Background: Clinically significant weight loss—which requires sustained dietary and physical activity changes—is central to treating NAFLD. Although behavioral interventions have demonstrated effectiveness in promoting weight loss among primary prevention populations, the data are limited among patients with NAFLD who need weight loss for treatment. We undertook this scoping review to map the existing data on the characteristics, weight-loss outcomes, and determinants of success of interventions evaluated among patients with NAFLD. Methods: We searched Medline, EMBASE, Cochrane, PsycINFO, and Web of Science from inception to January 1, 2023 to identify publications reporting weight loss among adults with NAFLD in behavioral weight-loss interventions. We summarized interventions and classified them as successful if there was an average weight loss of ≥ 5% from baseline across enrolled participants or achieved by ≥ 50% of enrolled participants. Results: We included 28 studies: 10 randomized control trials, ten quasi-experimental, and 8 observational studies. Intervention delivery, duration, and counseling frequency varied; 12 were successful. Retention was highest among telephone interventions and lowest among “real-world” face-to-face interventions. Patients who were women, younger, and/or had multiple metabolic conditions were most likely to dropout. Successful interventions had biweekly counseling, specific physical activity, and calorie targets, behavioral theory grounding, and promoted goal-setting, self-monitoring, and problem-solving. Conclusion: There are limited data on behavioral weight-loss interventions in NAFLD. Research is needed to develop effective interventions generalizable to diverse patient populations and that maximize adherence, particularly among patients who are diabetic, women, and younger.

Background We previously found that a 6-month multidimensional diabetes program, TIME ( T elehealth-Supported, I ntegrated Community Health Workers, Me dication-Access) resulted in improved clinical outcomes. Objective To follow TIME participant clinical outcomes for 24 months Participants Low-income Latino(a)s with type 2 diabetes Design and Intervention We collected post-intervention clinical data for five cohorts ( n = 101, mean n = 20/cohort) who participated in TIME programs from 2018 to 2020 in Houston, Texas. Main Measures We gathered HbA1c (primary outcome), weight, body mass index (BMI), and blood pressure data at baseline, 6 months (intervention end), and semiannually thereafter until 24 months after baseline to assess sustainability. We also evaluated participant loss to follow-up until 24 months. Key Results Participants decreased HbA1c levels during the intervention ( p < 0.0001) and maintained these improvements at each timepoint from baseline to 24 months ( p range: < 0.0001 to 0.015). Participants reduced blood pressure levels during TIME and maintained these changes at each timepoint from baseline until 18 months (systolic p range < 0.0001 to 0.0005, diastolic p range: < 0.0001 to 0.008) but not at 24 months (systolic: p = 0.065; diastolic: p = 0.85). There were no significant weight changes during TIME or post-intervention: weight ( p range = 0.07 to 0.77), BMI ( p range = 0.11 to 0.71). Attrition rates (loss to follow-up during the post-intervention period) were 5.9% (6 months), 24.8% (12 months), 35.6% (18 months), and 41.8% (24 months). Conclusions It is possible for vulnerable populations to maintain long-term glycemic and blood pressure improvements using a multiple dimensional intervention. Attrition rates rose over time but show promise given the majority of post-intervention timepoints occurred during the COVID-19 pandemic when low-income populations were most susceptible to suboptimal healthcare access. Future studies are needed to evaluate longitudinal outcomes of diabetes interventions conducted by local clinics rather than research teams.

Behavioral management is the key to the development and maintenance of a healthy lifestyle. Behavioral management strategies are aimed at helping patients develop the skills needed to achieve and maintain a healthier lifestyle. Current guidelines for the behavioral management of patients with obesity recommend 60–90-minute weekly sessions, either individual or group, for the first 6 months, followed by biweekly, then monthly sessions. The challenge of health care providers is to incorporate the behavioral strategies utilized successfully and adapt them in their own practices.

