Obesity.

Obesity is a common condition and a major cause of morbidity and mortality. Fortunately, weight loss treatment can reduce obesity-related complications. This review summarizes the evidence-based strategies physicians can employ to identify, prevent, and treat obesity, including best practices to diagnose and counsel patients, to assess and address the burden of weight-related disease including weight stigma, to address secondary causes of weight gain, and to help patients set individualized and realistic weight loss goals and an effective treatment plan. Effective treatments include lifestyle modification and adjunctive therapies such as antiobesity medications and metabolic and bariatric surgery.

The effects of early time restricted eating plus daily caloric restriction compared to daily caloric restriction alone on continuous glucose levels.

Background: The median eating duration in the U.S. is 14.75 h, spread throughout the period of wakefulness and ending before sleep. Food intake at an inappropriate circadian time may lead to adverse metabolic outcomes. Emerging literature suggests that time restricted eating (TRE) may improve glucose tolerance and insulin sensitivity. The aim was to compare 24-h glucose profiles and insulin sensitivity in participants after completing 12 weeks of a behavioral weight loss intervention based on early TRE plus daily caloric restriction (E-TRE+DCR) or DCR alone. Methods: Eighty-one adults with overweight or obesity (age 18-50 years, BMI 25-45 kg/m2) were randomized to either E-TRE+DCR or DCR alone. Each participant wore a continuous glucose monitor (CGM) for 7 days and insulin sensitivity was estimated using the homeostatic model assessment of insulin resistance (HOMA-IR) at Baseline and Week 12. Changes in CGM-derived measures and HOMA-IR from Baseline to Week 12 were assessed within and between groups using random intercept mixed models. Results: Forty-four participants had valid CGM data at both time points, while 38 had valid glucose, insulin, HOMA-IR, and hemoglobin A1c (A1c) data at both timepoints. There were no significant differences in sex, age, BMI, or the percentage of participants with prediabetes between the groups (28% female, age 39.2 ± 6.9 years, BMI 33.8 ± 5.7 kg/m2, 16% with prediabetes). After adjusting for weight, there were no between-group differences in changes in overall average sensor glucose, standard deviation of glucose levels, the coefficient of variation of glucose levels, daytime or nighttime average sensor glucose, fasting glucose, insulin, HOMA-IR, or A1c. However, mean amplitude of glycemic excursions changed differently over time between the two groups, with a greater reduction found in the DCR as compared to E-TRE+DCR (p = 0.03). Conclusion: There were no major differences between E-TRE+DCR and DCR groups in continuous glucose profiles or insulin sensitivity 12 weeks after the intervention. Because the study sample included participants with normal baseline mean glucose profiles and insulin sensitivity, the ability to detect changes in these outcomes may have been limited.

The Microbiome, Epigenome, and Diet in Adults with Obesity during Behavioral Weight Loss.

Obesity has been linked to the gut microbiome, epigenome, and diet, yet these factors have not been studied together during obesity treatment. Our objective was to evaluate associations among gut microbiota (MB), DNA methylation (DNAme), and diet prior to and during a behavioral weight loss intervention. Adults (n = 47, age 40.9 ± 9.7 years, body mass index (BMI) 33.5 ± 4.5 kg/m2, 77% female) with data collected at baseline (BL) and 3 months (3 m) were included. Fecal MB was assessed via 16S sequencing and whole blood DNAme via the Infinium EPIC array. Food group and nutrient intakes and Healthy Eating Index (HEI) scores were calculated from 7-day diet records. Linear models were used to test for the effect of taxa relative abundance on DNAme and diet cross-sectionally at each time point, adjusting for confounders and a false discovery rate of 5%. Mean weight loss was 6.2 ± 3.9% at 3 m. At BL, one MB taxon, Ruminiclostridium, was associated with DNAme of the genes COL20A1 (r = 0.651, p = 0.029), COL18A1 (r = 0.578, p = 0.044), and NT5E (r = 0.365, p = 0.043). At 3 m, there were 14 unique MB:DNAme associations, such as Akkermansia with DNAme of GUSB (r = -0.585, p = 0.003), CRYL1 (r = -0.419, p = 0.007), C9 (r = -0.439, p = 0.019), and GMDS (r = -0.559, p = 0.046). Among taxa associated with DNAme, no significant relationships were seen with dietary intakes of relevant nutrients, food groups, or HEI scores. Our findings indicate that microbes linked to mucin degradation, short-chain fatty acid production, and body weight are associated with DNAme of phenotypically relevant genes. These relationships offer an initial understanding of the possible routes by which alterations in gut MB may influence metabolism during weight loss.

