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

ABSTRACT: Education is a key dimension of well-being and a crucial indicator of development^1-4. The Sustainable Development Goals (SDGs) prioritize progress in education, with a new focus on inequality^5-7. 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.

SUBMITTER: Friedman J

PROVIDER: S-EPMC7332421 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

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

Friedman Joseph J York Hunter H Graetz Nicholas N Woyczynski Lauren L Whisnant Joanna J Hay Simon I SI Gakidou Emmanuela E

Nature 20200415 7805

Education is a key dimension of well-being and a crucial indicator of development<sup>1-4</sup>. The Sustainable Development Goals (SDGs) prioritize progress in education, with a new focus on inequality<sup>5-7</sup>. 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-universa ...[more]

PMID: 32350468

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Project description:BackgroundThe provision of safe water, sanitation, and hygiene (WASH) facilities and services for schools is vital to students' health, development, and educational performance. However, school WASH coverage in developing countries remains low. This study aimed to assess the adequacy of WASH services in Addis Ababa, Ethiopia.MethodsA school-based quantitative cross-sectional study was conducted from January to March 2020 in 98 schools. A multistage sampling technique was used to select schools included in the study. Data were collected using observational checklists and pretested interviewer-administered questionnaires. We entered the data into EPI Info version 7.2.2.6 and analyzed using SPSS 22.0. Logistic regression was used to examine the associated factors with school WASH services.ResultsThe basic school water, sanitation, and hygiene services were found to be 65.3%, 31.6%, and 36.7%, respectively. The facility-to-student ratio was 1:48 for drinking water point, 1:59 for toilet stance, and 1:147 for handwashing point. The analysis of facilities access by sex revealed that the toilet to student ratio was 1:68 for females and 1:49 for males, whereas the handwashing point-to-student ratio was 1:179 for females and 1:114 for males, indicating disparities in facilities access by sex. The non-functionality rates for drinking water, toilets, and handwashing facilities were 22.5%, 8%, and 19.5%, respectively. School ownership was significantly associated with the availability of basic water services [COR = 4.6, 95% CI: 1.466-14.426] and basic sanitation services [COR = 15, 95% CI: 3.27-68.28]. Moreover, the results demonstrate training on WASH [COR = 5, 95% CI: 1.087-23.018] and teaching programs on WASH [COR = 0.21, 95% CI: 0.056-0.810] were significantly associated with basic hygiene services.ConclusionsThe provision of WASH facilities and services in schools was inadequate and not on track to meet the targets of SDG 6. Training, WASH education program, and stakeholder commitment and cooperation at all levels are required to achieve the goal.

Project description:BackgroundSustainable Development Goal 3 (SDG 3), focusing on ensuring healthy lives and well-being for all, holds global significance and is particularly vital for Bangladesh. Neonatal Mortality Rate (NMR), Under-5 Mortality Rate (U5MR), Maternal Mortality Ratio (MMR) and Death Rate Due to Road Traffic Injuries (RTI) are considered responsible indicators of SDG 3 progress in Bangladesh. The objective of the study is to forecast these indicators of Bangladesh up to 2030 and compare these forecasts with predetermined 2030 targets. The data is obtained from the World Bank's (WB) website.MethodFor forecasting, time series models were employed, specifically Autoregressive Integrated Moving Average- ARIMA (0,2,1) with Akaike Information Criterion (AIC) 94.6 for NMR and ARIMA (2,1,2) with AIC 423.2 for U5MR, selected based on their lowest AIC values. Additionally, Machine Learning (ML) models, including Bidirectional Recurrent Neural Networks (BRNN) and Elastic Neural Networks (ENET), were employed for all the indicators.ResultsENET demonstrates superior performance compared to both BRNN and ARIMA in the context of NMR, achieving a Root Mean Absolute Error (RMAE) of 0.603446 and a Root Mean Square Error (RMSE) of 0.451162. Furthermore, when considering U5MR, MMR, and Death Rate Due to RTI, ENET consistently exhibits lower error metrics compared to the alternative models. Following the time series and ML analyses, a consistent trend emerges in the forecasted values for NMR and U5MR, which consistently fall below their respective 2030 targets. This promising finding suggests that Bangladesh is making significant progress toward meeting its 2030 targets for NMR and U5MR. However, in the cases of MMR and Death Rate Due to RTI, the forecasted values exceeded 2030 targets. This indicates that Bangladesh faces challenges in meeting the 2030 targets for MMR and Death Rate Due to RTI.ConclusionThe analyses underscore the importance of SDG 3 in Bangladesh and its progress towards ensuring healthy lives and well-being for all. While there is optimism regarding NMR and U5MR, more focused efforts may be needed to address the challenges posed by MMR and Death Rate Due to RTI to align with the 2030 targets. This study contributes valuable insights into Bangladesh's journey toward sustainable development in the realm of health and well-being.

Project description:INTRODUCTION:Nepal has made considerable progress on improving child survival during the Millennium Development Goal period, however, further progress will require accelerated reduction in neonatal mortality. Neonatal survival is one of the priorities for Sustainable Development Goals 2030. This paper examines the trends, equity gaps and factors associated with neonatal mortality between 2001 and 2016 to assess the likelihood of Every Newborn Action Plan (ENAP) target being reached in Nepal by 2030. METHODS:This study used data from the 2001, 2006, 2011 and 2016 Nepal Demographic and Health Surveys. We examined neonatal mortality rate (NMR) across the socioeconomic strata and the annual rate of reduction (ARR) between 2001 and 2016. We assessed association of socio-demographic, maternal, obstetric and neonatal factors associated with neonatal mortality. Based on the ARR among the wealth quintile between 2001 and 2016, we made projection of NMR to achieve the ENAP target. Using the Lorenz curve, we calculated the inequity distribution among the wealth quintiles between 2001 and 2016. RESULTS:In NDHS of 2001, 2006, 2011 and 2016, a total of 8400, 8600, 13,485 and 13,089 women were interviewed respectively. There were significant disparities between wealth quintiles that widened over the 15 years. The ARR for NMR declined with an average of 4.0% between 2001 and 2016. Multivariate analysis of the 2016 data showed that women who had not been vaccinated against tetanus had the highest risk of neonatal mortality (adjusted odds ratio [AOR] 3.38; 95% confidence interval [CI] 1.20-9.55), followed by women who had no education (AOR 1.87; 95% CI 1.62-2.16). Further factors significantly associated with neonatal mortality were the mother giving birth before the age of 20 (AOR 1.76; CI 95% 1.17-2.59), household air pollution (AOR 1.37; CI 95% 1.59-1.62), belonging to a poorest quintile (AOR 1.37; CI 95% 1.21-1.54), residing in a rural area (AOR 1.28; CI 95% 1.13-1.44), and having no toilet at home (AOR 1.21; CI 95% 1.06-1.40). If the trend of neonatal mortality rate of 2016 continues, it is projected that the poorest family will reach the ENAP target in 2067. CONCLUSIONS:Although neonatal mortality is declining in Nepal, if the current trend continues it will take another 50 years for families in the poorest group to attain the 2030 ENAP target. There are different factors associated with neonatal mortality, reducing the disparities for maternal and neonatal care will reduce mortality among the poorest families.

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

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

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