Early-life exposures could affect the risk of type 2 diabetes (T2D) in adulthood, but the mechanisms remain unclear. We included 319,951 (54.5% women) UK Biobank participants free of T2D at baseline and within the first year of follow-up to investigate whether early-life exposures contribute to T2D through biological aging estimated using the Klemera-Doubal (KDM) and PhenoAge methods. We first examined associations of exposures with biological age and T2D, respectively, using multivariable-adjusted linear models and Cox regression models. Next, we investigated the role of biological age acceleration in exposure-T2D associations using mediation analyses. Overall, the mean (standard deviation) chronological age of participants was 56.3 (8.1) years, KDM age was 40.9 (13.1) years, and PhenoAge was 44.4 (10.0) years. 17,062 T2D cases developed during a median (interquartile range) follow-up of 14.3 (13.5-15.0) years. Maternal smoking around birth, being part of a multiple birth, earlier puberty, and being relatively plumper or thinner at age ten were associated with both a higher biological age and T2D risk, while having a higher birth weight and being breastfed were associated with a lower T2D risk. Biological age acceleration partly mediated the exposure-T2D associations, ranging from a proportion of 8.3% (95%CI: 6.0-13.1%) of the association between birthweight-T2D being mediated by PhenoAge to a proportion of 27.7% (95%CI: 15.3-48.5%) of the association between breastfeeding-T2D being mediated by KDM. In conclusion, early-life exposures were associated with biological age acceleration that partly mediated the exposure-T2D associations, highlighting the importance of addressing early-life risks and biological aging in prevention strategies.

While diabetes-related complications have been widely investigated, the burden of infectious diseases across the diabetes spectrum remains relatively understudied. We developed a Bayesian approach to compare infection risk across 9,476 patients with type 1 diabetes (T1D), 74,270 with type 2 diabetes (T2D), and 32,095 with prediabetes. Patients with T1D, T2D, and prediabetes had multifold increased risk for all organ system- and pathogen-based composite infection outcomes. We also quantified risk for 1,401 individual infection outcomes, finding increased risk for most infections among patients with either T1D, T2D, or prediabetes. Patients had increased risk for well-established diabetes-associated infections (e.g., mucormycosis) and less commonly associated infections (e.g., West Nile Virus encephalitis). Finally, we found disparities in risk across sociodemographic subgroups (i.e., age, sex, ethnicity, ancestry, and insurance status). Our comprehensive findings advance previous research by quantifying risk for wide-ranging infection outcomes across diverse patients with T1D, T2D, and prediabetes through an innovative Bayesian approach.

The study aims to characterize the secretion dynamics of glucagon-related peptides, including GLP-1, GIP, and GLP-2, across different stages of metabolic-associated steatotic liver disease (MASLD), while evaluating the impact of type 2 diabetes (T2D) on these hormonal responses. Thirty-four MASLD subjects were stratified according with the liver transient elastography (TE ≥ 9kPa) and T2D in NF (no fibrosis, without T2D; n = 12), NFD (no fibrosis, with T2D; n = 8), F (fibrosis, without T2D; n = 5), and FD (fibrosis, with T2D; n = 9) and completed a standardized 3-h meal tolerance test (MTT). The presence of liver fibrosis, regardless of diabetes status, was associated with hyperglycemia, hyperinsulinemia, and greater insulin resistance compared to the non-fibrosis (NF) group. Significant differences in glucagon and GLP-1 response curves were observed across groups. People with T2D showed an elevated peak of glucagon and increased glucagon exposure, as indicated by both the 60-min area under the curve (AUC60') and total AUC during the MTT. In the FD group, fasting and peak GLP-1 levels, as well as AUC60' and total AUC GLP-1, were 1.9-, 1.8-, and 1.9-fold higher, respectively, compared to the NF group. GIP responses were similar across groups, except for elevated fasting levels in NFD (p = 0.002). GLP-2 mirrored GLP-1, with FD showing the highest fasting and postprandial levels. Stepwise regression identified fibrosis and FPG as the main predictors of GLP-1, while glucagon was linked to FPG, HbA1c, and BMI. Liver fibrosis and T2D impact glucagon-related peptides responses in MASLD, revealing important metabolic alterations that may guide therapeutic approaches.

