| Literature DB >> 35237406 |
Andrés Gaviria-Mendoza1, Danny Alberto Mejía-Mazo2, Carolina Duarte-Blandón2, Juan Daniel Castrillón-Spitia1, Manuel Enrique Machado-Duque1, Luis Fernando Valladales-Restrepo1, Jorge Enrique Machado-Alba3.
Abstract
AIM: Quarantine due to the COVID-19 pandemic altered the supply and demand of health services. This, together with the 'infodemic' and generalized panic, could alter the patterns of self-medication in the population. The objective was to characterize the patterns of self-medication in four cities of Colombia during mandatory preventive isolation in 2020.Entities:
Keywords: COVID-19; drug utilization; misinformation; pharmacoepidemiology; self-medication
Year: 2022 PMID: 35237406 PMCID: PMC8882931 DOI: 10.1177/20420986221072376
Source DB: PubMed Journal: Ther Adv Drug Saf ISSN: 2042-0986
General characteristics of the sample, discriminated by groups according to the history of self-medication since the beginning of isolation.
| Characteristics | Total ( | Self-medication ( | No Self-medication ( |
|---|---|---|---|
| Sex – | |||
| Woman | 231 (58.2) | 84 (61.8) | 147 (56.3) |
| Man | 164 (41.3) | 52 (38.2) | 112 (42.9) |
| Other | 2 (0.5) | 0 (0.0) | 2 (0.8) |
| Age – median (IQR) years | 31.0 (24.0–41.0) | 30.0 (23.0–39.0) | 31.0 (25.0–41.0) |
| Socioeconomic stratum – | |||
| Low (1–2) | 98 (24.7) | 29 (21.3) | 69 (26.4) |
| Medium (3–4) | 235 (59.2) | 80 (58.8) | 155 (59.4) |
| High (5–6) | 64 (16.1) | 27 (19.9) | 37 (14.2) |
| Affiliation to the health system –
| |||
| Contributory or pay regime | 288 (72.5) | 97 (71.3) | 191 (73.2) |
| Subsidized by the state | 52 (13.1) | 19 (14.0) | 33 (12.6) |
| Not affiliated | 36 (9.1) | 9 (6.6) | 27 (10.3) |
| Does not know | 21 (5.3) | 11 (8.1) | 10 (3.8) |
| Education – | |||
| Basic (primary/high school) | 73 (18.4) | 26 (19.1) | 47 (18.0) |
| Technical | 56 (14.1) | 23 (16.9) | 33 (12.6) |
| Advanced (professional/postgraduate) | 268 (67.5) | 87 (64.0) | 181 (69.3) |
| Ethnicity – | |||
| Mestizo | 364 (91.7) | 120 (88.2) | 244 (93.5) |
| None/does not know | 12 (3.0) | 7 (5.1) | 5 (1.9) |
| Others | 21 (5.3) | 9 (6.6) | 12 (4.6) |
| Area of residence – | |||
| Urban | 369 (92.9) | 128 (94.1) | 241 (92.3) |
| Rural | 28 (7.1) | 8 (5.9) | 20 (7.7) |
| Comorbidities– | |||
| None | 259 (65.2) | 86 (63.2) | 173 (66.3) |
| 1 or more chronic conditions | 138 (34.8) | 50 (36.8) | 88 (33.7) |
| 1 or more pathologies with a high risk of mortality from
COVID-19 | 86 (21.7) | 27 (19.9) | 59 (22.6) |
| Store medications at home – | 369 (92.9) | 135 (99.3) | 234 (89.7) |
| Recommend medications to other people – | 138 (34.8) | 61 (44.8) | 77 (29.5) |
IQR, interquartile range.
Pathologies with high mortality risk for COVID-19, according to the Centers for Disease Control and Prevention, CDC.
Number of self-medicated people for each pharmacological group (n = 136).
| Drug group | Frequency | % |
|---|---|---|
| Number of reported drugs per person – mean ± SD | 3.3 ± 1.9 | |
| One | 19 | 14.0 |
| Two | 29 | 21.3 |
| Three or more | 88 | 64.7 |
| Nervous system | 117 | 86.0 |
| Analgesics | 117 | 86.0 |
| Acetaminophen | 116 | 85.3 |
| Other (psycholeptics, psychoanaleptics) | 8 | 5.9 |
| Musculoskeletal system | 68 | 50.0 |
| Anti-inflammatory and antirheumatic products | 64 | 47.1 |
| Muscle relaxants | 5 | 3.7 |
| Respiratory system | 56 | 41.2 |
| Antihistamines for systemic use | 36 | 26.5 |
| Cough and cold preparations | 33 | 24.3 |
| Alimentary tract and metabolism | 54 | 39.7 |
| Vitamins | 29 | 21.3 |
| Drugs for acid-related disorders | 23 | 16.9 |
| Other (drugs for constipation, antidiarrheals, etc) | 9 | 6.6 |
| Antiinfectives for systemic use | 20 | 14.7 |
| Antibacterials for systemic use | 17 | 12.5 |
| Antimycotics for systemic use | 3 | 2.2 |
| Blood and blood forming organs (antithrombotic agents) | 18 | 13.2 |
| Genito-urinary system and sex hormones (contraceptives) | 10 | 7.4 |
| Antiparasitic products, insecticides, and repellents | 9 | 6.6 |
| Antiprotozoals | 5 | 3.7 |
| Anthelmintics | 4 | 2.9 |
| Other | ||
| Systemic hormonal preparations | 3 | 2.2 |
| Cardiovascular system | 2 | 1.5 |
| Dermatologicals | 1 | 0.7 |
| Other (natural products) | 26 | 19.1 |
SD, standard deviation.
