The Lancet Commission on diabetes: using data to transform diabetes care and patient lives

Efficient and Effective Diabetes Care in the Era of Digitalization and Hypercompetitive Research Culture: A Focused Review in the Western Pacific Region with Malaysia as a Case Study

There are approximately 220 million (about 12% regional prevalence) adults living with diabetes mellitus (DM) with its related complications, and morbidity knowingly or unconsciously in the Western Pacific Region (WP). The estimated healthcare cost in the WP and Malaysia was 240 billion USD and 1.0 billion USD in 2021 and 2017, respectively, with unmeasurable suffering and loss of health quality and economic productivity. This urgently calls for nothing less than concerted and preventive efforts from all stakeholders to invest in transforming healthcare professionals and reforming the healthcare system that prioritizes primary medical care setting, empowering allied health professionals, improvising health organization for the healthcare providers, improving health facilities and non-medical support for the people with DM. This article alludes to challenges in optimal diabetes care and proposes evidence-based initiatives over a 5-year period in a detailed roadmap to bring about dynamic and efficient healthcare services that are effective in managing people with DM using Malaysia as a case study for reference of other countries with similar backgrounds and issues. This includes a scanning on the landscape of clinical research in DM, dimensions and spectrum of research misconducts, possible common biases along the whole research process, key preventive strategies, implementation and limitations toward high-quality research. Lastly, digital medicine and how artificial intelligence could contribute to diabetes care and open science practices in research are also discussed.

Artificial intelligence based predictive tools for identifying type 2 diabetes patients at high risk of treatment Non-adherence: A systematic review

AIMS

Several Artificial Intelligence (AI) based predictive tools have been developed to predict non-adherence among patients with type 2 diabetes (T2D). Hence, this study aimed to describe and evaluate the methodological quality of AI based predictive tools for identifying T2D patients at high risk of treatment non-adherence.

METHODS

A systematic search was conducted across multiple databases including, EMBASE, Cochrane Library, MedLine, and Google Scholar search. The Prediction model Risk Of Bias ASsessment Tool (PROBAST) was used to assess the quality of studies. The performances of tools were assessed by Area Under the Curve (AUC), precision, recall, C-index, accuracy, sensitivity, specificity or F1 score.

RESULTS

Most studies measured predictive ability using AUC (75 %), and some only reported precision (25 %), recall (12.5 %), C-index (12.5 %), accuracy (37.5), sensitivity (12.5 %), specificity (12.5 %) or F1 score (25 %). All tools had moderate to high predictive ability (AUC > 0.70). However, only one study conducted external validation. Demographic characteristics, HbA1c, glucose monitoring data, and treatment details were typical factors used in developing tools.

CONCLUSIONS

The existing AI based tools holds significant promise for improving diabetes care. However, future studies should focus on refining the existing tools, validating in other settings, and evaluating the cost-effectiveness of AI-supported interventions.

Real world evidence of insulin and biosimilar insulin therapy-Opportunities to improve adherence, outcomes and cost-effectiveness

Insulin has been discovered for more than a century; however, its benefits to people with diabetes are yet to be fully realized due to barriers related to access, quality of care and costs. Insulin therapy remains the cornerstone of diabetes management. The multicausality of diabetes and its subtypes calls for comprehensive phenotyping and use of biomarkers to ensure timely use of insulin to achieve early glycaemic control for long-term benefits. Biosimilar insulins are biologic products that closely resemble originator insulins without significant differences in safety or efficacy. The lower investment costs needed for research and development make biosimilar insulin more affordable to improve access. While the efficacy of insulin products is proven in controlled settings, real world evidence (RWE) from real world data (RWD) plays a crucial role in assessing the safety, efficacy, cost-effectiveness, adherence to and impacts of different insulin products, including biosimilars, on clinical outcomes. In this narrative review, we summarized the trends of insulin use and patterns of biosimilar insulin utilization in real world practice across different regions. We reviewed RWE on clinical safety, efficacy and cost-effectiveness of biosimilar insulin, as well as therapeutic inertia and non-adherence with insulin therapy. We also highlighted barriers to insulin adherence and enablers for persistence, along with potential solutions to promote the use of insulin and technologies for optimizing glycaemic control in different subtypes of diabetes. During our extensive literature review, we identified data gaps in the usage of biosimilar insulin in real world practice. We advocate for implementing a diabetes register designed fit-for-purpose, managed by a trained doctor-nurse team with system support, to generate RWE. By setting up registers with structured data collection, we can generate high quality data for integrative analysis with electronic health records (EHR) and health claims to evaluate the impacts of insulin products and other diabetes programmes on clinical outcomes, quality of life and healthcare costs to inform practice and policies. PLAIN LANGUAGE SUMMARY: Diabetes affects approximately 10.5% of the global population and insulin is a vital treatment for diabetes management. Insulin was discovered more than a century ago, although its benefits to people with diabetes are yet to be fully realized due to barriers related to access, quality of care, and costs. Real-world evidence from real-world data plays a crucial role in assessing the safety, efficacy, cost-effectiveness, adherence to, and impacts of different insulin products, including biosimilars, on clinical outcomes. In this publication, the authors provided a detailed review of the patterns of use and cost-effectiveness of biosimilar insulin, and identified major data gaps. The authors explained the methodology, utility, and limitations of generating real-world evidence based on real-world data from sources such as registers, electronic health records and health claims for assessing treatment effectiveness and safety. The authors proposed the implementation of a purpose-built diabetes register with structured data collection, managed by a trained doctor-nurse team with system support. These high-quality data can be integrated with electronic health records and health claims for evaluation of interventions, including insulin on outcomes, quality of life, and costs to inform practice and policy. Based on these premises and available data, the authors summarized trends in insulin use including biosimilar insulin, and reviewed real-world evidence on the safety, efficacy, and cost-effectiveness of these products. They also identified barriers like therapeutic inertia and non-adherence, discussed enablers for persistence, and proposed solutions to evaluate the impacts of insulin products and other diabetes programs on clinical outcomes, quality of life, and healthcare costs to inform practice and policies.

Impact of bodyweight loss on type 2 diabetes remission: a systematic review and meta-regression analysis of randomised controlled trials

BACKGROUND

Bodyweight loss is associated with type 2 diabetes remission; however, the quantitative relationship between the degree of bodyweight loss and the likelihood of remission, after controlling for confounding factors, remains unknown. We aimed to analyse the relationship between the degree of bodyweight loss and diabetes remission after controlling for various confounding factors, and to provide estimates for the effect sizes of these factors on diabetes remission.

METHODS

This systematic review and meta-regression analysis followed Cochrane and PRISMA guidelines to systematically review, synthesise, and report global evidence from randomised controlled trials done in individuals with type 2 diabetes and overweight or obesity. The outcome was the proportion of participants with complete diabetes remission (HbA1c <6·0% [42 mmol/mol] or fasting plasma glucose [FPG] <100 mg/dL [5·6 mmol/L], or both, with no use of glucose-lowering drugs) or partial diabetes remission (HbA1c <6·5% [48 mmol/mol] or FPG <126 mg/dL [7·0 mmol/L], or both, with no use of glucose-lowering drugs) at least 1 year after a bodyweight loss intervention. We searched PubMed, Embase, and trial registries from database inception up to July 30, 2024. Data were extracted from published reports. Meta-analyses and meta-regressions were performed to analyse the data. The study protocol is registered with PROSPERO (CRD42024497878).

FINDINGS

We identified 22 relevant publications, encompassing 29 outcome measures of complete diabetes remission and 33 outcome measures of partial remission. The pooled mean proportion of participants with complete remission 1 year after the intervention was 0·7% (95% CI 0·1-4·6) in those with bodyweight loss less than 10%, 49·6% (40·4-58·9) in those with bodyweight loss of 20-29%, and 79·1% (68·6-88·1) in those with bodyweight loss of 30% or greater; no studies reported on complete remission with 10-19% bodyweight loss. The pooled mean proportion of participants with partial remission 1 year after the intervention was 5·4% (95% CI 2·9-8·4) in those with bodyweight loss less than 10%, 48·4% (36·1-60·8) in those with 10-19% bodyweight loss, 69·3% (55·8-81·3) in those with bodyweight loss of 20-29%, and 89·5% (80·0-96·6) in those with bodyweight loss of 30% or greater. There was a strong positive association between bodyweight loss and remission. For every 1 percentage point decrease in bodyweight, the probability of reaching complete remission increased by 2·17 percentage points (95% CI 1·94-2·40) and the probability of reaching partial remission increased by 2·74 percentage points (2·48-3·00). No significant or appreciable associations were observed between age, sex, race, diabetes duration, baseline BMI, HbA1c, insulin use, or type of bodyweight loss intervention and remission. Overall, data were derived from randomised controlled trials with a low risk of bias in all quality domains.

INTERPRETATION

A robust dose-response relationship between bodyweight loss and diabetes remission was observed, independent of age, diabetes duration, HbA1c, BMI, and type of intervention. These findings highlight the crucial role of bodyweight loss in managing type 2 diabetes and reducing the risk of diabetes-related complications.

FUNDING

Biomedical Research Program at Weill Cornell Medicine-Qatar and the Qatar National Research Fund (a member of Qatar Foundation).

Global, regional, and national burden of diabetes and its risk factors in women of child-bearing age, from 1990 to 2021

OBJECTIVE

To present a detailed analysis of temporal trends in the burden of diabetes mellitus (DM) among women of childbearing age (WCBA) across global and regional levels from 1990 to 2021.

STUDY DESIGN

Population-based Study.

