Active Commuting Research Articles

Active Commuting to University Is Positively Associated with Physical Activity and Perceived Fitness

Background: Fitness is a powerful marker of health associated with physical activity (PA) in university students. However, insufficient PA is a serious health concern among university students. Active commuting provides an opportunity for increased PA levels. Therefore, the aims of this study were (a) to describe the mode of commuting, PA and fitness in university students; (b) to analyze the associations of mode of commuting with PA and fitness; and c) to analyze the relationship between mode of commuting, PA recommendations and fitness. Methods: This was a cross-sectional study. A total of 1257 university students (52.4% women) participated (22.4 ± 5.6 years old). Results: Public commuting was the main mode to and from university. Active and public commuters were more likely to meet the PA recommendations and reported higher muscular strength than those using private commuting. Active and public commuters who met PA recommendations present the highest fitness in most of its components. Conclusions: Achieving the PA recommendations was more relevant than adopting an active mode of commuting in order to have better fitness. Further research targeting a broader understanding of the mode of commuting, PA levels and fitness in university students is needed.

Personal air pollution exposure during morning commute car and active transport journeys

IntroductionCommuting by car in cities during rush hour can potentially result in the commuter being exposed to large concentrations of pollutants. We investigated the differences in pollutant concentrations by commute type in real world journeys in a typical medium-sized city in the UK. MethodsNO2, O3 and PM2.5 concentrations were monitored on weekday morning commutes into Leicester city centre on four routes. A driving commute was made on all four routes and were paired with measurements made via an active commute (either driving or cycling). The average commute exposure to pollutants was determined and the inhaled dosage was estimated. ResultsAverage in-car NO2 concentrations were 30.3 μg m−3and 24.9 μg m-3 higher than that measured in the cycling commutes, and 31.6 μg m−3 and 5.7 μg m−3 higher than average concentrations measured during walking commutes. In-car O3 concentrations were higher than concentrations measured during cycling (8.4 μg m−3, 35.6 μg m−3) and walking commutes (15.5 μg m−3and 33.1 μg m−3). Average in car PM2.5 were 1.8 μg m−3 and 4.3 μg m −3 lower than average concentrations measured during cycling and 1.9 μg m−3 and 1.5 μg m−3 lower than average concentrations measured whilst walking. We calculated higher cumulative doses of pollutants in the active commute compared to the driving commute. However, the health benefits of exercise, through improved physical and mental health as outlined in the literature are expected to outweigh any adverse impacts of the inhaled dosage of pollutants monitored. ConclusionsConcentrations of air pollutants in cars can be considerably higher than concentrations faced by active travellers. Commuters sitting in cars can both miss the benefits of physical activity and be exposed to higher levels of NO2 than in active transport, which is particularly important in countries like the UK with NOx exceedances.

Establishing the Convergent Validity of the Travel Habit Questions in the Health Behavior in School-Aged Children Questionnaire by Quantifying Active Travel in Norwegian Adolescents.

BackgroundActive travel (cycling or walking to school) can be a substantial part of adolescents' daily physical activity. Research on transport activities primarily relies on self-reported indices of travel mode and travel time. However, many researchers do not report the psychometric properties of their instruments. The Health Behavior in School-aged Children (HBSC) questionnaire is a commonly used instrument, but the items in this questionnaire on travel habits have not yet been validated. The present study was conducted to investigate the convergent validity and agreement between the HBSC items and a travel diary on (1) transport mode to and from school and (2) travel time to school.MethodsThe study sample consisted of 50 participants in the 9th grade (15 ± 0.3 years, 62% girls) from seven Norwegian schools. Outcome variables included transport mode and travel time derived from the HBSC items and a five-day travel diary. Convergent validity was assessed by evaluating Cohen's kappa for travel mode and the correlation coefficient (Spearman Rho) for travel time. Simple agreement calculations between the two measurement methods were also conducted.ResultsThe association between the HBSC questionnaire and the diary for travel mode to and from school was κ = 0.63 (P < 0.001) and κ = 0.77 (P < 0.001), respectively. The total agreement between the HBSC questionnaire and the diary for was 78%. However, the agreement was higher for walking (88%) and cycling (91%) than for motorized transport (67%). For travel time, the Spearman correlation coefficient was ρ = 0.60 (P < 0.001) between the HBSC questionnaire and the diary. The total agreement on travel time was 67%; however, active commuters (86%) seemed to more accurately estimated travel time than motorized commuters (55%).ConclusionAlthough the overall agreement between the HBSC questionnaire and the diary for mode of transport was 78%, the HBSC questionnaire may underestimate the prevalence of motorized transport compared to walking and cycling.Trial RegistrationClinicalTrials.gov, identifier: NCT03817047.

