收藏切换
Relationship between prediabetes and risk of atrial fibrillation: a meta-analysis
收藏切换
PDF
Satoru Kodama1, ✉, Takaho Yamada2, Noriko Yagyuda2, Efrem D'Avila Ferreira2, Takaaki Sato2, Masaru Kitazawa2, Yasuhiro Matsubayashi2, Kazuya Fujihara2, Shiro Tanaka3, Chika Horikawa4, Yoko Yachi5, Hirohito Sone2
Journal of Geriatric Cardiology | 2026, 23(9) : 622 - 646
Less
收藏切换
Journal of Geriatric Cardiology | 2026, 23(9): 622-646
• RESEARCH ARTICLE •
Relationship between prediabetes and risk of atrial fibrillation: a meta-analysis
Full
Satoru Kodama1, ✉, Takaho Yamada2, Noriko Yagyuda2, Efrem D'Avila Ferreira2, Takaaki Sato2, Masaru Kitazawa2, Yasuhiro Matsubayashi2, Kazuya Fujihara2, Shiro Tanaka3, Chika Horikawa4, Yoko Yachi5, Hirohito Sone2
Affiliations
  • 1.Department of Prevention of Noncommunicable Diseases and Promotion of Health Checkups, Niigata University Graduate School of Medical and Dental Sciences, Niigata, Japan
  • 2.Department of Hematology, Endocrinology and Metabolism, Niigata University Graduate School of Medical and Dental Sciences, Niigata, Japan
  • 3.Department of Pharmacoepidemiology, Kyoto University School of Public Health, Kyoto, Japan
  • 4.Department of Health and Nutrition, Faculty of Human Life Studies, University of Niigata Prefecture, Niigata, Japan
  • 5.Department of Nutrition, Faculty of Health Care Science, Chiba Prefectural University of Health Sciences, Chiba, Japan
Published: 2026-09-28 doi: 10.26599/1671-5411.2026.09.003
Outline
收藏切换
Background

Diabetes is an established risk factor for atrial fibrillation (AF). However, whether prediabetes is also a risk factor for AF is unclear. This meta-analysis examined the relationship between prediabetes and AF risk.

Methods

EMBASE, MEDLINE, and Publicly Available Contents (from Jan. 1, 1950 to Jan. 29, 2025) were used to comprehensively search for observational studies of the incidence or prevalence of AF among those with prediabetes or normoglycemia. Each relative risk (RR) for prediabetes vs. normoglycemia and the population attributable fraction (PAF) of prediabetes to AF incidence in longitudinal studies and the odds ratio (OR) for prediabetes vs. normoglycemia in cross-sectional studies were pooled with a random-effects model.

Results

Identified were 46 eligible studies. Pooled RR and PAF (95% confidence interval [CI]) were 1.12 (1.06-1.18) and 2.7% (1.4%-4.0%), respectively. Pooled crude RR and crude OR (95% CI) were 1.49 (1.37-1.62) and 1.42 (1.23-1.64), respectively. Higher RR was revealed in populations ≥ 65 years old vs. < 65 years old (P = 0.02) and in Asian vs. non-Asian countries (P = 0.047). Higher PAF was revealed in studies with a population ≥ 65 years old vs. < 65 years old (P < 0.001) and in male-dominant vs. female-dominant studies (P < 0.001). Only by examining the RR for both diabetes and prediabetes vs. normoglycemia, the pooled RR/PAF (95% CI) was 1.12 (1.15-1.20)/1.6% (0.9%-2.3%) for prediabetes and 1.15 (1.10-1.20)/1.0% (0.7%-13%) for diabetes.

Conclusions

Prediabetes is a modest but significant risk factor for AF, comparable to that of diabetes. The impact of prediabetes was strong among the elderly, males, and Asian people.

