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Background: Higher levels of socioeconomic deprivation have been consistently associated with increased risk of premature mortality, but a detailed analysis by causes of death is lacking in Belgium. We aim to investigate the association between area deprivation and all-cause and cause-specific premature mortality in Belgium over the period 1998–2019. Methods: We used the 2001 and 2011 Belgian Indices of Multiple Deprivation to assign statistical sectors, the smallest geographical units in the country, into deprivation deciles. All-cause and cause-specific premature mortality rates, population attributable fraction, and potential years of life lost due to inequality were estimated by period, sex, and deprivation deciles. Results: Men and women living in the most deprived areas were 1.96 and 1.78 times more likely to die prematurely compared to those living in the least deprived areas over the period under study (1998–2019). About 28% of all premature deaths could be attributed to socioeconomic inequality and about 30% of potential years of life lost would be averted if the whole population of Belgium faced the premature mortality rates of the least deprived areas. Conclusion: Premature mortality rates have declined over time, but inequality has increased due to a faster pace of decrease in the least deprived areas compared to the most deprived areas. As the causes of death related to poor lifestyle choices contribute the most to the inequality gap, more effective, country-level interventions should be put in place to target segments of the population living in the most deprived areas as they are facing disproportionately high risks of dying., SCOPUS: ar.j, info:eu-repo/semantics/published

In countries lacking comprehensive systems of civil registration and vital statistics, the collection of demographic data through mobile surveys is increasingly feasible, as mobile phone coverage has rapidly expanded. However, mobile phone users are often younger, male, with higher education, and wealthier, potentially biasing demographic estimates based on phone surveys. We assess selection bias in estimates of under-five mortality and fertility using data from 34 Demographic and Health Surveys. We use logistic regressions to characterize individuals who own or have access to a mobile phone in terms of sociodemographic background characteristics, and Poisson regressions to estimate the association between mobile phone ownership (or access)and total fertility and under-five mortality rates. We further evaluate the potential reasons why estimates by mobile phone ownership may differ using a set of behavioral characteristics. Fertility and mortality rates would be biased downwards if estimates are only based on women who own or have access to mobile phones. Under-five mortality estimates can be adjusted through post-stratification using age, educational level, area of residence, wealth, and marital status as weights. However, fertility estimates remain biased even after adjusting for these covariates. This difference is associated with behavioral factors that are not captured by the post-stratification variables, but for which there are also differences between mobile phone owners and non-owners. In many countries, modern contraceptive use is positively associated with mobile phone ownership, which may complicate fertility estimates based on mobile phone surveys. Mobile phone surveys need to include background questions on socioeconomic status to be able to weight and adjust mortality estimates ex post-facto. Fertility estimates from mobile phone surveys will be biased unless further research uncovers the mechanisms driving the bias.

Background: In the past, deprivation has been mostly captured through simple and univariate measures such as low income or poor educational attainment in research on health and social inequalities in Belgium. This paper presents a shift towards a more complex, multidimensional measure of deprivation at the aggregate level and describes the development of the first Belgian Indices of Multiple Deprivation (BIMDs) for the years 2001 and 2011. Methods: The BIMDs are constructed at the level of the smallest administrative unit in Belgium, the statistical sector. They are a combination of six domains of deprivation: income, employment, education, housing, crime and health. Each domain is built on a suite of relevant indicators representing individuals that suffer from a certain deprivation in an area. The indicators are combined to create the domain deprivation scores, and these scores are then weighted to create the overall BIMDs scores. The domain and BIMDs scores can be ranked and assigned to deciles from 1 (the most deprived) to 10 (the least deprived). Results: We show geographical variations in the distribution of the most and least deprived statistical sectors in terms of individual domains and overall BIMDs, and we identify hotspots of deprivation. The majority of the most deprived statistical sectors are located in Wallonia, whereas most of the least deprived statistical sectors are in Flanders. Conclusion: The BIMDs offer a new tool for researches and policy makers for analyzing patterns of deprivation and identifying areas that would benefit from special initiatives and programs., SCOPUS: ar.j, info:eu-repo/semantics/published

Background The Sustainable Development Goals (SDGs), set in 2015 by the UN General Assembly, call for all countries to reach an under-5 mortality rate (U5MR) of at least as low as 25 deaths per 1000 livebirths and a neonatal mortality rate (NMR) of at least as low as 12 deaths per 1000 livebirths by 2030. We estimated levels and trends in under-5 mortality for 195 countries from 1990 to 2019, and conducted scenario-based projections of the U5MR and NMR from 2020 to 2030 to assess country progress in, and potential for, reaching SDG targets on child survival and the potential under-5 and neonatal deaths over the next decade. Methods Levels and trends in under-5 mortality are based on the UN Inter-agency Group for Child Mortality Estimation (UN IGME) database on under-5 mortality, which contains around 18 000 country-year datapoints for 195 countries—nearly 10 000 of those datapoints since 1990. The database includes nationally representative mortality data from vital registration systems, sample registration systems, population censuses, and household surveys. As with previous sets of national UN IGME estimates, a Bayesian B-spline bias-reduction model (B3) that considers the systematic biases associated with the different data source types was fitted to these data to generate estimates of under-5 (age 0–4 years) mortality with uncertainty intervals for 1990–2019 for all countries. Levels and trends in the neonatal mortality rate (0–27 days) are modelled separately as the log ratio of the neonatal mortality rate to the under-5 mortality rate using a Bayesian model. Estimated mortality rates are combined with livebirths data to calculate the number of under-5 and neonatal deaths. To assess the regional and global burden of under-5 deaths in the present decade and progress towards SDG targets, we constructed several scenario-based projections of under-5 mortality from 2020 to 2030 and estimated national, regional, and global under-5 mortality trends up to 2030 for each

Studies have shown that children in rural areas face excess risks of dying, but the little research on spatial inequalities in adult mortality has reached mixed conclusions. We examine rural–urban differences in mortality in 53 low- and middle-income countries. We consider how the rural–urban mortality gap evolves from birth to age 60 by estimating mortality based on birth and sibling histories from 138 Demographic and Health Surveys run between 1992 and 2018. We observe excess rural mortality until age 15, finding the largest differences between urban and rural sectors among 1–59-month-olds. While we cannot claim higher mortality among urban adults than those in rural areas, we find a reduced gap between the sectors over the life course and a diminishing urban advantage in adult mortality with age. This shift over the life course reflects a divergence in the epidemiologic transition between the rural and urban sectors.

