An Evaluation of Alternative Technology-Supported Counseling Approaches to Promote Multiple Lifestyle Behavior Changes in Patients With Type 2 Diabetes and Chronic Kidney Disease.

OBJECTIVES: Although technology-supported interventions are effective for reducing chronic disease risk, little is known about the relative and combined efficacy of mobile health strategies aimed at multiple lifestyle factors. The purpose of this clinical trial is to evaluate the efficacy of technology-supported behavioral intervention strategies for managing multiple lifestyle-related health outcomes in overweight adults with type 2 diabetes (T2D) and chronic kidney disease (CKD). DESIGN AND METHODS: Using a 2 × 2 factorial design, adults with excess body weight (body mass index ≥27 kg/m2, age ≥40 years), T2D, and CKD stages 2-4 were randomized to an advice control group, or remotely delivered programs consisting of synchronous group-based education (all groups), plus (1) Social Cognitive Theory-based behavioral counseling and/or (2) mobile self-monitoring of diet and physical activity. All programs targeted weight loss, greater physical activity, and lower intakes of sodium and phosphorus-containing food additives. RESULTS: Of 256 randomized participants, 186 (73%) completed 6-month assessments. Compared to the ADVICE group, mHealth interventions did not result in significant changes in weight loss, or urinary sodium and phosphorus excretion. In aggregate analyses, groups receiving mobile self-monitoring had greater weight loss at 3 months (P = .02), but between 3 and 6 months, weight losses plateaued, and by 6 months, the differences were no longer statistically significant. CONCLUSIONS: When engaging patients with T2D and CKD in multiple behavior changes, self-monitoring diet and physical activity demonstrated significantly larger short-term weight losses. Theory-based behavioral counseling alone was no better than baseline advice and demonstrated no interaction effect with self-monitoring.

Managing protein-energy wasting in hemodialysis patients: A comparison of animal- and plant-based protein foods.

Protein-energy wasting (PEW) is a major diet-related complication in hemodialysis (HD) patients. Nutrient-based dietary guidelines emphasize animal-based protein foods for preventing and managing PEW in HD patients. Although dietary protein intake is important for protein anabolism, other dietary factors contribute to PEW. In this article, we examine the diet-related etiologies of PEW in HD patients, and discuss how they may be affected differently by animal- and plant-based protein foods. In general, animal foods are superior sources of protein, but may contribute more to metabolic derangements that cause PEW. Given the potential mixed effects of animal-based protein foods on PEW, human research studies are needed to determine the impact of liberalizing the diet to allow plant-based protein foods on protein status.

Determinants and the Role of Self-Efficacy in a Sodium-Reduction Trial in Hemodialysis Patients.

OBJECTIVE: This study was to assess the impact of baseline dietary self-efficacy on the effect of a dietary intervention to reduce sodium intake in patients undergoing hemodialysis (HD) and to identify determinants of low dietary self-efficacy. METHODS: This is a post hoc analysis of the BalanceWise study, a randomized controlled trial that aimed to reduce dietary sodium intake in HD patients recruited from 17 dialysis centers in Pennsylvania. The main outcome measures include dietary self-efficacy and reported dietary sodium density. Analysis of variance with post hoc group-wise comparison was used to examine the effect of baseline dietary self-efficacy on changes in reported sodium density in the intervention and control groups at 8 and 16 weeks. Chi-square test, independent t tests, or Wilcoxon rank-sum tests were used to identify determinants of low dietary self-efficacy. RESULTS: The interaction between dietary self-efficacy and the impact of the intervention on changes in reported dietary sodium density approached significance at 8 and 16 weeks (P interaction = 0.051 and 0.06, respectively). Younger age and perceived income inadequacy were significantly associated with low self-efficacy in patients undergoing HD. CONCLUSION: The benefits of dietary interventions designed to improve self-efficacy may differ by the baseline self-efficacy status. This may be particularly important for HD patients who are younger and report inadequate income as they had lower dietary self-efficacy.

Objective Determination of Eating Occasion Timing: Combining Self-Report, Wrist Motion, and Continuous Glucose Monitoring to Detect Eating Occasions in Adults With Prediabetes and Obesity.

