Subclinical hypothyroidism and anxiety may contribute to metabolic syndrome in Sichuan of China: a hospital-based population study

Impact of sleep duration and dietary patterns on risk of metabolic syndrome in middle-aged and elderly adults: a cross-sectional study from a survey in Anhui, Eastern China

The aim of this study was to assess the sleep status of middle-aged and elderly adults in Bengbu City, Anhui Province, China, to identify the major dietary patterns, and to analyze the association of different sleep duration and dietary patterns with metabolic syndrome (MetS) and its related influencing factors, as well as to explore the predictive value of sleep duration and dietary patterns. A cross-sectional analysis was performed utilizing data collected from the Community-based Cardiovascular and Health Promotion Study 2019 (COCHPS 2019) conducted in Bengbu. The definition of MetS adhered to the criteria of Guidelines for the Prevention and Treatment of Dyslipidemia in Chinese Adults (2016 Revision). Dietary information was obtained using the Food Frequency Questionnaire (FFQ) to assess dietary intake over the past year. Principal component analysis (PCA) was performed to identify dominant dietary patterns. A logistic regression model was developed to analyze the associations among sleep duration, dietary patterns, and MetS, and a decision tree (DT) model was developed to compare factors affecting MetS and screen people at high risk for MetS. The prevalence of MetS was 13.4% among the 9132 middle-aged and elderly residents over 45 years of age included in COCHPS 2019. Participants were divided into short (< 6 h/d), normal (6-8 h/d), and long (> 8 h/d) groups based on their daily sleep duration. Three dietary patterns were identified by PCA, the fruit-milk pattern, the tubers-meat pattern, and the vegetable-cereal pattern. After adjusting for covariables, logistic regression analysis showed that long sleep duration was significantly negatively associated with MetS. The fruit-milk and vegetable-cereal patterns were negatively associated with MetS, whereas the tubers-meat pattern was positively correlated with MetS. The results of the DT model analysis showed that the vegetable-cereal pattern is the most important factor impacting MetS, followed by marital status, the tubers-meat pattern, the fruit-milk pattern, exercise, sleep duration, and gender. The DT model also screened out five types of MetS high-risk groups. The results of our study indicate that normal sleep duration and consumption of either a fruit-milk or vegetable-cereal diet may lower the likelihood of developing MetS in middle-aged and elderly adults.

Association of subclinical hypothyroidism with metabolic syndrome and its components among outpatients with first-episode drug-naïve major depressive disorder: a large-scale cross-sectional study

Both metabolic syndrome (MetS) and subclinical hypothyroidism (SCH) are prevalent in major depressive disorder (MDD) patients. However, their relationship in this population remains unknown. The study assessed the association between SCH and MetS in 1706 first-episode drug-naïve (FEDN) MDD patients. We also compared the relationship between MetS and clinical symptoms in patients with and without comorbid SCH. The Positive and Negative Syndrome Scale positive subscale, the Hamilton Anxiety Rating Scale, and the Hamilton Depression Rating Scale were used to detect clinical symptoms. Serum levels of free triiodothyronine, free thyroxine, thyroid stimulating hormone (TSH), anti-thyroglobulin, thyroid peroxidases antibody, cholesterol, triglycerides, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and fasting glucose were measured. The Area Under the Curve (AUC) was used to test the performance of serum TSH in identifying MetS patients. The prevalence of MetS and SCH was 34.5% (n = 585) and 61% (n = 1034), respectively. The presence of SCH increased the risk of MetS, hyperglycemia, hypertension, obesity, and low HDL-C by 4.91, 3.51, 3.54, 2.02, and 2.34 times, respectively. Serum TSH had a nice ability to distinguish MetS patients from non-MetS patients (AUC value = 0.77). MetS and its components exhibited a positive association with clinical profiles only in SCH patients, but not in non-SCH patients. Taken together, our study suggested SCH was closely related to MetS and might play a vital role in the relationship between MetS and clinical symptoms. Regular thyroid function checks might help early detect MetS.

