Skip Navigation
Skip to contents

Diabetes Metab J : Diabetes & Metabolism Journal

Search
OPEN ACCESS

Search

Page Path
HOME > Search
7 "Da Young Lee"
Filter
Filter
Article category
Keywords
Publication year
Authors
Funded articles
Review
Pathophysiology
Attention to Innate Circadian Rhythm and the Impact of Its Disruption on Diabetes
Da Young Lee, Inha Jung, So Young Park, Ji Hee Yu, Ji A Seo, Kyeong Jin Kim, Nam Hoon Kim, Hye Jin Yoo, Sin Gon Kim, Kyung Mook Choi, Sei Hyun Baik, Nan Hee Kim
Diabetes Metab J. 2024;48(1):37-52.   Published online January 3, 2024
DOI: https://doi.org/10.4093/dmj.2023.0193
  • 2,177 View
  • 219 Download
AbstractAbstract PDFPubReader   ePub   
Novel strategies are required to reduce the risk of developing diabetes and/or clinical outcomes and complications of diabetes. In this regard, the role of the circadian system may be a potential candidate for the prevention of diabetes. We reviewed evidence from animal, clinical, and epidemiological studies linking the circadian system to various aspects of the pathophysiology and clinical outcomes of diabetes. The circadian clock governs genetic, metabolic, hormonal, and behavioral signals in anticipation of cyclic 24-hour events through interactions between a “central clock” in the suprachiasmatic nucleus and “peripheral clocks” in the whole body. Currently, circadian rhythmicity in humans can be subjectively or objectively assessed by measuring melatonin and glucocorticoid levels, core body temperature, peripheral blood, oral mucosa, hair follicles, rest-activity cycles, sleep diaries, and circadian chronotypes. In this review, we summarized various circadian misalignments, such as altered light-dark, sleep-wake, rest-activity, fasting-feeding, shift work, evening chronotype, and social jetlag, as well as mutations in clock genes that could contribute to the development of diabetes and poor glycemic status in patients with diabetes. Targeting critical components of the circadian system could deliver potential candidates for the treatment and prevention of type 2 diabetes mellitus in the future.
Letter
Original Articles
Technology/Device
Clinical and Lifestyle Determinants of Continuous Glucose Monitoring Metrics in Insulin-Treated Patients with Type 2 Diabetes Mellitus
Da Young Lee, Namho Kim, Inha Jung, So Young Park, Ji Hee Yu, Ji A Seo, Jihee Kim, Kyeong Jin Kim, Nam Hoon Kim, Hye Jin Yoo, Sin Gon Kim, Kyung Mook Choi, Sei Hyun Baik, Sung-Min Park, Nan Hee Kim
Diabetes Metab J. 2023;47(6):826-836.   Published online August 24, 2023
DOI: https://doi.org/10.4093/dmj.2022.0273
  • 1,798 View
  • 191 Download
  • 1 Crossref
AbstractAbstract PDFSupplementary MaterialPubReader   ePub   
Background
There was limited evidence to evaluate the association between lifestyle habits and continuous glucose monitoring (CGM) metrics. Thus, we aimed to depict the behavioral and metabolic determinants of CGM metrics in insulin-treated patients with type 2 diabetes mellitus (T2DM).
Methods
This is a prospective observational study. We analyzed data from 122 insulin-treated patients with T2DM. Participants wore Dexcom G6 and Fitbit, and diet information was identified for 10 days. Multivariate-adjusted logistic regression analysis was performed for the simultaneous achievement of CGM-based targets, defined by the percentage of time in terms of hyper, hypoglycemia and glycemic variability (GV). Intake of macronutrients and fiber, step counts, sleep, postprandial C-peptide-to-glucose ratio (PCGR), information about glucose lowering medications and metabolic factors were added to the analyses. Additionally, we evaluated the impact of the distribution of energy and macronutrient during a day, and snack consumption on CGM metrics.
Results
Logistic regression analysis revealed that female, participants with high PCGR, low glycosylated hemoglobin (HbA1c) and daytime step count had a higher probability of achieving all targets based on CGM (odds ratios [95% confidence intervals] which were 0.24 [0.09 to 0.65], 1.34 [1.03 to 1.25], 0.95 [0.9 to 0.99], and 1.15 [1.03 to 1.29], respectively). And participants who ate snacks showed a shorter period of hyperglycemia and less GV compared to those without.
Conclusion
We confirmed that residual insulin secretion, daytime step count, HbA1c, and women were the most relevant determinants of adequate glycemic control in insulin-treated patients with T2DM. In addition, individuals with snack consumption were exposed to lower times of hyperglycemia and GV.

