Yuan L, Liu JJ, Li Z, Zhu YZ, Ren W, Liu YZ, Zhao XL, Du XD, Zhang XY. L-shaped association between fasting blood glucose and comorbid anxiety in Chinese patients with first-episode untreated major depressive disorder. World J Psychiatry 2026; 16(2): 113063 [DOI: 10.5498/wjp.v16.i2.113063]
Corresponding Author of This Article
Xiang-Yang Zhang, MD, PhD, Department of Psychiatry, Hefei Fourth People's Hospital, Anhui Mental Health Center, Affiliated Psychological Hospital of Anhui Medical University, No. 316 Huangshan Road, Shushan District, Hefei 230022, Anhui Province, China. zhangxy99@tsinghua.edu.cn.
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Psychiatry
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Observational Study
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Feb 19, 2026 (publication date) through Feb 2, 2026
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World Journal of Psychiatry
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Yuan L, Liu JJ, Li Z, Zhu YZ, Ren W, Liu YZ, Zhao XL, Du XD, Zhang XY. L-shaped association between fasting blood glucose and comorbid anxiety in Chinese patients with first-episode untreated major depressive disorder. World J Psychiatry 2026; 16(2): 113063 [DOI: 10.5498/wjp.v16.i2.113063]
Lian Yuan, Department of Mood Disorders, Suzhou Guangji Hospital, The Affiliated Guangji Hospital of Soochow University, Suzhou 215137, Jiangsu Province, China
Jun-Jun Liu, Department of Psychiatry, Nanjing Meishan Hospital, Nanjing 210000, Jiangsu Province, China
Zhe Li, Xue-Li Zhao, Department of Sleep Disorders, Suzhou Guangji Hospital, The Affiliated Guangji Hospital of Soochow University, Suzhou 215137, Jiangsu Province, China
Ying-Zhao Zhu, Wei Ren, Department of Psychiatry, Medical College of Soochow University, Suzhou 215000, Jiangsu Province, China
Ying-Zhao Zhu, Wei Ren, Yao-Zhi Liu, Xiang-Dong Du, Department of Psychiatry, Suzhou Guangji Hospital, The Affiliated Guangji Hospital of Soochow University, Suzhou 215137, Jiangsu Province, China
Yao-Zhi Liu, School of Psychiatry, North Sichuan Medical College, Nanchong 637000, Sichuan Province, China
Xiang-Yang Zhang, Department of Psychiatry, Hefei Fourth People's Hospital, Anhui Mental Health Center, Affiliated Psychological Hospital of Anhui Medical University, Hefei 230022, Anhui Province, China
Co-corresponding authors: Xiang-Dong Du and Xiang-Yang Zhang.
Author contributions: Yuan L and Liu JJ performed the data analysis; Yuan L drafted and revised the manuscript; Liu JJ and Li Z revised the manuscript; Zhu YZ and Ren W contributed to data curation and visualization; Liu YZ and Zhao XL contributed to data curation and investigation; Du XD contributed to funding acquisition, supervision, validation, and manuscript revision; Zhang XY was responsible for study design, project administration, and supervision. All authors reviewed and approved the final version of the manuscript for publication. Yuan L and Liu JJ contributed equally to this work as co-first authors. Du XD obtained the project funding, provided senior oversight of the study, supervised data validation procedures, and guided critical revisions of the manuscript, ensuring financial support, methodological rigor, and integrity of the reported findings. Zhang XY conceived the study, developed the protocol, and conducted project administration and operational supervision, directing study design, implementation, and coordination of research personnel. Their contributions are complementary and partly overlapping: Du XD provided resource stewardship and quality assurance, while Zhang XY led the study’s scientific design and execution. Consequently, both share responsibility for the study’s conceptualization, conduct, data integrity, and final manuscript approval. Accordingly, Du XD and Zhang XY are designated as joint corresponding authors to ensure unified external communication and accountability.
