Long COVID Is Associated with Decreased Quality of Life and Increased Mental Disability
1
Department of Physical Therapy, University of Utah, 520 Wakara Way, Salt Lake City, UT 84108, USA
2
Department of Pharmacotherapy, University of Utah, 30 South 2000 East, Salt Lake City, UT 84112, USA
3
Medical Group Population Health, University of Utah, 50 North Medical Drive, Salt Lake City, UT 84132, USA
4
Department of Economics, Hannam University, 70 Hannamro, Daedukgu, Daejeon 34430, Republic of Korea
*
Author to whom correspondence should be addressed.
COVID 2024, 4(11), 1719-1730; https://doi.org/10.3390/covid4110120
Submission received: 10 September 2024
/
Revised: 28 October 2024
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Accepted: 28 October 2024
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Published: 30 October 2024
Abstract
:COVID-19’s impact on quality of life (QoL) has been studied; however, data on the effects of long COVID on QoL and mental disability remain limited. This study aimed to investigate whether long COVID is associated with decreased QoL and increased mental disability. We analyzed data from adults (≥18 years) in the 2022 Medical Expenditure Panel Survey (MEPS). Physical and mental QoL were assessed using the Veterans RAND 12-Item Health Survey, while mental disability was measured with the Kessler Index. Long COVID was defined as experiencing COVID-related symptoms for over 3 months. To account for skewness in the outcome variables, the study employed survey-weighted generalized linear regression with a log link and gamma distribution. The analysis included 153,330,408 subjects (unweighted n = 10,975). The average age of those with and without long COVID was similar (51 vs. 52 years, p = 0.46). Subjects with long COVID had a 3% lower physical QoL (β = −0.03, p = 0.02), a 4% lower mental QoL (β = −0.04, p < 0.01), and a 26% higher mental disability score (β = 0.26, p < 0.01) compared to those without long COVID. These findings highlight the urgent need for targeted strategies to address long COVID and support patients in recovering their pre-COVID QoL and mental health.
1. Introduction
Coronavirus disease (COVID-19) has had a profound impact on people worldwide. The World Health Organization (WHO) reports over 775 million cases and over 7 million deaths attributable to COVID-19 since the beginning of the pandemic [1].
The COVID-19 pandemic continues to strain healthcare systems globally. A major ongoing concern is the long-term effects of COVID-19 infection, commonly referred to as long COVID. The Centers for Disease Control and Prevention (CDC) defines long COVID as a chronic condition that persists for at least 3 months after COVID-19 infection [2]. Long COVID is a debilitating illness affecting approximately 10% of severe COVID-19 cases, although estimates suggest that between 10 and 30% of individuals may be affected due to the prevalence of undocumented cases [3,4]. Although the symptoms of long COVID typically resolve in most cases [5], neuropsychiatric symptoms can persist for more than 6–12 months after acute COVID-19 [6]. Moreover, around 25% of people with long COVID report facing substantial limitations in their daily activities [7].
The health impacts of long COVID are substantial and can affect multiple organ systems, with more than 200 specific symptoms associated with the condition [8,9]. Common symptoms of long COVID include post-exertional malaise, fatigue, cognitive difficulties (often referred to as brain fog), dizziness, gastrointestinal problems, heart palpitations, and so on [10,11]. In particular, long COVID could be associated with the onset or worsening of neurological and mental health conditions such as attention-deficit/hyperactivity disorder (ADHD), anxiety, depression, altered taste (dysgeusia), diminished sense of smell (hyposmia), memory problems, balance issues, tinnitus, vertigo, hearing loss, insomnia, and post-traumatic stress disorder (PTSD) [10,12,13,14,15]. Given the adverse effects of persistent fatigue, pain, low physical activity, and mental health, long COVID may have a significant impact on quality of life (QoL) and mental disability.
Previous studies have explored the relationship between COVID-19 and QoL. A review reported that individuals with COVID-19 experienced declines in physical function, a reduced ability to perform activities of daily living, and diminished health-related QoL 1 to 6 months after infection [16]. However, data on the association between long COVID and both QoL and mental disability are limited. This study aimed to investigate whether long COVID is associated with decreased QoL and increased mental disability using national survey data.
2. Materials and Methods
2.1. Data
This study utilized the 2022 Full Year Consolidated Medical Expenditure Panel Survey (MEPS). The MEPS is a national survey representing the U.S. civilian noninstitutionalized population. It collects comprehensive data on various topics, including demographic information, income, health status, disability status, access to care, employment variables, health insurance status, healthcare use and expenditure, and COVID-19-related variables. The MEPS is a key resource for estimating national healthcare expenditures, analyzing the prevalence and costs of chronic conditions, and assessing the impact of COVID-19 on healthcare systems. More detailed information on these areas can be found in other publications and reports [17,18,19].
2.2. Subjects
Adults (≥18 years old) in 2022 were included in the study. Participants with responses of “don’t know”, “refused”, or “inapplicable” to the long-COVID question were excluded. Additionally, those with missing values for either the outcomes or covariates were excluded. Only participants who provided responses for both the physical and mental QoL, as well as the mental disability questions, were included in the analysis.
2.3. Outcomes
The study focused on three outcomes: physical QoL, mental QoL, and mental disability. QoL was measured using the Veterans RAND 12-Item Health Survey (VR-12), which consists of 12 items designed to assess health-related quality of life [17]. The VR-12 provides two component summaries: the Physical Component Summary (PCS), which measures physical QoL, and the Mental Component Summary (MCS), which measures mental QoL [20,21]. Higher scores indicate better physical and mental QoL. The mental disability was measured by the Kessler Index, known as K6, which consists of 6 questions that provide a summary measure of mental disability [17,22]. A higher score indicates greater mental disability. Both the VR-12 and the K6 measures are well validated and exhibit high reliability.
2.4. Covariates
The primary independent variable was whether participants experienced long COVID, as assessed in the MEPS with the question ‘Has the person had symptoms lasting three months or longer that were not present prior to contracting COVID-19?’ [17].
Control variables included factors potentially associated with QoL and mental disability [23,24,25,26,27]. These variables included age (18–30, 31–40, 41–50, 51–64, and ≥65 years old), sex (male vs. female), race/ethnicity (non-Hispanic white, Hispanic, non-Hispanic black, non-Hispanic Asian, and non-Hispanic other race or multiple races), census region (northeast, midwest, south, and west), type of health insurance (private insurance, Medicaid, Medicare, and no insurance), marital status (married, widowed/divorced/separated, and never married), high school graduate (Yes/No), hypertension (Yes/No), diabetes (Yes/No), asthma (Yes/No), high cholesterol (Yes/No), any cancer diagnosis (Yes/No), arthritis (Yes/No), physical limitation (Yes/No), cognitive limitation (Yes/No), and smoker (Yes/No).
2.5. Statistical Approach
Given that the data originated from a national survey, weighted summary statistics and weighted regressions were used to accurately represent the U.S. population. Taylor-series linearization estimated standard errors, accounting for the complex design of the MEPS [17].
Weighted summary statistics, including means, standard deviations (SD), and percentages, were used to describe the characteristics of subjects with and without long COVID. t-tests and Chi-square tests compared these characteristics. To address skewness in the outcome variables (physical QoL, mental QoL, and mental disability), weighted generalized linear regression with a log link and gamma distribution was applied, with coefficients interpreted as percentage changes. Statistical significance was set at p < 0.05, and all analyses were conducted using Stata 18.0.
3. Results
A total of 260,980,061 adults (unweighted n = 18,101) were included in the 2022 data. After excluding 6,676,249 subjects (unweighted n = 495) with inapplicable or missing long-COVID responses, 97,857,279 subjects (unweighted n = 6453) with missing QoL or mental disability data, and 8,202,910 subjects (unweighted n = 609) with incomplete covariate data, the final sample size was 148,243,623 (unweighted n = 10,544).
The average age of subjects with and without long COVID was similar (51 vs. 52 years, p = 0.46). A greater proportion of women had long COVID (63.6% vs. 51.7%, p < 0.01). Long COVID was more common among those with hypertension (44.2% vs. 35.2%, p < 0.01), asthma (25.1% vs. 13.7%, p < 0.01), and arthritis (38.4% vs. 27.1%, p < 0.01). Participants with long COVID had lower average (SD) physical and mental QoL scores (physical QoL: 46.31 (11.87) vs. 50.08 (10.09), p < 0.01; mental QoL: 48.53 (10.19) vs. 51.75 (8.71), p < 0.01). The mean (SD) mental disability score was higher in those with long COVID (4.72 (5.05) vs. 3.00 (3.91), p < 0.01) (Table 1).
In the weighted generalized linear regression models, individuals with long COVID exhibited a 3% lower physical QoL (β = −0.03, p = 0.01). Women had a 2% lower physical QoL compared to men (β = −0.02, p < 0.01), while those covered by Medicaid had a 5% lower physical QoL than individuals with private insurance (β = −0.05, p < 0.01). Furthermore, individuals with hypertension or diabetes showed a 4% and 5% lower physical QoL, respectively (β = −0.04, p < 0.01; β = −0.05, p < 0.01). Subjects with physical or cognitive limitations experienced significantly reduced physical QoL, decreasing by 28% and 13%, respectively (p < 0.01 for both) (Table 2).
Similarly, long COVID was associated with a 4% decrease in mental QoL (β = −0.04, p < 0.01). Older adults had higher mental QoL, with increases of 7% and 9% in the 51–64 and ≥65 age groups, respectively (β = 0.07, p < 0.01; β = 0.09, p <0.01). Individuals with physical or cognitive limitations exhibited 5% and 13% lower mental QoL, respectively (p < 0.01 for both) (Table 3).
Long COVID was associated with a 26% higher mental disability score (β = 0.26, p < 0.01), while women had scores 16% higher than men (β = 0.16, p < 0.01). Individuals with asthma and arthritis also had elevated mental disability scores, by 24% (p < 0.01) and 21% (p < 0.01), respectively (Table 4).
4. Discussion
This study makes two significant contributions: first, it utilizes population-level data to provide a robust assessment of quality of life (QoL) among individuals with long COVID; second, it offers a detailed evaluation of mental disability in this population. Our findings reveal a marked decline in both physical and mental QoL, along with an increase in mental disability among individuals with long COVID. Specifically, those with long COVID experienced 3% lower physical QoL and 4% lower mental QoL compared to individuals without long COVID. Several studies have reported similar declines in quality of life (QoL) among individuals with long COVID, though many are limited by smaller sample sizes. A survey study of 988 young adults living in Ireland with suspected and confirmed COVID-19 found a significant decrease in QoL among those with prolonged symptoms lasting more than 14 days [28]. Similarly, a focused group study of 47 individuals living with long COVID in Canada separated participants into two groups of those with and without pre-existing mental health conditions and reported significant mental health challenges, ineffective coping mechanisms, and diminished quality of life among adults affected by long COVID [29]. While these studies offer important insights, their sample sizes and specific participant characteristics limit their generalizability.
