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United States bicycle commuting rates are low compared to similarly developed countries like the Netherlands and Denmark. However, bicycle commuting shows promise for positive health outcomes, especially those related to chronic diseases like obesity, diabetes, and heart disease. Little research has been conducted in the U.S. to study the association between bicycle commuting and heart disease. Furthermore, U.S. cities need guidance on how to increase bicycle commuting rates. The purpose of this study was to evaluate the association between U.S. bicycle commuting rates and heart disease prevalence and to identify infrastructure and policy factors most significantly associated with bicycle commuting rates in large U.S. cities. This research quantitatively defined infrastructure and policy factors and analyzed ecologic associations across the 50 most populous U.S. cities. The results of this study are based on an ecologic analysis that evaluated associations at the census tract and city levels. Secondary data from nine sources as used to conduct the analysis. Data sources include the League of American Bicyclists Benchmarking Report, PeopleForBikes bicycle network analysis, the Centers for Disease Control and Prevention Behavioral Risk Factor Surveillance System, the U.S. Census Bureau American Community Survey, and more. A principal components analysis was conducted to identify relevant infrastructure factors for research question one; ordinary least squares regression models were derived to compare associations between infrastructure and policy factors for research question two, and latent class cluster analysis was conducted to calculate the prevalence odds ratios of the association between bicycle commuting rate and heart disease for research question three. Three factors accounted for 70% of the variation in bicycle commuting rates. Those three factors include the average number of cyclist fatalities, the number of city employees working on bicycle projects, and bicycle network connections to public transit. The results also show that the association between bicycle commuting rate and heart disease prevalence was only statistically significant in census tract populations with predominantly high socioeconomic status, low health risk factors, and white race. The ecologic study design likely masked any positive health outcomes in populations with low socioeconomic status. The findings of this study provide valuable insights for transportation and public health practitioners, and the conclusions set the stage for future research on cycling and chronic disease outcomes in the United States. / Doctor of Philosophy / In the U.S., about 1% of the population bicycle commutes to work. Bicycle commuting is uncommon in the U.S. because many people feel it is not a safe or practical form of transportation. However, several U.S. organizations are working to make roadways safer for cyclists. Some of these organizations include The League of American Bicyclists (LAB), PeopleForBikes (PFB), and Smart Growth America (SGA). The LAB has awarded nearly 500 towns and cities with a bicycle-friendly community award, while PFB has created tools to help urban planners examine bicycle networks in their communities. SGA also helps create bicycle-friendly cities by working with elected officials to advocate for policies that will make roadways safer for cyclists. LAB, PFB, and SGA all collect data as part of their work to learn what U.S. communities are doing to support cycling. I used LAB, PFB, and SGA data to determine the most important factors for bicycle-friendliness in the 50 largest U.S. cities. I evaluated the impact of 14 factors, including, but not limited to, protected bike lanes, network connectedness, and bicycle-friendly policy. I found that three factors had the strongest association with bicycle commuting rates in large U.S. cities: network connections to public transit, the number of city employees working on bicycle projects, and the number of deaths from cyclist fatalities. Cities looking to increase bicycle commuting should use these results to focus their efforts on improving public transit networks, increasing the number of work hours spent on bicycle projects, and identifying strategies to reduce cyclist fatalities. U.S. cities should work towards improving bicycle-friendliness because of the population health benefits. In the past 20 years, the percentage of Americans with obesity has increased by 40%, and the percentage of Americans with Type 2 diabetes has doubled. Multiple factors contribute to obesity and diabetes, including bicycle commuting, which has been associated with decreases in both obesity and diabetes. Bicycle commuting may also be associated with heart disease, which is the leading cause of death in the U.S., but more research is needed. In the second part of this study, I evaluated the relationship between bicycle commuting rate and the percentage of Americans living with heart disease. I used data from the Centers for Disease Control and Prevention (CDC) and the U.S. Census Bureau to understand the association between bicycle commuting and heart disease in 50 U.S. cities. I analyzed the data by census tract to understand health outcomes at a population level. I found that the association between bicycle commuting and heart disease was only significant in census tracts that were predominately high-income. I also found that bicycle commuting rates in high-income populations were three times greater than in low-income populations. In other words, health benefits were not visible in low-income populations because of low bicycle commuting rates. Low-income populations have higher rates of obesity and diabetes and would benefit the most from bicycle commuting, yet these populations confront several barriers to cycling. Cities interested in improving bicycle-friendliness should work to engage low-income populations in their work.