This study aims to determine the potential causal relationship between type 2 diabetes (T2D) and autoimmune liver disease (AILD) using Mendelian randomization (MR) combined with clinical case analysis. Summary statistics for T2D, autoimmune hepatitis, primary biliary cholangitis (PBC), and primary sclerosing cholangitis (PSC) were sourced from open genome-wide association study databases. The IVW method was used as the primary analysis. Additional sensitivity analysis was also performed to validate our results. Subsequently, clinical information on patients with AILD was collected retrospectively, while multiple potentially confounding independent effects were assessed using multivariate logistic regression analysis. The results of the forward MR analysis showed that genetically predicted T2D was associated with reduced risk of PSC (IVW: odds ratio [OR] = 0.85, 95% confidence interval [CI], 0.77-0.94, P = .001). Furthermore, the results of the reverse MR analysis revealed the genetically predicted PBC (OR = 1.96, 95% CI 1.31-3.40, P = .016) had a significant correlation with the higher risk of T2D (IVW: OR = 1.02, 95% CI, 1.00-1.04, P = .025). An analysis of the clinical sample revealed that the prevalence of T2D among patients with AILD was 27.6%. Notably, multifactorial logistic regression analysis indicated that immunoglobulin G and total bilirubin levels may serve as independent factors influencing the occurrence of T2D. Genetic evidence demonstrated that T2D reduced the risk of PSC, while PBC increased the risk of T2D. Clinical data further confirmed a high prevalence of T2D in patients with autoimmune liver disease, suggesting a bidirectional relationship that warrants further validation.

Continuous glucose monitoring (CGM) is increasing in insulin-treated type 2 diabetes (T2D). Yet, standardized CGM-based insulin titration is lacking. This study evaluated the feasibility of algorithmic CGM-based titration compared with self-monitoring blood glucose (SMBG) titration. We conducted a 16-week, two-site, randomized controlled trial in adults with T2D (glycated hemoglobin 7%-9%) using degludec and adjunctive noninsulin agents, without rapid-acting insulin. Participants were assigned (2:1) to weekly algorithmic CGM-based dose changes with open CGM (EXP) or weekly SMBG-based titration with blinded CGM (CTR). Both groups received dose notifications via phone. The primary endpoint was the change in CGM-measured time in range (TIR, 70-180 mg/dL) from baseline to week 16, tested for noninferiority (-5%-percentage points [%-pt]). The trial is registered at ClinicalTrials.gov: NCT06111508. A total of 30 participants were randomized. Mean (standard deviation) TIR increased from 54.1% (22.5%) to 75.3% (19.3%) in EXP and from 50.2% (22.1%) to 55.3% (22.7%) in CTR. Mean change was +20.3%-pt versus +8.3%-pt, yielding an estimated treatment difference (EXP - CTR) of +14.6%-pt; one-sided 95% confidence interval (CI) lower bound was +4.0%-pt, exceeding the noninferiority margin (P < 0.005). Exploratory superiority analysis showed two-sided 95% CI: 1.3-27.8 (P = 0.03). CGM-measured hypoglycemia (<70 mg/dL) was low (median [interquartile range]: 0.34% [0.09-0.90] vs. 0.00% [0.00-0.41]), and level 2 episodes (SMBG <54 mg/dL) were rare (1.1 vs. 2.2 patient-year of exposure). No severe hypoglycemia or serious adverse events occurred. Using CGM and receiving algorithmic CGM-based titrations were feasible, safe, and had favorable overall glycemic metrics. Long-term impact should be confirmed in broader populations.