Satoru Kodama, Takaho Yamada, Noriko Yagyuda, Efrem D'Avila Ferreira, Takaaki Sato, Masaru Kitazawa, Yasuhiro Matsubayashi, Kazuya Fujihara, Shiro Tanaka, Chika Horikawa, Yoko Yachi, Hirohito Sone. Relationship between prediabetes and risk of atrial fibrillation: a meta-analysis. 老年心脏病杂志(英文), 2026 , 23 (9) : 622 -646 . DOI: 10.26599/1671-5411.2026.09.003
Satoru Kodama, Takaho Yamada, Noriko Yagyuda, Efrem D'Avila Ferreira, Takaaki Sato, Masaru Kitazawa, Yasuhiro Matsubayashi, Kazuya Fujihara, Shiro Tanaka, Chika Horikawa, Yoko Yachi, Hirohito Sone. Relationship between prediabetes and risk of atrial fibrillation: a meta-analysis[J]. Journal of Geriatric Cardiology, 2026 , 23 (9) : 622 -646 . DOI: 10.26599/1671-5411.2026.09.003
  • Satoru Kodama is financially supported by a research grant from the Suzuki Manpei International Prize for Diabetes Research. Hirohito Sone is financially supported by the Japan Agency for Medical Research and Development (AMED) (No. 25gn0110087h0002). These sponsors had no influence over the design and conduct of the study; collection, management, analysis, and interpretation of the data; or preparation, review, or approval of the manuscript.
[1]
Xu S, Chen Y, Lin R, et al. Burden of atrial fibrillation and its attributable risk factors from 1990 to 2019: An analysis of the Global Burden of Disease study 2019. Front Cardiovasc Med 2022; 9: 997698.
[2]
Schnabel RB, Yin X, Gona P, et al. 50 year trends in atrial fibrillation prevalence, incidence, risk factors, and mortality in the Framingham Heart Study: a cohort study. Lancet 2015; 386: 154-162.
[3]
Gallagher C, Hendriks JM, Giles L, et al. Increasing trends in hospitalisations due to atrial fibrillation in Australia from 1993 to 2013. Heart 2019; 105: 1358-1363.
[4]
Pyykonen M, Linna M, Tykkylainen M, Delmelle E, Laatikainen T. Patient-specific and healthcare real-world costs of atrial fibrillation in individuals treated with direct oral anticoagulant agents or warfarin. BMC Health Serv Res 2021; 21: 1299.
[5]
Huxley RR, Lopez FL, Folsom AR, et al. Absolute and attributable risks of atrial fibrillation in relation to optimal and borderline risk factors: the Atherosclerosis Risk in Communities (ARIC) study. Circulation 2011; 123: 1501-1508.
[6]
Benjamin EJ, Levy D, Vaziri SM, D'Agostino RB, Belanger AJ, Wolf PA. Independent risk factors for atrial fibrillation in a population-based cohort. The Framingham Heart Study. JAMA 1994; 271: 840-844.
[7]
Pacher P, Ungvari Z, Nanasi PP, Kecskemeti V. Electrophysiological changes in rat ventricular and atrial myocardium at different stages of experimental diabetes. Acta Physiol Scand 1999; 166: 7-13.
[8]
Watanabe M, Yokoshiki H, Mitsuyama H, Mizukami K, Ono T, Tsutsui H. Conduction and refractory disorders in the diabetic atrium. Am J Physiol Heart Circ Physiol 2012; 303: H86-H95.
[9]
American Diabetes Association Professional Practice C.2. Diagnosis and classification of diabetes: Standards of Care in Diabetes-2025. Diabetes Care 2025; 48: S27-S49.
[10]
Centers for Disease Control and Prevention. National Diabetes Statistics Report. 2024. https://www.cdc.gov/diabetes/data/statistics-report/index.html (accessed on Apr 28, 2025).
