BMJ Open Diabetes Research & Care最新文献_第8页

Loneliness and the risk of type 2 diabetes 孤独与罹患 2 型糖尿病的风险

IF 4.1 2区医学 Q2 ENDOCRINOLOGY & METABOLISM

BMJ Open Diabetes Research & Care

Pub Date : 2024-03-01 DOI: 10.1136/bmjdrc-2023-003934

Siri Rosenkilde, Sofie Have Hoffmann, Anne Bonde Thorsted, Trine Allerslev Horsbøl, Katrine Rich Madsen, Sara Fokdal Lehn, Allan Kofoed-Enevoldsen, Peter Bindslev Iversen, Marie Stjerne Grønkjær, Lau Caspar Thygesen

Introduction The incidence of type 2 diabetes is increasing globally. Recent research suggests that loneliness could be a potential risk factor for the development of type 2 diabetes. We aimed to investigate the association between loneliness and type 2 diabetes and the modifying effect of mental disorders. Research design and methods We conducted a prospective study including 465 290 adults (aged ≥16 years) who participated in either the Danish Health and Morbidity Survey or the Danish National Health Survey between 2000 and 2017. Loneliness was based on self-report, while type 2 diabetes was measured using an algorithm combining several health registers including type 2 diabetes patients treated both within the hospital sector and general practice. Cox proportional hazards regressions were used to estimate hazard ratios (HRs) and 95% confidence intervals (95% CIs). Results During a mean follow-up time of 6.3 years, 13 771 individuals (3%) developed type 2 diabetes. Feeling lonely once in a while was associated with a 14% increased risk of type 2 diabetes (95% CI 1.09 to 1.20), while feeling lonely often was associated with a 24% increased risk (95% CI 1.14 to 1.34), independent of sociodemographic factors and body mass index. The association was stronger among individuals without a mental disorder (HR 1.21, 95% CI 1.10 to 1.34 among those feeling lonely often) compared with those with a mental disorder (HR 1.07, 95% CI 0.93 to 1.23). Conclusions Loneliness independently increased the risk of type 2 diabetes. The effect was more pronounced in individuals without a mental disorder, as having a mental disorder itself likely increases the risk of type 2 diabetes. These findings emphasize the importance of addressing loneliness as a modifiable risk factor in preventing type 2 diabetes. Data may be obtained from a third party and are not publicly available.

导言 2 型糖尿病的发病率在全球范围内不断上升。最近的研究表明，孤独可能是诱发 2 型糖尿病的潜在风险因素。我们旨在研究孤独与 2 型糖尿病之间的关系，以及精神障碍的调节作用。研究设计和方法我们进行了一项前瞻性研究，研究对象包括465 290名成年人（年龄≥16岁），他们在2000年至2017年间参加了丹麦健康和发病率调查或丹麦全国健康调查。孤独感以自我报告为基础，而2型糖尿病则采用一种算法进行测量，该算法结合了多个健康登记册，其中包括在医院和全科诊所接受治疗的2型糖尿病患者。采用 Cox 比例危险回归估算危险比 (HR) 和 95% 置信区间 (95%CI)。结果在平均 6.3 年的随访期间，有 13 771 人（3%）罹患 2 型糖尿病。偶尔感到孤独与罹患 2 型糖尿病的风险增加 14% 相关（95% CI 1.09 至 1.20），而经常感到孤独与罹患 2 型糖尿病的风险增加 24% 相关（95% CI 1.14 至 1.34），与社会人口因素和体重指数无关。与有精神障碍的人相比（HR 1.07，95% CI 0.93 至 1.23），没有精神障碍的人（经常感到孤独的人 HR 1.21，95% CI 1.10 至 1.34）与孤独的关联性更强。结论孤独感会增加罹患 2 型糖尿病的风险。这种影响在没有精神障碍的人群中更为明显，因为精神障碍本身就可能增加罹患 2 型糖尿病的风险。这些发现强调了将孤独感作为一个可改变的风险因素来预防 2 型糖尿病的重要性。数据可能来自第三方，不对外公开。

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引用次数: 0

Variation in the relationship between fasting glucose and HbA1c: implications for the diagnosis of diabetes in different age and ethnic groups 空腹血糖与 HbA1c 之间关系的差异：对不同年龄和种族群体糖尿病诊断的影响

IF 4.1 2区医学 Q2 ENDOCRINOLOGY & METABOLISM

BMJ Open Diabetes Research & Care

Pub Date : 2024-03-01 DOI: 10.1136/bmjdrc-2023-003470

Yashesvini Ram, Yongjin Xu, Alan Cheng, Timothy Dunn, Ramzi A Ajjan

Introduction Identify non-glycemic factors affecting the relationship between fasting plasma glucose (FPG) and glycated hemoglobin (HbA1c), in order to refine diabetes diagnostic criteria. Research design and methods Relationship between FPG–HbA1c was assessed in 12 531 individuals from 2001 to 2018 US National Health and Nutrition Examination Survey. Using a recently described method, FPG and HbA1c were used to calculate apparent glycation ratio (AGR) of red blood cells for different subgroups based on age, race, and gender. Results At an FPG of 7 mmol/L, black individuals had a higher HbA1c (p<0.001, mean: 50.2 mmol/mol, 95% CI (49.8 to 50.4)) compared with white individuals (47.4 mmol/mol (47.2 to 47.5)). This corresponds to NGSP (National Glycohemoglobin Standardization Program) units of 6.7% and 6.5% for black versus white individuals, respectively. Similarly, individuals under 21 years had lower HbA1c (p<0.001, 47.9 mmol/mol (47.7 to 48.1), 6.5%) compared with those over 50 years (48.3 mmol/mol (48.2 to 48.5), 6.6%). Differences were also observed between women (p<0.001, 49.2 mmol/mol (49.1 to 49.3), 6.7%) and men (47.0 mmol/mol (46.8 to 47.1), 6.5%). Of note, the difference in HbA1c at FPG of 7 mmol/L in black females over 50 and white males under 21 years was 5 mmol/mol (0.46%). AGR differences according to race (p<0.001), age (p<0.001), and gender (p<0.001) explained altered glucose–HbA1c relationship in the analyzed groups. Conclusions FPG–HbA1c relationship is affected by non-glycemic factors leading to incorrect diagnosis of diabetes in some individuals and ethnic groups. Assessment of AGR helps understand individual-specific relationship between glucose levels and HbA1c, which has the potential to more accurately diagnose and manage diabetes. Data are available in a public, open access repository. Data were compiled from the National Health and Nutrition Examination Survey (NHANES) cohorts, between the period of 2001 and 2018 which are publicly available on the US Centers for Disease and Control website.

