Modifications to the Healthy Eating Index and its ability to predict obesity: the Multi-Ethnic Study of Atherosclerosis.

Department of Epidemiology, University of Washington, Seattle, WA, USA.
American Journal of Clinical Nutrition (Impact Factor: 6.92). 07/2008; 88(1):64-9.
Source: PubMed

ABSTRACT The Healthy Eating Index (HEI) is a measure of diet quality developed based on the Dietary Guidelines for Americans (DGA).
The objective was to assess the diet quality of a multi-ethnic population using and comparing the 2 HEIs, the updated HEI (HEI-05) based on the 2005 DGA and the original 1990 HEI (HEI-90), with the objective of predicting obesity outcomes.
A longitudinal analysis of survey and clinical data from 6236 middle-aged and elderly white, African American, Hispanic, and Chinese participants of the Multi-Ethnic Study of Atherosclerosis (MESA) was conducted. Baseline diet quality was assessed with the use of HEI-90 and HEI-05. Baseline and 18-mo follow-up body mass index (BMI) and waist circumference (WC) data were predicted by using z score multiple regression models, and categorical obesity status was predicted by using multinomial logistic regression.
Overall, the HEI-05 had larger z score beta coefficients than did the HEI-90 (eg, in whites, -0.53 compared with -0.48 in baseline BMI, -0.54 compared with -0.47 in follow-up BMI, -1.67 compared with -1.56 in baseline WC, and -1.57 compared with -1.44 in follow-up WC). Among whites only, both HEIs were significant predictors of BMI and WC (all P < 0.001). The odds of being obese rather than normal weight were inversely related to HEI z scores primarily in whites (P < 0.05).
The changes to the 2005 DGA, as reflected by HEI-05, appear to better predict obesity outcomes in this multi-ethnic population, primarily in whites. Additional research on ethnic-specific DGA adherence and its relation to health outcomes is needed.

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    • "In the present study, the previously described HEI-2005 (Guenther et al. 2007, 2008), adapted to Brazilian dietary guidelines (B-HEI), was applied in an attempt to establish this relationship. The finding that the subset of individuals with the highest B-HEI values had better measures of body adiposity (lower BMI and waist circumference) is in agreement with the results of 2 other studies (Guo et al. 2004; Gao et al. 2008). It is noteworthy that in our analysis of single components, saturated fatty acids intake, which has been recognized as a major nutrient responsible for weight gain in modern societies, may have contributed to the finding of an inverse association with waist circumference (WHO 2003; Hooper et al. 2012). "
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    ABSTRACT: Eating habits may influence inflammatory status and insulin resistance, both involved in the genesis of cardiometabolic diseases; an index of overall diet quality may be useful to identify risk for these diseases. We investigated whether the Healthy Eating Index (HEI-2005), adapted to Brazilian habits (B-HEI), was associated with markers of inflammation, insulin resistance and lipid profile in individuals at cardiometabolic risk. Two hundred and four prediabetic individuals (64.7% women) were enrolled in this cross-sectional study. Anthropometric measurements, 24-h dietary recalls used to calculate the B-HEI, and blood samples were collected. ANOVA was used for comparisons of clinical variables across the B-HEI tertiles and multiple linear regressions employed to test associations between clinical variables and B-HEI total score. Significant trends to decrease mean values of body mass index (BMI) (p = 0.03) and C-reactive protein concentrations (p = 0.02) across the tertiles of B-HEI, but not other biomarkers, were observed. Waist circumference, HOMA-IR and C-reactive protein were inversely associated with the B-HEI (p < 0.05), after adjusting for age, sex, BMI, and physical activity level. Also, a direct association of adiponectin concentrations with B-HEI was detected after adjustments (p = 0.001). Data from this study indicate that the B-HEI may be useful to identify the body adiposity-induced pro-inflammatory status and insulin resistance in individuals at cardiometabolic risk.
    Applied Physiology Nutrition and Metabolism 04/2014; 39(4):497-502. DOI:10.1139/apnm-2013-0279 · 2.01 Impact Factor
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    • "Examination of the total diet and nutrient intake patterns of individuals may provide better measures of diet exposure, helping identify individuals who may benefit from targeted nutritional risk interventions [9] [10]. Few studies have evaluated overall dietary quality using composite dietary indices/scores in relation to abdominal adiposity, [10] [11] [12] [13] [14] [15] [16] and the majority are cross-sectional investigations [11] [12] [13] [14] [15]. Further, none of the existing composite dietary quality indices/scores are based on a specific evidence basis for the most consistent dietary determinants of abdominal or peripheral obesity. "
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    ABSTRACT: Background. Links between dietary quality and abdominal obesity are poorly understood. Objective. To examine the association between an obesity-specific dietary quality index and abdominal obesity risk in women. Methods. Over 12 years, we followed 288 Framingham Offspring/Spouse Study women, aged 30–69 years, without metabolic syndrome risk factors, cardiovascular disease, cancer, or diabetes at baseline. An 11-nutrient obesity-specific dietary quality index was derived using mean ranks of nutrient intakes from 3-day dietary records. Abdominal obesity (waist circumference >88 cm) was assessed during follow-up. Results. Using multiple logistic regression, women with poorer dietary quality were more likely to develop abdominal obesity compared to those with higher dietary quality (OR 1.87; 95% CI, 1.01, 3.47; P for trend = .048) independent of age, physical activity, smoking, and menopausal status. Conclusions. An obesity-specific dietary quality index predicted abdominal obesity in women, suggesting targets for dietary quality assessment, intervention, and treatment to address abdominal adiposity.
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    • "Previous studies examining the associations between food intake and obesity in the population have almost always relied on self-reported data, often identified eating patterns by factor analysis or cluster analysis, and occasionally used dietary indexes to measure diet quality (Gao et al., 2008; Heidemann et al., 2008; Hu et al., 2000; Kennedy et al., 1995). The current study differs from those previous studies, as we asked twins to compare their eating and physical activity behavior with that of their siblings, in this case their same-aged co-twins. "
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