[11]
Aune D, Feng T, Schlesinger S, Janszky I, Norat T, Riboli E. Diabetes mellitus, blood glucose and the risk of atrial fibrillation: A systematic review and meta-analysis of cohort studies. J Diabetes Complications 2018; 32: 501-511.
[12]
Sun Y, Hu D. The link between diabetes and atrial fibrillation: cause or correlation? J Cardiovasc Dis Res 2010; 1: 10-11.
[13]
Haldane JB. The estimation and significance of the logarithm of a ratio of frequencies. Ann Hum Genet 1956; 20: 309-311.
[14]
Higgins JP, Thompson SG. Quantifying heterogeneity in a meta-analysis. Stat Med 2002; 21: 1539-1558.
[15]
DerSimonian R, Laird N. Meta-analysis in clinical trials. Controlled clinical trials 1986; 7: 177-188.
[16]
Rothman KJ, Lash TL. Modern epidemiology: Third edition. 2011: 1-758.
[17]
Goldstein H, Yang M, Omar R, et al. Meta-analysis using multilevel models with an application to the study of class size effects. J R Stat Soc Ser C Appl Stat 2002; 49: 399-412.
[18]
Begg CB, Mazumdar M. Operating characteristics of a rank correlation test for publication bias. Biometrics 1994; 50: 1088-101.
[19]
Egger M, Davey Smith G, et al. Bias in meta-analysis detected by a simple, graphical test. BMJ 1997; 315: 629-634.
[20]
Duval S, Tweedie R. Trim and fill: A simple funnel-plot-based method of testing and adjusting for publication bias in meta-analysis. Biometrics 2000; 56: 455-463.
[21]
Sterne JA, Gavaghan D, Egger M. Publication and related bias in meta-analysis: power of statistical tests and prevalence in the literature. J Clin Epidemiol 2000; 53: 1119-1129.
[22]
Imano H, Iso H, Kitamura A, et al. Nonfasting Glucose and Incident Stroke and Its Types-The Circulatory Risk in Communities Study (CIRCS). Circ J 2018; 82: 1598-1604.
[23]
Yu X, Wang X, Dun S, et al. Obesity modifies the association between abnormal glucose metabolism and atrial fibrillation in older adults: a community-based longitudinal and prospective cohort study. Hellenic J Cardiol 2025. Doi: 10.1016/j.hjc.2024.12.007.
[24]
Kim J, Kim D, Jang E, et al. Associations of high-normal blood pressure and impaired fasting glucose with atrial fibrillation. Heart 2023; 109: 929-935.
[25]
Hsu JC, Yang YY, Chuang SL, et al. Prediabetes as a risk factor for new-onset atrial fibrillation: the propensity-score matching cohort analyzed using the Cox regression model coupled with the random survival forest. Cardiovasc Diabetol 2023; 22: 35.
[26]
Johansson C, Ortendahl L, Lind MM, et al. Diabetes, prediabetes, and atrial fibrillation-A population-based cohort study based on national and regional registers. J Intern Med 2023; 294: 605-615.
[27]
Rentsch CT, Garfield V, Mathur R, et al. Sex-specific risks for cardiovascular disease across the glycaemic spectrum: a population-based cohort study using the UK Biobank. Lancet Reg Health Eur 2023; 32: 100693.
[28]
Rorth R, Kriegbaum M, Grand MK, et al. Risk of atrial fibrillation in individuals with dysglycemia and diabetes. J Diabetes Complications 2023; 37: 108579.
[29]
Sumin AN, Bezdenezhnykh NA, Bezdenezhnykh AV, et al. Association of Alternative Markers of Carbohydrate Metabolism (Fructosamine and 1, 5-Anhydroglucitol) with Perioperative Characteristics and In-Hospital Complications of Coronary Artery Bypass Grafting in Patients with Type 2 Diabetes Mellitus, Prediabetes, and Normoglycemia. Diagnostics (Basel) 2023; 13: 969.
