Search

BackgroundType 2 diabetes mellitus (T2DM) is an international problem of alarming epidemic proportions. T2DM can develop due to multiple factors, and it usually begins with prediabetes. Fortunately, this disease can be prevented by following a healthy lifestyle. However, many health care systems fail to properly educate the public on disease prevention and to offer support in embracing behavioral interventions to prevent diabetes. SMS messaging has been combined with cost-effective ways to reach out to the population at risk for medical comorbidities. To our knowledge, the use of nationwide SMS messaging in the Middle East as a screening tool to identify individuals who might be at risk of developing T2DM has not been reported in the literature. ObjectiveThe primary aim of this study was to assess the feasibility of conducting a series of SMS messaging campaigns directed at random smartphone users in Kuwait for the detection and prevention of T2DM. It was predicted that 1% of those receiving the text message would find it relevant and participate in the study. The secondary aim of this study was to assess the incidence of participation of those who were forwarded the initial text message by family members and friends. MethodsIn this study, 5 separate text message screening campaigns were launched inviting recipients to answer 6 questions to determine the risk of developing T2DM. If subjects agreed to participate, a link to the prediabetes screening test devised by the Centers for Disease Control and Prevention was automatically transmitted to their mobile devices. Those identified as high risk were invited to participate in a diabetes prevention program. ResultsA total of 180,000 SMSs were sent to approximately 6% of the adult population in Kuwait. Of these, 0.14% (260/180,000) of the individuals who received the SMS agreed to participate, of whom 58.8% (153/260) completed the screening. Surprisingly, additional surveys were completed by 367 individuals who were invited via circulated SMS messages forwarded by family members and friends. Altogether, 23.3% (121/520) qualified and agreed to participate in a diabetes prevention program. The majority of those who chose to participate in the prevention program were overweight, aged 45-65 years, and reported being less physically active than those who chose not to participate (χ22=42.1, P

BackgroundIntensive lifestyle interventions are effective in reducing the risk of type 2 diabetes, but the implementation of learnings from landmark studies is expensive and time consuming. The availability of digital lifestyle interventions is increasing, but evidence of their effectiveness is limited. ObjectiveThis randomized controlled trial (RCT) aimed to test the feasibility of a web-based diabetes prevention program (DPP) with step-dependent feedback messages versus a standard web-based DPP in people with prediabetes. MethodsWe employed a two-arm, parallel, single-blind RCT for people at high risk of developing diabetes. Patients with a hemoglobin A1c (HbA1c) level of 39-47 mmol/mol were recruited from 21 general practices in London. The intervention integrated a smartphone app delivering a web-based DPP course with SMS texts incorporating motivational interviewing techniques and step-dependent feedback messages delivered via a wearable device over 12 months. The control group received the wearable technology and access to the web-based DDP but not the SMS texts. As this was a feasibility study, the primary aim was to estimate potential sample size at different stages of the study, including the size of the target study population and the proportion of participants who consented, were randomized, and completed follow-up. We also measured the main outcomes for a full-scale RCT, namely, change in weight and physical activity at 6- and 12-month follow-ups, and secondary outcomes, including changes in the HbA1c level, blood pressure, waist circumference, waist-to-hip ratio, and lipid levels. ResultsWe enrolled 200 participants: 98 were randomized to the intervention and 102 were randomized to the control group. The follow-up rate was higher in the control group (87/102, 85.3%) than in the intervention group (69/98, 70%) at 12 months. There was no treatment effect on weight at 6 months (mean difference 0.15; 95% CI −0.93 to 1.23) or 12 months (mean difference 0.07 kg; 95% CI −1.29 to 1.44) or for physical activity levels at 6 months (mean difference −382.90 steps; 95% CI −860.65 to 94.85) or 12 months (mean difference 92.64 steps; 95% CI −380.92 to 566.20). We did not observe a treatment effect on the secondary outcomes measured at the 6-month or 12-month follow-up. For the intervention group, the mean weight was 92.33 (SD 15.67) kg at baseline, 91.34 (SD 16.04) kg at 6 months, and 89.41 (SD 14.93) kg at 12 months. For the control group, the mean weight was 92.59 (SD 17.43) kg at baseline, 91.71 (SD 16.48) kg at 6 months, and 91.10 (SD 15.82) kg at 12 months. In the intervention group, the mean physical activity was 7308.40 (SD 4911.93) steps at baseline, 5008.76 (SD 2733.22) steps at 6 months, and 4814.66 (SD 3419.65) steps at 12 months. In the control group, the mean physical activity was 7599.28 (SD 3881.04) steps at baseline, 6148.83 (SD 3433.77) steps at 6 months, and 5006.30 (SD 3681.1) steps at 12 months. ConclusionsThis study demonstrates that it is feasible to successfully recruit and retain patients in an RCT of a web-based DPP. Trial RegistrationClinicalTrials.gov NCT02919397; http://clinicaltrials.gov/ct2/show/NCT02919397