Prevalence and risk factors for abnormal glucose metabolism in first-episode and drug-naïve major depressive disorder outpatients with comorbid anxiety: A cross-sectional study from a large sample of the Chinese Han population

BACKGROUND

Both abnormal glucose metabolism and anxiety have been reported to be common in major depressive disorder (MDD). However, few studies have explored glucose disturbances in first-episode and drug-naive (FEDN) MDD patients with anxiety. The purpose of this study was to examine the prevalence and risk factors of glucose disturbance in FEND MDD patients comorbid with anxiety.

METHODS

1718 FEDN MDD patients were included in this study. The positive subscale of the Positive and Negative Syndrome Scale (PANSS), Hamilton Anxiety Rating Scale (HAMA), and Hamilton Depression Rating Scale (HAMD) were used to measure psychotic, anxiety and depressive symptoms respectively. Sociodemographic and biochemical indicators were also collected.

RESULTS

The prevalence of glucose disorders in MDD patients combined with anxiety was 15.7 %, significantly higher than in MDD patients without anxiety symptoms (7.1 %). Glucose disturbances were associated with HAMD score, HAMA score, thyroid-stimulating hormone (TSH), thyroid peroxidase antibody (TPOAb), anti-thyroglobulin (TGAb), total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein (LDL-C), fasting blood glucose (FBG), systolic blood pressure (SBP), diastolic blood pressure (DBP), suicide attempts, and psychotic symptoms. Further logistic regression showed that illness duration, TSH, TGAb, and TPOAb levels were correlates of glucose disturbances in MDD patients with anxiety.

LIMITATIONS

No causal relationship could be drawn due to the cross-sectional design.

CONCLUSIONS

Our findings suggest that TSH, TGAb and TPOAb may be promising biomarkers of glucose disturbances in MDD comorbid with anxiety, suggesting the importance of regular assessment of thyroid function parameters for abnormal glucose metabolism prevention.

Sleep Quality, Nutrient Intake, and Social Development Index Predict Metabolic Syndrome in the Tlalpan 2020 Cohort: A Machine Learning and Synthetic Data Study

This study investigated the relationship between Metabolic Syndrome (MetS), sleep disorders, the consumption of some nutrients, and social development factors, focusing on gender differences in an unbalanced dataset from a Mexico City cohort. We used data balancing techniques like SMOTE and ADASYN after employing machine learning models like random forest and RPART to predict MetS. Random forest excelled, achieving significant, balanced accuracy, indicating its robustness in predicting MetS and achieving a balanced accuracy of approximately 87%. Key predictors for men included body mass index and family history of gout, while waist circumference and glucose levels were most significant for women. In relation to diet, sleep quality, and social development, metabolic syndrome in men was associated with high lactose and carbohydrate intake, educational lag, living with a partner without marrying, and lack of durable goods, whereas in women, best predictors in these dimensions include protein, fructose, and cholesterol intake, copper metabolites, snoring, sobbing, drowsiness, sanitary adequacy, and anxiety. These findings underscore the need for personalized approaches in managing MetS and point to a promising direction for future research into the interplay between social factors, sleep disorders, and metabolic health, which mainly depend on nutrient consumption by region.

Thyroid-stimulating hormone may participate in insulin resistance by activating toll-like receptor 4 in liver tissues of subclinical hypothyroid rats

BACKGROUND

Thyroid-stimulating hormone (TSH) is an independent risk factor of and closely associated with metabolic disorders. In the present study, we explored the potential mechanism and adverse effects of TSH on insulin resistance in the liver of subclinical hypothyroidism models in vivo.

METHODS

The mean glucose infusion rate (GIR), free fatty acids (FFAs), the homeostatic model assessment for insulin resistance (HOMA-IR), fasting plasma insulin (FINS), the TLR4 signal pathway and its intracellular negative regulator-toll-interacting protein (Tollip), and the modulators of insulin signaling were evaluated.

