The Combined Outcomes of the COVID-19 Pandemic and a Collapsing Economy on Quality of Life: A Cross-Sectional Study

Hala Sacre INSPECT-LB. Institut National de Santé Publique, Epidémiologie Clinique et Toxicologie-Liban. Beirut, Lebanon Aline Hajj Universite Saint-Joseph Danielle A Badro American University of Science and Technology Faculty of Health Sciences Carla Abou Selwan (  carla.abouselwan@sciencepro.me ) Science PRO https://orcid.org/0000-0002-8140-8694 Randa Aoun INSPECT-LB. Institut National de Santé Publique, Epidémiologie Clinique et Toxicologie-Liban. Beirut, Lebanon Pascale Salameh Universite Libanaise Faculte de Pharmacie

governments across the globe deployed public health responses and imposed containment measures, including social distancing, self-isolation, quarantine, and local and international travel restrictions. On 25 March 2020, an estimated 2.6 billion people (one-third of the human population) were under some form of lockdown. 4 As of 17 May 2020, the pandemic resulted in 4,534,731 con rmed cases of  infections and 307,537 deaths worldwide. 5 Throughout history, epidemics and pandemics have had manifold and profound long-lasting impacts on mental health and quality of life (QOL). 6 Thus, COVID-19 is expected to affect the quality of life (QOL), de ned by the World Health Organization (WHO) as "an individual's perception of their position in life in the context of the culture and value systems in which they live and in relation to their goals, expectations, standards, and concerns". 7 However, data on the impact of COVID-19 on the QOL remain scarce, and only a few reports evaluated it among special populations, such as patients with pelvic oor disorders, 6 Parkinson's disease, 8 in ammatory bowel disease, 9 or among general practitioners working with suspected or con rmed cases on the frontline of COVID-19. 10 Another impact of the COVID-19 is the slowing down of major world economies with a higher risk for developing ones. Indeed, containment strategies of attening the curve most countries adopted to avoid overwhelming the healthcare system, induced a global economic slowdown with layoffs and rms exits generating an abrupt increase in unemployment. 11,12 In Lebanon, the rst COVID-19 positive case was con rmed on 21 February 2020. As of this date, the government implemented stepwise measures to curb the spread of the disease; one week after, schools were closed. Other escalating steps followed until the sanitary lockdown on 15 March. 13 In parallel, awareness campaigns and electronic o cial platforms were launched to keep the public informed. 13,14 On 21 May, the Ministry of Public Health (MOPH) reported a total of 961 cumulative positive COVID-19 cases, 26 deaths, and 53 positive cases. Urban regions are the most affected, mainly the capital city Beirut. 14 In Lebanon, the COVID-19 outbreak coincided with an unprecedented economic crisis. This Middle-Eastern developing country was recently downgraded from a high-income to upper-middle-income country by the World Bank. 15 In 2011, the Lebanese population was estimated at 5,202,343 inhabitants and reached 6,848,925 in 2018. 16 This dramatic increase that has largely affected its economy is mainly due to the in ow of Syrian refugees who ed their country upon the declaration of war in 2012. 15 Lebanon's economy is highly volatile; it is service-oriented and relies heavily on the diaspora's money in ows. 17 Despite several periods of economic prosperity, Lebanon has been witnessing slow economic growth over the past few years that reached monetary tightening in 2019, 18 and resulted in an unprecedented crisis with massive demonstrations, strikes, and temporary bank closures. 19 Since then, banks have become unable to supply depositaries with money, whether Lebanese Pounds or US Dollars, the two currencies used in Lebanon. Furthermore, USD exchange rates have skyrocketed, making the paper money in that currency and other foreign currencies scarce or unavailable. 20 This economic frailty is mainly due to its non-productive structure coupled with corruption, political instability, and jostling, further aggravated by the signi cant in ux of Syrian refugees. 18 Despite its dreadful situation and an immediate economic vulnerability, Lebanon ranked among the countries with the most prepared health system for the handling the COVID-19. 21 Given that this pandemic has already affected the major world economies, with some of them heading towards a sharp recession, 12 it is expected that Lebanon will be no exception; the current health crisis will deepen the country's already collapsing economy, thereby altering QOL in the general population. Studies exploring this particular facet of the pandemic are lacking. Therefore, this study aimed at examining the combined outcomes of the COVID-19 pandemic and a collapsing economy on the quality of life of the general Lebanese population.

