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 Table of Contents  
Year : 2022  |  Volume : 23  |  Issue : 1  |  Page : 62-66

Medical and psychological comorbidity among COVID patients during the first wave in Dharwad District of South India: A cross-sectional study

1 Assistant Professor, Departments of Psychiatric Social Work, Dharwad Institute of Mental Health and Neuro Sciences, Dharwad, Karnataka, India
2 Professor, Department of Psychiatry, Dharwad Institute of Mental Health and Neuro Sciences, Dharwad, Karnataka, India
3 Assistant Professor, Department of Psychiatry, Institute of Psychiatry & Human Behaviour, Goa, India
4 Professor, Departments of Biostatistics, National Institute of Mental Health and Neuro Sciences (NIMHANS), Bangalore, India
5 Assistant Professor, Centre for PSS in Disaster Management, National Institute of Mental Health and Neuro Sciences (NIMHANS), Bangalore, India
6 MPhil scholar, Department of Social Work, Central University of Karnataka, Kalaburagi, Karnataka, India

Date of Submission14-Sep-2021
Date of Acceptance17-Dec-2021
Date of Web Publication04-Mar-2022

Correspondence Address:
Dr. Kannappa V Shetty
Department of Psychiatric Social Work, Dharwad Institute of Mental Health and Neuro Sciences, Dharwad, Karnataka
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/amh.amh_136_21

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Background: The COVID-19 is a viral communicable disease and the World Health Organization declared it as a public health emergency of international concern. This pandemic has challenged the entire world including India's health-care system and resources. It is a devastating recurrence in people with underlying health issues or comorbidities, eventually resulting in mortality. Comorbidities including both medical and psychological disorders among COVID patients have a large amount of impact on the individual's mental health as well as functioning.
Materials and Methods: The study comprised 800 hospitalized COVID-19 patients during the first wave from North Karnataka region in India. The data were collected using a structured interview schedule through hospital telephones. The ethical approval was obtained from the Institute Research Ethics Committee.
Results: The mean age of the hospitalized COVID patients was 41.02 ± 15.21, and the mean age of comorbidity was 47.69 ± 14.84. Following medical comorbidities such as diabetes (9.3%), hypertension (9.3%), cancer (1.8%), diabetes + hypertension (2.1%), and asthma (0.9%) and psychological comorbidities such as anxiety (3.8%) and depression (3.3%) were found among the hospitalized COVID patients during the first wave.
Conclusions: It can be observed that comorbidity may increase the risk of death among COVID patients who were hospitalized and appropriate medical and psychological interventions can be provided for various co comorbidities at the earliest to prevent further defuncting and distress caused by the pandemic.

Keywords: Comorbidity, COVID-19, first wave, hospitalization, medical and psychological intervention

How to cite this article:
Shetty KV, Desai M, Srivastava A, Marimuthu P, Manikappa SK, Bamney U. Medical and psychological comorbidity among COVID patients during the first wave in Dharwad District of South India: A cross-sectional study. Arch Ment Health 2022;23:62-6

How to cite this URL:
Shetty KV, Desai M, Srivastava A, Marimuthu P, Manikappa SK, Bamney U. Medical and psychological comorbidity among COVID patients during the first wave in Dharwad District of South India: A cross-sectional study. Arch Ment Health [serial online] 2022 [cited 2022 Oct 5];23:62-6. Available from: https://www.amhonline.org/text.asp?2022/23/1/62/339118

  Introduction Top

The pandemic has been described as a threat to people's lives and the normal functioning of society.[1] COVID-19 that has swept the globe, impacting people's social lives and has forced humanity to maintain social distance.[2] India, the second most populous country in the world after China, is the dominant region in the South Asian area. According to the World Health Organization, as of July 1, 2021, the global prevalence of COVID-19 confirmed cases are 181, 930, and 736 and 3,945,832 deaths, and in India, there have been 30,411,634 confirmed cases with 399,459 deaths.[3] In Karnataka, there are 28,47,013 confirmed cases and 35,134 deaths.[4] The Indian government had imposed a 3-week nationwide lockdown, beginning at midnight on March 24, 2020, to halt the spread of COVID-19, after 563 persons tested positive in the country.[5]

COVID-19 and physical health complications

COVID-19 is thought to have increasingly fast and devastating effects such as bronchitis, pneumonia, respiratory failure, or end-organ failure, especially in people with underlying health issues or comorbidities such as high blood pressure, diabetes, coronary heart disease, and cirrhosis, eventually resulting to mortality.[6] During the pandemic, individuals' lives are affected by social isolation because they are less active, more so in elderly, which may raise the risk of illness through lowering immunity.[7] Fatigue is the most often reported symptom followed by joint pain and chest discomfort following an acute COVID-19 infection.[8]

