Explaining differential socioeconomic effects in population health interventions: development and application of a new tool to classify intervention agentic demand.

BACKGROUND: The agentic demand of population health interventions (PHIs) might influence how interventions work. Highly agentic interventions (eg, information campaigns) rely on recipients noticing and responding to the intervention. Resources required for individuals to benefit from highly agentic interventions have a socioeconomical pattern, thus agentic demand might affect intervention effectiveness and equity. Systematic evidence exploring these associations is missing due to the absence of adequate tools to classify agentic demands. We aimed to develop such a tool and test its application. METHODS: Our iterative development process involved: (1) systematic identification of diet and physical activity PHIs; (2) coding of intervention actors and actions; (3) data synthesis; (4) expert qualitative feedback; and (5) reliability assessment. We searched nine databases for articles published between Jan 1, 2010, and Aug 17, 2020. For all included articles, we coded the actors (people required to act within an intervention) and their actions (what they were required to do for the intervention to have its intended effects). We combined these codes for similar intervention types to develop overarching schematic flow chart diagrams used to identify concepts, and we organised these into a draft tool. After expert feedback, and we assessed inter-rater reliability of the final version. We applied the final tool in a proof-of-concept review, extracting studies from three existing equity-focused systematic reviews on tool category, overall intervention effect, and differential socioeconomic effects and visualised findings. FINDINGS: We identified three concepts affecting agentic demands of intervention components: exposure, two levels (how recipients encounter the intervention); mechanism of action, five levels; and engagement, two levels (how recipients respond to the intervention). We then combined these concepts to form 20 categories that grouped together interventions with similar agentic demands. In the review, we applied the tool to 26 PHIs that included 163 components. Intervention components were concentrated in a small number of categories, and their categorisation was related to intervention equity but not to effectiveness. INTERPRETATION: We present a novel tool to classify the agentic demand of PHIs and demonstrate its feasibility within a systematic review. Linking intervention types to their effect on inequalities enables these factors to be considered when designing or selecting interventions. Users of the tool can avoid implementing intervention types that are likely to widen inequalities or implement them alongside counter-strategies to minimise any adverse equity effects. Applying this tool within future research, policy, and practice to design, select, evaluate, and synthesise evidence from PHIs has the potential to advance our understanding of how interventions work and their effect on socioeconomic inequalities. FUNDING: Public Health Policy Research Unit (PH-PRU), National Institute for Health and Care Research (NIHR) Policy Research Programme.

Equity impacts of cycling investment in England: A natural experimental study using longitudinally linked individual-level Census data.

Background: Cycling is beneficial for health and the environment but the evidence on the overall and differential impacts of interventions to promote cycling is limited. Here we assess the equity impacts of funding awarded to support cycling in 18 urban areas between 2005 and 2011. Methods: We used longitudinally linked 2001 and 2011 census data from 25,747 individuals in the Office for National Statistics Longitudinal Study of England and Wales. Logistic regression was used to assess the impacts of funding on commute mode as the interaction between time and area (intervention/comparison) in individual-level difference-in-difference analyses, adjusting for a range of potential confounding factors. Differential impacts were examined by age, gender, education and area-level deprivation, and uptake and maintenance of cycling were examined separately. Results: Difference-in-difference analyses showed no intervention impact on cycle commuting prevalence in the whole sample (AOR = 1.08; 95% CI 0.92, 1.26) or among men (AOR = 0.91; 95% CI 0.76, 1.10) but found an intervention effect among women (AOR = 1.56; 95% CI 1.16, 2.10). The intervention promoted uptake of cycling commuting in women (AOR = 2.13; 95% CI 1.56, 2.91) but not men (AOR = 1.19; 95% CI 0.93, 1.51). Differences in intervention effects by age, education and area-level deprivation were less consistent and more modest in magnitude. Conclusions: Living in an intervention area was associated with greater uptake of cycle commuting among women but not men. Potential gender differences in the determinants of transport mode choice should be considered in the design and evaluation of future interventions to promote cycling.

