Enablers and barriers to implementing obesity assessments in clinical practice: a rapid mixed-methods systematic review.

OBJECTIVES: This systematic review aims to improve our knowledge of enablers and barriers to implementing obesity-related anthropometric assessments in clinical practice. DESIGN: A mixed-methods systematic review. DATA SOURCES: Medline, Embase and CINAHL to November 2021. ELIGIBILITY CRITERIA: Quantitative studies that reported patient factors associated with obesity assessments in clinical practice (general practice or primary care); and qualitative studies that reported views of healthcare professionals about enablers and barriers to their implementation. DATA EXTRACTION AND SYNTHESIS: We used random-effects meta-analysis to pool ratios for categorical predictors reported in ≥3 studies expressed as pooled risk ratio (RR) with 95% CI, applied inverse variance weights, and investigated statistical heterogeneity (I2), publication bias (Egger's test), and sensitivity analyses. We used reflexive thematic analysis for qualitative data and applied a convergent integrated approach to synthesis. RESULTS: We reviewed 22 quantitative (observational) and 3 qualitative studies published between 2004 and 2020. All had ≥50% of the quality items for risk of bias assessments. Obesity assessment in clinical practice was positively associated with patient factors: female sex (RR 1.28, 95% CI 1.10 to 1.50, I2 99.8%, mostly UK/USA), socioeconomic deprivation (RR 1.21, 95% CI 1.18 to 1.24, I2 73.9%, UK studies), non-white race/ethnicity (RR 1.27, 95% CI 1.03 to 1.57, I2 99.6%) and comorbidities (RR 2.11, 95% CI 1.60 to 2.79, I2 99.6%, consistent across most countries). Obesity assessment was also most common in the heaviest body mass index group (RR 1.55, 95% CI 0.99 to 2.45, I2 99.6%). Views of healthcare professionals were positive about obesity assessments when linked to patient health (convergent with meta-analysis for comorbidities) and if part of routine practice, but negative about their role, training, time, resources and incentives in the healthcare system. CONCLUSIONS: Our evidence synthesis revealed several important enablers and barriers to obesity assessments that should inform healthcare professionals and relevant stakeholders to encourage adherence to clinical practice guideline recommendations.

Phenotypic Responses to a Lifestyle Intervention Do Not Account for Inter-Individual Variability in Glucose Tolerance for Individuals at High Risk of Type 2 Diabetes.

Background: Lifestyle interventions have been shown to delay or prevent the onset of type 2 diabetes among high risk adults. A better understanding of the variability in physiological responses would support the matching of individuals with the best type of intervention in future prevention programmes, in order to optimize risk reduction. The purpose of this study was to determine if phenotypic characteristics at baseline or following a 12 weeks lifestyle intervention could explain the inter-individual variability in change in glucose tolerance in individuals with high risk for type 2 diabetes. Methods: In total, 285 subjects with normal glucose tolerance (NGT, FINDRISC score > 12), impaired fasting glucose (IFG) and impaired glucose tolerance (IGT) were recruited for a 12 weeks lifestyle intervention. Glucose tolerance, insulin sensitivity, anthropometric characteristics and aerobic fitness were measured. Variability of responses was examined by grouping participants by baseline glycemic status, by cluster analysis based on the change in glucose tolerance and by Principal Component Analysis (PCA). Results: In agreement with other studies, the mean response to the 12 weeks intervention was positive for the majority of parameters. Overall, 89% improved BMI, 80% waist circumference, and 81% body fat while only 64% improved fasting plasma glucose and 60% 2 h glucose. The impact of the intervention by glycaemic group did not show any phenotypic differences in response between NGT, IFG, and IGT. A hierarchical cluster analysis of change in glucose tolerance identified four sub-groups of "responders" (high and moderate) and "non-responders" (no response or deteriorated) but there were few differences in baseline clincal and physiological parameters or in response to the intervention to explain the overall variance. A further PCA analysis of 19 clinical and physiological univariables could explain less than half (48%) of total variability. Conclusion: We found that phenotypic characteristics from standard clinical and physiological parameters were not sufficient to account for the inter-individual variability in glucose tolerance following a 12 weeks lifestyle intervention in inidivuals at high risk for type 2 diabetes. Further work is required to identify biomarkers that complement phenotypic traits and better predict the response to glucose tolerance.

α-Hydroxybutyric Acid Is a Selective Metabolite Biomarker of Impaired Glucose Tolerance.

