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 Table of Contents  
ORIGINAL ARTICLE
Year : 2022  |  Volume : 4  |  Issue : 4  |  Page : 217-223

Quality of life and psychological impact among chronic disease patients during the COVID-19 pandemic


1 Department of Nursing, Fatima College of Health Sciences, Al Ain, Abu Dhabi, United Arab Emirates
2 Department of Clinical Pharmacy and Therapeutics, Faculty of Pharmacy, Applied Science Private University, Amman, Jorden

Date of Submission06-Aug-2022
Date of Decision16-Sep-2022
Date of Acceptance27-Sep-2022
Date of Web Publication26-Dec-2022

Correspondence Address:
Dr. Mohammed Al Maqbali
Fatima College of Health Sciences, Al Ain, Abu Dhabi
United Arab Emirates
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/jin.jin_76_22

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  Abstract 


Objective: Patients diagnosed with chronic disease may experience psychological symptoms including depression, anxiety, insomnia, and fatigue, all of which may adversely affect their quality of life (QoL). The main objective of this study is to identify the level of QoL, to know the prevalence of these symptoms among chronic disease patients in Oman during the third wave of coronavirus disease 2019 (COVID-19) pandemic, and to explore the contributing factors.
Methods: A cross-sectional and descriptive correlational design was used. Convenience sampling was used to recruit participants. Data were collected using the Functional Assessment of Chronic Therapy (FACT)–General, Hospital Anxiety and Depression Scale, the Insomnia Severity Index, and the FACT–Fatigue subscale via Qualtrics® software. Linear regression analyses were used to explore factors that were associated with QoL.
Results: Of 990 patients with chronic disease who participated, the mean total QoL score was 67.7 (standard deviation = 16.1). Participants aged above 51, those with a basic education, those with heart disease, or those with more than one comorbidity had a significantly lower QoL. Linear regression revealed that the main factors associated with lower QoL included heart disease (β = 0.05, P = 0.02), diabetes (β = 0.12, P < 0.01), having taken one dose of COVID-19 vaccine (β = 0.05, P = 0.04), anxiety (β = −0.24, P < 0.01), depression (β = −0.31, P < 0.01), insomnia (β = −0.12, P < 0.01), and fatigue (β = 0.27, P < 0.01).
Conclusions: The COVID-19 pandemic has significantly reduced the individuals' level of QoL and affected the mental health of patients diagnosed with chronic diseases. Appropriate strategies to monitor psychological problems and interventions to prevent and reduce these among such patients are needed.

Keywords: Anxiety, chronic disease, coronavirus disease 2019, depression, fatigue, insomnia


How to cite this article:
Al Maqbali M, Alsayed A, Bashayreh I. Quality of life and psychological impact among chronic disease patients during the COVID-19 pandemic. J Integr Nurs 2022;4:217-23

How to cite this URL:
Al Maqbali M, Alsayed A, Bashayreh I. Quality of life and psychological impact among chronic disease patients during the COVID-19 pandemic. J Integr Nurs [serial online] 2022 [cited 2023 Jan 29];4:217-23. Available from: https://www.journalin.org/text.asp?2022/4/4/217/365325




  Introduction Top


In 2020, coronavirus disease 2019 (COVID-19) created a major challenge to health-care systems worldwide. COVID-19 is a highly contagious virus that causes severe acute respiratory distress in humans. In March 2020, the World Health Organization declared COVID-19 a global pandemic due to the rapid outbreak of the virus.[1] COVID-19 causes a significant and serious threat to people, especially those with underlying comorbidities such as diabetes.

