Asthma is one of the most common respiratory diseases in Canada. It not only brings pain to more than 7.8% of Canadians but it also costs millions of dollars every year. In this project we study the influence that environmental factors have on asthma based on the data from the National Population Health Survey (NPHS) conducted by Statistics Canada. A descriptive analysis is done first to get an initial understanding of the environmental factors' effects on asthma. Then we do a x2-test to test for the homogeneity of asthma distribution across the levels of each environmental factor. Most of the factors included in our study are significant except those representing whether living in the metropolitan areas of Montreal or Vancouver, the number of persons living in the household, and whether there are small children in the household. For ordinal variables we test for trend on asthma prevalence. The trend tests indicate that there are significant trends between asthma and most of the ordinal factors except for a few, including the number of bedrooms in the household and the number of cigarettes smoked daily by the daily smokers. Then odds ratio and relative risk analyses are done to obtain statistical insights on the relative risk of the factors. The result shows that living in Nova Scotia, Ontario and Quebec, urban areas, engaged in finance, community services, personal service, young, attend physical activities, born in Canada, white, single or widowed, separated, divorced, start smoking early, do not own the dwelling living in, female adult, male children, and overweight and underweight adult, are all contributing factors for asthma. To model and investigate the joint effect of factors on asthma prevalence, we use logistic and log-linear regression models. To avoid collinearity problems, a reduced number of predictors is used. The results suggest that environmental factors have a significant joint influence on asthma prevalence. / Thesis / Master of Science (MS)

Psychotropic medication use is widely implicated as a risk factor for injuries, and it is believed that the adverse effect profiles of these medications are exacerbated by the consumption of alcohol. The objectives of this study are (a) to examine the associations between the use of specific classes of psychotropic medications and injuries among elderly participants of the National Population Health Survey (NPHS), and (b) to determine whether and how associations between psychotropic medications and injuries are modified by the consumption of alcohol. Data from Cycles 1 (1994/95), 2 (1996/97), and 3 (1998/99) of the NPHS household longitudinal file were used in this study, selecting community-dwelling participants aged 65 years of age and older in 1994/95. Among antidepressant medications, the magnitude of the risk of injuries was higher for users of tricyclic derivatives (OR=1.4; 95%CI: 0.7 – 2.9) than SSRIs (OR=0.3; 95%CI: 0.1 – 1.0). Benzodiazepine use for any indication increased the risk of injuries, but that effect was not consistent across indications. The use of benzodiazepine antianxiety medications resulted in an increased risk of injuries (OR=2.0; 95%CI: 1.3 – 3.1), but there were no significant effects on the injury risk among benzodiazepine hypnotic and sedative users (OR=0.8; 95%CI: 0.4 – 1.7). Results pertaining to the second objective of this study raised as many questions as they resolved. Alcohol consumption decreased the odds of injury among hypnotic and sedative users, but otherwise, no consistent results were observed. Findings from this study underscore the importance of identifying appropriate alcohol measures for research among elderly populations. They also stress the need to separately consider the impact of different classes of psychotropic medications on injuries (tricyclic antidepressants separate from SSRI antidepressants and antianxiety benzodiazepines separate from hypnotic and sedative benzodiazepines).

Psychotropic medication use is widely implicated as a risk factor for injuries, and it is believed that the adverse effect profiles of these medications are exacerbated by the consumption of alcohol. The objectives of this study are (a) to examine the associations between the use of specific classes of psychotropic medications and injuries among elderly participants of the National Population Health Survey (NPHS), and (b) to determine whether and how associations between psychotropic medications and injuries are modified by the consumption of alcohol. Data from Cycles 1 (1994/95), 2 (1996/97), and 3 (1998/99) of the NPHS household longitudinal file were used in this study, selecting community-dwelling participants aged 65 years of age and older in 1994/95. Among antidepressant medications, the magnitude of the risk of injuries was higher for users of tricyclic derivatives (OR=1.4; 95%CI: 0.7 – 2.9) than SSRIs (OR=0.3; 95%CI: 0.1 – 1.0). Benzodiazepine use for any indication increased the risk of injuries, but that effect was not consistent across indications. The use of benzodiazepine antianxiety medications resulted in an increased risk of injuries (OR=2.0; 95%CI: 1.3 – 3.1), but there were no significant effects on the injury risk among benzodiazepine hypnotic and sedative users (OR=0.8; 95%CI: 0.4 – 1.7). Results pertaining to the second objective of this study raised as many questions as they resolved. Alcohol consumption decreased the odds of injury among hypnotic and sedative users, but otherwise, no consistent results were observed. Findings from this study underscore the importance of identifying appropriate alcohol measures for research among elderly populations. They also stress the need to separately consider the impact of different classes of psychotropic medications on injuries (tricyclic antidepressants separate from SSRI antidepressants and antianxiety benzodiazepines separate from hypnotic and sedative benzodiazepines).