BACKGROUND: Accurately identifying eating patterns, specifically the timing, frequency, and distribution of eating occasions (EOs), is important for assessing eating behaviors, especially for preventing and managing obesity and type 2 diabetes (T2D). However, existing methods to study EOs rely on self-report, which may be prone to misreporting and bias and has a high user burden. Therefore, objective methods are needed. METHODS: We aim to compare EO timing using objective and subjective methods. Participants self-reported EO with a smartphone app (self-report [SR]), wore the ActiGraph GT9X on their dominant wrist, and wore a continuous glucose monitor (CGM, Abbott Libre Pro) for 10 days. EOs were detected from wrist motion (WM) using a motion-based classifier and from CGM using a simulation-based system. We described EO timing and explored how timing identified with WM and CGM compares with SR. RESULTS: Participants (n = 39) were 59 ± 11 years old, mostly female (62%) and White (51%) with a body mass index (BMI) of 34.2 ± 4.7 kg/m2. All had prediabetes or moderately controlled T2D. The median time-of-day first EO (and interquartile range) for SR, WM, and CGM were 08:24 (07:00-09:59), 9:42 (07:46-12:26), and 06:55 (04:23-10:03), respectively. The median last EO for SR, WM, and CGM were 20:20 (16:50-21:42), 20:12 (18:30-21:41), and 21:43 (20:35-22:16), respectively. The overlap between SR and CGM was 55% to 80% of EO detected with tolerance periods of ±30, 60, and 120 minutes. The overlap between SR and WM was 52% to 65% EO detected with tolerance periods of ±30, 60, and 120 minutes. CONCLUSION: The continuous glucose monitor and WM detected overlapping but not identical meals and may provide complementary information to self-reported EO.

Diabetes Telemedicine Mediterranean Diet (DiaTeleMed) Study: study protocol for a fully remote randomized clinical trial evaluating personalized dietary management in individuals with type 2 diabetes.

Background: The Diabetes Telemedicine Mediterranean Diet (DiaTeleMed) Study is a fully remote randomized clinical trial evaluating personalized dietary management in individuals with type 2 diabetes (T2D). The study aims to test the efficacy of a personalized behavioral approach for dietary management of moderately-controlled T2D, versus a standardized behavioral intervention that uses one-size-fits-all dietary recommendations, versus a usual care control (UCC). The primary outcome will compare the impact of each intervention on the mean amplitude of glycemic excursions (MAGE). Methods: Eligible participants are between 21 to 80 years of age diagnosed with moderately-controlled T2D (HbA1c: 6.0-8.0%), and managed on lifestyle alone or lifestyle plus metformin. Participants must be willing and able to attend virtual counseling sessions and log meals into a dietary tracking smartphone application (DayTwo), and wear a continuous glucose monitor (CGM) for up to 12 days. Participants are randomized with equal allocation (n = 255, n = 85 per arm) to one of three arms: 1) Personalized, 2) Standardized, or 3) UCC. Measurements occur at 0 (baseline), 3, and 6 months. All participants receive isocaloric energy and macronutrients targets to meet Mediterranean diet guidelines plus 14 intervention contacts over 6 months (4 weekly then 10 biweekly) to cover diabetes self-management education. The first 4 UCC intervention contacts are delivered via synchronous videoconferences followed by educational video links. Participants in Standardized receive the same education content as UCC on the same schedule. However, all intervention contacts are conducted via synchronous videoconferences, paired with Social Cognitive Theory (SCT)-based behavioral counseling, plus dietary self-monitoring of planned meals using a mobile app that provides real-time feedback on calories and macronutrients. Participants in the Personalized arm receive all elements of the Standardized intervention, plus real-time feedback on predicted post-prandial glycemic response (PPGR) to meals and snacks logged into the mobile app. Discussion: The DiaTeleMed study will address an important gap in the current landscape of precision nutrition by determining the contributions of behavioral counseling and personalized nutrition recommendations on glycemic control in individuals with T2D. The fully remote methodology of the study allows for scalability and innovative delivery of personalized dietary recommendations at a population level. Trial registration: The DiaTeleMed Study is registered with ClinicalTrials.gov (Identifier: NCT05046886).

