Background: Delivering self-management support to people with type 2 diabetes mellitus is essential to reduce the health system burden and to empower people with the skills, knowledge, and confidence needed to take an active role in managing their own health. Objective: This study aims to evaluate the adoption, use, and effectiveness of the My Diabetes Coach (MDC) program, an app-based interactive embodied conversational agent, Laura, designed to support diabetes self-management in the home setting over 12 months. Methods: This randomized controlled trial evaluated both the implementation and effectiveness of the MDC program. Adults with type 2 diabetes in Australia were recruited and randomized to the intervention arm (MDC) or the control arm (usual care). Program use was tracked over 12 months. Coprimary outcomes included changes in glycated hemoglobin (HbA1c) and health-related quality of life (HRQoL). Data were assessed at baseline and at 6 and 12 months, and analyzed using linear mixed-effects regression models. Results: A total of 187 adults with type 2 diabetes (mean 57 years, SD 10 years; 41.7% women) were recruited and randomly allocated to the intervention (n=93) and control (n=94) arms. MDC program users (92/93 participants) completed 1942 chats with Laura, averaging 243 min (SD 212) per person over 12 months. Compared with baseline, the mean estimated HbA1c decreased in both arms at 12 months (intervention: 0.33% and control: 0.20%), but the net differences between the two arms in change of HbA1c (−0.04%, 95% CI −0.45 to 0.36; P=.83) was not statistically significant. At 12 months, HRQoL utility scores improved in the intervention arm, compared with the control arm (between-arm difference: 0.04, 95% CI 0.00 to 0.07; P=.04). Conclusions: The MDC program was successfully adopted and used by individuals with type 2 diabetes and significantly improved the users’ HRQoL. These findings suggest the potential for wider implementation of technology-enabled conversation-based programs for supporting diabetes self-management. Future studies should focus on strategies to maintain program usage and HbA1c improvement. Trial Registration: Australia New Zealand Clinical Trials Registry (ACTRN) 12614001229662; https://anzctr.org.au/Trial/Registration/TrialReview.aspx?ACTRN=12614001229662

To determine, the predictors of incident metabolic syndrome (MetS) in a community-based cohort of West Asians, during a mean follow-up of 9.3 years, a sample of 2858 non-MetS Iranian adults aged ≥ 20 years were examined at baseline and followed at three year intervals during three consecutive phases. The MetS was defined using the joint interim statement. Cox proportional hazard regression was used to determine the independent variables associated with incident MetS. Overall, 1117 new cases MetS were identified resulting in an incidence rate of 550.9/10000 person years (95% CI: 519.5-584.2). The corresponding incidence rates among women and men were 433.5/10000 person years (95% CI: 398.8-471.2) and 749.2/10000 person years (95% CI: 689.9-813.5), respectively. Baseline-adjusted predictors of developing MetS included all of the MetS components, being overweight or obese in both gender, and family history of diabetes and age only in women. There were significant effect modifications of gender on age (P<0.001), high blood pressure (0.026), high waist circumference (P<0001) and obesity categories (all P ≤ 0.01) in multivariate analysis. After considering HOMA–IR in the model, among women, all of the MetS predictors as well as those with HOMA-IR ≥ 2.23 showed a significant risk for incident MetS [HR: 1.63 (1.16-2.28)]; however, among men all the MetS components (WC was marginally significant) as well as the fourth quartile of HOMA-IR [HR: 1.50 (1.03-2.17)] and being overweight showed a significant risk. Finally, in the pooled analysis, we showed that female gender had lower risk for incident MetS than male [HR: 0.58 (0.47-0.70)]. In the Iranian population, high incidence of MetS, especially among men, was shown. Our findings confirmed that sex- specific risk predictors should be considered in primary prevention for incident MetS.

To investigate secular trends in cardiovascular disease (CVD) risk factors during a decade of follow-up in a Middle Eastern cohort, and to compare observed trends between diabetic and non-diabetic populations. In a population of 6181 participants (2622 males and 3559 females), diabetes status and CVD risk factors were evaluated in 4 study phases from 1999–2011. 1045 subjects had type 2 diabetes mellitus at baseline and 5136 participants were diabetes-free. To examine the trends of CVD risk factors, generalized estimation equation models were constructed. The interaction between the diabetes status and each phase of the study was checked in a separate model. During the follow-up period diabetic females significantly gained better control of their blood pressure, serum low density lipoprotein cholesterol and general and central obesity measures compared to non-diabetic counterparts, although 60% of them had high BP and 64% had high serum LDL-C levels till the end of the study. Diabetic males however, experienced significantly better control on their serum LDL-C and general and central obesity measures compared to their non-diabetic controls; but 24% of them were still smoker, 63% had high BP and 60% had high serum LDL-C levels at the end of the follow-up (all Ps _interaction <0.05). Use of lipid-lowering and antihypertensive medications increased consistently in both diabetic and non-diabetic populations. Although CVD risk factors have been controlled to some extent among diabetic population in Iran, still high numbers of people with diabetes have uncontrolled CVD risk factors that prompt more attention.

Obesity indicators are known to predict the presence of type 2 diabetes mellitus (T2DM); however, evidence for which indicator best identifies undiagnosed T2DM in the Indian population is still very limited. In the present study we examined the utility of different obesity indicators to identify the presence of undiagnosed T2DM and determined their appropriate cut point for each obesity measure. Individuals were recruited from the large-scale population-based Kerala Diabetes Prevention Program. Oral glucose tolerance tests was performed to diagnose T2DM. Receiver operating characteristic (ROC) curve analyses were used to compare the association of different obesity indicators with T2DM and to determine the optimal cut points for identifying T2DM. A total of 357 new cases of T2DM and 1352 individuals without diabetes were identified. The mean age of the study participants was 46⋅4 (sd 7⋅4) years and 62 % were men. Waist circumference (WC), waist:hip ratio (WHR), waist:height ratio (WHtR), BMI, body fat percentage and fat per square of height were found to be significantly higher (P < 0⋅001) among those with diabetes compared with individuals without diabetes. In addition, ROC for WHR (0⋅67; 95 % 0⋅59, 0⋅75), WHtR (0⋅66; 95 % 0⋅57, 0⋅75) and WC (0⋅64; 95 % 0⋅55, 0⋅73) were shown to better identify patients with T2DM. The proposed cut points with an optimal sensitivity and specificity for WHR, WHtR and WC were 0⋅96, 0⋅56 and 86 cm for men and 0⋅88, 0⋅54 and 83 cm for women, respectively. The present study has shown that WHR, WHtR and WC are better than other anthropometric measures for detecting T2DM in the Indian population. Their utility in clinical practice may better stratify at-risk patients in this population than BMI, which is widely used at present.