Spillover research has shown that workday stress hampers commuting safety, while ego depletion research has demonstrated that prior self-regulation leads to performance decrements in subsequent tasks. This study sought to unite these two lines of research by proposing that ego depletion-induced alterations in attention and motivation are the mechanisms by which workday experiences spill over to the commute and impair driving safety. To examine the daily influences of these within-person processes on driving behavior in the post-work commute, this study adopted a daily survey design, wherein participants took an online survey immediately before and after each post-work commute across one work week. In these daily surveys, fifty-six participants (N = 56; n = 250 day-level observations) reported their workday self-regulatory demands; pre-commute levels of attention, motivation, and affective states; and driving behavior during the commute home. Using multilevel path analysis to isolate within-person effects, the current study found no evidence to suggest that workday self-regulatory demands lowered pre-commute attention and motivation, nor did it detect associations of attention and motivation with post-work aberrant driving. Results indicated that an ego depleted state might impair attention and motivation but not driving safety in the commute. Instead, the results pointed to the person-level factor of trait self-control as potentially having a greater impact on post-work aberrant driving than daily experiences. / M.S. / Research has shown that employees tend to drive more unsafely when commuting home after a stressful workday. However, most of this research has examined what about the person makes them drive more unsafely than someone else, but it is also important to understand what about the workday makes someone drive more unsafely one day than another day. I predicted that a workday containing more self-control demands would make an employee drive more unsafely when commuting home from work because facing more self-control demands would lower the employee’s attention and motivation for driving safely. To test this idea, I gave participants two online surveys per day for five consecutive days, Monday through Friday – one at the end of their workday (asking about their workday demands and current levels of attention and motivation), and one at the end of their commute home (asking about their driving behavior during that post-work commute). The data from my final sample of 56 participants (N = 56; n = 250 study days) showed no evidence to support my hypotheses: the amount of workday self-control demands was not found to associate with attention and motivation before driving home, and attention and motivation before driving home were not found to relate to driving safety during that commute home. On the other hand, I did find that a person’s general ability to maintain self-control was associated with their driving safety during the commute home (regardless of workday self-control demands). These results suggest that a person’s character might be more important in determining their day-to-day driving safety during the commute home than the self-control demands they face during the workday.

