The D-score: a metric for interpreting the early development of infants and toddlers across global settings.

Journal: BMJ global health

Volume: 4

Issue: 6

Year of Publication: 

Affiliated Institutions:  School of Community Health Sciences, University of Nevada Reno, Reno, Nevada, USA. Inter-American Development Bank, Washington, District of Columbia, USA. Caribbean Institute for Health Research, University of the West Indies, Kingston, Jamaica. Netherlands Organization for Applied Scientific Research TNO, Leiden, Netherlands. Institute of Child Health, University College London, London, UK. School of Public Health, University of California Berkeley, Berkeley, California, USA. Maternal and Child Health Division, icddr,b, Dhaka, Bangladesh. Institute of Psychiatry, Psychology and Neuroscience, Health Service and Population Research Department, Centre for Global Mental Health, King's College London, London, UK. Department of Pediatrics, Federal University of Rio Grande, Rio Grande, Brazil. Center for Human Growth and Development, University of Michigan, Ann Arbor, Michigan, USA. Centre Médico-Educatif "Les Orchidées Blanches", Antananarivo, Madagascar. Centre of Excellence in Human Development, University of the Witwatersrand, Johannesburg, South Africa. Department of Pediatrics, University of Maryland School of Medicine, Baltimore, Maryland, USA.

Abstract summary 

Early childhood development can be described by an underlying latent construct. Global comparisons of children's development are hindered by the lack of a validated metric that is comparable across cultures and contexts, especially for children under age 3 years. We constructed and validated a new metric, the Developmental Score (D-score), using existing data from 16 longitudinal studies.Studies had item-level developmental assessment data for children 0-48 months and longitudinal outcomes at ages >4-18 years, including measures of IQ and receptive vocabulary. Existing data from 11 low-income, middle-income and high-income countries were merged for >36 000 children. Item mapping produced 95 'equate groups' of same-skill items across 12 different assessment instruments. A statistical model was built using the Rasch model with item difficulties constrained to be equal in a subset of equate groups, linking instruments to a common scale, the D-score, a continuous metric with interval-scale properties. D-score-for-age z-scores (DAZ) were evaluated for discriminant, concurrent and predictive validity to outcomes in middle childhood to adolescence.Concurrent validity of DAZ with original instruments was strong (average =0.71), with few exceptions. In approximately 70% of data rounds collected across studies, DAZ discriminated between children above/below cut-points for low birth weight (<2500 g) and stunting (-2 SD below median height-for-age). DAZ increased significantly with maternal education in 55% of data rounds. Predictive correlations of DAZ with outcomes obtained 2-16 years later were generally between 0.20 and 0.40. Correlations equalled or exceeded those obtained with original instruments despite using an average of 55% fewer items to estimate the D-score.The D-score metric enables quantitative comparisons of early childhood development across ages and sets the stage for creating simple, low-cost, global-use instruments to facilitate valid cross-national comparisons of early childhood development.

Authors & Co-authors:  Weber Ann M AM Rubio-Codina Marta M Walker Susan P SP van Buuren Stef S Eekhout Iris I Grantham-McGregor Sally M SM Araujo Maria Caridad MC Chang Susan M SM Fernald Lia Ch LC Hamadani Jena Derakhshani JD Hanlon Charlotte C Karam Simone M SM Lozoff Betsy B Ratsifandrihamanana Lisy L Richter Linda L Black Maureen M MM

Study Outcome 

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Statistics
Citations :  Phillips DA, Shonkoff JP. From neurons to neighborhoods: the science of early childhood development. National Academies Press, 2000.
Authors :  17
Identifiers
Doi : e001724
SSN : 2059-7908
Study Population
Male,Female
Mesh Terms
Other Terms
child development;global health;item response theory;psychometrics
Study Design
Study Approach
Quantitative
Country of Study
Publication Country
England