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IntroductionEarly childcare centers offer optimal settings to provide healthy built environments where preschool age children spend a majority of their week. Many evidence-based interventions (EBIs) promoting healthful eating and physical activity for early childcare settings exist, but there is a limited understanding of how best to support adoption, implementation and sustainability in community settings. This study examined how early childcare teachers and administrators from Chicago-area childcare centers serving children from low-income, racially/ethnically diverse communities viewed an EBI called Hip to Health (H3), and the factors they perceived as relevant for EBI adoption, implementation, and sustainability.MethodsA multiple methods study including key informant interviews and a brief survey was conducted. Key informant interviews with teachers and administrators from childcare centers located in Chicago, IL were completed between December 2020 and May 2021. An interview guide and coding guide based on the Consolidated Framework for Implementation Research (CFIR) was developed. Interview transcripts were team coded in MAXQDA Qualitative Data Analysis software. Thematic analysis was used to identify findings specific to adoption, implementation, and sustainability. Participants were also asked to respond to survey measures about the acceptability, feasibility, and appropriateness of H3.ResultsOverall, teachers (n = 20) and administrators (n = 16) agreed that H3 was acceptable, appropriate, and feasible. Low start-up costs, ease-of-use, adaptability, trialability, compatibility, and leadership engagement were important to EBI adoption. Timely and flexible training was critical to implementation. Participants noted sustainability was tied to low ongoing costs, access to ongoing support, and positive observable benefits for children and positive feedback from parents.ConclusionsThese findings suggest that EBIs suitable for adoption, implementation, and sustainment in childcare centers serving racially/ethnically diverse, low-income families should be adaptable, easy to use, and low-cost (initial and ongoing). There is also some evidence from these findings of the heterogeneity that exists among childcare centers serving low-income families in that smaller, less resourced centers are often less aware of EBIs, and the preparation needed to implement EBIs. Future research should examine how to better support EBI dissemination and implementation to these settings.

A stronger understanding of the factors influencing implementation of interventions in community-based early childcare settings is needed. The purpose of this systematic review was to synthesize existing research on facilitators and barriers to implementation and sustainability of nutrition and physical activity interventions in early childcare settings targeting 2-5-year-old children, including considerations for equitable implementation. This review adhered to PRISMA 2020 guidelines. Peer-reviewed literature was searched in PubMed, EMBASE, CINAHL, ERIC, and PsycINFO databases up to September 2020. Primary research studies that examined facilitators and barriers (or related synonyms) to the implementation and sustainability of nutrition and physical activity interventions in early childcare settings were eligible for inclusion. The search yielded 8092 records that were screened by four analysts in Covidence software with a final review of 24 studies. Two independent reviewers conducted study selection, data extraction, and quality appraisal (Mixed Methods Appraisal Tool). A "best fit" framework was applied using the Consolidated Framework for Implementation Research (CFIR) constructs to code barriers and facilitators. The most salient constructs were (1) "Available Resources," which was composed of time, staffing, space, and staff trainings; (2) adaptability; and (3) compatibility, the latter two indicating that easily modifiable interventions facilitated a smoother "fit" and were more likely to be successful, given adequate site-level resources. Only nine (28%) reported the use of a theory, model, or framework to guide evaluation; six studies (24%) included factors related to sustainability; and nine studies (38%) conducted their interventions with low-income or minoritized groups. The findings point to the need for intervention evaluations examining nutrition and physical activity to more consistently consider (a) sustainability factors early on in design and adoption phases; (b) use of theory, model, or framework to guide evaluation; and (c) equity-related frameworks and considerations for how equitable implementation.

Concerns have been raised regarding the impact of time-restricted eating (TRE) on sex hormones in females. This study examined how TRE affects sex steroids in premenopausal and postmenopausal females.This is a secondary analysis of an 8-week TRE study (4- to 6-hour eating window) conducted in adults with obesity. Men and perimenopausal females were excluded. Females were classified into two groups based on menstrual status: premenopausal (n = 12) or postmenopausal (n = 11).After 8 weeks, body weight decreased in premenopausal females (-3% ± 2%) and postmenopausal females (-4% ± 2%) (main effect of time, p 0.001), with no difference between groups (no group × time interaction). Circulating levels of testosterone, androstenedione, and sex hormone binding globulin (SHBG) did not change in either group (no group × time interaction). Dehydroepiandrosterone (DHEA) concentrations decreased (p 0.05) in premenopausal (-14% ± 32%) and postmenopausal females (-13% ± 34%; main effect of time, p = 0.03), with no difference between groups. Estradiol, estrone, and progesterone were measured only in postmenopausal females, and they remained unchanged.In premenopausal females, androgens and SHBG remained unchanged during TRE, whereas DHEA decreased. In postmenopausal females, estrogens, progesterone, androgens, and SHBG did not change, but DHEA was reduced.