[30]
Zhong X, Jiao H, Zhao D, et al. Association between serum uric acid levels and atrial fibrillation in different fasting glucose patterns: A case-control study. Front Endocrinol (Lausanne) 2023; 14: 1021267.
[31]
Upur H, Li JL, Zou XG, et al. Short and long-term prognosis of admission hyperglycemia in patients with and without diabetes after acute myocardial infarction: a retrospective cohort study. Cardiovasc Diabetol 2022; 21: 114.
[32]
Lind V, Hammar N, Lundman P, et al. Impaired fasting glucose: a risk factor for atrial fibrillation and heart failure. Cardiovasc Diabetol 2021; 20: 227.
[33]
Choe WS, Choi EK, Han KD, et al. Association of metabolic syndrome and chronic kidney disease with atrial fibrillation: A nationwide population-based study in Korea. Diabetes Res Clin Pract 2019; 148: 14-22.
[34]
Yang S, Choi EK, Han KD, et al. Risk of Atrial Fibrillation in Relation to the Time Course of Type 2 Diabetes Mellitus and Fasting Blood Glucose. Am J Cardiol 2019; 124: 1881-1888.
[35]
Kokubo Y, Watanabe M, Higashiyama A, Nakao YM, Kusano K, Miyamoto Y. Development of a Basic Risk Score for Incident Atrial Fibrillation in a Japanese General Population- The Suita Study. Circ J 2017; 81: 1580-1588.
[36]
Lee SS, Ae Kong K, Kim D, et al. Clinical implication of an impaired fasting glucose and prehypertension related to new onset atrial fibrillation in a healthy Asian population without underlying disease: a nationwide cohort study in Korea. Eur Heart J 2017; 38: 2599-2607.
[37]
Masnaghetti SE, Sarzi Braga S, Vaninetti R, et al. Altered fasting glycemia in cardiac patients during in-hospital rehabilitation: impact on short and long-term follow-up. J Cardiovasc Med (Hagerstown) 2017; 18: 625-630.
[38]
AbuShady MM, Mohamady Y, Enany B, Nammas W. Prevalence of prediabetes in patients with acute coronary syndrome: impact on in-hospital outcomes. Intern Med J 2015; 45: 183-188.
[39]
Nystrom PK, Carlsson AC, Leander K, de Faire U, Hellenius ML, Gigante B. Obesity, metabolic syndrome and risk of atrial fibrillation: a Swedish, prospective cohort study. PLoS One 2015; 10: e0127111.
[40]
Blasco ML, Sanjuan R, Palacios L, et al. Prognostic value of admission glycated haemoglobin in unknown diabetic patients with acute myocardial infarction. Eur Heart J Acute Cardiovasc Care 2014; 3: 347-353.
[41]
Sandhu RK, Conen D, Tedrow UB, et al. Predisposing factors associated with development of persistent compared with paroxysmal atrial fibrillation. J Am Heart Assoc 2014; 3: e000916.
[42]
Sano F, Ohira T, Kitamura A, et al. Heavy alcohol consumption and risk of atrial fibrillation. The Circulatory Risk in Communities Study (CIRCS). Circ J 2014; 78: 955-961.
[43]
Huxley RR, Alonso A, Lopez FL, et al. Type 2 diabetes, glucose homeostasis and incident atrial fibrillation: the Atherosclerosis Risk in Communities study. Heart 2012; 98: 133-138.
[44]
Schoen T, Pradhan AD, Albert CM, Conen D. Type 2 diabetes mellitus and risk of incident atrial fibrillation in women. J Am Coll Cardiol 2012; 60: 1421-1428.
[45]
Cicek G, Uyarel H, Ergelen M, et al. Hemoglobin A1c as a prognostic marker in patients undergoing primary angioplasty for acute myocardial infarction. Coron Artery Dis 2011; 22: 131-137.
[46]
Watanabe H, Tanabe N, Watanabe T, et al. Metabolic syndrome and risk of development of atrial fibrillation: the Niigata preventive medicine study. Circulation 2008; 117: 1255-1260.
