Chronic, systemic inflammation is mechanistically involved in processes associated with most major chronic diseases. The Dietary Inflammatory Index (DII) was developed to measure diet-based inflammatory potential, a strong risk factor for systemic inflammation. Participants included those attending baseline measurement clinics for the Healthy Eating and Active Living in the Spirit (HEALS) educational and behavioral intervention (2009-2012). HEALS, a randomized control trial set in faith-based communities, enrolled African Americans (AA) at high risk of chronic inflammation and related diseases. Baseline data were utilized for these analyses. Prior to each clinic visit, participants completed a questionnaire packet to assess demographic characteristics, physical activity, sleep habits (Pittsburgh Sleep Quality Index), health history, depression/stress, and social desirability, approval, and support. Dietary data were collected using a 144-item food frequency questionnaire (FFQ) which was modified based on the Block/NCI instrument. Dietary data from this FFQ, processed using the Nutrient Data System for Research (version 2012, Nutrition Coordinating Center, University of Minnesota, Minneapolis, Minnesota) was used to compute the DII. The DII is comprised of various micro and macronutrients, as well as several individual food items (collectively termed ‘food parameters’); each of which has an inflammatory effect score based on research from 1,943 diet and inflammation research articles. A “world” database (11 populations from around the world) consisting of means and standard deviations for the food parameters was subtracted from an individual's actual dietary intake and divided by its standard deviation, creating a z-score, which were centered around 0 and multiplied by the inflammatory effect score. These were summed across all parameters to create the overall DII score, which were categorized into quartiles. During clinic visits, participants had their blood pressure, height, weight, and percent body fat (via bioelectrical impedance assessment) measured. Physical activity levels were measured using Bodymedia's SenseWear® physical activity armband monitors. Blood samples were collected to characterize inflammatory biomarkers (i.e., high-sensitivity c-reactive protein [CRP] and interleukin-6 [IL-6]). In addition to using quantile regression for the main analyses, logistic regression was utilized when CRP was categorized as ≤3.0mg/L vs. >3.0mg/L. The population was middle-aged (average = 56.9±11.3 years), obese (mean BMI=32.6±6.9kg/m2) and primarily female (80%). Various population characteristics were described according to DII quartiles. Higher DII values were associated with younger age, being married or living with a partner, being employed fulltime, and having a higher BMI. Quantile regression was used to estimate the adjusted 25th, 75th, and 90th percentiles of both CRP and IL-6. The 75th and 90th percentiles of CRP for the fourth quartile of the DII were significantly greater than for the first DII quartile (β0.75=3.95, 95% confidence interval [95%CI]=1.71-6.19; β0.90=6.83, 95%CI=1.11-12.55). No significant findings were observed for IL-6. Logistic regression analyses agreed with the quantile regression results for CRP. Those in DII quartile 4 had 3.17 times (95%CI=1.52-6.62) the odds of having CRP values greater than 3.0mg/L compared to those in DII quartile 1. This is the first construct validation of the DII in an all AA population. Chronic inflammation is a risk factor for many major chronic diseases, diseases that AA suffer from disproportionately. Therefore, the DII may serve as a useful tool to track dietary inflammatory potential among AA populations, which, in turn, may reduce risk of chronic disease among these populations.
Citation Format: Michael Wirth, Nitin Shivappa, Lisa Davis, Thomas Hurley, Andrew Ortaglia, Ruby Drayton, Steven Blair, James Hebert. The dietary inflammatory index is associated with inflammatory biomarkers among a population of African Americans from South Carolina. [abstract]. In: Proceedings of the Eighth AACR Conference on The Science of Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; Nov 13-16, 2015; Atlanta, GA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2016;25(3 Suppl):Abstract nr A69.