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Weight loss motivations: a latent class analysis approach
Stephenie C Lemon1, Kristin L Schneider2, Monica L Wang3
1University of Massachusetts Medical School, Division of Preventive and Behavioral Medicine, Worcester, MA, USA. Stephenie.Lemon@umassmed.edu.
Objective:
To identify subgroups of adults with respect to weight loss motivations and assess factors associated with subgroup membership.
Method:
A cross-sectional survey among 414 overweight/ obese employees in 12 Massachusetts high schools was conducted. Latent class analysis (LCA) defined distinct weight loss motivation classes. Multinomial logistic regression assessed participant characteristics with class membership.
Results:
Three classes emerged: improving health; improving health and looking/feeling better; and improving health, looking/feeling, better and improving personal/social life. Compared to class 1, class 2 was more likely to be female and younger and class 3 was more likely to be female, younger, have children at home, and perceive themselves as very over-weight.
Conclusions:
Findings can inform targeted weight loss interventions.
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In regression analysis, a regression equation is determined based on the line of best fit– a line that best fits the data points plotted in a graph. This line is also called the regression line. The algebraic equation for the regression line is called the regression equation. It is represented as:
