| Literature DB >> 28690695 |
Mohamed A Hassali1, Mohammad Arief2, Fahad Saleem3, Muhammad U Khan4, Akram Ahmad5, Warisha Mariam6, Harika Bheemavarapu7, Iizhar A Syed8.
Abstract
OBJECTIVE: The present study was aimed to evaluate the practices and attitudes of young Malaysian adults towards the use of antibiotics, and to determine the socioeconomic factors associated with the antibiotic use.Entities:
Keywords: Anti-Bacterial Agents; Attitudes; Cross-Sectional Studies; Health Knowledge; Malaysia; Patient Medication Knowledge; Practice; Self Medication; Young Adult
Year: 2017 PMID: 28690695 PMCID: PMC5499350 DOI: 10.18549/PharmPract.2017.02.929
Source DB: PubMed Journal: Pharm Pract (Granada) ISSN: 1885-642X
Summary of demographic characteristics of the participants
| Demographic Data | Frequency | % |
|---|---|---|
| Age | ||
| 18-24 | 317 | 79 |
| 25-35 | 83 | 21 |
| Gender | ||
| Male | 171 | 42.75 |
| Female | 229 | 57.25 |
| Race | ||
| Chinese | 241 | 60.25 |
| Indian | 26 | 6.5 |
| Malay | 118 | 29.5 |
| Other[ | 15 | 3.75 |
| Marital status | ||
| Single | 31 | 77.75 |
| Married | 89 | 22.25 |
| Educational level | ||
| Secondary school | 61 | 15.25 |
| College | 79 | 19.75 |
| University | 260 | 65 |
| Employment status | ||
| Employed | 118 | 29.5 |
| Self-employed | 38 | 9.5 |
| Unemployed | 133 | 33.25 |
| Housewife | 15 | 3.75 |
| Others | 96 | 24 |
| Occupation | ||
| Health-care related | 115 | 28.75 |
| Non health-care related | 285 | 71.25 |
| Monthly income (Ringgits) | ||
| <1000 MYR | 29 | 57.25 |
| 1000-3000 MYR | 87 | 21.75 |
| 3000-5000 MYR | 53 | 13.25 |
| >5000 MYR | 31 | 7.75 |
| Do you have any kind of health insurance? | ||
| Yes | 249 | 62.25 |
| No | 151 | 37.75 |
= Filipino, Burmese, Indonesian, Vietnamese
Attitude of participants towards antibiotic usage
| Attitude towards Antibiotic Usage | Agree | Unsure | Disagree |
|---|---|---|---|
| 1. Antibiotics are safe drugs. | 189 | 153 (38.25%) | 58 (14.5%) |
| 2. Antibiotics are effective for fever. | 214 (53.5%) | 125 (31.25%) | 61 |
| 3. Antibiotics are effective for cold. | 171 (42.75%) | 157 (39.25%) | 72 |
| 4. Antibiotics are effective for headache. | 98 (24.5%) | 179 (44.75%) | 123 |
| 5. I expect the doctors to prescribe me antibiotics for my bacterial infection. | 262 | 110 (27.5%) | 28 (7%) |
| 6. I expect the doctors to prescribe me antibiotics for my viral infection. | 199 (49.75%) | 127 (31.75%) | 74 |
| 7. I keep antibiotics at home in case of emergency. | 156 (39%) | 58 (14.5%) | 186 |
| 8. I suggest my antibiotics to my family members who need it. | 117 (29.25%) | 66 (16.5%) | 217 |
| 9. Antibiotics can be taken according to product leaflet/label without consulting doctors. | 76 (19%) | 94 (23.5%) | 230 |
| 10. Expiry date of antibiotics should be checked before administered. | 355 | 37 (9.25%) | 8 (2%) |
| 11. Antibiotic resistance is dangerous for the society. | 171 | 191 (47.75%) | 38 (9.5%) |
| 12. It is necessary to enhance antibiotic education among public. | 310 | 81 (20.25%) | 9 (2.25%) |
Positive attitudes