Citations

Citations to this article as recorded by  
  • Explanatory variables of objectively measured 24-h movement behaviors in people with prediabetes and type 2 diabetes: A systematic review
    Lotte Bogaert, Iris Willems, Patrick Calders, Eveline Dirinck, Manon Kinaupenne, Marga Decraene, Bruno Lapauw, Boyd Strumane, Margot Van Daele, Vera Verbestel, Marieke De Craemer
    Diabetes & Metabolic Syndrome: Clinical Research & Reviews.2024; 18(4): 102995.     CrossRef
Others
Fasting Glucose Variability and the Risk of Dementia in Individuals with Diabetes: A Nationwide Cohort Study
Da Young Lee, Jaeyoung Kim, Sanghyun Park, So Young Park, Ji Hee Yu, Ji A Seo, Nam Hoon Kim, Hye Jin Yoo, Sin Gon Kim, Kyung Mook Choi, Sei Hyun Baik, Kyungdo Han, Nan Hee Kim
Diabetes Metab J. 2022;46(6):923-935.   Published online May 24, 2022
DOI: https://doi.org/10.4093/dmj.2021.0346
  • 5,617 View
  • 254 Download
  • 6 Web of Science
  • 6 Crossref
AbstractAbstract PDFSupplementary MaterialPubReader   ePub   
Background
We investigated whether fasting glucose (FG) variability could predict the risk of dementia.
Methods
This cohort study analyzed data from Koreans with diabetes after at least three health examinations by the Korean National Health Insurance Corporation between 2005 and 2010, which included at least one examination between 2009 and 2010. A total of 769,554 individuals were included, excluding those aged <40 years and those with dementia. FG variability was measured using the variability independent of the mean (FG-VIM). The incidence of dementia was defined by the International Classification of Diseases 10th Revision codes and prescription of anti-dementia medication and was subdivided into Alzheimer’s disease (AD) and vascular dementia (VD).
Results
During the 6.9-year follow-up, 54,837, 41,032, and 6,892 cases of all-cause dementia, AD, and VD, respectively, were identified. Cox proportional regression analyses showed that as the FG-VIM quartile increased, the risk of dementia serially increased after adjustment for metabolic factors, income status, and diabetes-related characteristics, including the mean FG. Participants in FG-VIM quartile 4 showed a 18%, 19%, and 17% higher risk for all-cause dementia, AD, and VD, respectively, than those in quartile 1; this particularly included non-obese patients with a longer duration of diabetes, high FG levels, dyslipidemia, and those taking glucose-lowering medications. Conversely, the baseline FG status and dementia showed a U-shaped association.
Conclusion
Increased FG variability over 5 years can predict the risk of dementia in individuals with diabetes in Korea. This finding was more pronounced in patients with less favorable metabolic profiles.

