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Journal Article

Citation

de Haas M, Kroesen M, Chorus C, Hoogendoorn-Lanser S, Hoogendoorn S. J. Transp. Health 2021; 22: e101113.

Copyright

(Copyright © 2021, Elsevier Publishing)

DOI

10.1016/j.jth.2021.101113

PMID

unavailable

Abstract

Introduction
It has been estimated that physical inactivity accounts for roughly 10% of premature mortality globally in any given year. Active travel (walking and cycling) has been promoted as an effective means to stimulate physical activity. However, many of the available studies on the relation between active travel and health are based on cross-sectional data and are therefore unable to determine the direction of causation. This study aims to unravel the bidirectional relationships between active travel measured by the active modes bicycle, e-bike and walking, on the one hand, and two health outcomes, namely body-mass index (BMI) and self-rated health (SRH), on the other.
Methods
To provide an initial assessment of the relationship between active travel and the two health outcomes, multivariate regression models are estimated. To study the direction of causation, Random-Intercept Cross-Lagged Panel Models (RI-CLPM) are estimated using three waves of the Netherlands Mobility Panel (MPN). Active travel is measured as travelled distances and trips with the bicycle, e-bike and walking. BMI is calculated based on weight and height, SRH is measured with a single question.
Results
The regression models show that a higher BMI and lower SRH are associated with less walking and cycling, while being obese is associated with more e-bike use. The results of the RI-CLPM indicate that cycling distance has a positive effect on SRH. Furthermore, walking distance has a negative effect on BMI and BMI has a negative effect on bicycle use among people without obesity. No relationships between BMI and active travel are found for people with obesity.
Conclusion
The results highlight the importance of longitudinal analyses when estimating the relationship between active travel and health. In addition, the results suggest that, relatively speaking, the increasing overweight and obesity rates may result in a decrease of bicycle use.


Language: en

Keywords

Active travel; Body-mass index (BMI); Panel data; Random intercept cross-lagged panel model (RI-CLPM); Self-rated health (SRH)

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