METHODS

This study extracted prevalence, disability-adjusted life years (DALYs), and risk factors in WCBA from the Global Burden of Disease (GBD) database. The average annual percent change (AAPC) was utilized to evaluate the evolving trends in the burden of DM.

RESULTS

From 1990 to 2021, the global age-standardized prevalence of diabetes in WCBA rose from 1.80 % to 4.06 %, with an AAPC of 2.68 %. While the age-standardized prevalence of type 1 DM (T1DM) has grown and the age-standardized DALYs associated with T1DM declined from 51.8 to 47.4 per 100,000 population. Conversely, the age-standardized DALYs rate for type 2 DM (T2DM) nearly doubled from 183.8 to 353.8 per 100,000 population. The DALYs rate for total DM rose almost three times faster in countries with high-middle Sociodemographic Index (SDI) compared to those with low SDI (AAPC: 2.10 % versus 0.71 %). High fasting plasma glucose (HFPG) levels remained the most significant risk factor for DALYs, while high body-mass index (BMI) and low physical activity for T2DM exhibited the largest increases in this period.

CONCLUSIONS

From 1990 to 2021, a global upward trend in the prevalence of DM among WCBA has been observed. HFPG remains a major risk factor for both T1DM and T2DM, while high BMI and low physical activity have emerged as significant challenges in managing T2DM.

Identifying and visualising temporal trajectories of hospitalisations for traditional and non-traditional complications in people with type 2 diabetes: a population-based study

Background

People with type 2 diabetes are increasingly susceptible to complications that are not specific to diabetes. We aimed to examine the temporal trajectories of hospitalisations for traditional and non-traditional complications in people with type 2 diabetes.

Methods

We included 758,254 people with incident type 2 diabetes between 2002 and 2018 in Hong Kong, followed up until 2019. We included hospitalisations for 72 selected diseases and all-cause deaths. We derived the temporal trajectories of hospitalisations based on pairs of disease associations and identified trajectory clusters using Markov Cluster Algorithm.

Findings

During a median follow-up of 7.8 (IQR: 4-12) years, 57.6% of people experienced a hospitalisation for any of the 72 selected diseases and 22.6% of people died. Among the 5184 directional disease pairs, 95 were identified as having a significant and directional association. The three most common disease pairs were hospitalisations for urinary tract infection followed by pneumonia, ischemic heart disease followed by heart failure, and ischemic stroke followed by pneumonia. Cardiovascular and kidney diseases were predominant in the hospitalisation trajectories. However, these traditional complications had complex associations both among themselves and with various non-traditional complications across multiple systems. Three distinct trajectory clusters were identified, with heart failure/chronic kidney disease, pneumonia, and urinary tract infection as central diseases.

Interpretation

Cardiovascular and kidney diseases interacted with a broad set of non-traditional complications to influence the overall patterns of hospitalisation progression in people with diabetes, highlighting the need to broaden diabetes care to consider complications beyond the traditional focus.

Funding

Direct Grant for Research from The Chinese University of Hong Kong.

Nanoconfinement-guided in situ co-deposition of single-atom cascade nanozymes combined with injectable sodium alginate hydrogels for enhanced diabetic wound healing

Treating diabetic wounds remains a major clinical challenge due to high glucose levels, bacterial infection, insufficient oxygen supply, and oxidative stress. Herein, guided by the nanoconfinement effect, single-atom Au/Pt nanoparticles (NPs) are in situ co-deposited in mesoporous metal-organic frameworks (MOF), while synergizing with DNA aptamer (DNA-Apt) with bacterial targeting functionality and an excellent biocompatible sodium alginate hydrogel (Gel), to prepare a multifunctional bimetallic cascade nanozyme combine hydrogels (Au-Pt@ZIF-8/Apt@gel). ZIF-8 degrades in the acidic environment of a wound infection, releasing Zn2+ and Au/Pt nanoparticles, which produce reactive oxygen species (ROS) under the catalysis of glucose to inactivate bacteria. Notably, Au-Pt@ZIF-8 nanozymes depositing Au/Pt nanoparticles exhibit a nanoconfinement effect that enhances the cascade nanozymes activity, which is about 2-3 times higher than that of monoconfined or nonconfined nanozyme. In addition, in vitro bacteriostatic tests show the nanozymes have broad-spectrum antimicrobial effects, with better inhibition of Gram-positive than negative bacteria. In vivo experiments indicate that Au-Pt@ZIF-8/Apt@gel has satisfactory antibacterial efficacy in both normal and diabetic mice, as well as optimal skin wound healing ability and significant reduction of inflammation in infected wounds. Consequently, the proposed system holds great potential for developing integrated nanoplatforms for on-demand treatment of bacterial-infected diabetic wounds.

Trends of diabetes in Beijing, China

BACKGROUND

The global rise in diabetes prevalence is a pressing concern. Despite initiatives like "The Healthy Beijing Action 2020-2030" advocating for increased awareness, treatment, and control, the specific situation in Beijing remains unexplored. This study aimed to analyze the trends in diabetes prevalence, awareness, treatment, and control among Beijing adults.

METHODS

Through a stratified multistage probability cluster sampling method, a series of representative cross-sectional surveys were conducted in Beijing from 2005 to 2022, targeting adults aged 18-79 years. A face-to-face questionnaire, along with body measurements and laboratory tests, were administered to 111,943 participants. Data from all survey were age- and/or gender-standardized based on the 2020 Beijing census population. Annual percentage rate change (APC) or average annual percentage rate change (AAPC) was calculated to determine prevalence trends over time. Complex sampling logistic regression models were employed to explore the relationship between various characteristics and diabetes.

RESULTS

From 2005 to 2022, the total prevalence of diabetes among Beijing adults aged 18-79 years increased from 9.6% (95% CI: 8.8-10.4%) to 13.9% (95% CI: 13.1-14.7%), with an APC/AAPC of 2.1% (95% CI: 1.1-3.2%, P <0.05). Significant increases were observed among adults aged 18-39 years and rural residents. Undiagnosed diabetes rose from 3.5% (95% CI: 3.2-4.0%) to 7.2% (95% CI: 6.6-7.9%) with an APC/AAPC of 4.1% (95% CI: 0.5-7.3%, P <0.05). However, diabetes awareness and treatment rates showed annual declines of 1.4% (95% CI: -3.0% to -0.2%, P <0.05) and 1.3% (95% CI: -2.6% to -0.2%, P <0.05), respectively. The diabetes control rate decreased from 21.5% to 19.1%, although not statistically significant (APC/AAPC = -1.5%, 95% CI: -5.6% to 1.9%). Overweight and obesity were identified as risk factors for diabetes, with ORs of 1.65 (95% CI: 1.38-1.98) and 2.48 (95% CI: 2.07-2.99), respectively.

CONCLUSIONS

The prevalence of diabetes in Beijing has significantly increased between 2005 and 2022, particularly among young adults and rural residents. Meanwhile, there has been a concerning decrease in diabetes awareness and treatment rates, while control rates have remained stagnant. Regular blood glucose testing, especially among adults aged 18-59 years, should be warranted. Furthermore, being male, elderly, overweight, or obese was associated with higher diabetes risk, suggesting the needs for targeted management strategies.

Triglyceride-glucose related indices as predictors for major adverse cardiovascular events and overall mortality in type-2 diabetes mellitus patients

BACKGROUND

Recent studies have indicated that triglyceride glucose (TyG)-waist height ratio (WHtR) and TyG-waist circumference (TyG-WC) are effective indicators for evaluating insulin resistance. However, research on the association in TyG-WHtR, TyG-WC, and the risk and prognosis of major adverse cardiovascular events (MACEs) in type 2 diabetes mellitus (T2DM) cases are limited.

AIM

To clarify the relation in TyG-WHtR, TyG-WC, and the risk of MACEs and overall mortality in T2DM patients.

METHODS

Information for this investigation was obtained from Action to Control Cardiovascular Risk in Diabetes (ACCORD)/ACCORD Follow-On (ACCORDION) study database. The Cox regression model was applied to assess the relation among TyG-WHtR, TyG-WC and future MACEs risk and overall mortality in T2DM cases. The RCS analysis was utilized to explore the nonlinear correlation. Subgroup and interaction analyses were conducted to prove the robustness. The receiver operating characteristic curves were applied to analysis the additional predicting value of TyG-WHtR and TyG-WC.

RESULTS

After full adjustment for confounding variables, the highest baseline TyG-WHtR cohort respectively exhibited a 1.353-fold and 1.420-fold higher risk for MACEs and overall mortality, than the lowest quartile group. Similarly, the highest baseline TyG-WC cohort showed a 1.314-fold and 1.480-fold higher risk for MACEs and overall mortality, respectively. Each 1 SD increase in TyG-WHtR was significantly related to an 11.7% increase in MACEs and a 14.9% enhance in overall mortality. Each 1 SD increase in TyG-WC corresponded to an 11.5% in MACEs and a 16.6% increase in overall mortality. Including these two indexes in conventional models significantly improved the predictive power for MACEs and overall mortality.

CONCLUSION

TyG-WHtR and TyG-WC were promising predictors of MACEs and overall mortality risk in T2DM cases.

Diabetes, obesity, and cardiovascular disease-what is the impact of lifestyle modification?