Furthermore, three studies conducted in South Korea, Switzerland, and Italy, involving sample sizes of 132, 112, and 572, respectively, administered questionnaires on health-related quality of life (HRQoL) to outpatients. These studies reported significant declines in HRQoL and overall negative perceptions of health status among the participants [6,30,31]. However, these studies were also limited by relatively small sample sizes, geographic restrictions, lack of diversity in participant characteristics, and lack of involvement of control groups. In contrast, our study, utilizing the extensive MEPS dataset, analyzed a nationally representative sample of over 153 million individuals in the U.S. civilian non-institutionalized population, which makes it unique in several ways. The MEPS dataset allows for the inclusion of a wide variety of covariates, such as race/ethnicity, income, insurance status, and multiple health comorbidities (e.g., hypertension, diabetes, cancer, asthma, and mental health conditions). This level of detail allows for a more in-depth exploration of quality-of-life variations across different population subgroups, considering potential factors that might influence the association between long COVID and overall well-being.
Several studies have explored the psychological, physical, and social dimensions of long COVID, highlighting its significant impact on quality of life (QoL). A survey study involving 253 participants with long COVID symptoms found that social stigma was strongly associated with worse mental health outcomes, including higher levels of perceived stress, depressive symptoms, and anxiety, as well as lower mental HRQoL. However, after controlling for confounders, social stigma was not significantly associated with physical HRQoL, which suggests that mental health is particularly vulnerable to the effects of social stigma in this population [32]. Our study utilizes a much larger and more diverse population, finding declines in both mental and physical QoL. Several studies have shown that fatigue, reduced physical activity, and functional decline are key predictors of lower physical QoL in long COVID patients, particularly among older adults, but these studies often involve smaller, specific populations [33,34,35]. One cross-sectional study utilizing the EuroQOL EQ-5D-5L and WHO Disability Assessment Schedule revealed that long COVID significantly affected both physical and mental health, with participants reporting considerable disability and functional impairments [34]. However, this study also had a limited sample and lacked controls for key factors like comorbidities and socioeconomic status. Lastly, larger studies, such as Carlile et al. (2024), which included 6070 participants, found that long COVID was linked to significant declines in health-related QoL, with a 0.37 quality-adjusted life-month reduction and a strong correlation between long COVID and reported physical disability [36].
This study demonstrates that long COVID leads to declines in both mental disability and quality of life (QoL), with findings that are consistent with previous studies. The 26% increase in mental disability among individuals with long COVID in our study is particularly concerning, as psychological symptoms such as anxiety and depression likely exacerbate the impact of long COVID on overall well-being. While some research suggests that QoL may initially decline after a COVID-19 infection but improve over time, the decrease in QoL due to mental health disorders—such as anxiety and depressive symptoms—often persists without significant improvement [6]. This observation is further supported by a study [31] that found that individuals with long COVID experienced notably poorer health-related QoL, particularly when compounded by anxious–depressive symptoms and sleep disturbances. The decline in QoL may also be influenced by emotional and social factors tied to the broader impacts of the COVID-19 pandemic, which vary across countries. Initially, social isolation was likely a major driver of reduced QoL during the pandemic. However, as the acute phase of the pandemic has passed, the ongoing effects of long COVID—rather than social isolation—have become the primary contributors to diminished QoL. This makes the study of long COVID’s impact on QoL especially timely, as attention now shifts to addressing the lingering consequences of the disease itself. Moreover, our results suggest that certain subgroups, including women and individuals with preexisting health conditions, are particularly vulnerable to the long-term effects of COVID-19. Women in our study reported significantly lower physical and mental QoL, as well as higher mental disability scores, reflecting a potential gender disparity in the experience of long COVID. This finding aligns with other research showing that women are more likely to experience long COVID and its associated neuropsychiatric symptoms [37].
Given the profound impact on QoL, continuous post-illness follow-up is essential for individuals with long COVID to ensure that they receive comprehensive care. This care should include not only medical management but also physical rehabilitation and psychosocial support to address the mental health challenges that many face. Coordinated efforts between healthcare providers and multidisciplinary teams are crucial to delivering holistic care, which should integrate mental health services, physical therapy, and chronic disease management.
Although this study provides valuable insights into the impact of long COVID on QoL and mental disability, several limitations should be acknowledged. First, the study focused exclusively on adults, limiting the generalizability of the findings to younger populations, such as children and adolescents. Since the MEPS does not capture QoL or long COVID data for these age groups, future research should explore the effects of long COVID on younger individuals. Second, unmeasured confounders may have influenced the outcomes. While the study controlled for various sociodemographic and health-related factors, other unobserved variables such as pre-existing mental health conditions or socioeconomic stressors could affect the relationship between long COVID and QoL outcomes. Third, the reliance on self-reported data introduces the potential for recall bias or inaccuracies in respondents’ answers. Fourth, subjects excluded from the study due to missing values may differ from those included in the analysis. If subjects with missing values had been included through imputation, the study results could differ, indicating potential biases. Lastly, one more limitation of this study is that we did not explore potential interactions between physical QoL, mental QoL, and mental disability within a single model. While testing these interactions could provide additional insights, our primary objective was to independently evaluate the direct associations between long COVID and each of these outcomes.
5. Conclusions
The current findings underscore the urgent need to develop targeted strategies for addressing long COVID and to establish support pathways that help patients restore their pre-COVID-19 QoL and mental health. Given the global scale of the pandemic, the healthcare needs of patients with COVID-19 sequelae are expected to increase in the future. A comprehensive understanding of long COVID is essential for creating the infrastructure and healthcare strategies necessary to enhance both the QoL and long-term health outcomes for COVID-19 survivors.
