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Clinical and Dietary Determinants of Muscle Mass in Patients with Type 2 Diabetes: Data from the Diabetes and Lifestyle Cohort Twente.

ABSTRACT: Low muscle mass in patients with type 2 diabetes is associated with a progressively higher risk of morbidity and mortality. The aim of this study was to identify modifiable targets for intervention of muscle mass in type 2 diabetes. Cross-sectional analyses were performed in 375 patients of the Diabetes and Lifestyle Cohort Twente-1 study. Muscle mass was estimated by 24 h urinary creatinine excretion rate (CER, mmol/24 h). Patients were divided in sex-stratified tertiles of CER. To study determinants of CER, multivariable linear regression analyses were performed. Protein intake was determined by Maroni formula and by a semi-quantitative Food Frequency Questionnaire. The mean CER was 16.1 ± 4.8 mmol/24 h and 10.9 ± 2.9 mmol/24 h in men and women, respectively. Lower CER was significantly associated with older age (p < 0.001) as a non-modifiable risk factor, whereas higher BMI (p = 0.015) and lower dietary protein intake (both methods p < 0.001) were identified as modifiable risk factors for lower CER. Overall body mass index (BMI) was high, even in the lowest CER tertile the mean BMI was 30.9 kg/m², mainly driven by someone's body weight (p = 0.004) instead of someone's height (p = 0.58). In the total population, 28% did not achieve adequate protein intake of >0.8 g/kg/day, with the highest percentage in the lowest CER tertile (52%, p < 0.001). Among patients with type 2 diabetes treated in secondary care, higher BMI and low dietary protein intake are modifiable risk factors for lower muscle mass. Considering the risk associated with low muscle mass, intervention may be useful. To that purpose, dietary protein intake and BMI are potential targets for intervention.

SUBMITTER: Jalving AC

PROVIDER: S-EPMC8623198 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Objective: To assess adherence to statin therapy and its association with sociodemographic data, medical characteristics, LDLc levels, and LDLc target attainment in real-world T2D patients treated in secondary care. Research Design and Methods: Cross-sectional analyses were performed on baseline data of 393 patients in the DIAbetes and LifEstyle Cohort Twente (DIALECT). The medication possession ratio (MPR), calculated with pharmacy dispensing data, was used to determine adherence to statins for an intended period of 24 months. Statins were included in the analyses if they were used for at least six consecutive months with at least three dispenses. Adherence was defined as an MPR ≥80%. Associations with adherence were assessed using descriptive statistics and binary logistic regression. Results: Overall, 80% of the patients had a statin prescription and of those, 89% were adherent. The proportion of patients who reached LDLc targets of ≤2.5 mmol/L and <1.8 mmol/L differed significantly between the adherent, nonadherent and non-statin group (90% vs. 74% vs. 46%; p < 0.01 and 56% vs. 26% vs. 6%; p < 0.01, respectively). Serum LDLc levels were lower in the adherent versus the nonadherent and non-statin group (1.76 ± 0.60 vs. 2.23 ± 0.90 vs. 2.71 ± 0.67 mmol/L; p < 0.01). Higher HbA1c levels were independently associated with nonadherence (OR: 1.05, 95% CI 1.01-1.08; p < 0.01). Mediation adherence (OR: 2.88, 95% CI 1.04-7.97; p = 0.041) and lower BMI (OR: 0.88, 95% CI 0.81-0.96; p < 0.01) were independently associated with attaining the LDLc target of ≤2.5 mmol/L. Conclusion: In patients with T2D treated in secondary care, statin adherence was relatively high and was associated with significantly lower LDLc levels. It is important to identify nonadherence as it appeared an important determinant of failure to reach LDLc targets. The finding that many patients who failed to attain LDLc targets did not receive statin treatment offers an opportunity to improve diabetes care.

Project description:BackgroundAlthough there are many effective lifestyle interventions for type 2 diabetes (T2DM) prevention, insight into effective intervention pathways, especially of long-term interventions, is often lacking. This study aims to provide insight into the effective intervention pathways of the SLIMMER diabetes prevention intervention using mediation analyses.MethodsIn total, 240 participants at increased risk of T2DM were included in the analyses over 18 months. The intervention was a combined lifestyle intervention with a dietary and a physical activity (PA) component. The primary and secondary outcomes were change in fasting insulin (pmol/L) and change in body weight (kg) after 18 months, respectively. Firstly, in a multiple mediator model, we investigated whether significant changes in these outcomes were mediated by changes in dietary and PA behavior. Secondly, in multiple single mediator models, we investigated whether changes in dietary and PA behavior were mediated by changes in behavioral determinants and the participants' psychological profile. The mediation analyses used linear regression models, where significance of indirect effects was calculated with bootstrapping.ResultsThe effect of the intervention on decreased fasting insulin was 40% mediated by change in dietary and PA behavior, where dietary behavior was an independent mediator of the association (34%). The effect of the intervention on decreased body weight was 20% mediated by change in dietary and PA behavior, where PA behavior was an independent mediator (17%). The intervention significantly changed intake of fruit, fat from bread spread, and fiber from bread. Change in fruit intake was mediated by change in action control (combination of consciousness, self-control, and effort), motivation, self-efficacy, intention, and skills. Change in fat intake was mediated by change in action control and psychological profile. No mediators could be identified for change in fiber intake. The change in PA behavior was mediated by change in action control, motivation, and psychological profile.ConclusionThe effect of the SLIMMER intervention on fasting insulin and body weight was mediated by changes in dietary and PA behavior, in distinct ways. These results indicate that changing dietary as well as PA behavior is important in T2DM prevention.

