The challenge in estimating mortality, both at national and sub-national levels, in developing countries such as South Africa is that neither of the death data sources (vital registration and census) are one hundred percent complete, that is, vital registration data is prone to incompleteness and deaths reported by household are subject to over- or under-reporting which may vary by age. Also, apart from issues with data sources, there is no method that estimates mortality accurately at subnational level and the methods for estimating the level of completeness of reporting of deaths cannot be applied at subnational level (due to issues with migration). Thus, measuring mortality rates at subnational level is a challenge. This research seeks to employ a method used by Dorrington, Moultrie and Timæus (2004) that makes use of both data sources in combination so as to overcome the weakness and makes use of the strength of each data source. To estimate the level of completeness in the year prior to the 2011 Census (to correct the number of deaths registered), first, the Death Distribution Methods (Synthetic Extinct Generations +delta and General Growth Balance method) are used to estimate the level of completeness of the vital registration deaths for the intercensal period 2001-2011 by population group. Thereafter, the level of completeness for each of the years in the intercensal period is estimated by fitting a logistic curve to the level of completeness for the intercensal period of 1996-2001 and 2001-2011 (derived by both Chinogurei (2017) and Richman (2017)). Thus, the number of deaths registered in the year prior to the 2011 census are then corrected for either under- or over-reporting using the estimates of completeness to obtain the true number of deaths by population group and age group for each sex. The corrected true numbers of registered deaths are then used to determine the age-specific correction factors by population group for correcting the household reported deaths at district level and thereafter estimates of mortality at district level are determined. Comparison of estimates derived in this study to estimates by other studies indicated that the method produces plausible estimates at district level, thus, findings in this research strengthens the reasonability of the method.

Includes abstract. / Includes bibliographical references (leaves 59-61). / This study develops the key components of the Synthetic Extinct Generations (SEG+delta) method in trying to answer research questions raised by Dorrington and Timeaus (2008) and in the process investigates the different sets of combinations of the key components of the SEG+delta method when applied to the 23 error scenarios used by Hill and Choi (2004). In addition, the study determines the pattern of estimates of 4sfi15 per set of combinations, the combination that results in the best estimate of 45q15 per scenario and per combination of scenarios and the best combination that result in best estimate of 4sfi15 across all 23 error scenarios. The current study assesses the errors in age reported in censuses by comparing the weighted average of the ages of seven countries in the sub-Saharan African region to the age error pattern used by Hill and Choi (2004). These findings suggest that there is no significant difference (except of the zig-zag pattern in age errors at older ages in the Hill and Choi scenario) in general pattern of age errors of the sub-Saharan African region and the pattern used by Hill and Choi (2004).

Includes bibliographical references (leaves 132-142). / This research examines child mortality risk associated with short preceding birth intervals in Mozambique in quinquennial periods between 1978 to 1998 using data from the 1997 and 2003 DHS. A log rate model for piecewise constant rates is applied. The piecewise hazard function assumes a constant hazard rate of child mortality in each 6 month category of the preceding birth interval. The negative binomial regression model is applied to account for the overdispersion present in the Poisson model.

Includes abstract. / Includes bibliographical references. / The traditional models used in population projections rely on the net migration method.The ASSA2008 AIDS and Demographic model is one such model. In this research, the nine provinces and the four population groups are aggregated to give rise to three regions. Using STATA12, the directional migration tables for the years covering the period 1996-2007 between the three regions, by age and sex, based on a 10% sample of the 2001 Census and a 2.5% sample of the 2007 Community Survey, are produced. Using MATLAB 2011a with built-in Levenberg-Marquardt algorithm with nonlinear least squares methods, Rogers-Castro multi-exponential age schedules are fitted to the census/survey migration data in order to obtain parameters used to estimate migration rates in the model for the period 1996-2007. After 2007, migration rates areextrapolated roughly linearly, assuming that migration will trend towards zero over a fixed number of years. The multi-regional adaptation of the ASSA model is tested and found to work, with a minor re-calibration to the HIV data for 2008. The projected regional population age structure and size implied by the model for 1996-2025 are consistent with the same estimates implied by the net migration model, and so are the projected net migration rates per 1,000. The level of the migration rates assumed in the multi-regional model accounts for an average of 89% of the change in the estimates of the population size relative to those generated by the net migration model, and the use of multi-regional modelling itself accounts for 11% of these changes. The proportions of the changes attributable to the level of migration rates assumed in the multi-regional model, and the use of the multi-regional modelling, show that the choice of the method by which population projections are done is important. Finally, the three-region model can be extended to a nine-province model that recognises that each province has unique demographic dynamics, but the construction of such a model requires a significant amount of extra work due to its size and complexity.