Background: Time restricted eating (TRE) is a form of intermittent fasting that involves confining the period of eating to 8-h and fasting with zero-calorie beverages for 16-h. Short-term studies (2-3 month) suggest that 8-h TRE produces moderate weight loss and improves blood pressure and plasma lipids. What remains unknown is whether these improvements by TRE would become more pronounced over longer periods of time (6-months) , and whether these benefits are comparable to that of daily calorie restriction (CR) . Objective: Accordingly, this study compared the effects of 8-h TRE versus CR and a no-intervention control group on body weight and cardiovascular disease risk factors in adults with obesity over 6-months. Design: Adults with obesity (n = 63) were randomized to 1 of 3 interventions for 6-months: 8-h TRE (ad libitum eating between 12:00 to 8:00 pm, fasting between 8:00 to 12:00 pm) ; CR (25% energy restriction daily) ; or control (ad libitum food intake with no meal timing restrictions) . Results: By month 6, body weight decreased (P = 0.02) by CR (-4.9 ± 1.4%) but not TRE (-3.4 ± 0.7%) , versus controls (-0.7 ± 1.1%) . Diastolic blood pressure was significantly (P = 0.04) reduced by TRE (-4.0 ± 1.4 mm Hg) , but not CR (-0.1 ± 1.7 mm Hg) , versus controls (1.6 ± 1.5 mm Hg) . Changes in systolic blood pressure, fat mass, visceral fat mass, lean mass, LDL cholesterol, HDL cholesterol, triglycerides, and heart rate did not differ between groups at month 6. Adherence to 8-h TRE remained high throughout the trial, i.e. subjects adhered to the 8-h eating window on 6 ± 0.1 days/week. Conclusions: These preliminary findings suggest CR may produce greater weight loss compared to TRE over 6-months. While TRE did not produce significant weight loss, the diet did lower diastolic blood pressure. This would suggest that this intermittent fasting regimen may produce improvements in cardiovascular parameters in the absence of body weight reductions. Disclosure S. Lin: None. S. Cienfuegos: None. K. Gabel: None. K. Varady: None. A. Mulas: None. Funding NIH-NIDDK (1R01DK128180 - 01A1)

Background: Approximately 65% of individuals with obesity have nonalcoholic fatty liver disease (NAFLD) . The primary treatment for NAFLD is regulating weight per diet and exercise. Alternate day fasting (ADF) has been shown to improve body composition and cardiometabolic risk factors in animals. This is the first human trial to compare the effects of ADF plus endurance exercise, ADF alone, endurance exercise alone versus a no intervention control, on body weight and metabolic disease risk factors in participants with obesity and NAFLD. Methods: Subjects with obesity and NAFLD (n = 48) were randomized to 1 of 4 groups for 12 weeks:1) ADF (600 kcal “fast day”, alternated with an ad libitum intake “feast day”) ,2) exercise (endurance exercise 5 times/week for 60 min/d) ,3) combination (ADF + exercise) ,or 4) control (usual diet) . Results: Body weight was reduced (P < 0.05) in the ADF group (-5.3 ± 1.0 %) and combination group (-4.9 ± 0.6 %) , but not the exercise group (-1.9 ± 0.6 %) , versus controls (-0.3 ± 1.2 %) . ALT was reduced (P < 0.05) in the combination group (-29 ± 9%) , but not in the ADF group (-9 ± 8%) , exercise group (1 ± 3%) , versus controls (17 ± 10%) . No significant changes were observed for liver fat, body composition, AST, lipid markers, or glucoregulatory factors. Subjects in the ADF and combination groups were adherent with the fast day energy goal (600 kcal) at week 12 (ADF: 548 kcal; combination: 657 kcal) . Subjects in the exercise and combination groups were adherent with attending the 5 workout sessions per week (exercise: 79% attendance; combination: 83% attendance) . Conclusion: These preliminary findings suggest that combination of ADF plus exercise and ADF alone may be effective non-pharmacological therapies to reduce body weight and ALT. However, neither combination intervention nor ADF alone have had any effect on liver fat, metabolic risk factors, or glucoregulatory factors such as insulin. Disclosure K. Gabel: None. K. Varady: None. S. Cienfuegos: None. Funding NIH/NIDDK (R01DK119783-03)

