scholarly journals The relationship between serum asymmetric dimethylarginine levels and subjective sleep quality in normotensive patients with type 2 diabetes mellitus

2015 ◽  
Vol 30 (3) ◽  
pp. 316 ◽  
Author(s):  
Alpay Aribas ◽  
Mehmet Kayrak ◽  
Mehmet Tekinalp ◽  
Hakan Akilli ◽  
Hayrudin Alibasic ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Sleep Quality ◽  
Asymmetric Dimethylarginine ◽  
Subjective Sleep Quality ◽  
Subjective Sleep ◽  
The Relationship

scholarly journals Impact of subjective sleep quality on glycemic control in type 2 diabetes mellitus

2011 ◽  
Vol 29 (1) ◽  
pp. 30-35 ◽  
Author(s):  
Y.-W. Tsai ◽  
N.-H. Kann ◽  
T.-H. Tung ◽  
Y.-J. Chao ◽  
C.-J. Lin ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Glycemic Control ◽  
Sleep Quality ◽  
Subjective Sleep Quality ◽  
Subjective Sleep

scholarly journals Sleep Characteristics in Diabetic Patients Depending on the Occurrence of Neuropathic Pain and Related Factors

2020 ◽  
Vol 17 (21) ◽  
pp. 8125
Author(s):  
Cristina Naranjo ◽  
María Dueñas ◽  
Carlos Barrera ◽  
Guillermo Moratalla ◽  
Inmaculada Failde
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Neuropathic Pain ◽  
Sleep Quality ◽  
Depression Scale ◽  
Anxiety And Depression ◽  
Diabetic Patients ◽  
The Relationship

This study aims to compare the sleep characteristics (structure and quality) in patients with type-2 diabetes mellitus with and without diabetic neuropathic pain (DNP), and to investigate the relationship of sensory phenotypes, anxiety, and depression with sleep quality in DNP patients. A cross-sectional study was performed in patients with type-2 diabetes mellitus and neuropathy. Patients were classified into two groups—with or without neuropathic pain—according to the “Douleur Neuropathique-4 (DN4)” scale. Sleep characteristics and quality (Medical Outcomes Study—MOS-sleep), pain phenotype (Neuropathic Pain Symptom Inventory—NPSI), mood status (Hospital Anxiety and Depression scale—HADS), pain intensity (Visual Analogue Scale—VAS), and quality of life (SF-12v2) were measured. The sample included 130 patients (65 with DNP). The mean scores in all the dimensions of the MOS-sleep scale were higher (more disturbances) in the DNP patients. Higher scores in anxiety or depression, greater intensity of pain or a higher score in the paroxysmal pain phenotype were associated with lower sleep quality in DNP patients. A shorter duration of the diabetes and lower levels of glycated hemoglobin were also associated with lower sleep quality. The results show the relationship between DNP and sleep quality, and the importance of assessing sensory phenotypes and mental comorbidities in these patients. Taking these factors into consideration, to adopt a multimodal approach is necessary to achieve better clinical results.

scholarly journals Relationship Between Social Capital and Depressive Symptoms Among Type 2 Diabetes Mellitus Patients in Northwest China: A Mediating Role of Sleep Quality

2021 ◽  
Vol 12 ◽  
Author(s):  
Liqun Wang ◽  
Jiangping Li ◽  
Yuqi Dang ◽  
Haiyu Ma ◽  
Yang Niu
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Depressive Symptoms ◽  
Sleep Quality ◽  
Northwest China ◽  
Mediating Role ◽  
The Relationship