Diet and Meal Pattern Determinants of Glucose Levels and Variability in Adults with and without Prediabetes or Early-Onset Type 2 Diabetes: A Pilot Study.

This observational pilot study examined the association between diet, meal pattern and glucose over a 2-week period under free-living conditions in 26 adults with dysglycemia (D-GLYC) and 14 with normoglycemia (N-GLYC). We hypothesized that a prolonged eating window and late eating occasions (EOs), along with a higher dietary carbohydrate intake, would result in higher glucose levels and glucose variability (GV). General linear models were run with meal timing with time-stamped photographs in real time, and diet composition by dietary recalls, and their variability (SD), as predictors and glucose variables (mean glucose, mean amplitude of glucose excursions [MAGE], largest amplitude of glucose excursions [LAGE] and GV) as dependent variables. After adjusting for calories and nutrients, a later eating midpoint predicted a lower GV (ß = -2.3, SE = 1.0, p = 0.03) in D-GLYC, while a later last EO predicted a higher GV (ß = 1.5, SE = 0.6, p = 0.04) in N-GLYC. A higher carbohydrate intake predicted a higher MAGE (ß = 0.9, SE = 0.4, p = 0.02) and GV (ß = 0.4, SE = 0.2, p = 0.04) in N-GLYC, but not D-GLYC. In summary, our data suggest that meal patterns interact with dietary composition and should be evaluated as potential modifiable determinants of glucose in adults with and without dysglycemia. Future research should evaluate causality with controlled diets.

Continuous glucose monitoring captures glycemic variability in obesity after sleeve gastrectomy: A prospective cohort study.

Objective: HbA1c is an insensitive marker for assessing real-time dysglycemia in obesity. This study investigated whether 1-h plasma glucose level (1-h PG) ≥155 mg/dL (8.6 mmol/L) during an oral glucose tolerance test (OGTT) and continuous glucose monitoring (CGM) measurement of glucose variability (GV) better reflected dysglycemia than HbA1c after weight loss from metabolic and bariatric surgery. Methods: This was a prospective cohort study of 10 participants with type 2 diabetes compared with 11 participants with non-diabetes undergoing sleeve gastrectomy (SG). At each research visit; before SG, and 6 weeks and 6 months post-SG, body weight, fasting lipid levels, and PG and insulin concentrations during an OGTT were analyzed. Mean amplitude of glycemic excursions (MAGE), a CGM-derived GV index, was analyzed. Results: The 1-h PG correlated with insulin resistance markers, triglyceride/HDL ratio and triglyceride glucose index in both groups before surgery. At 6 months, SG caused 22% weight loss in both groups. Despite a reduction in HbA1c by 3.0 ± 1.3% in the diabetes group (p < 0.01), 1-h PG, and MAGE remained elevated, and the oral disposition index, which represents pancreatic ß-cell function, remained reduced in the diabetes group when compared to the non-diabetes group. Conclusions: Elevation of GV markers and reduced disposition index following SG-induced weight loss in the diabetes group underscores persistent ß-cell dysfunction and the potential residual risk of diabetes complications.

A randomized clinical trial comparing low-fat with precision nutrition-based diets for weight loss: impact on glycemic variability and HbA1c.

