Structural equation modeling for analyzing erythrocyte fatty acids in framingham

James V. Pottala, Gemechis D. Djira, Mark A. Espeland, Jun Ye, Martin G. Larson, William Harris

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

Research has shown that several types of erythrocyte fatty acids (i.e., omega-3, omega-6, and trans) are associated with risk for cardiovascular diseases. However, there are complex metabolic and dietary relations among fatty acids, which induce correlations that are typically ignored when using them as risk predictors. A latent variable approach could summarize these complex relations into a few latent variable scores for use in statistical models. Twenty-two red blood cell (RBC) fatty acids were measured in Framingham (N = 3196). The correlation matrix of the fatty acids was modeled using structural equation modeling; the model was tested for goodness-of-fit and gender invariance. Thirteen fatty acids were summarized by three latent variables, and gender invariance was rejected so separate models were developed for men and women. A score was developed for the polyunsaturated fatty acid (PUFA) latent variable, which explained about 30% of the variance in the data. The PUFA score included loadings in opposing directions among three omega-3 and three omega-6 fatty acids, and incorporated the biosynthetic and dietary relations among them. Whether the PUFA factor score can improve the performance of risk prediction in cardiovascular diseases remains to be tested.

Original languageEnglish (US)
Article number160520
JournalComputational and Mathematical Methods in Medicine
Volume2014
DOIs
StatePublished - 2014
Externally publishedYes

Fingerprint

Structural Equation Modeling
Erythrocyte
Fatty Acids
Fatty acids
Erythrocytes
Unsaturated Fatty Acids
Polyunsaturated fatty acids
Latent Variables
Invariance
Cardiovascular Diseases
Omega-6 Fatty Acids
Omega-3 Fatty Acids
Statistical Models
Blood
Cells
Red Blood Cells
Research
Correlation Matrix
Goodness of fit
Statistical Model

ASJC Scopus subject areas

  • Applied Mathematics
  • Modeling and Simulation
  • Biochemistry, Genetics and Molecular Biology(all)
  • Medicine(all)
  • Immunology and Microbiology(all)

Cite this

Pottala, J. V., Djira, G. D., Espeland, M. A., Ye, J., Larson, M. G., & Harris, W. (2014). Structural equation modeling for analyzing erythrocyte fatty acids in framingham. Computational and Mathematical Methods in Medicine, 2014, [160520]. https://doi.org/10.1155/2014/160520

Structural equation modeling for analyzing erythrocyte fatty acids in framingham. / Pottala, James V.; Djira, Gemechis D.; Espeland, Mark A.; Ye, Jun; Larson, Martin G.; Harris, William.

In: Computational and Mathematical Methods in Medicine, Vol. 2014, 160520, 2014.

Research output: Contribution to journalArticle

Pottala, James V. ; Djira, Gemechis D. ; Espeland, Mark A. ; Ye, Jun ; Larson, Martin G. ; Harris, William. / Structural equation modeling for analyzing erythrocyte fatty acids in framingham. In: Computational and Mathematical Methods in Medicine. 2014 ; Vol. 2014.
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