导言找出影响空腹血浆葡萄糖（FPG）和糖化血红蛋白（HbA1c）之间关系的非血糖因素，以完善糖尿病诊断标准。研究设计与方法对 2001 年至 2018 年美国国家健康与营养调查中的 12 531 人进行了空腹血浆葡萄糖与糖化血红蛋白之间关系的评估。使用最近描述的方法，根据年龄、种族和性别，使用 FPG 和 HbA1c 计算不同亚组的红细胞表观糖化比（AGR）。结果当 FPG 为 7 mmol/L 时，黑人的 HbA1c 较高（p<0.001，平均值为 50.2 mmol/mol，平均值为 50.2 mmol/mol）：与白人（47.4 mmol/mol (47.2 to 47.5)）相比，黑人的 HbA1c 更高（p<0.001，平均值：50.2 mmol/mol，95% CI (49.8 to 50.4)）。这相当于国家糖化血红蛋白标准化计划（NGSP）的单位，黑人与白人分别为 6.7% 和 6.5%。同样，与 50 岁以上人群（48.3 mmol/mol（48.2-48.5），6.6%）相比，21 岁以下人群的 HbA1c 更低（p<0.001，47.9 mmol/mol（47.7-48.1），6.5%）。女性（P<0.001，49.2 mmol/mol（49.1 至 49.3），6.7%）和男性（47.0 mmol/mol（46.8 至 47.1），6.5%）之间也存在差异。值得注意的是，50 岁以上的黑人女性和 21 岁以下的白人男性在 FPG 为 7 mmol/L 时的 HbA1c 差异为 5 mmol/mol（0.46%）。种族（p<0.001）、年龄（p<0.001）和性别（p<0.001）的 AGR 差异解释了分析组中葡萄糖与 HbA1c 关系的改变。结论 FPG-HbA1c 关系受到非血糖因素的影响，导致某些个体和种族群体被误诊为糖尿病。评估 AGR 有助于了解血糖水平和 HbA1c 之间的个体特异性关系，从而有可能更准确地诊断和管理糖尿病。数据可在公开、开放的资源库中获取。数据来自美国国家健康与营养调查（NHANES）队列，时间跨度为 2001 年至 2018 年，可在美国疾病与控制中心网站上公开获取。

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引用次数: 0

Role of perirenal adiposity in renal dysfunction among CKD individuals with or without diabetes: a Japanese cross-sectional study 肾周脂肪在伴有或不伴有糖尿病的慢性肾功能衰竭患者肾功能障碍中的作用：一项日本横断面研究

IF 4.1 2区医学 Q2 ENDOCRINOLOGY & METABOLISM

BMJ Open Diabetes Research & Care

Pub Date : 2024-03-01 DOI: 10.1136/bmjdrc-2023-003832

Teruyuki Kono, Gulinu Maimaituxun, Hayato Tanabe, Moritake Higa, Haruka Saito, Kenichi Tanaka, Hiroaki Masuzaki, Masataka Sata, Junichiro J. Kazama, Michio Shimabukuro

Introduction It remains unclear whether increased perirenal fat (PRF) accumulation is equally related to renal involvement in patients with and without diabetes mellitus (DM). We evaluated the association between PRF volume (PRFV) and low glomerular filtration rate (GFR) and proteinuria in people with or without type 2 diabetes mellitus (T2DM). Research design and methods We performed a cross-sectional analysis of 473 individuals without T2DM (non-DM, n=202) and with T2DM (DM, n=271). PRFV (cm3), obtained from non-contrast CT, was indexed as PRF index (PRFV/body surface area, cm3/m2). Multivariate-adjusted models were used to determine the ORs of PRFV and PRFV index for detecting estimated GFR (eGFR) decrease of <60 mL/min/1.73 m2 proteinuria onset, or both. Results Although body mass index (BMI), visceral fat area, and waist circumference were comparable between the non-DM and DM groups, kidney volume, PRFV, and PRFV index were higher in individuals with T2DM than in those without T2DM. In the multivariate analysis, after adjusting for age, sex, BMI, hypertension, smoking history, and visceral fat area ≥100 cm2, the cut-off values of PRFV index were associated with an eGFR<60 in individuals with DM (OR 6.01, 95% CI 2.20 to 16.4, p<0.001) but not in those without DM. Conclusions PRFV is associated with low eGFR in patients with T2DM but not in those without T2DM. This suggests that PRF accumulation is more closely related to the onset and progression of diabetic kidney disease (DKD) than non-DKD. Clarifying the mechanisms through which PRF influences DKD development could pave the way for novel prevention and treatment strategies. Data are available upon reasonable request. All datasets generated and/or analyzed during the current study are not publicly available but are available from the corresponding author on reasonable request.