Background: Intermittent fasting has gained substantial popularity in the past decade. The most popular form of intermittent fasting is time restricted eating (TRE) , which involves eating within a 4-to-10-hour window and water fasting for the rest of the day. Short-term studies (2 months) indicate that TRE produces mild reductions in body weight and markers of glucose regulation. What remains unknown is whether longer durations of TRE (6-months) can lead to even greater improvements in these diabetes risk factors. In addition, whether TRE is more effective than daily calorie restriction (CR) for improving these endpoints, also remains unknown. Objective: The purpose of this study was to compare the effects of 8-h TRE versus daily CR on body weight, body composition, and markers of glucoregulation, in adults with obesity. Design: Participants were randomized to 1 of 3 groups for 6-months: 8-h TRE (n = 24, 12-8pm eating window, 8pm-12pm fasting window) , CR (n = 22, 25% energy restriction daily) , or a control (n = 19, no food or meal timing restrictions) . Results: Weight loss was not significantly different between the TRE (-3.4 ± 0.7%) and CR group (-4.9 ± 1.4%) by month 6. Only the CR group experienced significant weight loss (P = 0.02) versus controls (-0.7 ± 1.1%) . Changes in fat mass, lean mass, and visceral fat mass were not significantly different between groups post-treatment. Likewise, no significant changes in fasting glucose, fasting insulin, or HbA1c were observed. Changes in insulin resistance (assessed via HOMA-IR) did not differ between TRE (-0.50± 0.35 %) , CR (-0.56 ± 0.39 %) , or controls (0.37 ± 0.43%) . Conclusions: These findings suggest that TRE does not produce greater weight loss than traditional dieting (CR) over 6-months. Our findings also show that neither diet had any beneficial effect on body composition of markers of glucoregulation, versus controls, in adults with obesity. Disclosure S.Cienfuegos: None. S.Lin: None. K.Gabel: None. M.Mcstay: None. A.Mulas: None. K.Varady: None. Funding R01DK128180 , NIH (NIDDK)

Background: Time restricted feeding (TRF) involves deliberately restricting the times during which energy is ingested. Preliminary findings suggest that 8–10-h TRF improves sleep. However, the effects of shorter TRF windows (4–6 h) on sleep, remain unknown. Aims: This study compared the effects of 4-h versus 6-h TRF on sleep quality, duration, insomnia severity and the risk of obstructive sleep apnea. Methods: Adults with obesity ( n = 49) were randomized into one of three groups: 4-h TRF (eating only between 3 and 7 p.m.), 6-h TRF (eating only between 1 and 7 p.m.), or a control group (no meal timing restrictions) for 8 weeks. Results: After 8 weeks, body weight decreased ( p < 0.001) similarly by 4-h TRF (–3.9 ± 0.4 kg) and 6-h TRF (–3.4 ± 0.4 kg), versus controls. Sleep quality, measured by the Pittsburgh Sleep Quality Index (PSQI), did not change by 4-h TRF (baseline: 5.9 ± 0.7; week 8: 4.8 ± 0.6) or 6-h TRF (baseline: 6.4 ± 0.8; week 8: 5.3 ± 0.9), versus controls. Wake time, bedtime, sleep duration and sleep onset latency also remained unchanged. Insomnia severity did not change by 4-h TRF (baseline: 4.4 ± 1.0; week 8: 4.7 ± 0.9) or 6-h TRF (baseline: 8.3 ± 1.2; week 8: 5.5 ± 1.1), versus controls. Percent of participants reporting obstructive sleep apnea symptoms did not change by 4-h TRF (baseline: 44%; week 8: 25%) or 6-h TRF (baseline: 47%; week 8: 20%), versus controls. Conclusion: These findings suggest that 4- and 6-h TRF have no effect on sleep quality, duration, insomnia severity, or the risk of obstructive sleep apnea.