Diabetes, obesity, and cardiovascular disease (CVD) represent an escalating global health challenge, contributing significantly to morbidity, mortality, and healthcare costs. Evidence from large cohort studies and clinical trials underscores the impact of diabetes and obesity as major risk factors for CVD, causing systemic inflammation, insulin resistance, and neurohormonal activation. Frequently, a sedentary lifestyle and unbalanced dietary habits are associated with these risk factors. Physical activity and exercise training interventions, a Mediterranean and plant-based diet, smoking cessation, and reduction of alcohol have shown promise in mitigating these risks. The implementation of lifestyle and pharmacotherapy have emerged as new pillars of preventive medicine. This review discusses the evidence of lifestyle interventions to reduce the burden of diabetes, obesity, and CVD. It is highlighted that only a multifaceted, sustained approach integrating lifestyle interventions and pharmacological strategies can reduce the burden of disease and improve long-term outcomes.

Multi-omics approaches for biomarker discovery and precision diagnosis of prediabetes

Recent advancements in multi-omics technologies have provided unprecedented opportunities to identify biomarkers associated with prediabetes, offering novel insights into its diagnosis and management. This review synthesizes the latest findings on prediabetes from multiple omics domains, including genomics, epigenomics, transcriptomics, proteomics, metabolomics, microbiomics, and radiomics. We explore how these technologies elucidate the molecular and cellular mechanisms underlying prediabetes and analyze potential biomarkers with predictive value in disease progression. Integrating multi-omics data helps address the limitations of traditional diagnostic methods, enabling early detection, personalized interventions, and improved patient outcomes. However, challenges such as data integration, standardization, and clinical validation and translation remain to be resolved. Future research leveraging artificial intelligence and machine learning is expected to further enhance the predictive power of multi-omics technologies, contributing to the precision diagnosis and tailored management of prediabetes.

Correlation between diabetes mellitus and refracture risk in patients with osteoporotic fractures: a retrospective cohort study

BACKGROUND

Diabetes and osteoporosis are frequent long-term conditions. There is little information on the relationship between diabetes and the risk of refracture in people who have osteoporotic fractures (OPFs), even though both conditions have been individually associated with increased fracture risk.

METHODS

We conducted a retrospective cohort study using the Osteoporotic Fracture Registry System of the Affiliated Kunshan Hospital of Jiangsu University. The study included 2,255 patients aged 50 years or older who were admitted with OPFs, comprising 107 with diabetes and 2,148 without. The risk of refracture within 1, 3, and 5 years was evaluated using Cox proportional hazard regression models based on whether or not a diabetes diagnosis was made during the admission assessment. Furthermore, the rates of refracture between individuals with and without diabetes were compared using Kaplan-Meier curves.

RESULTS

In patients with OPFs, diabetes was significantly positively correlated with refracture risk. For the follow-up periods of 1, 3, and 5 years, the hazard ratios (HRs) in the fully adjusted model were 2.83 (95% confidence interval [CI]: 1.09 to 7.39, P-value = 0.033), 2.65 (95% CI: 1.27 to 5.52, P-value = 0.009), and 2.72 (95% CI: 1.39 to 5.32, P-value = 0.004), respectively.

CONCLUSIONS

The findings highlight the importance of monitoring bone health and implementing preventative interventions in individuals with diabetes, since they reveal that diabetic patients face a risk of refracture that is more than twice as high as that of non-diabetic individuals.

Combined face-to-face and online exercise program reduces medical expenses and medication in the Asian elderly with type 2 diabetes: A randomized controlled trial

To determine the impact of a combined face-to-face (f2f) and online training program on type 2 diabetes mellitus (T2DM) in elderly patients, a single-blinded randomized clinical trial was conducted from April 2021 to April 2023 at a tertiary public hospital in China. Participants aged 60+ were randomly allocated to intervention (n=20) and control (n=20) groups. After a six-month f2f program followed by 18 months of online guidance, intervention participants achieved significantly greater reductions in annual medical expenses (mean difference [SD], -946.39[244.75]; p=0.001), FBG (mean difference [SD], -0.64[0.20]; p=0.003), and 2hPBG (mean difference [SD], -2.68[0.87]; p=0.004) compared to the control group at 24 months. A greater proportion had reduced diabetes medications (RR,7.82; p=0.043). Self-management ability improved in the intervention group (mean difference [SD], 10.11[4.39]; p=0.028). HbA1c remained unchanged in the intervention group but increased in the control group (mean difference [SD], -0.68[0.14]; p<0.001). The combined f2f and online program reduces medical expenses and improves various health outcomes in elderly T2DM patients.

Call to action for clinicians in the South-East Asian regions on primary prevention of diabetes in people with prediabetes- A consensus statement

Primary prevention of diabetes still remains as an unmet challenge in a real world setting. While, translational programmes have been successful in the developed nations, the prevailing social and economic inequities in the low and middle income countries, fail to integrate diabetes prevention into their public health systems. The resulting exponential increase in the prevalence of diabetes and the cost of treatment has put primary prevention in the back seat. As a call to action, an expert group was formed to lay down practical guidelines for clinicians in the South East Asian regions to implement primary prevention programmes at an individual or at a community level. The guideline was developed based on the outcomes of the evidence based prevention programmes conducted in India. This decentralised self-guided approach for primary prevention of diabetes follows a three step implementation process of screening, diagnosis of intermediate hyperglycaemia and design and delivery of personalized interventions. Recommendations provided on dietary intake and physical activity can be tailored by the clinician to suit individual needs. Initiation of pharmacological treatment to achieve desired targets has also been addressed. A personalised approach by the clinician may be effective and offer a sustainable solution to curb the rising epidemic.

The Role of Ultra-Rapid-Acting Insulin Analogs in Diabetes: An Expert Consensus

Ultra-rapid-acting insulin analogs (URAA) are a further development and refinement of rapid-acting insulin analogs. Because of their adapted formulation, URAA provide an even faster pharmacokinetics and thus an accelerated onset of insulin action than conventional rapid-acting insulin analogs, allowing for a more physiologic delivery of exogenously applied insulin. Clinical trials have confirmed the superiority of URAA in controlling postprandial glucose excursions, with a safety profile that is comparable to the rapid-acting insulins. Consequently, many individuals with diabetes mellitus may benefit from URAA in terms of prandial glycemic control. Unfortunately, there are only few available recommendations from authoritative sources for use of URAA in clinical practice. Therefore, this expert consensus report aims to define populations of people with diabetes mellitus for whom URAA may be beneficial and to provide health care professionals with concrete, practical recommendations on how best to use URAA in this context.

Rising mortality rates linked to type-2 diabetes and obesity in the United States: An observational analysis from 1999 to 2022

BACKGROUND

The prevalence of type 2 diabetes (T2D) and obesity are increasing in the United States. However, population-level data for mortality trends due to T2D and obesity are limited. This study aims to assess these death trends among adults in the United States categorized by sex, race, and geographical location.

METHODS

We queried the CDC-WONDER database for multiple cause of death data of adults aged ≥25 years. The crude mortality rates (CMR), age-adjusted mortality rates (AAMRs), annual percent change (APC), and the average APC (AAPC) along with a 95% confidence interval (CI) were analyzed.

RESULTS

From 1999 to 2022, a total of 88,597 T2DM and obesity-related deaths were recorded in the United States. The AAMR consistently increased from 1999 to 2017 (APC: 7.64; 95% CI: 1.91-9.96), followed by a marked rise from 2017 to 2022 (APC: 20.13; 95% CI: 12.88-38.57). The AAMR was approximately 3.58 times higher during the COVID-19 pandemic compared to the period from 1999 to 2019. The AAMR for males was consistently greater than that for females. The highest AAMR was observed in non-Hispanic (NH) Blacks or African Americans, followed by NH White, Hispanic or Latino, and other NH populations. Rural areas (AAMR: 1.86, 95% CI: 1.83-1.89) exhibited a greater AAMR than urban regions 1.26 (95% CI: 1.25-1.27).

CONCLUSIONS

Our results indicate a substantial increasing trend of T2D and obesity-related deaths in the United States especially during the COVID-19 pandemic.

Association between sex, age, temporal trends, and glycemic control of 221,769 adults with type 2 diabetes in a multi-ethnic middle-income Asian country

AIMS

We examined the association between sex, age, temporal trends, and glycemic control among people with type 2 diabetes (T2D) in a multi-ethnic middle-income Asian country.

METHODS

Using the National Diabetes Registry (2011-2020), we analyzed data for 221,769 adult Malaysians with T2D.We used quantile regressions to estimate the association of sex, age, and their interaction on HbA1clevels at the 5th, 50th, and 95thpercentile and logistic regression to estimate the odds of good control (HbA1c < 7 %).

RESULTS

The participants were Malays (61.8 %), females (59.3 %), and aged 50-69 years (63.5 %). The median (interquartile range [IQR]) HbA1c was 7.2 % (6.4 %, 8.9 %) for males and 7.3 % (6.4 %, 9.0 %) for females. The prevalence of good control was 42.8 % for males and 41.8 % for females. Glycemic control improved from 2011 to 2020 for both females and males above 40. Control significantly improved with age among both sexes. However, females had increasingly better control than men with increasing age (PHeterogeneity < 0.001). The adjusted odds (95 % CI) of good control comparing females to males at 30, 50, and 70 years was 0.90 (0.81, 0.99), 0.93 (0.90, 0.97), and 1.12 (1.08, 1.16) respectively.

CONCLUSIONS

A more aggressive approach to type 2 diabetes management is needed for both sexes, targeting especially the younger age groups, to improve glycemic control and reduce diabetes burden.

Ahmedabad declaration: A framework to combat growing epidemic of young-onset type 2 diabetes in Asia

AIM

Rising prevalence of Type 2 Diabetes (T2D) among young Asians has emerged as a public health crisis that threatens the long-term health, economic stability, and productivity of nations across Asia (1). Early-onset T2D poses unique challenges, including higher rates of undiagnosed cases, more aggressive disease progression, an increased risk of chronic complications and higher mortality (2). Hyperglycemia during the reproductive age especially among the female population can potentially have transgenerational impact through epigenetic changes.

METHODS

A comprehensive search was conducted on PubMed with a combination of relevant keywords. A preliminary draft prepared after review of literature was electronically circulated among a panel of 64 experts from various parts of the region and representatives of the participating organizations - Diabetes India (www.diabetesindia.org.in) and the Diabetes Asia Study Group (DASG, www.da-sg.org).

RESULTS

This Ahmedabad Declaration outlines the scale of the problem, its root causes, and a comprehensive action plan for Asian populations. The objectives of this declaration include raising awareness, addressing systemic barriers, and advocating for evidence-based policies and interventions, limited to people with T2D. Through collaborative efforts, we aim to mitigate the growing burden of diabetes in young Asians and secure a healthier future.

Relationship between trajectory of Chinese visceral adiposity index and risk of type 2 diabetes mellitus: Evidence from the China-PAR project

AIMS

This study aimed to identify the distinct change trajectories of the Chinese visceral adiposity index (CVAI) over time and to investigate their associations with risk of type 2 diabetes mellitus (T2DM).

MATERIALS AND METHODS

This study included 52 394 participants from the prospective project, the Prediction for Atherosclerotic Cardiovascular Disease Risk in China (China-PAR). The CVAI was calculated using measures of age, body mass index, waist circumference, triglycerides and high-density lipoprotein cholesterol. Latent mixture modelling was conducted to fit distinct trajectory patterns. The logistic regression model was applied to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for the risk of T2DM with various CVAI trajectory patterns.

RESULTS

Four distinct CVAI trajectory patterns were identified: low-increasing, moderate-increasing, moderate high-increasing and high-increasing. Compared with low-increasing CVAI, participants with moderate-increasing (OR 1.73, 95% CI 1.49-2.00), moderate high-increasing (3.48, 3.01-4.03) and high-increasing CVAI (5.50, 4.67-6.47) had a significantly increased risk of T2DM. Similar trajectory patterns were identified in both men and women. The ORs (95% CI) for moderate-increasing, moderate high-increasing and high-increasing groups were 3.28 (2.56-4.19), 7.85 (6.09-10.13) and 13.21 (9.98-17.49) in women respectively, and 1.20 (0.99-1.45), 2.18 (1.82-2.62) and 3.60 (2.93-4.43) in men respectively, when compared to the low-increasing CVAI group. Further, significant effect modifications for age, smoking and physical activity (all Pinteraction <0.05) were observed in the relationship between CVAI trajectory patterns and T2DM.

CONCLUSIONS

Initially high and persistently elevated CVAI is significantly associated with an increased risk of T2DM, with a particular focus on women, younger people, nonsmokers and physically inactive individuals. Continuous monitoring of CVAI levels will benefit effective identification, early intervention and management of individuals at high risk of T2DM.

Type 2 diabetes: a contemporary view from the Asian lens

PURPOSE OF REVIEW

The aim of this article was to review the up-to-date evidence with regards to the unique features of the Type 2 diabetes (T2D) pathophysiology, complications, response to therapy with the possibility of precision medicine guiding therapeutic decision making in Asia.

RECENT FINDINGS

Asia is the epicenter of diabetes. There have been marked advances with genotyping and phenotyping of the Asian patient with T2D, particularly with young onset diabetes where early beta cell failure and rapid progression of complications are more frequent. As Asians have lower muscle mass and higher adiposity, sarcopenia is increasingly associated with diabetes. Response to lifestyle and pharmacotherapy are generally similar, but unique features exist with different populations. Across Asia, use of guideline directed medical therapy for cardio-renal protection are recommended, but uptake of these newer agents are suboptimal and barriers exist with regards to standardized care.

SUMMARY

Although many similarities have been observed across Asia, due to the heterogeneity of populations within Asia, further research is required to streamline and pave the way towards precision medicine. There is an urgent need for region wide consensus to minimize barriers to diabetes care and stigma in diabetes terminology across Asia.

Exploring the effect of adhering to a healthy lifestyle pattern on glycemic control in adults with type 1 diabetes mellitus

BACKGROUND AND AIMS

Diet, physical activity, sleep and smoking have been individually associated with glycemic control (GC) in adults with type 1 diabetes mellitus (T1D). However, the combined effect of these factors has not been investigated. The aim of the present study was to examine the single and combined effects of lifestyle parameters on GC of people with T1D (PwT1D).

METHODS AND RESULTS

Dietary, physical activity and sleep habits were evaluated using validated questionnaires. Diet quality was assessed with two scores (MedDietScore and PURE Diet Score) and two healthy lifestyle indices (HLI) were constructed (MLI based on MedDietScore and PLI based on PURE score). The score of both HLI ranged from 0 to 12 with higher scores indicating greater adherence to the healthy lifestyle pattern. One hundred ninety-two adults [61 % female, median age 42 (34, 51) years] with T1D were included in the analysis. Good GC (defined as HbA1c<7 %) was observed in 31 % of study participants. Examining lifestyle components separately, only smoking was marginally inversely associated with good GC [odds ratio (OR): 0.48, (95 % confidence interval, CI:0.23-1.00; p = 0.050)]. Individuals with better GC had significantly higher HLI scores (both p < 0.05). After adjusting for age, sex, body mass index, wearing an insulin pump and using continuous glucose monitoring, one-unit increase in the PLI was associated with 16 % higher likelihood of good GC (OR:1.16, 95 % CI:1.01-1.35, p = 0.04) and a similar trend was recorded for MLI (p = 0.05).

CONCLUSION

Our results suggest that adherence to a healthy lifestyle, more so than single lifestyle parameters, is associated with better GC in PwT1D.

In-situ oxygen-supplying ROS nanopurifier for enhanced healing of MRSA-infected diabetic wounds via microenvironment modulation

Hypoxia, high ROS levels and chronic inflammation are the main factors that hinder the healing of diabetic wounds. Long-term exposed wounds are prone to bacterial infection, especially MRSA infection, which exacerbates the complex wound microenvironment of diabetes and threatens patients' lives. Here, we developed a ROS nanopurifier (CSVNP), which was prepared by loading superoxide dismutase (SOD), catalase (CAT) and vancomycin into nanogels through in-situ polymerization. CSVNP can effectively increase enzyme loading and stability, and improve cascade reaction efficiency between enzymes through nanosize effect, so that CSVNP can use a variety of ROS (H2O2 and ·O2-) as oxygen sources to generate much oxygen in situ, which can effectively alleviate the hypoxic environment and inflammatory response of diabetic tissues, theraby promoting cell migration and angiogenesis, and accelerating wound healing. In addition, the generated oxygen can further promote the transformation of pro-inflammatory M1 macrophages into anti-inflammatory M2 macrophages and reduce pro-inflammatory factors (TNF-α, IL-6, and IL-1β) release. CSVNP can also effectively eradicate MRSA by releasing vancomycin, preventing bacterial infection from exacerbating the deterioration of diabetic wounds. This multifunctional ROS nanopurifier with antiphlogosis, antibacterial and in-situ oxygen supply, provides a new strategy with universal and translational prospects for clinical diabetic tissue damage. STATEMENT OF SIGNIFICANCE: Methicillin-resistant staphylococcus aureus (MRSA)-infected diabetic wounds face significant challenges in clinical care, characterized by high ROS levels, acute inflammation, vascular lesions, and hypoxia, which impede healing and risk severe complications. Here, we originally developed a reactive oxygen species (ROS) nanopurifier prepared by in-situ polymerization of superoxide dismutase (SOD), catalase (CAT), and vancomycin. It uses SOD and CAT to continuously convert ROS (H2O2 and ·O2-) into O2 in diabetic tissues, effectively improving hypoxia and chronic inflammation, thereby promoting angiogenesis and cell proliferation and migration, and accelerating diabetic wound healing. Vancomycin can effectively kill MRSA bacteria, avoid bacterial infection spread, and reduce complications risk. This safe, efficient and easy-to-prepare ROS nanopurifier provides a general strategy for repairing MRSA-infected diabetic tissue damage.

The Impact of Sodium-Glucose Co-Transporter-2 Inhibition on Insulin Resistance and Inflammation in Patients with Type 2 Diabetes: A Retrospective Study

Background and Objectives: Insulin resistance (IR) is a key factor involved in the development of type 2 diabetes (T2D). Besides its role in the pathogenesis of T2D, insulin resistance is associated with impairment of glycemic control, reduced achievement of glycemic targets, and increases in cardiovascular risk and diabetes complications, being thus a negative prognosis factor. Sodium-glucose co-transporter-2 inhibitors (SGLT2i) are therapies for T2D which demonstrated, besides glycemic control, improvements of biomarkers traditionally associated with IR and inflammation. This study aimed to evaluate the impact of SGLT2i treatment on IR and inflammation biomarkers in patients with T2D. Materials and Methods: In a retrospective study, 246 patients with T2D treated with SGLT2i for a median of 5 years were evaluated regarding IR (estimated glucose disposal rate-eGDR, triglyceride/glucose index, triglyceride/HDLc index) and inflammation biomarkers (neutrophils to lymphocyte ratio, platelets to lymphocytes ratio and C-reactive protein) before and after intervention with SGLT2i. Results: After a median 5 years of SGLT2i treatment, patients with T2D had a higher eGDR (6.07 vs. 5.24 mg/kg/min; p < 0.001), lower triglyceride/HDLc ratio (3.34 vs. 3.52, p < 0.001) and lower triglyceride/glucose index (9.23 vs. 9.58; p < 0.001). The inflammation biomarkers decreased after SGLT2i therapy: C-reactive protein (3.07 mg/L vs. 4.37 mg/L), NLR (0.68 vs. 0.72; p < 0.001), and PLR (115 vs. 122; p < 0.001). Intervention with SGLT2i also improved the biomarkers associated with diabetes complications and cardiovascular risk: HbA1c (7.1% vs. 8.4%; p < 0.001), body mass index (30.0 vs. 31.5 kg/m2; p < 0.001) and urinary albumin to creatinine ratio (4.75 vs. 11.00 mg/g; p < 0.001). Conclusions: Treatment with SGLT2i in patients with T2D leads to decreases in IR and inflammation. These mechanisms may partially explain the additional cardiovascular and renal risk reductions associated with SGLT2i therapy, alongside the improvements in glycemic control, in patients with T2D.

