Literature DB >> 25971717

Identifying cardiovascular risk factor-related dietary patterns with reduced rank regression and random forest in the EPIC-NL cohort.

Sander Biesbroek1, Daphne L van der A2, Marinka C C Brosens2, Joline W J Beulens3, W M Monique Verschuren2, Yvonne T van der Schouw3, Jolanda M A Boer2.   

Abstract

BACKGROUND: Several methods are used to determine dietary patterns. Hybrid methods incorporate information on nutrient intake or biological factors to extract patterns relevant to disease etiology.
OBJECTIVE: We explore differences between patterns derived with 2 hybrid methods with those obtained by a posteriori methods and compare associations of these patterns with coronary artery disease (CAD) and stroke risk.
DESIGN: Food-frequency questionnaires were used to estimate dietary intake in 34,644 participants of European Prospective Investigation into Cancer-Netherlands at baseline (1993-1997). Follow-up was complete until 31 December 2007. Hybrid methods to determine dietary patterns were reduced rank regression (RRR) and random forest with classification tree analysis (RF-CTA). Included risk factors were body mass index, total:high-density lipoprotein cholesterol ratio, and systolic blood pressure. Results were compared with those from principal component analysis (PCA) and k-means cluster analysis (KCA), respectively.
RESULTS: Both RRR and PCA derived a "Western," "prudent," and "traditional pattern." All RRR patterns were significantly associated with CAD risk [highest vs. lowest quartile factor score; HR: 1.45 (95% CI: 1.25, 1.69), 0.86 (0.74, 0.99), and 1.25 (1.07, 1.47), respectively]. Only the prudent RRR factor was statistically significant associated with stroke (HR: 0.76; 95% CI: 0.59, 0.97). From the PCA patterns, only the traditional pattern was associated with CAD (HR: 1.29; 95% CI: 1.11, 1.50). RF-CTA derived 7 dietary patterns that could be categorized as "Western-like," "prudent-like," and "traditional-like." KCA established a prudent and Western cluster. Compared with the RF-CTA "prudent-like 1" pattern, only the "traditional-like 1" pattern was associated with CAD (HR: 1.36; 955 CI: 1.12, 1.65). None of the RF-CTA groups were associated with stroke. Compared with the Western KCA cluster, the prudent cluster was not associated with CAD or stroke.
CONCLUSION: Including risk factors in RRR and RF-CTA resulted in small differences in food groups, contributing to similar patterns that showed in general stronger associations with CAD than PCA and KCA, respectively.
© 2015 American Society for Nutrition.

Entities:  

Keywords:  cardiovascular diseases; dietary patterns; principal component analysis; random forest; reduced rank regression

Mesh:

Year:  2015        PMID: 25971717     DOI: 10.3945/ajcn.114.092288

Source DB:  PubMed          Journal:  Am J Clin Nutr        ISSN: 0002-9165            Impact factor:   7.045


  11 in total

1.  Associations between dietary patterns and cardiovascular disease risk in Canadian adults: a comparison of partial least squares, reduced rank regression, and the simplified dietary pattern technique.

Authors:  Svilena V Lazarova; Mahsa Jessri
Journal:  Am J Clin Nutr       Date:  2022-08-04       Impact factor: 8.472

2.  Identification of dietary patterns associated with elevated blood pressure among Lebanese men: A comparison of principal component analysis with reduced rank regression and partial least square methods.

Authors:  Farah Naja; Laila Itani; Nahla Hwalla; Abla M Sibai; Samer A Kharroubi
Journal:  PLoS One       Date:  2019-08-16       Impact factor: 3.240

Review 3.  A review of statistical methods for dietary pattern analysis.

Authors:  Junkang Zhao; Zhiyao Li; Qian Gao; Haifeng Zhao; Shuting Chen; Lun Huang; Wenjie Wang; Tong Wang
Journal:  Nutr J       Date:  2021-04-19       Impact factor: 3.271

4.  Interactions between dietary patterns and genetic factors in relation to incident dementia among 70-year-olds.

Authors:  Ingmar Skoog; Anna Zettergren; Jessica Samuelsson; Jenna Najar; Ola Wallengren; Silke Kern; Hanna Wetterberg; Madeleine Mellqvist Fässberg; Henrik Zetterberg; Kaj Blennow; Lauren Lissner; Elisabet Rothenberg
Journal:  Eur J Nutr       Date:  2021-10-10       Impact factor: 5.614

5.  Visceral adiposity-related dietary patterns and the risk of cardiovascular disease in Iranian adults: A population-based cohort study.

Authors:  Nazanin Moslehi; Fatemeh Rahimi Sakak; Maryam Mahdavi; Parvin Mirmiran; Fereidoun Azizi
Journal:  Front Nutr       Date:  2022-07-28

6.  Associations between explorative dietary patterns and serum lipid levels and their interactions with ApoA5 and ApoE haplotype in patients with recently diagnosed type 2 diabetes.

Authors:  Katharina S Weber; Birgit Knebel; Klaus Strassburger; Jörg Kotzka; Peter Stehle; Julia Szendroedi; Karsten Müssig; Anette E Buyken; Michael Roden
Journal:  Cardiovasc Diabetol       Date:  2016-09-27       Impact factor: 9.951

7.  Nutrient-Derived Dietary Patterns and Their Association With Metabolic Syndrome in a Japanese Population.

Authors:  Tirani Bahari; Hirokazu Uemura; Sakurako Katsuura-Kamano; Miwa Yamaguchi; Mariko Nakamoto; Keisuke Miki; Masashi Ishizu; Kokichi Arisawa
Journal:  J Epidemiol       Date:  2017-11-18       Impact factor: 3.211

8.  Dietary patterns within educational groups and their association with CHD and stroke in the European Prospective Investigation into Cancer and Nutrition-Netherlands cohort.

Authors:  Sander Biesbroek; Mirjam C Kneepkens; Saskia W van den Berg; Heidi P Fransen; Joline W Beulens; Petra H M Peeters; Jolanda M A Boer
Journal:  Br J Nutr       Date:  2018-04       Impact factor: 3.718

9.  Food Liking-Based Diet Quality Indexes (DQI) Generated by Conceptual and Machine Learning Explained Variability in Cardiometabolic Risk Factors in Young Adults.

Authors:  Ran Xu; Bruce E Blanchard; Jeanne M McCaffrey; Stephen Woolley; Lauren M L Corso; Valerie B Duffy
Journal:  Nutrients       Date:  2020-03-25       Impact factor: 5.717

Review 10.  Advances in dietary pattern analysis in nutritional epidemiology.

Authors:  Christina-Alexandra Schulz; Kolade Oluwagbemigun; Ute Nöthlings
Journal:  Eur J Nutr       Date:  2021-04-25       Impact factor: 5.614

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