The Association Between Symptoms of Anxiety, Depression, and Cardiovascular Risk Factors

Rioli, Giulia; Tassi, Silvia; Mattei, Giorgio; Ferrari, Silvia; Galeazzi, Gian Maria; Mancini, S; Alboni, Silvia; Roncucci, Luca

doi:10.1097/nmd.0000000000000969

Cited by 12 publications

(5 citation statements)

References 47 publications

(26 reference statements)

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“…Poor mental health can have a negative impact on physical health. Evidence shows that mental health problems are responsible for chronic diseases, like cardiovascular disease [13]. Anxiety can also lead to physical symptoms, such as fatigue, sleep problems, and muscle spasms [14].…”

Section: Introductionmentioning

confidence: 99%

Anxiety symptoms and burnout among Chinese medical staff of intensive care unit: the moderating effect of social support

et al. 2020

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Background: Social support can be a critical resource to help medical staff cope with stressful events; however, the moderating effect of social support on the relationship between burnout and anxiety symptoms has not yet been explored. Methods: The final sample was comprised of 514 intensive care unit physicians and nurses in this cross-sectional study. Questionnaires were used to collect data. A moderated model was used to test the effect of social support. Results: The moderating effect of social support was found to be significant (b = − 0.06, p = 0.04, 95%CI [− 0.12, − 0.01]). The Johnson-Neyman technique indicated that when social support scores were above 4.26 among intensive care unit medical staff, burnout was not related to anxiety symptoms. Conclusions: This is the first study to test the moderating effect of social support on the relationship between burnout and anxiety symptoms among intensive care unit staff.

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Section: Introductionmentioning

confidence: 99%

Anxiety symptoms and burnout among Chinese medical staff of intensive care unit: the moderating effect of social support

et al. 2020

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“…In the case of women, an increased likelihood of facing significant risks related to cardiovascular diseases and sleep problems has been observed, especially for those in the postmenopausal stage, which, in turn, can contribute to the development of risks associated with MetS [73]. Additionally, they highlighted factors related to anxiety (TRAIT_ANX), despite the association between MetS and anxiety remaining a subject of debate due to various issues [74], this study, like some others [75][76][77][78], identified anxiety as one of the critical factors that predisposing women to MetS.…”

Section: Use Of Machine Learning With Synthetic Datamentioning

confidence: 80%

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

Gutiérrez-Esparza,

Martinez-Garcia,

Ramírez-delReal

et al. 2024

Nutrients

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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.

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“…The characteristics of the 24 cross-sectional studies are presented in Supplementary Table 3 . Twenty studies reported MetS as the dependent variable ( 12 , 14 , 15 , 17 , 18 , 30 – 37 , 39 , 40 , 43 – 47 ) and four studies reported anxiety as the dependent variable ( 19 , 20 , 22 , 41 ). Twenty-four studies used two methods to diagnose anxiety, seven studies used structured diagnostic interviews, and 17 studies used self-report symptom scales.…”

Section: Resultsmentioning

confidence: 99%

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

Chen²,

Zhou³

et al. 2023

Front. Psychiatry

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ObjectivePrevious 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.MethodsWe 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.ResultsThe 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.ConclusionCross-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.

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The Association Between Symptoms of Anxiety, Depression, and Cardiovascular Risk Factors

Abstract: Inflammation as a common factor in the occurrence of symptoms of anxiety, depression and cardiovascular risk factors: results from an Italian cross-sectional study.

Cited by 12 publications

References 47 publications

Anxiety symptoms and burnout among Chinese medical staff of intensive care unit: the moderating effect of social support

Anxiety symptoms and burnout among Chinese medical staff of intensive care unit: the moderating effect of social support

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

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

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