| Literature DB >> 32975179 |
Oluwaseyitan A Adesegun1, Tolulope Binuyo2, Oluwafunmilola Adeyemi3, Osaze Ehioghae4,1,5, David F Rabor1, Oyebola Amusan4,1, Olutosin Akinboboye1, Omiete F Duke6, Ayobami G Olafimihan7, Oluwafemi Ajose8, Akolade O Idowu4,1, Olumide Abiodun5,1.
Abstract
Within a short period of time, COVID-19 has spread globally, wreaking havoc in various facets of life. This study sought to measure the level of COVID-19 knowledge, attitudes, and practices of the Nigerian public. This was a cross-sectional online survey of the general population of educated Nigerians who had Internet access. Sociodemographic data and participants' knowledge, attitudes, and practices relating to COVID-19 were collected. Scores assessing knowledge, attitudes, and practices were allocated and graded based on specific stratified demarcations. Student's t-test, analysis of variance, and logistic regression analysis were used where appropriate. Of the total 1,015 respondents, most of them exhibited good knowledge of COVID-19, with a mean knowledge grade of 78%; this significantly affected their attitude and practice grades (66% and 60.4%, respectively). Most respondents expressed positive attitudes toward foreigners and other stigma-prone groups, while also practicing appropriate preventive measures. Those aged 21-30 years and those with medical-related occupations had significantly higher knowledge scores (P < 0.001); and having a medical-related occupation increased the likelihood of having good knowledge compared with being unemployed (odds ratio [95% CI]: 6.6 [2.5-17.3]). Male participants aged 21-30 years and those with medical-related occupations had significantly higher attitude scores (P < 0.05). Engaging literate Nigerians on various media platforms, particularly social media, will result in wider reach for the purpose of COVID-19 education. Further studies on other sociodemographic groups within the country (e.g., the less educated) would give a clearer picture of the Nigerian situation as regards COVID-19 knowledge, attitudes, and practices (coronavirus, COVID-19, Public health, Nigeria, Africa).Entities:
Mesh:
Year: 2020 PMID: 32975179 PMCID: PMC7646756 DOI: 10.4269/ajtmh.20-0461
Source DB: PubMed Journal: Am J Trop Med Hyg ISSN: 0002-9637 Impact factor: 2.345
Sociodemographics of respondents
| Categories | Percentage | ||
|---|---|---|---|
| Age-group at last birthday (years) | 10–20 | 147 | 14.5 |
| 21–30 | 700 | 69.0 | |
| 31–40 | 95 | 9.4 | |
| 41–50 | 44 | 4.3 | |
| 51–60 | 26 | 2.6 | |
| 61–70 | 3 | 0.3 | |
| Gender | Female | 549 | 54.1 |
| Male | 466 | 45.9 | |
| Religion | Christianity | 909 | 89.6 |
| Islam | 96 | 9.5 | |
| Traditional | 4 | 0.4 | |
| Areligious | 3 | 0.3 | |
| Atheism | 1 | 0.1 | |
| Agnostic | 1 | 0.1 | |
| Humanism | 1 | 0.1 | |
| Marital status | Single | 827 | 81.5 |
| Married | 181 | 17.8 | |
| Separated | 4 | 0.4 | |
| Widowed | 2 | 0.2 | |
| Others | 1 | 0.1 | |
| Occupation | Medical-related | 270 | 26.6 |
| Nonmedical-related | 705 | 69.5 | |
| Unemployed | 31 | 3.1 | |
| Missing | 9 | 0.8 | |
| Level of education | Tertiary | 958 | 94.4 |
| Secondary | 53 | 5.2 | |
| Missing | 4 | 0.4 | |
| State of residence (geopolitical zones) | Southwest | 660 | 65.0 |
| Southeast | 38 | 3.7 | |
| South–south | 93 | 9.2 | |
| North central | 187 | 18.4 | |
| Northwest | 26 | 2.6 | |
| Northeast | 11 | 1.1 | |
| Ethnicity | Yoruba | 633 | 62.4 |
| Igbo | 175 | 17.2 | |
| Hausa | 18 | 1.8 | |
| Others | 189 | 18.6 |
States in the geopolitical zones are as follows: Southwest—Lagos, Ogun, Oyo, Osun, Ondo, and Ekiti; Southeast—Abia, Anambra, Ebonyi, Enugu, and Imo; South–south—Akwa Ibom, Bayelsa, Cross River, and Delta and Edo rivers; North central—Benue, Kogi, Kwara, Nasarawa, Niger, Plateau, and the Federal Capital Territory; Northwest—Jigawa, Kaduna, Kano, Katsina, Kebbi, Sokoto, and Zamfara; Northeast—Adamawa, Bauchi, Borno, Gombe, Taraba, and Yobe.