BACKGROUND: Recent studies have demonstrated considerable interindividual variability in postprandial glucose response (PPGR) to the same foods, suggesting the need for more precise methods for predicting and controlling PPGR. In the Personal Nutrition Project, the investigators tested a precision nutrition algorithm for predicting an individual's PPGR. OBJECTIVE: This study aimed to compare changes in glycemic variability (GV) and HbA1c in 2 calorie-restricted weight loss diets in adults with prediabetes or moderately controlled type 2 diabetes (T2D), which were tertiary outcomes of the Personal Diet Study. METHODS: The Personal Diet Study was a randomized clinical trial to compare a 1-size-fits-all low-fat diet (hereafter, standardized) with a personalized diet (hereafter, personalized). Both groups received behavioral weight loss counseling and were instructed to self-monitor diets using a smartphone application. The personalized arm received personalized feedback through the application to reduce their PPGR. Continuous glucose monitoring (CGM) data were collected at baseline, 3 mo and 6 mo. Changes in mean amplitude of glycemic excursions (MAGEs) and HbA1c at 6 mo were assessed. We performed an intention-to-treat analysis using linear mixed regressions. RESULTS: We included 156 participants [66.5% women, 55.7% White, 24.1% Black, mean age 59.1 y (standard deviation (SD) = 10.7 y)] in these analyses (standardized = 75, personalized = 81). MAGE decreased by 0.83 mg/dL per month for standardized (95% CI: 0.21, 1.46 mg/dL; P = 0.009) and 0.79 mg/dL per month for personalized (95% CI: 0.19, 1.39 mg/dL; P = 0.010) diet, with no between-group differences (P = 0.92). Trends were similar for HbA1c values. CONCLUSIONS: Personalized diet did not result in an increased reduction in GV or HbA1c in patients with prediabetes and moderately controlled T2D, compared with a standardized diet. Additional subgroup analyses may help to identify patients who are more likely to benefit from this personalized intervention. This trial was registered at clinicaltrials.gov as NCT03336411.

AddREssing Social Determinants TO pRevent hypErtension (The RESTORE Network): Overview of the Health Equity Research Network to Prevent Hypertension.

BACKGROUND: The American Heart Association funded a Health Equity Research Network on the prevention of hypertension, the RESTORE Network, as part of its commitment to achieving health equity in all communities. This article provides an overview of the RESTORE Network. METHODS: The RESTORE Network includes five independent, randomized trials testing approaches to implement non-pharmacological interventions that have been proven to lower blood pressure (BP). The trials are community-based, taking place in churches in rural Alabama, mobile health units in Michigan, barbershops in New York, community health centers in Maryland, and food deserts in Massachusetts. Each trial employs a hybrid effectiveness-implementation research design to test scalable and sustainable strategies that mitigate social determinants of health (SDOH) that contribute to hypertension in Black communities. The primary outcome in each trial is change in systolic BP. The RESTORE Network Coordinating Center has five cores: BP measurement, statistics, intervention, community engagement, and training that support the trials. Standardized protocols, data elements and analysis plans were adopted in each trial to facilitate cross-trial comparisons of the implementation strategies, and application of a standard costing instrument for health economic evaluations, scale up, and policy analysis. Herein, we discuss future RESTORE Network research plans and policy outreach activities designed to advance health equity by preventing hypertension. CONCLUSIONS: The RESTORE Network was designed to promote health equity in the US by testing effective and sustainable implementation strategies focused on addressing SDOH to prevent hypertension among Black adults.

Time-restricted eating to improve cardiometabolic health: The New York Time-Restricted EATing randomized clinical trial - Protocol overview.

Re-aligning eating patterns with biological rhythm can reduce the burden of metabolic syndrome in older adults with overweight or obesity. Time-restricted eating (TRE) has been shown to result in weight loss and improved cardiometabolic health while being less challenging than counting calories. The New York Time-Restricted EATing study (NY-TREAT) is a two-arm, randomized clinical trial (RCT) that aims to examine the efficacy and sustainability of TRE (eating window ≤10 h/day) vs. a habitual prolonged eating window (HABIT, ≥14 h/day) in metabolically unhealthy midlife adults (50-75 years) with overweight or obesity and prediabetes or type 2 diabetes (T2D). Our primary hypothesis is that the TRE will result in greater weight loss compared to HABIT at 3 months. The efficacy of the TRE intervention on body weight, fat mass, energy expenditure, and glucose is tested at 3 months, and the sustainability of its effect is measured at 12 months, with ambulatory assessments of sleep and physical activity (ActiGraph), eating pattern (smartphone application), and interstitial glucose (continuous glucose monitoring). The RCT also includes state-of-the-art measurements of body fat (quantitative magnetic resonance), total energy expenditure (doubly-labelled water), insulin secretion, insulin resistance, and glucose tolerance. Adherence to self-monitoring and reduced eating window are monitored remotely in real-time. This RCT will provide further insight into the effects of TRE on cardiometabolic health in individuals with high metabolic risk. Sixty-two participants will be enrolled, and with estimated 30% attrition, 42 participants will return at 12 months. This protocol describes the design, interventions, methods, and expected outcomes. Clinical trial registration:NCT04465721 IRB: AAAS7791.

