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Optimal health and development from preconception to adulthood are critical for human flourishing and the formation of human capital. The Nurturing Care Framework, as adapted to age 20 years, conceptualizes the major influences during periods of development from pre-conception, through pregnancy, childhood and adolescence that affect human capital. In addition to mortality in children under five years of age, it is important to consider earlier (stillbirths) or later (from five to 20 years) loss of life. The global rate of mortality before 20 years has declined substantially since 2000, yet in 2019 an estimated 8·6 million deaths occurred between 28 weeks of gestation and 20 years of age, with over half, including stillbirths, occurring before 28 days of age. The 1,000 days from pre-conception to two years are especially influential for human capital. The prevalence of low birth weight is high in sub-Saharan Africa and even higher in South Asia. Growth faltering, especially from birth to two years of age, occurs in most world regions while overweight increases in many regions from the pre-primary school period through adolescence. Analyses of cohort data show that growth trajectories in early years of life are strong determinants of nutritional outcomes in adulthood.The accrual of knowledge and skills is affected by health, nutrition and home resources in early childhood and by educational opportunities. Linear growth in the first two years of life better predicts intelligence quotients among adults than increases in height in older children and adolescents. Learning-adjusted years of schooling range from about four years for sub-Saharan Africa to about 11 years in high-income countries. Human capital depends on children and adolescents surviving, thriving and learning until adulthood.

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Using data collected in the Nouna HDSS in Burkina Faso, we evaluate the reliability of mortality estimates based on the 2006 national census. We extracted from the census database all records referring to the population under surveillance in the HDSS. Life tables were estimated from recent household deaths reported in the census and compared to those obtained from the prospective mortality data. We linked census and HDSS records at the individual level and evaluated the reported ages of household members and those who died in the 12 months preceding the census against those in the HDSS. Life expectancies derived from recent deaths reported in households pointed to lower mortality than monitored in the HDSS, with a difference of 3.2 years for men and 6.8 years for women. Age errors were limited for the surviving population, but larger for the deceased. Underreporting of deaths plays a larger role than age errors.

