Summary Background The frequency of obesity has risen dramatically in recent years but only few safe and effective drugs are currently available. We assessed the effect of liraglutide on bodyweight ...and tolerability in obese individuals without type 2 diabetes. Methods We did a double-blind, placebo-controlled 20-week trial, with open-label orlistat comparator in 19 sites in Europe. 564 individuals (18–65 years of age, body-mass index 30–40 kg/m2 ) were randomly assigned, with a telephone or web-based system, to one of four liraglutide doses (1·2 mg, 1·8 mg, 2·4 mg, or 3·0 mg, n=90–95) or to placebo (n=98) administered once a day subcutaneously, or orlistat (120 mg, n=95) three times a day orally. All individuals had a 500 kcal per day energy-deficit diet and increased their physical activity throughout the trial, including the 2-week run-in. Weight change analysed by intention to treat was the primary endpoint. An 84-week open-label extension followed. This study is registered with ClinicalTrials.gov , number NCT00422058. Findings Participants on liraglutide lost significantly more weight than did those on placebo (p=0·003 for liraglutide 1·2 mg and p<0·0001 for liraglutide 1·8–3·0 mg) and orlistat (p=0·003 for liraglutide 2·4 mg and p<0·0001 for liraglutide 3·0 mg). Mean weight loss with liraglutide 1·2–3·0 mg was 4·8 kg, 5·5 kg, 6·3 kg, and 7·2 kg compared with 2·8 kg with placebo and 4·1 kg with orlistat, and was 2·1 kg (95% CI 0·6–3·6) to 4·4 kg (2·9–6·0) greater than that with placebo. More individuals (76%, n=70) lost more than 5% weight with liraglutide 3·0 mg that with placebo (30%, n=29) or orlistat (44%, n=42). Liraglutide reduced blood pressure at all doses, and reduced the prevalence of prediabetes (84–96% reduction) with 1·8–3·0 mg per day. Nausea and vomiting occurred more often in individuals on liraglutide than in those on placebo, but adverse events were mainly transient and rarely led to discontinuation of treatment. Interpretation Liraglutide treatment over 20 weeks is well tolerated, induces weight loss, improves certain obesity-related risk factors, and reduces prediabetes. Funding Novo Nordisk A/S, Bagsvaerd, Denmark.
Background: Muscle mass reflects and influences health status. Its reliable estimation would be of value for epidemiology.Objective: The aim of the study was to derive and validate anthropometric ...prediction equations to quantify whole-body skeletal muscle mass (SM) in adults.Design: The derivation sample included 423 subjects (227 women) aged 18–81 y with a body mass index (BMI; in kg/m2) of 15.9–40.8. The validation sample included 197 subjects (105 women) aged 19–83 y with a BMI of 15.7–36.4. Both samples were of mixed ethnic/racial groups. All underwent whole-body magnetic resonance imaging to quantify SM (dependent variable for multiple regressions) and anthropometric variables (independent variables).Results: Two prediction equations with high practicality and optimal derivation correlations with SM were further investigated to assess agreement and bias by using Bland-Altman plots and validated in separate data sets. Including race as a variable increased R2 by only 0.1% in men and by 8% in women. For men: SM (kg) = 39.5 + 0.665 body weight (BW; kg) − 0.185 waist circumference (cm) − 0.418 hip circumference (cm) − 0.08 age (y) (derivation: R2 = 0.76, SEE = 2.7 kg; validation: R2 = 0.79, SEE = 2.7 kg). Bland-Altman plots showed moderate agreement in both derivation and validation analyses. For women: SM (kg) = 2.89 + 0.255 BW (kg) − 0.175 hip circumference (cm) − 0.038 age (y) + 0.118 height (cm) (derivation: R2 = 0.58, SEE = 2.2 kg; validation: R2 = 0.59, SEE = 2.1 kg). Bland-Altman plots had a negative slope, indicating a tendency to overestimate SM among women with smaller muscle mass and to underestimate SM among those with larger muscle mass.Conclusions: Anthropometry predicts SM better in men than in women. Equations that include hip circumference showed agreement between methods, with predictive power similar to that of BMI to predict fat mass, with the potential for applications in groups, as well as epidemiology and survey settings.