Supported by Medical Research Key Project of Jiangsu Provincial Health Commission, No. K2023015/MR-32-25-009505; Suzhou Major Diseases Clinical Multi-Center Research Project, No. DZXYJ202414/MR-32-25-054379; Scientific and Technological Key Program of Suzhou, No. SYW2024008/MR-32-25-012227; Key Discipline of Psychiatry in Suzhou, No. SZXK202521; and Suzhou Science and Technology Tackling Key Problems Program Healthcare Innovation Project, No. SYWD2025154.
Institutional review board statement: The study was approved by the Institutional Review Board of Shanxi Medical University (No. 2016-Y27) and conducted in accordance with the Declaration of Helsinki.
Informed consent statement: Written informed consent was obtained from all participants prior to their inclusion in the study.
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: The data are available from the corresponding author on reasonable request.
Open Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (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: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Xiang-Yang Zhang, MD, PhD, Department of Psychiatry, Hefei Fourth People's Hospital, Anhui Mental Health Center, Affiliated Psychological Hospital of Anhui Medical University, No. 316 Huangshan Road, Shushan District, Hefei 230022, Anhui Province, China. zhangxy99@tsinghua.edu.cn.
Received: August 15, 2025 Revised: October 7, 2025 Accepted: November 12, 2025 Published online: February 19, 2026 Processing time: 168 Days and 15.2 Hours
Abstract
BACKGROUND
Major depressive disorder (MDD) frequently presents with comorbid anxiety, complicating treatment outcomes. While glucose metabolism dysfunction has been linked to both depression and anxiety, the specific relationship between fasting blood glucose (FBG) levels and comorbid anxiety in MDD remains inadequately characterized.
AIM
To investigate the relationship between FBG and comorbid anxiety in individuals with first-episode untreated MDD.
METHODS
This cross-sectional study included 1718 participants with first-episode untreated MDD. Demographic, anthropometric, and biochemical parameters, including FBG, were collected. Depressive and anxiety symptoms were assessed using the 17-item Hamilton Depression Rating Scale and Hamilton Anxiety Rating Scale, respectively. Potential non-linear relationships were examined using smoothing curves and two-piecewise logistic regression analysis.
RESULTS
The betweengroup comparison indicated that patients comorbid with anxiety have significantly higher FBG levels than those without comorbid anxiety (P < 0.001). Smoothing curve analysis identified a non-linear (L-shaped) association, with a threshold of 4.8 mmol/L. Below this threshold, FBG was inversely associated with comorbid anxiety (OR = 0.20, 95%CI: 0.06-0.67, P = 0.009), whereas no significant association was observed above this threshold (OR = 1.22, 95%CI: 0.91-1.63, P = 0.188).
CONCLUSION
Our results suggest an L-shaped non-linear association: Lower FBG correlates with elevated comorbid anxiety risk in Chinese Han first-episode untreated MDD patients, particularly when FBG is below 4.8 mmol/L.
Core Tip: Insights into the relationship between metabolic factors and psychiatric comorbidities in major depressive disorder (MDD) are limited. We conducted a cross-sectional analysis of 1718 Chinese patients with first-episode untreated MDD using advanced statistical modeling to investigate the association between fasting blood glucose (FBG) levels and comorbid anxiety. An L-shaped nonlinear relationship was revealed with a critical inflection point at 4.8 mmol/L, where FBG levels below this threshold significantly increased anxiety comorbidity risk (OR = 0.20, 95%CI: 0.06-0.67, P = 0.009), while levels above showed no association. These findings demonstrate that lower-normal FBG ranges may serve as a novel biomarker for anxiety risk stratification in MDD patients. With this knowledge, clinicians can incorporate routine FBG assessment into clinical evaluations to identify high-risk patients and optimize treatment strategies for MDD with anxiety comorbidity.