Excluding sex hormones and insulins (corticosteroids for systemic use).
Characterization of self-medication during mandatory preventive isolation (n = 136).
| Variable | % | |
|---|---|---|
| Reasons for self-medication | ||
| Pain | 113 | 83.1 |
| Respiratory symptoms | 62 | 45.6 |
| Flu | 38 | 27.9 |
| Allergies | 29 | 21.3 |
| Cough | 13 | 9.6 |
| Systemic symptoms | 45 | 33.1 |
| Gastrointestinal symptoms | 37 | 27.2 |
| Others | 42 | 30.9 |
| COVID-19 ‘prevention’ | 10 | 7.4 |
| Aspirin | 7 | 5.1 |
| Chloroquine | 2 | 1.5 |
| Hydroxychloroquine | 2 | 1.5 |
| Azithromycin | 1 | 0.7 |
| Dexamethasone | 1 | 0.7 |
| Ivermectin | 1 | 0.7 |
| Reasons for not consulting | ||
| People refer to know the treatment for their condition | 113 | 83.1 |
| Fear of being infected by coronavirus | 39 | 28.7 |
| Difficult access to services due to administrative procedures | 20 | 14.7 |
| Little time availability | 19 | 14.0 |
| Fear of being penalized for leaving home | 10 | 7.4 |
| Mistrust in health personnel or institutions | 8 | 5.9 |
| Economic difficulties | 4 | 2.9 |
| Difficulty in transportation | 2 | 1.5 |
| Health system affiliation problem | 2 | 1.5 |
| Information sources | ||
| Medical formula from previous consultation | 59 | 43.4 |
| By a relative, friend, neighbor, or acquaintance | 48 | 35.3 |
| By custom, tradition, or popular culture | 48 | 35.3 |
| In a pharmacy | 25 | 18.4 |
| Social networks, internet, WhatsApp | 15 | 11.0 |
| By a health worker not authorized to prescribe | 11 | 8.1 |
| As part of an ongoing university training | 7 | 5.1 |
| Television, radio, newspaper, and newscast | 6 | 4.4 |
| Drug sources | ||
| Pharmacy | 112 | 82.4 |
| Home/family kit/relative | 56 | 41.2 |
| Stores/supermarket | 25 | 18.4 |
| A third-party person | 8 | 5.9 |
| Assessment of knowledge about medicines | ||
| Very high | 36 | 26.5 |
| High | 42 | 30.9 |
| Low | 48 | 35.3 |
| None | 10 | 7.3 |
Main reasons for self-medication and the groups of drugs used by the participants.
| Drug group/self-medication reasons | Pain | Respiratory symptoms | Systemic symptoms | Gastrointestinal symptoms | Others | COVID-19 prevention | ||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| % | % | % | % | % | % | |||||||
| Nervous system | 106 | 93.8 | 53 | 85.5 | 40 | 88.9 | 33 | 89.2 | 33 | 78.6 | 8 | 80.0 |
| Musculoskeletal system | 64 | 56.6 | 30 | 48.4 | 31 | 68.9 | 23 | 62.2 | 20 | 47.6 | 3 | 30.0 |
| Respiratory system | 45 | 39.8 | 47 | 75.8 | 21 | 46.7 | 21 | 56.8 | 17 | 40.5 | 4 | 40.0 |
| Alimentary tract and metabolism | 47 | 41.6 | 27 | 43.5 | 21 | 46.7 | 28 | 75.7 | 20 | 47.6 | 5 | 50.0 |
| Anti-infectives for systemic use | 11 | 9.7 | 13 | 21.0 | 7 | 15.6 | 8 | 21.6 | 13 | 31.0 | 3 | 30.0 |
| Blood and blood forming organs (antithrombotic agents) | 15 | 13.3 | 9 | 14.5 | 6 | 13.3 | 7 | 18.9 | 8 | 19.0 | 7 | 70.0 |
| Genito-urinary system and sex hormones (contraceptives) | 10 | 8.8 | 4 | 6.5 | 4 | 8.9 | 3 | 8.1 | 9 | 21.4 | 0 | 0.0 |
| Antiparasitic products, insecticides and repellents | 8 | 7.1 | 5 | 8.1 | 5 | 11.1 | 4 | 10.8 | 5 | 11.9 | 4 | 40.0 |
| Other (natural products) | 21 | 18.6 | 15 | 24.2 | 11 | 24.4 | 9 | 24.3 | 13 | 31.0 | 4 | 40.0 |
| Drugs popularly associated with the treatment of COVID-19 | 9 | 8.0 | 8 | 12.9 | 7 | 15.6 | 4 | 10.8 | 7 | 16.7 | 4 | 40.0 |
Figure 1.Behaviors taken against different hypothetical symptoms by the study participants (n = 397).
*Menstrual cramps calculated on the total response of women.