Impact of changes in mode of travel to work on changes in body mass index: evidence from the British Household Panel Survey

Public transport use and mortality among older adults in England: A cohort study

BACKGROUND

Most evidence on transport use and mortality has focused on the commute to work. This study aims to fill a gap by assessing relationships between public transport use and mortality among older adults.

METHODS

Data come from a cohort of 10,186 individuals aged 50 or older who participated in the English Longitudinal Study of Ageing (ELSA), with survey data linked to mortality records over 16 years (2002-2018). We assessed a binary measure of public transport use and frequency of use from 'every day or nearly every day' to 'never'. Cox proportional-hazards regression models were used to estimate hazard ratios (HRs) with 95% confidence intervals (CIs) for associations between public transport use and mortality. Analyses were adjusted for a range of covariates including socio-demographic factors, chronic disease, and self-reported problems with daily living activities.

RESULTS

Overall, 3371 participants (33.1%) died within the study period. Mortality was lower among public transport users (21.3%) compared with non-users (64.2%). Adjusted analyses found that users had 34% lower mortality than non-users (HR 0.66 (95% CI 0.61;0.71)). Adjusted analyses showed similar association sizes across frequencies of public transport use, with those using public transport every day or nearly every day having 41% lower mortality than never users (HR 0.59 (0.49;0.71)). Associations were similar among those with and without a longstanding illness.

CONCLUSION

The use of public transport among older adults is linked to lower levels of mortality. Reductions in provision of public transport services could be detrimental to both transportation and population health.

Toward Heart-Healthy and Sustainable Cities: A Policy Statement From the American Heart Association

Nearly 56% of the global population lives in cities, with this number expected to increase to 6.6 billion or >70% of the world's population by 2050. Given that cardiometabolic diseases are the leading causes of morbidity and mortality in people living in urban areas, transforming cities and urban provisioning systems (or urban systems) toward health, equity, and economic productivity can enable the dual attainment of climate and health goals. Seven urban provisioning systems that provide food, energy, mobility-connectivity, housing, green infrastructure, water management, and waste management lie at the core of human health, well-being, and sustainability. These provisioning systems transcend city boundaries (eg, demand for food, water, or energy is met by transboundary supply); thus, transforming the entire system is a larger construct than local urban environments. Poorly designed urban provisioning systems are starkly evident worldwide, resulting in unprecedented exposures to adverse cardiometabolic risk factors, including limited physical activity, lack of access to heart-healthy diets, and reduced access to greenery and beneficial social interactions. Transforming urban systems with a cardiometabolic health-first approach could be accomplished through integrated spatial planning, along with addressing current gaps in key urban provisioning systems. Such an approach will help mitigate undesirable environmental exposures and improve cardiovascular and metabolic health while improving planetary health. The purposes of this American Heart Association policy statement are to present a conceptual framework, summarize the evidence base, and outline policy principles for transforming key urban provisioning systems to heart-health and sustainability outcomes.

Impact of changes in commuting mode on body weight among Japanese workers: a longitudinal study

OBJECTIVE

The health benefits of active commuting have been reported. However, few studies have assessed commuting modes using objective methods. This study clarified the association between changes in objectively measured commuting modes and body weight among Japanese workers.

METHODS

This longitudinal study used data from the annual health examinations and personnel records of a company with branches in all prefectures of Japan. Data from 2018 and 2019 were used as the baseline and follow-up data, respectively. The commuting mode was assessed using the commuting mode code included in the personnel records and classified into 3 types: walking, public transport, and car or motorcycle. The participants were classified into 9 categories based on the combination of their commuting modes in 2018 and 2019. Body weight was measured objectively during health examinations. The 1-year changes in body weight were calculated for the 9 categories and assessed using an analysis of covariance with adjustments for covariates.

RESULTS

The analysis included 6551 workers (men: 86.8%; mean age: 42.8 years). Overall, body weights tended to increase (+0.40 kg/y). The participants who switched to more active commuting, such as from car or motorcycle to walking (-0.13 kg/y), from car or motorcycle to public transport (+0.10 kg/y), and from public transport to walking (-0.07 kg/y), exhibited small weight gains or losses. A similar trend was observed even after adjustment.

CONCLUSIONS

Changing to a more active commuting mode may prevent weight gain among workers.

Changes in active commuting and changes in health: Within- and between-individual analyses among 16 881 Finnish public sector employees

BACKGROUND

Active commuting, such as walking or cycling to work, can be beneficial for health. However, because within-individual studies on the association between change in active commuting and change in health are scarce, the previous results may have been biased due to unmeasured confounding. Additionally, prior studies have often lacked information about commuting distance.

METHODS

We used two waves (2020, T1 and 2022, T2) of self-report data from the Finnish Public Sector study (N = 16,881; 80% female) to examine the within- and between associations (in a hybrid model) between active commuting and health. Exposure was measured by actively commuted kilometers per week, that is, by multiplying the number of walking or cycling days per week with the daily commuting distance. The primary outcome, self-rated health, was measured at T1 and T2. The secondary outcomes, psychological distress, and sleep problems were measured only at T2 and were therefore analyzed only in a between-individual design.

RESULTS

After adjustment for potential time-varying confounders such as socioeconomic factors, body mass index, and health behaviors, an increase equivalent to 10 additional active commuting kilometers per week was associated with a small improvement in self-rated health (within-individual unstandardized beta = 0.01, 95% CI 0.01-0.02; between-individual unstandardized beta = 0.03, 95% CI 0.02-0.04). No associations were observed between changes in active commuting and psychological distress or sleep problems.

CONCLUSIONS

An increase in active commuting may promote self-rated health. However, increase of tens of additional kilometers in commuting every day may be required to produce even a small effect on health.

Active commuting associations with BMI and self-rated health: a cross-sectional analysis of the Healthy Ireland survey

Aim

Active travel is advised to help meet recommended weekly physical activity levels. However limited research has examined active travel associations with health indicators. The aim of this study is to investigate active commuting associations with BMI and self-rated health (SRH) using data from the Healthy Ireland Survey.

Subjects and methods

Cross-sectional analysis of data was conducted from a nationally representative study of the Irish population. Participants who worked or attended education (n = 4038) provided information regarding their most common travel mode to work or education and demographic, lifestyle and health characteristics during an interview. Following comparative analysis, multivariable logistic regression was used to investigate associations between active commuting modes and overweight, obesity and SRH.

Results

Active commuting was associated with decreased likelihood of obesity (AOR 0.69, 95% CI = 0.52, 0.90) relative to non-active commuting. Examination of active commuting mode revealed further reduced obesity risk among cyclists (AOR 0.23, 95% CI = 0.09, 0.56) relative to non-cyclists and among those actively travelling ≥3 km (AOR 0.54, 95% CI = 0.30, 0.98). No associations between active commuting and overweight or SRH were observed.

