METHODOLOGY: FPG and HbA1c were taken from 40,667 eligible TMC participants that have no previous history of diabetes, aged between 35-70 years and were recruited from 2006 - 2012. Participants were classified as normal, diabetes and pre-diabetes based on the 2006 World Health Organization (WHO) criteria. Statistical analyses were performed using ANOVA and Chi-square test, while Pearson correlation and Cohen's kappa were used to examine the concordance rate between FPG and HbA1c.

RESULTS: The study samples consisted of 16,224 men and 24,443 women. The prevalence of diabetes among the participants was 5.7% and 7.5% according to the FPG and HbA1c level, respectively. Based on FPG, 10.6% of the participants had pre-diabetes but this increased to 14.2% based on HbA1c (r=0.86; P<0.001). HbA1c had a sensitivity of 58.20 (95% CI: 56.43, 59.96) and a specificity of 98.59 (95% CI: 98.46, 98.70).

Methods: A cross-sectional study was conducted at the Universiti Kebangsaan Malaysia Medical Centre (UKMMC) using outpatient population diabetic patients. Demographic data on social and clinical characteristics were collected from participants. Several questionnaires were administered, including the Beck Depression Inventory-II (BDI-II) to measure depressive symptoms, the Generalized Anxiety Disorder-7 (GAD-7) to assess anxiety symptoms, the Big Five Inventory (BFI) to evaluate personality traits, and the WHO Quality of Life-BREF (WHOQOL-BREF) to assess QOL. Multivariate binary logistic regression was performed to determine the predictors of poor glycaemic control.

Results: 300 patients with diabetes mellitus were recruited, with the majority (90%) having type 2 diabetes. In this population, the prevalence of poor glycaemic control (HbA1C ≥ 7.0%) was 69%, with a median HbA1C of 7.6% (IQR = 2.7). Longer duration of diabetes mellitus and a greater number of days of missed medications predicted poor glycaemic control, while older age and overall self-perception of QOL protected against poor glycaemic control. No psychological factors were associated with poor glycaemic control.

METHODS: Population-based surveys included 30,721 Malay, 10,865 Indian and 25,296 Chinese adults from The Malaysian Cohort, and 413,737 White adults from UK Biobank. Sex-specific linear regression models estimated associations of anthropometry and body composition (body mass index [BMI], waist circumference [WC], fat mass, appendicular lean mass) with systolic blood pressure (SBP), low-density lipoprotein cholesterol (LDL-C), triglycerides and HbA1c.

RESULTS: Compared to Malay and Indian participants, Chinese adults had lower BMI and fat mass while White participants were taller with more appendicular lean mass. For BMI and fat mass, positive associations with SBP and HbA1c were strongest among the Chinese and Malay and weaker in White participants. Associations with triglycerides were considerably weaker in those of Indian ethnicity (eg 0.09 [0.02] mmol/L per 5 kg/m2 BMI in men, vs 0.38 [0.02] in Chinese). For appendicular lean mass, there were weak associations among men; but stronger positive associations with SBP, triglycerides, and HbA1c, and inverse associations with LDL-C, among Malay and Indian women. Associations between WC and risk factors were generally strongest in Chinese and weakest in Indian ethnicities, although this pattern was reversed for HbA1c.

METHODS: This research was conducted following the PRISMA guidelines. The databases that had been searched included Web of Science, PubMed, Scopus, Cochrane Library and Ovid from 2017 to 2022. Study characteristics were retrieved and study outcomes such as adherence status and diabetes control were extracted and quantitatively analysed through meta-analysis.

RESULTS: Eight studies met the final inclusion criteria and were included in the analysis, contributing to a total of 884 subjects. The methodological quality of the included studies was variable. Three studies reported statistically significant improvement in medication adherence through mobile apps intervention. Additionally, the mobile apps intervention proved effective in reducing glycaemic outcomes. As compared to non-mobile apps users, glycated haemoglobin (HbA1c) significantly decreased by 0.36% (95% CI -0.47% to -0.25%), whereas fasting plasma glucose (FPG) significantly decreased by 16.75 mg/dL (95% CI -17.60 mg/dL to -15.80 mg/dL).

