Measuring and forecasting progress towards the education-related SDG targets.

Education is a key dimension of well-being and a crucial indicator of development1-4. The Sustainable Development Goals (SDGs) prioritize progress in education, with a new focus on inequality5-7. Here we model the within-country distribution of years of schooling, and use this model to explore educational inequality since 1970 and to forecast progress towards the education-related 2030 SDG targets. We show that although the world is largely on track to achieve near-universal primary education by 2030, substantial challenges remain in the completion rates for secondary and tertiary education. Globally, the gender gap in schooling had nearly closed by 2018 but gender disparities remained acute in parts of sub-Saharan Africa, and North Africa and the Middle East. It is predicted that, by 2030, females will have achieved significantly higher educational attainment than males in 18 countries. Inequality in education reached a peak globally in 2017 and is projected to decrease steadily up to 2030. The distributions and inequality metrics presented here represent a framework that can be used to track the progress of each country towards the SDG targets and the level of inequality over time. Reducing educational inequality is one way to promote a fairer distribution of human capital and the development of more equitable human societies.

Life Expectancy for White, Black, and Hispanic Race/Ethnicity in U.S. States: Trends and Disparities, 1990 to 2019.

BACKGROUND: Life expectancy (LE) differences within and between states by race/ethnicity have not been examined. OBJECTIVE: To estimate LE for selected race/ethnicity groups in states from 1990 to 2019. DESIGN: Cross-sectional time-series analysis. SETTING: United States. PARTICIPANTS: Deidentified death records and Census data were used to construct regression models with smoothed time series of mortality from 1990 to 2019. MEASUREMENTS: LE at birth, by sex and year, for subgroups of people reporting Hispanic, non-Hispanic Black, or non-Hispanic White race/ethnicity. RESULTS: Disparities in LE across states were 8.0 years for females and 12.2 years for males in 1990 and 7.9 years for females and 7.8 years for males in 2019. When race/ethnicity groups were accounted for, disparities across states were 20.7 years for females and 24.5 years for males in 1990, decreasing to 18.5 years for females and 23.7 years for males in 2019. Disparities across states increased within each race/ethnicity group between 1990 and 2019, with the largest increase for non-Hispanic White males and the smallest for Hispanic females. The disparity between race/ethnicity groups within states decreased for most of the 23 states with estimates for all 3 groups but increased for females in 7 states and males in 5 states. LIMITATION: Because of small sample size, LE was not estimated for 37 of 153 state-race/ethnicity groups. CONCLUSION: Disparity in LE across states was greater when race/ethnicity groups were considered. Disparities across all state-race/ethnicity groups in general have decreased over the past 3 decades. Within each race/ethnicity group, disparities across states have increased. Although racial/ethnic disparities decreased in most of the 23 states for which LE was estimated for all 3 groups, they increased for females in 7 states and males in 5 states. PRIMARY FUNDING SOURCE: National Heart, Lung, and Blood Institute.

Parental education and inequalities in child mortality: a global systematic review and meta-analysis.

