57
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Early Childhood Developmental Status in Low- and Middle-Income Countries: National, Regional, and Global Prevalence Estimates Using Predictive Modeling

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          The development of cognitive and socioemotional skills early in life influences later health and well-being. Existing estimates of unmet developmental potential in low- and middle-income countries (LMICs) are based on either measures of physical growth or proxy measures such as poverty. In this paper we aim to directly estimate the number of children in LMICs who would be reported by their caregivers to show low cognitive and/or socioemotional development.

          Methods and Findings

          The present paper uses Early Childhood Development Index (ECDI) data collected between 2005 and 2015 from 99,222 3- and 4-y-old children living in 35 LMICs as part of the Multiple Indicator Cluster Survey (MICS) and Demographic and Health Surveys (DHS) programs. First, we estimate the prevalence of low cognitive and/or socioemotional ECDI scores within our MICS/DHS sample. Next, we test a series of ordinary least squares regression models predicting low ECDI scores across our MICS/DHS sample countries based on country-level data from the Human Development Index (HDI) and the Nutrition Impact Model Study. We use cross-validation to select the model with the best predictive validity. We then apply this model to all LMICs to generate country-level estimates of the prevalence of low ECDI scores globally, as well as confidence intervals around these estimates.

          In the pooled MICS and DHS sample, 14.6% of children had low ECDI scores in the cognitive domain, 26.2% had low socioemotional scores, and 36.8% performed poorly in either or both domains. Country-level prevalence of low cognitive and/or socioemotional scores on the ECDI was best represented by a model using the HDI as a predictor. Applying this model to all LMICs, we estimate that 80.8 million children ages 3 and 4 y (95% CI 48.1 million, 113.6 million) in LMICs experienced low cognitive and/or socioemotional development in 2010, with the largest number of affected children in sub-Saharan Africa (29.4.1 million; 43.8% of children ages 3 and 4 y), followed by South Asia (27.7 million; 37.7%) and the East Asia and Pacific region (15.1 million; 25.9%). Positive associations were found between low development scores and stunting, poverty, male sex, rural residence, and lack of cognitive stimulation. Additional research using more detailed developmental assessments across a larger number of LMICs is needed to address the limitations of the present study.

          Conclusions

          The number of children globally failing to reach their developmental potential remains large. Additional research is needed to identify the specific causes of poor developmental outcomes in diverse settings, as well as potential context-specific interventions that might promote children’s early cognitive and socioemotional well-being.

          Abstract

          Using survey data from 35 low- and middle-income countries, Dana McCoy and colleagues estimate the prevalence of children who are reported by their caregivers to show low cognitive and/or socioemotional development.

          Author Summary

          Why Was This Study Done?
          • Previous research suggests that more than 200 million children under age five living in low- and middle-income countries (LMICs) experience malnutrition and poverty.

          • Despite this known risk, little is known about the status of young children’s cognitive and socioemotional development.

          • Estimates of the number of children facing developmental setbacks are important for policy and resource allocation, as well as for tracking progress toward meeting global development goals (for example, the Sustainable Development Goals).

          What Did the Researchers Do and Find?
          • This study extrapolates data from nearly 100,000 three- and four-year-old children living in 35 LMICs sampled as part of the Multiple Indicator Cluster Survey and the Demographic Health Surveys.

          • The results suggest that one in every three preschool-aged children living in LMICs is failing to meet basic milestones in either their cognitive or socioemotional development, with an additional 16% facing setbacks in their physical growth.

          What Do These Findings Mean?
          • The results highlight the ongoing challenges faced by young children living in developing countries in meeting basic developmental milestones.

          • Additional intervention is needed to improve children’s cognitive and socioemotional well-being worldwide.

          • Future research should consider additional dimensions of children’s development across a broader age range.

          Related collections

          Most cited references11

          • Record: found
          • Abstract: found
          • Article: not found

          Understanding the Mechanisms Through Which an Influential Early Childhood Program Boosted Adult Outcomes.

          A growing literature establishes that high quality early childhood interventions targeted toward disadvantaged children have substantial impacts on later life outcomes. Little is known about the mechanisms producing these impacts. This paper uses longitudinal data on cognitive and personality traits from an experimental evaluation of the influential Perry Preschool program to analyze the channels through which the program boosted both male and female participant outcomes. Experimentally induced changes in personality traits explain a sizable portion of adult treatment effects.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Effect of a nutrition intervention during early childhood on economic productivity in Guatemalan adults.

