Diabetes research and clinical practice最新文献

{"title":"Association of age at diagnosis of type 2 diabetes mellitus with the risks of the morbidity of cardiovascular disease, cancer and all-cause mortality: Evidence from a real-world study with a large population-based cohort study","authors":"Yuhao Li ,&nbsp;Jinbin Luo ,&nbsp;Kaifang Bao ,&nbsp;Qiaohui Wei ,&nbsp;Xiaohong Wang ,&nbsp;Jieping Chen ,&nbsp;Tao Zhang ,&nbsp;Fengying Wang ,&nbsp;Yimin Zhu","doi":"10.1016/j.diabres.2024.111870","DOIUrl":"10.1016/j.diabres.2024.111870","url":null,"abstract":"<div><h3>Aims</h3><div>To investigate the impact of diagnosis age of type 2 diabetes mellitus (T2DM) on subsequent adverse outcomes within the Chinese population.</div></div><div><h3>Methods</h3><div>549,959 eligible T2DM patients were included from Ningbo and Jinhua city in Zhejiang province, China. Standardized ratio was used to evaluate the risks of coronary heart disease (CHD), stroke, cancer and all-cause death in different T2DM diagnosis age groups.</div></div><div><h3>Results</h3><div>For all adverse outcomes, higher excess risks were observed in the youngest age group (30–39) than in the oldest age group (≥80) with T2DM. The standardized incidence ratios (SIR) were 5.93 (95% CI: 3.46, 10.14) for CHD, 5.45 (95% CI: 3.72, 7.99) for stroke and 1.85 (95% CI: 1.38, 2.49) for cancer in the youngest age group, and were 1.32 (95% CI: 1.08, 1.60) for CHD, 1.25 (95% CI: 1.08, 1.44) for stroke, and 0.78 (95% CI: 0.56, 1.09) for cancer, respectively, in the oldest age group. The standardized mortality ratios (SMR) for all-cause death were 3.15 (1.69, 5.84) vs. 1.12 (0.88, 1.43). These excess risks decreased with increasing diagnosis age (all P value &lt; 0.001). Consistent results were observed when individuals were stratified by sex or further excluded with the time from T2DM diagnosis to endpoints less than 1 or 2 years.</div></div><div><h3>Conclusions</h3><div>Th earlier the diagnosis of T2DM, the higher the risk for subsequent adverse outcomes. It is imperative to enhance the management and monitoring of early-onset patients during follow-up.</div></div>","PeriodicalId":11249,"journal":{"name":"Diabetes research and clinical practice","volume":"217 ","pages":"Article 111870"},"PeriodicalIF":6.1,"publicationDate":"2024-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142343474","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mortality in type 1 diabetes mellitus: A single centre experience from the ICMR – Youth onset diabetes registry in India","authors":"S.V. Madhu ,&nbsp;P. Shukla ,&nbsp;T. Kaur ,&nbsp;R.S. Dhaliwal","doi":"10.1016/j.diabres.2024.111868","DOIUrl":"10.1016/j.diabres.2024.111868","url":null,"abstract":"<div><h3>Introduction</h3><div>The prevalence of youth onset diabetes is rising globally along with a greater burden of complications and mortality in them. The current study was undertaken to examine the mortality and causes of death in patients with youth onset diabetes<!--> <!-->registered in a tertiary care hospital in North India.</div></div><div><h3>Methods</h3><div>We analyzed mortality and causes of death in 1088 patients with youth onset diabetes registered from 2006 to 2019 at University College of Medical Sciences, Delhi. Information of death was obtained telephonically or by home visit or from hospital records wherever available. Verbal autopsy according to ICMR questionnaire was performed and cause of death determined as per WHO ICD-10/11.</div></div><div><h3>Results</h3><div>Among 898 youth onset type 1 diabetes mellitus (T1D) patients who had a mean follow up of 6.4 years, 105 deaths (11.6 %) occurred. Forty three percent of deaths had diabetes onset at 15 years or below, and 75.6 % had HbA1C &gt; 10 %. Deaths occurred in 24.2 % within 2 years and in 53.6 % within 3 years of diagnosis. Chronic Kidney disease, infections and ketoacidosis were the commonest causes.