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Predictors of type 2 diabetes remission in the Diabetes Remission Clinical Trial (DiRECT).
Thom, G, Messow, CM, Leslie, WS, Barnes, AC, Brosnahan, N, McCombie, L, Al-Mrabeh, A, Zhyzhneuskaya, S, Welsh, P, Sattar, N, et al
Diabetic medicine : a journal of the British Diabetic Association. 2021;(8):e14395
Abstract
AIM: To identify predictors of type 2 diabetes remission in the intervention arm of DiRECT (Diabetes Remission Clinical Trial). METHODS Participants were aged 20-65 years, with type 2 diabetes duration of <6 years and BMI 27-45 kg/m2 , and were not receiving insulin. Weight loss was initiated by total diet replacement (825-853 kcal/day, 3-5 months, shakes/soups), and weight loss maintenance support was provided for 2 years. Remissions (HbA1c <48 mmol/mol [<6.5%], without antidiabetes medications) in the intervention group (n = 149, mean age 53 years, BMI 35 kg/m2 ) were achieved by 68/149 participants (46%) at 12 months and by 53/149 participants (36%) at 24 months. Potential predictors were examined by logistic regression analyses, with adjustments for weight loss and effects independent of weight loss. RESULTS Baseline predictors of remission at 12 and 24 months included being prescribed fewer antidiabetes medications, having lower triglyceride and gamma-glutamyl transferase levels, and reporting better quality of life with less anxiety/depression. Lower baseline HbA1c was a predictor at 12 months, and older age and male sex were predictors at 24 months. Being prescribed antidepressants predicted non-remission. Some, but not all effects were explained by weight loss. Weight loss was the strongest predictor of remission at 12 months (adjusted odds ratio per kg weight loss 1.24, 95% CI 1.14, 1.34; P < 0.0001) and 24 months (adjusted odds ratio 1.23, 95% CI 1.13, 1.35; P <0.0001). Weight loss in kilograms and percentage weight loss were equally good predictors. Early weight loss and higher programme attendance predicted more remissions. Baseline BMI, fasting insulin, fasting C-peptide and diabetes duration did not predict remission. CONCLUSIONS Other than weight loss, most predictors were modest, and not sufficient to identify subgroups for which remission was not a worthwhile target.
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Dietary Glycemic Index and Load and the Risk of Type 2 Diabetes: A Systematic Review and Updated Meta-Analyses of Prospective Cohort Studies.
Livesey, G, Taylor, R, Livesey, HF, Buyken, AE, Jenkins, DJA, Augustin, LSA, Sievenpiper, JL, Barclay, AW, Liu, S, Wolever, TMS, et al
Nutrients. 2019;(6)
Abstract
Published meta-analyses indicate significant but inconsistent incident type-2 diabetes(T2D)-dietary glycemic index (GI) and glycemic load (GL) risk ratios or risk relations (RR). It is nowover a decade ago that a published meta-analysis used a predefined standard to identify validstudies. Considering valid studies only, and using random effects dose-response meta-analysis(DRM) while withdrawing spurious results (p < 0.05), we ascertained whether these relationswould support nutrition guidance, specifically for an RR > 1.20 with a lower 95% confidence limit>1.10 across typical intakes (approximately 10th to 90th percentiles of population intakes). Thecombined T2D-GI RR was 1.27 (1.15-1.40) (p < 0.001, n = 10 studies) per 10 units GI, while that forthe T2D-GL RR was 1.26 (1.15-1.37) (p < 0.001, n = 15) per 80 g/d GL in a 2000 kcal (8400 kJ) diet.The corresponding global DRM using restricted cubic splines were 1.87 (1.56-2.25) (p < 0.001, n =10) and 1.89 (1.66-2.16) (p < 0.001, n = 15) from 47.6 to 76.1 units GI and 73 to 257 g/d GL in a 2000kcal diet, respectively. In conclusion, among adults initially in good health, diets higher in GI or GLwere robustly associated with incident T2D. Together with mechanistic and other data, thissupports that consideration should be given to these dietary risk factors in nutrition advice.Concerning the public health relevance at the global level, our evidence indicates that GI and GLare substantial food markers predicting the development of T2D worldwide, for persons ofEuropean ancestry and of East Asian ancestry.