[47]
O'Sullivan CJ, Hynes N, Mahendran B, et al. Haemoglobin A1c (HbA1C) in non-diabetic and diabetic vascular patients. Is HbA1C an independent risk factor and predictor of adverse outcome? Eur J Vasc Endovasc Surg 2006; 32: 188-197.
[48]
Boxhammer E, Hammerer M, Schernthaner C, et al. The Silent Threat: A Retrospective Cohort Study on the Impact of Prediabetes on ST-Elevation Myocardial Infarction Survival-A Call to Action! Biomedicines 2024; 12: 2223.
[49]
Cheang I, Zhu X, Huang JY, et al. Prediabetes is associated with increased cardiac events in patients with cancer who are prescribed anthracyclines. Cancer 2024; 130: 2795-806.
[50]
Zaki SM, El Karsh DS, Yousef S, Jamal T, Alsaddah A. The association between components of metabolic syndrome and abnormal electrocardiograms in the saudi population: a retrospective study. Cureus 2024; 16: e56782.
[51]
Kim YG, Roh SY, Jeong JH, et al. Long-term increase in fasting blood glucose is associated with increased risk of sudden cardiac arrest. Cardiovasc Diabetol 2023; 22: 38.
[52]
Tang CC, Tsai JP, Chen YH, et al. Associations of glucometabolic indices with aortic stiffness in patients undergoing peritoneal dialysis with and without diabetes mellitus. Int J Mol Sci 2023; 24: 17094.
[53]
Zhang D, Liu Z, Liu P, et al. Association of baseline fasting plasma glucose with 1-year mortality in non-diabetic patients with acute cerebral infarction: a multicentre observational cohort study. BMJ Open 2023; 13: e069716.
[54]
Djupsjo C, Kuhl J, Andersson T, et al. Admission glucose as a prognostic marker for all-cause mortality and cardiovascular disease. Cardiovasc Diabetol 2022; 21: 258.
[55]
Gündoğmuş PD, Keskin Ü. Effect of Admission Hyperglycemia on Mortality in Diabetic and Non-diabetic Geriatric Patients with Non-ST-segment Elevation Myocardial Infarction. J Updates Cardiovasc Med 2022; 10: 72-82.
[56]
Lupu L, Taha L, Farkash R, et al. Hemoglobin A1C as a prognostic factor and the pre-diabetic paradox in patients admitted to a tertiary care medical center intensive cardiac care unit: The Jerusalem platelets thrombosis and intervention in cardiology (JUPITER-6) study group. Cardiovasc Diabetol 2022; 21: 86.
[57]
Veugen MGJ, Onete VG, Henry RMA, et al. Health burden in type 2 diabetes and prediabetes in The Maastricht Study. Sci Rep 2022; 12: 7337.
[58]
Wei W, Liang Y, Guo D, et al. Hyperglycemia newly detected by glycated hemoglobin affects all-cause mortality in coronary artery disease patients: a retrospective cohort study. Diabetes Res Clin Pract 2022; 191: 110053.
[59]
Kim BG, Kim GY, Cha JK. Pre-diabetes is a predictor of short-term poor outcomes after acute ischemic stroke using IV thrombolysis. BMC Neurol 2021; 21: 72.
[60]
Wnuk M, Popiela T, Drabik L, et al. Fasting hyperglycemia and long-term outcome in patients with acute ischemic stroke treated with mechanical thrombectomy. J Stroke Cerebrovasc Dis 2020; 29: 104774.
[61]
Fu L, Deng H, Lin WD, et al. Association between elevated blood glucose level and non-valvular atrial fibrillation: a report from the Guangzhou heart study. BMC Cardiovasc Disord 2019; 19: 270.