Insulin therapy adherence and its associated factors among diabetic patients in a Ghanaian primary care hospital

BACKGROUND

Diabetes mellitus (DM) is a global health problem. Adherence to intensive insulin therapy is necessary to achieve better glycemic control in types 1 and 2 DM. This study aimed to evaluate the extent of adherence to insulin therapy, its predictors and to identify barriers to its adherence.

METHOD

This was a cross-sectional survey among adult (≥18 years) diabetic patients who are currently using insulin, either alone or in combination with an oral antidiabetic regimen, and seeking primary care at Kwame Nkrumah University of Science and Technology Hospital in Ghana. A total of one hundred and eight-six patients were conveniently sampled, and interviewed. Insulin adherence was determined using the Medication Adherence Reporting Scale-5. Descriptive statistics, a chi-square test of independence, and a multiple logistic regression analysis were performed using STATA version 14 (StataCorp, TX USA).

RESULTS

The majority of the patients interviewed were over 60 years (40.32%); female (61.83%); married (68.82%); and had completed secondary education (48.39%). 67.20% of the patients were adherent to insulin therapy. Adherence level was associated with age (p = 0.020), marital status (p = 0.001), employment status (p = 0.012), type of DM (p<0.001), regular follow-up (p = 0.007) and comorbidities (p = 0.002) and was only predicted by the type of DM (aOR = 14.82 C.I 1.34-163.50, p-value = 0.028).

CONCLUSION

Adherence to insulin therapy among our study population was suboptimal, which is a concern considering the associated increased risk of complications. Adherence assessment and counselling by healthcare professionals to address barriers to poor adherence must be continually undertaken to achieve optimal glycemic control.

IMPACT OF FINDINGS ON PRACTICE STATEMENTS

Continuous adherence assessment and counselling must be offered to all diabetes mellitus patients on insulin therapy as part of their ambulatory care to help improve outcomes.Using the Medication Adherence Reporting Scale-5 to determine patient adherence levels is an easy-to-use and an inexpensive method; however, it should be used with caution due to the potential for misclassification.Efforts must be made to provide appropriate strategies to deal with barriers to insulin adherence at ambulatory care clinics as part of the individualized comprehensive diabetic care to reduce diabetic complications.

Green sanctuaries: residential green and garden space and the natural environment mitigate mental disorders risk of diabetic patients

BACKGROUND

The co-occurrence of diabetes and mental disorders is an exceedingly common comorbidity with poor prognosis. We aim to investigate the impact of green space, garden space, and the natural environment on the risk of mental disorders among the population living with diabetes.

METHODS

We performed a longitudinal analysis based on 39,397 participants with diabetes from the UK Biobank. Residential green and garden space modeled from land use data and the natural environment from Land Cover Map were assigned to the residential address for each participant. Cox proportional hazards model was used to analyze the associations between nature exposures and mental disorders of diabetes. Casual mediation analysis was used to quantify indirect effect of air pollution.

RESULTS

During a mean follow-up of 7.55 years, 4513 incident mental disorders cases were identified, including 2952 depressive disorders and 1209 anxiety disorders. Participants with natural environment at 300 m buffer in the second and third tertiles had 7% (HR = 0.93, 95%CI: 0.86-0.99) and 12% (HR = 0.88, 95%CI: 0.82-0.94) lower risks of incident mental disorders compared with those in the first tertile, respectively. The risk of mental disorders incidence among diabetes patients will decrease by 13% when exposed to the third tertile of garden space at 300 m buffer. The natural environment and garden space individually prevented 6.65% and 10.18% of mental disorders incidents among diabetes patients. The risk of incident mental disorders was statistically decreased when exposed to the third tertile of green space at 1000 m buffer (HR = 0.84, 95% CI: 0.78-0.90). Protective effects of three nature exposures against depressive and anxiety disorders in diabetes patients were also observed. Air pollution, particularly nitrogen dioxide, nitrogen oxides, and fine particulate matter, significantly contributed to the associations between nature exposures and mental disorders, mediating 48.3%, 29.2%, and 62.4% of the associations, respectively.

CONCLUSIONS

Residential green and garden space and the natural environment could mitigate mental disorders risk in diabetes patients, with air pollution playing a vital mediator. This highlights the potential for local governments to enhance the sustainability of such interventions, grounded in public health and urban planning, through strategic planning initiatives.

Higher magnesium depletion score increases the risk of all‑cause and cardiovascular mortality in US adults with diabetes

BACKGROUND

Both dietary magnesium and serum magnesium are associated with the prognosis of diabetic patients. However, the impact of the magnesium depletion score (MDS), which assesses systemic magnesium deficiency, on the prognosis of diabetic patients remains unclear. This cohort study aims to explore the potential association between the MDS and all-cause and cardiovascular mortality in diabetic patients.

METHODS

In this study, we analyzed data from 5,219 diabetic individuals from National Health and Nutrition Examination Survey (NHANES) 2003-2018. Participant mortality information was sourced from the National Death Index records. MDS was divided into lower MDS (0-1 points), middle MDS (2 points), and higher MDS (3-5 points) groups. Weighted multivariable Cox regression was utilized to explore the potential association between MDS and mortality in diabetic patients. Stratified analyses and sensitivity analyses were employed to validate the robustness of our findings.

RESULTS

Among the 5,219 participants included in this study, 1,212 experienced all-cause mortality, and 348 experienced cardiovascular mortality. Weighted multivariable Cox regression indicated that higher MDS was strongly linked to a heightened risk of mortality in all models, including the fully adjusted model (all-cause mortality: HR = 1.58, 95% CI: 1.20-2.08; cardiovascular mortality: HR = 1.92, 95% CI: 1.28-2.88). In the stratified analysis, we found that the association between MDS and all-cause mortality was stronger among individuals aged <60 years. No significant differences were found in the relationship between MDS and mortality within other subgroups. In the sensitivity analyses, our results remained robust.

CONCLUSIONS

An increase in MDS is significantly correlated with a higher risk of all-cause and cardiovascular mortality in diabetic patients. The risk of all-cause mortality was higher in diabetic patients aged <60. Early monitoring and management of MDS, as well as optimizing magnesium nutritional status, may benefit diabetic patients.

Association of socioeconomic status with diabetic microvascular complications: a UK Biobank prospective cohort study

BACKGROUND

Prior studies on the link between socioeconomic status (SES) and diabetic microvascular complications have been inconclusive. This study aimed to explore whether SES is associated with the risk of diabetic retinopathy (DR), nephropathy (DN) and diabetic peripheral neuropathy (DPN) using large prospective cohort.

METHODS

SES was evaluated using education attainment (individual level), household income (household level), and Townsend deprivation index (TDI, neighborhood level). This study included 28,339 participants without DR, 29,951 without DN and 29,762 without DPN at baseline from the UK Biobank. Weighted Cox proportional hazard models were used to investigate the relationship between SES and the risk of diabetic microvascular complications.

RESULTS

The median follow-ups of the DR, DN and DPN cohorts were 12.95, 12.89 and 13.02 years, respectively. In total, 3,177 (11.2%) participants developed DR, 4,418 (14.8%) developed DN and 1,604 (5.4%) developed DPN. After adjusting for confounders, higher education levels (DN: hazard ratios [HR] = 0.85; 95% CI, 0.82-0.89; P < 0.001; DPN: HR = 0.93; 95% CI, 0.87-1.00; P = 0.040), higher household income (DN: HR = 0.80; 95% CI, 0.75-0.85; P < 0.001; DPN: HR = 0.80; 95% CI, 0.73-0.89; P < 0.001), and lower TDI (DN: HR = 1.19; 95% CI, 1.14-1.23; P < 0.001; DPN: HR = 1.27; 95% CI, 1.19-1.36; P < 0.001) were associated with a lower risk of DN and DPN. In contrast, a lower risk of DR was only related to higher household income (HR = 0.92; 95% CI, 0.87-0.97; P = 0.004) and lower TDI (HR = 1.08; 95% CI, 1.02-1.13; P = 0.004).

CONCLUSIONS

Low SES increases the risk of diabetic microvascular complications, emphasizing the need for equitable medical resource allocation to reduce diabetes-related inequity.

The global, regional, and national burden of type 2 diabetes mellitus attributable to low physical activity from 1990 to 2021: a systematic analysis of the global burden of disease study 2021

BACKGROUND

Low physical activity (LPA) is a leading risk factor for type 2 diabetes mellitus (T2DM). We examine the temporal and spatial trends in the burden of T2DM attributable to LPA at the global, regional, and country scales.

