Fat Data and Body Measurements

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Description

This data set illustrates the relationship between body measurements and body fat in 252 males aged between 21 and 81 years.

Usage

1
data(fat)

Format

A data frame with 252 rows and 26 variables.

Obs

observation number.

Perc.body.fat.Brozek

percent body fat using Brozek's equation, i.e., 457/Density - 414.2.

Perc.body.fat.Siri

percent body fat using Siri's equation, i.e., 495/Density - 450.

Density

density (\frac{g}{cm^3}).

Age

age (years).

Weight

weight (lbs).

Height

height (inches).

Adiposity.index

adiposity index computed as Weight/Height^2 (\frac{kg}{m^2}).

Fat.free.weight

fat free weight computed as (1 - Brozek's percent body fat) * Weight (lbs).

Neck.circ

neck circumference (cm).

Chest.circ

chest circumference (cm).

Abdomen.circ

abdomen circumference (cm) measured at the umbilicus and level with the iliac crest.

Hip.circ

hip circumference (cm).

Thigh.circ

thigh circumference (cm).

Knee.circ

knee circumference (cm).

Ankle.circ

ankle circumference (cm).

Biceps.circ

extended biceps circumference (cm).

Forearm.circ

forearm circumference (cm).

Wrist.circ

wrist circumference (cm).

inv.Density

inverse of density (\frac{cm^3}{g}).

z1

log of weight divided by log of height (allometric measure).

z2

abdomen circumference divided by chest circumference (beer gut factor).

z3

index based on knee, wrist, and ankle circumference relative to height (\frac{(Knee.circ * Wrist.circ * Ankle.circ)^(1/3)}{Height}).

z4

fleshiness index based on biceps, thigh, forearm, knee, wrist, and ankle circumference (\frac{Biceps.circ * Thigh.circ * Forearm.circ}{Knee.circ * Wrist.circ * Ankle.circ}).

z5

age standardized to zero mean and unit variance.

z6

square of standardized age.

Details

Burnham and Anderson (2002, p. 268) use this data set to show model selection uncertainty in the context of all possible combinations of explanatory variables. The data are originally from Penrose et al. (1985) who used only the first 143 cases of the 252 observations in the data set. Johnson (1996) later used these data as an example of multiple regression. Note that observation number 42 originally had an erroneous height of 29.5 inches and that this value was changed to 69.5 inches.

Burnham and Anderson (2002, p. 274) created six indices based on the original measurements (i.e., z1 – z6). Although Burnham and Anderson (2002) indicate that the fleshiness index (z4) involved the cubic root in the equation, the result table for the full model on p. 276 suggests that the index did not include the cubic root for z4. The latter is the version of z4 used in the data set here.

Source

Burnham, K. P., Anderson, D. R. (2002) Model Selection and Multimodel Inference: a practical information-theoretic approach. Second edition. Springer: New York.

Johnson, J. W. (1996). Fitting percentage of body fat to simple body measurements. Journal of Statistics Education 4 [online].

Penrose, K., Nelson, A., Fisher, A. (1985) Generalized body composition prediction equation for men using simple measurement techniques Medicine and Science in Sports and Exercise 17, 189.

Examples

1
2
data(fat)
str(fat)

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