Biomaterial Database

Prediction equations for the estimation of body composition in the elderly using anthropometric data. 1994

M Visser, and E van den Heuvel, and P Deurenberg

Department of Human Nutrition, Wageningen Agricultural University, The Netherlands.

To study the relationship between health and nutritional status in elderly populations, information about body composition is essential. To collect this information in large epidemiological studies, practical methods based on anthropometric data must be available. In the present study the relationship between body composition, determined by densitometry, and anthropometric data in 204 elderly men and women, aged 60-87 years, was analysed. Existing prediction equations described in the literature, and mainly based on young and middle-aged subjects, generally underestimated percentage body fat in the elderly study population. Therefore, new prediction equations were developed, based on sex and the sum of two (biceps and triceps) or four (biceps, triceps, suprailiaca and subscapula) skinfolds or the body mass index (BMI). Addition of age or body circumferences to the models did not improve the prediction of body density. Internal cross validation and external validation revealed that the formulas are valid for the estimation of body density in elderly subjects. The standard errors of estimate of the three models, expressed as percentage body fat, were 5.6, 5.4 and 4.8% respectively.

UI	MeSH Term	Description	Entries
D008297	Male		Males
D008875	Middle Aged	An adult aged 45 - 64 years.	Middle Age
D008954	Models, Biological	Theoretical representations that simulate the behavior or activity of biological processes or diseases. For disease models in living animals, DISEASE MODELS, ANIMAL is available. Biological models include the use of mathematical equations, computers, and other electronic equipment.	Biological Model,Biological Models,Model, Biological,Models, Biologic,Biologic Model,Biologic Models,Model, Biologic
D009752	Nutritional Status	State of the body in relation to the consumption and utilization of nutrients.	Nutrition Status,Status, Nutrition,Status, Nutritional
D011237	Predictive Value of Tests	In screening and diagnostic tests, the probability that a person with a positive test is a true positive (i.e., has the disease), is referred to as the predictive value of a positive test; whereas, the predictive value of a negative test is the probability that the person with a negative test does not have the disease. Predictive value is related to the sensitivity and specificity of the test.	Negative Predictive Value,Positive Predictive Value,Predictive Value Of Test,Predictive Values Of Tests,Negative Predictive Values,Positive Predictive Values,Predictive Value, Negative,Predictive Value, Positive
D012044	Regression Analysis	Procedures for finding the mathematical function which best describes the relationship between a dependent variable and one or more independent variables. In linear regression (see LINEAR MODELS) the relationship is constrained to be a straight line and LEAST-SQUARES ANALYSIS is used to determine the best fit. In logistic regression (see LOGISTIC MODELS) the dependent variable is qualitative rather than continuously variable and LIKELIHOOD FUNCTIONS are used to find the best relationship. In multiple regression, the dependent variable is considered to depend on more than a single independent variable.	Regression Diagnostics,Statistical Regression,Analysis, Regression,Analyses, Regression,Diagnostics, Regression,Regression Analyses,Regression, Statistical,Regressions, Statistical,Statistical Regressions
D001823	Body Composition	The relative amounts of various components in the body, such as percentage of body fat.	Body Compositions,Composition, Body,Compositions, Body
D003720	Densitometry	The measurement of the density of a material by measuring the amount of light or radiation passing through (or absorbed by) the material.	Densitometries
D005260	Female		Females
D006801	Humans	Members of the species Homo sapiens.	Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man