Role of Sociodemographic Variables and the Mother's Active Behavior on Active Commuting to School in Children and Adolescents.

The main objective of the current study was to analyze how parents' sociodemographic characteristics, mode of commuting and physical activity (PA) act as indicators of active commuting to school (ACS) in their children and adolescents. A total of 684 paired parents (52.8% mothers) and their respective offspring (33.7% girls) were included. The participants self-reported their sociodemographic characteristics, mode of commuting, and PA. Logistic regression analyses were performed using a stepwise approach, including, as indicators, parental characteristics, mode of commuting and PA. The main outcome was child and adolescent ACS. The odds ratio (OR) and R2 of Nagelkerke were obtained for each step. Parental sociodemographic characteristics were greater indicators of child ACS than the parental mode of commuting and PA. In children, the greatest predictive variables of ACS explained 38% of the variance and were as follows: car availability (OR = 0.24), father's educational level (OR = 0.47), mother's educational level (OR = 1.95), mother's active commuting to work (OR = 4.52) and mother's salary/month (OR = 0.67). In adolescents, the greatest predictive variables of ACS explained 40% of the variance and were as follows: socioeconomic level (OR = 0.43) and father's active commuting (OR = 10.6). In conclusion, sociodemographic factors are better indicators of ACS than parents' physical activity and active commuting to work.

The identification of significant features towards travel mode choice and its prediction via optimised random forest classifier: An evaluation for active commuting behavior

IntroductionPhysical activity is the foundation to staying healthy, but sedentary activities have become not uncommon that ought to be mitigated immediately. The study aims to highlight the role of a transport system that encourages physical activity among users by applying an active door-to-door transport system. Users’ mode choice is studied to understand their preferences for active commuting. The use of machine learning has since been ubiquitous in a myriad of fields, including transportation studies and hence is also investigated towards its efficacy in predicting travel mode choice. MethodologyThe application of the Random Forest (RF) model to identify travel mode choice is explored using the Revealed/Stated Preferences (RP/SP) Survey data in Kuantan City during weekdays. A total of 386 respondents were involved in this survey. The efficacy of the tuned RF models towards predicting the travel mode choice is evaluated via the Classification Accuracy (CA) performance indicator. In addition, a Feature Importance study is also carried out in order to identify significant factors that contribute towards travel mode choice. ResultsThe results from the present investigation demonstrated that the default RF model has acceptable predictability for both training and test dataset of users’ mode choice, with a CA of 70.2% and 69.3%, respectively. Upon identifying the significant features and further refining the hyperparameters of the RF model heuristically, it was shown that with 145 trees, the CA improved to up to 71.6% and 70.1% for both the training and test dataset, respectively. Through the feature selection technique, the most significant features that affect users mode choice are total travel time (TT), waiting time at a public transport stop (WT), region, walking distance from the last stop to destination (WD2), and walking distance from home to the nearest bus stop (WD1). ConclusionsThe study has illustrated the efficacy of the optimised RF in predicting travel mode choice as well as identified the significant factors for the selection. The findings of the present study provide significant insight for policymakers to improve the performance of the public transportation system so that the users will benefit in terms of health and well-being from active commuting.

Active Commuting and Healthy Behavior among Adolescents in Neighborhoods with Varying Socioeconomic Status: The NESLA Study

(1) Background: The World Health Organization recommends active commuting as a source of physical activity. Active commuting is determined by various factors, including the socioeconomic status (SES) of families and neighborhoods, distance to schools, perceived neighborhood safety, lifestyles and availability of walkways and biking paths. This study aimed to assess factors associated with modes of transportation to and from school among adolescents aged 16–19 living in a middle-sized city in Sweden. (2) Method: Three hundred and fourteen students, of whom 55% were females, from schools in the city of Västerås participated in the study. Printed as well as web-based self-administered questionnaires were used to collect the data. (3) Results: Adolescents living in high SES neighborhoods were 80% more likely to bike or walk to school (OR = 1.80; CI: 1.01, 3.20) than adolescents living in low SES neighborhoods. Furthermore, active commuting was associated with higher consumption of fruits and vegetables (OR = 1.77; CI: 1.05, 2.97) and less consumption of junk foods (OR = 0.43; CI: 0.26, 0.71), as compared to passive commuting. (4) Conclusions: Active commuting is a cost-effective and sustainable source of regular physical activity and should be encouraged at a societal level.