BACKGROUND AND AIMS: This study examined if the weight loss and metabolic benefits of alternate day fasting (ADF) varies according to sex and menopausal status in adults with obesity. METHODS AND RESULTS: This secondary analysis pooled the data of men and women (n = 75) who participated in three 12-week ADF studies (500 kcal fast day; alternated with an ad libitum intake feast day). Body weight decreased in premenopausal women (−4.6 ± 3.2%), postmenopausal women (−6.5 ± 3.2%) and men (−6.2 ± 4.4%) (main effect of time, P < 0.001), with no difference between groups (no group × time interaction). Energy intake on fast days was higher than prescribed in all groups (~400-500 excess kcal consumed), with no differences between groups. Fat mass, lean mass, fasting insulin, and insulin resistance, and blood pressure decreased similarly in all groups (main effect of time, P < 0.05 for all comparisons). LDL cholesterol decreased more in postmenopausal versus premenopausal women (group × time interaction, P = 0.01). Fasting glucose, HDL cholesterol, and triglycerides remained unchanged in all groups. CONCLUSION: These findings suggest that the weight loss and metabolic benefits of ADF do not generally vary according to sex or menopausal status in adults with obesity.

Innovative non-pharmacological lifestyle strategies to treat non-alcoholic fatty liver disease (NAFLD) are critically needed. This study compared the effects of alternate day fasting (ADF) combined with exercise to fasting alone, or exercise alone, on intrahepatic triglyceride (IHTG) content. Adults with obesity and NAFLD (n = 80, 81% female, age: 23-65 years) were randomized to 1 of 4 groups for 3 months: combination of ADF (600 kcal/2,500 kJ "fast day" alternated with an ad libitum intake "feast day") and moderate-intensity aerobic exercise (5 session per week, 60 min/session); ADF alone; exercise alone; or a no-intervention control group. By month 3, IHTG content was significantly reduced in the combination group (-5.48%; 95% CI, -7.77% to -3.18%), compared with the exercise group (-1.30%; 95% CI, -3.80% to 1.20%; p = 0.02) and the control group (-0.17%; 95% CI, -2.17% to 1.83%; p 0.01) but was not significantly different versus the ADF group (-2.25%; 95% CI, -4.46% to -0.04%; p = 0.05). Body weight, fat mass, waist circumference, and alanine transaminase (ALT) levels significantly decreased, while insulin sensitivity significantly increased in the combination group compared with the control group. Lean mass, aspartate transaminase (AST), HbA1c, blood pressure, plasma lipids, liver fibrosis score, and hepatokines (fetuin-A, FGF-21, and selenoprotein P) did not differ between groups. Combining intermittent fasting with exercise is effective for reducing hepatic steatosis in patients with NAFLD but may offer no additional benefit versus fasting alone.

This review examines the effects of two popular intermittent fasting regimens on sleep in adults with overweight and obesity. Specifically, the effects of time restricted eating (TRE; eating all food within a 4–10 h window) and alternate day fasting (ADF; 600 kcal fast day alternated with ad libitum feast day) on sleep quality, sleep duration, sleep latency, sleep efficiency, insomnia severity, and risk of obstructive sleep apnea, will be summarized. The role of weight loss will also be discussed. Results from our review reveal that the majority of these trials produced weight loss in the range of 1–6% from baseline. Sleep quality and sleep duration remained unaltered with TRE and ADF, as assessed by the Pittsburgh Sleep Quality Index (PSQI). The effects of intermittent fasting on sleep latency and sleep efficiency are mixed, with one study showing worsening of these parameters, and others showing no effect. Insomnia severity and the risk of obstructive sleep apnea remained unchanged in the trials assessing these metrics. Taken together, these preliminary findings suggest that TRE and ADF produce mild to moderate weight loss (1–6%) but their effects on sleep remain unclear. Solid conclusions are difficult to establish since participants in the studies had healthy sleep durations and no clinical insomnia at baseline, leaving little room for improvement in these metrics. Moreover, none of the trials were adequately powered to detect statistically significant changes in any measure of sleep. Future well-powered trials, conducted in individuals with diagnosed sleep disturbances, will be necessary to elucidate the effect of these popular diets on sleep.