Aim: To compare hepatic stiffness and fat fraction in patients with obesity and type 1 diabetes (T1D) with type 2 diabetes (T2D) with a similar body mass index (BMI). Methods: In this prospective cross‐sectional study, 90 participants with T1D (BMI 30.5 ± 4.5 kg/m2; diabetes duration 20.5 ± 9.8 years; HbA1c 8.2% ± 1.4%) and 69 with T2D (BMI: 30.8 ± 4.6 kg/m2; diabetes duration: 11.7 ± 7.8 years; HbA1c: 7.3% ± 1.4%) were included. Liver fat fraction and stiffness were examined by magnetic resonance imaging and elastography, respectively. Logistic regressions were used to evaluate associations with biomedical variables. Results: The mean liver stiffness score in patients with obesity and T1D was 2.2 ± 0.5 kPa, while in T2D it was 2.6 ± 0.8 kPa (P <.001). The liver fat fraction in patients with obesity and T1D was 3.7% ± 6.3%, and in T2D it was 10.6% ± 7.9% (P <.001). Metabolic dysfunction‐associated steatotic liver disease (MASLD) was present in 13.3% of patients with T1D and in 69.6% of patients with T2D, whereas fibrosis was suggested in 7.8% of patients with T1D and in 27.5% of patients with T2D. Liver stiffness was four times higher in patients with T2D compared with those with T1D (odds ratio = 5.4, 95% confidence interval: 2.1‐13.6, P <.001). Aspartate transaminase (AST), alanine transaminase, gamma‐glutamyl transferase (GGT), triglycerides and the android‐to‐gynoid ratio were associated with elevated fat fraction in both cohorts. AST and GGT were associated with elevated liver stiffness in both cohorts. Conclusions: Patients with obesity and T1D had lower liver fat and liver stiffness compared with those patients with T2D, despite similar levels of BMI, a longer duration of diabetes and worse glycaemic control. [ABSTRACT FROM AUTHOR]

This study aimed to investigate the association of physical activity and sleep metrics, measured via wrist-worn accelerometers, with depression in people with type 1 diabetes. Patients and Methods: People with type 1 diabetes were recruited from the Dasman Diabetes Institute in Kuwait and were invited to wear a wrist-worn accelerometer device for 7 days. Mean physical activity (overall acceleration), inactivity, light activity, moderate activity, vigorous activity, the distribution of physical activity intensity (intensity gradient), sleep duration and sleep efficiency were quantified from the accelerometer data. The associations of these metrics with depression were investigated using multiple linear regression. Results: A total of 551 people with type 1 diabetes (age 33.1 (9.5) years) were included. Overall physical activity (B = − 0.09, CI = − 0.14 to – 0.04), moderate intensity activity (B = − 0.02, CI = − 0.02 to − 0.01), vigorous intensity activity (B = − 0.16, CI = − 0.27 to − 0.05), and the intensity gradient (B = − 2.11, CI = − 3.51 to − 0.72) were negatively associated with depression score (p < 0.01) and these associations remain significant even after adjustment for age, sex, diabetes duration, and BMI. However, sleep duration and efficiency were not associated with depression. After mutual adjustment overall physical activity (B = − 0.07, CI = − 0.12 to − 0.01), but not the intensity gradient (B = − 0.90, CI = − 2.47 to 0.68), remained associated with depression. Conclusion: Overall, moderate and vigorous physical activity, and the intensity gradient were associated with lower symptoms of depression. Overall physical activity, rather than the distribution of activity intensity, appears more important in depression. This information can help guide physical activity interventions to improve depression in people with type 1 diabetes. [ABSTRACT FROM AUTHOR]

Background: People living with diabetes often encounter psychosocial challenges, including diabetes distress and depression. Despite this, little research has focused on the co-occurrence of these conditions. This study aimed to explore the prevalence of depressive symptoms and diabetes distress in people with type 1 diabetes in Kuwait and to identify clinical and demographic factors associated with these conditions. Methods: A total of 832 people with type 1 diabetes (females: 54.1%, mean age: 29 ± 8.5 years), were invited to participate in Dose Adjustment for Normal Eating (DAFNE) course. Diabetes distress was measured using the Problem Areas in Diabetes (PAID) scale and depressive symptoms were measured using the Patient Health Questionnaire-9 (PHQ-9). Depressive symptoms were defined as PHQ-9 scores =10. Data on biomedical outcomes, lifestyle factors, and sociodemographic information were collected. Results: The prevalence rates of diabetes distress and depressive symptoms were 27.8% and 38.3%, respectively. Notably, 19.6% of people experienced both conditions. In the regression analysis, PAID scale and PHQ-9 scores were significantly associated, patients with higher score on depressive symptoms scale were more likely to suffer diabetes distress (B= 2.65, p < 0.001). Female sex (odds ratio [OR]= 2.2, 95% CI= 1.5, 3.2), higher hemoglobin A1c levels (OR= 1.6, 95% CI= 1.0, 2.5), obesity (OR= 1.7, 95% CI= 1.1, 2.8), inactivity (OR= 2.4, 95% CI= 1.6, 3.6), microvascular complications (OR= 2.8, 95% CI= 1.5, 5.4), and lipohypertrophy (OR= 1.7, 95% CI= 1.1, 2.5) were associated with greater odds for the cooccurrence of diabetes distress and depressive symptoms (p< 0.05 for all). Conclusion: The majority of people with type 1 diabetes in Kuwait experience both diabetes distress and depressive symptoms. The strong correlation between diabetes distress and depressive symptoms suggests mutual predictability. The co-occurrence of both symptoms is associated with many sociodemographic and clinical factors. [ABSTRACT FROM AUTHOR]