Wu CC, Sun WH, Yang QQ, Xue L, Zhao WD. Anxiety-depression comorbidity prevalence in type 2 diabetes mellitus and correlation with insulin resistance. World J Psychiatry 2026; 16(9): 119917 [DOI: 10.5498/wjp.119917]
Corresponding Author of This Article
Wen-Di Zhao, MM, Department of Endocrine and Metabolic Diseases, The First Affiliated Hospital of Bengbu Medical University, No. 287 Changhuai Road, Longzihu District, Bengbu 233030, Anhui Province, China. wendy1071@163.com
Research Domain of This Article
Psychology
Article-Type of This Article
research-article
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA
Share the Article
Wu CC, Sun WH, Yang QQ, Xue L, Zhao WD. Anxiety-depression comorbidity prevalence in type 2 diabetes mellitus and correlation with insulin resistance. World J Psychiatry 2026; 16(9): 119917 [DOI: 10.5498/wjp.119917]
Chen-Chen Wu, Wei-Hua Sun, Qing-Qing Yang, Li Xue, Wen-Di Zhao, Department of Endocrine and Metabolic Diseases, The First Affiliated Hospital of Bengbu Medical University, Bengbu 233030, Anhui Province, China
Author contributions: Wu CC designed the research and wrote the first manuscript; Wu CC, Sun WH, Yang QQ, Xue L, and Zhao WD contributed to conceiving the research and analyzing data; Wu CC and Zhao WD conducted the analysis and provided guidance for the research; and all authors reviewed and approved the final manuscript.
AI contribution statement: We have never used AI tools in writing and editing this article.
Institutional review board statement: This study was approved by the Ethic Committee of the First Affiliated Hospital of Bengbu Medical University.
Informed consent statement: Patients were not required to give informed consent to the study because the analysis used anonymous clinical data that were obtained after each patient agreed to treatment by written consent.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
STROBE statement: The authors have read the STROBE Statement-checklist of items, and the manuscript was prepared and revised according to the STROBE Statement-checklist of items.
Data sharing statement: No additional data are available.
Corresponding author: Wen-Di Zhao, MM, Department of Endocrine and Metabolic Diseases, The First Affiliated Hospital of Bengbu Medical University, No. 287 Changhuai Road, Longzihu District, Bengbu 233030, Anhui Province, China. wendy1071@163.com
Received: April 14, 2026 Revised: May 14, 2026 Accepted: June 10, 2026 Published online: September 19, 2026 Processing time: 131 Days and 22.1 Hours
Abstract
BACKGROUND
Patients with type 2 diabetes mellitus (T2DM) are prone to psychological symptoms such as anxiety, depression, or their comorbidity. Adverse mood can induce greater insulin resistance (IR), thereby negatively affecting T2DM development and prognosis.
AIM
To analyze anxiety-depression comorbidity status in T2DM and correlate it with IR.
METHODS
Using convenience sampling, this study enrolled eligible T2DM patients visiting The First Affiliated Hospital of Bengbu Medical University (January 2024 to June 2025). Demographic and clinical information were collected using a basic information questionnaire, and psychological symptoms were assessed using the Hamilton Anxiety Scale and Hamilton Depression Scale. Patients were categorized into T2DM, T2DM + anxiety, T2DM + depression, and T2DM + anxiety-depression groups according to anxiety and depression scores. Blood glucose and lipid levels, as well as islet function, were compared among groups. IR-associated factors in patients with T2DM with comorbid depression and anxiety were explored using logistic regression analysis.
RESULTS
Among the 197 patients with T2DM, 20.3% had neither anxiety nor depression, 29.4% had anxiety, 26.4% had depression, and 23.9% had both symptoms. Glycosylated hemoglobin, fasting plasma glucose, and 2-hour postprandial glucose levels differed significantly among groups (P < 0.05), with the highest levels observed in the T2DM + anxiety-depression group (P < 0.05). Additionally, patients with T2DM complicated by psychological symptoms showed significantly increased in triglyceride and low-density lipoprotein cholesterol levels and decreased total cholesterol and high-density lipoprotein cholesterol levels compared with patients without psychological symptoms (P < 0.05). The highest fasting insulin and fasting C-peptide levels were observed in the T2DM + anxiety-depression group (P < 0.05), while no significant differences in fasting C-peptide levels were found among the T2DM + anxiety, T2DM + depression, and T2DM + anxiety-depression groups (P > 0.05). Compared with the other groups, the T2DM + anxiety-depression group exhibited higher Homeostasis Model Assessment of IR and lower Homeostasis Model Assessment of insulin sensitivity levels (P < 0.05). Anxiety-depression comorbidity increased the risk of IR in patients with T2DM.