Abstract Calorie-labelling has been suggested as an anti-obesity measure but evidence on its impact is scarce and formatting guidance not well-defined. This study tested the impact of prominent ...calorie-labelling on sales of the labelled items. Prominent calorie labels were posted in front of two popular items for a period of a month. Sales were recorded for two consecutive months, prior to and during labelling. Muffins sales (the higher calorie-item) fell by 30% while sales of scones rose by 4%, a significant difference (X2 = 10.258, p=0.0014). Calorie-labelling is effective when noticed. Wider-adoption of calorie-labelling for all food-business and strengthening legislation with formatting guidelines should be the next step in public health policy.
Type 2 diabetes is a chronic disorder that requires lifelong treatment. We aimed to assess whether intensive weight management within routine primary care would achieve remission of type 2 diabetes.
...We did this open-label, cluster-randomised trial (DiRECT) at 49 primary care practices in Scotland and the Tyneside region of England. Practices were randomly assigned (1:1), via a computer-generated list, to provide either a weight management programme (intervention) or best-practice care by guidelines (control), with stratification for study site (Tyneside or Scotland) and practice list size (>5700 or ≤5700). Participants, carers, and research assistants who collected outcome data were aware of group allocation; however, allocation was concealed from the study statistician. We recruited individuals aged 20–65 years who had been diagnosed with type 2 diabetes within the past 6 years, had a body-mass index of 27–45 kg/m2, and were not receiving insulin. The intervention comprised withdrawal of antidiabetic and antihypertensive drugs, total diet replacement (825–853 kcal/day formula diet for 3–5 months), stepped food reintroduction (2–8 weeks), and structured support for long-term weight loss maintenance. Co-primary outcomes were weight loss of 15 kg or more, and remission of diabetes, defined as glycated haemoglobin (HbA1c) of less than 6·5% (<48 mmol/mol) after at least 2 months off all antidiabetic medications, from baseline to 12 months. These outcomes were analysed hierarchically. This trial is registered with the ISRCTN registry, number 03267836.
Between July 25, 2014, and Aug 5, 2017, we recruited 306 individuals from 49 intervention (n=23) and control (n=26) general practices; 149 participants per group comprised the intention-to-treat population. At 12 months, we recorded weight loss of 15 kg or more in 36 (24%) participants in the intervention group and no participants in the control group (p<0·0001). Diabetes remission was achieved in 68 (46%) participants in the intervention group and six (4%) participants in the control group (odds ratio 19·7, 95% CI 7·8–49·8; p<0·0001). Remission varied with weight loss in the whole study population, with achievement in none of 76 participants who gained weight, six (7%) of 89 participants who maintained 0–5 kg weight loss, 19 (34%) of 56 participants with 5–10 kg loss, 16 (57%) of 28 participants with 10–15 kg loss, and 31 (86%) of 36 participants who lost 15 kg or more. Mean bodyweight fell by 10·0 kg (SD 8·0) in the intervention group and 1·0 kg (3·7) in the control group (adjusted difference −8·8 kg, 95% CI −10·3 to −7·3; p<0·0001). Quality of life, as measured by the EuroQol 5 Dimensions visual analogue scale, improved by 7·2 points (SD 21·3) in the intervention group, and decreased by 2·9 points (15·5) in the control group (adjusted difference 6·4 points, 95% CI 2·5–10·3; p=0·0012). Nine serious adverse events were reported by seven (4%) of 157 participants in the intervention group and two were reported by two (1%) participants in the control group. Two serious adverse events (biliary colic and abdominal pain), occurring in the same participant, were deemed potentially related to the intervention. No serious adverse events led to withdrawal from the study.
