Aim: To quantify the effect of weight loss on glycated haemoglobin (HbA1c) at group level, based on data from published weight loss trials in overweight and obese patients with type 2 diabetes (T2D).

Methods: A systematic literature search in MEDLINE, EMBASE and Cochrane CENTRAL (January 1990 through December 2012) was conducted to identify prospective trials of energy-reduced diets, obesity drugs or bariatric surgery in adult, overweight and obese patients with T2D. Based on clinical data with follow-up from 3 to 24 months, a linear model was developed to describe the effect of weight reduction on HbA1c.

Results: The literature search identified 58 eligible articles consisting of 124 treatment groups and 17 204 subjects, yielding a total of 250 data points with concurrent mean changes from baseline in weight and HbA1c. The model-based analyses indicated a linear relationship between weight loss and HbA1c reduction, with an estimated mean HbA1c reduction of 0.1 percentage points for each 1 kg of reduced body weight for the overall population. Baseline HbA1c was a significant covariate for the relationship between weight loss and HbA1c: high HbA1c at baseline was associated with a greater reduction in HbA1c for the same degree of weight loss. The collected trial data also indicated weight-loss-dependent reductions in antidiabetic medication.

Conclusions: At group level, weight loss in obese and overweight patients with T2D was consistently accompanied by HbA1c reduction in a dose-dependent manner. The model developed in the present study estimates that for each kg of mean weight loss, there is a mean HbA1c reduction of 0.1 percentage points. HbA1c-lowering is greater in populations with poor glycaemic control than in well controlled populations with the same degree of weight loss. This summary of data from previous trials regarding the effect of weight reduction on HbA1c may be used to support the design and interpretation of future studies that aim to demonstrate the efficacy of weight loss interventions for T2D treatment.

Download full-text PDF

Source
http://dx.doi.org/10.1111/dom.12971DOI Listing

Publication Analysis

Top Keywords

weight loss
40
hba1c reduction
16
weight
15
weight reduction
12
loss hba1c
12
hba1c
11
loss
10
glycated haemoglobin
8
loss trials
8
patients type
8

Similar Publications

For patients considering bariatric surgery, it is essential to have clear answers to common questions to ensure the success of the procedure. Patients should understand that surgery is not a quick fix but a tool that must be complemented by lifestyle changes, including dietary adjustments and regular physical activity. The procedure carries potential risks that should be weighed against the potential benefits.

View Article and Find Full Text PDF

In the current investigation, the efficiency inhibition of two newly synthesized bi-pyrazole derivatives, namely 2,3-bis[(bis((1 H-pyrazol-1-yl) methyl) amino)] pyridine (Tetra-Pz-Ortho) and 1,4-bis[(bis((1 H-pyrazol-1-yl) methyl) amino)] benzene (Tetra-Pz-Para) for corrosion of carbon steel (C&S) in 1 M HCl medium was evaluated. A Comparative study of inhibitor effect of Tetra-Pz-Ortho and Tetra-Pz-Para was conducted first using weight loss method and EIS (Electrochemical Impedance Spectroscopy) and PDP (Potentiodynamic Polarisation) techniques. Tetra-Pz-Ortho and Tetra-Pz-Para had a maximum inhibition efficacy of 97.

View Article and Find Full Text PDF

Loss-of-function mutations induced by CRISPR-Cas9 in the TaGS3 gene homoeologs show non-additive dosage-dependent effects on grain size and weight and have potential utility for increasing grain yield in wheat. The grain size in cereals is one of the component traits contributing to yield. Previous studies showed that loss-of-function (LOF) mutations in GS3, encoding Gγ subunit of the multimeric G protein complex, increase grain size and weight in rice.

View Article and Find Full Text PDF

Remote sensing images often suffer from the degradation effects of atmospheric haze, which can significantly impair the quality and utility of the acquired data. A novel dehazing method leveraging generative adversarial networks is proposed to address this challenge. It integrates a generator network, designed to enhance the clarity and detail of hazy images, with a discriminator network that distinguishes between dehazed and real clear images.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!