Child Development with the D-score
Child Development with the D-score
About this Gateway
Children learn to walk, speak, and think at an astonishing pace. The D-score captures this process as a one-number summary. The D-score chapters explain why we need the D-score, how we construct it, and how we calculate it. Application of the D-score enables comparisons in child development across populations, groups, and individuals.
The Gateway contains two chapters:
Chapter 1: Turning Milestones into Measurement has been written by Stef van Buuren and Iris Eekhout, with contributions from Marianne de Wolff, Child Health, TNO, to Section 1; Manon Grevinga, Real-World Evidence & Data Analytics, Open Health, to Section 8; Paula van Dommelen, Child Health, TNO, to Section 9; and Maria C. Olthof, Ki Global Health, to Section 9
Chapter 2: Tuning Instruments to Unity has been written by Iris Eekhout and Stef van Buuren
Further chapters on the D-score are underway under the following titles:
Chapter 3: Tailoring Tests to Fit the Occasion
Chapter 4: Taking Off the Hood
This ongoing series addresses conceptual aspects of the D-score, discusses practical issues, and introduces a dedicated set of R packages.
The Health Birth Growth and Development knowledge integration (ki) program of the Gates Foundation kindly supports the work.
Gateway Advisors
Stef van Buuren is a professor of Statistical Analysis of Incomplete Data at the University of Utrecht and statistician at the Netherlands Organisation for Applied Scientific Research TNO in Leiden. His interests include the analysis of incomplete data and child growth and development (h-index 61). Van Buuren is the inventor of the MICE algorithm for multiple imputation of missing data (>85.000 downloads per month) and has written the accessible monograph Flexible Imputation of Missing Data. Second Edition, CRC/Chapman & Hall. He designed the growth charts for the Dutch child health care system and invented the D-score, a new method for expressing child development on a quantitative scale. He consults for the World Health Organization and the Gates Foundation. More background at https://stefvanbuuren.name, and software at https://github.com/stefvanbuuren.
Iris Eekhout holds a double masters in clinical psychology and methodology and statistics of psychology (Leiden University). She obtained her PhD at the Department of Epidemiology and Biostatistics of the VU University medical centre in Amsterdam. Her dissertation work resulted in novel ways of dealing with missing data in questionnaire items and total scores. Currently, Iris teaches a course on missing data analysis in the epidemiology master’s program at VU University medical centre. At TNO, Iris works on a variety of projects as a methodologist and statistical analyst related to child health, e.g., measuring child development (D-score) and adaptive screenings for psycho-social problems (psycat). More background at https://www.iriseekhout.com, and software at https://github.com/iriseekhout.
Preface
The foundations of adult health and wellbeing have their origins early in life, often measured by children’s early growth and development (Clark et al. 2020). Growth standards established by the World Health Organization (WHO) have been adopted globally and are used as indices and targets for improvement. For example, in 2018, 219 million children under 5 years of age (21.9%) were stunted (height for age < -2 standard deviations of the WHO growth standards) (UNICEF 2019). Stunting early in life has been associated with negative childhood development, academic achievement, and adult productivity. In the absence of direct population-based metrics for childhood development, stunting and poverty have been used as proxy indicators to estimate the number of children not reaching their developmental potential (Lu, Black, and Richter 2016).
Although stunting and poverty have been effective indicators and have contributed to advances in global childhood development policies and programs (Black et al. 2017), they lack the sensitivity to measure changes associated with programmatic interventions. Early childhood development is a latent construct comprised of an ordinal sequence of developmental domains (motor, language, cognitive, personal-social). A valid and easily interpretable metric is needed to interpret the underlying latent construct of early childhood development that can represent change and is comparable across cultures and contexts. Chapter I - Turning milestones into measurement - shows that the D-score (Developmental score) meets those criteria.
Chapter II - Tuning instruments to unity - deals with the problem of how to define and calculate the D-score from data obtained from multiple studies and multiple instruments. After harmonizing longitudinal measures of childhood development among over 36,000 children from 11 countries (Weber et al. 2019), the statistical analysis produced a D-score scale with interval qualities that can reflect change over time and enable within and across country comparisons. In addition, the D-score is responsive to environmental conditions that may impact children’s development, ranging from community programs and policies to macro-level conditions from migration, inequities, or climate. Applied to populations, direct metrics of children’s early growth and development assess the current status of the population’s health and well-being, establish predictions of future health and well-being, and provide opportunities to measure changes. Thus, applying the D-score to the early development of children extends to populations and society as a whole.
Maureen Black, University of Maryland, USA, July 2020
The Gateway contains two chapters:
Chapter 1: Turning Milestones into Measurement has been written by Stef van Buuren and Iris Eekhout, with contributions from Marianne de Wolff, Child Health, TNO, to Section 1; Manon Grevinga, Real-World Evidence & Data Analytics, Open Health, to Section 8; Paula van Dommelen, Child Health, TNO, to Section 9; and Maria C. Olthof, Ki Global Health, to Section 9
Chapter 2: Tuning Instruments to Unity has been written by Iris Eekhout and Stef van Buuren
Further chapters on the D-score are underway under the following titles:
Chapter 3: Tailoring Tests to Fit the Occasion
Chapter 4: Taking Off the Hood
This ongoing series addresses conceptual aspects of the D-score, discusses practical issues, and introduces a dedicated set of R packages.
