Auxology of small samples: A method to describe child growth when restrictions prevent surveys.

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  • Additional Information
    • Source:
      Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE
    • Publication Information:
      Original Publication: San Francisco, CA : Public Library of Science
    • Subject Terms:
      COVID-19*/epidemiology ; Child Development*; Adolescent ; Child ; Cross-Sectional Studies ; Female ; Humans ; Male ; Sample Size ; Surveys and Questionnaires ; Young Adult
    • Abstract:
      Background: Child growth in populations is commonly characterised by cross-sectional surveys. These require data collection from large samples of individuals across age ranges spanning 1-20 years. Such surveys are expensive and impossible in restrictive situations, such as, e.g. the COVID pandemic or limited size of isolated communities. A method allowing description of child growth based on small samples is needed.
      Methods: Small samples of data (N~50) for boys and girls 6-20 years old from different socio-economic situations in Africa and Europe were randomly extracted from surveys of thousands of children. Data included arm circumference, hip width, grip strength, height and weight. Polynomial regressions of these measurements on age were explored.
      Findings: Polynomial curves based on small samples correlated well (r = 0.97 to 1.00) with results of surveys of thousands of children from same communities and correctly reflected sexual dimorphism and socio-economic differences.
      Conclusions: Fitting of curvilinear regressions to small data samples allows expeditious assessment of child growth in a number of characteristics when situations change rapidly, resources are limited and access to children is restricted.
      Competing Interests: The authors have declared that no competing interests exist.
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    • Publication Date:
      Date Created: 20220607 Date Completed: 20220609 Latest Revision: 20220716
    • Publication Date:
      20221213
    • Accession Number:
      PMC9173602
    • Accession Number:
      10.1371/journal.pone.0269420
    • Accession Number:
      35671303