Estimation and prediction of average vehicle occupancies using traffic accident records

As congestion management strategies begin to put more emphasis on person trips than vehicle trips, the need for vehicle occupancy data has become more critical. The traditional methods of collecting these data include the roadside windshield method and the carousel method. These methods are labor-intensive and expensive. An alternative to these traditional methods is to make use of the vehicle occupancy information in traffic accident records. This method is cost effective and may provide better spatial and temporal coverage than the traditional methods. However, this method is subject to potential biases resulting from under- and over-involvement of certain population sectors and certain types of accidents in traffic accident records. In this dissertation, three such potential biases, i.e., accident severity, driver’s age, and driver’s gender, were investigated and the corresponding bias factors were developed as needed. The results show that although multi-occupant vehicles are involved in higher percentages of severe accidents than are single-occupant vehicles, multi-occupant vehicles in the whole accident vehicle population were not overrepresented in the accident database. On the other hand, a significant difference was found between the distributions of the ages and genders of drivers involved in accidents and those of the general driving population. An information system that incorporates adjustments for the potential biases was developed to estimate the average vehicle occupancies (AVOs) for different types of roadways on the Florida state roadway system. A reasonableness check of the results from the system shows AVO estimates that are highly consistent with expectations. In addition, comparisons of AVOs from accident data with the field estimates show that the two data sources produce relatively consistent results. While accident records can be used to obtain the historical AVO trends and field data can be used to estimate the current AVOs, no known methods have been developed to project future AVOs. Four regression models for the purpose of predicting weekday AVOs on different levels of geographic areas and roadway types were developed as part of this dissertation. The models show that such socioeconomic factors as income, vehicle ownership, and employment have a significant impact on AVOs.

Shifting Our Gaze to the Strengths of Alternative Education Students

This study addresses the need for educators to understand what matters for alternative education students. Three male alternative education students were interviewed about their educational memories, realities and aspirations. Results revealed family influences prevailed over inhospitable socioeconomic factors in students’ educational choices. Findings supported recommendations for alternative education teacher development.

Estimation and Prediction of Average Vehicle Occupancies using Traffic Accident Records

As congestion management strategies begin to put more emphasis on person trips than vehicle trips, the need for vehicle occupancy data has become more critical. The traditional methods of collecting these data include the roadside windshield method and the carousel method. These methods are labor-intensive and expensive. An alternative to these traditional methods is to make use of the vehicle occupancy information in traffic accident records. This method is cost effective and may provide better spatial and temporal coverage than the traditional methods. However, this method is subject to potential biases resulting from under- and over-involvement of certain population sectors and certain types of accidents in traffic accident records. In this dissertation, three such potential biases, i.e., accident severity, driver¡¯s age, and driver¡¯s gender, were investigated and the corresponding bias factors were developed as needed. The results show that although multi-occupant vehicles are involved in higher percentages of severe accidents than are single-occupant vehicles, multi-occupant vehicles in the whole accident vehicle population were not overrepresented in the accident database. On the other hand, a significant difference was found between the distributions of the ages and genders of drivers involved in accidents and those of the general driving population. An information system that incorporates adjustments for the potential biases was developed to estimate the average vehicle occupancies (AVOs) for different types of roadways on the Florida state roadway system. A reasonableness check of the results from the system shows AVO estimates that are highly consistent with expectations. In addition, comparisons of AVOs from accident data with the field estimates show that the two data sources produce relatively consistent results. While accident records can be used to obtain the historical AVO trends and field data can be used to estimate the current AVOs, no known methods have been developed to project future AVOs. Four regression models for the purpose of predicting weekday AVOs on different levels of geographic areas and roadway types were developed as part of this dissertation. The models show that such socioeconomic factors as income, vehicle ownership, and employment have a significant impact on AVOs.