导言：对于糖尿病（DM）患者和非糖尿病（DM）患者，肾周脂肪（PRF）堆积的增加是否同样与肾脏受累有关，目前仍不清楚。我们评估了 2 型糖尿病（T2DM）患者或非 2 型糖尿病（T2DM）患者肾周脂肪量（PRFV）与低肾小球滤过率（GFR）和蛋白尿之间的关系。研究设计和方法我们对 473 名无 T2DM（非 T2DM，n=202）和有 T2DM（DM，n=271）的人进行了横断面分析。从非对比 CT 中获得的 PRFV（立方厘米）被指数化为 PRF 指数（PRFV/体表面积，立方厘米/平方米）。使用多变量调整模型确定 PRFV 和 PRFV 指数检测估计 GFR（eGFR）下降<60 mL/min/1.73 m2 蛋白尿发病或两者的 OR。结果虽然非糖尿病组和糖尿病组的体重指数（BMI）、内脏脂肪面积和腰围相当，但 T2DM 患者的肾脏体积、PRFV 和 PRFV 指数均高于非 T2DM 患者。在多变量分析中，在调整了年龄、性别、体重指数、高血压、吸烟史和内脏脂肪面积≥100 cm2 后，PRFV 指数的临界值与 DM 患者的 eGFR<60 相关（OR 6.01，95% CI 2.20 至 16.4，p<0.001），但与非 DM 患者无关。结论 PRFV 与 T2DM 患者的低 eGFR 相关，但与非 T2DM 患者无关。这表明，与非糖尿病肾病相比，PRF 的积累与糖尿病肾病（DKD）的发生和发展关系更为密切。阐明 PRF 影响 DKD 发展的机制可为新型预防和治疗策略铺平道路。如有合理要求，可提供相关数据。本研究中生成和/或分析的所有数据集均未公开，但可向通讯作者索取。

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引用次数: 0

Influence of diabetes and other risk factors on in-hospital mortality following kidney transplantation: an analysis of the Spanish National Hospital Discharge Database from 2016 to 2020 糖尿病和其他风险因素对肾移植术后院内死亡率的影响：2016 年至 2020 年西班牙国家医院出院数据库分析

IF 4.1 2区医学 Q2 ENDOCRINOLOGY & METABOLISM

BMJ Open Diabetes Research & Care

Pub Date : 2024-03-01 DOI: 10.1136/bmjdrc-2023-003799

Ana Lopez-de-Andres, Rodrigo Jimenez-Garcia, Marta Lopez-Herranz, José Javier Zamorano-Leon, David Carabantes-Alarcon, Valentin Hernandez-Barrera, Javier de Miguel-Diez, Francisco Carricondo, Barbara Romero-Gomez, Natividad Cuadrado-Corrales

Introduction To assess time trends in incidence, clinical characteristics, complications, and hospital outcomes among patients with type 1 diabetes (T1D), with type 2 diabetes (T2D), and patients without diabetes who underwent kidney transplant (KT); to identify variables associated with in-hospital mortality (IHM); and to determine the impact of the COVID-19 pandemic. Research design and methods We used a nationwide discharge database to select KT recipients admitted to Spanish hospitals from 2016 to 2020. We stratified patients according to diabetes status. We used multivariable logistic regression to identify the variables associated with IHM. Results A total of 14 594 KTs were performed in Spain (T2D, 22.28%; T1D, 3.72%). The number of KTs rose between 2016 and 2019 and and decreased from 2019 to 2020 in all groups. In patients with T2D, the frequency of KT complications increased from 21.08% in 2016 to 34.17% in 2020 (p<0.001). Patients with T2D had significantly more comorbidity than patients with T1D and patients without diabetes (p<0.001). Patients with T1D experienced KT rejection significantly more frequently (8.09%) than patients with T2D (5.57%). COVID-19 was recorded in 26 out of the 2444 KTs performed in 2020, being found in 6 of the 39 patients deceased that year (15.38%) and in 0.83% of the survivors. The variables associated with IHM were comorbidity and complications of KT. The presence of T1D was associated with IHM (OR 2.6; 95% CI 1.36 to 5.16) when patients without diabetes were the reference category. However, T2D was not associated with a higher IHM (OR 0.86; 95% CI 0.61 to 1.2). Conclusions The COVID-19 pandemic led to a decrease in the number of transplants. Patients with T1D have more rejection of the transplanted organ than patients with T2D. Fewer women with T2D undergo KT. The presence of T1D is a risk factor for IHM. Data may be obtained from a third party and are not publicly available.

简介：目的评估接受肾移植（KT）的 1 型糖尿病（T1D）患者、2 型糖尿病（T2D）患者和非糖尿病患者的发病率、临床特征、并发症和住院预后的时间趋势；确定与院内死亡率（IHM）相关的变量；并确定 COVID-19 大流行的影响。研究设计与方法我们利用全国性出院数据库，选择了 2016 年至 2020 年期间在西班牙医院住院的 KT 受者。我们根据糖尿病状态对患者进行了分层。我们使用多变量逻辑回归来确定与 IHM 相关的变量。结果西班牙共进行了 14 594 例 KT（T2D，22.28%；T1D，3.72%）。2016 年至 2019 年期间，所有组别的 KT 数量均有所上升，2019 年至 2020 年期间则有所下降。在T2D患者中，KT并发症的发生率从2016年的21.08%上升到2020年的34.17%（P<0.001）。T2D患者的合并症明显多于T1D患者和非糖尿病患者（p<0.001）。T1D 患者发生 KT 排斥的比例（8.09%）明显高于 T2D 患者（5.57%）。在 2020 年进行的 2444 例 KT 中，有 26 例记录到 COVID-19，在当年死亡的 39 例患者中，有 6 例（15.38%）和 0.83% 的幸存者中发现了 COVID-19。与 IHM 相关的变量是合并症和 KT 并发症。以无糖尿病患者为参照类别时，T1D 的存在与 IHM 相关（OR 2.6；95% CI 1.36 至 5.16）。然而，T2D 与较高的 IHM 无关（OR 0.86；95% CI 0.61 至 1.2）。结论 COVID-19 大流行导致移植数量减少。与 T2D 患者相比，T1D 患者对移植器官的排斥反应更严重。接受 KT 的 T2D 女性患者较少。T1D 患者是 IHM 的危险因素。数据可能来自第三方，不对外公开。

