Sex differences in mortality among children, adolescents, and young people aged 0-24 years: a systematic assessment of national, regional, and global trends from 1990 to 2021.

BACKGROUND: Differences in mortality exist between sexes because of biological, genetic, and social factors. Sex differentials are well documented in children younger than 5 years but have not been systematically examined for ages 5-24 years. We aimed to estimate the sex ratio of mortality from birth to age 24 years and reconstruct trends in sex-specific mortality between 1990 and 2021 for 200 countries, major regions, and the world. METHODS: We compiled comprehensive databases on the mortality sex ratio (ratio of male to female mortality rates) for individuals aged 0-4 years, 5-14 years, and 15-24 years. The databases contain mortality rates from death registration systems, full birth and sibling histories from surveys, and reports on household deaths in censuses. We modelled the sex ratio of age-specific mortality as a function of the mortality in both sexes using Bayesian hierarchical time-series models. We report the levels and trends of sex ratios and estimate the expected female mortality and excess female mortality rates (the difference between the estimated female mortality and the expected female mortality) to identify countries with outlying sex ratios. FINDINGS: Globally, the mortality sex ratio was 1·13 (ie, boys were more likely to die than girls of the same age) for ages 0-4 years (90% uncertainty interval 1·11 to 1·15) in 2021. This ratio increased with age to 1·16 (1·12 to 1·20) for 5-14 years, reaching 1·65 for 15-24 years (1·52 to 1·75). In all age groups, the global sex ratio of mortality increased between 1990 and 2021, driven by faster declines in female mortality. In 2021, the probability of a newborn male reaching age 25 years was 94·1% (93·7 to 94·4), compared with 95·1% for a newborn female (94·7 to 95·3). We found a disadvantage of females versus males (compared with countries with similar total mortality) in 2021 in five countries for ages 0-4 years (Algeria, Bangladesh, Egypt, India, and Iran), one country (Suriname) for ages 5-14 years, and 13 countries for ages 15-24 years (including Bangladesh and India). We found the reverse pattern (disadvantage of males vs females compared with countries of similar total mortality) in one country in ages 0-4 years (Vietnam) and eight countries in ages 15-24 years (including Brazil and Mexico). Globally, the number of excess female deaths from birth to age 24 years was 86 563 (-6059 to 164 000) in 2021, down from 544 636 (453 982 to 633 265) in 1990. INTERPRETATION: The global sex ratio of mortality for all age groups in the first 25 years of life increased between 1990 and 2021. Targeted interventions should focus on countries with outlying sex ratios of mortality to reduce disparities due to discrimination in health care, nutrition, and violence. FUNDING: The Bill & Melinda Gates Foundation, US Agency for International Development, and King Abdullah University of Science and Technology.

New Measures for Family Planning and Exposure to Risk of Pregnancy Based on Sexual Activity and Contraceptive Use Data.

Family planning measures for unmarried women are based on contraceptive demand and use among sexually active women. Sexual activity status is commonly defined based on comparing reported time-since-last-sex to a cutoff time, with women defined to be sexually active if their most recent sex was within the last four weeks. While easy to understand and compute, this approach to constructing family planning measures results in a limited understanding of family planning and exposure to unintended pregnancy because it cannot comprehensively capture the frequency of sex at the population level. We propose a new statistical approach to quantify sexual activity, using reported time-since-last-sex data. Based on estimated frequencies of sex among users and nonusers in need of family planning, we propose new family planning measures, including the ratio of protected exposure over all women's exposure to risk of unintended pregnancy.

Alignment between Desires and Outcomes among Women Wanting to Avoid Pregnancy: A Global Comparative Study of "Conditional" Unintended Pregnancy Rates.

Since childbearing desires, and trends in these desires, differ across populations, the inclusion of women who want to become pregnant in the denominator for unintended pregnancy rates complicates interpretation of intercountry differences and trends over time. To address this limitation, we propose a rate that is the ratio of the number of unintended pregnancies to the number of women wanting to avoid pregnancy; we term these conditional rates. We computed conditional unintended pregnancy rates for five-year periods from 1990 to 2019. In 2015-2019, these conditional rates per 1,000 women per year wanting to avoid pregnancy ranged from 35 in Western Europe to 258 in Middle Africa. Rates with all women of reproductive age in the denominator have concealed stark global disparities in the ability of women to avoid unintended pregnancies, and they have understated progress in regions where the fraction of women wanting to avoid pregnancy has increased.

