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Background: Assessments of age-specific mortality and life expectancy have been done by the UN Population Division, Department of Economics and Social Affairs (UNPOP), the United States Census Bureau, WHO, and as part of previous iterations of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD). Previous iterations of the GBD used population estimates from UNPOP, which were not derived in a way that was internally consistent with the estimates of the numbers of deaths in the GBD. The present iteration of the GBD, GBD 2017, improves on previous assessments and provides timely estimates of the mortality experience of populations globally. Methods: The GBD uses all available data to produce estimates of mortality rates between 1950 and 2017 for 23 age groups, both sexes, and 918 locations, including 195 countries and territories and subnational locations for 16 countries. Data used include vital registration systems, sample registration systems, household surveys (complete birth histories, summary birth histories, sibling histories), censuses (summary birth histories, household deaths), and Demographic Surveillance Sites. In total, this analysis used 8259 data sources. Estimates of the probability of death between birth and the age of 5 years and between ages 15 and 60 years are generated and then input into a model life table system to produce complete life tables for all locations and years. Fatal discontinuities and mortality due to HIV/AIDS are analysed separately and then incorporated into the estimation. We analyse the relationship between age-specific mortality and development status using the Socio-demographic Index, a composite measure based on fertility under the age of 25 years, education, and income. There are four main methodological improvements in GBD 2017 compared with GBD 2016: 622 additional data sources have been incorporated; new estimates of population, generated by the GBD study, are used; statistical methods used in different components of the analysis have been further standardised and improved; and the analysis has been extended backwards in time by two decades to start in 1950. Findings: Globally, 187% (95% uncertainty interval 184â€Ì190) of deaths were registered in 1950 and that proportion has been steadily increasing since, with 588% (582â€Ì593) of all deaths being registered in 2015. At the global level, between 1950 and 2017, life expectancy increased from 481 years (465â€Ì496) to 705 years (701â€Ì708) for men and from 529 years (517â€Ì540) to 756 years (753â€Ì759) for women. Despite this overall progress, there remains substantial variation in life expectancy at birth in 2017, which ranges from 491 years (465â€Ì517) for men in the Central African Republic to 876 years (869â€Ì881) among women in Singapore. The greatest progress across age groups was for children younger than 5 years; under-5 mortality dropped from 2160 deaths (1963â€Ì2381) per 1000 livebirths in 1950 to 389 deaths (356â€Ì4283) per 1000 livebirths in 2017, with huge reductions across countries. Nevertheless, there were still 54 million (52â€Ì56) deaths among children younger than 5 years in the world in 2017. Progress has been less pronounced and more variable for adults, especially for adult males, who had stagnant or increasing mortality rates in several countries. The gap between male and female life expectancy between 1950 and 2017, while relatively stable at the global level, shows distinctive patterns across super-regions and has consistently been the largest in central Europe, eastern Europe, and central Asia, and smallest in south Asia. Performance was also variable across countries and time in observed mortality rates compared with those expected on the basis of development. Interpretation: This analysis of age-sex-specific mortality shows that there are remarkably complex patterns in population mortality across countries. The findings of this study highlight global successes, such as the large decline in under-5 mortality, which reflects significant local, national, and global commitment and investment over several decades. However, they also bring attention to mortality patterns that are a cause for concern, particularly among adult men and, to a lesser extent, women, whose mortality rates have stagnated in many countries over the time period of this study, and in some cases are increasing. Funding: Bill & Melinda Gates Foundation. © 2018 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license

A number of prospective cohort studies are ongoing worldwide to investigate the impact of foetal and neonatal exposures to chemical substances on child health. To assess multiple exposure (mixture) effects and low prevalence health outcomes it is useful to pool data from several studies and conduct mega-data-analysis. To discuss a path towards data harmonization, representatives from several large-scale birth cohort studies and a biomonitoring programme formed a collaborative group, the Environment and Child Health International Birth Cohort Group (ECHIBCG). In this study, an intra-laboratory trial was performed to harmonize existing blood lead measurements within the groups' studies. Then, decentralized analyses were conducted in individual countries' laboratories to evaluate blood lead levels (BLL) in each study. The measurements of pooled BLL samples in French, German and three Japanese laboratories resulted in an overall mean blood lead concentration of 8.66 ng¯1 (95% confidence interval: 8.59-8.72 ng¯1) with 3.0% relative standard deviation. Except for China's samples, BLL from each study were comparable with mean concentrations below or close to 10ng¯1. The decentralized multivariate analyses revealed that all models had coefficients of determination below 0.1. Determinants of BLL were current smoking, age >35 years and overweight or obese status. The three variables were associated with an increase in BLL in each of the five studies, most strongly in France by almost 80% and the weakest effect being in Norway with only 15%; for Japan, with the far largest sample (~18,000), the difference was 36%. This study successfully demonstrated that the laboratory analytical methods were sufficiently similar to allow direct comparison of data and showed that it is possible to harmonize the epidemiological data for joint analysis. This exercise showed the challenges in decentralized data analyses and reinforces the need for data harmonization among studies. © 2019 The Authors. Published by Elsevier GmbH.

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