Indirect methods of mortality and fertility estimation: new techniques for new realities

Armed conflict and famine often have large-scale population
consequences. Yet the measurement of the mortality consequences of
such crises is challenging, given that accurate data at the population
level before, during and after such crises is often lacking and
classical demographic methods and model life tables are ill-suited for
such situations. In this paper, I explore the flexible,
two-dimensional mortality model recently proposed by Wilmoth et
al. (2012) and consider its adaptation to crisis mortality
situations. Specifically, I draw on high quality data from a diverse
array of demographic surveillance sites, population censuses,
longitudinal surveys, and series from the Human Mortality Database to explore the suitability of this mortality
modeling approach to famine and armed conflict situations. These
situations include a diverse array of armed conflict and famine
situations from both contemporary and historical populations. I
contrast this approach with existing approaches used by the United
Nations Population Division and the World Health Organization and
conclude with an assessment of this indirect mortality modeling
approach and outline future research directions to advance crisis
mortality estimation approaches.

The own-children method is a reverse-survival technique to estimate fertility measures using census or survey data. Although the method has been developed in the 1960s, it is still a useful method for analysing fertility measures as it provides single-year estimates of fertility for 15 years prior to a census. This paper presents the fertility trends in Iran during 1997 and 2011 derived from the 2010 IrMIDHS and the 2011 Census, and examines the validity of the own-children method of fertility estimates. The results are assessed by a detailed investigation of mortality assumptions, the presence of non-own children, and age misreporting. ASFRS and TFRs are estimated for Iran by area of residence, province, and district. The fertility estimates obtained alternatively from two matching procedures (using relationship to head of household and mothers’ line number) are investigated to see the accuracy of the results. The OCM estimates are also compared with those obtained from other direct and indirect methods. The results show consistency between the own-children estimates obtain from the two data sources as well as from the two matching procedure. The TFR for 2011 is estimated to be around 1.75 indicating a rather slow decline in recent years. Our district level fertility estimates shed light on the future of fertility in Iran.

Monitoring maternal mortality is extremely challenging due to issues with data availability and quality. The maternal mortality estimates published by the WHO in 2012 include data adjustment parameters to account for data quality issues, but there is a discrepancy between the WHO assumption about, and observed variability in, misclassification errors in VR observations. Bayesian modeling approaches can be used to provide more data-driven insights into maternal mortality estimates and data adjustment parameters. We propose a Bayesian time series model for the VR adjustment parameters to assess the extent of VR misclassification errors and to provide a plausible assessment of the uncertainty associated with VR observations for which no external quantification of misreporting is available. We find that the proposed model gives a distribution for VR adjustments that is more comparable to the observed biases than the WHO expert distribution. However, given the lack of, and issues with maternal mortality data, validation of modeling assumptions and findings is challenging; more research on measuring maternal mortality and assessing data quality is urgently needed.

Fertility forecasting in the case of Brazil constitutes a great challenge due to the regional heterogeneity of its fertility transition, making the application of the known projection techniques difficult. Thus, the paper presents a methodology that allows to forecast the pattern and level of fertility by defining scenarios for a small geographical unit based on the fertility behavior of the total population. In this case, Brazilian Federate States (BFS) and the whole country as a unit. We use National Household Surveys, Demographic Censuses (2000 and 2010) and vital statistics where data are reliable. We assume that the trend of reproductive behavior outlined for the country as a whole is a transition process to be experienced by all BFS, differing only by the timing it occurs. From this assumption it is possible to identify –using the more recent BFS’ TFR as a first parameter– the timing of its corresponding fertility transition. Then, using interpolation procedures we replicate the national transition experienced by each ASFR. The robustness of this technique is given by the coincidence of the sum of births generated by the FBS’s ASFR and the total births generated by the ASFR defined for the whole country.

This study investigates the extent of bias in the estimates of infant and under-five mortality derived from the Brass children ever born children surviving (CEB/CS) method as a result of HIV/AIDS. The bias is estimated by comparing the infant and under-five mortality derived from the CEB/CS method with direct estimates from the full birth history data from recent DHS data. The estimates from the full birth history data have been corrected for bias due to HIV/AIDS using the method used by IGME.

IMRs and U5MRs derived from data from women aged 25-39 were underestimated by up to 15% in the six countries studied. Estimates of bias in data derived from women aged 20-24 differed between countries. The results from these younger women could be affected by differences between the indirect and direct methods of estimation. In two of the countries, estimates of overall bias of more than 30% were observed. The bulk of the overall bias is due to the effect of HIV on the survival of mothers and their children. The choice of model life table does not introduce much bias, especially in estimates of under-five mortality where the absolute bias in most countries was less than 3%.