Reliable und valide Informationen zur Häufigkeit und zu Korrelaten von Depression in der Allgemeinbevölkerung sind eine Voraussetzung für eine wissenschaftlich fundierte Gesundheitsversorgung und für Präventionsmaßnahmen. Die Vielfalt an Definitionen und die klinische Heterogenität von „Depression“ stellt eine Herausforderung für das Gesundheitsmonitoring und für die epidemiologische Forschung dar. Dies spiegelt sich in der Vielzahl an Depressionsmaßen wider. Daran anknüpfend ist das Ziel dieser kumulativen Dissertation, die Häufigkeiten und soziodemographischen und gesundheitsbezogenen Korrelate – mit einem Schwerpunkt auf der somatischen Komorbidität – eines breiten Spektrums etablierter Depressionsmaße in der erwachsenen Allgemeinbevölkerung in Deutschland zu untersuchen: von aktueller psychischer Belastung, depressiver Symptomatik und einem depressiven Syndrom über eine selbstberichtete ärztliche Depressionsdiagnose bis hin zu einer klinischen Major Depression. Datenbasis für die vier Originalarbeiten der Dissertation sind die bundesweit repräsentativen Querschnittstudien „Gesundheit in Deutschland aktuell“ (GEDA, 18 Jahre und älter) und die „Studie zur Gesundheit Erwachsener in Deutschland“ (DEGS1, 19-79 Jahre) mit dem Modul Psychische Gesundheit (DEGS1-MH) des Robert Koch-Instituts (RKI). In Kapitel 1 werden Forschungshintergrund, Fragestellungen und Methoden der vier Originalarbeiten zusammengefasst und die Ergebnisse dargestellt. Es ergeben sich hohe Prävalenzen auf Basis aller Depressionsmaße. Zugleich wird deutlich, dass die jeweiligen Maße zu unterschiedlichen Prävalenzschätzungen führen und dass es nur moderate Schnittmengen der jeweils identifizierten Fallgruppen gibt. Weiterhin zeigt sich eine weitgehende, jedoch keine vollständige Übereinstimmung in assoziierten soziodemographischen und gesundheitsbezogenen Korrelaten. Dies betrifft auch die Assoziation mit chronischen somatischen Erkrankungen, für die sich teilweise unterschiedliche Muster zwischen den untersuchten Depressionsmaßen und zwischen den Altersgruppen zeigen. Es folgen eine synthetisierende Ergebnisdiskussion und die Ableitung von Implikationen für die epidemiologische Forschung, das Gesundheitsmonitoring und die klinische Praxis. Kapitel 2 enthält die vier Originalarbeiten der Dissertation.

McMaster University MASTER OF PUBLIC HEALTH (2020) Hamilton, Ontario (Health Research Methods, Evidence, and Impact) TITLE: Applying Machine Learning to Determine Nutrients Predictive of Cardiovascular Disease Using Canadian Linked Population-Based Data AUTHOR: Jason D. Morgenstern, B.Sc. (University of Guelph), M.D. (Western University) SUPERVISOR: Professor L.N. Anderson, NUMBER OF PAGES: xv, 121 / The use of big data and machine learning may help to address some challenges in nutritional epidemiology. The first objective of this thesis was to explore the use of machine learning prediction models in a hypothesis-generating approach to evaluate how detailed dietary features contribute to CVD risk prediction. The second objective was to assess the predictive performance of the models. A population-based retrospective cohort study was conducted using linked Canadian data from 2004 – 2018. Study participants were adults age 20 and older (n=12 130 ) who completed the 2004 Canadian Community Health Survey, Cycle 2.2, Nutrition (CCHS 2.2). Statistics Canada has linked the CCHS 2.2 data to the Discharge Abstracts Database and the Canadian Vital Statistics Death database, which were used to determine cardiovascular outcomes (stroke or ischemic heart disease events or deaths). Conditional inference forests were used to develop models. Then, permutation feature importance (PFI) and accumulated local effects (ALEs) were calculated to explore contributions of nutrients to predicted disease. Supplement-use (median PFI (M)=4.09 x 10-4, IQR=8.25 x 10-7 – 1.11 x 10-3) and caffeine (M=2.79 x 10-4, IQR= -9.11 x 10-5 – 5.86 x 10-4) had the highest median PFIs for nutrition-related features. Supplement-use was associated with decreased predicted risk of CVD (accumulated local effects range (ALER)= -3.02 x 10-4 – 2.76 x 10-4) and caffeine was associated with increased predicted risk (ALER= -9.96 x 10-4 – 0.035). The best-performing model had a logarithmic loss of 0.248. Overall, many non-linear relationships were observed, including threshold, j-shaped, and u-shaped. The results of this exploratory study suggest that applying machine learning to the nutritional epidemiology of CVD, particularly using big datasets, may help elucidate risks and improve predictive models. Given the limited application thus far, work such as this could lead to improvements in public health recommendations and policy related to dietary behaviours. / Thesis / Master of Public Health (MPH) / This work explores the potential for machine learning to improve the study of diet and disease. In chapter 2, opportunities are identified for big data to make diet easier to measure. Also, we highlight how machine learning could find new, complex relationships between diet and disease. In chapter 3, we apply a machine learning algorithm, called conditional inference forests, to a unique Canadian dataset to predict whether people developed strokes or heart attacks. This dataset included responses to a health survey conducted in 2004, where participants’ responses have been linked to administrative databases that record when people go to hospital or die up until 2017. Using these techniques, we identified aspects of nutrition that predicted disease, including caffeine, alcohol, and supplement-use. This work suggests that machine learning may be helpful in our attempts to understand the relationships between diet and health.