Study Design and Sampling
A cross-sectional study was conducted from 10-18 May 2020, using an online-based questionnaire created on Google forms. Due to the government-mandated sanitary lockdown, the survey was distributed to participants through social media platforms and WhatsApp groups, using the snowball sampling technique. All individuals over 18 years of age with access to the Internet were eligible. A total of 502 respondents lled out the questionnaire that required between 15 and 20 minutes to complete.

Minimal sample size calculation
The minimum sample size was calculated using the G-Power software, version 3.0.10. The calculated effect size was 0.0526, expecting a squared multiple correlation of 0.05 (R 2 deviation from 0) related to the Omnibus test of multiple regression. The minimum necessary sample was n=454, considering an alpha error of 5%, a power of 80%, and allowing 25 predictors to be included in the model.

Questionnaire
The online questionnaire was available in Arabic, the native language in Lebanon. It consisted of three parts. The rst part assessed the sociodemographic features of the participants, such as age, gender, marital status, educational level, employment status, region, household size, current household monthly income (divided into ve levels, according to the o cial exchange rate: no income, low< 675,000 LBP (450 USD), moderate 675,000-1,500,000 LBP (450-1,000 USD), intermediate 1,500,000-3,000,000 LBP (1,000-2,000 USD), and high income >3,000,000 LBP (2,000USD)); the socioeconomic status was assessed using quartiles of individual income (household income divided by the household size).
Questions were also asked about medical coverage, smoking and alcohol consumption, self-perception of the nancial situation, having been infected or in contact with people infected with coronavirus, and physical activity before and during COVID-19.
The second part of the questionnaire, addressed to working people and those seeking a job, consisted of a set of 20 questions related to current employment and how it was affected by either the economic crisis or the COVID-19. Examples of questions asked: Do you have to go out to make a living despite the sanitary lockdown? Are you able to apply social distancing while working (1.5-2m safety distance)? Did your company change the working hours because of the economic crisis or the COVID-19 pandemic? Has your salary/income been affected by the economic crisis or the COVID-19 pandemic? Are you worried about the long-term impact of the economic crisis or the COVID-19 pandemic on your business/job? Did the economic crisis or the COVID-19 pandemic result in decreasing the salaries of employees? Did the economic crisis or the COVID-19 pandemic cause the dismissal of some employees? What were the criteria used to lay-off employees?
The third part consisted of the several measures using validated scales, after obtaining the due permission from their copyright holders when necessary: The World Health Organization-Five Well-Being Index (WHO-5) This short self-reported tool is validated in Lebanon 22 and consists of ve questions graded from 0 to 5 to evaluate mental well-being and quality of life in the past month. The total score ranges from 0 to 25; higher scores indicate a better quality of life (α Cronbach =0.796).

The fear of COVID-19 scale
This 7-item tool is used to measure the extent of fear of the COVID-19 in adult people. 23 It is scored on a 5-point Likert scale from 1 (strongly disagree) to 5 (strongly agree). The total score ranges from 1 to 35, with higher scores indicating a greater fear of COVID-19 (α Cronbach =0.893).

The InCharge Financial Distress/Financial Well-Being Scale (IFDFW)
This tool includes eight items that assess the perceived nancial distress/ nancial well-being on a linear scale from 1 to 10. 24 Lower scores re ect higher nancial distress and lower well-being (α Cronbach =0.925).
Since this tool is copyrighted, written permission was obtained from the authors for cross-cultural validation and use in Lebanon.