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Is there a dose-response relation of dietary glycemic load to risk of type 2 diabetes? Meta-analysis of prospective cohort studies.
Livesey, G, Taylor, R, Livesey, H, Liu, S
The American journal of clinical nutrition. 2013;(3):584-96
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Abstract
BACKGROUND Although much is known about the association between dietary glycemic load (GL) and type 2 diabetes (T2D), prospective cohort studies have not consistently shown a positive dose-response relation. OBJECTIVE We performed a comprehensive examination of evidence on the dose response that links GL to T2D and sources of heterogeneity among all prospective cohort studies on healthy adults available in the literature. DESIGN We conducted a systematic review of all prospective cohort studies and meta-analyses to quantify the GL-T2D relation both without and with adjustment for covariates. RESULTS Among 24 prospective cohort studies identified by August 2012, the GL ranged from ∼60 to ∼280 g per daily intake of 2000 kcal (8.4 MJ). In a fully adjusted meta-analysis model, the GL was positively associated with RR of T2D of 1.45 (95% CI: 1.31, 1.61) for a 100-g increment in GL (P < 0.001; n = 24 studies; 7.5 million person-years of follow-up). Sex (P = 0.03), dietary instrument validity (P < 0.001), and ethnicity (European American compared with other; P = 0.04) together explained 97% of the heterogeneity among studies. After adjustment for heterogeneities, we used both funnel and trim-and-fill analyses to identify a negligible publication bias. Multiple influence, cumulative, and forecast analyses indicated that the GL-T2D relation tended to have reached stability and to have been underestimated. The relation was apparent at all doses of GL investigated, although it was statistically significant only at >95 g GL/2000 kcal. CONCLUSION After we accounted for several sources of heterogeneity, findings from prospective cohort studies that related the GL to T2D appear robust and consistently indicate strong and significantly lower T2D risk in persons who consume lower-GL diets. This review was registered at http://www.crd.york.ac.uk/PROSPERO as CRD42011001810.
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Glycemic response and health--a systematic review and meta-analysis: the database, study characteristics, and macronutrient intakes.
Livesey, G, Taylor, R, Hulshof, T, Howlett, J
The American journal of clinical nutrition. 2008;(1):223S-236S
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BACKGROUND Reduction of dietary glycemic response has been proposed as a means of reducing the risk of diabetes and coronary heart disease. Its role in health maintenance and management, alongside unavailable carbohydrate (eg, fiber), is incompletely understood. OBJECTIVE We aimed to assess the evidence relating the glycemic impact of foods to a role in health maintenance and management of disease. DESIGN We searched the literature for relevant controlled dietary intervention trials on glycemic index (GI) according to inclusion and exclusion criteria, extracted the data to a database, and synthesized the evidence via meta-analyses and meta-regression models. RESULTS Among literature to January 2005, 45 relevant publications were identified involving 972 subjects with good health or metabolic disease. With small reductions in GI (<10 units), increases in available carbohydrate, energy, and protein intakes were found in all studies combined. Falling trends in energy, available carbohydrate, and protein intakes then occurred with progressive reductions in GI. Fat intake was essentially unchanged. Unavailable carbohydrate intake was generally higher for intervention diets but showed no trend with GI (falling or rising). Among studies reporting on GI, variation in glycemic load was approximately equally explained by variation in GI and variation in available carbohydrate intake. An exchange of available and unavailable carbohydrate (approximately 1 g/g) was evident in these studies. CONCLUSIONS Among GI studies, observed reductions in glycemic load are most often not solely due to substitution of high for low glycemic carbohydrate foods. Available carbohydrate intake is a confounding factor. The role of unavailable carbohydrate remains to be accounted for.