High- and normal-protein diets improve body composition and glucose control in adults with type 2 diabetes: a randomized trial.

OBJECTIVE: Weight loss of ≥10% improves glucose control and may remit type 2 diabetes (T2D). High-protein (HP) diets are commonly used for weight loss, but whether protein sources, especially red meat, impact weight loss-induced T2D management is unknown. This trial compared an HP diet including beef and a normal-protein (NP) diet without red meat for weight loss, body composition changes, and glucose control in individuals with T2D. METHODS: A total of 106 adults (80 female) with T2D consumed an HP (40% protein) diet with ≥4 weekly servings of lean beef or an NP (21% protein) diet excluding red meat during a 52-week weight loss intervention. Body weight, body composition, and cardiometabolic parameters were measured before and after intervention. RESULTS: Weight loss was not different between the HP (-10.2 ± 1.6 kg) and NP (-12.7 ± 4.8 kg, p = 0.336) groups. Both groups reduced fat mass and increased fat-free mass percent. Hemoglobin A1c, glucose, insulin, insulin resistance, blood pressure, and triglycerides improved, with no differences between groups. CONCLUSIONS: The lack of observed effects of dietary protein and red meat consumption on weight loss and improved cardiometabolic health suggests that achieved weight loss, rather than diet composition, should be the principal target of dietary interventions for T2D management.

A pre-conception clinical trial to reduce intergenerational obesity and diabetes risks: The NDPP-NextGen trial protocol.

BACKGROUND: Intrauterine exposure to maternal overweight/obesity or diabetes transmits risks to offspring, perpetuating a disease cycle across generations. Prenatal interventions to reduce maternal weight or dysglycemia have limited impact, while postpartum interventions can alter the intrauterine environment only if child-bearing continues. Efficacious preconception interventions are needed, especially for underserved populations, and with the potential to be scaled up sustainably. Research is also needed to assess intervention effects at conception, throughout pregnancy, and among offspring. METHODS: This two-arm, parallel randomized clinical trial will include 360 biological females with overweight/obesity and moderate-to-high likelihood of pregnancy within 24 months. Participants will be randomized 1:1 to a yearlong pre-conception lifestyle intervention based on the National Diabetes Prevention Program (NDPP-NextGen) or usual care. Data collection will occur at enrollment (before conception), post-conception (<8 weeks gestation), late pregnancy (28-32 weeks gestation), and delivery (before discharge) for participants who become pregnant within 24 months of enrollment. Main outcomes are post-conception body mass index (<8 weeks gestation; primary outcome), post-conception fasting glucose (<8 weeks gestation; secondary outcome), and neonatal adiposity (<2 days post-birth). Additional clinical, behavioral, perinatal and offspring data will be collected, and biospecimens (blood, urine, stool, cord blood) will be banked for future ancillary studies. CONCLUSION: This clinical trial will evaluate an intervention model (NDPP-NextGen) with potential to improve maternal health among the >50% of US females with overweight/obesity or diabetes risks in pregnancy. If successful, it can be scaled among >1800 organizations delivering NDPP in the United States to benefit the health of future generations.

Impact of the built, social, and food environment on long-term weight loss within a behavioral weight loss intervention.