Associations of active and inactive travel with chronic diseases in Taipei City

ObjectivesActive travel promotes transport-related physical activity and inactive travel increases sedentary times. Active travel might be a modifiable and efficient approach for preventing chronic diseases in urban populations. The purpose of this study was to explore associations of active and inactive travel with urban residents’ overweight, obesity, and chronic diseases. MethodsA cross-sectional study was conducted in Taipei City through an anonymous street-intercept survey. A self-reported transport physical activity questionnaire was used to collect data on the amount of travel time using active travel modes (by walking, cycling, bus, the subway, or train) and inactive travel modes (by motorcycle or car) in the past week. Descriptive analyses, independent t-tests, a one-way ANOVA, and a logistic regression were performed for data analysis. ResultsIn total, 1365 urban residents responded; 391 (28.64%) participants had at least one diagnosis of a chronic disease. Participants who were female, single, aged 20–34 years, and with a college or graduate degree had a significantly higher weekly average amount of time using active travel modes than did their counterparts. The amount of residents’ travel time using the subway and train (odds ratio (OR): 0.95 [95% confidence interval: 0.91, 0.99]) revealed a significant negative association, while the amounts of travel time using a car as a driver (OR: 1.08 [1.04, 1.12]) and using a car as a passenger (OR: 1.10 [1.02, 1.18]) revealed significant positive associations with the odds of all chronic diseases. ConclusionsUrban residents who engage in active travel have potential benefits of physical activity and health promotion. Transforming urban residents from inactive into active commuters is recommended to prevent chronic diseases in urban populations.

Correlates of Active Commuting to School among Portuguese Adolescents: An Ecological Model Approach.

Active commuting to and from school can be an important contribution to improving health in adolescents. This study aimed to analyze the influence of multilevel variables of the ecological model in the active commuting of a representative sample of Portuguese adolescents. The 2018 Health Behaviour in School-Aged Children questionnaire was applied to 5695 adolescents with an average age of 15.5 years old (SD ± 1.8), 53.9% of whom were girls. The associations were studied by applying chi-square tests and multivariate logistic regression models. In this study, 36.5% of the participants reported walking or cycling to school. Active commuting to school was directly associated with age (OR = 1.2; p < 0.05), strong family support (OR = 1.2; p < 0.05), a moderate to low financial level of the family (OR = 1.3; p < 0.05) and living near the school (OR = 2.4; p < 0.05). The results revealed that an adolescent’s choice to travel to and from school using an active mode of transportation increased with strong family support. As a result, promotion campaigns should consider the adolescent’s family context.

Accelerometer derived physical activity patterns in 27.890 middle‐aged adults: The SCAPIS cohort study

The present study aims to describe accelerometer‐assessed physical activity (PA) patterns and fulfillment of PA recommendations in a large sample of middle‐aged men and women, and to study differences between subgroups of socio‐demographic, socio‐economic, and lifestyle‐related variables. A total of 27 890 (92.5% of total participants, 52% women, aged 50–64 years) middle‐aged men and women with at least four days of valid hip‐worn accelerometer data (Actigraph GT3X+, wGT3X+ and wGT3X‐BT) from the Swedish CArdioPulmonary bioImage Study, SCAPIS, were included. In total, 54.5% of daily wear time was spent sedentary, 39.1% in low, 5.4% in moderate, and only 0.1% in vigorous PA. Male sex, higher education, low financial strain, born in Sweden, and sedentary/light working situation were related to higher sedentary time, but also higher levels of vigorous PA. High BMI and having multiple chronic diseases associated strongly with higher sedentary time and less time in all three PA intensities. All‐year physically active commuters had an overall more active PA pattern. The proportion fulfilling current PA recommendations varied substantially (1.4% to 92.2%) depending on data handling procedures and definition used. Twenty‐eight percent was defined as having an “at‐risk” behavior, which included both high sedentary time and low vigorous PA. In this large population‐based sample, a majority of time was spent sedentary and only a fraction in vigorous PA, with clinically important variations between subgroups. This study provides important reference material and emphasizes the importance of a comprehensive assessment of all aspects of the individual PA pattern in future research and clinical practice.

