The aim of this study is to explore the relationship between active travel and psychological wellbeing. This study used data on 17,985 adult commuters in eighteen waves of the British Household Panel Survey (1991/2-2008/9). Fixed effects regression models were used to investigate how (i.) travel mode choice, (ii.) commuting time, and (iii.) switching to active travel impacted on overall psychological wellbeing and how (iv.) travel mode choice impacted on specific psychological symptoms included in the General Health Questionnaire. After accounting for changes in individual-level socioeconomic characteristics and potential confounding variables relating to work, residence and health, significant associations were observed between overall psychological wellbeing (on a 36-point Likert scale) and (i.) active travel (0.185, 95% CI: 0.048 to 0.321) and public transport (0.195, 95% CI: 0.035 to 0.355) when compared to car travel, (ii.) time spent (per 10minute change) walking (0.083, 95% CI: 0.003 to 0.163) and driving (-0.033, 95% CI: -0.064 to -0.001), and (iii.) switching from car travel to active travel (0.479, 95% CI: 0.199 to 0.758). Active travel was also associated with reductions in the odds of experiencing two specific psychological symptoms when compared to car travel. The positive psychological wellbeing effects identified in this study should be considered in cost-benefit assessments of interventions seeking to promote active travel.

Commuting between home and work is routinely performed by workers and any wellbeing impacts of commuting will consequently affect a large proportion of the population. This paper presents findings from analyses of the impact of commuting (time and mode) on multiple aspects of Subjective Well-Being (SWB), including: satisfaction with life overall and the SWB sub-domains of job satisfaction, satisfaction with leisure time availability and self-reported health. Measures of strain and mental health (GHQ-12) are also examined. Six waves of individual-level panel data from Understanding Society (2009/10 to 2014/15) are analysed, providing a sample of over 26,000 workers living in England. Associations between commuting and SWB are identified, paying particular attention to those arising from individual changes in commuting circumstances over the six waves. It is found that longer commute times are associated with lower job and leisure time satisfaction, increased strain and poorer mental health. The strongest association is found for leisure time satisfaction. Despite these negative associations with the SWB sub-domains, longer commute times were not associated with lower overall life satisfaction (except where individuals persisted with them over all six waves). Workers in England appear to be successful in balancing the negative aspects of commuting against the wider benefits, e.g. access to employment, earnings and housing. Differences amongst selected population sub-groups are also examined. The job satisfaction of younger adults and lower income groups are not found to be negatively associated with longer commute times; longer commute times are more strongly negatively associated with the job satisfaction of women compared to men. With respect to mode of transport, walking to work is associated with increased leisure time satisfaction and reduced strain. The absence of the commute, via working from home, is associated with increased job satisfaction and leisure time satisfaction. Overall, the study indicates that shorter commute times and walkable commutes can contribute to improved SWB—particularly through the release of leisure time. But life satisfaction overall will only be maintained if the benefits of undertaking the commute (earnings and satisfactory housing/employment) are not compromised.

Background: Active commuting is associated with various health benefits, but little is known about its causal relationship with body mass index (BMI). Methods: We used cohort data from three consecutive annual waves of the British Household Panel Survey, a longitudinal study of nationally representative households, in 2004/2005 (n=15 791), 2005/2006 and 2006/2007. Participants selected for the analyses (n=4056) reported their usual main mode of travel to work at each time point. Self-reported height and weight were used to derive BMI at baseline and after 2 years. Multivariable linear regression analyses were used to assess associations between switching to and from active modes of travel (over 1 and 2 years) and change in BMI (over 2 years) and to assess dose–response relationships. Results: After adjustment for socioeconomic and health-related covariates, the first analysis (n=3269) showed that switching from private motor transport to active travel or public transport (n=179) was associated with a significant reduction in BMI compared with continued private motor vehicle use (n=3090; −0.32 kg/m², 95% CI −0.60 to −0.05). Larger adjusted effect sizes were associated with switching to active travel (n=109; −0.45 kg/m², −0.78 to −0.11), particularly among those who switched within the first year and those with the longest journeys. The second analysis (n=787) showed that switching from active travel or public transport to private motor transport was associated with a significant increase in BMI (0.34 kg/m², 0.05 to 0.64). Conclusions: Interventions to enable commuters to switch from private motor transport to more active modes of travel could contribute to reducing population mean BMI.

