Evan D. Peet

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

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.

Risk Factors for Childhood Stunting in 137 Developing Countries: A Comparative Risk Assessment Analysis at Global, Regional, and Country Levels.

Background Stunting affects one-third of children under 5 y old in developing countries, and 14% of childhood deaths are attributable to it. A large number of risk factors for stunting have been identified in epidemiological studies. However, the relative contribution of these risk factors to stunting has not been examined across countries. We estimated the number of stunting cases among children aged 24–35 mo (i.e., at the end of the 1,000 days’ period of vulnerability) that are attributable to 18 risk factors in 137 developing countries. Methods and Findings We classified risk factors into five clusters: maternal nutrition and infection, teenage motherhood and short birth intervals, fetal growth restriction (FGR) and preterm birth, child nutrition and infection, and environmental factors. We combined published estimates and individual-level data from population-based surveys to derive risk factor prevalence in each country in 2010 and identified the most recent meta-analysis or conducted de novo reviews to derive effect sizes. We estimated the prevalence of stunting and the number of stunting cases that were attributable to each risk factor and cluster of risk factors by country and region. The leading risk worldwide was FGR, defined as being term and small for gestational age, and 10.8 million cases (95% CI 9.1 million–12.6 million) of stunting (out of 44.1 million) were attributable to it, followed by unimproved sanitation, with 7.2 million (95% CI 6.3 million–8.2 million), and diarrhea with 5.8 million (95% CI 2.4 million–9.2 million). FGR and preterm birth was the leading risk factor cluster in all regions. Environmental risks had the second largest estimated impact on stunting globally and in the South Asia, sub-Saharan Africa, and East Asia and Pacific regions, whereas child nutrition and infection was the second leading cluster of risk factors in other regions. Although extensive, our analysis is limited to risk factors for which effect sizes and country-level exposure data were available. The global nature of the study required approximations (e.g., using exposures estimated among women of reproductive age as a proxy for maternal exposures, or estimating the impact of risk factors on stunting through a mediator rather than directly on stunting). Finally, as is standard in global risk factor analyses, we used the effect size of risk factors on stunting from meta-analyses of epidemiological studies and assumed that proportional effects were fairly similar across countries. Conclusions FGR and unimproved sanitation are the leading risk factors for stunting in developing countries. Reducing the burden of stunting requires a paradigm shift from interventions focusing solely on children and infants to those that reach mothers and families and improve their living environment and nutrition.

Schooling and wage income losses due to early-childhood growth faltering in developing countries: national, regional, and global estimates

BACKGROUND The growth of >300 million children <5 y old was mildly, moderately, or severely stunted worldwide in 2010. However, national estimates of the human capital and financial losses due to growth faltering in early childhood are not available. OBJECTIVE We quantified the economic cost of growth faltering in developing countries. DESIGN We combined the most recent country-level estimates of linear growth delays from the Nutrition Impact Model Study with estimates of returns to education in developing countries to estimate the impact of early-life growth faltering on educational attainment and future incomes. Primary outcomes were total years of educational attainment lost as well as the net present value of future wage earnings lost per child and birth cohort due to growth faltering in 137 developing countries. Bootstrapped standard errors were computed to account for uncertainty in modeling inputs. RESULTS Our estimates suggest that early-life growth faltering in developing countries caused a total loss of 69.4 million y of educational attainment (95% CI: 41.7 million, 92.6 million y) per birth cohort. Educational attainment losses were largest in South Asia (27.6 million y; 95% CI: 20.0 million, 35.8 million y) as well as in Eastern (10.3 million y; 95% CI: 7.2 million, 12.9 million y) and Western sub-Saharan Africa (8.8 million y; 95% CI: 6.4 million, 11.5 million y). Globally, growth faltering in developing countries caused a total economic cost of

Early Childhood Development and Schooling Attainment: Longitudinal Evidence from British, Finnish and Philippine Birth Cohorts

176.8 billion (95% CI:

Returns to education in developing countries: Evidence from the living standards and measurement study surveys

100.9 billion,

Female Participation in Household Decision Making and the Justification of Wife Beating in Bangladesh

262.6 billion)/birth cohort at nominal exchange rates, and

Early childhood developmental status in low- and middle-income countries: National, regional, and global prevalence estimates using predictive modeling: National, Regional, and Global Prevalence Estimates Using Predictive Modeling

616.5 billion (95% CI:

Returns to Education in Low and Middle-Income Countries: Evidence from the Living Standards and Measurement Surveys

365.3 billion,

Risk Factors for Childhood Stunting in 137 Developing Countries

898.9 billion) at purchasing power parity-adjusted exchange rates. At the regional level, economic costs were largest in South Asia (

Schooling and Wage Income Losses Due to Early-Childhood Growth Faltering in Developing Countries

46.6 billion; 95% CI: