Assessing the Psychological Impact of the Pandemic COVID -19 in Uninfected High-Risk Population.

PURPOSE: To assess the impact of the COVID-19 pandemic on the psyche of uninfected people with chronic diseases in the Elduim community, White Nile State, Sudan, during the COVID -19 pandemic.
METHODS: We used a generalized anxiety disorder scale (GAD -7) and a patient health questionnaire (PHQ-9) for psychological assessment. The study included two hundred thirty-four participants; all participants with a chronic disease but not infected with COVID -19 were between 24 and 65 years of age. Residents of the study area were randomly selected. Descriptive statistics and a t-test were used for associations with a p-value of 0.05 or less.
RESULTS: This study found that anxiety rated by GAD 7 was either mild (18, 7.7%), moderate (98, 41.9%), or severe (41, 17.5%) among participants. PHQ 9-rated depression showed 22 (9.4%) mild depression, most of them in participants aged 36-44 years. Participants with kidney disease showed major depression 11 (42.31%). Factors that significantly affected anxiety scores were age 24-35 years (P =0.002), university graduates (P < 0.000), married (P < 0.000), those with diabetes and hypertension (P =0.041), and urban residents (P < 0.023). Those who had secondary education were married and smoked were significantly more likely to have major depression than those with another educational status (p < 0.05).
CONCLUSION: COVID 19 pandemic had a significant impact on the psyche of uninfected people with chronic diseases in Sudan, and significant associated factors were identified. Unique interventions are strongly recommended to reduce the psychological impact of the COVID 19 pandemic.

Introduction

In late 2019, the novel coronavirus, abbreviated COVID19, in Wuhan, China, became a global pandemic,1 which is of great concern1–3 and has a significant impact on the psychological state of individuals.4,5 Anxiety and depression associated with the pandemic have been reported,6 with many clinical features. Specific and nonspecific clinical features related to COVID-19 include clinical characteristics of mental disorders.7–10 The co-occurrence of mental problems negatively affects the prognosis of treatment of respiratory symptoms of the disease.11 Few sporadic case reports in the literature12 showed that severe disease with long-lasting symptoms was more susceptible.13 Fear of becoming infected increased as the pandemic progressed, especially after the declaration of WHO and the change in physical distance. Several factors added additional stress, including living away from Family for many reasons, the elderly, and social media contributed even more to the current situation.14,15

The ongoing pandemic has affected the efficiency of health care systems worldwide. In Africa, the situation is weaker because the health sector in most African countries is vulnerable, which will overwhelm health systems. In particular, the vulnerable population with chronic diseases needs regular health care.16 The associated social stigma poses an additional challenge for control and prevention COVID -19. Sudan has a high mortality rate due to limited testing and health services. Patients with chronic diseases are at higher risk. The health system needs urgent support to improve health care and reporting and monitoring services.17

Chronic diseases such as diabetes mellitus, hypertension, renal disease, respiratory disease, and gastrointestinal disease pose a high risk for infection, morbidity, and mortality, in addition to preexisting comorbidities.18 In addition to physical health, COVID -19 also affects mental health and increases stress for patients with chronic diseases. The rapid outbreak of the COVID -19 pandemic resulted in severe illness and even death.19

The regularly reported deaths and high cases are staggering and full of stress, especially in those with known risk factors and long-term medications. This study assessed the impact of the COVID -19 pandemic on the psyche of uninfected people with chronic diseases in Elduim locality, White Nile State, Sudan, during the COVID -19 pandemic.

Method

Study Setting

This is a descriptive cross-sectional study was conducted in primary health care (PHC) centers. PHC is the first point of contact for patient care. During the current COVID-19 pandemic, PHCs have been busy. Patients with chronic diseases are followed up regularly at PHCs and referred to tertiary facilities only if they develop complications. Health care in Sudan is mainly provided by primary health centers, rural Hospitals, and tertiary hospitals.

Participants

A total of 234 participants were enrolled in this study. All participants who had chronic disease but were not infected with COVID-19 were between 24 and over 65 years of age. Residents of the study area were randomly selected.