Objective To evaluate a “telephone first” approach, in which all patients wanting to see a general practitioner (GP) are asked to speak to a GP on the phone before being given an appointment for a face to face consultation. Design Time series and cross sectional analysis of routine healthcare data, data from national surveys, and primary survey data. Participants 147 general practices adopting the telephone first approach compared with a 10% random sample of other practices in England. Intervention Management support for workload planning and introduction of the telephone first approach provided by two commercial companies. Main outcome measures Number of consultations, total time consulting (59 telephone first practices, no controls). Patient experience (GP Patient Survey, telephone first practices plus controls). Use and costs of secondary care (hospital episode statistics, telephone first practices plus controls). The main analysis was intention to treat, with sensitivity analyses restricted to practices thought to be closely following the companies’ protocols. Results After the introduction of the telephone first approach, face to face consultations decreased considerably (adjusted change within practices −38%, 95% confidence interval −45% to −29%; P<0.001). An average practice experienced a 12-fold increase in telephone consultations (1204%, 633% to 2290%; P<0.001). The average duration of both telephone and face to face consultations decreased, but there was an overall increase of 8% in the mean time spent consulting by GPs, albeit with large uncertainty on this estimate (95% confidence interval −1% to 17%; P=0.088). These average workload figures mask wide variation between practices, with some practices experiencing a substantial reduction in workload and others a large increase. Compared with other English practices in the national GP Patient Survey, in practices using the telephone first approach there was a large (20.0 percentage points, 95% confidence interval 18.2 to 21.9; P<0.001) improvement in length of time to be seen. In contrast, other scores on the GP Patient Survey were slightly more negative. Introduction of the telephone first approach was followed by a small (2.0%) increase in hospital admissions (95% confidence interval 1% to 3%; P=0.006), no initial change in emergency department attendance, but a small (2% per year) decrease in the subsequent rate of rise of emergency department attendance (1% to 3%; P=0.005). There was a small net increase in secondary care costs. Conclusions The telephone first approach shows that many problems in general practice can be dealt with over the phone. The approach does not suit all patients or practices and is not a panacea for meeting demand. There was no evidence to support claims that the approach would, on average, save costs or reduce use of secondary care.

Financial incentives, including taxes and subsidies, can be used to encourage behavior change. They are common in transport policy for tackling externalities associated with use of motor vehicles, and in public health for influencing alcohol consumption and smoking behaviors. Financial incentives also offer policymakers a compromise between "nudging," which may be insufficient for changing habitual behavior, and regulations that restrict individual choice. The literature review identified studies published between January 1997 and January 2012 of financial incentives relating to any mode of travel in which the impact on active travel, physical activity, or obesity levels was reported. It encompassed macroenvironmental schemes, such as gasoline taxes, and microenvironmental schemes, such as employer-subsidized bicycles. Five relevant reviews and 20 primary studies (of which nine were not included in the reviews) were identified. The results show that more-robust evidence is required if policymakers are to maximize the health impact of fiscal policy relating to transport schemes of this kind. Drawing on a literature review and insights from the SLOTH (sleep, leisure, occupation, transportation, and home-based activities) time-budget model, this paper argues that financial incentives may have a larger role in promoting walking and cycling than is acknowledged generally.

Background: The NHS Health Check programme is a prevention initiative offering cardiovascular risk assessment and management advice to adults aged 40–74 years across England. Its effectiveness depends on uptake. When it was introduced in 2009, it was anticipated that all those eligible would be invited over a 5-year cycle and 75% of those invited would attend. So far in the current cycle from 2013 to 2018, 33.8% of those eligible have attended, which is equal to 48.5% of those invited to attend. Understanding the reasons why some people do not attend is important to maximise the impact of the programmes.Aim: To review why people do not attend NHS Health Checks.Design and setting: A systematic review and thematic synthesis of qualitative studies.Method: An electronic literature search was carried out of MEDLINE, Embase, Health Management Information Consortium, Cumulative Index to Nursing and Allied Health Literature, Global Health, PsycINFO, Web of Science, OpenGrey, the Cochrane Library, NHS Evidence, Google Scholar, Google, ClinicalTrials.gov, and the ISRCTN registry from 1 January 1996 to 9 November 2016, and the reference lists of all included papers were also screened manually. Inclusion criteria were primary research studies that reported the views of people who were eligible for but had not attended an NHS Health Check.Results: Nine studies met the inclusion criteria. Reasons for not attending included lack of awareness or knowledge, misunderstanding the purpose of the NHS Health Check, aversion to preventive medicine, time constraints, difficulties with access to general practices, and doubts regarding pharmacies as appropriate settings.Conclusion: The findings particularly highlight the need for improved communication and publicity around the purpose of the NHS Health Check programme and the personal health benefits of risk factor detection.