Resumen: Objetivo: Examinar la fiabilidad y la validez de una escala para evaluar las barreras percibidas en el desplazamiento activo al centro escolar en jóvenes españoles. Método: La validez de la ...escala fue evaluada en una muestra de 465 adolescentes (14-18 años de edad) mediante un análisis factorial confirmatorio y a través de la asociación con el transporte activo autorreportado. Una submuestra completó la escala dos veces, con una separación de una semana, a fin de evaluar su fiabilidad. Resultados: Los resultados mostraron que la escala tenía índices de ajuste satisfactorios con dos factores. Un factor incluyó los ítems relativos a ambiente y seguridad (α = 0,72), y otro los ítems sobre planificación y aspectos psicosociales (α = 0,64). El transporte activo se relacionó significativamente con la puntuación total de la escala de barreras (rho = −0,27; p <0,001), con las barreras ambientales/seguridad (rho = −0,22; p <0,001) y con las barreras de planificación/psicosociales (rho = −0,29; p <0,001). Los test-retest (coeficiente de correlación intraclase) para las barreras mostraron valores entre 0,68 y 0,77. Conclusión: La escala muestra una validez aceptable y una fiabilidad adecuada para evaluar las barreras en el transporte activo al centro educativo en jóvenes españoles. Abstract: Objective: To examine the reliability and validity of a scale to measure perceived barriers to active commuting to school among Spanish young people. Method: The validity of the scale was assessed in a sample of 465 adolescents (14–18 years) using a confirmatory factor analysis and studying its association with self-reported active commuting to school. The reliability of the instrument was evaluated in a sub-sample that completed the scale twice separated by a one-week interval. Results: The results showed that the barriers scale had satisfactory fit indices, and two factors were determined. The first included environment- and safety-related items (α = 0.72), while the other concerned planning and psychosocial items (α = 0.64). Active commuting to school showed significant correlations with the total score of the barriers scale (rho = −0.27; p <0.001), with the environmental/safety barriers (rho = −0.22; p <0.001), as well as with the planning/psychosocial barriers (rho = −0.29; p <0.001). Test-retest ICCs for the barriers ranged from 0.68 to 0.77. Conclusion: The developed scale has acceptable validity and good reliability to assess barriers to active commuting to school among Spanish young people. Palabras clave: Transporte activo, Adolescentes, Ambiente, Vecindario, Keywords: Active commuting, Adolescents, Environment, Neighbourhood
Active commuting to school has been recognized as a potential avenue to increase physical activity in children and adolescents. However, active commuting to school has declined over time, and ...interventions are needed to reverse this trend. The main aim in the current study was to update a previous systematic review on interventions focused on active travel to school, following the same methodology and addressing the quality and effectiveness of new studies detected in the more recent scientific literature. A systematic review was conducted to identify intervention studies of active commuting to school published from February 2010 to December 2016. Five electronic databases and a manual search were conducted. Detailed information was extracted, including a quantitative assessment comparing the effect sizes, with Cohen's d, and a qualitative assessment using the Evaluation of Public Health Practice Projects tool. We identified 23 interventions that focused on active commuting to school. Among the 23 interventions, three were randomized control trials, 22 had a pre/post design, and 12 used control groups. Most interventions reported a small effect size on active commuting to school (14/23) (d: from ‐1.45 to 2.37). The quality assessment was rated as weak in most studies (21/23). Government funding continues investing in public policies to promote active commuting to school. However, even though seven years have passed since the last systematic review, research with high quality designs with randomization, greater sample size, and the use of valid and reliable instruments are needed.
•Active commuting to school could be used to increase physical activity in youth.•New intervention strategies are needed to prevent the decrease of active commuting.•Twenty-three studies have been identified in this systematic review.•Most of studies reported a small effect size and a weak quality designs.•Higher quality study designs should be conducted to improve future interventions.
•GSEM outperforms SEM in the research on built environment (BE) and active commuting.•The clustering effects of neighborhood- and city-level BE attributes are revealed.•City-level BE is more related ...to active commuting time, BMI and life satisfaction, but less to active commuting mode.•Active commuting mode does not matter to BMI, but to life satisfaction while active commuting time shows the opposite associations.•Life satisfaction is related to active commuting mode and BMI, but not to active commuting time.
The effects of the built environment (BE) on modes of transport have been extensively evaluated in the literature with a primary focus on the neighborhood-level BE. Moreover, it has been revealed that transportation modes are associated with an individual’s life choices and the resulting quality of life (QoL). However, the effects of the BE on the transportation, which in turn affects the QoL, remain largely unknown. This is especially true considering that the BE can be evaluated at different spatial scales, which further involves both observed and unobserved clustering effects. Based on data from 8,862 respondents living in 97 Chinese cities (collected in 2014), this study builds a generalized structural equation model (GSEM) to explore the complex relationships between both neighborhood- and city-level BE attributes, active commuting, body mass index (BMI), and life satisfaction within a unified analysis framework. The results show that: (1) GSEM significantly outperforms the conventional structural equation model; (2) life satisfaction is related to both active commuting modes and BMI, while the active commuting time is related to BMI; and (3) the city-level BE has a much stronger relevance to active commuting time, BMI, and life satisfaction, but a weaker relevance to active commuting modes, than the neighborhood-level BE.