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In view of the economic and social transcendence of a region's labour market on its competitiveness, the quality of life of its citizens, its economic evolution or its level of resilience to external shocks and fluctuations, this thesis focuses on analysing the employment situation of those groups that traditionally had greater impediments when it comes to take part of the labour force: immigrants and women. Two lines of work have been established for the development of the thesis. The first one (Chapters 2 and 3) examines commuting patterns based on individual data, exploring the differential behaviour which is observed according to the immigrant status, on the one hand, and gender, on the other. Analysing the commuting patterns of both groups is relevant for understanding their employment situation as it reflects individual decisions and behaviour in the residential and labour spheres and is a good indicator of the likely existence of a spatial mismatch between labour supply and demand. Both analysis are based on a rich, nationally representative database and incorporate the use of econometric techniques of decomposition that are new in this field of study, and that allow quantifying the joint and individual influence of a wide range of explanatory factors. In this sense, Chapter 2 focuses on the differences in commuting length between native and immigrant employees in Spain, a relevant issue since immigrants' longer commuting times may reflect an imperfect spatial matching of their labour supply and demand with negative implications for their relative labour outcomes and their individual well-being. The research differentiates immigrants according to their origin. The evidence obtained shows that, although a relevant part of the explanation of the greater commuting observed for immigrants is related to observed elements such as a different use of modes of transport, they make overall significantly longer journeys when comparing with observationally similar natives. This commuting penalty occurs yet only in the case of immigrants from emerging countries, as it does not exist for those from advanced economies. Although the penalty is overall rather similar along several sociodemographic and occupational lines, it is much more pronounced for individuals living in large municipalities, which implies that previous analyses focusing on specific densely populated territories could overestimate the phenomenon. To conclude, the additional novel evidence about the potential explanations of the commuting penalty of immigrants shows that it does not seem to derive from a hypothetically greater tolerance to commuting. Chapter 3 examines gender differences in commuting in Spain, a relevant issue since women's shorter commuting times partially explain their poorer work outcomes. The analysis considers the importance of the level of education workers have. The evidence obtained indicates that although the shorter commuting times of women are partially explained by factors such as their greater household responsibilities, there is a systematic pattern of less mobility that persists when women are compared with men with the same characteristics. This pattern is consistent with the theoretical hypothesis that there are cultural or social constraints that restrict women's commuting and worsen their job opportunities. This circumstance is also consistent with the findings that there is no pattern of lesser mobility for certain groups of women whose behaviour is in general more assimilable to that of men, such as women without family responsibilities, and that the origin of the gender differences in commuting is not women's lesser tolerance for this phenomenon. The second line of work (Chapter 4) focuses on women and analyses the impact of the characteristics of the Labour Market Area of residence on their participation and employment rates in Spain. In view of the importance of regional attributes on individual employability, this analysis has made it possible to identify which regional factors favour or impede the good performance of women in the labour market. In this case, the territorial unit of analysis is the Spanish LMAs, areas which reflect the regional mobility of workers and which are coherent when analysing labour market phenomena. The use of these territorial areas has allowed an ad hoc recoding of the microdata from the 2011 Population and Housing Census, so that it is possible to know the Labour Market Area of residence of each of the individuals in the sample. Thanks to this database, average variables of the individual behaviour recorded in the census microdata for each of the LMAs have been calculated for the first time for Spain. This type of variable reflects the average characteristics of the composition of each market, allowing for a better measurement of the phenomenon. In addition, spatial econometric methods are used to detect possible spatial relationships between markets derived from the presence of spatial autocorrelation. These techniques allow us to determine the influence of the characteristics of the LMA on female participation and employment rates, as well as the effect of the characteristics of neighbouring markets. The evidence obtained shows the presence of notable territorial differences in the distribution of female participation and employment rates. When considering these spatial autocorrelation patterns in the models, a spatial distance matrix of 50 kilometres has been considered. The econometric results show that female participation rates follow a process of spatial autocorrelation in the residuals that may derive from the economic/regulatory situation influenced by belonging to the same Autonomous Community, and from social/cultural factors shared by the closest LMAs. Likewise, participation rates are positively influenced by certain internal characteristics of a market, especially the presence of the service sector and the proportion of women with a higher average level of education, and by the disturbance term of neighbouring regions. The employment rate, on the other hand, presents a process of local spatial dependence in which both the characteristics of a market and the characteristics and shocks derived from neighbouring markets are considered relevant. These results show, as in the case of participation, the existence of territorial relations between the closest markets that go beyond the strictly labour-related ones and that may derive from economic or legislative aspects. Among the explanatory regional characteristics considered to favour female employment are the higher proportion of women with a high level of education, the higher percentage of women employed in services and the higher average income level. To check the effect of the spatial relationships of Madrid LMA with its closest LMAs, the analysis has been complemented by extending the distance matrix to 67 kilometres. In line with the previous analysis, the results confirm the existence of a pattern of local spatial autocorrelation in the distribution of the female participation rate. Alternatively, the spatial pattern observed in female employment rates becomes localized in the endogenous variable. This global pattern is characterized by the chain transmission of spatial relationships from neighbours to neighbours. These results reveal that the importance in economic and employment terms of the Madrid LMA prevails over the other markets, and the importance of using territorial units appropriate to the object of study. Thus, previous analyses carried out in this field, based on territorial units that were probably too large on average, may have overestimated the spatial effect associated with the phenomena analysed. / Financiada por la Agencia Estatal de Investigación (Ministerio de Ciencia e Innovación, Gobierno de España) y el Fondo Social Europeo (FSE): Ayudas para contratos predoctorales para la formación de doctores, Subprograma Estatal de Formación del Programa Estatal de Promoción del Talento y su Empleabilidad en I+D+i, Plan Estatal de I+D+i 2017-2020 (ayuda PRE2018-085908). Con el apoyo de los proyectos CSO2017-86474-R (AEI, Plan Estatal de I+D+i), PID2020-114896RB-I00 (AEI/10.13039/501100011033, Plan Estatal de I+D+i) y AICO/2021/062 (Conselleria de Innovación, Universidades, Ciencia y Sociedad Digital; Programa de I+D+I de la Comunitat Valenciana).

published_or_final_version / abstract / Transport Policy and Planning / Master / Master of Arts in Transport Policy and Planning

As a descriptive, pilot study utilizing an online survey, this study explores the perceptions of CSUSB student nurses related to their commute and ontime arrival at clinical sites, typically in the San Bernardino and Riverside Counties, and whether or not the commute is perceived as being stressful.

published_or_final_version / abstract / toc / Transport Policy and Planning / Master / Master of Arts in Transport Policy and Planning

published_or_final_version / abstract / toc / Transport Policy and Planning / Master / Master of Arts in Transport Policy and Planning