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Buzzetti R, Candido R, Esposito K, Giaccari A, Mannucci E, Nicolucci A, Russo GT. Open questions on basal insulin therapy in T2D: a Delphi consensus. Acta Diabetol 2024:10.1007/s00592-024-02285-2. [PMID: 38767675 DOI: 10.1007/s00592-024-02285-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/29/2023] [Accepted: 04/07/2024] [Indexed: 05/22/2024]
Abstract
AIMS The revolution in the therapeutic approach to type 2 diabetes (T2D) requires a rethinking of the positioning of basal insulin (BI) therapy. Given the considerable number of open questions, a group of experts was convened with the aim of providing, through a Delphi consensus method, practical guidance for doctors. METHODS A group of 6 experts developed a series of 29 statements on: the role of metabolic control in light of the most recent guidelines; BI intensification strategies: (1) add-on versus switch; (2) inertia in starting and titrating; (3) free versus fixed ratio combination; basal-bolus intensification and de-intensification strategies; second generation analogues of BI (2BI). A panel of 31 diabetologists, by accessing a dedicated website, assigned each statement a relevance score on a 9-point scale. The RAND/UCLA Appropriateness Method was adopted to assess the existence of disagreement among participants. RESULTS Panelists showed agreement for all 29 statements, of which 26 were considered relevant, one was considered not relevant and two were of uncertain relevance. Panelists agreed that the availability of new classes of drugs often allows the postponement of BI and the simplification of therapy. It remains essential to promptly initiate and titrate BI when required. BI should always, unless contraindicated, be started in addition to, and not as a replacement, for ongoing treatments with cardiorenal benefits. 2BIs should be preferred for their pharmacological profile, greater ease of self-titration and flexibility of administration. CONCLUSION In a continuously evolving scenario, BI therapy still represents an important option in the management of T2D patients.
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Affiliation(s)
- Raffaella Buzzetti
- Department of Experimental Medicine, Sapienza University of Rome, Rome, Italy
| | - Riccardo Candido
- Department of Medical Surgical and Health Sciences, University of Trieste, Trieste, Italy
| | - Katherine Esposito
- Department of Advanced Medical and Surgical Sciences, Università della Campania "Luigi Vanvitelli", Naples, Italy
| | - Andrea Giaccari
- Center for Endocrine and Metabolic Diseases, Fondazione Policlinico Universitario A. Gemelli IRCCS and Università Cattolica del Sacro Cuore, Rome, Italy
| | - Edoardo Mannucci
- Diabetology, Careggi Hospital and University of Florence, Florence, Italy
| | - Antonio Nicolucci
- CORESEARCH - Center for Outcomes Research and Clinical Epidemiology, Corso Umberto I, 103, 65122, Pescara, Italy.
| | - Giuseppina T Russo
- Department of Clinical and Experimental Medicine, University of Messina, Messina, Italy
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Song Y, Zhang H, Sun J, Long Y, Zhang K, Yin Q, Duan X. Glycemic Variability and the Risk of Diabetic Peripheral Neuropathy: A Meta-Analysis. Horm Metab Res 2024; 56:358-367. [PMID: 37820699 DOI: 10.1055/a-2165-3579] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/13/2023]
Abstract
Glycemic variability (GV) has been related to complications in patients with diabetes. The aim of the systematic review and meta-analysis was to investigate whether GV is also associated with the incidence of diabetic peripheral neuropathy (DPN). A systematic search of Medline, Web of Science, Embase, and Cochrane Library database was conducted to identify relevant observational studies with longitudinal follow-up. The Newcastle-Ottawa Scale was used for study quality evaluation. A random-effects model was utilized to pool the results, accounting for heterogeneity. Ten observational studies including 72 565 patients with diabetes were included. The quality score was 8-9, indicating generally good quality of the included studies. With a mean follow-up duration of 7.1 years, 11 532 patients (15.9%) were diagnosed as DPN. Compared to patients with low GV, patients with high GV were associated with an increased risk incidence of DPN (risk ratio: 1.51, 95% confidence interval: 1.23 to 1.85, p<0.001; I2=78%). In addition, subgroup analysis showed consistent results in patients with type 1 and type 2 diabetes, and in studies evaluating the short-term and long-term GV (p for subgroup difference=0.82 and 0.53). Finally, results of subgroup analysis also suggested that the association between GV and risk of DPN were not significantly affected by study design, follow-up durations, diagnostic methods for DPN, adjustment of mean glycated hemoglobin A1c, or study quality scores (p for subgroup difference all>0.05). A high GV may be associated with an increased incidence of DPN.