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引用次数: 0

External validation and application of the Diabetes Population Risk Tool (DPoRT) for prediction of type 2 diabetes onset in the US population 外部验证和应用糖尿病人口风险工具 (DPoRT) 预测美国人口中 2 型糖尿病的发病情况

IF 4.1 2区医学 Q2 ENDOCRINOLOGY & METABOLISM

BMJ Open Diabetes Research & Care

Pub Date : 2024-03-01 DOI: 10.1136/bmjdrc-2023-003905

Kathy Kornas, Christopher Tait, Ednah Negatu, Laura C Rosella

Introduction Characterizing diabetes risk in the population is important for population health assessment and diabetes prevention planning. We aimed to externally validate an existing 10-year population risk model for type 2 diabetes in the USA and model the population benefit of diabetes prevention approaches using population survey data. Research design and methods The Diabetes Population Risk Tool (DPoRT), originally derived and validated in Canada, was applied to an external validation cohort of 23 477 adults from the 2009 National Health Interview Survey (NHIS). We assessed predictive performance for discrimination (C-statistic) and calibration plots against observed incident diabetes cases identified from the NHIS 2009–2018 cycles. We applied DPoRT to the 2018 NHIS cohort (n=21 187) to generate 10-year risk prediction estimates and characterize the preventive benefit of three diabetes prevention scenarios: (1) community-wide strategy; (2) high-risk strategy and (3) combined approach. Results DPoRT demonstrated good discrimination (C-statistic=0.778 (males); 0.787 (females)) and good calibration across the range of risk. We predicted a baseline risk of 10.2% and 21 076 000 new cases of diabetes in the USA from 2018 to 2028. The community-wide strategy and high-risk strategy estimated diabetes risk reductions of 0.2% and 0.3%, respectively. The combined approach estimated a 0.4% risk reduction and 843 000 diabetes cases averted in 10 years. Conclusions DPoRT has transportability for predicting population-level diabetes risk in the USA using routinely collected survey data. We demonstrate the model’s applicability for population health assessment and diabetes prevention planning. Our modeling predicted that the combination of community-wide and targeted prevention approaches for those at highest risk are needed to reduce diabetes burden in the USA. Data are available in a public, open access repository. The NHIS data are available from www.cdc.gov/nchs/nhis/index.htm.

导言：描述人群中的糖尿病风险对于人群健康评估和糖尿病预防规划非常重要。我们旨在从外部验证美国现有的 2 型糖尿病 10 年人口风险模型，并利用人口调查数据建立糖尿病预防方法的人口受益模型。研究设计和方法糖尿病人群风险工具（DPoRT）最初是在加拿大衍生和验证的，我们将其应用于 2009 年全国健康访谈调查（NHIS）中的 23 477 名成年人组成的外部验证队列。我们根据 2009-2018 年国家健康访谈调查周期中发现的糖尿病病例，评估了分辨力（C 统计量）和校准图的预测性能。我们将 DPoRT 应用于 2018 年 NHIS 队列（n=21 187），以生成 10 年风险预测估计值，并描述三种糖尿病预防方案的预防效益：(1）全社区策略；（2）高风险策略；（3）综合方法。结果 DPoRT 在整个风险范围内表现出良好的区分度（C 统计量=0.778（男性）；0.787（女性））和校准性。我们预测 2018 年至 2028 年美国糖尿病的基线风险为 10.2%，新增病例为 21 076 000 例。全社区策略和高风险策略估计糖尿病风险分别降低了 0.2% 和 0.3%。综合方法估计可降低 0.4% 的风险，并在 10 年内避免 843 000 例糖尿病病例。结论 DPoRT 具有可移植性，可利用日常收集的调查数据预测美国人群的糖尿病风险。我们展示了该模型在人口健康评估和糖尿病预防规划方面的适用性。我们的模型预测，要减轻美国的糖尿病负担，需要将整个社区和针对高危人群的针对性预防方法结合起来。数据可在公开、开放的资源库中获取。NHIS 数据可从 www.cdc.gov/nchs/nhis/index.htm 获取。

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引用次数: 0

Postprandial glucose variability and clusters of sex hormones, liver enzymes, and cardiometabolic factors in a South African cohort of African ancestry 南非非裔队列中的餐后血糖变异性与性激素、肝酶和心脏代谢因素的群集

IF 4.1 2区医学 Q2 ENDOCRINOLOGY & METABOLISM

BMJ Open Diabetes Research & Care

Pub Date : 2024-03-01 DOI: 10.1136/bmjdrc-2023-003927

Bontle Masango, Julia H Goedecke, Michèle Ramsay, Karl-Heinz Storbeck, Lisa K Micklesfield, Tinashe Chikowore