Comparing mean COVID-19 knowledge scores between sociodemographic groups of the respondents
| Variable | Categories | Knowledge score (mean ± SD) | ||
|---|---|---|---|---|
| Age-group (years) | 10–20 | 18.66 ± 2.6 | 6.310 | |
| 21–30 | 19.82 ± 2.8 | |||
| 31–40 | 19.07 ± 3.2 | |||
| 41–50 | 18.72 ± 3.0 | |||
| 51–60 | 18.37 ± 2.1 | |||
| 61–70 | 19.33 ± 3.4 | |||
| Gender | Male | 19.39 ± 3.0 | −1.121 | 0.263 |
| Female | 19.59 ± 2.8 | |||
| State of residence (geopolitical zones) | Southwest | 19.54 ± 2.9 | 0.724 | 0.606 |
| Southeast | 18.75 ± 2.8 | |||
| South–south | 19.51 ± 2.7 | |||
| North central | 19.43 ± 2.7 | |||
| Northwest | 19.49 ± 2.9 | |||
| Northeast | 20.25 ± 3.7 | |||
| Marital status | Single | 19.62 ± 2.8 | 2.243 | 0.063 |
| Married | 18.96 ± 3.0 | |||
| Separated | 18.80 ± 1.2 | |||
| Widowed | 18.70 ± 3.0 | |||
| Others | 17.40 | |||
| Occupation | Medical-related | 21.30 ± 2.2 | 83.976 | |
| Nonmedical-related | 18.87 ± 2.8 | |||
| Unemployed | 18.42 ± 2.8 | |||
| Level of education | Secondary | 19.83 ± 3.1 | −0.836 | 0.404 |
| Tertiary | 19.49 ± 2.9 | |||
| Source of information | Traditional media only | 19.71 ± 2.7 | 1.065 | 0.345 |
| Internet media only | 19.62 ± 2.6 | |||
| Both | 19.37 ± 3.0 |
N = 1,015; level of significance < 0.05. The bold values are the P-values that are statistically significant (at P < 0.05).
Occupation, N = 1,006.
Level of education, N = 1,011.
Comparing mean COVID-19 knowledge scores between attitude and practice grades of the respondents
| Variable | Categories | Frequency (%) | Knowledge score (mean ± SD) | Student | |
|---|---|---|---|---|---|
| Attitude grade | Poor | 93 (9.2) | 17.72 ± 3.6 | −6.362 | |
| Good | 922 (90.8) | 19.68 ± 2.7 | |||
| Practice grade | Poor | 248 (24.4) | 19.13 ± 2.9 | −2.342 | |
| Good | 767 (75.6) | 19.62 ± 2.9 |
N = 1,015; level of significance < 0.05. The bold values are the P-values that are statistically significant (at P < 0.05).
Logistic regression to determine predictors of good knowledge of COVID-19
| Variable | Odds ratio (95% CI) | |
|---|---|---|
| Age* | 0.99 (0.97–1.01) | 0.630 |
| Gender | ||
| Male | 1.1 (0.8–1.5) | 0.679 |
| Female | – | – |
| Level of education | ||
| Tertiary | 0.8 (0.4–1.6) | 0.570 |
| Secondary | – | – |
| Occupation | ||
| Medical-related | 6.6 (2.5–17.3) | |
| Nonmedical-related | 1.0 (0.5–2.4) | 0.938 |
| Unemployed | – | – |
| Source of information | ||
| Traditional media | 1.6 (0.8–3.5) | 0.204 |
| Internet media | 1.2 (0.9–1.7) | 0.193 |
| Both | – | – |
The logistic regression model predicts the likelihood that any of the categories of the independent (predictor) variables would have a higher order of COVID-19 knowledge, graded as poor, intermediate, and good knowledge. Level of significance (P-value) set at < 0.05. The bold values are the P-values that are statistically significant (at P < 0.05).
* Age is a continuous variable.
Reference group within variable.
Comparing mean COVID-19 attitude scores between sociodemographic groups of the respondents
| Variable | Categories | Attitude score (mean ± SD) | ||
|---|---|---|---|---|
| Age-group (years) | 10–20 | 7.52 ± 1.9 | 2.597 | |
| 21–30 | 7.98 ± 1.7 | |||
| 31–40 | 8.05 ± 1.7 | |||
| 41–50 | 7.93 ± 1.9 | |||
| 51–60 | 8.35 ± 1.9 | |||
| 61–70 | 6.33 ± 1.5 | |||
| Gender | Male | 8.13 ± 1.8 | 3.522 | |
| Female | 7.74 ± 1.7 | |||
| State of residence (geopolitical zones) | Southwest | 7.90 ± 1.7 | 0.448 | 0.815 |
| Southeast | 7.63 ± 1.7 | |||
| South–south | 8.10 ± 1.8 | |||
| North central | 7.97 ± 1.8 | |||
| Northwest | 7.96 ± 1.3 | |||
| Northeast | 7.82 ± 2.2 | |||
| Marital status | Single | 7.92 ± 1.8 | 0.635 | 0.638 |
| Married | 7.98 ± 1.7 | |||
| Separated | 6.75 ± 2.9 | |||
| Widowed | 7.00 ± 1.4 | |||
| Others | 8.00 | |||
| Occupation | Medical-related | 8.30 ± 1.5 | 8.846 | |
| Nonmedical-related | 7.78 ± 1.8 | |||
| Unemployed | 7.97 ± 1.8 | |||
| Level of education | Secondary | 7.66 ± 1.7 | 1.150 | 0.250 |
| Tertiary | 7.94 ± 1.7 | |||
| Source of information | Traditional media only | 7.91 ± 1.6 | 0.074 | 0.928 |
| Internet media only | 7.95 ± 1.7 | |||
| Both | 7.90 ± 1.8 |
N = 1,015; level of significance < 0.05. The bold values are the P-values that are statistically significant (at P < 0.05).
Occupation, N = 1,006.
Level of education, N = 1,011.