It has been reported that fatal cases of COVID-19 are highly prevalent among patients with comorbidities.[2],[3] A systematic review and meta-analysis of 22 studies involving 3286 patients with laboratory-confirmed COVID-19 was conducted by Cheng et al.[4] to identify the association of comorbidities in severe and nonsevere cases. The review found that a higher prevalence of comorbidities was associated with fatal cases. Several studies found that those with specific comorbidities, including hypertension, coronary artery diseases,[5] diabetes mellitus, and cancer,[6] are at higher risk of mortality. In addition, people with chronic diseases are more vulnerable to the negative psychological effects of COVID-19.[7] Given that COVID-19 is a highly infectious and rapidly transmitted disease which results in increased numbers of cases and deaths, especially among chronic disease patients, this may reduce the quality of life (QoL) in these patients, and they may also experience psychological distress.[8] The unpredictability and the uncertainty of different chronic diseases in terms of their epidemiology and the effectiveness of methods of treatment expose people to stressful situations of varying magnitude.[9] Fear of the consequences of a potentially deadly disease such as COVID-19, combined with a lowering of QoL, presence of other underlying comorbidities, severe anxiety, and mental distress, all of which can coincide with insomnia, can create unfavorable conditions for patients.[10],[11]

To date, the impact of the COVID-19 pandemic on QoL and, specifically, the psychological impact on individuals with chronic diseases, has not been systematically reported. Therefore, the aim of this study was to assess QoL of chronic disease patients in the third wave of the COVID-19 pandemic in Oman, and to determine the prevalence of anxiety, depression, insomnia, and fatigue among them. Moreover, this study seeks to identify the factors that could contribute to a decrease in the QoL in chronic disease patients during the third wave of the COVID-19 pandemic.


  Methods Top


Study design

The study employed a large-scale cross-sectional, descriptive, correlational design. The survey was developed using an online platform (Qualtrics®).

Setting and sampling

Convenience sampling was used to recruit participants from across two clinics in the Al Buraimi governorate, Oman. The study was conducted from June 2021 to September 2021. The sample size was determined by using the Raosoft software calculator based on a 99% confidence level, margin of error of 5%, and 50% nonresponse rate, and the sample size required was 629 participants.[12]

Inclusion criteria for participation were as follows: adult patients over 18 years of age, able to speak and write in Arabic, and with no known psychiatric or neurological disorders that could interfere with study participation. In addition, they must be diagnosed with a chronic disease. Exclusion criterion for the participants was if the patient was <18 years of age.

Measures

The questionnaire included detailed demographics, background history, and psychometric scales, including the Arabic versions of the Functional Assessment of Chronic Therapy–General (FACT-G), the Hospital Anxiety and Depression Scale (HADS), the Insomnia Severity Index (ISI), and FACT–Fatigue subscale (FACT-F).

Demographics

Information about the participants' age, sex, marital status, educational level, employment status, time since diagnosis, and other comorbidities was obtained in the survey.

Quality of life

QoL is an important aspect of patients' care. The FACT-G self-administration questionnaire was used to assess QoL in the study.[13],[14] The FACT-G measures QoL with 27 items across the following four domains: physical well-being (PWB) (7 items), social/family well-being (SWB) (7 items), emotional well-being (EWB) (6 items), and functional well-being (FWB) (7 items). Each subscale score can be calculated separately if more than 50% of the items are answered. The response options consist of a 5-point scale for each item, ranging from 0 to 4 (0 = not at all; 1 = a little bit; 2 = somewhat; 3 = quite a bit; and 4 = very much). The total score was calculated by summing all the individuals' subscales (PWB + SWB + EWB + FWB), and the possible score ranged from 0 to 108. Higher scores indicate greater QoL. The Arabic version of FACT-G has demonstrated high internal consistency of 0.92.[15]

Level of depression and anxiety

The HADS comprises 14 items assessing anxiety (7-items) and depression (7-items) which are rated using a 4-point response (from 0 to 3). The scores in each subscale are computed by summing the corresponding items, with a maximum score of 21 for each subscale. A score of 0–7 is considered normal, 8–10 as a borderline case, and 11–21 as a case exhibiting anxiety or depression.[16] The Arabic version of HADS demonstrated very good internal consistency (Cronbach's α = 0.83).[17]