Introduction This study aimed to, first, determine the clusters of sex hormones, liver enzymes, and cardiometabolic factors associated with postprandial glucose (PPG) and, second to evaluate the variation these clusters account for jointly and independently with polygenic risk scores (PRSs) in South Africans of African ancestry men and women. Research design and methods PPG was calculated as the integrated area under the curve for glucose during the oral glucose tolerance test (OGTT) using the trapezoidal rule in 794 participants from the Middle-aged Soweto Cohort. Principal component analysis was used to cluster sex hormones, liver enzymes, and cardiometabolic factors, stratified by sex. Multivariable linear regression was used to assess the proportion of variance in PPG accounted for by principal components (PCs) and type 2 diabetes (T2D) PRS while adjusting for selected covariates in men and women. Results The T2D PRS did not contribute to the PPG variability in both men and women. In men, the PCs’ cluster of sex hormones, liver enzymes, and cardiometabolic explained 10.6% of the variance in PPG, with PC1 (peripheral fat), PC2 (liver enzymes and steroid hormones), and PC3 (lipids and peripheral fat) contributing significantly to PPG. In women, PC factors of sex hormones, cardiometabolic factors, and liver enzymes explained a similar amount of the variance in PPG (10.8%), with PC1 (central fat) and PC2 (lipids and liver enzymes) contributing significantly to PPG. Conclusions We demonstrated that inter-individual differences in PPG responses to an OGTT may be differentially explained by body fat distribution, serum lipids, liver enzymes, and steroid hormones in men and women. Data are available in a public, open access repository. Data are available upon reasonable request. The dataset used in this study is available in the European Genome-phenome Archive (EGA) database () under the study accession code EGAS00001002482. The genotype dataset accession code is EGAD00010001996. The availability of these datasets is subject to controlled access through, the Data and Biospecimen Access Committee of the H3Africa Consortium. The augmented MASC data are available upon reasonable request.

引言本研究的目的首先是确定与餐后血糖（PPG）相关的性激素、肝酶和心脏代谢因素群，其次是评估这些群与多基因风险评分（PRSs）共同和独立作用于南非非洲裔男性和女性的差异。研究设计和方法采用梯形法则计算中年索韦托队列中 794 名参与者在口服葡萄糖耐量试验（OGTT）期间的葡萄糖曲线下的综合面积。采用主成分分析法将性激素、肝酶和心脏代谢因素按性别进行分类。使用多变量线性回归评估了主成分（PC）和 2 型糖尿病（T2D）PRS 在 PPG 变异中所占的比例，同时调整了男性和女性的选定协变量。结果 T2D PRS 对男性和女性的 PPG 变异性均无影响。在男性中，性激素、肝酶和心脏代谢的 PC 群解释了 10.6% 的 PPG 变异，其中 PC1（外周脂肪）、PC2（肝酶和类固醇激素）和 PC3（血脂和外周脂肪）对 PPG 有显著贡献。在女性中，性激素、心脏代谢因素和肝酶的 PC 因子对 PPG 变异的解释量相似（10.8%），其中 PC1（中心脂肪）和 PC2（血脂和肝酶）对 PPG 有显著的贡献。结论我们证明，男性和女性的体脂分布、血清脂质、肝酶和类固醇激素可不同程度地解释 PPG 对 OGTT 反应的个体间差异。数据可在公开、开放的资源库中获取。如有合理要求，可提供数据。本研究中使用的数据集可在欧洲基因组-表型组档案（EGA）数据库（）中查阅，研究加入代码为 EGAS00001002482。基因型数据集的登录代码为 EGAD00010001996。这些数据集的提供须通过 H3Africa Consortium 的数据和生物样本访问委员会（Data and Biospecimen Access Committee）进行受控访问。如有合理要求，可提供扩增的 MASC 数据。

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引用次数: 0

Greater persistence and adherence to basal insulin therapy is associated with lower healthcare utilization and medical costs in patients with type 2 diabetes: a retrospective database analysis 基础胰岛素治疗的持续性和依从性越高，2 型糖尿病患者的医疗利用率和医疗费用就越低：一项回顾性数据库分析

IF 4.1 2区医学 Q2 ENDOCRINOLOGY & METABOLISM

BMJ Open Diabetes Research & Care

Pub Date : 2024-03-01 DOI: 10.1136/bmjdrc-2023-003825

Vanita R Aroda, Nick Nielsen, Kamal K Mangla, Jasjit Multani, Victoria Divino, Tarlan Namvar, Jigar Rajpura

Introduction We aimed to assess persistence and adherence to basal insulin therapy, their association with all-cause healthcare resource utilization (HCRU) and direct medical costs, and predictors of persistence and adherence in adults with type 2 diabetes. Research design and methods A retrospective cohort study was conducted with US adults with type 2 diabetes initiating basal insulin therapy between January 1, 2016, and December 31, 2018, using IQVIA PharMetrics Plus claims data. Persistence and adherence were assessed during 1 year post-initiation per previous definitions. Demographic/clinical characteristics were assessed during the 1 year pre-initiation. Inverse probability of treatment weighting (IPTW) was used to adjust for confounding variables. Post-IPTW, all-cause HCRU and direct medical costs were assessed during the first-year and second-year post-initiation by persistence and adherence status. Multivariable logistic regression was used to identify predictors of persistence and adherence. Results The final sample comprised 64,953 patients; 56.8% demonstrated persistence and 41.9% demonstrated adherence. Patients demonstrating persistence and adherence were significantly less likely to have a hospitalization than patients demonstrating non-persistence or non-adherence, respectively. In the second-year post-initiation, total mean all-cause direct medical costs per patient were lower for patients demonstrating persistence and significantly lower for patients demonstrating adherence. Prior use of both oral and injectable antidiabetic medication predicted persistence and adherence compared with patients with only prior oral antidiabetic medication use (persistence OR, 1.50 (95% CI, 1.44 to 1.57); adherence OR, 1.48 (95% CI, 1.42 to 1.55)). Conclusions Persistence and adherence to basal insulin was associated with fewer hospitalizations and lower direct medical costs. Data are available upon reasonable request. The underlying data sets used in this study are available with permission from IQVIA, but restrictions apply to the availability of these data, which were used under license for the current study and therefore are not publicly available.

