Background: The Coronavirus Disease 2019 (COVID-19) caused by the SARS-CoV-2 virus has taken the lives of more than 100,000 healthcare workers (HCWs) so far. Those who survived continuously work under immense physical and psychological pressure, and their quality of life (QoL) is impacted. The study aimed to assess the QoL among HCWs in Bangladesh who recovered from COVID-19. Methods: This cross-sectional, telephonic interview-based study was conducted among 322 randomly selected HCWs from Bangladesh who were positive for COVID-19 and recovered from the infection before the interview. Data were collected from June to November 2020. We examined the impact of COVID on the QoL of the participants using the validated Bangladesh version of the World Health Organization (WHO) Quality of life questionnaire brief (WHOQOL-BREF). All analyses were done by STATA (Version 16.1). Results: More than half of the health care professionals were male (56.0%), aged between 26–35 years (51%), and completed graduation (49%). The majority of the study participants in the four domains were married (n = 263, 81%) and living in Dhaka. The average score of the participants was 70.91 ± 13.07, 62.68 ± 14.99, 66.93 ± 15.14, and 63.56 ± 12.11 in physical, psychological, social relationship and environmental domains, respectively. HCWs in urban areas enjoyed 2.4 times better socially stable lives (OR: 2.42, 95% CI: 1.18–4.96) but 72% less psychologically satisfactory lives. Conclusion: HCWs' post-COVID quality of life depended on variable interaction of demographic socioeconomic, including old age, female sex, graduation, and higher monthly income. The findings indicate the issues which should be addressed to improve the quality of life of frontline workers who fight against the pandemic.
Keywords: Bangladesh; COVID-19; Quality of life (QoL); Healthcare workers; WHOQOL-BREF
Supplementary Information The online version contains supplementary material available at https://doi.org/10.1186/s12913-022-07961-z.
The Coronavirus Disease 2019 (COVID-19) caused by the SARS-CoV-2 virus was first identified in China in late 2019 as a cluster of unexplained pneumonia cases. Since then, it has spread worldwide and become a global public health concern by infecting millions of people and claiming hundreds and thousands of lives [[
A Chinese study reported 3000 HCWs infected (3.8%) with five deaths by early February 2020. In Italy, this rate jagged to 10.5% in late April, and 157 HCW deaths were documented in England until early May 2020 [[
According to World Health Organization (WHO), "an individual's perception of their position in life in the context of the culture and value systems in which they live and concerning their goals, expectations, standards, and concerns are defined as the quality of life" [[
A significant decline in QoL was observed among people who worked in healthcare facilities during previous pandemic periods [[
From June 2020 to November 2020, we conducted this research on the COVID-19 positive HCWs identified and confirmed to be such by Reverse Transcription-Polymerase Chain Reaction (RT-PCR) who had either improved clinically or tested negative for the virus. For three days, clinical recovery was classified as a consecutive absence of fever, cough, or respiratory distress for mild to moderate pneumonia patients and released with hospital advice. For the asymptomatic patients, passing 14 days after the first diagnosis was regarded as a clinically cure. The study excluded those treated for COVID-19, pregnant women, and the critically ill. In our earlier nationwide study, we collected a list of COVID-19 positive cases from the whole country [[
To assess the QoL of the HCWs, we collected participants' sociodemographic information, including age, gender, domicile, religion, educational attainment, marital status, and financial condition. In addition, we also recorded the details of their COVID-19 related hospitalization history, personal habits, presence of any chronic diseases such as heart disease, hypertension (HTN), asthma/chronic obstructive pulmonary disease (COPD), diabetes mellitus (DM), chronic kidney disease (CKD), and cancer. Symptoms that may arise or persist in the post-COVID period were also documented during the survey.