Citations

Citations to this article as recorded by  
  • Fasting glucose variability and risk of dementia in Parkinson’s disease: a 9-year longitudinal follow-up study of a nationwide cohort
    Sung Hoon Kang, Yunjin Choi, Su Jin Chung, Seok-Joo Moon, Chi Kyung Kim, Ji Hyun Kim, Kyungmi Oh, Joon Shik Yoon, Sang Won Seo, Geum Joon Cho, Seong-Beom Koh
    Frontiers in Aging Neuroscience.2024;[Epub]     CrossRef
  • Effects of a Diabetic Microenvironment on Neurodegeneration: Special Focus on Neurological Cells
    Vishal Chavda, Dhananjay Yadav, Snehal Patel, Minseok Song
    Brain Sciences.2024; 14(3): 284.     CrossRef
  • The Association of Glucose Variability and Dementia Incidence in Latinx Adults with Type 2 Diabetes: A Retrospective Study
    Heather Cuevas, Elizabeth Muñoz, Divya Nagireddy, Jeeyeon Kim, Grace Ganucheau, Fathia Alomoush
    Clinical Nursing Research.2023; 32(2): 249.     CrossRef
  • The effects of long-term cumulative HbA1c exposure on the development and onset time of dementia in the patients with type 2 diabetes mellitus: Hospital based retrospective study (2005–2021)
    Sunyoung Cho, Choon Ok Kim, Bong-soo Cha, Eosu Kim, Chung Mo Nam, Min-Gul Kim, Min Soo Park
    Diabetes Research and Clinical Practice.2023; 201: 110721.     CrossRef
  • Physiological Mechanisms Inherent to Diabetes Involved in the Development of Dementia: Alzheimer’s Disease
    Himan Mohamed-Mohamed, Victoria García-Morales, Encarnación María Sánchez Lara, Anabel González-Acedo, Teresa Pardo-Moreno, María Isabel Tovar-Gálvez, Lucía Melguizo-Rodríguez, Juan José Ramos-Rodríguez
    Neurology International.2023; 15(4): 1253.     CrossRef
  • Cumulative effect of impaired fasting glucose on the risk of dementia in middle-aged and elderly people: a nationwide cohort study
    Jin Yu, Kyu-Na Lee, Hun-Sung Kim, Kyungdo Han, Seung-Hwan Lee
    Scientific Reports.2023;[Epub]     CrossRef
Short Communication
Technology/Device
Comparison of Laser and Conventional Lancing Devices for Blood Glucose Measurement Conformance and Patient Satisfaction in Diabetes Mellitus
Jung A Kim, Min Jeong Park, Eyun Song, Eun Roh, So Young Park, Da Young Lee, Jaeyoung Kim, Ji Hee Yu, Ji A Seo, Kyung Mook Choi, Sei Hyun Baik, Hye Jin Yoo, Nan Hee Kim
Diabetes Metab J. 2022;46(6):936-940.   Published online March 30, 2022
DOI: https://doi.org/10.4093/dmj.2021.0293
  • 5,276 View
  • 256 Download
  • 1 Web of Science
  • 1 Crossref
AbstractAbstract PDFPubReader   ePub   
Self-monitoring of capillary blood glucose is important for controlling diabetes. Recently, a laser lancing device (LMT-1000) that can collect capillary blood without skin puncture was developed. We enrolled 150 patients with type 1 or 2 diabetes mellitus. Blood sampling was performed on the same finger on each hand using the LMT-1000 or a conventional lancet. The primary outcome was correlation between glucose values using the LMT-1000 and that using a lancet. And we compared the pain and satisfaction of the procedures. The capillary blood sampling success rates with the LMT-1000 and lancet were 99.3% and 100%, respectively. There was a positive correlation (r=0.974, P<0.001) between mean blood glucose levels in the LMT-1000 (175.8±63.0 mg/dL) and conventional lancet samples (172.5±63.6 mg/dL). LMT-1000 reduced puncture pain by 75.0% and increased satisfaction by 80.0% compared to a lancet. We demonstrated considerable consistency in blood glucose measurements between samples from the LMT-1000 and a lancet, but improved satisfaction and clinically significant pain reduction were observed with the LMT-1000 compared to those with a lancet.

Citations

Citations to this article as recorded by  
  • Comparison between a laser-lancing device and automatic incision lancet for capillary blood sampling from the heel of newborn infants: a randomized feasibility trial
    Chul Kyu Yun, Eui Kyung Choi, Hyung Jin Kim, Jaeyoung Kim, Byung Cheol Park, Kyuhee Park, Byung Min Choi
    Journal of Perinatology.2024;[Epub]     CrossRef
Original Article
Clinical Complications
Incidence and Risk Factors for Dementia in Type 2 Diabetes Mellitus: A Nationwide Population-Based Study in Korea
Ji Hee Yu, Kyungdo Han, Sanghyun Park, Hanna Cho, Da Young Lee, Jin-Wook Kim, Ji A Seo, Sin Gon Kim, Sei Hyun Baik, Yong Gyu Park, Kyung Mook Choi, Seon Mee Kim, Nan Hee Kim
Diabetes Metab J. 2020;44(1):113-124.   Published online November 12, 2019
DOI: https://doi.org/10.4093/dmj.2018.0216
  • 7,865 View
  • 198 Download
  • 31 Web of Science
  • 32 Crossref
AbstractAbstract PDFSupplementary MaterialPubReader   
Background

Diabetes mellitus is associated with an increased risk of dementia. We aimed to comprehensively analyze the incidence and risk factors for dementia and young-onset dementia (YOD) in diabetic patients in Korea using the National Health Insurance Service data.

