Clustering of developmental delays in Bavarian preschool children - a repeated cross-sectional survey over a period of 12 years

BMC Pediatr. 2014 Jan 23:14:18. doi: 10.1186/1471-2431-14-18.

Abstract

Background: While most children display a normal development, some children experience developmental delays compared to age specific development milestones assessed during school entry examination. Data exist on prevalence of delays in single areas, but there is lack of knowledge regarding the clustering patterns of developmental delays and their determinants.

Methods: During the observation period 1997-2008, 12 399 preschool children (5-7 years of age) in one district of Bavaria, Germany, were assessed in twelve schooling-relevant development areas. The co-occurrence of developmental delays was studied by means of Pearson's correlation. Subsequently, a two-step cluster algorithm was applied to identify patterns of developmental delays, and multinomial logistic regression was conducted to identify variables associated with the specific patterns.

Results: Fourteen percent of preschool children displayed developmental delays in one and 19% in two or more of the studied areas. Among those with at least two developmental delays, most common was the combination of delays in "fine motor skills" + "grapho-motor coordination" (in 9.1% of all children), followed by "memory/concentration" + "endurance" (5.8%) and "abstraction" + "visual perception" (2.1%). In the cluster analysis, five distinct patterns of delays were identified, which displayed different associations with male gender and younger age.

Conclusions: While developmental delays can affect single areas, clustering of multiple developmental delays is common. Such clustering should be taken into account when developing diagnostic tests, in pediatric practice and considering interventions to reduce delays.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Child, Preschool
  • Cluster Analysis
  • Cross-Sectional Studies
  • Developmental Disabilities / epidemiology*
  • Female
  • Germany / epidemiology
  • Humans
  • Male
  • Time Factors