To our knowledge, this is the first study to use EQ5D 5L UK value set to assess the patients’ HRQOL with chronic disease in Lebanon. A recently published study highlighted negative impact of type II diabetes on the patients' quality of life in Middle Eastern countries[4]. In our study, patients with a history of heart disease and hypertension, had a negative impact on their quality of life compared to patients without heart disease or hypertension, similar to previous studies[16–18]. Furthermore, results showed a decreasing trend of the HRQOL of patients with dyslipidemia and diabetes mellitus. This negative correlation with the HRQOL was not statistically significant was probably due to the low number of participants. Evaluation of EQ5D in China for different chronic diseases including heart disease, diabetes and hypertension demonstrated a stronger negative correlation of HRQOL with hypertension than with diabetes mellitus[17].
The number of comorbidities is another factor influencing the patient’s quality of life. This study demonstrated an inverse correlation between HRQOL and the number of comorbidities. This inverse relationship has also been observed elsewhere in various chronic conditions such as dementia, psoriasis and cancer[19–22]. Furthermore, the number of prescribed medications equal or more to seven being prescribed 7 or more medication was negatively correlated with the HRQOL which is in line with previous findings in the literature[23]. In fact, the number of prescribed drugs may be considered as a proxy for general morbidity and another indicator of comorbid conditions that were not actively sought by patients[23].
Anti-hypertensive medications were the most frequently used s which is expected since hypertension was the most prevalent cardiovascular disease.
The HRQOL was affected by the sociodemographic characteristics. Female patients had poorer HRQOL compared to male patients. Many studies demonstrated gender differences in HRQOL among patients with chronic diseases such as coronary artery disease; for instance, Yinko et al found that after adjusting for disease characteristics and management, several factors were found to be significantly associated with HRQOL including femininity score, household responsibility and social support[24].
Elderly people were more represented in this sample due to the nature of the studied diseases. Increased age was associated with poorer HrQOL in both bivariate and multivariate linear regression. The coefficient for age was greater than that of the frequency of hospitalization and the presence of hypertension. These results should be interpreted with caution as a cut off of 75 years of age was considered for analysis meaning that only advanced age (> 75) is strongly and significantly correlated with poorer health related quality of life.
More patients live with their family than alone due to characteristics of the Middle Eastern culture. Most of the patients have Middle to high socio-economic status probably because the pharmacies are in areas where middle to high income people live (to validate). More than half of the patients were on their current treatment for more than 12 month which increases the internal validity of the study showing that we included patients with chronic diseases. Majority of patients had more than two consultations per year, reflecting the rate of visits of patients who have chronic diseases. Having middle to high socio-economic status, these patients had more access to their health care professionals.
More patients lived with their family than alone owing to the Middle Eastern culture and social consideration. Most of the patients reported middle to high socio-economic status which may reflect the location of these pharmacies. Patients with higher socioeconomic status had statistically significantly better HRQOL. Previous studies demonstrated similar association between level of income, education, social class and HRQOL[25, 26].
More than half of the patients were on their current treatment for more than 12 months which could be considered a validation of the targeted population of those with chronic diseases. The majority of patients did more than two physician consultations per year, which would reflect the rate of visits of patients with chronic diseases, their access to healthcare professionals, and reported socioeconomic status[25, 26].
The frequency of physician and or hospital visits can be considered as surrogate markers of the severity of the disease and comorbidities, which explains the positive correlation between these two factors and the HRQOL. The study results confirm previous study findings in various patient groups showing a link between healthcare resource utilization and HRQOL. In addition, EQ5D was found to be an accurate measure that predicts mortality, emergency department utilization and hospital discharge rates[27].
Furthermore, the positive correlation of the treatment satisfaction with HRQOL, further consolidates the results of a study done in Lebanon by Khabaz et al that showed positive associated between increased adherence to treatment, a higher global satisfaction and an increase in quality of life[28].
As for the EQ5D descriptive part, this study demonstrated that self-care was the least affected dimension with 72.5% of the people reporting having no problems with self-care. Although Zhang Li et al reported that hypertension was related to lower scores in mobility, self-care and usual activity, our findings might be partly explained by the fact that the survey was done at community pharmacies where patients were filling their prescriptions in person[16, 18]. Similar to a previous study, the score in the domain of pain/discomfort among individuals with cardiovascular disease was the most affected dimension[29]. In fact, Zang li et al reported that hypertensive individuals with body pain/discomfort might have a poorer HRQOL than the general population[18].
The main strength of this study is that it is the first and only study to measure the EQ5D by health utility index scores based on UK Tariff, which reflects EQ5D utility index scores among patients with chronic diseases in Lebanon.
The study limitations include the health utility index which could be influenced by the choice of value set used to convert self-classification scores. Also, patient recruitment was limited to one geographic area (capital city) and may have limited the subgroup analysis of EQ5D per disease. EQ5D and socioeconomic status were self-reported which lead to potential subjective bias. In additions, a sampling bias may exist because only patients who presented personally to the pharmacy were included so generally, they might have higher mobility and thus better quality of life. In the absence of a health utility index specific to Lebanon, EQ5D UK value set was used.