Author Contributions
Conceptualization, J.K.; methodology, J.K.; formal analysis, J.K. and S.L.; investigation, J.K., E.E.D., P.W. and S.L.; writing—original draft preparation, J.K., E.E.D., P.W. and S.L.; writing—review and editing, J.K., E.E.D., P.W. and S.L. All authors have read and agreed to the published version of the manuscript.
Funding
This research received no external funding.
Institutional Review Board Statement
As we utilized a publicly available dataset, IRB approval for the study was not required.
Informed Consent Statement
As we utilized a publicly available dataset, informed consent for the study was not required.
Data Availability Statement
The data underlying the results presented in the study are available from the Medical Expenditure Panel Survey website: https://meps.ahrq.gov/mepsweb/data_stats/download_data_files.jsp (accessed on 2 September 2024).
Conflicts of Interest
The authors declare no conflicts of interest.
References
- Demko, Z.O.; Yu, T.; Mullapudi, S.K.; Varela Heslin, M.G.; Dorsey, C.A.; Payton, C.B.; Tornheim, J.A.; Blair, P.W.; Mehta, S.H.; Thomas, D.L.; et al. Two-Year Longitudinal Study Reveals That Long COVID Symptoms Peak and Quality of Life Nadirs at 6–12 Months Postinfection. Open Forum Infect. Dis. 2024, 11, ofae027. [Google Scholar] [CrossRef] [PubMed]
- Cascella, M.; Rajnik, M.; Aleem, A.; Dulebohn, S.C.; Di Napoli, R. Features, Evaluation, and Treatment of Coronavirus (COVID-19); StatPearls: Treasure Island, FL, USA, 2024. [Google Scholar]
- Stokes, E.K.; Zambrano, L.D.; Anderson, K.N.; Marder, E.P.; Raz, K.M.; El Burai Felix, S.; Tie, Y.; Fullerton, K.E. Coronavirus Disease 2019 Case Surveillance—United States, January 22–May 30, 2020. MMWR Morb. Mortal. Wkly. Rep. 2020, 69, 759–765. [Google Scholar] [CrossRef]
- Gotlib, I.H.; Miller, J.G.; Borchers, L.R.; Coury, S.M.; Costello, L.A.; Garcia, J.M.; Ho, T.C. Effects of the COVID-19 Pandemic on Mental Health and Brain Maturation in Adolescents: Implications for Analyzing Longitudinal Data. Biol. Psychiatry Glob. Open Sci. 2022, 3, 912–918. [Google Scholar] [CrossRef]
- Yelin, D.; Moschopoulos, C.D.; Margalit, I.; Gkrania-Klotsas, E.; Landi, F.; Stahl, J.P.; Yahav, D. ESCMID rapid guidelines for assessment and management of long COVID. Clin. Microbiol. Infect. 2022, 28, 955–972. [Google Scholar] [CrossRef]
- Kim, Y.; Bae, S.; Chang, H.H.; Kim, S.W. Long COVID prevalence and impact on quality of life 2 years after acute COVID-19. Sci. Rep. 2023, 13, 11207. [Google Scholar]
- Ford, N.D.; Agedew, A.; Dalton, A.F.; Singleton, J.; Perrine, C.G.; Saydah, S. Notes from the Field: Long COVID Prevalence Among Adults—United States, 2022. MMWR Morb. Mortal. Wkly. Rep. 2024, 73, 135–136. [Google Scholar] [CrossRef]
- Aiyegbusi, O.L.; Hughes, S.E.; Turner, G.; Rivera, S.C.; McMullan, C.; Chandan, J.S.; Haroon, S.; Price, G.; Davies, E.H.; Nirantharakumar, K.; et al. Symptoms, complications and management of long COVID: A review. J. R. Soc. Med. 2021, 114, 428–442. [Google Scholar] [CrossRef]
- Nalbandian, A.; Sehgal, K.; Gupta, A.; Madhavan, M.V.; McGroder, C.; Stevens, J.S.; Cook, J.R.; Nordvig, A.S.; Shalev, D.; Sehrawat, T.S.; et al. Post-acute COVID-19 syndrome. Nat. Med. 2021, 27, 601–615. [Google Scholar] [CrossRef]
- Davis, H.E.; McCorkell, L.; Vogel, J.M.; Topol, E.J. Long COVID: Major findings, mechanisms and recommendations. Nat. Rev. Microbiol. 2023, 21, 133–146. [Google Scholar] [CrossRef]
- Thaweethai, T.; Jolley, S.E.; Karlson, E.W.; Levitan, E.B.; Levy, B.; McComsey, G.A.; McCorkell, L.; Nadkarni, G.N.; Parthasarathy, S.; Singh, U.; et al. Development of a Definition of Postacute Sequelae of SARS-CoV-2 Infection. JAMA 2023, 329, 1934–1946. [Google Scholar] [CrossRef]
- Lopez-Leon, S.; Wegman-Ostrosky, T.; Perelman, C.; Sepulveda, R.; Rebolledo, P.A.; Cuapio, A.; Villapol, S. More than 50 long-term effects of COVID-19: A systematic review and meta-analysis. Sci. Rep. 2021, 11, 16144. [Google Scholar] [CrossRef] [PubMed]
- Shanbehzadeh, S.; Tavahomi, M.; Zanjari, N.; Ebrahimi-Takamjani, I.; Amiri-Arimi, S. Physical and mental health complications post-COVID-19: Scoping review. J. Psychosom. Res. 2021, 147, 110525. [Google Scholar] [CrossRef] [PubMed]
- Subramanian, A.; Nirantharakumar, K.; Hughes, S.; Myles, P.; Williams, T.; Gokhale, K.M.; Taverner, T.; Chandan, J.S.; Brown, K.; Simms-Williams, N.; et al. Symptoms and risk factors for long COVID in non-hospitalized adults. Nat. Med. 2022, 28, 1706–1714. [Google Scholar] [CrossRef] [PubMed]
- Warren, A.M.; Khetan, R.; Bennett, M.; Pogue, J.; Waddimba, A.C.; Powers, M.B.; Sanchez, K. The relationship between stigma and mental health in a population of individuals with COVID-19. Rehabil. Psychol. 2022, 67, 226–230. [Google Scholar] [CrossRef]
- De Oliveira Almeida, K.; Nogueira Alves, I.G.; de Queiroz, R.S.; de Castro, M.R.; Gomes, V.A.; Santos Fontoura, F.C.; Brites, C.; Neto, M.G. A systematic review on physical function, activities of daily living and health-related quality of life in COVID-19 survivors. Chronic Illn. 2023, 19, 279–303. [Google Scholar] [CrossRef]
- Agency for Healthcare Research and Quality. MEPS HC 243 2022 Full Year Consolidated Data File of Site. Available online: https://meps.ahrq.gov/data_stats/download_data/pufs/h243/h243doc.shtml (accessed on 8 September 2024).
