| Literature DB >> 30818373 |
Grace-Ange Elong Ekambi1, Cécile Okalla Ebongue2, Ida Calixte Penda3, Emmanuel Nnanga Nga1, Emmanuel Mpondo Mpondo1, Carole Else Eboumbou Moukoko2,4.
Abstract
Benefits of antibiotics are threatened by the self-medication, people's lack of knowledge and inappropriate use of antibiotics, especially in developing countries. This study was designed to determine knowledge; attitudes and practices toward antibiotics use in an urban community, and evaluate the factors that are associated with antibiotic use. Between January and March 2015, a cross sectional and prospective study was conducted in all pharmacies within the Douala IV health district, Cameroon. Anonymous interviews including both open and closed ended questions were conducted in participants selected by convenience sampling Descriptive and logistic regression analysis were performed using StataSE11 software (version 11 SE) and R software (version 3.1.1) in data analysis. Overall 402 (33.7%) of 1,192 customers purchased antibiotics and of these, 47% bought antibiotics without a prescription. 60.7% of purchased antibiotics was for adult 'patients and around 60% of parents carried out self-medication on their children. The vast majority reported that all microbes can be treated with antibiotics (88.3%). The belief that antibiotics are appropriate for bacterial infections was more common among those with a higher level education (OR = 4.03, 95%CI:1.89-8.57, p<0.0001) and among public/private servants (OR = 2.47, 95%CI:1.21-5.08, p = 0.013). Physicians provide less explanations about antibiotics are and their potential side effects than the pharmacy auxiliaries (OR = 0.205, 95%CI = 0.09-0.46, p<0.0001), but more than pharmacists (OR = 3.692, 95%CI:1.44-9.25, p = 0.005). Indications on antibiotics use were 7 times more given to customers with a prescription compared to those without a prescription (OR = 7.37, 95% CI = 2.13-25.43, p = 0.002). Adult male (OR = 2.32, 95%CI:1.24-4.34, p = 0.009) and higher education (OR = 2.05, 95%CI:1.08-3.89, p = 0.027) were significantly associated with self-medication. Misuse, little "practical knowledge" and high self-medication confirm the unsatisfactory prescription and dispensing practices of the antibiotics in our country. These results highlight the important of the development and implementation appropriate guidelines for the responsible use of antibiotics for health care providers and health education targeting community members themselves.Entities:
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Year: 2019 PMID: 30818373 PMCID: PMC6394986 DOI: 10.1371/journal.pone.0212875
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Fig 1Flow chart of participants through the study according to the type of medication.
Characteristics by gender of participants visiting the pharmacies to purchase antibiotics.
| 33.1 (9.8) | 36.76 (10.9) | 35.02 (10.5) | 0.0001 | |
| Out-of-school | 0 (0.0) | 6 (2.9) | 6 (1.5) | Reference |
| Primary | 23 (11.9) | 23 (11.0) | 46 (11.4) | 0.023 |
| Secondary | 105 (54.4) | 111 (53.1) | 216 (53.7) | 0.020 |
| University | 65 (33.7) | 69 (33.0) | 134 (33.3) | 0.021 |
| Unmarried | 61 (31.6) | 62 (29.6) | 123 (30.6) | Reference |
| Widowed/Divorced | 8 (4.1) | 1 (0.5) | 9 (2.2) | 0,023 |
| Married/Concubinage | 124 (64.3) | 146 (69.9) | 270 (67.2) | 0,285 |
| Pupils/Students | 31 (16.1) | 19 (9.1) | 50 (12.4) | Reference |
| Unemployed | 33 (17.1) | 6 (2.9) | 39 (9.7) | 0,031 |
| Public sector employee | 13 (6.7) | 18 (8.6) | 31 (7.7) | 0,108 |
| Private sector employee | 53 (27.5) | 104 (49.8) | 157 (39.1) | 0,001 |
| Informal sector | 63 (32.6) | 62 (29.7) | 125 (31.1) | 0,182 |
Data are number and/or proportion (%), unless otherwise indicated.
