Obesity and its associated complications have reached epidemic proportions in the USA and also worldwide, highlighting the need for new and more effective treatments. Although the neuropeptide ...oxytocin (OXT) is well recognised for its peripheral effects on reproductive behaviour, the release of OXT from somatodendrites and axonal terminals within the central nervous system (CNS) is also implicated in the control of energy balance. In this review, we summarise historical data highlighting the effects of exogenous OXT as a short‐term regulator of food intake in a context‐specific manner and the receptor populations that may mediate these effects. We also describe what is known about the physiological role of endogenous OXT in the control of energy balance and whether serum and brain levels of OXT relate to obesity on a consistent basis across animal models and humans with obesity. We describe recent data on the effectiveness of chronic CNS administration of OXT to decrease food intake and weight gain or to elicit weight loss in diet‐induced obese (DIO) and genetically obese mice and rats. Of clinical importance is the finding that chronic central and peripheral OXT treatments both evoke weight loss in obese animal models with impaired leptin signalling at doses that are not associated with visceral illness, tachyphylaxis or adverse cardiovascular effects. Moreover, these results have been largely recapitulated following chronic s.c. or intranasal treatment in DIO non‐human primates (rhesus monkeys) and obese humans, respectively. We also identify plausible mechanisms that contribute to the effects of OXT on body weight and glucose homeostasis in rodents, non‐human primates and humans. We conclude by describing the ongoing challenges that remain before OXT‐based therapeutics can be used as a long‐term strategy to treat obesity in humans.
The worldwide obesity epidemic
makes it important to understand how lipid turnover (the capacity to store and remove lipids) regulates adipose tissue mass. Cross-sectional studies have shown that ...excess body fat is associated with decreased adipose lipid removal rates
. Whether lipid turnover is constant over the life span or changes during long-term weight increase or loss is unknown. We determined the turnover of fat cell lipids in adults followed for up to 16 years, by measuring the incorporation of nuclear bomb test-derived
C in adipose tissue triglycerides. Lipid removal rate decreases during aging, with a failure to reciprocally adjust the rate of lipid uptake resulting in weight gain. Substantial weight loss is not driven by changes in lipid removal but by the rate of lipid uptake in adipose tissue. Furthermore, individuals with a low baseline lipid removal rate are more likely to remain weight-stable after weight loss. Therefore, lipid turnover adaptation might be important for maintaining pronounced weight loss. Together these findings identify adipose lipid turnover as an important factor for the long-term development of overweight/obesity and weight loss maintenance in humans.
AbstractObjectiveTo investigate the association between weight changes across adulthood and mortality.DesignProspective cohort study.SettingUS National Health and Nutrition Examination Survey ...(NHANES) 1988-94 and 1999-2014.Participants36 051 people aged 40 years or over with measured body weight and height at baseline and recalled weight at young adulthood (25 years old) and middle adulthood (10 years before baseline).Main outcome measuresAll cause and cause specific mortality from baseline until 31 December 2015.ResultsDuring a mean follow-up of 12.3 years, 10 500 deaths occurred. Compared with participants who remained at normal weight, those moving from the non-obese to obese category between young and middle adulthood had a 22% (hazard ratio 1.22, 95% confidence interval 1.11 to 1.33) and 49% (1.49, 1.21 to 1.83) higher risk of all cause mortality and heart disease mortality, respectively. Changing from obese to non-obese body mass index over this period was not significantly associated with mortality risk. An obese to non-obese weight change pattern from middle to late adulthood was associated with increased risk of all cause mortality (1.30, 1.16 to 1.45) and heart disease mortality (1.48, 1.14 to 1.92), whereas moving from the non-obese to obese category over this period was not significantly associated with mortality risk. Maintaining obesity across adulthood was consistently associated with increased risk of all cause mortality; the hazard ratio was 1.72 (1.52 to 1.95) from young to middle adulthood, 1.61 (1.41 to 1.84) from young to late adulthood, and 1.20 (1.09 to 1.32) from middle to late adulthood. Maximum overweight had a very modest or null association with mortality across adulthood. No significant associations were found between various weight change patterns and cancer mortality.ConclusionsStable obesity across adulthood, weight gain from young to middle adulthood, and weight loss from middle to late adulthood were associated with increased risks of mortality. The findings imply that maintaining normal weight across adulthood, especially preventing weight gain in early adulthood, is important for preventing premature deaths in later life.