METHODS

Data were obtained from the Global Burden of Disease Study 2021. The numbers of deaths and disability-adjusted life years (DALYs) of LPA-related T2DM, and the corresponding age-standardized mortality rate (ASMR) and age-standardized DALYs rate (ASDR) were compared across regions and countries by age, sex, and sociodemographic index (SDI). The annual percentage changes (EAPCs) in the ASMR or ASDR were calculated to quantify temporal trends from 1990 to 2021. We also quantified the relationship between SDI and the ASMR and ASDR of T2DM attributable to LPA.

RESULTS

Globally, the number of T2DM deaths and DALYs attributable to LPA were approximately 0.15 million and 5.52 million respectively in 2021, which more than doubled compared to 1990. Over the past 32 years, the global EAPCs of ASMR and ASDR were 0.26 (95% CI: 0.20, 0.31) and 0.97 (95% CI: 0.93, 1.02), respectively. The ASMR or ASDR had a reverse U-shaped relationship with the SDI, with the most severe burden observed in the low-middle and middle SDI regions. The age group older than 60 years had the highest rate of DALYs for LPA-related T2DM in 2021, while the 25-44 age group showed the largest increase between 1990 and 2021.

CONCLUSIONS

Over the past 32 years, the global burden of LPA-related T2DM has continued to increase at an alarming rate in almost all countries, particularly in regions with low-middle and middle SDI. Substantial increases in national action are urgently needed to target elder populations especially in low-middle and middle SDI regions, and special efforts should be made to promote physical activity in young adults with LPA.

Latent class analysis of the capacity of countries to manage diabetes and its relationship with diabetes-related deaths and healthcare costs

BACKGROUND

The prevalence of diabetes is escalating globally, underscoring the need for comprehensive evidence to inform health systems in effectively addressing this epidemic. The purpose of this study was to examine the patterns of countries' capacity to manage diabetes using latent class analysis (LCA) and to determine whether the patterns are associated with diabetes-related deaths and healthcare costs.

METHODS

Eight indicators of country-level capacity were drawn from the World Health Organization Global Health Observatory dataset: the widespread availability of hemoglobin A1C (HbA1c) testing, existence of diabetes registry, national diabetes management guidelines, national strategy for diabetes care, blood glucose testing, diabetic retinopathy screening, sulfonylureas, and metformin in the public health sector. We performed LCA of these indicators, testing 1-5 class solutions, and selecting the best model based on Bayesian Information Criteria (BIC), entropy, corrected Akaike Information Criteria (cAIC), as well as theoretical interpretability. Multivariable linear regression was used to assess the association between capacity to manage diabetes (based on the latent class a country belongs) and diabetes-related deaths and healthcare costs.

RESULTS

We included 194 countries in this secondary analysis. Countries were classified into "high capacity" (88.7%) and "limited capacity" (11.3%) countries based on the two-class solution of the LCA (entropy = 0.91, cAIC = 1895.93, BIC = 1862.93). Limited capacity countries were mostly in Africa. Limited capacity countries had significantly higher percentage of their deaths attributable to diabetes (adjusted beta = 1.34; 95% CI: 0.15, 2.53; p = 0.027) compared to high capacity countries even after adjusting for income status and diabetes prevalence.

CONCLUSIONS

Our findings support the report by the Lancet commission on diabetes, which suggests that differences in diabetes outcomes among countries may be explained by variations in the capacity of and investments made in their health systems. Future studies should evaluate initiatives such as the WHO Global Diabetes Compact that are currently underway to improve the capacity of resource-limited countries.

Animal models in biomedical research: Relevance of Drosophila melanogaster

Animal models have become veritable tools in gaining insight into the pathogenesis and progression of several human diseases. These models could range in complexity from Caenorhabditis elegans to non-human primates. With the aid of these animal models, a lot of new knowledge has been gained about several diseases which otherwise would not have been possible. Most times, the utilization of these animal models is predicated on the level of homology they share with humans, which suggests that outcomes of studies using them could be extrapolated to humans. However, this has not always been the case. Drosophila melanogaster is becoming increasingly relevant as preferred model for understanding the biochemical basis of several human diseases. Apart from its relatively short lifespan, high fecundity and ease of rearing, the simplicity of its genome and lower redundancy of its genes when compared with vertebrate models, as well as availability of genetic tool kit for easy manipulation of its genome, have all contributed to its emergence as a valid animal model of human diseases. This review aimed at highlighting the contributions of selected animal models in biomedical research with a focus on the relevance of Drosophila melanogaster in understanding the biochemical basis of some diseases that have continued to plague mankind.

Association of homocysteine and uric acid with type 2 diabetes mellitus: a case-control study

The aim of this study was to examine the association between homocysteine (Hcy), uric acid (UA) and type 2 diabetes mellitus (T2DM), and to explore whether there was an interaction between Hcy and UA in the development of T2DM. A total of 1250 diabetic patients and 1250 non-diabetic controls were included in this case-control study. Binary logistic regression and interaction analysis were used to evaluate the association between Hcy, UA, and T2DM, and the combined effects of Hcy and UA on T2DM, respectively. Plasma Hcy and UA levels were significantly higher in diabetic patients compared to non-diabetic controls (p < 0.001, p = 0.002). Elevated Hcy and UA were risk factors for T2DM. Binary logistic regression analysis showed that compared with the lowest quartile of Hcy and UA, the highest quartile had a significantly increased risk of T2DM (OR = 1.629, 95% CI: 1.303, 2.035 for Hcy; OR = 1.596, 95% CI: 1.277, 1.995 for UA). Stratified analysis suggested a significant association between Hcy and T2DM for those aged < 65 years and males. A significant association between UA and T2DM was found in those aged ≥ 65 years, males, and BMI ≥ 24 kg/m2. No significant interaction was observed between Hcy and UA (p > 0.05). Hcy and UA were risk factors for T2DM. However, there was no interaction between Hcy and UA in the risk of T2DM.

The status of care for youth with type 1 diabetes within and coming from humanitarian crises settings: a narrative review

BACKGROUND

Humanitarian crises bring unique, and potentially growing challenges to people with type 1 diabetes (T1D). We aimed to determine, in youth with T1D (mean age (± 1SD) 0-17.9 years) within and coming from humanitarian crises settings (HCS), the reported prevalence that meet international consensus targets for glycaemic, blood pressure and lipid management, and incidence of severe hypoglycaemia or diabetic ketoacidosis.

METHODS

A narrative review of quantitative data was conducted, using a systematic process. MEDLINE (Ovid), Global Health, Web of Science, Scopus, Embase, CINAHL, APA PsycINFO, Cochrane trials, and the reference lists of eligible records were searched (January 2014-February 2024); ten records covering ten separate studies were retrieved.

RESULTS

Glycaemic management was consistently suboptimal in HCS. However, among individuals coming from HCS, glycaemia varied. Across both groups, data relating to blood pressure, lipids, severe hypoglycaemia or diabetic ketoacidosis were either unavailable or limited.

CONCLUSION

Findings expose the dearth of data relating to defined youth with T1D within and coming from HCS, leaving the status of this population largely uncharacterised. With limited data indicating suboptimal T1D management, there is a pressing need for the development of a consensus guideline on, and core indicators relating to such youth within and coming from HCS, plus monitoring systems and outcome data.

Oral Health and Quality of Life in Type 2 Diabetic Patients: Key Findings from a Romanian Study

Background: Diabetes mellitus is associated with various oral health complications that can negatively impact quality of life. Despite evidence of the relationship between diabetes and oral health issues, limited research exists on the perceptions, behaviors, and oral health-related quality of life (OHRQoL) of diabetic patients in Romania. This study aims to evaluate self-reported oral health, knowledge, behaviors, and OHRQoL among diabetic patients in western Romania. Methods: A cross-sectional study was conducted in early 2024 at Pius Brinzeu County Emergency Hospital, Timisoara, involving 121 patients with type 2 diabetes. Data were collected using self-administered questionnaires that assessed oral health status, behaviors, and OHRQoL, with the OHIP-14 instrument employed for quality-of-life measurement. Statistical analyses included descriptive statistics, multiple linear regression, and correlation analyses to identify the predictors of oral health knowledge and OHRQoL. Results: Participants (mean age: 63.24 years; 52.1% female; 60.5% urban residents) reported significant oral health challenges. Over half (56.2%) did not visit a dentist regularly, with financial constraints identified as the primary barrier (23.5%). Oral hygiene practices were suboptimal: only 38.0% brushed twice daily, while 78.5% used fluoride toothpaste. Auxiliary hygiene tools, such as mouthwash and toothpicks, were rarely used (13.22% and 11.57%, respectively). Regression analyses identified the significant predictors of oral health knowledge, including tooth mobility (β = 0.33, p < 0.01) and brushing frequency (β = -0.18, p < 0.05). The mean OHIP-14 score (0.55) indicated a moderate impact on OHRQoL, with domains such as psychological discomfort and social disability revealing nuanced challenges. Conclusions: Diabetic patients in Romania face oral health challenges and care barriers, emphasizing the need for preventive strategies, oral health education, and integrated diabetes care. Addressing these gaps can improve oral health outcomes and overall quality of life in this vulnerable population.

