Potential health impact of switching from car to public transportation when commuting to work

Transit Use and Health Care Costs: A Cross-sectional Analysis

INTRODUCTION

Greater transit use is associated with higher levels of physical activity, which is associated with lower health risks and better health outcomes. However, there is scant evidence about whether health care costs differ based on level of transit ridership.

METHODS

A sample (n=947) of members of Kaiser Permanente in the Portland, Oregon area were surveyed in 2015 about their typical use of various modes of travel including transit. Electronic medical record-derived health care costs were obtained among these members for the prior three years. Analysis examined proportional costs between High transit users (3+ days/week), Low transit users (1-2 days/week), and Non-users adjusting for age and sex, and then individually (base models) and together for demographic and health status variables.

RESULTS

In separate base models across individual covariates, High transit users had lower total health care costs (59-69% of Non-user's costs) and medication costs (31-37% of Non-users' costs) than Non-users. Low transit users also had lower total health care (69%-76% of Non-users' costs) and medication costs (43-57% transit of Non-user's costs) than Non-users. High transit users' outpatient costs were also lower (77-82% of Non-users). In fully-adjusted models, total health care and medication costs were lower among High transit users' (67% and 39%) and Low transit users' (75% and 48%) compared to Non-users, but outpatient costs did not differ by transit use.

CONCLUSIONS

Findings have implications for the potential cost benefit of encouraging and supporting more transit use, although controlled longitudinal and experimental evidence is needed to confirm findings and understand mechanisms.

Physical activity and sedentary behaviour related to transport activity assessed with multiple body-worn accelerometers: the RECORD MultiSensor Study

OBJECTIVES

The study explored the physical activity and sedentary behaviours related to transport activity. The aim was to provide evidence to support public health and transport policies encouraging people to reach daily recommendations of physical activity.

STUDY DESIGN

The study design of this study is a cross-sectional study design.

METHODS

Between 2013 and 2015, the RECORD MultiSensor Study collected data from 155 participants using two accelerometers worn on the thigh and trunk. In addition, data were collected from Global Positioning System (GPS) receivers and a GPS-based mobility survey. Relationships between transport modes and the durations and partition patterns of physical behaviours were established at the trip stage (n = 7692) and trip levels (n = 4683) using multilevel linear models with a random effect at the individual level and taking into account temporal autocorrelation.

RESULTS

Participants travelled for a median of 1 h 45 min per day. Trip stages and trips involving walking, other active modes or public transport were associated with a lower sitting duration and a higher moderate-to-vigorous physical activity (MVPA) duration than trips with a personal motorised vehicle. Using public transport was associated with a lower number of transitions between sedentary behaviours and non-sedentary behaviours, and with a higher number of transitions between non-sedentary behaviours and MVPA than relying on a private motorised vehicle.

CONCLUSIONS

This study is the first to assess the association of transport mode with physical activity and sedentary behaviours captured with thigh- and trunk-worn accelerometers at both the trip stage and trip levels. The results demonstrate that, in addition to active transport modes, encouraging people to use public transport increases physical activity and reduces sedentary time.

Physical activity accrued as part of public transport use in England

BACKGROUND

Walking and cycling for transport (active travel) is an important source of physical activity with established health benefits. However, levels of physical activity accrued during public transport journeys in England are unknown.

METHODS

Using the English National Travel Survey 2010-14 we quantified active travel as part of public transport journeys. Linear regression models compared levels of physical activity across public transport modes, and logistic regression models compared the odds of undertaking 30 min a day of physical activity.

RESULTS

Public transport users accumulated 20.5 min (95% confidence interval=19.8, 21.2) a day of physical activity as part of public transport journeys. Train users accumulated 28.1 min (26.3, 30.0) with bus users 16.0 min (15.3, 16.8). Overall, 34% (32%, 36%) of public transport users achieved 30 min a day of physical activity in the course of their journeys; 21% (19%, 24%) of bus users and 52% (47%, 56%) of train users.

CONCLUSION

Public transport use is an effective way to incorporate physical activity into daily life. One in three public transport users meet physical activity guidelines suggesting that shifts from sedentary travel modes to public transport could dramatically raise the proportion of populations achieving recommended levels of physical activity.