BACKGROUND In low- and middle-income countries, mortality levels are commonly derived from retrospective reports on deceased relatives collected in sample surveys and censuses. These data sources are potentially affected by recall errors. OBJECTIVE Using high-quality data collected by the Nouna Health and Demographic Surveillance System (HDSS) in Burkina Faso, we evaluate the reliability of mortality estimates based on the 2006 national census. METHODS 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. To evaluate age errors and assess their impact on mortality, we linked census and HDSS records at the individual level for the surviving population and the deceased. Indirect estimates of mortality were also calculated based on the reported survival of children and parents. RESULTS Life expectancies at birth derived from recent household deaths pointed to a lower mortality than monitored in the HDSS, with a difference of 4 years for men and 8 years for women. Underreporting of deaths among the population aged 60 and above accounted for more than half of these differences. Age errors were small for the surviving population and larger for the deceased, but their effects on mortality estimates were modest. Indirect estimates of child mortality were consistent with the HDSS data, but orphanhood-based estimates were implausibly low. CONCLUSION Additional elicitation questions should be asked during the census interviews to improve the collection of data on recent household deaths. CONTRIBUTION Mortality rates derived from recent household deaths can seriously underestimate mortality. In Burkina Faso the downward bias in the 2006 census was larger among females and was mostly attributable to underreporting of deaths.

Optimal health and development from preconception to adulthood are crucial for human flourishing and the formation of human capital. The Nurturing Care Framework, as adapted to age 20 years, conceptualises the major influences during periods of development from preconception, through pregnancy, childhood, and adolescence that affect human capital. In addition to mortality in children younger than 5 years, stillbirths and deaths in 5–19-year-olds are important to consider. The global rate of mortality in individuals younger than 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 more than half of deaths, including stillbirths, occurring before 28 days of age. The 1000 days from conception to 2 years of age are especially influential for human capital. The prevalence of low birthweight is high in sub-Saharan Africa and even higher in south Asia. Growth faltering, especially from birth to 2 years, occurs in most world regions, whereas overweight increases in many regions from the preprimary 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 in older children and adolescents. Linear growth in the first 2 years of life better predicts intelligence quotients in adults than increases in height in older children and adolescents. Learning-adjusted years of schooling range from about 4 years in sub-Saharan Africa to about 11 years in high-income countries. Human capital depends on children and adolescents surviving, thriving, and learning until adulthood.

Background The COVID-19 pandemic has led to major shocks in mortality trends in many countries. Yet few studies have evaluated the heterogeneity of the mortality shocks at the sub-national level, rigorously accounting for the different sources of uncertainty. Methods Using death registration data from Belgium, we first assess change in the heterogeneity of districts’ standardized mortality ratios in 2020, when compared to previous years. We then measure the shock effect of the pandemic using district-level values of life expectancy, comparing districts’ observed and projected life expectancy, accounting for all sources of uncertainty (stemming from life-table construction at district level and from projection methods at country and district levels). Bayesian modelling makes it easy to combine the different sources of uncertainty in the assessment of the shock. This is of particular interest at a finer geographical scale characterized by high stochastic variation in annual death counts. Results The heterogeneity in the impact of the pandemic on all-cause mortality across districts is substantial: while some districts barely show any impact, the Bruxelles-Capitale and Mons districts experienced a decrease in life expectancy at birth of 2.24 (95% CI:1.33–3.05) and 2.10 (95% CI:0.86–3.30) years, respectively. The year 2020 was associated with an increase in the heterogeneity of mortality levels at a subnational scale in comparison to past years, measured in terms of both standardized mortality ratios and life expectancies at birth. Decisions on uncertainty thresholds have a large bearing on the interpretation of the results. Conclusion Developing sub-national mortality estimates taking careful account of uncertainty is key to identifying which areas have been disproportionately affected.

Socioeconomic deprivation is associated with increased premature mortality. Our aim is to measure the health inequality in premature mortality in the Belgian population between 1991-2020 by using the Belgian Index of Multiple Deprivation 2011 (BIMD2011). We built the time- and area-specific BIMD2011 combining data on income, employment, education, crime and housing from the census 2011, National Register, Intermutualistisch Agentschap, and the Federal Police. We then utilized mortality data at ages 0-74 between 1991 and 2020 to compute age-and-sex-standardized premature mortality rates, population attributable fraction (PAF) and potential years-life-lost (PYLLs) due to premature mortality in overall and cause-specific mortality. Finally, we calculated these health inequality indicators by major causes of death in Belgium. Our study covered 294 million person-years in people aged from 0 to 74, with 1,164,777 premature deaths occurring between 1991 and 2020. In total, 29.7% (95%CI:29.1-29.9) premature deaths were attributable to SE inequality causing a mean of YLLs of 8.7 per person in the observed period. Out of 74 564 premature deaths that occurred between 1998 and 2017 and that were attributable to socioeconomic inequality, the causes of death that contributed most deaths were diseases of circulatory system (23,763;31%), diseases of respiratory system (16,690;22%) and neoplasm (14,108;19%). We created a small-area BIMD that can locate hot spots of SE inequality and help policy makers to effectively allocate funding and put in place new SE policies. Our findings showed that deprivation in Belgium is strongly associated with health inequality and interventions addressing SE inequality should be prioritized.

Producing accurate estimates of sex ratios of mortality rates is essential in understanding population structure and dynamics, and in revealing sex discrimination. We introduce a Bayesian hierarchical model to estimate the disparity in age-specific mortality by sex for all countries over time, focusing on youth (15--24) mortality. The Bayesian model synthesizes data with varying levels, trends and associated uncertainties. The hierarchical modeling structure allows information exchange between data-saturated country-periods and data-poor ones to assist estimation in country-periods lacking observations. We model the global expected sex ratio using all the observations with a random walk model of order 2 (RW2). The RW2 is flexible to capture the non-linear global trend and is computationally efficient relative to splines model. The model can be used to estimate sex disparity in mortality for other age groups. We conclude that the Bayesian model is an efficient and robust approach for estimating sex ratios of mortality.

Sibling survival history (SSH) data can be used to estimate adult mortality rates. However, SSH data may be subject to substantial reporting errors in the form of omissions of siblings, or misreported years of birth and age at death. We present a new Bayesian survival modeling approach (B-Surv) to estimate agecohort-specific survival probabilities from SSH data while accounting for bias and uncertainty introduced by the age reporting errors. In the model, true survival by cohort and age is captured with a twodimensional splines function. SSH reported date of birth (DoB) and age at death (AaD) are the sum of the latent true outcome and a reporting error. A bivariate distribution of reporting errors in (DoB, AaD) is obtained from an analysis of such errors and its predictors, obtained from a comparison of SSH data with gold-standard data obtained in recent validation study conducted in a health demographic surveillance system in Senegal. We illustrate the approach using simulations and apply it to estimate adult survival in Senegal from DHS data.