Since December 2019, coronavirus disease 2019 (COVID-19) has been spreading steadily, resulting in overwhelmed health-care systems and numerous deaths worldwide. To counter these outcomes, many ...countries, including France, put in place strict lockdown measures, requiring the temporary closure of all but essential places and causing an unprecedented disruption of daily life.
Our objective was to explore potential changes in dietary intake, physical activity, body weight, and food supply during the COVID-19 lockdown and how these differed according to individual characteristics.
The analyses included 37,252 adults from the French web-based NutriNet-Santé cohort who completed lockdown-specific questionnaires in April–May 2020. Nutrition-related changes and their sociodemographic, lifestyle, and health-status correlates were investigated using multivariable logistic regression models. Clusters of participants were defined using an ascending hierarchical classification of change profiles derived from multiple correspondence analyses.
During the lockdown, trends of unfavorable changes were observed: decreased physical activity (reported by 53% of the participants), increased sedentary time (reported by 63%), increased snacking, decreased consumption of fresh food (especially fruit and fish), and increased consumption of sweets, cookies, and cakes. Yet, the opposite trends were also observed: increased home cooking (reported by 40%) and increased physical activity (reported by 19%). Additionally, 35% of the participants gained weight (mean weight gain in these individuals, 1.8 kg ± SD 1.3 kg) and 23% lost weight (2 kg ± SD 1.4 kg weight loss). All of these trends displayed associations with various individual characteristics.
These results suggest that nutrition-related changes occurred during the lockdown in both unfavorable and favorable directions. The observed unfavorable changes should be considered in the event of a future lockdown, and should also be monitored to prevent an increase in the nutrition-related burden of disease, should these diet/physical activity changes be maintained in the long run. Understanding the favorable changes may help extend them on a broader scale. This trial was registered at clinicaltrials.gov as NCT03335644.
Both low and high gestational weight gain have been associated with adverse maternal and infant outcomes, but optimal gestational weight gain remains uncertain and not well defined for all ...prepregnancy weight ranges.
To examine the association of ranges of gestational weight gain with risk of adverse maternal and infant outcomes and estimate optimal gestational weight gain ranges across prepregnancy body mass index categories.
Individual participant-level meta-analysis using data from 196 670 participants within 25 cohort studies from Europe and North America (main study sample). Optimal gestational weight gain ranges were estimated for each prepregnancy body mass index (BMI) category by selecting the range of gestational weight gain that was associated with lower risk for any adverse outcome. Individual participant-level data from 3505 participants within 4 separate hospital-based cohorts were used as a validation sample. Data were collected between 1989 and 2015. The final date of follow-up was December 2015.
Gestational weight gain.
The main outcome termed any adverse outcome was defined as the presence of 1 or more of the following outcomes: preeclampsia, gestational hypertension, gestational diabetes, cesarean delivery, preterm birth, and small or large size for gestational age at birth.
Of the 196 670 women (median age, 30.0 years quartile 1 and 3, 27.0 and 33.0 years and 40 937 were white) included in the main sample, 7809 (4.0%) were categorized at baseline as underweight (BMI <18.5); 133 788 (68.0%), normal weight (BMI, 18.5-24.9); 38 828 (19.7%), overweight (BMI, 25.0-29.9); 11 992 (6.1%), obesity grade 1 (BMI, 30.0-34.9); 3284 (1.7%), obesity grade 2 (BMI, 35.0-39.9); and 969 (0.5%), obesity grade 3 (BMI, ≥40.0). Overall, any adverse outcome occurred in 37.2% (n = 73 161) of women, ranging from 34.7% (2706 of 7809) among women categorized as underweight to 61.1% (592 of 969) among women categorized as obesity grade 3. Optimal gestational weight gain ranges were 14.0 kg to less than 16.0 kg for women categorized as underweight; 10.0 kg to less than 18.0 kg for normal weight; 2.0 kg to less than 16.0 kg for overweight; 2.0 kg to less than 6.0 kg for obesity grade 1; weight loss or gain of 0 kg to less than 4.0 kg for obesity grade 2; and weight gain of 0 kg to less than 6.0 kg for obesity grade 3. These gestational weight gain ranges were associated with low to moderate discrimination between those with and those without adverse outcomes (range for area under the receiver operating characteristic curve, 0.55-0.76). Results for discriminative performance in the validation sample were similar to the corresponding results in the main study sample (range for area under the receiver operating characteristic curve, 0.51-0.79).