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

Background

Associations between driving and physical-activity (PA) intensities are unclear, particularly among older adults. We estimated prospective associations of travel modes with total PA, sedentary time (ST), light-intensity PA (LPA), and moderate-to-vigorous intensity PA (MVPA) among adults aged 39–70 years.

Methods

We studied 90 810 UK Biobank participants (56.1 ± 7.8 years). Driving status, specific travel modes (non-work travel; commuting to/from work) and covariates were assessed by questionnaire (2006–10). PA was assessed over 7 days by wrist-worn accelerometers (2013–15). We estimated associations using overall and age-stratified multivariable linear-regression models.

Results

Drivers accumulated 1.4% more total PA (95% confidence interval: 0.9, 1.9), 11.2 min/day less ST (–12.9, –9.5), 12.2 min/day more LPA (11.0, 13.3) and 0.9 min/day less MVPA (–1.6, –0.2) than non-drivers. Compared with car/motor-vehicle users, cyclists and walkers had the most optimal activity profiles followed by mixed-mode users (e.g. for non-work travel, cyclists: 10.7% more total PA, 9.0, 12.4; 20.5 min/day less ST, –26.0, –15.0; 14.5 min/day more MVPA, 12.0, 17.2; walkers: 4.2% more total PA, 3.5, 5.0; 7.5 min/day less ST –10.2, –4.9; 10.1 min/day more MVPA, 8.9, 11.3; mixed-mode users: 2.3% more total PA, 1.9, 2.7; 3.4 min/day less ST –4.8, –2.1; 4.9 min/day more MVPA, 4.3, 5.5). Some associations varied by age (p interaction < 0.05), but these differences appeared small.

Conclusions

Assessing specific travel modes rather than driving status alone may better capture variations in activity. Walking, cycling and, to a lesser degree, mixed-mode use are associated with more optimal activity profiles in adults of all ages.

Population health impacts of China's climate change policies

Rapid and wide-ranging reductions in greenhouse gas emissions are required to meet the climate targets agreed upon at the 2015 Paris climate conference. There will be significant transition risks for health, livelihoods, and ecosystems associated with large-scale mitigation, but also opportunities. The aim of this study was to investigate the impacts, positive and negative, of climate policies on population health in China. We review the Intended Nationally Determined Contribution (INDC) that China took to the Paris meeting, link commitments in the INDC to national planning documents relevant to environment and health, and search the literature for Chinese publications on health trade-offs and synergies. Synergies are evident in the measures taken to reduce local air pollution in China: controls on coal burning have materially improved local air quality and benefited health. But there may be risks to health also, depending on how policies are implemented and what safeguards are provided. To date most assessments of the health impacts of climate policies in China have been modelling studies. We recommend work of this kind is complemented by observational research to identify unexpected impacts and vulnerabilities. It will become even more important to undertake this work as emission reductions accelerate to meet the Paris climate targets.

The measurement of time spent outdoors in child myopia research: a systematic review

The purpose of this article is to summarize the methods most commonly used to measure time spent outdoors and provide a comprehensive review of time and activity recording methods with the aim of encouraging the development of new methods. PubMed, Embase and the Cochrane Library were searched from Jan. 1^st, 1990 to Aug. 31^th, 2017. Studies including the following specific terms: "outdoor", "outside", "outdoor activity", "outside activity", "outdoor time", "outside time", and "outdoor AND measurement of time spent outdoors" were considered for this review. In total, three kinds of outdoor time measurements were discussed. Questionnaires have the longest history and are the most thoroughly revised instruments for assessing time spent outdoors, but recall bias is their most substantial drawback. Global positioning system (GPS) tracking can distinguish between indoor and outdoor locations, but its utility is limited due to several factors such as subject compatibility. Light exposure measurement devices are newly emerging, but all of these devices require good subject cooperation. Further efforts and exploration are needed to develop better methods and new tools to record exposure to the outdoors in real time. Moreover, inventing a new device by combining two or more types of devices mentioned above and using the latest technology of en ergy supplementation and autoswitching may make the best use of the advantages and bypass the disadvantages of each tool.

