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Factors Associated with Utilization of COVID-19 Preventive Measures by Patients Attending Private Healthcare Facilities in Southwest Nigeria

Factors Associated with Utilization of COVID-19 Preventive Measures by Patients Attending Private Healthcare Facilities in Southwest Nigeria

Okunbor, H. N.*1, Dairo M.D.3, Oluwole, T. O.1,2, Okunbor, L. O.4, and Akinsolu F.5

1Department of Medical Microbiology, Babcock University Teaching Hospital, Nigeria

21Department of Medical Microbiology, School of Basic Clinical Sciences, Babcock University, Nigeria

3Department of Epidemiology and Medical Statistics, Faculty of Public Health, University of Ibadan., Nigeria

4Department of Family Medicine, Babcock University Teaching Hospital, Nigeria

5Department of Public Health, Lead City University, Ibadan., Nigeria

*Corresponding Author


Received: 01 February 2024; Revised: 16 February 2024; Accepted: 21 February 2024; Published: 28 March 2024



Understanding disease risk is important for prevention. Identifying high-risk COVID-19 patients helps healthcare professionals implement precautions. This study examined factors related to COVID-19 prevention in patients at private healthcare facilities in Southwest Nigeria, during the early stages of the pandemic.


A descriptive cross-sectional survey was conducted in two hospitals using multi-stage sampling. 400 respondents were selected two out of 78 private healthcare facilities in in Southwest Nigeria. Trained interviewers administered a questionnaire to collect information on risk profile, symptoms, perception of COVID-19 risk, and preventive practices. Data was analyzed using descriptive statistics, chi-square test, and binary logistic regression at a significance level of 0.05.


The average age of participants was 27.83 + 10.46 years. 52.8% of respondents were female. 70.5% were single, 75.8% belonged to the Yoruba ethnic group, and 72% identified as Christians. None had a history of international travel or contact with a confirmed COVID-19 case in the past 14 days, but 12.75% had been in contact with suspected cases. 47% reported having a fever. The majority had a low risk score for COVID-19. Most did not smoke (98.5%), consume alcohol (83.75%), or visit club houses (85.75%). Only 9.5% underwent COVID-19 testing, and 16.0% of those tested were positive. The main reason for test refusal was a lack of perception of susceptibility to COVID-19. Adherence to preventive practices was poor in all investigated circumstances.

Conclusion: Patients presenting in hospitals during the early phase of the COVID-19 pandemic had a low risk of COVID-19. However, their poor compliance with preventive protocols and low testing uptake make them a potential source of transmission. Strategies to promote adoption of preventive measures are needed, especially among patients at private healthcare facilities.

Keywords: utilization, COVID-19 preventive measures, private healthcare facilities.


The coronavirus disease 2019 (COVID-19) pandemic, caused by a new strain of coronavirus, is a highly contagious respiratory illnesss (WHO, 2020a). It spreads through respiratory droplets and can cause mild to severe symptoms such as fever, cough, and fatigue. The incubation period is around 5 to 14 days. The first case was reported in Wuhan, China on December 31, 2019, and Nigeria confirmed its first case in Lagos on February 27, 2020 (CDC, 2020; WHO, 2020b).

Understanding the burden and distribution of risk factors is crucial in decision-making for implementing preventive measures (Ye et al., 2021; Alkhaldi et al., 2021; Sánchez-Arenas et al., 2021; Feyisa, 2021). An individual’s perception of their risk to COVID-19 is influenced by personal and social factors. Having an accurate perception of one’s risk is vital in motivating individuals to take necessary protective actions. Adherence to preventive measures can effectively prevent and control the spread of the disease. Limited awareness of COVID-19 symptoms and risk factors may hinder willingness to adopt preventive measures. Identifying common risk factors can enhance preventive efforts (Otu et al., 2018). Early identification of a patient’s risk category can contribute to curtailing the spread of the disease (Y. H. Jin et al., 2020). The objective of this study was to determine the risk category of patients seeking care during the pandemic and identify factors associated with the adoption of COVID-19 preventive practices among patients attending a private healthcare facility in Oluyole Local Government, Ibadan.


This was a descriptive cross-sectional study involving 400 outpatients visiting private healthcare facilities in Oyo State. This study aimed at investigating factors related to the utilization of COVID-19 preventive measures in two private healthcare facilities in Southwest, Nigeria.