RESULTS

Compared to the normal control group (NC group), the subclinical hypothyroidism rat group (SCH group) showed decreases in GIR and increases in FFAs, FINS, and HOMA-IR. The levels of TLR4 and of its downstream molecules like p-NF-κB, p-IRAK-1, IL-6 and TNF-α were evidently higher in the SCH group than in the NC group. Conversely, the level of Tollip was significantly lower in the SCH group than in the NC group. Compared to the NC group, the levels of phosphorylated IRS-1-Tyr and GLUT2 were decreased in the SCH group. Macrophage infiltration was higher in the SCH group than in the NC group.

CONCLUSION

TSH may participate in aggravating inflammation by increasing macrophage infiltration; furthermore, it may activate the TLR4-associated inflammatory signaling pathway, thus interfering with insulin signals in liver tissues. Targeting TSH may have therapeutic benefits against metabolic disorders.

Metabolomic profiling of early inactive hepatic alveolar and cystic echinococcosis

Hepatic alveolar echinococcosis (AE) and cystic echinococcosis (CE) are severe helminthic zoonoses and leading causes of parasitic liver damage. They pose a high mortality risk due to invisible clinical signs, especially at the early inactive stage. However, the specific metabolic profiles induced by inactive AE and CE lesions remain largely unclear. Therefore, we used gas chromatography-mass spectrometry-based metabolomic profiling to identify the global metabolic variations in AE and CE patient sera to differentiate between the two diseases and reveal the mechanisms underlying their pathogenesis. In addition, specific serum biomarkers of inactive hepatic AE and CE were screened using receiver operating curves, which can contribute to the clinical diagnosis of both diseases, especially in the earlier phase. These differential metabolites are involved in glycine, serine, tyrosine, and phenylalanine metabolism. Further analysis of key metabolic pathways showed that inactive AE lesions strongly alter amino acid metabolism in the host. CE lesions have an altered metabolism of oxidative stress response. These changes suggest these metabolite-associated pathways can serve as biomarkers to distinguish individuals with inactive AE and CE from healthy populations. This study also investigated the differences in serum metabolic profiles in patients with CE and AE. The biomarkers identified belonged to different metabolic pathways, including lipid, carnitine, androgen, and bile acid metabolism. Taken together, by investigating the different phenotypes of CE and AE with metabolomic profiling, serum biomarkers facilitating early diagnosis were identified.

A community-based cross-sectional study of anxiety and metabolic syndrome

BACKGROUND

The prevalence of anxiety and other psychological disorders has increased during the COVID-19 pandemic, especially among the elderly. Anxiety and metabolic syndrome (MetS) may aggravate each other. This study further clarified the correlation between the two.

METHODS

Adopting a convenience sampling method, this study investigated 162 elderly people over 65 years of age in Fangzhuang Community, Beijing. All participants provided baseline data on sex, age, lifestyle, and health status. The Hamilton Anxiety Scale (HAMA) was used to assess anxiety. Blood samples, abdominal circumference, and blood pressure were used to diagnose MetS. The elderly were divided into MetS and control groups according to the diagnosis of MetS. Differences in anxiety between the two groups were analysed and further stratified by age and gender. Multivariate logistic regression analysis was used to analyse the possible risk factors for MetS.

RESULTS

Compared with the control group, anxiety scores of the MetS group were statistically higher (Z = 4.78, P < 0.001). There was a significant correlation between anxiety levels and MetS (r = 0.353, P < 0.001). Multivariate logistic regression revealed that anxiety (possible anxiety vs no anxiety: odds ratio [OR] = 2.982, 95% confidence interval [CI] 1.295-6.969; definite anxiety vs no anxiety: OR = 14.573, 95%CI 3.675-57.788; P < 0.001) and BMI (OR = 1.504, 95% CI 1.275-1.774; P < 0.001) were possible risk factors for MetS.