Conclusion

Our findings, which indicate an inverse association between active commuting and obesity, represent a significant contribution to the evidence base supporting promotion of active travel for obesity prevention.

How Can We Act to Mitigate the Global Syndemic of Obesity, Undernutrition, and Climate Change?

PURPOSE OF REVIEW

The goal of this manuscript is to identify dietary and active transport strategies that reduce greenhouse gases and obesity, and thereby mitigate the effects of climate change on crop yields and micronutrient content.

RECENT FINDINGS

This report builds on our earlier publication that described the Global Syndemic of Obesity, Undernutrition, and Climate Change. We focus here on the contributions that the USA makes to the Global Syndemic and the policy solutions necessary to reduce the effects of the transport and food and agriculture systems on greenhouse gas emissions and environmental degradation. A recent study suggests that people are interested and ready to address local solutions to climate change. Changing the individual behaviors that sustain the US transport and food and agriculture systems is the first step to the broader engagement necessary to build the political will that to achieve institutional, municipal, state, and federal policy.

Active commuting, commuting modes, and the risk of diabetes: 14-year follow-up data from the Hisayama Study

Aims/Introduction

We aimed to investigate the association of active commuting (cycling or walking to work), as well as the association of the individual commuting modes, with the risk of diabetes in a prospective cohort of community‐dwelling adults in Japan.

Material and Methods

A total of 1,270 residents aged 40–79 years were followed up for a median of 14 years. Active commuting was defined as either cycling or walking to work. A Cox proportional hazards model was used to examine the association of active commuting with the risk of diabetes. Associations for different forms of active commuting (cycling, walking and mixed modes of cycling or walking with non‐active components) were also examined.

Results

During the follow‐up period, 191 participants developed diabetes. Active commuting was associated with a lower risk of diabetes than non‐active commuting after adjustment for potential confounders (hazard ratio [HR] 0.54, 95% confidence interval [CI] 0.31–0.92). With regard to the commuting modes, the risk of diabetes was significantly lower in individuals who commuted by cycling alone (HR 0.46, 95% CI 0.22–0.98), and tended to be lower in individuals who commuted by walking alone (HR 0.14, 95% CI 0.02–1.02) compared with that in individuals with non‐active commuting. Meanwhile, no significant associations were observed for the mixed mode of walking and non‐active commuting (HR 1.69, 95% CI 0.77–3.71).

Conclusions

Active commuting, particularly that consisting exclusively of cycling or walking, was associated with a reduced risk of diabetes. Our findings support a public health policy that promotes the choice of active commuting for the prevention of diabetes.

How Sustainable Is People’s Travel to Reach Public Transit Stations to Go to Work? A Machine Learning Approach to Reveal Complex Relationships

Several previous studies examined the variables of public-transit-related walking and privately owned vehicles (POVs) to go to work. However, most studies neglect the possible non-linear relationships between these variables and other potential variables. Using the 2017 U.S. National Household Travel Survey, we employ the Bayesian Network algorithm to evaluate the non-linear and interaction impacts of health condition attributes, work trip attributes, work attributes, and individual and household attributes on walking and privately owned vehicles to reach public transit stations to go to work in California. The authors found that the trip time to public transit stations is the most important factor in individuals’ walking decision to reach public transit stations. Additionally, it was found that this factor was mediated by population density. For the POV model, the population density was identified as the most important factor and was mediated by travel time to work. These findings suggest that encouraging individuals to walk to public transit stations to go to work in California may be accomplished by adopting planning practices that support dense urban growth and, as a result, reduce trip times to transit stations.

Does commuting mode choice impact health?

Governments around the world are encouraging people to switch away from sedentary modes of travel towards more active modes, including walking and cycling. The aim of these schemes is to improve population health and to reduce emissions. There is considerable evidence on the latter, but relatively little on the former. This paper investigates the impact of mode choice on physical and mental health. Using data from the UK Household Longitudinal Study, we exploit changes in mode of commute to identify health outcome responses. Individuals who change modes are matched with those whose mode remains constant. Overall we find that mode switches affect both physical and mental health. When switching from car to active travel we see an increase in physical health for women and in mental health for both genders. In contrast, both men and women who switch from active travel to car are shown to experience a significant reduction in their physical health and health satisfaction, and a decline in their mental health when they change from active to public transport.

National and metropolitan trends in public transit use, transit-related walking, and ridesharing between 2009 and 2017

Introduction

Walking is a common form of physical activity and is the most frequent way to access public transit. On-going changes in the US transportation system are occurring, notably increases in smartphone application-based ridesharing. The goal of this research is to assess whether increasing use of ridesharing was associated with a change in transit-related walking. This is important to both public health and transportation, as it can inform changes in active transportation which promotes both physical activity and transit use.

Methods

We examined the association between change in transit use, transit-related walking, and ridesharing nationally and for selected metropolitan areas using the 2009 and 2017 National Household Travel Survey (≥18 years; n = 263,572 and n = 230,592, respectively). Analyses were conducted in 2019. Covariates included sex, age, race/ethnicity, education, employment, work from home, household size, number of vehicles, population density, Census region, metro area size and heavy rail transit category and season.

Results

The national prevalence of transit use in the past month in 2009 was 16.9% (95% CI: 16.4%-17.4%) and in 2017 was 16.1% (15.6%-16.6%), a significant decrease (p < 0.02). The prevalence of daily transit-related walking in 2009 was 4.2% (4.0%-4.4%) and in 2017 was 4.4% (4.2%-4.6%; p = 0.22). The prevalence of daily taxi use in 2009 was 0.5% (0.4%-0.6%) and taxi/rideshare in 2017 was 1.1% (1.0%-1.2%), a significant increase (p < 0.0001). The relationships remained after covariate adjustment. Finally, there was not a significant change in transit-related walking or interaction between year and taxi/rideshare use after additional adjustment for taxi/rideshare. Changes in transit-related walking in metros were largely not significant, whereas increases in taxi/rideshare were largely significant.

Conclusions

Results suggest that increased use of ridesharing may not be linked with changes in transit-related walking. Continued surveillance of travel mode prevalence is required to track potential reductions in population-level physical activity with technology-related changes in travel.