A Bayesian Cohort Component Projection Model to Estimate Women of Reproductive Age at the Subnational Level in Data-Sparse Settings.

Accurate estimates of subnational populations are important for policy formulation and monitoring population health indicators. For example, estimates of the number of women of reproductive age are important to understand the population at risk of maternal mortality and unmet need for contraception. However, in many low-income countries, data on population counts and components of population change are limited, and so subnational levels and trends are unclear. We present a Bayesian constrained cohort component model for the estimation and projection of subnational populations. The model builds on a cohort component projection framework, incorporates census data and estimates from the United Nation's World Population Prospects, and uses characteristic mortality schedules to obtain estimates of population counts and the components of population change, including internal migration. The data required as inputs to the model are minimal and available across a wide range of countries, including most low-income countries. The model is applied to estimate and project populations by county in Kenya for 1979-2019 and is validated against the 2019 Kenyan census.

Country-specific estimates of unintended pregnancy and abortion incidence: a global comparative analysis of levels in 2015-2019.

INTRODUCTION: Internationally comparable estimates of unintended pregnancy and abortion incidence can illuminate disparities in sexual and reproductive health and autonomy. Country-specific estimates are essential to enable international comparison, and to inform country-level policy and programming. METHODS: We developed a Bayesian model which jointly estimated unintended pregnancy and abortion rates using information on contraceptive needs and use, contraceptive method mix, birth rates, the proportions of births from unintended pregnancies and abortion incidence data. Main outcomes were the estimated rates of unintended pregnancy and abortion for 150 countries and territories, reported for the 5-year period 2015-2019, as annual averages per 1000 women aged 15-49 years. RESULTS: Estimated unintended pregnancy rates ranged from 11 (80% uncertainty interval: 9 to 13) in Montenegro to 145 (131 to 159) in Uganda per 1000 women aged 15-49 years. Between-country heterogeneity was substantial in all Sustainable Development Goal (SDG) regions, but was greatest in sub-Saharan Africa. Estimated abortion rates ranged from 5 (5 to 6) in Singapore to 80 (55 to 113) in Georgia. Variation between country estimates was similar in all SDG regions except for Europe and Northern America, where estimated abortion rates were generally lower. CONCLUSION: The estimates reflect variation in the degree to unintended pregnancy and abortion that are experienced in countries throughout the world. This evidence highlights the importance of investing in access to contraception and comprehensive abortion care, including in regions which may have lower rates of unintended pregnancy or abortion, respectively, as countries may differ substantially from regional averages.

Estimating misclassification errors in the reporting of maternal mortality in national civil registration vital statistics systems: A Bayesian hierarchical bivariate random walk model to estimate sensitivity and specificity for multiple countries and years with missing data.

Civil registration vital statistics (CRVS) systems provide data on maternal mortality that can be used for monitoring trends and to inform policies and programs. However, CRVS maternal mortality data may be subject to substantial reporting errors due to misclassification of maternal deaths. Information on misclassification is available for selected countries and periods only. We developed a Bayesian hierarchical bivariate random walk model to estimate sensitivity and specificity for multiple populations and years and used the model to estimate misclassification errors in the reporting of maternal mortality in CRVS systems. The proposed Bayesian misclassification (BMis) model captures differences in sensitivity and specificity across populations and over time, allows for extrapolations to periods with missing data, and includes an exact likelihood function for data provided in aggregated form. Validation exercises using maternal mortality data suggest that BMis is reasonably well calibrated and improves upon the CRVS-adjustment approach used until 2018 by the UN Maternal Mortality Inter-Agency Group (UN-MMEIG) to account for bias in CRVS data resulting from misclassification error. Since 2019, BMis is used by the UN-MMEIG to account for misclassification errors when estimating maternal mortality using CRVS data.

Global, regional, and national trends in under-5 mortality between 1990 and 2019 with scenario-based projections until 2030: a systematic analysis by the UN Inter-agency Group for Child Mortality Estimation.