Metabolic Sequelae and Quality of Life in Early Post-Treatment Period in Adolescents with Hodgkin Lymphoma

Background/Objectives: The long-term consequences of intensive treatment for Hodgkin lymphoma (HL), including metabolic syndrome (MetS) and cardiovascular diseases, but also deteriorated quality of life (QoL), are present in many survivors of childhood HL. Methods: Adolescents and young adults diagnosed with HL who continued the follow-up after successful treatment for HL were included. Anthropometric parameters, body composition, laboratory data, blood pressure values, compliance to the Mediterranean diet (MD), QoL and lifestyle habits were evaluated at the follow-up. Available data were also extracted retrospectively at the time of diagnosis. The primary objective was to determine metabolic sequelae in the early post-treatment period in adolescents treated for HL. Additionally, QoL and compliance with MD were explored, and the correlation of MetS with QoL was investigated. Results: Sixty percent of patients had at least one risk factor for metabolic syndrome, with obesity/abdominal obesity, high blood pressure and low HDL being most commonly observed, present in 66.7%, 44.4% and 44.4% of patients, respectively. The number of obese patients increased from 6.3% at the diagnosis to 31.3% at the follow-up. The majority of patients (53.3%) had low adherence to the MD. Participants had comparable quality-of-life domains to those of the healthy population at the follow-up. The physical health domain of QoL was positively correlated with compliance to the MD in young adults (r = 0.8, p = 0.032) and negatively correlated with obesity/overweight in adolescents (r = -0.85, p = 0.008). Conclusions: Healthy lifestyle choices can impact not only the metabolic health of survivors but also their quality of life, and therefore should be encouraged in these patients.

New exploration on pathogenesis and early diagnosis of gestational diabetes

Gestational diabetes mellitus (GDM) refers to varying degrees of abnormal glucose metabolism that occur during pregnancy and excludes patients previously diagnosed with diabetes. GDM is a unique among the four subtypes of diabetes classified by the international World Health Organization standards. Although GDM patients constitute a small proportion of the total number of diabetes cases, the incidence of GDM has risen significantly over the past decade, posing substantial risk to pregnant women and infants. Therefore, it warrants considerable attention. The pathogenesis of GDM is generally considered to resemble that of type II diabetes, though it may have distinct characteristics. Analyzing blood biochemical proteins in the context of GDM can help elucidate its pathogenesis, thereby facilitating more effective prevention and management strategies. This article reviews this critical clinical issue to enhance the medical community's sufficient understanding of GDM.

Diabetes in China: epidemiology, pathophysiology and multi-omics

Although diabetes is now a global epidemic, China has the highest number of affected people, presenting profound public health and socioeconomic challenges. In China, rapid ecological and lifestyle shifts have dramatically altered diabetes epidemiology and risk factors. In this Review, we summarize the epidemiological trends and the impact of traditional and emerging risk factors on Chinese diabetes prevalence. We also explore recent genetic, metagenomic and metabolomic studies of diabetes in Chinese, highlighting their role in pathogenesis and clinical management. Although heterogeneity across these multidimensional areas poses major analytic challenges in classifying patterns or features, they have also provided an opportunity to increase the accuracy and specificity of diagnosis for personalized treatment and prevention. National strategies and ongoing research are essential for improving diabetes detection, prevention and control, and for personalizing care to alleviate societal impacts and maintain quality of life.

Monocyte-lymphocyte ratio predicts cardiovascular diseases death in individuals with type 2 diabetes

PURPOSE

Previous studies have shown higher cardiovascular mortality risk with higher monocyte-lymphocyte ratio levels in general population. However, the levels of oxidative stress in individuals with type 2 diabetes are higher than those in the general population, which may affect the link between monocyte-to-lymphocyte ratio and cardiovascular disease deaths. And the association between the monocyte-to-lymphocyte ratio and mortality risk in people with type 2 diabetes still be unknown. This study aimed to investigate the prognostic significance of monocyte-to-lymphocyte ratio in type 2 diabetes.

METHODS

This analysis involved 2,954 individuals with type 2 diabetes from the National Health and Nutrition Examination Survey 1999-2010. The National Death Index records through December 31, 2019, was used to determine all-cause and cardiovascular mortality. The prognostic roles were determined using Cox regression models, restricted cubic spline analysis, and time-dependent receiver operating characteristic curve analysis.

RESULTS

During an average follow-up period of 12.4 years, a total of 1,007 deaths occurred, while 252 were due to cardiovascular disease. An elevated monocyte-to-lymphocyte ratio level exhibited a significant dose-response relationship with an increased risk of all-cause mortality (1.34 [95% CI 1.12, 1.60] for all-cause mortality [P trend = 0.001]). The multivariable-adjusted HR was 1.81 (95% CI 1.25, 2.63) (P trend = 0.001) for cardiovascular mortality indicating a U-shaped relationship (P nonlinear = 0.013).

CONCLUSIONS

The results of this study indicate a U-shaped relationship between the monocyte-to-lymphocyte ratio and cardiovascular mortality in individuals with diabetes. Both very low and high monocyte-to-lymphocyte ratio monocyte-to-lymphocyte ratio values were found to be associated with increased cardiovascular mortality risk.

Temporal incremental healthcare costs associated with complications in Hong Kong Chinese patients with type 2 diabetes: A prospective study in Joint Asia diabetes evaluation (JADE) Register (2007-2019)

OBJECTIVE

We examined incremental healthcare costs (inpatient and outpatient) related to complications in Chinese patients with type 2 diabetes (T2D) during the year of occurrence and post-event years, utilizing the Joint Asia Diabetes Evaluation (JADE) Register cohort of Hong Kong Chinese patients with T2D between 2007 and 2019.

RESEARCH DESIGN AND METHODS

19,440 patients with T2D underwent structured evaluation utilizing the JADE platform with clinical outcomes data retrieved from territory-wide electronic medical records including inpatient, outpatient and emergency care. Two-part model was adopted to account for skewed healthcare costs distribution. Incremental healthcare costs associated with nine non-fatal diabetes complications and all-cause death were estimated, adjusted for demographic, clinical, lifestyle factors and comorbidities.

RESULTS

In this prospective cohort [mean ± SD age:59.9 ± 11.9 years, 56.6 % men, duration of diabetes:7.3 ± 7.5 years, HbA1C:7.5 ± 1.6 %] observed for 7 (interquartile range:4-9) years (142,132 patient-years), the mean annual healthcare costs, mainly due to inpatient cost, were USD$2,990 ± 9,960. Lower extremity amputation (LEA) (USD$31,302; 95 %CI: 25,706-37,004), hemorrhagic stroke (USD$21,164; 17,680-24,626), ischemic stroke (USD$17,976; $15,937-20,352) and end-stage disease (ESRD) (USD$14,774; 13,405-16,250) in the year of event incurred the highest cost. Residual healthcare costs in the post-event years were highest for ESRD, LEA, haemorrhagic stroke and incident cancer.

CONCLUSION

These comprehensive temporal healthcare cost estimates for diabetes-related complications allows the performance of long-term, patient-level, cost-effectiveness analyses on T2D prevention and treatment strategies relevant to an Asian and possibly global contexts. These may inform decision-makers on resource allocation aimed at reducing the burden of T2D and chronic diseases.

Association between reduced hemoglobin-to-red cell distribution width ratio and elevated cardiovascular mortality in patients with diabetes: Insights from the National Health and Nutrition Examination Study, 1999-2018

OBJECTIVE

The purpose of this research was to examine the relationship between the hemoglobin-to-red blood cell distribution width ratio (HRR) and cardiovascular disease (CVD)-related mortality in people who have diabetes.

METHODS

Data derived from the National Health and Nutrition Examination Survey (NHANES), between the years 1999 to 2018, were meticulously analyzed. Mortality data, encompassing events until December 31, 2019, were systematically collected. A comprehensive group comprising of 8,732 participants were subjected to scrutiny, and subsequently, classified into four distinct groups predicated upon quartiles of baseline HRR levels: Q1 (n = 2,183), Q2 (n = 2,181), Q3 (n = 2,185), and Q4 (n = 2,183). The correlation between HRR and CVD-related mortality was examined through the use of survival curves and Cox proportional hazard regression models, the latter incorporating weights as advised by NHANES.

RESULTS

Among the 8,732 participants in the study cohort, CVD-related mortality was identified in 710 cases. The Kaplan-Meier analysis demonstrated a significant association, indicating that a decreased HRR was correlated with a reduction in survival in cases with CVD. Both univariate and multivariable Cox proportional hazard regression analyses consistently indicated that patients exhibiting a lower HRR exhibited a markedly elevated risk of CVD-related mortality in comparison to those with higher HRR. Notably, the correlation between HRR and decreasing CVD-related mortality was discerned to be non-linear.

CONCLUSION

In patients with diabetes, a decreased HRR was associated with an increased risk of CVD-related mortality.

Association between the triglyceride to high-density lipoprotein cholesterol ratio and type 2 diabetes mellitus in non-alcoholic fatty liver disease

This study evaluated the ability of the triglyceride (TG) to high-density lipoprotein cholesterol (TG/HDL-C) ratio to identify individuals at risk of type 2 diabetes mellitus (T2DM) in the non-alcoholic fatty liver disease (NAFLD) population. We retrospectively studied 4,769 patients with NAFLD from the Affiliated Hospital of Hangzhou Normal University (2020-2023). Binary logistic regression models were used to evaluate the association between the TG/HDL-C ratio and lipid parameters with T2DM. TG/HDL-C ratio was positively associated with T2DM in patients with NAFLD, with an odds ratio (OR) of 2.72 (95% confidence interval, 2.23-3.31, p < 0.001) for T2DM in the highest TG/HDL-C ratio quartile compared with the lowest one after adjusting for known confounders. The OR for the TG/HDL-C ratio had a stronger predictive value than those of TG, total cholesterol, HDL-C, and low-density lipoprotein cholesterol, indicating that the TG/HDL-C ratio could be a better discriminator of T2DM. The TG/HDL-C ratio better identifies potential risks of T2DM in individuals with NAFLD than individual lipid parameters. Therefore, clinicians should pay attention to individuals with high TG and low HDL-C levels during T2DM risk assessment in NAFLD cohorts.