Estimated effects of air pollution and space-time-activity on cardiopulmonary outcomes in healthy adults: A repeated measures study

BACKGROUND

Exposure to air pollution is known to affect both short and long-term outcomes of the cardiopulmonary system; however, findings on short-term outcomes have been inconsistent and often from isolated and long-term rather than coexisting and short-term exposures, and among susceptible/unhealthy rather than healthy populations.

AIMS

We aimed to investigate separately the annual, daily and daily space-time-activity-weighted effect of ambient air pollution, as well as confounding or modification by other environmental (including noise) or space-time-activity (including total daily physical activity) exposures, on cardiopulmonary outcomes in healthy adults.

METHODS

Participants (N=57: 54% female) had indicators of cardiopulmonary outcomes [blood pressure (BP), pulse (HR) and heart rate variability (HRV {SDNN}), and lung function (spirometry {FEV₁, FVC, SUM})] measured on four different mornings (at least five days apart) in a clinical setting between 2011 and 2014. Spatiotemporal ESCAPE-LUR models were used to estimate daily and annual air pollution exposures (including PM₁₀, PM_Coarse, but not Ozone {derived from closest station}) at participant residential and occupational addresses. Participants' time-activity diaries indicated time spent at either address to allow daily space-time-activity-weighted estimates, and capture total daily physical activity (total-PA {as metabolic-equivalents-of-task, METs}), in the three days preceding health measurements. Multivariate-adjusted linear mixed-effects models (using either annual or daily estimates) were adjusted for possible environmental confounders or mediators including levels of ambient noise and greenness. Causal mediation analysis was also performed separately considering these factors as well as total-PA. All presented models are controlled by age, height, sex and season.

RESULTS

An increase in 5μg/m³ of daily space-time-activity-weighted PM_Coarse exposure was statistically significantly associated with a 4.1% reduction in total heart rate variability (SDNN; p=0.01), and remained robust after adjusting for suspected confounders [except for occupational-address noise (β=-2.7, p=0.20)]. An increase in 10ppb of annual mean Ozone concentration at the residential address was statistically significantly associated with an increase in diastolic BP of 6.4mmHg (p<0.01), which lost statistical significance when substituted with daily space-time-activity-weighted estimates. As for pulmonary function, an increase in 10μg/m³ of annual mean PM₁₀ concentration at the residential address was significantly associated with a 0.3% reduction in FVC (p<0.01) and a 0.5% reduction in SUM (p<0.04), for which again significance was lost when substituted for daily space-time-activity-weighted estimates These associations with pulmonary function remained robust after adjusting for suspected confounders, including annual Ozone, as well as total-PA and bioaerosol (pollen and fungal spore) levels (but not residential-neighborhood greenness {β=-0.22, p=0.09; β=-0.34, p=0.15, respectively}). Multilevel mediation analysis indicated that the proportion mediated as a direct effect on cardiopulmonary outcomes by suspected confounders (including total-PA, residential-neighborhood greenness, and occupational-address noise level) from primary exposures (including PM₁₀, PM_Coarse, and O₃) was not statistically significant.

CONCLUSION

Our findings suggest that increased daily space-time-activity-weighted PM_Coarse exposure levels significantly adversely affect cardiac autonomic modulation (as reduced total HRV) among healthy adults. Additionally, increased annual levels at the residential address of Ozone and PM₁₀ significantly increase diastolic blood pressure and reduce lung function, respectively, among healthy adults. These associations typically remained robust when adjusting for suspected confounders. Occupational-address noise and residential-neighborhood greenness levels, however, were seen as mediators of cardiovascular and pulmonary outcomes, respectively. Total daily physical activity was not seen as a mediator of any of the studied outcomes, which supports the promotion of active mobility within cities.

Free Bus Travel and Physical Activity, Gait Speed, and Adiposity in the English Longitudinal Study of Ageing

OBJECTIVES

We investigated associations between having a bus pass, enabling free local bus travel across the United Kingdom for state pension-aged people, and physical activity, gait speed, and adiposity.

METHODS

We used data on 4650 bus pass-eligible people (aged ≥ 62 years) at wave 6 (2012-2013) of the English Longitudinal Study of Ageing in regression analyses.