[62]
Nochioka K, Sakata Y, Miura M, et al. Impaired glucose tolerance and albuminuria in patients with chronic heart failure: a subanalysis of the SUPPORT trial. ESC Heart Fail 2019; 6: 1252-1261.
[63]
Khoo K, Lew J, Neef P, et al. Routine use of HbA1c amongst inpatients hospitalised with decompensated heart failure and the association of dysglycaemia with outcomes. Sci Rep 2018; 8: 13564.
[64]
Marto JP, Saraiva M, Ladeira F, et al. Prediabetes is associated with unfavorable outcome in young adult patients with ischemic stroke. J Stroke Cerebrovasc Dis 2018; 27: 352-356.
[65]
Itzhaki Ben Zadok O, Kornowski R, Goldenberg I, et al. Admission blood glucose and 10-year mortality among patients with or without pre-existing diabetes mellitus hospitalized with heart failure. Cardiovasc Diabetol 2017; 16: 102.
[66]
Brunisholz KD, Joy EA, Hashibe M, et al. Incidental Risk of Type 2 diabetes mellitus among patients with confirmed and unconfirmed prediabetes. PLoS One 2016; 11: e0157729.
[67]
Sun S, Pan Y, Zhao X, et al. The association between impaired glucose regulation and prognosis of chinese patients with intracerebral hemorrhage. Sci Rep 2016; 6: 36220.
[68]
Johansen OE, Brustad E, Enger S, Tveit A. Prevalence of abnormal glucose metabolism in atrial fibrillation: a case control study in 75-year old subjects. Cardiovasc Diabetol 2008; 7: 28.
[69]
Kaneko H, Itoh H, Kiriyama H, et al. Fasting plasma glucose and subsequent cardiovascular disease among young adults: Analysis of a nationwide epidemiological database. Atherosclerosis 2021; 319: 35-41.
[70]
Li Y, Deng J, Li L. Association between prediabetes and the risk of atrial fibrillation: a systematic review and meta-analysis. Front Endocrinol (Lausanne) 2025; 16: 1763810.
[71]
Guyatt GH, Oxman AD, Sultan S, et al. GRADE guidelines: 9. Rating up the quality of evidence. J Clin Epidemiol 2011; 64: 1311-1316.
[72]
Kodama S, Saito K, Tanaka S, et al. Alcohol consumption and risk of atrial fibrillation: a meta-analysis. J Am Coll Cardiol 2011; 57: 427-436.
[73]
Lee Y, Cha SJ, Park JH, et al. Association between insulin resistance and risk of atrial fibrillation in non-diabetics. Eur J Prev Cardiol 2020; 27: 1934-1941.
[74]
Chan YH, Chang GJ, Lai YJ, et al. Atrial fibrillation and its arrhythmogenesis associated with insulin resistance. Cardiovasc Diabetol 2019; 18: 125.
[75]
Echouffo-Tcheugui JB, Perreault L, Ji L, Dagogo-Jack S. Diagnosis and management of prediabetes: a review. JAMA 2023; 329: 1206-1216.
[76]
Morseth B, Geelhoed B, Linneberg A, et al. Age-specific atrial fibrillation incidence, attributable risk factors and risk of stroke and mortality: results from the MORGAM Consortium. Open Heart 2021; 8: e001624.
[77]
Nie Z, Xu H, Chen C, et al. Population attributable risks of potential modifiable factors for atrial fibrillation in china: a national survey. Risk Manag Healthc Policy 2022; 15: 1215-1224.
[78]
Hauguel-Moreau M, Hergault H, Cazabat L, et al. Prevalence of prediabetes and undiagnosed diabetes in a large urban middle-aged population: the CARVAR 92 cohort. Cardiovasc Diabetol 2023; 22: 31.
[79]
Zhang F, Hu Y, Wang J, et al. Sex Differences in the Association between Polygenic Risk Score and Atrial Fibrillation Incidence: A Prospective Cohort Study. Can J Cardiol 2025; 41: 2554-2563.