Patient self-care and caregiver contribution to self-care in chronic illnesses should be considered together as a dyadic phenomenon called "dyadic illness management." The possibility of classifying dyadic engagement in chronic conditions care may uncover behavioral patterns useful for improving disease management. Mixed-effects models have been used to obtain dyadic scores, which serve as inputs for latent class analysis. However, the advantages of this approach over simpler synthetic dyadic measures remain unclear. The aim of this study was to compare two methods for obtaining dyadic scores to serve as inputs for identifying distinct patterns of dyadic illness management for type 2 diabetes (T2D) through latent class analysis. This work uses data from a cross-sectional study on 251 patients with T2D and their informal caregivers. Patient self-care and caregiver contribution to self-care were measured by the Self-Care of Diabetes Inventory and the Caregiver Contribution to Self-Care in Diabetes Inventory, respectively. To assess dyadic illness management, we first adopted the incongruence model, a mixed-effects model with a specific codification that enables the estimation of both the average and incongruence in the outcome within each dyad, through random intercepts and random slopes. These estimated coefficients were then used to perform a latent class analysis that was able to identify patterns of dyadic management. As an alternative approach, we calculated the dyadic average and incongruence using the raw means and difference between patient and caregiver scores. These values were then used as inputs for latent class analysis. The latent class analysis clustered the same dyads into the same classes across both approaches, with identical fit indices. The three-class model showed the best performance in terms of both fit and characterization of the dyads. Mixed-effects models account for interdependence within the dyad and measurement error, returning predicted measures that are shrunk toward the overall mean. However, this approach yielded the same clusters as the simpler method based on observed measures.

Glucagon-like peptide-1 receptor agonists (GLP-1RAs) are effective therapies for type 2 diabetes (T2D) and obesity, yet patient responses are variable, with GLP1R gene variation potentially linked to therapeutic outcomes. A GLP1R natural missense variant, A316T, protects against T2D and cardiovascular disease. Here, we generated and characterized a human GLP1R A316T mouse model. Human GLP1RA316T/A316T mice displayed lower fasting blood glucose versus wild-type littermates even under metabolic stress, as well as slower weight gain and alterations in islet cytoarchitecture, glucagon secretion, and liver metabolism under a high-fat, high-sucrose diet. This was however associated with blunted responses to pharmacological GLP-1RAs in vivo. Further investigations in β cell models demonstrated that human GLP1R A316T exhibits characteristics of constitutive activation but dampened GLP-1RA responses. Results are further supported by cryo-EM analyses and molecular dynamics simulations of GLP-1R A316T structure, collectively demonstrating that the A316T variant governs basal GLP-1R activity and pharmacological responses to GLP-1R-targeting therapies.

This study aimed to examine the health literacy (HL) levels of ministry employees, assess their risk of developing type 2 diabetes (T2D), and evaluate the relationship between HL and the risk of developing T2D. Conducted using a cross-sectional design, the study included data from 351 participants working at the Republic of Türkiye Ministry of Environment, Urbanization, and Climate Change between October 2020 and March 2021. Data were collected using the Turkish Health Literacy Scale (TSOY-32) and the Finnish Diabetes Risk Score (FINDRISC). The mean HL score of participants was 31.92±7.85, with 59% of employees classified as having problematic or inadequate HL. Regarding T2D risk, 9.4% of participants were categorized as “high risk” and 1.1% as “very high risk” for developing T2D within the next 10 years. Descriptive findings indicated that as HL levels decreased, the risk of T2D increased. However, multiple linear regression analysis showed that HL was not independently associated with T2D risk when variables such as age and perceived general health were controlled. These findings suggest that although HL is not a direct determinant of T2D risk, it remains an important factor to consider in diabetes prevention programs due to its association with preventive health behaviors. The high prevalence of low HL among employees highlights the need for systematic assessment and enhancement of HL in workplace diabetes prevention initiatives. Longitudinal studies are necessary to understand better the potential causal relationships between HL and the risk of T2D.

MASLD affects over one-third of pediatric patients with T2D. These findings support early liver health screening in this high-risk group. Future research is needed to validate non-invasive tests for liver disease assessment in pediatric diabetes care. • Type 2 diabetes (T2D) is a strong risk factor for metabolic dysfunction-associated steatotic liver disease (MASLD). • The epidemiology of MASLD in children and adolescents with T2D remains poorly characterized. • MASLD affects an estimated 36.61% of pediatric patients with T2D, with substantial variation according to the diagnostic modality used. • This high prevalence underscores the need for early liver health screening in pediatric T2D.

