### 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 language | English (US) |
---|---|

Article number | 160520 |

Journal | Computational and Mathematical Methods in Medicine |

Volume | 2014 |

DOIs | |

State | Published - 2014 |

Externally published | Yes |

### Fingerprint

### ASJC Scopus subject areas

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

### Cite this

*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.

Research output: Contribution to journal › Article

*Computational and Mathematical Methods in Medicine*, vol. 2014, 160520. https://doi.org/10.1155/2014/160520

}

TY - JOUR

T1 - Structural equation modeling for analyzing erythrocyte fatty acids in framingham

AU - Pottala, James V.

AU - Djira, Gemechis D.

AU - Espeland, Mark A.

AU - Ye, Jun

AU - Larson, Martin G.

AU - Harris, William

PY - 2014

Y1 - 2014

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=84902201131&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84902201131&partnerID=8YFLogxK

U2 - 10.1155/2014/160520

DO - 10.1155/2014/160520

M3 - Article

C2 - 24959197

AN - SCOPUS:84902201131

VL - 2014

JO - Computational and Mathematical Methods in Medicine

JF - Computational and Mathematical Methods in Medicine

SN - 1748-670X

M1 - 160520

ER -