Identification of Customers’ perceptions of antibiotic use*.
| Customers’ population | p | |||
|---|---|---|---|---|
| Female (N = 192) | Male (N = 208) | Total (N = 400) | ||
| 184 (95.8) | 193 (92,8) | 377 (94.2) | 0.137 | |
| Treat all | 14 (7.6) | 12 (6.2) | 26 (6.9) | 0.371 |
| Decrease fever | 10 (5.4) | 14 (7,2) | 24 (6.4) | 0,305 |
| Treat microbes | 166 (90.2) | 167 (86.5) | 333 (88.3) | 0.170 |
| Treat bacterial disease | 81 (44.0) | 84 (43.5) | 165 (43.7) | 0,502 |
| Treat viral disease | 25 (13.5) | 20 (10.3) | 45 (11.8) | 0.210 |
| Treat parasitic disease | 11 (6,0) | 12 (6.2) | 23 (6.1) | 0.547 |
| Treat fungal disease | 15 (8.1) | 15 (7.8) | 30 (7.9) | 0.521 |
| Calm pain | 17 (9.2) | 23 (11.9) | 40 (10.6) | 0.250 |
| Fight against tiredness | 1 (0.5) | 7 (3.6) | 8 (2.1) | 0.039 |
| 192 (100) | 208 (100) | 400 (100) | / | |
| 120 (62.5) | 113 (54.3) | 233 (58.2) | 0.060 | |
| Digestive disorders | 35 (29.2) | 33 (29.2) | 68 (29.2) | 0.555 |
| Allergies/Itching | 59 (49.2) | 64 (56.6) | 123 (52.8) | 0.156 |
| Dizziness | 29 (24.2) | 19 (16.8) | 48 (20.6) | 0.110 |
| Tiredness | 26 (21.7) | 13 (11.5) | 39 (16.7) | 0.028 |
| Other | 13 (10.8) | 12 (10.6) | 25 (10.7) | 0.564 |
Data are number and/or proportion (%)
*, Under-15 years old were excluded from the analysis
$, Anorexia, headache, hum, deficient immune system, difficulty swallowing and, palpitations.
Fig 2Antibiotics prescribers to outpatient in the Douala IV health district in Douala.
Sources of self-medication among patients concerned with the antibiotics and reasons for the antibiotics self-medication.
| Female (N = 83) | Male (N = 106) | Total (N = 189) | OR (95% CI) | p | |
|---|---|---|---|---|---|
| Difficulties accessing healthcare | 15 (18.1) | 10 (9.43) | 25 (13.2) | / | Reference |
| 44 (53,0) | 49 (46,2) | 93 (49.2) | 1.67 (0.68–4.1) | 0.263 | |
| Pharmacist | 20 (45.4) | 17 (35.4) | 37 (40.2) | ||
| Practitioner | 6 (13.6) | 6 (12.5) | 12 (13.0) | ||
| Auxiliary pharmacy | 11 (25.0) | 15(31.2) | 26 (28.3) | ||
| Nurse | 7 (15.9) | 10 (20.8) | 17 (18.5) | ||
| 3 (3.61) | 10 (9.43) | 13 (6,88) | 4.99 (1.1–22.8) | 0.038 | |
| Relative | 2 (66.7) | 9 (90.0) | 11 (84.6) | ||
| Medical delegate | 1 (33.3) | 1 (10.0) | 2 (15.4) | ||
| 21 (25.3) | 37 (34.91) | 58 (30.7) | 2.64 (1.01–6.92) | 0.048 | |
| Drug-taking practice | 6 (28.6) | 9 (23.3) | 15 (25.4) | ||
| Finance cost reduction | 1 (4.8) | 1 (2.7) | 3 (5.1) | ||
| Prevention | 1 (4.8) | 4 (10.8) | 5 (8.5) | ||
| Renewal treatment or Resumption | 6 (28.6) | 8 (21.6) | 14 (23.7) | ||
| Family medication | 1 (4.8) | 1 (2.7) | 2 (3.4) | ||
| Recidivism | 6 (28.6) | 14 (37.8) | 20 (33.9) |
Data are number and/or proportion (%)
, Friends, neighbors or parents.