Despite high burdens of mental illness among people with type 1 diabetes (T1D), little is known about how affected individuals experience this dual disease burden. This qualitative study aimed to address this gap. Five online focus groups were conducted with 21 adults with T1D and a history of mental illness. We analysed data using a six-step descriptive phenomenological approach: (1) collecting data, (2) gaining an overall sense of participants' perspectives, (3) segmenting narratives into units of meaning, (4) synthesizing units into themes, (5) determining the structure of the phenomenon, and (6) integrating features into an essential description of living with T1D and mental illness. Two overarching themes were identified. The first, The Weight of Unseen Struggles, encompasses pervasive stressors, including the mental load of diabetes management, experiences of medical trauma, hypervigilance, burnout and the cyclical interplay between diabetes and mental health. These stressors manifest as a range of psychological and somatic symptoms, including depression, anxiety, obsessive thoughts and behaviours, sleep disturbances and trauma responses that affect daily functioning. The second, The Burden of Being 'Othered', highlights how interpersonal, institutional and societal factors contribute to experiences of judgement, stigma and ostracism. Adults with T1D endure a complex interplay of psychological, interpersonal and environmental stressors that exacerbate mental health symptoms and hinder treatment-seeking. Integrating tailored clinical psychological support within diabetes care settings and developing mental health intake policies for people with T1D may enhance access to mental health treatment and improve health outcomes.

This study aimed to identify what young adults with type 1 diabetes (T1D) do to make diabetes care fit in their lives and the impact of diabetes and diabetes care on living. Dutch young adults with T1D (18-30 years old) submitted photographed real-life situations of efforts to make care fit and of the impact of care on their lives. Participants organised their photos in themes, which guided the focus group discussions. We added a reflective questionnaire, semi-structured interview and iterative validation to identify participant-defined themes and summarise the data. Participants (N = 18) submitted 240 photographs in total, showing a broad range of situations and emotions. Participants identified 16 themes, grouped into four overarching categories describing their experiences with diabetes: (1) My diabetes: glucose levels, workload, 24/7 present; (2) My life: flow of (daily) life, special and irregular circumstances, life changes, body and health; (3) Support: devices and technology, social network, clinical (diabetes) care; (4) Mental aspects: emotional processes, perspective, being a patient. In the overlap of My diabetes and My life, they identified eating and counting carbohydrates, activity and exercise, recreational substances. Young adults with T1D face the complex challenge of fitting their care into their ever-changing lives. While support systems, such as devices, healthcare professionals and social networks can help, they can also create burdens. Participants emphasised the importance of mental health in their lives with T1D. This study highlights the need for diabetes care that acknowledges the emotional, social and practical realities of young adults' lives.

Salivary extracellular vesicles and Raman spectroscopy in precision diagnostics of type 2 diabetes.

Background: Type 1 diabetes (T1D) is associated with metabolic and neuromuscular impairments that may influence fatigue mechanisms and limit exercise tolerance. Although previous investigations have characterized muscle performance in T1D, the peripheral fatigue threshold, defined as the maximal sustainable level of peripheral fatigue, remains poorly understood in this population. This study aimed to compare the amplitude of the maximal peripheral fatigue threshold between individuals with T1D and healthy controls to elucidate the effects of T1D on neuromuscular function. Methods: Twenty-two participants (11 with T1D and 11 healthy controls) completed two randomized experimental sessions. In each session, 60 quadriceps maximal voluntary contractions (MVCs) were completed, performed for 3 s with 2 s of rest between contractions. One session was conducted under a non-fatigued control condition (CTRL), and the other followed a fatiguing neuromuscular electrical stimulation (FNMES) protocol. Central and peripheral fatigue were evaluated from the pre- to post-exercise changes in potentiated twitch force (ΔPtw) and voluntary activation (ΔVA), respectively. Critical torque (CT) was calculated as the average torque produced during the last 12 contractions, whereas the curvature constant of the torque–duration relationship (W′) was quantified as the area above CT. Results: Although both groups exhibited a decline in pre-exercise Ptw following the FNMES condition, no significant within-group differences in ΔPtw were observed between sessions (T1D: p = 0.34; controls: p = 0.23). Nevertheless, the extent of peripheral fatigue was significantly lower in participants with T1D than in controls (ΔPtw = −38 ± 11% vs. −52 ± 17%; p &lt; 0.05). Additionally, W′ values were reduced by 24% in the T1D group relative to controls during the CTRL condition (p = 0.02), and CT was significantly lower in T1D participants (262 ± 49 N) compared to controls (353 ± 71 N; p &lt; 0.01). A significant positive correlation was observed between ΔPtw and W′ across groups (r2 = 0.62, p &lt; 0.001), suggesting a mechanistic link between peripheral fatigue tolerance and work capacity. Conclusions: The present results indicate that, although individuals with T1D retain the capacity to develop peripheral fatigue, their fatigue threshold and critical torque are markedly attenuated relative to those of healthy individuals. This reduction reflects impaired neuromuscular efficiency and diminished tolerance to sustained contractile activity. The strong relationship between peripheral fatigue and work capacity underscores the contribution of peripheral mechanisms to exercise intolerance in T1D. These results enhance current understanding of fatigue physiology in diabetes and emphasize the need for tailored exercise and rehabilitation strategies to improve fatigue resistance and functional performance in this population.