</div></div><div><h3>Conclusion</h3><div>We found poor glycaemic control and high mortality in people with youth onset T1D being treated at a tertiary care hospital in north India.</div></div>","PeriodicalId":11249,"journal":{"name":"Diabetes research and clinical practice","volume":"217 ","pages":"Article 111868"},"PeriodicalIF":6.1,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142343571","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Associations of triglyceride–glucose index cumulative exposure and variability with the transitions from normoglycaemia to prediabetes and prediabetes to diabetes: Insights from a cohort study","authors":"Yaqin Wang ,&nbsp;Lei Liu ,&nbsp;Pingting Yang ,&nbsp;Ying Li ,&nbsp;Yufu Zhou ,&nbsp;Saiqi Yang ,&nbsp;Kui Chen ,&nbsp;Shuwen Deng ,&nbsp;Xiaoling Zhu ,&nbsp;Xuelian Liu ,&nbsp;Changfa Wang","doi":"10.1016/j.diabres.2024.111867","DOIUrl":"10.1016/j.diabres.2024.111867","url":null,"abstract":"<div><h3>Aim</h3><div>This study aimed to investigate the separate and joint associations of triglyceride–glucose (TyG) index accumulation and variability with prediabetes and diabetes risk.</div></div><div><h3>Methods</h3><div>Health check-up participants who underwent 3 sequential health examinations during 2012–2016 and were followed up from 2017 to 2021 were enrolled and categorized into two subcohorts: (a) progression from normoglycaemia to prediabetes subcohort (n = 9373) and (b) progression from prediabetes to diabetes subcohort (n = 4563). Cumulative TyG (cumTyG) and TyG variability from Exams 1–3 were the exposures of interest in our study. The outcomes were newly incident prediabetes or diabetes.</div></div><div><h3>Results</h3><div>In the prediabetes development subcohort, 2,074 participants developed prediabetes over a 2.42-year follow-up. Higher cumTyG (HR, 2.02; 95 % CI, 1.70–2.41), but not greater TyG variability alone, was significantly associated with increased prediabetes risk. In the diabetes development subcohort, 379 participants developed diabetes over a 3.0-year follow-up. Higher cumTyG (HR, 3.54; 95 % CI, 2.29–5.46), but not greater TyG variability alone, was significantly associated with increased diabetes risk. The “cumTyG+variability” combination had the highest predictive value for prediabetes and diabetes beyond a single baseline TyG measurement.</div></div><div><h3>Conclusion</h3><div>Higher cumTyG exposure independently predicts prediabetes and diabetes incidence. Coexisting cumTyG and variability could further yield incrementally greater risks.</div></div>","PeriodicalId":11249,"journal":{"name":"Diabetes research and clinical practice","volume":"217 ","pages":"Article 111867"},"PeriodicalIF":6.1,"publicationDate":"2024-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142327716","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A prediction model for gestational diabetes mellitus based on steroid hormonal changes in early and mid-down syndrome screening: A multicenter longitudinal study","authors":"Bo Zhu ,&nbsp;Binbin Yin ,&nbsp;Hui Li ,&nbsp;Xuelian Chu ,&nbsp;Zhifeng Mi ,&nbsp;Yanni Sun ,&nbsp;Xiaofen Yuan ,&nbsp;Rongchang Chen ,&nbsp;Zhixin Ma","doi":"10.1016/j.diabres.2024.111865","DOIUrl":"10.1016/j.diabres.2024.111865","url":null,"abstract":"<div><h3>Background</h3><div>Steroid hormones (SH) during pregnancy are associated with the development of gestational diabetes mellitus (GDM). Early and mid-Down syndrome screening is used to assess the risk of Down syndrome in the fetus. It is unclear whether changes in SH during this period can be used as an early predictor of GDM.