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Affiliation(s)
- Ying Song
- Department of Endocrinology and Metabolism, Xichang People's Hospital, Xichang, China
| | - Haiyan Zhang
- Department of Endocrinology and Metabolism, Xichang People's Hospital, Xichang, China
| | - Ju Sun
- Department of Endocrinology and Metabolism, Xichang People's Hospital, Xichang, China
| | - Ying Long
- Department of Endocrinology and Metabolism, Xichang People's Hospital, Xichang, China
| | - Kaixiang Zhang
- Department of Endocrinology and Metabolism, Xichang People's Hospital, Xichang, China
| | - Qian Yin
- Department of Endocrinology and Metabolism, Xichang People's Hospital, Xichang, China
| | - Xiaorong Duan
- Department of Endocrinology and Metabolism, Xichang People's Hospital, Xichang, China
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Yang X, Su G, Zhang T, Yang H, Tao H, Du X, Dong J. Comparison of admission glycemic variability and glycosylated hemoglobin in predicting major adverse cardiac events among type 2 diabetes patients with heart failure following acute ST-segment elevation myocardial infarction. J Transl Int Med 2024; 12:188-196. [PMID: 38978967 PMCID: PMC11229884 DOI: 10.2478/jtim-2024-0006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/10/2024] Open
Abstract
Background and Objectives Hyperglycemia is associated with adverse outcomes in patients with acute myocardial infarction (AMI) as well as in patients with heart failure. However, the significance of admission glycemic variability (GV) in predicting outcomes among diabetes patients with heart failure (HF) following acute ST-segment elevation myocardial infarction (ASTEMI) remains unclear. This study aims to explore the prognostic value of admission GV and admission glycosylated hemoglobin (HbA1c) levels in individuals diagnosed with type 2 diabetes and HF following ASTEMI. Methods We measured GV and HbA1c upon admission in 484 consecutive patients diagnosed with type 2 diabetes and HF following ASTEMI. GV, indicated as the mean amplitude of glycemic excursions (MAGE), was assessed utilizing a continuous glucose monitoring system (CGMS). admission MAGE values were categorized as < 3.9 or ≥ 3.9 mmol/L, while HbA1c levels were classified as < 6.5 or ≥ 6.5%. Participants were followed up prospectively for 12 months. The relationship of admission MAGE and HbA1c to the major adverse cardiac event (MACE) of patients with type 2 diabetes and HF following ASTEMI was analyzed. Results Among the 484 enrolled patients, the occurrence of MACE differed significantly based on MAGE categories (< 3.9 vs. ≥ 3.9 mmol/L), with rates of 13.6% and 25.3%, respectively (P = 0.001). While MACE rates varied by HbA1c categories (< 6.5 vs. ≥ 6.5%) at 15.7% and 21.8%, respectively (P = 0.086). Patients with higher MAGE levels exhibited a notably elevated risk of cardiac mortality and an increased incidence of HF rehospitalization. The Kaplan-Meier curves analysis demonstrated a significantly lower event-free survival rate in the high MAGE level group compared to the low MAGE level group (log-rank test, P < 0.001), while HbA1c did not exhibit a similar distinction. In multivariate analysis, high MAGE level was significantly associated with incidence of MACE (hazard ratio 3.645, 95% CI 1.287-10.325, P = 0.015), whereas HbA1c did not demonstrate a comparable association (hazard ratio 1.075, 95% CI 0.907-1.274, P = 0.403). Conclusions Elevated admission GV emerges as a more significant predictor of 1-year MACE in patients with type 2 diabetes and HF following ASTEMI, surpassing the predictive value of HbA1c.
