Impact of third wave of COVID-19 pandemic on mental health and its related lifestyle: a cross sectional survey

INTRODUCTION

As the coronavirus disease 2019 (COVID-19) pandemic approaches two years, it is critical to recognise the negative impact it is having on mental health at the individual level. The coronavirus outbreak threatens the global healthcare system and has an adverse impact on all facets of human life. Numerous steps have been taken to reduce the socioeconomic impact of the coronavirus, but many problems still exist. One of these problems is mental health and its related lifestyle.

When this study was started, India had entered the third wave and in the next 15 days saw the peak of the third wave with 2,115,100 confirmed cases on 17^th January 2022.¹ Panic, anxiety, and depression are just a few examples of the mental health conditions that have emerged as a result of the COVID-19 pandemic’s lack of endpoint and lack of treatment in sight. The COVID-19 pandemic increases the mental health problems of the global population, particularly health care workers. The general population and non-medical staff had a lower risk of distress than health workers.² Anxiety-inducing topics connected to this emergence of the health and socioeconomic crisis need to be quickly identified in order to early detect dysfunctional processes and maladaptive lifestyle changes potentially leading to the onset of psychiatric conditions as the general population became more exposed to them.³ Resilience and increased social support are protective factors that may help with regard to lifestyle changes and re-adaptation mechanisms, even though it has been hypothesised that specific and uncontrolled fears related to infection, pervasive anxiety, frustration, and boredom, and loneliness affect subjective wellbeing and quality of life.³

Massive global effects of the COVID-19 pandemic include high mortality and morbidity rates, income loss, and prolonged social isolation for billions of people. Worldwide, mental health disorders are a major public health concern. Due to the COVID-19 virus’s complicated pathogenicity and ongoing mutation, the recent third wave of the pandemic has raised anxiety and fear about the virus worldwide.⁴ Understanding and researching the causes, incidence, and prevalence of anxiety during the third wave of the COVID-19 pandemic in India receives insufficient attention. Due to its ignorance, India is unable to fully assist and support its citizens as they deal with the unprecedented COVID-19 pandemic. Given this context, the goal of this work was to study the impact of the COVID-19 pandemic on mental health, its related lifestyle habits, and quality of life among the Indian population.

METHODS

A cross-sectional study was performed from 28^th December 2021 to 29^th January 2022. Only adults (aged ≥18 years) who were able to provide written informed consent were recruited in the study using convenience sampling method. An online as well as written semi structured questionnaire, both in Hindi and English language was completed by the participants. Literate people coming to OPD were given written form and illiterate people were interviewed by trained staff of institute for verbal survey and people involved in neighborhood offices were provided with google form and approached by electronic medium. 401 participants completed a validated questionnaire which includes socio-demographic data and four parts that assessed dysfunctional anxiety associated with the coronavirus crisis via CAS-coronavirus anxiety scale, mental health-related lifestyle changes, the indicators of negative mental health impacts, and social and family support. Participant personal information including names was anonymized to maintain and protect confidentiality. Survey second section i.e., coronavirus anxiety scale was taken from CAS Sherman et al and third to fifth section was taken from Zhang et al.^5,6 The study protocol was approved by the ethical committee of the institute and the advisory committee of Central Council for Research in Homoeopathy.

