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Issues in the assessment of nutritional status using anthropometry
J Gorstein1, K Sullivan, R Yip
1Department of International Health, University of Michigan, Ann Arbor.
Bulletin of the World Health Organization
|January 1, 1994
Summary
Choosing the right anthropometric index and scale, like z-scores, is crucial for accurate population health assessments. Understanding growth reference limitations, especially around age two, ensures correct interpretation of anthropometric data.
Area of Science:
- Public Health
- Human Biology
- Growth Monitoring
Background:
- Anthropometry is vital for assessing population and individual health.
- Accurate interpretation of anthropometric data is essential for effective public health interventions.
- Existing methods for anthropometric analysis present several challenges.
Purpose of the Study:
- To discuss key issues in the use and interpretation of anthropometry.
- To provide criteria for assessing the severity of low anthropometry in populations.
- To highlight limitations in current growth references and data collection methods.
Main Methods:
- Comparative analysis of different anthropometric indices (weight-for-height, height-for-age, weight-for-age).
- Evaluation of various scales for index expression (z-scores, percentiles, percent-of-median).
- Discussion of limitations within the current WHO growth reference, particularly the age-2 disjunction.
Main Results:
- No single anthropometric index is universally adequate; selection depends on context.
- z-Scores offer superior properties for scaling anthropometric indices compared to percentiles or percent-of-median.
- A disjunction exists in growth curves at age 2 due to the use of different reference populations, necessitating careful interpretation.
Conclusions:
- Appropriate selection of anthropometric indices and scales is critical for accurate health assessments.
- Researchers must be aware of growth reference limitations, such as the age-2 disjunction, for correct interpretation.
- Standardized and carefully considered anthropometric data collection and analysis are fundamental for reliable public health surveillance.