Quantification of air quality in space and time and its effects on health

The long-term adverse effects on health associated with air pollution exposure can be estimated using either cohort or spatio-temporal ecological designs. In a cohort study, the health status of a cohort of people are assessed periodically over a number of years, and then related to estimated ambient pollution concentrations in the cities in which they live. However, such cohort studies are expensive and time consuming to implement, due to the long-term follow up required for the cohort. Therefore, spatio-temporal ecological studies are also being used to estimate the long-term health effects of air pollution as they are easy to implement due to the routine availability of the required data. Spatio-temporal ecological studies estimate the health impact of air pollution by utilising geographical and temporal contrasts in air pollution and disease risk across $n$ contiguous small-areas, such as census tracts or electoral wards, for multiple time periods. The disease data are counts of the numbers of disease cases occurring in each areal unit and time period, and thus Poisson log-linear models are typically used for the analysis. The linear predictor includes pollutant concentrations and known confounders such as socio-economic deprivation. However, as the disease data typically contain residual spatial or spatio-temporal autocorrelation after the covariate effects have been accounted for, these known covariates are augmented by a set of random effects. One key problem in these studies is estimating spatially representative pollution concentrations in each areal which are typically estimated by applying Kriging to data from a sparse monitoring network, or by computing averages over modelled concentrations (grid level) from an atmospheric dispersion model. The aim of this thesis is to investigate the health effects of long-term exposure to Nitrogen Dioxide (NO2) and Particular matter (PM10) in mainland Scotland, UK. In order to have an initial impression about the air pollution health effects in mainland Scotland, chapter 3 presents a standard epidemiological study using a benchmark method. The remaining main chapters (4, 5, 6) cover the main methodological focus in this thesis which has been threefold: (i) how to better estimate pollution by developing a multivariate spatio-temporal fusion model that relates monitored and modelled pollution data over space, time and pollutant; (ii) how to simultaneously estimate the joint effects of multiple pollutants; and (iii) how to allow for the uncertainty in the estimated pollution concentrations when estimating their health effects. Specifically, chapters 4 and 5 are developed to achieve (i), while chapter 6 focuses on (ii) and (iii). In chapter 4, I propose an integrated model for estimating the long-term health effects of NO2, that fuses modelled and measured pollution data to provide improved predictions of areal level pollution concentrations and hence health effects. The air pollution fusion model proposed is a Bayesian space-time linear regression model for relating the measured concentrations to the modelled concentrations for a single pollutant, whilst allowing for additional covariate information such as site type (e.g. roadside, rural, etc) and temperature. However, it is known that some pollutants might be correlated because they may be generated by common processes or be driven by similar factors such as meteorology. The correlation between pollutants can help to predict one pollutant by borrowing strength from the others. Therefore, in chapter 5, I propose a multi-pollutant model which is a multivariate spatio-temporal fusion model that extends the single pollutant model in chapter 4, which relates monitored and modelled pollution data over space, time and pollutant to predict pollution across mainland Scotland. Considering that we are exposed to multiple pollutants simultaneously because the air we breathe contains a complex mixture of particle and gas phase pollutants, the health effects of exposure to multiple pollutants have been investigated in chapter 6. Therefore, this is a natural extension to the single pollutant health effects in chapter 4. Given NO2 and PM10 are highly correlated (multicollinearity issue) in my data, I first propose a temporally-varying linear model to regress one pollutant (e.g. NO2) against another (e.g. PM10) and then use the residuals in the disease model as well as PM10, thus investigating the health effects of exposure to both pollutants simultaneously. Another issue considered in chapter 6 is to allow for the uncertainty in the estimated pollution concentrations when estimating their health effects. There are in total four approaches being developed to adjust the exposure uncertainty. Finally, chapter 7 summarises the work contained within this thesis and discusses the implications for future research.

Explaining dinophysis cf. acuminata abundance in Antifer (Normandy, France) using dynamic linear regression

Classical regression analysis can be used to model time series. However, the assumption that model parameters are constant over time is not necessarily adapted to the data. In phytoplankton ecology, the relevance of time-varying parameter values has been shown using a dynamic linear regression model (DLRM). DLRMs, belonging to the class of Bayesian dynamic models, assume the existence of a non-observable time series of model parameters, which are estimated on-line, i.e. after each observation. The aim of this paper was to show how DLRM results could be used to explain variation of a time series of phytoplankton abundance. We applied DLRM to daily concentrations of Dinophysis cf. acuminata, determined in Antifer harbour (French coast of the English Channel), along with physical and chemical covariates (e.g. wind velocity, nutrient concentrations). A single model was built using 1989 and 1990 data, and then applied separately to each year. Equivalent static regression models were investigated for the purpose of comparison. Results showed that most of the Dinophysis cf. acuminata concentration variability was explained by the configuration of the sampling site, the wind regime and tide residual flow. Moreover, the relationships of these factors with the concentration of the microalga varied with time, a fact that could not be detected with static regression. Application of dynamic models to phytoplankton time series, especially in a monitoring context, is discussed.

