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This thesis investigates long-term cognitive outcome in two cohorts of adolescents and young adults exposed to stressors during the perinatal period: one group born preterm (&lt;37 weeks of gestation and birth weight &lt;1,500 g); one group exposed to two or more courses of antenatal corticosteroids (ACS), to stimulate lung maturation in the face of threatening preterm birth. In fetal life the brain undergoes dramatic growth, and a disruption to the early establishment of functional neural networks may interrupt development in ways that are difficult to predict. Executive function refers to a set of cognitive processes that are important for purposeful regulation of thought, emotion, and behavior, and even a subtle depreciation may influence overall functioning. Study I investigated the stability of executive function development after preterm birth. Executive functions were differentiated into working memory and cognitive flexibility. Both components were highly stable from preschool age to late adolescence. In Study II, we identified subgroups within the group of children born preterm with respect to cognitive profiles at 5½ and 18 years, and identified longitudinal streams. Outcome after preterm birth was diverse, and insufficiently predicted by perinatal and family factors. Individuals performing at low levels at 5½ years were unlikely to improve over time, while a group of individuals performing at or above norm at 5½ years had improved their performance relative to term-born peers by age 18. Studies I and II pointed to the need for developmental monitoring of those at risk, prior to formal schooling. Study III investigated long-term cognitive outcome after repeat ACS treatment. The study did not provide support for the concern that repeat ACS exposure will have an adverse impact on cognitive function later in life. In sum, exposure to perinatal stressors resulted in great variation in outcome. However, for many, their rough beginnings had not left a lasting mark. / <p>At the time of the doctoral defense, the following paper was unpublished and had a status as follows: Paper 1: Submitted.</p>

In 1997, the UK's Labour government introduced several health policy changes, including plans for greater collaboration with private providers. Building on previous cross-sectional research, we explore longitudinal inequities in physician access as these policy changes were materializing. Using GEE models we examine the effect of income and private health insurance (PHI) coverage on access to physicians in the general UK population from 1997 to 2003. The study finds no income inequities in GP access. In contrast, those in the highest income quintile are more likely to access consultants overall (OR:1.10, CI: 1.01,1.19), particularly private consultants (OR:2.49, CI:1.80,3.44). Not surprisingly, PHI is a strong predictor of private consultant access (OR:8.72 CI: 7.04,10.82), but a weak predictor of overall consultant access (OR:1.09, CI:1.01, 1.17). None of these findings exhibited significant time trends across the years of study, thus indicating that the existing inequities remained stable in the UK, despite the aforementioned reforms.

Thesis (Ph. D.)--University of Texas Health Science Center at Houston, School of Public Health, 2006. / Includes bibliographical references (leaves 158-166).

Thesis (Ph. D.)--University of California, Los Angeles, 1986. / Includes bibliographical references.

Thesis (Ph.D. in Biostatistics) -- University of Colorado at Denver and Health Sciences Center, 2006. / Typescript. Includes bibliographical references (leaves 72-75). Free to UCD Anschutz Medical Campus. Online version available via ProQuest Digital Dissertations;

Thesis (Ph.D. in Analytic Health Sciences, Department of Preventive Medicine and Biometrics) -- University of Colorado Denver, 2007. / Typescript. Includes bibliographical references (leaves 75-77). Free to UCD affiliates. Online version available via ProQuest Digital Dissertations;

Recent research in economics and psychology has examined the childhood noncognitive skills which predict future economic success. However, there has been relatively little research on whether these skills predict future unemployment. This thesis uses data from four cohort studies (total N = 47,328) from Great Britain and the United States to examine how lifetime trajectories of unemployment are affected by childhood differences in self-control (chapter 3), conscientiousness (4), and mental health (5-6). These are some of the first studies to examine how pre-labor market measures of these psychological characteristics prospectively predict future unemployment. Chapters 3, 5 and 6 are the first studies to examine how early psychological characteristics interact with recessions to produce differential unemployment outcomes. After adjusting for cognitive ability and key sociodemographic indicators (e.g. gender, SES), all three of these psychological characteristics are found to predict future unemployment. The effects are statistically significant and economically meaningful, comparable in magnitude to the effects of intelligence. Chapter 3 shows that childhood with poor self-control were disproportionately more likely than their more self-controlled peers to become unemployed during the 1980s UK recession, and chapters 5 and 6 find a similar effect for children with high psychological distress compared to their less distressed peers during the 1980s UK recession and 2007 US recession. These studies demonstrate the value of using psychological research to examine economic outcomes. The chief policy implication is that interventions which improve childhood levels of self-control, conscientiousness and mental health may be an effective way to reduce future population unemployment levels. In the short term, remediation programs which take into account individual psychological differences may improve the efficacy of unemployment interventions, particularly during recessions when certain groups are more likely than others to become unemployed.