Physical activity behaviour and barriers to activity in adults at high risk of obstructive sleep apnoea

INTRODUCTION Physical inactivity is a risk factor for disease severity among people with obstructive sleep apnoea. AIM To determine physical activity levels in patients at risk of obstructive sleep apnoea and explore their perceptions about barriers to participation in physical activity. METHODS This was a cross-sectional observational study. Eligible participants were adults with symptoms of obstructive sleep apnoea hypopnea syndrome and Epworth Sleepiness Scale score ≥11, awaiting prioritisation for a diagnostic overnight sleep study at the local sleep clinic. Sixty participants (mean age±standard deviation: 51±12 years) each attended an individual appointment. Anthropometric measurements were taken and standardised questionnaires regarding quality of life, physical activity behaviour and perceptions of physical activity were completed. RESULTS Over one-third of the cohort did not meet World Health Organization guidelines for weekly physical activity. Hypertension, type 2 diabetes and obesity were also more prevalent in this subgroup. Low motivation and pain were commonly reported barriers to activity in participants not meeting the physical activity guidelines. Overall, 53 (88%) participants stated they would like to be more active. DISCUSSION Physical inactivity represents an additional risk factor for adults at high risk of obstructive sleep apnoea. Lack of motivation and pain were the most commonly perceived barriers to participation in activity. Physical activity interventions tailored to the individual, and including a motivational component, need to be included as integral components of management to reduce cardiovascular and metabolic risk factors more effectively in this group.

Active Transportation and Obesity Indicators in Adults from Latin America: ELANS Multi-Country Study

PURPOSE

The aim of this study was to determine the association between active transportation and obesity indicators in adults from eight Latin American countries.

METHODS

Data from the ELANS study, an observational multi-country study (n: 8336; 18-65 years), were used. Active transportation (walking and cycling) and leisure time physical activity was assessed using the International Physical Activity Questionnaire (long version). The obesity indicators considered were: body mass index, and waist and neck circumference.

RESULTS

In the total sample, the average time dedicated to active transportation was 24.3 min/day, with the highest amount of active transportation being Costa Rica (33.5 min/day), and the lowest being Venezuela (15.7 min/day). The countries with the highest proportion of active transportation were Ecuador (71.9%), and the lowest was Venezuela (40.5%). Results from linear regression analyses suggest that active transportation was significantly and independently associated with a lower body mass index (β: -0.033; 95% CI: -0.064; -0.002), but not with waist circumference (β: -0.037; 95% CI: -1.126; 0.390 and neck circumference (β: -0.007; 95% CI: -0.269; 0.130).

CONCLUSIONS

Active transportation is significantly associated with a lower body mass index. Governments should incentivize this type of transportation as it could help to reduce the obesity pandemic in Latin America.

Fuelling walking and cycling: human powered locomotion is associated with non-negligible greenhouse gas emissions

Reducing motorized transport and increasing active transport (i.e. transport by walking, cycling and other active modes) may reduce greenhouse gas (GHG) emissions and improve health. But, active modes of transport are not zero emitters. We aimed to quantify GHG emissions from food production required to fuel extra physical activity for walking and cycling. We estimate the emissions (in kgCO₂e) per kilometre travelled for walking and cycling from energy intake required to compensate for increased energy expenditure, and data on food-related GHG emissions. We assume that persons who shift from passive modes of transport (e.g. driving) have increased energy expenditure that may be compensated with increased food consumption. The GHG emissions associated with food intake required to fuel a kilometre of walking range between 0.05 kgCO₂e/km in the least economically developed countries to 0.26 kgCO₂e/km in the most economically developed countries. Emissions for cycling are approximately half those of walking. Emissions from food required for walking and cycling are not negligible in economically developed countries which have high dietary-related emissions. There is high uncertainty about the actual emissions associated with walking and cycling, and high variability based on country economic development. Our study highlights the need to consider emissions from other sectors when estimating net-emissions impacts from transport interventions.

What we can learn from five naturalistic field experiments that failed to shift commuter behaviour

Across five field experiments with employees of a large organization (n = 68,915), we examined whether standard behavioural interventions ('nudges') successfully reduced single-occupancy vehicle commutes. In Studies 1 and 2, we sent letters and emails with nudges designed to increase carpooling. These interventions failed to increase carpool sign-up or usage. In Studies 3a and 4, we examined the efficacy of other well-established behavioural interventions: non-cash incentives and personalized travel plans. Again, we found no positive effect of these interventions. Across studies, effect sizes ranged from Cohen's d = -0.01 to d = 0.05. Equivalence testing, using study-specific smallest effect sizes of interest, revealed that the treatment effects observed in four out of five of our experiments were statistically equivalent to zero (P < 0.04). The failure of these well-powered experiments designed to nudge commuting behaviour highlights both the difficulty of changing commuter behaviour and the importance of publishing null results to build cumulative knowledge about how to encourage sustainable travel.

Area-Wide Traffic-Calming Zone 30 Policy of Japan and Incidence of Road Traffic Injuries Among Cyclists and Pedestrians

Objectives. To quantify the impact of the "Zone 30" policy introduced in September 2011 on the incidence of cyclist and pedestrian injuries in Japan.Methods. This was an interrupted time-series study. We used the data of cyclist and pedestrian injuries recorded by the Japanese police between 2005 and 2016. We evaluated the monthly number of deaths and serious injuries per person-time on narrow roads (width < 5.5 m, subjected to the policy) compared with that on wide roads (≥ 5.5 m) to control for secular trends. We regressed the injury rate ratio on 2 predictors: the numbers of months after January 2005 and after September 2011. Using the regression results, we estimated the number of deaths and serious injuries prevented.Results. There were 266 939 deaths and serious injuries. By 2016, the cumulative changes in the rate ratio spanned from -0.26 to -0.046, depending on sex and age, and an estimated number of 1704 (95% confidence interval = 1293, 2198) injuries were prevented.Conclusions. The policy had a large preventive impact on cyclist and pedestrian deaths and serious injuries at the national level.

Association of changes in commute mode with body mass index and visceral adiposity: a longitudinal study

BACKGROUND

Prospective data are sparse for active commuting to work and body weight in Asia. We assessed the association of 5-year changes in commuting mode with body mass index (BMI) and the indicators of abdominal obesity in Japanese working adults.

METHODS

In this longitudinal study, we studied 29,758 participants (25,808 men and 3950 women) in Japan aged 30 to 64 years at baseline who underwent further health examination 5 years after the baseline examination. Changes in BMI were calculated from objectively measured body height and weight at baseline and follow-up examination. Visceral and subcutaneous fat areas and waist circumference measured by computed tomography scans were used as indicators for abdominal adiposity. Linear regression was applied to estimate the association of changes in commuting mode with the obesity outcomes.