Fatigue

For measuring fatigue, the study used the FACT-F. This is a 13-item questionnaire that assesses self-reported fatigue in the past 7 days.[18] The response options used a 5-point scale for each item, ranging from 0 to 4 (0 = not at all; 1 = a little bit; 2 = somewhat; 3 = quite a bit; and 4 = very much). The possible score ranged from 0 to 52. A higher score indicates lower fatigue. However, Van Belle et al.[19] identify 34 as the cutoff point for the diagnosis of fatigue in patients with cancer. In other words, a score that is ≤34 indicates clinically significant fatigue. The Arabic version of FACT-F demonstrated very good internal consistency (Cronbach's α = 0.92).[15]

Insomnia

The ISI is a 7-item self-report questionnaire assessing the nature, severity, and impact of insomnia.[20] A 5-point scale is used to rate each item (e.g., 0 = no problem; 4 = very severe problem), yielding a total possible score of 0–28. The total score is interpreted as follows: absence of insomnia (0–7); sub-threshold insomnia (8–14); moderate insomnia (15–21); and severe insomnia (22–28). A cutoff value of 15 has been used as the threshold for clinically relevant insomnia. A previous study has reported good internal consistency for the Arabic version (Cronbach's α = 0.82).[21]

Statistical analysis

The data were transferred into the Statistical Package for Social Sciences version 25 (SPSS Inc., IBM Company, Chicago, IL, USA). In order to address the research questions, descriptive statistics were calculated in the form of means, standard deviations (SDs), standard errors, frequencies, percentages of all the scales and subscales, and participant variables. Independent t-test and ANOVA were used to test whether the levels of QoL differed in terms of demography and treatment, fatigue, anxiety, depression, and insomnia. Dummy variables were created for categorical variables. Multiple linear regression analyses were used to determine predictors of the FACT-G scale and subscale. P < 0.05 was considered to be statistically significant for all analyses.

Ethical considerations

Ethical permission was sought from the Health Ethics Committee at the Ministry of Health, Al Buraimi governorate (MoH/DGBA/PROPOSAL_APPROVED/06/2021). The confidentiality and privacy of the participants were maintained. Consent was obtained using a consent statement which was presented on the first screen of the survey tool.


  Results Top


A total of 1013 patients completed this survey. Nearly 990 (97.7%) patients were included in the analysis. Twenty-three patients were not included in the study: 8 declined to participate and 15 did not complete enough of the questionnaire for their responses to be included. With regard to gender, 520 (52.5%) were female and 470 (47.5%) were male. The majority (281 [28.4%]) were aged between 18 and 30 years, followed by the >60 years' age group (221 [22.3%]). Most participants were married (640 [64.6%]). There were 346 (34.9%) participants who had completed only basic education. The majority were unemployed (538 [54.3%]); 504 (50.9%) had more than one comorbidity, only 281 (28.4%) had been infected with COVID-19, and 536 (54.1%) had taken only one dose of the COVID-19 vaccination.

The FACT-G scores ranged from 19 to 108 with a mean of 67.7 (SD = 16.1). The prevalence of anxiety was 65.4% (647/990), and 49.1% (486/990) of the participants had depression, whereas 75.1% (743/990) complained of fatigue. Insomnia was presented by 77.6% (768/990) of the participants. The participants in the 51–60 years' age group (mean = 66.4, SD = 16.3) and those >60 years (Mean = 63.7, SD = 15.9) had significantly lower mean scores on the QoL scale compared with the other age groups. QoL among those with chronic illnesses was shown to be significantly lower in the case of participants who had basic education (mean = 63.5, SD = 16.2) compared with those at other education levels. Participants with heart disease (mean = 68.0, SD = 15.4) and more than one comorbidity (mean = 64.1, SD = 15.8) had a significantly lower QoL compered with patients with diabetes.