Children’s exposure to BC and PM pollution, and respiratory tract deposits during commuting trips to school

Although children have been identified as a vulnerable group highly susceptible to traffic-related air pollution, their exposure during school commutes to traffic-related pollutants and the relevant health impact is rarely studied. In this study, we measured black carbon (BC) and particulate matter (PM: PM1, PM2.5, and PM10) concentrations that children are exposed to during their multi-modal (walking, private cars, and e-bikes) commuting trips to schools in Xi'an, China. A multi-parameter inhalation rate assessment model was developed in combination with the Multi-Path Particle Dosimetry (MPPD) model to quantify the deposition dose in different parts of children’s respiratory system (head, tracheobronchial (TB), pulmonary (PUL)). Results show that walking to school exposed children to the lowest PM1, PM2.5, and BC concentrations, whereas riding an e-bike led to significantly elevated exposure to PM1 and BC than the other two modes. This is due to children’s closer proximity to vehicle tail pipe emissions when they bike to school on road or roadside. The PM and BC concentrations showed remarkable increases in comparison to background concentrations during children’s school commutes. Urban background (UB) concentration, traffic volume (TV), time of day, and meteorological parameters could influence a child’s personal exposure, and the impact of each factor vary across different transportation modes. Particle size of the pollutant affects its deposition site in the respiratory system. Deposition fractions (DFs) and deposition doses in the head region (DF > 50%) were the highest for PM and BC, for which fine particles (BC, PM1, and PM2.5) were then most easily deposited in the PUL region while coarse particles rarely reach PUL. Children inhaled higher doses of polluted air during active commuting (walking) than passive commuting (private cars, e-bikes), due to longer times of exposure coupled with more active breathing.

Active commuting to school: A longitudinal analysis examining persistence of behavior over time in four New Jersey cities

Evidence suggests that healthy behaviors initiated during childhood may continue over time. The objective of this study was to determine whether active commuting to/from school (ACS) at baseline predicted continued ACS at follow-up two to five years later.Two cohorts of households with 3–15 year-olds in four low-income New Jersey cities were randomly sampled and followed for two to five year periods between 2009 and 2017. Children who walked, bicycled, or skateboarded to/from school at least one day/week were classified as active commuters. Children with complete data at both time points were included in this analysis (n = 383). Multivariate logistic regression was used to examine the association between ACS at T1 and T2. Models adjusted for child age, sex, and race/ethnicity; parent’s education and nativity status (native-born vs foreign-born); household poverty level; car availability; neighborhood level characteristics; and distance from home to school.Children who engaged in ACS at T1 had over seven times the odds of ACS at T2 compared to children who did not actively commute at T1 (p < 0.001), after adjusting for distance to school and other relevant covariates. Distance, regardless of active commuting status at T1 was inversely associated with active commuting at T2.Policies and interventions encouraging ACS, and those that decrease the distance between a child’s home and school, may result in increased, habitual active commuting and physical activity behavior throughout childhood and possibly into adulthood.

Perceived physical activity during stay-at-home COVID-19 pandemic lockdown March-April 2020 in Polish adults.

BackgroundLockdowns amid the COVID-19 pandemic drastically reduced the possibility of undertaking physical activity (PA) in gyms, swimming pools, or work-related PA, e.g., active commuting. However, the stay-at-home order could have reduced PA the most, i.e., the ban of unnecessary outdoor activities. It affected free walking, running, skiing, active tourism, etc. It is, therefore, crucial to estimate how the stay-at-home order affected PA. We estimated how the stay-at-home order affected perceived PA and sedentary behavior compared to the pre-pandemic time in Poland.MethodsWe used a self-reported International Physical Activity Questionnaire—Long Form (IPAQ-LF) to estimate the time (minutes per day) of vigorous and moderate PA and walking and sitting time.ResultsWe gathered data from 320 Polish participants. Bayesian approaches, including t-test and Bayesian correlations, were used to find differences and correlations between PA before and during the stay-at-home lockdown. Our data supported the hypotheses that vigorous PA, as well as walking, declined during the lockdown. Surprisingly, our data did not support the hypothesis that moderate physical activity was reduced. We found that moderate PA during lockdown increased compared to the pre-lockdown PA. As hypothesized, our data strongly evinced that sitting time inclined during the lockdown. PA decline was not correlated with the available living space. People who had access to gardens did not demonstrate a higher PA level than those without.DiscussionWalking and sitting time have drastically changed during the stay-at-home lockdown, decreasing and increasing, respectively. Given results from studies focusing on lockdowns without the stay-at-home restriction, it may be assumed that letting people go outside is crucial in keeping them more active and less sedentary. Authorities should take into account the effect the stay-at-home order may have on PA and sedentary behavior and as a result, on health. Stay-at-home orders should be the last considered restriction, given its detrimental consequences.