RESULTS

Within the 5-year study period, adults who maintained inactive commuting gained weight, and compared with this group, adults who switched to inactive commuting had higher weight gain; conversely, adults who switched to active or public transportation commuting and especially those who maintained active or public transportation commuting experienced less weight gain. Subgroup analysis showed similar tendency across the different transitions of leisure-time exercise or occupational physical activity. For example, among adults who maintained no exercise (n = 16,087), the adjusted mean (95% confidence intervals) of the BMI change over 5 years in kg/m² were 0.27 (0.24 to 0.30) for maintained inactive commuting group (reference), 0.34 (0.30 to 0.38) for switching to inactive commuting group (P = 0.046), 0.20 (0.18 to 0.22) for switching to active commuting or public transportation group (P = 0.001), and 0.09 (0.06 to 0.13) for maintained active commuting or public transportation group (P < 0.001). Maintained inactive commuting tended to be associated with larger gain in abdominal adiposity indicators.

CONCLUSION

Switching from inactive commuting mode to more physically active commuting mode and maintaining active commuting can promote body weight control among working adults across different levels of occupational or leisure-time physical activity.

Associations between active travel and diet: cross-sectional evidence on healthy, low-carbon behaviours from UK Biobank

OBJECTIVES

To examine whether there are associations between active travel and markers of a healthy, low-carbon (HLC) diet (increased consumption of fruit and vegetables (FV), reduced consumption of red and processed meat (RPM)).

DESIGN

Cross-sectional analysis of a cohort study.

SETTINGS

Population cohort of over 500 000 people recruited from 22 centres across the UK. Participants aged between 40 and 69 years were recruited between 2006 and 2010.

PARTICIPANTS

412 299 adults with complete data on travel mode use, consumption of FV and RPM, and sociodemographic covariates were included in the analysis.

EXPOSURE MEASURES

Mutually exclusive mode or mode combinations of travel (car, public transport, walking, cycling) for non-work and commuting journeys.

OUTCOME MEASURES

Consumption of FV measured as portions per day and RPM measured as frequency per week.

RESULTS

Engaging in all types of active travel was positively associated with higher FV consumption and negatively associated with more frequent RPM consumption. Cycling exclusively or in combination with walking was most strongly associated with increased dietary consumption of FV and reduced consumption of RPM for both non-work and commuting journeys. Overall, the strongest associations were between non-work cycling and FV consumption (males: adjusted OR=2.18, 95% CI 2.06 to 2.30; females: adjusted OR=2.50, 95% CI 2.31 to 2.71) and non-work cycling and RPM consumption (males: adjusted OR=0.57, 95% CI 0.54 to 0.60; females: adjusted OR=0.54, 95% CI 0.50 to 0.59). Associations were generally similar for both commuting and non-work travel, and were robust to adjustment with sociodemographic and behavioural factors.

CONCLUSIONS

There are strong associations between engaging in active travel, particularly cycling, and HLC dietary consumption, suggesting that these HLC behaviours are related. Further research is needed to better understand the drivers and dynamics between these behaviours within individuals, and whether they share common underlying causes.

Transforming Our Cities: Best Practices Towards Clean Air and Active Transportation

PURPOSE OF REVIEW

By 2050, 70% of the global population will live in urban areas, exposing a greater number of people to specific city-related health risks that will only be exacerbated by climate change. Two prominent health risks are poor air quality and physical inactivity. We aim to review the literature and state the best practices for clean air and active transportation in urban areas.

RECENT FINDINGS

Cities have been targeting reductions in air pollution and physical inactivity to improve population health. Oslo, Paris, and Madrid plan on banning cars from their city centers to mitigate climate change, reduce vehicle emissions, and increase walking and cycling. Urban streets are being redesigned to accommodate and integrate various modes of transportation to ensure individuals can become actively mobile and healthy. Investments in pedestrian, cycling, and public transport infrastructure and services can both improve air quality and support active transportation. Emerging technologies like electric and autonomous vehicles are being developed and may reduce air pollution but have limited impact on physical activity. Green spaces too can mitigate air pollution and encourage physical activity. Clean air and active transportation overlap considerably as they are both functions of mobility. The best practices of clean air and active transportation have produced impressive results, which are improved when enacted simultaneously in integrated policy packages. Further research is needed in middle- and low-income countries, using measurements from real-world interventions, tracing air pollution back to the sources responsible, and holistically addressing the entire spectrum of exposures and health outcomes related to transportation.

Cross-sectional and longitudinal analysis of the active commuting behaviors of U.S. Department of the Interior employees

BACKGROUND

Despite evolving evidence of the health and economic benefits of active transportation (AT) to work, few studies have examined the determinants of AT in large organizations with multiple worksites nor how trends in commuting change over time.

METHODS

The data were obtained from the U.S. Department of the Interior Employee Commuting Census of 2010 (n = 23,230), and 2012-2016 (n = 21,725-25,974). The respondents were grouped into four commuting categories: non-active mode, walking, biking, and mixed-mode. Multinomial logistic regression analysis was utilized to examine the correlates of choosing AT to work for the 2010 data. Next, a repeated cross-sectional analysis was completed for all six years of data.

RESULTS

In 2010, AT modes were only chosen by approximately 10% of respondents. Employees who lived farther from work and did not have a public transit station within 0.5 miles from home were generally less likely to choose AT. Respondents working in non-metro workplaces were less likely to bike or take mixed-modes to work, but more likely to walk. Men were more likely to choose AT modes, particularly biking. Respondents aged ≤30 yrs. were less likely to bike than those 31 to 40 yrs., but more likely than those ≥61 yrs. In 2010, the number of respondents that walked was higher, and biked and took mixed-modes was lower when compared to 2016, while the choice to take mixed-modes was higher in 2012 and 2013 when compared to 2016. Daily commuting distances in 2016 tended to be lower than 2010 and 2012, and higher than 2013. However, overall AT choice and commute distance remained reasonably stable over time.

CONCLUSIONS

Respondents who lived close to their workplace and a public transportation station, worked in a metro location, were male and younger were more likely to choose AT modes to work. The results provide insight for the U.S. Department of the Interior and other large organizations to develop intervention strategies that support AT to work. Further research is warranted to understand the concurrent individual, social, and environmental barriers and facilitators for choosing AT to work.

Associations of Public Transportation Use With Cardiometabolic Health: A Systematic Review and Meta-Analysis

Public transportation provides an opportunity to incorporate physical activity into journeys, but potential health impacts have not been systematically examined. We searched the literature for articles on public transportation and health published through December 2017 using Google (Google Inc., Mountain View, California), 5 medical databases, and 1 transportation-related database. We identified longitudinal studies which examined associations between public transportation and cardiometabolic health (including adiposity, type 2 diabetes mellitus, and cardiovascular disease). We assessed study quality using the Newcastle-Ottawa Scale for cohort studies and performed meta-analyses where possible. Ten studies were identified, 7 investigating use of public transportation and 3 examining proximity to public transportation. Seven studies used individual-level data on changes in body mass index (BMI; weight (kg)/height (m)²), with objective outcomes being measured in 6 studies. Study follow-up ranged from 1 year to 10 years, and 3 studies adjusted for nontransportation physical activity. We found a consistent association between use of public transportation and lower BMI. Meta-analysis of data from 5 comparable studies found that switching from automobile use to public transportation was associated with lower BMI (−0.30 units, 95% confidence interval: −0.47, −0.14). Few studies have investigated associations between public transportation use and nonadiposity outcomes. These findings suggest that sustainable urban design which promotes public transportation use may produce modest reductions in population BMI.

