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Recently much attention is paid to the lack of physical activities that may cause the health problems in many counties. Travel activities provide a certain amount of physical activities, and the active transportation, such as walking and cycling, becomes more important as an essential element of transportation. The active transportation is expected to contribute to improving human health by reducing cardiovascular disease, obesity, and premature death. However, detailed relationship between the transportation choices and human health has not been well understood. Therefore, there is a need for investigating traveler behaviors and how their choices affect physical activities and public health. The first part of the dissertation explores the role of societal cultures and their impact on choosing active transportation modes. Through a multinational survey conducted in the selected cities of the United States, South Korea, Saudi Arabia, and Iraq, the sociocultural factors that influence transportation mode choices especially active transportation are identified. The second part of the study involves using a mobile application platform named Physical Activity through Smart Travel Activity (PASTA) to monitor the travel and physical activities of transportation users. The PASTA platform includes mobile data communication, big data analysis, activity classification, transportation mode detection, and physical activity quantification on different interfaces, such as smartphones, cloud databases, and computers. The platform provides data to compare physical activities attributable to transportation across different geographical areas. The PASTA platform is tested in Texas and Michigan and proves to be useful in apportioning the total physical activity into travel-related physical activities and non-travel related physical activities. A transportation mode detection (TMD) system is also developed to process the data collected from PASTA based on machine learning techniques. The third part of the dissertation employs the integrated transportation and health impact model (ITHIM) and enhances the concept of ITHIM by adding the quantitative data obtained from PASTA. Mechanisms for collecting data on physical activities (PA) related to or not related to transportation in previous studies relied on questionnaires and interviews of specific samples in the community. Instead, the PASTA platform provides an automated mechanism for gathering the daily activities of people, especially with regard to physical activities and travel behaviors. The study also introduces the physical activity minute (PAM), an indicator of changes in activity levels, which is an alternative to the metabolic equivalence of the task (METs), which is often a constant value for any type of physical activity. By coupling the data from PASTA, this research substantially reduces the limitations in the previous ITHIM and upgrades the model to conform to the current technological advances. The last part of the dissertation discusses the relationship between the levels of physical activity of individuals, their socio-economic features and body shapes using descriptive analysis and path analysis. Three sets of data are used in this study, such as the questionnaire, body shape tests, and physical activity levels associated with transportation. Socio-economic and body shape factors such as race, age, gender, state of residence, percent of body fat, are found to have significant direct and indirect effects on physical activity. The findings of this study help in incorporating human health into transportation planning by addressing health outcomes impacted by physical activities associated with transportation choices considering peoples socioeconomic and body composition profiles. This dissertation makes an effort to analyze and quantify participants actual physical activities by using recent wearable devices with sensing and GPS tracking technology. The dissertation addresses health outcomes impacted by physical activities associated with transportation options. The study provides information that can be used to enhance community awareness of the health benefits that resulted from different transportation mode choices. Overall, the findings of this study can be used to incorporate human health in transportation planning.