There is ample evidence regarding positive health effects of cycling or walking to work (active commuting AC). However, little is known about the effects of AC on work ability. Therefore, we examined ...422 Thai chicken meat industry workers who assessed their current work ability (CWA) compared to their lifetime best by assigning scores ranging from 0 to 10. The CWA was compared between active and non-active commuters using linear regression, cumulative distributions, and quantile regression. Overall, 46 workers (11%) were active commuters. The average CWA score was 8.2 (standard deviation, 1.3; range, 4–10). It was higher by 0.5 units (95% confidence interval: 0.2–0.8) in active commuters. Cumulative distributions showed higher CWA scores among active commuters throughout the CWA scale, with the greatest difference (one CWA unit) at scores of 8–9. This benefit of AC persisted after adjustments and was observed at the 33rd, 50th, and 67th percentiles of CWA but not at percentiles higher or lower than the aforementioned ones. The model-predicted CWA scores for selected combinations of personal and work-related factors were up to two units higher among active commuters. In conclusion, active commuters have better work ability than non-active commuters. However, the potential effects may be limited to workers with good work ability.
Relevance to the industry: Since commuting is a necessary daily activity for most of the working population, AC may offer great potential to produce positive effects on work ability and health. AC should be encouraged and included in health promotion programs at national and organizational levels.
•Effects of active commuting (walking or biking) on work ability are not well known.•Work ability (scores 1–10) was compared between active and non-active commuters.•Work ability score was up to 1 unit higher among active than non-active commuters.•Active commuting may benefit mainly workers with moderate or good work ability.•Promoting active commuting has great potential to enhance work ability.
Abstract 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 10 minute 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.
Objectives: Changing the mode of commuting from nonactive by car or motorcycle to active by walking, cycling, or public transport is expected to benefit health. However, the proportion of nonactive ...commuters who can change their commute mode to active forms remains unclear. The aim of this study was to determine the proportions of nonactive commuters and of those who can change their commute mode to an active form in various regions in Japan. Methods: In this descriptive study, data were used from an online survey conducted from April to May 2021. Participants included 3,000 adults (20 to 79 years), who were registered with an online survey company. Workers were asked their means of transportation to work and commuting time. Workers using a car or motorcycle for more than 1 minute for commuting were defined as nonactive commuters, and the others were defined as active commuters. Then, nonactive commuters were asked about the possibility of changing their commute mode to active commuting (0%–100%, 11 options in 10% increments). The possibility of change was classified into four groups, i.e., impossible (0%), difficult (10%–40%), probably possible (50%–90%), and possible (100%). The proportions of nonactive commuters and nonactive commuters who can transition to active commuting were described by region. Results: A total of 2,683 participants answered the survey, including 1,647 workers, of whom 1,551 were commuters. The nonactive commuters accounted for 41.4% of commuters overall. The proportion of nonactive commuters was higher in rural than in urban regions. The proportion of nonactive commuters who could change their commute mode was 32.9% of the nonactive commuters or 12.8% of all workers. Among the nonactive commuters, the proportion who could change their commute mode was higher in urban than in rural regions. Of the total workers, the proportion of nonactive commuters who could change their commute mode was higher in rural regions. Conclusion: Nonactive commuters accounted for 41.4% of all commuters. The proportion of nonactive commuters who could change their commute mode among nonactive commuters was higher in urban regions. However, in rural regions, as the proportion of nonactive commuters was high, the proportion of nonactive commuters who could change their commute mode among total workers was also high. These results suggest that some of nonactive commuters can change their commute mode from nonactive to active commuting, in rural as well as in urban regions.
Aim:
To determine the extent to which level of active commute mode use is associated with self-rated health and work ability.
Methods:
The data were sourced from the Finnish Public Sector Study ...survey in 2020 (n = 38,223). The associations between active commuting – assessed with the frequency of using active commute modes – and self-rated health and work ability were examined with negative binomial regression analyses. Passive commuting and low-to-moderate levels of active commuting were compared with active commuting, and the models were adjusted for sociodemographic factors, working time mode, and lifestyle risk factors. We also assessed separate associations between walking and cycling as a mode of commuting by additionally considering the commuting distance and the outcomes.
Results:
After adjustment, when using active commuters as a reference, passive commuters had a 1.23-fold (95% confidence intervals (CI) 1.19 to 1.29) risk of suboptimal self-rated health and a 1.18-fold (95% CI 1.13 to 1.22) risk of suboptimal work ability. More frequent and/or longer distance by foot and especially by bicycle, was positively associated with health and work ability. Never commuting by bicycle was associated with a 1.65-fold (95% CI 1.55 to 1.74) risk of suboptimal health and a 1.27-fold (95% CI 1.21 to 1.34) risk of suboptimal work ability when using high-dose bicycle commuting as a reference.
Conclusions:
Passive commuting was associated with suboptimal self-rated health and suboptimal work ability. Our results suggest that using active commute modes, particularly cycling, may be beneficial for employee health and work ability.
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