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Affiliation(s)
- Xiuxiu Yang
- Department of Cardiology, Beijing Anzhen Hospital, Capital Medical University, Beijing 100029, China
| | - Gong Su
- Department of Cardiology, Aerospace Center Hospital, Peking University Aerospace School of Clinical Medicine, Beijing 100049, China
| | - Tao Zhang
- Department of Cardiology, Beijing Anzhen Hospital, Capital Medical University, Beijing 100029, China
| | - Hongxia Yang
- Department of Cardiology, Beijing Anzhen Hospital, Capital Medical University, Beijing 100029, China
| | - Hong Tao
- Department of Endocrinology, Beijing Anzhen Hospital, Capital Medical University, Beijing 100029, China
| | - Xin Du
- Department of Cardiology, Beijing Anzhen Hospital, Capital Medical University, Beijing 100029, China
| | - Jianzeng Dong
- Department of Cardiology, Beijing Anzhen Hospital, Capital Medical University, Beijing 100029, China
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McGill JB, Agarwal R, Anker SD, Bakris GL, Filippatos G, Pitt B, Ruilope LM, Birkenfeld AL, Caramori ML, Brinker M, Joseph A, Lage A, Lawatscheck R, Scott C, Rossing P. Effects of finerenone in people with chronic kidney disease and type 2 diabetes are independent of HbA1c at baseline, HbA1c variability, diabetes duration and insulin use at baseline. Diabetes Obes Metab 2023; 25:1512-1522. [PMID: 36722675 DOI: 10.1111/dom.14999] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Revised: 01/24/2023] [Accepted: 01/26/2023] [Indexed: 02/02/2023]
Abstract
AIM To evaluate the effect of finerenone by baseline HbA1c, HbA1c variability, diabetes duration and baseline insulin use on cardiorenal outcomes and diabetes progression. MATERIALS AND METHODS Composite efficacy outcomes included cardiovascular (cardiovascular death, non-fatal myocardial infarction, non-fatal stroke or hospitalization for heart failure), kidney (kidney failure, sustained ≥ 57% estimated glomerular filtration rate decline or renal death) and diabetes progression (new insulin initiation, increase in antidiabetic medication, 1.0% increase in HbA1c from baseline, new diabetic ketoacidosis diagnosis or uncontrolled diabetes). RESULTS In 13 026 participants, risk reductions in the cardiovascular and kidney composite outcomes with finerenone versus placebo were consistent across HbA1c quartiles (P interaction .52 and .09, respectively), HbA1c variability (P interaction .48 and .10), diabetes duration (P interaction .12 and .75) and insulin use (P interaction .16 and .52). HbA1c variability in the first year of treatment was associated with a higher risk of cardiovascular and kidney events (hazard ratio [HR] 1.20; 95% confidence interval [CI] 1.07-1.35; P = .0016 and HR 1.36; 95% CI 1.21-1.52; P < .0001, respectively). There was no effect on diabetes progression with finerenone or placebo (HR 1.00; 95% CI 0.95-1.04). Finerenone was well-tolerated across subgroups; discontinuation and hospitalization because of hyperkalaemia were low. CONCLUSIONS Finerenone efficacy was not modified by baseline HbA1c, HbA1c variability, diabetes duration or baseline insulin use. Greater HbA1c variability appeared to be associated with an increased risk of cardiorenal outcomes.
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Affiliation(s)
- Janet B McGill
- Division of Endocrinology, Metabolism and Lipid Research, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Rajiv Agarwal
- Richard L. Roudebush VA Medical Center and Indiana University, Indianapolis, Indiana, USA
| | | | - George L Bakris
- Department of Medicine, University of Chicago Medicine, Chicago, Illinois, USA
| | - Gerasimos Filippatos
- Department of Cardiology, School of Medicine, National and Kapodistrian University of Athens, Attikon University Hospital, Athens, Greece
| | - Bertram Pitt
- Department of Medicine, University of Michigan School of Medicine, Ann Arbor, Michigan, USA
| | - Luis M Ruilope
- Cardiorenal Translational Laboratory and Hypertension Unit, Institute of Research imas12, Madrid, Spain
- CIBER-CV, Hospital Universitario 12 de Octubre, Madrid, Spain
- Faculty of Sport Sciences, European University of Madrid, Madrid, Spain
| | - Andreas L Birkenfeld
- Department of Diabetology, Endocrinology and Nephrology, University Clinic, Tübingen, Germany
- Institute for Diabetes Research and Metabolic Diseases of Helmholtz Center Munich, German Center of Diabetes Research (DZD e.V.), University of Tübingen, Tübingen, Germany
| | - Maria L Caramori
- Diabetes & Metabolism Institute, Cleveland Clinic, Cleveland, Ohio, USA