导言我们旨在评估基础胰岛素治疗的持续性和依从性、它们与全因医疗资源利用率（HCRU）和直接医疗成本的关联，以及2型糖尿病成人患者持续性和依从性的预测因素。研究设计与方法使用 IQVIA PharMetrics Plus 索赔数据，对 2016 年 1 月 1 日至 2018 年 12 月 31 日期间开始基础胰岛素治疗的美国成人 2 型糖尿病患者进行了一项回顾性队列研究。根据之前的定义，对启动后一年内的持续性和依从性进行了评估。人口统计学/临床特征在启动前 1 年进行评估。采用反向治疗概率加权法（IPTW）调整混杂变量。IPTW后，按持续性和依从性状况评估了启动后第一年和第二年的全因HCRU和直接医疗费用。多变量逻辑回归用于确定持续性和依从性的预测因素。结果最终样本包括 64953 名患者；56.8% 的患者表现为坚持治疗，41.9% 的患者表现为坚持治疗。表现出坚持和依从性的患者住院的几率分别明显低于表现出不坚持或不依从性的患者。在开始治疗后的第二年，坚持治疗的患者人均全因直接医疗总费用较低，而坚持治疗的患者人均全因直接医疗总费用明显较低。与之前只使用过口服抗糖尿病药物的患者相比，之前同时使用过口服和注射抗糖尿病药物的患者更容易坚持和依从治疗（坚持OR，1.50（95% CI，1.44-1.57）；依从OR，1.48（95% CI，1.42-1.55））。结论坚持使用基础胰岛素可减少住院次数和直接医疗费用。如有合理要求，可提供相关数据。本研究中使用的基础数据集由 IQVIA 许可提供，但这些数据的提供受到限制，因为这些数据是在许可下用于本研究的，因此不能公开提供。

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引用次数: 0

Omentin associates with serum metabolite profiles indicating lower diabetes risk: KORA F4 Study 奥门冬酰胺与血清代谢物特征相关，表明糖尿病风险较低：KORA F4 研究

IF 4.1 2区医学 Q2 ENDOCRINOLOGY & METABOLISM

BMJ Open Diabetes Research & Care

Pub Date : 2024-03-01 DOI: 10.1136/bmjdrc-2023-003865

Jacqueline M Ratter-Rieck, Mengya Shi, Karsten Suhre, Cornelia Prehn, Jerzy Adamski, Wolfgang Rathmann, Barbara Thorand, Michael Roden, Annette Peters, Rui Wang-Sattler, Christian Herder

Introduction Circulating omentin levels have been positively associated with insulin sensitivity. Although a role for adiponectin in this relationship has been suggested, underlying mechanisms remain elusive. In order to reveal the relationship between omentin and systemic metabolism, this study aimed to investigate associations of serum concentrations of omentin and metabolites. Research design and methods This study is based on 1124 participants aged 61–82 years from the population-based KORA (Cooperative Health Research in the Region of Augsburg) F4 Study, for whom both serum omentin levels and metabolite concentration profiles were available. Associations were assessed with five multivariable regression models, which were stepwise adjusted for multiple potential confounders, including age, sex, body mass index, waist-to-hip ratio, lifestyle markers (physical activity, smoking behavior and alcohol consumption), serum adiponectin levels, high-density lipoprotein cholesterol, use of lipid-lowering or anti-inflammatory medication, history of myocardial infarction and stroke, homeostasis model assessment 2 of insulin resistance, diabetes status, and use of oral glucose-lowering medication and insulin. Results Omentin levels significantly associated with multiple metabolites including amino acids, acylcarnitines, and lipids (eg, sphingomyelins and phosphatidylcholines (PCs)). Positive associations for several PCs, such as diacyl (PC aa C32:1) and alkyl-alkyl (PC ae C32:2), were significant in models 1–4, whereas those with hydroxytetradecenoylcarnitine (C14:1-OH) were significant in all five models. Omentin concentrations were negatively associated with several metabolite ratios, such as the valine-to-PC ae C32:2 and the serine-to-PC ae C32:2 ratios in most models. Conclusions Our results suggest that omentin may influence insulin sensitivity and diabetes risk by changing systemic lipid metabolism, but further mechanistic studies investigating effects of omentin on metabolism of insulin-sensitive tissues are needed. Data from this KORA Study are not publicly available because the data are subject to national data protection laws, and restrictions were imposed by the Ethics Committee of the Bavarian Chamber of Physicians to ensure data privacy of the study participants. However, data are available on request to researchers through a project agreement from KORA (). Requests should be sent to [kora.passt@helmholtz-muenchen.de][1] and are subject to approval by the KORA board. [1]: http://kora.passt@helmholtz-muenchen.de

导言循环网膜素水平与胰岛素敏感性呈正相关。虽然有人认为脂肪连通素在这种关系中发挥作用，但其潜在机制仍然难以捉摸。为了揭示网织蛋白与系统代谢之间的关系，本研究旨在调查血清中网织蛋白浓度与代谢物之间的关联。研究设计和方法本研究基于以人群为基础的 KORA（奥格斯堡地区合作健康研究）F4 研究的 1124 名 61-82 岁参与者，这些参与者的血清网秦水平和代谢物浓度曲线均可获得。通过五个多变量回归模型评估了两者之间的关系，并逐步调整了多种潜在的混杂因素，包括年龄、性别、体重指数、腰臀比、生活方式指标（体育锻炼、吸烟行为和饮酒量）、这些因素包括年龄、性别、体重指数、腰臀比、生活方式指标（体力活动、吸烟行为和饮酒）、血清脂肪连接蛋白水平、高密度脂蛋白胆固醇、降脂药物或抗炎药物的使用情况、心肌梗死和中风病史、胰岛素抵抗的稳态模型评估2、糖尿病状态以及口服降糖药物和胰岛素的使用情况。结果网织红蛋白水平与多种代谢物（包括氨基酸、酰基肉碱和脂质，如鞘磷脂和磷脂酰胆碱（PCs））有明显关联。在模型 1-4 中，二酰基（PC aa C32:1）和烷基-烷基（PC ae C32:2）等几种 PC 的正相关性显著，而与羟基十四碳酰肉碱（C14:1-OH）的正相关性在所有五个模型中均显著。在大多数模型中，网秦浓度与几种代谢物的比率呈负相关，如缬氨酸-PC ae C32:2 比率和丝氨酸-PC ae C32:2 比率。结论我们的研究结果表明，网秦可能会通过改变全身脂质代谢来影响胰岛素敏感性和糖尿病风险，但还需要进一步开展机理研究，探讨网秦对胰岛素敏感组织代谢的影响。这项 KORA 研究的数据不对外公开，因为这些数据受国家数据保护法的限制，而且巴伐利亚州医师协会伦理委员会为确保研究参与者的数据隐私也施加了限制。不过，研究人员可通过 KORA () 的项目协议索取数据。申请请发送至 [kora.passt@helmholtz-muenchen.de][1]，并须获得 KORA 董事会的批准。[1]: http://kora.passt@helmholtz-muenchen.de