Background: Behavioral weight loss interventions can lead to an average weight loss of 5%-10% of initial body weight, however there is wide individual variability in treatment response. Although built, social, and community food environments can have potential direct and indirect influences on body weight (through their influence on physical activity and energy intake), these environmental factors are rarely considered as predictors of variation in weight loss. Objective: Evaluate the association between built, social, and community food environments and changes in weight, moderate-to-vigorous physical activity (MVPA), and dietary intake among adults who completed an 18-month behavioral weight loss intervention. Methods: Participants included 93 adults (mean ± SD; 41.5 ± 8.3 years, 34.4 ± 4.2 kg/m2, 82% female, 75% white). Environmental variables included urbanicity, walkability, crime, Neighborhood Deprivation Index (includes 13 social economic status factors), and density of convenience stores, grocery stores, and limited-service restaurants at the tract level. Linear regressions examined associations between environment and changes in body weight, waist circumference (WC), MVPA (SenseWear device), and dietary intake (3-day diet records) from baseline to 18 months. Results: Grocery store density was inversely associated with change in weight (ß = -0.95; p = 0.02; R 2 = 0.062) and WC (ß = -1.23; p < 0.01; R 2 = 0.109). Participants living in tracts with lower walkability demonstrated lower baseline MVPA and greater increases in MVPA versus participants with higher walkability (interaction p = 0.03). Participants living in tracts with the most deprivation demonstrated greater increases in average daily steps (ß = 2048.27; p = 0.02; R 2 = 0.039) versus participants with the least deprivation. Limited-service restaurant density was associated with change in % protein intake (ß = 0.39; p = 0.046; R 2 = 0.051). Conclusion: Environmental factors accounted for some of the variability (<11%) in response to a behavioral weight loss intervention. Grocery store density was positively associated with weight loss at 18 months. Additional studies and/or pooled analyses, encompassing greater environmental variation, are required to further evaluate whether environment contributes to weight loss variability.

Altered motivation states for physical activity and 'appetite' for movement as compensatory mechanisms limiting the efficacy of exercise training for weight loss.

Weight loss is a major motive for engaging in exercise, despite substantial evidence that exercise training results in compensatory responses that inhibit significant weight loss. According to the Laws of Thermodynamics and the CICO (Calories in, Calories out) model, increased exercise-induced energy expenditure (EE), in the absence of any compensatory increase in energy intake, should result in an energy deficit leading to reductions of body mass. However, the expected negative energy balance is met with both volitional and non-volitional (metabolic and behavioral) compensatory responses. A commonly reported compensatory response to exercise is increased food intake (i.e., Calories in) due to increased hunger, increased desire for certain foods, and/or changes in health beliefs. On the other side of the CICO model, exercise training can instigate compensatory reductions in EE that resist the maintenance of an energy deficit. This may be due to decreases in non-exercise activity thermogenesis (NEAT), increases in sedentary behavior, or alterations in sleep. Related to this EE compensation, the motivational states associated with the desire to be active tend to be overlooked when considering compensatory changes in non-exercise activity. For example, exercise-induced alterations in the wanting of physical activity could be a mechanism promoting compensatory reductions in EE. Thus, one's desires, urges or cravings for movement-also known as "motivation states" or "appetence for activity"-are thought to be proximal instigators of movement. Motivation states for activity may be influenced by genetic, metabolic, and psychological drives for activity (and inactivity), and such states are susceptible to fatigue-or reward-induced responses, which may account for reductions in NEAT in response to exercise training. Further, although the current data are limited, recent investigations have demonstrated that motivation states for physical activity are dampened by exercise and increase after periods of sedentarism. Collectively, this evidence points to additional compensatory mechanisms, associated with motivational states, by which impositions in exercise-induced changes in energy balance may be met with resistance, thus resulting in attenuated weight loss.

Proteomics, dietary intake, and changes in cardiometabolic health within a behavioral weight-loss intervention: A pilot study.