Application of conventional demographic approaches in studying fertility poses major analytical hindrance to the successful implementation of various global and national interventions on population in developing countries. Inadequate infrastructure and personnel capacity to capture and reliably track the dynamics of her 160 million population coupled with sustained high fertility rates provide compelling grounds for a review of the current processes, as the country’s population policy remains unrealised. This study sought to explore the inclusion of the stakeholder analysis approach of Health Systems Research in the study of fertility in order to improve our understanding of the dynamics of population change and its consequent effect on the overall reproductive health of a highly populous nation.
The study used data of males abstracted from the 2003 Nigeria Demographic and Health Survey (NDHS). An empirical analysis of variations in fertility outcomes and reproductive preferences of males across the six geo- political zones and other socio-demographic characteristics was done. Peculiar factors which are significantly associated with completed family size/ children ever born (CEB) were also analysed.

Standard techniques of indirect estimation of child mortality use data from summary birth histories consisting of only two questions - number of children ever born alive and the number of children dead. However the estimation is based on several assumptions about fertility and mortality patterns, and rates computed for recent periods are biased. We propose and apply an innovative approach based on imputation of full birth histories onto summary birth histories. The resulting imputed full birth history is used to calculate child mortality rates using standard life table procedures. We apply the approach to data from the Malawi 2008 Population Census and the 2004 and 2010 Demographic and Health Survey datasets. Preliminary results are promising, with most of the imputed child mortality rates falling within the 95% confidence intervals of the rates directly computed from the 2010 DHS survey. In addition, choice of the existing full birth history data for the imputation did not appear to affect the resulting mortality rates computed from the imputed full birth history data.

Levels, patterns and trends of male fertility are little documented in sub-Saharan Africa. Most existing studies have been conducted at the local level, and are relatively old. Yet, data collected in DHS contain valuable information on male fertility, and have largely been untapped. The objectives of this paper are (1) to evaluate to what extent the DHS data in sub-Saharan Africa can be used to measure levels, patterns and trends of male fertility, and (2) to provide a broad overview of male fertility levels, patterns and trends in Africa. Three methods are compared: the own children method, the crisscross method, and the date of last birth method. Results suggest that the own children method is the most appropriate to measure male fertility in a wide range of countries and periods. Preliminary results show three broad patterns of male fertility. They also show declines in male fertility in several sub-Saharan African countries.

The aim of the study is to show the reduction in fertility from 1990 to 2010 in Mexico, by analyzing two important sources of information: Census of Population and Birth Certificates from administrative data.
First we will show through Birth Certificates how fertility has shown a reduction in the period, both in the Global fertility Rate and in Specific Fertility Rates too. We will present two sets of data, one calculated from the year of registration of birth using three years of information, and another from the age record, using up to thirty five months. We want to show by this, that both calculations produce similar information, and that using the age of registration gives opportunity, because we do not have to wait too much to have data.
On the other hand, we will present data from the 1990, 2000 and 2010 Population Census, and we calculate fertility by direct (using the question of last live birth) and indirect methods (the own children method). We can compare the information obtained directly and indirectly, demonstrating that is relevant in both ways, to estimate fertility through Population Census.
In both cases we use the information from specializing surveys in fertility to compare the results that we produce.

In sub-Saharan and south Asian countries with incomplete vital registration, adult mortality rates are estimated by asking respondents of household-based surveys (e.g., DHS) about the survival of their maternal siblings. These siblings' survival histories (SSH) are inexpensive to collect but are affected by biases, including sample selection and recall biases. Statistical adjustments have been proposed to correct for sample selection biases, but respondent errors (e.g., forgetting of siblings) are considered inevitable. We test whether a new survey instrument - the siblings enhanced life calendar (SELC) – improves the quality of mortality data relative to standard instruments currently used in DHS surveys. The SELC is based on a life history calendar, a tool widely used in other areas of survey research (e.g., migration histories, sexual behavior research) but not to improve the recall of adult mortality data in developing countries. It also incorporates recall cues developed through cognitive interviews. We report results of a randomized trial of the SELC conducted in a rural population of Senegal (Niakhar) that has been under demographic surveillance (DSS) for the past 50 years. To compare error rates in each arm of the trial, we link DSS data (our “gold standard”) to SSH and SELC data at the individual level.