We utilized WHOQOL-BREF, a brief validated version of the WHOQOL-100 quality of life assessment questionnaire [[
Considering the present pandemic situation, we performed interviews over the phone. We approached all the randomly selected HCWs and recorded the response of those who felt comfortable participating in the survey. Besides, we informed the participants that there was no correct or wrong answer before the interview. Items that were misunderstood were replied, and interviewees were motivated to respond to the questions as they saw fit. The WHOQOL-BREF section of the questionnaire was scored following the manual [[
We applied descriptive and inferential methods to describe the quality of life of the Covid-19 recovered healthcare workers and explore the determinants of QoL among them. Statistical software STATA (Version 16.1) was used for statistical analysis. QoL scores were explored separately in four domains: physical, psychological, social, and environmental. Analyzing variance (ANOVA) models and verifying the normality assumption allowed us to compare continuous variables across different categories. We performed an independent sample t-test to compare the means of two continuous variables. We used frequencies (percent) to describe the categorical variables and chi-square tests to determine the associations between groups. For binary logistic regression analysis, QoL scores were translated into binary scores by treating a value greater or equal to 50 as 1 ("good"), otherwise 0 ("poor"). All tests were two-tailed, and p-values less than or equal to 0.05 were considered statistically significant.
Table 1 illustrates the sociodemographic variable of the study respondents. Among 322 health care professionals, more than half were male (n = 180, 56%), aged between 26–35 years (51%), and completed graduation (n = 158, 49%). Physicians accounted for 68% of our respondents, nurses for 27%, and others for 5% (such as laboratory technicians, pharmacists). The majority of the study participants were married (n = 263, 81%), urban dwellers (n = 247, 77%) and living in Dhaka (n = 154, 48%). According to the income distribution, most participants (n = 103, 35.64%) earned 20,000–40,000 BDT per month. Diabetes (16%), asthma/COPD (16%), and hypertension (15%) were the most prevalent comorbidities, followed by heart disease, cancer, and chronic kidney disease. One-fourth of the interviewee was smokers/past smokers (n = 80, 25%). Around 43% of HCW (n = 137, 42.55%) had to be hospitalized due to COVID-19 severity, while the other COVID-19 infected health care professionals were at home/institutional isolation during the whole infection period.
Table 1 Socio-demographics variable of the study participants (n = 322)
Name of Variable Frequency (%) < 26 40 (12%) 26–30 96 (30%) 31–35 69 (21%) 36–40 45 (14%) 41–45 37 (12%) 46 + 35 (11%) Male 180 (56%) Female 142 (44%) Barisal 32 (10%) Chattogram 70 (22%) Dhaka 154 (48%) Khulna 5 (2%) Mymensingh 18 (6%) Rajshahi 14 (4%) Rangpur 12 (4%) Sylhet 17 (5%) Rural 44 (14%) Urban 247 (77%) Semi-urban 31 (9%) Muslim 255 (79%) Non-Muslim 67 (21%) Below Graduation (SSC/HSC) 104 (32%) Graduation 158 (49%) Post-graduation 60 (19%) Single 57 (18%) Married 263 (81%) others 2 (1%) < 20,000 56 (19%) 20,000–40,000 103 (36%) 4000–60,000 56 (19%) 60,000 + 74 (26%) Never smoked 242 (75%) Current smoker 58 (18%) Past smoker 22 (7%) Hypertension 48 (15%) Diabetes 51 (16%) Asthma/ COPD 50 (16%) Heart disease 23 (7%) Chronic kidney disease 9 (3%) Cancer 12 (4%) 137 (43%)
We found the mean score of individual's overall perception of QoL and their health (as assessed by Q1 and Q2, scored in a range of 1 to 5) were 3.65 ± 0.78 and 3.68 ± 0.81, respectively, which were slightly higher than the possible middle score (i.e., 3) (Fig. 1). The mean domain-specific scores of QoL were observed highest in the physical domain (70.91 ± 13.07), followed by social relationships (66.93 ± 15.14), environmental (63.56 ± 12.11), and psychological domain (62.68 ± 14.99) (Table 2).