Many protracted crises are largely in resource poor settings affecting billions of people around the world. Efforts are being made globally to mitigate the impact of protracted crises on affected populations. However, these places typically lack the required health information systems for the collection of birth and death records needed to conduct a comprehensive assessment of the public health status and needs of the population. In particular, Yemen has been experiencing drawn out conflict, exposing children and adults to untold hardship and diseases as well as the risk of losing their lives increases as the crisis continues. A comprehensive nationwide analysis of the impact of the protracted crisis in Yemen on mortality is lacking. However, over the course of the crisis in Yemen, series of small-scale surveys have been conducted on regional/zonal levels for planning purposes by humanitarian organizations operating on ground. Because of the costs and the impracticability of conducting an indepth, nation-wide assessment, we have attempted to conduct an effective and robust investigation for a better understanding of the impact of the conflict on mortality by combining the sparse, publicly available data. We started by assessing the methods used for the collection and presentation of mortality data obtained from the small-scale survey. We found no strict adherence to standardized methodology guidelines, and reporting of mortality and sample size data. Adherence to methodological guidelines and complete reporting of surveys in humanitarian settings will vastly improve the estimation of mortality rate and also uptake of key data on health indicators of the affected population. We also assessed the change in number of deaths as a result of the conflict using a Bayesian mixture model approach. Despite an increase in the estimated number of deaths attributed to the conflict, we observed uncertainty surrounding the point estimates, which calls for caution while interpretin, (SP - Sciences de la santé publique) -- UCL, 2022

Background Poor housing conditions have been associated with increased mortality. Our objective is to investigate the association between housing inequality and increased mortality in Belgium and to estimate the number of deaths that could be prevented if the population of the whole country faced the mortality rates experienced in areas that are least deprived in terms of housing. Methods We used individual-level mortality data extracted from the National Register in Belgium and relative to deaths that occurred between Jan. 1, 1991, and Dec. 31, 2020. Spatial and time-specific housing deprivation indices (1991, 2001, and 2011) were created at the level of the smallest geographical unit in Belgium, with these units assigned into deciles from the most to the least deprived. We calculated mortality associated with housing inequality as the difference between observed and expected deaths by applying mortality rates of the least deprived decile to other deciles. We also used standard life table calculations to estimate the potential years of life lost due housing inequality. Results Up to 18.5% (95% CI 17.7–19.3) of all deaths between 1991 and 2020 may be associated with housing inequality, corresponding to 584,875 deaths. Over time, life expectancy at birth increased for the most and least deprived deciles by about 3.5 years. The gap in life expectancy between the two deciles remained high, on average 4.6 years. Life expectancy in Belgium would increase by approximately 3 years if all deciles had the mortality rates of the least deprived decile. Conclusions Thousands of deaths in Belgium could be avoided if all Belgian neighborhoods had the mortality rates of the least deprived areas in terms of housing. Hotspots of housing inequalities need to be located and targeted with tailored public actions.

Background: Poor housing conditions have been associated with increased mortality. Our objective is to investigate the association between housing inequality and increased mortality in Belgium and to estimate the number of deaths that could be prevented if the population of the whole country faced the mortality rates experienced in areas that are least deprived in terms of housing. Methods: We used individual-level mortality data extracted from the National Register in Belgium and relative to deaths that occurred between Jan. 1, 1991, and Dec. 31, 2020. Spatial and time-specific housing deprivation indices (1991, 2001, and 2011) were created at the level of the smallest geographical unit in Belgium, with these units assigned into deciles from the most to the least deprived. We calculated mortality associated with housing inequality as the difference between observed and expected deaths by applying mortality rates of the least deprived decile to other deciles. We also used standard life table calculations to estimate the potential years of life lost due housing inequality. Results: Up to 18.5% (95% CI 17.7–19.3) of all deaths between 1991 and 2020 may be associated with housing inequality, corresponding to 584,875 deaths. Over time, life expectancy at birth increased for the most and least deprived deciles by about 3.5 years. The gap in life expectancy between the two deciles remained high, on average 4.6 years. Life expectancy in Belgium would increase by approximately 3 years if all deciles had the mortality rates of the least deprived decile. Conclusions: Thousands of deaths in Belgium could be avoided if all Belgian neighborhoods had the mortality rates of the least deprived areas in terms of housing. Hotspots of housing inequalities need to be located and targeted with tailored public actions., SCOPUS: ar.j, info:eu-repo/semantics/published

info:eu-repo/semantics/inPress

In the past, African family are mostly considered as a stable institution. However, presently, the African family is a changing institution where the composition and structure are largely affected by the life trajectories caused by economic, sociopolitical and demographic dynamics. In a context where the family unit is the only institution that ensures well-being because of the lack of an efficient social security system and the insufficiency of public health services, these perturbations have an influence on the family’s ability to provide care to its most vulnerable members, especially children and the elderly. This thesis on family dynamics and child health in West Africa examines the consequences of this permanent family instability. Based on a longitudinal approach using data from five Health and Demographic surveillance systems located in Burkina Faso (Ouagadougou and Nanoro), Senegal (Niakhar and Mlomp) and The Gambia (Farafenni), it revisits the family environment from the children’s point of view and examines its influence on health via immunization and under 5 mortality., (POLS - Sciences politiques et sociales) -- UCL, 2021

Sibling survival histories are a major source of adult mortality estimates in countries where death registration is incomplete. We evaluate age and date reporting errors in sibling histories collected during a validation study in the Niakhar Health and Demographic Surveillance System (Senegal). Participants were randomly assigned to the questionnaire used in Demographic and Health Surveys or to a questionnaire incorporating an event history calendar, recall cues and increased probing strategies. We linked 60–62% of survey reports of siblings to the reference database using manual and probabilistic approaches. Both questionnaires had high sensitivity (>96%) and specificity (>97%) in recording the vital status of siblings. Respondents underestimated the ages of living siblings, ages at death, and the time since deaths. These reporting errors introduced downward biases in mortality estimates. The revised questionnaire improved the reporting of ages of living siblings but not the reporting of ages at death or the timing of deaths.