CONCLUSION
Anxiety and depression are prevalent among patients with T2DM, and some individuals develop comorbid conditions. Patients with anxiety-depression comorbidity exhibit relatively severe IR. Anxiety-depression comorbidity is an independent predictor of IR in T2DM.
Core Tip: This study highlights the substantial clinical burden of psychological symptoms in patients with type 2 diabetes mellitus, emphasizing that comorbid anxiety and depression are significantly associated with aggravated metabolic dysfunction. Those with concurrent anxiety and depression had worse glycemic control and greater lipid disturbances than individuals with either or no psychological symptoms. Notably, this comorbidity could independently predict severe insulin resistance, a condition featuring Homeostasis Model Assessment of insulin resistance elevation and Homeostasis Model Assessment of insulin sensitivity reduction. These findings suggest an amplified adverse effect of anxiety-depression comorbidity on insulin sensitivity, underscoring the urgency and necessity of metabolic-mental health integrated screening strategies to improve overall outcomes for type 2 diabetes mellitus patients.
Citation: Wu CC, Sun WH, Yang QQ, Xue L, Zhao WD. Anxiety-depression comorbidity prevalence in type 2 diabetes mellitus and correlation with insulin resistance. World J Psychiatry 2026; 16(9): 119917
In parallel with intensified population aging and lifestyle changes, diabetes mellitus (DM) has rapidly become a disease with extensive health impacts in the 21st century, representing a major global public health issue[1]. Being a metabolic disorder, it features insulin secretion insufficiency and insulin resistance (IR)-induced hyperglycemia[2]. Among its subtypes, type 2 DM (T2DM) is the most common. Its pathogenesis is related to the pancreas’s inability to produce sufficient insulin or the body’s inability to effectively utilize the generated insulin[3]. T2DM, a life-long disease, has no definitive cure presently. Due to seriously disrupted normal life rhythms by long-term dietary control, blood glucose (BG) monitoring, and insulin therapy, elderly T2DM patients are prone to anxiety, depression, and other adverse moods that substantially reduce their quality of life[4]. As emotional disorders, anxiety and depression mainly show in the form of low mood, grief, and slowed cognitive processing. Over time, patients are highly likely to develop a resistant mentality that hinders their adherence to follow-up interventions and impairs disease control[5].
T2DM shows a close and positive correlation with emotional dysregulation like anxiety and depression[6]. Previous international studies have reported a two-fold higher possibility of depression development in diabetics compared to non-diabetic individuals, with an anxiety disorder prevalence exceeding 20%[7,8]. This could be attributed to socioeconomic and personal factors, including lifestyle changes due to the need for long-term BG monitoring and insulin injections, additional medication expenses, and excessive concerns regarding complications and lifelong treatment[9]. Anxiety and depression, when present concurrently, exert a more severe impact on disease control than either condition alone in T2DM patients. IR is actually the “sluggish response” of the body’s cells to insulin[10]. Insulin, an essential pancreas-derived hormone, is responsible for transporting glucose in the blood into cells for energy production or storage[11]. When IR occurs, cells fail to effectively absorb glucose despite adequate insulin, resulting in BG accumulation that may eventually cause T2DM. IR, found in approximately 90% of T2DM patients, is considered a primary contributor to T2DM onset[12]. Therefore, ameliorating IR levels is key for slowing disease progression and reducing complications in patients with T2DM. Previous research has shown poorer glycemic control in patients with T2DM complicated by depression and/or anxiety compared with uncomplicated diabetics. However, whether anxiety-depression comorbidity is associated with more severe glycemic dysregulation and IR remains unclear. Therefore, this study investigated the status of anxiety-depression comorbidity in patients with T2DM and explored the effects of anxiety and depression on IR and related parameters, aiming at provide evidence for clinical management and intervention strategies to improve patient prognosis.