Household income, active travel, and their interacting impact on body mass index in a sample of urban Canadians: a Bayesian spatial analysis

Background

Active travel for utilitarian purposes contributes to total physical activity and may help counter the obesity epidemic. However, the evidence linking active travel and individual-level body weight is equivocal. Statistical modeling that accounts for spatial autocorrelation and unmeasured spatial predictors has not yet used to explore whether the health benefits of active travel are shared equally across socioeconomic groups.

Methods

Bayesian hierarchical models with spatial random effects were developed using travel survey data from Saskatoon, Canada (N = 4625). Differences in log-transformed body mass index (BMI) were estimated for levels of active travel use (vehicular travel only, mixed vehicular/active travel, and active travel only), household income, and neighbourhood deprivation after controlling for sociodemographic and physical activity variables. The modifying effect of household income on the association between active travel and BMI was also evaluated.

Results

Significant and meaningful decreases in BMI were observed for mixed (β = − 0.02, CrI − 0.036 to − 0.004) and active only (β = − 0.043, CrI − 0.06 to − 0.025) compared to vehicular only travelers. BMI was significantly associated with levels of household income and neighbourhood deprivation. Accounting for the interaction between travel mode and household income, decreases in BMI were observed for active only compared to vehicular only travellers in the highest income category (β = − 0.061, CrI − 0.115 to − 0.007).

Conclusion

Strategies to increase active travel use can support healthy weight loss and maintenance, but the opportunity to benefit from active travel use may be limited by low income. Considerations should be given to how interventions to increase active transportation might exacerbate social inequalities in BMI. Spatial statistical models are needed to account for unmeasured but spatially structured neighbourhood factors.

Electronic supplementary material

The online version of this article (10.1186/s12942-019-0168-x) contains supplementary material, which is available to authorized users.

Transport mode choice and body mass index: Cross-sectional and longitudinal evidence from a European-wide study

BACKGROUND

In the fight against rising overweight and obesity levels, and unhealthy urban environments, the renaissance of active mobility (cycling and walking as a transport mode) is encouraging. Transport mode has been shown to be associated to body mass index (BMI), yet there is limited longitudinal evidence demonstrating causality. We aimed to associate transport mode and BMI cross-sectionally, but also prospectively in the first ever European-wide longitudinal study on transport and health.

METHODS

Data were from the PASTA project that recruited adults in seven European cities (Antwerp, Barcelona, London, Oerebro, Rome, Vienna, Zurich) to complete a series of questionnaires on travel behavior, physical activity levels, and BMI. To assess the association between transport mode and BMI as well as change in BMI we performed crude and adjusted linear mixed-effects modeling for cross-sectional (n = 7380) and longitudinal (n = 2316) data, respectively.

RESULTS

Cross-sectionally, BMI was 0.027 kg/m² (95%CI 0.015 to 0.040) higher per additional day of car use per month. Inversely, BMI was -0.010 kg/m² (95%CI -0.020 to -0.0002) lower per additional day of cycling per month. Changes in BMI were smaller in the longitudinal within-person assessment, however still statistically significant. BMI decreased in occasional (less than once per week) and non-cyclists who increased cycling (-0.303 kg/m², 95%CI -0.530 to -0.077), while frequent (at least once per week) cyclists who stopped cycling increased their BMI (0.417 kg/m², 95%CI 0.033 to 0.802).

CONCLUSIONS

Our analyses showed that people lower their BMI when starting or increasing cycling, demonstrating the health benefits of active mobility.

Associations of increases in public transport use with physical activity and adiposity in older adults

Background

We investigated predictors of two increases in older people’s public transport use: initiating public transport use among non-users; and increasing public transport use amongst users. We also investigated associations of these changes with physical activity, Body Mass Index (BMI) and waist circumference.

Methods

Data come from the 2008 and 2012 English Longitudinal Study of Ageing (ELSA). Logistic regression assessed predictors of increases in public transport use among adults aged ≥50 years. Gender-stratified logistic and linear models assessed associations of increases in public transport use with changes in physical activity and adiposity.

Results

Those becoming eligible for a free older person’s bus pass were more likely to both initiate and increase public transport use (e.g. for initiating public transport use Adjusted Odds Ratio (AORs) 1.77, 95% Confidence Interval 1.35; 2.33). Retiring from paid work was also associated with both initiating and increasing public transport use e.g. AOR 1.57 (1.29; 1.91) for initiating use.

Women who increased public transport use had mean BMI 2.03 kg/m² lower (− 2.84, − 1.21) at follow up than those who did not, although this was attenuated after adjusting for BMI at baseline (− 0.40 kg/m², − 0.82, 0.01). After adjustment for baseline physical activity those initiating public transport use were more likely to undertake at least some physical activity in 2012 (e.g. AOR for women 1.67, 1.03; 2.72).

Conclusions

Both initiating and increasing public transport use were associated with increased physical activity and may be associated with lower adiposity among women. These findings strengthen the case for considering public transport provision as an effective means of promoting healthier ageing.

Current issues in the impacts of transport on health

INTRODUCTION OR BACKGROUND

Transport affects health in many ways. Benefits include access to education, employment, goods, services and leisure, and opportunities for incorporating physical activity into daily living. There are major inequalities: benefits generally accrue to wealthier people and harms to the more deprived, nationally and globally.

SOURCES OF DATA

Health on the Move 2; Journal of Transport and Health.

AREAS OF AGREEMENT

Benefits of travel for access and physical activity. Harms include health impacts of air and noise pollution; injuries and fatalities from falls or collisions; sedentary behaviour with motorized transport; community severance (barrier effect of busy roads and transport infrastructure); global climate change; impacts on inequalities; transport's role in facilitating spread of communicable diseases.

AREAS OF CONTROVERSY INCLUDE

Biofuels; cycle safety; driving by older people.

GROWING POINTS AND AREAS FOR RESEARCH INCLUDE

Effects of default 20 mph speed limits; impacts of autonomous vehicles on health and inequalities.

Do active modes of transport cause lower body mass index? Findings from the HABITAT longitudinal study

Background

Few studies have examined the causal relationship between transport mode and body mass index (BMI).