COVID-19 and mental health complications

COVID-19 is expected to have a significant and long-term impact on mental health and well-being.[9] Since the coronavirus epidemic in India, there has been a 20% increase in mental health problems.[10] Self-isolation and quarantine have had an impact on people's normal activities, habits, and livelihoods, potentially leading to an increase in loneliness, anxiety, sadness, sleeplessness, dangerous alcohol and drug usage, as well as self-harm or suicide conduct.[11] Hence, our study is intended to understand the medical and psychological comorbidity among COVID patients during the first COVID-19 wave in Dharwad district, Karnataka.

  Materials And Methods Top

The current study needed to be carried because- (1) Looking at both medical and psychological comorbidities and monitoring them regularly during COIVD-19 can lead to better preparedness and response by both health and mental health professionals. (2) People with psychological comorbidities may have poor knowledge or misconceptions, so identifying the source and magnitude of the problem are crucial for health-care professionals. (3) Preparing individuals, families and communities medically, psychologically and socially in all stages of a pandemic for a healthy response to medical and psychological comorbidities. The findings of this study would lead to better biopsychosocial methods and approaches that can be used to design psychosocial counseling modules for persons with medical and psychological comorbidities during biological disasters. The study would also be basis for further research in these areas.

Study design

a cross-sectional descriptive research design to determine the medical and psychological comorbidity among COVID patients during the first COVID-19 wave was used.

Study setting

The research institute, a state-run tertiary mental health care center, has been designated as a counseling center for COVID-19 patients in the district. The institute has been receiving the list of such patients from multiple hospitals for the purpose of counseling on a daily basis. The data were collected using a semi-structured interview schedule between July and December 2020. The assessment was done through hospital telephones.


All patients diagnosed with COVID-19 of Dharwad district, Karnataka were part of universe of study. The criteria for inclusion were as follows: (1) hospitalized (only mild-to-moderate symptoms) and home isolated patients, (2) those who were willing to participate in the research study, (3) those who could understand Kannada, English, or Hindi language, and (4) the patients who had a telephone facility.

Sample selection

Eight hundred out of 5295 hospitalized patients from North Karnataka were selected using a simple random sampling approach.

Medical diagnosis

The medical comorbidity was assessed by physicians of the primary hospitals, and the same data were shared with the telecounseling center for psychosocial interventions.

Psychiatric diagnosis

A team of qualified mental health professionals screened the COVID patients for psychological comorbidity using the International Classification of Diseases-10 criteria while doing telecounseling, and the same was confirmed by one of the researchers of the study, who is the senior professor of the Department of Psychiatry of DIMHANS, Dharwad.


An interview schedule was developed to collect the sociodemographic variables such as age, gender, marital status, religion, education, occupation, family type, residence, and medical and psychological comorbidity variables.

Ethical consideration

Ethical approval for this research was obtained from the Institutional Review Board (No-DIMHANS/I.E.R.B/2020-21). Before beginning each telephonic interview, the aim and voluntary nature of the study were described to the participants and caregivers, and the verbal permission was obtained from them. The interview confidentiality was ensured. The patients who indicated psychosocial concerns during and after the interviews were provided with supportive counseling, and the appropriate referral was also made for those who needed further interventions.


The researchers had expected subjective bias as many of their relatives/known people were also affected with COVID-19 and a certain level of selection bias would operate in the study due to the hospital cum community nature of the study and the online assessments. To overcome this bias, the research team has performed all assessments in a standardized manner, and the same was cross-checked by the senior professor of psychiatry.

Statistical methods

The data were computed in Excel and exported to SPSS-21. Frequency and central tendencies were performed. Other tests such as Chi-square (χ2) and Pearson correlation were applied.