A importância da doença arterial coronariana (DAC) na sociedade \"moderna\" é atestada pelo grande número de pessoas afetadas por ela. Os dados da Organização Mundial de Saúde estimam que a doença isquêmica do coração será a segunda principal causa de morte em todo o mundo até 2030. Além disso, com o advento das ferramentas de predição de riscos e estudos de associação genômica ampla (GWAS, do inglês Genome-Wide Association Studies), vários estudos tem demonstrado o uso de escores genéticos de risco para predizer DAC, porém estes escores apresentam apenas uma discreta melhora em nossa capacidade de avaliação. O presente estudo desenvolveu um escore genético de risco (GRS, do inglês Genetic risk score) para DAC, utilizando polimorfismos previamente associados a DAC e/ou a fenótipos relacionados à doença. Mil, trezentos e quarenta e nove indivíduos, provenientes do Estudo Longitudinal da Saúde do Adulto (ELSA-BRASIL), foram genotipados para nosso estudo. Usando polimorfismos de nucleotídeo único (SNP, do inglês Single Nucleotide Polymorphisms) obtidos a partir da base de dados online de GWAS avaliamos a associação de cada polimorfismo escolhido com os fatores de risco para doença cardiovascular. Os indivíduos foram submetidos à determinação do escore de cálcio (EC) coronário e um EC > 100 foi usado como desfecho. Modelos Zero-inflacionados foram utilizados para a construção do escore de risco genético (GRS). Escore de risco de Framingham para DAC em 10 anos (FRS, do inglês Framingham Risk Score) foi calculado de acordo com o descrito por Wilson e D\'Agostino. Nosso GRS foi composto de 47 variantes genéticas, ajustado por sexo e idade, associadas com DAC ou outros fenótipos da doença coronária ou fatores de risco. O GRS mostrou precisão significativamente melhor do que o Escore de Risco de Framingham para predizer o risco de CHD (AUC, 0,90; IC 95%: 0,88-0,93; P < 0,01). Também foram criados outros dois escores: o primeiro, um modelo com apenas a idade e sexo; o segundo, apenas utilizando a informação genética. Comparamos o modelo Idade+Sexo com o GRS e FRS por meio de curva ROC e avaliamos o desempenho dos modelos em comparação com FRS. Análises do NRI e IDI foram realizadas para avaliar a reclassificação do GRS e do modelo Idade+Sexo em relação ao FRS, que é o atualmente utilizado para a estratificação de indivíduos da população geral. O escore apenas com os SNPs foi utilizado para comparar sua adição a um modelo com fatores de risco. Por fim, analisamos a associação entre o GRS, fatores de risco e CAC usando modelos lineares generalizados. Em suma, criamos um GRS composto por 47 SNPs associado com doença coronariana ou fatores de risco cardiovascular que apresentou bons resultados na predição de risco para DAC. O GRS melhorou a reclassificação de risco para doença arterial coronariana, e melhorou significativamente a discriminação entre os indivíduos afetados e não afetados / Importance of coronary artery disease (CAD) in \"modern\" society is attested by the large increase of people affected by it. Data from the World Health Organization estimated that ischemic heart disease is the second leading cause of death worldwide by 2030. Futhermore, with the advent of predictive risk tools and genome-wide association studies, several studies have demonstrated the use of genetic risk scores (GRS) for predicting CAD, but these scores shows a slight improvement in the assessment. This study built a genetic risk score for CAD, using polymorphisms previously associated with CAD and phenotypes related to disease. One thousand, Three hundred forty-nine individuals, from the Brazilian Longitudinal Study of Adults Health (in Portuguese, Estudo Longitudinal da Saúde do Adulto-BRASIL), were genotyped for our study. Using single nucleotide polymorphisms (SNPs) obtained from the online database of GWAS evaluated the association of each polymorphism chosen with risk factors for cardiovascular disease. Individuals underwent determination of calcium artery coronary score (CACS) and CAC > 100 was used as the end-point. Zero inflated models were used for the construction of GRS. Framingham Risk Score (FRS) for CHD in 10 years was calculated as described by Wilson and D\'Agostino. In addition, our GRS consists of 47 genetic variants, adjusted for sex and age, associated with CHD or other phenotypes of coronary heart disease or risk factors. GRS showed significantly better accuracy than the Framingham Risk Score to predict the risk of CAD (AUC, 0.90; 95% CI: 0.88 0.93; P < 0.01). Also other two scores were created: first, a model with only age and sex; second, only the genetic information. We compare the Age+Sex model with the GRS and FRS through ROC curve and evaluate the performance of models compared with FRS. NRI and IDI analysis were performed to evaluate the reclassification of GRS and Age + Sex model in relation to the FRS model. The score only the SNPs was used to compare their addition to a model with risk factors. Finally, we analyzed the association between the GRS, risk factors and CAC using generalized linear models. In short, we create a GRS composed of 47 SNPs associated with coronary heart disease or cardiovascular risk factors that showed good results in risk prediction for CAD. GRS improved reclassification of risk for coronary artery disease, and significantly improves the discrimination between affected and unaffected individuals