Soluble Receptor for Advanced Glycation End Products (sRAGE) Isoforms Predict Changes in Resting Energy Expenditure in Adults with Obesity during Weight Loss.

Background: Accruing evidence indicates that accumulation of advanced glycation end products (AGEs) and activation of the receptor for AGEs (RAGE) play a significant role in obesity and type 2 diabetes. The concentrations of circulating RAGE isoforms, such as soluble RAGE (sRAGE), cleaved RAGE (cRAGE), and endogenous secretory RAGE (esRAGE), collectively sRAGE isoforms, may be implicit in weight loss and energy compensation resulting from caloric restriction. Objectives: We aimed to evaluate whether baseline concentrations of sRAGE isoforms predicted changes (∆) in body composition [fat mass (FM), fat-free mass (FFM)], resting energy expenditure (REE), and adaptive thermogenesis (AT) during weight loss. Methods: Data were collected during a behavioral weight loss intervention in adults with obesity. At baseline and 3 mo, participants were assessed for body composition (bioelectrical impedance analysis) and REE (indirect calorimetry), and plasma was assayed for concentrations of sRAGE isoforms (sRAGE, esRAGE, cRAGE). AT was calculated using various mathematical models that included measured and predicted REE. A linear regression model that adjusted for age, sex, glycated hemoglobin (HbA1c), and randomization arm was used to test the associations between sRAGE isoforms and metabolic outcomes. Results: Participants (n = 41; 70% female; mean ± SD age: 57 ± 11 y; BMI: 38.7 ± 3.4 kg/m2) experienced modest and variable weight loss over 3 mo. Although baseline sRAGE isoforms did not predict changes in ∆FM or ∆FFM, all baseline sRAGE isoforms were positively associated with ∆REE at 3 mo. Baseline esRAGE was positively associated with AT in some, but not all, AT models. The association between sRAGE isoforms and energy expenditure was independent of HbA1c, suggesting that the relation was unrelated to glycemia. Conclusions: This study demonstrates a novel link between RAGE and energy expenditure in human participants undergoing weight loss.This trial was registered at clinicaltrials.gov as NCT03336411.

The RAGE/DIAPH1 axis: mediator of obesity and proposed biomarker of human cardiometabolic disease.

Overweight and obesity are leading causes of cardiometabolic dysfunction. Despite extensive investigation, the mechanisms mediating the increase in these conditions are yet to be fully understood. Beyond endogenous formation of advanced glycation end products (AGEs) in overweight and obesity, exogenous sources of AGEs accrue through the heating, production and consumption of highly-processed foods. Evidence from cellular and mouse model systems indicates that the interaction of AGEs with their central cell surface receptor for AGE (RAGE) in adipocytes suppresses energy expenditure and that AGE/RAGE contributes to increased adipose inflammation and processes linked to insulin resistance. In human subjects, the circulating soluble forms of RAGE, which are mutable, may serve as biomarkers of obesity and weight loss. Antagonists of RAGE signaling, through blockade of the interaction of the RAGE cytoplasmic domain with the formin, Diaphanous-1 (DIAPH1), target aberrant RAGE activities in metabolic tissues. This review focuses on the potential roles for AGEs and other RAGE ligands and RAGE/DIAPH1 in the pathogenesis of overweight and obesity and their metabolic consequences.

Effect of a Personalized Diet to Reduce Postprandial Glycemic Response vs a Low-fat Diet on Weight Loss in Adults With Abnormal Glucose Metabolism and Obesity: A Randomized Clinical Trial.