Our findings show that, at 12 months, almost half of participants achieved remission to a non-diabetic state and off antidiabetic drugs. Remission of type 2 diabetes is a practical target for primary care.
Diabetes UK.
Fear of weight gain is a barrier to smoking cessation and significant cause of relapse for many people. The provision of nutritional advice as part of a smoking cessation programme may assist some in ...smoking cessation and perhaps limit weight gain. The aim of this study was to determine the effect of a structured programme of dietary advice on weight change and food choice, in adults attempting smoking cessation.
Cluster randomised controlled design. Classes randomised to intervention commenced a 24-week intervention, focussed on improving food choice and minimising weight gain. Classes randomised to control received "usual care".
Twenty-seven classes in Greater Glasgow were randomised between January and August 2008. Analysis, including those who continued to smoke, showed that actual weight gain and percentage weight gain was similar in both groups. Examination of data for those successful at giving up smoking showed greater mean weight gain in intervention subjects (3.9 (SD 3.1) vs. 2.7 (SD 3.7) kg). Between group differences were not significant (p = 0.23, 95% CI -0.9 to 3.5). In comparison to baseline improved consumption of fruit and vegetables and breakfast cereal were reported in the intervention group. A higher percentage of control participants continued smoking (74% vs. 66%).
The intervention was not successful at minimising weight gain in comparison to control but was successful in facilitating some sustained improvements in the dietary habits of intervention participants. Improved quit rates in the intervention group suggest that continued contact with advisors may have reduced anxieties regarding weight gain and encouraged cessation despite weight gain. Research should continue in this area as evidence suggests that the negative effects of obesity could outweigh the health benefits achieved through reductions in smoking prevalence.
The association between aging-related testosterone deficiency and late-onset hypogonadism in men remains a controversial concept. We sought evidence-based criteria for identifying late-onset ...hypogonadism in the general population on the basis of an association between symptoms and a low testosterone level.
We surveyed a random population sample of 3369 men between the ages of 40 and 79 years at eight European centers. Using questionnaires, we collected data with regard to the subjects' general, sexual, physical, and psychological health. Levels of total testosterone were measured in morning blood samples by mass spectrometry, and free testosterone levels were calculated with the use of Vermeulen's formula. Data were randomly split into separate training and validation sets for confirmatory analyses.
In the training set, symptoms of poor morning erection, low sexual desire, erectile dysfunction, inability to perform vigorous activity, depression, and fatigue were significantly related to the testosterone level. Increased probabilities of the three sexual symptoms and limited physical vigor were discernible with decreased testosterone levels (ranges, 8.0 to 13.0 nmol per liter 2.3 to 3.7 ng per milliliter for total testosterone and 160 to 280 pmol per liter 46 to 81 pg per milliliter for free testosterone). However, only the three sexual symptoms had a syndromic association with decreased testosterone levels. An inverse relationship between an increasing number of sexual symptoms and a decreasing testosterone level was observed. These relationships were independently confirmed in the validation set, in which the strengths of the association between symptoms and low testosterone levels determined the minimum criteria necessary to identify late-onset hypogonadism.
Late-onset hypogonadism can be defined by the presence of at least three sexual symptoms associated with a total testosterone level of less than 11 nmol per liter (3.2 ng per milliliter) and a free testosterone level of less than 220 pmol per liter (64 pg per milliliter).
