Determinants of quality of life among COVID-19 patients in Southwestern region of Bangladesh

Study design and participants

This cross-sectional study was conducted on COVID-19 patients of Jhenaidah district, Bangladesh. Jhenaidah is located in the southwestern part of Bangladesh with an area of 1.964.77 km² and 1,771,304 populations. The survey was conducted on COVID-19-positive patients from March 1, 2021, to March 21, 2021. Information was collected through computer-assisted telephone interviews using a structured questionnaire. The participants were recruited through social media (e.g., Facebook). A total of 557 interviews were taken. Each of the interviews was recorded by a recorder along with completing the Google Forms of the questionnaire manually to assure the accuracy of the data. Participation was voluntary. The person who avoided the phone calls, who were disturbed to participate, performed incomplete interviews, and who were untraceable were excluded from the study.

Sample size

Since in this study, HRQoL outcome was measured as a binary outcome, the following formula, which is recommended by Walters (2002),^[5] has been used to determine the sample size,

Where,

n_OR = Sample size

Z_1–α/2 = Value of standard normal distribution for the 100(1–α/2) percentiles.

Z_1–β = Value of standard normal distribution for the 100(1–β).

OR_Binary = Odds ratio

$\overline{\pi }$ = average proportion on the different group.

About 5% level of significance and 90% power were considered for the study. Since there was no previous study in Bangladesh on HRQoL of COVID-19 patients using the EQ-5D-5L instrument in Bangladesh, odds ratio and average proportion were used of Ping (2020)^[6] which were used in this study. The odds ratio of the Ping’s (2020)^[6] study was ranging from 0.166 ($\overline{\pi }$= 0.013) and 9.156 ($\overline{\pi }$ = 0.017). Using those values at 5% level of significance and 90% power, we get sample sizes 508 and 257. Finally, in a computer-assisted telephone survey conducted in 2019,^[7] the overall response rate among the known eligible respondent was 89.0%. Adjusting the response rate, we got the sample size 570 and 288. Considering the complex nature of the HRQoL, we have chosen 570 as the final sample size of this study.

Data collection

Data were collected from March 1, 2021, to March 21, 2021, in Jhenaidah, Bangladesh, during home confinement through telephone (or mobile) interviews and records review. We used an online structural questionnaire related to HRQoL of COVID-19 patients. We recorded each interview by a recorder and completed the Google Forms of the questionnaire manually to assure the accuracy of the data. By briefing the actual motive of the data collection, informed consent was attained from the participant. Hence, the participation was voluntary. We have made the phone call to 570 patients. Among those patients, 13 patients, who avoided the phone calls or were disturbed to participate or performed incomplete interviews, or were untraceable, were excluded from the study. Therefore, the final study population was 557.

Measures

Sociodemographic and clinical factors

The independent variables used in this study were categorized as sociodemographic and clinical factors such as gender, age, education, occupation, physical exercise, body mass index (BMI), comorbidities, and place of care.

Statistical analysis

Frequency and percentage distribution were used to show the descriptive nature. Chi-square test was deployed to find out the association between the domains of HRQOL and sociodemographic and clinical factors. Finally, binary logistic regression was fitted to find out the predictors of HRQoL. All the statistical analyses were performed using R-programming version 4.0.

Ethical statement

The participation of COVID-19 patients in this study was voluntary for this study. The objective and nature of this study were explained to each participant, and their informed consent was taken before the interview. The unanimity of the participants was ensured, and the guidelines of Helsinki Declarations for conducting any study using human subjects were followed in this study.

Sociodemographic and clinical characteristic of participants

A total of 557 participants (417 males and 140 females) responded to the survey. Most of the participants (51.17%) were less than 41 years old. About 19.93% of participants were in the age group of 41–49 years and the rest (more than 50 years) were 28.90%. Concerning the education level, the majority (58.89%) have higher education (more than 10 years), 35.01% have an education level of 6–10 years, and 6.10% have less than 5 years. About 52.78% service holders participated in this study, 13.29% were unemployed, and the rest (33.93%) had other jobs. About 32.68% commit to regular exercise and 67.32% don’t do it regularly. We found 83.30% of the participants took treatments at home when they became COVID-19 positive and 16.70% were treated in hospital. The majority (52.06%) had normal weight, 43.45% had overweight, and the least (4.49%) had underweight. About 8.98% of the participants reported that they suffered from a heart problem. Most patients (82.23%) informed that they did not have hypertension, and 15.26% had diabetes. It was a matter of joy that 98.38% of the patients had no stroke.

Health-related quality of life

Among the five dimensions of EQ-5D-5L, only 15.26% reported moderate or severe mobility problem. The percentage of moderate or severe usual activities problem was 11.85. The most frequently reported problems were anxiety and depression, approximate two-fifth of the participants described moderate or severe problem. Whereas, a tiny fraction (2.51%) of the respondents felt moderate or severe problem for self-care. Using the Thai value set,^[9] the overall health states was determined. More than half (57.27%) of the study population faced moderate or severe problem.