To meet the SDG requirement of spatial disaggregation of indicators, several methods have been developed to generate estimates of under-five mortality at the sub-national level. The reliability of sub-national mortality estimates in children aged 5-14 with the available survey data has not been evaluated so far. We generate Admin-1 sub-national estimates of the risk of dying in children aged less than five (5q0) and those aged 5 to 14 years old (10q5). We use 96 Demographic and Health Surveys (DHS) in 20 Sub-Saharan countries having at least 3 surveys designed to be representative at a sub-national level. The estimates account for the complex sample design of DHS and HIV-related biases in young children. A Bayesian space-time model previously developed for under-five mortality is used to smooth estimates across space and time in both age groups to reduce problems associated with data sparsity. The posterior distributions of the probability 10q5 are used to compute coefficients of variation and assess precision. Sufficiently precise estimates are retained to study the sub-national relationship between age-specific mortality rates (5q0 and 10q5), accounting for uncertainty in sub-national levels. Out of 1,132 space-time estimates, 62.3% are considered sufficiently precise with high heterogeneity across countries. Across all periods, sub-national estimates of mortality in children aged 0-4 are highly correlated with those in older children and young adolescents but this correlation is largely driven by the mortality decline. Within specific periods of time, it is often impossible to assess the relationship between mortality rates in the two age groups at the sub-national level, except in Nigeria, Ethiopia, Cameroon, Senegal and Zambia. As increased attention is devoted to survival after age 5, more research is needed to ensure that sub-national areas with specific interventions required for older children can be correctly identified.

Background - The global health community is devoting considerable attention to adolescents and young people, but risk of death in this population is poorly measured. We aimed to reconstruct global, regional, and national mortality trends for youths aged 15–24 years between 1990 and 2019. Methods - In this systematic analysis, we used all publicly available data on mortality in the age group 15–24 years for 195 countries, as compiled by the UN Inter-agency Group for Child Mortality Estimation. We used nationally representative vital registration data, estimated the completeness of death registration, and extracted mortality rates from surveys with sibling histories, household deaths reported in censuses, and sample registration systems. We used a Bayesian B-spline bias-reduction model to generate trends in 10q15, the probability that an adolescent aged 15 years would die before reaching age 25 years. This model treats observations of the 10q15 probability as the product of the actual risk of death and an error multiplier that varies depending on the data source. The main outcome that we assessed was the levels of and trends in youth mortality and the global and regional mortality rates from 1990 to 2019. Findings - Globally, the probability of an individual dying between age 15 years and 24 years was 11.2 deaths (90% uncertainty interval [UI] 10.7–12.5) per 1000 youths aged 15 in 2019, which is about 2.5 times less than infant mortality (28.2 deaths [27.2–30.0] by age 1 year per 1000 live births) but is higher than the risk of dying from age 1 to 5 (9.7 deaths [9.1–11.1] per 1000 children aged 1 year). The probability of dying between age 15 years and 24 years declined by 1.4% per year (90% UI 1.1–1.8) between 1990 and 2019, from 17.1 deaths (16.5–18.9) per 1000 in 1990; by contrast with this total decrease of 34% (27–41), under-5 mortality declined by 59% (56–61) in this period. The annual number of deaths declined from 1.7 million (90% UI 1.7–1.9) in 1990 to 1.4 mi

In sub-Saharan African cities, the dearth of accurate and detailed data is a major problem in the study of health and socioeconomic changes driven by rapid urbanization. Data on both health determinants and health outcomes are often lacking or are of poor quality. Proxies associated with socioeconomic differences are needed to compensate the lack of data. One of the most straightforward proxies is housing quality, which is a multidimensional concept including characteristics of both the built and natural environments. In this work, we combined the 2013 census data with remotely sensed land cover and land use data at a very high resolution in order to develop an integrated housing quality-based typology of the neighbourhoods in Dakar, Senegal. Principal component analysis and hierarchical classification were used to derive neighbourhood housing quality indices and four neighbourhood profiles. Paired tests revealed significant variations in the censusderived mortality rates between profile 1, associated with the lowest housing quality, and the three other profiles. These findings demonstrate the importance of housing quality as an important health risk factor. From a public health perspective, it should be a useful contribution for geographically targeted planning health policies, at the neighbourhood spatial level, which is the most appropriate administrative level for interventions.

Strengthening civil registration systems requires a better understanding of motivations and barriers related to the registration of deaths. We used data from the 2013 Senegalese census to identify deaths that are more likely to be registered in the Dakar region, where the completeness of death registration is higher than 80%. We also interviewed relatives of the deceased whose death had been registered to collect data on reasons for registration and sources of information about the process. The likelihood of death registration was positively associated with age at death and household wealth. Death registration was also more likely in households whose head was older, had attended school, and had a birth certificate. At the borough commune level, the geographical accessibility of civil registration centres and population density were both positively associated with completeness of death registration. The main motivations for registering deaths were compliance with the legal obligation to do so and willingness to obtain a burial permit and a death certificate. Families, health facilities, and friends were the primary sources of information about death registration. Further research is needed to identify effective interventions to increase death registration completeness in Dakar, particularly amongst the poorest households and neighbourhoods on the outskirts of the city.

The COVID-19 pandemic has caused major mortality shocks in many countries. Yet few studies have evaluated the heterogeneity of the mortality shock at a sub-national level. First, we assess the change in subnational mortality levels’ heterogeneity in 2020 versus previous years. Then, we measure the shock of the pandemic using loss in life expectancy between the observed and projected districts life expectancy. We used the Chiang method to account for the uncertainty in life table computations at the district scale in 2020. We propose a method to project districts life expectancy in 2020. The Bayesian modelling approach makes it easy to combine the different sources of uncertainty in the shock assessment. This is of particular interest at a finer geographical scale characterized by high stochastic variation in annual death counts. Heterogeneity in the impact of the pandemic on all-cause mortality across districts is substantial, with some districts barely showing any impact whereas the Bruxelles-Capital and Mons districts show a decrease in life expectancy at birth of 2.5 (95\% CI: 1.9-3.1) and 2.3 (95\% CI: 1.3-3.4) years, respectively. Providing sub-national mortality estimates with their uncertainty is key to understand why certain areas have been hard hit in comparison to others.