The sections of questionnaire were as follow: I) The questionnaire was formed of five sections: first section has sociodemographic information included name, age, sex, education, occupation, contact no., if you are a healthcare professional, email id and pre-existing illness. II) Second section: the coronavirus anxiety scale (CAS) is a self-report mental health screener of dysfunctional anxiety associated with the coronavirus crisis. The CAS-coronavirus anxiety scale was created to assist clinicians and researchers in quickly identifying cases of people who are functionally impaired by coronavirus-related anxiety due to the significant number of people who experience clinically significant fear and anxiety during an infectious disease outbreak. Independent studies of adults from all over the United States have shown that the CAS is a trustworthy instrument (s>0.90), with strong construct (correlated with anxiety, depression, suicidal ideation, and drug/alcohol coping) and factorial (single-factor; invariant across socio-demographics) validity. The CAS has diagnostic qualities that are comparable to related screening tools as the generalized anxiety disorder-7 (90% sensitivity and 85% specificity). Based on experiences during the last two weeks, each CAS item is assessed on a 5-point scale, from 0 (not at all) to 4 (almost every day). The DSM-5’s cross-cutting symptom measure is consistent with this scaling style. A CAS total score ≥9 indicates probable dysfunctional coronavirus-related anxiety. Elevated scores on a single item or a high total scale score (9) may indicate that the individual is experiencing significant symptoms that require additional evaluation and/or treatment. III) The third section deals with a validated questionnaire that was used to investigate the impact of the COVID-19 pandemic on mental health-related lifestyle changes. Participants were asked to rate whether they had paid less or more attention to their mental health in the previous fifteen days (response options: decreased, unchanged/same as before, increased). Participants were also asked whether they were spending less or more time resting, relaxing, and exercising. These questions included the following response options: unchanged/same as before, increased, and decreased. IV) Fourth section dealt with six questions assessing the negative mental health impact. These questions had a Cronbach’s alpha of 0.88. These following domains assessed the changes in stress from work, financial stress, stress from home, horrified feelings due to the COVID-19 pandemic, apprehensive due to the COVID-19 pandemic, and helpless feelings due to the COVID-19 pandemic. These questions included the following response options: yes, no, and don’t know much. V) The fifth section included a validated questionnaire that examined the influence of the COVID-19 pandemic on social and family support (Cronbach’s alpha =0.87). This questionnaire’s five items assessed support from friends, support from family members, sharing feelings with other family members, sharing sentiments with others, and caring for the feelings of family members. These questions included the following response options: unchanged/same as before, increased, and decreased.

Statistical methods

The data obtained was entered into an excel sheet, and responses were coded appropriately. Statistical analysis was performed using IBN SPSS version 12. All results of quantitative variables were reported either as mean±standard deviation or frequency. A Chi-square test was employed to assess if there was a significant association between categorical variables. The association between different forms of health impacts, adjusting for demographic factors were derived using logistic regression analysis methods. The results were interpreted and depicted appropriately in tables with 95% CI and p<0.05, considered to be significant.

RESULTS

Participant characteristics

401 participants (i.e., 174 males and 227 females) were recruited into the study. The mean age of participants was 36.9±11.5, and 34.2%, aged between 18 and 30 years. Near about half of the participants (42.9%) had a higher level of education. In terms of employment status, 33.7% of participants had a full-time job, 41.1% had no job, 6.7% were students, 8.7% were self-employed and 9.7% had a part-time job (Table 1).

Impact on corona anxiety scale

Of 401 participants, only 29 participants (i.e. 7.2%) reported CAS≥9, 372 participants have CAS>9. Out of 29 participants, 23 were female and 6 males. Out of 29 participants, 86 % falls into age group 18-40 years.

Association of CAS score with demographic factors: CAS is significantly higher in female than in male. CAS is significantly higher in housewife and not working employment group (i.e. 69%) (Table 2).

Awareness and lifestyle

There were 18.2% of participants who reported that they were paying more attention to their mental health following the pandemic and in 72% there was no change. Additionally, 17.7% of participants reported that they were spending more time to rest and no change in 76%. 14.4% stated that they were spending more time to relaxing and no change in 77%. 19.9% reported that they were spending more time exercising and 66.5% reported no change. There was a significant association between gender and some of the responses including ‘did you spend enough time for rest?’ (p=0.032) did you spend time for exercise? (p=0.004) There was a significant association between education and some of the responses including ‘did you pay attention to mental health?’ (p=0.001),’did you spend enough time for rest?’ (p=0.009), ‘did you spend time for exercise?’ (p=0.001). There was significant association between occupation and some of the responses including ‘did you pay attention to mental health?’ (p=0.016), ‘did you spend time for exercise?’ (p=0.001). There was significant association between pre-existing illness and some of the responses including ‘did you pay attention to mental health?’ (p=0.012), ‘Did you spend enough time for rest?’ (p=0.001). The variable of age group was not associated with the indicators of lifestyle changes (Table 3).

