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      The Relationship of Dietary Pattern and Genetic Risk Score with the Incidence of Dyslipidemia: 14-Year Follow-Up Cohort Study

      research-article
      1 , 2 , 3 , 4 , * , 1 , *
      Nutrients
      MDPI
      diet, dyslipidemia, genetics, cohort study

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          Abstract

          This study was conducted to investigate the relationship between dietary pattern and genetic risk score (GRS) for dyslipidemia risk among Korean adults. Hypercholesterolemia and hypertriglyceridemia defined as total cholesterol ≥240 mg/dL and triglyceride ≥200 mg/dL or use dyslipidemia medication. The GRS was calculated by summing the risk alleles of the selected seven single-nucleotide polymorphisms related to dyslipidemia. Dietary patterns were identified by principal component analysis based on the frequency of 36 food groups, “whole grain and soybean products” pattern, “meat, fish and vegetables” pattern, and “bread and noodle” pattern were identified. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using the multivariate Cox proportional hazards regression model. High intake of a “whole grain and soybean products” pattern decreased risks of hypercholesterolemia (HR: 0.82, 95% CI: 0.72–0.93, p for trend = 0.0006) and hypertriglyceridemia (HR: 0.85, 95% CI: 0.75–0.97, p for trend = 0.0344). In the highest tertile of GRS, the “whole grain and soybean products” pattern was inversely related to hypercholesterolemia risk. Therefore, for people with genotypes that can cause hypercholesterolemia, eating whole grains and soybean products may have a meaningful response, these results could be utilized for genome-based nutrition management.

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          Most cited references45

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          Third Report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) final report.

          (2002)
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            Dietary pattern analysis: a new direction in nutritional epidemiology.

            Frank Hu (2002)
            Recently, dietary pattern analysis has emerged as an alternative and complementary approach to examining the relationship between diet and the risk of chronic diseases. Instead of looking at individual nutrients or foods, pattern analysis examines the effects of overall diet. Conceptually, dietary patterns represent a broader picture of food and nutrient consumption, and may thus be more predictive of disease risk than individual foods or nutrients. Several studies have suggested that dietary patterns derived from factor or cluster analysis predict disease risk or mortality. In addition, there is growing interest in using dietary quality indices to evaluate whether adherence to a certain dietary pattern (e.g. Mediterranean pattern) or current dietary guidelines lowers the risk of disease. In this review, we describe the rationale for studying dietary patterns, and discuss quantitative methods for analysing dietary patterns and their reproducibility and validity, and the available evidence regarding the relationship between major dietary patterns and the risk of cardiovascular disease.
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              Vegetarian, vegan diets and multiple health outcomes: a systematic review with meta-analysis of observational studies.

              Beneficial effects of vegetarian and vegan diets on health outcomes have been supposed in previous studies.
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                Author and article information

                Journal
                Nutrients
                Nutrients
                nutrients
                Nutrients
                MDPI
                2072-6643
                16 December 2020
                December 2020
                : 12
                : 12
                : 3840
                Affiliations
                [1 ]Department of Food and Nutrition, College of BioNano Technoloyg, Gachon University, Gyeonggi 13120, Korea; chris0825@ 123456hanmail.net
                [2 ]Research Group of Healthcare, Korea Food Research Institute, Wanju 55365, Korea; truka@ 123456kfri.re.kr
                [3 ]Department of Food Biotechnology, Korea University of Science and Technology, Daejeon 34113, Korea
                [4 ]Chaum Life Center, CHA University, Seoul 06062, Korea
                Author notes
                [* ]Correspondence: sang.choi@ 123456cha.ac.kr (S.-W.C.); skysea@ 123456gachon.ac.kr or skysea1010@ 123456gmail.com (H.-J.L.); Tel.: +82-31-750-5968 (H.-J.L.); Fax: +82-31-724-4411 (H.-J.L.)
                [†]

                These authors contributed equally to this work.

                Author information
                https://orcid.org/0000-0002-1825-1815
                https://orcid.org/0000-0002-5020-3397
                https://orcid.org/0000-0001-8353-3619
                Article
                nutrients-12-03840
                10.3390/nu12123840
                7765618
                33339179
                a5956534-9bc7-4bb9-9ba6-13c63949c1c9
                © 2020 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 20 November 2020
                : 13 December 2020
                Categories
                Article

                Nutrition & Dietetics
                diet,dyslipidemia,genetics,cohort study
                Nutrition & Dietetics
                diet, dyslipidemia, genetics, cohort study

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