Importance: Interindividual variability in postprandial glycemic response (PPGR) to the same foods may explain why low glycemic index or load and low-carbohydrate diet interventions have mixed weight loss outcomes. A precision nutrition approach that estimates personalized PPGR to specific foods may be more efficacious for weight loss. Objective: To compare a standardized low-fat vs a personalized diet regarding percentage of weight loss in adults with abnormal glucose metabolism and obesity. Design, Setting, and Participants: The Personal Diet Study was a single-center, population-based, 6-month randomized clinical trial with measurements at baseline (0 months) and 3 and 6 months conducted from February 12, 2018, to October 28, 2021. A total of 269 adults aged 18 to 80 years with a body mass index (calculated as weight in kilograms divided by height in meters squared) ranging from 27 to 50 and a hemoglobin A1c level ranging from 5.7% to 8.0% were recruited. Individuals were excluded if receiving medications other than metformin or with evidence of kidney disease, assessed as an estimated glomerular filtration rate of less than 60 mL/min/1.73 m2 using the Chronic Kidney Disease Epidemiology Collaboration equation, to avoid recruiting patients with advanced type 2 diabetes. Interventions: Participants were randomized to either a low-fat diet (<25% of energy intake; standardized group) or a personalized diet that estimates PPGR to foods using a machine learning algorithm (personalized group). Participants in both groups received a total of 14 behavioral counseling sessions and self-monitored dietary intake. In addition, the participants in the personalized group received color-coded meal scores on estimated PPGR delivered via a mobile app. Main Outcomes and Measures: The primary outcome was the percentage of weight loss from baseline to 6 months. Secondary outcomes included changes in body composition (fat mass, fat-free mass, and percentage of body weight), resting energy expenditure, and adaptive thermogenesis. Data were collected at baseline and 3 and 6 months. Analysis was based on intention to treat using linear mixed modeling. Results: Of a total of 204 adults randomized, 199 (102 in the personalized group vs 97 in the standardized group) contributed data (mean [SD] age, 58 [11] years; 133 women [66.8%]; mean [SD] body mass index, 33.9 [4.8]). Weight change at 6 months was -4.31% (95% CI, -5.37% to -3.24%) for the standardized group and -3.26% (95% CI, -4.25% to -2.26%) for the personalized group, which was not significantly different (difference between groups, 1.05% [95% CI, -0.40% to 2.50%]; P = .16). There were no between-group differences in body composition and adaptive thermogenesis; however, the change in resting energy expenditure was significantly greater in the standardized group from 0 to 6 months (difference between groups, 92.3 [95% CI, 0.9-183.8] kcal/d; P = .05). Conclusions and Relevance: A personalized diet targeting a reduction in PPGR did not result in greater weight loss compared with a low-fat diet at 6 months. Future studies should assess methods of increasing dietary self-monitoring adherence and intervention exposure. Trial Registration: ClinicalTrials.gov Identifier: NCT03336411.

A Smartphone Intervention to Promote Time Restricted Eating Reduces Body Weight and Blood Pressure in Adults with Overweight and Obesity: A Pilot Study.

The goal of this study was to test the feasibility of time restricted eating (TRE) in adults with overweight and obesity. Participants (n = 50) logged all eating occasions (>0 kcal) for a 2-week run-in period using a smartphone application. Participants with eating duration ≥14 h enrolled in an open label, non-randomized, prospective 90-day TRE intervention, with a self-selected reduced eating window of 10 h. No dietary counseling was provided. Changes in anthropometrics, eating patterns and adherence after TRE were analyzed using t-tests or Wilcoxon Rank-Sum Test. The mean duration of the baseline eating window was 14 h 32 m ± 2 h 36 m (n = 50) with 56% of participants with duration ≥14 h. TRE participants (n = 16) successfully decreased their eating window from 16 h 04 m ± 1 h 24 m to 11 h 54 m ± 2 h 06 m (p < 0.001), and reduced the number of daily eating occasions by half (p < 0.001). Adherence to logging and to the reduced eating window was 64% ± 22% and 47% ± 19%, respectively. TRE resulted in decreases in body weight (-2.1 ± 3.0 kg, p = 0.017), waist circumference (-2.2 ± 4.6 cm, p = 0.002) and systolic blood pressure (-12 ± 11 mmHg, p = 0.002). This study demonstrates the feasibility and efficacy of TRE administered via a smartphone, in adults with overweight and obesity.

The Moderating Effect of Physical Activity on the Relationship between Sleep and Emotional Distress and the Difference between Blacks and Whites: A Secondary Data Analysis Using the National Health Interview Survey from 2005-2015.