Trends and inequalities in distance to and use of nearest natural space in the context of the 20-min neighbourhood: A 4-wave national repeat cross-sectional study, 2013 to 2019.

The 20-min neighbourhood is a policy priority for governments worldwide; a key feature of this policy is providing access to natural space (NS) within 800 m of home. The study aims were to (1) examine the association between distance to nearest NS and frequent use over time and (2) examine whether frequent use and changes in use were patterned by income and housing tenure over time. Bi-annual Scottish Household Survey data were obtained for 2013 to 2019 (n:42128 aged 16+). Adults were asked the walking distance to their nearest NS, the frequency of visits to this space and their housing tenure, as well as age, sex and income. We examined the association between distance from home of nearest NS, housing tenure, and the likelihood of frequent NS use (visited once a week or more). Two-way interaction terms were further applied to explore variation in the association between tenure and frequent NS use over time. We found that 87% of respondents lived within 10 min walk of a NS, meeting the policy specification for a 20-min neighbourhood. Greater proximity to NS was associated with increased use; individuals living a 6-10 min walk and over 10 min walk were respectively 53% and 78% less likely to report frequent NS use than those living within a 5 min walk. Housing tenure was an important predictor of frequent NS use; private renters and homeowners were more likely to report frequent NS use than social renters. Our findings provide evidence that proximity to NS is a strong predictor of frequent use. Our study provides important evidence that time-based access measures alone do not consider deep-rooted socioeconomic variation in use of NS. Policy makers should ensure a nuanced lens is applied to operationalising and monitoring the 20-min neighbourhood to safeguard against exacerbating existing inequalities.

Using natural experimental studies to guide public health action: turning the evidence-based medicine paradigm on its head.

Despite smaller effect sizes, interventions delivered at population level to prevent non-communicable diseases generally have greater reach, impact and equity than those delivered to high-risk groups. Nevertheless, how to shift population behaviour patterns in this way remains one of the greatest uncertainties for research and policy. Evidence about behaviour change interventions that are easier to evaluate tends to overshadow that for population-wide and system-wide approaches that generate and sustain healthier behaviours. Population health interventions are often implemented as natural experiments, which makes their evaluation more complex and unpredictable than a typical randomised controlled trial (RCT). We discuss the growing importance of evaluating natural experiments and their distinctive contribution to the evidence for public health policy. We contrast the established evidence-based practice pathway, in which RCTs generate 'definitive' evidence for particular interventions, with a practice-based evidence pathway in which evaluation can help adjust the compass bearing of existing policy. We propose that intervention studies should focus on reducing critical uncertainties, that non-randomised study designs should be embraced rather than tolerated and that a more nuanced approach to appraising the utility of diverse types of evidence is required. The complex evidence needed to guide public health action is not necessarily the same as that which is needed to provide an unbiased effect size estimate. The practice-based evidence pathway is neither inferior nor merely the best available when all else fails. It is often the only way to generate meaningful evidence to address critical questions about investing in population health interventions.

A systematic review of the effect of infrastructural interventions to promote cycling: strengthening causal inference from observational data.