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 scenario. FINDINGS: The global U5MR decreased by 59% (90% uncertainty interval [UI] 56-61) from 93·0 (91·7-94·5) deaths per 1000 livebirths in 1990 to 37·7 (36·1-40·8) in 2019, while the annual number of global under-5 deaths declined from 12·5 (12·3-12·7) million in 1990 to 5·2 (5·0-5·6) million in 2019-a 58% (55-60) reduction. The global NMR decreased by 52% (90% UI 48-55) from 36·6 (35·6-37·8) deaths per 1000 livebirths in 1990, to 17·5 (16·6-19·0) in 2019, and the annual number of global neonatal deaths declined from 5·0 (4·9-5·2) million in 1990, to 2·4 (2·3-2·7) million in 2019, a 51% (47-54) reduction. As of 2019, 122 of 195 countries have achieved the SDG U5MR target, and 20 countries are on track to achieve the target by 2030, while 53 will need to accelerate progress to meet the target by 2030. 116 countries have reached the SDG NMR target with 16 on track, leaving 63 at risk of missing the target. If current trends continue, 48·1 million under-5 deaths are projected to occur between 2020 and 2030, almost half of them projected to occur during the neonatal period. If all countries met the SDG target on under-5 mortality, 11 million under-5 deaths could be averted between 2020 and 2030. INTERPRETATION: As a result of effective global health initiatives, millions of child deaths have been prevented since 1990. However, the task of ending all preventable child deaths is not done and millions more deaths could be averted by meeting international targets. Geographical and economic variation demonstrate the possibility of even lower mortality rates for children under age 5 years and point to the regions and countries with highest mortality rates and in greatest need of resources and action. FUNDING: Bill & Melinda Gates Foundation, US Agency for International Development.

Temporal Models for Demographic and Global Health Outcomes in Multiple Populations: Introducing a New Framework to Review and Standardise Documentation of Model Assumptions and Facilitate Model Comparison.

There is growing interest in producing estimates of demographic and global health indicators in populations with limited data. Statistical models are needed to combine data from multiple data sources into estimates and projections with uncertainty. Diverse modelling approaches have been applied to this problem, making comparisons between models difficult. We propose a model class, Temporal Models for Multiple Populations (TMMPs), to facilitate both documentation of model assumptions in a standardised way and comparison across models. The class makes a distinction between the process model, which describes latent trends in the indicator interest, and the data model, which describes the data generating process of the observed data. We provide a general notation for the process model that encompasses many popular temporal modelling techniques, and we show how existing models for a variety of indicators can be written using this notation. We end with a discussion of outstanding questions and future directions.

Using family planning service statistics to inform model-based estimates of modern contraceptive prevalence.

The annual assessment of Family Planning (FP) indicators, such as the modern contraceptive prevalence rate (mCPR), is a key component of monitoring and evaluating goals of global FP programs and initiatives. To that end, the Family Planning Estimation Model (FPEM) was developed with the aim of producing survey-informed estimates and projections of mCPR and other key FP indictors over time. With large-scale surveys being carried out on average every 3-5 years, data gaps since the most recent survey often exceed one year. As a result, survey-based estimates for the current year from FPEM are often based on projections that carry a larger uncertainty than data informed estimates. In order to bridge recent data gaps we consider the use of a measure, termed Estimated Modern Use (EMU), which has been derived from routinely collected family planning service statistics. However, EMU data come with known limitations, namely measurement errors which result in biases and additional variation with respect to survey-based estimates of mCPR. Here we present a data model for the incorporation of EMU data into FPEM, which accounts for these limitations. Based on known biases, we assume that only changes in EMU can inform FPEM estimates, while also taking inherent variation into account. The addition of this EMU data model to FPEM allows us to provide a secondary data source for informing and reducing uncertainty in current estimates of mCPR. We present model validations using a survey-only model as a baseline comparison and we illustrate the impact of including the EMU data model in FPEM. Results show that the inclusion of EMU data can change point-estimates of mCPR by up to 6.7 percentage points compared to using surveys only. Observed reductions in uncertainty were modest, with the width of uncertainty intervals being reduced by up to 2.7 percentage points.

Global, regional, and national estimates and trends in stillbirths from 2000 to 2019: a systematic assessment.

