IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/30357.html
   My bibliography  Save this paper

Using weight-for-age for predicting wasted children

Author

Listed:
  • Nguefack-Tsague, Georges
  • Tanya K. N., Agatha

Abstract

Background: The equipments for taking body weights (scales) are more frequent in Cameroon health centres than measuring boards for heights. Even when the later exist there are some difficulties inherent in their qualities; thus the height measurement is not always available or accurate. Objective: To construct statistical models for predicting wasting from weight-for-age. Methods: 3742 children a ged 0 to 59 months were enrolled in a cross-sectional household survey (2004 Cameroon Demographic and Health Surveys (DHS)) covering the entire Cameroon national territory. Results: There were highly significant association between underweight and wasting. For all discriminant statistical methods used, the test error rates (using an independent testing sample) are less than 5%; the Area Under the Curve (AUC) using the Receiver Operating Characteristic (ROC) is 0.86. Conclusions: Weight-for-age can be used for accurately classifying a child whose wasting status is unknown. The result is useful in Cameroon as too often the height measurements may not be feasible, thus the need for estimating wasted children.

Suggested Citation

  • Nguefack-Tsague, Georges & Tanya K. N., Agatha, 2011. "Using weight-for-age for predicting wasted children," MPRA Paper 30357, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:30357
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/30357/1/MPRA_paper_30357.pdf
    File Function: original version
    Download Restriction: no

    More about this item

    Keywords

    Anthropometric measures; nutritional status; discriminant analysis; underweight; wasting;

    JEL classification:

    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pra:mprapa:30357. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Joachim Winter). General contact details of provider: http://edirc.repec.org/data/vfmunde.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.