Mobility and Health: The Interaction of Activity-Travel Patterns, Overall Well-Being, Transport-Related Social Exclusion on Health Parameters

Dharmowijoyo, Dimas Bayu Endrayana; Joewono, Tri Basuki

doi:10.1007/978-981-15-0102-9_4

Cited by 16 publications

(13 citation statements)

References 72 publications

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“…Settlement area, trade centre, and industrial area are 33.5%, 34.9%, and 47.1% positively correlated with physical health, respectively, whereas they are 26.4%, 31.7%, and 25.8% positively associated with social health. This result also exhibits that those living in the poverty areas, denser industrial and agriculture areas, are socially excluded, increasing social and physical health problems [7].…”

Section: Discussionmentioning

confidence: 87%

“…Regarding gender, males have better physical and social health than females because males are engaged with more out-of-home mandatory, leisure, maintenance, and social activities. As mentioned in recent studies, males participate more in out-of-home activities than females because men have a different level of activity, which improves their physical and social health [7,32,52]. In addition, students show the highest level of physical and social health because of the daily participation of physical and social activities within and with other family members at different locations on a given day throughout the week.…”

Section: Variablesmentioning

confidence: 96%

“…Regarding gender, males have better physical and social health than females because males are engaged with more out-of-home mandatory, leisure, maintenance, and social activities. As mentioned in recent studies, males participate more in out-of-home activities than females because men have a different level of activity, which improves their physical and social health [7,32,52]. In addition, students show the highest level of physical and social health because of the daily participation of physical and social activities within and (M-IPA) i, h, t = (α i, h + u i + u h ) + β 1 S i, h + β 2 B i, h + β 3 Act i, h, t + β 4 Trip i, h, t + β 5 Travel i, h, t, + β 6 Social i, h, t + ε i, h, t (3) (S-IPA) i, h, t = (α i, h + u i + u h ) + β 7 S i, h + β 8 B i, h + β 9 Act i, h, t + β 10 Trip i, h, t + β 11 Travel i, h, t, + β 12 Social i, h, t + ε i, h, t…”

Section: Variablesmentioning

confidence: 99%

“…An individual has needs, desires, and available resources such as a car and money and wants to travel and participate in an activity at different locations. However, due to physical (e.g., broken legs, blindness, sickness and disorder), social (e.g., family/friends pressure), or mental health (e.g., stress), they may be unable to travel and participate in an activity [7,18,27]. The conceptual model/framework for the interaction of activity-travel participation and health is shown in Figure 1.…”

Section: Introductionmentioning

confidence: 99%

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

Ali

Dharmowijoyo

Azevedo³

et al. 2021

Sustainability

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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.

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Section: Discussionmentioning

confidence: 87%

Section: Variablesmentioning

confidence: 96%

“…Regarding gender, males have better physical and social health than females because males are engaged with more out-of-home mandatory, leisure, maintenance, and social activities. As mentioned in recent studies, males participate more in out-of-home activities than females because men have a different level of activity, which improves their physical and social health [7,32,52]. In addition, students show the highest level of physical and social health because of the daily participation of physical and social activities within and (M-IPA) i, h, t = (α i, h + u i + u h ) + β 1 S i, h + β 2 B i, h + β 3 Act i, h, t + β 4 Trip i, h, t + β 5 Travel i, h, t, + β 6 Social i, h, t + ε i, h, t (3) (S-IPA) i, h, t = (α i, h + u i + u h ) + β 7 S i, h + β 8 B i, h + β 9 Act i, h, t + β 10 Trip i, h, t + β 11 Travel i, h, t, + β 12 Social i, h, t + ε i, h, t…”

Section: Variablesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

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

Ali

Dharmowijoyo

Azevedo³

et al. 2021

Sustainability

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show abstract

“…Myung [56] defined this model of non-full information SEM as 2SLS, where it is as being contrary to FIML-SEM and 3SLS. Detailed discussion of hierarchical SEM can be found elsewhere [24,[55][56][57][58][59][60][61]. The hypotheses of this study are as follows.…”

Section: Proposed Model Constructmentioning

confidence: 99%

Does Job Satisfaction Influence the Productivity of Ride-Sourcing Drivers? A Hierarchical Structural Equation Modelling Approach for the Case of Bandung City Ride-Sourcing Drivers

2021

Self Cite

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With various benefits being offered by ride-sourcing companies, Indonesian cities have experienced a substantial increase in the number of ride-sourcing drivers in the past five years. However, with tense working conditions, there is a question as to how drivers perceive their work satisfaction and how this satisfaction influences their productivity. This study aims to investigate the factors that influence ride-sourcing drivers’ job satisfaction and productivity. For this purpose, a questionnaire was distributed to ride-sourcing drivers in 2019 and analysed using hierarchical structural equation modelling (SEM). Wage competitiveness and financial safety are found to be appreciated the most by ride-sourcing drivers, while undertaking multiple jobs tends to be associated with low satisfaction. Satisfaction is also found to positively influence trip productivity. Drivers who perceive themselves as being exposed to health and safety risks tend to have lower satisfaction.

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Relationship Among Socio-demographic Characteristics, Activity-Travel Participation, Travel Parameter, Physical Activity Intensity, and Health Parameters

Ali,

Macioszek

2024

Lecture Notes in Networks and Systems

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Mobility and Health: The Interaction of Activity-Travel Patterns, Overall Well-Being, Transport-Related Social Exclusion on Health Parameters

Cited by 16 publications

References 72 publications

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

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

Does Job Satisfaction Influence the Productivity of Ride-Sourcing Drivers? A Hierarchical Structural Equation Modelling Approach for the Case of Bandung City Ride-Sourcing Drivers

Relationship Among Socio-demographic Characteristics, Activity-Travel Participation, Travel Parameter, Physical Activity Intensity, and Health Parameters

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