Factors affecting the mode choice behavior before and during COVID-19 pandemic in Pakistan

The transport sector has been hit hard by the COVID-19 pandemic disrupting travel behaviors and mobility patterns around the globe. The pandemic has also affected mode choice behavior. This research study modeled the mode choice behavior before and during the COVID-19 pandemic in Pakistan. Data was collected through an online questionnaire survey consisting of questions about socio-economic characteristics, factors affecting mode choice, and mode chosen for shorter as well as longer distances for both before and during COVID-19 pandemic situations. The results indicated that public transport use declined, whereas walking and bicycling slightly increased during the pandemic. The respondents placed more priority on safety and security, comfort, cleanliness, infection concerns, personal social status, availability of hand-sanitizers, waiting, and paying more for less congested vehicles during the pandemic. Factor analysis was performed to explore the underlying factors affecting mode choice before and during the pandemic. Discrete choice models were developed to model the mode choice behavior. Monthly household income and pandemic-related underlying factor were significant predictors of mode choice for shorter distances (i.e., < 5 km) during the pandemic. Whereas, gender, car ownership and monthly household income were significant predictors of mode choice for longer distances (i.e., > 5 km) during the pandemic. Understanding the modal shift during a pandemic will surely help urban and transport planners to prepare better for effective transport management in the future. Policy implications are also presented to help policymakers in developing policies for post-pandemic mobility needs, particularly in developing countries.

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.