Citation: Yuan L, Liu JJ, Li Z, Zhu YZ, Ren W, Liu YZ, Zhao XL, Du XD, Zhang XY. L-shaped association between fasting blood glucose and comorbid anxiety in Chinese patients with first-episode untreated major depressive disorder. World J Psychiatry 2026; 16(2): 113063
Major depressive disorder (MDD) represents a prevalent and debilitating mental illness. It features persistent low mood, significant anhedonia, and recurrent suicidal ideation, resulting in substantial impairments in daily functioning and quality of life[1]. The Global Burden of Disease Study 2021 showed that depressive disorders affected around 332 million individuals worldwide[2]. Notably, diabetes, depressive disorders and anxiety disorders showed the most marked increases in age-standardized disability-adjusted life year rates among the top 25 third-level causes of years lived with disability from 2010 to 2021[3].
Comorbid depression and anxiety represent a common clinical phenomenon[4]. Substantial comorbidity between depressive and anxiety disorders was elucidated in the China Mental Health Survey, with an estimated concurrent prevalence of 29.8% among Chinese adults[5]. In our earlier research, 80.3% of patients with first-episode untreated MDD were observed to have comorbid anxiety[6]. Importantly, individuals with comorbid anxiety and depression tend to have increased symptom severity, poorer treatment response, elevated suicide risk, and less favorable prognoses compared to those with depression alone[7-9]. Evidence from a cohort study suggests that depression with comorbid anxiety represents a distinct subtype that significantly elevates the risk of suffering from type 2 diabetes mellitus (T2DM)[10].
Accumulating evidence highlights complex interactions among depression, anxiety and glucose metabolism. Some studies focused on anxiety and depression in diabetes. A recent review confirmed a bidirectional relationship, where mental disorders increase the risk of T2DM and worsen its outcomes, while diabetes elevates the risk of depression and anxiety[11]. Anxiety, depression, and pain or discomfort were reported as the most prevalent issues among T2DM patients in Ghana[12]. Furthermore, individuals with insulin-dependent diabetes and poor glycemic control experience substantially higher levels of anxiety, depression, and daily living difficulties compared with those maintaining adequate glucose regulation[13]. Despite extensive research, findings regarding the relationship between glucose-related biomarkers and depression risk remain inconsistent. For instance, a recent cohort study involving more than 200000 participants reported that elevated glucose levels are linked with an elevated probability of future depression, anxiety and stress-related disorders[14]. Similarly, several studies have identified positive correlations between glucose levels and depression risk[15-18]. Nevertheless, conflicting evidence exists, with Golden et al[19] demonstrating a negative correlation between glycemic concentrations and depression risk, whereas Vogelzang et al[20] reported no significant correlation. In addition, a Mendelian randomization study further indicated no causal relationship between depression and elevated fasting blood glucose (FBG) levels[21]. On the other hand, the association between anxiety and glucose metabolism indicators has also been investigated. Results from a community-based sample showed that elevated FBG levels were markedly correlated with increased anxiety symptoms among participants with clinical or diabetic FBG levels[22]. An Indian study based on diabetic population suggested that the anxiety scores of the Hospital Anxiety and Depression Scale (HADS) showed a positive correlation with glycated hemoglobin (HbA1c) and postprandial blood glucose levels[23]. A study on healthy individuals suggests that glucose supports the process of fear extinction, particularly the consolidation of fear extinction memory[24].
To date, investigations examining the association between FBG levels and comorbid anxiety among Chinese Han individuals with MDD remained limited. Given the complex bidirectional relationship between glycemic parameters, depression and anxiety, exploring these associations in this specific population holds significant clinical implications. Probing this issue in first-episode untreated patients provides a unique opportunity to minimize the influence of confounders including pharmacological interventions, disease duration and comorbidities associated with chronic MDD patients. Therefore, this study aimed to investigate the association between FBG levels and the risk of comorbid anxiety in a large cohort of Chinese Han first-episode untreated MDD patients. Clarifying this relationship may help improve risk stratification and identify potential metabolic intervention targets for this vulnerable population.
MATERIALS AND METHODS
Participants
A cross-sectional study was conducted. This study included 1718 participants (588 men and 1130 women; mean age 34.87 ± 12.43 years) who were consecutively recruited at the Department of Psychiatry, First Clinical Medical College, Shanxi Medical University between 2015 and 2017.
