Thesis (Ph. D.)--University of Wisconsin--Madison, 1980. / Typescript. Vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 96-98).

Thesis--Wisconsin. / Vita. Includes bibliographical references (leaves 138-140).

VILNIAUS MIESTO GYVENTOJŲ SVEIKO GYVENIMO TRUKMĖ Tyrimo tikslas: Įvertinti Vilniaus miesto gyventojų sveiko gyvenimo trukmę 2006 metais. Tyrimo uždaviniai: 1. Sullivano metodu apskaičiuoti Vilniaus miesto gyventojų sveiko gyvenimo trukmę pagal amžių, lytį, remiantis išgyvenamumo (mirtingumo) lentelėmis ir subjektyviu savo sveikatos vertinimu. 2. Išanalizuoti gautus rezultatus pagal amžiaus grupes ir lytį. 3. Palyginti Vilniaus miesto gyventojų sveiko gyvenimo trukmę su Lietuvos gyventojų ir kitų šalių gyventojų sveiko gyvenimo trukme. 4. Palyginti Vilniaus miesto 65 metų ir vyresnių gyventojų sveiko gyvenimo trukmę su 2001 metų 65 metų ir vyresnių Vilniaus rajono gyventojų sveiko gyvenimo trukme. Tyrimo metodika ir apimtis: Vilniaus miesto gyventojų sveiko gyvenimo trukmė apskaičiuota Sullivan‘o metodu, apjungiančio sergamumo ir mirtingumo rodiklius į vieną rodiklį. Sveiko gyvenimo trukmės apskaičiavimui panaudotos 2006 metų Vilniaus miesto gyventojų išgyvenamumo (mirtingumo) lentelės. Duomenys apie subjektyvų sveikatos vertinimą gauti iš Lietuvos Statistikos departamento atlikto tyrimo. Rezultatai ir išvados. Nustatyta, kad 2006 metais Vilniaus miesto vyrų vidutinė gyvenimo trukmė 15-19 metų amžiaus grupėje – 52,46 metai, VSGT – 46,64 metai, VGT-VSGT – 5,82 metai, procentinis VSGT/VGT – 88,91. Atitinkamo amžiaus moterų: VGT – 63,51 metai, VSGT – 52,74 metai, VTGT-VSGT – 10,77 metai, procentinis VSGT/VGT santykis – 83,04. Moterų vidutinė gyvenimo trukmė visose amžiaus grupėse... [toliau žr. visą tekstą] / HEALTHY LIFE EXPECTANCY OF VILNIUS CITY POPULATION The aim of the study was to evaluate healthy life expectancy of Vilnius city population in 2006 years. The tasks of the study: 1. To calculate healthy life expectancy by age groups and sex of Vilnius city population according to Sullivan‘s method, using life tables and data of self-perceived health. 2. To analyze the final rezults by gender and age groups. 3. To compare healthy life expectancy of Vilnius city population with healthy life expectancy of Lithuanian population and other countries. 4. To compare healthy life expectancy of people aged 65 and more years of Vilnius city population in 2006 with healthy life expectancy of people aged 65 and more years of Vilnius area in 2001 years. The methods of study: Healthy life expectancy of Vilnius city were calculated by Sullivan method, which combines information on mortality and morbidity into one index. The data about Vilnius city population were availible from the Lithuania Department of Statistics, life tables for 2006 were created and life expectancy estimated. The data on self – perceived health of the Vilnius city population were acquired from the Lithuania Department of Statistics. The results and conclusions: According our data, 46,64 of the 52,46 years that male at age group 15 – 19 years may expect to live, on avarage, will be healthy in 2006 years. For female at the same age group 52,74 of 63,51 years may expect to live on avarage will be healthy. Life expectancy of... [to full text]

A conceptual model which relates demographic, social, and economic variables to immigrant life expectancy is developed. The model accounts for the impacts of stressors and coping mechanisms involved in the adaptation of immigrants to new environments. From the conceptual model a simplified linear model was derived. The model hypothesizes that the life expectancy change for immigrants is explained by altered living conditions ('Conditions'), the support structure of an immigrant group ('Support'), the brought and acquired skills of an immigrant group ('Skills'), and the length of residence in the destination ('Time'). The model was tested with Canadian data for 1941. Empirical indices of the dimensions Support, Skills, and Time were derived from the factor analysis of the characteristics of the immigrant groups. The model was also tested in part with Australian data for 1911-21 and 1921-33. Only the variable Conditions was included in the model since other data were not available. The parameters of the equations were obtained through regression techniques. Separate analyses were conducted for males and females. A comparison was also made of the life expectancies of immigrants in Canada with those of immigrants in Australia. The variable Conditions contributed significantly in accounting for the life expectancy change for male and female immigrants in Australia and for male immigrants in Canada. For female immigrants in Canada Support was the only variable to influence life expectancy change. Support also determined, though to a lesser degree than Conditions, life expectancy change for male immigrants in Canada. The finding that the support structure influences life expectancy change, especially for females, has important policy implications. It points to the benefits of a policy of cultural pluralism as opposed to one of rapid assimilation. The significant role of the destination conditions indicates that an extensive exploration of the differences in the environmental, technological, political, social, and cultural systems of the origin and destination countries has potential for defining specific factors contributing to disease prevalence and mortality. / Graduate and Postdoctoral Studies / Graduate