Methods

Between January 1, 2009 and December 31, 2012, a total of 1,917,702 participants with diabetes were included and followed until the date of dementia diagnosis or until December 31, 2015. We evaluated the incidence and risk factors for all dementia, Alzheimer's disease (AD), and vascular dementia (VaD) by Cox proportional hazards analyses. We also compared the impact of risk factors on the occurrence of YOD and late-onset dementia (LOD).

Results

During an average of 5.1 years of follow-up, the incidence of all types of dementia, AD, or VaD was 9.5, 6.8, and 1.3/1,000 person-years, respectively, in participants with diabetes. YOD comprised 4.8% of all dementia occurrence, and the ratio of AD/VaD was 2.1 for YOD compared with 5.5 for LOD. Current smokers and subjects with lower income, plasma glucose levels, body mass index (BMI), and subjects with hypertension, dyslipidemia, vascular complications, depression, and insulin treatment developed dementia more frequently. Vascular risk factors such as smoking, hypertension, and previous cardiovascular diseases were more strongly associated with the development of VaD than AD. Low BMI and a history of stroke or depression had a stronger influence on the development of YOD than LOD.

Conclusion

The optimal management of modifiable risk factors may be important for preventing dementia in subjects with diabetes mellitus.

Citations

Citations to this article as recorded by  
  • Unlocking the Protective Potential of Upper Respiratory Infection Treatment Histories against Alzheimer’s Disease: A Korean Adult Population Study
    Ho Suk Kang, Ji Hee Kim, Joo-Hee Kim, Woo Jin Bang, Hyo Geun Choi, Nan Young Kim, Ha Young Park, Mi Jung Kwon
    Journal of Clinical Medicine.2024; 13(1): 260.     CrossRef
  • Hepatopancreatic metabolic disorders and their implications in the development of Alzheimer's disease and vascular dementia
    Francisco I. Pinheiro, Irami Araújo-Filho, Amália C.M. do Rego, Eduardo P. de Azevedo, Ricardo N. Cobucci, Fausto P. Guzen
    Ageing Research Reviews.2024; 96: 102250.     CrossRef
  • Amygdala activity and amygdala-hippocampus connectivity: Metabolic diseases, dementia, and neuropsychiatric issues
    Juhyun Song
    Biomedicine & Pharmacotherapy.2023; 162: 114647.     CrossRef
  • The effects of long-term cumulative HbA1c exposure on the development and onset time of dementia in the patients with type 2 diabetes mellitus: Hospital based retrospective study (2005–2021)
    Sunyoung Cho, Choon Ok Kim, Bong-soo Cha, Eosu Kim, Chung Mo Nam, Min-Gul Kim, Min Soo Park
    Diabetes Research and Clinical Practice.2023; 201: 110721.     CrossRef
  • Association of triglyceride/high-density lipoprotein cholesterol ratio with severe complications of COVID-19
    Yoonkyung Chang, Jimin Jeon, Tae-Jin Song, Jinkwon Kim
    Heliyon.2023; 9(6): e17428.     CrossRef
  • Akkermansia muciniphila in neuropsychiatric disorders: friend or foe?
    Wenhui Lei, Yiwen Cheng, Jie Gao, Xia Liu, Li Shao, Qingming Kong, Nengneng Zheng, Zongxin Ling, Weiming Hu
    Frontiers in Cellular and Infection Microbiology.2023;[Epub]     CrossRef
  • The Association Between Eye Disease and Incidence of Dementia: Systematic Review and Meta-Analysis
    Jiayi Feng, Cuihong Huang, Lei Liang, Chuang Li, Xiaojie Wang, Jianping Ma, Xinhui Guan, Bin Jiang, Shaofen Huang, Pei Qin
    Journal of the American Medical Directors Association.2023; 24(9): 1363.     CrossRef