In Belgium, life expectancy is now twice what it was 170 years ago due to improvements in public and private hygiene, nutrition, medical procedures and the organization of health services. The average lifespan of a Belgian resident is now over 80 years, but inequalities persist and sometimes even intensify. In Belgium, like in other European countries, a negative relationship has been demonstrated between socio-economic position on the one hand and health and mortality on the other hand. This project aimed to investigate whether or not this social gradient in health and mortality is associated with the growing de-standardisation of employment arrangements and family situations. The goal was to obtain information about the mechanisms by which social differences in mortality and health are generated in Belgium, in order to provide insight in policy measures that could prove effective in countering these inequalities. In a first part of the project, the evolution of mortality inequalities in Belgium between 1991 and 2016 was studied. It has been shown, based on a multidimensional indicator combining educational level, employment category and housing characteristics, that social inequalities in death are significant in Belgium and that they have been increasing for both women and men since at least the 1990s. In relative terms, gaps between social groups are especially wide between 25 and 50 years but have little impact on differences in life expectancy because the risk of dying is inherently low at these ages. The social disparities in mortality for older people (65+) – and especially the delay of the underprivileged in the health transition and the fight against cardiovascular diseases – have a far greater effect on differences in life expectancy. In general, social inequalities in mortality and their variation along the social continuum are observed for each of the major causes of death, but they are particularly pronounced for diseases of the respiratory and circulatory systems. The results also point out that spatial disparities in mortality linger and have been worsening for at least a quarter century. The spatial pattern of mortality for the underprivileged social group resembles the spatial patterns of the privileged and intermediate social groups. Within the same social group, spatial disparities endure. This indicates that beyond the socioeconomic composition of regions and districts, other factors – environmental, cultural and behavioural – are involved and affect mortality across social groups in the same way. The second part of the project focused on the relationship between employment situation and (cause-specific) mortality. Mortality inequalities by employment status were considered, controlled for other dimensions of socio-economic position. The association between mortality and unemployment in Belgium was investigated in detail at the individual level. Results showed that the unemployed have a two times higher mortality risk than the employed. Even when they have a high educational level, excellent housing conditions and healthy living arrangements, unemployed men still have a higher mortality risk than their employed counterparts. Conclusions for women were comparable, but inequalities were smaller. A slight protective effect of education against the detrimental health impact of unemployment was demonstrated. Analyses clearly showed that the mortality excess of the unemployed results from an excess mortality in practically all main cause groups. Focusing on specific causes within each main group, we observed large inequalities for alcohol-related mortality. Furthermore, our results illustrated the importance of municipality of district characteristics, such as urbanicity, the aggregated unemployment rate, etcetera. The mortality excess for unemployed men and women was for example smaller in regions with higher aggregate unemployment levels. The higher mortality of the unemployed suggests a positive effect of having a job, which is a reasonable assumption since employment is a key factor determining the financial and psychological wellbeing of individuals and their families. Getting people into work should therefore be an important goal of labour market policies and is of critical importance for reducing health inequalities. However, this is not the whole picture. Analyses including non-standard types of contract show that jobs need to be sustainable as well. Overall and cause-specific mortality differentials by marital status and type of family situation were the focus of a third part of the CAUSINEQ project, in order to gain insight into the effect of the de-standardisation of family formation processes. With regard to marital status, it does appear that matrimonial behaviour varies from one Belgian administrative region to another. Flanders is characterised by a greater share of married couples and a lower proportion of divorced and single people. In contrast, isolated individuals are overrepresented in Brussels, compared to Flanders in particular, but also compared to Wallonia. At the same time, married individuals and those who are not married but live in a couple do seem to be subject to lower levels of mortality in each of the three regions of Belgium. Results from Poisson regression models point out the interactions between the undermortality of (married) couples and the differences in matrimonial behaviour between the three regions are relatively small and do not provide a satisfying explanation for the differences in mortality observed between the regions. The main factor explaining regional differences in mortality is the socio-economic situation of the residents. With regard to type of family situation, excess mortality was revealed for children under 5 years of age living in single-parent families, even after controlling for the main socio-demographic variables. This excess mortality is particularly pronounced for violent deaths. This observation raises questions. Is this a manifestation of less parental supervision or is it a reflection of less safe housing or living conditions? In order to characterise violent deaths in single-parent families and to distinguish them from those in two-parent families, Chi-square tests were used with the place of death (home, school, etc.), the type of death (traffic accident, other accidents, etc.) and the day of the week in which the death occurred. However, none of these analyses was statistically significant. Finally, analyses were performed to show how adverse health – as an important precursor of mortality – varies jointly by employment and living arrangements. A typology of labour market positions was constructed and enriched with survey-data information about respondents’ employment conditions (for those in waged employment). This endeavour shows Belgium as a country with a stable, low prevalence of precarious employment when compared to other EU-countries. However, the prevalence of one particular type of precarious employment is considerable and growing in Belgium, namely ‘precarious unsustainable employment’, characterised mainly by low working hours and low monthly wages and often held by female workers. The labour market typology shows clear relationships with the health of individuals. Three labour market positions are most likely to be associated with general and mental health problems: unemployment, precarious employment and instrumental employment. Controlling for social precarity indicators causes a (sometimes spectacular) reduction in the odds for poor health, which clearly shows how the broader social situation “interacts” with labour market positions in creating social health inequalities. It is therefore important to keep in mind that the accumulation of health-damaging positions in different life spheres is in fact a worrisome reality for a part of the Belgian population. These results indicate that precarious labour market situations are to be taken serious as a public health risk and suggest that stable and secure employment of good quality is the “healthiest form of employment”. From a policy perspective, our findings make clear that the potential health impact of labour market policies should be considered whenever labour market reforms are planned. Policy makers should be aware of the fact that flexible labour market policies may stand at odds with policies aiming for longer and sustainable working careers.