</div></div><div><h3>Methods</h3><div>This study was a multicenter, longitudinal cohort study. GDM is diagnosed by an oral glucose tolerance test (OGTT) between 24 and 28 weeks of gestation. We measured SH levels at early and mid-Down syndrome screening, respectively. Based on the SH changes, logistic regression analysis was used to construct a prediction model for GDM. Finally, evaluated the model’s predictive performance by creating a receiver operating characteristic curve (ROC) and performing external validation.</div></div><div><h3>Results</h3><div>This study enrolled 193 pregnant women (discovery cohort, n = 157; validation cohort, n = 36). SH changes occur dynamically after pregnancy. At early Down syndrome screening, only cortisol (F) (<em>p</em> &lt; 0.05, 95 % CI 4780.95–46083.68) was elevated in GDM. At mid-Down syndrome screening, free testosterone (FT) (<em>p</em> &lt; 0.01, 95 % CI 0.10–0.55) and estradiol (E2) (<em>p</em> &lt; 0.05, 95 % CI 203.55–1784.78) were also significantly elevated. There were significant differences in the rates of change in E2 (Fold change (FC) = 1.3425, <em>p</em> = 0.0072), albumin (ALB) (FC=1.5759, <em>p</em> = 0.0117), and dihydrotestosterone (DHT) (FC=-2.1234, <em>p</em> = 0.0165) between GDM and no-GDM. Stepwise logistic regression analysis resulted in the best predictive model, including six variables (Δweight, ΔF, Δcortisone (E), ΔE2, Δprogesterone (P), ΔDHT). The area under the curve for this model was 0.791, and for the external validation cohort, it was 0.799.</div></div><div><h3>Conclusions</h3><div>A GDM prediction model can be constructed using SH measures during early and mid-Down syndrome screening.</div></div>","PeriodicalId":11249,"journal":{"name":"Diabetes research and clinical practice","volume":"217 ","pages":"Article 111865"},"PeriodicalIF":6.1,"publicationDate":"2024-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142281900","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sleep quality and glucose control in adults with type 1 diabetes during the seasonal daylight saving time shifts","authors":"Silvia Angelino ,&nbsp;Miriam Longo ,&nbsp;Paola Caruso ,&nbsp;Lorenzo Scappaticcio ,&nbsp;Nicole Di Martino ,&nbsp;Concetta Di Lorenzo ,&nbsp;Daniela Forestiere ,&nbsp;Vanda Amoresano Paglionico ,&nbsp;Giuseppe Bellastella ,&nbsp;Maria Ida Maiorino ,&nbsp;Katherine Esposito","doi":"10.1016/j.diabres.2024.111859","DOIUrl":"10.1016/j.diabres.2024.111859","url":null,"abstract":"<div><h3>Aim</h3><p>There is a bidirectional relationship between glucose control and sleep quality and timing in type 1 diabetes (T1D). The aim of the study was to investigate the sleep quality and the glucose metrics in people with T1D at the seasonal clock adjustment.</p></div><div><h3>Methods</h3><p>This observational study retrospectively compared the continuous glucose monitoring (CGM) derived metrics and sleep quality observed before (Time 0) and after (Time 1) transition in autumn and before (Time 2) and after (Time 3) transition in spring. We included adults with T1D, treated with CGM systems, who completed the Pittsburgh Sleep Quality Index questionnaire. The main outcome measure was the change in glucose monitoring indicator (GMI), time in range (TIR), time above range (TAR) and time below range.</p></div><div><h3>Results</h3><p>Sixty-two participants showed no changes in sleep quality at time transitions. GMI values increased during both time transitions and the percentage of TIR decreased from Time 0 to Time 1 and from Time 2 to Time 3. The percentage of level 2 TAR increased during the observation.</p></div><div><h3>Conclusions</h3><p>At similar level of sleep quality, adults with T1D underwent the worsening of most of CGM-derived glucose control metrics during the transition time.