[80]
Arnar DO, Thorvaldsson S, Manolio TA, et al. Familial aggregation of atrial fibrillation in Iceland. Eur Heart J 2006; 27: 708-712.
[81]
Chugh SS, Havmoeller R, Narayanan K, et al. Worldwide epidemiology of atrial fibrillation: a Global Burden of Disease 2010 Study. Circulation 2014; 129: 837-847.
[82]
Zhu Y, Sidell MA, Arterburn D, et al. Racial/Ethnic Disparities in the Prevalence of Diabetes and Prediabetes by BMI: Patient Outcomes Research To Advance Learning (PORTAL) Multisite Cohort of Adults in the U. S. Diabetes Care 2019; 42: 2211-2219.
[83]
Dewland TA, Olgin JE, Vittinghoff E, Marcus GM. Incident atrial fibrillation among Asians, Hispanics, blacks, and whites. Circulation 2013; 128: 2470-2477.
[84]
Fuster V, Ryden LE, Cannom DS, et al. 2011 ACCF/AHA/HRS focused updates incorporated into the ACC/AHA/ESC 2006 guidelines for the management of patients with atrial fibrillation: a report of the American College of Cardiology Foundation/American Heart Association Task Force on practice guidelines. Circulation 2011; 123: e269-367.
[85]
Chiang CE, Naditch-Brule L, Murin J, et al. Distribution and risk profile of paroxysmal, persistent, and permanent atrial fibrillation in routine clinical practice: insight from the real-life global survey evaluating patients with atrial fibrillation international registry. Circ Arrhythm Electrophysiol 2012; 5: 632-639.
[86]
Cai X, Zhang Y, Li M, et al. Association between prediabetes and risk of all cause mortality and cardiovascular disease: updated meta-analysis. BMJ 2020; 370: m2297.
[87]
Guyatt GH, Oxman AD, Kunz R, et al. GRADE guidelines: 7. Rating the quality of evidence-inconsistency. J Clin Epidemiol 2011; 64: 1294-1302.
[88]
Li L, Zhang M, Holman D. Population versus hospital controls for case-control studies on cancers in Chinese hospitals. BMC Med Res Methodol 2011; 11: 167.
Year 2026 volume 23 Issue 9
PDF
12
0
Cite this Article
BibTeX
Article Info
doi: 10.26599/1671-5411.2026.09.003
  • Online Date:2026-10-30
  • Published:2026-09-28
Article Data
Affiliations
History
Funding
Satoru Kodama is financially supported by a research grant from the Suzuki Manpei International Prize for Diabetes Research. Hirohito Sone is financially supported by the Japan Agency for Medical Research and Development (AMED) (No. 25gn0110087h0002). These sponsors had no influence over the design and conduct of the study; collection, management, analysis, and interpretation of the data; or preparation, review, or approval of the manuscript.
Affiliations
    1.Department of Prevention of Noncommunicable Diseases and Promotion of Health Checkups, Niigata University Graduate School of Medical and Dental Sciences, Niigata, Japan
    2.Department of Hematology, Endocrinology and Metabolism, Niigata University Graduate School of Medical and Dental Sciences, Niigata, Japan
    3.Department of Pharmacoepidemiology, Kyoto University School of Public Health, Kyoto, Japan
    4.Department of Health and Nutrition, Faculty of Human Life Studies, University of Niigata Prefecture, Niigata, Japan
    5.Department of Nutrition, Faculty of Health Care Science, Chiba Prefectural University of Health Sciences, Chiba, Japan

Corresponding:

References
Share
https://castjournals.cast.org.cn/joweb/jgc/EN/10.26599/1671-5411.2026.09.003
Share to
QR

Scan QR to access full text

Cite this article
BibTeX
Citations
表12种不同金属材料的力学参数
科
Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)
属
Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
关闭全屏
  • BibTeX
  • EndNote
  • RefWorks
  • TxT