OBJECTIVE: Identifying associations among circulating proteins, dietary intakes, and clinically relevant indicators of cardiometabolic health during weight loss may elucidate biologically relevant pathways affected by diet, allowing for an incorporation of precision nutrition approaches when designing future interventions. This study hypothesized that plasma proteins would be associated with diet and cardiometabolic health indicators within a behavioral weight-loss intervention. METHODS: This secondary data analysis included participants (n = 20, mean [SD], age: 40.1 [9.5] years, BMI: 34.2 [4.0] kg/m2 ) who completed a 1-year behavioral weight-loss intervention. Cardiovascular disease-related plasma proteins, diet, and cardiometabolic health indicators were evaluated at baseline and 3 months. Associations were determined via linear regression and integrated networks created using Visualization Of LineAr Regression Elements (VOLARE). RESULTS: A total of 16 plasma proteins were associated with ≥1 diet or health indicator at baseline (p < 0.001); changes in 42 proteins were associated with changes in diet or health indicators from baseline to 3 months (p < 0.005). Baseline tumor necrosis factor receptor superfamily member 10C (TNFRSF10C) was associated with intakes of dark green vegetables (r = -0.712), and fatty acid-binding protein 4 (FABP4) was associated with intakes of unsweetened coffee (r = -0.689). Changes in refined-grain intakes were associated with changes in scavenger receptor cysteine-rich type 1 protein M130 (CD163; r = 0.725), interleukin-1 receptor type 1 (IL1R-T1; r = 0.624), insulin (r = 0.656), and triglycerides (r = 0.648). CONCLUSIONS: Circulating cardiovascular disease-related proteins were associated with diet and cardiometabolic health indicators prior to and in response to weight loss.

Creating an algorithm to identify indices of sleep quantity and quality from a wearable armband in adults.

Objective: To develop an algorithm to quantify indices of sleep quantity and quality using the SenseWear armband (SWA) and to compare indices of sleep from this novel algorithm to standard wrist actigraphy (Actiwatch 2; AW2) under free-living conditions. Material and Methods: Thirty participants (47±10 years; 33.0±4.8kg/m2) wore the SWA and AW2 for seven consecutive days. Participants self-reported bedtime and waketime across these 7 days. Bedtime, sleep onset, sleep offset, waketime, total sleep time (TST), time in bed (TIB), sleep effciency (SE), sleep onset latency (SOL), wake after sleep onset (WASO), sleep fragmentations (SF), sleep regularity (calculated as SD of waketime), and mid-point of sleep were calculated using each device. Results: There was significant evidence for equivalence of means (or mean ranks) for bedtime, sleep onset, sleep offset, waketime, TST, TIB, SOL, WASO, and midpoint of sleep measured by the SWA and AW2 (p<0.05). There was insuffcient evidence for equivalence of means in SF (SW: 25±6 vs. AW2: 10±3 events; p=1.0), mean ranks in sleep regularity (SW: 58±33 vs. AW2: 68±40 min; p=0.11), and mean ranks in SE (SW: 84.7±5.1% vs. AW2: 86.3±5.5%; p=0.05). When comparing minute-by-minute sleep/wake status, the sensitivity and specificity of the SWA were 0.94 (95%CI: 0.93, 0.95) and 0.88 (95%CI: 0.85, 0.90), respectively, using AW2 as the criterion measure. Conclusion: The algorithm developed for the SWA produced relatively accurate and consistent measurements of sleep quantity, timing, and quality compared to the AW2 under free-living conditions. Thus, the SWA is a viable alternative to standard wrist actigraphy.

Comparison of weight loss induced by daily caloric restriction versus intermittent fasting (DRIFT) in individuals with obesity: study protocol for a 52-week randomized clinical trial.

