1
|
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.
Collapse
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
| |
Collapse
|
2
|
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.
Collapse
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
| |
Collapse
|
3
|
Wu TE, Su YW, Chen HS. Mean HbA1c and HbA1c variability are associated with differing diabetes-related complications in patients with type 2 diabetes mellitus. Diabetes Res Clin Pract 2022; 192:110069. [PMID: 36067915 DOI: 10.1016/j.diabres.2022.110069] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/03/2022] [Revised: 08/18/2022] [Accepted: 08/31/2022] [Indexed: 11/03/2022]
Abstract
AIMS To study the different effects of mean HbA1c and HbA1c variability on diabetes-related complications in patients with type 2 diabetes mellitus. METHODS 1869 patients with type 2 diabetes were followed-up for a median of 9.5 years in a Diabetes Shared Care Program. Mean HbA1c (HbA1c-mean) and standard deviation of HbA1c (HbA1c-SD) were calculated during the first 5 years. The clinical outcomes included nephropathy (urine albumin-to-creatinine ratio [UACR] > 300 mg/g and doubling of serum creatinine), retinopathy (any and advanced), and mortality (due to all-causes, and cardiovascular disease [CVD]). RESULTS HbA1c-mean was independently associated with UACR > 300 mg/g (Hazard ratio [HR] 1.308 [95% confidence interval {CI}, 1.194-1.433]), any retinopathy (HR 1.274 [1.171-1.385]), and advanced retinopathy (HR 1.237 [1.014-1.509]). HbA1c-SD was independently associated with UACR > 300 mg/g (HR 1.478 [1.189-1.837]), doubling of serum creatinine (HR 2.133 [1.470-3.095]), all-cause mortality (HR 1.880 [1.561-2.266]), and CVD mortality (HR 1.431 [1.069-1.915]). Receiver operating characteristic (ROC) curves showed HbA1c-mean was more associated with any retinopathy, whereas HbA1c-SD was more associated with doubling of serum creatinine, all-cause and CVD mortality. CONCLUSION Both HbA1c-mean and HbA1c-SD predicted most diabetes-related complications in patients with type 2 diabetes. However, HbA1c-mean was more effective at predicting retinopathy, while HbA1c-SD was more effective at predicting deterioration of renal function and increased mortality.
Collapse
Affiliation(s)
- Tzu-En Wu
- Department of Ophthalmology, Shin-Kong Wu Ho-Su Memorial Hospital, Taipei, Taiwan
| | - Yu-Wen Su
- Division of Endocrinology and Metabolism, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan; School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Harn-Shen Chen
- Division of Endocrinology and Metabolism, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan; School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan.
| |
Collapse
|
4
|
Wang T, Zhang X, Liu J. Long-Term Glycemic Variability and Risk of Cardiovascular Events in Type 2 Diabetes: A Meta-Analysis. Horm Metab Res 2022; 54:84-93. [PMID: 35130569 DOI: 10.1055/a-1730-5029] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Long-term glycemic fluctuation has been associated with cardiovascular risk in patients with type 2 diabetes mellitus (T2DM). However, the findings are inconsistent. We performed a meta-analysis to summarize the association between parameters of long-term glycemic variability and risk of cardiovascular events in T2DM patients. Medline, Embase, and Web of Science databases were searched for longitudinal follow-up studies comparing the incidence of cardiovascular events in T2DM patients with higher or lower long-term glycemic variability. A random-effect model incorporating the potential heterogeneity among the included studies was used to pool the results. Twelve follow-up studies with 146 653 T2DM patients were included. The mean follow-up duration was 4.9 years. Pooled results showed that compared to those with the lowest glycemic variability, patients with the highest glycemic variability had significantly increased risk of cardiovascular events, as evidenced by the standard deviation of glycated hemoglobin [HbA1c-SD: relative risk (RR)=1.44, 95% confidence interval (CI): 1.23 to 1.69, p<0.001; I2=70%], HbA1c coefficient of variation (HbA1c-CV: RR=1.46, 95% CI: 1.19 to 1.79. p<0.001; I2=83%), standard deviation of fasting plasma glucose (FPG-SD: RR=1.33, 95% CI: 1.07 to 1.65, p=0.009; I2=0%), and FPG coefficient of variation (FPG-CV: RR=1.29, 95% CI: 1.01 to 1.64, p=0.04; I2=47%). In conclusion, increased long-term glycemic variability may be an independent risk factor for cardiovascular events in T2DM patients.