The QoL score was significantly lower in participants who had not been infected with COVID-19 (mean = 65, SD = 16.8) compared to those who had (mean = 68.7, SD = 15.7). Analysis revealed that participants who had not taken the COVID-19 vaccination (mean = 61.5, SD = 14.1) were more likely to have lower QoL compared to vaccinated participants. Participants with anxiety (mean = 61.6, SD = 13.6), depression (mean = 59.6, SD = 13.7), fatigue (mean = 62.9, SD = 13.8), and insomnia (mean = 64.8, SD = 15) were all more likely to report a significantly lower QoL score, as shown in [Table 1].
Table 1: Demographic and clinical characteristic of chronic medical illness (n=990)

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Predictive factors for the FACT-G scale and subscale

The FACT-G total score was the outcome variable in the first multiple linear regression analysis. Heart disease (β = 0.05, P = 0.02), diabetes (β = 0.12, P < 0.01), no previous COVID-19 status (β = 0.06, P < 0.01), having taken one dose of COVID-19 vaccine (β = 0.05, P = 0.04), above threshold HADS anxiety score (β = −0.24, P < 0.01), HADS depression score (β = −0.31, P < 0.01), ISI score (β = −0.12, P < 0.01) and a FACT-F score (β = 0.27, P < 0.01) were significantly associated with lower QoL [Table 2].
Table 2: Multiple linear regression for possible related factors of Functional Assessment of Chronic Therapy-General

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  Discussion Top


This study was conducted 15 months after the pandemic in Oman to identify QoL among participants with chronic medical conditions. Throughout the pandemic, undoubtedly many individuals demonstrated fear and anxiety with regard to COVID-19. Several researchers have linked the fear and the reduction of the QoL level to the psychological and PWB of individuals.[22],[23] Therefore, it is important to identify those experiencing the negative influences of the COVID-19 pandemic on their QoL.

The results of this survey showed that overall, the QoL of patients with a chronic condition after 18 months of the pandemic was poor (mean score = 67.7 [SD = 16.1]). This finding is consistent with studies conducted earlier in the COVID-19 pandemic.[24],[25],[26] Making a comparison with the general population, Horesh et al.[27] conducted a cross-sectional survey to identify QoL among the general population during the COVID-19 pandemic and found that those who presented with a chronic condition were significantly associated with a lower QoL. The present study was conducted between June and September 2021, during the third wave of the pandemic, when there was a higher death rate than during the first or second wave. This may have been responsible for the even lower levels of QoL and the increase in the prevalence of psychological symptoms among the participants in the current study.

In addition, in this study, the reported prevalence of anxiety was 65.4%; that of depression was 49.1%, and that of insomnia was 77.6%. Previous studies have reported rates of prevalence among those with chronic medical conditions during the COVID-19 pandemic of 20% (anxiety),[28] 25% (depression),[29] and 49% (insomnia).[30] This variation of prevalence in terms of QoL, anxiety, depression, and insomnia may be partly attributed to differences in the geographical regions studied, socioeconomic status of the samples, health-care systems, and methodologies used. Another possible contributor might be the stage of the pandemic at which studies were conducted.

In this study, those participants aged above 51 years had a lower total QoL score than participants younger than 51 years. This may be explained by the fact that individuals over 40 years old had a higher risk for COVID-19 mortality.[31] Further, the study found that infected participants had a higher level of QoL compared to noninfected participants. Furthermore, participants who had received the COVID-19 vaccination reported a higher level of QoL compared to nonvaccinated participants. This may be because those participants understand that they more likely to suffer less severe COVID-19 symptoms than would have been the case if they were not infected or vaccinated.[32],[33] In addition, they may have realized that infection would likely develop their body's immunity, which might reduce the risk of recurrence or re-infection.[34],[35]

Participants with a secondary school education had a significantly lower level of QoL compared to participants who had a degree and above. This may be due to the limited knowledge of COVID-19 and the upsetting news. However, participants with a low education level may not be able to obtain accurate information about COVID-19.[22] In line with this information, fabricated reports or misinformation about the COVID-19 pandemic can raise anxiety and depression, which might lead to a lowering of the level of QoL.[36]