Life expectancy in countries of Central and Eastern Europe (CCEE) is substantially shorter than in Western Europe, and similar divide exists in self-rated health. The project described in this thesis was set up to study the effects of socio-economic factors (such as material deprivation, education and inequalities) and psychosocial factors (perceived control, psychosocial work environment) on self-rated health (a predictor of mortality in prospective studies). Cross-sectional surveys were conducted in seven CCEE: Russia, Lithuania, Latvia, Estonia, Poland, Czech Republic and Hungary. Data were collected by interviews in randomly selected national samples in all seven countries (total 7,599 subjects), and by questionnaires in random community samples in 4 countries (total 6,642 subjects). The data included socio-economic and psychosocial factors, self-rated health (SRH) and behavioural risk factors. Overall, 17% of men and 23% of women rated their health as worse than average. In the national samples, perceived control, material deprivation and education were strongly related to poor SRH. In the pooled data, adjusted odds ratio (OR) of poor health for 1 standard deviation (SD) increase in perceived control was 0.59 (95% Cl 0.54-0.63). The OR for 1 SD increase in the material deprivation score was 1.35 (95% Cl 1.26-1.46). The ORs for vocational, secondary and university education, compared with primary education, were 0.75,0.58 and 0.53, respectively. We also examined the ecological effects of income inequality; the OR for the most versus the least unequal populations (using the Gini coefficient of income inequality) was 1.88 (95% Cl 1.55-2.28). In multivariate analyses, however, the effect of inequality was eliminated by adjustment for material deprivation and perceived control. In the community samples, the results were similar. Among psychosocial factors at work, the effort-reward imbalance appeared to be the strongest predictor of self-rated health; work variety was also a predictor of self-rated health. Job strain was not associated with SRH. Our results suggest that (a) the prevalence of poor SRH in CCEE is high, and (b) socioeconomic and psychosocial factors are strongly related to self-rated health in these populations. The gradients were present in all populations, and were of the same direction and similar magnitude as in the West. Prospective studies are needed to address the problems of temporality and reporting bias, which are the major problems of these results.

No description available.

Background: Life expectancy (LE) estimation is an important part of both screening and treatment decision-making for potentially curable prostate cancer. Clinicians’ estimation of patient life expectancy is typically made using population-based life tables and intuition and it is often inaccurate. This study explores methods to improve LE prediction by formally considering patient co-morbid illness status, in addition to age, in the development of a LE prediction tool. Methods: We conducted a population-based retrospective cohort study of patients from the Ontario Cancer Registry who were curative treatment candidates, identified between 1990-1998. We analyzed data on three sub-populations of this cohort, and we used LE estimates from the Ontario Life Tables. Each model utilized Cox proportional hazards analysis, and/or the declining exponential approximation of LE, to estimate the survival experience of potential curative treatment candidates, including the impact due to both age and co-morbid illness status. We developed five separate models, tested them using a random subset of the cohort study sample, and compared their predictive accuracy by measuring both discriminative ability and calibration to determine the ‘best’ model. We also conducted a supplementary analysis using logistic regression to develop a model to predict the probability of 10-year survival. Results: The ‘best’ of our models demonstrated a c-index of 0.65 and very good calibration. Further analysis revealed that our ‘best’ model violated the Cox PH assumption for age and it’s predictions consistently over-estimated observed LE. Supplementary analysis of the logistic regression prediction model demonstrated a c-index of 0.70. Conclusions: Our exploration of methods to predict LE resulted in modest predictive accuracy. However, based on the results of the logistic regression model, we conclude that the results of our LE prediction models are reasonable, and obtaining a high level of predictive accuracy may not be possible given just age and co-morbidities as predictors. Further studies should continue to explore these and other methods for LE prediction. External validation of the ‘best’ model from the current study is required before the model and its accompanying LE reference tables can be recommended for use in a clinical setting for screening or treatment decision-making. / Thesis (Master, Community Health & Epidemiology) -- Queen's University, 2011-04-07 19:11:34.216

Albania was noteworthy, not just for the isolationist policy of its government, or its domestic rigid policies applied to Europe's poorest country, but because of its high life expectancy at birth. At the end of the eighties, life expectancy at birth passed the boundary of seventy, although the country's GDP per capita was $2500 in 1990, the lowest in Europe (Madison 1995).This puzzled scholars, who either doubted the success of Albania, or because of the lack of firm information, speculated with different explanations (Watson, 1995). This research was initiated by this controversy in trying to first, estimate the scale of Albania's success in improving life expectancy and document the mortality transition in Albania during the period 1950-1990. It also looks at the social, economic and political factors behind the success of improving life expectancy at birth from 51 to 71 years in a relatively short period of 40 years. The research attempts to explain why the Albanian pattern of mortality, with very high infant and child mortality and very low adult mortality, is so different from that of other East European countries, which had the same social and economic backgrounds. The analysis concludes that the life style factors are the most likely factors in explaining the controversial mortality pattern of Albania. The research uses a new set of complete data, obtained from formerly-closed Albanian State Archives, which were made available only after 1994. It is the first time that the cause specific data are used to analyse the mortality transition in Albania. The research starts with a description of country's cultural and historical background. It continues with the political, social and economic transition during the communist rule 1945-1990, which are of particular importance in understanding the demographic regime in general, and the mortality transition in particular (Caldwell, 1986). The research continues with a detailed analysis of the availability and quality of mortality data. The analysis of mortality trends and patterns during this period confirms the success of Albania in achieving high life expectancy at birth by the end of eighties. It also shows that this was achieved by very low adult mortality, and relatively high infant and child mortality. The later analysis shows that this finding is related to the cause specific pattern of mortality, as well as regional differences within the country. The research ends with an international comparison of mortality trends and patterns in Albania, in the context of whether the Albanian success was part of the experience of countries that had "a good health at low cost" (Caldwell, 1986), or if the Albanian way is another route to low mortality.

Thesis--Auburn University, 2008. / Abstract. Vita. Includes bibliographical references (p. 60-75).

Thesis (Ph. D.)--University of Hawaii at Manoa, 2004. / Includes bibliographical references (leaves 186-194).