BACKGROUND: Stillbirths are a major public health issue and a sensitive marker of the quality of care around pregnancy and birth. The UN Global Strategy for Women's, Children's and Adolescents' Health (2016-30) and the Every Newborn Action Plan (led by UNICEF and WHO) call for an end to preventable stillbirths. A first step to prevent stillbirths is obtaining standardised measurement of stillbirth rates across countries. We estimated stillbirth rates and their trends for 195 countries from 2000 to 2019 and assessed progress over time. METHODS: For a systematic assessment, we created a dataset of 2833 country-year datapoints from 171 countries relevant to stillbirth rates, including data from registration and health information systems, household-based surveys, and population-based studies. After data quality assessment and exclusions, we used 1531 datapoints to estimate country-specific stillbirth rates for 195 countries from 2000 to 2019 using a Bayesian hierarchical temporal sparse regression model, according to a definition of stillbirth of at least 28 weeks' gestational age. Our model combined covariates with a temporal smoothing process such that estimates were informed by data for country-periods with high quality data, while being based on covariates for country-periods with little or no data on stillbirth rates. Bias and additional uncertainty associated with observations based on alternative stillbirth definitions and source types, and observations that were subject to non-sampling errors, were included in the model. We compared the estimated stillbirth rates and trends to previously reported mortality estimates in children younger than 5 years. FINDINGS: Globally in 2019, an estimated 2·0 million babies (90% uncertainty interval [UI] 1·9-2·2) were stillborn at 28 weeks or more of gestation, with a global stillbirth rate of 13·9 stillbirths (90% UI 13·5-15·4) per 1000 total births. Stillbirth rates in 2019 varied widely across regions, from 22·8 stillbirths (19·8-27·7) per 1000 total births in west and central Africa to 2·9 (2·7-3·0) in western Europe. After west and central Africa, eastern and southern Africa and south Asia had the second and third highest stillbirth rates in 2019. The global annual rate of reduction in stillbirth rate was estimated at 2·3% (90% UI 1·7-2·7) from 2000 to 2019, which was lower than the 2·9% (2·5-3·2) annual rate of reduction in neonatal mortality rate (for neonates aged <28 days) and the 4·3% (3·8-4·7) annual rate of reduction in mortality rate among children aged 1-59 months during the same period. Based on the lower bound of the 90% UIs, 114 countries had an estimated decrease in stillbirth rate since 2000, with four countries having a decrease of at least 50·0%, 28 having a decrease of 25·0-49·9%, 50 having a decrease of 10·0-24·9%, and 32 having a decrease of less than 10·0%. For the remaining 81 countries, we found no decrease in stillbirth rate since 2000. Of these countries, 34 were in sub-Saharan Africa, 16 were in east Asia and the Pacific, and 15 were in Latin America and the Caribbean. INTERPRETATION: Progress in reducing the rate of stillbirths has been slow compared with decreases in the mortality rate of children younger than 5 years. Accelerated improvements are most needed in the regions and countries with high stillbirth rates, particularly in sub-Saharan Africa. Future prevention of stillbirths needs increased efforts to raise public awareness, improve data collection, assess progress, and understand public health priorities locally, all of which require investment. FUNDING: Bill & Melinda Gates Foundation and the UK Foreign, Commonwealth and Development Office.

Projecting sex imbalances at birth at global, regional and national levels from 2021 to 2100: scenario-based Bayesian probabilistic projections of the sex ratio at birth and missing female births based on 3.26 billion birth records.

INTRODUCTION: Skewed levels of the sex ratio at birth (SRB) due to sex-selective abortions have been observed in several countries since the 1970s. They will lead to long-term sex imbalances in more than one-third of the world's population with yet unknown social and economic impacts on affected countries. Understanding the potential evolution of sex imbalances at birth is therefore essential for anticipating and planning for changing sex structures across the world. METHODS: We produced probabilistic SRB projections from 2021 to 2100 based on different scenarios of sex ratio transition and assessed their implications in terms of missing female births at global, regional and national levels. Based on a comprehensive SRB database with 3.26 billion birth records, we project the skewed SRB and missing female births with a Bayesian hierarchical time series mixture model. The SRB projections under reference scenario S1 assumed SRB transitions only for countries with strong statistical evidence of SRB inflation, and the more extreme scenario S2 assumed a sex ratio transition for countries at risk of SRB inflation but with no or limited evidence of ongoing inflation. RESULTS: Under scenario S1, we projected 5.7 (95% uncertainty interval (1.2; 15.3)) million additional missing female births to occur by 2100. Countries affected will be those already affected in the past by imbalanced SRB, such as China and India. If all countries at risk of SRB inflation experience a sex ratio transition as in scenario S2, the projected missing female births increase to 22.1 (12.2; 39.8) million with a sizeable contribution of sub-Saharan Africa. CONCLUSION: The scenario-based projections provide important illustrations of the potential burden of future prenatal sex discrimination and the need to monitor SRBs in countries with son preference. Policy planning will be needed in the years to come to minimise future prenatal sex discrimination and its impact on social structures.

