1
|
Hjort A, Iggman D, Rosqvist F. Glycemic variability assessed using continuous glucose monitoring in individuals without diabetes and associations with cardiometabolic risk markers: A systematic review and meta-analysis. Clin Nutr 2024; 43:915-925. [PMID: 38401227 DOI: 10.1016/j.clnu.2024.02.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Revised: 02/06/2024] [Accepted: 02/13/2024] [Indexed: 02/26/2024]
Abstract
BACKGROUND & AIMS Continuous glucose monitoring (CGM) provides data on short-term glycemic variability (GV). GV is associated with adverse outcomes in individuals with diabetes. Whether GV is associated with cardiometabolic risk in individuals without diabetes is unclear. We systematically reviewed the literature to assess whether GV is associated with cardiometabolic risk markers or outcomes in individuals without diabetes. METHODS Searches were performed in PubMed/Medline, Embase and Cochrane from inception through April 2022. Two researchers were involved in study selection, data extraction and quality assessment. Studies evaluating GV using CGM for ≥24 h were included. Studies in populations with acute and/or critical illness were excluded. Both narrative synthesis and meta-analyzes were performed, depending on outcome. RESULTS Seventy-one studies were included; the majority were cross-sectional. Multiple measures of GV are higher in individuals with compared to without prediabetes and GV appears to be inversely associated with beta cell function. In contrast, GV is not clearly associated with insulin sensitivity, fatty liver disease, adiposity, blood lipids, blood pressure or oxidative stress. However, GV may be positively associated with the degree of atherosclerosis and cardiovascular events in individuals with coronary disease. CONCLUSION GV is elevated in prediabetes, potentially related to beta cell dysfunction, but less clearly associated with obesity or traditional risk factors. GV is associated with coronary atherosclerosis development and may predict cardiovascular events and type 2 diabetes. Prospective studies are warranted, investigating the predictive power of GV in relation to incident disease. GV may be an important risk measure also in individuals without diabetes.
Collapse
Affiliation(s)
- Anna Hjort
- Department of Biology and Biological Engineering, Division of Food and Nutrition Science, Chalmers University of Technology, Kemivägen 10, 41296 Gothenburg, Sweden.
| | - David Iggman
- Center for Clinical Research Dalarna, Uppsala University, Nissers väg 3, 79182 Falun, Sweden; Department of Public Health and Caring Sciences, Clinical Nutrition and Metabolism, Uppsala University, Husargatan 3, BMC, Box 564, 75122 Uppsala, Sweden.
| | - Fredrik Rosqvist
- Department of Public Health and Caring Sciences, Clinical Nutrition and Metabolism, Uppsala University, Husargatan 3, BMC, Box 564, 75122 Uppsala, Sweden.
| |
Collapse
|
2
|
Wen X, Yang H, Yang M, Tao W, Chen J, Zhao S, Yin M, Zhou X, Yang Y, Li Y. Factors that determine glucose variability, defined by the coefficient of variation in continuous glucose monitoring values, in a Chinese population with type 2 diabetes. Diabetes Obes Metab 2024; 26:611-621. [PMID: 37953677 DOI: 10.1111/dom.15350] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Revised: 10/11/2023] [Accepted: 10/13/2023] [Indexed: 11/14/2023]
Abstract
AIMS To elucidate the clinical determinants of the coefficient of variation (CV) of glucose by analysing the pancreatic β-cell function of subjects with type 2 diabetes mellitus (T2DM). METHODS A total of 716 Chinese subjects with T2DM were included. Continuous glucose monitoring (CGM) was used to assess blood glucose, and the CV was calculated. C-peptide concentration at 0, 0.5, 1, 2 and 3 hours (Cp0h, Cp0.5h, Cp1h, Cp2h and Cp3h, respectively) was measured after a standard 100-g steamed bun meal test to assess pancreatic β-cell function. The determinants of glucose variability defined by the CV of CGM values were explored from two perspectives: the CV of qualitative variables and the CV of quantitative variables. RESULTS Our data revealed that C-peptide concentration (Cp0h, Cp0.5h, Cp1h, Cp2h, Cp3h), area under the curve for C-peptide concentration at 0.5 and 3 hours (AUC-Cp0.5h and AUC-Cp3h) decreased with increasing CV quartile (P < 0.05). The CV was negatively correlated with homeostatic model assessment of β-cell function index, C-peptide concentration at all timepoints, and AUC-Cp0.5h and AUC-Cp3h (P < 0.001). Quantile regression analysis showed that AUC-Cp0.5h had an overall negative effect on the CV in the 0.05 to 0.95 quartiles, and AUC-Cp3h tended to have a negative effect on the CV in the 0.2 to 0.65 quartiles. After adjusting for confounders, multinomial logistic regression showed that each 1-unit increase in AUC-Cp0.5h was associated with a 31.7% reduction in the risk of unstable glucose homeostasis (CV > 36%; P = 0.036; odds ratio 0.683; 95% confidence interval 0.478-0.976). We also identified the AUC-Cp0.5h (0.735 ng/mL) and AUC-Cp3h (13.355 ng/mL) cut-off values for predicting unstable glucose homeostasis (CV >36%) in T2DM subjects. CONCLUSION Our study suggests that impaired pancreatic β-cell function may be a clinical determining factor of CV of glucose in people with T2DM.