Background: We assessed the bioavailability of orange juice (poly)phenols by monitoring urinary flavanone metabolites and ring fission catabolites produced by the action of the colonic ...microbiota.Objective: Our objective was to identify and quantify metabolites and catabolites excreted in urine 0–24 h after the acute ingestion of a (poly)phenol-rich orange juice by 12 volunteers.Design: Twelve volunteers 6 men and 6 women; body mass index (in kg/m2): 23.9–37.2 consumed a low (poly)phenol diet for 2 d before first drinking 250 mL pulp-enriched orange juice, which contained 584 μmol (poly)phenols of which 537 μmol were flavanones, and after a 2-wk washout, the procedure was repeated, and a placebo drink was consumed. Urine collected for a 24-h period was analyzed qualitatively and quantitatively by using high-performance liquid chromatography–mass spectrometry (HPLC-MS) and gas chromatography–mass spectrometry (GC-MS).Results: A total of 14 metabolites were identified and quantified in urine by using HPLC-MS after orange juice intake. Hesperetin-O-glucuronides, naringenin-O-glucuronides, and hesperetin-3′-O-sulfate were the main metabolites. The overall urinary excretion of flavanone metabolites corresponded to 16% of the intake of 584 μmol (poly)phenols. The GC-MS analysis revealed that 8 urinary catabolites were also excreted in significantly higher quantities after orange juice consumption. These catabolites were 3-(3′-methoxy-4′-hydroxyphenyl)propionic acid, 3-(3′-hydroxy-4′-methoxyphenyl)propionic acid, 3-(3′-hydroxy-4′-methoxyphenyl)hydracrylic acid, 3-(3′-hydroxyphenyl)hydracrylic acid, 3′-methoxy-4′-hydroxyphenylacetic acid, hippuric acid, 3′-hydroxyhippuric acid, and 4′-hydroxyhippuric acid. These aromatic acids originated from the colonic microbiota-mediated breakdown of orange juice (poly)phenols and were excreted in amounts equivalent to 88% of (poly)phenol intake. When combined with the 16% excretion of metabolites, this percentage raised the overall urinary excretion to ∼100% of intake.Conclusions: When colon-derived phenolic catabolites are included with flavanone glucuronide and sulfate metabolites, orange juice (poly)phenols are much-more bioavailable than previously envisaged. In vitro and ex vivo studies on mechanisms underlying the potential protective effects of orange juice consumption should use in vivo metabolites and catabolites detected in this investigation at physiologic concentrations. The trial was registered at BioMed Central Ltd (www.controlledtrials.com) as ISRCTN04271658.
To assess functional β-cell capacity in type 2 diabetes during 2 years of remission induced by dietary weight loss.
A Stepped Insulin Secretion Test with Arginine was used to quantify functional ...β-cell capacity by hyperglycemia and arginine stimulation. Thirty-nine of 57 participants initially achieved remission (HbA
<6.5% <48 mmol/mol and fasting plasma glucose <7 mmol/L on no antidiabetic drug therapy) with a 16.4 ± 7.7 kg weight loss and were followed up with supportive advice on avoidance of weight regain. At 2 years, 20 participants remained in remission in the study. A nondiabetic control (NDC) group, matched for age, sex, and weight after weight loss with the intervention group, was studied once.
During remission, median (interquartile range) maximal rate of insulin secretion increased from 581 (480-811) pmol/min/m
at baseline to 736 (542-998) pmol/min/m
at 5 months, 942 (565-1,240) pmol/min/m
at 12 months (
= 0.028 from baseline), and 936 (635-1,435) pmol/min/m
at 24 months (
= 0.023 from baseline;
= 20 of 39 of those initially in remission). This was comparable to the NDC group (1,016 857-1,507 pmol/min/m
) by 12 (
= 0.064) and 24 (
= 0.244) months. Median first-phase insulin response increased from baseline to 5 months (42 4-67 to 107 59-163 pmol/min/m
;
< 0.0001) and then remained stable at 12 and 24 months (110 59-201 and 125 65-166 pmol/min/m
, respectively;
< 0.0001 vs. baseline) but lower than that of the NDC group (250 226-429 pmol/min/m
;
< 0.0001).
A gradual increase in assessed functional β-cell capacity occurred after weight loss, becoming similar to that of NDC group participants by 12 months. This result was unchanged at 2 years with continuing remission of type 2 diabetes.
Summary
A systematic review of published evidence on micronutrient intake/status with carbohydrate‐restricted diets (CRD) was conducted in Web of Science, Medline, Embase, Scopus, CENTRAL, and ...ClinicalTrials.gov up to October 2018. We identified 10 studies: seven randomized controlled trials (RCTs) (“Atkins”‐style, n = 5; “Paleolithic” diets, n = 2), two Atkins‐style noncontrolled trials and one cross‐sectional study. Prescribed carbohydrate varied 4% to 34% of energy intake. Only one noncontrolled trial prescribed multivitamin supplements. Dietary intakes/status were reported over 2 to 104 weeks, with weight losses from 2 to 9 kg. No diagnoses of deficiency were reported. Intakes of thiamine, folate, magnesium, calcium, iron, and iodine all decreased significantly (−10% to −70% from baseline) with any CRD types. Atkins diet trials (n = 6; 4%‐34%E carbohydrate) showed inconsistent changes in vitamin A, E, and β‐carotene intakes, while a single “Paleolithic” diet trial (28%E carbohydrate) reported increases in these micronutrients. One other “Paleolithic” diet (30%E carbohydrate) reported a rise in moderate iodine deficiency from 15% to 73% after 6 months. In conclusion, few studies have assessed the impacts of CRD on micronutrients. Studies with different designs point towards reductions in several vitamins and minerals, with potential risk of micronutrient inadequacies. Trial reporting standards are expected to include analysis of micronutrient intake/status. Micronutrients in foods and/or supplements should be considered when designing, prescribing or following CRDs.
Purpose
Evidence of low-carbohydrate, high-fat diets (LCHF) for type 2 diabetes (T2DM) prevention is scarce. We investigated how carbohydrate intake relates to HbA1c and T2DM prevalence in a ...nationally representative survey dataset.
Methods
We analyzed dietary information (4-day food diaries) from 3234 individuals aged ≥ 16 years, in eight waves of the UK National Diet and Nutrition Survey (2008–2016). We calculated LCHF scores (0–20, higher score indicating lower %food energy from carbohydrate, with reciprocal higher contribution from fat) and UK Dietary Reference Value (DRV) scores (0–16, based on UK dietary recommendations). Associations between macronutrients and diet scores and diabetes prevalence were analyzed (in the whole sample) using multivariate logistic regression. Among those without diabetes, analyses between exposures and %HbA1c (continuous) were analyzed using multivariate linear regression. All analyses were adjusted for age, sex, body mass index, ethnicity, smoking status, total energy intake, socioeconomic status and survey years.
Results
In the overall study sample, 194 (6.0%) had diabetes. Mean intake was 48.0%E for carbohydrates, and 34.9%E for total fat. Every 5%E decrease in carbohydrate, and every 5%E increase in fat, was associated with 12% (95% CI 0.78–0.99;
P
=
0.03
) and 17% (95% CI 1.02–1.33;
P
= 0.02) higher odds of diabetes, respectively. Each two-point increase in LCHF score is related to 8% (95% CI 1.02–1.14;
P
= 0.006) higher odds of diabetes, while there was no evidence for association between DRV score and diabetes. Among the participants without diagnosed diabetes (
n
= 3130), every 5%E decrease in carbohydrate was associated with higher %HbA1c by + 0.016% (95% CI 0.004–0.029;
P
= 0.012), whereas every 5%E increase in fat was associated with higher %HbA1c by + 0.029% (95% CI 0.015–0.043;
P
< 0.001). Each two-point increase in LCHF score is related to higher %HbA1c by + 0.010% (0.1 mmol/mol), while each two-point increase in the DRV score is related to lower %HbA1c by − 0.023% (0.23 mmol/mol).
Conclusions
Lower carbohydrate and higher fat intakes were associated with higher HbA1c and greater odds of having diabetes. These data do not support low(er) carbohydrate diets for diabetes prevention.
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