Factors Associated with Quality of Life among People with Atrial Fibrillation: Jordan Atrial Fibrillation Registry Study

Author:

Al-Bashaireh Ahmad M.1ORCID,Alkouri Osama2ORCID,Alharbi Abdulhafith3ORCID,Khader Yousef4ORCID,Hammoudeh Ayman5ORCID,Aljawarneh Yousef1ORCID,Alotaibi Nader E.6,Qaladi Omar7ORCID,Ababneh Anas2ORCID,Schultz Tim8

Affiliation:

1. Department of Nursing, Faculty of Health Sciences, Higher Colleges of Technology, Abu Dhabi P.O. Box 1626, United Arab Emirates

2. Faculty of Nursing, Yarmouk Univerity, P.O. Box 566, Irbid 21163, Jordan

3. College of Nursing, University of Hail, Hail 21424, Saudi Arabia

4. Department of Public Health, Community Medicine, Jordan University of Science and Technology, Irbid 21163, Jordan

5. Istishari Hospital, Amman 840431, Jordan

6. Medical Surgical Nursing Department, College of Nursing, King Saud University, Riyadh 12372, Saudi Arabia

7. Community and Psychiatric Mental Health Nursing Department, King Saud University, Riyadh 11362, Saudi Arabia

8. Flinders Health and Medical Research Institute, Flinders University, Sturt Road, Bedford Park South Australia 5042, P.O. Box 2100, Adelaide, SA 5001, Australia

Abstract

Background and Objectives: Atrial fibrillation (AF) is a common arrhythmia that may adversely affect the quality of life (QoL). Several factors could be associated with the QoL among patients with AF; however, evidence regarding these factors is still limited and controversial. Therefore, this study aimed to identify the level of QoL and its associated factors among Jordanian patients with AF. Subjects and methods: A case study design was implemented. A sample of 620 participants were recruited from 28 outpatient clinics registered in the Jordan atrial fibrillation registry AF (JoFIB). Data on QoL were gathered through the self-reported Atrial Fibrillation Effect on Quality-of-life tool (AFEQT). A QoL questionnaire was validated in this population before starting this study. The cardiac nurse then provided the research assistant with data relating to patients’ characteristics and associated comorbidities. Results: The overall AFEQT scores were positively skewed (median 21.3, IQR: 14.4–31.9). This pattern was reflected for the AFEQT sub-scales ‘Symptoms’ (20.8, 8.3–33.3), ‘Daily activities’ (16.7, 10.4–27.1), and ‘Treatment concerns’ (27.8, 19.4–41.7), whereas ‘Treatment satisfaction’ was negatively skewed (91.7, 83.3–91.7). Patients in the higher quartiles, indicating a better QoL, tended to be younger and were less likely to experience dyslipidemia, stroke, pulmonary hypertension, or other comorbidities. Over 90% of patients were currently experiencing AF, and patients with a better QoL tended to be less likely to be currently experiencing AF and more likely to have had their latest episode of AF more than a month ago (compared to less than a month ago). Age, BMI, dyslipidemia, heart failure, COPD, CAD, history of ablation, and the use of anticoagulants were significantly associated with the overall AFEQT score (R2 = 0.278). Conclusions: This study demonstrates that AF Jordanian patients had low levels of QoL. Patients in higher quartiles for the overall AFEQT score were younger, with fewer disease comorbidities and less experience of current AF episodes. Several modifiable and non-modifiable factors were associated with QoL in AF patients. Age, BMI, dyslipidemia, heart failure, COPD, CAD, history of ablation, and the use of oral anticoagulants were significantly associated with the overall AFEQT score. Healthcare providers should target these factors as indicators or interventions for which QoL is continuously monitored.

Publisher

MDPI AG

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