- Department of Medicine, University of Minnesota, Minneapolis, MN, USA
| | - Meike Brinker
- Cardiology and Nephrology Clinical Development, Bayer AG, Wuppertal, Germany
| | - Amer Joseph
- Cardiology and Nephrology Clinical Development, Bayer AG, Berlin, Germany
| | - Andrea Lage
- Cardiology and Nephrology Clinical Development, Bayer SA, São Paulo, Brazil
| | | | | | - Peter Rossing
- Steno Diabetes Center Copenhagen, Herlev, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
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Li F, Zhang L, Shen Y, Liu HH, Zhang ZY, Hu G, Wang RX. Higher glucose fluctuation is associated with a higher risk of cardiovascular disease: Insights from pooled results among patients with diabetes. J Diabetes 2023; 15:368-381. [PMID: 37070713 PMCID: PMC10172020 DOI: 10.1111/1753-0407.13386] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Revised: 01/10/2023] [Accepted: 03/21/2023] [Indexed: 04/19/2023] Open
Abstract
BACKGROUND The relationship between glucose fluctuation and the risk of cardiovascular disease (CVD) in patients with diabetes remains elusive. Glycated hemoglobin (HbA1c) variability is a key parameter of glucose fluctuation. METHODS PubMed, Cochrane Library, Web of Science, and Embase were searched up to 1 July 2022. Studies reporting associations of HbA1c variability (HbA1c-SD), coefficient of variation of HbA1c (HbA1c-CV), and HbA1c variability score [HVS] with the risk of CVD among patients with diabetes were included. We used three different insights (a high-low value meta-analysis, a study-specific meta-analysis, and a non-linear dose-response meta-analysis) to explore the relationship between HbA1c variability and CVD risk. A subgroup analysis was also performed to screen the potential confounding factors. RESULTS A total of 14 studies with 254 017 patients with diabetes were eligible. The highest HbA1c variability was significantly associated with increased risks of CVD (HbA1c-SD, risk ratio [RR] 1.45; HbA1c-CV, RR 1.74; HVS, RR 2.46; all p < .001) compared to the lowest HbA1c variability. The RRs of CVD for per HbA1c variability were significantly >1 (all p < .001). The subgroup analysis for per HbA1c-SD found a significant exposure-covariate interaction in the types of diabetes (p = .003 for interaction). The dose-response analysis showed a positive association between HbA1c-CV and CVD risk (P for nonlinearity <.001). CONCLUSIONS Our study suggests that the higher glucose fluctuation is significantly associated with the higher CVD risk in diabetes patients based on HbA1c variability. The CVD risk associated with per HbA1c-SD might be higher among patients type 1 diabetes than patients with type 2 diabetes.
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Affiliation(s)
- Feng Li
- Department of Cardiology, Wuxi People's Hospital Affiliated to Nanjing Medical University, Wuxi, China
| | - Lei Zhang
- Department of Cardiology, Wuxi People's Hospital Affiliated to Nanjing Medical University, Wuxi, China
| | - Yun Shen
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
- Pennington Biomedical Research Center, Baton Rouge, Louisiana, USA
| | - Huan-Huan Liu
- Department of Cardiology, Wuxi People's Hospital Affiliated to Nanjing Medical University, Wuxi, China
| | - Zhen-Ye Zhang
- Department of Cardiology, Wuxi People's Hospital Affiliated to Nanjing Medical University, Wuxi, China
| | - Gang Hu
- Pennington Biomedical Research Center, Baton Rouge, Louisiana, USA
| | - Ru-Xing Wang
- Department of Cardiology, Wuxi People's Hospital Affiliated to Nanjing Medical University, Wuxi, China
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Kikani N, Balasubramanyam A. Remission in Ketosis-Prone Diabetes. Endocrinol Metab Clin North Am 2023; 52:165-174. [PMID: 36754492 DOI: 10.1016/j.ecl.2022.06.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Heterogeneous forms of Ketosis-prone diabetes (KPD) are characterized by patients who present with diabetic ketoacidosis (DKA) but lack the typical features and biomarkers of autoimmune T1D. The A-β+ subgroup of KPD provides unique insight into the concept of "remission" since these patients have substantial preservation of beta-cell function permitting the discontinuation of insulin therapy, despite initial presentation with DKA. Measurements of C-peptide levels are essential to predict remission and guide potential insulin withdrawal. Further studies into predictors of remission and relapse can help us guide patients with A-β+ KPD toward remission and develop targeted treatments for this form of atypical diabetes.
