Michael R. Le Grande, Alison Beauchamp, Andrea Driscoll, Debra Kerr, Alun C Jackson
{"title":"Is Self-Reported Obstructive Sleep Apnea Associated with Cardiac Distress? A Network Analysis","authors":"Michael R. Le Grande, Alison Beauchamp, Andrea Driscoll, Debra Kerr, Alun C Jackson","doi":"10.4103/hm.hm-d-24-00017","DOIUrl":null,"url":null,"abstract":"\n \n \n The relationship between obstructive sleep apnea (OSA), obesity, various metabolic variables, and psychosocial outcomes is complex. No studies have examined the association between these predictors and disease-specific distress related to heart disease (cardiac distress). We aimed to study the association between OSA and cardiac distress using a network analysis framework.\n \n \n \n This secondary analysis of an observational cross-sectional study conducted in 2021 consisted of 405 hospital- and community-sourced adults from Australia and the United States who reported an acute coronary event (such as a myocardial infarction, or procedures such as coronary artery bypass graft surgery, or percutaneous coronary intervention) in the previous 12 months. Participants were surveyed in relation to sociodemographic variables, clinical risk factors, comorbidities (including time since event, OSA, obesity, diabetes, hypertension, and hyperlipidemia), and cardiac distress (reported by the Cardiac Distress Inventory Short-Form). These data were subjected to bootstrapped exploratory graph analysis (EGA), which identifies the dimensions of variables that cluster together. Variables that contributed to the EGA dimensions were used to predict cardiac distress using multivariable logistic regression.\n \n \n \n Three distinct dimensions were identified by the EGA: Dimension 1 – clinical risk factors and conditions including OSA, Dimension 2 – variables related to the heart event, and Dimension 3 – variables closely related to cardiac distress. For Dimension 1, only OSA was a significant predictor of cardiac distress in the fully adjusted model (adjusted odds ratio = 2.08, 95% confidence interval = 1.02–4.25, P = 0.044). Further analysis indicated that OSA was associated with physical challenges and changes in roles and relationships.\n \n \n \n This study identified that self-reported OSA is associated with cardiac distress, particularly distress that was associated with physical challenges and changes to roles and relationships. These findings imply that OSA could potentially increase stress in a relationship; however, distress was only assessed from the perspective of the participant with OSA in this study. EGA is a useful method for describing complex associations between diverse predictor variables such as OSA and cardiac distress. Owing to the self-reported aspect of the data, further investigation to confirm study outcomes is warranted.\n","PeriodicalId":34653,"journal":{"name":"Heart and Mind","volume":null,"pages":null},"PeriodicalIF":1.0000,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Heart and Mind","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4103/hm.hm-d-24-00017","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"CARDIAC & CARDIOVASCULAR SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
The relationship between obstructive sleep apnea (OSA), obesity, various metabolic variables, and psychosocial outcomes is complex. No studies have examined the association between these predictors and disease-specific distress related to heart disease (cardiac distress). We aimed to study the association between OSA and cardiac distress using a network analysis framework.
This secondary analysis of an observational cross-sectional study conducted in 2021 consisted of 405 hospital- and community-sourced adults from Australia and the United States who reported an acute coronary event (such as a myocardial infarction, or procedures such as coronary artery bypass graft surgery, or percutaneous coronary intervention) in the previous 12 months. Participants were surveyed in relation to sociodemographic variables, clinical risk factors, comorbidities (including time since event, OSA, obesity, diabetes, hypertension, and hyperlipidemia), and cardiac distress (reported by the Cardiac Distress Inventory Short-Form). These data were subjected to bootstrapped exploratory graph analysis (EGA), which identifies the dimensions of variables that cluster together. Variables that contributed to the EGA dimensions were used to predict cardiac distress using multivariable logistic regression.
Three distinct dimensions were identified by the EGA: Dimension 1 – clinical risk factors and conditions including OSA, Dimension 2 – variables related to the heart event, and Dimension 3 – variables closely related to cardiac distress. For Dimension 1, only OSA was a significant predictor of cardiac distress in the fully adjusted model (adjusted odds ratio = 2.08, 95% confidence interval = 1.02–4.25, P = 0.044). Further analysis indicated that OSA was associated with physical challenges and changes in roles and relationships.
This study identified that self-reported OSA is associated with cardiac distress, particularly distress that was associated with physical challenges and changes to roles and relationships. These findings imply that OSA could potentially increase stress in a relationship; however, distress was only assessed from the perspective of the participant with OSA in this study. EGA is a useful method for describing complex associations between diverse predictor variables such as OSA and cardiac distress. Owing to the self-reported aspect of the data, further investigation to confirm study outcomes is warranted.