Effort-reward imbalance and sedentary lifestyle: an observational study in a large occupational cohort

Objectives: To investigate the association between effort-reward imbalance (ERI) at work and sedentary lifestyle. Methods: Cross-sectional data from the ongoing Finnish Public Sector Study related to 30 433 women and 7718 men aged 17-64 were used (n = 35 918 after exclusion of participants with missing values in covariates). From the responses to a questionnaire, an aggregated mean score for ERI in a work unit was assigned to each participant. The outcome was sedentary lifestyle defined as <2.00 metabolic equivalent task (MET) hours/day. Logistic regression with generalized estimating equations was used as an analysis method to include both individual and work unit level predictors in the models. Adjustments were made for age, marital status, occupational status, job contract, smoking, and heavy drinking. Results: Twenty five percent of women and 27% of men had a sedentary lifestyle. High individual level ERI was associated with a higher likelihood of sedentary lifestyle both among women (odds ratio (OR) = 1.08, 95% CI 1.01 to 1.16) and men (OR = 1.17, 95% CI 1.02 to 1.33). These associations were not explained by relevant confounders and they were also independent of work unit level job strain measured as a ratio of job demands and control. Conclusions: A mismatch between high occupational effort spent and low reward received in turn seems to be associated with an elevated risk of sedentary lifestyle, although this association is relatively weak.

The evolution of the occupational status in Spain: An intergenerational approach

The relationship between the socio-economic status of parents and children is referred by the literature as intergenerational social mobility. The scope of this mobility encompasses different aspects such as educational attainment, income, wealth, prestige and occupational status. In particular, intergenerational occupational mobility is an interesting topic in the economic literature because it is positively associated with the economic achievement and the professional success. Low mobility implies that human capital, skills and talent can be misallocated. As a consequence, the workers’ efforts, their motivation and productivity could be negatively affected, which would have adverse effects on the economy growth and its competitiveness. This paper attempts to carry out the study of the evolution of intergenerational social mobility in Spain during the 21st century. The methodology applied involves to associate the National Classification of Occupations (CNO-94) with the New International Socio-economic Index of Occupational Status (ISEI-08), in order to establish a socio-economic hierarchy. Afterwards, once the occupational ranking is defined, we use statistic and econometric methods to assess the occupational transitions between fathers and children and to analyse the covariates’ effects on these transitions, including as explanatory variable the children’s educational attainment. Data used corresponds to the 2005 and 2011 Living Condition Survey (INE, 2005, 2011). The results of the study are displayed by distinguishing children according to their birth cohort.

Predictors of Patient Activation Among Underserved Patients in a Nurse-managed Health Center: A Pilot Study

The concept of patient activation has gained traction as the term referring to patients who understand their role in the care process and have “the knowledge, skills and confidence” necessary to manage their illness over time (Hibbard & Mahoney, 2010). Improving health outcomes for vulnerable and underserved populations who bear a disproportionate burden of health disparities presents unique challenges for nurse practitioners who provide primary care in nurse-managed health centers. Evidence that activation improves patient self-management is prompting the search for theory-based self-management support interventions to activate patients for self-management, improve health outcomes, and sustain long-term gains. Yet, no previous studies investigated the relationship between Self-determination Theory (SDT; Deci & Ryan, 2000) and activation. The major purpose of this study, guided by the Triple Aim (Berwick, Nolan, & Whittington, 2008) and nested in the Chronic Care Model (Wagner et al., 2001), was to examine the degree to which two constructs– Autonomy Support and Autonomous Motivation– independently predicted Patient Activation, controlling for covariates. For this study, 130 nurse-managed health center patients completed an on-line 38-item survey onsite. The two independent measures were the 6-item Modified Health Care Climate Questionnaire (mHCCQ; Williams, McGregor, King, Nelson, & Glasgow, 2005; Cronbach’s alpha =0.89) and the 8-item adapted Treatment Self-Regulation Questionnaire (TSRQ; Williams, Freedman, & Deci, 1998; Cronbach’s alpha = 0.80). The Patient Activation Measure (PAM-13; Hibbard, Mahoney, Stock, & Tusler, 2005; Cronbach’s alpha = 0.89) was the dependent measure. Autonomy Support was the only significant predictor, explaining 19.1% of the variance in patient activation. Five of six autonomy support survey items regressed on activation were significant, illustrating autonomy supportive communication styles contributing to activation. These results suggest theory-based patient, provider, and system level interventions to enhance self-management in primary care and educational and professional development curricula. Future investigations should examine additional sources of autonomy support and different measurements of autonomous motivation to improve the predictive power of the model. Longitudinal analyses should be conducted to further understand the relationship between autonomy support and autonomous motivation with patient activation, based on the premise that patient activation will sustain behavior change.