Association of demographic characteristics with attitude towards antibiotics
| Attitude towards antibiotics | p-value | Adjusted | ||
|---|---|---|---|---|
| Positive | Negative | |||
| Age | ||||
| 18-25 | 133 (42.6%) | 184 (57.3%) | 1.00 | |
| 25-35 | 38 (45%) | 45 (55%) | 0.383 | 0.963 (0.263-1.669) |
| Gender | ||||
| Male | 71(41.5%) | 100 (59%) | 1.00 | |
| Female | 100 (44%) | 129 (56%) | 0.289 | 1.077 (0.697-1.665) |
| Race | ||||
| Malay | 55 (46%) | 64 (54%) | 1.00 | |
| Chinese | 99 (41%) | 142 (59%) | 0.047 | 1.836 (1.059-2.013) |
| Indians | 11 (42.3%) | 15 (57.6%) | 0.950 | 1.030 (0.409-2.595) |
| Others | 6 (42.8%) | 8 (57%) | 0.794 | 1.167 (0.365-2.224) |
| Marital status | ||||
| (unmarried) | 132 (42.7%) | 177 (57.2%) | 1.00 | |
| Married | 39 (42.8%) | 52 (57%) | 0.265 | 0.975 (0.164-2.643) |
| Education | ||||
| Secondary school | 23 (37.7%) | 38 (62%) | 1.00 | |
| College | 39 (48.7%) | 41 (51.2%) | 0.228 | 0.777 (0.460-1.313) |
| University | 109 (42%) | 150(58%) | 0.056 | 1.689 (1.061-3.316) |
| Employment | ||||
| Unemployed | 58 (46.2%) | 78 (57.3%) | 1.00 | |
| Employed | 40 (34%) | 77 (65.8%) | 0.340 | 1.308 (0.753-2.274) |
| Self employed | 21(52.5%) | 19 (47.5%) | 0.207 | 1.575 (0.778-3.191) |
| House wife | 8 (53%) | 7 (47%) | 0.523 | 0.753 (0.315-1.801) |
| Others | 44 (47.8%) | 48 (52%) | 0.522 | 0.652 (0.176-2.417) |
| Occupation | ||||
| Non-healthcare | 127(44.4%) | 159 (55.5%) | 1.00 | |
| Healthcare | 44(38.5%) | 70 (61.4%) | 0.054 | 1.806 (1.323-2.431) |
| Income | ||||
| <1000 | 107(46.3%) | 124 (53.6%) | 1.00 | |
| 1000-3000 | 35(37.2%) | 59 (62.7%) | 0.210 | 1.471 (0.805-2.689) |
| 3000-5000 | 20(42.5%) | 27 (57.4%) | 0.450 | 1.396 (0.588-3.316) |
| >5000 | 9(32%) | 19 (67.8%) | 0.044 | 2.071 (1.308-6.056) |
Adjusted for age, gender, race, education, employment status, occupation, income Overall predictive accuracy of the model is 62% omnibus test of model coefficients:-2 Log Likelihood= 524.4, Nagelkerke R square= 0.071. Statistically significant variables are in bold.
Antibiotics practices among participants.
| Statements | Yes | No |
|---|---|---|
| 1. I use antibiotics when I have a common cold. | 121 (30.25%) | 279 (69.75%) |
| 2. I use antibiotics when I have a cough. | 120 (30%) | 280 (70%) |
| 3. I use antibiotics whenever I am not feeling well. | 114 (28.5%) | 286 (71.5%) |
| 4. I use leftover antibiotic. | 61 (15.25%) | 339 (84.75%) |
| 5. I keep antibiotic for future use. | 115 (28.75%) | 285 (71.25%) |
| 6. I take antibiotic without consulting the doctor most of the time. | 75 (18.75%) | 325 (81.25%) |
| 7. I discontinue antibiotics once symptoms subside. | 158 (39.5%) | 242 (60.5%) |
| 8. I return the leftover antibiotics to the pharmacist/doctor | 30 (9.5%) | 360 (90.5%) |
| 9. I consult pharmacist for the modification of my prescription | 141 (35.25%) | 259 (64.75%) |
| 10. I follow correct dosage instruction | 295 (73.75%) | 105 (26.25%) |
Good practice
Common source of antibiotics and reason for not consulting the physician
| Statements | Yes | No |
|---|---|---|