According to the World Health Organization, more than 650 million adults in 2016 were obese. In addition, 39% of adults over age 18 years old were overweight. It has been estimated that at least 2.8 million people die each year because of being either overweight or obese. These grim statistics are even more prominent in the United States. According to the National Center for Health Statistics, 42.5% of US adults over the age of 20 have obesity as reported in the 2017-2018 National Health and Nutrition Examination Survey, while an additional 31% are overweight. Thus, almost three quarters of the adult population in the United States are currently overweight or have obesity! While most physicians understand the significant links between obesity, coronary heart disease, diabetes, and the metabolic syndrome, many health care professionals do not recognize that obesity also predisposes individuals to multiple complications from COVID-19. Thus, during this terrible pandemic of COVID-19, the twin epidemic of obesity has exacerbated both the degree and severity of illness and resulted in substantial increases in mortality. While the metabolic complications of obesity (eg, coronary heart disease, diabetes, metabolic syndrome, and even some cancers) are well known to practitioners of lifestyle medicine, the link between obesity and COVID-19 is less well known. Since obesity is in many ways the quintessential lifestylerelated disease, it is important for all physicians to counsel individuals who are overweight and those with obesity that they are substantially increasing their risk of the terrible complications related to the ongoing COVID-19 pandemic.

Introduction Community clinics often face pragmatic barriers, hindering program initiation and replication of controlled research trial results. Mentoring is a potential strategy to overcome these barriers. We piloted an in-person and telehealth mentoring strategy to implement the Telehealth-supported, Integrated Community Health Workers (CHWs), Medication-access, group visit Education (TIME) program in a community clinic.Research design and methods Participants (n=55) were low-income Latino(a)s with type 2 diabetes. The study occurred in two, 6-month phases. Phase I provided proof-of-concept and an observational experience for the clinic team; participants (n=37) were randomized to the intervention (TIME) or control (usual care), and the research team conducted TIME while the clinic team observed. Phase II provided mentorship to implement TIME, and the research team mentored the clinic team as they conducted TIME for a new single-arm cohort of participants (n=18) with no previous exposure to the program. Analyses included baseline to 6-month comparisons of diabetes outcomes (primary outcome: hemoglobin A1c (HbA1c)): phase I intervention versus control, phase II (within group), and research-run (phase I intervention) versus clinic-run (phase II) arms. We also evaluated baseline to 6-month CHW knowledge changes.Results Phase I: compared with the control, intervention participants had superior baseline to 6-month improvements for HbA1c (mean change: intervention: −0.73% vs control: 0.08%, p=0.016), weight (p=0.044), target HbA1c (p=0.035), hypoglycemia (p=0.021), medication non-adherence (p=0.0003), and five of six American Diabetes Association (ADA) measures (p<0.001–0.002). Phase II: participants had significant reductions in HbA1c (mean change: −0.78%, p=0.006), diastolic blood pressure (p=0.004), body mass index (0.012), weight (p=0.010), medication non-adherence (p<0.001), and six ADA measures (p=0.007–0.005). Phase I intervention versus phase II outcomes were comparable. CHWs improved knowledge from pre-test to post-tests (p<0.001).Conclusions A novel, mentored approach to implement TIME into a community clinic resulted in improved diabetes outcomes. Larger studies of longer duration are needed to fully evaluate the potential of mentoring community clinics.

Objective This study aimed to determine the medical cost impact and return on investment (ROI) of a large, commercial, digital, weight-management intensive lifestyle intervention (ILI) program (Real Appeal). Methods Participants in this program were compared with a control group matched by age, sex, geographic region, health risk, baseline medical costs, and chronic conditions. Medical costs were defined as the total amount paid for all medical expenses, inclusive of both the insurers' and the study participants' responsibility. Results In the 3 years following program registration, the intent-to-treat (ITT) cohort had significantly lower medical expenditures than the matched controls, with an average of -$771 or 12% lower costs (P = 0.002). Among 4,790 ITT participants, a total savings of $3,693,090 compared with total program costs of $1,639,961 translated into a 2.3:1 ROI. Program completers (n = 3,990), who attended more sessions than the overall ITT group, had greater mean weight loss (-4.4%), greater cost savings (-$956 or 14%), and an ROI of 2.0:1 over the 3-year time frame compared with matched controls. Conclusions The findings demonstrated that the digital weight-management ILI was associated with a significantly positive ROI. Employers and payers willing to cover the cost of an ILI that produces both weight loss and demonstrated cost benefits can improve health and save money for their population with overweight or obesity.

