Dietary energy density is associated with obesity and other biomarkers of chronic disease in US adults
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Given the current prevalence of obesity, it is important to identify dietary factors that may aid in disease prevention. The objective of the present study was to evaluate the association between consumption of an energy-dense diet and established markers factors for chronic disease, including body weight and measures of body fatness.
Data from a nationally representative sample of 9,551 adults ≥18 years who participated in the 2005–2008 National Health and Nutrition Examination Survey were analyzed. The association between dietary energy density (ED, energy per weight of food, kcal/g) and markers for obesity [including body mass index (BMI) and waist circumference (WC)], insulin insensitivity [including fasting glucose, insulin and homeostasis assessment model for insulin resistance (HOMA-IR)], and markers for inflammation was examined.
Dietary ED was positively associated with obesity in both men and women in multivariate models. Overall, obese adults had a significantly higher dietary ED than lean adults (p < 0.0001). Current smokers had significantly higher ED than non-smokers (2.00 vs. 1.75, p < 0.01), and it was determined that smoking status modified the relationship between ED and weight status in women (p interaction 0.03). In both sexes, there was a positive linear relationship between BMI and ED (p trend 0.01 and 0.0002, respectively); a linear trend between WC and ED was also observed in women (p trend <0.001) after adjusting for relevant cofactors. In women, ED was positively associated with HOMA-IR and fasting insulin; though, this relationship was not observed in men. No significant associations between ED and C-reactive protein were observed in either sex.
These findings support recent obesity and disease prevention recommendations to consume a diet low in ED.
KeywordsEnergy density NHANES Waist circumference BMI Obesity
This study was supported in part by a Grant from American Institute of Cancer Research (10A078). We acknowledge the assistance provided by the Population Research Center at The Pennsylvania State University, which is supported by an infrastructure grant by the National Institutes of Health (2R24HD041025-11).
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