My dissertation is composed of an introductory chapter followed by three independent chapters focusing on two themes: health and retirement. The last chapter concludes. After the introductory chapter, the second chapter investigates whether self reported general stress is a mediator in the relationship between socio-economic status (SES) and health. I use a six-year long panel of the Canadian Survey of Labour and Income Dynamics and employ dynamic econometric modelling techniques to study men and women who are major income earners in their families. I find little evidence that general stress is a pathway from SES to health. While the results suggest a strong negative association between stress and health for both men and women, they provide little support to the hypothesis of a significant effect of income on stress, consistent with the direction of the SES-health gradient. The third chapter studies whether self-assessed health status (SAH) contains information about future mortality and morbidity, beyond the information that is contained in standard "observable" characteristics of individuals (including pre-existing diagnosed medical conditions). Using a ten-year span of the Canadian National Population Health Survey, we find evidence that SAH does contain private information for future mortality and morbidity. Moreover, the extra information in SAH is greater at older ages. Our results suggest that a shift from defined benefit to defined contribution pension arrangements may carry with it the cost of exacerbated adverse selection in the market for annuities, especially at older ages. That would make it more difficult for older individuals to insure longevity risk. The fourth chapter looks at whether differences in early retirement pathways are associated with differences in post-retirement outcomes of health, stress and dwelling tenure. I use a 5 ample of men from the Canadian Survey of Labour and Income Dynamics, years 1996 to 2004. I find that differences in pre-retirement health indicators (such as self-assessed health and disability), as pathways to early retirement, are likely to be associated with differences in post-retirement health and stress. In addition, the results suggest that "involuntary" retirees (men who may have retired because of health and/or health related coniitions) are more likely to experience worse post-retirement outcomes (in terms of health and stress) than men who retire "voluntarily". Retirement circumstances are found to have no statistically significant effect on dwelling tenure. / Thesis / Doctor of Philosophy (PhD)

No description available.

Utilizing the longitudinal component of the National Population Health Survey (NPHS) (1994/1995-2000/2001), designed to collect comprehensive information on the health status of the Canadian population and related socio-demographic information, differences in health status between immigrants and non-immigrants (i.e., native-born individuals) were explored. Specifically, the analysis investigated how chronic conditions influence the health of immigrants, the role of stress and mental health upon immigrant health status, and the influence and role of previously underrepresented variables such as age and arrival cohorts on foreign-born health status. The conceptual approach of this project draws upon a 'population health' perspective, which suggests that the most influential determinants of human health status are non-medical in nature, but rather can be identified as the social and economic characteristics of individuals. Analysis was completed through the use of ordinary least squares stepwise regression and logistic stepwise regression in association with descriptive stochastic methodologies. Analysis of the mental health and stress variables suggests that, contrary to what has been expressed in literature in the past, both immigrants and the native-born do not perceive stress, distress, or depression to be major problems or health concerns in their lives. Furthermore, the analysis indicated, as was expected, that older immigrants are at greater risk of developing more chronic conditions relative to younger groups, and that arrival cohorts, the period in which an immigrant entered the nation, do exert a considerable influence on the health status of the foreign-born. Surprisingly, this analysis indicates that the Healthy Immigrant Effect (HIE), which proposes that recent immigrants, regardless of country of birth, tend to be in better health than the Canadian-born population upon entering the nation, may be more apparent than real, especially when investigating mental health and stress conditions amongst the foreign-born. / Thesis / Master of Arts (MA)