BACKGROUND: The educational attainment of parents, particularly mothers, has been associated with lower levels of child mortality, yet there is no consensus on the magnitude of this relationship globally. We aimed to estimate the total reductions in under-5 mortality that are associated with increased maternal and paternal education, during distinct age intervals. METHODS: This study is a comprehensive global systematic review and meta-analysis of all existing studies of the effects of parental education on neonatal, infant, and under-5 child mortality, combined with primary analyses of Demographic and Health Survey (DHS) data. The literature search of seven databases (CINAHL, Embase, MEDLINE, PsycINFO, PubMed, Scopus, and Web of Science) was done between Jan 23 and Feb 8, 2019, and updated on Jan 7, 2021, with no language or publication date restrictions. Teams of independent reviewers assessed each record for its inclusion of individual-level data on parental education and child mortality and excluded articles on the basis of study design and availability of relevant statistics. Full-text screening was done in 15 languages. Data extracted from these studies were combined with primary microdata from the DHS for meta-analyses relating maternal or paternal education with mortality at six age intervals: 0-27 days, 1-11 months, 1-4 years, 0-4 years, 0-11 months, and 1 month to 4 years. Novel mixed-effects meta-regression models were implemented to address heterogeneity in referent and exposure measures among the studies and to adjust for study-level covariates (wealth or income, partner's years of schooling, and sex of the child). This study was registered with PROSPERO (CRD42020141731). FINDINGS: The systematic review returned 5339 unique records, yielding 186 included studies after exclusions. DHS data were compiled from 114 unique surveys, capturing 3 112 474 livebirths. Data extracted from the systematic review were synthesized together with primary DHS data, for meta-analysis on a total of 300 studies from 92 countries. Both increased maternal and paternal education showed a dose-response relationship linked to reduced under-5 mortality, with maternal education emerging as a stronger predictor. We observed a reduction in under-5 mortality of 31·0% (95% CI 29·0-32·6) for children born to mothers with 12 years of education (ie, completed secondary education) and 17·3% (15·0-18·8) for children born to fathers with 12 years of education, compared with those born to a parent with no education. We also showed that a single additional year of schooling was, on average, associated with a reduction in under-5 mortality of 3·04% (2·82-3·23) for maternal education and 1·57% (1·35-1·72) for paternal education. The association between higher parental education and lower child mortality was significant for both parents at all ages studied and was largest after the first month of life. The meta-analysis framework incorporated uncertainty associated with each individual effect size into the model fitting process, in an effort to decrease the risk of bias introduced by study design and quality. INTERPRETATION: To our knowledge, this study is the first effort to systematically quantify the transgenerational importance of education for child survival at the global level. The results showed that lower maternal and paternal education are both risk factors for child mortality, even after controlling for other markers of family socioeconomic status. This study provides robust evidence for universal quality education as a mechanism to achieve the Sustainable Development Goal target 3.2 of reducing neonatal and child mortality. FUNDING: Research Council of Norway, Bill & Melinda Gates Foundation, and Rockefeller Foundation-Boston University Commission on Social Determinants, Data, and Decision Making (3-D Commission).

Measuring human capital: a systematic analysis of 195 countries and territories, 1990-2016.

BACKGROUND: Human capital is recognised as the level of education and health in a population and is considered an important determinant of economic growth. The World Bank has called for measurement and annual reporting of human capital to track and motivate investments in health and education and enhance productivity. We aim to provide a new comprehensive measure of human capital across countries globally. METHODS: We generated a period measure of expected human capital, defined for each birth cohort as the expected years lived from age 20 to 64 years and adjusted for educational attainment, learning or education quality, and functional health status using rates specific to each time period, age, and sex for 195 countries from 1990 to 2016. We estimated educational attainment using 2522 censuses and household surveys; we based learning estimates on 1894 tests among school-aged children; and we based functional health status on the prevalence of seven health conditions, which were taken from the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016). Mortality rates specific to location, age, and sex were also taken from GBD 2016. FINDINGS: In 2016, Finland had the highest level of expected human capital of 28·4 health, education, and learning-adjusted expected years lived between age 20 and 64 years (95% uncertainty interval 27·5-29·2); Niger had the lowest expected human capital of less than 1·6 years (0·98-2·6). In 2016, 44 countries had already achieved more than 20 years of expected human capital; 68 countries had expected human capital of less than 10 years. Of 195 countries, the ten most populous countries in 2016 for expected human capital were ranked: China at 44, India at 158, USA at 27, Indonesia at 131, Brazil at 71, Pakistan at 164, Nigeria at 171, Bangladesh at 161, Russia at 49, and Mexico at 104. Assessment of change in expected human capital from 1990 to 2016 shows marked variation from less than 2 years of progress in 18 countries to more than 5 years of progress in 35 countries. Larger improvements in expected human capital appear to be associated with faster economic growth. The top quartile of countries in terms of absolute change in human capital from 1990 to 2016 had a median annualised growth in gross domestic product of 2·60% (IQR 1·85-3·69) compared with 1·45% (0·18-2·19) for countries in the bottom quartile. INTERPRETATION: Countries vary widely in the rate of human capital formation. Monitoring the production of human capital can facilitate a mechanism to hold governments and donors accountable for investments in health and education. FUNDING: Institute for Health Metrics and Evaluation.