BACKGROUND: The standard of care for treating overweight and obesity is daily caloric restriction (DCR). While this approach produces modest weight loss, adherence to DCR declines over time and weight regain is common. Intermittent fasting (IMF) is an alternative dietary strategy for reducing energy intake (EI) that involves >60% energy restriction on 2-3 days per week, or on alternate days, with habitual intake on fed days. While numerous studies have evaluated IMF as a weight loss strategy, there are several limitations including lack of a standard-of-care DCR control, failure to provide guideline-based behavioral support, and failure to rigorously evaluate dietary and PA adherence using objective measures. To date, only three longer-term (52-week) trials have evaluated IMF as a weight loss strategy. None of these longer-duration studies reported significant differences between IMF and DCR in changes in weight. However, each of these studies has limitations that prohibit drawing generalizable conclusions about the relative long-term efficacy of IMF vs. DCR for obesity treatment. METHODS: The Daily Caloric Restriction vs. Intermittent Fasting Trial (DRIFT) is a two-arm, 52-week block randomized (1:1) clinical weight loss trial. The two intervention arms (DCR and IMF) are designed to prescribe an equivalent average weekly energy deficit from baseline weight maintenance energy requirements. Both DCR and IMF will be provided guideline-based behavioral support and a PA prescription. The primary outcome is change in body weight at 52 weeks. Secondary outcomes include changes in body composition (dual-energy x-ray absorptiometry (DXA)), metabolic parameters, total daily energy expenditure (TDEE, doubly labeled water (DLW)), EI (DLW intake-balance method, 7-day diet diaries), and patterns of physical activity (PA, activPAL device). DISCUSSION: Although DCR leads to modest weight loss success in the short-term, there is wide inter-individual variability in weight loss and poor long-term weight loss maintenance. Evidence-based dietary approaches to energy restriction that are effective long-term are needed to provide a range of evidence-based options to individuals seeking weight loss. The DRIFT study will evaluate the long-term effectiveness of IMF vs. DCR on changes in objectively measured weight, EI, and PA, when these approaches are delivered using guideline-based behavioral support and PA prescriptions.

Effect of sleep on weight loss and adherence to diet and physical activity recommendations during an 18-month behavioral weight loss intervention.

BACKGROUND/OBJECTIVES: To examine the association between indices of sleep quantity and quality with dietary adherence, physical activity adherence, and weight loss during a behavioral weight loss intervention. METHODS: Adults (n = 156) with overweight and obesity (40 ± 9 years, 84% female, BMI: 34.4 ± 4.2 kg/m2) participated in an 18-month behavioral weight loss intervention which prescribed a reduced calorie diet (1200-1800 kcal/d) and increased physical activity (300 min/wk). Body weight, indices of sleep (SenseWear armband; SWA), energy intake (EI, 3-day food records), and moderate-to-vigorous physical activity (SWA) were measured at baseline, 6, 12, and 18 months. Linear mixed effects models examined the association between sleep and weight change over time. Additional models were adjusted for covariates including age, BMI, sex, race, ethnicity, study completion, randomization, EI, and physical activity. Secondary analyses examined the association between sleep and adherence to diet and physical activity recommendations. RESULTS: Mean weight loss was 7.7 ± 5.4, 8.4 ± 7.9, and 7.1 ± 9.0 kg at 6, 12, and 18 months, respectively. Lower sleep efficiency, higher wake after sleep onset (WASO), more awakenings, and higher sleep onset latency (SOL) were significantly associated with attenuated weight loss (p < 0.05). Lower sleep efficiency, more awakenings, and higher SOL remained significantly associated with blunted weight loss after adjustment for covariates (p < 0.05). Later waketime, longer time in bed, longer sleep duration, higher WASO, more awakenings, and higher SOL were associated with lower odds of achieving ≥300 min/wk of moderate-to-vigorous physical activity, adjusted for covariates (FDR p < 0.05). CONCLUSIONS: Future studies should evaluate whether incorporating strategies to improve sleep health within a behavioral weight loss intervention leads to improved adherence to diet and physical activity recommendations and enhanced weight loss. CLINICAL TRIALS IDENTIFIER: NCT01985568.

Early time-restricted eating compared with daily caloric restriction: A randomized trial in adults with obesity.