- Ben-Umeh, K.C.; Kim, J. Income disparities in COVID-19 vaccine and booster uptake in the United States: An analysis of cross-sectional data from the Medical Expenditure Panel Survey. PLoS ONE 2024, 19, e0298825. [Google Scholar] [CrossRef]
- Kim, J.; Stevens, P.; Carbone, P.S.; Jones, K.B. Health Care Use and Spending of Pediatric Patients with an Intellectual or Developmental Disability. Med. Care 2020, 58, 468–473. [Google Scholar] [CrossRef]
- Selim, A.; Rogers, W.; Qian, S.; Rothendler, J.A.; Kent, E.E.; Kazis, L.E. A new algorithm to build bridges between two patient-reported health outcome instruments: The MOS SF-36(R) and the VR-12 Health Survey. Qual. Life Res. 2018, 27, 2195–2206. [Google Scholar] [CrossRef]
- Boston University School of Public Health. VR-36, VR-12, and VR-6D of Site. Available online: https://www.bu.edu/sph/research/centers-and-groups/vr-36-vr-12-and-vr-6d/ (accessed on 8 September 2024).
- Kessler, R.C.; Andrews, G.; Colpe, L.J.; Hiripi, E.; Mroczek, D.K.; Normand, S.L.; Walters, E.E.; Zaslavsky, A.M. Short screening scales to monitor population prevalences and trends in non-specific psychological distress. Psychol. Med. 2002, 32, 959–976. [Google Scholar] [CrossRef]
- Burstrom, K.; Johannesson, M.; Diderichsen, F. Health-related quality of life by disease and socio-economic group in the general population in Sweden. Health Policy 2001, 55, 51–69. [Google Scholar] [CrossRef]
- Heyworth, I.T.; Hazell, M.L.; Linehan, M.F.; Frank, T.L. How do common chronic conditions affect health-related quality of life? Br. J. Gen. Pract. 2009, 59, e353–e358. [Google Scholar] [CrossRef] [PubMed]
- Akbari Sari, A.; Karimi, F.; Emrani, Z.; Zeraati, H.; Olyaeemanesh, A.; Daroudi, R. The impact of common chronic conditions on health-related quality of life: A general population survey in Iran using EQ-5D-5L. Cost Eff. Resour. Alloc. 2021, 19, 28. [Google Scholar] [CrossRef] [PubMed]
- Parker, L.; Moran, G.M.; Roberts, L.M.; Calvert, M.; McCahon, D. The burden of common chronic disease on health-related quality of life in an elderly community-dwelling population in the UK. Fam. Pract. 2014, 31, 557–563. [Google Scholar] [CrossRef] [PubMed]
- Poudel, A.N.; Zhu, S.; Cooper, N.; Roderick, P.; Alwan, N.; Tarrant, C.; Ziauddeen, N.; Yao, G.L. Impact of Covid-19 on health-related quality of life of patients: A structured review. PLoS ONE 2021, 16, e0259164. [Google Scholar] [CrossRef]
- O’Mahony, L.; Buwalda, T.; Blair, M.; Forde, B.; Lunjani, N.; Ambikan, A.; Neogi, U.; Barrett, P.; Geary, E.; O’Connor, N.; et al. Impact of Long COVID on health and quality of life. HRB Open Res. 2022, 5, 31. [Google Scholar] [CrossRef]
- Kennelly, C.E.; Nguyen, A.T.; Sheikhan, N.Y.; Strudwick, G.; Ski, C.F.; Thompson, D.R.; Bartram, M.; Soklaridis, S.; Rossell, S.L.; Castle, D.; et al. The lived experience of long COVID: A qualitative study of mental health, quality of life, and coping. PLoS ONE 2023, 18, e0292630. [Google Scholar] [CrossRef]
- Malesevic, S.; Sievi, N.A.; Baumgartner, P.; Roser, K.; Sommer, G.; Schmidt, D.; Vallelian, F.; Jelcic, I.; Clarenbach, C.F.; Kohler, M. Impaired health-related quality of life in long-COVID syndrome after mild to moderate COVID-19. Sci. Rep. 2023, 13, 7717. [Google Scholar] [CrossRef]
- Mastrorosa, I.; Del Duca, G.; Pinnetti, C.; Lorenzini, P.; Vergori, A.; Brita, A.C.; Camici, M.; Mazzotta, V.; Baldini, F.; Chinello, P.; et al. What is the impact of post-COVID-19 syndrome on health-related quality of life and associated factors: A cross-sectional analysis. Health Qual. Life Outcomes 2023, 21, 28. [Google Scholar] [CrossRef]