The role of m6A modification in cardiovascular disease: A systematic review and integrative analysis

BACKGROUND AND AIMS

This study focused on the recent advancements in understanding the association between N6-methyladenosine (m6A) modification and cardiovascular disease (CVD).

METHODS

The potential mechanisms of m6A related to CVD were summarized by literature review. Associations between m6A levels and CVD were explored across 8 electronic databases: PubMed, Embase, Web of Science, Cochrane Library, Sinomed, Wan Fang, CNKI, and Vip. Standard mean difference (SMD) and 95 % confidence interval (95 % CI) were calculated to assess the total effect in integrated analysis.

RESULTS

The systematic review summarized previous studies on the association between m6A modification and CVD, highlighting the potential role of m6A in CVD progression. A total of 11 studies were included for integrative analysis. The mean m6A levels were significantly higher in CVD than those in normal controls (SMD = 1.86, 95 % CI: 0.16-3.56, P < 0.01).

CONCLUSIONS

This systematic review provided new targets for early detection and treatment for CVD. And the integrated analysis showed that increased level of m6A was associated with CVD.

Innovations in Diabetes Management for Pregnant Women: Artificial Intelligence and the Internet of Medical Things

Pregnancies impacted by diabetes face the compounded challenge of strict glycemic control with mounting insulin resistance as the pregnancy progresses. New technological advances, including artificial intelligence (AI) and the Internet of Medical Things (IoMT), are revolutionizing health care delivery by providing innovative solutions for diabetes care during pregnancy. Together, AI and the IoMT are a multibillion-dollar industry that integrates advanced medical devices and sensors into a connected network that enables continuous monitoring of glucose levels. AI-driven clinical decision support systems (CDSSs) can predict glucose trends and provide tailored evidence-based treatments with real-time adjustments as insulin resistance changes with placental growth. Additionally, mobile health (mHealth) applications facilitate patient education and self-management through real-time tracking of diet, physical activity, and glucose levels. Remote monitoring capabilities are particularly beneficial for pregnant persons with diabetes as they extend quality care to underserved populations and reduce the need for frequent in-person visits. This high-resolution monitoring allows physicians and patients access to an unprecedented wealth of data to make more informed decisions based on real-time data, reducing complications for both the mother and fetus. These technologies can potentially improve maternal and fetal outcomes by enabling timely, individualized interventions based on personalized health data. While AI and IoMT offer significant promise in enhancing diabetes care for improved maternal and fetal outcomes, their implementation must address challenges such as data security, cost-effectiveness, and preserving the essential patient-provider relationship. KEY POINTS: · The IoMT expands how patients interact with their health care.. · AI has widespread application in the care of pregnancies complicated by diabetes.. · A need for validation and black-box methodologies challenges the application of AI-based tools.. · As research in AI grows, considerations for data privacy and ethical dilemmas will be required..

Employing Machine Learning Models to Predict Potential α-Glucosidase Inhibitory Plant Secondary Metabolites Targeting Type-2 Diabetes and Their In Vitro Validation

The need for new antidiabetic drugs is evident, considering the ongoing global burden of type-2 diabetes mellitus despite notable progress in drug discovery from laboratory research to clinical application. This study aimed to build machine learning (ML) models to predict potential α-glucosidase inhibitors based on the data set comprising over 537 reported plant secondary metabolite (PSM) α-glucosidase inhibitors. We assessed 35 ML models by using seven different fingerprints. The Random forest with the RDKit fingerprint was the best-performing model, with an accuracy (ACC) of 83.74% and an area under the ROC curve (AUC) of 0.803. The resulting robust ML model encompasses all reported α-glucosidase inhibitory PSMs. The model was employed to predict potential α-glucosidase inhibitors from an in-house 5810 PSM database. The model identified 965 PSMs with a prediction activity ≥0.90 for α-glucosidase inhibition. Twenty-four predicted PSMs were subjected to in vitro assay, and 13 were found to inhibit α-glucosidase with IC50 ranging from 0.63 to 7 mg/mL. Among them, seven compounds recorded IC50 values less than the standard drug acarbose and were investigated further to have optimal drug-likeness and medicinal chemistry characteristics. The ML model and in vitro experiments have identified nervonic acid as a promising α-glucosidase inhibitor. This compound should be further investigated for its potential integration into the diabetes treatment system.

Exploring the Potential of Epigallocatechin Gallate in Combating Insulin Resistance and Diabetes

BACKGROUND/OBJECTIVES

In this study, the potential effects are evaluated of epigallocatechin gallate (EGCG) on the prognosis of diabetes and insulin resistance.

METHODS

In an experiment, 35 male Wistar albino rats were used and in the streptozotocin (STZ)-induced diabetic rats, the effects were examined of different doses (50 mg/kg, 100 mg/kg, 200 mg/kg) of EGCG on metabolic parameters associated with diabetes and insulin resistance.

RESULTS

The findings show favorable effects of EGCG on fasting blood glucose levels, insulin secretion, insulin resistance, and beta cell function. In this study, it was observed that EGCG was able to significantly lower fasting blood glucose levels, especially at high doses (200 mg/kg), providing the most significant improvement. Furthermore, EGCG has been found to reduce insulin resistance and improve insulin sensitivity by increasing insulin secretion. When the biochemical parameters of increased insulin secretion are evaluated, it is also observed that it creates clinically significant changes. At doses of 100 mg/kg and 200 mg/kg, EGCG has the potential to help control diabetes by most effectively improving insulin resistance and beta cell function. The study results suggest that EGCG, especially at high doses, is an effective component in the treatment of diabetes and the management of insulin resistance.

CONCLUSIONS

The inclusion of EGCG as a natural flavonoid in medical nutrition therapy may contribute to glycemic control and improve insulin sensitivity in individuals with diabetes. These findings suggest that EGCG may be used as an alternative option in the treatment of diabetes and future studies may further clarify the potential benefits in this area.

Predicting responsiveness to GLP-1 pathway drugs using real-world data

BACKGROUND

Medications targeting the glucagon-like peptide-1 (GLP-1) pathway are an important therapeutic class currently used for the treatment of Type 2 diabetes (T2D). However, there is not enough known about which subgroups of patients would receive the most benefit from these medications.

OBJECTIVE

The goal of this study was to develop a predictive model for patient responsiveness to medications, here collectively called GLP-1 M, that include GLP-1 receptor agonists and dipeptidyl peptidase-4 (DPP4) inhibitors (that normally degrade endogenously-produced GLP-1). Such a model could guide clinicians to consider certain patient characteristics when prescribing second line medications for T2D.

METHODS

We analyzed de-identified electronic health records of 7856 subjects with T2D treated with GLP-1 M drugs at Vanderbilt University Medical Center from 2003-2019. Using common clinical features (including commonly ordered lab tests, demographic information, other T2D medications, and diabetes-associated complications), we compared four different models: logistic regression, LightGBM, artificial neural network (ANN), and support vector classifier (SVC).

RESULTS

Our analysis revealed that the traditional logistic regression model outperforms the other machine learning models, with an area under the Receiver Operating Characteristic curve (auROC) of 0.77.Our model showed that higher pre-treatment HbA1C is a dominant feature for predicting better response to GLP-1 M, while features such as use of thiazolidinediones or sulfonylureas is correlated with poorer response to GLP-1 M, as assessed by lowering of hemoglobin A1C (HbA1C), a standard marker of glycated hemoglobin used for assessing glycemic control in individuals with diabetes. Among female subjects under 40 taking GLP-1 M, the simultaneous use of non-steroidal anti-inflammatory drugs (NSAIDs) was associated with a greater reduction in HbA1C (0.82 ± 1.72% vs 0.28 ± 1.70%, p = 0.008).

CONCLUSION

These findings indicate a thorough analysis of real-world electronic health records could reveal new information to improve treatment decisions for the treatment of T2D. The predictive model developed in this study highlights the importance of considering individual patient characteristics and medication interactions when prescribing GLP-1 M drugs.

Barriers and facilitators in the acquisition of diabetes knowledge among tertiary-care nurses in central and southern Malawi: an exploratory-descriptive qualitative study

BACKGROUND

Numerous studies report low diabetes knowledge among nurses in sub-Saharan Africa. However, little is known about the factors that hinder and promote their acquisition of knowledge on diabetes mellitus. Understanding these factors is a pivotal step towards ensuring that nurses are knowledgeable and competent in the provision of care and education for patients with diabetes mellitus.

METHODS

The study employed an exploratory-descriptive qualitative (EDQ) approach. Participants were identified from two tertiary hospitals. Twenty-six participants were purposively selected from these facilities. Data were collected through focus group discussions and analysis was done using Braun and Clarke's approach to thematic analysis.

RESULTS

The following themes relating to barriers and facilitators in the nurses' acquisition of diabetes knowledge emerged from the study: (a) individual hindrances; (b) organizational drawbacks; (c) personal ways of knowing; (d) organizational factors enhancing knowledge; and (e) suggestions for improving the nurses' knowledge.

CONCLUSIONS

The study brings to light various challenges and opportunities in the acquisition of diabetes knowledge among tertiary-care nurses in Malawi. Given our study results, we believe that cost-effective measures can be utilised to address the barriers to the acquisition of diabetes knowledge among nurses. This is a crucial step towards ensuring that nurses are knowledgeable and competent in the provision of care for patients with diabetes in low-resource countries.