RESUMO
A recent Nature article modelled within-country inequalities in primary, secondary, and tertiary education and forecast progress towards Sustainable Development Goal (SDG) targets related to education (SDG 4). However, their paper entirely overlooks inequalities in achieving Target 4.2, which aims to achieve universal access to quality early childhood development, care and preschool education by 2030. This is an important omission because of the substantial brain, cognitive and socioemotional developments that occur in early life and because of increasing evidence of early-life learning's large impacts on subsequent education and lifetime wellbeing. We provide an overview of this evidence and use new analyses to illustrate medium- and long-term implications of early learning, first by presenting associations between pre-primary programme participation and adolescent mathematics and science test scores in 73 countries and secondly, by estimating the costs of inaction (not making pre-primary programmes universal) in terms of forgone lifetime earnings in 134 countries. We find considerable losses, comparable to or greater than current governmental expenditures on all education (as percentages of GDP), particularly in low- and lower-middle-income countries. In addition to improving primary, secondary and tertiary schooling, we conclude that to attain SDG 4 and reduce inequalities in a post-COVID era, it is essential to prioritize quality early childhood care and education, including adopting policies that support families to promote early learning and their children's education.
RESUMO
CONTEXT: The design and evaluation of adolescent health programs rarely account for socioeconomic differences in reproductive health needs and service utilization among young women in developing countries. METHODS: Nationally representative Demographic and Health Survey data for 12 developing countries were used to assess socioeconomic differentials in reproductive health outcomes and service utilization among young women. For each country, chi-square tests were performed to identify statistically significant differences between the poorest and the richest quintiles, which were constructed using a household wealth index. RESULTS: In most countries, young women from the poorest households were more likely than those from the richest households to be married by age 18 and to have had at least one child by that age; they were less likely to report a mistimed birth, to be practicing contraception, to use maternal health services and to know how to prevent sexual transmission of HIV. Economic autonomy, school enrollment and regular exposure to mass media were less common among poor than among rich adolescents. CONCLUSIONS: Poor adolescents may be overlooked by current service delivery modes that rely solely on mass media, clinics or schools. Alternative strategies, such as community-based outreach programs, must be implemented to serve the needs of poor young women.