RESULTS

Bus pass holders were more likely to be female (odds ratio [OR] = 1.67; 95% confidence interval [CI] = 1.38, 2.02; P < .001), retired (OR = 2.65; 95% CI = 2.10, 3.35; P < .001), without access to a car (OR = 2.78; 95% CI = 1.83, 4.21; P < .001), to use public transportation (OR = 10.26; 95% CI = 8.33, 12.64; P < .001), and to be physically active (OR = 1.43; 95% CI = 1.12, 1.84; P = .004). Female pass holders had faster gait speed (b = 0.06 meters per second; 95% CI = 0.02, 0.09; P = .001), a body mass index 1 kilogram per meter squared lower (b = -1.20; 95% CI = -1.93, -0.46; P = .001), and waist circumference 3 centimeters smaller (b = -3.32; 95% CI = -5.02, -1.62; P < .001) than women without a pass.

CONCLUSIONS

Free bus travel for older people helps make transportation universally accessible, including for those at risk for social isolation. Those with a bus pass are more physically active. Among women in particular, the bus pass is associated with healthier aging.

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

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.

Examining the link between public transit use and active commuting

BACKGROUND

An established relationship exists between public transportation (PT) use and physical activity. However, there is limited literature that examines the link between PT use and active commuting (AC) behavior. This study examines this link to determine if PT users commute more by active modes.

METHODS

A volunteer, convenience sample of adults (n = 748) completed an online survey about AC/PT patterns, demographic, psychosocial, community and environmental factors. t-test compared differences between PT riders and non-PT riders. Binary logistic regression analyses examined the effect of multiple factors on AC and a full logistic regression model was conducted to examine AC.

RESULTS

Non-PT riders (n = 596) reported less AC than PT riders. There were several significant relationships with AC for demographic, interpersonal, worksite, community and environmental factors when considering PT use. The logistic multivariate analysis for included age, number of children and perceived distance to work as negative predictors and PT use, feelings of bad weather and lack of on-street bike lanes as a barrier to AC, perceived behavioral control and spouse AC were positive predictors.

CONCLUSIONS

This study revealed the complex relationship between AC and PT use. Further research should investigate how AC and public transit use are related.

Does active commuting improve psychological wellbeing? Longitudinal evidence from eighteen waves of the British Household Panel Survey

OBJECTIVE

The aim of this study is to explore the relationship between active travel and psychological wellbeing.

METHOD

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.

RESULTS

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.

CONCLUSION

The positive psychological wellbeing effects identified in this study should be considered in cost-benefit assessments of interventions seeking to promote active travel.

Application of global positioning system methods for the study of obesity and hypertension risk among low-income housing residents in New York City: a spatial feasibility study

The purpose of this study was to evaluate the feasibility of using global positioning system (GPS) methods to understand the spatial context of obesity and hypertension risk among a sample of low-income housing residents in New York City (n = 120). GPS feasibility among participants was measured with a pre- and post-survey as well as adherence to a protocol which included returning the GPS device as well as objective data analysed from the GPS devices. We also conducted qualitative interviews with 21 of the participants. Most of the sample was overweight (26.7%) or obese (40.0%). Almost one-third (30.8%) was pre-hypertensive and 39.2% was hypertensive. Participants reported high ratings of GPS acceptability, ease of use and low levels of wear-related concerns in addition to few concerns related to safety, loss or appearance, which were maintained after the baseline GPS feasibility data collection. Results show that GPS feasibility increased over time. The overall GPS return rate was 95.6%. Out of the total of 114 participants with GPS, 112 (98.2%) delivered at least one hour of GPS data for one day and 84 (73.7%) delivered at least one hour on 7 or more days. The qualitative interviews indicated that overall, participants enjoyed wearing the GPS devices, that they were easy to use and charge and that they generally forgot about the GPS device when wearing it daily. Findings demonstrate that GPS devices may be used in spatial epidemiology research in low-income and potentially other key vulnerable populations to understand geospatial determinants of obesity, hypertension and other diseases that these populations disproportionately experience.