Active Commuting and the Health of Workers

Active Commuting and the Health of Workers

An integrated model of structural equations with cognitive and environmental factors for the study of active commuting

IntroductionThe active commuting can be defined as the action of displacement to the educational or work centre by way of any non-motorised means of transport, usually by walking or cycling. The aim of this study is to identify and evaluate cognitive and environmental factors for the active commuting. MethodsIn order to propose a set of beliefs and attitudes that explain the main possible motivations for an individual to carry out the active commuting, a model based on the Theory of Planned Behaviour, health and environment is developed. To compute the results, a structural equations model is proposed instead of another standard regression technique, due to the use of multiple indicators for each latent construct. The proposed model permits to evaluate each of the aspects and to quantify their contribution to the global behavioural intention. ResultsThe computation of the structural equations model concludes that, for the intention to practise active commuting, the most influential variable is attitude, followed by health and environmental awareness. It is interesting to see that perceived behavioural control exerts a negative influence on the intention, while the subjective norm has no significant effect. ConclusionsFrom the results of this study can be induced that the perceived behavioural control, health, and environmental awareness exert a significant influence on attitude and intention to practice active commuting. Furthermore, the results also show that attitude influences as a precursor to the intention of practicing and permit to rank the relative weight of each aspect: attitude, health and environmental awareness. Hence, political measures that publicise the benefits of active commuting in these particular aspects should have significant results in the promotion of this activity.

Barriers and Determinants of Active Commuting to School in Slovenia

There is a growing body of literature reporting the health benefits of active commuting to school. This study investigated barriers and determinants of active commuting in children in Slovenia living within walking or cycling distance to school, i.e., 3 km. The sample consisted of 339 children (163 girls) aged 11–14 years who reported their mode of commuting, as well as their parents who described the socioeconomic environment of the family. Every third child in this study traveled to school exclusively by car/public transport, while every fifth participant used a passive means of transport when returning home from school. Potential household poverty, education of the mother and parental encouragement for physical activity were not associated with the commuting mode. In addition, conformist family barriers dominated among reasons for not choosing active commuting. A distance to school that was perceived to be too long was the most frequently cited barrier (72% of participants who passively commuted in both directions), followed by concern about being late for school (38% of participants who passively commute in one direction). Parents from all social strata who drive their children to school in either one or both directions while living in a walking or cycling range are a promising target population for active commuting interventions.

Green Space and Physical Activity in China: A Systematic Review

Green space may play an essential role in residents’ physical activity (PA), but evidence remains scattered in China. This study systematically reviewed scientific evidence regarding the influence of green space on PA among residents in China. Keyword and reference searches were conducted in PubMed, Web of Science, Scopus, EBSCO, and CNKI from the inception of an electronic bibliographic database to May 2021. Eligibility criteria included the following: study designs—observational (e.g., longitudinal or cross-sectional studies) and experimental studies; study subjects—people of all ages; exposures—green space (e.g., parks, vegetation areas, open green fields); outcomes—leisure-time and work/school-related PA (e.g., active commuting); and country—China. All but two studies identified at least one measure of green space to be associated with PA. Street greenness was associated with increased odds of active commuting (e.g., cycling) and walking, and a reduced risk of physical inactivity. Access to green space was associated with increased PA levels and green space usage. Distance to green space was inversely associated with the odds of PA. By contrast, evidence linking overall greenness exposure to PA remains limited. Future studies adopting experimental study design are warranted to establish more robust scientific evidence of causality between green space and PA in China. Future studies are also warranted to examine the underlining mechanisms and the differential impacts of green space on population subgroups in China.

Associations Between Active Commuting and Cardiovascular Disease in the United States.

Active commuting is inversely related with cardiovascular disease (CVD) risk factors yet associations with CVD prevalence in the US population are unknown. Aggregate data from national surveys conducted in 2017 provided state-level percentages of adults who have/had coronary heart disease, myocardial infarction, and stroke, and who actively commuted to work. Associations between active commuting and CVD prevalence rates were assessed using Pearson correlations and generalized additive models controlling for covariates. Significant correlations were observed between active commuting and all CVD rates (r range = -.31 to -.47; P < .05). The generalized additive model analyses for active commuting (walking, cycling, or public transport) in all adults found no relationships with CVD rates; however, a significant curvilinear association was observed for stroke within men. The generalized additive model curves when examining commuting via walking or cycling in all adults demonstrated nuanced, generally negative linear or curvilinear associations between coronary heart disease, myocardial infarction, and stroke. Significant negative correlations were observed between active commuting and prevalence rates of coronary heart disease, myocardial infarction, and stroke. Controlling for covariates influenced these associations and highlights the need for future research to explore the potential of active commuting modes to reduce CVD in the United States.