The Family APGAR Index
This short self-reported instrument evaluates the satisfaction with global family function. 25 It consists of ve questions, each corresponding to a component of family function, i.e., Adaptation, Partnership, Growth, Affection, and Resolve (APGAR). All items are scored on a 3-point Likert scale: 0 (hardly ever), 1 (some of the time), and 2 (almost always). The total score ranges from 0 to 10. Higher scores indicate higher satisfaction with family function (α Cronbach =0.927).

Translation Procedure and Piloting
All the scales used in this paper were translated into Arabic, except for the WHO-5, already validated and available in this language. Three authors performed the forward translation, and the other three, the back translation. Discrepancies between original English versions and translated ones were resolved by consensus.
The questionnaire was pilot-tested with ten people unfamiliar with the study to get to the nal version; answers were not included in the nal dataset.

Statistical Analysis
Data were collected using Google Forms and generated on an Excel sheet, then transferred to IBM SPSS® software, version 23.0 for analysis. The database was weighted according to gender, age, and region of residence, based on the Central Administration of Statistics, 26 before analysing it.
For the descriptive analysis, frequencies and percentages were used for categorical variables, and means and standard deviation for quantitative variables. For the dependent variable (WHO-5), the median and interquartile range were presented as well.
The distribution of the WHO-5 variable was considered normal using visual inspection of the histogram, while the skewness and kurtosis were both lower than 1. These conditions are considered compatible with normality in a sample size higher than 300. 27 For the bivariate analysis of continuous variables, the Student's T-test was used to compare the means between two groups and ANOVA between three groups or more, after checking for homogeneity of variances using Levene's test; when variances were not homogenous, the corrected T-Test and the Kruskal-Wallis test were used, respectively. Post-hoc analyses were conducted, after ANOVA and Kruskal-Wallis comparisons, using Bonferroni adjustment. The McNemar-Bowker test was used to compare categorical variables before and after the beginning of the economic crisis. A Spearman correlation coe cient was used to correlate between scale variables. In all cases, a p-value lower than 0.05 was considered signi cant.
As for the multivariable analysis, a multiple linear regression was conducted to assess the correlates of WHO-5 in the whole sample, after checking the residues normality, linearity of the relationship, absence of multicollinearity, and homoscedasticity assumptions; a stepwise method was used to reach the most parsimonious model. As for the workers/trying to work subgroup analysis, a linear regression using the Generalized Linear Model was used, since the additional variables related to work conditions were multinomial; the ENTER method was used to reach the appropriate model with appropriate assumptions. Independent variables included in the models had a p-value lower than 0.1 in the bivariate analysis, taking into account the allowed maximal number of variables to be included given the sample size. The beta coe cient, its 95% Con dence Interval (CI), and the p-value were reported in both models.

Sociodemographic characteristics of participants
The sample included 502 participants, with 52.7% females, 57.8% married, and 88.5% university degree holders. The distribution over the regions was as follows: 16.7% in Beirut (the city capital), 44.2% in Mount Lebanon, 15.9% in the North, 13.8% in the South, and 9.5% in the Beqaa. Only 32% of participants lived in a household of less than four persons; 58.8% had one or more dependent child, and 33.2% were living in a house of fewer than ve rooms. Moreover, 39.3% of participants never consumed alcohol, 66.6% never smoked cigarettes, and 72.3% never smoked waterpipe. Around 6% reported verbal violence at home, while other reported types of domestic violence accounted for less than 2%. Furthermore, 71.9% of the sample had an employment (61.9%) or were looking for one (10%), 10.3% were housewives or never worked, 9.9% were students, and 7.9% had retired ( Table 1).

Sociodemographic characteristics and QOL
A better mean QOL was associated with the male gender (15.61), an education below the university level (16.03), no consumption of alcohol (15.29), no smoking of waterpipe (15.10), and greater satisfaction with family life (APGAR). Occasional cigarette smokers (13.69) and participants who reported violence in their homes (11.37) had lower mean QOL. Additionally, a signi cant positive correlation was found for the APGAR family scale and the WHO-5 (r=0.251). Signi cant differences were not found for the rest of the characteristics (Table 1).