  Results Top

[Figure 1] shows the age-wise comorbidity among the COVID patients during the first COVID-19 wave in the North Karnataka region. The mean age of the patients who were not having any comorbidity was 39.61 ± 14.92, whereas the patients those who were having medical and/or psychological comorbidity reported to have the mean age of 49.69 ± 14.84. The further analysis on these variables revealed that there is a statistically significant difference (P < 0.001) between the groups.
Figure 1: Age-wise comorbidity among the COVID patients

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[Table 1] explains the sociodemographic and comorbidity variables of the COVID patients during the first wave. The mean age of the hospitalized COVID patients was 41.02 ± 15.21, and majority of the patients 456 (58.1%) were male. Half of the patients 410 (51.3%) studied up to 12th standard (grade). Occupation-wise analysis revealed that 158 (19.8%) of them were involved in business and 157 (19.6%) were homemakers, and interestingly, 103 (12.9%) of them were medical professionals (doctors). Majority of them 711 (88.9%) were part of nuclear family, and 661 (82.6%) of them were living in urban areas. Four hundred and fifty (56.3%) of them were hospitalized, whereas 350 (43.8%) them were in home isolation. The medical comorbidity analysis shows: diabetes 74 (9.3%), hypertension 74 (9.3%), cancer 14 (1.8%), diabetes + hypertension 17 (2.1%), and asthma 7 (0.9%). Psychological comorbidity analysis reveals anxiety 30 (3.8%) and depression 26 (3.3%) among the COVID patients.
Table 1: Sociodemographic and comorbidity variables of the COVID-19 patients

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[Table 2] explains the association between anxiety, depression (the researchers could not assess other psychiatric conditions such as post-traumatic stress disorder, substance dependence, and grief as such reactions are usually seen among survivors in the later phase of disasters) and this study was conducted in early stage of the COVID-19 pandemic where the most common reactions were anxiety and depression and sociodemographic variables of the COVID-19 patients. Education, type of the family, and residency were found to be associated with psychological comorbidities.
Table 2: Association between anxiety and depression on education, type of family, residency, marital status, gender, and occupation of the COVID-19 patients

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  Discussion Top

COVID-19 has affected physical, social, and psychological aspects of human life, so it becomes imperative to understand from an intervention point of view how these factors influence one another and lead to further psychological and mental health comorbidities. The current study is an attempt toward this aspect of the pandemic in India, where disaster management research needs to be prioritized. Another uniqueness of this study is that it has tried to find out the correlation between medical and psychological comorbidities and sociodemographic background of the COVID patients.

The mean age in our study sample was 41.02+/‒15.21 years, which is similar to that, reported in Indian literature.[12] There was a slight male preponderance in our study. Among the study sample of 800 patients with COVID-19 infection, 21.3% had at least one medical comorbidity, most common being diabetes mellitus and hypertension. Although the percentage of medical comorbidity reported in our study is lower than that reported from European countries and also few Indian studies, the pattern of medical comorbidity was similar with diabetes and hypertension being most common in almost all of them. The lower percentage of medical comorbidities in our study could also be due to the underreporting at the primary level of physicians. However, the meta-analysis study of COVID-19 comorbidities done by Paudel[13] also reported the percentage and pattern of medical illnesses similar to our study. The people with chronic medical illnesses such as diabetes, hypertension, and chronic kidney disorders, especially those uncontrolled are at increased risk of infections including COVID-19, known to intensify the diabetes condition by increasing insulin resistance and/or targeting the islet cells in pancreas. In addition, the use of steroids in many of the patients as mainstay of the treatment worsens diabetes including precipitating de novo diabetes cases and thus increasing susceptibility to secondary infections and mortality. The other medical conditions found in our sample were cancer and asthma. Therefore, looking for medical comorbidity and monitoring them regularly during COVID-19 management can further better treatment rather than adding to the burden of illness.

When looking for psychological comorbidities, the current study elicited anxiety and depression in 3.8% and 3.3% of the study population making a total of 7.1% of the sample. Mental health issues were significantly related to being less educated among the psychological comorbidity subset with almost two-thirds (66%) of those with psychological comorbidity had either no education or education less than 12th standard. Similar results have been reported by Lei et al.[14] Later, Zhou et al.[15] reported contrasting results that those with higher grades have increased prevalence of depression and anxiety syndromes. Hence, on the one hand, education may have protective role by giving better information and probably better health-care access opportunities, and on the other hand, it can be hypothesized that academic stress may affect mental health during this pandemic.

In the current study population, the majority of the respondents who reported psychological comorbidity were from urban residential status compared to rural areas of residence (approximately 70% v/s 30%). Lei et al. and Özdin et al.[14],[16] published similar results. This brings out the fact that the urban residential location poses preexisting geographical, lifestyle, occupational, and socioeconomic challenges. Lockdown has further worsened this scenario more so in the urban areas.

Female gender is reported as a risk factor for psychological issues, but in this study, the relationship was not found to be significant. Similarly, no occupational status reached significance level when looked for association with psychological comorbidities. Probably loss or reduction of socioeconomic and occupational status, which has not been collected as a part of study data, would have given a better correlation and becomes a limitation of the study. Another limitation of our study is inadequate data capturing at various levels through digital communications.

