The Healthy Eating Index-2015 (HEI-2015) was created to assess conformance of dietary intake with the Dietary Guidelines for Americans (DGA) 2015–2020. We assessed the association between the HEI-2015 and mortality from all-cause, cardiovascular disease (CVD), and cancer in the Multiethnic Cohort (MEC). White, African American, Native Hawaiian, Japanese American, and Latino adults (n > 215,000) from Hawaii and California completed a quantitative food-frequency questionnaire at study enrollment. HEI-2015 scores were divided into quintiles for men and women. Radar graphs were used to demonstrate how dietary components contributed to HEI-2015 scores. Mortality was documented over 17–22 years of follow-up. Hazard ratios (HRs) and 95% confidence intervals (CIs) were computed using Cox proportional hazards models. High HEI-2015 scores were inversely associated with risk of mortality from all-cause, CVD, and cancer for men and women (p-trend <0.0001 for all models). For men, the HRs (CIs) for all-cause, CVD, and cancer comparing the highest to the lowest quintile were 0.79 (0.76, 0.82), 0.76 (0.71, 0.82), and 0.80 (0.75, 0.87), respectively. For women, the HRs were 0.79 (0.76, 0.82), 0.75 (0.70, 0.81), and 0.84 (0.78, 0.91), respectively. These results, in a multiethnic population, demonstrate that following a diet aligned with the DGAs 2015–2020 recommendations is associated with lower risk of mortality from all-cause, CVD, and cancer.

Intermittent energy restriction combined with a Mediterranean diet (IER+MED) has shown promise to reduce body fat and insulin resistance. In the Multiethnic Cohort Adiposity Phenotype Study, Japanese Americans had the highest visceral adipose tissue (VAT) when adjusting for total adiposity. We conducted this pilot study to demonstrate feasibility and explore efficacy of following IER+MED for 12 weeks to reduce VAT among East Asians in Hawaii. Sixty volunteers (aged 35–55, BMI 25–40 kg/m², VAT ≥ 90 cm² for men and ≥ 80 cm² for women) were randomized to IER+MED (two consecutive days with 70% energy restriction and 5 days euenergetic MED) or an active comparator (euenergetic Dietary Approaches to Stop Hypertension (DASH) diet). Participants and clinic staff (except dietitians) were blinded to group assignments. IER+MED had significantly larger reductions in DXA-measured VAT and total fat mass (−22.6 ± 3.6 cm² and −3.3 ± 0.4 kg, respectively) vs. DASH (−10.7 ± 3.5 cm² and −1.6 ± 0.4 kg) (p = 0.02 and p = 0.005). However, after adjusting for total fat mass, change in VAT was not statistically different between groups; whereas, improvement in alanine transaminase remained significantly greater for IER+MED vs. DASH (−16.2 ± 3.8 U/L vs. −4.0 ± 3.6 U/L, respectively, p = 0.02). Attrition rate was 10%, and participants adhered well to study prescriptions with no reported major adverse effect. Results demonstrate IER+MED is acceptable, lowers visceral and total adiposity among East Asian Americans, and may improve liver function more effectively than a healthful diet pattern. ClinicalTrials.gov Identifier: NCT03639350.

Understanding of behavioral factors associated with obesity is of importance in addressing this issue. This study examined the association between cognitive restraint, uncontrolled eating, emotional eating and body mass index (BMI) and amount of food plated, consumed, leftovers, and leftover food thrown into the trash (food wasted) in early adolescent girls nine to 13 years in O’ahu, Hawai’i (n = 93). Food plated, consumed, leftovers, and food wasted were estimated using a three-day mobile food record™ (mFR). Weight and height were measured to compute BMI (kg/m²). The three-factor eating questionnaire provided a score from 0 to 100 for cognitive restraint, uncontrolled eating, and emotional eating. Higher scores are indicative of greater cognitive restraint, uncontrolled eating, and emotional eating. Pearson’s correlations were computed to examine the relationship between three factor eating scores and BMI. General linear models were conducted to examine the effect of each of three-factor eating scores on food plated, consumed, leftovers, and food wasted. Cognitive restraint was positively correlated with BMI (r = 0.36, p < 0.001) and with BMI z-score (r = 0.40, p < 0.001). There were no associations between three-factor eating scores and food plated, consumed, leftovers, and food wasted at lunch. However, at dinner, total energy plated, left over, and food wasted increased by 4.24 kcal/day (p = 0.030), 1.67 kcal/day (p = 0.002), and 0.93 kcal/day (p = 0.031), respectively, with a unit increase in uncontrolled eating score. Similarly, total energy plated and energy left over at dinner increased by 3.40 kcal/day (p = 0.045) and 1.51 kcal/day (p = 0.001), respectively, with a unit increase in emotional eating score. Additional research should examine the specific roles of cognitive restraint, uncontrolled eating, emotional eating and food waste in the development of obesity in adolescents.