A multi-stage sampling technique was used to select participants for this study (in the first stage a simple random sampling method was used to select the Local Government Area (LGA), thereafter a simple random sampling without replacement was used to select two hospitals among the 78 healthcare facilities within the LGA, systematic random sampling was utilized in the third stage to recruit participants into the study.

Data was collected through using an interviewer-administered questionnaire, focusing on socio-demographic characteristics and prevention practices such as physical distancing, hand washing, use of hand sanitizers, use of facemask. Participants had to be willing, able to understand information, and adults aged 18-60 who had visited two hospitals. Exclusions included those taking antipyretics, severely ill individuals, and those who did not provide informed consent.

The questionnaire was administered to respondents who met the inclusion criteria until the desired sample size was reached. Ethical approval was obtained from the Oyo State Ministry of Health participants concern was obtained and their confidentiality was ensured (by de-identifying the questionnaire). The questionnaires were counted, screened, coded, and entered into SPSS version 23. Binary logistic regression was used to identify predictors for utilization of pratices for COVID-19. A p-value of less than 0.05 was considered statistically significant.


The average age is 27.83 + 10.46 years. 57.8% of the population is below 20 years old, while 17.0% falls within the 20-29 age range. 52.8% are female. 70.5% of the population is unmarried. 303 individuals identify as Yoruba, 8.5% as Igbo, and 4.3% as Hausa. 72.0% of the population is Christian. 56.8% are students. 58.1% have completed secondary education, while 42.3% have completed tertiary education. 17% of the population reports medical conditions, with hypertension being the most prevalent at 38.8%, followed by respiratory disease at 19%, diabetes mellitus at 3.5%, and hemoglobinopathy at 2.25% (Table 1).

Adherence to preventive practices during individual conversations

Table 2 reveals that the respondents displayed a lack of adherence to preventive practices. In individual conversations, only 21.5% of individuals wore facemasks, while a staggering 97.7% did not maintain physical distance. Similarly, during social gatherings, 96.0% did not utilize hand sanitizer, 96.3% failed to maintain physical distance, 97.5% neglected to wash their hands, and 88.3% were not subjected to temperature checks. During religious gatherings, 95.3% did not use hand sanitizer, 92.7% did not wash their hands, 85% were not temperature checked, and only 19.3% practiced physical distancing. However, according to Table 3, there was no significant correlation between adherence to preventive measures and demographic information. Interestingly, females, older individuals, those with no formal education, and lecturers were more inclined to adopt preventive practices. Nevertheless, no demographic factors had a significant impact on the implementation of preventive measures. This finding contradicts the results of an online survey conducted among 368 dental healthcare workers in Jordan, where almost all participants (88.3%) consistently wore facemasks during conversations (Khader et al., 2020). Furthermore, this finding also differs from another online cross-sectional descriptive study conducted among 136 Ugandan healthcare workers in four teaching hospitals, which found that 54% of healthcare workers regularly wore facemasks during conversations (Olum et al., 2020). These findings are in contrast to the studies conducted by Sánchez-Arenas et al. (2021) and Ye et al. (2021), both of which found that factors such as being female (OR: 1.08; CI: 1.04, 1.13), older age (OR: 1.002; CI: 1.0008, 1.003), and higher literacy (OR: 1.003; CI: 1.001, 1.004) were associated with the utilization of preventive methods.

Adherence to preventive practices during outdoor gathering

Results from Tables 4 and 5 revealed that precautionary measures were implemented at outdoor gathering venues, with gender and employment status playing significant roles in adherence. Females demonstrated higher adherence compared to males, while unemployed individuals exhibited greater adherence compared to those employed in other occupations. Specifically, males had a 61% decrease in the odds of adhering to preventive measures, whereas the unemployed were 8 times more likely to adhere. Therefore, when promoting adherence, it is crucial to consider gender and employment factors. In Table 5, respondents displayed adherence to preventive measures during a recent religious gathering. Occupation was the only significant factor, with lecturers being 3 times more likely to adhere compared to students (OR 2.775; CI: 1.006 – 7.655). Although unemployment was associated with higher adherence, it did not reach statistical significance. Notably, a survey conducted in Jordan among 368 dentists found that the majority believed in the importance of instructing patients on physical distancing and consistently practiced hand hygiene (Khader et al., 2020). Similarly, a survey in China involving 4704 participants revealed that males were less inclined to adopt outdoor preventive measures, while individuals with lower incomes were more willing to adopt such measures (Ye et al., 2021). In Mexico, a survey of 1030 adults indicated that being female was associated with engaging in preventive health behavior (Sánchez-Arenas et al., 2021). Lastly, a study conducted in Ethiopia with 384 youths found that male youths were less likely to practice preventive measures (Feyisa, 2021).