Economic characteristics and QOL
People who subjectively classi ed themselves as belonging to the middle class both prior to the economic crisis and the pandemic (15.02) and after (15.39) had a better QOL; the more people feared poverty, the lower their QOL (r=-0.236). On the contrary, the better their current nancial situation, the better their QOL (r=0.206) ( Table 2). Figure 2 shows the sample's subjective assessment of the socioeconomic status before and after the COVID-19 pandemic; it revealed a signi cant decrease (p<0.001) of rich and middle classes selfclassi cation, versus a notable increase in low and below poverty categories.

Professional characteristics and QOL
When comparing individuals who were employed and those looking for employment (looking for a job/licensed from work), the latter had a lower mean QOL (12.77) compared to those still working (mean QOL varies from [14][15]. Since the beginning of the economic crisis (not the COVID-19 crisis), workers who were still employed (15.51) had the best QOL compared to all other categories (12 to 14). Employees who reported a current decrease in salary (25-50%), or were dismissed from work (25-75%) had signi cantly affected QOL compared to workers employed at companies that were not being affected by the crisis. Moreover, incremental concern that the current crisis would affect one's employment was inversely related to QOL (r=-0.206) ( Table 3).

COVID-19 exposure, health characteristics, and QOL
As for health-related matters, only 0.6% of participants reported having been infected with COVID-19.
Physical activity signi cantly improved QOL (15.23 vs. 14.05, with nearly 30% of the population reporting an increase in the time they dedicated to physical exercising), while having a chronic disease decreased QOL (13.90 vs. 15.04). In addition, the fear of becoming unable to supply themselves with their medications (13.67) and the fear of going out to receive treatment (13.16) were signi cantly associated with lower QOL. The higher the fear of COVID-19, the lower the QOL (r=-0.228) ( Table 4).

Multivariable analyses: Correlates of WHO-5
The multivariable analysis (Table 5) showed that correlates of QOL differed between the full sample and the workers/looking for a job subsample. In the full sample, better satisfaction from family (beta=0.380) and a better nancial situation (beta=0.029) were signi cantly correlated with better QOL. However, a lower QOL was signi cantly different among females (beta=-1.533), participants who attended university (beta=-2.119), participants who manifested fear of COVID-19 (beta=-0.131), participants who manifested fear of poverty (beta=-0.232), participants who reported verbal violence at home (beta=-3.464), and the ones who had a chronic disease (beta=-1.307).
In the subsample of workers/looking for a job, additional factors affected QOL: waterpipe smoking (current [beta=3.079] or none [beta=2.297] versus previous) and physical exercise (beta=1.318) were associated with better QOL, while being self-employed before the crisis (beta=-1.22), working from home since the economic crisis (-1.853), , closure of the institution (beta=-1.2), and worrying about the longterm effect of the crisis on one's employment status (beta=-0.433) were associated with a lower QOL. It is noteworthy that the fear of COVID-19 was not signi cantly associated with QOL (p>0.05).