Type 2 diabetes (T2D) is a heterogenous metabolic condition characterized by varying degrees of insulin resistance and β-cell dysfunction. Preclinical mouse models are essential tools to investigate the mechanisms of T2D pathogenesis and develop therapeutic targets; yet, researchers often fail to specify which aspects of the spectrum of human T2D phenotypes are being modeled. In this mini-review, we critically examine mouse models of T2D and categorize them into recently redefined T2D subtypes according to key pathophysiological features. We focus on models that exhibit (1) insulin deficiency, (2) insulin resistance independent of weight gain, or (3) insulin resistance associated with weight gain. Onset, severity, and progression of metabolic phenotypes are described and discussed in context with clinical presentation in humans. While we find current T2D mouse models do not fully capture the heterogeneity of T2D, strategic model combinations and longer-term phenotyping could help better mimic clinical progression. Existing phenotyping data are often incomplete and largely available only for young male mice. We highlight the urgent need for thorough and standardized phenotyping of both sexes in all models. We also encourage the field to move toward using age-appropriate mice to better reflect human T2D pathophysiology and to advance precision medicine efforts in diabetes research.

The efficacy of adding various noninsulin hypoglycemic drugs to automated insulin delivery (AID) systems in patients with type 1 diabetes (T1D) was investigated in randomized controlled trials (RCTs), yet no meta-analysis has been conducted. This study aimed to systematically analyze the existing evidence. Four datasets were searched up to August 31, 2025. Inclusion criteria were as follows: T1D populations of any age; comparing any type of noninsulin hypoglycemic drug added to AID systems or not; and reporting primary outcomes (time in range [TIR] = 70-180 mg/dL, 3.9-10.0 mmol/L). Results were pooled using a random-effect meta-analysis. Risk of bias was assessed using the Cochrane RoB2 tool. Quality of evidence was assessed by the Grading of Recommendations Assessment, Development, and Evaluation approach (Registered number: CRD420251107996). Nine RCTs met the inclusion criteria, investigating sodium-glucose cotransporter-2 inhibitor (SGLT-2i) (N = 5), glucagon-like peptide-1 receptor agonist (GLP-1 RA) (N = 2), and dipeptidyl peptidase-4 inhibitor (DPP-4i) (N = 2), respectively. Overall, these drugs with AID systems improved TIR by +10.0% (7.4%-12.6%) and time in tight range (TITR; 70-140 mg/dL, 3.9-7.8 mmol/L) by +8.9% (6.8%-11.0%) with I2 of 60.4% and 15.4% (P < 0.001). These improvements were primarily driven by reductions in time above range (TAR) >250 mg/dL (>13.9 mmol/L; -4.3 [-5.8 to -2.8] %), TAR >180 mg/dL (>10.0 mmol/L; -11.6 [-14.7 to -8.5] %), and coefficient of variation (-2.9 [-4.5 to -1.4] %) without increased hypoglycemia. Daily insulin dose decreased by 8.9 units. Among these, SGLT-2i conferred the greatest TIR improvement (+12.5%), followed by GLP-1 RA (+7.1%) and DPP-4i (+6.4%). No significant differences were found in severe hypoglycemia (SH) and diabetic ketoacidosis (DKA). SGLT-2i, DPP-4i, and GLP-1 RA may serve as effective and safe adjuncts for T1D individuals using AID systems, offering improvements in TIR, reductions in hyperglycemia, and reduced insulin requirements without evidence of increasing DKA and SH.