One key strength of this study lies in validity and reliability of perception constructs that has been derived with a robust statistical method. A limiting factor of this study is the likely recall bias among participants, which may be based on their willingness to voluntarily and correctly start COVID-19 result outcome, but this may not necessarily imply they were intentionally done.


Understanding factors that drive utilization of preventive practices should guide policy and risk communication strategies to achieve more positive uptake behaviour. Our study found that occupation with gender were positively associated with high utilization of COVID-19 preventive practices. While intent towards compliance with preventive measures tend to vary over time, due to increased awareness, this utilization will likely change throughout the different phase of the COVID-19 pandemic.


All data relevant to the study are included in the article or uploaded as supplementary information.


All authors were involved during: Concept and design, acquisition, analysis or interpretation of data, drafting and critical revision of the manuscript.


The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Table 1: Socio-demographics characteristics of the study population

CHARACTERISTICS   Frequency (n= 400) Percentage (%)
AGE   < 20year 20-29 year 30 – 39year 40-49 year 50 – 59year ≥60 years 231 68 57 26 18 0 57.8 17.0 14.3 6.5 4.5 0
GENDER Male Female 189 211 47.3 52.8
ETHNICITY Yoruba Hausa Ibo Others 303 17 34 46 75.8 4.3 8.5 11.5
RELIGION   Christianity Islam Traditional 288 111 1 72.0 27.8 0.3
MARITAL STATUS   Single Married Separated Widowed 282 116 2 0 70.5 29.0 0.5 0.0
  LEVEL OF EDUCATION No formal Primary Secondary Tertiary 3 1 229 169 0.8 0.3 58.1 42.3
OCCUPATION Student lecturer Civil servant Unemployed Others 227 19 18 6 130 56.8 4.8 4.5 1.5 32.5
MEDICAL CONDITIONS   Hypertension Heart  disease Diabetes mellitus Kidney disease Respiratory disease Hemoglobinopathy 35 0 14 0 19 9 8.75 0 3.5 0 4.75 2.25

TABLE 2: Preventive practice adopted in various situation

Preventive practice during a conversation with a person within the past 24 hour Yes No
Wearing a masks 86(21.5) 314(78.5)
keeping physical distancing of about 6 feet 9(2.3) 391(97.7)
Preventive practice adopted during a visit to a place of social gathering
Use of hand sanitizer at the venue 16(4.0) 384(96.0)
Keep physical distancing 15(3.7) 385(96.3)
Wash hands 10(2.5) 390(97.5)
Temperature check 47(11.7) 353(88.3)
Preventive measure adopted  during recent visit to a place of religious gathering
Use of hand sanitizer at the venue 19(4.7) 381(95.3)
Keep physical distancing 77(19.3) 323(80.7)
Wash hands 29(7.3) 371(92.7)
Temperature check 60(15) 340(85)

Table 3:  output of binary logistic analysis between preventive measures adopted in one on one conversation with a person within the past 24 hours and the demographic information such as gender, religious. Level of education and occupation of the respondents

B Sig. Exp(B) Odd Ratio 95% C.I.for EXP(B)
Lower Upper
  Age 0.005 0.768 1.005 0.970 1.043
Female 1
Male -.329 .190 .720 .440 1.177
Traditional .994 1
Christianity 19.811 1.000 401524237.570 0.000 .
Islam 19.841 1.000 413890628.768 0.000 .
Level of education
Tertiary .657 1
No formal .441 .727 1.554 0.131 18.462
Primary -20.504 1.000 0.000 0.000 .
Secondary -0.348 0.255 0.706 0.388 1.286
Others .872 1
student -0.150 .724 .860 0.373 1.984
lecturer 0.165 .766 1.179 0.398 3.491
civil servant -0.661 .325 0.516 0.138 1.928
unemployed -20.048 .999 0.000 0.000 .
Constant -20.794 1.000 0.000