Methods

We examined between-person differences and within-person changes in BMI by transport mode over four time points between 2007 and 2013. Data were from the How Areas in Brisbane Influence HealTh and AcTivity project, a population-representative study of persons aged 40–65 in 2007 (baseline) residing in 200 neighbourhoods in Brisbane, Australia. The analytic sample comprised 9931 respondents who reported on their main transport for all travel purposes (work-related and non-work-related). Transport mode was measured as private motor vehicle (PMV), public transport, walking and cycling. Self-reported height and weight were used to derive BMI. Sex-specific analyses were conducted using multilevel hybrid regression before and after adjustment for time-varying and time-invariant confounders.

Results

Independent of transport mode and after adjustment for confounders, average BMI increased significantly and linearly across the four time points for both men and women. Men and women who walked or cycled had a significantly lower BMI than their counterparts who used a PMV. BMI was nearly always lower during the time men and women walked or cycled than when they used a PMV; however, few statistically significant differences were observed. For women, BMI was significantly higher during the time they used public transport than when using a PMV.

Conclusion

The findings suggest a causal association between transport mode and BMI and support calls from health authorities to promote walking and cycling for transport as a way of incorporating physical activity into everyday life to reduce the risk of chronic disease.

Associations of active commuting with body fat and visceral adipose tissue: A cross-sectional population based study in the UK

The promotion of active travel (walking and cycling) is one promising approach to prevent the development of obesity and related cardio-metabolic disease. However the associations between active travel and adiposity remain uncertain. We used the Fenland study (a population based-cohort study; Cambridgeshire, UK, 2005-15) to describe the association of commuting means with DEXA measured body fat and visceral adipose tissue (VAT) among commuters (aged 29-65years; n=7680). We stratified our sample into those living near (within five miles) and far (five miles or further) from work, and categorised commuting means differently for each group reflecting their different travel options. Associations were adjusted for age, education, Mediterranean diet score, smoking, alcohol consumption, test site and either self-reported physical activity or objective physical activity. Among those living near to work, people who reported regularly cycling to work had lower body fat than those who only used the car (adjusting for self-reported physical activity: women, -1.74%, 95% CI: -2.27% to -0.76%; men, -1.30%, -2.26% to -0.33%). Among those who lived far from work, people who reported regular car-use with active travel had lower body fat (women; -1.18%, 95% CI: -2.23% to -0.13%; men, -1.19%, -1.93% to -0.44%). Findings were similar for VAT and when adjusting for objectively measured physical activity instead of self-reported physical activity. In conclusion, active commuting may reduce adiposity and help prevent related cardio-metabolic disease. If people live too far from work to walk or cycle the whole journey, incorporating some active travel within the commute is also beneficial.

Transit Rider Body Mass Index Before and After Completion of Street Light-Rail Line in Utah

OBJECTIVES

To determine whether 2012 to 2015 (times 1-3) ridership changes correlated with body mass index (BMI) changes after transit line completion in Salt Lake City, Utah.

METHODS

We used Global Positioning System/accelerometry-measured transit ridership measures in 2012 to 2013 (times 1-2) to compare objective and self-reported ridership. Regression models related changes in objectively measured ridership (times 1-2) and self-reported ridership (times 1-2 and times 1-3) to BMI changes, adjusting for control variables.

RESULTS

Objective and self-reported ridership measures were consistent. From time 1 to 2 (P = .021) or to 3 (P = .015), BMI increased among self-reported former riders and decreased among new riders (P = .09 for both times 1-2 and times 1-3), although the latter was nonsignificant. Time 3 attrition adjustment had no effect on results. Adjusting for baseline BMI, the nonsignificant effect for new riders remained nonsignificant, indicating no BMI change; the BMI increase after discontinuing transit remained significant.

CONCLUSIONS

Observed BMI increases subsequent to stopping transit ridership persisted for more than 2 years (postintervention). These results suggest that transit ridership protects against BMI gains and support the need to provide convenient transit for public health.

Obesity-related health impacts of fuel excise taxation- an evidence review and cost-effectiveness study

BACKGROUND

Reducing automobile dependence and improving rates of active transport may reduce the impact of obesogenic environments, thereby decreasing population prevalence of obesity and other diseases where physical inactivity is a risk factor. Increasing the relative cost of driving by an increase in fuel taxation may therefore be a promising public health intervention for obesity prevention.

METHODS

A scoping review of the evidence for obesity or physical activity effect of changes in fuel price or taxation was undertaken. Potential health benefits of an increase in fuel excise taxation in Australia were quantified using Markov modelling to simulate obesity, injury and physical activity related health impacts of a fuel excise taxation intervention for the 2010 Australian population. Health adjusted life years (HALYs) gained and healthcare cost savings from diseases averted were estimated. Incremental cost-effectiveness ratios (ICERs) were reported and results were tested through sensitivity analysis.

RESULTS

Limited evidence on the effect of policies such as fuel taxation on health-related behaviours currently exists. Only three studies were identified reporting associations between fuel price or taxation and obesity, whilst nine studies reported associations specifically with physical activity, walking or cycling. Estimates of the cross price elasticity of demand for public transport with respect to fuel price vary, with limited consensus within the literature on a probable range for the Australian context. Cost-effectiveness modelling of a AUD0.10 per litre increase in fuel excise taxation using a conservative estimate of cross price elasticity for public transport suggests that the intervention would be cost-effective from a limited societal perspective (237 HALYs gained, AUD2.6 M in healthcare cost savings), measured against a comparator of no additional increase in fuel excise. Under "best case" assumptions, the intervention would be more cost-effective (3181 HALYs gained, AUD34.2 M in healthcare cost savings).

CONCLUSIONS

Exploratory analysis suggests that an intervention to increase fuel excise taxation may deliver obesity and physical activity related benefits. Whilst such an intervention has significant potential for cost-effectiveness, potential equity and acceptability impacts would need to be minimised. A better understanding of the effectiveness and cost-effectiveness of a range of transport interventions is required in order to achieve more physically active transport environments.

Cardiovascular risk factors-using repeated cross-sectional surveys to assess time trends in socioeconomic inequalities in neighbouring countries

OBJECTIVES

This study compares trends in socioeconomic inequalities related to key cardiovascular risk factors in neighbouring countries Northern Ireland (NI) and the Republic of Ireland (RoI).

DESIGN

Repeated cross-sectional studies.

SETTING

Population based.

PARTICIPANTS

3500-4000 in national surveys in NI and 5000-9000 in RoI, aged 20-69 years.