Includes bibliographical references (leaves 73-74). / The orphanhood method of estimating adult mortality is widely used in developing countries. The method is subject to a number of assumptions, some of which are violated when a generalized high-prevalence HIV epidemic is present. Non-independence of the mortality of children and mothers, relationships between HIV infection and fertility, and changes in age-specific mortality result in biases that affect the accuracy of the method. An earlier study has examined some of these sources of error, and proposed adjustments to enable continued use of the method. This earlier research, however, uses data from populations with lower HIV prevalence rates than are currently being experienced in much of southern Africa, and is based on specific assumptions about HIV and its effects on mortality and fertility. The effects of HIV on the method are investigated in this research using mathematical modelling of the effects on Black South African females - a population with high HIV prevalence. More is now known about HIV and its effects on mortality and fertility, and these effects are explicitly reflected in the ASSA2002 model which provides much of the data for this research. The research compares the simulated survival of various cohorts of women: those aged 25 in a certain year, women (with an age profile identical to that of mothers), mothers, and mothers as reported by their children. In this way the various sources of error are explicitly identified and the errors quantified. The timing, magnitude, and combined effects of the errors are studied in relation to the emergence and spread of HIV, indicating when the errors might be expected to be large enough to invalidate the method. Errors that bias the outcomes of the orphanhood method take a number of years to develop after HIV starts spreading. Substantial biases in reported survival emerge between 20 and 35 years after the start of an HIV epidemic, in a high prevalence setting. These errors are reduced by the use of antiretroviral and prevention of mother-to-child transmission, but biases remain large enough to invalidate outcomes when the unadjusted method is applied in most southern African countries. An adjusted method has been proposed which substantially reduces error, except when adjusting survival reported by the two youngest age groups. This adjusted method can be applied, but further research to identify revised adjustments would further improve the accuracy of the method.

No description available.

Reducing maternal mortality is number five in the United Nations Millennium Development Goals. Preeclampsia is a particular form of hypertension during the pregnancy period that can cause maternal deaths. In Colombia, is the first cause of morbidity and maternal mortality (Serrano-Díaz & Díaz-Martinez 2005). This study attempts to determine how the socio-demographic causes that are involved in the development in order to contribute to the description of the environmental causes, more specifically to determine if socio-demographic factors influence the development of the disease. This study is based on data from two sources especially, one from the National Department of Statistics (DANE) or Statistics Colombia to give a better contextualization about the rates and tendencies of the Maternal Mortality Ratio (MMR) on ICD-10 codes related with obstetric risks. The other called GenPE project (Genetics and Preeclampsia), which has been developed in Colombia and it has had a great impact on the genetic factors but contains socio-demographic information. For this purpose some statistical robustness checks as chi-square tests, logistic regression and multilevel models to determine which is the way to conceptualize the problem. The findings stress on more prenatal care early in the pregnancy (p<0.01) as well as the intensity or number of controls (p<0.01) to decrease the risk of preeclampsia. Besides, familiar background regarding hypertensive disorders is still important in the development of the disease (p<0.01), which gives information as an environmental and genetic contribution. / GenPE proyect in genetics and preeclampsia