  Conclusion Top

The comorbidities have additional deteriorating outcomes with respect to morbidity and mortality in patients with COVID-19. Patients of COVID-19 with diseases such as diabetes, hypertension, and preexisting lung disease tend to have worse prognosis. Therefore, the patients with comorbidities form a high-risk subset and need special attention and monitoring during management of COVID-19 infection.


The authors are grateful to all the COVID-19 patients and their families.

Financial support and sponsorship


Conflicts of interest

There are no conflicts of interest.

  References Top

Nunes J. The COVID-19 pandemic: Securitization, neoliberal crisis, and global vulnerabilization. Cad Saude Publica 2020;36:e00063120.  Back to cited text no. 1
Jena PK. Impact of pandemic COVID-19 on education in India. International journal of current research (IJCR). 2020;12-7;12582-6.  Back to cited text no. 2
WHO. Coronavirus Disease Situation Dashboard; 2021. Available from: https://covid19.who.int. [Last accessed on 2021 Jul 01].  Back to cited text no. 3
GovtKarnataka. COVID-19 Information Portal; 2021. Available from: https://covid19.karnataka.gov.in/english. [Last accessed on 2021 Jul 01].   Back to cited text no. 4
Pulla P. COVID-19: India imposes lockdown for 21 days and cases rise. BMJ 2020;368:m1251.  Back to cited text no. 5
Sanyaolu A, Okorie C, Marinkovic A, Patidar R, Younis K, Desai P, et al. Comorbidity and its Impact on Patients with COVID-19. SN Compr Clin Med 2020:1-8. 10.1007/s42399-020-00363-4. Epub ahead of print. PMID: 32838147; PMCID: PMC7314621.  Back to cited text no. 6
Srivastav AK, Sharma N, Samuel AJ. Impact of coronavirus disease-19 (COVID-19) lockdown on physical activity and energy expenditure among physiotherapy professionals and students using web-based open E-survey sent through WhatsApp, Facebook and Instagram messengers. Clin Epidemiol Glob Health 2021;9:78-84.  Back to cited text no. 7
Del Rio C, Collins LF, Malani P. Long-term health consequences of COVID-19. JAMA 2020;324:1723-4.  Back to cited text no. 8
O'Connor RC, Wetherall K, Cleare S, McClelland H, Melson AJ, Niedzwiedz CL, et al. Mental health and well-being during the COVID-19 pandemic: Longitudinal analyses of adults in the UK COVID-19 Mental Health & Wellbeing study. Br J Psychiatry 2021;218:326-33.  Back to cited text no. 9
Roy A, Singh AK, Mishra S, Chinnadurai A, Mitra A, Bakshi O. Mental health implications of COVID-19 pandemic and its response in India. Int J Soc Psychiatry 2021;67:587-600.  Back to cited text no. 10
WHO. Coronavirus Disease (COVID-19): Situation Report, 166. WHO; 2020.  Back to cited text no. 11
Mohandas P, Periasamy S, Marappan M, Sampath A, Garfin Sundaram VK, Cherian VK. Clinical review of COVID-19 patients presenting to a quaternary care private hospital in South India: A retrospective study. Clin Epidemiol Glob Health 2021;11:100751.  Back to cited text no. 12
Paudel SS. A meta-analysis of 2019 novel corona virus patient clinical characteristics and comorbidities. Research Square; 2020. DOI: 10.21203/rs.3.rs-21831/v1.  Back to cited text no. 13
Lei L, Huang X, Zhang S, Yang J, Yang L, Xu M. Comparison of prevalence and associated factors of anxiety and depression among people affected by versus people unaffected by quarantine during the COVID-19 epidemic in Southwestern China. Med Sci Monit 2020;26:e924609.  Back to cited text no. 14
Zhou SJ, Zhang LG, Wang LL, Guo ZC, Wang JQ, Chen JC, et al. Prevalence and socio-demographic correlates of psychological health problems in Chinese adolescents during the outbreak of COVID-19. Eur Child Adolesc Psychiatry 2020;29:749-58.  Back to cited text no. 15
Özdin S, Bayrak Özdin Ş. Levels and predictors of anxiety, depression and health anxiety during COVID-19 pandemic in Turkish society: The importance of gender. Int J Soc Psychiatry 2020;66:504-11.  Back to cited text no. 16


  [Figure 1]

  [Table 1], [Table 2]


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