Objective: There are few studies about the relationship between social capital (SC) and depression among type 2 diabetes mellitus (T2DM) patients, and the mechanism explaining how SC leads to decreased depression is unclear. The current study aims to explore the relationship between SC and depressive symptoms among the T2DM patients in northwest China, with a particular focus on the mediating role of sleep quality.Methods: A cross-sectional study of 1,761 T2DM patients from Ningxia Province was conducted. The Center for Epidemiological Survey Depression Scale (CES-D) and self-report sleep quality questionnaire coupled with the SC scales were administered during the face-to-face survey. The Bootstrap methods PROCESS program is employed to test the mediation model.Results: The prevalence of depressive symptoms among T2DM patients was 24.8%. After controlling for covariates, the SC (r = −0.23, p < 0.001) was negatively correlated with CES-D score; the sleep quality was also negatively correlated with CES-D score (r = −0.31, p < 0.001); and the SC was positively correlated with sleep quality (r = 0.10, p < 0.001). Logistic regression analysis showed that SC was inversely related to the risk of depressive symptoms. Meanwhile, sleep quality was negatively associated with depressive symptoms. Sleep quality has mediated the relationship between SC and depressive symptoms among T2DM patients (explaining 12.6% of the total variance).Conclusions: We elucidated how SC interacted with depressive symptoms through the mediation pathway of sleep quality using a representative sample of the Chinese diabetes patients. The findings indicate that the improvement of SC and sleep quality may help in maintaining mental health among T2DM patients. Hence, clinicians can suggest that patients communicate more with others to improve the SC and, in turn, maintain their health.

scholarly journals The Relationship between the Gut Microbiome and Metformin as a Key for Treating Type 2 Diabetes Mellitus

2021 ◽  
Vol 22 (7) ◽  
pp. 3566
Author(s):  
Chae Bin Lee ◽  
Soon Uk Chae ◽  
Seong Jun Jo ◽  
Ui Min Jerng ◽  
Soo Kyung Bae
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Glucose Metabolism ◽  
Gut Microbiome ◽  
Metabolic Disorders ◽  
Current Knowledge ◽  
Potential Target ◽  
The Relationship

Metformin is the first-line pharmacotherapy for treating type 2 diabetes mellitus (T2DM); however, its mechanism of modulating glucose metabolism is elusive. Recent advances have identified the gut as a potential target of metformin. As patients with metabolic disorders exhibit dysbiosis, the gut microbiome has garnered interest as a potential target for metabolic disease. Henceforth, studies have focused on unraveling the relationship of metabolic disorders with the human gut microbiome. According to various metagenome studies, gut dysbiosis is evident in T2DM patients. Besides this, alterations in the gut microbiome were also observed in the metformin-treated T2DM patients compared to the non-treated T2DM patients. Thus, several studies on rodents have suggested potential mechanisms interacting with the gut microbiome, including regulation of glucose metabolism, an increase in short-chain fatty acids, strengthening intestinal permeability against lipopolysaccharides, modulating the immune response, and interaction with bile acids. Furthermore, human studies have demonstrated evidence substantiating the hypotheses based on rodent studies. This review discusses the current knowledge of how metformin modulates T2DM with respect to the gut microbiome and discusses the prospect of harnessing this mechanism in treating T2DM.

scholarly journals The Effect of Surrounding Greenness on Type 2 Diabetes Mellitus: A Nationwide Population-Based Cohort in Taiwan

2020 ◽  
Vol 18 (1) ◽  
pp. 267
Author(s):  
Hui-Ju Tsai ◽  
Chia-Ying Li ◽  
Wen-Chi Pan ◽  
Tsung-Chieh Yao ◽  
Huey-Jen Su ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Population Based ◽  
Research Database ◽  
Individual Level ◽  
The Relationship

This study determines whether surrounding greenness is associated with the incidence of type 2 diabetes Mellitus (T2DM) in Taiwan. A retrospective cohort study determines the relationship between surrounding greenness and the incidence of T2DM during the study period of 2001–2012 using data from the National Health Insurance Research Database. The satellite-derived normalized difference vegetation index (NDVI) from the global MODIS database in the NASA Earth Observing System is used to assess greenness. Cox proportional hazard models are used to determine the relationship between exposure to surrounding greenness and the incidence of T2DM, with adjustment for potential confounders. A total of 429,504 subjects, including 40,479 subjects who developed T2DM, were identified during the study period. There is an inverse relationship between exposure to surrounding greenness and the incidence of T2DM after adjustment for individual-level covariates, comorbidities, and the region-level covariates (adjusted HR = 0.81, 95% CI: 0.79–0.82). For the general population of Taiwan, greater exposure to surrounding greenness is associated with a lower incidence of T2DM.

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