Introduction: Type I diabetes mellitus (T1DM) is the most common form of diabetes diagnosed in childhood. The Diabetes in Children and Adolescents Registry (Di-CARE) in Malaysia reported that many of these patients are between 10 and 19 years old. However, little is known about the association of their health literacy and numeracy with their glycemic control. Methodology: A cross-sectional study among T1DM patients aged 12 to 19 years old who attended Paediatric Endocrine Clinic at Hospital Tunku Ampuan Besar Tuanku Aishah Rohani and Hospital Tunku Azizah was conducted from March 2025 to March 2026. Participants answered 14 questions on the Diabetes Numeracy Test (DNT-14) and completed a 29-item health literacy questionnaire (myMOHLAA-Q). Data analysis was performed using SPSS version 30. The relationship of health literacy and numeracy with glucose control (HbA1c) was analyzed using Spearman’s rank order correlation. Results: A total of 43 adolescents with T1DM were recruited with a median age of 15.2 years (IQR: 13.2–17.2 years). There were 22 female (51.2%) and 21 male (48.8%) participants. The majority of the participants (n = 27, 62%) had moderate glycemic control with a median HbA1c of 8.3% (IQR: 7.5–9.6%). A Spearman’s correlation revealed a negative relationship between mean HbA1c and knowledge on blood glucose monitoring, rs (43) = −0.34, p <0.05. Additionally, positive relationships were found of knowledge on blood glucose monitoring and knowledge on insulin with total DNT-14 score, rs (43) = 0.54, p <0.001 and rs (43) = 0.78, p <0.001, respectively. The small sample size may have limited the ability to detect other significant relationships. Conclusion The majority of T1DM adolescents have moderate glycemic control. Active intervention in improving knowledge on blood glucose monitoring and insulin helps to improve glycemic control, reiterating the importance of diabetes education in the long-term management and glycemic control in adolescents with type 1 diabetes.
Adolescent ; Humans ; Diabetes Mellitus, Type 1 ; Glycemic Control ; Health Literacy

Introduction: The nutritional status of children with Attention-Deficit/Hyperactivity Disorder (ADHD) and Down Syndrome (DS) is influenced by multiple food environment determinants. However, the precise relationship between food environment determinants and nutritional outcomes in these children remains unclear. This study aimed to understand the food environment determinants that are associated with the intake and nutritional status of these children in Malaysia, Lao PDR, and Indonesia. Methods: This cross-sectional study involved 7- to 18-year-old students with ADHD and DS in three Southeast Asian countries. Sociodemographic characteristics, dietary habits, and repeated 24-hour food recall data were collected through a structured questionnaire. Anthropometric data were obtained through direct measurements and analysed using the WHO AnthroPlus software. Further analyses were done using descriptive statistics and chi-square tests. Results: Total participants were 284 children, comprised of 37.7% with ADHD and 62.3% with DS; 62.3% of the children were boys and 37.7% were girls. Among the food environment determinants collected during the study, monthly household income and school food assistance status had significant associations (p<0.05) with BMI-for-age z-score category and total energy, protein, zinc, and calcium intakes. While the country, type of residence, and type of school had significant associations with total energy, protein, zinc, and calcium intakes. Conclusions: Food environment determinants, particularly household income and access to school food assistance, significantly influence the nutritional status and intake of children with ADHD and Down Syndrome. Thus, strengthening inclusive nutrition programmes may improve outcomes for this vulnerable group in Southeast Asia.

