In the present paper, we examine the effect of socioeconomic characteristics on the life expectancy of men and women in the Stockholm metropolitan area. Detailed individual data allows for a novel approach where observations can be displayed in high resolution. As is often the case with geographical data, the variables display high spatial autocorrelations, which imply that observations in proximity are more, or less, similar than what could be expected under the assumption of independent and identically distributed observations. Presence of spatial autocorrelation makes conventional regression models nonfunctional, and a model that accounts for this is therefore specified. In addition, a distance-band which reflects the distance and association between observations is determined. Lagrange Multiplier tests, AIC, log-likelihood, and the Schwarz criterion suggest that a spatial error model with a 300-meter distance band is appropriate for the data at hand. The findings suggest that: (1) Belonging to a minority group has the strongest effect on life expectancies and (2) the effect is negative for both genders, although the negative impact is stronger for males. Tests for spatial autocorrelation on the residuals suggest that the adopted spatial error model captures nearly all spatial autocorrelation in the data, compared to alternative models.

Masters of Commerce / The provision of health care in South Africa is undergoing major restructuring. The aim is to achieve substantial, visible and sustainable improvements to the efficiency and accessibility of primary healthcare (PHC) services for all South Africans. One of the country's most critical problems is the weak and fragmented public sector PHC system. The most critical problems contributing to this are the maldistribution of resources (financial, physical and human) between hospitals and the primary care system, and between rural and urban areas. The health sector, therefore, faces the challenge of a complete restructuring and transformation of the national health care delivery system and related institutions. Choices need to be made about which services to cut, which to streamline and where savings can be made. Ways need to be found to use ALL of South Africa's resources optimally. This process of restructuring would be facilitated by the availability of accurate information on resource utilisation in the health sector. This study estimates the difference in the cost of primary diabetes treatment at dayhospitals and a provincial hospital in the Western Cape in 1992/93. Health economics is in its infancy in South Africa and serious data limitations exist. This study is therefore a pioneering effort in many ways. An appropriate methodological framework in which to conduct the costing had to be developed. The South African health sector, health spending arid the cost of primary diabetes treatment at day-hospitals and the provincial hospital are reviewed. Theoretical perspectives of the health care market and the methodologies of cost analysis are discussed. The cost analysis method of study is chosen, and arguments are advanced for its suitability in the South African context. A simple method of calculating the direct costs to obtain the average cost is proposed for the purpose of the study. Direct costs consist of staff costs and other related costs, such as medical supplies, non-medical supplies, building operations, equipment etc. These costs are then used to calculate the average costs per diabetic patient at the day-hospitals and the provincial hospital. The average cost per diabetic patient at day-hospitals amounted to R18.76, while at the provincial hospital the cost was R59.60. https://

For decades, blacks have faced shorter life expectancy than their white counterparts. This persistent disparity has led to a gap in life expectancy between the two groups. Nationally, this gap has decreased over the last 40 years. However, this is not the case at the state-level as some states have experienced little or no improvement in the life expectancy gap. Such is the case in Wisconsin, where the life expectancy gap is the largest in the nation for males, and the gap actually has grown for females over the last two decades. This study seeks to examine this persistent gap in Wisconsin by looking at different causes of death and the ages when they contribute most to the gap. Additionally, this study will examine how the contribution of certain causes of death have changed over time, both between blacks and whites, and also within each group. Using 1999-2001 and 2009-2011 data from the National Center for Health Statistics, this study found that heart disease and malignant neoplasms (cancer) contributed most to the life expectancy gap between blacks and whites and also over time within each group. For females, diabetes and perinatal conditions were found to be top contributors to the black-white gap. Diabetes contributed most after the age of 50. For males, homicide was found to be a top contributor to the black-white gap, particularly among youth aged 15 to 29. Homicide among males frequently ranked near heart disease and malignant neoplasms as a leading contributor to the gap. These findings tell us that by reducing death rates from these causes at particular moments in the life course, the life expectancy gap between blacks and whites can be reduced. This study provides important evidence that health policy makers can use to address racial disparities in life expectancy.

This paper examined the nexus between health care expenditure and economic growth in Sub-Saharan Africa. It is widely acknowledged that health is a type of human capital and a critical factor in the process of economic growth. Health production, in turn, is a major determinant of health outcomes. While the former relationship has been extensively researched in developed countries, very few studies have attempted to investigate this relationship in developing countries, particularly Sub-Saharan Africa (SSA). Furthermore, very few studies have been conducted in SSA to investigate the relationship between health determinants, health outcomes, and economic growth. This study takes on the challenge of investigating this three-way relationship for SSA countries. Different variables like population, saving and foreign direct investment were found to be statistically significant determinants of economic growth using the Arellano-Bond Dynamic GMM technique for 26 SSA countries, while food availability were found to be significant determinants of life expectancy. On the other hand, none of the health indicators are significant determinants of economic growth in the region, implying that health outcomes must be improved in order to have a significant impact on growth. The findings should prompt immediate policy changes to harmful indicators in order to better stimulate health-led economic growth in SSA.