Graph: Fig. 1 Individual's overall perception of QoL and health of the study respondents
Table 2 Overall and domain specific score averages of the survey respondents
WHOQOL-BREF Overall mean SD Overall 1 (Q1) Individual's overall perception of QoL 3.65 0.78 Overall 2 (Q2) Individual's overall perception of their health 3.68 0.81 Domain 1 Physical 70.91 13.07 Domain 2 Psychological 62.68 14.99 Domain 3 Social relationships 66.93 15.14 Domain 4 Environmental 63.56 12.11
We observed a significant difference in the physical and psychological QoL scores among our HCW in different age groups (p = 0.001 and p = 0.0004, respectively) (Table 3). In both domains mean score of QoL deteriorated with the increase of age. We noticed average QoL score of Covid-19 recovered female HCWs was significantly lower than their male counterparts in psychological, social relationships, and environmental domains (p < 0.05). Interestingly, the mean scores of psychological, social relationships and environmental domains of HCWs differed significantly based on their corresponding division. Place of residence was a significant factor in modifying the social relationships domain (p < 0.05), and HCWs from urban areas scored highest in this sector. Respondents with a postgraduate level of education had a better environmental domain score than that of lower educational categories. While single HCW had a better physical and psychological QoL than married and divorced HCW, married respondents had a better social life. However, divorced/widowed HCWs lived the worst quality of life in both scenarios. As expected, study subjects hospitalized due to COVID-19 had a considerably lesser physical and psychological QoL than the home quarantined participants (p < 0.001). We observed proportionate deterioration of QoL scores due to chronic diseases in physical, psychological, and social relationships domains (p < 0.05). We also noticed the individual disease-specific worsening of QoL scores in each domain due to these chronic diseases. The analysis results were provided in the supplementary files (Supplementary 1).
Table 3 Comparison of individual domains score against socio-demographics variables
Variables Physical Psychological Social Environmental < 26 76.83 ± 11.72 66.88 ± 14.92 64.43 ± 15.90 60.15 ± 12.76 26 – 30 71.69 ± 13.74 65.76 ± 15.72 66.67 ± 16.91 64.10 ± 12.06 31 – 35 72.01 ± 12.72 62.84 ± 13.29 66.83 ± 14.10 62 ± 12.96 36 – 40 68.47 ± 11.07a 59.47 ± 13.98 66.09 ± 15.07 65 ± 12.45 41 – 45 69.35 ± 12.63 53.84 ± 14.21abc 68.57 ± 14.87 66.32 ± 12.32 46 + 64.6 ± 13.40a 62.6 ± 14.51 68.09 ± 11.65 64.29 ± 7.95 p 0.832 0.206 Male 72.03 ± 13.69 64.9 ± 15.06 69.22 ± 15.68 65.11 ± 12.86 Female 69.48 ± 12.14 59.87 ± 14.48 64.03 ± 13.95 61.60 ± 12.83 p 0.082 Barisal 71.5 ± 10.25 60.72 ± 9.01 62.5 ± 12.84 59.19 ± 11.55 Chattogram 74.11 ± 14.21 67.34 ± 14.87 67.77 ± 16.20 64.76 ± 10.17 Dhaka 70.52 ± 13.18 60.36 ± 15.77b 68.46 ± 15.77 64.73 ± 12.72 Khulna 65.2 ± 16.45 49.8 ± 27.24 46.2 ± 12.13bc 65 ± 9.57 Mymensingh 70.61 ± 10.27 68.83 ± 14.37 62.5 ± 11.56 64.11 ± 15.33 Rajshahi 68.07 ± 7.13 62.14 ± 8.02 65.64 ± 11.17 55.43 ± 6.99 Rangpur 62.58 ± 15.75 70.42 ± 11.31 62 ±.9.88 57.83 ± 9.34 Sylhet 70.29 ± 13.53 60.41 ± 13.29 73.24 ± 11.84d 66 ± 13.01 p 0.14 Rural 73.09 ± 12.72 66.73 ± 11.78 62.93 ± 16.64 63.73 ± 12.93 Urban 70.64 ± 12.99 61.79 ± 15.06 68.30 ± 14.89 63.83 ± 12.16 Semi-urban 69.90 ± 14.25 64 ± 17.71 61.71 ± 13.10 61.19 ± 10.51 p 0.471 0.116 0.52 Muslim 71.46 ± 13.27 63.75 ± 15.16 66.77 ± 15.80 63.58 ± 12.46 Non-Muslim 68.81 ± 12.15 58.63 ± 13.72 67.52 ± 12.38 63.49 ± 10.73 p 0.14 0.719 0.958 Below graduation (SSC/HSC) 71.00 ± 12.84 62.56 ± 15.72 65.88 ± 14.66 62.60 ± 12.45 Graduation 70.91 ± 12.46 63.35 ± 13.89 66.53 ± 15.76 62.34 ± 11.71 Post-graduation 70.73 ± 15.1 61.13 ± 16.58 69.8 ± 14.14 68.45 ± 11.49e p 0.992 0.620 0.252 Single 75.19 ± 13.23 68.44 ± 14.35 62.96 ± 12.99 63.30 ± 12.08 Married 70.14 ± 12.79 61.77 ± 14.40a 68.03 ± 15.21a 63.63 ± 12.13 Others 50 ± 8.49ab 18.5 ± 17.68ab 34.5 ± 13.44ab 62.5 ± 17.68 p 0.975 < 20,000 71.68 ± 12.49 63 ± 14.77 63.52 ± 16.85 61.27 ± 13.80 20,000–40,000 71.22 ± 13.21 64.91 ± 13.87 65.90 ± 12.80 61.28 ± 10.07 4000–60,000 70.45 ± 12.85 63.68 ± 13.98 68.39 ± 17.95 64.54 ± 12.15 60,000 + 70.28 ± 13.4 62.74 ± 16.52 66.84 ± 15.47 64.51 ± 12.85 p 0.920 0.77 0.393 0.158 No 73.59 ± 13.18 66.29 ± 14.45 67.97 ± 15.09 63.48 ± 12.25 Yes 67.28 ± 12.04 57.81 ± 14.37 65.52 ± 15.15 63.68 ± 11.96 p 0.151 0.881 No 71.99 ± 13.05 63.81 ± 14.34 67.83 ± 14.49 62.40 ± 11.09 Yes 68.09 ± 12.33 57.9 ± 15.89a 63.59 ± 15.88 67.86 ± 15.25a Past smoker 66.41 ± 13.64 62.82 ± 17.67 65.86 ± 19.17 65 ± 11.01 p 0.151 0 73.19 ± 12.25 64.45 ± 14.86 67.21 ± 14.47 62.51 ± 11.46 1 69.62 ± 14.24 62.59 ± 13.94 69.04 ± 15.49 65.21 ± 11.98 2 63.56 ± 9.33a 54.31 ± 15.36a 65.31 ± 9.73 65.44 ± 8.78 3 + 57.75 ± 8.61ab 51.1 ± 13.38ab 57.2 ± 20.66ab 66.8 ± 19.15 p 0.188
Scores were expressed as mean ± standard deviation (SD) p-value was determined by one-way ANOVA with Posthoc analysis by Tukey p-value significant at < 0.05 level in comparison to a) first category, b) second category, c) third category and d) fourth category within a variable. Significant p-values are marked in bold
The results of the domain-specific univariate analysis were portrayed in Table 4, where we tried to detect the individual factors responsible for modifying the quality of life scores among HCWs. Participants living in urban areas enjoyed 2.4 times better socially stable lives (OR: 2.42, 95% CI: 1.18–4.96) but 72% less psychologically healthy (OR: 0.28, 95% CI: 0.10–0.81) than those respondents living in rural areas. HCWs who completed post-graduation degrees enjoyed 3.7 times more environmentally secured lives than HCWs who failed to complete graduation (3.67, 1.33–10.14). Eventually, married HCWs led to 57% less psychologically sound quality of life (0.43, 0.18–0.99) than single HCW. An almost similar trend (0.40, 0.17–0.95) was observed for respondents who earned more than 60,000 BDT per month. On the other hand, we noticed a positive trend among the HCWs in the environmental domain, making more than 40,000 BDT. As expected, participants admitted to hospitals during the infection period were 65% (0.35, 0.21–0.60) less likely to stay psychologically healthy than those who were not. Likewise, smokers were more at risk in terms of psychological (0.30, 0.16–0.56) and social (0.45, 0.24–0.87) quality of life than non-smokers. Notwithstanding, a significant deterioration of the patients' QoL was observed with comorbidities except in the environment domain.