Table 4:  Output of binary logistic analysis between preventive measures adopted at their recent visit to a place of social gathering and the demographic information such as gender, religious. Level of education and occupation of the respondents

B Sig. Exp(B) Odd Ratio 95% C.I.for EXP(B)
Lower Upper
Age 0.034 0.080 1.035 0.996 1.075
Female 1
Male -0.942 0.001* 0.390 0.225 0.676
Traditional 0.704 1
Christianity 19.380 1.000 260973828.709 0.000 .
Islam 19.138 1.000 204874023.894 0.000 .
Level of education
Tertiary .557 1
No formal -20.097 0.999 0.000 0.000
Primary -20.889 1.000 0.000 0.000 .
Secondary -0.464 0.150 0.629 0.334 1.182
Others 0.119
student .588 0.211 1.800 0.716 4.523
lecturer .899 0.103 2.458 0.834 7.247
civil servant .178 0.767 1.195 0.368 3.887
unemployed 2.016 0.027* 7.508 1.258 44.807
Constant -21.470 1.000 0.000

Table 5:  Output of binary logistic analysis between preventive measures adopted at their recent visit to a place of religious gathering and the demographic information such as gender, religious, Level of education and occupation of the respondents

B Sig. Exp(B) Odd Ratio 95% C.I.for EXP(B)
Lower Upper
Age 0.002 0.883 1.002 0.971 1.035
Female 1
Male -0.079 0.708 0.924 0.611 1.398
Traditional .704 1
Christianity 20.725 1.000 1001650718.504 .000 .
Islam 20.923 1.000 1221278671.369 .000 .
Level of education
Tertiary .563 1
No formal 1.483 .236 4.405 0.378 51.272
Primary -20.550 1.000 .000 .000 .
Secondary 0.261 0.323 1.298 0.774 2.177
Others 0.151
student -0.033 0.930 0.968 .467 2.004
lecturer 1.021 2.775 1.006 7.655
civil servant 0.592 0.248 1.808 0.661 4.944
unemployed 1.342 0.138 3.826 0.651 22.497
Constant -21.501 1.000 .000