Collapse
Affiliation(s)
- Xi Wen
- Department of Endocrinology, The Affiliated Hospital of Yunnan University and The Second People's Hospital of Yunnan Province, Kunming, China
- Dali University, Dali, China
| | - Huijun Yang
- Department of Endocrinology, The Affiliated Hospital of Yunnan University and The Second People's Hospital of Yunnan Province, Kunming, China
| | - Man Yang
- Department of Endocrinology, The Affiliated Hospital of Yunnan University and The Second People's Hospital of Yunnan Province, Kunming, China
| | - Wenyu Tao
- Department of Endocrinology, The Affiliated Hospital of Yunnan University and The Second People's Hospital of Yunnan Province, Kunming, China
| | - Jiaoli Chen
- Department of Endocrinology, The Affiliated Hospital of Yunnan University and The Second People's Hospital of Yunnan Province, Kunming, China
| | - Shanshan Zhao
- Department of Endocrinology, The Affiliated Hospital of Yunnan University and The Second People's Hospital of Yunnan Province, Kunming, China
| | - Mingliu Yin
- Department of Endocrinology, The Affiliated Hospital of Yunnan University and The Second People's Hospital of Yunnan Province, Kunming, China
- Dali University, Dali, China
| | - Xing Zhou
- Department of Endocrinology, The Affiliated Hospital of Yunnan University and The Second People's Hospital of Yunnan Province, Kunming, China
- Kunming Medical University, Kunming, China
| | - Ying Yang
- Department of Endocrinology, The Affiliated Hospital of Yunnan University and The Second People's Hospital of Yunnan Province, Kunming, China
| | - Yiping Li
- Department of Endocrinology, The Affiliated Hospital of Yunnan University and The Second People's Hospital of Yunnan Province, Kunming, China
| |
Collapse
|
3
|
Zhao G, Yu X, Wang L, Jin Y, Yang A, Sun F, Wang X, Jing X, Gao B. Serum 25-hydroxyvitamin D level is associated with short-term glycemic variability metrics derived from continuous glucose monitoring in T2DM. Sci Rep 2023; 13:18463. [PMID: 37891255 PMCID: PMC10611772 DOI: 10.1038/s41598-023-45846-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Accepted: 10/24/2023] [Indexed: 10/29/2023] Open
Abstract
This study aims to investigate the association between 25-hydroxyvitamin D (25OHD) and continuous glucose monitoring-assessed short-term glycemic variability (GV) and HbA1c among patients with type 2 diabetes mellitus (T2DM). We conducted a cross-sectional study recruiting 325 patients. The association between 25OHD and GV metrics (mean amplitude of glycemic excursions [MAGE], coefficient of variation [CV], standard deviation of sensor glucose [SD], and TIR) and HbA1c were analyzed using multivariable linear and logistic regression analyses. The 25OHD level and GV metrics showed significant differences among HbA1c groups (P < 0.01). CV, MAGE, SD and HbA1c decreased, and TIR increased with ascending 25OHD tertiles (P < 0.05). Serum 25OHD was inversely associated with CV (β = - 0.211 [- 0.350 to - 0.071], P < 0.01) and HbA1c (β = - 0.061 [- 0.114 to - 0.031], P < 0.01), and further multivariable analyses confirmed these results (P < 0.05). However, no association of HbA1c and 25OHD was found with the highest tertile of CV. These findings revealed that increased GV and HbA1c were both associated with lower 25OHD, and the relationship between HbA1c and 25OHD was attenuated with higher glucose CV in T2DM. Taken together, the analyses suggest that increasing vitamin D status has effects on improvements in long-term glycemic control and low glycemic variability.
Collapse
Affiliation(s)
- Guohong Zhao
- Department of Endocrinology, Tangdu Hospital, Air Force Medical University, Xi'an, 710038, Shaanxi Province, People's Republic of China
| | - Xinwen Yu
- Department of Endocrinology, Tangdu Hospital, Air Force Medical University, Xi'an, 710038, Shaanxi Province, People's Republic of China
| | - Lin Wang
- College of Medicine, Xi'an International University, Xi'an, 710077, Shaanxi Province, People's Republic of China
- Engineering Research Center of Personalized Anti-Aging Health Product Development and Transformation, Universities of Shaanxi Province, Xi'an, 710077, Shaanxi Province, People's Republic of China
| | - Yuxin Jin
- Department of Endocrinology, Tangdu Hospital, Air Force Medical University, Xi'an, 710038, Shaanxi Province, People's Republic of China
| | - Aili Yang
- Department of Endocrinology, Tangdu Hospital, Air Force Medical University, Xi'an, 710038, Shaanxi Province, People's Republic of China
| | - Fei Sun
- Department of Endocrinology, Tangdu Hospital, Air Force Medical University, Xi'an, 710038, Shaanxi Province, People's Republic of China
| | - Xin Wang
- Department of Endocrinology, Tangdu Hospital, Air Force Medical University, Xi'an, 710038, Shaanxi Province, People's Republic of China
| | - Xiaorui Jing
- Department of Endocrinology, Tangdu Hospital, Air Force Medical University, Xi'an, 710038, Shaanxi Province, People's Republic of China
| | - Bin Gao
- Department of Endocrinology, Tangdu Hospital, Air Force Medical University, Xi'an, 710038, Shaanxi Province, People's Republic of China.