OBJECTIVE: Plasma metabolites that distinguish isolated impaired glucose tolerance (iIGT) from isolated impaired fasting glucose (iIFG) may be useful biomarkers to predict IGT, a high-risk state for the development of type 2 diabetes. RESEARCH DESIGN AND METHODS: Targeted metabolomics with 23 metabolites previously associated with dysglycemia was performed with fasting plasma samples from subjects without diabetes at time 0 of an oral glucose tolerance test (OGTT) in two observational cohorts: RISC (Relationship Between Insulin Sensitivity and Cardiovascular Disease) and DMVhi (Diabetes Mellitus and Vascular Health Initiative). Odds ratios (ORs) for a one-SD change in the metabolite level were calculated using multiple logistic regression models controlling for age, sex, and BMI to test for associations with iIGT or iIFG versus normal. Selective biomarkers of iIGT were further validated in the Botnia study. RESULTS: α-Hydroxybutyric acid (α-HB) was most strongly associated with iIGT in RISC (OR 2.54 [95% CI 1.86-3.48], P value 5E-9) and DMVhi (2.75 [1.81-4.19], 4E-5) while having no significant association with iIFG. In Botnia, α-HB was selectively associated with iIGT (2.03 [1.65-2.49], 3E-11) and had no significant association with iIFG. Linoleoyl-glycerophosphocholine (L-GPC) and oleic acid were also found to be selective biomarkers of iIGT. In multivariate IGT prediction models, addition of α-HB, L-GPC, and oleic acid to age, sex, BMI, and fasting glucose significantly improved area under the curve in all three cohorts. CONCLUSIONS: α-HB, L-GPC, and oleic acid were shown to be selective biomarkers of iIGT, independent of age, sex, BMI, and fasting glucose, in 4,053 subjects without diabetes from three European cohorts. These biomarkers can be used in predictive models to identify subjects with IGT without performing an OGTT.

Fasting plasma glucose as initial screening for diabetes and prediabetes in irish adults: The Diabetes Mellitus and Vascular health initiative (DMVhi).

OBJECTIVE: Type 2 diabetes has a long pre clinical asymptomatic phase. Early detection may delay or arrest disease progression. The Diabetes Mellitus and Vascular health initiative (DMVhi) was initiated as a prospective longitudinal cohort study on the prevalence of undiagnosed Type 2 diabetes and prediabetes, diabetes risk and cardiovascular risk in a cohort of Irish adults aged 45-75 years. RESEARCH DESIGN AND METHODS: Members of the largest Irish private health insurance provider aged 45 to 75 years were invited to participate in the study. EXCLUSION CRITERIA: already diagnosed with diabetes or taking oral hypoglycaemic agents. Participants completed a detailed medical questionnaire, had weight, height, waist and hip circumference and blood pressure measured. Fasting blood samples were taken for fasting plasma glucose (FPG). Those with FPG in the impaired fasting glucose (IFG) range had a 75gm oral glucose tolerance test performed. RESULTS: 122,531 subjects were invited to participate. 29,144 (24%) completed the study. The prevalence of undiagnosed diabetes was 1.8%, of impaired fasting glucose (IFG) was 7.1% and of impaired glucose tolerance (IGT) was 2.9%. Dysglycaemia increased among those aged 45-54, 55-64 and 65-75 years in both males (10.6%, 18.5%, 21.7% respectively) and females (4.3%, 8.6%, 10.9% respectively). Undiagnosed T2D, IFG and IGT were all associated with gender, age, blood pressure, BMI, abdominal obesity, family history of diabetes and triglyceride levels. Using FPG as initial screening may underestimate the prevalence of T2D in the study population. CONCLUSIONS: This study is the largest screening study for diabetes and prediabetes in the Irish population. Follow up of this cohort will provide data on progression to diabetes and on cardiovascular outcomes.

A novel test for IGT utilizing metabolite markers of glucose tolerance.

The oral glucose tolerance test (OGTT) is the only method to diagnose patients having impaired glucose tolerance (IGT), but its use has diminished considerably in recent years. Metabolomic profiling studies have identified a number of metabolites whose fasting levels are associated with dysglycemia and type 2 diabetes. These metabolites may serve as the basis of an alternative test for IGT. Using the stable isotope dilution technique, quantitative assays were developed for 23 candidate biomarker metabolites. These metabolites were measured in fasting plasma samples taken just prior to an OGTT from 1623 nondiabetic subjects: 955 from the Relationship between Insulin Sensitivity and Cardiovascular Disease Study (RISC Study; 11.7% IGT) and 668 subjects from the Diabetes Mellitus and Vascular Health Initiative (DMVhi) cohort from the DEXLIFE project (11.8% IGT). The associations between metabolites, anthropometric, and metabolic parameters and 2hPG values were assessed by Pearson correlation coefficients and Random Forest classification analysis to rank variables for their ability to distinguish IGT from normal glucose tolerance (NGT). Multivariate logistic regression models for estimating risk of IGT were developed and evaluated using AUCs calculated from the corresponding ROC curves. A model based on the fasting plasma levels of glucose, α-hydroxybutyric acid, ß-hydroxybutyric acid, 4-methyl-2-oxopentanoic acid, linoleoylglycerophosphocholine, oleic acid, serine and vitamin B5 was optimized in the RISC cohort (AUC = 0.82) and validated in the DMVhi cohort (AUC = 0.83). A novel, all-metabolite-based test is shown to be a discriminate marker of IGT. It requires only a single fasted blood draw and may serve as a more convenient surrogate for the OGTT or as a means of identifying subjects likely to be IGT.