  • Risk of Neurodegenerative Diseases in Elderly Koreans with an Initial Diagnosis of Type 2 Diabetes: A Nationwide Retrospective Cohort Study
    Hee-Cheol Kim, Ho-Jun Lee, Yang-Tae Kim, Byeong-Churl Jang, Asirvatham Alwin Robert
    Journal of Diabetes Research.2023; 2023: 1.     CrossRef
  • Type-2 Diabetes Alters Hippocampal Neural Oscillations and Disrupts Synchrony between the Hippocampus and Cortex
    Gratianne Rabiller, Zachary Ip, Shahram Zarrabian, Hongxia Zhang, Yoshimichi Sato, Azadeh Yazdan-Shahmorad, Jialing Liu
    Aging and disease.2023;[Epub]     CrossRef
  • Sarcopenia and diabetes-induced dementia risk
    Mingyang Sun, Zhongyuan Lu, Wan-Ming Chen, Szu-Yuan Wu, Jiaqiang Zhang
    Brain Communications.2023;[Epub]     CrossRef
  • Association of periodontitis with microvascular complications of diabetes mellitus: A nationwide cohort study
    Moo-Seok Park, Jimin Jeon, Tae-Jin Song, Jinkwon Kim
    Journal of Diabetes and its Complications.2022; 36(2): 108107.     CrossRef
  • Association between oral health and cardiovascular outcomes in patients with hypertension: a nationwide cohort study
    Jinkwon Kim, Hyung Jun Kim, Jimin Jeon, Tae-Jin Song
    Journal of Hypertension.2022; 40(2): 374.     CrossRef
  • Diabetic retinopathy and cognitive dysfunction: a systematic review and meta-analysis
    Mei Wu, Fan Mei, Kaiyan Hu, Liyuan Feng, Zhe Wang, Qianqian Gao, Fei Chen, Li Zhao, Xiaohui Li, Bin Ma
    Acta Diabetologica.2022; 59(4): 443.     CrossRef
  • Associations between depression and cognition, mild cognitive impairment and dementia in persons with diabetes mellitus: A systematic review and meta-analysis
    Yeng Yan Chow, Milou Verdonschot, Claire T. McEvoy, Geeske Peeters
    Diabetes Research and Clinical Practice.2022; 185: 109227.     CrossRef
  • Diabetes Mellitus: A Path to Amnesia, Personality, and Behavior Change
    Rahnuma Ahmad, Kona Chowdhury, Santosh Kumar, Mohammed Irfan, Govindool Reddy, Farhana Akter, Dilshad Jahan, Mainul Haque
    Biology.2022; 11(3): 382.     CrossRef
  • Hypothyroidism and Diabetes-Related Dementia: Focused on Neuronal Dysfunction, Insulin Resistance, and Dyslipidemia
    Hee Kyung Kim, Juhyun Song
    International Journal of Molecular Sciences.2022; 23(6): 2982.     CrossRef
  • Type 2 Diabetes Mellitus as a Risk Factor for Alzheimer’s Disease: Review and Meta-Analysis
    Athanasia Athanasaki, Konstantinos Melanis, Ioanna Tsantzali, Maria Ioanna Stefanou, Sofia Ntymenou, Sotirios G. Paraskevas, Theodosis Kalamatianos, Eleni Boutati, Vaia Lambadiari, Konstantinos I. Voumvourakis, George Stranjalis, Sotirios Giannopoulos, Ge
    Biomedicines.2022; 10(4): 778.     CrossRef
  • Cardiometabolic measures and cognition in early menopause - Analysis of baseline data from a randomized controlled trial
    Lubna Pal, Kelly Morgan, Nanette F. Santoro, JoAnn E. Manson, Hugh S. Taylor, Virginia M. Miller, Eliot A. Brinton, Rogerio Lobo, Genevieve Neal-Perry, Marcelle I. Cedars, S. Mitchell Harman, Taryn T. James, Carey E. Gleason
    Maturitas.2022; 162: 58.     CrossRef
  • Dysfunctional Glucose Metabolism in Alzheimer’s Disease Onset and Potential Pharmacological Interventions
    Vijay Kumar, So-Hyeon Kim, Kausik Bishayee
    International Journal of Molecular Sciences.2022; 23(17): 9540.     CrossRef
  • Metabolically healthy obesity: it is time to consider its dynamic changes
    Yun Kyung Cho, Chang Hee Jung
    Cardiovascular Prevention and Pharmacotherapy.2022; 4(4): 123.     CrossRef
  • Association between cholesterol levels and dementia risk according to the presence of diabetes and statin use: a nationwide cohort study