Type 1 diabetes (T1D) is driven by autoreactive T cells, which destroy insulin-producing β cells. Antigen-specific immunotherapies (ASITs) aim to restore immune tolerance while avoiding the broad immunosuppression of current therapies. Soluble antigen arrays (SAgAs) are multivalent antigen constructs built on a low-molecular-weight hyaluronic acid (HA) backbone, previously validated in preclinical models. Here, we generated SAgAs displaying human T1D autoantigen epitopes, including Insulin B:9-23 (InsB:9-23) and a hybrid insulin peptide (HIP), alongside a hemagglutinin (HAg):306-318 control. We confirmed their structure, valency, and ability to engage human epitope-specific T cell clones. Both InsB:9-23-SAgA and HIP-SAgA demonstrated strong specificity, supporting their utility as T cell probes and potential candidates for ASIT in T1D.

Older adults with type 2 diabetes (T2D) face an elevated risk of falls due to combined physical and cognitive impairments. The DiaActive feasibility study evaluated the safety, feasibility, and acceptability of a novel fall-prevention exercise program integrating multitask rhythm-based movement, activities of daily living (ADL) exercises, and a structured social component. Eight community-dwelling adults (≥ 65 years) with T2D participated in two 60-minute physiotherapist-led sessions per week for four weeks (total 480min). The program combined rhythm-based (Rythma) and ADL exercises with structured social interaction. Feasibility outcomes included adherence, safety, satisfaction, and overall acceptability. Adherence was high, with a median attendance of 88% (range 75-100%) and 100% questionnaire completion. No injuries or adverse events occurred, indicating good safety and tolerability. Participants reported that session difficulty progressed appropriately, shifting from "too easy" early on to "appropriately challenging" by week four. Satisfaction increased over time, with most rating sessions as "satisfactory" or "very satisfactory." Qualitative feedback evolved from exercise-focused comments to broader reflections on body awareness and social connectedness. The positive group atmosphere and structured social elements were key motivators supporting adherence and engagement. The DiaActive protocol-combining rhythm-based, ADL-focused, and social components-was safe, feasible, and well accepted by older adults with T2D. High adherence, absence of adverse events, and increasing satisfaction support progression to a fully powered randomized controlled trial to assess clinical efficacy and long-term adherence.

Type-2 diabetes mellitus (DM) increases tuberculosis (TB) risk and can worsen treatment outcomes. Both diseases and their treatments induce significant metabolic and biochemical perturbations that influence disease progression and management. This study longitudinally evaluated clinical, metabolic, and serum biochemical changes in patients with pulmonary TB with and without DM before and during anti-TB therapy. Ninety-five adult patients newly diagnosed with pulmonary TB in Ghana were stratified into TB-Only (n = 49; HbA1c < 6.5%) and TB-DM (n = 46; HbA1c ≥ 6.5%) groups, including treated (TB-DMt) and untreated (TB-DMnt) diabetes subgroups. Serum samples collected at baseline (t0), day 28 (t28), and day 56 (t56) were analyzed for electrolytes, renal function, liver enzymes, and lipid profiles using validated clinical chemistry analyzer. TB-DM cohorts exhibited significantly lower chloride levels at all time points relative to the TB-Only cohort (e.g., 98 vs. 100 mmol/L at t0, p < 0.001). Hyponatremia (serum sodium < 136 mmol/L) was prevalent during the intensive anti-TB treatment phase, affecting 53.1% of TB-Only patients, 61.1% of TB-DMt patients, and 70.0% of TB-DMnt patients. Liver function tests revealed elevated bilirubin, gamma-glutamyl transferase (g-GT), alkaline phosphatase (ALP), and alanine aminotransferase (ALT) levels, particularly in TB-DMnt patients, with normalization over time. Lipid profiles showed a pro-atherogenic pattern with elevated triglycerides and total cholesterol (p < 0.05). High-density and low-density lipoproteins were increased at select time points. Positive correlations were noted among albumin, cholesterol fractions, and electrolytes. Primary microbiological treatment outcomes, including sputum conversion and completion rates, were similar regardless of diabetic status. The distinctive metabolic and biochemical derangements in TB-DM, especially untreated diabetes, highlight the importance of integrated clinical management. Elevated hepatic enzymes in TB-DMnt may delay metformin initiation, suggesting a need to optimize timing post hepatic recovery, while the prevalence of hyponatremia underscores the need for routine electrolyte monitoring in TB patients with diabetes. The dysregulated lipid profile highlights cardiovascular risk that warrants routine monitoring. Despite metabolic challenges, effective TB treatment outcomes are achievable with comprehensive care.

