Correlates of weight patterns during middle age characterized by functional principal components analysis
Molly E Waring1, Charles B Eaton, Thomas M Lasater
1Department of Community Health, Brown University, Providence, RI, USA. molly.waring@umassmed.edu
Annals of Epidemiology
|February 18, 2010
Summary
Weight patterns in middle age were identified using functional principal component analysis (PCA). Early weight status at 25 years strongly predicted these patterns, highlighting the need for early intervention.
Area of Science:
- Health Sciences
- Biostatistics
- Epidemiology
Background:
- Understanding weight trajectories is crucial for comprehending health impacts.
- Functional methods offer advanced approaches to analyze dynamic health data.
Purpose of the Study:
- To characterize distinct weight patterns during middle age.
- To identify sociodemographic and lifestyle correlates of these weight patterns.
Main Methods:
- Functional principal component analysis (PCA) applied to body mass index (BMI) data from ages 40-55.
- Analysis of a subset from the Framingham Heart Study original cohort (n=1,429).
- Gender-specific logistic regression models used to assess associations.
Main Results:
- Identified weight patterns including overall weight status, weight changes, and weight cycling.
- Overweight/obesity at age 25 was a significant predictor of middle-age weight patterns.
- Specific associations found for overall overweight, obesity, and weight cycling, with varying odds ratios for men and women.
Conclusions:
- Functional PCA effectively described middle-age weight patterns.
- Early-life weight status (at 25 years) is a strong determinant of later weight patterns.
- Emphasizes the critical importance of addressing weight management earlier in life.
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