The Health Birth Growth and Development knowledge integration (ki) program of the Gates Foundation kindly supports the work.
Gateway Advisors
Stef van Buuren is a professor of Statistical Analysis of Incomplete Data at the University of Utrecht and statistician at the Netherlands Organisation for Applied Scientific Research TNO in Leiden. His interests include the analysis of incomplete data and child growth and development (h-index 61). Van Buuren is the inventor of the MICE algorithm for multiple imputation of missing data (>85.000 downloads per month) and has written the accessible monograph Flexible Imputation of Missing Data. Second Edition, CRC/Chapman & Hall. He designed the growth charts for the Dutch child health care system and invented the D-score, a new method for expressing child development on a quantitative scale. He consults for the World Health Organization and the Gates Foundation. More background at https://stefvanbuuren.name, and software at https://github.com/stefvanbuuren.
Iris Eekhout holds a double masters in clinical psychology and methodology and statistics of psychology (Leiden University). She obtained her PhD at the Department of Epidemiology and Biostatistics of the VU University medical centre in Amsterdam. Her dissertation work resulted in novel ways of dealing with missing data in questionnaire items and total scores. Currently, Iris teaches a course on missing data analysis in the epidemiology master’s program at VU University medical centre. At TNO, Iris works on a variety of projects as a methodologist and statistical analyst related to child health, e.g., measuring child development (D-score) and adaptive screenings for psycho-social problems (psycat). More background at https://www.iriseekhout.com, and software at https://github.com/iriseekhout.
Preface
The foundations of adult health and wellbeing have their origins early in life, often measured by children’s early growth and development (Clark et al. 2020). Growth standards established by the World Health Organization (WHO) have been adopted globally and are used as indices and targets for improvement. For example, in 2018, 219 million children under 5 years of age (21.9%) were stunted (height for age < -2 standard deviations of the WHO growth standards) (UNICEF 2019). Stunting early in life has been associated with negative childhood development, academic achievement, and adult productivity. In the absence of direct population-based metrics for childhood development, stunting and poverty have been used as proxy indicators to estimate the number of children not reaching their developmental potential (Lu, Black, and Richter 2016).
Although stunting and poverty have been effective indicators and have contributed to advances in global childhood development policies and programs (Black et al. 2017), they lack the sensitivity to measure changes associated with programmatic interventions. Early childhood development is a latent construct comprised of an ordinal sequence of developmental domains (motor, language, cognitive, personal-social). A valid and easily interpretable metric is needed to interpret the underlying latent construct of early childhood development that can represent change and is comparable across cultures and contexts. Chapter I - Turning milestones into measurement - shows that the D-score (Developmental score) meets those criteria.
Chapter II - Tuning instruments to unity - deals with the problem of how to define and calculate the D-score from data obtained from multiple studies and multiple instruments. After harmonizing longitudinal measures of childhood development among over 36,000 children from 11 countries (Weber et al. 2019), the statistical analysis produced a D-score scale with interval qualities that can reflect change over time and enable within and across country comparisons. In addition, the D-score is responsive to environmental conditions that may impact children’s development, ranging from community programs and policies to macro-level conditions from migration, inequities, or climate. Applied to populations, direct metrics of children’s early growth and development assess the current status of the population’s health and well-being, establish predictions of future health and well-being, and provide opportunities to measure changes. Thus, applying the D-score to the early development of children extends to populations and society as a whole.
Maureen Black, University of Maryland, USA, July 2020
Gateway Areas
This chapter equips the reader with a basic understanding of robust psychometric methods that are needed to turn developmental milestones into measurements, introducing the fundamental issues in defining a unit for child development and demonstrates the relevant quantitative methodology. It reviews quantitative approaches to measuring child development; introduces the Rasch model in a non-technical way; shows how to estimate model parameters from real data; puts forth a set of principles for model evaluation and assessment of scale quality; analyses the relation between early D-scores and later intelligence; and compares the D-scores from three studies that all use the same instrument.
This chapter familiarises the reader with an intuitive yet powerful methodology to tune instruments to a common unit, presenting a fresh approach that expresses measurements made by different instruments on the D-score scale. As a result, the reader may compare D-scores between ages, children or cohorts. It shows how to exploit common developmental milestones to bridge instruments and cohorts; presents an analysis to obtain D-scores from 16 cohorts and 14 instruments; compares D-score age-distribution across populations from four continents; suggests an indicator for the United Nations Sustainable Development Goals; and defines developmentally-on-track.
Gateway Advisors
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Iris Eekhout
Netherlands Organization for Applied Scientific Research TNO, Leiden, The Netherlands -
Stef van Buuren
Netherlands Organization for Applied Scientific Research TNO, Leiden, The Netherlands