OBJECTIVE:The Action for Health in Diabetes (Look AHEAD) study previously reported that intensive lifestyle intervention (ILI) reduced incident depressive symptoms and improved health-related quality of life (HRQOL) over nearly 10 years of intervention compared with a control group (the diabetes support and education group [DSE]) in participants with type 2 diabetes and overweight or obesity. The present study compared incident depressive symptoms and changes in HRQOL in these groups for an additional 6 years following termination of the ILI in September 2012. METHODS:A total of 1,945 ILI participants and 1,900 DSE participants completed at least one of four planned postintervention assessments at which weight, mood (via the Patient Health Questionnaire-9), antidepressant medication use, and HRQOL (via the Medical Outcomes Scale, Short Form-36) were measured. RESULTS:ILI participants and DSE participants lost 3.1 (0.3) and 3.8 (0.3) kg [represented as mean (SE); p = 0.10], respectively, during the 6-year postintervention follow-up. No significant differences were observed between groups during this time in incident mild or greater symptoms of depression, antidepressant medication use, or in changes on the physical component summary or mental component summary scores of the Short Form-36. In both groups, mental component summary scores were higher than physical component summary scores. CONCLUSIONS:Prior participation in the ILI, compared with the DSE group, did not appear to improve subsequent mood or HRQOL during 6 years of postintervention follow-up.

Background Many individuals with diabetes live in low- or middle-income settings. Glycemic control is challenging, particularly in resource-limited areas that face numerous healthcare barriers. Objective To compare HbA1c outcomes for individuals randomized to TIME, a T elehealth-supported, I ntegrated care with CHWs (Community Health Workers), and ME dication-access program (intervention) versus usual care (wait-list control). Design Randomized clinical trial. Participants Low-income Latino(a) adults with type 2 diabetes. Interventions TIME consisted of (1) CHW-participant telehealth communication via mobile health (mHealth) for 12 months, (2) CHW-led monthly group visits for 6 months, and (3) weekly CHW-physician diabetes training and support via telehealth (video conferencing). Main Measures Investigators compared TIME versus control participant baseline to month 6 changes of HbA1c (primary outcome), blood pressure, body mass index (BMI), weight, and adherence to seven American Diabetes Association (ADA) standards of care. CHW assistance in identifying barriers to healthcare in the intervention group were measured at the end of mHealth communication (12 months). Key Results A total of 89 individuals participated. TIME individuals compared to control participants had significant HbA1c decreases (9.02 to 7.59% (− 1.43%) vs. 8.71 to 8.26% (− 0.45%), respectively, p = 0.002), blood pressure changes (systolic: − 6.89 mmHg vs. 0.03 mmHg, p = 0.023; diastolic: − 3.36 mmHg vs. 0.2 mmHg, respectively, p = 0.046), and ADA guideline adherence ( p < 0.001) from baseline to month 6. At month 6, more TIME than control participants achieved > 0.50% HbA1c reductions (88.57% vs. 43.75%, p < 0.001). BMI and weight changes were not significant between groups. Many (54.6%) TIME participants experienced > 1 barrier to care, of whom 91.7% had medication issues. CHWs identified the majority (87.5%) of barriers. Conclusions TIME participants resulted in improved outcomes including HbA1c. CHWs are uniquely positioned to identify barriers to care particularly related to medications that may have gone unrecognized otherwise. Larger trials are needed to determine the scalability and sustainability of the intervention. Clinical Trial NCT03394456, accessed at https://clinicaltrials.gov/ct2/show/NCT03394456