OBJECTIVE: This trial aimed to evaluate the acceptability and efficacy of early time-restricted eating plus daily caloric restriction (E-TRE+DCR) compared with DCR alone within a behavioral weight-loss intervention. METHODS: Participants (n = 81, 69 women, mean [SD] age: 38.0 [7.8] years, BMI: 34.1 [5.7] kg/m2 ) were randomized to E-TRE (10-hour eating window starting within 3 hours of waking) plus DCR or DCR alone (~35% DCR) for 39 weeks. The primary outcome was body weight (measured with digital scale) at week 12. Secondary outcomes measured at week 12 included hemoglobin A1c, lipids, energy intake (photographic food records), physical activity (accelerometry), dietary adherence (questionnaires), and body composition (dual-energy x-ray absorptiometry). Weight and body composition were also assessed at week 39. RESULTS: Mean [SD] weight loss was not different between groups at week 12 (E-TRE+DCR: -6.2 [4.1] kg vs. DCR: -5.1 [3.2] kg) or at week 39 (E-TRE: -4.9 [5.3] kg vs. DCR: -4.3 [5.3] kg). There were no between-group differences in changes in body composition, dietary adherence, energy intake, physical activity, hemoglobin A1c, or lipids at week 12. CONCLUSIONS: E-TRE+DCR was found to be an acceptable dietary strategy, resulting in similar levels of adherence and weight loss compared with DCR alone.

The impact of yoga on components of energy balance in adults with overweight or obesity: A systematic review.

Background: Yoga may reduce body weight in individuals with overweight or obesity, but whether this occurs through decreased energy intake (EI) or increased energy expenditure (EE)/physical activity (PA) is unclear. Methods: A systematic search of PubMed, Web of Science, Embase, and PsychINFO was conducted from inception until April 26, 2021. Eligible studies included randomized controlled trials or single-arm pre-post studies with any type and duration of yoga intervention in adults with overweight or obesity. Studies with measures related to EI , EE, or PA were eligible. The review initially identified 1,373 articles. Results: Of the 10 included studies, one used indirect calorimeter measures of resting EE, while nine used self-reported measures of EI and PA. Of the seven studies measuring parameters related to EI, only one found greater decreases in EI relative to the control group, although three other investigations reported trends toward improved dietary intake. Of the eight studies measuring PA, two reported greater increases in resting EE or PA in the yoga group relative to the control group. Two reported significant within-group increases in PA from pre-post intervention, and four studies reported a trend for increased PA with no p-values reported. Conclusions: Limited evidence suggests yoga may reduce EI and increase PA in adults with overweight or obesity. Additional studies that investigate the effects of yoga interventions on energy balance parameters using objective techniques are warranted.

Effect of Morning and Evening Exercise on Energy Balance: A Pilot Study.

The purpose of this study was to evaluate the feasibility and acceptability of randomizing adults with overweight and obesity (BMI 25-40 kg/m2) to morning (06:00-10:00) or evening (15:00-19:00) aerobic exercise. Participants completed four exercise sessions per week in the morning (AM, n = 18) or evening (PM, n = 15). The exercise program was 15 weeks and progressed from 70 to 80% heart rate maximum and 750-2000 kcal/week. Bodyweight, body composition, total daily energy expenditure (TDEE), energy intake (EI), sleep, sedentary behavior (SB), non-exercise physical activity (NEPA), and maximal aerobic capacity were assessed at baseline and week 15. Study retention was 94% and adherence to the supervised exercise program was ≥90% in both groups. Weight change was -0.9 ± 2.8 kg and -1.4 ± 2.3 kg in AM and PM, respectively. AM and PM increased TDEE (AM: 222 ± 399 kcal/day, PM: 90 ± 150 kcal/day). EI increased in AM (99 ± 198 kcal/day) and decreased in PM (-21 ± 156 kcal/day) across the intervention. It is feasible to randomize adults with overweight and obesity to morning or evening aerobic exercise with high levels of adherence. Future trials are needed to understand how the timing of exercise affects energy balance and body weight regulation.