(1) Background: Unhealthy sleep durations (short and long sleep) are associated with emotional distress (ED). Minority populations, specifically Blacks, are more burdened with unhealthy sleep durations and ED. The ameliorative effect of physical activity (PA) on ED and sleep duration may provide insight into how to reduce the burden among Blacks and other minorities. However, it is unclear whether PA attenuates the relationship between sleep and ED, and whether this relationship differs by race. (2) Methods: We analyzed data from the nationally representative 2005-2015 National Health Interview Survey (NHIS) dataset. ED, physical activity, and sleep duration were collected through self-reports. Regression analyses investigated the moderating effect of PA on the relationship between sleep and ED (adjusting for age, sex, BMI, and employment status) and stratified by race. (3) Results: We found that sleep duration was independently associated with ED. Physical activity moderated the relationship between sleep and ED, the full population, and Whites, but not Blacks. (4) Conclusion: PA moderated the relationship between short, average, or long sleep and ED, but in stratified analyses, this was only evident for Whites, suggesting Blacks received differing protective effects from physical activity. Further research should be performed to understand the connection of physical activity to sleep and mental health.

Challenges of conducting a remote behavioral weight loss study: Lessons learned and a practical guide.

OBJECTIVES: To describe challenges and lessons learned in conducting a remote behavioral weight loss trial. METHODS: The Personal Diet Study is an ongoing randomized clinical trial which aims to compare two mobile health (mHealth) weight loss approaches, standardized diet vs. personalized feedback, on glycemic response. Over a six-month period, participants attended dietitian-led group meetings via remote videoconferencing and were encouraged to self-monitor dietary intake using a smartphone app. Descriptive statistics were used to report adherence to counseling sessions and self-monitoring. Challenges were tracked during weekly project meetings. RESULTS: Challenges in connecting to and engaging in the videoconferencing sessions were noted. To address these issues, we provided a step-by-step user manual and video tutorials regarding use of WebEx, encouraged alternative means to join sessions, and sent reminder emails/texts about the WebEx sessions and asking participants to join sessions early. Self-monitoring app-related issue included inability to find specific foods in the app database. To overcome this, the study team incorporated commonly consumed foods as "favorites" in the app database, provided a manual and video tutorials regarding use of the app and checked the self-monitoring app dashboard weekly to identify nonadherent participants and intervened as appropriate. Among 135 participants included in the analysis, the median attendance rate for the 14 remote sessions was 85.7% (IQR: 64.3%-92.9%). CONCLUSIONS: Experience and lessons shared in this report may provide critical and timely guidance to other behavioral researchers and interventionists seeking to adapt behavioral counseling programs for remote delivery in the age of COVID-19.

Temporal Eating Patterns and Eating Windows among Adults with Overweight or Obesity.

We aim to describe temporal eating patterns in a population of adults with overweight or obesity. In this cross-sectional analysis, data were combined from two separate pilot studies during which participants entered the timing of all eating occasions (>0 kcals) for 10-14 days. Data were aggregated to determine total eating occasions, local time of the first and last eating occasions, eating window, eating midpoint, and within-person variability of eating patterns. Eating patterns were compared between sexes, as well as between weekday and weekends. Participants (n = 85) had a median age of 56 ± 19 years, were mostly female (>70%), white (56.5%), and had a BMI of 31.8 ± 8.0 kg/m2. The median eating window was 14 h 04 min [12 h 57 min-15 h 21 min], which was significantly shorter on the weekend compared to weekdays (p < 0.0001). Only 13.1% of participants had an eating window <12 h/d. Additionally, there was greater irregularity with the first eating occasion during the week when compared to the weekend (p = 0.0002). In conclusion, adults with overweight or obesity have prolonged eating windows (>14 h/d). Future trials should examine the contribution of a prolonged eating window on adiposity independent of energy intake.

Age and Racial/Ethnic Differences in Dietary Sources of Protein, NHANES, 2011-2016.