As child mortality has declined in developing countries, more people are reaching older ages, yet little is known about old age mortality in these settings, where civil registration and vital statistics is lacking. Surveys can be a good alternative, but existing data collection instruments do not cover deaths above age 60. We propose using parental survival histories (PSH) which build on four simple questions – vital status of biological parents, age of parent, or age at death, and timing of death. We examine sample selection biases in mortality estimates from PSH. We employ data from Health and Demographic Surveillance Systems (HDSS) to assess the possible correlation between mortality rates above age 50 and the time-varying number of surviving children of “respondent age”, using semi-parametric Cox models. Preliminary analysis, on three HDSS in Senegal suggests that women who have never had children have higher survival than women who have had children, but there seem to be no differences in female survival according to the number of female surviving children. These results are encouraging, suggesting that selection bias in PSH may only be an artifact of having children or not, and not the number of children alive to report on their parent’s survival.

Sibling survival histories are widely used to estimate adult mortality in low- and middle-income countries with deficient death registration statistics. However, collecting full sibling histories is time-consuming because they require asking questions about ages at survey time or ages at death and time of death. Using data from 53 countries and microsimulations, we evaluate the performance of an indirect method requiring only summary sibling histories (the total number of siblings who reached 15 years and those alive at the time of the survey). We also introduce two new period-derived methods which focus on recent deaths, using a synthetic cohort approach or imputing a date of birth for each sibling based on the age of the respondent. We demonstrate that reliable estimates can be obtained from summary sibling histories, opening up new possibilities for measuring mortality through censuses or rapid surveys conducted in settings disrupted by conflict, disaster, or epidemics.

As observed with many indicators, there is substantial spatial variation in gender bias in child mortality in India, reflecting the varying extent of daughter-neglect across subnational areas. With this context, this study aims to examine the role of key demographic and socioeconomic factors explaining district-level variation in the index of female disadvantage in under-five mortality, using district-level census data and geographically weighted regression (GWR) models for 1991 and 2011. Our study shows that the extent of female disadvantage has greatly reduced in India between the 1991 and 2011 census, with the number of districts with an index larger than 0.15% declining from 347 to 239 districts over the period. Despite this, the pockets of districts with atypically significant high values of female disadvantage were broadly the same in 1991 and 2011. Factors such as higher fertility, higher gender inequality, and poor economic condition have emerged as the significant local predictors of the index of female disadvantage in the districts from these regions. Findings from this study suggest that tackling gender inequality in child mortality in a regionally diverse country like India requires designing context-specific interventions.

In countries lacking comprehensive systems of death registration, adult mortality rates are regularly estimated from parental survival through the orphanhood method. The HIV epidemic has introduced breaches in assumptions underpinning this method, for example due to increased correlation between maternal and child survival. This study evaluates the magnitude of HIV-related bias in orphanhood-based estimates and introduces new adjustments. A set of 576 populations with substantial mortality from AIDS are generated with microsimulations. Orphanhood estimates are compared to the underlying mortality levels. Revised coefficients to convert proportions of respondents with surviving parents into survivorship probabilities are calculated and applied to survey and census data from 16 African countries facing severe HIV epidemics. Without adjustment for HIV-related biases, the orphanhood method produces downward-biased mortality levels, with mean percentage errors reaching 37% in reports from young children aged 5-14 in simulations. Unbiased mortality rates can be obtained by combining two sets of proportions of parents surviving, and using revised coefficients accounting for trends in seroprevalence and coverage of antiretroviral therapy. In most countries with large HIV epidemics, this new approach provides estimates that are in agreement with those of the United Nations. Orphanhood-based estimates can fill data gaps on adult mortality in low- and middle-income countries, including those with high HIV prevalence. Further research is needed to correct for biases in male mortality inferred from paternal orphanhood.

In sub-Saharan African cities, the dearth of accurate and detailed data is a major problem in the study of health and socioeconomic changes driven by rapid urbanization. Data on both health determinants and health outcomes are often lacking or are of poor quality. Proxies associated with socioeconomic differences are needed to compensate the lack of data. One of the most straightforward proxies is housing quality, which is a multidimensional concept including characteristics of both the built and natural environments. In this work, we combined the 2013 census data with remotely sensed land cover and land use data at a very high resolution in order to develop an integrated housing quality-based typology of the neighbourhoods in Dakar, Senegal. Principal component analysis and hierarchical classification were used to derive neighbourhood housing quality indices and four neighbourhood profiles. Paired tests revealed significant variations in the censusderived mortality rates between profile 1, associated with the lowest housing quality, and the three other profiles. These findings demonstrate the importance of housing quality as an important health risk factor. From a public health perspective, it should be a useful contribution for geographically targeted planning health policies, at the neighbourhood spatial level, which is the most appropriate administrative level for interventions., SCOPUS: ar.j, info:eu-repo/semantics/published

Background: In sub-Saharan Africa, socioeconomic factors such as place of residence, mother’s educational level, or household wealth, are strongly associated with risk factors of under-five mortality (U5M) such as health behavior or exposure to diseases and injuries. The aim of the study was to assess the relative contribution of four known socioeconomic factors to the variability in U5M in sub-Saharan countries. Methods: The study was based on birth histories from the Demographic and Health Surveys conducted in 32 sub-Saharan countries in 2010–2016. The relative contribution of sex of the child, place of residence, mother’seducational level, and household wealth to the variability in U5M was assessed using a regression-based decomposition of a Gini-type index. Results: The Gini index–measuring the variability in U5M related to the four socioeconomic factors–varied from0.006 (95%CI: 0.001–0.010) in Liberia 2013 to 0.034 (95%CI: 0.029–0.039) in Côte d’Ivoire 2011/12. The main contributors to the Gini index (with a relative contribution higher than 25%) were different across countries:mother’s educational level in 13 countries, sex of the child in 12 countries, household wealth in 11 countries, and place of residence in 8 countries (in some countries, more than one main contributor was identified). Conclusions: Factors related to socioeconomic status exert varied effects on the variability in U5M in sub-Saharan African countries. The findings provide evidence in support of prioritizing intersectoral interventions aiming at improving child survival in all subgroups of a population.