OBJECTIVE: This study sought to identify demographic, clinical, and genetic factors that may contribute to increased insulin resistance or worsening of glycaemic control in patients with T2DM.

SETTING: This prospective cohort study included 156 patients with T2DM and severe or acute hyperglycaemia who were treated with insulin at any medical ward of the National University of Malaysia Medical Centre.

METHOD: Insulin resistance was determined using the homeostatic model assessment-insulin resistance index. Glycaemic control during the episode of hyperglycaemia was assessed as the degree to which the patient achieved the target glucose levels. The polymerase chain reaction-restriction fragment length polymorphism method was used to identify polymorphisms in insulin receptor substrate (IRS) genes.

MAIN OUTCOME MEASURE: Identification of possible predictors (demographic, clinical, or genetic) for insulin resistance and glycaemic control during severe/acute hyperglycaemia.

RESULTS: A polymorphism in IRS1, r.2963 G>A (p.Gly972Arg), was a significant predictor of both insulin resistance [odds ratios (OR) 4.48; 95 % confidence interval (CI) 1.2-16.7; P = 0.03) and worsening of glycaemic control (OR 6.04; 95 % CI 0.6-64.6; P = 0.02). The use of loop diuretics (P < 0.05) and antibiotics (P < 0.05) may indirectly predict worsening of insulin resistance or glycaemic control in patients with severe/acute hyperglycaemia.

METHODOLOGY: The AFES ASEAN Survey Of Needs in Endocrinology (AFES A.S.-O.N.E.) was an open-ended questionnaire that was sent to the presidents and representatives of the AFES member countries by email. Responses from Societies were collated and synthesized to obtain perspectives on the emergent issues in endocrinology in the Southeast Asian region during this pandemic.

RESULTS: The burden of COVID-19 cases varied widely across the AFES member countries, with the least number of cases in Vietnam and Myanmar, and the greatest number of cases in either the most populous countries (Indonesia and the Philippines), or a country with the highest capability for testing (Singapore). The case fatality rate was also the highest for Indonesia and the Philippines at around 6%, and lowest for Vietnam at no fatalities. The percentage with diabetes among patients with COVID-19 ranged from 5% in Indonesia to 20% in Singapore, approximating the reported percentages in China and the United States. The major challenges in managing patients with endocrine diseases involved inaccessibility of health care providers, clinics and hospitals due to the implementation of lockdowns, community quarantines or movement control among the member countries. This led to disruptions in the continuity of care, testing and monitoring, and for some, provision of both preventive care and active management including surgery for thyroid cancer or pituitary and adrenal tumors, and radioactive iodine therapy. Major disruptions in the endocrine fellowship training programs were also noted across the region, so that some countries have had to freeze hiring of new trainees or to revise both program requirements and approaches to training due to the closure of outpatient endocrine clinics. The same observations are seen for endocrine-related researches, as most research papers have focused on the pandemic. Finally, the report ends by describing innovative approaches to fill in the gap in training and in improving patient access to endocrine services by Telemedicine.

METHODS: A total of 110 hospitalized geriatric patients aged 60 years and older were selected using convenience sampling method in a cross-sectional study. Sociodemographic data and medical history were obtained from the medical records. Questionnaires were used during the in-person semistructured interviews, which were conducted in the wards. Linear regression analyses were used to determine the predictors of each domain of quality of life.

RESULTS: Multiple regression analysis showed that activities of daily living, depression, and appetite were the determinants of physical health domain of quality of life (R(2)=0.633, F(3, 67)=38.462; P<0.001), whereas depression and instrumental activities of daily living contributed to 55.8% of the variability in psychological domain (R(2)=0.558, F(2, 68)=42.953; P<0.001). Social support and cognitive status were the determinants of social relationship (R(2)=0.539, F(2, 68)=39.763; P<0.001) and also for the environmental domain of the quality of life (R(2)=0.496, F(2, 68)=33.403; P<0.001).