| From whom would you get the information about antibiotics? | ||
| Friends | 100 (25%) | 300 (75%) |
| Community pharmacists | 62 (15.5%) | 338 (84.5%) |
| Books/ Websites | 24 (6%) | 376 (94%) |
| School/ University | 19 (4.75%) | 381 (95.25%) |
| I usually obtain antibiotic from: | ||
| Hospital | 172 (43%) | 228 (57%) |
| Clinic | 314 (78.5%) | 86 (21.5%) |
| Retail pharmacy | 107 (26.75%) | 293 (73.25%) |
| Street vendor | 3 (0.75%) | 397 (99.25%) |
| Use someone else’s | 22 (5.5%) | 374 (4.5%) |
| What are your reasons for not consulting physician: | ||
| I feel inconvenient to go see physician | 117 (29.25%) | 283 (70.75%) |
| I find it expensive to go see physician | 137 (34.25%) | 263 (65.75%) |
| I take antibiotics based on advice from family members or friends | 59 (14.75%) | 341 (85.25%) |
| I know how to treat my own illness | 94 (23.5%) | 306 (76.5%) |
| I have unpleasant experience from previous physician visits | 22 (5.5%) | 378 (94.5%) |
| I don’t see doctor for minor illness | 256 (64%) | 144 (36%) |
Association of demographic characteristics with practice towards antibiotics
| Practice towards antibiotics | p-value | Adjusted | ||
|---|---|---|---|---|
| Poor | Good | |||
| Age | ||||
| 18-25 | 103 (33%) | 216 (66.9%) | 1.00 | |
| 25-35 | 28 (32.8%) | 53 (67.1%) | 0.688 | 0.788 (0.224-2.116) |
| Gender | ||||
| Male | 53 (30.9%) | 118 (69%) | 1.00 | |
| Female | 78 (34%) | 151 (65.9%) | 0.035 | 1.934 (1.354-2.876) |
| Race | ||||
| Malay | 57 (47.8%) | 62 (52.1%) | 1.00 | |
| Chinese | 58 (24%) | 183 (75.9%) | 0.004 | 3.309 (1.964-5.573) |
| Indians | 10 (38.4%) | 16 (61.5%) | 0.405 | 1.492 (0.582-3.824) |
| Others | 6 (42.8%) | 8 (57.1%) | 0.678 | 1.282 (0.397-4.141) |
| Marital status | ||||
| (unmarried) | 100 (32.3%) | 209 (67.6%) | 1.00 | |
| Married | 31 (34%) | 60 (65.9%) | 0.396 | 1.204 (0.387-2.465) |
| Education | ||||
| Secondary school | 20 (32.7%) | 41 (67.2%) | 1.00 | |
| College | 27 (33.7%) | 53 (66.2%) | 0.469 | 1.306 (0.635-2.687) |
| University | 84 (32.4%) | 175 (67.5%) | 0.667 | 1.135 (0.637-2.022) |
| Employment | ||||
| Unemployed | 37 (27.2%) | 99 (72.7%) | 1.00 | |
| Employed | 34 (29%) | 83 (71%) | 0.300 | 1.376 (0.752-2.519) |
| Self employed | 19 (47.5%) | 21 (52.5%) | 0.590 | 0.815 (0.388-1.713) |
| House wife | 8 (53.3%) | 7 (46.6%) | 0.028 | 0.350 (0.137-0.891) |
| Others | 33 (35.8%) | 59 (64%) | 0.063 | 0.267 (0.066-1.076) |
| Occupation | ||||
| Non-healthcare | 97 (33.9%) | 189 (66%) | 1.00 | |
| Healthcare | 34 (29.8%) | 80 (70%) | 0.075 | 1.543 (1.014-2.605) |
| Income | ||||
| <1000 MYR | 82 (35.4%) | 149 (64.5%) | 1.00 | |
| 1000-3000 MYR | 29 (30.8%) | 65 (69%) | 0.043 | 1.957 (1.023-3.745) |
| 3000-5000 MYR | 13 (27.6%) | 34 (72.3%) | 0.016 | 2.498 (1.278-6.385) |
| >5000 MYR | 7 (25%) | 21 (75%) | 0.143 | 2.371 (0.747-7.525) |
Adjusted for age, gender, race, education, employment status, occupation, income Overall predictive accuracy of the model is 70.5% omnibus test of model coefficients:-2 Log Likelihood= 464.6, Nagelkerke R square= 0.137. Statistically significant variables are in bold.