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Dietary patterns, insulin sensitivity and adiposity in the multi-ethnic Insulin Resistance Atherosclerosis Study population

  • Angela D. Liese (a1), Mandy Schulz (a1) (a2), Charity G. Moore (a1) and Elizabeth J. Mayer-Davis (a1) (a3)
  • DOI: http://dx.doi.org/10.1079/BJN20041279
  • Published online: 09 March 2007
Abstract

Epidemiological investigations increasingly employ dietary-pattern techniques to fully integrate dietary data. The present study evaluated the relationship of dietary patterns identified by cluster analysis with measures of insulin sensitivity (SI) and adiposity in the multi-ethnic, multi-centre Insulin Resistance Atherosclerosis Study (IRAS, 1992–94). Cross-sectional data from 980 middle-aged adults, of whom 67% had normal and 33% had impaired glucose tolerance, were analysed. Usual dietary intake was obtained by an interviewer-administered, validated food-frequency questionnaire. Outcomes included SI, fasting insulin (FI), BMI and waist circumference. The relationship of dietary patterns to log(SI+1), log(FI), BMI and waist circumference was modelled with multivariable linear regressions. Cluster analysis identified six distinct diet patterns – ‘dark bread’, ‘wine’, ‘fruits’, ‘low-frequency eaters’, ‘fries’ and ‘white bread’. The ‘white bread’ and the ‘fries’ patterns over-represented the Hispanic IRAS population predominantly from two centres, while the ‘wine’ and ‘dark bread’ groups were dominated by non-Hispanic whites. The dietary patterns were associated significantly with each of the outcomes first at the crude, clinical level (P<0·001). Furthermore, they were significantly associated with FI, BMI and waist circumference independent of age, sex, race or ethnicity, clinic, family history of diabetes, smoking and activity (P<0.004), whereas significance was lost for SI. Studying the total dietary behaviour via a pattern approach allowed us to focus both on the qualitative and quantitative dimensions of diet. The present study identified highly consistent associations of distinct dietary patterns with measures of insulin resistance and adiposity, which are risk factors for diabetes and heart disease.

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*Corresponding author: Dr Angela D. Liese, fax +1 803 777 2524, email, Liese@sc.edu
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