As expected, this study found that anxiety, depression, insomnia, and fatigue may have deleterious effects on QoL. The result shows that persistent anxiety, depression, insomnia, and fatigue have a significant association with reducing the level of QoL. These findings are similar to those of recent studies showing that a poorer level of QoL was associated with a high prevalence of anxiety, depression, insomnia, and fatigue.[37],[38],[39]

The COVID-19 pandemic has reduced QoL levels and increased mental health problems in Oman and throughout the world. QoL, anxiety, depression, insomnia, and fatigue are significant problems for individuals with chronic disease. The results of the current study have a number of potential implications for interventions to improve QoL and the psychological well-being of such individuals. Currently, most health-care professionals in Oman do not assess QoL and psychological symptoms on a regular basis. This study provides evidence that individuals with chronic disease in Oman experience poor levels of QoL and a higher prevalence of anxiety, depression, insomnia, and fatigue. Thus, it would be advisable for health-care professionals to conduct regular assessments of QoL and psychological symptoms and provide appropriate management. The results strongly suggest the need for comprehensive interventions to prevent mental health problems among chronic disease patients related to the COVID-19 pandemic.

The study has a number of limitations. First, it was conducted in one country – Oman – which may limit generalization to other nations. Second, the study utilized a cross-sectional design and it was unable to investigate the causal relationships, if any, between QoL and the psychological symptoms resulting from the COVID-19 pandemic. Third, the study used online recruitment using a convenience sampling method, which may lead to sampling error as well as selection bias. Finally, the study relied on the use of self-report questionnaires to assess the psychological problems, and possibly results may differ from a clinical diagnostic interview.

Further research should include a qualitative interview approach. This would help to provide a comprehensive in-depth understanding of QoL and associated symptoms and inform recommendations to improve further practice for relieving these symptoms. Further research is needed to investigate the patients' perceptions about the management strategy with regard to how best to manage the problem.


  Conclusions Top


This is the first study to provide evidence with regard to the level of QoL and the prevalence of anxiety, depression, insomnia, and fatigue among chronic diseases patients in Oman during the COVID-19 pandemic. Anxiety, depression, insomnia, and fatigue were significantly related to decreased QoL for this patient group. Furthermore, as the COVID-19 virus continues to spread, this finding gives a solid foundation for the next step of the research, which should involve the identification of appropriate management strategies to improve the QoL and reduce the psychological symptoms of patients with chronic diseases.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

1.
WHO. International Health Regulations Emergency Committee on Novel Coronavirus in China; 2020. Available from: https://www.who.int/news-room/events/detail/2020/01/30/default-calendar/international-health-regulations-emergency-committee-on-novel- coronavirus-in-china. [Last accessed on 2020 Sep 12].  Back to cited text no. 1
    
2.
Gold MS, Sehayek D, Gabrielli S, et al. COVID-19 and comorbidities: A systematic review and meta-analysis. Postgrad Med 2020;132:749-55.  Back to cited text no. 2
    
3.
Sanyaolu A, Okorie C, Marinkovic A, et al. Comorbidity and its impact on patients with COVID-19. SN Compr Clin Med 2020;2:1069-76.  Back to cited text no. 3
    
4.
Cheng S, Zhao Y, Wang F, et al. Comorbidities' potential impacts on severe and non-severe patients with COVID-19: A systematic review and meta-analysis. Medicine (Baltimore) 2021;100:e24971.  Back to cited text no. 4
    
5.
Tabata S, Imai K, Kawano S, et al. Clinical characteristics of COVID-19 in 104 people with SARS-CoV-2 infection on the Diamond Princess cruise ship: A retrospective analysis. Lancet Infect Dis 2020;20:1043-50.  Back to cited text no. 5
    
6.
Ng WH, Tipih T, Makoah NA, et al. Comorbidities in SARS-CoV-2 patients: A systematic review and meta analysis. mBio 2021;12:e03647-20.  Back to cited text no. 6
    