Study Population

The study population was uninfected Sudanese with chronic diseases who came to a PHC for routine care. Those who had COVID -19 infections were excluded from the study. They were included in the study population after giving their informed consent. We started data collection after received the opinion of the bioethics committee.

Data Collection

Relevant data were collected using a self-completion questionnaire that was validated by a panel of experts. Determine differences in anxiety and depression scores during the pandemic COVID -19 associated with some demographic variables such as sex, age, academic status, marital status, family size, smoking, type of chronic illness, occupation, and residence. A generalized anxiety disorder scale (GAD -7) and the Patient Health Questionnaire-9 (PHQ-9) scale were used as survey methods. Sources of information about the disease among the subjects also included radio and television, social media, and medical personnel.

Anxiety Measurement

From validation previously,20 we used the psychological evaluation, we used a scale of generalized anxiety disorders (GAD-7), and a patient health questionnaire (PHQ-9). Present of anxiety in the past two weeks and scored accordingly: (0–21) categorized impaired, were (0–4) minimum, (5–9) mild, (10–14) moderate, and (15–21) severe anxiety.21,22 Although there are several instruments for assessing or screening anxiety disorders, one of the most common anxiety disorders encountered in general medical practice and in general is generalized anxiety disorder (GAD). The GAD -7 scale was used. The GAD -7 is a valuable and effective tool for screening GAD and assessing severity in clinical practice and research.

Measures of Depression Symptoms

It was measured by a patient health questionnaire (PHQ-9). PHQ-9 was used as a screening and monitoring tool for severity determination and scaling.23,24 Ten questions evaluated depression; the answers were never, some days, most time, and always. Categorization was based on the two questions related to interest on activities and feelings (sad, hopeless or depressed).

Statistical Analysis

Data are analyzed using Statistical Package for Social Sciences software after being grouped and tabulated. Descriptive statistics and a t-test were used for associations. The data are expressed as mean ± standard deviation. They are interpreted in the form of a statement, table, and figure - with a p-value of 0.05 or less.

Results

Two hundred and thirty four (234) participants were included in this study. More than half were female, 120 (51.28%), and about 127 (54.2%) participants were above 45 years. 164 (70.05%) were attended secondary education and above. About 135 (57.69%) were married, family size between (4–6) was a high percentage (41.45), most of the participants were not smoking (64.0%). Diabetes and hypertension are more distributed diseases among the study sample (38.46%) and (36.75%) respectively, few were employed, 33 (14.1%), social media was the mean source for collecting information about COVID-19 (38.03), and urban was a great place for residence for the participants (89.74%) (Table 1).

Table 1

Demographic Characteristics of the Participants (n = 234)

Variable	Category	Frequency	Percentage (%)
Gender	Male	114	(49)
	Female	120	(51)
Age	24–35	32	(13.7)
	36–44	75	(32.1)
	45–64	101	(43.10)
	Over 65	26	(11.10)
Educational status	Illiterate	15	(6.41)
	Literate	21	(8.97)
	Primary school	34	(14.53)
	Secondary	75	(32.05)
	University	89	(38.00)
Marital status	Single	59	(25.21)
	Married	135	(57.69)
	Widows	25	(10.68)
	Divorced	15	(6.41)
Family size	1–3	85	(36.32)
	4–6	97	(41.45)
	Over 6	52	(22.22)
Smoking	Yes	84	(36.0)
	No	150	(64.0)
Chronic disease	Asthma	07	(2.99)
	Cancer	11	(4.70)
	Heart disease	13	(5.56)
	Diabetes	90	(38.46)
	Kidney disease	26	(11.11)
	Hypertension	86	(36.75)
	Liver disease	01	(0.43)
Employment status	Employ	201	(85.90)
	Non-Employ	33	(14.10)
Source information about COVID-19	T.V and radio	117	(50.0)
	Social media	89	(38.03)
	Health workers	28	(11.97)
Residence	Urban	210	(89.74)
	Rural	24	(10.26)