MATERIALS AND METHODS
Research participants
Using a convenience sampling method, eligible patients with T2DM visiting The First Affiliated Hospital of Bengbu Medical University between January 2024 and June 2025 were enrolled. Eligibility criteria were as follows: (1) Diagnosis of T2DM according to the World Health Organization criteria, including fasting plasma glucose (FPG) ≥ 7 mmol/L, 2-hour post-oral glucose tolerance test BG ≥ 11.1 mmol/L, and glycosylated hemoglobin (HbA1c) ≥ 6.5%; (2) Adults aged ≥ 18 years with a DM duration ≥ 3 months; and (3) Normal cognitive and intellectual function with adequate reading and communication abilities. Ineligibility criteria were as follows: (1) Type 1 DM or other types of DM; (2) Use of hormone drugs or immunomodulators within the previous three months; (3) Thyroid dysfunction or pituitary/adrenal diseases; (4) Previous or ongoing anti-anxiety or antidepressant treatment; (5) Insulin therapy; (6) Pregnancy or postpartum status; (7) Severe DM-induced complications; and (8) Sever cardiac, hepatic, or renal dysfunction.
Investigation tools
Socio-demographic and clinical data survey: Patients’ sex, age, body mass index, DM duration, family history of DM, educational level, and marital status were collected through electronic medical records and self-designed questionnaires.
Laboratory indicators: Patients were asked to have light or low-fat diets three days preceding blood sampling, with alcohol strictly prohibited within 24 hours before blood collection, and strenuous exercises avoided. After an 8-hour fasting period, patients underwent a venipuncture for blood sampling from the elbow vein at 8:00 a.m. the following morning. Laboratory indicators included parameters associated with lipid metabolism, glycemic control, and IR, namely total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), FPG, 2-hour postprandial blood glucose (2hPG), HbA1c, fasting insulin (FINS), and fasting C-peptide (FCP).
Anxiety and depression evaluation: Anxiety was assessed using the Hamilton Anxiety Scale (HAMA), a 14-item observer-rated scale in which each item is scored from 0 to 4 (0 = asymptomatic; 4 = extremely severe), with higher scores indicating greater anxiety severity. The scoring criteria were as follows: ≥ 29, possible severe anxiety; ≥ 21, definite obvious anxiety; ≥ 14, definite anxiety; ≥ 7, possible anxiety; and < 7, no anxiety. Depression was assessed using the Hamilton Depression Scale (HAMD), a 7-item observer-rated scale. Items 1 to 9 were scored on a 5-point scale (0: None; 1: Mild; 2: Moderate; 3: Severe; 4: Extremely severe), whereas items 10-17 were scored on a 3-point scale (0: None; 1: Mild-to-moderate; 2: Severe). Based on total HAMD scores, patients were categorized as having no depression (< 8), possible depression (8-20), definite depression (20-35), or severe depression (> 35). This study used the thresholds for definite anxiety and depression, namely HAMA ≥ 14 and HAMD ≥ 20, to classify the participants into non-anxiety/depression, anxiety, depression, and anxiety-depression groups for subsequent analyses.
Homeostasis Model Assessment: Homeostasis Model Assessment (HOMA) was used to evaluate β-cell function (HOMA-β), IR index (HOMA-IR), and insulin sensitivity index (HOMA-IS). The formulas were as follows: HOMA-β (%) = 20 × FINS/(FPG - 3.5); HOMA-IR = FINS × FPG/22.5; HOMA-IS = 1/HOMA-IR.
Investigation methods and quality control
The questionnaire survey was conducted by postgraduate students from our college who served as investigators. Before the survey, all investigators underwent unified training regarding the study purpose, significance, major research content, and questionnaire administration procedures. Before the formal research was launched, professional psychologists conducted scale (HAMD/HAMA) interpretation for the investigators, guided them to maintain objectivity and avoid leading questions during the assessment process, and instructed them on communication skills with patients. To ensure inter-rater consistency, we implemented a trial evaluation process first. All investigators achieved high-level agreement on assessment criteria. Throughout the research process, the same evaluation team was used, effectively reducing longitudinal variabilities in scoring.
After face-to-face interviews, an immediate questionnaire recovery was conducted to check for completeness. Patients were asked to supplement omitted items promptly if found to improve questionnaire validity. Laboratory results were acquired via medical record review, with all data checked and recorded independently by two researchers. Questionnaire validity was re-checked before data entry, with double entry further employed to ensure data accuracy.
Statistical analysis
The events per variable principle was used for sample size determination. Considering the inclusion of five independent variables in multivariable logistic regression and the 10-15 events per variable rule, at least 50-75 IR cases were required. 116 IR cases were identified in our cohort (n = 197), meeting the minimum sample threshold requirement for model stability.