- Scholz, U.; Bierbauer, W.; Luscher, J. Social Stigma, Mental Health, Stress, and Health-Related Quality of Life in People with Long COVID. Int. J. Environ. Res. Public Health 2023, 20, 3927. [Google Scholar] [CrossRef]
- Shanbehzadeh, S.; Zanjari, N.; Yassin, M.; Yassin, Z.; Tavahomi, M. Association between long COVID, functional activity, and health-related quality of life in older adults. BMC Geriatr. 2023, 23, 40. [Google Scholar] [CrossRef]
- Tak, C.R. The health impact of long COVID: A cross-sectional examination of health-related quality of life, disability, and health status among individuals with self-reported post-acute sequelae of SARS CoV-2 infection at various points of recovery. J. Patient Rep. Outcomes 2023, 7, 31. [Google Scholar] [CrossRef] [PubMed]
- Vélez-Santamaría, R.; Fernández-Solana, J.; Méndez-López, F.; Domínguez-García, M.; González-Bernal, J.J.; Magallón-Botaya, R.; Oliván-Blázquez, B.; González-Santos, J.; Santamaría-Peláez, M. Functionality, physical activity, fatigue and quality of life in patients with acute COVID-19 and Long COVID infection. Sci. Rep. 2023, 13, 19907. [Google Scholar] [CrossRef] [PubMed]
- Carlile, O.; Briggs, A.; Henderson, A.D.; Butler-Cole, B.F.; Tazare, J.; Tomlinson, L.A.; Marks, M.; Jit, M.; Lin, L.Y.; Bates, C.; et al. Impact of long COVID on health-related quality-of-life: An OpenSAFELY population cohort study using patient-reported outcome measures (OpenPROMPT). Lancet Reg. Health Eur. 2024, 40, 100908. [Google Scholar] [CrossRef] [PubMed]
- Juszko, K.; Szary, P.; Mazurek, J.; Rutkowski, S.; Cieślik, B.; Szczepańska-Gieracha, J.; Gajda, R. Long-Term Consequences of COVID-19 Disease Specific to Women: Exploratory Research. Int. J. Environ. Res. Public Health 2022, 20, 150. [Google Scholar] [CrossRef]
Table 1.
Characteristics of subjects with and without long COVID.
| Long COVID | ||||
|---|---|---|---|---|
| No | Yes | Total | p-Value | |
| N | 137,383,489 (92.7%) | 10,860,135 (7.3%) | 148,243,623 (100.0%) | |
| Age as continuous (mean (SD)) | 50.886 (18.371) | 51.551 (16.689) | 50.934 (18.253) | 0.46 |
| Age category | <0.01 | |||
| 18–30 | 23,491,002 (17.1%) | 1,558,664 (14.4%) | 25,049,666 (16.9%) | |
| 31–40 | 23,432,341 (17.1%) | 1,698,726 (15.6%) | 25,131,067 (17.0%) | |
| 41–50 | 20,228,972 (14.7%) | 1,708,724 (15.7%) | 21,937,696 (14.8%) | |
| 51–64 | 31,693,484 (23.1%) | 3,467,823 (31.9%) | 35,161,307 (23.7%) | |
| ≥65 | 38,537,689 (28.1%) | 2,426,199 (22.3%) | 40,963,888 (27.6%) | |
| Sex | <0.01 | |||
| Male | 66,383,525 (48.3%) | 3,949,273 (36.4%) | 70,332,798 (47.4%) | |
| Female | 70,999,964 (51.7%) | 6,910,862 (63.6%) | 77,910,825 (52.6%) | |
| Race/Ethnicity | <0.01 | |||
| Non-Hispanic White | 89,990,941 (65.5%) | 8,037,256 (74.0%) | 98,028,197 (66.1%) | |
| Hispanic | 20,372,105 (14.8%) | 1,425,975 (13.1%) | 21,798,080 (14.7%) | |
| Non-Hispanic Black | 14,810,860 (10.8%) | 789,758 (7.3%) | 15,600,618 (10.5%) | |
| Non-Hispanic Asian | 8,593,691 (6.3%) | 264,264 (2.4%) | 8,857,955 (6.0%) | |
| Non-Hispanic other races or multiple races | 3,615,892 (2.6%) | 342,881 (3.2%) | 3,958,773 (2.7%) | |
| Census region | 0.04 | |||
| Northeast | 22,726,723 (16.5%) | 1,479,755 (13.6%) | 24,206,478 (16.3%) | |
| Midwest | 31,853,178 (23.2%) | 3,039,448 (28.0%) | 34,892,625 (23.5%) | |
| South | 52,269,666 (38.0%) | 3,739,239 (34.4%) | 56,008,904 (37.8%) | |
| West | 30,533,923 (22.2%) | 2,601,693 (24.0%) | 33,135,616 (22.4%) | |
| Type of health insurance | 0.01 | |||