ObjectiveThis study evaluated weight changes after cessation of the 10‐year intensive lifestyle intervention (ILI) in the Look AHEAD (Action for Health in Diabetes) study. It was hypothesized that ILI participants would be more likely to gain weight during the 2‐year observational period following termination of weight‐loss–maintenance counseling than would participants in the diabetes support and education (DSE) control group.MethodsLook AHEAD was a randomized controlled trial that compared the effects of ILI and DSE on cardiovascular morbidity and mortality in participants with overweight/obesity and type 2 diabetes. Look AHEAD was converted to an observational study in September 2012.ResultsTwo years after the end of the intervention (EOI), ILI and DSE participants lost a mean (SE) of 1.2 (0.2) kg and 1.8 (0.2) kg, respectively (P = 0.003). In addition, 31% of ILI and 23.9% of DSE participants gained ≥ 2% (P < 0.001) of EOI weight, whereas 36.3% and 45.9% of the respective groups lost ≥ 2% of EOI weight (P = 0.001). Two years after the EOI, ILI participants reported greater use of weight‐control behaviors than DSE participants.ConclusionsBoth groups lost weight during the 2‐year follow‐up period, but more ILI than DSE participants gained ≥ 2% of EOI weight. Further understanding is needed of factors that affected long‐term weight change in both groups.

OBJECTIVE:This study was designed to determine whether intensive lifestyle intervention (ILI) aimed at weight loss lowers cancer incidence and mortality.METHODS:Data from the Look AHEAD trial were examined to investigate whether participants randomized to ILI designed for weight loss would have reduced overall cancer incidence, obesity-related cancer incidence, and cancer mortality, as compared with the diabetes support and education (DSE) comparison group. This analysis included 4,859 participants without a cancer diagnosis at baseline except for nonmelanoma skin cancer.RESULTS:After a median follow-up of 11 years, 684 participants (332 in ILI and 352 in DSE) were diagnosed with cancer. The incidence rates of obesity-related cancers were 6.1 and 7.3 per 1,000 person-years in ILI and DSE, respectively, with a hazard ratio (HR) of 0.84 (95% CI: 0.68-1.04). There was no significant difference between the two groups in total cancer incidence (HR, 0.93; 95% CI: 0.80-1.08), incidence of nonobesity-related cancers (HR, 1.02; 95% CI: 0.83-1.27), or total cancer mortality (HR, 0.92; 95% CI: 0.68-1.25).CONCLUSIONS:An ILI aimed at weight loss lowered incidence of obesity-related cancers by 16% in adults with overweight or obesity and type 2 diabetes. The study sample size likely lacked power to determine effect sizes of this magnitude and smaller.

OBJECTIVE To assess the cost-effectiveness (CE) of an intensive lifestyle intervention (ILI) compared to standard diabetes support and education (DSE) in adults with overweight/obesity and type 2 diabetes, as implemented in the Action for Health in Diabetes study. RESEARCH DESIGN AND METHODS Data were from 4,827 participants during the first 9 years of the study from 2001 to 2012. Information on Health Utility Index-2 and -3, SF-6D, and Feeling Thermometer [FT]), cost of delivering the interventions, and health expenditures were collected during the study. CE was measured by incremental cost-effectiveness ratios (ICERs) in costs per quality-adjusted life year (QALY). Future costs and QALYs were discounted at 3% annually. Costs were in 2012 US dollars. RESULTS Over the 9 years studied, the mean cumulative intervention costs and mean cumulative health care expenditures were $11,275 and $64,453 per person for ILI and $887 and $68,174 for DSE. Thus, ILI cost $6,666 more per person than DSE. Additional QALYs gained by ILI were not statistically significant measured by the HUIs and were 0.17 and 0.16, respectively, measured by SF-6D and FT. The ICERs ranged from no health benefit with a higher cost based on HUIs, to $96,458/QALY and $43,169/QALY, respectively, based on SF-6D and FT. Conclusions Whether ILI was cost-effective over the 9-year period is unclear because different health utility measures led to different conclusions.