A Microsoft Excel-based database was established, with double independent data entry adopted and data verification conducted. SPSS 25.0 was used to analyze the data collected. This study used the χ2 test to compare counting data [shown as n (%)]. Measurement data are presented as mean ± SD. Independent sample t-tests and rank-sum tests were used for between-group comparisons, whereas one-way ANOVA with Turkey’s post-hoc test were used for multi-group comparisons. Logistic regression analysis was performed to identify the influencing factors associated with IR. A significance level of α = 0.05 was applied, with P < 0.05 considered statistically significant.
RESULTS
Patient demographic characteristics
A total of 236 questionnaires were distributed, of which 197 (83.5%) valid questionnaires were recovered. The mean age of the patients was 51.08 ± 5.93 years; 47.7% were male, 22.3% had a university degree or above, and 58.9% were married. Table 1 shows additional demographic characteristics.
Table 1 Demographic characteristics of all patients.
Among the 197 patients with T2DM, the mean HAMA and HAMD scores were 13.85 ± 6.50 and 19.17 ± 9.29, respectively. Using cut-off values of 14 for anxiety and 20 for depression, 20.3% of the patients had neither anxiety nor depression symptoms, 29.4% had anxiety, 26.4% had depression, and 23.9% had both conditions (Table 2).
Comparison of demographic characteristics revealed no statistically significant differences among the four groups in sex, age, body mass index, or family history of DM (P > 0.05). However, DM duration differed significantly among groups (P < 0.05). Patients with psychological symptoms had a longer DM duration than uncomplicated T2DM patients (P < 0.05), and those with anxiety-depression comorbidity had the longest duration (Table 3).
Table 3 Comparison of demographic characteristics.
Comparative analysis of BG and lipid levels showed significant intergroup differences in HbA1c, FPG, and 2hPG levels (P < 0.05), with the T2DM + anxiety-depression group demonstrating the highest levels among all groups (P < 0.05). Significant differences were also observed in lipid metabolism indicators, TG, TC, HDL-C, and LDL-C (P < 0.05). Compared with uncomplicated T2DM patients, those with psychological symptoms showed significantly higher TG and LDL-C levels and lower TC and HDL-C levels (P < 0.05). In addition, high-sensitivity C-reactive protein levels were significantly elevated in T2DM patients with psychological symptoms compared with the T2DM group, and the T2DM + anxiety-depression group exhibited significantly higher high-sensitivity C-reactive protein levels than the T2DM + anxiety and T2DM + depression groups (P < 0.05; Table 4).
Table 4 Comparison of blood glucose and blood lipid levels.
Comparison of islet function indices across groups
Comparative analysis of FINS showed that the T2DM + anxiety-depression group had significantly higher FINS levels than the remaining groups (P < 0.05), where no significant different were observed among the other groups (P > 0.05). Regarding FCP, T2DM patients with psychological symptoms exhibited higher levels than uncomplicated patients with T2DM (P < 0.05), while FCP levels were comparable among the T2DM + anxiety, T2DM + depression, and T2DM + anxiety-depression groups (P > 0.05).
HOMA indices were calculated using FPG and FINS levels. The T2DM + anxiety-depression group exhibited the highest HOMA-IR level (P < 0.05). Although HOMA-IR levels were higher in the T2DM + anxiety and T2DM + depression groups than in the T2DM group, the differences were not statistically significant (P > 0.05). No significant differences in HOMA-β levels were observed across groups (P > 0.05). Regarding HOMA-IS, the T2DM + anxiety-depression group showed significantly lower levels than the other three groups (P < 0.05), while no significant differences were identified among the remaining groups (P > 0.05; Table 5).
According to clinical criteria[13,14], patients were classified as IR (HOMA-IR ≥ 2.69) or non-IR (HOMA-IR < 2.69). As shown in Table 6, IR incidence in the T2DM + anxiety-depression group reached 87.2%, which was significantly higher than that in the other groups (P < 0.05).
Table 6 Comparison of insulin resistance incidence.
IR contributors in T2DM patients with psychological symptoms were analyzed. Anxiety-depression comorbidity was identified as independent predictor of IR, conferring an 8.776-fold increased risk of IR in T2DM patients with anxiety-depression comorbidity compared with non-comorbid patients (odds ratio = 8.776, 95% confidence interval: 3.001-25.667). These findings indicate that anxiety-depression comorbidity is an important IR contributor in patients with T2DM (Table 7).