BACKGROUND: Previous reviews have suggested that infrastructural interventions can be effective in promoting cycling. Given inherent methodological complexities in the evaluation of such changes, it is important to understand whether study results obtained depend on the study design and methods used, and to describe the implications of the methods used for causality. The aims of this systematic review were to summarize the effects obtained in studies that used a wide range of study designs to assess the effects of infrastructural interventions on cycling and physical activity, and whether the effects varied by study design, data collection methods, or statistical approaches. METHODS: Six databases were searched for studies that evaluated infrastructural interventions to promote cycling in adult populations, such as the opening of cycling lanes, or the expansion of a city-wide cycling network. Controlled and uncontrolled studies that presented data before and after the intervention were included. No language or date restrictions were applied. Data was extracted for any outcome presented (e.g. bikes counted on the new infrastructure, making a bike trip, cycling frequency, cycling duration), and for any purpose of cycling (e.g. total cycling, recreational cycling, cycling for commuting). Data for physical activity outcomes and equity effects was extracted, and quality assessment was conducted following previous methodologies and the UK Medical Research Council guidance on natural experiments. The PROGRESS-Plus framework was used to describe the impact on subgroups of the population. Studies were categorized by outcome, i.e. changes in cycling behavior, or usage of the cycling infrastructure. The relative change was calculated to derive a common outcome across various metrics and cycling purposes. The median relative change was presented to evaluate whether effects differed by methodological aspects. RESULTS: The review included 31 studies and all were conducted within urban areas in high-income countries. Most of the evaluations found changes in favor of the intervention, showing that the number of cyclists using the facilities increased (median relative change compared to baseline: 62%; range: 4 to 438%), and to a lesser extent that cycling behavior increased (median relative change compared to baseline: 22%; range: - 21 to 262%). Studies that tested for statistical significance and studies that used subjective measurement methods (such as surveys and direct observations of cyclists) found larger changes than those that did not perform statistical tests, and those that used objective measurement methods (such as GPS and accelerometers, and automatic counting stations). Seven studies provided information on changes of physical activity behaviors, and findings were mixed. Three studies tested for equity effects following the opening of cycling infrastructure. CONCLUSIONS: Study findings of natural experiments evaluating infrastructural interventions to promote cycling depended on the methods used and the approach to analysis. Studies measuring cycling behavior were more likely to assess actual behavioral change that is most relevant for population health, as compared to studies that measured the use of cycling infrastructure. Triangulation of methods is warranted to overcome potential issues that one may encounter when evaluating environmental changes within the built environment. TRIAL REGISTRATION: The protocol of this study was registered at PROSPERO (CRD42018091079).

Longitudinal associations between built environment characteristics and changes in active commuting.

BACKGROUND: Few studies have assessed the predictors of changes in commuting. This study investigated the associations between physical environmental characteristics and changes in active commuting. METHODS: Adults from the population-based European Prospective Investigation into Cancer (EPIC)-Norfolk cohort self-reported commuting patterns in 2000 and 2007. Active commuters were defined as those who reported 'always' or 'usually' walking or cycling to work. Environmental attributes around the home and route were assessed using Geographical Information Systems. Associations between potential environmental predictors and uptake and maintenance of active commuting were modelled using logistic regression, adjusting for age, sex and BMI. RESULTS: Of the 2757 participants (62% female, median baseline age: 52, IQR: 50-56 years), most were passive commuters at baseline (76%, n = 2099) and did not change their usual commute mode over 7 years (82%, n = 2277). In multivariable regression models, participants living further from work were less likely to take up active commuting and those living in neighbourhoods with more streetlights were more likely to take up active commuting (both p < 0.05). Findings for maintenance were similar: participants living further from work (over 10 km, OR: 0.06; 95% CI: 0.25 to 0.13) and had a main or secondary road on route were more likely to maintain their active commuting (OR: 0.52; 95% CI: 0.28 to 0.98). Those living in neighbourhoods with greater density of employment locations were more likely to maintain their active commuting. CONCLUSIONS: Co-locating residential and employment centres as well as redesigning urban areas to improve safety for pedestrians and cyclists may encourage active commuting. Future evaluative studies should seek to assess the effects of redesigning the built environment on active commuting and physical activity.

Can environmental improvement change the population distribution of walking?

