The art and science of regression modelling; methods for building valid models to explore hormone and body composition interactions.
Multiple linear regression modelling is commonly used to investigate how hormones and body composition interact, but for valid interpretation a sound methodological approach must be used. It is particularly important that the assumptions for regression are met so that spurious associations are not generated. In this article we show how different approaches to building a multiple linear regression model can influence perceived associations, using examples from the literature and our own data related to predicting fasting insulin and leptin levels from total body fat and fat distribution in children.
Garnett
Sarah P
SP
Institute of Endocrinology and Diabetes, the Children's Hospital at Westmead, Australia. sarahg@chw.edu.au
Hayen
Andrew
A
Peat
Jennifer
J
D000273:Adipose Tissue; D001823:Body Composition; D002648:Child; D005215:Fasting; D005260:Female; D006728:Hormones / Q000502:physiology*; D006801:Humans; D007328:Insulin / Q000097:blood; D007334:Insulin-Like Growth Factor I / Q000032:analysis; D020738:Leptin / Q000097:blood; D016014:Linear Models; D008297:Male; D008433:Mathematics
D006728:Hormones; D007328:Insulin; D020738:Leptin; D007334:Insulin-Like Growth Factor I