Introduction: Cafeteria environments within universities have a significant influence over sustainable and healthy dietary behaviours. Hence, this study aimed to understand the nutritional landscape of food options in university cafeterias and to identify the factors contributing to unhealthy food options from the perspective of food service vendors. Methods: Using a mixed-methods approach, 122 food options from all 12 residential campus cafeterias in Universiti Malaya (UM) were collected between October and December 2024. All food options were grouped into (i) bread, (ii) meat dishes, (iii) drinks, (iv) Western dishes, and (v) rice- or noodle-based fried food group; they were further analysed for calories, fat, saturated fat, dietary fibre, and salt using the Malaysian Food Composition Database (MyFCD) and the Singapore Food Composition Database (SFCD). Nutrient classification (high vs. low) was based on the criteria outlined in the Labelling Guidelines 2023. Additionally, food service vendors were interviewed to explore operational challenges, with data collection ceasing upon reaching thematic saturation. The interviews were then transcribed and analysed using thematic analysis. Results: Quantitative findings showed that there were 36 bread-based meals, 16 meat-based dishes, 18 beverages, 30 Westernstyle meals, and 22 rice- or noodle-based fried foods. The study also revealed an over-reliance on high-calorie, high-fat, and low-fibre foods, with limited availability of sustainable and nutritious options. Qualitative findings highlighted the influence of affordability, vendor practices, and student preferences on campus food choices. Conclusion: The study underscored the need for internal policy intervention, improved vendor education and sustainability practices, and increased accessibility to healthier meals on campus.

Background: The genetic basis for hyperglycaemia in pregnancy remain unclear. This study aimed to uncover the genetic determinants of gestational diabetes mellitus (GDM) and investigate their applications. Methods: We performed a meta-analysis of genome-wide association studies (GWAS) for GDM in Chinese women (464 cases and 1,217 controls), followed by de novo replications in an independent Chinese cohort (564 cases and 572 controls) and in silico replication in European (12,332 cases and 131,109 controls) and multi-ethnic populations (5,485 cases and 347,856 controls). A polygenic risk score (PRS) was derived based on the identified variants. Results: Using the genome-wide scan and candidate gene approaches, we identified four susceptibility loci for GDM. These included three previously reported loci for GDM and type 2 diabetes mellitus (T2DM) at MTNR1B (rs7945617, odds ratio [OR], 1.64; 95% confidence interval [CI],1.38 to 1.96]), CDKAL1 (rs7754840, OR, 1.33; 95% CI, 1.13 to 1.58), and INS-IGF2-KCNQ1 (rs2237897, OR, 1.48; 95% CI, 1.23 to 1.79), as well as a novel genome-wide significant locus near TBR1-SLC4A10 (rs117781972, OR, 2.05; 95% CI, 1.61 to 2.62; Pmeta=7.6×10-9), which has not been previously reported in GWAS for T2DM or glycaemic traits. Moreover, we found that women with a high PRS (top quintile) had over threefold (95% CI, 2.30 to 4.09; Pmeta=3.1×10-14) and 71% (95% CI, 1.08 to 2.71; P=0.0220) higher risk for GDM and abnormal glucose tolerance post-pregnancy, respectively, compared to other individuals. Conclusion Our results indicate that the genetic architecture of glucose metabolism exhibits both similarities and differences between the pregnant and non-pregnant states. Integrating genetic information can facilitate identification of pregnant women at a higher risk of developing GDM or later diabetes.