CONCLUSION

The elderly with MetS had higher anxiety scores. Anxiety may be a potential risk factor for MetS, which provides a new perspective on anxiety and MetS.

Association between anxiety and metabolic syndrome: An updated systematic review and meta-analysis

Objective

Previous studies have demonstrated an association between anxiety and metabolic syndrome (MetS). However, the association is still controversial. This updated meta-analysis aimed to reanalyze the association between anxiety and MetS.

Methods

We comprehensively searched PubMed, Embase and Web of Science for all related studies published before January 23, 2023. Observational studies that informed effect size with 95% confidence interval (CI) for the association between anxiety and MetS were included. According to heterogeneity between studies, fixed or random effects models were applied to calculate the pooled effect size. Publication bias was examined by funnel plots.

Results

The research included 24 cross-sectional studies: 20 studies used MetS as the dependent variable with a pooled OR of 1.07 (95% CI: 1.01-1.13) and four studies used anxiety as the dependent variable with a pooled OR of 1.14 (95% CI: 1.07-1.23). Three cohort studies were found: two studies detected the association of baseline anxiety with the risk of MetS, one of the studies demonstrated a significant association, but a similar result was not found in another study; one study showed no significant association between baseline MetS and the risk of anxiety.

Conclusion

Cross-sectional studies indicated an association between anxiety and MetS. The results from cohort studies are still inconsistent and limited. More large-scale prospective studies are needed to further reveal the causal relationship of anxiety with MetS.

Clinical symptoms, thyroid dysfunction, and metabolic disturbances in first-episode drug-naïve major depressive disorder patients with suicide attempts: A network perspective

BACKGROUNDS

Co-occurrence of thyroid dysfunction, metabolic disturbances, and worsening clinical symptoms in major depressive disorder (MDD) patients with suicidal attempts (SA) are common. However, their relationship in SA patients remains unexplored. We aimed to (1) determine the independent association of thyroid dysfunction, clinical symptoms, and metabolic disturbances with SA; and (2) identify their interactions in SA patients via the network approach.

METHODS

1718 FEDN MDD patients were recruited. Depressive, anxiety, and psychotic symptoms were assessed by the Hamilton Rating Scale for Depression (HAMD), the Hamilton Rating Scale for Anxiety (HAMA), and the Positive and Negative Syndrome Subscale positive subscale, respectively. The serum levels of thyroid hormones and other metabolic parameters were assessed. Logistic regression model was applied to determine the correlates of SA. Network analysis was applied to determine the interaction between thyroid dysfunction, clinical symptoms, and metabolic disturbances.

RESULTS

SA patients had significant worse metabolic disturbances, thyroid dysfunction, and clinical symptoms than non-SA patients. Thyroid peroxidases antibody, thyroid stimulating hormone (TSH), HAMD scores, HAMA scores, and systolic blood pressure was independently associated with SA. Network analysis suggested that TSH was the hub of the network, exhibiting substantial associations with metabolic disturbances, anxiety, and psychotic symptoms in SA patients.

CONCLUSIONS

Our work highlights the predominant role of serum TSH levels in the pathophysiology of SA. Regular thyroid function tests might help early detect SA. Targeting increased TSH levels may help reduce metabolic disturbances and clinical symptoms in SA patients.

Association between thyroid dysfunction, metabolic disturbances, and clinical symptoms in first-episode, untreated Chinese patients with major depressive disorder: Undirected and Bayesian network analyses

AIMS

Thyroid dysfunction and metabolic disturbances are common in major depressive disorder (MDD) patients. We aimed to assess the relationship between thyroid dysfunction, metabolic disturbances, and clinical symptoms in Chinese first-episode, drug-naïve (FEDN) MDD patients using undirected and Bayesian network methods.

