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Prediction equations for the estimation of body composition in the elderly using anthropometric data
M Visser1, E van den Heuvel, P Deurenberg
1Department of Human Nutrition, Wageningen Agricultural University, The Netherlands.
The British Journal of Nutrition
|June 1, 1994
Summary
Accurate body composition assessment in older adults is crucial. New prediction equations using anthropometric data, like skinfolds and BMI, improve body fat estimation in the elderly population.
Area of Science:
- Gerontology
- Nutritional Science
- Human Physiology
Background:
- Assessing body composition is vital for understanding health and nutritional status in elderly populations.
- Practical anthropometric methods are needed for large-scale epidemiological studies in this demographic.
Purpose of the Study:
- To analyze the relationship between body composition (determined by densitometry) and anthropometric data in elderly individuals.
- To develop and validate new prediction equations for body composition in older adults, as existing formulas often underestimate body fat.
Main Methods:
- The study involved 204 men and women aged 60-87 years.
- Body composition was determined by densitometry.
- New prediction equations were developed using anthropometric data, including skinfold measurements (biceps, triceps, suprailiaca, subscapula) and body mass index (BMI).
Main Results:
- Existing prediction equations generally underestimated percentage body fat in the elderly.
- New equations based on sex and combinations of skinfolds or BMI showed good predictive validity.
- Adding age or body circumferences did not enhance prediction accuracy.
Conclusions:
- Developed prediction equations are valid for estimating body density in elderly subjects.
- These anthropometric-based formulas offer a practical approach for body composition assessment in older populations.
- The models achieved standard errors of estimate for percentage body fat ranging from 4.8% to 5.6%.