Background Trends in cause-specific mortality in most African countries are currently estimated from epidemiological models because the coverage of the civil registration system is low and national statistics on causes of death are unreliable at the national level. We aim to evaluate the performance of the death notification system in Antananarivo, the capital city of Madagascar, to inform cause-of-death statistics. Methods Information on the sex of the deceased, dates of birth and death, and underlying cause of death were transcribed from death registers maintained in Antananarivo. Causes of death were coded in ICD-9 and mapped to cause categories from the Global Burden of Disease 2016 Study (GBD). The performance of the notification system was assessed based on the Vital Statistics Performance Index, including six dimensions: completeness of death registration, quality of cause of death reporting, quality of age and sex reporting, internal consistency, level of cause-specific detail, and data availability and timeliness. We redistributed garbage codes and compared cause-specific mortality fractions in death records and estimates from the GBD with concordance correlation coefficients. Results The death notification system in Antananarivo performed well on most dimensions, although 31% of all deaths registered over the period 1976–2015 were assigned to ICD codes considered as “major garbage codes” in the GBD 2016. The completeness of death notification, estimated with indirect demographic techniques, was higher than 90% in the period 1975–1993, and recent under-five mortality rates were consistent with estimates from Demographic and Health Surveys referring to the capital city. After redistributing garbage codes, cause-specific mortality fractions derived from death notification data were consistent with GBD 2016 for the whole country in the 1990s, with concordance correlation coefficients higher than 90%. There were larger deviations in recent years, with concordan

Description of the Moramanga health survey in urban and rural areas in Madagascar (MHURAM) project

Objectives More than 20 people die each year in snow avalanches in Switzerland. Previous studies have primarily described these victims, but were not population based. We investigated sociodemographic factors for avalanche mortality between 1995 and 2014 in the entire Swiss resident population. Design and methods Within the Swiss National Cohort we ascertained avalanche deaths by anonymous data linkage with the avalanche accident database at the Swiss WSL Institute of Snow and Avalanche Research SLF. We calculated incidence rates, by dividing the number of deaths from avalanches by the number of person-years, and hazard ratios (HRs) for sociodemographic and economic characteristics using Cox proportional hazard models. Results The data linkage yielded 250 deaths from avalanche within the SNC population for the 20 years 1995 to 2014. The median distance between the place of residence and the place of the event (avalanche) was 61.1 km. Male gender, younger age (15–45 years), Swiss nationality, living in the Alpine regions, higher education, living in the highest socioeconomic quintile of neighbourhoods, being single, and living in a household with one or more children were associated with higher avalanche mortality rates. Furthermore, for younger persons (<40 years) the hazard of dying in an avalanche between 2005 and 2014 was significantly lower than in the years 1995 to 2004 (HR = 0.56, 95%-CI: 0.36–0.85). Conclusion Over a 20-year period in Switzerland, higher rates of dying in an avalanche were observed in men, in younger age groups, and persons with tertiary education, living in the highest socioeconomic quintile of neighbourhoods, and living in an Alpine region. For younger persons (<40 years), the hazard declined during the study period.

Background: In low- and middle-income countries (LMICs), data on causes of death is often inaccurate or incomplete. In this paper, we test whether adding a few questions about injuries and accidents to mortality questionnaires used in representative household surveys would yield accurate estimates of the extent of mortality due to external causes (accidents, homicides, or suicides). Methods: We conduct a validation study in Niakhar (Senegal), during which we compare reported survey data to high-quality prospective records of deaths collected by a health and demographic surveillance system (HDSS). Results: Survey respondents more frequently list the deaths of their adult siblings who die of external causes than the deaths of those who die from other causes. The specificity of survey data is high, but sensitivity is low. Among reported deaths, less than 60% of the deaths classified as due to external causes by the HDSS are also classified as such by survey respondents. Survey respondents better report deaths due to road-traffic accidents than deaths from suicides and homicides. Conclusions: Asking questions about deaths resulting from injuries and accidents during surveys might help measure mortality from external causes in LMICs, but the resulting data displays systematic bias in a rural population of Senegal. Future studies should 1) investigate whether similar biases also apply in other settings and 2) test new methods to further improve the accuracy of survey data on mortality from external causes. Contribution: This study helps strengthen the monitoring of sustainable development targets in LMICs by validating a simple approach for the measurement of mortality from external causes.

Les femmes représentent 59% des personnes infectées par le virus du sida en Afrique subsaharienne, mais 47% des décès adultes liés au VIH. Pour bien comprendre leur surreprésentation dans la population séropositive, il faut considérer les différences entre hommes et femmes dans trois domaines : l’exposition au risque d’infection, la susceptibilité à l’infection, et la survie après l’infection. L’avantage féminin en matière d’espérance de vie, qui s’était réduit jusqu’au début des années 2000 suite à l’épidémie de sida, se creuse à nouveau depuis la généralisation des traitements.

Comprehensive analysis of the impact of humanitarian emergencies on nutrition and mortality is limited in Ethiopia. This is mainly due to either the lack of nationally representative data or non-generalizability of subnational health surveys in such settings. Consequently, humanitarian decisions and advocacy are often based on anecdotal information or non-representative data with limited geographical coverage. The aims of this study are therefore to investigate the burden of malnutrition and mortality, and to identify its causes in humanitarian settings. Given the data challenges, we apply advanced epidemiological methods in existing population-based health surveys. The key findings are: i) the burden of child undernutrition is declining, but are persistent and higher in moderate drought areas; ii) the burden of child mortality falls below both the emergency and baseline thresholds for sub-Saharan Africa; iii) the burden of women’s undernutrition is higher near the borders. On the basis of these findings, we provide propositions to guide effective humanitarian interventions., (SP - Sciences de la santé publique) -- UCL, 2018

Background From 1990 to 2016, the mortality of children younger than 5 years decreased by more than half, and there are plentiful data regarding mortality in this age group through which we can track global progress in reducing the under-5 mortality rate. By contrast, little is known on how the mortality risk among older children (5–9 years) and young adolescents (10–14 years) has changed in this time. We aimed to estimate levels and trends in mortality of children aged 5–14 years in 195 countries from 1990 to 2016. Methods In this analysis of empirical data, we expanded the United Nations Inter-agency Group for Child Mortality Estimation database containing data on children younger than 5 years with 5530 data points regarding children aged 5–14 years. Mortality rates from 1990 to 2016 were obtained from nationally representative birth histories, data on household deaths reported in population censuses, and nationwide systems of civil registration and vital statistics. These data were used in a Bayesian B-spline bias-reduction model to generate smoothed trends with 90% uncertainty intervals, to determine the probability of a child aged 5 years dying before reaching age 15 years. Findings Globally, the probability of a child dying between the ages 5 years and 15 years was 7·5 deaths (90% uncertainty interval 7·2–8·3) per 1000 children in 2016, which was less than a fifth of the risk of dying between birth and age 5 years, which was 41 deaths (39–44) per 1000 children. The mortality risk in children aged 5–14 years decreased by 51% (46–54) between 1990 and 2016, despite not being specifically targeted by health interventions. The annual number of deaths in this age group decreased from 1·7 million (1·7 million–1·8 million) to 1 million (0·9 million–1·1 million) in 1990–2016. In 1990–2000, mortality rates in children aged 5–14 years decreased faster than among children aged 0–4 years. However, since 2000, mortality rates in children younger than 5 years have decreased