In this meta-analysis of pooled individual participant data from 25 cohort studies, the risk for adverse maternal and infant outcomes varied by gestational weight gain and across the range of prepregnancy weights. The estimates of optimal gestational weight gain may inform prenatal counseling; however, the optimal gestational weight gain ranges had limited predictive value for the outcomes assessed.
Phase 3 trials have not compared semaglutide and liraglutide, glucagon-like peptide-1 analogues available for weight management.
To compare the efficacy and adverse event profiles of once-weekly ...subcutaneous semaglutide, 2.4 mg, vs once-daily subcutaneous liraglutide, 3.0 mg (both with diet and physical activity), in people with overweight or obesity.
Randomized, open-label, 68-week, phase 3b trial conducted at 19 US sites from September 2019 (enrollment: September 11-November 26) to May 2021 (end of follow-up: May 11) in adults with body mass index of 30 or greater or 27 or greater with 1 or more weight-related comorbidities, without diabetes (N = 338).
Participants were randomized (3:1:3:1) to receive once-weekly subcutaneous semaglutide, 2.4 mg (16-week escalation; n = 126), or matching placebo, or once-daily subcutaneous liraglutide, 3.0 mg (4-week escalation; n = 127), or matching placebo, plus diet and physical activity. Participants unable to tolerate 2.4 mg of semaglutide could receive 1.7 mg; participants unable to tolerate 3.0 mg of liraglutide discontinued treatment and could restart the 4-week titration. Placebo groups were pooled (n = 85).
The primary end point was percentage change in body weight, and confirmatory secondary end points were achievement of 10% or more, 15% or more, and 20% or more weight loss, assessed for semaglutide vs liraglutide at week 68. Semaglutide vs liraglutide comparisons were open-label, with active treatment groups double-blinded against matched placebo groups. Comparisons of active treatments vs pooled placebo were supportive secondary end points.
Of 338 randomized participants (mean SD age, 49 13 years; 265 women 78.4%; mean SD body weight, 104.5 23.8 kg; mean SD body mass index, 37.5 6.8), 319 (94.4%) completed the trial, and 271 (80.2%) completed treatment. The mean weight change from baseline was -15.8% with semaglutide vs -6.4% with liraglutide (difference, -9.4 percentage points 95% CI, -12.0 to -6.8; P < .001); weight change with pooled placebo was -1.9%. Participants had significantly greater odds of achieving 10% or more, 15% or more, and 20% or more weight loss with semaglutide vs liraglutide (70.9% of participants vs 25.6% odds ratio, 6.3 {95% CI, 3.5 to 11.2}, 55.6% vs 12.0% odds ratio, 7.9 {95% CI, 4.1 to 15.4}, and 38.5% vs 6.0% odds ratio, 8.2 {95% CI, 3.5 to 19.1}, respectively; all P < .001). Proportions of participants discontinuing treatment for any reason were 13.5% with semaglutide and 27.6% with liraglutide. Gastrointestinal adverse events were reported by 84.1% with semaglutide and 82.7% with liraglutide.
Among adults with overweight or obesity without diabetes, once-weekly subcutaneous semaglutide compared with once-daily subcutaneous liraglutide, added to counseling for diet and physical activity, resulted in significantly greater weight loss at 68 weeks.
ClinicalTrials.gov Identifier: NCT04074161.
Artificial sweeteners have been widely used in the modern diet, and their observed effects on human health have been inconsistent, with both beneficial and adverse outcomes reported. Obesity and type ...2 diabetes have dramatically increased in the U.S. and other countries over the last two decades. Numerous studies have indicated an important role of the gut microbiome in body weight control and glucose metabolism and regulation. Interestingly, the artificial sweetener saccharin could alter gut microbiota and induce glucose intolerance, raising questions about the contribution of artificial sweeteners to the global epidemic of obesity and diabetes. Acesulfame-potassium (Ace-K), a FDA-approved artificial sweetener, is commonly used, but its toxicity data reported to date are considered inadequate. In particular, the functional impact of Ace-K on the gut microbiome is largely unknown. In this study, we explored the effects of Ace-K on the gut microbiome and the changes in fecal metabolic profiles using 16S rRNA sequencing and gas chromatography-mass spectrometry (GC-MS) metabolomics. We found that Ace-K consumption perturbed the gut microbiome of CD-1 mice after a 4-week treatment. The observed body weight gain, shifts in the gut bacterial community composition, enrichment of functional bacterial genes related to energy metabolism, and fecal metabolomic changes were highly gender-specific, with differential effects observed for males and females. In particular, ace-K increased body weight gain of male but not female mice. Collectively, our results may provide a novel understanding of the interaction between artificial sweeteners and the gut microbiome, as well as the potential role of this interaction in the development of obesity and the associated chronic inflammation.