BACKGROUND: Few studies have explored the impact of environmental change on walking using controlled comparisons. Even fewer have examined whose behaviour changes and how. In a natural experimental study of new walking and cycling infrastructure, we explored changes in walking, identified groups who changed in similar ways and assessed whether exposure to the infrastructure was associated with trajectories of walking. METHODS: 1257 adults completed annual surveys assessing walking, sociodemographic and health characteristics and use of the infrastructure (2010-2012). Residential proximity to the new routes was assessed objectively. We used latent growth curve models to assess change in total walking, walking for recreation and for transport, used simple descriptive analysis and latent class analysis (LCA) to identify groups who changed in similar ways and examined factors associated with group membership using multinomial regression. RESULTS: LCA identified five trajectories, characterised by consistently low levels; consistently high levels; decreases; short-lived increases; and sustained increases. Those with lower levels of education and lower incomes were more likely to show both short-lived and sustained increases in walking for transport. However, those with lower levels of education were less likely to take up walking. Proximity to the intervention was associated with both uptake of and short-lived increases in walking for transport. CONCLUSIONS: Environmental improvement encouraged the less active to take up walking for transport, as well as encouraging those who were already active to walk more. Further research should disentangle the role of socioeconomic characteristics in determining use of new environments and changes in walking.

Longitudinal associations of active commuting with wellbeing and sickness absence.

OBJECTIVE: Our aim was to explore longitudinal associations of active commuting (cycling to work and walking to work) with physical wellbeing (PCS-8), mental wellbeing (MCS-8) and sickness absence. METHOD: We used data from the Commuting and Health in Cambridge study (2009 to 2012; n=801) to test associations between: a) maintenance of cycling (or walking) to work over a one year period and indices of wellbeing at the end of that one year period; and b) associations between change in cycling (or walking) to work and change in indices of wellbeing. Linear regression was used for testing associations with PCS-8 and MCS-8, and negative binomial regression for sickness absence. RESULTS: After adjusting for sociodemographic variables, physical activity and physical limitation, those who maintained cycle commuting reported lower sickness absence (0.46, 95% CI: 0.14-0.80; equivalent to one less day per year) and higher MCS-8 scores (1.50, 0.10-2.10) than those who did not cycle to work. The association for sickness absence persisted after adjustment for baseline sickness absence. No significant associations were observed for PCS-8. Associations between change in cycle commuting and change in indices of wellbeing were not significant. No significant associations were observed for walking. CONCLUSIONS: This work provides some evidence of the value of cycle commuting in improving or maintaining the health and wellbeing of adults of working age. This may be important in engaging employers in the promotion of active travel and communicating the benefits of active travel to employees.

Quantifying the physical activity energy expenditure of commuters using a combination of global positioning system and combined heart rate and movement sensors.

BACKGROUND: Active commuting may help to increase adults' physical activity levels. However, estimates of its energy cost are derived from a small number of studies which are laboratory-based or use self-reported measures. METHODS: Adults working in Cambridge (UK) recruited through a predominantly workplace-based strategy wore combined heart rate and movement sensors and global positioning system (GPS) devices for one week, and completed synchronous day-by-day travel diaries in 2010 and 2011. Commuting journeys were delineated using GPS data, and metabolic intensity (standard metabolic equivalents; MET) was derived and compared between journey types using mixed-effects linear regression. RESULTS: 182 commuting journeys were included in the analysis. Median intensity was 1.28 MET for car journeys; 1.67 MET for bus journeys; 4.61 MET for walking journeys; 6.44 MET for cycling journeys; 1.78 MET for journeys made by car in combination with walking; and 2.21 MET for journeys made by car in combination with cycling. The value for journeys made solely by car was significantly lower than those for all other journey types (p<0.04). On average, 20% of the duration of journeys incorporating any active travel (equating to 8 min) was spent in moderate-to-vigorous physical activity (MVPA). CONCLUSIONS: We have demonstrated how GPS and activity data from a free-living sample can be used simultaneously to provide objective estimates of commuting energy expenditure. On average, incorporating walking or cycling into longer journeys provided over half the weekly recommended activity levels from the commute alone. This may be an efficient way of achieving physical activity guidelines and improving population health.

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

BACKGROUND: Active 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. METHODS: In 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. RESULTS: Compared 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. CONCLUSIONS: We 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.

Effectiveness and equity impacts of town-wide cycling initiatives in England: a longitudinal, controlled natural experimental study.