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Several substantive observations formed the basis for this research. First, the observation of stagnating life expectancy in the United States over the first two decades of the 21st century, representing a dubious form of American exceptionalism. Second, evidence suggesting that novel measures of biological aging might provide allow for early evaluation of population-level health trajectories, based on direct observation of health status in still-living people. Third, the opportunity to apply these measures for study of population-level phenomena, using methods routinely used in the fields of sociology, demography, and economics. This dissertation represents a proof-of-concept work to support the application of biological aging measures to population health surveillance. In Chapter 2, I conduct a systematic literature review of novel measures and approaches to the quantification of population aging published since 2000, and identify 3 major classes of novel population aging measures. Biological-aging measures can be understood as a specific application of Sanderson and Scherbov’s α-ages approach, which indexes “true age” to the distribution of some aging-related characteristic in a reference sample. Relative to other novel measures and approaches, however, biological-aging algorithms hold particular promise in their ability to provide direct measures of pre-clinical, aging-related health risk across the entire adult age range of a population. In chapters 3 and 4, I apply published biological aging algorithms to blood-chemistry and organ-test data collected by the National Health and Nutrition Examination Surveys (NHANES) to test whether the U.S. population has grown biologically older over the past two decades, as some interpretations of life expectancy data would suggest, and to evaluate the extent to which selected social and environmental exposures might explain these trends. Formal age-period-cohort analysis revealed consistent period increases in biological aging from 1999-2018; while population aging slowed after the training cohort was measured in NHANES III (1988-1994), aging trajectories have reverted towards early-1990s levels since the turn of the century. Limited evidence of cohort effects was observed, with findings consistent regardless of age, race, and sex – although racial disparities in biological aging persisted over the entire study period. Kitagawa-Blinder-Oaxaca decomposition analysis of four candidate exposures (i.e., BMI, smoking status, blood lead, and urinary polycyclic aromatic hydrocarbon levels) suggested that changes in the distribution of behavioral and environmental risk factors accounted for a substantial proportion of observed period trends and/or racial disparities in biological aging over the first two decades of the 21st century. Broadly, these results suggest that measures of biological aging can provide earlier and more precise readouts of population health trajectories and their drivers, ultimately informing next-generation public health efforts to promote healthy aging and aging health equity.

Introdução: No contexto do envelhecimento populacional, uma questão fundamental é avaliar se as estratégias de prevenção de doenças crônicas poderiam contribuir para o aumento dos anos vividos em boas condições de saúde, pela população idosa. Objetivo: Avaliar se a eliminação de determinadas doenças crônicas é capaz de levar à compressão da morbidade em indivíduos idosos. Métodos: Estudo transversal analítico, de base populacional, utilizando dados oficiais secundários para o Município de São Paulo, em 2000, e dados obtidos a partir do estudo SABE. O método de Sullivan foi utilizado para o cálculo de expectativas de vida livre de incapacidade (E.V.L.I.). O impacto da eliminação de uma doença na prevalência de incapacidade foi estimado com um modelo de regressão logística múltipla. Tábuas de vida de eliminação de causas foram utilizadas para calcular as probabilidades de morte com a eliminação de doenças. O efeito da eliminação das doenças crônicas foi avaliado, considerando a teoria de riscos competitivos e a abordagem proposta por Nusselder e colaboradores. Resultados: Os maiores ganhos em E.V.L.I., com a eliminação de doenças crônicas, ocorreram no sexo feminino, levando a um processo de compressão absoluta da morbidade. Nos indivíduos de idade mais avançada, os ganhos em E.V.L.I., ocorreram em função de um processo de compressão relativa da morbidade. Nos homens com idade de 75 anos, todas as doenças estudadas, com exceção da doença cardíaca e da hipertensão arterial sistêmica, levaram a um processo de expansão absoluta da morbidade, mas simultaneamente a um processo de compressão relativa da morbidade, ao serem eliminadas. A doença cardíaca apresentou-se como aquela que mais promoveria a compressão da morbidade, caso fosse eliminada, em ambos os sexos. Conclusão: A eliminação de doenças crônicas na população idosa poderia levar a uma compressão da morbidade em homens e mulheres, tanto na idade de 60 anos, quanto na de 75 anos / Introduction: In the context of the aging process, a key issue is to assess whether strategies to prevent chronic diseases may contribute to the increase in years lived in good health among elderly individuals. Objective: To evaluate whether elimination of certain chronic diseases can lead to the compression of morbidity, in the elderly. Methods: Analytical cross-sectional survey, based on official data for the city of São Paulo, in 2000, and data obtained from the SABE study. Sullivans method was used for the calculation of disability-free life expectancy (DFLE). Cause-deleted disability prevalence was estimated using multiple logistic regression model. Cause-deleted probabilities of dying were derived with the cause-elimination life-table technique, considering the independence of the causes of based on the approach proposed by Nusselder and co-workers. Results: The greatest gains in DFLE, with the elimination of chronic diseases, occurred in women, leading to a process of absolute compression of morbidity. Among individuals of a more advanced age, gains in DFLE occurred due to a relative compression of morbidity process. Among men aged 75 years, all diseases eliminated, except heart disease and hypertension, led to a process of absolute expansion of morbidity, but simultaneously, to a relative compression of morbidity. If eliminated, heart disease was the condition that would most lead to the compression of morbidity in both genders. Conclusion: The elimination of chronic diseases in the elderly population could lead to the compression of morbidity in men and women at both 60 years of age and in 75 years of age or older