Eligibility criteria included: (1) Han Chinese ethnicity, aged 18-60 years; (2) Fulfilling the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition standards for MDD; (3) Exhibiting first-episode depressive symptoms with a duration not exceeding 24 months; (4) No prior treatment with antidepressants or antipsychotics; and (5) A score of 24 or higher on the 17-item Hamilton Depression Rating Scale (HAMD-17).
Exclusion criteria were applied: (1) Significant physical diseases (including diabetes); (2) Substance abuse (other than smoking) within the past six months; (3) Pregnancy or lactation; and (4) Concurrent severe Axis I psychiatric disorders.
After the research procedures were fully explained, every participant submitted written informed consent. The research protocol received ethical approval from the Institutional Review Board of the First Clinical Medical College, Shanxi Medical University (ID number: 2016-Y27), and executed as per the Declaration of Helsinki.
Demographic and anthropometric characteristics
A structured, researcher-designed questionnaire was employed by trained researchers to collect clinical and sociodemographic data. These data comprised gender, age, age at onset, marital status, education, and illness duration. Calibrated equipment was used following standardized protocols to obtain anthropometric measurements, such as height, weight, and diastolic and systolic blood pressures (DBP and SBP). The calculation of body mass index (BMI) involves dividing the subject's weight in kilograms by the square of their height in meters (kg/m²).
Clinical interview assessments
Clinical assessments were conducted using standardized rating scales administered by two board-certified psychiatrists, each of whom had at least five years of clinical experience. Inter-rater reliability was verified through repeated assessments, yielding an intraclass correlation coefficient of greater than 0.8, indicating strong inter-observer agreement.
HAMD-17 was utilized for the assessment of depressive symptoms. It comprises nine and eight items scored from 0-4 and 0-2, respectively, with a total score ranging from 0-52[25]. Higher scores denote greater depressive symptom severity. With widespread application in China, the scale has been highly reliable and valid in prior studies[26-28].
The 14-item Hamilton Anxiety Rating Scale (HAMA) was applied to measure anxiety symptom severity. It is a clinician-administered instrument rated on a five-point scale (0-4 = absent to severe), with total scores ranging from 0 to 56. Comorbid anxiety was defined as a HAMA score ≥ 18[6].
The positive subscale of the Positive and Negative Syndrome Scale was administered to evaluate psychotic symptoms. Each item rated from 1-7 (absent to extremely severe), generating total scores between 7 and 49[29]. Participants with and without psychotic symptoms were differentiated by establishing a cut-off score of 15[30].
Suicide attempts refer to non-fatal, self-initiated behaviors undertaken with suicidal intent. The assessment was performed via direct inquiry (“Have you ever attempted suicide in your life?”), with affirmative responses categorizing participants as suicide attempters[31].
Biochemical parameters
All participants underwent a standardized overnight fast beginning at 20:00. Venous blood samples were performed between 06:00 and 08:00 the subsequent morning. Biological specimens were instantly transported to the hospital's central laboratory, with all analyses completed by 11:00. The evaluated biochemical parameters consisted of FBG, total cholesterol (TC), triglycerides (TG), low- and high-density lipoprotein cholesterol (LDL-C and HDL-C), free thyroxine and triiodothyronine (FT4 and FT3), thyroid-stimulating hormone (TSH), anti-thyroglobulin antibody (TGAb) and thyroid peroxidase antibody (TPOAb). Glucose oxidase was used to quantify FBG levels. Additional biochemical parameters were analyzed utilizing either a Cobas E610 Analyzer (Roche Diagnostics, Basel, Switzerland) or a Roche C6000 Electrochemiluminescence Immunoassay Analyzer (Roche Diagnostics, Indianapolis, IN, United States). To minimize potential bias, laboratory personnel performing biochemical analyses were blinded to study objectives.
Statistical analysis
Normality of continuous variables was assessed using the Kolmogorov-Smirnov test. Continuous variables were summarized as mean ± SD or median (IQR) according to distribution; categorical variables as frequencies and percentages. FBG was analyzed both continuously and by tertiles; for piecewise models, knots were prespecified at the 10th, 50th, and 90th percentiles of the FBG distribution. Across FBG tertiles, one-way ANOVA tested normal continuous variables, Kruskal-Wallis H tested non-normal continuous variables, and χ2 tested categorical variables. For comparisons between MDD patients with and without comorbid anxiety, Mann-Whitney U tested nonparametric continuous variables and χ2 tested categorical variables.