</p></div>","PeriodicalId":11249,"journal":{"name":"Diabetes research and clinical practice","volume":"217 ","pages":"Article 111859"},"PeriodicalIF":6.1,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0168822724007691/pdfft?md5=634c9dc676c402fca942e09956120407&pid=1-s2.0-S0168822724007691-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142272011","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Diabetes distress profiles and health outcomes of individuals with type 2 diabetes and overweight/obesity: A cluster analysis","authors":"Yiyun Zhang ,&nbsp;Dan Zhang ,&nbsp;Tianxue Long,&nbsp;Yi Wu,&nbsp;Jing Huang,&nbsp;Yating Zhang,&nbsp;Mingzi Li","doi":"10.1016/j.diabres.2024.111863","DOIUrl":"10.1016/j.diabres.2024.111863","url":null,"abstract":"<div><h3>Aims</h3><p>To determine the prevalence and patterns of diabetes distress, and evaluate the differences in health outcomes between profiles.</p></div><div><h3>Methods</h3><p>This cross-sectional study included 330 adults with T2DM and overweight/obesity. The participants completed questionnaires on diabetes distress, sleep quality, self-efficacy, depression, anxiety and positive and negative affect. A cluster analysis was performed to identify different patterns of diabetes distress and one-way ANOVA was used to investigate the differences in physical and psychological outcomes between profiles.</p></div><div><h3>Results</h3><p>30.6% of patients were identified as moderately to highly distressed, with the regimen-related distress found to be the most prominent. The Cluster analysis revealed four distinct clusters: (1) “comprehensively exhausted profile”; (2) “strained profile”; (3) “high internal anguish profile”; (4) “unperturbed profile”. The measures of fasting blood glucose (FBG), glycated hemoglobin (HbA1c), low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, sleep quality, depression, anxiety, positive and negative affect and self-efficacy differ between clusters.</p></div><div><h3>Conclusions</h3><p>This study identified important differences that existed in patterns of diabetes distress among people with T2DM and overweight/obesity, and this variation can be utilized to tailor intervention strategies to the particular needs of different subgroups within individuals with T2DM.</p></div>","PeriodicalId":11249,"journal":{"name":"Diabetes research and clinical practice","volume":"217 ","pages":"Article 111863"},"PeriodicalIF":6.1,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142271901","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Diabetes mellitus is associated with low exercise capacity and impaired peripheral vasodilation in patients with heart failure − a propensity score-matched study","authors":"Miroslava Valentova ,&nbsp;Mirela Vatic ,&nbsp;Tania Garfias-Veitl ,&nbsp;Anja Sandek ,&nbsp;Tarek Bekfani ,&nbsp;Ewa A. Jankowska ,&nbsp;John G.F. Cleland ,&nbsp;Andrew L. Clark ,&nbsp;Mitja Lainscak ,&nbsp;Ali Ahmed ,&nbsp;Nadja Jauert ,&nbsp;Gerd Hasenfuss ,&nbsp;Stefan D. Anker ,&nbsp;Wolfram Doehner ,&nbsp;Stephan von Haehling","doi":"10.1016/j.diabres.2024.111864","DOIUrl":"10.1016/j.diabres.2024.111864","url":null,"abstract":"<div><h3>Aims</h3><div>Diabetes mellitus (DM) and heart failure (HF) share vascular, skeletal and metabolic abnormalities that can reduce exercise capacity. We investigated whether exercise capacity differ in patients with type 2 DM compared to those without DM with HF of similar severity.</div></div><div><h3>Methods and results</h3><div>The Studies Investigating Co-morbidities Aggravating HF (SICA-HF) prospectively enrolled 615 patients with chronic HF, 259 (42.1 %) of whom had DM. We assembled a propensity score-matched cohort of 231 pairs of patients with HF with or without DM who were balanced on age, sex and variables reflecting HF severity. Patients with DM had lower median peak VO₂ (15.7 [13.0–19.1] <em>vs.