Menopause, rurlity, and obesity in rural African American women

In the US, one in every eight deaths is due to an obesity-related chronic health condition (ORCHC). More than half of African American women (AAW) 20 years old or older are obese or morbidly obese, as are 63% of menopausal AAW. Many have ORCHC that increase their morbidity and mortality and increase health care costs. In 2013, 42.6 percent of AAs living in South Carolina (SC) were obese. The purpose of this cross-sectional study was to identify the cognitive, behavioral, biological, and demographic factors that influence health outcomes (BMI, and ORCHC) of AAW living in rural SC. A sample of 200 AAW (50 in each of the 4 groups of rurality by menopausal status), 18-64 years, completed the: Menopausal Rating Scale (symptoms); Body Image Assessment for Obesity (self-perception of body); Mental Health Inventory; Block Food Frequency Questionnaire; Eating Behaviors and Chronic Conditions, Traditional Food Habits, and Food Preparation Technique questionnaires — and measures for Body Mass Index. Most rural, and premenopausal AAW were single and not living with a partner. Premenopausal women had significantly higher educational levels. Sixty percent of AAW had between 1 and 5 ORCHC. Most AAW used salt based seasonings, ate deep fried foods 1 to 3 times a week, and ate outside the home 1 to 3 times a month. Few AAW knew the correct daily serving for grains and dairy, and most consumed less than the recommended daily serving of fruits, vegetables and dairy. Morbidly obese AAW used more traditional food preparation techniques than obese and normal-weight AAW. Rural, and menopausal AAW had significantly higher morbid obesity levels, consumed larger portions of meats and vegetables, and reported more body image dissatisfaction than very rural AAW, and premenopausal AAW, respectively. Controlling for socioeconomic factors the relationships between perceptions of body images, psychological distress, and psychological wellbeing remained significant for numbers of ORCHC^

Menopause, Rurality, And Obesity in Rural African American Women

In the US, one in every eight deaths is due to an obesity-related chronic health condition (ORCHC). More than half of African American women (AAW) 20 years old or older are obese or morbidly obese, as are 63% of menopausal AAW. Many have ORCHC that increase their morbidity and mortality and increase health care costs. In 2013, 42.6 percent of AAs living in South Carolina (SC) were obese. The purpose of this cross-sectional study was to identify the cognitive, behavioral, biological, and demographic factors that influence health outcomes (BMI, and ORCHC) of AAW living in rural SC. A sample of 200 AAW (50 in each of the 4 groups of rurality by menopausal status), 18-64 years, completed the: Menopausal Rating Scale (symptoms); Body Image Assessment for Obesity (self-perception of body); Mental Health Inventory; Block Food Frequency Questionnaire; Eating Behaviors and Chronic Conditions, Traditional Food Habits, and Food Preparation Technique questionnaires – and measures for Body Mass Index. Most rural, and premenopausal AAW were single and not living with a partner. Premenopausal women had significantly higher educational levels. Sixty percent of AAW had between 1 and 5 ORCHC. Most AAW used salt based seasonings, ate deep fried foods 1 to 3 times a week, and ate outside the home 1 to 3 times a month. Few AAW knew the correct daily serving for grains and dairy, and most consumed less than the recommended daily serving of fruits, vegetables and dairy. Morbidly obese AAW used more traditional food preparation techniques than obese and normal-weight AAW. Rural, and menopausal AAW had significantly higher morbid obesity levels, consumed larger portions of meats and vegetables, and reported more body image dissatisfaction than very rural AAW, and premenopausal AAW, respectively. Controlling for socioeconomic factors the relationships between perceptions of body images, psychological distress, and psychological wellbeing remained significant for numbers of ORCHC

The drivers of perception: Identifying the driving factors of resident perceptions of municipal service quality in cities of South Florida

The idea of comparative performance assessment is crucial. Recent study findings show that in South Florida the use by most municipalities of external benchmarks for performance comparison is virtually non-existent. On one level this study sought to identify the factors impacting resident perceptions of municipal service quality. On a different and more practical level, this study sought to identify a core set of measures that could serve for multi jurisdictional comparisons of performance. ^ This study empirically tested three groups of hypotheses. Data were collected via custom designed survey instruments from multiple jurisdictions, representing diverse socioeconomic backgrounds, and across two counties. A second layer of analysis was conducted on municipal budget documents for the presence of performance measures. A third layer of analysis was conducted via face-to-face interviews with residents at the point of service delivery. Research questions were analyzed using descriptive and inferential statistic methodologies. ^ Results of survey data yielded inconsistent findings. In absolute aggregated terms, the use of sociological determinants to guide inquiry failed to yield conclusive answers regarding the factors impacting resident perceptions of municipal service quality. At disaggregated community levels, however, definite differences emerged but these had weak predictive ability. More useful were the findings of performance measures reporting via municipal budget documents and analyses of interviews with residents at the point of service delivery. Regardless of socio-economic profile, neighborhood characteristics, level of civic engagement or type of community, the same aspects were important to citizens when making assessments of service quality. For parks and recreation, respondents most frequently cited maintenance, facility amenities, and program offerings as important while for garbage collection services timely and consistent service delivery mattered most. Surprisingly municipalities participating in the study track performance data on items indicated as important by citizen assessments but regular feed back from residents or reporting to the same is rarely done. ^ The implications of these findings suggest that endeavors, such as the one undertaken in this study, can assist in determining a core set of measures for cross jurisdictional comparisons of municipal service quality, improving municipal delivery of services, and to communicate with the public. ^