Associations between FBG and comorbid anxiety were estimated using logistic regression, with OR and 95%CI reported. Models were built sequentially: Crude Model (unadjusted); Model I adjusted for age, gender, and education; Model II additionally for suicide attempts and psychotic symptoms; Model III further adjusted for HAMD, TC, TG, and LDL-C; Model IV further for further for TSH, TGAb, TPOAb, SBP, and DBP. Multicollinearity was assessed using variance inflation factor (VIF), with variables having VIF > 5 excluded. Potential confounders were selected based on clinical relevance and statistical criteria: Variables changing the FBG effect estimate by 10% or having P < 0.10 in univariable analysis[32]. When FBG was analyzed as tertiles, trend tests ensured consistency with continuous analyses. Potential non-linear associations were evaluated using smoothing plots from generalized additive models and two-piecewise logistic regression to identify threshold effects. Model fit of the two-piecewise logistic specification was compared against the linear logistic specification using a log-likelihood ratio test. Subgroup analyses were performed with stratification by gender, education, marital status, and history of suicide attempts.
R (version 4.3.2; R Foundation for Statistical Computing, Vienna, Austria) and EmpowerStats (version 4.0; X&Y Solutions Inc., Boston, MA, United States) were used for conducting statistical analyses. GraphPad Prism (version 10.0; GraphPad Software, San Diego, CA, United States) was utilized to generate graphical representations. All variables included in the analyses were complete, with no missing data observed. Statistical significance was set at a two-tailed P value < 0.05 for all analyses.
RESULTS
Baseline characteristics of participants
This study included 1718 first-episode untreated MDD patients, of whom 588 (34.2%) were male and 1130 (65.8%) were female. Comorbid anxiety was present in 1380 (80.3%) patients. Participants were categorized into tertiles based on serum FBG levels, and their baseline characteristics are demonstrated in Table 1. Most variables significantly differed across FBG tertiles (P < 0.001), except for demographic variables (gender, age, education and marital status), thyroid hormones (FT3 and FT4) and age at onset. The highest FBG tertile (T3) showed a significantly greater prevalence of comorbid anxiety (85.7%) in comparison with T1 (77.1%) and T2 (78.1%) (P < 0.001).
Table 1 Baseline characteristics between major depressive disorder comorbid anxiety and non-comorbid anxiety, n (%).
Figure 1 Association of fasting blood glucose levels with the likelihood of comorbid anxiety.
It was observed that fasting blood glucose levels were nonlinearly associated with the likelihood of comorbid anxiety after adjusting for gender, age, education, 17-item Hamilton Rating Scale for Depression, thyroglobulin antibody, thyroid-stimulating hormone, thyroid peroxidase antibody, total cholesterol, triglyceride, low-density lipoprotein cholesterol, diastolic and systolic blood pressures, suicide attempts as well as psychotic symptoms in patients with first-episode untreated major depressive disorder. FBG: Fasting blood glucose.
Comparison of characteristics between patients with and without comorbid anxiety
Table 2 shows that, compared with patients without comorbid anxiety, those with comorbid anxiety and MDD had significantly higher symptom severity (HAMD, HAMA), higher FBG levels, elevated thyroid indices (TSH, TPOAb, TGAb), and higher blood pressure measurements (DBP and SBP) (all P < 0.001). Levels of TC, LDL-C and TG were also significantly higher in the comorbid anxiety group (all P < 0.05). Psychotic symptoms and suicide attempts were more prevalent among patients with comorbid anxiety (all P < 0.001). No significant betweengroup differences were observed in age, age at onset, duration of illness, gender, education, marital status, FT3, FT4, HDL-C or BMI (all P > 0.05).