Active transportation and public transportation use to achieve physical activity recommendations? A combined GPS, accelerometer, and mobility survey study

BACKGROUND

Accurate information is lacking on the extent of transportation as a source of physical activity, on the physical activity gains from public transportation use, and on the extent to which population shifts in the use of transportation modes could increase the percentage of people reaching official physical activity recommendations.

METHODS

In 2012-2013, 234 participants of the RECORD GPS Study (French Paris region, median age = 58) wore a portable GPS receiver and an accelerometer for 7 consecutive days and completed a 7-day GPS-based mobility survey (participation rate = 57.1%). Information on transportation modes and accelerometry data aggregated at the trip level [number of steps taken, energy expended, moderate to vigorous physical activity (MVPA), and sedentary time] were available for 7,644 trips. Associations between transportation modes and accelerometer-derived physical activity were estimated at the trip level with multilevel linear models.

RESULTS

Participants spent a median of 1 h 58 min per day in transportation (8.2% of total time). Thirty-eight per-cent of steps taken, 31% of energy expended, and 33% of MVPA over 7 days were attributable to transportation. Walking and biking trips but also public transportation trips with all four transit modes examined were associated with greater steps, MVPA, and energy expenditure when compared to trips by personal motorized vehicle. Two simulated scenarios, implying a shift of approximately 14% and 33% of all motorized trips to public transportation or walking, were associated with a predicted 6 point and 13 point increase in the percentage of participants achieving the current physical activity recommendation.

CONCLUSIONS

Collecting data with GPS receivers, accelerometers, and a GPS-based electronic mobility survey of activities and transportation modes allowed us to investigate relationships between transportation modes and physical activity at the trip level. Our findings suggest that an increase in active transportation participation and public transportation use may have substantial impacts on the percentage of people achieving physical activity recommendations.

Relation between higher physical activity and public transit use

OBJECTIVES

We isolated physical activity attributable to transit use to examine issues of substitution between types of physical activity and potential confounding of transit-related walking with other walking.

METHODS

Physical activity and transit use data were collected in 2008 to 2009 from 693 Travel Assessment and Community study participants from King County, Washington, equipped with an accelerometer, a portable Global Positioning System, and a 7-day travel log. Physical activity was classified into transit- and non-transit-related walking and nonwalking time. Analyses compared physical activity by type between transit users and nonusers, between less and more frequent transit users, and between transit and nontransit days for transit users.

RESULTS

Transit users had more daily overall physical activity and more total walking than did nontransit users but did not differ on either non-transit-related walking or nonwalking physical activity. Most frequent transit users had more walking time than least frequent transit users. Higher physical activity levels for transit users were observed only on transit days, with 14.6 minutes (12.4 minutes when adjusted for demographics) of daily physical activity directly linked with transit use.

CONCLUSIONS

Because transit use was directly related to higher physical activity, future research should examine whether substantive increases in transit access and use lead to more physical activity and related health improvements.

Health-related factors associated with mode of travel to work

Active commuting (AC) to the workplace is a potential strategy for incorporating physical activity into daily life and is associated with health benefits. This study examined the association between health-related factors and mode of travel to the workplace. Methods. A volunteer convenience sample of employed adults completed an online survey regarding demographics, health-related factors, and the number of times/week walking, biking, driving, and using public transit to work (dichotomized as no walk/bike/drive/PT and walk/bike/drive/PT 1 + x/week). Logistic regression was used to predict the likelihood of each mode of transport and meeting PA recommendations from AC according to demographics and health-related factors. Results. The sample (n = 1175) was aged 43.5 ± 11.4 years and was primarily White (92.7%) and female (67.9%). Respondents reported walking (7.3%), biking (14.4%), taking public transit (20.3%), and driving (78.3%) to work at least one time/week. Among those reporting AC, 9.6% met PA recommendations from AC alone. Mode of travel to work was associated with several demographic and health-related factors, including age, number of chronic diseases, weight status, and AC beliefs. Discussion. Mode of transportation to the workplace and health-related factors such as disease or weight status should be considered in future interventions targeting AC.

Financial incentives to promote active travel: an evidence review and economic framework

CONTEXT

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.

EVIDENCE ACQUISITION

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.