Project description:BackgroundUnderstanding of the genetic basis of type 2 diabetes (T2D) has progressed rapidly, but the interactions between common genetic variants and lifestyle risk factors have not been systematically investigated in studies with adequate statistical power. Therefore, we aimed to quantify the combined effects of genetic and lifestyle factors on risk of T2D in order to inform strategies for prevention.Methods and findingsThe InterAct study includes 12,403 incident T2D cases and a representative sub-cohort of 16,154 individuals from a cohort of 340,234 European participants with 3.99 million person-years of follow-up. We studied the combined effects of an additive genetic T2D risk score and modifiable and non-modifiable risk factors using Prentice-weighted Cox regression and random effects meta-analysis methods. The effect of the genetic score was significantly greater in younger individuals (p for interaction ?=?1.20×10-4). Relative genetic risk (per standard deviation [4.4 risk alleles]) was also larger in participants who were leaner, both in terms of body mass index (p for interaction ?=?1.50×10-3) and waist circumference (p for interaction ?=?7.49×10-9). Examination of absolute risks by strata showed the importance of obesity for T2D risk. The 10-y cumulative incidence of T2D rose from 0.25% to 0.89% across extreme quartiles of the genetic score in normal weight individuals, compared to 4.22% to 7.99% in obese individuals. We detected no significant interactions between the genetic score and sex, diabetes family history, physical activity, or dietary habits assessed by a Mediterranean diet score.ConclusionsThe relative effect of a T2D genetic risk score is greater in younger and leaner participants. However, this sub-group is at low absolute risk and would not be a logical target for preventive interventions. The high absolute risk associated with obesity at any level of genetic risk highlights the importance of universal rather than targeted approaches to lifestyle intervention.

Project description:BACKGROUND:People with prediabetes have an increased risk of developing type 2 diabetes (T2D). Few studies have evaluated the influence of lifestyle factors on the risk of progression to diabetes and reversion to normoglycemia. The aim of this study was to determine the incidence of T2D in a large cohort of workers with prediabetes, and to evaluate the influence of sociodemographic, clinical, metabolic, and lifestyle factors that affect the persistence of prediabetes and the progression to T2D. METHODS:A cohort study of 27,844 adult workers (aged 20 to 65 years) from Spain who had prediabetes based on an occupational medical examination from 2012 to 2013. Prediabetes was defined as fasting plasma glucose (FPG) between 100 and 125 mg/dL. At the baseline evaluation, sociodemographic, anthropometric, metabolic, and lifestyle data were collected. At the 5-year follow-up, incident T2D was defined as an FPG of at least 126 mg/dL or initiation of an antidiabetic medication. RESULTS:Among 235,995 initially screened workers, the prevalence of T2D was 14.19% (95% confidence interval (CI) 14.05 to 14.33) and the prevalence of prediabetes was 11.85% (95% CI 11.71 to 11.99). Follow-up data were available for 23,293 individuals with prediabetes. Among them, 36.08% (95% CI 35.46 to 36.70) returned to normoglycemia, 40.92% (95% CI 40.29 to 41.55) had persistent prediabetes, and 23.00% (95% CI 22.46 to 23.54) progressed to T2D. The risk for persistence of prediabetes and for progression to T2D increased with age, body mass index (BMI), triglyceride level, and less than 150 min/week of physical activity. An HbA1c level of 6% or greater was the strongest individual predictor of progression to T2D. CONCLUSIONS:Physical activity, diet, smoking, and BMI are modifiable factors that are associated with the persistence of prediabetes and the progression to T2D. The workplace is a feasible setting for the early detection of prediabetes and the promotion of lifestyles that can prevent progression to T2D.

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Clinical and Dietary Determinants of Muscle Mass in Patients with Type 2 Diabetes: Data from the Diabetes and Lifestyle Cohort Twente.

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