Cycling confers health and environmental benefits, but few robust studies have evaluated large-scale programmes to promote cycling. In England, recent years have seen substantial, town-wide cycling initiatives in six Cycling Demonstration Towns (funded 2005-2011) and 12 Cycling Cities and Towns (funded 2008-2011). The initiatives involved mixtures of capital investment (e.g. cycle lanes) and revenue investment (e.g. cycle training), tailored to each town. This controlled before-after natural experimental study used English census data to examine impacts on the prevalence of travelling to work by bicycle and other modes, comparing changes in the intervention towns with changes in three comparison groups (matched towns, unfunded towns and a national comparison group). We also compared effects between more and less deprived areas, and used random-effects meta-analysis to compare intervention effects between towns. Among 1.3 million commuters in 18 intervention towns, we found that the prevalence of cycling to work rose from 5.8% in 2001 to 6.8% in 2011. This represented a significant increase relative to all three comparison groups (e.g. +0.69 (95% CI 0.60,0.77) percentage points for intervention vs. matched towns). Walking to work also increased significantly compared with comparison towns, while driving to work decreased and public transport use was unchanged. These effects were observed across all fifths of area deprivation, with larger relative changes in deprived areas. There was substantial variation in effect sizes between towns, however, and the average town-level effect on cycling was non-significant (+0.29 (-0.26,0.84) percentage points for intervention vs. matched towns). We conclude that to date, cycling to work has increased (and driving to work decreased) in the intervention towns, in a relatively equitable manner. The variation in effects between towns indicates uncertainty regarding the likely impact of comparable investment in future towns. Nevertheless these results support the case for implementing and evaluating further town-wide cycling initiatives.

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.

Individual, socio-cultural and environmental predictors of uptake and maintenance of active commuting in children: longitudinal results from the SPEEDY study.

BACKGROUND: Active commuting is prospectively associated with physical activity in children. Few longitudinal studies have assessed predictors of change in commuting mode. PURPOSE: To investigate the individual, socio-cultural and environmental predictors of uptake and maintenance of active commuting in 10-year-old children. METHODS: Children were recruited in 2007 and followed-up 12 months later. Children self-reported usual travel mode to school. 31 child, parent, socio-cultural and physical environment characteristics were assessed via self-reported and objective methods. Associations with uptake and maintenance of active travel were studied using multi-level multiple logistic regression models in 2012. RESULTS: Of the 912 children (59.1% girls, mean ± SD baseline age 10.2 ± 0.3 yrs) with complete data, 15% changed their travel mode. Those children who lived less than 1 km from school were more likely to take up (OR: 4.73, 95% CI: 1.97, 11.32, p = 0.001) and maintain active commuting (OR: 2.80 95% CI: 0.98, 7.96, p = 0.02). Children whose parents reported it was inconvenient to use the car for school travel were also more likely to take up (OR: 2.04, 95% CI: 1.08, 3.85, p = 0.027) and maintain their active commuting (OR: 5.43 95% CI: 1.95, 15.13, p = 0.001). Lower socio-economic status and higher road safety were also associated with uptake. CONCLUSIONS: Findings from this longitudinal study suggest that reducing the convenience of the car and improving the convenience of active modes as well as improving the safety of routes to school may promote uptake and maintenance of active commuting and the effectiveness of these interventions should be evaluated.

Healthy travel and the socio-economic structure of car commuting in Cambridge, UK: a mixed-methods analysis.