Segmenting children’s active school travel behaviour: insights on caregivers’ perceived risks and social norms

PurposeActive school travel (AST) programmes aim to change commuting behaviour to improve children's physical and mental health. However, very limited health education programmes for children use segmentation to create tailored solutions that understand the specific characteristics of each group of children and their caregivers in order to yield better results. The aim of this study is to use a statistical segmentation analysis (two-step cluster analysis) to gain insights on the examination of specific groups to design future health education interventions and campaigns that can improve children's health.Design/methodology/approachGuided by the Ecological and Cognitive Active Commuting (ECAC) framework, a market segmentation analysis was performed. An online survey was designed to collect data from caregivers of children between 5 and 12 years attending school and responsible for taking the child to and/or from school in Victoria and Queensland, Australia. Using 3,082 responses collected from Australian caregivers of primary school children, a two-step cluster analysis was performed.FindingsAnalysis revealed the most important variables for group formation were previous child walking behaviour, distance from school and caregiver income. Perceived risk of the physical environment was the most important psychographic segmentation variable for group formation, followed by social norms. Four distinct groups with different characteristics were identified from the analysis.Originality/valueThis is the first study that applies the ECAC framework to perform market segmentation in the AST context. Results revealed four market segments that demand different tailored solutions. Findings shed light on how to better design AST interventions and campaigns to promote children's health using segmentation techniques.

Time Trends and Sociodemographic Inequalities in Physical Activity and Sedentary Behaviors Among Brazilian Adults: National Surveys from 2003 to 2019.

The authors analyzed time trends and sociodemographic inequalities in different physical activity and sedentary behavior domains between 2003 and 2019. A secondary analysis of data from 5 cross-sectional Brazilian epidemiological surveys (World Health Survey-2003, National Household Sample Survey-2008/2015, and Brazilian Health Survey-2013/2019) conducted among a nationally representative sample of Brazilian adults. The authors used data on different domains of physical activity (leisure, commute, total transport, and total physical activity) and sedentary behavior (TV viewing and other types of screens) that were available in the different surveys. Gender, age group, country region, ethnicity, type of area and city, and quintiles of income and educational achievement were used as sociodemographic correlates. The prevalence of leisure-time physical activity increased over time (2008: 7.0% vs 2019: 26.5%). There was also an increased trend of social inequality in leisure-time physical activity. A trend of reduction was observed for active commuting (2008: 35.0% vs 2019: 21.8%), while total transport physical activity was stable (2013: 49.5% vs 2019: 49.6%). Directions of findings were opposite for sedentary behavior, with reduced trend for >3 hours per day of TV viewing (2008: 34.8% vs 2019: 21.8%) and increased trend for >3 hours per day of other types of screen time (2008: 6.4% vs 2019: 22.2%). A positive trend exists in leisure-time physical activity, but there was also an increase in social inequalities for physical activity in Brazil.

Patterns of Active Commuting to School in Spanish Preschool Children and Its Associations with Socio-Economic Factors: The PREFIT Project.

The aims of this study were to describe patterns of active commuting to school (ACS) of preschool children, and to analyse the relationship between ACS and family socio-economic factors. A total of 2636 families of preschoolers (3-to-5 years old) were asked to complete a questionnaire at home about the mode of commuting to school of their children and marital status, educational level, and profession of both father and mother. Chi-square analyses were applied to compare ACS between school grades and gender of the children. To analyse the association of ACS with socio-economic factors, logistic regression analyses were performed. Almost 50% of participants reported ACS of their offspring, with a higher rate in 3rd preprimary grade (5 years old) than in 1st and 2nd preprimary grades (3- and 4-years old. All, p < 0.05). Those preschool children who had parents with lower educational level and no managerial work had higher odds to ACS than those who had parents with higher educational level and managerial work (all, p ≤ 0.001). Around half of the Spanish preschool children included in this study commuted actively to school and families with lower educational levels or worse employment situation were related to active commuting to school.