Table 7 Logistic regression analysis of insulin resistance.
Chronic adverse symptoms associated with DM often induce clinically relevant anxiety and depression. Psychological status plays a crucial role in DM occurrence, development, outcome, and prognosis. Adverse mood is associated with metabolic imbalance and difficulty predicting prognosis in patients with diabetes, causing serious harm to both physical and mental health[15]. Although glucose control remains key to DM diagnosis and treatment, the World Health Organization also emphasizes the importance of improving quality of life and mental health, highlighting the key role of psychological stress factors in disease progression.
Among our cohort (n = 197), anxiety, depression, and anxiety-depression comorbidity were identified in 29.4%, 26.4%, and 23.9%, respectively. Studies by Khuwaja et al[16] and Egede et al[17] reported that 43.5% of patients with T2DM had depression and 57.9% had anxiety. The incidence of depression and anxiety in patients with T2DM is approximately twice that of the general population. Given the chronic nature of the disease, patients with T2DM require life-long medication and daily lifestyle modifications for glucose control, which, to an extent, increase psychological stress and mental burden and negatively affect quality of life. In the present study, significant intergroup differences were observed in HbA1c, FPG, and 2hPG levels, with the highest levels identified in patients with anxiety-depression comorbidity. Anxiety and depression are associated with marked emotional fluctuations and irritability, which may significantly elevate blood adrenaline levels and induce platelet hyperfunction, thereby aggravating hyperglycemia and vascular embolism symptoms[18]. Long-term uncontrolled hyperglycemia can further trigger various complications[19]. Clinical evidence has also demonstrated that greater psychological stress is associated with greater BG fluctuations[20]. During anxiety or depression, activation of the hypothalamus-pituitary-adrenal (HPA) axis promotes substantial release of cortisol and adrenaline, which may adversely affect glucose metabolism[21,22]. Additionally, T2DM patients with psychological symptoms exhibited significant TG and LDL-C elevations and TC and HDL-C reductions than those without. Therefore, anxiety and depression can affect lipid metabolism in T2DM patients, possibly by influencing the neuroendocrine system, behavioral patterns, and metabolic pathways[23,24]. Long-term exposure to anxiety or depression can lead to HPA axis activation that increases the secretion of cortisol and other stress hormones[25]. Cortisol, in turn, promotes lipolysis to release free fatty acids in large quantities into the circulation; in the meantime, the hepatic synthesis of TG and LDL-C is stimulated, which inhibits HDL-C production, eventually inducing dyslipidemia[26]. Interestingly, TC and HDL-C were found to be lower in the comorbidity group than in controls. This finding, though seemingly counterintuitive, may reflect the complex mechanism of action between psychological stress and lipid metabolism. Depression, typically leading to inappetence and thus reduced food intake, potentially lowers endogenous cholesterol levels[27]. Moreover, prolonged HPA axis activation during anxiety and depression may increase the consumption of cholesterol, a precursor for continuous cortisol synthesis[28]. Low-level cholesterol has been shown to associate with altered serotonin receptor function in the brain, implicating cholesterol in the pathophysiology of emotional dysregulation[29,30]. Collectively, the metabolic status of T2DM patients with psychiatric comorbidity is also influenced by behavioral and neuroendocrine adaptations, in addition to IR.
Subsequently, we evaluated islet function-associated indices. The results showed statistically up-regulated FINS and FCP in the T2DM + anxiety-depression group compared with the other three groups; however, FCP differed non-significantly among the T2DM + anxiety, T2DM + depression, and T2DM groups. In addition, the T2DM + anxiety-depression group had the highest HOMA-IR and the lowest HOMA-IS. Persistent stress may be associated with chronic inflammation and adipokine imbalances, thereby inducing IR. Under these conditions, the cells are unable to effectively utilize glucose despite sufficient insulin secretion, resulting in difficult BG level control[31]. In animal experiments, abnormalities in neuronal insulin receptors are shown to affect HPA axis functioning, further aggravating the vicious cycle of emotional dysregulation and metabolic disturbances[32]. Logistic regression analysis further demonstrated the ability of anxiety-depression comorbidity to independently predict IR in T2DM. When experiencing emotional disorders, the body is often in a low-grade chronic inflammation status, characterized by elevated C-reactive protein and interleukin-6 levels[33]. These markers interfere with insulin receptor substrate phosphorylation and block insulin signaling transduction, driving the occurrence of IR[34]. Obesity can amplify this effect, as pro-inflammatory cytokines secreted by adipose tissue further interact with emotional disorders. Simultaneously, clinical evidence also supports more severe IR in comorbid patients.