Table 4 Factors associated with each domain of WHOQOL-BREF among the study participants in univariate logistic regression analysis
Variables Physical Psychological Social relationships Environmental < 26 1.00 1.00 1.00 1.00 26 – 30 0.25 0.03 – 2.02 0.88 0.32 – 2.44 1.29 0.57 – 2.91 2.14 0.96 – 4.78 31 – 35 0.42 0.04 – 3.86 0.64 0.22 -1.80 1.37 0.60 – 3.11 36 – 40 0.36 0.03 – 3.60 0.35 0.12 – 1.03 1.98 0.71 – 5.50 41 – 45 0.29 0.03 – 2.93 2.74 0.86 – 8.75 46 + 1.06 0.29 – 3.82 2.07 0.68 – 6.28 Male 1.00 1.00 1.00 1.00 Female 0.83 0.39 – 1.78 0.64 0.38 – 1.07 0.64 0.37 – 1.10 0.79 0.47 – 1.34 Rural 1.00 1.00 1.00 1.00 Urban 0.51 0.12 – 2.27 1.53 0.75 – 3.14 Semi-urban 0.20 0.04 – 1.06 0.52 0.13 – 2.12 0.98 0.37 – 2.62 1.75 0.58 – 5.26 Muslim 1.00 1.00 1.00 1.00 Non-Muslim 1.29 0.47 – 3.51 0.57 0.32 – 1.05 2.08 0.94 – 4.60 1.25 0.64 -2.45 Below graduation (SSC/HSC) 1.00 1.00 1.00 1.00 Graduation 1.57 0.63 – 3.93 1.42 0.78 – 2.58 1.08 0.59 – 1.96 0.95 0.54 – 1.68 Post-graduation 0.60 0.23 – 1.58 0.78 0.38 – 1.58 1.85 0.77 – 4.43 Single 1.00 1.00 1.00 1.00 Married 0.75 0.25 – 2.26 1.29 0.65 – 2.58 1.18 0.60 – 2.3 Others 0.08 0.003 – 1.45 1 0 1 0 0.33 0.02 – 5.55 < 20,000 1.00 1.00 1.00 1.00 20,000–40,000 0.43 0.12 – 1.59 1.04 0.43 -2.54 1.56 0.74 – 3.31 1.87 0.93 – 3.78 40,000–60,000 0.58 0.13 – 2.54 1 0.36 – 2.74 1.64 0.68 – 3.94 60,000 + 0.64 0.15 – 2.69 1.45 0.65 – 3.23 No 1.00 1.00 1.00 1.00 Yes 0.49 0.23 – 1.06 0.63 0.37 – 1.1 1.31 0.76 – 2.24 No 1.00 1.00 1.00 1.00 Yes 1.35 0.45 – 4.08 1.32 0.64 – 2.71 Past smoker 0.63 0.17 – 2.31 1.03 0.33 – 3.18 0.69 0.24 – 1.99 1.39 0.45 – 4.26 0 1.00 1.00 1.00 1.00 1 0.83 0.43 – 1.59 1.18 0.58 – 2.40 1.71 0.86 – 3.42 2 0.42 0.08 – 2.08 1.55 0.34 – 7.09 2.25 0.50 – 10.21 3 + 0.60 0.23 – 1.57
OR (95% CI) shown in bold are statistically significant at p<0.05 level
We performed multivariable logistic regression analysis to analyze each variable against each domain to classify the critical factors related to QoL (Table 5). After adjusting the variables, we found that the participants over 46 years of age enjoyed better psychologically sound (AOR: 23.71, 95% CI: 1.31–430.32) and environmentally secure (AOR: 17.23, 95% CI: 1.88–165.52) life than the respondents aged below 26 years. Psychologically and socially, female HCWs were 74% and 59% less likely (0.24, 0.08–0.67; 0.41, 0.19–0.89) to have a good QoL than male HCWs, respectively. In urban areas, the HCW's chance of living a good-quality social life was 3.37 times higher than the rural participants (3.37, 1.37–8.30), while HCWs living in the semi-urban areas led physically impoverished life (0.07, 0.006–0.86). Besides, graduated HCWs had a 2.46 times greater probability of having a decent psychological (2.46, 1.06–5.68) QoL than those