In recent decades, the influence of negative health behaviors on physical health and mortality has garnered a great deal of attention (Institute of Medicine 2001). Research suggests that these negative health behaviors, such as smoking, binge drinking, and lack of exercise, are leading preventable causes of morbidity and early mortality in the U.S. (Institute of Medicine 2001). Yet, little research has explored whether there are differential impacts of risky health behaviors on health outcomes by social groups such as race/ethnicity. Using the National Health and Nutrition Examination Survey, 2003-2008, linked with the National Death Index, My dissertation focuses on filling existing gaps in the literature by exploring the associations between health behaviors, physiological distress, and mortality and how these associations vary by race and ethnicity in the U.S. I examine 1) how these relationships (health behaviors, physiological dysregulation, death) vary by race/ethnicity; 2) the role health behaviors play in the relationship between physiological dysregulation and mortality as well as how this role varies by race/ethnicity and; 3) investigate how the individual items (biomarkers) that make up the physiological dysregulation measure can be grouped by behaviors and race/ethnicity in a way that further elucidates the previously mentioned relationships. First, negative binomial regressions show a differential relationship between negative health behaviors and physiological dysregulation by race/ethnicity. Namely, Whites experience a significantly higher detrimental impact of negative health behaviors on their physiological dysregulation than do Blacks, and to a lesser extent Mexican Americans. Yet, running Cox Proportional Hazards models on the risk of mortality reveals no racial/ethnic differentials in the impact of health behaviors on mortality. The latent class analysis of the biomarker indicators is then used to further parse out why there is a difference in the racial/ethnic variations in the relationship between poor health behaviors and physiological distress but not mortality. These findings suggest that respondents' biomarkers do cluster into healthy, cardiovascular, metabolic, and inflammatory groups. The cardiovascular group is defined by higher proportion of minorities, particularly Blacks, as well as a stronger relationship with negative health behaviors. The group is also the most likely to experience mortality. The already high likelihood of minorities having high cardiovascular risk may explain why there is a weaker relationship between physiological dysregulation and risky health behaviors. This research could extend information on the consequences of risky health behaviors as well as inform public policy on the importance of considering social differentials when addressing health behavior risk. / A Dissertation submitted to the Department of Sociology in partial fulfillment of the requirements for the degree of Doctor of Philosophy. / Fall Semester 2015. / July 14, 2015. / Includes bibliographical references. / Miles G. Taylor, Professor Directing Dissertation; Dan McGee, University Representative; Isaac Eberstein, Committee Member; Amy Burdette, Committee Member.

The overall objective of this dissertation is to develop and empirically assess an integrated and systematic theoretical framework to illuminate the effects of polygyny on infant mortality. Mosley and Chen's analytic model was integrated with that of Nam, Eberstein, Deeb and Terrie to provide a unique framework for guiding the application of multi-equation structural models to data from the Ghana Demographic and Health Surveys (GDHS). / The pertinent question examined in this study relates to the role marriage form plays in infant mortality. The key point is that if polygyny is beneficial as expected from the environmental theory, for example, then comparable infants should have a lower probability of dying in polygynous than in monogamous unions. This analysis tests the relative effects and the mechanisms through which polygyny affects infant survival. Another dimension studied is the mediating role which polygyny plays in the link between background factors and infant survival. / The study is carried out using a sample of infants born in the five years preceding the 1988 Ghana Demographic and Health Survey (GDHS). Two statistical models are used, a structural equation method and simulations. A causal model is constructed in which maternal education, maternal occupation, place of residence, ethnicity, polygyny, age at first marriage, preceding birth interval, prenatal care, breastfeeding, and type of toilet facility in the household are examined as determinants of infant mortality/survival. Socioeconomic variables are considered as exogenous with polygyny, age at first marriage, preceding birth interval, prenatal care, breastfeeding, and toilet facility as endogenous in the model. The model is tested by maximum likelihood method and logistic regression. / The findings indicate that maternal education, occupation, rural residence and ethnicity positively influence polygyny, which in turn affects infant survival. Polygyny is found to be an important mediating factor between background characteristics and the proximate determinants in affecting infant survival. Traditional care, unsupplemented breastfeeding, and the presence of sanitary toilet facilities are also found to affect infant survival. The results from both the logistic regression and maximum likelihood procedure indicate that the effect of the proximate determinants are in the expected direction. These findings highlight the relevance of family structure (polygyny) as an intervening factor in accounting for infant survival. / In conclusion there is evidence to suggest that maternal socioeconomic characteristics are associated with not only polygyny but also maternal behavior, environmental contamination and infant survival. Overall, polygyny appears to mediate the effect of socioeconomic variables and proximate determinants on infant survival. / In terms of policy implication it is suggested that mothers be given basic techniques regarding disease prevention. Above all, consideration must be given to family structure in planning and implementing programs with respect to birthspacing, prenatal care and breastfeeding. / Source: Dissertation Abstracts International, Volume: 54-07, Section: A, page: 2747. / Major Professor: Isaac W. Eberstein. / Thesis (Ph.D.)--The Florida State University, 1993.

Mortality in the terminal age intervals may increase as societal conditions improve, because increases in death rates for chronic conditions may offset declines in death rates for acute diseases. We examine mortality at ages fifty and above in female populations of thirty-eight countries. We control for variation in quality of the mortality data, and find that economic development, economic distributional inequality, and primary health care have independent cross-national effects on cause of death structures. These effects are not uniform across the age intervals of interest. As improvements occur in level of living and health care, age-specific death rates decline except at the oldest ages, at which point they may increase. These results are interpreted in terms of their relevance for mortality research, theory, and policy. / Source: Dissertation Abstracts International, Volume: 45-01, Section: A, page: 0309. / Thesis (Ph.D.)--The Florida State University, 1983.