^Cchi-square test

Negative health impact

During the survey, more than half of the participants (57.3%) reported no increased stress from work. Additionally, 54% of participants reported that they did not experience increased stress from home. 53% mentioned that they experience increased financial stress arising from the pandemic. On the other hand, 51% of participants reported that they felt horrified and apprehensive due to the COVID-19 pandemic. However, the majority of participants (56%) did not feel helpless due to the pandemic. There was a significant association between gender and some of the responses including ‘did you feel increase in stress from work?’ (p=0.004), ‘did you find increase in stress from home?’ (p=0.001); ‘did you feel horrified due to COVID-19?’ (p=0.031); ‘did you feel apprehensive due to COVID-19?’ (p=0.003). There was a significant association between education and some of responses including ‘did you find increase in stress from home?’ (p=0.001); ‘did you feel horrified due to COVID-19?’ (p=0.008); ‘did you feel helpless due to COVID-19?’ (p=0.033) ‘did you feel apprehensive due to COVID-19?’ (p=0.029). There was a significant association between occupation and some of the responses including ‘did you find increase in stress from home?’ (p=.059); ‘did you find increase in stress from home?’ (p=.019). Other sociodemographic variables including age group and pre-existing illness were not associated with the indicators of negative mental health impact (Table 4).

Impact on social and family support

Participants reported that they received increased support from friends (18.2%) and no change in 65.5 %. There was increased support from family members (27.9%) and no change in 63.8%. They also experienced an increased shared feelings with family members (27.1%) and no change in 64.8%, increased shared feelings with others when feeling blue (25.4%) and no change in 62.8%, and increased caring for family members’ feelings (41.1%) and no change in 54.8%. There was a significant association between gender and responses including, ‘did you get support from friends?’ (p=0.035); ‘did you get support from family members?’ (p=0.009); ‘did you share feeling with family members?’ (p=0.001); ‘did you share your feelings with others when in blue?’ (p=0.05); did you care for family member’s feelings?’. There was a significant association between education, and responses like ‘did you get support from friends?’ (p=0.019); ‘did you get support from family members?’(p=0.001); ‘did you share feeling with family members?’ (p=0.012); ‘did you share your feelings with others when in blue?’ (p=.012); ‘did you care for family member's feelings?’ (p=0.001). There was association between occupation and responses like ‘did you get support from friends?’ (p=0.002); ‘did you get support from family members?’ (p=0.001); ‘did you share feeling with family members?’ (p=0.006); ‘did you share your feelings with others when in blue?’ (p=0.037); ‘did you care for family member's feelings?’ (p=0.001). Other sociodemographic variables including age group and pre-existing illness were not associated with the indicators of changes in family (Table 5).

The association between items of family support and awareness and lifestyle and negative mental health is summarized in Table 6. Awareness and lifestyle could be better if family support was there whereas negative mental health impact could decrease in presence of family support. The odd ratios were statistically significant for all items of awareness and lifestyle, except time spend for exercise verses share feelings with family members [adjusted odd ratio =1.5 (0.94-2.35)]. It was seen that friends support and support from family members is significantly associated with all the items of awareness and lifestyle. Sharing feelings with others when in blue was statistically associated with attention to mental health and spend time for relaxation with adjusted OR=2.9. Care for family members feeling was highly significant with adjusted ratio =2.9 (1.74-4.94). Similarly, items indicator of family support was statistically associated with items of negative mental health impact except increase in stress from home and increase in stress from work. It was observed that getting friends and family support was significantly required while horrified due to COVID-19 with adjusted odd ratio =2.8 (1.77-4.3) and adjusted OR=2.7(1.75-4.23). Share feeling with family members and others were significantly associated while helpless due to COVID-19 and apprehensive due to COVID-19. Care for family member’s feelings was significantly associated when apprehensive due to COVID-19 adjusted OR =2.5 (1.59-3.84).

^* p<0.05; ** p<0.001. ^a Odds ratio, adjusted for age, gender, education, occupation and Pre-existing illness (logistic regression analysis). ^b 95% confidence interval (in brackets).

DISCUSSION

The COVID-19 pandemic has wiped out human civilization worldwide since 2020. Because the virus genetic makeup is constantly changing, the pandemic is recurring in waves. In this study we investigated the impact on mental health, lifestyle choices related to it, and quality of life, family and social support as well as the variables linked to the impact of the COVID-19 during the third wave of the COVID-19 pandemic.