EVIDENCE SYNTHESIS

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.

CONCLUSIONS

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.

Is active travel associated with greater physical activity? The contribution of commuting and non-commuting active travel to total physical activity in adults

BACKGROUND

To complement findings that active travel reduces the risk of morbidity and mortality from chronic diseases, an understanding of the mechanisms through which active travel may lead to improved health is required.

PURPOSE

The aim of this study is to examine the descriptive epidemiology of all active travel and its associations with recreational and total physical activity in a sample of adults in the UK.

METHODS

In April 2010, data were collected from 3516 adults as part of the baseline survey for the iConnect study in the UK. Travel and recreational physical activity were assessed using detailed seven-day recall instruments. Linear regression analyses, controlling for demographic characteristics, examined associations between active travel, defined as any walking and cycling for transport, and recreational and total physical activity.

RESULTS

65% of respondents (mean age 50.5 years) reported some form of active travel, accumulating an average of 195 min/week (standard deviation=188.6). There were no differences in the recreational physical activity levels of respondents by travel mode category. Adults who used active travel did however report significantly higher total physical activity than those who did not.

CONCLUSIONS

Substantial physical activity can be accumulated through active travel which also contributes to greater total physical activity.

Bicycling to school is associated with improvements in physical fitness over a 6-year follow-up period in Swedish children

OBJECTIVE

To examine whether modes of commuting to school at baseline and changes in commuting were related to 6-year changes in cardiorespiratory fitness in youth.

METHODS

A total of 262 (142 girls) Swedish children (9 years at entry) were measured at baseline (1998/9) and follow-up (2004/5). Mode of commuting to school was assessed by questionnaire and fitness by a maximal bicycle test.

RESULTS

At baseline, 34% of children used passive modes of commuting (e.g., car, motorcycle, bus, train), 54% walked, and 12% bicycled to school. Six years later the percentage of bicyclists increased 19% and the percentage of walkers decreased 19%. On average, children who bicycled to school increased their fitness 13% (p=0.03) more than those who used passive modes and 20% (p=0.002) more than those who walked. Children who used passive modes or walked at baseline and bicycled to school at 6 years later increased their fitness 14% (p=0.001) more than those who remained using passive modes or walking at follow-up.

CONCLUSIONS

Implementing initiatives that encourage bicycling to school may be a useful strategy to increase cardiorespiratory fitness of children.

Physical activity associated with public transport use--a review and modelling of potential benefits

Active travel, particularly walking and cycling, has been recommended because of the health benefits associated with increased physical activity. Use of public transport generally involves some walking to bus stops or train stations. This paper is a systematic review of how much time is spent in physical activity among adults using public transport. It also explores the potential effect on the population level of physical activity if inactive adults in NSW, Australia, increased their walking through increased use of public transport. Of 1,733 articles, 27 met the search criteria, and nine reported on absolute measures of physical activity associated with public transport. A further 18 papers reported on factors associated with physical activity as part of public transport use. A range of 8–33 additional minutes of walking was identified from this systematic search as being attributable to public transport use. Using “bootstrapping” statistical modelling, if 20% of all inactive adults increased their walking by only 16 minutes a day for five days a week, we predict there would be a substantial 6.97% increase in the proportion of the adult population considered “sufficiently active”. More minutes walked per day, or a greater uptake of public transport by inactive adults would likely lead to significantly greater increases in the adult population considered sufficiently active.

A review of spatial methods in epidemiology, 2000-2010

Understanding the impact of place on health is a key element of epidemiologic investigation, and numerous tools are being employed for analysis of spatial health-related data. This review documents the huge growth in spatial epidemiology, summarizes the tools that have been employed, and provides in-depth discussion of several methods. Relevant research articles for 2000-2010 from seven epidemiology journals were included if the study utilized a spatial analysis method in primary analysis (n = 207). Results summarized frequency of spatial methods and substantive focus; graphs explored trends over time. The most common spatial methods were distance calculations, spatial aggregation, clustering, spatial smoothing and interpolation, and spatial regression. Proximity measures were predominant and were applied primarily to air quality and climate science and resource access studies. The review concludes by noting emerging areas that are likely to be important to future spatial analysis in public health.