The effects of the COVID-19 pandemic on weight loss in participants in a behavioral weight-loss intervention.

OBJECTIVE: This study aimed to assess the effects of the COVID-19 pandemic on weight loss, physical activity, and sleep in adults with overweight or obesity participating in a 39-week weight-loss intervention. METHODS: Participants (n = 81, 85% female, mean [SD] age 38.0 [7.8] years, BMI 34.1 [5.7] kg/m2 ) were enrolled in 3 separate cohorts. Cohorts 1 and 2 were studied prior to the pandemic (pre-COVID cohorts). Cohort 3 (COVID cohort) transitioned to a virtual intervention at week 6, when "stay-at-home" orders were implemented in Colorado. Weight was assessed at baseline, week 12, and week 39 with clinic scales before the pandemic and home scales during the pandemic. Diet was assessed with Likert scales at weeks 4, 8, and 12. Physical activity and sleep were assessed at baseline and week 12 with actigraphy. RESULTS: Participants in the COVID cohort reported greater dietary adherence (p = 0.004) and lost more weight than those in the pre-COVID cohorts at week 12 (-7.7 [3.3] kg vs. -3.7 [3.0] kg, p < 0.001) and week 39 (-8.5 [4.4] kg vs. -2.8 [4.6] kg, p < 0.001). Energy intake did not differ between cohorts (p = 0.51). The COVID cohort increased both sedentary time while awake and time in bed at night. CONCLUSIONS: Although the pandemic caused disruptions for the COVID cohort, participants still achieved weight loss with continued behavioral support.

Weight loss and cystic disease progression in autosomal dominant polycystic kidney disease.

Progression of autosomal dominant polycystic kidney disease (ADPKD) is modified by metabolic defects and obesity. Indeed, reduced food intake slows cyst growth in preclinical rodent studies. Here, we demonstrate the feasibility of daily caloric restriction (DCR) and intermittent fasting (IMF) in a cohort of overweight or obese patients with ADPKD. Clinically significant weight loss occurred with both DCR and IMF; however, weight loss was greater and adherence and tolerability were better with DCR. Further, slowed kidney growth correlated with body weight and visceral adiposity loss independent of dietary regimen. Similarly, we compared the therapeutic efficacy of DCR, IMF, and time restricted feeding (TRF) using an orthologous ADPKD mouse model. Only ADPKD animals on DCR lost significant weight and showed slowed cyst growth compared to ad libitum, IMF, or TRF feeding. Collectively, this supports therapeutic feasibility of caloric restriction in ADPKD, with potential efficacy benefits driven by weight loss.

Improving lifestyle obesity treatment during the COVID-19 pandemic and beyond: New challenges for weight management.

Objective: The COVID-19 pandemic has resulted in significant changes to daily life and many health-related behaviors. The objective of this study was to examine how the stay-at-home/safer-at-home mandates issued in Colorado (March 2020-May 2020) impacted lifestyle behaviors and mental health among individuals with overweight or obesity participating in two separate behavioral weight loss trials (n = 82). Methods: Questionnaires were used to collect qualitative and quantitative data on challenges to weight loss presented by the COVID-19 pandemic, including changes in dietary intake, physical activity, sedentary behavior, and mental health during the stay-at-home/safer-at-home mandates. Results: Using a convergent mixed method approach integrating qualitative and quantitative data, the greatest challenge experienced by participants was increased stress and anxiety, which led to more unhealthy behaviors. The majority perceived it to be harder to adhere to the prescribed diet (81%) and recommended physical activity (68%); however, self-reported exercise on weekdays increased significantly and 92% of participants lost weight or maintained weight within ±1% 5-6 weeks following the stay-at-home mandate. Conclusion: Study results suggest that obesity treatment programs should consider and attempt to address the burden of stress and anxiety stemming from the COVID-19 pandemic and other sources due to the negative effects they can have on weight management and associated behaviors.