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引用次数: 0

Predictive biomarkers of rapidly developing insulin deficiency in children with type 1 diabetes. 1 型糖尿病儿童胰岛素缺乏症快速发展的预测性生物标志物。

IF 4.1 2区医学 Q2 ENDOCRINOLOGY & METABOLISM

BMJ Open Diabetes Research & Care

Pub Date : 2024-02-27 DOI: 10.1136/bmjdrc-2023-003924

Per Lundkvist, Annika Grönberg, Per-Ola Carlsson, Johnny Ludvigsson, Daniel Espes

Introduction: The rate of progression to complete insulin deficiency varies greatly in type 1 diabetes. This constitutes a challenge, especially when randomizing patients in intervention trials aiming to preserve beta cell function. This study aimed to identify biomarkers predictive of either a rapid or slow disease progression in children with new-onset type 1 diabetes.

Research design and methods: A retrospective, longitudinal cohort study of children (<18 years) with type 1 diabetes (N=46) was included at diagnosis and followed until complete insulinopenia (C-peptide <0.03 nmol/L). Children were grouped into rapid progressors (n=20, loss within 30 months) and slow progressors (n=26). A sex-matched control group of healthy children (N=45) of similar age was included for comparison. Multiple biomarkers were assessed by proximity extension assay (PEA) at baseline and follow-up.

Results: At baseline, rapid progressors had lower C-peptide and higher autoantibody levels than slow. Three biomarkers were higher in the rapid group: carbonic anhydrase 9, corticosteroid 11-beta-dehydrogenase isozyme 1, and tumor necrosis factor receptor superfamily member 21. In a linear mixed model, 25 proteins changed over time, irrespective of group. One protein, a coxsackievirus B-adenovirus receptor (CAR) increased over time in rapid progressors. Eighty-one proteins differed between type 1 diabetes and healthy controls. Principal component analysis could not distinguish between rapid, slow, and healthy controls.

Conclusions: Despite differences in individual proteins, the combination of multiple biomarkers analyzed by PEA could not distinguish the rate of progression in children with new-onset type 1 diabetes. Only one marker was altered significantly when considering both time and group effects, namely CAR, which increased significantly over time in the rapid group. Nevertheless, we did find some markers that may be useful in predicting the decline of the C-peptide. Moreover, these could potentially be important for understanding type 1 diabetes pathogenesis.

简介1 型糖尿病患者发展为完全胰岛素缺乏的速度差异很大。这构成了一项挑战，尤其是在旨在保护β细胞功能的干预试验中对患者进行随机分组时。本研究旨在确定预测新发1型糖尿病儿童疾病进展快慢的生物标志物：研究设计和方法：一项对儿童进行的回顾性纵向队列研究（结果：在基线时，病情进展快的儿童比病情进展慢的儿童更容易患病）：基线时，快速进展者的 C 肽和自身抗体水平均低于缓慢进展者。快速组中有三种生物标志物含量较高：碳酸酐酶 9、皮质类固醇 11-beta-脱氢酶同工酶 1 和肿瘤坏死因子受体超家族成员 21。在线性混合模型中，有 25 种蛋白质随着时间的推移而发生变化，与组别无关。有一种蛋白质，即柯萨奇病毒B-腺病毒受体（CAR）在快速进展者中随着时间的推移而增加。81种蛋白质在1型糖尿病和健康对照组之间存在差异。主成分分析无法区分快速、缓慢和健康对照组：结论：尽管单个蛋白质存在差异，但通过主成分分析法分析的多种生物标记物组合无法区分新发1型糖尿病儿童的进展速度。考虑到时间和组别效应，只有一个标记物发生了显著变化，即CAR，在快速组中随着时间的推移显著增加。尽管如此，我们还是发现了一些可能有助于预测 C 肽下降的标志物。此外，这些指标可能对了解 1 型糖尿病的发病机制非常重要。

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引用次数: 0

Cancer risk according to fasting blood glucose trajectories: a population-based cohort study. 基于空腹血糖轨迹的癌症风险：一项基于人群的队列研究。

IF 4.1 2区医学 Q2 ENDOCRINOLOGY & METABOLISM

BMJ Open Diabetes Research & Care

Pub Date : 2024-02-27 DOI: 10.1136/bmjdrc-2023-003696

Thi Minh Thu Khong, Thi Tra Bui, Hee-Yeon Kang, Jinhee Lee, Eunjung Park, Jin-Kyoung Oh

Introduction: Diabetes mellitus is known to increase the risk of cancer. Fasting blood glucose (FBG) levels can be changed over time. However, the association between FBG trajectory and cancer risk has been insufficiently studied. This research aims to examine the relationship between FBG trajectories and cancer risk in the Korean population.

Research design and methods: We analyzed data from the National Health Insurance Service-National Health Screening Cohort collected between 2002 and 2015. Group-based trajectory modeling was performed on 256,271 Koreans aged 40-79 years who had participated in health examinations at least three times from 2002 to 2007. After excluding patients with cancer history before 2008, we constructed a cancer-free cohort. The Cox proportional hazards model was applied to examine the association between FBG trajectories and cancer incidence by cancer type, after adjustments for covariates. Cancer case was defined as a person who was an outpatient thrice or was hospitalized once or more with a cancer diagnosis code within the first year of the claim.