who failed to complete graduation. The participants who were married enjoyed better physical life than those single. The HCWs who earned more than 60,000 BDT monthly enjoyed better-secured lives than the participants who earned less than 20,000 BDT. Hospitalized HCWs were 86% less probability of enjoying a better QoL in the physical domain (0.14, 0.04–0.55) than those who were not. Environmental QoL was more favourable for ex-smokers than non-smokers (15.72, 1.28–192.46). Current smokers had a 76% lower chance (0.24, 0.07–0.85) of maintaining a good psychological QoL than never smoker participants. HCWs with three or more comorbidities had a worse QoL on psychological, social, and environmental measures than those without comorbidity. Finally, for each week since they recovered, people with COVID-19 were more likely to get a better physical quality of life (1.16, 1.035–1.309).
Table 5 Factors associated with each domain of WHOQOL-BREF among the study participants in multivariable logistic regression analysis
Variables Physical Psychological Social Environmental < 26 1.00 1.00 1.00 1.00 26 – 30 0.07 0.005 – 1.06 0.93 0.25 – 3.49 0.90 0.32 – 2.55 1.39 0.51 – 3.91 31 – 35 0.07 0.004 – 1.23 0.81 0.18 – 3.64 1.25 0.36 – 4.26 0.87 0.29 – 2.63 36 – 40 0.12 0.005 – 2.84 0.43 0.08 – 2.17 1.49 0.37 – 5.93 1.52 0.38 – 6.10 41 – 45 0.10 0.003 – 3.73 0.30 0.05 – 1.60 1.72 0.37 – 7.92 2.00 0.46 – 8.77 46 + 0.05 0.002 – 1.10 3.99 0.64 – 25.07 Male 1.00 1.00 1.00 1.00 Female 1.15 0.34 – 3.87 1.04 0.52 – 2.08 Rural 1.00 1.00 1.00 1.00 Urban 0.82 0.08 – 8.28 0.26 0.06 – 1.15 2.22 0.90 – 5.49 Semi-urban 0.25 0.04 – 1.64 1.05 0.32 – 3.43 2.54 0.69 – 9.38 Muslim 1.00 1.00 1.00 1.00 Non-Muslim 3.19 0.47 – 21.55 1.44 0.52 – 4.01 1.52 0.56 – 4.12 0.72 0.30 – 1.72 Below graduation (SSC/HSC) 1.00 1.00 1.00 1.00 Graduation 3.24 0.78 – 13.45 1.21 0.58 – 2.51 0.74 0.36 – 1.49 Post-graduation 0.86 0.14 – 5.20 2.76 0.67 – 11.40 1.29 0.35 – 4.77 2.77 0.63 – 12.16 Single 1.00 1.00 1.00 1.00 Married 1.40 0.43 – 4.57 1.13 0.43 – 2.97 0.994 0.41 – 2.38 Others 0.28 0.004 – 20.42 1 0 1 0 0.06 0.001 – 1.94 < 20,000 1.00 1.00 1.00 1.00 20,000–40,000 0.47 0.08 – 2.86 1.26 0.38 – 4.16 1.38 0.55 – 3.43 1.70 0.72 – 3.98 4000–60,000 1.22 0.13 – 11.01 1.06 0.27 – 4.13 1.25 0.42 – 3.72 2.18 0.77 – 6.17 60,000 + 0.46 0.06 – 3.31 0.42 0.13 – 1.37 1.90 0.65 – 5.57 No 1.00 1.00 1.00 1.00 Yes 0.46 0.20 – 1.03 0.66 0.32 – 1.37 1.39 0.68 – 2.86 No 1.00 1.00 1.00 1.00 Yes 3.90 0.57 – 26.86 0.53 0.18 – 1.55 3.06 0.90 – 10.38 Past smoker 6.06 0.16 – 225.92 1 0 1.06 0.22 – 5.04 0 1.00 1.00 1.00 1.00 1 0.39 0.09 – 1.63 1.32 0.45 – 3.84 0.83 0.33 – 2.10 0.88 0.35 – 2.25 2 1.14 0.06 – 20.58 0.40 0.05 – 3.14 0.59 0.09 – 3.81 0.25 0.36 – 1.72 3 + 0.29 0.03 – 3.06 1.05 0.962—1.149 1.05 0.981—1.129 1.04 0.970—1.115
