounder assessment included demographic factors (age, sex, ethnicity, smoking, area social deprivation, urban or rural location), lifestyle factors (body mass index and physical activity), and neighbourhood green space. RESULTS Nitrogen dioxide and particulate matter concentrations were associated with type 2 diabetes in unadjusted models. There was no statistically significant association between nitrogen dioxide concentration and type 2 diabetes after adjustment for demographic factors (odds: 1.08; 95% CI: 0.91, 1.29). The odds of type 2 diabetes was 1.10 (95% CI: 0.92, 1.32) after further adjustment for lifestyle factors and 0.91 (95% CI: 0.72, 1.16) after yet further adjustment for neighbourhood green space. The associations between particulate matter concentrations and type 2 diabetes were also explained away by demographic factors. There was no evidence of exposure definition bias. CONCLUSIONS Demographic factors seemed to explain the association between air pollution and type 2 diabetes in this cross-sectional study. High-quality longitudinal studies are needed to improve our understanding of the association.

Neighbourhood greenspace is associated with a slower decline in physical activity in older adults: A prospective cohort study

Maintaining physical activity in later life is important for maintaining health and function. Activity outdoors, such as walking, jogging and cycling, may provide an accessible, sociable and practical solution, but maintaining outdoor mobility may be a challenge in later life. Providing green environments which are supportive of physical activity may facilitate this, yet research into how greenspace could be best used is inconclusive. This study evaluates the role of greenspace in protecting against decline in physical activity over time in older adults. Data from the European Prospective Investigation of Cancer Norfolk, UK, cohort 1993–2009 (N=15,672) was used. Linear regression modelling was used to examine the association between exposure to greenspace in the home neighbourhood and change in overall, recreational and outdoor physical activity measured in terms of metabolic equivalent cost (MET) in hours/week. Mediation analysis was conducted to assess if dog walking explained the relationship between greenspace and physical activity change. Models were adjusted for known and hypothesised confounders. People living in greener neighbourhoods experienced less of a decline in physical activity than those living in less green areas. Comparing change for those living in the greenest versus least green quartiles, participants showed a difference in overall physical activity of 4.21 MET hours/week (trend P=0.001), adjusted for baseline physical activity, age, sex, BMI, social class and marital status. This difference was 4.03 MET hours/week for recreational physical activity (trend P<0.001) and 1.28 MET hours/week for outdoor physical activity (trend P=0.007). Dog walking partially mediated the association between greenspace and physical activity change, by 22.6% for overall, 28.1% for recreational and 50.0% for outdoor physical activity (all P<0.001). Greenspace in the home neighbourhood may be protective against decline in physical activity among older people as they age. Dog walking is a potential mechanism in this relationship, and warrants further investigation as a way of maintaining physical activity in later life.

Changes in health in the countries of the UK and 150 English Local Authority areas 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016