Results: During the follow-up time (2008-2015), 18,991 cancer cases were identified. Four glucose trajectories were found: low-stable (mean of FBG at each wave <100 mg/dL), elevated-stable (113-124 mg/dL), elevated-high (104-166 mg/dL), and high-stable (>177 mg/dL). The high-stable group had a higher risk of multiple myeloma, liver cancer and gastrointestinal cancer than the low-stable group, with HR 4.09 (95% CI 1.40 to 11.95), HR 1.68 (95% CI 1.25 to 2.26) and HR 1.27 (95% CI 1.11 to 1.45), respectively. In elevated-stable trajectory, the risk increased for all cancer (HR 1.08, 95% CI 1.02 to 1.16) and stomach cancer (HR 1.24, 95% CI 1.07 to 1.43). Significant associations were also found in the elevated-high group with oral (HR 2.13, 95% CI 1.01 to 4.47), liver (HR 1.50, 95% CI 1.08 to 2.08) and pancreatic cancer (HR 1.99, 95% CI 1.20 to 3.30).

Conclusions: Our study highlights that the uncontrolled high glucose level for many years may increase the risk of cancer.

导言众所周知，糖尿病会增加罹患癌症的风险。空腹血糖（FBG）水平可随时间而改变。然而，人们对 FBG 轨迹与癌症风险之间的关系研究不足。本研究旨在探讨韩国人群中 FBG 轨迹与癌症风险之间的关系：我们分析了 2002 年至 2015 年期间收集的国民健康保险服务-国民健康检查队列数据。我们对 256,271 名年龄在 40-79 岁之间、在 2002 年至 2007 年期间至少参加过三次健康检查的韩国人进行了基于群体的轨迹建模。在排除了2008年以前有癌症病史的患者后，我们构建了一个无癌症队列。在对协变量进行调整后，我们采用 Cox 比例危险模型按癌症类型研究了 FBG 轨迹与癌症发病率之间的关系。癌症病例的定义是，在索赔的第一年内，门诊三次或住院一次或一次以上且有癌症诊断代码的人：结果：在随访期间（2008-2015 年），共发现 18991 例癌症病例。发现了四种血糖轨迹：低稳定组（每次波次的 FBG 平均值为 177 mg/dL）。高稳定组患多发性骨髓瘤、肝癌和胃肠道癌症的风险高于低稳定组，分别为 HR 4.09（95% CI 1.40 至 11.95）、HR 1.68（95% CI 1.25 至 2.26）和 HR 1.27（95% CI 1.11 至 1.45）。在升高-稳定轨迹中，所有癌症（HR 1.08，95% CI 1.02 至 1.16）和胃癌（HR 1.24，95% CI 1.07 至 1.43）的风险都有所增加。在血糖升高组中，还发现口腔癌（HR 2.13，95% CI 1.01 至 4.47）、肝癌（HR 1.50，95% CI 1.08 至 2.08）和胰腺癌（HR 1.99，95% CI 1.20 至 3.30）与血糖升高有显著关联：我们的研究强调，多年未控制的高血糖水平可能会增加患癌症的风险。

{"title":"Cancer risk according to fasting blood glucose trajectories: a population-based cohort study.","authors":"Thi Minh Thu Khong, Thi Tra Bui, Hee-Yeon Kang, Jinhee Lee, Eunjung Park, Jin-Kyoung Oh","doi":"10.1136/bmjdrc-2023-003696","DOIUrl":"10.1136/bmjdrc-2023-003696","url":null,"abstract":"Introduction: Diabetes mellitus is known to increase the risk of cancer. Fasting blood glucose (FBG) levels can be changed over time. However, the association between FBG trajectory and cancer risk has been insufficiently studied. This research aims to examine the relationship between FBG trajectories and cancer risk in the Korean population.Research design and methods: We analyzed data from the National Health Insurance Service-National Health Screening Cohort collected between 2002 and 2015. Group-based trajectory modeling was performed on 256,271 Koreans aged 40-79 years who had participated in health examinations at least three times from 2002 to 2007. After excluding patients with cancer history before 2008, we constructed a cancer-free cohort. The Cox proportional hazards model was applied to examine the association between FBG trajectories and cancer incidence by cancer type, after adjustments for covariates. Cancer case was defined as a person who was an outpatient thrice or was hospitalized once or more with a cancer diagnosis code within the first year of the claim.Results: During the follow-up time (2008-2015), 18,991 cancer cases were identified. Four glucose trajectories were found: low-stable (mean of FBG at each wave <100 mg/dL), elevated-stable (113-124 mg/dL), elevated-high (104-166 mg/dL), and high-stable (>177 mg/dL). The high-stable group had a higher risk of multiple myeloma, liver cancer and gastrointestinal cancer than the low-stable group, with HR 4.09 (95% CI 1.40 to 11.95), HR 1.68 (95% CI 1.25 to 2.26) and HR 1.27 (95% CI 1.11 to 1.45), respectively. In elevated-stable trajectory, the risk increased for all cancer (HR 1.08, 95% CI 1.02 to 1.16) and stomach cancer (HR 1.24, 95% CI 1.07 to 1.43). Significant associations were also found in the elevated-high group with oral (HR 2.13, 95% CI 1.01 to 4.47), liver (HR 1.50, 95% CI 1.08 to 2.08) and pancreatic cancer (HR 1.99, 95% CI 1.20 to 3.30).Conclusions: Our study highlights that the uncontrolled high glucose level for many years may increase the risk of cancer.","PeriodicalId":9151,"journal":{"name":"BMJ Open Diabetes Research & Care","volume":"12 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10900343/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139982408","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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