Maternal Age and Infant Mortality for White, Black, and Mexican Mothers in the United States

Funding for Open Access provided by the UMD Libraries Open Access Publishing Fund.

Gender, Behavioral Assessment of Negative Reinforcement Driven Risk Taking Propensity, and Cigarette Smoking

Cigarette smoking remains the leading preventable cause of death and disability in the United States and most often is initiated during adolescence. An emerging body of research suggests that a negative reinforcement model may explain factors that contribute to tobacco use during adolescence and that negative reinforcement processes may contribute to tobacco use to a greater extent among female adolescents than among male adolescents. However, the extant literature both on the relationship between negative reinforcement processes and adolescent tobacco use as well as on the relationship between gender, negative reinforcement processes, and adolescent tobacco use is limited by the sole reliance on self-report measures of negative reinforcement processes that may contribute to cigarette smoking. The current study aimed to further disentangle the relationships between negative reinforcement based risk taking, gender and tobacco use during older adolescence by utilizing a behavioral analogue measure of negative reinforcement based risk taking, the Maryland Resource for the Behavioral Utilization of the Reinforcement of Negative Stimuli (MRBURNS). Specifically, we examined the relationship between pumps on the MRBURNS, an indicator of risk taking, and smoking status as well as the interaction between MRBURNS pumps and gender for predicting smoking status. Participants included 103 older adolescents (n=51 smokers, 50.5% female, Age (M(SD) = 19.41(1.06)) who all attended one experimental session during which they completed the MRBURNS as well as self-report measures of tobacco use, nicotine dependence, alcohol use, depression, and anxiety. We utilized binary logistic regressions to examine the relationship between MRBURNS pumps and smoking status as well as the interactive effect of MRBURNS pumps and gender for predicting smoking status. Controlling for relevant covariates, pumps on the MRBURNS did not significantly predict smoking status and the interaction between pumps on the MRBURNS and gender also did not significantly predict smoking status. These findings highlight the importance of future research examining various task modifications to the MRBURNS as well as the need for replications of this study with larger, more diverse samples.

Essays on mixed-frequency data : forecasting and unit root testing

Doutoramento em Economia

Análise de sobrevivência ao cancro colo-retal nos períodos 2000-2001 e 2007-2008 na região norte de Portugal

O cancro colo-retal é um dos tipos de cancro mais comuns, em ambos os sexos, tendo em conta os dados existentes nos registos oncológicos nas mais diversas regiões do globo, facto que acontece também na região Norte de Portugal. O objetivo desta dissertação foi utilizar métodos de análise de sobrevivência tradicional e de análise de sobrevivência relativa, em dados do cancro colo-retal, considerando um período de observação de 5 anos. Os dados analisados são provenientes do Registo Oncológico Regional do Norte (RORENO), obtendo-se, após inspeção e tratamento prévio, um total de 2855 pacientes aos quais foi diagnosticado cancro colo-retal em dois períodos distintos, 2000-2001 e 2007- 2008. Pretendeu-se também determinar de que forma as covariáveis influenciam a sobrevivência, e como esta evoluiu entre essas duas coortes. Dado não existir informação sobre as causas de morte, foi objetivo deste estudo estimar que parte da mortalidade observada se deve à doença em questão e que parte se deve a outras causas que afetam a mortalidade da população geral. Foram, também, estimados os coeficientes das covariáveis consideradas para os modelos adotados. Todos os resultados foram obtidos utilizando como recurso o software R e seus pacotes adequados. Utilizaram-se diversos métodos tais como Kaplan-Meier, Cox, Ederer II e Net Survival, sendo este último considerado o mais adequado a este tipo de estudo pois é considerado pela comunidade científica o único estimador centrado para análise de sobrevivência relativa e cujas propriedades estatísticas permitem a sua utilização em estudos comparativos entre países. Verificou-se, por este estimador, que não existem diferenças significativas na sobrevivência em função do sexo, idade, distrito ou localização do cancro (cólon ou reto). Por outro lado verificaram-se diferenças significativas para a sobrevivência em função do estadio e das coortes, registando-se um acréscimo global de 8.5% na sobrevivência aos 5 anos de 2000-2001 para 2007-2008. Por fim destacam-se alguns aspetos que merecem atenção em estudos futuros.

