Dataset Information

Dietary Quality Assessed by the HEI-2010 and Biomarkers of Cardiometabolic Disease: An Exploratory Analysis.

ABSTRACT: Objectives: This study explores relationships between cardiometabolic measures of antioxidant capacity or inflammation and diet quality assessed by the Healthy Eating Index (HEI)-2010 which measures conformity to Dietary Guidelines for Americans. This cross-sectional study was an ancillary analysis of baseline data for a randomized controlled trial with older adults at risk for cardiometabolic disease (ClinicalTrials.gov #NCT00955903). Methods: Community-dwelling older adults (n?=?133, 49% male, 70.4?±?4.8?years) with a body mass index of 30-40?kg/m2 provided a fasted blood sample for measurement of antioxidant capacity, high-sensitivity C-reactive protein, tumor necrosis factor-alpha, and interleukin-6. Dietary data were generated from the mean of three 24-hour recalls. Results: After adjustment for potential confounders, HEI-2010 composite scores were not significantly associated with decreased inflammation or greater antioxidant capacity. In analysis of the 12 components composing the HEI-2010, significant positive association was observed between total dairy and total serum antioxidant capacity (0.043; 95% CI, 0.008-0.069). Significant associations observed in inflammatory markers were between total vegetable and tumor necrosis factor-alpha (-0.078; 95% CI, -0.151 to -0.005), sodium and interleukin-6 (0.091; 95% CI, 0.023-0.158), and scores for combined calories from solid fats, alcoholic beverages, and added sugars and interleukin-6 (0.139; 95% CI, 0.027-0.252). In models adjusting for HEI-2010 composite score when significant associations were observed between component scores and biomarkers, two of six associations were strengthened by adding the composite score as a potential confounder. Conclusions: Largely null findings along with those inconsistent with scientific expectations suggest caution in extrapolating adherence to the HEI-2010 with an individual's inflammatory or antioxidant status. Results merit additional investigation with other biomarkers of chronic disease and emphasis on dietary patterns given potential synergy within food combinations.

SUBMITTER: Crowe-White KM

PROVIDER: S-EPMC7405913 | biostudies-literature | 2019 Sep-Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Dietary Quality Assessed by the HEI-2010 and Biomarkers of Cardiometabolic Disease: An Exploratory Analysis.

Crowe-White Kristi M KM Ellis Amy C AC Mehta Tapan T Locher Julie L JL Ard Jamy D JD

Journal of the American College of Nutrition 20190530 7

<b>Objectives:</b> This study explores relationships between cardiometabolic measures of antioxidant capacity or inflammation and diet quality assessed by the Healthy Eating Index (HEI)-2010 which measures conformity to Dietary Guidelines for Americans. This cross-sectional study was an ancillary analysis of baseline data for a randomized controlled trial with older adults at risk for cardiometabolic disease (ClinicalTrials.gov #NCT00955903). <b>Methods:</b> Community-dwelling older adults (n = ...[more]

PMID: 31145045

Similar Datasets

Project description:BackgroundAway from home (AFH) meals are known to be energy-dense and of poor diet quality. Both direct and indirect exposure (for example, neighborhood restaurant density) to AFH meals have been implicated as contributors to higher body weight and adverse health outcomes.ObjectiveTo examine the association of frequency of eating AFH and fast-food meals with biomarkers of chronic disease and dietary intake.DesignThis cross-sectional study used frequency of AFH and fast-food meal and biomarker data from the NHANES 2005-2010. Information on weekly frequency of AFH and fast-food meals was collected via questionnaire during the household interview. The metabolic biomarkers examined included body mass index (BMI), serum cholesterol (total, high-density lipoprotein (HDL) and low-density lipoprotein (LDL)), triglycerides, glycohemoglobin and fasting glucose (n=8314, age⩾20, National Health and Nutrition Examination Surveys (NHANES) 2007-2010). Biomarkers of dietary exposure included serum concentrations of vitamins A, D, E, C, B-6, B-12, folate and carotenoids (n=4162; 2005-2006). Multiple linear and logistic regression methods adjusted for complex survey methodology and covariates.ResultsAmerican adults reported a mean of 3.9 (95% confidence interval 3.7, 4.0) AFH and 1.8 (1.6, 1.9) fast-food meals/week. Over 50% of adults reported ⩾3 AFH and >35% reported ⩾2 fast-food meals/week. The mean BMI of more frequent AFH or fast-food meal reporters was higher (Ptrend⩽0.0004). Serum concentrations of total, LDL and HDL-cholesterol were related inversely with frequency of AFH meals (P<0.05). Frequencies of fast-food meals and serum HDL-cholesterol were also related inversely (P=0.0001). Serum concentrations of all examined micronutrients (except vitamin A and lycopene) declined with increasing frequency of AFH meals (P<0.05); women and ⩾50-year olds were at higher risk.ConclusionsReporters of frequent AFH and fast-food meals had higher BMI and lower concentrations of HDL-cholesterol; however, profiles of other biomarkers did not indicate higher metabolic risk. However, the serum concentrations of nutrients with mostly plant foods as sources declined with increasing AFH meal frequency.