Fpemlocal: Estimating family planning indicators in R for a single population of interest.

The global Family Planning Estimation model (FPEM) combines a Bayesian hierarchical model with country-specific time trends to yield estimates of contraceptive prevalence and unmet need for family planning for countries worldwide. In this paper, we introduce the R package fpemlocal that carries out the estimation of family planning indicators for a single population, for example, for a single country or smaller area. In this implementation of FPEM, all non-population-specific parameters are fixed at outcomes obtained in a prior global FPEM run. The development of this model was motivated by the demand for computational efficiency, without loss of model accuracy, when estimates and projections from FPEM were needed only for a single country. We present use cases to produce estimates for a single population of women by union status or all women based on package-provided data bases and user-specified data. We also explain how to aggregate estimates across multiple populations. The R package forms the basis of the Track20 Family Planning Estimation Tool to monitor trends in family planning indicators for the FP2020 initiative. Fpemlocal is available from: https://github.com/AlkemaLab/fpemlocal.

Global, regional, and national mortality trends in youth aged 15-24 years between 1990 and 2019: a systematic analysis.

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 million (1·3-1·5) in 2019. In sub-Saharan Africa, the number of deaths increased by 20·8% from 1990 to 2019. Although 18·3% of the population aged 15-24 years were living in sub-Saharan Africa in 2019, the region accounted for 37·9% (90% UI 34·8-41·9) of all worldwide deaths in youth. INTERPRETATION: It is urgent to accelerate progress in reducing youth mortality. Efforts are particularly needed in sub-Saharan Africa, where the burden of mortality is increasingly concentrated. In the future, a growing number of countries will see youth mortality exceeding under-5 mortality if current trends continue. FUNDING: UN Children's Fund, Bill & Melinda Gates Foundation, United States Agency for International Development.

What increase in modern contraceptive use is needed in FP2020 countries to reach 75% demand satisfied by 2030? An assessment using the Accelerated Transition Method and Family Planning Estimation Model.

Background: Sustainable Development Goal 3.7 aims to ensure universal access to sexual and reproductive health services. One suggested benchmark is to have at least 75% of the demand for contraception satisfied with modern methods (DS) in all countries by 2030. The translation of DS-based targets into targets for the modern contraceptive prevalence rate (mCPR) is needed to make targets actionable. Methods: We propose the Accelerated Transition (AT) method for determining the mCPR needed to reach demand-satisfied targets by 2030. The starting point for this method is the projection of DS under "business as usual" using the one-country implementation of the Family Planning Estimation Model (FPEMcountry). For countries in which the DS target is projected to be later than 2030, the AT method assumes that meeting the DS target by 2030 requires an acceleration of the contraceptive use transition such that the DS target, and its associated mCPR, will be reached in 2030 as opposed to the later year. The DS-target-associated mCPR becomes the mCPR target for the year 2030. Results: We apply the AT method to assess progress needed for attaining the 75% DS target for married or in-union women in the world's poorest countries. For 50 out of 68 countries, we estimate that accelerations are needed, with required mCPR increases ranging from 4.3 to 50.8 percentage points. Conclusions: The AT method quantifies the acceleration needed - as compared to business as usual projections - for a country to meet a family planning target. The method can be used to determine the mCPR needed to reach demand-satisfied targets.

Unintended pregnancy and abortion by income, region, and the legal status of abortion: estimates from a comprehensive model for 1990-2019.

