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Latent classes of early childhood development and their predictors in Low- and middle-income countries: Results from multiple indicator cluster surveys 2010 - 2020

  • Jin Sun
  • , Yudong Zhang*
  • , Qianjin Guo
  • , Mengyuan Liang
  • , Zeyi Li
  • , Li Zhang
  • *此作品的通讯作者
  • University of Macau
  • Northwestern University
  • University of Pittsburgh
  • The University of Chicago
  • The University of Hong Kong

科研成果: 期刊稿件文章同行评审

摘要

Investing in early childhood development (ECD) is critical for individual and societal development. Variable-centered research on ECD has shown that family wealth, maternal education, and parenting practices predict childhood outcomes overall. However, little is known about differences in the ECD patterns and their predictors. This study examined the latent classes of ECD using data from three waves of the Multiple Indicators Cluster Surveys (MICS) conducted in 29 low- and middle-income countries (LMICs) between 2010 and 2020 (MICS 4, 5, and 6) and identified their predictors at different ecological levels. The total sample size for analyses was 226,374 (nMICS4 = 70,082, nMICS5 = 91,652, nMICS6 = 64,640; Mage = 47.23(months), SDage = 6.87). Three classes, Learning Challenged but On Track for Physical and Social-emotional Development, Academically Challenged but Approaches-to-Learning Competent, On Track for Physical and Social-emotional Development, and Competent across All Domains, were consistently identified across MICS 4–6 using latent class analysis. Three variables, all at the microsystem level, predicted class membership with acceptable effect sizes in one or more waves of the MICS data: preschool attendance, number of books at home, and maternal education. The study has implications for future research and the development of policies aimed at monitoring and supporting ECD in LMICs.

源语言英语
页(从-至)65-75
页数11
期刊Early Childhood Research Quarterly
68
DOI
出版状态已出版 - 1 7月 2024

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