            Substantial, but indirect, evidence suggests that improving nutrition in early childhood in developing countries is a long-term economic investment. We investigated the direct effect of a nutrition intervention in early childhood on adult economic productivity. We obtained economic data from 1424 Guatemalan individuals (aged 25-42 years) between 2002 and 2004. They accounted for 60% of the 2392 children (aged 0-7 years) who had been enrolled in a nutrition intervention study during 1969-77. In this initial study, two villages were randomly assigned a nutritious supplement (atole) for all children and two villages a less nutritious one (fresco). We estimated annual income, hours worked, and average hourly wages from all economic activities. We used linear regression models, adjusting for potentially confounding factors, to assess the relation between economic variables and exposure to atole or fresco at specific ages between birth and 7 years. Exposure to atole before, but not after, age 3 years was associated with higher hourly wages, but only for men. For exposure to atole from 0 to 2 years, the increase was US$0.67 per hour (95% CI 0.16-1.17), which meant a 46% increase in average wages. There was a non-significant tendency for hours worked to be reduced and for annual incomes to be greater for those exposed to atole from 0 to 2 years. Improving nutrition in early childhood led to substantial increases in wage rates for men, which suggests that investments in early childhood nutrition can be long-term drivers of economic growth.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              The economics, technology, and neuroscience of human capability formation.

              This article begins the synthesis of two currently unrelated literatures: the human capital approach to health economics and the economics of cognitive and noncognitive skill formation. A lifecycle investment framework is the foundation for understanding the origins of human inequality and for devising policies to reduce it.
                Bookmark

                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                PLoS Med
                PLoS Med
                plos
                plosmed
                PLoS Medicine
                Public Library of Science (San Francisco, CA USA )
                1549-1277
                1549-1676
                7 June 2016
                June 2016
                : 13
                : 6
                : e1002034
                Affiliations
                [1 ]Department of Global Health and Population, T. H. Chan School of Public Health, Harvard University, Boston, Massachusetts, United States of America
                [2 ]Graduate School of Education, Harvard University, Cambridge, Massachusetts, United States of America
                [3 ] MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom
                [4 ]Department of Epidemiology, T. H. Chan School of Public Health, Harvard University, Boston, Massachusetts, United States of America
                [5 ]School of Medicine, University of Maryland, Baltimore, Baltimore, Maryland, United States of America
                [6 ]RTI International, Research Triangle Park, North Carolina, United States of America
                Makerere University Medical School, UGANDA
                Author notes

                The authors have declared that no competing interests exist.

                Conceived and designed the experiments: DM EP ME MB WF GF. Analyzed the data: DM EP GF. Contributed reagents/materials/analysis tools: ME GD CR. Wrote the first draft of the manuscript: DM EP GF. Contributed to the writing of the manuscript: DM EP ME GD MB CR WF GF. Agree with the manuscript’s results and conclusions: DM EP ME GD MB CR WF GF. All authors have read, and confirm that they meet, ICMJE criteria for authorship.

                Author information
                http://orcid.org/0000-0001-6147-3475
                http://orcid.org/0000-0002-2109-8081
                Article
                PMEDICINE-D-15-03366
                10.1371/journal.pmed.1002034
                4896459
                27270467
                29bcc65b-372e-48a8-aead-d9851c26ac48
                © 2016 McCoy et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 9 November 2015
                : 20 April 2016
                Page count
                Figures: 8, Tables: 4, Pages: 18
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100004828, Grand Challenges Canada;
                Award ID: 0073-03
                Funding for the present study was provided by the Saving Brains Program from Grand Challenges Canada (grant number 0073-03; http://www.grandchallenges.ca/saving-brains/). The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                People and Places
                Population Groupings
                Age Groups
                Children
                People and Places
                Population Groupings
                Families
                Children
                People and Places
                Geographical Locations
                Asia
                Biology and Life Sciences
                Behavior
                Medicine and Health Sciences
                Pediatrics
                Child Health
                Medicine and Health Sciences
                Public and Occupational Health
                Child Health
                Research and Analysis Methods
                Mathematical and Statistical Techniques
                Statistical Methods
                Forecasting
                Physical Sciences
                Mathematics
                Statistics (Mathematics)
                Statistical Methods
                Forecasting
                Biology and Life Sciences
                Nutrition
                Medicine and Health Sciences
                Nutrition
                People and Places
                Geographical Locations
                Africa
                Biology and Life Sciences
                Neuroscience
                Cognitive Science
                Cognition
                Custom metadata
                All data for the present study were taken from publicly available data sources. In particular, all MICS files are available from UNICEF's online database at http://mics.unicef.org/surveys. All DHS files are available from the DHS online database at http://www.dhsprogram.com/Data/.

                Medicine
                Medicine

                Comments

                Comment on this article

                scite_

                Similar content160

                Cited by185

                Most referenced authors436