Project description:Evaluating dietary guidelines using diet quality (DQ) offers valuable insights into the healthfulness of a population's diet. We conducted a forensic analysis using DQ metrics to compare the Malaysian Dietary Guidelines (MDG-2020) with its former version (MDG-2010) in relation to cardiometabolic risk (CMR) for an adult Malaysian population. A DQ analysis of cross-sectional data from the Malaysia Lipid Study (MLS) cohort (n = 577, age: 20-65yrs) was performed using the healthy eating index-2015 (HEI-2015) framework in conformation with MDG-2020 (MHEI2020) and MDG-2010 (MHEI2010). Of 13 dietary components, recommended servings for whole grain, refined grain, beans and legumes, total protein, and dairy differed between MDGs. DQ score associations with CMR, dietary patterns and sociodemographic factors were examined. Out of 100, total DQ scores of MLS participants were 'poor' for both MHEI2020 (37.1 ± 10.3) and MHEI2010 (39.1 ± 10.4), especially among young adults, males, Malays, and those frequently 'eating out' as well as those with greatest adherence to Sugar-Sweetened Beverages pattern and lowest adherence to Food Plant pattern. Both metrics shared similar correlations with CMR markers, with MHEI2020 exhibiting stronger correlations with WC, BF%, TG, insulin, HOMA2-IR, and smallLDL than MHEI2010, primarily attributed to reduced refined grain serving. Notably, participants with the highest adherence to MHEI2020 scores exhibited significantly reduced odds for elevated TG (AOR 0.44, 95% CI 0.21-0.93, p = 0.030), HOMA2-IR (AOR 0.44, 95% CI 0.21-0.88, p = 0.022), and hsCRP (AOR 0.54, 95% CI 0.31-0.96, p = 0.040, compared to those with the lowest adherence. Each 5-unit increase in MHEI2020 scores reduced odds for elevated BMI (- 14%), WC (- 9%), LDL-C (- 32%), TG (- 15%), HOMA2-IR (- 9%) and hsCRP (- 12%). While MHEI2020 scores demonstrated better calibration with CMR indicators, the overall sub-optimally 'poor' DQ scores of this population call for health promotion activities to target the public to achieve adequate intake of healthful fruits, non-starchy vegetables and whole grain, and moderate intake of refined grain, added sugar and saturated fat.

Project description:Diet quality indices score dietary intakes against recommendations, whereas dietary patterns consider the pattern and combination of dietary intakes. Studies evaluating both methodologies in relation to cardiometabolic health in a nationally representative sample are limited. The aim of the present study was to investigate the relationship between diet quality, dietary patterns and markers of cardiometabolic health in Australian adults.Dietary data, using two 24-h dietary recalls, were collected from adults in the cross-sectional Australian Health Survey 2011-2013 (n?=?2121; 46.4 (SE 0.48) years). Diet quality was estimated using the Dietary Guideline Index (DGI). Dietary patterns (DPs), derived using reduced rank regression, were estimated using fiber density, SFA: PUFA and total sugars intake as intermediate markers. Multi-variable adjusted linear regression analyses were used to examine associations between diet quality and DPs and blood biomarkers, body mass index, waist circumference, diastolic and systolic blood pressure and an overall cardiometabolic risk score.DGI was associated with lower glucose (coef -?0.009, SE 0.004; P-trend?=?0.033), body mass index (coef -?0.017, SE 0.007; P-trend?=?0.019) and waist circumference (coef -?0.014, SE 0.005; P-trend?=?0.008). Two dietary patterns were derived: dietary pattern-1 was characterized by higher intakes of pome fruit and wholegrain bread, while dietary pattern-2 was characterized by higher intakes of added sugars and tropical fruit. Dietary pattern-1 was associated with lower body mass index (coef -?0.028, SE 0.007; P-trend<?0.001) and waist circumference (coef -?0.017, SE 0.005; P-trend?=?0.001). There was a trend towards lower cardiometabolic risk score. Dietary pattern-2 was associated with lower HDL-cholesterol (coef -?0.026, SE 0.012; P-trend?=?0.028). There was a trend towards lower diastolic blood pressure. No associations with other markers were observed.Better diet quality and healthier dietary patterns were primarily associated with favorable anthropometric markers of cardiometabolic health. Findings support the need for comparison of whole-diet based methodologies that take into consideration the interactions between foods and nutrients. Longitudinal studies are warranted to better understand causal relationships between diet and cardiometabolic health.

Dataset Information

Dietary Quality Assessed by the HEI-2010 and Biomarkers of Cardiometabolic Disease: An Exploratory Analysis.

Publications

Dietary Quality Assessed by the HEI-2010 and Biomarkers of Cardiometabolic Disease: An Exploratory Analysis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets