Total Diet Replacement Within an Integrated Intensive Lifestyle Intervention for Remission of Type 2 Diabetes: Lessons From DiRECT

Low serum glycine strengthens the association between branched-chain amino acids and impaired insulin sensitivity assessed before and after weight loss in a population with pre-diabetes: The PREVIEW_NZ cohort

AIM

Accumulation of circulating branched-chain amino acids (BCAA) is a hallmark feature of impaired insulin sensitivity. As intracellular BCAA catabolism is dependent on glycine availability, we hypothesised that the concurrent measurement of circulating glycine and BCAA may yield a stronger association with markers of insulin sensitivity than either BCAA or glycine alone. This study therefore examined the correlative relationships of BCAA, BCAA and glycine together, plus glycine alone on insulin sensitivity-related markers before and after an 8-week low energy diet (LED) intervention.

METHODS

This is a secondary analysis of the PREVIEW (PREVention of diabetes through lifestyle Intervention and population studies in Europe and around the World) Study New Zealand sub-cohort. Eligible participants with pre-diabetes at baseline who achieved ≥8 % body weight loss following an LED intervention were included, of which 167 paired (Week 0 and Week 8) blood samples were available for amino acid analysis. Glycemic and other data were retrieved from the PREVIEW consortium database. Repeated measures linear mixed models were used to test the association between amino acids and insulin sensitivity-related markers (HOMA2-IR, glucose, insulin, and C-peptide).

RESULTS

Elevated BCAA was associated with impaired insulin sensitivity (p < 0.05), with strength of association (ηp2) almost doubled when glycine was added to the model. However, glycine in isolation was not associated with insulin sensitivity-related markers. The magnitude (β-estimates) of positive association between BCAA and HOMA2-IR, and inverse association between glycine and HOMA2-IR, increased when body weight was higher (Body weight∗BCAA, Body weight∗glycine, p < 0.05, both).

CONCLUSION

Low serum glycine strengthened the association between BCAA and impaired insulin sensitivity. Given that glycine is necessary to facilitate intracellular BCAA catabolism, measurement of glycine is necessary to complement BCAA analysis to comprehensively understand the contribution of amino acid metabolism in insulin sensitivity.

CLINICAL TRIAL REGISTRATION

This study was registered with ClinicalTrials.gov (NCT01777893).

Transferability of the NHS low-calorie diet programme: A qualitative exploration of factors influencing the programme's transfer ahead of wide-scale adoption

INTRODUCTION

Although behavioural interventions have been found to help control type 2 diabetes (T2D), it is important to understand how the delivery context can influence implementation and outcomes. The NHS committed to testing a low-calorie diet (LCD) programme designed to support people living with excess weight and T2D to lose weight and improve diabetes outcomes. Understanding what influenced implementation during the programme pilot is important in optimising rollout. This study explored the transferability of the NHS LCD Programme prior to wider adoption.

METHODS

Twenty-five interviews were undertaken with stakeholders involved in implementing the LCD programme in pilot sites (health service leads, referring health professionals and programme deliverers). Interviews with programme participants (people living with T2D) were undertaken within a larger programme of work, exploring what worked, for whom and why, which is reported separately. The conceptual Population-Intervention-Environment-Transfer Model of Transferability (PIET-T) guided study design and data collection. Constructs of the model were also used as a deductive coding frame during data analysis. Key themes were identified which informed recommendations to optimise programme transfer.

RESULTS

Population: Referral strategies in some areas lacked consideration of population characteristics. Many believed that offering a choice of delivery model would promote acceptability and accessibility of the eligible population.

INTERVENTION

Overall, stakeholders had confidence in the LCD programme due to the robust evidence base along with anecdotal evidence, but some felt the complex referral process hindered engagement from GP practices.

ENVIRONMENT

Stakeholders described barriers to accessing the programme, including language and learning difficulties. Transferability: Multidisciplinary working and effective communication supported successful implementation.

CONCLUSION

Referral strategies to reach underrepresented groups should be considered during programme transfer, along with timely data from service providers on access and programme benefits. A choice of delivery models may optimise uptake. Knowledge sharing between sites on good working practices is encouraged, including increasing engagement with key stakeholders.

Translation of a Diabetes Remission Service into Australian Primary Care: Findings from the Evaluation of DiRECT-Australia

Background

The Diabetes Remission Clinical Trial (DiRECT) study demonstrated that an intensive and structured weight management program in UK primary care resulted in high rates of diabetes remission in adults with recent onset type 2 diabetes mellitus (T2DM). This study was aimed at evaluating the translation of the DiRECT intervention into an Australian primary care setting.

Methods

All patients enrolled in the DiRECT-Australia Type 2 Diabetes Remission Service in a region of Sydney (Macarthur region, South Western Sydney, Australia) were included. Eligible participants were aged 20-70 years, noninsulin treated, with T2DM of ≤6 years' duration, and body mass index (BMI) ≥ 27 kg/m2. Total diet replacement of 825-853 kcal/day using meal replacements was implemented for 12 weeks, followed by an ongoing structured program until 52 weeks, with regular follow-up with a general practitioner, dietitian, and/or practice nurse.

Results

Of 39 recruited participants, 32 (82.1%) and 27 (69.2%) completed 12 weeks and 52 weeks of the structured program, respectively. Decrease in weight by -12.0 kg (95% CI: -9.6, -14.4; p < 0.001) and -9.1 kg (95% CI: -5.2, -12.9; p < 0.001) and decrease in glycated haemoglobin (HbA1c) by -1.1% (95% CI: -0.6, -1.6; p < 0.001) and -0.6% (95% CI: -0.1, -1.1; p = 0.013) were observed at 12 and 52 weeks, respectively. At the end of 12 and 52 weeks, 93.8% (30/32) and 55.6% (15/27) of those with follow-up data met the criteria for diabetes remission, respectively. Quality of life and wellbeing scores increased over the course of 12 weeks, remaining significantly higher at 52 weeks. Participants reported they would be willing to pay A$92.50 (95% CI: A$75.80, A$109.30) per fortnight for the low-calorie meal replacement shakes.

Conclusions

These findings support the feasibility of a structured diabetes remission service in an Australian primary care setting to achieve improvements in glycaemia, weight, and quality of life and wellbeing, and suggest a substantial willingness to pay for diet replacement products among participants.

No Evidence That Circulating GLP-1 or PYY Are Associated with Increased Satiety during Low Energy Diet-Induced Weight Loss: Modelling Biomarkers of Appetite

Bariatric surgery and pharmacology treatments increase circulating glucagon-like peptide-1 (GLP-1) and peptide YY (PYY), in turn promoting satiety and body weight (BW) loss. However, the utility of GLP-1 and PYY in predicting appetite response during dietary interventions remains unsubstantiated. This study investigated whether the decrease in hunger observed following low energy diet (LED)-induced weight loss was associated with increased circulating 'satiety peptides', and/or associated changes in glucose, glucoregulatory peptides or amino acids (AAs). In total, 121 women with obesity underwent an 8-week LED intervention, of which 32 completed an appetite assessment via a preload challenge at both Week 0 and Week 8, and are reported here. Visual analogue scales (VAS) were administered to assess appetite-related responses, and blood samples were collected over 210 min post-preload. The area under the curve (AUC_0-210), incremental AUC (iAUC_0-210), and change from Week 0 to Week 8 (∆) were calculated. Multiple linear regression was used to test the association between VAS-appetite responses and blood biomarkers. Mean (±SEM) BW loss was 8.4 ± 0.5 kg (-8%). Unexpectedly, the decrease in ∆AUC_0-210 hunger was best associated with decreased ∆AUC_0-210 GLP-1, GIP, and valine (p < 0.05, all), and increased ∆AUC_0-210 glycine and proline (p < 0.05, both). The majority of associations remained significant after adjusting for BW and fat-free mass loss. There was no evidence that changes in circulating GLP-1 or PYY were predictive of changes in appetite-related responses. The modelling suggested that other putative blood biomarkers of appetite, such as AAs, should be further investigated in future larger longitudinal dietary studies.

Associations of Dietary-Lifestyle Patterns with Obesity and Metabolic Health: Two-Year Changes in MeDiSH® Study Cohort

This study aimed to evaluate changes in diet, adiposity, and metabolic outcomes after two years. In all, 358 Polish men aged 19-40 years old participated in the study. Data regarding dietary and lifestyle characteristics as well as family, socio-economic, and demographic status were collected using the food frequency questionnaire KomPAN®. Dietary lifestyle patterns were previously derived from data for 358 men by principal component analysis (PCA). Changes over time were examined in 95 men who returned after two years by calculating relative differences (RD, %) in mean values and markers distribution. Diet quality was described with two predefined scores: pro-Healthy-Diet-Index (pHDI) and non-Healthy-Diet-Index (nHDI). After two years, changes were observed in diet quality and metabolic health markers. No significant changes were observed in family, socio-economic, and demographic status, as well as other lifestyle factors. In the "sandwiches and convenience foods" pattern, an nHDI decrease (RD = -25.3%) was associated with a fasting blood glucose decrease (RD = -6.1%). In the "protein food, fried-food and recreational physical activity" and the "healthy diet, activity at work, former smoking" patterns, pHDI decreases (RD = -13.6% and -14.6%, respectively,) were associated with an adiposity increase. In the "fast foods and stimulants" pattern, no changes in pHDI and nHDI were observed, while adiposity markers and systolic blood pressure worsened. Conclusion: in the two-year perspective, dietary improvement was associated with improved glycemic control, despite no changes in body weight, while worsening of the diet quality or maintenance of unhealthy dietary behaviours were associated with the deterioration of metabolic health.