BACKGROUND: Unintended pregnancy and abortion estimates document trends in sexual and reproductive health and autonomy. These estimates inform and motivate investment in global health programmes and policies. Variability in the availability and reliability of data poses challenges for measuring and monitoring trends in unintended pregnancy and abortion. We developed a new statistical model that jointly estimated unintended pregnancy and abortion that aimed to better inform efforts towards global equity in sexual and reproductive health and rights. METHODS: We developed a model that simultaneously estimated incidence of unintended pregnancy and abortion within a Bayesian framework. Data on pregnancy intentions and abortion were compiled from country-based surveys, official statistics, and published studies found through a literature search, and we obtained data on livebirths from the World Population Prospects. We analysed results by World Bank income groups, Sustainable Development Goal regional groupings, and the legal status of abortion. FINDINGS: In 2015-19, there were 121·0 million unintended pregnancies annually (80% uncertainty interval [UI] 112·8-131·5), corresponding to a global rate of 64 unintended pregnancies (UI 60-70) per 1000 women aged 15-49 years. 61% (58-63) of unintended pregnancies ended in abortion (totalling 73·3 million abortions annually [66·7-82·0]), corresponding to a global abortion rate of 39 abortions (36-44) per 1000 women aged 15-49 years. Using World Bank income groups, we found an inverse relationship between unintended pregnancy and income, whereas abortion rates varied non-monotonically across groups. In countries where abortion was restricted, the proportion of unintended pregnancies ending in abortion had increased compared with the proportion for 1990-94, and the unintended pregnancy rates were higher than in countries where abortion was broadly legal. INTERPRETATION: Between 1990-94 and 2015-19, the global unintended pregnancy rate has declined, whereas the proportion of unintended pregnancies ending in abortion has increased. As a result, the global average abortion rate in 2015-19 was roughly equal to the estimates for 1990-94. Our findings suggest that people in high-income countries have better access to sexual and reproductive health care than those in low-income countries. Our findings indicate that individuals seek abortion even in settings where it is restricted. These findings emphasise the importance of ensuring access to the full spectrum of sexual and reproductive health services, including contraception and abortion care, and for additional investment towards equity in health-care services. FUNDING: UK Aid from the UK Government, Dutch Ministry of Foreign Affairs, UNDP/UNFPA/UNICEF/WHO/World Bank Special Programme of Research, Development and Research Training in Human Reproduction (HRP), and The Bill & Melinda Gates Foundation.

National, regional, and global levels and trends in neonatal mortality between 1990 and 2017, with scenario-based projections to 2030: a systematic analysis.

BACKGROUND: Reducing neonatal mortality is an essential part of the third Sustainable Development Goal (SDG), to end preventable child deaths. To achieve this aim will require an understanding of the levels of and trends in neonatal mortality. We therefore aimed to estimate the levels of and trends in neonatal mortality by use of a statistical model that can be used to assess progress in the SDG era. With these estimates of neonatal mortality between 1990 and 2017, we then aimed to assess how different targets for neonatal mortality could affect the burden of neonatal mortality from 2018 to 2030. METHODS: In this systematic analysis, we used nationally-representative empirical data related to neonatal mortality, including data from vital registration systems, sample registration systems, and household surveys, to estimate country-specific neonatal mortality rates (NMR; the probability of dying during the first 28 days of life) for all countries between 1990 (or the earliest year of available data) and 2017. For our analysis, we used all publicly available data on neonatal mortality from databases compiled annually by the UN Inter-agency Group for Child Mortality Estimation, which were extracted on or before July 31, 2018, for data relating to the period between 1950 and 2017. All nationally representative data were assessed. We used a Bayesian hierarchical penalised B-splines regression model, which allowed for data from different sources to be weighted differently, to account for variable biases and for the uncertainty in NMR to be assessed. The model simultaneously estimated a global association between NMR and under-5 mortality rate and country-specific and time-specific effects, which enabled us to identify countries with an NMR that was higher or lower than expected. Scenario-based projections were made at the county level by use of current levels of and trends in neonatal mortality and historic or annual rates of reduction that would be required to achieve national targets. The main outcome that we assessed was the levels of and trends in neonatal mortality and the global and regional NMRs from 1990 to 2017. FINDINGS: Between 1990 and 2017, the global NMR decreased by 51% (90% uncertainty interval [UI] 46-54), from 36·6 deaths per 1000 livebirths (35·5-37·8) in 1990, to 18·0 deaths per 1000 livebirths (17·0-19·9) in 2017. The estimated number of neonatal deaths during the same period decreased from 5·0 million (4·9 million-5·2 million) to 2·5 million (2·4 million-2·8 million). Annual NMRs vary widely across the world, but west and central Africa and south Asia had the highest NMRs in 2017. All regions have reported reductions in NMRs since 1990, and most regions accelerated progress in reducing neonatal mortality in 2000-17 versus 1990-2000. Between 2018 and 2030, we project that 27·8 million children will die in their first month of life if each country maintains its current rate of reduction in NMR. If each country achieves the SDG neonatal mortality target of 12 deaths per 1000 livebirths or fewer by 2030, we project 22·7 million cumulative neonatal deaths by 2030. More than 60 countries need to accelerate their progress to reach the neonatal mortality SDG target by 2030. INTERPRETATION: Although substantial progress has been made in reducing neonatal mortality since 1990, increased efforts to improve progress are still needed to achieve the SDG target by 2030. Accelerated improvements are most needed in the regions and countries with high NMR, particularly in sub-Saharan Africa and south Asia. FUNDING: Bill & Melinda Gates Foundation, United States Agency for International Development.