The overall CAS score in participants indicated anxiety in 7.2 % only. One possible reason for this finding is that the most of study population consists of the patients attending the OPD and the institute is conducting regular awareness and sensitization program on covid appropriate behaviour under Jan Andolan campaign and conducted regular counselling sessions at OPD as well.

In this study CAS is found to be higher in female (79.3%) than in male. CAS is significantly higher in housewife and not working employment group (i.e. 69%). Previous studies have implicated that being female increases the risk for developing anxiety and depression during an outbreak.⁷ The strongest predictor for anxiety and depression is the female gender.^8-12

Out of 227 females 23 have anxiety i.e. 10.1%. Among the females who have anxiety only 8.6% were involved in increased physical activity and the females who do not have anxiety have 14.7% physically active females. It is in correlation with one study which identified that women who were engaged in less physical activity due to COVID-19 reported significantly lower mental health scores, lower social, emotional and psychological well-being, and significantly higher generalized anxiety, while women who engaged in more physical activity had improved mental health scores.¹³

Our findings suggest that no elder above the age of 60 years have the anxiety related to COVID-19 outbreak. It was consistent with one study where the physical, psychological, and spiritual well-being of the elderly had not been seriously impaired by the events related to the pandemic, although most of the participants reported a worsening of their social life and a moderate/high fear of COVID-19.¹⁴

There was no significant relation between age group and lifestyle choices, negative health impact and social and family support in our study. There was significant relation of gender, education and occupation with lifestyle choices.

About 18-20% respondents paid more attention to their mental health, and took more time to rest, for relaxation or doing exercise. During the survey, more than half of the participants (57.3%) reported no increased stress from work. Additionally, 54% of participants reported that they did not experience increased stress from home. So, these were the positive impacts, however 53 % mentioned that they experience increased financial stress arising from the pandemic. The association between income and mental health has been well documented.^15,16 Our study also found that income affected by the pandemic is a predictor for anxiety. On the other hand, 51% of participants reported that they felt horrified and apprehensive due to the COVID-19 pandemic. However, the majority of participants (56%) did not feel helpless due to the pandemic. There was significant relation of gender, education and occupation with negative health impact and social and family support.

This situation has brought some positive impacts on social and family support. Despite the fact that more than half of the respondents in several situations reported no changes, positive change percentages were substantially higher than negative change percentages. Over 41% of the respondents stated that they cared more about the family members’ feelings. About 18-30% stated that they found increased support from friends and family members. They also experienced an increased shared feelings with family members (27.1%), increased shared feelings with others when feeling blue (25.4%). Awareness and lifestyle could be better if family support is there whereas negative mental health impact could decrease in presence of family support.

The gradual changes in the affected person’s mental health outcomes may not be revealed by this cross-sectional study. Cross-sectional analysis can only identify associations, not causes and effects. We did not evaluate the psychological health of our individuals prior to the pandemic, so we were unable to rule out any pre-existing anxiety or depression in them. Furthermore, comparisons cannot be performed because we did not also collect data from other pandemic stages. The study’s result and application are all constrained by these considerations.

CONCLUSION

Only a small percentage of research participant i.e. 7.2 % experienced anxiety, of whom 79.3% were female. 53% of respondents reported that the pandemic had exacerbated their financial burden. The pandemic had some beneficial effects on social/family support, mental health awareness, and lifestyle adjustments. These good outcomes were linked to other significant negative impacts and may serve as important buffers against the negative impact. According to research, public health activities should concentrate on women and those whose financial situations deteriorate as a result of the pandemic. Interventions that encourage psychological adaptability may lessen the pandemic’s effects. The development of suitable methods and policies to support women in any crisis, such as the covid pandemic, requires the collaboration of policymakers, healthcare providers, and social support organisations. The foundation of public health is mental health. Important elements of mental health include caring for feelings and maintaining healthy family relationships. This justifies raising awareness of the need for mental health care at all levels and developing suitable interventions, particularly for the vulnerable population. The significant lessons learnt so far can be used to improve public health intervention and prevention methods as well as personal mental health recommendations.

Funding: No funding sources

Conflict of interest: None declared

Ethical approval: The study was approved by the Institutional Ethics Committee

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