Summary Background Previous studies have reported national and regional Global Burden of Disease (GBD) estimates for the UK. Because of substantial variation in health within the UK, action to improve it requires comparable estimates of disease burden and risks at country and local levels. The slowdown in the rate of improvement in life expectancy requires further investigation. We use GBD 2016 data on mortality, causes of death, and disability to analyse the burden of disease in the countries of the UK and within local authorities in England by deprivation quintile. Methods We extracted data from the GBD 2016 to estimate years of life lost (YLLs), years lived with disability (YLDs), disability-adjusted life-years (DALYs), and attributable risks from 1990 to 2016 for England, Scotland, Wales, Northern Ireland, the UK, and 150 English Upper-Tier Local Authorities. We estimated the burden of disease by cause of death, condition, year, and sex. We analysed the association between burden of disease and socioeconomic deprivation using the Index of Multiple Deprivation. We present results for all 264 GBD causes of death combined and the leading 20 specific causes, and all 84 GBD risks or risk clusters combined and 17 specific risks or risk clusters. Findings The leading causes of age-adjusted YLLs in all UK countries in 2016 were ischaemic heart disease, lung cancers, cerebrovascular disease, and chronic obstructive pulmonary disease. Age-standardised rates of YLLs for all causes varied by two times between local areas in England according to levels of socioeconomic deprivation (from 14 274 per 100 000 population [95% uncertainty interval 12 791–15 875] in Blackpool to 6888 [6145–7739] in Wokingham). Some Upper-Tier Local Authorities, particularly those in London, did better than expected for their level of deprivation. Allowing for differences in age structure, more deprived Upper-Tier Local Authorities had higher attributable YLLs for most major risk factors in the GBD. The population attributable fractions for all-cause YLLs for individual major risk factors varied across Upper-Tier Local Authorities. Life expectancy and YLLs have improved more slowly since 2010 in all UK countries compared with 1990–2010. In nine of 150 Upper-Tier Local Authorities, YLLs increased after 2010. For attributable YLLs, the rate of improvement slowed most substantially for cardiovascular disease and breast, colorectal, and lung cancers, and showed little change for Alzheimers disease and other dementias. Morbidity makes an increasing contribution to overall burden in the UK compared with mortality. The age-standardised UK DALY rate for low back and neck pain (1795 [1258–2356]) was higher than for ischaemic heart disease (1200 [1155–1246]) or lung cancer (660 [642–679]). The leading causes of ill health (measured through YLDs) in the UK in 2016 were low back and neck pain, skin and subcutaneous diseases, migraine, depressive disorders, and sense organ disease. Age-standardised YLD rates varied much less than equivalent YLL rates across the UK, which reflects the relative scarcity of local data on causes of ill health. Interpretation These estimates at local, regional, and national level will allow policy makers to match resources and priorities to levels of burden and risk factors. Improvement in YLLs and life expectancy slowed notably after 2010, particularly in cardiovascular disease and cancer, and targeted actions are needed if the rate of improvement is to recover. A targeted policy response is also required to address the increasing proportion of burden due to morbidity, such as musculoskeletal problems and depression. Improving the quality and completeness of available data on these causes is an essential component of this response. Funding Bill & Melinda Gates Foundation and Public Health England.

OP48 Determinants of Active Commuting: Longitudinal Results from the Commuting and Health in Cambridge Study

Background Numerous cross-sectional studies have examined the associations between individual, psychological and environmental characteristics and active commuting, but few longitudinal studies exist to support more robust causal inference. Using two complementary approaches to longitudinal analysis, we aimed to build on this evidence by exploring whether (a) individual, psychological, workplace and route environmental characteristics, (b) changes in route environmental characteristics, were associated with changes in active commuting. Methods 655 adult commuters completed postal questionnaires concerning past-week commuting trips at similar times of year in 2009 and 2010. We computed changes in time spent walking and cycling and the proportion of car trips, and identified those who took up or maintained walking, cycling or alternatives to the car as the usual mode of travel. Using multivariable logistic regression, we assessed the associations between uptake and maintenance of travel behaviours and baseline individual, psychological and perceived and objective environmental characteristics and between changes in active commuting and changes in perceived environmental characteristics of the route to work. Results Mean within-participant changes in active commuting were relatively small (walking: +3.0 minutes/week; cycling: -5.3 minutes/week). A lack of free workplace parking predicted uptake of walking and alternatives to the car, while less favourable attitudes towards car use predicted continued use of alternatives to the car. Self-reported and objectively-assessed convenience of public transport respectively predicted uptake of walking (OR 2.47 [95% CI 1.44, 4.25]) and cycling (2.59 [0.99, 6.78]). Those who reported an increase in the convenience of public transport were more likely to take up alternatives to the car (3.24 [1.28, 8.14]) and those who reported convenient cycle routes at baseline were more likely to take up cycling (2.48 [1.04, 5.93]) and alternatives to the car (4.65 [1.45, 14.92]). Those who reported an increase in the perceived danger of cycling reported 8% more car trips, whereas those who reported a decrease were more likely to take up alternatives to the car (2.50 [1.07, 5.86]). Discussion Individual, psychological and environmental factors were associated with uptake of active commuting. A few environmental characteristics relating to the convenience and safety of routes for active travel and the convenience of public transport were associated with changes in active commuting both as baseline predictors of change and as dynamic correlates of change, suggesting that these may be suitable targets for interventions to promote walking and cycling to work.