    You-Bin Lee, Min Young Kim, Kyungdo Han, Bongsung Kim, Jiyun Park, Gyuri Kim, Kyu Yeon Hur, Jae Hyeon Kim, Sang-Man Jin
    Scientific Reports.2022;[Epub]     CrossRef
  • The insulin resistance by triglyceride glucose index and risk for dementia: population-based study
    Sangmo Hong, Kyungdo Han, Cheol-Young Park
    Alzheimer's Research & Therapy.2021;[Epub]     CrossRef
  • The identification of established modifiable mid-life risk factors for cardiovascular disease which contribute to cognitive decline: Korean Longitudinal Study of Aging (KLoSA)
    Yebeen Ysabelle Boo, Otto-Emil Jutila, Meghan A. Cupp, Logan Manikam, Sung-Il Cho
    Aging Clinical and Experimental Research.2021; 33(9): 2573.     CrossRef
  • Examining the effects of multiple chronic conditions on cognitive decline and potential moderators among older Koreans: Findings from the Korean Longitudinal Study of Ageing 2006–2016
    Yura Lee, Chi C. Cho
    Archives of Gerontology and Geriatrics.2021; 95: 104424.     CrossRef
  • Cumulative Exposure to Metabolic Syndrome Components and the Risk of Dementia: A Nationwide Population-Based Study
    Yunjung Cho, Kyungdo Han, Da Hye Kim, Yong-Moon Park, Kun-Ho Yoon, Mee Kyoung Kim, Seung-Hwan Lee
    Endocrinology and Metabolism.2021; 36(2): 424.     CrossRef
  • Cardiovascular risks of periodontitis and oral hygiene indicators in patients with diabetes mellitus
    Tae-Jin Song, Jimin Jeon, Jinkwon Kim
    Diabetes & Metabolism.2021; 47(6): 101252.     CrossRef
  • Association Between Diabetic Retinopathy and Cognitive Impairment: A Systematic Review and Meta-Analysis
    Dihe Cheng, Xue Zhao, Shuo Yang, Guixia Wang, Guang Ning
    Frontiers in Aging Neuroscience.2021;[Epub]     CrossRef
  • Improving Cognition with Nutraceuticals Targeting TGF-β1 Signaling
    Margherita Grasso, Giuseppe Caruso, Justyna Godos, Angela Bonaccorso, Claudia Carbone, Sabrina Castellano, Walter Currenti, Giuseppe Grosso, Teresa Musumeci, Filippo Caraci
    Antioxidants.2021; 10(7): 1075.     CrossRef
  • The risk of Alzheimer’s disease according to dynamic changes in metabolic health and obesity: a nationwide population-based cohort study
    Yun Kyung Cho, Jiwoo Lee, Hwi Seung Kim, Joong-Yeol Park, Woo Je Lee, Ye-Jee Kim, Chang Hee Jung
    Aging.2021; 13(13): 16974.     CrossRef
  • Letter: Hypoglycemia and Dementia Risk in Older Patients with Type 2 Diabetes Mellitus: A Propensity-Score Matched Analysis of a Population-Based Cohort Study (Diabetes Metab J 2020;44:125–33)
    Jin Hwa Kim
    Diabetes & Metabolism Journal.2020; 44(2): 356.     CrossRef
  • The Interplay between Diabetes and Alzheimer’s Disease—In the Hunt for Biomarkers
    Adriana Kubis-Kubiak, Aleksandra Dyba, Agnieszka Piwowar
    International Journal of Molecular Sciences.2020; 21(8): 2744.     CrossRef
  • Association between cytomegalovirus end-organ diseases and moderate-to-severe dementia: a population-based cohort study
    Kyoung Hwa Lee, Da Eun Kwon, Kyung Do Han, Yeonju La, Sang Hoon Han
    BMC Neurology.2020;[Epub]     CrossRef
Editorial
Clinical Diabetes & Therapeutics
Changes in the Bone Mineral Density of Femur Neck and Total Hip Over a 52-Week Treatment with Lobeglitazone
Da Young Lee, Ji A Seo
Diabetes Metab J. 2017;41(5):374-376.   Published online October 24, 2017
DOI: https://doi.org/10.4093/dmj.2017.41.5.374
  • 3,057 View
  • 27 Download
PDFPubReader   

Diabetes Metab J : Diabetes & Metabolism Journal