MEASURES

Educational attainment was used as a socioeconomic indicator by which the magnitude and direction of trends in inequalities for smoking, diabetes, obesity and physical inactivity in NI and RoI were examined between 1997/1998 and 2007/2011. Gender-specific relative and absolute inequalities were calculated using the Relative Index of Inequality (RII) and Slope Index of Inequality (SII) for both countries.

RESULTS

In both countries, the prevalence of diabetes and obesity increased whereas levels of smoking and physical inactivity decreased over time. In NI relative inequalities increased for obesity (RII 1.1 in males and 2.1 in females in 2010/2011) and smoking (RII 4.5 in males and 4.2 in females in 2010/2011) for both genders and absolute inequalities increased for all risk factors in men and increased for diabetes and obesity in women. In RoI greater inequality was observed in women, particularly for smoking (RII 2.8 in 2007) and obesity (RII 8.2 in 2002) and in men for diabetes (RII 3.2 in 2002).

CONCLUSIONS

Interventions to reduce inequalities in risk factors, particularly smoking, obesity and diabetes are encouraged across both countries.

Active transport and obesity prevention - A transportation sector obesity impact scoping review and assessment for Melbourne, Australia

Given the alarming prevalence of obesity worldwide and the need for interventions to halt the growing epidemic, more evidence on the role and impact of transport interventions for obesity prevention is required. This study conducts a scoping review of the current evidence of association between modes of transport (motor vehicle, walking, cycling and public transport) and obesity-related outcomes. Eleven reviews and thirty-three primary studies exploring associations between transport behaviours and obesity were identified. Cohort simulation Markov modelling was used to estimate the effects of body mass index (BMI) change on health outcomes and health care costs of diseases causally related to obesity in the Melbourne, Australia population. Results suggest that evidence for an obesity effect of transport behaviours is inconclusive (29% of published studies reported expected associations, 33% mixed associations), and any potential BMI effect is likely to be relatively small. Hypothetical scenario analyses suggest that active transport interventions may contribute small but significant obesity-related health benefits across populations (approximately 65 health adjusted life years gained per year). Therefore active transport interventions that are low cost and targeted to those most amenable to modal switch are the most likely to be effective and cost-effective from an obesity prevention perspective. The uncertain but potentially significant opportunity for health benefits warrants the collection of more and better quality evidence to fully understand the potential relationships between transport behaviours and obesity. Such evidence would contribute to the obesity prevention dialogue and inform policy across the transportation, health and environmental sectors.

What Is Driving Obesity? A Review on the Connections Between Obesity and Motorized Transportation

PURPOSE OF REVIEW

Traveling by automobile rather than walking or cycling can encourage obesity by eliminating physical activity. As national obesity rates in the USA have reached 37.9% in 2014, understanding the connections between obesity and transportation choices can help policymakers in the public health community propose effective obesity interventions at the national level.

RECENT FINDINGS

Following from foundational studies examining associations between the built environment and leisure walking, recent studies consider a diverse set of transportation choices regarding mode (e.g., automobile, walking, public transit) and purpose (e.g., commuting, leisure), along with studies on the effectiveness of several transportation-related interventions for obesity. The reviewed studies point toward potential interventions for obesity; there is emerging evidence that commuting by public transit may be one such intervention. Moreover, new data-gathering tools such as global positioning systems, geographic information systems, and accelerometers may alleviate statistical obstacles in conducting future studies.

"If You Don't Do Parking Management .. Forget Your Behaviour Change, It's Not Going to Work.": Health and Transport Practitioner Perspectives on Workplace Active Travel Promotion

OBJECTIVES

After having conducted two studies of the effectiveness of workplace travel plans for promoting active travel, we investigated health and transport practitioners' perspectives on implementing workplace travel plans to share some of the lessons learnt. The objectives of this study were to describe perceived elements of effective workplace travel plans, barriers and enablers to workplace travel planning, their experiences of working with the other profession on travel plan implementation, their recommendations for workplace travel planning, and also to explore similarities and differences in transport and health practitioner perspectives.

MATERIALS AND METHODS

Fourteen health and ten transport practitioners who had prior involvement in workplace travel plan programs were purposefully selected from workplaces in Australia. We conducted 20 in-depth interviews since data saturation had been reached at this point, and data were subject to framework analysis.

RESULTS

Perceived essential elements of effective workplace travel plans included parking management; leadership, organisational commitment and governance; skills and other resources like a dedicated travel plan coordinator; and, pre-conditions including supportive transport infrastructure in the surrounds. Recommendations for promoting travel plans included supportive government policy, focusing on business benefits and working at different scales of implementation (e.g. single large worksites and business precincts). Health and transport practitioner perspectives differed, with transport practitioners believing that parking management is the key action for managing travel demand at a worksite.

CONCLUSIONS

Health practitioners implementing travel plans may require training including concepts of travel demand management, and support from transport planners on parking management strategies. Promoting an understanding of the shared travel behaviour change skills of transport and health practitioners may assist further collaboration. For take-up by organisations to be of sufficient scale to create meaningful population level reductions in driving and increases in active travel, promotion and travel plans should be focused on the priorities of the organisations. Supportive government policy is also required.

Change in commute mode and body-mass index: prospective, longitudinal evidence from UK Biobank

BACKGROUND

Insufficient physical activity is a determinant of obesity and cardiovascular disease. Active travel to work has declined in high-income countries in recent decades. We aimed to determine which socioeconomic and demographic characteristics predicted switching to or from active commuting, whether switching from passive to active commuting (or the reverse) independently predicts change in objectively measured body-mass index (BMI), and to ascertain whether any association is attenuated by socioeconomic, demographic, or behavioural factors.

METHODS

This study used longitudinal data from UK Biobank. Baseline data collection occurred at 22 centres between March, 2006, and July, 2010, with a repeat assessment at one centre (Stockport) between August, 2012, and June, 2013, for a subset of these participants. Height and weight were objectively measured at both timepoints. We included individuals present at both timepoints with complete data in the analytic sample. Participants were aged 40-69 years and commuted from home to a workplace on a regular basis at both baseline and follow-up. Two exposures were investigated: transition from car commuting to active or public transport commuting and transition from active or public transport to car commuting. Change in BMI between baseline and repeat assessment was the outcome of interest, assessed with bivariate and multivariate logistic regression models.

FINDINGS

502 656 individuals provided baseline data, with 20 346 participating in the repeat assessment after a median of 4·4 years (IQR 3·7-4·9). 5861 individuals were present at both timepoints and had complete data for all analytic variables. Individuals who transitioned from car commuting at baseline to active or public transportation modes at follow-up had a decrease in BMI of -0·30 kg/m² (95% CI -0·47 to -0·13; p=0·0005). Conversely, individuals who transitioned from active commuting at baseline to car commuting at follow-up had a BMI increase of 0·32 kg/m² (0·13 to 0·50; p=0·008). These effects were not attenuated by adjustment for hypothesised confounders. Change in household income emerged as a determinant of commute mode transitions.