7.
Kang C, Yang S, Yuan J, et al. Patients with chronic illness urgently need integrated physical and psychological care during the COVID-19 outbreak. Asian J Psychiatr 2020;51:102081.  Back to cited text no. 7
    
8.
Bo HX, Li W, Yang Y, et al. Posttraumatic stress symptoms and attitude toward crisis mental health services among clinically stable patients with COVID-19 in China. Psychol Med 2021;51:1052-3.  Back to cited text no. 8
    
9.
Zandifar A, Badrfam R. Iranian mental health during the COVID-19 epidemic. Asian J Psychiatr 2020;51:101990.  Back to cited text no. 9
    
10.
Addis SG, Nega AD, Miretu DG. Psychological impact of COVID-19 pandemic on chronic disease patients in Dessie town government and private hospitals, Northeast Ethiopia. Diabetes Metab Syndr 2021;15:129-35.  Back to cited text no. 10
    
11.
Singh K, Kondal D, Mohan S, et al. Health, psychosocial, and economic impacts of the COVID-19 pandemic on people with chronic conditions in India: A mixed methods study. BMC Public Health 2021;21:685.  Back to cited text no. 11
    
12.
Raosoft. Raosoft Sample Size Calculator, Raosoft Inc.; 2004. Available from: http://www.raosoft.com/samplesize.html. [Last accessed on 2018 Oct 16].  Back to cited text no. 12
    
13.
Cella DF, Tulsky DS, Gray G, et al. The Functional Assessment of Cancer Therapy scale: Development and validation of the general measure. J Clin Oncol 1993;11:570-9.  Back to cited text no. 13
    
14.
Webster K, Cella D, Yost K. The Functional Assessment of Chronic Illness Therapy (FACIT) Measurement System: Properties, applications, and interpretation. Health Qual Life Outcomes 2003;1:79.  Back to cited text no. 14
    
15.
Al Maqbali M, Hughes C, Gracey J, et al. Psychometric properties of the Arabic version of the functional assessment of chronic illnesses therapy-fatigue in Arabic cancer patients. J Pain Symptom Manage 2020;59:130-8.e2.  Back to cited text no. 15
    
16.
Zigmond AS, Snaith RP. The hospital anxiety and depression scale. Acta Psychiatr Scand 1983;67:361-70.  Back to cited text no. 16
    
17.
Al Maqbali M, Madkhali N, Dickens GL. Psychometric properties of the insomnia severity index among Arabic chronic diseases patients. SAGE Open Nurs 2022;8:23779608221107278, 1-8.  Back to cited text no. 17
    
18.
Yellen SB, Cella DF, Webster K, et al. Measuring fatigue and other anemia-related symptoms with the Functional Assessment of Cancer Therapy (FACT) measurement system. J Pain Symptom Manage 1997;13:63-74.  Back to cited text no. 18
    
19.
Van Belle S, Paridaens R, Evers G, et al. Comparison of proposed diagnostic criteria with FACT-F and VAS for cancer-related fatigue: Proposal for use as a screening tool. Support Care Cancer 2005;13:246-54.  Back to cited text no. 19
    
20.
Morin CM, Belleville G, Bélanger L, et al. The Insomnia Severity Index: Psychometric indicators to detect insomnia cases and evaluate treatment response. Sleep 2011;34:601-8.  Back to cited text no. 20
    
21.
Suleiman KH, Yates BC. Translating the insomnia severity index into Arabic. J Nurs Scholarsh 2011;43:49-53.  Back to cited text no. 21
    
22.
Nguyen HC, Nguyen MH, Do BN, et al. People with suspected COVID-19 symptoms were more likely depressed and had lower health-related quality of life: The potential benefit of health literacy. J Clin Med 2020;9:965.  Back to cited text no. 22
    