Long-term efficacy and safety of once-weekly insulin icodec (icodec) vs insulin glargine U100 (IGlar), both with non-insulin glucose-lowering agents, including SGLT2i and GLP‑1 RA, were assessed in ...this randomized, open-label, treat-to-target phase 3a trial (52-week + 26-week extension) in insulin-naïve adults with T2D (NCT04460885). Participants (n=984) were randomized 1:1 to icodec or IGlar. Prespecified primary analysis at week 52 showed A1C reduction from a baseline (BL) of 8.5% to 6.9% with icodec vs 8.4% to 7.1% with IGlar (estimated treatment difference ETD: −0.19%-points 95% CI: −0.36, −0.03), confirming non‑inferiority (p<0.0001) and superiority (p=0.0210) of icodec. Time spent in target glycemic range (TIR, from week 48-52) was significantly improved to 72% (icodec) vs 67% (IGlar), confirming superiority; ETD 4.27%-points (95% CI: 1.92; 6.62, p=0.0004). There were no significant differences in mean weekly insulin dose (week 50-52), or in body weight change from BL. Level 2 or 3 hypoglycemia rates (BL to week 52) were low in both groups, with numerically higher rates with icodec. A higher proportion achieved A1C <7% without level 2 or 3 hypoglycemia with icodec vs IGlar (52.6% vs 42.6%, p=0.0028). In totality, glycemic control (A1C, TIR, A1C <7% without hypoglycemia) was significantly improved by once-weekly icodec vs daily glargine U100 with low rates of hypoglycemia in both arms.
Disclosure
J.Rosenstock: Advisory Panel; Applied Therapeutics Inc., Boehringer Ingelheim Inc., Eli Lilly and Company, Novo Nordisk, Oramed Pharmaceuticals, Sanofi, Zealand Pharma A/S, Intarcia Therapeutics, Inc., Hanmi Pharm. Co., Ltd., Research Support; Applied Therapeutics Inc., Boehringer Ingelheim Inc., Eli Lilly and Company, Merck & Co., Inc., Novartis, Novo Nordisk, Pfizer Inc., Sanofi, Intarcia Therapeutics, Inc. S.C.Bain: Advisory Panel; Novo Nordisk, Sanofi, Lilly, Boehringer Ingelheim Inc., AstraZeneca. A.Gowda: Employee; Novo Nordisk A/S. H.Horio: Employee; Novo Nordisk. E.Jodar: Other Relationship; Amgen Inc., AstraZeneca, Eli Lilly and Company, FAES, Novo Nordisk, UCB, Inc., Speaker's Bureau; Merck & Co., Inc., Asofarma, ZP Pharmaceuticals. L.Lang lehrskov: Employee; Novo Nordisk A/S, Stock/Shareholder; Novo Nordisk A/S. I.Lingvay: Advisory Panel; Novo Nordisk A/S, Lilly Diabetes, Boehringer-Ingelheim, Sanofi, Consultant; Carmot Therapeutics, Inc., Merck Sharp & Dohme Corp., Janssen Scientific Affairs, LLC, Pfizer Inc., Intercept, Intarcia, Valeritas, TargetRWE, Shionogi, Zealand Pharma, Structure, Bayer, Research Support; Novo Nordisk A/S, Boehringer-Ingelheim. R.Trevisan: Advisory Panel; Novo Nordisk, AstraZeneca, Eli Lilly and Company, Other Relationship; Boehringer Ingelheim Inc., Sanofi. O.Mosenzon: Advisory Panel; Novo Nordisk, AstraZeneca, Boehringer-Ingelheim, Bayer Inc., Employee; BOL Pharma, Research Support; Novo Nordisk, AstraZeneca, Boehringer-Ingelheim, Speaker's Bureau; Novo Nordisk, AstraZeneca, Boehringer-Ingelheim, Eli Lilly and Company, Merck Sharp & Dohme Corp., Sanofi.