Forecasting life expectancy, years of life lost, and all-cause and cause-specific mortality for 250 causes of death: reference and alternative scenarios for 2016-40 for 195 countries and territories.

BACKGROUND: Understanding potential trajectories in health and drivers of health is crucial to guiding long-term investments and policy implementation. Past work on forecasting has provided an incomplete landscape of future health scenarios, highlighting a need for a more robust modelling platform from which policy options and potential health trajectories can be assessed. This study provides a novel approach to modelling life expectancy, all-cause mortality and cause of death forecasts -and alternative future scenarios-for 250 causes of death from 2016 to 2040 in 195 countries and territories. METHODS: We modelled 250 causes and cause groups organised by the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) hierarchical cause structure, using GBD 2016 estimates from 1990-2016, to generate predictions for 2017-40. Our modelling framework used data from the GBD 2016 study to systematically account for the relationships between risk factors and health outcomes for 79 independent drivers of health. We developed a three-component model of cause-specific mortality: a component due to changes in risk factors and select interventions; the underlying mortality rate for each cause that is a function of income per capita, educational attainment, and total fertility rate under 25 years and time; and an autoregressive integrated moving average model for unexplained changes correlated with time. We assessed the performance by fitting models with data from 1990-2006 and using these to forecast for 2007-16. Our final model used for generating forecasts and alternative scenarios was fitted to data from 1990-2016. We used this model for 195 countries and territories to generate a reference scenario or forecast through 2040 for each measure by location. Additionally, we generated better health and worse health scenarios based on the 85th and 15th percentiles, respectively, of annualised rates of change across location-years for all the GBD risk factors, income per person, educational attainment, select intervention coverage, and total fertility rate under 25 years in the past. We used the model to generate all-cause age-sex specific mortality, life expectancy, and years of life lost (YLLs) for 250 causes. Scenarios for fertility were also generated and used in a cohort component model to generate population scenarios. For each reference forecast, better health, and worse health scenarios, we generated estimates of mortality and YLLs attributable to each risk factor in the future. FINDINGS: Globally, most independent drivers of health were forecast to improve by 2040, but 36 were forecast to worsen. As shown by the better health scenarios, greater progress might be possible, yet for some drivers such as high body-mass index (BMI), their toll will rise in the absence of intervention. We forecasted global life expectancy to increase by 4·4 years (95% UI 2·2 to 6·4) for men and 4·4 years (2·1 to 6·4) for women by 2040, but based on better and worse health scenarios, trajectories could range from a gain of 7·8 years (5·9 to 9·8) to a non-significant loss of 0·4 years (-2·8 to 2·2) for men, and an increase of 7·2 years (5·3 to 9·1) to essentially no change (0·1 years [-2·7 to 2·5]) for women. In 2040, Japan, Singapore, Spain, and Switzerland had a forecasted life expectancy exceeding 85 years for both sexes, and 59 countries including China were projected to surpass a life expectancy of 80 years by 2040. At the same time, Central African Republic, Lesotho, Somalia, and Zimbabwe had projected life expectancies below 65 years in 2040, indicating global disparities in survival are likely to persist if current trends hold. Forecasted YLLs showed a rising toll from several non-communicable diseases (NCDs), partly driven by population growth and ageing. Differences between the reference forecast and alternative scenarios were most striking for HIV/AIDS, for which a potential increase of 120·2% (95% UI 67·2-190·3) in YLLs (nearly 118 million) was projected globally from 2016-40 under the worse health scenario. Compared with 2016, NCDs were forecast to account for a greater proportion of YLLs in all GBD regions by 2040 (67·3% of YLLs [95% UI 61·9-72·3] globally); nonetheless, in many lower-income countries, communicable, maternal, neonatal, and nutritional (CMNN) diseases still accounted for a large share of YLLs in 2040 (eg, 53·5% of YLLs [95% UI 48·3-58·5] in Sub-Saharan Africa). There were large gaps for many health risks between the reference forecast and better health scenario for attributable YLLs. In most countries, metabolic risks amenable to health care (eg, high blood pressure and high plasma fasting glucose) and risks best targeted by population-level or intersectoral interventions (eg, tobacco, high BMI, and ambient particulate matter pollution) had some of the largest differences between reference and better health scenarios. The main exception was sub-Saharan Africa, where many risks associated with poverty and lower levels of development (eg, unsafe water and sanitation, household air pollution, and child malnutrition) were projected to still account for substantive disparities between reference and better health scenarios in 2040. INTERPRETATION: With the present study, we provide a robust, flexible forecasting platform from which reference forecasts and alternative health scenarios can be explored in relation to a wide range of independent drivers of health. Our reference forecast points to overall improvements through 2040 in most countries, yet the range found across better and worse health scenarios renders a precarious vision of the future-a world with accelerating progress from technical innovation but with the potential for worsening health outcomes in the absence of deliberate policy action. For some causes of YLLs, large differences between the reference forecast and alternative scenarios reflect the opportunity to accelerate gains if countries move their trajectories toward better health scenarios-or alarming challenges if countries fall behind their reference forecasts. Generally, decision makers should plan for the likely continued shift toward NCDs and target resources toward the modifiable risks that drive substantial premature mortality. If such modifiable risks are prioritised today, there is opportunity to reduce avoidable mortality in the future. However, CMNN causes and related risks will remain the predominant health priority among lower-income countries. Based on our 2040 worse health scenario, there is a real risk of HIV mortality rebounding if countries lose momentum against the HIV epidemic, jeopardising decades of progress against the disease. Continued technical innovation and increased health spending, including development assistance for health targeted to the world's poorest people, are likely to remain vital components to charting a future where all populations can live full, healthy lives. FUNDING: Bill & Melinda Gates Foundation.