</em> 17.3 [14.1–21.0] ml/min/kg; p = 0.005). Forearm blood flow reserve (per 1 ml/min/100 ml increase) was associated with lower exercise capacity (peak VO2 ≤ 16.6 ml/min/kg) in patients with DM (OR, 0.92; 95 % CI, (0.85–0.98; p = 0.014), but not in those without DM (OR, 0.98; 95 % CI, 0.93–1.02). A similar heterogeneity was also observed for HDL cholesterol.</div></div><div><h3>Conclusions</h3><div>Diabetes is associated with a reduced exercise capacity in patients with HF. Most predictors of lower exercise capacity in HF are similar regardless of DM except impaired vascular function and lower HDL cholesterol which predict lower exercise capacity only in those with DM.</div></div>","PeriodicalId":11249,"journal":{"name":"Diabetes research and clinical practice","volume":"217 ","pages":"Article 111864"},"PeriodicalIF":6.1,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142281901","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Computed tomography-based body composition indicative of diabetes after hypertriglyceridemic acute pancreatitis","authors":"Yingbao Huang ,&nbsp;Yi Zhu ,&nbsp;Weizhi Xia ,&nbsp;Huanhuan Xie ,&nbsp;Huajun Yu ,&nbsp;Lifang Chen ,&nbsp;Liuzhi Shi ,&nbsp;Risheng Yu","doi":"10.1016/j.diabres.2024.111862","DOIUrl":"10.1016/j.diabres.2024.111862","url":null,"abstract":"<div><h3>Background</h3><p>Post‑acute pancreatitis prediabetes/diabetes mellitus (PPDM‑A) is one of the common sequelae of acute pancreatitis (AP). The aim of our study was to build a machine learning (ML)-based prediction model for PPDM-A in hypertriglyceridemic acute pancreatitis (HTGP).</p></div><div><h3>Methods</h3><p>We retrospectively enrolled 165 patients for our study. Demographic and laboratory data and body composition were collected. Multivariate logistic regression was applied to select features for ML. Support vector machine (SVM), linear discriminant analysis (LDA), and logistic regression (LR) were used to develop prediction models for PPDM-A.</p></div><div><h3>Results</h3><p>65 patients were diagnosed with PPDM-A, and 100 patients were diagnosed with non-PPDM-A. Of the 84 body composition-related parameters, 15 were significant in discriminating between the PPDM-A and non-PPDM-A groups. Using clinical indicators and body composition parameters to develop ML models, we found that the SVM model presented the best predictive ability, obtaining the best AUC=0.796 in the training cohort, and the LDA and LR model showing an AUC of 0.783 and 0.745, respectively.</p></div><div><h3>Conclusions</h3><p>The association between body composition and PPDM-A provides insight into the potential pathogenesis of PPDM-A. Our model is feasible for reliably predicting PPDM-A in the early stages of AP and enables early intervention in patients with potential PPDM-A.</p></div>","PeriodicalId":11249,"journal":{"name":"Diabetes research and clinical practice","volume":"217 ","pages":"Article 111862"},"PeriodicalIF":6.1,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142243856","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Physical activity and sedentary behaviour in relation to body composition, estimated insulin sensitivity and arterial stiffness in adults with type 1 diabetes","authors":"Simon Helleputte ,&nbsp;Jan Stautemas ,&nbsp;Marieke De Craemer ,&nbsp;Lotte Bogaert ,&nbsp;Tine De Backer ,&nbsp;Patrick Calders ,&nbsp;Bruno Lapauw","doi":"10.1016/j.diabres.2024.111860","DOIUrl":"10.1016/j.diabres.2024.111860","url":null,"abstract":"<div><h3>Aims</h3><p>To examine the association of daily PA levels and sedentary behaviour with body composition, estimated insulin sensitivity, and arterial stiffness in adults with type 1 diabetes (T1D).