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This paper estimates child mortality by race and nativity for the U.S. as a whole and the Death Registration Area based on the public use micro- samples of the 1900 and 1910 censuses. We compare indirect estimates to mortality rates and parameters based on published census and vital statistics data. The censuses of 1900 and 1910 both asked adult women about children ever born and children surviving which, when tabulated by age or marriage duration can be used to estimate probabilities of their children dying at various ages up to 25. Data on children ever born for 1910 were partially tabulated and published in conjunction with the 1940 federal census but the information on children surviving was never tabulated and published; nor was information from 1900. The public use micro samples of the 1900 census permit the application of these well-established indirect methods. This paper applies the basic indirect age and marriage duration methods, and a method using the backward projection of age distribution of surviving own-children of younger adult women. The results match well to life tables calculated from aggregaed census and vital statistics for the total white, native white and foreign-born white populations. The results are less definite for African-Americans but it seems that mortality was substantialy better than indicated by the widely cited Glover life tables for 1900/02, 1901/10, and 1909/11 for the original the original Death Registration Area of 1900. Overall, however, it appears that calculated life tables from published vital statistics and census popula- tions for the Death Registration Areas of 1900 and 1910 describe the remainder of the population relatively well.
This paper illustrates the application of indirect techniques of fertility and mortality estimation to historical census data, both in published form and as micro census samples derived from the original enumerators' manuscripts. There are many instances in which census data exist but adequate vital registration data do not, such as in the United States prior to 1933, when the Birth and Death Registration Areas finally covered the entire nation. Since the United States has taken decennial censuses since 1790, and since all the original population schedules except those for 1890 have been preserved, it is possible to apply these indirect methods. For example, the censuses of 1900 and 1910 asked questions on children ever born, children surviving, and duration of current marriage, but this information was never tabulated or used for 1900 and only partly tabulated for 1910. The Public Use Samples of the 1900 and 1910 censuses make possible the utilization of those data to estimate levels, differentials, and even recent trends in childhood mortality. Application of own-children methods to samples of the censuses since 1850 permits estimation of age-specific overall and marital fertility rates. Finally, the use of the 1900 Public Use Sample in conjunction with published data on parity from the 1910 census (or tabulations from the 1910 Public Use Sample) allows application of the two-census, parity increment method of birth rate estimation.
Child mortality is an important metric used in quantifying and monitoring the health of a population's children. Moreover, child mortality can be a key indicator of the overall health of a population, and is often used to quantify mortality at other ages. Over the past several decades, there have been huge global reductions in child mortality. However, child mortality remains large in many low and middle income countries (LMICs). The United Nations' Sustainable Development Goals (SDGs) call for a reduction of child mortality in the period 2015--2030. In particular, SDG 3.2 continues the global initiative to improve chid mortality outcomes by calling for an end to preventable child deaths and reaching a target under-five mortality rate (U5MR) of 25 deaths before age 5 per 1000 births and 12 deaths per 1000 births in the first month of life by the year 2030. Many methods exist for estimation of national child mortality measures, but there is a growing desire for more and better methods for subnational estimation of child mortality. Improved methods for subnational estimation of U5MR can allow for a better understanding of the geographic differences of trends in U5MR and more targeted intervention for child mortality reduction. Though there are many ways to think about geographic variability within a country, in this thesis we focus on the administrative divisions of a country that have political and infrastructural meaning. The national level of a country is referred to as Admin-0, the coarsest subnational administrative division is referred to as Admin-1, and the next coarsest as Admin-2. Many sources of child mortality data collect information for which Admin-1 estimates are reasonable, but this leads to small sample sizes at the Admin-2 level. The focus of this thesis is on subnational child mortality estimation at the Admin-2 level. In this thesis, we provide a review of demographic and statistical methods for age-specific period child mortality, synthesize notation across fields, and develop two methods for subnational estimation of U5MR at the Admin-2 data in LMICs. We make use of child mortality data from household surveys throughout this thesis and discuss in detail how an individual's mortality information is used in various existing demographic and statistical methods for mortality estimation. The two methods we develop for subnational child mortality estimation in LMICs at the Admin-2 level take different approaches to accounting for the method of data collection in the household surveys and one method incorporates census data. We apply the method developed to incorporate census data separately to the countries of Kenya and Malawi. We find mixed evidence of improvements in estimation with the incorporation of census data, and note the method's shortcomings when small sample sizes result in many Admin-2 areas with no observed deaths. The limitations of this method, motivate the need for a method that can be applied more broadly to countries with sparser coverage of household survey data. We develop a method and reproducible, replicable pipeline for data acquisition, cleaning, estimation, and visualization. We apply this method to Admin-1 and Admin-2 levels in 22 LMICs, fitting separate models for each country and administrative division. The country-specific modeling and steps in the pipeline allow us to address the unique context of child mortality in each country if the generic base model is inappropriate, such as in countries with generalized HIV/AIDs epidemics, the genocide events in Rwanda, and Cyclone Nargis in Myanmar. The estimates for 22 LMICs have been published in collaboration with UNICEF and the UN Inter-agency Group for Child Mortality Estimation, have undergone review in consultations with country representatives, and are available at \url{https://childmortality.org}. This thesis improves on the current understanding in the processing and use of child mortality data in the literature and develops two new methods for estimation of child mortality in LMICs at the Admin-2 level. In particular, the development of a clearly-defined and replicable pipeline that allows for easy adaptation to address the unique mortality estimation needs of individual countries fills a previous gap in existing methodology. However, there are areas for future research and methodological improvement. Throughout the thesis we make note of ongoing work to improve existing aspects of the developed methods and make clear the issues that remain unaddressed.
Current efforts to measure child mortality for municipalities in Brazil are hampered by the relative rarity of child deaths, which often results in unstable and unreliable estimates. As a result, it is not possible to accurately assess true levels of child mortality for many areas, hindering efforts towards constructing and implementing effective policy initiatives for the reduction of child mortality. However, with a spatial smoothing process based upon Bayesian Statistics it is possible to "borrow" information from neighboring areas in order to generate more stable and accurate estimates of mortality in smaller areas. The objective of this study is to use this spatial smoothing process to derive estimates of child mortality at the level of the municipality in Brazil. Using data from the 2000 Brazil Census, I derive both Bayesian and non-Bayesian estimates of mortality for each municipality. In comparing the smoothed and raw estimates of this parameter, I find that the Bayesian estimates yield a clearer spatial pattern of child mortality with smaller variances in less populated municipalities, thus, more accurately reflecting the true mortality situation of those municipalities. These estimates can then be used, ultimately, to lead to more effective policies and health initiatives in the fight for the reduction of child mortality in Brazil.
The last 35 years or so have witnessed a dramatic shift in the demography of many developing countries. Before 1960, there were substantial improvements in life expectancy, but fertility declines were very rare. Few people used modern contraceptives, and couples had large families. Since 1960, however, fertility rates have fallen in virtually every major geographic region of the world, for almost all political, social, and economic groups. What factors are responsible for the sharp decline in fertility? What role do child survival programs or family programs play in fertility declines? Casual observation suggests that a decline in infant and child mortality is the most important cause, but there is surprisingly little hard evidence for this conclusion. The papers in this volume explore the theoretical, methodological, and empirical dimensions of the fertility-mortality relationship. It includes several detailed case studies based on contemporary data from developing countries and on historical data from Europe and the United States.