For Publishers
DiscoveryMetadataPeer reviewHostingPublishing
For Researchers
JoinPublishReviewCollect
Register
Blog
About
Search
Advanced search
My ScienceOpen
Search
For Publishers
For Researchers
Blog
About
12
views
37
references
 Top references
cited by
15
    
0 reviews
 Review
0
comments
 Comment
0
recommends
+1 Recommend
0 collections
    0
    shares
      257
      similar
       All similar
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Association between Dietary Patterns and Cardiovascular Risk Factors among Middle-Aged and Elderly Adults in Taiwan: A Population-Based Study from 2003 to 2012

      research-article

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          Cardiovascular disease (CVD) is one of the leading causes of mortality and loss of disability-adjusted life years in developed countries. This study derived a dietary pattern using an a priori method and additionally derived dietary patterns using a posteriori methods, and assessed the relationship with CVD risk factors in Taiwanese middle-aged and elderly adults.

          Methods

          Cross-sectional analyses of 62,965 subjects aged 40 years and above from the Mei Jau (MJ) database collected between 2003 and 2012 in Taiwan. Diet was assessed using a 22 item semi-quantitative food frequency questionnaire. Using this information, three dietary patterns were generated. The a priori diet was labeled the Taiwanese dietary pattern and was derived using hypothesized effect of 22 food groups, while two a posteriori dietary patterns, “vegi-fruits” and “meat-processed”, were derived using principal component analysis. The association between dietary patterns and a range of CVD risk factors (i.e. blood lipids, blood glucose and C-reactive protein) was evaluated using linear regression.

          Results

          The results showed that high intake (Q5, quintile 5) of Taiwanese diet was negatively associated with CVD risk factors at ( p < 0.001, model 3), but not with triacylglycerol. In addition, high intake of vegi-fruit dietary pattern (Q5) was negatively associated with CVD risk factors ( p < 0.001), but not with high-density lipoprotein, while high consumption of meat-processed dietary pattern (Q5) was positively associated with CVD risk factors ( p < 0.001), but negatively related with triacylglycerol in Q3 level and no association with C-reactive protein.

          Conclusion

          A negative association was observed between Taiwanese or vegi-fruit dietary patterns and CVD risk factors, while a positive association was found between meat-processed dietary pattern and CVD risk factors. The findings suggested that a diet rich in vegetables and fruits has a beneficial effect in the management of CVD risk factors.

          Related collections

          Most cited references37

          • Record: found
          • Abstract: found
          • Article: not found

          Metabolic effects of dietary fiber consumption and prevention of diabetes.

          Martin Weickert, Andreas F H Pfeiffer (2008)
          A high dietary fiber (DF) intake is emphasized in the recommendations of most diabetes and nutritional associations. It is accepted that viscous and gel-forming properties of soluble DF inhibit macronutrient absorption, reduce postprandial glucose response, and beneficially influence certain blood lipids. Colonic fermentation of naturally available high fiber foods can also be mainly attributed to soluble DF, whereas no difference between soluble and insoluble DF consumption on the regulation of body weight has been observed. However, in prospective cohort studies, it is primarily insoluble cereal DF and whole grains, and not soluble DF, that is consistently associated with reduced diabetes risk, suggesting that further, unknown mechanisms are likely to be involved. Recent research indicates that DF consumption contributes to a number of unexpected metabolic effects independent from changes in body weight, which include improvement of insulin sensitivity, modulation of the secretion of certain gut hormones, and effects on various metabolic and inflammatory markers that are associated with the metabolic syndrome. In this review, we briefly summarize novel findings from recent interventions and prospective cohort studies. We discuss concepts and potential mechanisms that might contribute to the further understanding of the involved processes.
          Article 0 comments Cited 164 times – based on 0 reviews     Review now
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Dairy consumption, obesity, and the insulin resistance syndrome in young adults: the CARDIA Study.