Discussion
This study shed light on the combined effects of the current economic crisis and COVID-19 pandemic on the quality of life in the general population in Lebanon. It showed that during the pandemic, economic and other factors, directly or indirectly related to COVID-19, signi cantly affected QOL of the general population. However, fear of COVID-19 lost its signi cance in the workers' group, who reported that the main factors negatively affecting their QOL were those directly related to their employment status and the already collapsing Lebanese economy. In all groups, individuals with a more favourable nancial status seemed to be at lower risk of being affected by both the pandemic and the economic situation, since the IFDFW scores were positively correlated with a better QOL.
In the current context, fear of poverty is illustrated by the subjective economic assessment, showing a signi cant shift towards low and below poverty classes, thereby revealing the direct impact of di cult nancial situations on their quality of life. Prior to the COVID-19 outbreak, the World Bank had forecasted that by 2020, the proportion of Lebanese below the poverty line would increase from 30 to 50%. 28 Regarding the workers' group, individuals owning their businesses before the crisis, working from home since the beginning of the economic crisis, and worrying about the long-term effect of the crisis on their employment status experienced the worst QOL. The main impact was directly related to worrying about their work: those who worked remotely from home feared a wage cut-down or even dismissal if the situation persisted. Business owners feared a complete collapse in income, in the absence of governmental nancial support, since budgetary policies are lacking in Lebanon. 29 Although "economic damage" can only be assessed when the pandemic subsides, 30 nancial loss creates long-lasting socioeconomic distress with anger and anxiety that can last months after the pandemic. A recent report from the World Bank pointed out a substantial impact of COVID-19 on the Lebanese economy (11% decrease in GDP), especially with uncertainties about the duration of the pandemic and the drastic changes in the nancial system. 29 In such a vulnerable system, workers were highly preoccupied with the wilting economy and outcomes of lockdown on their employment rather than fearing the virus itself.
In contrast, unemployed respondents (retired, students, and housewives) worried about contracting the virus and not being able to afford the treatment. Our results are different from those reported in China, where the helplessness feeling of participants was low, although more than half of them declared feeling horri ed and apprehensive because of the COVID-19 pandemic. 31 A possible explanation is that China being the world's second-largest economy, people can afford to stop working and rest during the lockdown, without their QOL being affected. 31 Another signi cant aspect is the level of education. Our results showed that the higher the level of education, the lower the QOL. This outcome is not surprising since being unable to plan, face unforeseen expenses, and overcome any sudden deterioration in people's economic environment has an impact on their QOL. 32 Therefore, in our study, participants holding university degrees might have felt deceived and worried about their future in Lebanon due to the current challenging context.
In addition to the economic factors, our results showed that some sociodemographic factors also affected the QOL of Lebanese people; lower QOL was associated with the female gender, having a chronic disease, and experiencing verbal violence at home, whereas a better family satisfaction was correlated with a better QOL. These associations can be explained by homeschooling led by mothers 33 and forced con nement with a violent partner, 34 while family support improves QOL. 31 Furthermore, vulnerable people, particularly those with chronic diseases, require special attention. Studies exploring the impact of the pandemic on the QOL of these patients are scarce and results con icting.
Although research, with relatively small sample size, failed at identifying a negative impact of COVID-19 on the overall QOL among a population with in ammatory bowel disease, 9 another study demonstrated that patients with Parkinson's disease experienced worse mental health with lower QOL. 8 Around 20% of our respondents had a chronic disease and exhibited a lower QOL in the whole group and the workers' subgroup. Lebanon has high percentages of vulnerable populations, such as elderly, 35 and chronic diseases, 36-38 considered at higher risk for COVID-19 and lower QOL. 39 Reasons in this context could include panic due unreliable information for patients, 40 especially in an era of massive misinformation in the media, 41,42 added to the economic situation itself. Furthermore, the healthcare system in Lebanon is mainly private, 43  Finally, only in the workers' group, current smoking status was signi cantly associated with better QOL versus previous smokers. It is noteworthy that in Lebanon, behavioural/motivational factors for smoking cessation are mainly driven by health-related issues. Thus, this particular population of "previous smokers" might be at higher risk of vulnerability and chronic diseases (including pulmonary diseases), exposing them to lower QOL scores. 44 The positive correlation among current waterpipe smokers (regular and occasional) might seem surprising since tobacco exposure is known to be a major risk factor for decreased QOL. 45 However, smokers might have felt some relief reducing their stress and anxiety towards hardship, through the already known "self-medication" hypothesis of smoking, postulating that individuals turn towards smoking to alleviate their depression and anxiety symptoms; 46,47 this is added to the speci cities of waterpipe smoking (positive and negative reinforcement, social aspect and conviviality). 44 Our study also revealed the bene cial effects of physical activity/exercise on overall QOL, particularly in the subgroup of workers, with almost 30% of them reporting an increase in the time allocated for exercise. Several reports have been published recently regarding the importance of physical exercise as a therapy to ght the mental and physical consequences of COVID-19 lockdown. 48,49 Physical activity and exercise help also maintain immune system function in the current precarious environment and are particularly recommended in vulnerable populations such as those with chronic diseases 50 who scored a lower QOL in our study.