To describe the design and examine the psychometric properties of the Hypoglycaemia Cues Questionnaire (HypoC-Q) for assessing thoughts, feelings, and behaviours related to hypoglycaemia among adults with type 1 diabetes (T1D). The HypoC-Q was designed iteratively, informed by exploratory interviews with 17 adults with T1D with impaired awareness of hypoglycaemia and/or recurrent severe hypoglycaemia, and consultation with diabetologists. Psychometric analyses were completed on baseline data from the Hypo-METRICS study. Data from adults with T1D, reporting at least one hypoglycaemic event, were eligible if they had completed the baseline HypoC-Q. Completion rates, latent structure, internal consistency, construct and known-groups validity were examined. In Hypo-METRICS, 154 participants (62% females; mean ± SD age 44 ± 15 years; T1D duration: 23 ± 16 years) were eligible. All completed all 40 HypoC-Q items, demonstrating its acceptability. Exploratory factor analysis identified four scales with satisfactory internal consistency (α = 0.69-0.81): 1) low concern (7 items), 2) burnout (6 items), 3) missing cues (5 items), and 4) delaying treatment (9 items); plus eight items, treated separately. Construct validity was supported by significant moderate correlations between 'burnout' and fear of hypoglycaemia and diabetes distress, and between 'missing' and 'delay' with impaired awareness of hypoglycaemia; all three distinguished between those with intact and impaired awareness (known-groups validity); but not by history of severe hypoglycaemia. The HypoC-Q is an acceptable, valid, and reliable measure of thoughts, feelings, and behaviours related to hypoglycaemia among adults with T1D. It is available for informing and assessing the effect of interventions to reduce hypoglycaemia exposure and impact.

This study aimed to investigate the association of smoking status and years since cessation with the onset, progression, and prognosis of cardio-renal-metabolic (CRM) multimorbidity (CRMM). This study included participants from the UK Biobank who were free of CRM disease at baseline. Covariates adjusted Cox proportional hazards models were employed to evaluate the associations of smoking status and years since smoking cessation with the risks of individual CRM diseases, including ischemic heart disease (IHD), stroke, type 2 diabetes (T2D), and chronic kidney disease (CKD), as well as with each state in CRMM progression, including first CRM disease (FCRMD), CRMM (defined as the occurrence of two or more CRM diseases), and death. Multi-state models were used to analyze the associations between smoking-related behaviors and CRMM progression. The effects of smoking cessation were further explored within subgroups according to sex, age at smoking initiation, smoking duration, smoking intensity, and genetic risk scores for individual CRM diseases. In total, 356,071 participants (median age 57years; 44.9% male) who were free of CRM disease (healthy) at baseline and had complete information on smoking status were included. During a median follow-up of 13.6years, 56,786 participants developed a FCRMD, and 11,508 progressed to CRMM, of whom 2,796 subsequently died. Across all transitions from healthy to FCRMD, then to CRMM, and ultimately to death, current smoking had a greater impact on transitions leading to mortality. Compared with never smokers, current smokers had an adjusted hazard ratio of 1.44 (95% CI: 1.40-1.47) for the transition from healthy to FCRMD and 2.49 (95% CI: 2.38-2.60) for the transition from healthy to death. Approximately 25years of smoking cessation were required for risks across all transitions in CRMM progression among former smokers to became not significantly different from those of never smokers. Compared with current smokers, former smokers experienced significantly lower risks for transitions leading to death shortly after cessation, whereas risk reductions for the transitions from healthy to FCRMD and from FCRMD to CRMM were not observed until more than 5 and 20years after cessation, respectively. When disease-specific transitions were further considered, longer post-cessation periods were required to achieve significant risk reductions for transitions from healthy to T2D or CKD and from IHD or T2D to death, compared with current smokers. The effects of smoking cessation on CRMM progression varied by sex and previous smoking behavior, but not by genetic susceptibility to specific CRM diseases. Smoking has substantial but varied impacts across transitions in CRMM progression and disease-specific pathways. Long-term smoking cessation is an important strategy for reducing the risk of CRMM onset and progression. Individuals with specific prior smoking patterns (e.g., male or heavy smokers) and those at certain transition states warrant particular attention during the short-term period following smoking cessation.