ObjectiveTo examine the effects of an intensive lifestyle intervention (ILI) on cardiovascular disease (CVD), the Action for Health in Diabetes (Look AHEAD) trial randomized 5,145 participants with type 2 diabetes and overweight/obesity to a ILI or diabetes support and education. Although the primary outcome did not differ between the groups, there was suggestive evidence of heterogeneity for prespecified baseline CVD history subgroups (interaction P = 0.063). Event rates were higher in the ILI group among those with a CVD history (hazard ratio 1.13 [95% CI: 0.90‐1.41]) and lower among those without CVD (hazard ratio 0.86 [95% CI: 0.72‐1.02]).MethodsThis study conducted post hoc analyses of the rates of the primary composite outcome and components, adjudicated cardiovascular death, nonfatal myocardial infarction (MI), stroke, and hospitalization for angina, as well as three secondary composite cardiovascular outcomes.ResultsInteraction P values for the primary and two secondary composites were similar (0.060‐0.064). Of components, the interaction was significant for nonfatal MI (P = 0.035). This interaction was not due to confounding by baseline variables, different intervention responses for weight loss and physical fitness, or hypoglycemic events. In those with a CVD history, statin use was high and similar by group. In those without a CVD history, low‐density lipoprotein cholesterol levels were higher (P = 0.003) and statin use was lower (P ≤ 0.001) in the ILI group.ConclusionsIntervention response heterogeneity was significant for nonfatal MI. Response heterogeneity may need consideration in a CVD‐outcome trial design.

In the article cited above, there were some differences in means and proportions of a few variables between the published data and …

Background: Community health workers (CHWs) are a well-established source to improve patient health care, yet their training and support remain suboptimal. This limits program expansion and potentially compromises patient safety. The objective of the study was to evaluate the feasibility and acceptability of weekly training and support by telemedicine (videoconferencing). Materials and Methods: CHWs (n = 6) who led diabetes group visits for low-income Latinos met weekly with a health care professional for training and support. Feasibility and acceptability outcome measures included telemedicine usability, knowledge of diabetes (baseline to 6 months), and program satisfaction. Results: Telemedicine training and support were found to be feasible and acceptable as measured by usability (Telehealth Usability Questionnaire: average 4.7/5.0, +/- 0.4), knowledge (Diabetes Knowledge Test: pretest 15.8 +/- 1.3, posttest 21.8 +/- 1.2, p < 0.001, respectively), and satisfaction (Texas Department of State Health Services survey: average 5.8/6.0, +/- 0.5). All CHWs preferred telemedicine to in-person training. Conclusions: Telemedicine is a feasible and acceptable modality to train and support CHWs.

Summary Objective To compare depressive symptomatology as assessed by two frequently used measures, the Beck Depression Inventory (BDI‐1A) and Patient Health Questionnaire (PHQ‐9). Methods Investigators conducted a cross‐sectional secondary analysis of data collected as part of the follow‐up observational phase of the Look AHEAD study. Rates of agreement between the BDI‐1A and PHQ‐9 were calculated, and multivariable logistic regression was used to examine the relationship between differing depression category classifications and demographic factors (ie, age, sex, race/ethnicity) or comorbidities (ie, diabetes control, cardiovascular disease). Results A high level of agreement (κ = 0.47, 95% CI (0.43 to 0.50)) was found in the level of depressive symptomatology between the BDI‐1A and PHQ‐9. Differing classifications (minimal, mild, moderate, and severe) occurred in 16.8% of the sample. Higher scores on the somatic subscale of the BDI‐1A were significantly associated with disagreement as were having a history of cardiovascular disease, lower health‐related quality of life, and minority racial/ethnic classification. Conclusions Either the BDI‐1A or PHQ‐9 can be used to assess depressive symptomatology in adults with overweight/obesity and type 2 diabetes. However, further assessment should be considered in those with related somatic symptoms, decreased quality of life, and in racial/ethnic minority populations.

BACKGROUND:Prior studies have supported the efficacy of diabetes group visits. However, the benefit of diabetes group visits for low-income and underserved individuals is not clear. The purpose of this study was to conduct a narrative review in order to clarify the efficacy of diabetes group visits in low-income and underserved settings. METHODS:The authors performed a narrative review, categorizing studies into nonrandomized and randomized. RESULTS:A total of 14 studies were identified. Hemoglobin A1c was the most commonly measured outcome, which improved for the majority of group visit participants. Preventive care showed consistent improvement for intervention arms. There were several other study outcomes including metabolic (i.e., blood pressure), behavioral (i.e., exercise), functional (i.e., quality of life), and system-based (i.e., cost). CONCLUSION:Diabetes group visits for low-income and underserved individuals resulted in superior preventive care but the impact on glycemic control remains unclear.