Aim: To investigate how 24-h physical behaviours differ across type 2 diabetes (T2DM) subtypes. Materials and methods: We included participants living with T2DM, enrolled as part of an ongoing observational study. Participants wore an accelerometer for 7 days to quantify physical behaviours across 24 h. We used routinely collected clinical data (age at onset of diabetes, glycated haemoglobin level, homeostatic model assessment index of beta-cell function, homeostatic model assessment index of insulin resistance, body mass index) to replicate four previously identified subtypes (insulin-deficient diabetes [INS-D], insulin-resistant diabetes [INS-R], obesity-related diabetes [OB] and age-related diabetes [AGE]), via k-means clustering. Differences in physical behaviours across the diabetes subtypes were assessed using generalized linear models, with the AGE cluster as the reference. Results: A total of 564 participants were included in this analysis (mean age 63.6 ± 8.4 years, 37.6% female, mean age at diagnosis 53.1 ± 10.0 years). The proportions in each cluster were as follows: INS-D: n = 35, 6.2%; INS-R: n = 88, 15.6%; OB: n = 166, 29.4%; and AGE: n = 275, 48.8%. Compared to the AGE cluster, the OB cluster had a shorter sleep duration (-0.3 h; 95% confidence interval [CI] -0.5, -0.1), lower sleep efficiency (-2%; 95% CI -3, -1), lower total physical activity (-2.9 mg; 95% CI -4.3, -1.6) and less time in moderate-to-vigorous physical activity (-6.6 min; 95% CI -11.4, -1.7), alongside greater sleep variability (17.9 min; 95% CI 8.2, 27.7) and longer sedentary time (31.9 min; 95% CI 10.5, 53.2). Movement intensity during the most active continuous 10 and 30 min of the day was also lower in the OB cluster. Conclusions: In individuals living with T2DM, the OB subtype had the lowest levels of physical activity and least favourable sleep profiles. Such behaviours may be suitable targets for personalized therapeutic lifestyle interventions.

Aims: To examine the independent associations between relative protein intake (g kg-1 day 1 ) and markers of physical function in those with type 2 diabetes, while also comparing with current guidelines for protein intake. Methods: This analysis reports data from the ongoing Chronotype of Patients with Type 2 Diabetes and Effect on Glycaemic Control (CODEC) study. Functional assessments included: Short Physical Performance Battery (SPPB), 60 s sit-to-stand (STS-60), 4-m gait speed, time to rise from a chair (×5) and handgrip strength. Participants also completed a self-reported 4 day diet diary. Regression analyses assessed whether relative protein intake was associated with markers of physical function. Interaction terms assessed whether the associations were modified by sex, age, HbA1c or body mass index (BMI). Results: 413 participants were included (mean ± SD:age = 65.0 ± 7.7 years, 33% female, BMI = 30.6 ± 5.1 kg/m2 ). The average total protein intake was 0.88 ± 0.31 g kg-1 day-1 . 33% of individuals failed to meet the reference nutrient intake for the United Kingdom (≥0.75 g kg-1 day-1 ), and 87% for European recommendations (≥1.2 g kg-1 day-1 ). After adjustment, each 0.5 g/kg of protein intake was associated with an 18.9% (95% CI: 2.3, 35.5) higher SPPB score, 22.7% (1.1, 44.3) more repetitions in STS-60, 21.1% (4.5, 37.7) faster gait speed and 33.2% (16.9, 49.5) lower chair rise time. There were no associations with handgrip strength or any interactions. Conclusions: Relative protein intake was positively associated with physical function outcomes, even after consideration of total energy intake. As a number of individuals were below the current guidelines, protein intake may be a modifiable factor of importance for people with type 2 diabetes.

Background: The diagnosis of type 2 diabetes (T2D) in younger adults, an increasingly common public health issue, is associated with a higher risk of cardiovascular complications and mortality, which may be due to a more adverse cardiovascular risk profile in individuals diagnosed at a younger age. Aim: To investigate the association between age at diagnosis and the cardiovascular risk profile in adults with T2D. Methods: A pooled dataset was used, comprised of data from five previous studies of adults with T2D, including 1409 participants of whom 196 were diagnosed with T2D under the age of 40 years. Anthropometric and blood biomarker measurements included body weight, body mass index (BMI), waist circumference, body fat percentage, glycaemic control (HbA1c), lipid profile and blood pressure. Univariable and multivariable linear regression models, adjusted for diabetes duration, sex, ethnicity and smoking status, were used to investigate the association between age at diagnosis and each cardiovascular risk factor. Results: A higher proportion of participants diagnosed with T2D under the age of 40 were female, current smokers and treated with glucose-lowering medications, compared to participants diagnosed later in life. Participants diagnosed with T2D under the age of 40 also had higher body weight, BMI, waist circumference and body fat percentage, in addition to a more adverse lipid profile, compared to participants diagnosed at an older age. Modelling results showed that each one year reduction in age at diagnosis was significantly associated with 0.67 kg higher body weight [95% confidence interval (CI): 0.52-0.82 kg], 0.18 kg/m2 higher BMI (95%CI: 0.10-0.25) and 0.32 cm higher waist circumference (95%CI: 0.14-0.49), after adjustment for duration of diabetes and other confounders. Younger age at diagnosis was also significantly associated with higher HbA1c, total cholesterol, low-density lipoprotein cholesterol and triglycerides. Conclusion: The diagnosis of T2D earlier in life is associated with a worse cardiovascular risk factor profile, compared to those diagnosed later in life.