INTERPRETATION

Incorporation of increased levels of physical activity as part of the commute to work could reduce obesity among middle-aged adults in the UK.

FUNDING

UK Medical Research Council.

Longitudinal associations of active commuting with body mass index

OBJECTIVE

To investigate the longitudinal associations between active commuting (walking and cycling to work) and body mass index (BMI).

METHOD

We used self-reported data on height, weight and active commuting from the Commuting and Health in Cambridge study (2009 to 2012; n=809). We used linear regression to test the associations between: a) maintenance of active commuting over one year and BMI at the end of that year; and b) change in weekly time spent in active commuting and change in BMI over one year.

RESULTS

After adjusting for sociodemographic variables, other physical activity, physical wellbeing and maintenance of walking, those who maintained cycle commuting reported a lower BMI on average at one year follow-up (1.14kg/m(2), 95% CI: 0.30 to 1.98, n=579) than those who never cycled to work. No significant association remained after adjustment for baseline BMI. No significant associations were observed for maintenance of walking. An increase in walking was associated with a reduction in BMI (0.32kg/m(2), 95% CI: 0.03 to 0.62, n=651, after adjustment for co-variates and baseline BMI) only when restricting the analysis to those who did not move. No other significant associations between changes in weekly time spent walking or cycling on the commute and changes in BMI were observed.

CONCLUSIONS

This work provides further evidence of the contribution of active commuting, particularly cycling, to preventing weight gain or facilitating weight loss. The findings may be valuable for employees choosing how to commute and engaging employers in the promotion of active travel.

Potential Health Implications and Health Cost Reductions of Transit-Induced Physical Activity

Transit has the potential to increase an individual's level of physical activity due to the need to walk or bike at the beginning and end of each trip. Consideration of these health benefits would allow transit proponents to better demonstrate its true costs and benefits. In light of transit's potential health-related impacts, this study contributes to the growing discussion in the emerging field of health and transportation by providing a review of the current level of understanding and evidence related to the physical activity implications of transit use and its associated health cost benefits. Findings from the review revealed that transit use is associated with increased levels of physical activity and improved health outcomes, but the magnitude of these effects is uncertain. There were few studies that estimated the health care cost savings of transit systems, and those that did tended to be imprecise and simplistic. Objective physical activity measures and frequency-based transit measures would allow for greater consistency across studies and help more directly attribute physical activity gains to transit ridership. Additionally, research in this area would benefit from disaggregate estimation techniques and more robust health datasets that can be better linked with existing transit data.

Active commuting and obesity in mid-life: cross-sectional, observational evidence from UK Biobank

BACKGROUND

Physical inactivity is a leading cause of obesity and premature mortality. We aimed to examine the relation between active commuting and obesity in mid-life using objectively measured anthropometric data from UK Biobank.

METHODS

Cross-sectional, observational data from UK Biobank were used. These were collected from individuals aged 40-69 years who visited 22 assessment centres across the UK between 2006 and 2010. Self-reported commuting method was operationalised into seven categories, ordered to reflect typical levels of physical exertion. The outcomes assessed were BMI (based on objectively measured weight and height) and percentage body fat. Hypothesised confounders were income, area deprivation, urban or rural residence, education, alcohol intake, smoking, leisure physical activity, recreational walking, occupational physical activity, general health, and limiting illness or disability. We used sex-stratified multivariate linear-regression models.

FINDINGS

Final complete case sample sizes were 72 999 men and 83 667 women for the BMI outcome and 72 139 men and 82 788 women for the percentage body fat outcome. Active commuting was significantly and independently associated with reduced BMI and percentage body fat for both sexes, with a graded pattern apparent across the seven commuting categories. In fully adjusted models, compared with their car-only counterparts, mixed public and active transport commuters had significantly lower BMI (men: β coefficient -1·00 kg/m(2) [95% CI -1·14 to -0·87], p<0·0001; women: -0·67 kg/m(2) [-0·86 to -0·47], p<0·0001), as did cycling or cycling and walking commuters (men: -1·71 kg/m(2) [95% CI -1·86 to -1·56], p<0·0001; women: -1·65 kg/m(2) [-1·92 to -1·38], p<0·0001). Similarly, compared with car-only commuters, mixed public transport and active commuters had significantly lower percentage body fat (men: -1·32% [95% CI -1·53 to -1·12], p<0·0001; women: -1·10% [-1·40 to -0·81], p<0·0001), as did cycling or cycling and walking commuters (men: -2·75% [95% CI -3·03 to -2·48], p<0·0001; women: -3·26% [-3·80 to -2·71], p<0·0001).

INTERPRETATION

This study is the first to use UK Biobank data to address the topic of active commuting and obesity and shows robust, independent associations between active commuting and healthier bodyweight and composition. These findings support the case for interventions to promote active travel as a population-level policy response for prevention of obesity in mid-life.

FUNDING

UK Medical Research Council.

Change in active transportation and weight gain in pregnancy

BACKGROUND

Pregnancy is characterised by large weight gain over a short period, and often a notable change in mode of transportation. This makes pregnancy suitable for examining the plausible, but in the scientific literature still unclear, association between active transportation and weight gain. We hypothesize that women continuing an active mode of transportation to work or school from pre- to early pregnancy will have a lower gestational weight gain (GWG) than those who change to a less active mode of transportation.

METHODS

We analysed prospective data from the Norwegian Fit for Delivery (NFFD) trial. Between September 2009 and February 2013 606 women were consecutively enrolled in median gestational week 16 (range; 8-20). Of 219 women who used an active mode of transportation (biking, walking, public transportation) pre-pregnancy, 66 (30%) converted to a less active mode in early pregnancy ("active-less active" group), and 153 (70%) continued with active transportation ("active-active" group). Pre-pregnancy weight was self-reported. Weight at gestational (GA) weeks 16, 30, 36, and at term delivery was objectively measured. Weight gain was compared between the two groups. Linear mixed effects analysis of the repeated weight measures was performed including the group*time interaction.

RESULTS

A significant overall group effect was observed for the four time points together ("active-active" group: 77.3 kg vs. "active-less active" group: 78.8 kg, p = 0.008). The interaction term group*time was significant indicating different weight gain throughout pregnancy for the two groups; the mean differences between the groups were 0.7 kg at week 16, 1.4 kg at week 30, 2.1 kg at week 36, and 2.2 kg at term delivery, respectively.

CONCLUSION

The findings indicate that active transportation is one possible approach to prevent excessive weight gain in pregnancy.