Obesity, cardiovascular disease risk factors and weight loss in a population of adult Mexican Americans

The study of obesity has evolved into one of the most important public health issues in the United States (U.S.), particularly in Hispanic populations. Mexican Americans, the largest Hispanic ethnic subgroup in the U.S., have been significantly impacted by obesity and related cardiovascular diseases. Mexican Americans living in the Lower Rio Grande Valley (the Valley) in the Texas-Mexico border are one of the most disadvantaged and hard-to-reach minority groups. Demographic factors, socioeconomic status, acculturation, and physical activity behavior have been found to be important predictors of health, although research findings are mixed when establishing predictors of obesity in this population. Furthermore, while obesity has long been linked to cardiovascular disease (CVD) risk factors such as hypertension, type 2 diabetes, and dyslipidemia; information on the relationships between obesity and these CVD risk factors have been mostly from non-minority population groups. Overall, research has been mixed in establishing the association between obesity and related CVD risk factors in this population calling attention to the need for further research. Nevertheless, identifying predictors of success for weight loss in this population will be important if health disparities are to be addressed. The overall objective of the findings presented in this dissertation was to attain a more informed profile of obesity and CVD risk factors in this population. In particular, we examined predictors of obesity, measures of obesity and association with cardiovascular disease risk factors in a sample of 975 Mexican Americans participating in a health promotion program in the Valley region. Findings suggest acculturation factors to be one of the most important predictors of obesity in this population. Results also point to the need of identifying other possible risk factors for predicting CVD risk. Finally, initial body mass index is an important predictor of weight loss in this population group. Thus, indicating that this population is not only amenable to change, but that improvements in weight loss are feasible. This finding strengthens the relevance of prevention programs such as Beyond Sabor for Mexican populations at risk, in particular, food bank recipients.

Obesity, Cardiovascular Risk Factors, and Weight Loss in a Population of Adult Mexican Americans

The study of obesity has evolved into one of the most important public health issues in the United States (U.S.), particularly in Hispanic populations. Mexican Americans, the largest Hispanic ethnic subgroup in the U.S., have been significantly impacted by obesity and related cardiovascular diseases. Mexican Americans living in the Lower Rio Grande Valley (the Valley) in the Texas-Mexico border are one of the most disadvantaged and hard-to-reach minority groups. Demographic factors, socioeconomic status, acculturation, and physical activity behavior have been found to be important predictors of health, although research findings are mixed when establishing predictors of obesity in this population. Furthermore, while obesity has long been linked to cardiovascular disease (CVD) risk factors such as hypertension, type 2 diabetes, and dyslipidemia; information on the relationships between obesity and these CVD risk factors have been mostly from non-minority population groups. Overall, research has been mixed in establishing the association between obesity and related CVD risk factors in this population calling attention to the need for further research. Nevertheless, identifying predictors of success for weight loss in this population will be important if health disparities are to be addressed. The overall objective of the findings presented in this dissertation was to attain a more informed profile of obesity and CVD risk factors in this population. In particular, we examined predictors of obesity, measures of obesity and association with cardiovascular disease risk factors in a sample of 975 Mexican Americans participating in a health promotion program in the Valley region. Findings suggest acculturation factors to be one of the most important predictors of obesity in this population. Results also point to the need of identifying other possible risk factors for predicting CVD risk. Finally, initial body mass index is an important predictor of weight loss in this population group. Thus, indicating that this population is not only amenable to change, but that improvements in weight loss are feasible. This finding strengthens the relevance of prevention programs such as Beyond Sabor for Mexican populations at risk, in particular, food bank recipients.