Collapse
Affiliation(s)
- Ting Wang
- Department of Medical Administration, The First Hospital of Hunan University of Chinese Medicine, Changsha, China
| | - Xin Zhang
- Department of Gastroenterology, The Fourth Hospital of Changsha, Changsha, China
| | - Jian Liu
- Department of Emergency, The First Hospital of Hunan University of Chinese Medicine, Changsha, China
| |
Collapse
|
5
|
Ceriello A, Lucisano G, Prattichizzo F, La Grotta R, Franzén S, Svensson AM, Eliasson B, Nicolucci A. HbA1c variability predicts cardiovascular complications in type 2 diabetes regardless of being at glycemic target. Cardiovasc Diabetol 2022; 21:13. [PMID: 35073913 PMCID: PMC8788128 DOI: 10.1186/s12933-022-01445-4] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Accepted: 12/28/2021] [Indexed: 01/09/2023] Open
Abstract
Background HbA1c variability has emerged as risk factor for cardiovascular diseases in diabetes. However, the impact of HbA1c variability on cardiovascular diseases in subjects within the recommended HbA1c target has been relatively unexplored. Methods Using data from a large database, we studied 101,533 people with type 2 diabetes without cardiovascular diseases. HbA1c variability was expressed as quartiles of the standard deviation of HbA1c during three years (exposure phase). The primary composite outcome included non-fatal myocardial infarction, non-fatal stroke, all-cause mortality and was assessed during five years following the first three years of exposure to HbA1c variability (longitudinal phase). An expanded composite outcome including non-fatal myocardial infarction, non-fatal stroke, coronary revascularization/reperfusion procedures, peripheral revascularization procedures, and all-cause mortality was also considered, as well as a series of specific cardiovascular complications. Cox models were adjusted for a large range of risk factors and results were expressed as adjusted hazard ratios. Results An association between HbA1c variability and all the outcomes considered was found. The correlation between HbA1c variability and cardiovascular complications development was confirmed in both the subgroups of subjects with a mean HbA1c ≤ 53 mmol/mol (recommended HbA1c target) or > 53 mmol/mol during the exposure phase. The risk related to HbA1c variability was higher in people with mean HbA1c ≤ 53 mmol/mol for the primary outcome (p for interaction 0.004), for the expanded secondary outcome (p for interaction 0.001) and for the stroke (p for interaction 0.001), even though HbA1c remained at the target during the follow-up. Conclusions These findings suggest that HbA1c variability may provide additional information for an optimized management of diabetes, particularly in people within the target of HbA1c. Supplementary Information The online version contains supplementary material available at 10.1186/s12933-022-01445-4.