Systematic assessment of the sex ratio at birth for all countries and estimation of national imbalances and regional reference levels.

The sex ratio at birth (SRB; ratio of male to female live births) imbalance in parts of the world over the past few decades is a direct consequence of sex-selective abortion, driven by the coexistence of son preference, readily available technology of prenatal sex determination, and fertility decline. Estimation of the degree of SRB imbalance is complicated because of unknown SRB reference levels and because of the uncertainty associated with SRB observations. There are needs for reproducible methods to construct SRB estimates with uncertainty, and to assess SRB inflation due to sex-selective abortion. We compile an extensive database from vital registration systems, censuses and surveys with 10,835 observations, and 16,602 country-years of information from 202 countries. We develop Bayesian methods for SRB estimation for all countries from 1950 to 2017. We model the SRB regional and national reference levels, the fluctuation around national reference levels, and the inflation. The estimated regional reference levels range from 1.031 (95% uncertainty interval [1.027; 1.036]) in sub-Saharan Africa to 1.063 [1.055; 1.072] in southeastern Asia, 1.063 [1.054; 1.072] in eastern Asia, and 1.067 [1.058; 1.077] in Oceania. We identify 12 countries with strong statistical evidence of SRB imbalance during 1970-2017, resulting in 23.1 [19.0; 28.3] million missing female births globally. The majority of those missing female births are in China, with 11.9 [8.5; 15.8] million, and in India, with 10.6 [8.0; 13.6] million.

Pregnancies, abortions, and pregnancy intentions: a protocol for modeling and reporting global, regional and country estimates.

BACKGROUND: Estimates of pregnancies, abortions and pregnancy intentions can help assess how effectively women and couples are able to fulfil their childbearing aspirations. Abortion incidence estimates are also a necessary foundation for research on the safety of abortions performed and the consequences of unsafe abortion. Furthermore, periodic estimates of these indicators are needed to help inform policy and programmes. METHODS: We will develop a Bayesian hierarchical times series model which estimates levels and trends in pregnancy rates, abortion rates, and percentages of pregnancies and births unintended for each five-year period between 1990 and 2019. The model will be informed by data on abortion incidence and the percentage of births or pregnancies that were unintended. We will develop a data classification process to be applied to all available data. Model-based estimates and associated uncertainty will take account of data sparsity and quality. Our proposed approach will advance previous work in two key ways. First, we will estimate pregnancy and abortion rates simultaneously, and model the propensity to abort an unintended pregnancy, as opposed to modeling abortion rates directly as in prior work. Secondly, we will produce estimates that are reproducible at the country level by publishing the data inputs, data classification processes and source code. DISCUSSION: This protocol will form the basis for updated global, regional and national estimates of intended and unintended pregnancy rates, abortion rates, and the percent of unintended pregnancies ending in abortion, from 1990 to 2019.

Global, regional, and national mortality trends in older children and young adolescents (5-14 years) from 1990 to 2016: an analysis of empirical data.

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 faster than mortality rates in children aged 5-14 years. The annual rate of reduction in mortality among children younger than 5 years has been 4·0% (3·6-4·3) since 2000, versus 2·7% (2·3-3·0) in children aged 5-14 years. Older children and young adolescents in sub-Saharan Africa are disproportionately more likely to die than those in other regions; 55% (51-58) of deaths of children of this age occur in sub-Saharan Africa, despite having only 21% of the global population of children aged 5-14 years. In 2016, 98% (98-99) of all deaths of children aged 5-14 years occurred in low-income and middle-income countries, and seven countries alone accounted for more than half of the total number of deaths of these children. INTERPRETATION: Increased efforts are required to accelerate reductions in mortality among older children and to ensure that they benefit from health policies and interventions as much as younger children. FUNDING: UN Children's Fund, Bill & Melinda Gates Foundation, United States Agency for International Development.