METHODS

1718 FEDN MDD patients were recruited. Serum levels of free triiodothyronine (FT3), free thyroxine (FT4), thyroid stimulating hormone (TSH), anti-thyroglobulin (TgAb), thyroid peroxidases antibody (TPOAb), total cholesterol (TC), total triglycerides (TG), high-density lipoprotein (HDL-C), low-density lipoprotein (LDL-C), and glucose were assessed. Blood pressure and body mass index were measured. Hamilton Rating Scale for Depression (HAMD), Hamilton Rating Scale for Anxiety, and positive subscale of Positive And Negative Syndrome Scales were used to detect clinical symptoms. An undirected network with EBICglasso default and a directed acyclic graph (DAG) using the Bayesian network approach was conducted.

RESULTS

The prevalence rates of clinical symptoms, thyroid dysfunction, and metabolic dysfunction were as follows: anxiety (n=894, 52%), psychotic symptoms (171, 10%), subclinical hypothyroidism (SCH, n=1041, 61%), abnormal TgAb (n=297, 17%), abnormal TPOAb (n=438, 25%), hyperthyroidism (n=5, 0.3%), hypothyroidism (n=3, 0.2%), hyperglycemia (n=241, 14%), hypertriglyceridemia (n=668, 39%), low HDL-C (n=429, 25%), hypercholesterolemia (421, 25%), abnormal TC (357, 21%), abnormal LDL-C (185, 11%). overweight or obesity (n=1026, 60%), and hypertension (n=92, 5.4%). Both networks demonstrated serum TSH and TC levels and the severity of depression played an important role in the pathophysiology of MDD.

CONCLUSIONS

MDD patients may have thyroid and metabolic dysfunction in the early stage. Targeting hypercholesterolemia, depressive symptoms, and SCH in MDD patients may hold promise in reducing clinical symptoms, metabolic disturbances, and thyroid dysfunction.

Association between serum 25-hydroxyvitamin d and myeloperoxidase: A cross-sectional study of a general population in China

Background

Several studies have found a strong association between cardiovascular diseases and myeloperoxidase (MPO) as a marker of oxidative stress. Although the anti-inflammatory effects of vitamin D in adults have been validated, evidence about the relationship between MPO and 25(OH)D is lacking. This study aimed to investigate the relationship between MPO and 25(OH)D in the general Chinese population.

Methods

From November 2018 to August 2019, a total of 6414 subjects were enrolled in a tertiary referral hospital in China, which included 3,122 women and 3,292 men. The dependent and independent variables were MPO and 25(OH)D, respectively. The confounders included age, sex, body mass index, waist-hip ratio, smoking status, alcohol drinking status, calcium, and parathyroid hormone concentration.

Results

In the fully adjusted model, we found that MPO decreased by 0.12 (95% CI −0.16, −0.08), ng/mL for each unit (1 nmol/L) increase in 25(OH)D. When 25(OH) D was divided into quartiles, compared with Q1 (< 41.4 nmol/L), the adjusted beta coefficients (β) of MPO in Q2–Q4 were −2.29 (95% CI, −4.31 to −0.27), −4.76 (95% CI, −6.83 to −2.69), and −6.07 (95% CI, −8.23 to −3.92), respectively (P for the trend < 0.0001). When 25(OH) D was divided according to clinical severity, compared with the severely deficient (< 30 nmol/L) s≥ 30, < 50 nmol/L) and sufficient groups (≥ 50 nmol/L) were −2.59 (95% CI, −5.87 to 0.69) and −5.87 (95% CI, −9.17 to −2.57), respectively (P for the trend < 0.0001).

Conclusion

After adjusting for age, sex, BMI, waist-hip ratio, smoking status, alcohol status, calcium, and PTH, circulating 25(OH)D was negatively associated with MPO.

Sex-specific Association of Subclinical Hypothyroidism With Incident Metabolic Syndrome: A Population-based Cohort Study

OBJECTIVE

Subclinical hypothyroidism is known to increase the risk of cardiovascular diseases and mortality. However, the longitudinal association between subclinical hypothyroidism and incident metabolic syndrome remains unclear.

