Predisposing, enabling, and need factors influencing health-related quality of life among people with metabolic syndrome

Abstract

Background: Metabolic syndrome (MetS) continues to impact the health-related quality of life (HRQoL) of patients despite various available therapeutic interventions. There is a dearth of information on how patient-centered factors holistically predict HRQoL to provide more insights on addressing MetS.

Objective: To predict the HRQoL of patients with MetS in the Southern states, using the predisposing, enabling, and need factors.

Methods: The study adopted a cross-sectional approach in collecting 706 complete surveys on HRQoL assessment using the EQ-5D-5L survey and demographic characteristics based on the predisposing, enabling, and need factors of Andersen's Behavioral model. The study focused on people with MetS in the southern states of the United States. Multinomial logistic regression was conducted to investigate the relationship between the number of comorbidities and each HRQoL dimension. Ordinal regression was used to explore factors predicting HRQoL. Sensitivity analysis was conducted using bootstrapping analysis to evaluate the regression's robustness.

Results: Over 70% were females and 30% had at least a bachelor's degree, while 47% were married. Most respondents (71.1%) had no problem with self-care. However, 20.0% had severe problems with pain, while the highest proportion (8.6%) was observed for extreme problems with anxiety or depression. A unit increase in comorbidities resulted in higher odds of having extreme problems with mobility (odds ratio [OR] = 1.95), usual activities (OR = 1.73), and pain (OR = 1.70). Only 40.8% of the respondents had good HRQoL, compared to 26.2% with poor HRQoL. Age, race, geographical area, marital status, household income, number of prescription drugs, comorbidities, and body mass index were predictors of HRQoL.

Conclusion: An increase in comorbidities significantly increased the odds of having challenges with the HRQoL dimensions. Demographic, socioeconomic, and health-related factors significantly predicted HRQoL. Therefore, health care providers must consider these factors as a component of patient-centered care to address health disparities and promote optimal health outcomes among people with MetS.