*p < 0.05
The extraordinary devastation induced by the COVID-19 pandemic has put millions of lives in danger and caused significant disruption to the financial system. Those who become infected with COVID-19 had to go through the most agonizing experiences. HCWs are the most vulnerable groups which render their service in front of the highest possible threat. So, assessing the quality of life of the COVID-19 recovered HCWs was a time-demanding necessity in the current situation.
We observed an improvement in the individuals' overall perception of QoL and their health (Q1 3.65 ± 0.78, Q2 3.68 ± 0.81) after getting recovered from the COVID-19. This positive observation was in harmony with four domains of QoL, where the physical domain scored the highest, shadowed by social relationship, environmental, and psychological domains, respectively. Eventually, the promising scores corresponding to each domain assert the overall improvement of the QoL among the HCWs.
Despite the recovered HCWs presenting with improved QoL, a variation in their domain-specific scores representing QoL was observed. To be specific, they showed significant variation concerning different sociodemographic variables, including age, gender, urban residence, higher educational attainment, marital status, higher income, past smoking and the presence of chronic disease. The findings of the earlier studies performed on the general population are congruent to the current study [[
We noticed that the chance of having good psychological and environmental scores increased with increasing age when adjusted for other factors. The possible explanation for such findings is that HCWs start their careers later than other professions. Due to the lengthy education system, many HCWs do not begin earning substantial incomes until they are 45 or older, well after most of their peers from other professions [[
Our current study found that female HCWs are more vulnerable to observing a substandard psychological and social life than their male counterparts. Females experienced 31% deterioration in their psychological and social quality of life due to gender issues, in line with the previous studies conducted on normal adults of Bangladesh [[
Participants living in the urban areas had good social relationships domain scores than the rural participants. According to Shucksmith et al., rural communities led to a substantially poorer quality of life than metropolitan areas [[
We found that married HCWs who recovered from COVID-19 enjoyed a better physical life than the single respondents. The presence of a person to look after during the COVID affected days might be the possible reason for their quick physical ailment in this particular domain.