Car use is associated with substantial health and environmental costs but research in deprived populations indicates that car access may also promote psychosocial well-being within car-oriented environments. This mixed-method (quantitative and qualitative) study examined this issue in a more affluent setting, investigating the socio-economic structure of car commuting in Cambridge, UK. Our analyses involved integrating self-reported questionnaire data from 1142 participants in the Commuting and Health in Cambridge study (collected in 2009) and in-depth interviews with 50 participants (collected 2009-2010). Even in Britain's leading 'cycling city', cars were a key resource in bridging the gap between individuals' desires and their circumstances. This applied both to long-term life goals such as home ownership and to shorter-term challenges such as illness. Yet car commuting was also subject to constraints, with rush hour traffic pushing drivers to start work earlier and with restrictions on, or charges for, workplace parking pushing drivers towards multimodal journeys (e.g. driving to a 'park-and-ride' site then walking). These patterns of car commuting were socio-economically structured in several ways. First, the gradient of housing costs made living near Cambridge more expensive, affecting who could 'afford' to cycle and perhaps making cycling the more salient local marker of Bourdieu's class distinction. Nevertheless, cars were generally affordable in this relatively affluent, highly-educated population, reducing the barrier which distance posed to labour-force participation. Finally, having the option of starting work early required flexible hours, a form of job control which in Britain is more common among higher occupational classes. Following a social model of disability, we conclude that socio-economic advantage can make car-oriented environments less disabling via both greater affluence and greater job control, and in ways manifested across the full socio-economic range. This suggests the importance of combining individual-level 'healthy travel' interventions with measures aimed at creating travel environments in which all social groups can pursue healthy and satisfying lives.

Commuting and health in Cambridge: a study of a 'natural experiment' in the provision of new transport infrastructure.

BACKGROUND: Modifying transport infrastructure to support active travel (walking and cycling) could help to increase population levels of physical activity. However, there is limited evidence for the effects of interventions in this field, and to the best of our knowledge no study has convincingly demonstrated an increase in physical activity directly attributable to this type of intervention. We have therefore taken the opportunity presented by a 'natural experiment' in Cambridgeshire, UK to establish a quasi-experimental study of the effects of a major transport infrastructural intervention on travel behaviour, physical activity and related wider health impacts. DESIGN AND METHODS: The Commuting and Health in Cambridge study comprises three main elements: a cohort study of adults who travel to work in Cambridge, using repeated postal questionnaires and basic objective measurement of physical activity using accelerometers; in-depth quantitative studies of physical activity energy expenditure, travel and movement patterns and estimated carbon emissions using household travel diaries, combined heart rate and movement sensors and global positioning system (GPS) receivers; and a longitudinal qualitative interview study to elucidate participants' attitudes, experiences and practices and to understand how environmental and social factors interact to influence travel behaviour, for whom and in what circumstances. The impacts of a specific intervention - the opening of the Cambridgeshire Guided Busway - and of other changes in the physical environment will be examined using a controlled quasi-experimental design within the overall cohort dataset. DISCUSSION: Addressing the unresolved research and policy questions in this area is not straightforward. The challenges include those of effectively combining different disciplinary perspectives on the research problems, developing common methodological ground in measurement and evaluation, implementing robust quantitative measurement of travel and physical activity behaviour in an unpredictable 'natural experiment' setting, defining exposure to the intervention, defining controls, and conceptualising an appropriate longitudinal analytical strategy.

Equity of access to physical activity facilities in an English city.

OBJECTIVE: To examine associations between household income, access to sports facilities and gyms, and physical activity in an English city. METHOD: A cross sectional geographical study was conducted in six neighbourhoods in the city of Norwich in August and September 2004. Participants were (n=401) adults who received, completed, and returned questionnaires. Road distances to facilities were calculated using Geographical Information System. RESULTS: For all facility types except gyms, mean income was lowest amongst those living farthest away. Compared to those with the lowest incomes, the most affluent participants lived on average just over 0.5 km closer to a facility of any type, 1 km closer to a sports facility but 900 m farther from a gym (all p<0.001). In general, those living farther from facilities reported that they were less active although they did not tend to report a desire to exercise more. CONCLUSION: People in low income households, who are more likely to adopt low levels of activity, are least well served by affordable facilities that would enable them to become more active. If the British Government is to meet targets for improving levels of physical activity, it may need to consider how market forces might be creating an inequitable distribution of facility provision.