By knocking out all four EGFR ligands expressed in MDCK cells, this study shows the redundant and specific roles of each EGFR ligand in the ERK activation waves during collective cell migration., Epidermal growth factor receptor (EGFR) plays a pivotal role in collective cell migration by mediating cell-to-cell propagation of extracellular signal-regulated kinase (ERK) activation. Here, we aimed to determine which EGFR ligands mediate the ERK activation waves. We found that epidermal growth factor (EGF)–deficient cells exhibited lower basal ERK activity than the cells deficient in heparin-binding EGF (HBEGF), transforming growth factor alpha (TGFα) or epiregulin (EREG), but all cell lines deficient in a single EGFR ligand retained the ERK activation waves. Surprisingly, ERK activation waves were markedly suppressed, albeit incompletely, only when all four EGFR ligands were knocked out. Re-expression of the EGFR ligands revealed that all but HBEGF could restore the ERK activation waves. Aiming at complete elimination of the ERK activation waves, we further attempted to knockout NRG1, a ligand for ErbB3 and ErbB4, and found that NRG1-deficiency induced growth arrest in the absence of all four EGFR ligand genes. Collectively, these results showed that EGFR ligands exhibit remarkable redundancy in the propagation of ERK activation waves during collective cell migration.

Cardiovascular disease is a major global health burden. Machine learning may be used on big data from national surveys to develop models that predict various cardiovascular risk factors. We used machine learning to evaluate and compare generalized linear, stochastic gradient boosting, random forest, and neural network model performance on predicting cardiovascular risk factors, such as hypertension, body mass index, and total cholesterol level on 5,992 adults in the US National Health and Nutrition Examination Survey (NHANES). The highest accuracy of 73% was found for predicting hypertension status, using a random forest model on a combination of demographic, diet and physical activity behavior, and mental state predictor variables. We demonstrate the use of the machine learning model through the development of an Application Programming Interface (API), which is called by a mHealth smartphone app and web interface. This work has promise for future intervention studies that assess how users respond to feedback on cardiovascular risk predictions, and which could evaluate improvements in costeffective cardiovascular healthcare.

Summary Time-restricted feeding (TRF) regimens have grown in popularity; however, very few studies have examined their weight-loss efficacy. We conducted the first human trial (Clinicaltrials.gov NCT03867773) to compare the effects of two popular forms of TRF (4 and 6 h) on body weight and cardiometabolic risk factors. Adults with obesity were randomized to 4-h TRF (eating only between 3 and 7 p.m.), 6-h TRF (eating only between 1 and 7 p.m.), or a control group (no meal timing restrictions). After 8 weeks, 4- and 6-h TRF produced comparable reductions in body weight (∼3%), insulin resistance, and oxidative stress, versus controls. Energy intake was reduced by ∼550 kcal/day in both TRF groups, without calorie counting. These findings suggest that 4- and 6-h TRF induce mild reductions in body weight over 8 weeks and show promise as interventions for weight loss. These diets may also improve some aspects of cardiometabolic health.

Using food recall data collected from over 8000 Americans, we used Machine Learning to classify a person’s demographic characteristics (age, gender, race, and income) based on the foods they consumed in a 24-h period. The best-performing models predicted gender correctly 61%, race 44%, and age 43% of the time on independent validation data. The model was subsequently used to provide tailored recommendations for healthier food options based on low-calorie and low-fat options for specific food groups that are typically consumed by other Americans that match the person’s demographics. This system is part of a larger Smart Human-Centered System that assists users in recording the foods they consume, recognizes nutritional content of the food, offers tailored recommendations for consuming healthier foods, and tracking behavior change over time.

BACKGROUND: Time restricted feeding (TRF) involves confining the eating window to a specific number of hours, and fasting for the remaining hours of the day. OBJECTIVE: This study examined if changes in body weight and metabolic risk factors during TRF, differ between premenopausal and postmenopausal women. METHODS: This is a secondary analysis of an 8-week TRF study (4–6 h eating window, 18–20 h fasting window daily) conducted in adults with obesity. Male participants were excluded, and female subjects were classified in two groups based on menstrual status: premenopausal (n = 13), or postmenopausal (n = 19). Perimenopausal women were excluded from the original study. RESULTS: Body weight decreased by week 8 in premenopausal women (−3.3 ± 0.4%) and postmenopausal women (−3.3 ± 0.5%) (main effect of time, P < 0.001), with no difference between groups (no group × time interaction). Adherence was excellent in both groups, with premenopausal women adhering to their prescribed eating window on 6.2 ± 0.1 d/week, and postmenopausal women adhering to their window on 6.2 ± 0.2 d/week. Fat mass, lean mass, fasting insulin, insulin resistance, and 8-isoprostane (marker of oxidative stress) were reduced similarly in both groups (main effect of time, P < 0.05 for all comparisons). Visceral fat mass, relative skeletal muscle index (RSMI), blood pressure, LDL cholesterol, HDL cholesterol, triglycerides, fasting glucose, HbA1c, TNF-alpha and IL-6 remained unchanged in both groups by week 8. CONCLUSION: These findings suggest that the weight loss and metabolic benefits of TRF do not differ between premenopausal and postmenopausal women with obesity.