Self-reported vaccination in the elderly : SABE Bogotá study, Colombia

Objectives: To determine the frequency of vaccination in older adults within the city of Bogotá and to estimate the association with sociodemographic and health factors. Methods: This is a secondary data analysis from the SABE-Bogotá Study, a cross-sectional population-based study that included a total of 2,000 persons aged 60 years. Weighted percentages for self-reported vaccination [influenza, pneumococcal, tetanus] were determined. The association between vaccination and covariates was evaluate by logistic regression models. Results: A total of 73.0% of respondents received influenza, 57.8% pneumococcal and 47.6% tetanus vaccine. Factors independently associated with vaccination included: 1- age (65-74 years had higher odds of receiving vaccinations, compared to 60-64 years; 2- socioeconomic status (SES) (higher SES had lower odds of having influenza and pneumococcal vaccines, compared to those with lower SES); 3- health insurance (those with contributive or subsidized health insurance had higher odds (between 3 and 5 times higher) of having vaccinations, compared to those with no insurance); 4- older adults with better functional status (greater Lawton scores) had increased odds for all vaccinations; 5- older adults with higher comorbidity had increased odds for influenza and pneumococcal vaccinations. Conclusion: Vaccination campaigns should be strengthened to increase vaccination coverage, especially in the group more reticent to vaccination or vulnerable to reach it such as the disable elder.

A Retrospective-Longitudinal Examination of the Relationship between Apportionment of Seat Time in Community-College Algebra Courses and Student Academic Performance

During the past decade, there has been a dramatic increase by postsecondary institutions in providing academic programs and course offerings in a multitude of formats and venues (Biemiller, 2009; Kucsera & Zimmaro, 2010; Lang, 2009; Mangan, 2008). Strategies pertaining to reapportionment of course-delivery seat time have been a major facet of these institutional initiatives; most notably, within many open-door 2-year colleges. Often, these enrollment-management decisions are driven by the desire to increase market-share, optimize the usage of finite facility capacity, and contain costs, especially during these economically turbulent times. So, while enrollments have surged to the point where nearly one in three 18-to-24 year-old U.S. undergraduates are community college students (Pew Research Center, 2009), graduation rates, on average, still remain distressingly low (Complete College America, 2011). Among the learning-theory constructs related to seat-time reapportionment efforts is the cognitive phenomenon commonly referred to as the spacing effect, the degree to which learning is enhanced by a series of shorter, separated sessions as opposed to fewer, more massed episodes. This ex post facto study explored whether seat time in a postsecondary developmental-level algebra course is significantly related to: course success; course-enrollment persistence; and, longitudinally, the time to successfully complete a general-education-level mathematics course. Hierarchical logistic regression and discrete-time survival analysis were used to perform a multi-level, multivariable analysis of a student cohort (N = 3,284) enrolled at a large, multi-campus, urban community college. The subjects were retrospectively tracked over a 2-year longitudinal period. The study found that students in long seat-time classes tended to withdraw earlier and more often than did their peers in short seat-time classes (p < .05). Additionally, a model comprised of nine statistically significant covariates (all with p-values less than .01) was constructed. However, no longitudinal seat-time group differences were detected nor was there sufficient statistical evidence to conclude that seat time was predictive of developmental-level course success. A principal aim of this study was to demonstrate—to educational leaders, researchers, and institutional-research/business-intelligence professionals—the advantages and computational practicability of survival analysis, an underused but more powerful way to investigate changes in students over time.