            Martha Slattery, Rúben Pereira, Alex Kartashov … (2002)
            Components of the insulin resistance syndrome (IRS), including obesity, glucose intolerance, hypertension, and dyslipidemia, are major risk factors for type 2 diabetes and heart disease. Although diet has been postulated to influence IRS, the independent effects of dairy consumption on development of this syndrome have not been investigated. To examine associations between dairy intake and incidence of IRS, adjusting for confounding lifestyle and dietary factors. The Coronary Artery Risk Development in Young Adults (CARDIA) study, a population-based prospective study. General community sample from 4 US metropolitan areas of 3157 black and white adults aged 18 to 30 years who were followed up from 1985-1986 to 1995-1996. Ten-year cumulative incidence of IRS and its association with dairy consumption, measured by diet history interview. Dairy consumption was inversely associated with the incidence of all IRS components among individuals who were overweight (body mass index > or =25 kg/m(2)) at baseline but not among leaner individuals (body mass index or =35 times per week, 24/102 individuals) compared with the lowest (<10 times per week, 85/190 individuals) category of dairy consumption. Each daily occasion of dairy consumption was associated with a 21% lower odds of IRS (odds ratio, 0.79; 95% confidence interval, 0.70-0.88). These associations were similar for blacks and whites and for men and women. Other dietary factors, including macronutrients and micronutrients, did not explain the association between dairy intake and IRS. Dietary patterns characterized by increased dairy consumption have a strong inverse association with IRS among overweight adults and may reduce risk of type 2 diabetes and cardiovascular disease.
            Article 0 comments Cited 128 times – based on 0 reviews     Review now
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Dietary patterns are associated with biochemical markers of inflammation and endothelial activation in the Multi-Ethnic Study of Atherosclerosis (MESA).

              David R Jacobs, Rui Jiang, P Mayer … (2006)
              Dietary patterns may influence cardiovascular disease risk through effects on inflammation and endothelial activation. We examined relations between dietary patterns and markers of inflammation and endothelial activation. At baseline, diet (food-frequency questionnaire) and concentrations of C-reactive protein (CRP), interleukin 6 (IL-6), homocysteine, soluble intercellular adhesion molecule-1 (sICAM-1), and soluble E selectin were assessed in 5089 nondiabetic participants in the Multi-Ethnic Study of Atherosclerosis. Four dietary patterns were derived by using factor analysis. The fats and processed meats pattern (fats, oils, processed meats, fried potatoes, salty snacks, and desserts) was positively associated with CRP (P for trend < 0.001), IL-6 (P for trend < 0.001), and homocysteine (P for trend = 0.002). The beans, tomatoes, and refined grains pattern (beans, tomatoes, refined grains, and high-fat dairy products) was positively related to sICAM-1 (P for trend = 0.007). In contrast, the whole grains and fruit pattern (whole grains, fruit, nuts, and green leafy vegetables) was inversely associated with CRP, IL-6, homocysteine (P for trend < or = 0.001), and sICAM-1 (P for trend = 0.034), and the vegetables and fish pattern (fish and dark-yellow, cruciferous, and other vegetables) was inversely related to IL-6 (P for trend = 0.009). CRP, IL-6, and homocysteine relations across the fats and processed meats and whole grains and fruit patterns were independent of demographics and lifestyle factors and were not modified by race-ethnicity. CRP and homocysteine relations were independent of waist circumference. These results corroborate previous findings that empirically derived dietary patterns are associated with inflammation and show that these relations in an ethnically diverse population with unique dietary habits are similar to findings in more homogeneous populations.
              Article 0 comments Cited 125 times – based on 0 reviews     Review now
                Bookmark
                All references

