Literature DB >> 12716666

Patterns of food consumption and risk factors for cardiovascular disease in the general Dutch population.

Rob M van Dam1, Linda Grievink, Marga C Ocké, Edith J M Feskens.   

Abstract

BACKGROUND: Few studies have examined food consumption patterns in relation to biological risk factors for cardiovascular disease.
OBJECTIVE: The objective of the study was to describe food consumption patterns in the general Dutch population and their association with cardiovascular risk factors.
DESIGN: We performed a cross-sectional study of 19 750 randomly selected men and women aged 20-65 y from 3 Dutch municipalities. Food consumption patterns were identified with the use of factor analysis of data from a validated food-frequency questionnaire.
RESULTS: Three food consumption patterns were identified: the "cosmopolitan" pattern (greater intakes of fried vegetables, salad, rice, chicken, fish, and wine), the "traditional" pattern (greater intakes of red meat and potatoes and lesser intakes of low-fat dairy and fruit), and the "refined-foods" pattern (greater intakes of French fries, high-sugar beverages, and white bread and lesser intakes of whole-grain bread and boiled vegetables). Higher scores for the traditional pattern were associated with older age, and higher scores for the refined-foods pattern were associated with younger age, but both were associated with lower educational level, cigarette smoking, less physical activity, and higher body mass index. Independent of other lifestyle factors and body mass index, the cosmopolitan-pattern score was significantly associated with lower blood pressure and higher HDL-cholesterol concentrations, and the traditional-pattern score was associated with higher blood pressure and higher concentrations of HDL cholesterol, total cholesterol, and glucose. The refined-foods-pattern score was associated with higher total cholesterol concentrations and lower intakes of micronutrients.
CONCLUSION: In this Dutch population, food consumption patterns were independently associated with blood pressure and plasma glucose and cholesterol concentrations.

Entities:  

Mesh:

Substances:

Year:  2003        PMID: 12716666     DOI: 10.1093/ajcn/77.5.1156

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


  45 in total

1.  Associations between dietary patterns and flow cytometry-measured biomarkers of inflammation and cellular activation in the Atherosclerosis Risk in Communities (ARIC) Carotid Artery MRI Study.

Authors:  Jennifer A Nettleton; Nena Matijevic; Jack L Follis; Aaron R Folsom; Eric Boerwinkle
Journal:  Atherosclerosis       Date:  2010-04-29       Impact factor: 5.162

2.  Patterns of dietary intake and relation to respiratory disease, forced expiratory volume in 1 s, and decline in 5-y forced expiratory volume.

Authors:  Tricia M McKeever; Sarah A Lewis; Patricia A Cassano; Marga Ocké; Peter Burney; John Britton; Henriette A Smit
Journal:  Am J Clin Nutr       Date:  2010-06-16       Impact factor: 7.045

3.  Cardiovascular disease: optimal approaches to risk factor modification of diet and lifestyle.

Authors:  Daniel Forman; Bernard E Bulwer
Journal:  Curr Treat Options Cardiovasc Med       Date:  2006-02

4.  A prospective study of dietary patterns, meat intake and the risk of gestational diabetes mellitus.

Authors:  C Zhang; M B Schulze; C G Solomon; F B Hu
Journal:  Diabetologia       Date:  2006-09-07       Impact factor: 10.122

5.  Does food group consumption vary by differences in socioeconomic, demographic, and lifestyle factors in young adults? The Bogalusa Heart Study.

Authors:  Priya Deshmukh-Taskar; Theresa A Nicklas; Su-Jau Yang; Gerald S Berenson
Journal:  J Am Diet Assoc       Date:  2007-02

Review 6.  Optimizing management of metabolic syndrome to reduce risk: focus on life-style.

Authors:  Cristina Bianchi; Giuseppe Penno; Giuseppe Daniele; Luca Benzi; Stefano Del Prato; Roberto Miccoli
Journal:  Intern Emerg Med       Date:  2008-02-13       Impact factor: 3.397

7.  Comparison of 3 methods for identifying dietary patterns associated with risk of disease.

Authors:  Julia R DiBello; Peter Kraft; Stephen T McGarvey; Robert Goldberg; Hannia Campos; Ana Baylin
Journal:  Am J Epidemiol       Date:  2008-10-22       Impact factor: 4.897

8.  Dietary patterns are associated with metabolic syndrome in adult Samoans.

Authors:  Julia R DiBello; Stephen T McGarvey; Peter Kraft; Robert Goldberg; Hannia Campos; Christine Quested; Tuiasina Salamo Laumoli; Ana Baylin
Journal:  J Nutr       Date:  2009-08-26       Impact factor: 4.798

9.  A comparison of principal component analysis, partial least-squares and reduced-rank regressions in the identification of dietary patterns associated with bone mass in ageing Australians.

Authors:  Yohannes Adama Melaku; Tiffany K Gill; Anne W Taylor; Robert Adams; Zumin Shi
Journal:  Eur J Nutr       Date:  2017-06-12       Impact factor: 5.614

10.  Dietary patterns and glucose tolerance abnormalities in Chinese adults.

Authors:  Yuna He; Guansheng Ma; Fengying Zhai; Yanping Li; Yisong Hu; Edith J M Feskens; Xiaoguang Yang
Journal:  Diabetes Care       Date:  2009-08-12       Impact factor: 19.112

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.