Literature DB >> 18065595

Intake of whole grains, refined grains, and cereal fiber measured with 7-d diet records and associations with risk factors for chronic disease.

P K Newby1, Janice Maras, Peter Bakun, Denis Muller, Luigi Ferrucci, Katherine L Tucker.   

Abstract

BACKGROUND: Research studies examining foods are important, because they account for biological interactions that might otherwise be lost in the analysis of individual nutrients. Single-nutrient studies are also needed to explore the mechanisms by which foods may be protective.
OBJECTIVE: Our objective was to examine associations between whole grains, refined grains, and cereal fiber and chronic disease risk factors.
DESIGN: In a cross-sectional analysis of participants in the Baltimore Longitudinal Study of Aging, associations between dietary intakes and risk factors were examined with multivariate linear regression analysis. Dietary intakes were assessed with 7-d dietary records and quantified in g/d.
RESULTS: Compared with subjects in the lowest quintile (Q1) of whole-grain intake, subjects in the highest quintile (Q5) had lower body mass index (BMI; in kg/m(2); Q1: 25.5; Q5: 24.8; P for trend <0.0001) and weight (Q1: 75.0 kg; Q5: 72.4 kg; P for trend = 0.004) and smaller waist circumference (Q1: 87.4 cm; Q5: 85.0 cm; P for trend = 0.002). Whole grains were also inversely associated with total cholesterol (P for trend = 0.02), LDL cholesterol (P for trend = 0.04), and 2-h glucose (P for trend = 0.0006). Associations between cereal fiber and anthropometrics and plasma lipids were similar. In subgroup analyses, refined grains were positively associated with fasting insulin among women (P for trend = 0.002).
CONCLUSIONS: Similar associations of whole grains and cereal fiber with weight, BMI, waist circumference, plasma cholesterol, and 2-h glucose were observed, suggesting that cereal fiber and its constituents may in part mediate these relations. Refined grains were associated with fasting insulin among women but not men. Additional research should explore potential interaction effects with BMI, sex, age, and genes.

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Year:  2007        PMID: 18065595      PMCID: PMC2646086          DOI: 10.1093/ajcn/86.5.1745

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


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