Background: The genetic basis for hyperglycaemia in pregnancy remain unclear. This study aimed to uncover the genetic determinants of gestational diabetes mellitus (GDM) and investigate their applications. Methods: We performed a meta-analysis of genome-wide association studies (GWAS) for GDM in Chinese women (464 cases and 1,217 controls), followed by de novo replications in an independent Chinese cohort (564 cases and 572 controls) and in silico replication in European (12,332 cases and 131,109 controls) and multi-ethnic populations (5,485 cases and 347,856 controls). A polygenic risk score (PRS) was derived based on the identified variants. Results: Using the genome-wide scan and candidate gene approaches, we identified four susceptibility loci for GDM. These included three previously reported loci for GDM and type 2 diabetes mellitus (T2DM) at MTNR1B (rs7945617, odds ratio [OR], 1.64; 95% confidence interval [CI],1.38 to 1.96]), CDKAL1 (rs7754840, OR, 1.33; 95% CI, 1.13 to 1.58), and INS-IGF2-KCNQ1 (rs2237897, OR, 1.48; 95% CI, 1.23 to 1.79), as well as a novel genome-wide significant locus near TBR1-SLC4A10 (rs117781972, OR, 2.05; 95% CI, 1.61 to 2.62; Pmeta=7.6×10-9), which has not been previously reported in GWAS for T2DM or glycaemic traits. Moreover, we found that women with a high PRS (top quintile) had over threefold (95% CI, 2.30 to 4.09; Pmeta=3.1×10-14) and 71% (95% CI, 1.08 to 2.71; P=0.0220) higher risk for GDM and abnormal glucose tolerance post-pregnancy, respectively, compared to other individuals. Conclusion Our results indicate that the genetic architecture of glucose metabolism exhibits both similarities and differences between the pregnant and non-pregnant states. Integrating genetic information can facilitate identification of pregnant women at a higher risk of developing GDM or later diabetes.

Background: The genetic basis for hyperglycaemia in pregnancy remain unclear. This study aimed to uncover the genetic determinants of gestational diabetes mellitus (GDM) and investigate their applications. Methods: We performed a meta-analysis of genome-wide association studies (GWAS) for GDM in Chinese women (464 cases and 1,217 controls), followed by de novo replications in an independent Chinese cohort (564 cases and 572 controls) and in silico replication in European (12,332 cases and 131,109 controls) and multi-ethnic populations (5,485 cases and 347,856 controls). A polygenic risk score (PRS) was derived based on the identified variants. Results: Using the genome-wide scan and candidate gene approaches, we identified four susceptibility loci for GDM. These included three previously reported loci for GDM and type 2 diabetes mellitus (T2DM) at MTNR1B (rs7945617, odds ratio [OR], 1.64; 95% confidence interval [CI],1.38 to 1.96]), CDKAL1 (rs7754840, OR, 1.33; 95% CI, 1.13 to 1.58), and INS-IGF2-KCNQ1 (rs2237897, OR, 1.48; 95% CI, 1.23 to 1.79), as well as a novel genome-wide significant locus near TBR1-SLC4A10 (rs117781972, OR, 2.05; 95% CI, 1.61 to 2.62; Pmeta=7.6×10-9), which has not been previously reported in GWAS for T2DM or glycaemic traits. Moreover, we found that women with a high PRS (top quintile) had over threefold (95% CI, 2.30 to 4.09; Pmeta=3.1×10-14) and 71% (95% CI, 1.08 to 2.71; P=0.0220) higher risk for GDM and abnormal glucose tolerance post-pregnancy, respectively, compared to other individuals. Conclusion Our results indicate that the genetic architecture of glucose metabolism exhibits both similarities and differences between the pregnant and non-pregnant states. Integrating genetic information can facilitate identification of pregnant women at a higher risk of developing GDM or later diabetes.

Background: The genetic basis for hyperglycaemia in pregnancy remain unclear. This study aimed to uncover the genetic determinants of gestational diabetes mellitus (GDM) and investigate their applications. Methods: We performed a meta-analysis of genome-wide association studies (GWAS) for GDM in Chinese women (464 cases and 1,217 controls), followed by de novo replications in an independent Chinese cohort (564 cases and 572 controls) and in silico replication in European (12,332 cases and 131,109 controls) and multi-ethnic populations (5,485 cases and 347,856 controls). A polygenic risk score (PRS) was derived based on the identified variants. Results: Using the genome-wide scan and candidate gene approaches, we identified four susceptibility loci for GDM. These included three previously reported loci for GDM and type 2 diabetes mellitus (T2DM) at MTNR1B (rs7945617, odds ratio [OR], 1.64; 95% confidence interval [CI],1.38 to 1.96]), CDKAL1 (rs7754840, OR, 1.33; 95% CI, 1.13 to 1.58), and INS-IGF2-KCNQ1 (rs2237897, OR, 1.48; 95% CI, 1.23 to 1.79), as well as a novel genome-wide significant locus near TBR1-SLC4A10 (rs117781972, OR, 2.05; 95% CI, 1.61 to 2.62; Pmeta=7.6×10-9), which has not been previously reported in GWAS for T2DM or glycaemic traits. Moreover, we found that women with a high PRS (top quintile) had over threefold (95% CI, 2.30 to 4.09; Pmeta=3.1×10-14) and 71% (95% CI, 1.08 to 2.71; P=0.0220) higher risk for GDM and abnormal glucose tolerance post-pregnancy, respectively, compared to other individuals. Conclusion Our results indicate that the genetic architecture of glucose metabolism exhibits both similarities and differences between the pregnant and non-pregnant states. Integrating genetic information can facilitate identification of pregnant women at a higher risk of developing GDM or later diabetes.