BACKGROUND Smartphone diet-tracking apps may help individuals lose weight, manage chronic conditions, and understand dietary patterns; however, the usabilities and functionalities of these apps have not been well studied. OBJECTIVE The aim of this study was to review the usability of current iPhone operating system (iOS) and Android diet-tracking apps, the degree to which app features align with behavior change constructs, and to assess variations between apps in nutrient coding. METHODS The top 7 diet-tracking apps were identified from the iOS iTunes and Android Play online stores, downloaded and used over a 2-week period. Each app was independently scored by researchers using the System Usability Scale (SUS), and features were compared with the domains in an integrated behavior change theory framework: the Theoretical Domains Framework. An estimated 3-day food diary was completed using each app, and food items were entered into the United States Department of Agriculture (USDA) Food Composition Databases to evaluate their differences in nutrient data against the USDA reference. RESULTS Of the apps that were reviewed, LifeSum had the highest average SUS score of 89.2, whereas MyDietCoach had the lowest SUS score of 46.7. Some variations in features were noted between Android and iOS versions of the same apps, mainly for MyDietCoach, which affected the SUS score. App features varied considerably, yet all of the apps had features consistent with Beliefs about Capabilities and thus have the potential to promote self-efficacy by helping individuals track their diet and progress toward goals. None of the apps allowed for tracking of emotional factors that may be associated with diet patterns. The presence of behavior change domain features tended to be weakly correlated with greater usability, with R2 ranging from 0 to .396. The exception to this was features related to the Reinforcement domain, which were correlated with less usability. Comparing the apps with the USDA reference for a 3-day diet, the average differences were 1.4% for calories, 1.0% for carbohydrates, 10.4% for protein, and −6.5% for fat. CONCLUSIONS Almost all reviewed diet-tracking apps scored well with respect to usability, used a variety of behavior change constructs, and accurately coded calories and carbohydrates, allowing them to play a potential role in dietary intervention studies.

BackgroundSmartphone diet-tracking apps may help individuals lose weight, manage chronic conditions, and understand dietary patterns; however, the usabilities and functionalities of these apps have not been well studied. ObjectiveThe aim of this study was to review the usability of current iPhone operating system (iOS) and Android diet-tracking apps, the degree to which app features align with behavior change constructs, and to assess variations between apps in nutrient coding. MethodsThe top 7 diet-tracking apps were identified from the iOS iTunes and Android Play online stores, downloaded and used over a 2-week period. Each app was independently scored by researchers using the System Usability Scale (SUS), and features were compared with the domains in an integrated behavior change theory framework: the Theoretical Domains Framework. An estimated 3-day food diary was completed using each app, and food items were entered into the United States Department of Agriculture (USDA) Food Composition Databases to evaluate their differences in nutrient data against the USDA reference. ResultsOf the apps that were reviewed, LifeSum had the highest average SUS score of 89.2, whereas MyDietCoach had the lowest SUS score of 46.7. Some variations in features were noted between Android and iOS versions of the same apps, mainly for MyDietCoach, which affected the SUS score. App features varied considerably, yet all of the apps had features consistent with Beliefs about Capabilities and thus have the potential to promote self-efficacy by helping individuals track their diet and progress toward goals. None of the apps allowed for tracking of emotional factors that may be associated with diet patterns. The presence of behavior change domain features tended to be weakly correlated with greater usability, with R2 ranging from 0 to .396. The exception to this was features related to the Reinforcement domain, which were correlated with less usability. Comparing the apps with the USDA reference for a 3-day diet, the average differences were 1.4% for calories, 1.0% for carbohydrates, 10.4% for protein, and −6.5% for fat. ConclusionsAlmost all reviewed diet-tracking apps scored well with respect to usability, used a variety of behavior change constructs, and accurately coded calories and carbohydrates, allowing them to play a potential role in dietary intervention studies.