Motivational profiles and change in physical activity during a weight loss intervention: a secondary data analysis.

BACKGROUND: High levels of moderate-to-vigorous intensity physical activity (MVPA) are strongly associated with sustained weight loss, however the majority of adults are unsuccessful in maintaining high levels of MVPA long-term. Our goal was to identify profiles based on exercise motives, and examine the association between motivational profile and longitudinal changes in MVPA during a weight loss intervention. METHODS: Adults with overweight or obesity (n = 169, mean ± SE; age 39 ± 0.7 years, BMI 34.4 ± 0.3 kg/m2, 83% female) underwent an 18-month behavioral weight loss program, including 6 months of supervised exercise, followed by 6 months of unsupervised exercise. Participants self-reported behavioral regulations for exercise at baseline (BREQ-2). Latent profile analysis identified subgroups from external, introjected, identified, and intrinsic regulations measured at baseline. Mean differences in device-measured total MVPA were compared across motivational profiles at baseline, after 6 months of supervised exercise and after a subsequent 6 months of unsupervised exercise. RESULTS: Three motivational profiles emerged: high autonomous (high identified and intrinsic, low external regulations; n = 52), high combined (high scores on all exercise regulations; n = 25), and moderate combined (moderate scores on all exercise regulations; n = 92). Motivational profile was not associated with baseline level of MVPA or the increase in MVPA over the 6-month supervised exercise intervention (high autonomous: 21 ± 6 min/d; high combined: 20 ± 9 min/d; moderate combined: 33 ± 5 min/d; overall P > 0.05). However, during the transition from supervised to unsupervised exercise, MVPA decreased, on average, within all three profiles, but the high autonomous profile demonstrated the least attenuation in MVPA (- 3 ± 6 min/d) compared to the moderate combined profile (- 20 ± 5 min/d; P = 0.043). CONCLUSIONS: Results were in alignment with the Self-Determination Theory. Adults motivated by autonomous reasons (value benefits of exercise, intrinsic enjoyment) may be more likely to sustain increases in MVPA once support is removed, whereas participants with moderate-to-high scores on all types of exercise regulations may need additional long-term support in order to sustain initial increases in MVPA. CLINICAL TRIAL REGISTRATION: NCT01985568. Registered 24 October 2013.

Predictors of long-term weight loss trajectories during a behavioral weight loss intervention: An exploratory analysis.

BACKGROUND: Substantial interindividual variability in response to behavioral weight loss interventions remains a critical challenge in obesity treatment. An improved understanding of the complex factors that contribute to this variability may improve obesity treatment outcomes. OBJECTIVE: To identify weight change trajectories during a behavioral weight loss intervention and to explore differences between trajectory groups in sociodemographic, biologic, behavioral, and psychosocial factors. METHODS: Adults (n = 170, 40 ± 9 years, BMI 34 ± 4 kg/m2, 84% female) participated in an 18-month behavioral weight loss intervention. Weight was measured at 0, 3, 6, 9, 12, 15, 18, and 24 months. Among participants with at least two weights after baseline (n = 140), clusters of longitudinal trajectories of changes in weight were identified using a latent class growth mixture model. The association between baseline factors or changes in factors over time and trajectory group was examined. RESULTS: Two weight change trajectories were identified: "weight regainers" (n = 91) and "weight loss maintainers" (n = 49). Black participants (90%, 19/21) were more likely than non-Black participants to be regainers versus maintainers (p < 0.01). Maintainers demonstrated greater increases in device-measured physical activity, autonomous motivation for exercise, diet self-efficacy, cognitive restraint, and engagement in weight management behaviors and greater reductions in barriers for exercise, disinhibition, and depressive symptoms over 24 months versus regainers (p < 0.05). CONCLUSION: Maintainers and regainers appear to be distinct trajectories that are associated with specific sociodemographic, behavioral, and psychosocial factors. Study results suggest potential targets for more tailored, multifaceted interventions to improve obesity treatment outcomes.