Why age is so important in body composition testing
Oserio's algorithms for analyzing and calculating body composition results utilize a mix of measured and input data. Measured data includes weight and impedance. Input data includes height, gender, and age.
All of these are important for helping algorithms determine body composition, but today we'll be focusing on age, and why we take it into consideration during analysis!
As anyone who's found themselves grunting involuntarily as they lower themselves into a chair can attest, our bodies constantly change with age: for most people, this means decreasing max heart rate and blood volume. In particular, decrease in muscle mass and effectiveness is fairly common as people age, especially past around 50 years of age. This can, of course be slowed or reversed with dedicated training and well-planned nutrition, but generally speaking, it takes much more effort to maintain the same level of fitness compared to a younger person.
Something that's particularly interesting is that among older subjects, muscles can lose strength faster than they loss mass! In this study published in the Journal of Gerontology, researchers studied changes in muscle mass and strength over 3 years for nearly 2000 adults. They found that although muscle mass is correlated with decline in strength (which is to be expected), decline in strength was much faster than the concomitant loss in muscle mass, indicating that muscle quality can be somewhat separate from mass.
Source: The Loss of Skeletal Muscle Strength, Mass, and Quality in Older Adults: The Health, Aging and Body Composition Study, The Journals of Gerontology https://academic.oup.com/biomedgerontology/article/61/10/1059/600461
And of course, there's the decline in bone mass and density among elders, which is why it's much easier for them to suffer from bone breaks after falls.
Due to the physiological changes our bodies undergo throughout the aging process, it should be clear why we feel it's important to take age into account when calculating body composition. It is possible to formulate algorithms that don't take age into account, just as it's possible to create one that might ignore height. However, we've found that incorporation of age significantly increases the accuracy of end results - click here to learn more about the validity of our algorithms!