| |
Collapse
|
4
|
Li C, Guo J, Zhao Y, Sun K, Abdelrahman Z, Cao X, Zhang J, Zheng Z, Yuan C, Huang H, Chen Y, Liu Z, Chen Z. Visit-to-visit HbA1c variability, dementia, and hippocampal atrophy among adults without diabetes. Exp Gerontol 2023; 178:112225. [PMID: 37263368 DOI: 10.1016/j.exger.2023.112225] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Revised: 05/13/2023] [Accepted: 05/26/2023] [Indexed: 06/03/2023]
Abstract
OBJECTIVES Adults without diabetes are not completely healthy; they are probably heterogeneous with several potential health problems. The management of hemoglobin A1c (HbA1c) is crucial among patients with diabetes; but whether similar management strategy is needed for adults without diabetes is unclear. Thus, this study aimed to investigate the associations of visit-to-visit HbA1c variability with incident dementia and hippocampal volume among middle-aged and older adults without diabetes, providing potential insights into this question. METHODS We conducted a prospective analysis for incident dementia in 10,792 participants (mean age 58.9 years, 47.8 % men) from the UK Biobank. A subgroup of 3793 participants (mean age 57.8 years, 48.6 % men) was included in the analysis for hippocampal volume. We defined HbA1c variability as the difference in HbA1c divided by the mean HbA1c over the 2 sequential visits ([latter - former]/mean). Dementia was identified using hospital inpatient records with ICD-9 codes. T1-structural brain magnetic resonance imaging was conducted to derive hippocampal volume (normalized for head size). The nonlinear and linear associations were examined using restricted cubic spline (RCS) models, Cox regression models, and multiple linear regression models. RESULTS During a mean follow-up (since the second round) of 8.4 years, 90 (0.8 %) participants developed dementia. The RCS models suggested no significant nonlinear associations of HbA1c variability with incident dementia and hippocampal volume, respectively (All P > 0.05). Above an optimal cutoff of HbA1c variability at 0.08, high HbA1c variability (increment in HbA1c) was associated with an increased risk of dementia (Hazard Ratio, 1.88; 95 % Confidence Interval, 1.13 to 3.14, P = 0.015), and lower hippocampal volume (coefficient, -96.84 mm3, P = 0.037), respectively, in models with adjustment of covariates including age, sex, etc. Similar results were found for a different cut-off of 0. A series of sensitivity analyses verified the robustness of the findings. CONCLUSIONS Among middle-aged and older adults without diabetes, increasing visit-to-visit HbA1c variability was associated with an increased dementia risk and lower hippocampal volume. The findings highlight the importance of monitoring and controlling HbA1c fluctuation in apparently healthy adults without diabetes.
Collapse
Affiliation(s)
- Chenxi Li
- School of Public Health, The Second Affiliated Hospital, The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou 310058, Zhejiang, China
| | - Junyan Guo
- School of Public Health, The Second Affiliated Hospital, The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou 310058, Zhejiang, China
| | - Yining Zhao
- School of Public Health, The Second Affiliated Hospital, The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou 310058, Zhejiang, China
| | - Kaili Sun
- School of Public Health, The Second Affiliated Hospital, The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou 310058, Zhejiang, China
| | - Zeinab Abdelrahman
- Department of Neurobiology, Department of Orthopedics, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310009, Zhejiang, China; NHC and CAMS Key Laboratory of Medical Neurobiology, MOE Frontier Science Center for Brain Research and Brain-Machine Integration, School of Brain Science and Brain Medicine, Zhejiang University, Hangzhou 310058, Zhejiang, China; Department of Rehabilitation Medicine, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, Zhejiang, China
| | - Xingqi Cao
- School of Public Health, The Second Affiliated Hospital, The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou 310058, Zhejiang, China
| | - Jingyun Zhang
- School of Public Health, The Second Affiliated Hospital, The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou 310058, Zhejiang, China
| | - Zhoutao Zheng
- School of Public Health, The Second Affiliated Hospital, The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou 310058, Zhejiang, China
| | - Changzheng Yuan
- Department of Big Data in Health Science School of Public Health, The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou 310058, Zhejiang, China
| | - Huiqian Huang
- Clinical Research Center, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310009, Zhejiang, China
| | - Yaojing Chen
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
| | - Zuyun Liu
- School of Public Health, The Second Affiliated Hospital, The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou 310058, Zhejiang, China.
| | - Zuobing Chen
- Department of Rehabilitation Medicine, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, Zhejiang, China.
| |
Collapse
|