Associations of socioeconomic status with transport-related physical activity: combining a household travel survey and accelerometer data using random forests

- This study analyses transport-related moderate-to-vigorous physical activity (T-MVPA).
- To analyze socioeconomic disparities in T-MVPA, large datasets are needed.
- Accelerometer data for large-scale travel studies are very expensive.
- Precise accelerometer measures are predicted for a large-scale transport survey.
- The education level had a positive association with transport-related MVPA.
- The household income had a negative association with transport-related MVPA.

BackgroundSocioeconomic disparities in active transport have been documented in household travel surveys. However, active transport in these studies was operationalized with self-reported measures, which poorly approximate physical activity. Unfortunately, objective accelerometer data are very expensive to obtain in large-scale travel studies.PurposeTo benefit from a large sample and objective physical activity data, this study linked a cross-sectional household travel survey with accelerometer data from a small sample to investigate the association between socioeconomic disadvantage and the daily level of transport-related moderate-to-vigorous physical activity (T-MVPA) in an adult population (35-83 years).MethodsAccelerometer data for participants' trips over 7 days from the RECORD GPS Study (7138 trips, 229 participants) were combined with information on participants' trips over 1 day from the Global Transport Survey (Enquête Globale Transport, EGT) (82084 trips, 21332 participants). Trip-level T-MVPA data from the RECORD sample were used to train a random forests prediction model, enabling the prediction of T-MVPA for each participant׳s trip from EGT. The associations between socioeconomic indicators and daily T-MVPA were analyzed with negative binomial regression models.ResultsAn average time of 18.9 min (95% confidence interval: 18.6-19.2) of T-MVPA was found for these 35-83 year old adults. The education level had a positive association with T-MVPA. Household income had a negative association with T-MVPA, especially for those people without a motorized vehicle.ConclusionsThis study developed a methodology exporting precise sensor-based knowledge to a large survey sample to shed light on population-level socioeconomic disparities in transport-related physical activity.