Assessment of anxiety by GAD 7 revealed that it was mild in 18 (7.7%), moderate in 98 (41.9%), and severe in 41 (17.5%). Factors significantly impact the presence of anxiety were age (p=0.00), university graduates had a high score (P < 0.000), married people who have a family member over six had a significantly higher GAD -7 score than other family members (P < 0.000). The participants who smoke are not significantly anxious (P < 0.102). Participants suffering from diabetes and hypertension were significantly more anxious compared to other chronic diseases. Working participants (P = 0.041), participants who used social media as a source of information (P = 0.023), and urban dwellers (P < 0.023) had a significantly higher GAD7 score. Female, 45–64 years old, university graduate, married, with more than six family members, nonsmoker, with chronic diseases, employed, social media user, and urban dweller had a higher risk of developing severe anxiety. (Table 2).

Table 2

The Sociodemographic Distribution of the Participants and Its Association with Anxiety (N = 234)

Variable	Category	Anxiety Level N (%)				P-value
		Minimal	Mild	Moderate	Severe
Gender	Male	5 (4.39)	27 (23.68)	63(55.26)	19 (16.67)	0.025
	Female	13 (10.83)	50 (41.67)	35 (29.17)	22 (18.33)
Age	24–35	4 (12.5)	13 (40.62)	13 (40.62)	2 (6.25)	0.002
	36–44	4 (5.3)	46 (61.33)	22 (29.33)	3 (4.00)
	45–64	4 (3.96)	50 (49.5)	36 (35.64)	11 (10.89)
	Over 65	2 (7.69)	12 (46.15)	7 (26.92)	5(19.23)
Educational status	Illiterate	5 (33.33)	4(26.67)	5 (33.33)	1(6.67)	0.000
	Literate	6 (28.57)	3 (14.29)	11(52.38)	1(4.76)
	Primary school	2 (5.88)	19(55.88)	10(29.41)	3(8.82)
	Secondary	11(14.67)	29 (38.67)	33(44)	5(6.67)
	University	2(2.25)	55(61.80)	21(23.60)	11(12.36)
Marital status	Single	13(22.03)	22(37.29)	22 (37.29)	2(3.39)	0.000
	Married	11(8.15)	69(51.11)	49 (36.30)	6(4.44)
	Widows	4(16.00)	14 (56.0)	2(8.00)	5 (20.00)
	Divorced	7(46. 67)	3(20.0)	1(6.67)	4 (26.67)
Family size	1–3	18(21.18)	32(37.65)	32(37.65)	3 (3.52)	0.001
	4–6	6 (6.19)	50(51.55)	37 (38.14)	4 (4.12)
	Over 6	11 (21.15)	26 (50.0)	5 (9.62)	10 (19.23)
Smoking	Yes	24 (28.57)	31(36.90)	27(32.14)	3(3.57)	0.102
	No	18 (12.0)	76 (50.67)	42 (28.0)	14 (9.33)
Chronic disease	Asthma	3 (42.86)	2 (28.57)	1 (14.29)	1 (14.29)	0.000
	Cancer	1(9.09)	4(36.36)	5 (45.45)	1 (9.09)
	Heart disease	2 (15.38)	3 (23.08)	7 (53.85)	1(7.69)
	Diabetes	24(26.67)	35(38.89)	29 (32.22)	2 (2.22)
	Liver disease	0.0	0.0	0.0	1(100.0)
	Hypertension	4(4.65)	48(55.81)	26 (30.23)	8 (9.30)
	Kidney disease	7 (26.92)	14 (53.85)	1 (3.85)	4(15.38)
Employment status	Employ	31(15.42)	89 (44.28)	66 (32.84)	13(6.47)	0.041
	Non-Employ	11(33.33)	17 (51.51)	1 (3.03)	4(12.12)
Source information about COVID-19	T.V and radio	20 (17.09)	42 (35.90)	45 (38.46)	10 (8.55)	0.023
	Social media	4(4.49)	42 (47.19)	33 (37.08)	10 (11.24)
	Health workers	7 (25.0)	16 (57.14)	1(3.57)	4(14.29)
Residence	Urban	24(11.43)	90 (42.86)	78 (37.14)	20 (9.52)	0.023
	Rural	7 (29.17)	12 (50.0)	1 (4.17)	4 (16.67)