Biologic and epigenetic impact of commuting to work by car or using public transportation: a case-control study

BACKGROUND AND AIMS

Commuting by public transportation (PT) entails more physical activity and energy expenditure than by cars, but its biologic consequences are unknown.

METHODS

In 2009-2010, we randomly sampled New York adults, usually commuting either by car (n=79) or PT (n=101). Measures comprised diet and physical activity questionnaires, weight and height, white blood cell (WBC) count, C reactive protein, (CRP) gene-specific methylation (IL-6), and global genomic DNA methylation (LINE-1 methylation).

RESULTS

Compared to the 101 PT commuters, the 79 car drivers were about 9 years older, 2 kg/m(2) heavier, more often non-Hispanic whites, and ate more fruits and more meats. The 2005 guidelines for physical activity were met by more car drivers than PT users (78.5% vs. 65.0%). There were no differences in median levels of CRP (car vs. PT: 0.6 vs. 0.5mg/dl), mean levels of WBC (car vs. PT: 6.7 vs. 6.5 cells/mm(3)), LINE-1 methylation (car vs. PT: 78.0% vs. 78.3%), and promoter methylation of IL-6 (car vs. PT: 56.1% vs. 58.0%).

CONCLUSIONS

PT users were younger and lighter than car drivers, but their commute mode did not translate into a lower inflammatory response or a higher DNA methylation, maybe because, overall, car drivers were more physically active.

Health impacts of the built environment: within-urban variability in physical inactivity, air pollution, and ischemic heart disease mortality

BACKGROUND

Physical inactivity and exposure to air pollution are important risk factors for death and disease globally. The built environment may influence exposures to these risk factors in different ways and thus differentially affect the health of urban populations.

OBJECTIVE

We investigated the built environment's association with air pollution and physical inactivity, and estimated attributable health risks.

METHODS

We used a regional travel survey to estimate within-urban variability in physical inactivity and home-based air pollution exposure [particulate matter with aerodynamic diameter ≤ 2.5 μm (PM2.5), nitrogen oxides (NOx), and ozone (O3)] for 30,007 individuals in southern California. We then estimated the resulting risk for ischemic heart disease (IHD) using literature-derived dose-response values. Using a cross-sectional approach, we compared estimated IHD mortality risks among neighborhoods based on "walkability" scores.

RESULTS

The proportion of physically active individuals was higher in high- versus low-walkability neighborhoods (24.9% vs. 12.5%); however, only a small proportion of the population was physically active, and between-neighborhood variability in estimated IHD mortality attributable to physical inactivity was modest (7 fewer IHD deaths/100,000/year in high- vs. low-walkability neighborhoods). Between-neighborhood differences in estimated IHD mortality from air pollution were comparable in magnitude (9 more IHD deaths/100,000/year for PM2.5 and 3 fewer IHD deaths for O3 in high- vs. low-walkability neighborhoods), suggesting that population health benefits from increased physical activity in high-walkability neighborhoods may be offset by adverse effects of air pollution exposure.

POLICY IMPLICATIONS

Currently, planning efforts mainly focus on increasing physical activity through neighborhood design. Our results suggest that differences in population health impacts among neighborhoods are similar in magnitude for air pollution and physical activity. Thus, physical activity and exposure to air pollution are critical aspects of planning for cleaner, health-promoting cities.

Using global positioning systems in health research: a practical approach to data collection and processing

The use of GPS devices in health research is increasingly popular. There are currently no best-practice guidelines for collecting, processing, and analyzing GPS data. The standardization of data collection and processing procedures will improve data quality, allow more-meaningful comparisons across studies and populations, and advance this field more rapidly. This paper aims to take researchers, who are considering using GPS devices in their research, through device-selection criteria, device settings, participant data collection, data cleaning, data processing, and integration of data into GIS. Recommendations are outlined for each stage of data collection and analysis and indicates challenges that should be considered. This paper highlights the benefits of collecting GPS data over traditional self-report or estimated exposure measures. Information presented here will allow researchers to make an informed decision about incorporating this readily available technology into their studies. This work reflects the state of the art in 2011.