METHODS

A total of 3615 participants from Beijing Health Management Cohort were enrolled from 2012 to 2014 and followed through 2019. People were placed into subclinical hypothyroidism and euthyroidism groups according to serum-free thyroxine and TSH concentrations. We used Cox proportional hazards regression models to investigate the relationship between TSH level and incident metabolic syndrome considering the modification effect of sex and age.

RESULTS

Of 3615 participants, 1929 were men (53.4%); mean (SD) age was 43.51 (11.73) years. Throughout the follow-up (median [interquartile range], 3.0 [2.8-3.2] years), 738 individuals developed metabolic syndrome. Subclinical hypothyroidism was significantly associated with metabolic syndrome development only in men, and the adjusted hazard ratio was 1.87 (95% CI, 1.21-2.90) compared with euthyroidism group. Of note, there was no increased risk of metabolic syndrome in people aged 50 years or older with subclinical hypothyroidism.

CONCLUSIONS

Subclinical hypothyroidism is associated with incident metabolic syndrome in young men. Further studies are needed to evaluate the targeted threshold and benefit of thyroid hormone replacement therapy for metabolic health.

Construction of Xinjiang metabolic syndrome risk prediction model based on interpretable models

Background

We aimed to construct simple and practical metabolic syndrome (MetS) risk prediction models based on the data of inhabitants of Urumqi and to provide a methodological reference for the prevention and control of MetS.

Methods

This is a cross-sectional study conducted in the Xinjiang Uygur Autonomous Region of China. We collected data from inhabitants of Urumqi from 2018 to 2019, including demographic characteristics, anthropometric indicators, living habits and family history. Resampling technology was used to preprocess the data imbalance problems, and then MetS risk prediction models were constructed based on logistic regression (LR) and decision tree (DT). In addition, nomograms and tree diagrams of DT were used to explain and visualize the model.

Results

Of the 25,542 participants included in the study, 3,267 (12.8%) were diagnosed with MetS, and 22,275 (87.2%) were diagnosed with non-MetS. Both the LR and DT models based on the random undersampling dataset had good AUROC values (0.846 and 0.913, respectively). The accuracy, sensitivity, specificity, and AUROC values of the DT model were higher than those of the LR model. Based on a random undersampling dataset, the LR model showed that exercises such as walking (OR=0.769) and running (OR= 0.736) were protective factors against MetS. Age 60 ~ 74 years (OR=1.388), previous diabetes (OR=8.902), previous hypertension (OR=2.830), fatty liver (OR=3.306), smoking (OR=1.541), high systolic blood pressure (OR=1.044), and high diastolic blood pressure (OR=1.072) were risk factors for MetS; the DT model had 7 depth layers and 18 leaves, with BMI as the root node of the DT being the most important factor affecting MetS, and the other variables in descending order of importance: SBP, previous diabetes, previous hypertension, DBP, fatty liver, smoking, and exercise.

Conclusions

Both DT and LR MetS risk prediction models have good prediction performance and their respective characteristics. Combining these two methods to construct an interpretable risk prediction model of MetS can provide methodological references for the prevention and control of MetS.

Women with Subclinical Hypothyroidism are at Higher Prevalence of Metabolic Syndrome and Its Components Compared to Men in an Older Chinese Population

