Dietary patterns: biomarkers and chronic disease riskThis paper is one of a selection of papers published in the CSCN–CSNS 2009 Conference, entitled Are dietary patterns the best way to make nutrition recommendations for chronic disease prevention?

Author:

Kant Ashima K.1

Affiliation:

1. Deptartment of Family, Nutrition, and Exercise Sciences, Remsen Hall, Room 306E, Queens College of the City University of New York, Flushing, NY 11367, USA (e-mail: ).

Abstract

With increasing appreciation of the complexity of diets consumed by free-living individuals, there is interest in the assessment of the overall diet or dietary patterns in which multiple related dietary characteristics are considered as a single exposure. The 2 most frequently used methods to derive dietary patterns use (i) scores or indexes based on prevailing hypotheses about the role of dietary factors in disease prevention; and (ii) factors and clusters from exploration of available dietary data. A third method, a hybrid of the hypothesis-driven and data-driven methods, attempts to predict food combinations related to nutrients or biomarkers with hypothesized associations with particular health outcomes. Dietary patterns derived from the first 2 approaches have been examined in relation to nutritional and disease biomarkers and various health outcomes, and generally show the desirable dietary pattern to be consistent with prevalent beliefs about what constitutes a healthful diet. Results from observational studies suggest that the healthful dietary patterns were associated with significant but modest risk reduction (15%–30%) for all-cause mortality and coronary heart disease. Findings for various cancers have been inconsistent. The available randomized controlled intervention trials with a long-term follow-up to examine dietary patterns in relation to health outcome have generally produced null findings. Novel findings with the potential to change existing beliefs about diet and health relationships are yet to emerge from the dietary patterns research. The field requires innovation in methods to derive dietary patterns, validation of prevalent methods, and assessment of the effect of dietary measurement error on dietary patterns.

Publisher

Canadian Science Publishing

Subject

Physiology (medical),Nutrition and Dietetics,Physiology,General Medicine,Endocrinology, Diabetes and Metabolism

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