  1. Africa, T. C. (2018) Why some people don’t want to take a COVID-19 test. Available at:  (Accessed: 15 March 2021).
  2. AfricaSource (2020) Barriers to mass testing for COVID-19 in Africa. Available at: (Accessed: 3 November 2021).
  3. Alkhaldi, G. et al. (2021) ‘Perceptions towards COVID-19 and adoption of preventive measures among the public in Saudi Arabia: a cross-sectional study’, BMC public health. BMC Public Health, 21(1), p. 1251. doi: 10.1186/s12889-021-11223-8.
  4. Barrett, E. S. et al. (2020) ‘Prevalence of SARS-CoV-2 infection in previously undiagnosed health care workers at the onset of the U.S. COVID-19 epidemic’, medRxiv, p. 2020.04.20.20072470. doi: 10.1101/2020.04.20.20072470.
  5. CDC (2020) FIRST CASE OF CORONA VIRUS DISEASE CONFIRMED IN NIGERIA. Available at: (Accessed: 22 September 2020).
  6. Dan-Nwafor, C. et al. (2020) ‘Nigeria’s public health response to the COVID-19 pandemic: January to May 2020’, Journal of Global Health, 10(2). doi: 10.7189/JOGH.10.020399.
  7. Elimian, K. O. et al. (2020) ‘Descriptive epidemiology of coronavirus disease 2019 in Nigeria, 27 February-6 June, 2020’, Epidemiology and Infection, (September). doi: 10.1017/S095026882000206X.
  8. Federal Ministry of Health (2019) NIGERIA Health Facility Registry (HFR). Available at: (Accessed: 21 March 2021).
  9. Feyisa, Z. T. (2021) ‘Factors limiting youths’ practice of preventive measures toward the outbreak of COVID-19 in Oromia special zone surrounding Finfinnee, Ethiopia’, PLoS ONE, 16(3 March), pp. 1–15. doi: 10.1371/journal.pone.0248495.
  10. Halvatsiotis, P. et al. (2020) ‘Demographic and clinical features of critically ill patients with COVID-19 in Greece: The burden of diabetes and obesity’, Diabetes Research and Clinical Practice. Elsevier B.V., 166, p. 108331. doi: 10.1016/j.diabres.2020.108331.
  11. Ibadan Development Association (2020) Local Government. Available at: (Accessed: 21 March 2021).
  12. Jin, J. M. et al. (2020) ‘Gender Differences in Patients With COVID-19: Focus on Severity and Mortality’, Frontiers in Public Health, 8. doi: 10.3389/fpubh.2020.00152.
  13. Jin, Y. H. et al. (2020) ‘Perceived infection transmission routes, infection control practices, psychosocial changes, and management of COVID-19 infected healthcare workers in a tertiary acute care hospital in Wuhan: A cross-sectional survey’, Military Medical Research. Military Medical Research, 7(1), pp. 1–13. doi: 10.1186/s40779-020-00254-8.
  14. Khader, Y. et al. (2020) ‘Dentists’ Awareness, Perception, and Attitude Regarding COVID-19 and Infection Control: Cross-Sectional Study Among Jordanian Dentists’, JMIR Public Health and Surveillance, 6(2), p. e18798. doi: 10.2196/18798.
  15. Kim, L. et al. (2020) ‘Hospitalization Rates and Characteristics of Children Aged < 18 Years Hospitalized with Laboratory-Confirmed COVID-19’, Morbidity and Mortality Weekly Report, 69(32), pp. 1081–1088.
  16. Klein, S. L. and Morgan, R. (2020) ‘The impact of sex and gender on immunotherapy outcomes’, Biology of Sex Differences. Biology of Sex Differences, 11(1), pp. 1–13. doi: 10.1186/s13293-020-00301-y.
  17. Olum, R. et al. (2020) ‘Coronavirus Disease-2019: Knowledge, Attitude, and Practices of Health Care Workers at Makerere University Teaching Hospitals, Uganda’, Frontiers in Public Health, 8(April), pp. 1–9. doi: 10.3389/fpubh.2020.00181.
  18. Osibogun, A. et al. (2021) ‘Outcomes of COVID-19 patients with comorbidities in southwest Nigeria’, PLoS ONE, 16(3 March), pp. 1–12. doi: 10.1371/journal.pone.0248281.
  19. Otu, A. et al. (2018) ‘An account of the Ebola virus disease outbreak in Nigeria : implications and lessons learnt’. BMC Public Health, pp. 1–8. doi: 10.1186/s12889-017-4535-x.
  20. Oyo State EOC (no date) COVID-19 Risk scoring guige.
  21. Perrotta, F. et al. (2020) ‘COVID-19 and the elderly: insights into pathogenesis and clinical decision-making’, Aging Clinical and Experimental Research. Springer International Publishing, 32(8), pp. 1599–1608. doi: 10.1007/s40520-020-01631-y.
  22. Sánchez-Arenas, R. et al. (2021) ‘Factors associated with COVID-19 preventive health behaviors among the general public in Mexico City and the State of Mexico’, PLoS ONE, 16(7 July), pp. 1–18. doi: 10.1371/journal.pone.0254435.
  23. The Jakarta post (2020) Stigma, precarity deter Indonesians from getting tested for COVID-19. Available at:  (Accessed: 15 March 2021).
  24. Turcotte, J. J. et al. (2020) ‘Risk factors for severe illness in hospitalized Covid-19 patients at a regional hospital’, PloS one, 15(8), p. e0237558. doi: 10.1371/journal.pone.0237558.
  25. WHO (2020a) Coronavirus. Available at: (Accessed: 22 September 2020).
  26. WHO (2020b) Coronavirus disease 2019 (COVID-19) Situation Report – 94.
  27. Ye, Y. et al. (2021) ‘Preventive behaviours and family inequalities during the COVID-19 pandemic : a cross-sectional study in China’, Infectious Diseases of Poverty. BioMed Central, pp. 1–14. doi: 10.1186/s40249-021-00884-7.
  28. Zealand, R. N. (2020) Doctors frustrated by patients refusing Covid-19 tests. Available at:   (Accessed: 15 March 2021).

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