PHQ9 Scale evaluates depression; 105 (92.1%) of males perceived some degree of depression, with moderate and moderate-severe depression being the most common in 37 (32.46%), then mild depression in 26 (22.8%). Although not significantly linked, those who had a severe form of depression were 36–44 yrs (p<0.5). Those with secondary school degrees had significantly higher severe depression than other educational status (p < 0.046). Also, those who were married had significantly higher severe depression (p < 0.012). The participants with diabetes were high mild depression 29 (32.22%). Those who had kidney diseases were severely high depression 11 (42.31%), there was no significant association statistically among smoking and residence with depressive levels (p < 0.046). We can summarize that those who are female, have a high school degree, are married, have a large family, suffer from kidney disease, are employed, and get information from social media have a higher risk of developing severe depression. (Table 3).

Table 3

The Sociodemographic Distribution of the Participants and Its Association with Depression (N = 234)

Variable	Category	Depression Level					P-value
		Minimal	Mild	Moderate	M. Severe	Severe
Gender	Male	9 (7.89)	26 (22.81)	37 (32.46)	37(32.46)	5 (4.39)	0.032
	Female	13 (10.83)	12 (10.0)	20 (16.67)	45 (37.5)	30 (25.0)
Age	24–35	7 (21.89)	4 (12.5)	4(12.5)	13(40.62)	4(12.5)	0.59
	36–44	23 (30.67)	18 (24.0)	11(14.67)	12 (16.0)	11(14.67)
	45–64	31(30.69)	22 (21.78)	25 (24.75)	14(13.86)	9 (8.91)
	Over 65	6 (23.08)	4 (15.38)	3(11.54)	7(26.92)	6(23.08)
Educational status	Illiterate	4 (26.67)	5 (33.33)	3(20.0)	1(6.67)	2(13.33)	0.046
	Literate	3 (14.29)	8(38.1)	4 (19.05)	4(19.05)	2 (9.52)
	Primary school	6 (17.65)	1(2.94)	5(14.71)	4(11.76)	18 (52.94)
	Secondary	18(24.0)	20 (26.67)	11(14.67)	7 (9.33)	19 (25.33)
	University	11(12.36)	6 (6.74)	38 (50.67)	17 (19.10)	17 (19.10)
Marital status	Single	21 (35.60)	9 (15.25)	6 (10.17)	6(10.17)	17 (28.81)	0.012
	Married	6 (4.44)	14 (10.37)	20 (14.81)	45(33.33)	50 (37.04)
	Widows	1(4.0)	2 (8.0)	8 (32.0)	11(44.0)	3 (12.0)
	Divorced	1(6.67)	1 (6.67)	6 (4.0)	4 (26.67)	3 (20.0)
Family size	1–3	21(24.71)	9 (10.59)	8 (9.41)	18 (21.18)	29(34.12)	0.003
	4–6	4 (4.12)	12 (12.37)	14 (14.43)	33 (34.02)	34 (35.05)
	Over 6	6 (11.54)	5 (9.62)	18 (34.62)	15(28.85)	8 (15.38)
Smoking	Yes	33(39.29)	19 (22.62)	13 (15.48)	9 (10.71)	10 (11.90)	0.96
	No	43 (28.67)	35 (23.33)	31 (20.67)	14 (9.33)	17 (11.33)
Chronic disease	Asthma	3 (42.86)	1(14.29)	1(14.29)	1(14.29)	1(14.29)	0.036
	Cancer	5(45.45)	1 (9.09)	1(9.09)	3 (27.27)	1(9.09)
	Heart disease	4 (30.78)	4(30.78)	3(23.08)	1(7.69)	1(7.69)
	Diabetes	30 (33.33)	29 (32.22)	13(14.44)	8 (8.89)	9 (10.0)
	Liver disease	0.0	0.0	0.0	0.0	1 (100.0)
	Hypertension	28(32.56)	23 (26.74)	21(24.42)	10 (11.63)	4 (4.65)
	Kidney disease	4(15.38)	5 (19.23)	3 (11.54)	3(11.54)	11(42.31)
Employment status	Employ	20 (9.95)	54 (26.87)	43 (21.39)	38 (18.91)	46 (22.89)	0.028
	Non-Employ	11(33.33)	4 (12.12)	5 (15.15)	5 (15.15)	8 (24.24)
Information Source about COVID-19	T.V and radio	10 (8.55)	38 (32.49)	27 (23.08)	21 (17.95)	21 (17.95)	0.038
	Social media	6 (6.74)	19 (21.35)	18 (20.22)	21(23.60)	25 (28.09)
	Health workers	11(39.29)	5 (17.86)	4 (14.29)	3 (10.71)	5 (17.86)
Residence	Urban	68 (32.38)	55 (26.19)	40 (19.05)	27 (12.86)	20 (9.52)	0.279
	Rural	4 (16.67)	5(20.83)	3 (12.5)	5 (20.83)	7(29.17)