Limitations and strengths
Some limitations could be noted in our study. Although our sample was weighted for gender, age, and regions, it mainly consisted of people with a university level of education with high computer literacy; thus, our results might not be generalized to the whole population. This outcome was expected since the survey used was online, and only computer literate people with Internet access were able to participate.
However, this selection bias is not expected to affect the associations found in the multivariable analysis since the education factor was taken into account as a potential confounder. Moreover, although the questionnaire was piloted to improve its clarity, there is a probability of information bias, since the questionnaire was self-administered online, with no possibility to explain confusing questions to respondents, if any; however, this is expected to decrease the subjectivity related to interviews and drive the results towards a non-differential bias, thus underestimating the real associations. An additional potential bias would be the residual confounding since not all confounders could be measured.
Nevertheless, and despite these limitations, to the best of our knowledge, this is the largest (sample size large enough to account for statistical power of main comparisons) and the rst study evaluating the combined effect of the COVID-19 pandemic and the economic crisis on the QOL in the general population. Moreover, a standardized questionnaire with validated scales was used to evaluate QOL, economy or COVID-19-related factors. Finally, our study pilot-tested the validity of the questionnaires, and all used scales have shown very good to excellent reliability.

Conclusion
This study shed light on the combined outcomes of the current economic crisis and COVID-19 pandemic on the quality of life in a developing country. It showed that during the pandemic, economic and other factors, directly or indirectly related to COVID-19, signi cantly affected quality of life. The fear of COVID-19 and fear of poverty mainly impacted the QOL of the general population; however, the fear of COVID-19 lost its signi cance among workers, who reported that factors negatively affecting their QOL are directly related to their employment and the already collapsing economy in Lebanon.

Declarations
Ethics approval and consent to participate The Institutional Review Board of the American University of Science and Technology approved this study protocol (AUST-IRB-20200527-01). The topic was explained to all participants in the introductory section of the survey and consent to participate was implicit. Anonymity of participants was guaranteed throughout the process of data collection and analysis.
Consent for publication: Not applicable.
Availability of data and materials: The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.
Competing interests: None declared.
Authors' contributions: All authors had full access to all data in the study and take responsibility for the integrity of the data and accuracy of analysis. HS and AH contributed in literature search, study design, data collection, and drafting the manuscript. DB, CAS and RA contributed in literature search, data collection, and drafting the manuscript. PS designed the study, analysed the data and contributed in data collection and drafting the manuscript.     Fear of COVID score a Stepwise Likelihood ratio method; linear regression, assumptions checked. Included in rst step: Age, gender, education, alcohol, cigarette, waterpipe, verbal violence, APGAR score, fear of poverty score, IFDFW, physical activity, chronic disease, fear of COVID score. b ENTER method; linear regression using GEE, assumptions checked; Included in rst step: Age, gender, education, alcohol, cigarette, waterpipe, verbal violence, APGAR score, fear of poverty score, IFDWF, physical activity, chronic disease, fear of COVID score; working on its own, being jobless, professional change since the crisis started; salary changes in the enterprise, licensing employees in the enterprise, worrying about long-term crisis effects on its job. Figure 1 Histogram of Quality of Life in the Lebanese Population (n=502) Figure 2 Subjective Economic Status Assessment of Lebanese Population Before and After COVID-19 crisis.

Figures
Percentages are shown; P-value for McNemar-Bowker test <0.001.