"If we take the antilog of the regression coefficient associated with obesity, exp(0.415) = 1.52 we get the odds ratio adjusted for age. The odds of developing CVD are 1.52 times higher among obese persons as compared to non obese persons, *adjusting for age".
This is an excerpt from an article on Log Odds. May I know what the word 'adjusting' means in this context?
Link to the article ---->
https://sphweb.bumc.bu.edu/otlt/mph-modules/bs/bs704_multivariable/bs704_multivariable8.html
Assuming obesity is an indicator variable (0 for non and 1 for obese), then when someone is NOT obese, value of 0.415 * obese = 0. When obese = 1, then 0.415 is added to the 0.655 * age group.
Without the age group, the equation is intercept (a constant) + either 0 or 0.415 depending if the person is obese. Then we take that value and "adjust" it by some factor of the age group.
A little weird vocabulary. Probably depends what the author is trying to show. Obese or not gives the base value. Then depending upon your age group the results change. It also could be phrased the other way - Your age group defines your base risk. But if you are obese then your risk increases by some value. Adjust vs change vs increase/decrease.