Background: Dietary protein serves a pivotal role in providing the body with essential amino acids, which are required for the maintenance of body proteins, and the assimilation of structural and functional components required for basic survival. Understanding how dietary protein sources potentially vary for different population subgroups will allow for future nutrition interventions to be more targeted for specific needs. Objective: The purpose of this analysis was to identify the top ten food category sources of dietary protein by age and race and ethnicity in a nationally representative sample. Methods: Cross-sectional data on adults (18+ years) from the National Health and Nutrition Examination Survey (NHANES) 2011-2016 with one 24-h dietary recall were analyzed (n = 15,697). Population proportions were calculated based on protein intake (g/day) for What We Eat In America food categories. Results: The analytic sample (n = 15,697) was 15.0% Hispanic (95% CI [12.1, 17.9], 65.0% non-Hispanic White (95% CI [60.8, 69.3]), 11.5% non-Hispanic Black (95% CI [9.1, 13.9]), 5.4% non-Hispanic Asian (95% CI [4.3, 6.6]), and 3.1% other (95% CI [2.5, 3.6]). In all racial and ethnic groups, as well as age categories, chicken (whole pieces) was the top-ranked source of dietary protein. In addition to chicken (whole pieces), beef (excludes ground), eggs and omelets, and meat mixed dishes food categories ranked in the top ten sources of protein for every race/ethnicity. Only two solely plant-based proteins appeared in the top ten sources: beans, peas and legumes for Hispanics, and nuts and seeds for Other. For all age categories, beef (excludes ground) was among the top five sources and egg/omelets appear in the top ten sources. Conclusion: The top ten sources of protein accounted for over 40% of dietary protein irrespective of race/ethnicity or age category, having major implications for the sustainability of our nation's food supply. Public health strategies that encourage diversity in protein sources in food preparation and incorporate legumes and nuts along with poultry have the potential to shift the overall population protein intake distribution toward improving overall diet quality.

A cross-sectional analysis of dietary protein intake and body composition among Chinese Americans.

Favourable body composition has been associated with higher dietary protein intake. However, little is known regarding this relationship in a population of Chinese Americans (CHA), who have lower BMI compared with other populations. The aim of the present study was to assess the relationship between dietary protein intake, fat mass (FM) and fat-free mass (FFM) in CHA. Data were from the Chinese American Cardiovascular Health Assessment (CHA CHA) 2010-2011 (n 1707); dietary intake was assessed using an adapted and validated FFQ. Body composition was assessed using bioelectrical impedance analysis. The associations between protein intake (% energy intake) and BMI, percentage FM (FM%), percentage FFM (FFM%), FM index (FMI) and FFM index (FFMI) were examined using multiple linear regression adjusted for age, sex, physical activity, acculturation, total energy intake, sedentary time, smoking status, education, employment and income. There was a significant positive association between dietary protein and BMI (B = 0·056, 95 % CI 0·017, 0·104; P = 0·005), FM (B = 0·106, 95 % CI 0·029, 0·184; P = 0·007), FM% (B = 0·112, 95 % CI 0·031, 0·194; P = 0·007) and FMI (B = 0·045, 95 % CI 0·016, 0·073; P = 0·002). There was a significant negative association between dietary protein and FFM% (B = -0·116, 95 % CI -0·196, -0·036; P = 0·004). In conclusion, higher dietary protein intake was associated with higher adiposity; however, absolute FFM and FFMI were not associated with dietary protein intake. Future work examining the relationship between protein source (i.e. animal) and body composition is warranted in this population of CHA.

The rationale and design of the personal diet study, a randomized clinical trial evaluating a personalized approach to weight loss in individuals with pre-diabetes and early-stage type 2 diabetes.

Weight loss reduces the risk of type 2 diabetes mellitus (T2D) in overweight and obese individuals. Although the physiological response to food varies among individuals, standard dietary interventions use a "one-size-fits-all" approach. The Personal Diet Study aims to evaluate two dietary interventions targeting weight loss in people with prediabetes and T2D: (1) a low-fat diet, and (2) a personalized diet using a machine-learning algorithm that predicts glycemic response to meals. Changes in body weight, body composition, and resting energy expenditure will be compared over a 6-month intervention period and a subsequent 6-month observation period intended to assess maintenance effects. The behavioral intervention is delivered via mobile health technology using the Social Cognitive Theory. Here, we describe the design, interventions, and methods used.