Visceral adiposity, more so than overall adiposity, is associated with chronic disease and mortality. There has been, to our knowledge, little research exploring the association between diet quality and visceral adipose tissue (VAT) among a mulitethnic population aged 18–80 y. The primary objective of this cross-sectional analysis was to examine the association between diet quality [Healthy Eating Index–2010 (HEI-2010) scores] and VAT among a multiethnic population of young, middle, and older aged adults in the United States. Secondary objectives were to repeat these analyses with overall adiposity and blood-based biomarkers for type 2 diabetes and cardiovascular disease risk as outcome measures. A total of 540 adults (dropped out: n = 4; age: 18–40 y, n = 220; 40–60 y, n = 183; 60–80 y, n = 133) were recruited across 3 sites (Honolulu County, San Francisco, and Baton Rouge) for the Shape Up! Adults study. Whole-body DXA, anthropometry, fasting blood draw, and questionnaires (food frequency, physical activity, and demographic characteristics) were completed. Linear regression was used to assess the associations between HEI-2010 tertiles and VAT and secondary outcome measures among all participants and age-specific strata, while adjusting for known confounders. VAT, BMI (kg/m²), body fat percentage, total body fat, trunk fat, insulin, and insulin resistance were inversely related to diet quality (all P values < 0.004). When stratified by age, diet quality was inversely associated with VAT among participants aged 60–80 y (P < 0.006) and VAT/subcutaneous adipose tissue (SAT) among participants aged 40–60 y (P < 0.008). Higher-quality diet was associated with lower VAT, overall adiposity, and insulin resistance among this multiethnic population of young, middle, and older aged adults with ages ranging from 18 to 80 y. More specifically, adherence to a high-quality diet may minimize VAT accumulation in adults aged 60–80 y and preferentially promote storage of SAT compared with VAT in adults aged 40–60 y. This study was registered at clinicaltrials.gov as NCT03637855.

Background: We examined the utility of self-rated adherence to dietary and physical activity (PA) prescriptions as a method to monitor intervention compliance and facilitate goal setting during the Healthy Diet and Lifestyle Study (HDLS). In addition, we assessed participants’ feedback of HDLS. HDLS is a randomized pilot intervention that compared the effect of intermittent energy restriction combined with a Mediterranean diet (IER + MED) to a Dietary Approaches to Stop Hypertension (DASH) diet, with matching PA regimens, for reducing visceral adipose tissue area (VAT).Methods: Analyses included the 59 (98%) participants who completed at least 1 week of HDLS. Dietary and PA adherence scores were collected 8 times across 12 weeks, using a 0–10 scale (0 = not at all, 4 = somewhat, and 10 = following the plan very well). Adherence scores for each participant were averaged and assigned to high and low adherence categories using the group median (7.3 for diet, 7.1 for PA). Mean changes in VAT and weight from baseline to 12 weeks are reported by adherence level, overall and by randomization arm. Participants’ feedback at completion and 6 months post-intervention were examined.Results: Mean ± SE, dietary adherence was 6.0 ± 0.2 and 8.2 ± 0.1, for the low and high adherence groups, respectively. For PA adherence, mean scores were 5.9 ± 0.2 and 8.5 ± 0.2, respectively. Compared to participants with low dietary adherence, those with high adherence lost significantly more VAT (22.9 ± 3.7 cm²vs. 11.7 ± 3.9 cm²[95% CI, − 22.1 to − 0.3]) and weight at week 12 (5.4 ± 0.8 kg vs. 3.5 ± 0.6 kg [95% CI, − 3.8 to − 0.0]). For PA, compared to participants with low adherence, those with high adherence lost significantly more VAT (22.3 ± 3.7 cm²vs. 11.6 ± 3.6 cm²[95% CI, − 20.7 to − 0.8]). Participants’ qualitative feedback of HDLS was positive and the most common response, on how to improve the study, was to provide cooking classes.Conclusions: Results support the use of self-rated adherence as an effective method to monitor dietary and PA compliance and facilitate participant goal setting. Study strategies were found to be effective with promoting compliance to intervention prescriptions.Trial registration: ClinicalTrials.gov Identifier:NCT03639350. Registered 21st August 2018—retrospectively registered.

The commercial application Openfit allows for automatic identification and quantification of food intake through short video capture without a physical reference marker. There are no known peer-reviewed publications on the validity of this Nutrition Artificial Intelligence (AI). To test the validity of Openfit to identify food automatically and semiautomatically (with user correction), test the validity of Openfit at quantifying energy intake (kcal) automatically and semiautomatically, and assess satisfaction and usability of Openfit. During a laboratory-based visit, adults (7 male and 17 female), used Openfit to automatically and semiautomatically record provided meals, which were covertly weighed. Foods logged were identified as an “exact match,” “far match,” or an “intrusion” using Food and Nutrient Database for Dietary Studies (FNDDS) codes. Descriptive data were stratified by meal, food item, and FNDDS group, and presented with or without beverages. Bland–Altman analyses assessed errors over levels of energy intake. Participants completed a User Satisfaction Survey (USS) and the Computer Systems Usability Questionnaire (CSUQ). Open-ended questions were assessed with qualitative methods. Exact matches, far matches, and intrusions were 46%, 41%, and 13% for automated identification, and 87%, 23%, and 0% for semiautomated identification, respectively. Error for automated and semiautomated energy estimates were 43% and 33% with beverages, and 16% and 42% without beverages. Bland–Altman analyses indicated larger error for higher energy meals. Overall mean scores were 2.4 for the CSUQ and subscale means scores ranged from 4.1 to 5.5. for the USS. Participants recommended improvements to Openfit’s Nutrition AI, manual estimation, and overall app. Openfit worked relatively well for automatically and semiautomatically identifying foods. Error in automated energy estimates was relatively high; however, after excluding beverages, error was relatively low (16%). For semiautomated energy estimates, error was comparable to previous studies. Improvements to the Nutrition AI, manual estimation and overall application may increase Openfit’s usability and validity. This trial was registered at clinicaltrials.gov as NCT05343585.