Collapse
|
6
|
Ren X, Wang Z, Guo C. Long-term glycemic variability and risk of stroke in patients with diabetes: a meta-analysis. Diabetol Metab Syndr 2022; 14:6. [PMID: 35022087 PMCID: PMC8756678 DOI: 10.1186/s13098-021-00770-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/22/2021] [Accepted: 12/15/2021] [Indexed: 12/12/2022] Open
Abstract
OBJECTIVES Long-term glycemic variability has been related to increased risk of vascular complication in patients with diabetes. However, the association between parameters of long-term glycemic variability and risk of stroke remains not fully determined. We performed a meta-analysis to systematically evaluate the above association. METHODS Medline, Embase, and Web of Science databases were searched for longitudinal follow-up studies comparing the incidence of stroke in diabetic patients with higher or lower long-term glycemic variability. A random-effect model incorporating the potential heterogeneity among the included studies were used to pool the results. RESULTS Seven follow-up studies with 725,784 diabetic patients were included, and 98% of them were with type 2 diabetes mellitus (T2DM). The mean follow-up duration was 7.7 years. Pooled results showed that compared to those with lowest category of glycemic variability, diabetic patients with the highest patients had significantly increased risk of stroke, as evidenced by glycemic variability analyzed by fasting plasma glucose coefficient of variation (FPG-CV: risk ratio [RR] = 1.24, 95% confidence interval [CI] 1.11 to 1.39, P < 0.001; I2 = 53%), standard deviation of FPG (FPG-SD: RR = 1.16, 95% CI 1.02 to 1.31, P = 0.02; I2 = 74%), HbA1c coefficient of variation (HbA1c-CV: RR = 1.88, 95% CI 1.61 to 2.19 P < 0.001; I2 = 0%), and standard deviation of HbA1c (HbA1c-SD: RR = 1.73, 95% CI 1.49 to 2.00, P < 0.001; I2 = 0%). CONCLUSIONS Long-term glycemic variability is associated with higher risk of stroke in T2DM patients.
Collapse
Affiliation(s)
- Xiaoli Ren
- Neurology Department, Tianjin First Central Hospital, 24 Fukang Road, Nankai District, Tianjin, 300192, China
| | - Zhiyun Wang
- Neurology Department, Tianjin First Central Hospital, 24 Fukang Road, Nankai District, Tianjin, 300192, China.
| | - Congfang Guo
- Health Management Center, Tianjin First Central Hospital, Tianjin, China
| |
Collapse
|
7
|
Park MJ, Choi KM. Association between Variability of Metabolic Risk Factors and Cardiometabolic Outcomes. Diabetes Metab J 2022; 46:49-62. [PMID: 35135078 PMCID: PMC8831817 DOI: 10.4093/dmj.2021.0316] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Accepted: 12/07/2021] [Indexed: 11/10/2022] Open
Abstract
Despite strenuous efforts to reduce cardiovascular disease (CVD) risk by improving cardiometabolic risk factors, such as glucose and cholesterol levels, and blood pressure, there is still residual risk even in patients reaching treatment targets. Recently, researchers have begun to focus on the variability of metabolic variables to remove residual risks. Several clinical trials and cohort studies have reported a relationship between the variability of metabolic parameters and CVDs. Herein, we review the literature regarding the effect of metabolic factor variability and CVD risk, and describe possible mechanisms and potential treatment perspectives for reducing cardiometabolic risk factor variability.
Collapse
Affiliation(s)
- Min Jeong Park
- Division of Endocrinology & Metabolism, Department of Internal Medicine, Korea University College of Medicine, Seoul, Korea
| | - Kyung Mook Choi
- Division of Endocrinology & Metabolism, Department of Internal Medicine, Korea University College of Medicine, Seoul, Korea
- Corresponding author: Kyung Mook Choi https://orcid.org/0000-0001-6175-0225 Division of Endocrinology & Metabolism, Department of Internal Medicine, Korea University Guro Hospital, Korea University College of Medicine, 148 Gurodong-ro, Guro-gu, Seoul 08308, Korea E-mail:
| |
Collapse
|
8
|
Jeon JY, Kim DJ. Cardiovascular disease in patients with type 2 diabetes. J Diabetes Investig 2021; 13:614-616. [PMID: 34953095 PMCID: PMC9017622 DOI: 10.1111/jdi.13742] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/28/2021] [Revised: 12/22/2021] [Accepted: 12/22/2021] [Indexed: 12/03/2022] Open
Affiliation(s)
- Ja Young Jeon
- Department of Endocrinology and Metabolism, Ajou University School of Medicine, Suwon, Republic of Korea
| | - Dae Jung Kim
- Department of Endocrinology and Metabolism, Ajou University School of Medicine, Suwon, Republic of Korea
| |
Collapse
|