This study still has several limitations. First, this study was conducted at a single hospital, which may limit the generalizability of the findings across different socioeconomic and regional contexts. Second, although rigorous training and consensus-building sessions were conducted to improve the reliability of HAMD and HAMA assessments, inter-rater consistency indices such as Kappa statistics were not formally quantified, which may have introduced subjective variability. Third, the sample size of the anxiety-depression comorbidity subgroup was relatively small, resulting in a wide 95% confidence interval for the estimated odds ratio in the multivariate model. Although the findings support a significant independent association between psychological distress and IR, the precision of the estimated effect size should be interpreted cautiously. Forth, patients with a history of anxiety or depression and those currently receiving insulin therapy were excluded. Although this approach minimized the metabolic side effects of psychiatric medications, it may also have introduced selection bias. These exclusion criteria may have identified a subgroup of patients with T2DM with more advanced disease progression, longer disease duration, and more severe underlying complications. The participants therefore represented individuals with untreated psychological distress, in whom the absence of therapeutic intervention may have exacerbated HPA axis activation and systemic inflammation, potentially overestimating the effect of mental disorders on IR. Accordingly, this study’s results should be extrapolated cautiously to patients with T2DM already receiving pharmacological or psychological interventions, as treatment may modify the psychometabolic relationship. Therefore, large-scale, multi-center prospective studies are warranted to provide more precise estimates and validate these findings.
CONCLUSION
In summary, comorbid anxiety and depression predispose patients with T2DM to abnormalities in blood lipid and glucose metabolism, as well as greater IR severity. Medical staff should pay close attention to T2DM patients with anxiety-depression comorbidity and provide appropriate psychological counseling. Meanwhile, strengthening BG and lipid control in these patients is critical.
Liu N, Heng CN, Cui Y, Li L, Guo YX, Liu Q, Cao BH, Wu D, Zhang YL. The Relationship between Trait Impulsivity and Everyday Executive Functions among Patients with Type 2 Diabetes Mellitus: The Mediating Effect of Negative Emotions.J Diabetes Res. 2023;2023:5224654.
[RCA] [PubMed] [DOI] [Full Text][Cited by in RCA: 4][Reference Citation Analysis (0)]
Wang Q, Li Y, Ren H, Huang Q, Wang X, Zhou Y, Wu Q, Liu Y, Li M, Wang Y, Liu T, Zhang X. Metabolic characteristics, prevalence of anxiety and its influencing factors in first-episode and drug-naïve major depressive disorder patients with impaired fasting glucose.J Affect Disord. 2023;324:341-348.
[RCA] [PubMed] [DOI] [Full Text][Cited by in RCA: 9][Reference Citation Analysis (0)]
Hinds JA, Sanchez ER. The Role of the Hypothalamus–Pituitary–Adrenal (HPA) Axis in Test-Induced Anxiety: Assessments, Physiological Responses, and Molecular Details.Stresses. 2022;2:146-155.
[PubMed] [DOI] [Full Text]
Sayadi AR, Seyed Bagheri SH, Khodadadi A, Jafari Torababadi R. The effect of mindfulness-based stress reduction (MBSR) training on serum cortisol levels, depression, stress, and anxiety in type 2 diabetic older adults during the COVID-19 outbreak.J Med Life. 2022;15:1493-1501.
[RCA] [PubMed] [DOI] [Full Text][Cited by in RCA: 7][Reference Citation Analysis (0)]
Tatayeva R, Tussupova A, Koygeldinova S, Serkali S, Suleimenova A, Askar B. The Level of Serotonin and the Parameters of Lipid Metabolism Are Dependent on the Mental Status of Patients with Suicide Attempts.Psychiatry Int. 2024;5:773-792.
[PubMed] [DOI] [Full Text]
Pan K, Gao Y, Zong H, Zhang Y, Qi Y, Wang H, Chen W, Zhou T, Zhao J, Yin T, Guo H, Wang M, Wang H, Pang T, Zang Y, Li J. Neuronal CCL2 responds to hyperglycaemia and contributes to anxiety disorders in the context of diabetes.Nat Metab. 2025;7:1052-1072.
[RCA] [PubMed] [DOI] [Full Text][Cited by in RCA: 17][Reference Citation Analysis (0)]