This research was conducted to evaluate the contribution of verbal autopsies (VA) integrated in the 72 civil registration centers of the Dakar region. Reported deaths over a two-month period were identified and the 2016 WHO-VA instrument was administered to relatives of the deceased. The InterVA5 software identified the main causes and circumstances of death. VA were completely administered to 42.8% of deaths reported in vital registration centers, and 66.7% of eligible cases. Death occurred at home in 35.9% of cases, in a health facility in 36.6%. The primary respondent designated to answer the questions was the father or mother of the deceased, in 39.5% of the cases. The analysis of the causes of death found a preponderance of cardiovascular diseases. VA integrated in vital registration centers are an accessible mean of collecting cause-of-death data in urban settings in Senegal to strengthen the health information system.

Based on deaths registers maintained by the Municipal Hygiene Office from Antananarivo, this study assesses seasonal patterns and its changes over the period 1976-2015 of all-cause and cause-specific mortality by age groups, using Generalized Additive Mixed regression models. Among children, risks of dying were the highest during the hot and rainy season, but the seasonality in child mortality significantly reduced since the mid-1970s, due to declines in the burden of infectious diseases and nutritional deficiencies. In adults aged 60 and above, all-cause mortality rates are the highest in the dry and cold season, due to peaks in cardiovascular diseases, with little change over time. Changes in the seasonality within broad categories of causes of death have been modest. To conclude, shifts in disease patterns brought by the epidemiological transition, rather than changes in seasonal variations in cause-specific mortality, are the main drivers of trends in the seasonality of all-cause mortality.

All-cause and cause-specific mortality rates in sub-Saharan Africa remain poorly estimated due to the incompleteness of death registration systems and a high percentage of home deaths. Even though health facility data are increasingly used to monitor changes in disease patterns, they are not representative of the general population. We take advantage of a death notification system that was set up in Antananarivo (Madagascar) to document over time (1976-2015) the hidden causes of deaths that are not usually reported in health facility data. In Antananarivo, age at death has increased and the overall proportion of death occurring in health facilities has declined over time. However, these changes have been uneven across causes of death and the concordance between cause-specific mortality fractions inferred from deaths that occurred in health facilities and those based on all deaths is gradually increasing. Yet some deaths remain consistently under-represented, especially those due to respiratory diseases.

Across the world, around one million children aged between 5 and 15 years died in 2017. For a child on its fifth birthday, the risk of dying before reaching its fifteenth birthday is 7.2 per 1,000. This is five times lower than the risk for a newborn of dying before age 5 (39 per 1,000). Mortality between ages 5 and 15 halved between 1990 and 2017, and most deaths in this age group now occur in low- and middle-income countries. In 2017, one-third of all deaths were concentrated in West and Central Africa, where the probability of dying at these ages is more than 20 times higher than in Western Europe.

Entre 1990 et 2015, la plupart des pays en développement ont connu des progrès notables de leur espérance de vie, mais d’ampleur très diverse. Cet article fait le point sur l’évolution de la mortalité des enfants (à moins de 5 ans) et de la mortalité adulte (de 15 à 60 ans) dans les 109 pays à bas et moyen revenu de plus d’un million d’habitants. Il met l’accent sur l’évolution des disparités géographiques et de sexe entre pays, et sur les inégalités internes (instruction, niveaux de vie, milieux d’habitat) dans dix pays retenus aux caractéristiques très différentes sur les plans socioéconomique, politique et démographique (Afghanistan, Afrique du Sud, Bolivie, Brésil, Burkina Faso, Chine, Égypte, Inde, Indonésie, Nigeria). Il revisite également la question de la transition épidémiologique et examine plus particulièrement la mortalité par sida et la mortalité maternelle. Les progrès ont bénéficié principalement aux enfants, et souvent (mais pas toujours) aux femmes et aux pays et groupes sociaux les plus défavorisés. Parler de convergence vers une faible mortalité paraît néanmoins prématuré, car en dépit des progrès réalisés, les inégalités entre pays et internes aux pays demeurent conséquentes, et méritent une attention particulière tant des acteurs de la santé publique que des chercheurs.