Evidence regarding differences in mortality between urban and rural areas of Sub-Saharan Africa has been largely based on the experience of children. Urban-rural mortality differentials in adults are often obtained by inferring from child mortality rates and model life tables. However, the rapid urbanization in Sub-Saharan Africa is associated with some health challenges specific to adults, such as HIV/AIDS, tuberculosis, occupational hazards, violence, road traffic accidents, and a growing burden of non-communicable diseases. For this reason, urban-rural mortality differentials in adults should be measured, and not modelled. Measuring these differentials, and making sense of the resulting estimates also requires to take into account the issue of migration. Urban and rural areas are historically interlinked through important migration flows. In this context, the main objectives of this dissertation are to contribute to the measurement of urban-rural mortality differentials in adults and to the analysis of the impact of migration on that differential in Sub-Saharan Africa. The analysis draws mainly on the case of Burkina Faso, and combines various sources of data, (including sample surveys, Health and Demographic Surveillance Systems, and censuses) to circumvent the scarcity of data on adult survival. This dissertation shows that mortality indicators derived from censuses in rural areas can be severely underestimated, in particular in women. The measurement of urban-rural mortality differentials based on census data can be affected by underreporting of deaths, age misreporting and misreporting of the place of residence of deceased persons due to the mobility of dying individuals. Apart from censuses, other sources of data on adult survival based on the survival of close relatives (parents and siblings) are also plagued by underreporting of deaths, and most importantly missing information on the place of residence of individuals exposed to the risk of dying. Despite t, (POLS - Sciences politiques et sociales) -- UCL, 2018

En 2017 un million d’enfants ayant entre 5 et 15 ans sont morts dans le monde. Le risque pour un enfant fêtant son 5e anniversaire de mourir avant d'atteindre son 15e anniversaire s’élève à 7,2 pour mille, il est cinq fois moindre que celui pour un nouveauné de mourir avant son 5e anniversaire (39 pour mille). La mortalité entre 5 et 15 ans a baissé de moitié entre 1990 et 2017. Elle est concentrée dans les pays à revenu faible et moyen. L'Afrique de l’Ouest et l'Afrique centrale rassemblent à elles seules un tiers des décès mondiaux en 2017. Dans ces régions, la probabilité de décéder à ces âges est plus de vingt fois plus élevée qu'en Europe de l’Ouest.

Based on data from Ouagadougou and Nanoro HDSSs, this research aims to analyse the interaction between migration and fertility for men and women, as well as the relationship between this interaction and the processes of fertility transition and urban transition in Burkina Faso. In order to achieve this goal, migration is analyzed as a fertility factor and fertility as a migration factor. The period analysed is from 1st January 2010 to 1st January 2014. In addition to descriptive analyses, the relationships between migration and fertility are estimated using Cox proportional risk models. The originality of this research is in the presentation of a comparative analysis of the interaction between migration and fertility for men and women. Taking return migration into account enriches the basic assumptions of the relationship between migration and fertility, socialization, selection, adaptation and disruption, with those of readaptation and diffusion. Return migration is set as a distinct and complementary process to outward migration. The results highlighted a process of areal fertility transformation due to the differentiated selection of migrants in rural and urban areas according to their reproductive behaviour and their destination. The socialization of rural-rural migrants, return migration to rural areas and rural-urban male migration maintain high rural fertility. The level of fertility is related to the contextual characteristics of the studied area and the decline in fertility in the urban area is associated with the transformation of these contextual characteristics., Basée sur les données des observatoires de population de Ouagadougou et Nanoro, cette recherche a pour objectif l'analyse de l'interaction entre la migration et la fécondité pour les hommes et les femmes, ainsi que la relation entre cette interaction et les processus de transition de la fécondité et de transition urbaine au Burkina Faso. Afin d'atteindre cet objectif, la migration est analysée comme facteur de la fécondité et la fécondité comme facteur de la migration. La période analysée s'étend du 1er janvier 2010 au 1er janvier 2014. Hormis les analyses descriptives, les relations de cause à effet entre la migration et la fécondité ont été estimées à l'aide de modèles à risques proportionnels de Cox. L'originalité de cette recherche est de présenter une analyse comparative de l'interaction entre la migration et la fécondité pour les hommes et les femmes. La prise en compte de la migration de retour conduit à enrichir les hypothèses de bases de la relation entre la migration et la fécondité, la Socialisation, la Sélection, l'Adaptation et la Perturbation, avec celles de la Réadaptation et de la Diffusion. La migration de retour se présente comme un processus distinct et complémentaire de la migration allée. Les résultats ont mis en avant un processus de transformation spatiale de la fécondité à cause de la sélection différentiée des migrants dans les milieux rural et urbain en fonction de comportement reproductif et de leur milieu de destination. La socialisation des migrants intraruraux, les migrations de retour vers le milieu rural et les migrations masculines rurale-urbaines entretiennent la forte fécondité rurale. Le niveau de la fécondité est lié aux caractéristiques du milieu étudié et la baisse de la fécondité dans le milieu urbain est associée à la transformation des caractéristiques contextuelles., (POLS - Sciences politiques et sociales) -- UCL, 2018

Objective: To compare the 2016 United Nations Programme on HIV/AIDS (UNAIDS) modelled estimates of adult mortality in sub-Saharan Africa to empirical estimates. Design: Age-specific mortality rates were obtained from nationally representative sibling survival data, recent household deaths and vital registration, and directly compared with UNAIDS estimates. Orphanhood prevalence derived from UNAIDS mortality estimates was compared with survey and census reports on the survival of children's parents. Methods: Age-specific mortality rates for adults aged 15–59 years were calculated from Demographic and Health Surveys and deaths reported in censuses or vital registration, adjusted for underreporting, whenever possible. Proportions of orphans were extracted from censuses and surveys for children aged 5–9 years. Results: UNAIDS estimates were significantly higher than sibling mortality estimates, except among men in countries with very high HIV prevalence. There was a better agreement between rates based on household deaths or vital registration and model outputs. Sex ratios (M/F) of adult mortality were lower in UNAIDS estimates. The modelled orphan prevalence was significantly higher than in surveys and censuses, again with the exception of paternal orphans in countries with very high HIV prevalence. Ratios of paternal-to-maternal orphans were lower in the UNAIDS model than surveys and censuses. Among women, increases in mortality due to AIDS were more concentrated in the age range 25–50 years in model outputs, as compared with empirical estimates. Conclusion: Discrepancies in levels, sex ratios and age patterns of adult mortality between empirical and UNAIDS estimates call for additional data quality assessments and improvements in estimation methods.

