| Literature DB >> 32434552 |
Emelda E Chukwu1, David A Oladele2, Oluwatoyin B Awoderu3, Ebelechukwu E Afocha3, Rahman G Lawal3, Ismail Abdus-Salam4, Folasade T Ogunsola5, Rosemary A Audu6.
Abstract
BACKGROUND: One of the objectives of the Global Action Plan by the World Health Organization (WHO) to contain antimicrobial resistance (AMR), is to improve global awareness through effective communication and education. Comprehensive information on the level of awareness of AMR among Nigerian public is deficient. This study was therefore designed to assess the current level of awareness and knowledge of the Nigerian public of AMR.Entities:
Keywords: Antibiotics; Antimicrobial resistance; Awareness; General public; Nigeria
Mesh:
Substances:
Year: 2020 PMID: 32434552 PMCID: PMC7238560 DOI: 10.1186/s13756-020-00739-0
Source DB: PubMed Journal: Antimicrob Resist Infect Control ISSN: 2047-2994 Impact factor: 4.887
Socio-Demographic characteristics of participants
| Variable | Frequency | Percentage (%) |
|---|---|---|
| Gender | ||
| Male | 240 | 49.8 |
| Female | 242 | 50.2 |
| Age | ||
| 18–24 | 91 | 18.9 |
| 25–34 | 116 | 24.1 |
| 35–44 | 63 | 13.1 |
| 45–54 | 33 | 6.8 |
| 55–64 | 16 | 3.3 |
| 65–74 | 5 | 1.03 |
| 75+ | 3 | 0.6 |
| Missing | 155 | 32.2 |
| State | ||
| Borno | 76 | 15.8 |
| Delta | 82 | 17 |
| Ebonyi | 78 | 16.2 |
| Jigawa | 75 | 15.6 |
| Lagos | 94 | 19.5 |
| Plateau | 77 | 16 |
| LGA | ||
| Rural | 208 | 43.2 |
| Urban | 274 | 56.8 |
| Degree | ||
| No schooling | 40 | 8.3 |
| Primary education | 37 | 7.7 |
| Secondary education | 167 | 34.6 |
| Vocational training | 49 | 10.2 |
| Bachelor’s degree | 129 | 26.8 |
| Master’s degree | 30 | 6.2 |
| Doctorate degree | 2 | 0.4 |
| Non-formal education | 28 | 5.8 |
| Last intake of antibiotics | ||
| In the last month | 200 | 41.5 |
| In the last 6 months | 122 | 25.3 |
| In the last year | 36 | 7.5 |
| More than a year ago | 48 | 10 |
| Never | 16 | 3.3 |
| Can’t remember | 60 | 12.4 |
| Received prescription | ||
| Yes | 331 | 68.7 |
| No | 151 | 31.3 |
Fig. 1Antibiotics commonly used by the respondents
Distribution of knowledge score among respondents
| Variable | Knowledge Score | Chi-squared (X2) | |||
|---|---|---|---|---|---|
| Poor (%) | Fair (%) | Good (%) | |||
| Gender | |||||
| Male | 76 (31.7) | 138 (57.5) | 26 (10.8) | 4.07 | 0.13 |
| Female | 83 (34.3) | 45 (59.9) | 14 (5.8) | ||
| Total | 159 (33.0) | 283 (58.7) | 40 (8.3) | ||
| Settlement category | |||||
| Rural | 80 (38.5) | 114 (54.8) | 14 (6.7) | 5.36 | 0.069 |
| Urban | 79 (28.8) | 169 (61.7) | 26 (9.5) | ||
| State | |||||
| Borno | 36 (47.4) | 38 (50.0) | 2 (2.6) | 53.22 | < 0.0001 |
| Delta | 19 (23.2) | 52 (63.4) | 11 (13.4) | ||
| Ebonyi | 9 (11.5) | 55 (70.5) | 14 (17.9) | ||
| Jigawa | 20 (26.7) | 51 (68.0) | 4 (5.3) | ||
| Lagos | 41 (43.6) | 52 (55.3) | 1 (1.1) | ||
| Plateau | 34 (44.2) | 35 (45.5) | 8 (10.4) | ||
| Education | |||||
| No schooling completed | 20 (50.0) | 18 (45.0) | 2 (5.0) | 39.156 | < 0.0001 |
| Primary Education | 19 (51.4) | 18 (48.6) | 0 (0) | ||
| Secondary Education | 51 (30.5) | 103 (61.7) | 13 (7.8) | ||
| Vocational Training | 24 (49.0) | 23 (46.9) | 2 (4.1) | ||
| Bachelor’s degree | 35 (19.4) | 88 (68.2) | 16 (12.4) | ||
| Master’s degree | 7 (23.3) | 17 (56.7) | 6 (20.0) | ||
| Doctorate degree | 1 (50.0) | 1 (50.0) | 0 (0) | ||
| Non-formal Education | 12 (42.9) | 15 (53.6) | 1 (3.6) | ||
Distribution of Knowledge score according to settlement category within States
| State | Knowledge score | Total | X2 | |||||
|---|---|---|---|---|---|---|---|---|
| Poor (%) | Fair (%) | Good (%) | ||||||
| Area | Rural | 25 (71.4) | 10 (28.6) | 0 (0) | 35 | 15.59 | < 0.001 | |
| Urban | 11 (26.8) | 28 (68.3) | 2 (4.9) | 41 | ||||
| Area | Rural | 10 (27.8) | 20 (55.6) | 6 (16.6) | 36 | 1.72 | 0.423 | |
| Urban | 9 (19.6) | 32 (69.6) | 5 (10.9) | 46 | ||||
| Area | Rural | 4 (12.1) | 23 (69.7) | 6 (18.2) | 33 | 0.024 | 0.988 | |
| Urban | 5 (11.1) | 32 (71.1) | 8 (17.8) | 45 | ||||
| Area | Rural | 11 (34.4) | 20 (62.5) | 1 (3.1) | 32 | 2.0 | 0.367 | |
| Urban | 9 (20.9) | 31 (72.1) | 3 (7.0) | 43 | ||||
| Area | Rural | 21 (46.7) | 24 (53.3) | 0 (0) | 45 | 1.16 | 0.559 | |
| Urban | 20 (40.8) | 28 (57.1) | 1 (2.0) | 49 | ||||
| Area | Rural | 9 (33.3) | 17 (63.0) | 1 (3.7) | 27 | 5.696 | 0.069 | |
| Urban | 25 (50.0) | 18 (36.0) | 7 (14.0) | 50 | ||||
| Total | ||||||||
| Area | Rural | 80 (38.5) | 114 (54.8) | 14 (6.7) | 208 | 5.358 | 0.069 | |
| Urban | 79 (28.8) | 169 (61.7) | 26 (9.5) | 274 | ||||
Fig. 2Participants’ response to conditions that can be treated with antibiotics. The grey bars represent common misconception of the use of antibiotics for viral infections
Fig. 3Respondents familiarity with terms used for drug resistance
Fig. 4Source of information on Antimicrobial resistance
Fig. 5Overview of Responses to knowledge questions