Purpose: This study investigated the impact of sex differences on the relationship of subclinical hypothyroidism (SCH) with the prevalence of metabolic syndrome (MetS) and its components in an older Chinese population.Methods: The study included 1842 older Chinese individuals aged 65 years or older who received annual health checkups. The impact of sex differences on the relationship of SCH with the prevalence of MetS and its components was investigated by multivariate logistic regression analysis. Interaction effect between sex and SCH on the prevalence of MetS and its components were evaluated using a multivariate logistic regression model which includes interaction terms (sex-SCH).Results: The study comprised 1701 (92.3%) individuals with euthyroidism and 141 (7.7%) with SCH. In men, SCH was not associated with MetS or any components of the MetS. In women, the SCH group had higher prevalence of MetS [odds ratio (OR), 1.870; 95% confidence interval (CI), 1.136-3.079], abdominal obesity (OR, 1.693; 95% CI, 1.043-2.748), hypertriglyceridemia (OR, 1.711; 95% CI, 1.054-2.775) and low high-density lipoprotein cholesterol (HDL-C) (OR, 3.039; 95% CI, 1.576-5.861). There was an interaction between sex and SCH in terms of the effect on the prevalence of MetS and its components, including abdominal obesity and hypertriglyceridemia (P < .01 for all), and with a trend for low HDL-C (P = .098).Conclusion: There were sex differences in the correlation of SCH with the prevalence of MetS and its components in the older Chinese population. An interaction effect between sex and SCH on the prevalence of MetS and its components was found.

The association between subclinical hypothyroidism and metabolic syndrome: an update meta-analysis of observational studies

The association between subclinical hypothyroidism (SCH) and metabolic syndrome (MetS) has been widely discussed. This study aimed to conduct an update and comprehensive meta-analysis to reveal the risk of MetS and its components in SCH. PubMed, Embase and ISI Web of Knowledge were searched to identify relevant studies through February 20^th, 2020. Review Manager 5.3 and Stata 14.0 were used to conduct the meta-analysis. Both fixed-effects and random-effects models were used. In total, 18 articles (19 studies) incorporating 79,727 participants were included. The pooled OR for MetS comparing subjects with SCH with euthyroid subjects was 1.28 (95% CI: 1.19 to 1.39, p = 0.04, I² = 40%). Subgroup analysis results showed significant associations of SCH and MetS in the adult subgroup (OR = 1.28, 95% CI: 1.18-1.40), Asian population subgroup (OR = 1.30, 95% CI: 1.19-1.42) and cross-sectional study design subgroup (OR = 1.31, 95% CI: 1.16-1.47). Significant associations of SCH and MetS also existed in all MetS definition criteria subgroups except the Chinese Diabetes Society (CDS) subgroup. SCH was correlated with MetS and was not affected by the subgroup analysis stratified by the proportion of females in the total population, the TSH cutoff value in SCH diagnostic criteria, or the adjustment for confounding factors. SCH was identified to be associated with an increased risk of obesity, hypertension, high triglyceride (TG) levels and low high-density lipoprotein cholesterol (HDL-C) levels. In conclusion, SCH is significantly associated with an increased risk of MetS and four out of five components of MetS.

The prevalence and related factors of metabolic syndrome in outpatients with first-episode drug-naive major depression comorbid with anxiety

Metabolic syndrome (MetS) is associated with depression, but its role in major depressive disorder comorbid with anxiety (AMD) is unclear. This study aimed to investigate the prevalence and clinical correlates of MetS in first-episode drug-naive (FEDN) patients with AMD in a Chinese Han population. In total, 1380 FEDN outpatients with AMD were recruited in this cross-sectional study. The sociodemographic features, clinical characteristics, history of suicide attempts, thyroid-stimulating hormone (TSH) levels, and MetS parameters of each subject were evaluated. All subjects were rated on the Hamilton Depression Rating Scale (HAM-D), Hamilton Anxiety Rating Scale (HAM-A), and the Positive and Negative Syndrome Scale positive symptom subscale. The prevalence of MetS among AMD patients was 8.04%. Compared to the non-MetS group, age, age of onset, TSH level, HAM-A and HAM-D scores, history of attempted suicide, and comorbid psychiatric symptoms were higher in the MetS group. Those in this group were also more likely to be married, and they had a lower educational level. Furthermore, age, psychiatric symptoms, suicide attempts, and higher TSH levels were independently associated with MetS in AMD patients. This study suggests a lower prevalence of MetS in FEDN patients with AMD in a Chinese Han population. Older age, comorbid psychiatric symptoms, history of attempted suicide, and higher TSH levels are related factors for MetS in AMD patients.