Background: Apolipoprotein A-I (ApoA-I) is a key cardioprotective lipoprotein. Nevertheless, it remains unclear how ApoA-I relates to ischemic risk across glucose metabolism statuses in patients with coronary artery disease (CAD). This study investigated whether glucose metabolism status influences the association between ApoA-I and ischemic risk in CAD patients. Methods: This cohort study included 10,724 consecutive CAD patients undergoing percutaneous coronary intervention, who were classified into diabetes mellitus (DM), pre-DM, and normal glucose regulation (NGR) groups. The primary clinical endpoint was major adverse cardiac and cerebrovascular event (MACCE), defined as a composite of all-cause death, myocardial infarction, revascularization, and stroke. Results: Of the 10,232 patients ultimately included, 2,139 (20.9%) experienced MACCE over 5 years. A significant interaction was observed between ApoA-I levels and glucose metabolism status (P for interaction=0.041). In the DM group, an L-shaped association between ApoA-I and MACCE was found, with lower ApoA-I levels linked to a higher risk of MACCE (P for non-linearity= 0.044). Multivariate Cox regression analysis showed that patients in the lowest quintile of ApoA-I had a 1.327-fold increased risk of MACCE compared to those at the lowest risk (hazard ratio, 1.327; 95% confidence interval, 1.097 to 1.604). However, no significant association was observed in the pre-DM or NGR groups (both P>0.05). Conclusion This large-scale, 5-year follow-up study is the first to demonstrate that lower ApoA-I levels are associated with increased MACCE risk in CAD patients with DM, highlighting the potential value of ApoA-I in risk stratification and as a therapeutic target.

Metabolic associated fatty liver disease (MAFLD) has become one of the leading causes of cirrhosis and hepatocellular carcinoma. Therefore, identifying high-risk MAFLD patients accurately and providing monitoring and treatment is crucial.Invasive liver biopsy has inherent defects such as high costs, low patient acceptance, and significant inconsistencies in readings between individual pathologists. Non-invasive testing technologies have become a core measure in the management of MAFLD. This paper summarizes and discusses the latest application progress of non-invasive testing technologies in the field of MAFLD and explores the key aspects that urgently need improvement, with the aim of providing clinical doctors with references for effectively assessing the progression trends of MAFLD patients and implementing intervention treatments.

Metabolic associated fatty liver disease (MAFLD) has become one of the leading causes of cirrhosis and hepatocellular carcinoma. Therefore, identifying high-risk MAFLD patients accurately and providing monitoring and treatment is crucial.Invasive liver biopsy has inherent defects such as high costs, low patient acceptance, and significant inconsistencies in readings between individual pathologists. Non-invasive testing technologies have become a core measure in the management of MAFLD. This paper summarizes and discusses the latest application progress of non-invasive testing technologies in the field of MAFLD and explores the key aspects that urgently need improvement, with the aim of providing clinical doctors with references for effectively assessing the progression trends of MAFLD patients and implementing intervention treatments.