In this paper, we consider the challenge of death registration and mortality estimation for populations affected by conflict and displacement, where conventional systems of civil registration are seldom functional. Our analysis and discussion are framed around a short case study that showcases existing registration systems in Yemen and presents a descriptive mortality analysis based on these existing data sources. We first provide a general discussion of the registration of displaced people, who are playing an increasingly key role in shaping the demographic trends in the Arab region. We then introduce some of the challenges to death registration in Yemen and review the registration process in place in the country for refugees and IDPs. We describe two databases maintained by UNHCR: the refugee registration information system (ProGres) and the Health Information System (Twine). We present preliminary results based on changes in the size and composition of populations of PoCs, basic demographic rates, and cause-specific mortality fractions. Finally, we discuss the potential for data collected by UNHCR to contribute to official vital statistics in Yemen.

Objective: Due to incomplete death registration in Madagascar, trends in cause-specific mortality are known from epidemiological models such as the Global Burden of Disease Study 2013 (GBD 2013). The external validity of such model-based estimates is difficult to establish, however, since all possible data are usually included. In Madagascar, the GBD 2013 study used death registration data from Antananarivo but only for the period 1984-1995. Using death records up to 2014, we aim to describe trends in mortality by age and sex and compare the distribution of causes of death observed in death records with GBD 2013. Methods: Information on the sex of the deceased, date of birth and death and underlying cause of death were transcribed from death registers. Causes of death were converted in GBD cause categories. The completeness of the registration of deaths was assessed using indirect demographic techniques. Findings: The completeness of the registration of deaths is higher than 90% in Antananarivo. The proportion of deaths attributed to "garbage codes" amounts to 19.4% when considering codes for symptoms, signs and ill-defined conditions, deaths from injuries whose intent is not determined, and ill-defined cardiovascular diseases and neoplasms. Significant differences are observed between the distributions of deaths by cause in the GBD 2013 estimates and death registers referring to the capital city. Conclusions: Death registration in Antananarivo, and possibly other African cities, is a low-cost and untapped data source which can help to refine disease burden estimates.

Despite a renewed interest for the situation of orphans, census data on parental survival remain seldom used. Numerous African censuses contain information on parental deaths, and census data have the potential to portray a much more exhaustive picture of orphanhood than sample surveys. The chapter starts with prevalence of orphanhood estimated from a large series of countries. When successive censuses are available, trends are assessed. We also show how census data can be used to work at the district level and identify sub-national regions with high orphan burden. Finally, the chapter focus on the vulnerability of orphans by studying school enrollment, living arrangements and labor participation of orphans.

Due to the lack of civil registration data in sub-Saharan Africa, adult mortality rates are often estimated in two stages; first, measures of child survival are combined with model schedules of mortality, then AIDS-related deaths are factored in. Model-based estimates are mostly sensitive to the choice of age pattern used to infer the background mortality and to violations of assumptions made to predict the number of AIDS-related deaths. They need to be regularly evaluated against survey or census data. In this paper, United Nations estimates of adult mortality are compared with survival probabilities calculated from sibling histories collected in DHS surveys. UNAIDS orphan prevalences are compared with proportions of orphaned children observed in censuses and household surveys. If parental and sibling survival provide plausible lower bounds, then adult mortality rates are underestimated in countries severely affected by the HIV/AIDS epidemic, especially in Southern Africa and among males. In addition, as the HIV epidemic unfolds, the age patterns of mortality derived from DHS surveys differ markedly from model outputs.