Table 2 Baseline characteristics between major depressive disorder comorbid anxiety and non-comorbid anxiety, n (%).
Logistic regression analysis of FBG and comorbid anxiety
Multivariate logistic regression analyses assessing the association between FBG levels and comorbid anxiety are shown in Table 3 across five models: The crude model (unadjusted), Model I adjusted for demographic variables (gender, age and education), Model II additionally adjusted for disease-related variables (suicide attempts, psychotic symptoms, HAMD score), Model III further adjusted for metabolic indicators (TC, TG, and LDL-C, DBP and SBP), Model IV further adjusted for thyroid function indicators (TSH, TGAb, TPOAb). When modeled as a continuous variable, higher FBG was significantly associated with comorbid anxiety in the crude model and Model I (both P < 0.001) and remained significant in Model II (P = 0.038), but not in Model III or Model IV. In tertile analyses (with T2 as the reference), T1 showed no significant association in any model, whereas T3 was significantly associated with comorbid anxiety in the crude model and Model I (both P < 0.001) and in Model II (P = 0.034), but not in Model III or Model IV.
Table 3 Relationship of fasting blood glucose with comorbid anxiety in different models.
Nonlinear relationship between FBG and comorbid anxiety
A smooth-fitting curve illustrates an L-shaped association between FBG levels and comorbid anxiety (Figure 1). As detailed in Table 4, a two-segment logistic regression model further verified a non-linear relationship with a point of inflection at 4.8 mmol/L. An obvious inverse correlation was observed below the threshold (P = 0.009), suggesting that each one-unit decrease in FBG levels was associated with 80% higher odds of comorbid anxiety. For FBG levels exceeding 4.8 mmol/L, no significant statistical association was detected (P = 0.188). The log-likelihood ratio test (P = 0.005) demonstrated that the non-linear model provided a significantly superior fit to the linear one, which revealed a threshold effect in the FBG-anxiety relationship. The threshold effect remained robust across subgroups stratified by gender, education, marital status, and suicide attempt history (all P for interaction > 0.05) (Figure 2).
Figure 2 Subgroup analysis of the association between fasting blood glucose and comorbid anxiety.
The OR (95%CI) was derived from the logistic regression model (gender, age, education, Hamilton Rating Scale for Depression, thyroglobulin antibody, thyroid-stimulating hormone, thyroid peroxidase antibody, total cholesterol, triglyceride, low-density lipoprotein cholesterol, diastolic and systolic blood pressures, suicide attempts and psychotic symptom were adjusted).
Table 4 Two-piecewise logistic regression model results.
The present study, based on a relatively large sample, for the first time explores the nonlinear relationship between FBG levels and comorbid anxiety in patients with first-episode untreated MDD. Our results revealed an L-shaped relationship between FBG levels and comorbid anxiety, with a point of inflection at 4.8 mmol/L. Lower FBG levels showed a significant association with an elevated odds of comorbid anxiety below the threshold, whereas the relationship was positive but not statistically significant above this point. These associations were still consistent across all the examined subgroups, including gender, marital status, education, and history of suicide attempts. These findings suggest that decreased FBG concentrations may act as a potential biomarker for identifying comorbid anxiety in patients with first-episode untreated MDD.