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Affiliation(s)
- Nupur Kikani
- Department of Endocrine Neoplasia and Hormonal Disorders, University of Texas MD Anderson Cancer Center, Unit 1461, 1515 Holcombe Boulevard, Houston, TX 77030, USA
| | - Ashok Balasubramanyam
- Division of Diabetes, Endocrinology, and Metabolism, Baylor College of Medicine, BCM 179A, One Baylor Plaza, Houston, TX 77030, USA.
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Zhai L, Lu J, Cao X, Zhang J, Yin Y, Tian H. Association Between the Variability of Glycated Hemoglobin and Retinopathy in Patients with Type 2 Diabetes Mellitus: A Meta-Analysis. Horm Metab Res 2023; 55:103-113. [PMID: 36223803 DOI: 10.1055/a-1931-4400] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
Abstract
Visit-to-visit variability of glycated hemoglobin (HbA1c) is a marker of long-term glycemic fluctuation, which has been related to increased risk of macrovascular complications in patients with type 2 diabetes mellitus (T2DM). The association between HbA1c variability and retinopathy in patients with T2DM, however, has been inconsistent in previous studies. In order to fully evaluate the above association, we conducted a meta-analysis. Observational studies related to the aim of the meta-analysis were identified by search of PubMed, Web of Science, and Embase databases. Studies with HbA1c variability evaluated as the standard deviation (SD) and/or the coefficients of variation (CV) of HbA1c were included. The results were analyzed using a random-effects model that incorporated potential heterogeneity between studies. Twelve observational studies involving 44 662 T2DM patients contributed to the meta-analysis. Overall, 5150 (11.5%) patients developed retinopathy. Pooled results showed that compared to patients with lower HbA1c variability, T2DM patients with higher HbA1c-SD (relative risk [RR]: 1.48, 95% confidence interval [CI]: 1.24 to 1.78, p<0.001, I2=34%) and higher HbA1c-CV (RR: 1.29, 95% CI: 1.05 to 1.59, p=0.02, I2=0%) were both associated with higher risk of DR. For studies with HbA1c-SD, the association was not significantly affected by study characteristics such as country, study design, mean age, disease duration, adjustment of mean HbA1c, or quality scores (p for subgroup difference all>0.05). In conclusion, higher HbA1c variability may be associated with an increased risk of retinopathy in patients with T2DM.
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Affiliation(s)
- Liping Zhai
- Department of Endocrinology, Taizhou Hospital of Traditional Chinese Medicine, Taizhou, China
| | - Jun Lu
- Department of Ophthalmology, Taizhou Hospital of Traditional Chinese Medicine, Taizhou, China
| | - Xinjian Cao
- Department of Clinical Medicine, Taizhou Hospital of Traditional Chinese Medicine, Taizhou, China
| | - Jun Zhang
- Department of Clinical Medicine, Taizhou Hospital of Traditional Chinese Medicine, Taizhou, China
| | - Yong Yin
- Department of Clinical Medicine, Taizhou Hospital of Traditional Chinese Medicine, Taizhou, China
| | - Hu Tian
- Department of Clinical Medicine, Taizhou Hospital of Traditional Chinese Medicine, Taizhou, China
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Yoshimura E, Hamada Y, Hatanaka M, Nanri H, Nakagata T, Matsumoto N, Shimoda S, Tanaka S, Miyachi M, Hatamoto Y. Relationship between intra-individual variability in nutrition-related lifestyle behaviors and blood glucose outcomes under free-living conditions in adults without type 2 diabetes. Diabetes Res Clin Pract 2023; 196:110231. [PMID: 36565723 DOI: 10.1016/j.diabres.2022.110231] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Revised: 09/25/2022] [Accepted: 12/19/2022] [Indexed: 12/24/2022]
Abstract