23.
Schimmenti A, Billieux J, Starcevic V. The four horsemen of fear: An integrated model of understanding fear experiences during the COVID-19 pandemic. Clin Neuropsychiatry 2020;17:41-5.  Back to cited text no. 23
    
24.
Lim SL, Woo KL, Lim E, et al. Impact of COVID-19 on health-related quality of life in patients with cardiovascular disease: A multi-ethnic Asian study. Health Qual Life Outcomes 2020;18:387.  Back to cited text no. 24
    
25.
O'Dwyer MC, Meixner K, Albiac LC, et al. Health-related quality of life for people with acute and chronic illnesses during the COVID-19 pandemic. J Am Board Fam Med 2021;34:509-21.  Back to cited text no. 25
    
26.
Zhang J, Lyu S, Yin H, et al. Investigation of the quality of life of patients with coronary heart disease during COVID-19 and analysis of influencing factors. Psychol Health Med 2022;27:409-20.  Back to cited text no. 26
    
27.
Horesh D, Kapel Lev-Ari R, Hasson-Ohayon I. Risk factors for psychological distress during the COVID-19 pandemic in Israel: Loneliness, age, gender, and health status play an important role. Br J Health Psychol 2020;25:925-33.  Back to cited text no. 27
    
28.
Addis SG, Nega AD, Miretu DG. Depression, anxiety and stress levels among chronic disease patients during COVID-19 pandemic in Dessie Town Hospitals, Ethiopia. Open Psychol J 2021;14:249-57.  Back to cited text no. 28
    
29.
Sisman P, Polat I, Aydemir E, et al. How the COVID-19 outbreak affected patients with diabetes mellitus? Int J Diabetes Dev Ctries 2022;42:53-61.  Back to cited text no. 29
    
30.
Li Y, Chen B, Hong Z, et al. Insomnia symptoms during the early and late stages of the COVID-19 pandemic in China: A systematic review and meta-analysis. Sleep Med 2022;91:262-72.  Back to cited text no. 30
    
31.
Bauer P, Brugger J, König F, et al. An international comparison of age and sex dependency of COVID-19 deaths in 2020: A descriptive analysis. Sci Rep 2021;11:19143.  Back to cited text no. 31
    
32.
Harris RJ, Hall JA, Zaidi A, et al. Effect of vaccination on household transmission of SARS-CoV-2 in England. N Engl J Med 2021;385:759-60.  Back to cited text no. 32
    
33.
Mason TF, Whitston M, Hodgson J, et al. Effects of BNT162b2 mRNA vaccine on COVID-19 infection and hospitalisation amongst older people: Matched case control study for England. BMC Med 2021;19:275.  Back to cited text no. 33
    
34.
Sette A, Crotty S. Adaptive immunity to SARS-CoV-2 and COVID-19. Cell 2021;184:861-80.  Back to cited text no. 34
    
35.
Zhou X, Ye Q. Cellular immune response to COVID-19 and potential immune modulators. Front Immunol 2021;12:646333.  Back to cited text no. 35
    
36.
Salari N, Hosseinian-Far A, Jalali R, et al. Prevalence of stress, anxiety, depression among the general population during the COVID-19 pandemic: A systematic review and meta-analysis. Global Health 2020;16:57.  Back to cited text no. 36
    
37.
Alimoradi Z, Broström A, Tsang HW, et al. Sleep problems during COVID-19 pandemic and its' association to psychological distress: A systematic review and meta-analysis. EClinicalMedicine 2021;36:100916.  Back to cited text no. 37
    
38.
Moncorps F, Jouet E, Bayen S, et al. Specifics of chronic fatigue syndrome coping strategies identified in a French flash survey during the COVID-19 containment. Health Soc Care Community 2022;30:1-10.  Back to cited text no. 38
    
39.
Santomauro DF, Herrera AM, Shadid J, et al. Global prevalence and burden of depressive and anxiety disorders in 204 countries and territories in 2020 due to the COVID-19 pandemic. Lancet 2021;398:1700-12.  Back to cited text no. 39
    



 
 
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