The observed association between lower FBG and increased anxiety symptoms partially aligns with findings from the Greater Beirut Area Cardiovascular Cohort, which demonstrated that among participants with baseline FBG < 126 mg/dL, depressive and anxiety symptoms were inversely associated with FBG levels[22]. This suggests that glucose-anxiety associations may extend beyond clinical populations to the general community. Despite these parallels, evidence regarding the association between glucose metabolism biomarkers and anxiety remains inconclusive. Several studies have established positive associations between dysregulated glucose metabolism and anxiety. For instance, a retrospective study of patients with T2DM indicated that blood glucose fluctuations and poor glycemic control were correlated with increased risk of both depression and anxiety[33]. Likewise, a Greek study reported that HbA1c and blood glucose levels were positively correlated with the HADS total scores and anxiety, respectively[34]. Zeng et al[35] further highlighted that one-hour plasma glucose levels are a critical risk factor for postpartum anxiety in women with gestational diabetes mellitus. Furthermore, research involving young adults in the Deep South of the United States indicated that anxiety symptoms and stress were associated with an elevated likelihood for metabolic syndrome, especially elevated glucose levels[36]. Buchberger et al[37] revealed associations between levels of depressive and glycemic control, along with tripartite interactions among HbA1c, blood glucose monitoring frequency and depression-related diabetes-specific stress. Of note, they further noticed that anxiety symptoms exerted a negative influence on glycemic control. In contrast, not all studies identified significant links between glucose metabolism and anxiety. A large-scale Dutch cross-sectional study involving 2667 participants reported that depressive symptoms were associated with glucose metabolism rather than anxiety symptoms[38]. Moreover, a study from the Hertfordshire Cohort (n = 2997) found that baseline HADS scores were linked to glucose, TG and insulin resistance (IR) in males, and HDL-C in females. However, Hospital Anxiety and Depression Scale-Anxiety subscale scores demonstrated no similar association[39]. These discrepancies may arise from differences in study design, sample characteristics, assessment tools, and the control of potential confounders. Further insights arise from research on trait and state anxiety. The Midlife in the United States study found that trait anxiety in Black women was associated with elevated glucose levels, insulin as well as higher homeostatic model assessment of IR[40]. Moreover, Smith and Foster[41], Smith and Foster[42] and Smith et al[43] demonstrated that glucose enhanced memory performance in healthy adolescents, with trait anxiety levels mediating this effect through anxiety-associated biological mechanisms. Overall, these findings underline the complex relationships of glucose metabolism biomarkers with anxiety. The inconsistencies may be attributable to heterogeneity in study populations (clinical vs community samples), differences in study design (cross-sectional vs longitudinal designs), variability in assessment tools for anxiety and depression, and the influence of potential confounding variables. In addition, the biological underpinnings of these associations may involve multiple pathways, including stress hormone regulation, inflammatory processes, neurotransmitter systems and hypothalamic-pituitary-adrenal axis function.
Although the underlying mechanisms linking lower-normal FBG levels to an increased risk of anxiety in MDD patients remain incompletely elucidated, a few pathophysiological pathways may contribute to this association. One prominent neurobiological mechanism may concern disturbances in cerebral energy metabolism. Despite occupying merely 2% of total body weight, the brain consumes around 20% of the glucose-derived energy of the body, which underlines its reliance on a continuous glucose supply to sustain optimal function[44]. Even mild reductions in glucose availability within the normal physiological range can disrupt neuronal bioenergetics, and potentially impair brain function and emotional regulation. This hypothesis is supported by neuroimaging studies in neuropsychiatric and neurodegenerative diseases. For instance, anxiety symptoms in women have been associated with decreased gray matter volume and reduced brain glucose metabolism[45]. Furthermore, the findings from a prospective cohort study signify that neuropsychiatric symptoms (including depression and anxiety) co-occurring with regional cerebral glucose hypometabolism predict an elevated susceptibility to mild cognitive dysfunction[46]. These observations suggest that even subtle alterations in the utilization of cerebral glucose may cause anxiety symptoms in vulnerable populations. Findings from animal studies have provided further mechanistic insights. It has been demonstrated that prenatal immune activation in rat models can alter early neurodevelopmental processes, with elevated brain glucose utilization correlating with increased anxiety-like behaviors during adolescence and impaired recognition memory during adulthood[47]. Beyond that, exposure to static magnetic fields in rats has been shown to induce abnormalities in brain glucose metabolism and thereby trigger anxiety-like behaviors[48]. Notably, recent experimental evidence indicates that a single insulin-induced hypoglycemic episode in rats elicits anxiety responses possibly through allostatic mechanisms mediating adaptive anxiety during periods of acute energy deficit[49]. Pharmacological studies have highlighted the role of impaired glucose metabolism in anxiety as well. For example, methylphenidate administration in male rats resulted in glucose hypometabolism and disrupted metabolic networks in the orbitofrontal cortex, which ultimately induced anxiety-like behaviors[50]. Nutritional studies have also substantiated the association of dietary glycemic index (GI) with psychiatric disorders. An Iranian population-based study demonstrated a positive relationship between GI and depression risk while revealing inverse relationships between glycemic load and mental disorders, including depression and psychological distress[51].