Online education, accrediting standards, and student success: An examination of the relationship between the southern association of colleges and schools commission on colleges standards for online education and student success

Prior to 2000, there were less than 1.6 million students enrolled in at least one online course. By fall 2010, student enrollment in online distance education showed a phenomenal 283% increase to 6.1 million. Two years later, this number had grown to 7.1 million. In light of this significant growth and skepticism about quality, there have been calls for greater oversight of this format of educational delivery. Accrediting bodies tasked with this oversight have developed guidelines and standards for online education. ^ There is a lack of empirical studies that examine the relationship between accrediting standards and student success. The purpose of this study was to examine the relationship between the presence of Southern Association of Colleges and Schools Commission on College (SACSCOC) standards for online education in online courses, (a) student support services and (b) curriculum and instruction, and student success. An original 24-item survey with an overall reliability coefficient of .94 was administered to students (N=464) at Florida International University, enrolled in 24 university-wide undergraduate online courses during fall 2014, who rated the presence of these standards in their online courses. The general linear model was utilized to analyze the data. The results of the study indicated that the two standards, student support services and curriculum and instruction were both significantly and positively correlated with student success but with small R2 and strengths of association less than .35 and .20 respectively. Mixed results were produced from Chi-square tests for differences in student success between higher and lower rated online courses when controlling for various covariates such as discipline, gender, race/ethnicity, GPA, age, and number of online courses previously taken. A multiple linear regression analysis revealed that the curriculum and instruction standard was the only variable that accounted for a significant amount of unique variance in student success. Another regression test revealed that no significant interaction effect exists between the two SACSCOC standards and GPA in predicting student success. ^ The results of this study are useful for administrators, faculty, and researchers who are interested in accreditation standards for online education and how these standards relate to student success.^

Exploring Calling Work Orientation: Construct Clarity and Organizational Implications

Employees maintain a personal view toward their work, which can be referred to as their work orientation. Some employees view their work as their life’s purpose (i.e., calling work orientation) and they tend to be 1) prosocially motivated, 2) derive meaning from work, and 3) feel that their purpose is from beyond the self. The purpose of the current dissertation was to differentiate calling work orientation from other similar workplace constructs, to investigate the most common covariates of calling work orientation, and to empirically test two possible moderators of the relationship between calling work orientation and work-related outcomes of job satisfaction, job performance, and work engagement. Two independent samples were collected for the purpose of testing hypotheses: data were collected from 520 working students and from 520 non-student employees. Participants from the student sample were recruited at Florida International University, and participants from the employee sample were recruited via the Amazon Mechanical Turk website. Participants from the student sample answered demographic questions and responded to self-report measures of job satisfaction, job performance, work engagement, spirituality, meaningful work, prosocial motivation, and work orientation. The procedure was similar for the employee sample, but their survey also included measures of counterproductive work behaviors, organizational citizenship behaviors, conscientiousness, and numerical ability. Additionally, employees were asked whether they would be willing to have a direct supervisor, peer, co-worker, client, or subordinate rate their job performance. Hierarchical regression findings suggest calling work orientation was predictive of overall job performance above and beyond two common predictors of performance, conscientiousness and numerical ability. The results for the covariate analyses provided evidence that prosocial motivation, meaningful work, and spirituality do play a significant role in the development of an employees’ work orientation. Perceived career opportunities moderated the relationship between calling work orientation and job performance for the employee sample. Core self-evaluations moderated the relationship between calling work orientation and job performance, and core self-evaluations moderated the relationship between calling work orientation and work engagement. Collectively, findings from the current study highlight the benefits of examining work orientation in the prediction of workplace outcomes.

NEIGHBORHOOD PERCEPTION OF SAFETY AND THE MOBILITY GAP BETWEEN MEN AND WOMEN IN OLD AGE

Thesis (Master, Community Health & Epidemiology) -- Queen's University, 2016-10-02 21:02:07.735

¬FISH DISTRIBUTIONS IN LAKE ONTARIO’S EASTERN BASIN AND THE UPPER ST. LAWRENCE RIVER: AN ANALYSIS USING GIS AND OCCUPANCY MODELLING TECHNIQUES

Predictive models of species distributions are important tools for fisheries management. Unfortunately, these predictive models can be difficult to perform on large waterbodies where fish are difficult to detect and exhaustive sampling is not possible. In recent years the development of Geographic Information Systems (GIS) and new occupancy modelling techniques has improved our ability to predict distributions across landscapes as well as account for imperfect detection. I surveyed the nearshore fish community at 105 sites between Kingston, Ontario and Rockport, Ontario with the objective of modelling geographic and environmental characteristics associated with littoral fish distributions. Occupancy modelling was performed on Round Goby, Yellow perch, and Lepomis spp. Modelling with geographic and environmental covariates revealed the effect of shoreline exposure on nearshore habitat characteristics and the occupancy of Round Goby. Yellow Perch, and Lepomis spp. occupancy was most strongly associated negatively with distance to a wetland. These results are consistent with past research on large lake systems indicate the importance of wetlands and shoreline exposure in determining the fish community of the littoral zone. By examining 3 species with varying rates of occupancy and detection, this study was also able to demonstrate the variable utility of occupancy modelling.