Association of HRQoL with sociodemographic and clinical factors

There are 11 variables including gender, age, education, occupations, regular exercise, place of care, BMI, heart problem, hypertension, diabetes, and stroke. Dependent variables – quality, mobility, self-care, usual activities, pain discomfort, and anxiety-depression all are categorical variables. Among the participants, women (25%) were more interested to report the problem in mobility than men (12%). Similarly, women reported the most problem in self-care and usual activities than men (7.1% compare to 1% and 22.9% compare to 8.2%, respectively). Compare to others age group, 50+ age group people were more likely to indicate a problem in mobility (25.5%), usual activities (16.6%), pain discomfort (58.4%), and anxiety-depression (53.4%). Opposite result was found for quality of life of the people cured from COVID-19. Among the groups, less than 41 years age people were more likely to report severe problem in context of their life quality (63.9%). Less than 5 years educated respondents claimed that they felt the problem in quality (67.6%) and usual activities (20.6%) compare to other groups. On the other hand, people who had 6–10 years of education were more likely to face anxiety-depression (52.8%). Unemployed participants reported the problem in mobility (32.4%), self-care (10.8%), usual activities (23%), and anxiety-depression (47.3%) than other groups. Compare to the people had a tendency to exercise regularly, no regular exercise respondents were more likely to face anxiety-depression problem (46.1%). Respondents receiving care in the hospital during COVID-19 reported the most problem in mobility (25.8%), self-care (6.5%), and usual activities (20.4%). Those who had heart problem were more likely to report problem in mobility (46%), usual activities (30%), pain discomfort (54%), and anxiety-depression (56%). About 22.2% and 52.5% of respondents who had hypertension problem reported the problem in mobility and anxiety-depression, respectively. On the contrary, people who had no hypertension problem were more likely to report problem in quality of life and similar result was found for diabetic people (60.2%). Majority of the respondents (88.9%) who had any stroke history were more prone to anxiety-depression.

Logistics regression

Table 1 presents the odds ratio of the risk factors for different domains for COVID-19 patients. The logistic regression demonstrated that gender, age, occupation, place of care, and heart problem had a significant association with mobility dimension. Male had 0.304 times (OR = 0.304 CI: 0.166–0.552) fewer mobility difficulties than female whereas aged people had faced great difficulties (for people aged more than 50, OR = 3.92, CI: 2.03–7.75, P < 0.001) in mobility compared to the people aged less than 41. People who were service holders had 64% less (OR = 0.354, CI: 0.173– 0.726) mobility problem than unemployed people (maximum unemployed people are in <18 or 50+ age group). Place of care is a significant factor to determine COVID-19 patient’s post-COVID-19 health conditions. People who had to take treatment in a hospital were more likely (OR = 1.971 CI: 1.056–3.615) to face mobility difficulties. Heart patients were more likely to face mobility difficulties compared to the people who had no heart problem.

Gender, occupation, place of care, and heart problems were significantly associated with the self-care module. Male had 0.123 times (OR = 0.123, CI: 0.028–0.435) fewer self-caring problems than female. Service holders were felt 92% (OR = 0.079, CI: 0.010–0.370) fewer problems in self-caring than unemployed people while the people who were involved in other occupations felt 76% (OR = 0.240, CI: 0.059–0.854) fewer problems in self-caring compared to unemployed people. People who took treatment in hospital (OR = 3.665, CI: 1.037–12.456) and the people who had heart problem (OR = 8.969, CI: 2.407–34.280) were more likely to face difficulties in self-caring.

Results showed that male (OR = 0.269, CI: 0.146–0.492), age (age group 41–49: OR = 2.626, CI: 1.226–5.593; and age group more than 50: OR = 2.312, CI: 1.144–4.720), service holder (OR = 0.422, CI: 0.192–0.937), care at hospital (OR = 2.137, CI: 1.106–4.024), and heart problem (OR = 2.771, CI: 1.294–5.768) were significantly associated with usual activities dimension.

People aged more than 50 were more prone (OR = 3.089, CI: 2.024–4.741) to feel pain or discomfort in their body compared to the people aged less than 41. Diabetic people were more likely (OR = 1.689 CI: 1.032–2.774) to have pain or discomfort.

Educated people such as people who had education more than 10 years were less prone (OR = 0.51, CI: 0.33–0.78) to feel anxiety or depression. Result shows that regular exercise plays a significant role in reducing anxiety or depression. People who exercise regularly were 56% less likely (OR = 0.44, CI: 0.29–0.66) to feel anxiety or depression in post-COVID-19 period compared to the people who did not exercise regularly. Diabetic people were more likely (OR = 1.92, CI: 1.14–3.25) to feel anxiety or depression than non-diabetic people.

People who were aged more than 50 experiencing 40% less bad quality of life than people aged less than 41. Diabetic people were less likely (OR = 0.574, CI: 0.349, 0.937) to have bad quality of life.

Limitations

The authors are concerned with the limitation of telephone interviews which might not address some more precise information as unveiled by face-to-face interviews.