Funding
Novo Nordisk A/S
It is currently unknown what factor(s) may promote entry into a weight loss plateau. Given intensive lifestyle interventions (ILI) for weight loss include changes in diet, we evaluated how diet ...quality impacts characteristics of a weight loss plateau. Daily weights were obtained remotely via electronic scale from 62 adults with obesity (73% female, mean age 42±11 y and BMI 37±5 kg/m2) undergoing a 24-week ILI. Periods (≥14 d) of active weight loss or plateau were identified by threshold regression modeling. Active weight loss was defined as a per day % weight change from baseline equivalent to ≥0.5 lb loss/wk and a weight loss plateau as ±0.25lbs/wk after a period of active weight loss (in which ≥3.5% weight loss was achieved). Three unannounced self-reported ASA24 dietary recalls were obtained at baseline and 3 mo. Diet quality was assessed by the healthy eating index (HEI)-2015. 53% reached a plateau after active weight loss (27% did not achieve >3.5% weight loss, 19% re-gained directly after loss). Weight loss (i.e., plateau depth) was associated with longer time to plateau (β=–10d, P<0.01). Higher baseline diet quality (total HEI) was associated with shorter time to plateau (β=–2.6d, P=0.03), but not overall depth of plateau (β=0.1%, P=0.28). Specifically, shorter time to plateau was related to lower baseline consumption of saturated fats (β=–15d, P=0.01) and greater plateau depth was related to lower baseline consumption of added sugars (β=1.3%, P=0.04). Mean diet quality improved minimally during ILI (ΔHEI 1.9±2.2). Lower baseline HEI correlated with greater improvement in diet quality at 3 mo (β=–0.5, P<0.001, N=46), but ΔHEI did not associate with any plateau characteristics (time: β=1.1d, P=0.15; depth: β=–0.1%, P=0.16, N=25). Higher diet quality upon entry into an ILI predicted a shorter duration of weight loss prior to reaching a plateau, suggesting that individuals with healthy eating patterns may derive less sustained weight loss benefit from participation in an ILI.
Disclosure
S.J.Melhorn: None. L.E.Sewaybricker: None. H.Gao: None. M.De leon: None. M.Webb: None. M.Lyle: None. S.J.Beatty: None. M.Kratz: Other Relationship; Nourished by Science LLC. E.Schur: None.
Funding
National Institutes of Health (DK089036, DK1176223, K24HL144917); University of Washington (NORC, DK035816)
People with obesity may seek clinical, nutritional, activity, and psychosocial guidance, but recommendations they receive in clinical settings may be inadequate or lack sufficient personalization to ...be implemented into their lives. Understanding unmet information needs may enable more tailored weight guidance. We used health narratives posted in a weight loss forum to research topics of information being sought. Public posts (N=52,576) from 1/2020-1/2022 were extracted from r/LoseIt, a Reddit weight loss forum of 3.8M members. From these, 63,006 questions were extracted using a research-purpose BERT language model tested and fine-tuned on 500 hand-annotated questions. Extracted questions were clustered into distinct topics by Top2Vec and hierarchical clustering. Excluding 2 uninterpretable topics, 27 of 28 (96%) topics represented requests for personalized recommendations. Topics focused on diet (7%), exercise (7%), sensemaking (11%), how to implement a behavior change or solve a weight-loss problem (11%), tips for specific stages of weight loss (beginning, plateau) (7%), and comparing weight loss experiences (11%). Weight-loss forum users requested personalized recommendations to support sensemaking of frustrating weight loss problems and ask for help choosing and deploying behavior change. Results call for interventions customized to individuals’ weight loss stage, process, experiences, and motivations.
Disclosure
C.Clark: Employee; UnitedHealth Group, Stock/Shareholder; UnitedHealth Group. J.Stremmel: None. R.G.Mccoy: Consultant; Emmi. M.Jarvis: Employee; Optum Labs, UnitedHealth Group, Stock/Shareholder; Oramed Pharmaceuticals, UnitedHealth Group, Dexcom, Inc., Apple, Hologic Inc., Intuitive Surgical. J.D.Ard: Advisory Panel; Novo Nordisk, Consultant; Eli Lilly and Company, Intuitive Surgical, Regeneron, Other Relationship; Optum Labs, Weight Watchers International, Research Support; Nestlé Health Science, Boehringer Ingelheim Inc., Epitomee, KVK Tech. N.Lambert: Employee; Optum Labs.
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