Discussion

The current study examined the psychological impact (anxiety, depression) on the population suffering from a chronic disease. COVID 19 pandemic has significantly affected the psychological impact of people. A person with chronic illness was mainly concerned with the preventive measures recommended by WHO.25

This study found that the psychological disorders among the participants were anxiety (35%) and depression (29.4%). These results are in agreement with a study conducted in Saudi Arabia where 28%26 were reported during the current COVID 19 pandemic, 32%26 in Spain, and 28% in a systematic review reported 28%.27 Our results were lower than those reported in India for anxiety 43% and depression 39%.28

We found that being female is more likely to develop anxiety and depression during the pandemic COVID 19. The results are consistent with findings from India, Iran, and China.29–32 Women’s increased susceptibility to chronic illness, suffering more than men, is related to emotional symptoms.33

This study found that people who have more family members are more likely to develop anxiety than people with fewer family members, apart from people with chronic illnesses. This could be because many household members contact more people, which increases the stress of becoming infected.34,35 Chronic diseases increase the risk, especially in people with existing mental conditions or risk factors.7 This finding is consistent with studies from China and Ethiopia.29,34

Those who used social media as their main source of information about COVID -19 were at least 28.09% more likely to develop severe anxiety during a stressful situation such as the current COVID -19 pandemic. Some authors35,36 linked the association between social media and the development of major depression to social media use during the COVID -19 pandemic. Psychological distress may increase in workers with chronic diseases and those who work with others.37,38 High work demands, low job control, a strong imbalance between performance and reward, low relational equity, low procedural equity, role stress, bullying, and low social support in the workplace are associated with a higher risk of common mental health problems. Married participants were more likely to develop depression compared to divorced and widowed participants. This is consistent with the findings of a recent study conducted by Ettman et al in the United States.39,40 Further, Krupa et al41 document that the associated anxiety of returning to normal society after a quarantine period led to some psychological problems and difficulties such as hallucinations. This could be explained by the stress associated with social status as a widow or divorcee. During the stressful phase of the pandemic, psychological support was provided by trained nurses and trained volunteers from non-governmental organizations.

Patients presented a fear related to the return to society and normal functioning after quarantine. Additionally, some study participants voiced concerns related to their mental health; some cases of hallucinations were reported.

This study calls urgent attention to reduce the impact of COVID 19 psychological consequences in patients with chronic diseases. Appropriate counseling during medical care of patients with chronic illnesses can reduce the COVID 19 associated psychological consequences. Addressing the related risk factors is the essential measure to improve the psychological status of patients with chronic diseases.

Conclusion

COVID 19 pandemic affected the psychological status significantly on the psyche of uninfected people with chronic diseases in Sudan, and the significant associated factors were identified. Unique interventions are highly recommended for reducing the psychological implication of the COVID 19 pandemic.