U.S. Children "Learning Online" during COVID-19 without the Internet or a Computer: Visualizing the Gradient by Race/Ethnicity and Parental Educational Attainment.

The coronavirus disease 2019 pandemic has caused unprecedented disruptions to education in the United States, with a large proportion of schooling moving to online formats, which has the potential to exacerbate existing racial/ethnic and socioeconomic disparities in learning. The authors visualize access to online learning technologies using data from the Household Pulse Survey from the early fall 2020 school period (August 19 to October 26). The authors find that 10.1 percent of children participating in online learning nationally did not have adequate access to the Internet and a computer. Rates of inadequate access varied nearly 20-fold across the gradient of parental race/ethnicity and education, from 1.9 percent for children of Asian parents with graduate degrees to 35.5 percent among children of Black parents with less than a high school education. These findings indicate alarming gaps in potential learning among U.S. children. Renewed investments in equitable access to distance-learning resources will be necessary to prevent widening racial/ethnic and class learning disparities.

Form and Function in Human Song.

Humans use music for a variety of social functions: we sing to accompany dance, to soothe babies, to heal illness, to communicate love, and so on. Across animal taxa, vocalization forms are shaped by their functions, including in humans. Here, we show that vocal music exhibits recurrent, distinct, and cross-culturally robust form-function relations that are detectable by listeners across the globe. In Experiment 1, internet users (n = 750) in 60 countries listened to brief excerpts of songs, rating each song's function on six dimensions (e.g., "used to soothe a baby"). Excerpts were drawn from a geographically stratified pseudorandom sample of dance songs, lullabies, healing songs, and love songs recorded in 86 mostly small-scale societies, including hunter-gatherers, pastoralists, and subsistence farmers. Experiment 1 and its analysis plan were pre-registered. Despite participants' unfamiliarity with the societies represented, the random sampling of each excerpt, their very short duration (14 s), and the enormous diversity of this music, the ratings demonstrated accurate and cross-culturally reliable inferences about song functions on the basis of song forms alone. In Experiment 2, internet users (n = 1,000) in the United States and India rated three contextual features (e.g., gender of singer) and seven musical features (e.g., melodic complexity) of each excerpt. The songs' contextual features were predictive of Experiment 1 function ratings, but musical features and the songs' actual functions explained unique variance in function ratings. These findings are consistent with the existence of universal links between form and function in vocal music.