                Author and article information

                Contributors
                Shahrad Taheri: Role: Editor
                Journal
                Journal ID (nlm-ta): PLoS One
                Journal ID (iso-abbrev): PLoS ONE
                Journal ID (publisher-id): plos
                Journal ID (pmc): plosone
                Title: PLoS ONE
                Publisher: Public Library of Science (San Francisco, CA USA )
                ISSN (Electronic): 1932-6203
                Publication date (Electronic): 1 July 2016
                Publication date Collection: 2016
                Volume: 11
                Issue: 7
                Electronic Location Identifier: e0157745
                Affiliations
                [1 ]School of Nutrition and Health Sciences, College of Public Health and Nutrition, Taipei Medical University, Taipei, Taiwan
                [2 ]International Health Program, Institute of Public Health, National Yang-Ming University, Taipei, Taiwan
                [3 ]Department of Information Management, National Taipei University of Nursing and Health Sciences, Taipei, Taiwan
                [4 ]Master Program in Global Health and Development, College of Public Health and Nutrition, Taipei Medical University, Taipei, Taiwan
                [5 ]Graduate Institute of Biomedical Informatics, College of Medical Technology, Taipei Medical University, Taipei, Taiwan
                [6 ]Nutrition Research Center, Taipei Medical University Hospital, Taipei, Taiwan
                Weill Cornell Medical College in Qatar, QATAR
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: MAM JCJC. Performed the experiments: MAM POO JCJC. Analyzed the data: POO MAM JCJC CYH HHR. Contributed reagents/materials/analysis tools: CYH HHR. Wrote the paper: MAM POO JCJC. Managed dataset and retrieved data: CYH HHR.

                Article
                Publisher ID: PONE-D-15-53051
                DOI: 10.1371/journal.pone.0157745
                PMC ID: 4930186
                PubMed ID: 27366909
                SO-VID: 52f73af4-07b7-4356-b9d1-7e944f17db7d
                Copyright © © 2016 Muga et al
                License:

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                Date received : 7 December 2015
                Date accepted : 4 June 2016
                Page count
                Figures: 1, Tables: 5, Pages: 18
                Funding
                The authors have no support or funding to report.
                Categories
                Subject: Research Article
                Subject: Medicine and Health Sciences
                Subject: Cardiovascular Medicine
                Subject: Cardiovascular Diseases
                Subject: Biology and Life Sciences
                Subject: Nutrition
                Subject: Diet
                Subject: Medicine and Health Sciences
                Subject: Nutrition
                Subject: Diet
                Subject: Biology and Life Sciences
                Subject: Nutrition
                Subject: Diet
                Subject: Food
                Subject: Medicine and Health Sciences
                Subject: Nutrition
                Subject: Diet
                Subject: Food
                Subject: Biology and Life Sciences
                Subject: Agriculture
                Subject: Animal Products
                Subject: Meat
                Subject: Biology and Life Sciences
                Subject: Nutrition
                Subject: Diet
                Subject: Food
                Subject: Meat
                Subject: Medicine and Health Sciences
                Subject: Nutrition
                Subject: Diet
                Subject: Food
                Subject: Meat
                Subject: Biology and Life Sciences
                Subject: Physiology
                Subject: Physiological Processes
                Subject: Food Consumption
                Subject: Medicine and Health Sciences
                Subject: Physiology
                Subject: Physiological Processes
                Subject: Food Consumption
                Subject: Medicine and Health Sciences
                Subject: Vascular Medicine
                Subject: Blood Pressure
                Subject: Biology and Life Sciences
                Subject: Anatomy
                Subject: Body Fluids
                Subject: Blood
                Subject: Medicine and Health Sciences
                Subject: Anatomy
                Subject: Body Fluids
                Subject: Blood
                Subject: Biology and Life Sciences
                Subject: Physiology
                Subject: Body Fluids
                Subject: Blood
                Subject: Medicine and Health Sciences
                Subject: Physiology
                Subject: Body Fluids
                Subject: Blood
                Subject: Medicine and Health Sciences
                Subject: Hematology
                Subject: Blood
                Subject: Research and Analysis Methods
                Subject: Mathematical and Statistical Techniques
                Subject: Statistical Methods
                Subject: Multivariate Analysis
                Subject: Principal Component Analysis
                Subject: Physical Sciences
                Subject: Mathematics
                Subject: Statistics (Mathematics)
                Subject: Statistical Methods
                Subject: Multivariate Analysis
                Subject: Principal Component Analysis
                Custom metadata
                Data Availability All relevant data are within the paper and its Supporting Information files.

                ScienceOpen disciplines: Uncategorized
                Data availability:
                ScienceOpen disciplines: Uncategorized

                Comments

                Comment on this article

                scite_

                Similar content257

                See all similar

                Cited by25

                See all cited by