| Private insurance | 75,078,565 (54.6%) | 6,038,599 (55.6%) | 81,117,165 (54.7%) | |
| Medicaid | 15,199,795 (11.1%) | 1,655,749 (15.2%) | 16,855,544 (11.4%) | |
| Medicare | 37,961,407 (27.6%) | 2,396,583 (22.1%) | 40,357,991 (27.2%) | |
| Uninsured | 9,143,721 (6.7%) | 769,203 (7.1%) | 9,912,925 (6.7%) | |
| Marital status | 0.02 | |||
| Married | 72,973,639 (53.1%) | 5,990,952 (55.2%) | 78,964,591 (53.3%) | |
| Widowed/divorced/separated | 29,159,111 (21.2%) | 2,730,966 (25.1%) | 31,890,077 (21.5%) | |
| Never married | 35,250,739 (25.7%) | 2,138,217 (19.7%) | 37,388,956 (25.2%) | |
| High school graduate | 120,474,437 (87.7%) | 9,470,083 (87.2%) | 129,944,521 (87.7%) | 0.71 |
| Hypertension | 48,344,168 (35.2%) | 4,802,859 (44.2%) | 53,147,027 (35.9%) | <0.01 |
| Diabetes | 16,840,775 (12.3%) | 1,514,742 (13.9%) | 18,355,517 (12.4%) | 0.19 |
| Asthma | 18,813,356 (13.7%) | 2,729,768 (25.1%) | 21,543,124 (14.5%) | <0.01 |
| High cholesterol | 47,042,602 (34.2%) | 4,690,029 (43.2%) | 51,732,631 (34.9%) | <0.01 |
| Any cancer | 17,437,530 (12.7%) | 1,721,674 (15.9%) | 19,159,204 (12.9%) | 0.04 |
| Arthritis | 37,218,175 (27.1%) | 4,166,821 (38.4%) | 41,384,996 (27.9%) | <0.01 |
| Physical limitation | 16,854,321 (12.3%) | 2,331,767 (21.5%) | 19,186,088 (12.9%) | <0.01 |
| Cognitive limitation | 7,229,603 (5.3%) | 1,158,708 (10.7%) | 8,388,311 (5.7%) | <0.01 |
| Current smoker | 14,930,512 (10.9%) | 1,365,977 (12.6%) | 16,296,489 (11.0%) | 0.24 |
| Outcome | ||||
| Physical quality of life | 50.08 (10.08) | 46.31 (11.87) | 49.80 (10.27) | <0.01 |
| Mental quality of life | 51.75 (8.71) | 48.53 (10.19) | 51.51 (8.87) | <0.01 |
| Mental disability score | 3.00 (3.91) | 4.72 (5.05) | 3.13 (4.03) | <0.01 |
Table 2.
Factors associated with physical quality of life.
| Variable | Coefficient | p-Value | 95% Confidence Interval | |
|---|---|---|---|---|
| Long COVID | −0.03 | 0.01 | −0.05 | −0.01 |
| Age category | ||||
| 18–30 | reference | |||
| 31–40 | 0.00 | 0.58 | −0.01 | 0.01 |
| 41–50 | −0.02 | <0.01 | −0.03 | −0.01 |
| 51–64 | −0.03 | <0.01 | −0.05 | −0.02 |
| ≥65 | −0.04 | 0.09 | −0.09 | 0.01 |
| Female | −0.02 | <0.01 | −0.02 | −0.01 |
| Race/Ethnicity | ||||
| Non-Hispanic White | reference | |||
| Hispanic | 0.00 | 0.64 | −0.01 | 0.01 |
| Non-Hispanic Black | 0.00 | 0.74 | −0.02 | 0.01 |
| Non-Hispanic Asian | −0.02 | 0.06 | −0.04 | 0.00 |
| Non-Hispanic other races or multiple races | −0.02 | 0.15 | −0.04 | 0.01 |
| Census region | ||||
| Northeast | 0.02 | <0.01 | 0.01 | 0.04 |
| Midwest | 0.01 | 0.08 | 0.00 | 0.02 |
| South | reference | |||
| West | 0.01 | 0.03 | 0.00 | 0.03 |
| Type of health insurance | ||||
| Private insurance | reference | |||
| Medicaid | −0.05 | <0.01 | −0.06 | −0.03 |
| Medicare | −0.02 | 0.32 | −0.07 | 0.02 |
| Uninsured | −0.01 | 0.23 | −0.02 | 0.01 |
| Marital status | ||||
| Married | reference | |||
| Widowed/divorced/separated | −0.01 | 0.07 | −0.03 | 0.00 |
| Never married | 0.01 | 0.22 | 0.00 | 0.02 |
| High school graduate | 0.04 | <0.01 | 0.02 | 0.05 |
| Hypertension | −0.04 | <0.01 | −0.05 | −0.03 |
| Diabetes | −0.05 | <0.01 | −0.07 | −0.04 |
| Asthma | −0.01 | 0.02 | −0.03 | 0.00 |
| High cholesterol | −0.01 | 0.01 | −0.03 | 0.00 |
| Any cancer | −0.01 | 0.08 | −0.03 | 0.00 |
| Arthritis | −0.06 | <0.01 | −0.07 | −0.05 |
| Physical limitation | −0.28 | <0.01 | −0.31 | −0.26 |
| Cognitive limitation | −0.13 | <0.01 | −0.16 | −0.10 |
| Current smoker | −0.02 | <0.01 | −0.04 | −0.01 |
Table 3.
Factors associated with mental quality of life.