Taken together, converging evidence from neuroimaging, animal models, and pharmacological and nutritional studies supports the following conclusion: Suboptimal glucose availability within the lower-normal physiological range contributes to neuro-energetic dysfunction and heightened vulnerability to anxiety symptoms in patients with MDD. Within this mechanistic framework, the FBG threshold of 4.8 mmol/L holds important clinical relevance. MDD patients below this level require more vigilant anxiety monitoring. Use brief standardized screening with tools such as the GAD7 or HAMA at initial assessment and early followup. Given its observational origin, this threshold is intended for risk stratification rather than as a diagnostic cutoff. Further studies are warranted to clarify the underlying mechanisms and to determine whether interventions that optimize glucose metabolism confer therapeutic benefit for patients with depression and anxiety.
Several study limitations warrant consideration. First, the cross-sectional design precluded causal inferences between FBG and comorbid anxiety. It is necessary to conduct prospective and longitudinal cohort studies to explore causality. Second, the study population was restricted to outpatients from a single medical facility, which may introduce selection bias and limit external validity to other populations, including inpatients and community-based patients. Therefore, subsequent research will recruit participants from multiple centers across diverse settings to validate these findings and strengthen external validity. Third, patients diagnosed with diabetes were excluded from this study. Hence, the results cannot be generalized to this population. Future research may investigate this correlation in diabetic populations. Fourth, adjusting for multiple covariates failed to help rule out the influence of unmeasured confounding factors on the results. Future studies should incorporate these potential confounders, including but not limited to lifestyle choices, dietary patterns, family income and substance use. Fourth, despite multivariable adjustment for a wide array of confounders, residual confounding cannot be ruled out. In particular, detailed lifestyle factors (e.g., dietary patterns, physical activity), family income, medications not directly related to psychiatric conditions, and family history of mental disorders may influence the observed associations. Future studies will collect these variables and adjust for them, and will implement sensitivity analyses to assess the robustness of the findings to unmeasured confounding. Fifth, the HAMA scale was not designed for diagnostic purposes despite being employed to quantify anxiety symptoms. To achieve a thorough evaluation and accurate classification, subsequent research should employ structured diagnostic tools like the Mini-International Neuropsychiatric Interview.
CONCLUSION
In summary, this study found an L-shaped nonlinear relationship between FBG and comorbid anxiety in Chinese Han first-episode untreated MDD patients, with a point of inflection at 4.8 mmol/L. The results showed that below this inflection point, FBG were negatively correlated with comorbid anxiety, whereas no significant relationship was observed above this threshold. These findings suggest that maintaining FBG levels within a specific range may help manage anxiety symptoms in MDD patients. However, these results should be interpreted with caution given the insufficient understanding of potential mechanisms, the inherent limitations of this cross-sectional study and the aforementioned study limitations. To strengthen and validate these preliminary results, future studies should employ larger-scale longitudinal cohorts and incorporate standardized assessment tools and a wider array of relevant variables.
ACKNOWLEDGEMENTS
We thank all the participants in this study and the First Clinical Medical College of Shanxi Medical University for their support.
Footnotes
Provenance and peer review: Unsolicited article; Externally peer reviewed.
Peer-review model: Single blind
Specialty type: Psychiatry
Country of origin: China
Peer-review report’s classification
Scientific Quality: Grade A, Grade B, Grade D
Novelty: Grade A, Grade C, Grade C
Creativity or Innovation: Grade A, Grade C, Grade C
Scientific Significance: Grade A, Grade B, Grade C
P-Reviewer: Baghirova-Busang L, MD, Botswana; Yu J, MD, PhD, China; Zhang ZJ, PhD, Chief Physician, Professor, China S-Editor: Qu XL L-Editor: A P-Editor: Yu HG
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