A positive relationship was observed in the psychological domain between the QoL scores and the level of education among the study participants. Our findings were in line with the worldwide study conducted by Skevington et al. [[
HCWs admitted into the hospital due to COVID-19 had lower scores in the physical domain of the QoL index after recovery. The persistence of post-COVID-19 symptoms, functional disabilities, slow healing, and posttraumatic mental distress after severe infection might be the reason behind the declining physical quality of life. The persistence of symptoms after recovery was related to the patients' low physical QoL [[
As expected, we noticed that the active smokers participants were less likely to have a good score in the psychological domain of QoL. However, smoking did not affect catching the coronavirus [[
We observed that almost all of the six non-communicable comorbid diseases, namely HTN, DM, IHD, BA/COPD, CKD, and cancer, were responsible for significantly lower QoL scores in the physical health, psychological, and social relationship, and environmental domains of life among the HCWs. We found that the higher the number of comorbidities, the lower the chance of enjoying a satisfactory quality of life. Previous research conducted on COVID and non-COVID patients corroborates these findings [[
Lastly, the physical QoL of the COVID-19 recovered HCWs was found to be improved over time. As the physical domain solely depended on patients' physical wellbeing, the finding was relevant. On the other hand, it was evident from other research that COVID-19 exerted a tremendous negative impact on people's psychological domain [[
The relatively limited number of individuals who gave data can be viewed as a drawback in the generalizability of the results. Future studies should reveal more generalizable findings by gathering data from a larger sample of HCWs. Given that the current study is a cross-sectional research case, longitudinal studies examining the pandemic's long-term impacts are warranted. The gender of the participant was found to have a substantial effect on the social and psychological QoL of the HCWs. Thus, additional gender-based comparative research examining the factors of HCWs' working conditions during the COVID-19 epidemic may better understand the issue.
HCWs' post-COVID QoL was affected by various demographic and socioeconomic determinants, including their age, gender, education, and monthly salary. One or more areas of QoL were significantly impacted when disease severity and the degree of comorbidities were considered. However, all the domains of QoL improved over the period where the physical domain had been found significant. Researchers in national and worldwide communities would surely be interested in our findings, which would lead policymakers in developing particular recuperation and rehabilitation plans, initiatives, and strategies for COVID-19-affected health care workers.
We would like to express our sincere thanks and gratitude to the study participants for their patience and cooperation during the telephone interview.
MUR, MASK, MDHH, MHN and KD conceived and designed framework of this study. MUR, MASK, SKS, SYB, MH, MMAH, and MAH collected data. MASK, MUR, SKS, MMAH, MAH executed the statistical analysis. MUR, SKS, SYB, and MH drafted the manuscript. KD, MDHH, and MHN reviewed the manuscript critically. All authors read and approved the final manuscript.
Open access funding provided by Mid Sweden University. This research did not receive any funding from any agency in the public, commercial, or not-for-profit sectors.
Data could be available from Dr Mohammad Delwer Hossain Hawlader (mohammad.hawlader@northsouth.edu)
Ethical approval was obtained from the Institutional Review Board (IRB)/Ethical Review Committee (ERC) of North South University (No:2020/OR-NSU/IRB-No.0801). The ethical criteria outlined in the 1964 Declaration of Helsinki and its subsequent revisions and equivalent ethical norms were observed. The ethical criteria outlined in the 1964 Declaration of Helsinki and its subsequent revisions, or equivalent ethical standards, were followed whenever needed. Verbal informed consent was obtained from all study respondents during the phone interview.
N.A.
The authors declare that they have no competing interests.
Graph: Additional file 1:Supplementary 1. Comparison of individual domain score by chronic disease status.
• ANOVA
- Analyzing variance
• AOR
- Adjusted odds ratio
- COVID-19
- Coronavirus disease 2019
• COPD
- Chronic obstructive pulmonary disease
• CKD
- Chronic kidney disease
• DM
- Diabetes mellitus
• HCWs
- Healthcare workers
• HRQoL
- Health-related quality of life
• HSC
- Higher secondary school certificate
• HTN
- Hypertension
• OR
- Odds ratio
• PPE
- Personal protective equipment
• QoL
- Quality of life
• RT-PCR
- Reverse Transcription-Polymerase Chain Reaction
• SSC
- Secondary School Certificate
• WHO
- World health organization
- WHOQOL-BREF
- World Health Organization Quality of life questionnaire brief
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By Md Utba Rashid; Md Abdullah Saeed Khan; Koustuv Dalal; Soumik Kha Sagar; Mosharop Hossian; Sabrina Yesmin Barsha; Miah Md. Akiful Haque; Mohammad Ali Hossain; Mohammad Hayatun Nabi and Mohammad Delwer Hossain Hawlader
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