Dispensing practices in the pharmacies.
| Self-medication | Prescription | Total | |||||
|---|---|---|---|---|---|---|---|
| Female | Male | Total | Female | Male | Total | ||
| 83 | 106 | 189 | 110 | 103 | 213 | 402 | |
| Pharmacy auxiliaries | 60 (72.3) | 81 (76.4) | 141 (74,6) | 93 (84.6) | 81 (78.6) | 174 (81,69) | 315 (78.4) |
| Pharmacists | 23 (27.7) | 25 (23.6) | 48 (25,4) | 17 (15.4) | 22 (21.4) | 39 (18,31) | 87 (21.6) |
| 74 (89,2) | 97 (91;5) | 171 (90,48) | 109 | 101 | 210 (98,59) | 381 (94.8) | |
| Practitioners | 0 (0.0) | 1 (1.0) | 1 (0,6) | 11 (10.1) | 7 (6.9) | 18 (8.6) | 19 (5.0) |
| Practitioners & Pharmacy auxiliaries | 0 (0.0) | 2 (2.1) | 2 (1,2) | 48 (44.0) | 38 (37.6) | 86 (40.9) | 88 (23.1) |
| Practionners & Pharmacysts | 0 (0.0) | 0 (0.00) | 0 (0,0) | 17 (15.6) | 19 (18. 8) | 36 (17.1) | 36 (9.4) |
| Pharmacysts | 22 (29.7) | 24 (24.7) | 46 (26,9) | 2 (1.8) | 3 (3.0) | 5 (2.4) | 51 (13.4) |
| Pharmcysts & Nurses | 0 (0.0) | 0 (0.0) | 0 (0,0) | 0 (0.0) | 1 (1.0) | 1 (0.5) | 1 (0.3) |
| Nurses | 1 (1.3) | 0 (0.0) | 1 (0,6) | 2 (1.8) | 0 (0.0) | 2 (0.9) | 3 (0.8) |
| Nurses & Pharmacy auxiliaries | 5 (6.8) | 4 (4.1) | 9 (5,3) | 15 (13.8) | 21 (20.8) | 36 (17.1) | 45 (11.8) |
| Pharmacy auxiliaries | 46 (62.2) | 66 (68.0) | 112 (65,50) | 14 (12.8) | 12 (11.9) | 26 (12.4) | 138 (36.2) |
Data are number and/or proportion (%).
Multivariate analysis of factors associated with type of medication according to antibiotic target groups.
| Antibiotics target groups | Self-medication | Prescription | Total | Univariate analysis | Multivariate | ||
|---|---|---|---|---|---|---|---|
| OR (95%CI) | p | OR (95%CI) | p | ||||
| 93 (38,1) | 151 (61,9) | 244 | |||||
| Female | 38 (28.2) | 97 (71.8) | 135 (55.3) | Reference | |||
| Male | 55 (50.5) | 54 (49.5) | 109 (44.7) | 2.60 (1.53–4.42) | <0.0001 | 2.22 (1.17–4.18) | 0.014 |
| 38.2 (13.0) | 34,8 (11,1) | 36.1 (11.9) | / | 0.034 | |||
| < = 40 | 60 (64.5) | 118 (78.1) | 178 (72.9) | 1.97 (1.11–3.49) | 0.021 | 2.18 (1.07–4.46) | 0.032 |
| >48 | 33 (35.5) | 33 (21.9) | 66 (27.1) | Reference | |||
| 69 (39.0) | 108 (61.0) | 177 | 2.07 (1.10–4.00) | 0.031 | |||
| Out-of-school & primary | 8 (11.6) | 17 (15.7) | 25 (14.1) | Reference | |||
| Secondary | 28 (40.6) | 58 (53.7) | 86 (48.6) | 1.02 (0.94–2.66) | 0.958 | ||
| University | 33 (47.8) | 33 (30,6) | 66 (37.3) | 2.07 (1.10–4.00) | 0,031 | 2.14 (1.11–4.09) | 0.022 |
| Gender | 96 (60.8) | 62 (39.2) | 158 | ||||
| Boys | 49 (61.2) | 31 (38.8) | 80 (50.6) | Reference | |||
| Girls | 47 (60.3) | 31 (39.7) | 78 (49.4) | 1.04 (0.55–1.97) | 0.898 | ||
| Mean age (Sd), years | 2.73 (2.6) | 2.59 (2.4) | 2.7 (2.5) | / | 0.801 |
Data are number and/or proportion (%), unless otherwise indicated
$, People over 15 years
*, Variables used as reference
£, Analysis on the impact of these variables was done only among people who came to buy their own antibiotics
#, Comparison made between self-medication and prescription groups for the variable indicated.