</p></div><div><h3>Methods</h3><p>Cross-sectional study in adults with T1D (n = 54). PA levels (daily steps, and time in moderate-to-vigorous intensity PA (MVPA)) and sedentary behaviour were measured using accelerometry for 7 days (<em>McRoberts® DynaPort MoveMonitor</em>). Cardiopulmonary exercise test for VO_2max. Anthropometrics were collected, and body composition (total and % of fat mass (FM_tot, FM_%), total and % of lean mass (LM_tot, LM_%), and estimated visceral adipose tissue (VAT)) volume was assessed with dual energy X-ray-absorptiometry (DXA). Estimates of insulin sensitivity were determined (estimated glucose disposal rate (eGDR) and total daily insulin dose). Arterial stiffness was assessed with carotid-femoral pulse wave velocity (cf-PWV (m/s); <em>SphygmoCor®</em>).</p></div><div><h3>Results</h3><p>Lower 10-years HbA1_c associated moderately with all PA measures. Favourable moderate associations were also found between PA measures and BMI, waist, VAT but not FM and LM. PA measures were favourably associated with a lower total daily insulin dose and higher eGDR. All PA parameters associated moderately with cf-PWV however not independent from traditional risk factors. VO_2max was inversely associated with cf-PWV independent of age, T1D duration and 24-hour mean blood pressure.</p></div><div><h3>Conclusions</h3><p>Higher levels of PA, lower sedentary behaviour and greater exercise capacity are favourably associated with long-term glycaemic control, body composition, insulin dosage, estimated insulin sensitivity and arterial stiffness in adults with T1D. Therefore, regular PA and limiting sedentary time should be encouraged to improve metabolic and cardiovascular health in this population. Future longitudinal studies should explore mutual interactions and synergistic effects of PA on these outcomes.</p></div>","PeriodicalId":11249,"journal":{"name":"Diabetes research and clinical practice","volume":"217 ","pages":"Article 111860"},"PeriodicalIF":6.1,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142243854","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Association of ideal cardiovascular health and history of gestational diabetes mellitus in NHANES 2007–2018","authors":"Rabail Sadiq ,&nbsp;Eric K. Broni ,&nbsp;Lisa D. Levine ,&nbsp;Ravi Retnakaran ,&nbsp;Justin B. Echouffo-Tcheugui","doi":"10.1016/j.diabres.2024.111857","DOIUrl":"10.1016/j.diabres.2024.111857","url":null,"abstract":"<div><h3>Background</h3><p>Population-based studies of ideal cardiovascular health (CVH) and gestational diabetes mellitus (GDM) are scarce.</p></div><div><h3>Methods</h3><p>We conducted a cross-sectional analysis of 2007–2018 National Health Examination and Nutrition Survey women aged ≥ 20 years, who had data on Life’s Simple 7 (LS7) metrics and self-reported GDM history. Each LS7 metric was assigned a score of 0 (non-ideal) and 1(ideal) and summed to obtain total ideal CVH scores (0–7). We used logistic regression models to assess associations between LS7 ideal CVH scores (0–7) and GDM history, accounting for socio-demographic factors.</p></div><div><h3>Results</h3><p>Among 9199 women (mean age: 46 years, 8 % with a GDM history), there was a progressive decrease in the odds of past GDM history across increasing ideal CVH scores. Compared to females with 0–1 ideal CVH scores, females with ideal CVH scores of 3, 4 and 5–7 had an associated 39 % lower [odds ratio: 0.61 (95 % CI: 0.41–0.90)], 50 % lower [0.50 (0.33–0.76)] and 66 % lower [0.34 (0.20–0.56)] odds of past GDM history, respectively. There were notable racial/ethnic and citizenship/nativity differences in these associations.</p></div><div><h3>Conclusions</h3><p>Women with higher ideal CVH scores had lower odds of GDM history. Our findings underscore the importance of optimizing cardiometabolic health among women with GDM history.</p></div>","PeriodicalId":11249,"journal":{"name":"Diabetes research and clinical practice","volume":"217 ","pages":"Article 111857"},"PeriodicalIF":6.1,"publicationDate":"2024-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142272010","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}