| Variable | Coefficient | p-Value | 95% Confidence Interval | |
|---|---|---|---|---|
| Long COVID | −0.04 | <0.01 | −0.06 | −0.02 |
| Age category | ||||
| 18–30 | reference | |||
| 31–40 | 0.01 | 0.53 | −0.01 | 0.03 |
| 41–50 | 0.02 | 0.02 | 0.00 | 0.04 |
| 51–64 | 0.07 | <0.01 | 0.05 | 0.09 |
| ≥65 | 0.09 | <0.01 | 0.05 | 0.14 |
| Female | −0.03 | <0.01 | −0.04 | −0.02 |
| Race/Ethnicity | ||||
| Non-Hispanic White | reference | |||
| Hispanic | 0.04 | <0.01 | 0.03 | 0.06 |
| Non-Hispanic Black | 0.03 | <0.01 | 0.02 | 0.05 |
| Non-Hispanic Asian | 0.02 | 0.04 | 0.00 | 0.04 |
| Non-Hispanic other races or multiple races | 0.01 | 0.52 | −0.02 | 0.04 |
| Census region | ||||
| Northeast | −0.01 | 0.05 | −0.03 | 0.00 |
| Midwest | −0.01 | 0.32 | −0.02 | 0.01 |
| South | reference | |||
| West | −0.03 | <0.01 | −0.04 | −0.01 |
| Type of health insurance | ||||
| Private insurance | reference | |||
| Medicaid | −0.02 | 0.02 | −0.04 | 0.00 |
| Medicare | 0.01 | 0.65 | −0.03 | 0.05 |
| Uninsured | 0.01 | 0.30 | −0.01 | 0.03 |
| Marital status | ||||
| Married | reference | |||
| Widowed/divorced/separated | −0.02 | <0.01 | −0.03 | −0.01 |
| Never married | −0.02 | 0.03 | −0.03 | 0.00 |
| High school graduate | 0.01 | 0.24 | −0.01 | 0.02 |
| Hypertension | −0.01 | 0.07 | −0.02 | 0.00 |
| Diabetes | −0.02 | <0.01 | −0.04 | −0.01 |
| Asthma | −0.04 | <0.01 | −0.05 | −0.02 |
| High cholesterol | −0.01 | 0.01 | −0.02 | 0.00 |
| Any cancer | 0.01 | 0.21 | 0.00 | 0.02 |
| Arthritis | −0.02 | <0.01 | −0.03 | −0.01 |
| Physical limitation | −0.05 | <0.01 | −0.06 | −0.03 |
| Cognitive limitation | −0.13 | <0.01 | −0.16 | −0.10 |
| Current smoker | −0.05 | <0.01 | −0.07 | −0.03 |
Table 4.
Factors associated with mental disability score.
| Variable | Coefficient | p-Value | 95% Confidence Interval | |
|---|---|---|---|---|
| Long COVID | 0.26 | <0.01 | 0.16 | 0.37 |
| Age category | ||||
| 18–30 | reference | |||
| 31–40 | −0.09 | 0.13 | −0.20 | 0.03 |
| 41–50 | −0.29 | <0.01 | −0.42 | −0.17 |
| 51–64 | −0.61 | <0.01 | −0.72 | −0.49 |
| ≥65 | −0.81 | <0.01 | −1.27 | −0.36 |
| Female | 0.16 | <0.01 | 0.10 | 0.22 |
| Race/Ethnicity | ||||
| Non-Hispanic White | reference | |||
| Hispanic | −0.40 | <0.01 | −0.53 | −0.28 |
| Non-Hispanic Black | −0.35 | <0.01 | −0.46 | −0.24 |
| Non-Hispanic Asian | −0.13 | 0.14 | −0.30 | 0.04 |
| Non-Hispanic other races or multiple races | −0.02 | 0.82 | −0.20 | 0.16 |
| Census region | ||||
| Northeast | 0.03 | 0.60 | −0.08 | 0.14 |
| Midwest | 0.02 | 0.63 | −0.08 | 0.13 |
| South | reference | |||
| West | 0.14 | 0.01 | 0.04 | 0.25 |
| Type of health insurance | ||||
| Private insurance | reference | |||
| Medicaid | 0.13 | 0.02 | 0.02 | 0.23 |
| Medicare | 0.03 | 0.88 | −0.40 | 0.47 |
| Uninsured | −0.06 | 0.49 | −0.23 | 0.11 |
| Marital status | ||||
| Married | reference | |||
| Widowed/divorced/separated | 0.15 | <0.01 | 0.07 | 0.23 |
| Never married | 0.17 | <0.01 | 0.09 | 0.26 |
| High school graduate | −0.08 | 0.13 | −0.19 | 0.02 |
| Hypertension | 0.05 | 0.19 | −0.02 | 0.12 |
| Diabetes | 0.12 | 0.01 | 0.03 | 0.20 |
| Asthma | 0.24 | <0.01 | 0.16 | 0.32 |
| High cholesterol | 0.12 | <0.01 | 0.05 | 0.19 |
| Any cancer | 0.02 | 0.71 | −0.08 | 0.11 |
| Arthritis | 0.21 | <0.01 | 0.13 | 0.29 |
| Physical limitation | 0.44 | <0.01 | 0.35 | 0.53 |
| Cognitive limitation | 0.62 | <0.01 | 0.50 | 0.74 |
| Current smoker | 0.28 | <0.01 | 0.18 | 0.38 |
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MDPI and ACS Style
Kim, J.; Duru, E.E.; Weir, P.; Lee, S. Long COVID Is Associated with Decreased Quality of Life and Increased Mental Disability. COVID 2024, 4, 1719-1730. https://doi.org/10.3390/covid4110120
AMA Style
Kim J, Duru EE, Weir P, Lee S. Long COVID Is Associated with Decreased Quality of Life and Increased Mental Disability. COVID. 2024; 4(11):1719-1730. https://doi.org/10.3390/covid4110120
Chicago/Turabian StyleKim, Jaewhan, Emeka Elvis Duru, Peter Weir, and Sanghoon Lee. 2024. "Long COVID Is Associated with Decreased Quality of Life and Increased Mental Disability" COVID 4, no. 11: 1719-1730. https://doi.org/10.3390/covid4110120
APA StyleKim, J., Duru, E. E., Weir, P., & Lee, S. (2024). Long COVID Is Associated with Decreased Quality of Life and Increased Mental Disability. COVID, 4(11), 1719-1730. https://doi.org/10.3390/covid4110120
