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Time-Use and Spatio-Temporal Variables Influence on Physical Activity Intensity, Physical and Social Health of Travelers

Author

Listed:
  • Mujahid Ali

    (Department of Civil and Environmental Engineering, Universiti Teknologi PETRONAS, Perak Seri Iskandar 32610, Perak, Malaysia)

  • Dimas Bayu Endrayana Dharmowijoyo

    (Department of Civil and Environmental Engineering, Universiti Teknologi PETRONAS, Perak Seri Iskandar 32610, Perak, Malaysia)

  • Afonso R. G. de Azevedo

    (LECIV—Civil Engineering Laboratory, UENF—State University of the Northern Rio de Janeiro, Campos dos Goytacazes 28013-602, Brazil)

  • Roman Fediuk

    (Polytechnic Institute, Far Eastern Federal University, 690922 Vladivostok, Russia)

  • Habil Ahmad

    (School of Civil, Mining and Environmental Engineering, University of Wollongong, Wollongong 2522, Australia)

  • Bashir Salah

    (Department of Industrial Engineering, College of Engineering, Kind Saud University, P.O. Box 800, Riyadh 11421, Saudi Arabia)

Abstract

Using a multi-dimensional three-week household time-use and activity diary, this study aims to investigate the interaction between time-use and activity travel participation, built environment, leisure-time physical activity, travel parameters, and physical intensity on physical and social health. The relationship between time-use and activity travel participation is complex. Therefore, physical activity (PA) intensity is assumed to intermediate the relationship between endogenuous and exogenous variables. This study use a comprehensive set of data that was collected at a household level for twenty-one (21) consecutive days. A total of 732 individuals and 191 households were recorded, representing 0.029% total population of Bandung Metropolitan Area (BMA). The data analyzed with descriptive and linear regression analysis using Statistical Package for Social Sciences SPSS version 26.0.0 software (IBM: Armonk, NY, USA). An advanced model, such as the hierarchical Structural Equation Model (SEM), is used to validate the relationship between activity patterns and health parameters. The estimated results indicate that a minute increase in public transport mode has an 8.8% positive correlation with physical health and 9.0% with social health. Furthermore, an increase in the one-minute duration of in-home maintenance and out-of-home leisure activities are positively correlated by 2.9% and 3.2%, respectively, with moderate-intensity PA and by 4.5% and 1.8% strenuous-intensity PA. Additionally, high accessibility and availability of basic amenities at a walkable distance and using auxiliary time in social activities are significantly correlated with better physical and social health. Moreover, this study adopted multidisciplinary approaches for better transport policy and a healthier society with a better quality of life.

Suggested Citation

  • Mujahid Ali & Dimas Bayu Endrayana Dharmowijoyo & Afonso R. G. de Azevedo & Roman Fediuk & Habil Ahmad & Bashir Salah, 2021. "Time-Use and Spatio-Temporal Variables Influence on Physical Activity Intensity, Physical and Social Health of Travelers," Sustainability, MDPI, vol. 13(21), pages 1-24, November.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:21:p:12226-:d:672942
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    References listed on IDEAS

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    Cited by:

    1. Panyu Tang & Mahdi Aghaabbasi & Mujahid Ali & Amin Jan & Abdeliazim Mustafa Mohamed & Abdullah Mohamed, 2022. "How Sustainable Is People’s Travel to Reach Public Transit Stations to Go to Work? A Machine Learning Approach to Reveal Complex Relationships," Sustainability, MDPI, vol. 14(7), pages 1-18, March.
    2. Yu Chen & Mahdi Aghaabbasi & Mujahid Ali & Sergey Anciferov & Linar Sabitov & Sergey Chebotarev & Karina Nabiullina & Evgeny Sychev & Roman Fediuk & Rosilawati Zainol, 2021. "Hybrid Bayesian Network Models to Investigate the Impact of Built Environment Experience before Adulthood on Students’ Tolerable Travel Time to Campus: Towards Sustainable Commute Behavior," Sustainability, MDPI, vol. 14(1), pages 1-26, December.
    3. Wenlong Tao & Mahdi Aghaabbasi & Mujahid Ali & Abdulrazak H. Almaliki & Rosilawati Zainol & Abdulrhman A. Almaliki & Enas E. Hussein, 2022. "An Advanced Machine Learning Approach to Predicting Pedestrian Fatality Caused by Road Crashes: A Step toward Sustainable Pedestrian Safety," Sustainability, MDPI, vol. 14(4), pages 1-18, February.

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