Low survival prospects, especially among adults, are holding back African development and reducing the chances to reap a demographic dividend. Gains in life expectancy have lagged far behind those experienced in other regions, despite impressive mortality declines among children under age five in the last decade. With a life expectancy still below 60 in 2015, Sub-Saharan Africa is also the region where uncertainty about levels and trends in mortality is the greatest. This is because the vital registration systems operating in the vast majority of countries fail to provide full national coverage. Few deaths have a cause certified by a medical practitioner, and there is limited evidence on the leading causes of death to make informed decisions about how to spend scarce human and financial resources. This chapter provides a cursory overview of the different data sources, and present trends in mortality among children and adults, using survey reports on the survival of close relatives. The chapter then describes major changes in the leading causes of death and highlights specific characteristics of the process of demographic aging in SSA.

Entre 1990 et 2015, la plupart des pays du monde ont enregistré de remarquables progrès en matière de survie. En 25 ans, l’espérance de vie à la naissance a augmenté en moyenne de 12 ans dans les pays à faible revenu, de 7 ans dans les pays à revenu intermédiaire et de 5 ans dans ceux à revenu élevé (tableau annexe ; Nations unies, 2015). Ces progrès ont touché toutes les régions, avec des gains de 7 ans en Asie de l’Est et de l’Ouest, de près de 8 ans en Amérique latine, et de 9 et 10 ans dans les deux régions les plus désavantagées au départ, l’Asie du Sud et centrale et l’Afrique subsaharienne. Tous les groupes d’âges ont enregistré des reculs de mortalité, mais les progrès ont été particulièrement importants chez les enfants. Dans le monde, le nombre de décès à moins de 5 ans est passé de 12,7 millions en 1990 à 5,9 millions en 2015 (UN IGME, 2015), le risque de mortalité à ces âges est passé de 91 à 43 décès pour 1000 naissances. Ces progrès ne se sont pas effectués au même rythme dans toutes les régions, les pays, les milieux d’habitat ou les groupes sociaux, si bien que les inégalités qui caractérisent les chances de survie dans ces pays ont également évolué au cours des 25 dernières années., Between 1990 and 2015, life expectancy increased substantially in most low- and middle-income countries, although progress was very uneven. This article provides an overview of trends in early childhood mortality (0-5 years) and adult mortality (15-60 years) in the 109 low- and middle-income countries with populations of more than one million. It analyses trends in geographical and gender disparities across countries, and patterns of within-country inequalities (education, living standards, place of residence) in ten countries with very different socioeconomic, political and demographic characteristics (Afghanistan, Bolivia, Brazil, Burkina Faso, China, Egypt, India, Indonesia, Nigeria, South Africa). It takes a new look at the epidemiological transition and makes a detailed analysis of AIDS mortality and maternal deaths. Progress has benefited children especially, and often (though not always) women and the most disadvantaged countries or social groups. It would be premature to speak of mortality convergence, however, since despite the progress made, inequalities between and within countries remain large and deserve particular attention from public health policy makers and scientists.

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.

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.

The rapid decline in mortality in sub-Saharan African countries, mostly driven by improved survival below age 5, has resulted in an expansion of kinship networks around children. However, this increase in the number of related kin is not necessarily reflected in co-residential household arrangements or domestic units of children. Migration flows and the reconfiguration of domestic units can offset the expansion of kin groups induced by demographic changes. The articulation between "observed kinship" around children and the entire "potential kinship" is however difficult to apprehend from conventional survey or census data which usually only consider co-residential living arrangements. Here we compare the extent of the “potential kinship” network of children estimated from microsimulations with the “observed kinship” measured with a demographic survey located in a rural area in Mali, and examine their evolution as mortality declines. This comparison shows that despite the important increase in the number of children’s close kin, the number of relatives around children in their domestic unit stays fairly stable over time, because of migrations and reconfiguration of these units.

Background: Women’s malnutrition, particularly undernutrition, remains an important public health challenge in Ethiopia. Although various studies examined the levels and determinants of women’s nutritional status, the influence of living close to an international border on women’s nutrition has not been investigated. Yet, Ethiopian borders are regularly affected by conflict and refugee flows, which might ultimately impact health. Objective: To investigate the impact of living close to borders in the nutritional status of women in Ethiopia, while considering other important covariates. Design: Our analysis was based on the body mass index (BMI) of 6,334 adult women aged 20–49 years, obtained from the 2011 Ethiopian Demographic and Health Survey (EDHS). A Bayesian multilevel multinomial logistic regression analysis was used to capture the clustered structure of the data and the possible correlation that may exist within and between clusters. Results: After controlling for potential confounders, women living close to borders (i.e. ≤100 km) in Ethiopia were 59% more likely to be underweight (posterior odds ratio [OR]=1.59; 95% credible interval [CrI]: 1.32–1.90) than their counterparts living far from the borders. This result was robust to different choices of border delineation (i.e. ≤50, ≤75, ≤125, and ≤150 km). Women from poor families, those who have no access to improved toilets, reside in lowland areas, and are Muslim, were independently associated with underweight. In contrast, more wealth, higher education, older age, access to improved toilets, being married, and living in urban or lowlands were independently associated with overweight. Conclusions: The problem of undernutrition among women in Ethiopia is most worrisome in the border areas. Targeted interventions to improve nutritional status in these areas, such as improved access to sanitation, economic and livelihood support, are recommended.

Estimating child mortality worldwide is a challenging issue. Due to the lack of comprehensive vital registration system in most of countries, analysts rely principally on birth histories collected retrospectively among women of reproductive age in censuses and surveys. More specifically, summary birth histories that consist in the simplest pieces of data – the number of children ever born and children surviving – constitute a low-cost alternative to vital registration systems. This dissertation provides new knowledge on indirect methods for estimating the under-five mortality rate from summary birth histories. Two types of indirect methods are currently available to users: model-based methods derived from the pioneering work of Brass and empirically based methods developed more recently at the Institute for Health Metrics and Evaluation (IHME). Using microsimulation, variants of summary birth history methods were studied under different demographic conditions reflecting international experiences. The dissertation tops out with new recommendations and advocates for a methodological shift toward empirically based methods., (POLS - Sciences politiques et sociales) -- UCL, 2016

Analyses de l'évolution des inégalités sociales de mortalité en Belgique et de ses déterminants (emploi, logement, niveau d'instruction, état-civil)