AIMS This study determined the relationship between intra-individual variability in day-to-day nutrition-related lifestyle behaviors (meal timing, eating window, food intake, movement behaviors, sleep conditions, and body weight) and glycemic outcomes under free-living conditions in adults without type 2 diabetes. METHODS We analyzed 104 adults without type 2 diabetes. During the 7-day measurement period, dietary intake, movement behaviors, sleep conditions, and glucose outcomes were assessed. Daily food intake was assessed using a mobile-based health application. Movement behaviors and sleep conditions were assessed using a tri-axial accelerometer. Meal timing was assessed from the participant's daily life record. Blood glucose levels were measured continuously using a glucose monitor. Statistical analyses were conducted using a linear mixed-effects model, with mealtime, food intake, body weight, movement behaviors, and sleep conditions as fixed effects and participants as a random effect. RESULTS Dinner time and eating window were positively significantly correlated with mean (dinner time, p = 0.003; eating window, p = 0.001), standard deviation (SD; both at p < 0.001), and maximum (both at p < 0.001) blood glucose levels. Breakfast time was negatively associated with glucose outcomes (p < 0.01). Sedentary time was positively significantly associated with blood glucose SD (p = 0.040). Total sleep time was negatively significantly correlated with SD (p = 0.035) and maximum (p = 0.032) blood glucose levels. Total daily energy intake (p = 0.001), carbohydrate intake (p < 0.001), and body weight (p < 0.05) were positively associated with mean blood glucose levels. CONCLUSION Intra-individual variations in nutrition-related lifestyle behaviors, especially morning and evening body weight, and food intake, were associated with mean blood glucose levels, and a long sedentary time and total sleep time were associated with glucose variability. Earlier dinner times and shorter eating windows per day resulted in better glucose control.
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Affiliation(s)
- Eiichi Yoshimura
- Department of Nutrition and Metabolism, National Institute of Health and Nutrition, National Institutes of Biomedical Innovation, Health and Nutrition, Tokyo 162-8636, Japan; Collaborative Research Center for Health and Medicine, National Institutes of Biomedical Innovation, Health and Nutrition, Osaka 566-0002, Japan.
| | - Yuka Hamada
- Department of Nutrition and Metabolism, National Institute of Health and Nutrition, National Institutes of Biomedical Innovation, Health and Nutrition, Tokyo 162-8636, Japan
| | - Mana Hatanaka
- Department of Nutrition and Metabolism, National Institute of Health and Nutrition, National Institutes of Biomedical Innovation, Health and Nutrition, Tokyo 162-8636, Japan
| | - Hinako Nanri
- Collaborative Research Center for Health and Medicine, National Institutes of Biomedical Innovation, Health and Nutrition, Osaka 566-0002, Japan; Department of Physical Activity Research, National Institute of Health and Nutrition, National Institutes of Biomedical Innovation, Health and Nutrition, Tokyo 162-8636, Japan
| | - Takashi Nakagata
- Collaborative Research Center for Health and Medicine, National Institutes of Biomedical Innovation, Health and Nutrition, Osaka 566-0002, Japan; Department of Physical Activity Research, National Institute of Health and Nutrition, National Institutes of Biomedical Innovation, Health and Nutrition, Tokyo 162-8636, Japan
| | - Naoyuki Matsumoto
- Faculty of Environmental & Symbiotic Sciences, Prefectural University of Kumamoto, 3-1-100 Tsukide, Higashi-ku, Kumamoto 862-8502, Japan
| | - Seiya Shimoda
- Faculty of Environmental & Symbiotic Sciences, Prefectural University of Kumamoto, 3-1-100 Tsukide, Higashi-ku, Kumamoto 862-8502, Japan
| | - Shigeho Tanaka
- Kagawa Nutrition University, 3-9-21 Chiyoda, Sakado, Saitama 350-0288, Japan
| | - Motohiko Miyachi
- Department of Nutrition and Metabolism, National Institute of Health and Nutrition, National Institutes of Biomedical Innovation, Health and Nutrition, Tokyo 162-8636, Japan; Department of Physical Activity Research, National Institute of Health and Nutrition, National Institutes of Biomedical Innovation, Health and Nutrition, Tokyo 162-8636, Japan; Faculty of Sport Sciences, Waseda University, 2-579-1 Mikajima, Tokorozawa, Saitama 359-1192, Japan
| | - Yoichi Hatamoto
- Department of Nutrition and Metabolism, National Institute of Health and Nutrition, National Institutes of Biomedical Innovation, Health and Nutrition, Tokyo 162-8636, Japan; Collaborative Research Center for Health and Medicine, National Institutes of Biomedical Innovation, Health and Nutrition, Osaka 566-0002, Japan
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