Role of sociodemographic, clinical, behavioral, and molecular factors in precision prevention of type 2 diabetes: a systematic review
Bodhini, D.; Morton, R. W.; Santhakumar, V.; Nakabuye, M.; Pomares-Millan, H.; Clemmensen, C.; Fitzpatrick, S. L.; Guasch-Ferre, M.; Pankow, J.; Ried-Larsen, M.; Franks, P. W.; ADA/EASD Precision Medicine in Diabetes Initiative, ; Tobias, D. K.; Merino, J.; Viswanathan, M.; Loos, R. J.
Show abstract
The variability in the effectiveness of type 2 diabetes (T2D) preventive interventions highlights the potential to identify the factors that determine treatment responses and those that would benefit the most from a given intervention. We conducted a systematic review to synthesize the evidence to support whether sociodemographic, clinical, behavioral, and molecular characteristics modify the efficacy of dietary or lifestyle interventions to prevent T2D. Among the 80 publications that met our criteria for inclusion, the evidence was low to very low to attribute variability in intervention effectiveness to individual characteristics such as age, sex, BMI, race/ethnicity, socioeconomic status, baseline behavioral factors, or genetic predisposition. We found evidence, albeit low certainty, to support conclusions that those with poorer health status, particularly those with prediabetes at baseline, tend to benefit more from T2D prevention strategies compared to healthier counterparts. Our synthesis highlights the need for purposefully designed clinical trials to inform whether individual factors influence the success of T2D prevention strategies.
Matching journals
The top 8 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- A Microbiome-targeting Fiber-enriched Nutritional Formula is Well Tolerated and Improves Quality of Life and Hemoglobin A1c in Type 2 Diabetes: A Double-Blind, Randomized, Placebo-Controlled Trial 94%
- Treatment outcomes with oral anti-hyperglycaemic therapies in people with diabetes secondary to a pancreatic condition (type 3c diabetes): A population-based cohort study 92%
- Comparative Effects of Weight Loss and Incretin-Based Therapies on Endothelial Vasodilatory and Fibrinolytic Function 92%
Similar papers in this journal
- Predictive value of circulating NMR metabolic biomarkers for type 2 diabetes risk in the UK Biobank study 94%
- Maternal smoking during pregnancy and type 1 diabetes in the offspring: A nationwide register-based study with family-based designs 92%
- Meat consumption and risk of 25 common conditions: outcome-wide analyses in 475,000 men and women in the UK Biobank study 90%
Similar papers in this journal
- Time-restricted eating and exercise training before and during pregnancy for people with increased risk of gestational diabetes: the BEFORE THE BEGINNING randomised controlled trial 94%
- Emulating the GRADE Trial Using Real-World Data 91%
- Vitamin D Supplements for Prevention of Covid-19 or other Acute Respiratory Infections: a Phase 3 Randomized Controlled Trial (CORONAVIT) 90%
Similar papers in this journal
- Nothing About Us Without Us: A Scoping Review and Priority-Setting Partnership in Type 1 Diabetes and Exercise 92%
- Vitamin B12 and Risk of Diabetes: New insight from Cross-Sectional and Longitudinal Analyses of the China Stroke Primary Prevention Trial (CSPPT) 92%
- A plasma metabolite score of three eicosanoids predicts incident type 2 diabetes – a prospective study in three independent cohorts 91%
Similar papers in this journal
- Discovery of biomarkers for glycaemic deterioration before and after the onset of type 2 diabetes: an overview of the data from the epidemiological studies within the IMI DIRECT Consortium 93%
- Role of Weight Loss Induced Prediabetes Remission in the Prevention of Type 2 Diabetes – Time to Improve Diabetes Prevention 92%
- Birth weight, BMI in adulthood and latent autoimmune diabetes in adults: A Mendelian randomization study 92%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.