| Literature DB >> 29300318 |
Xiaosheng Lei1, Heng Jiang2,3, Chaojie Liu4, Adamm Ferrier5, Janette Mugavin6.
Abstract
BACKGROUND: This study aims to examine the prevalence and predictors associated with self-medication, and related consequences in Wuhan, China.Entities:
Keywords: Chinese residents; associated factors; practice; self-medication
Mesh:
Substances:
Year: 2018 PMID: 29300318 PMCID: PMC5800167 DOI: 10.3390/ijerph15010068
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 3.390
Figure 1Conceptual framework of the modified Andersen model of health service utilization.
Characteristics of the study respondents (N = 258).
| Characteristics | Frequency | Percentage |
|---|---|---|
| Gender | ||
| Male | 127 | 49.2 |
| Female | 131 | 50.8 |
| Age (years) | ||
| 18–20 | 17 | 6.6 |
| 21–40 | 94 | 36.4 |
| 41–60 | 110 | 42.6 |
| >60 | 37 | 14.4 |
| Occupation | ||
| Worker | 40 | 15.5 |
| Peasant | 22 | 8.5 |
| Teacher | 29 | 11.2 |
| Civil servant | 19 | 7.4 |
| Medical staff | 8 | 3.1 |
| Business owner | 33 | 12.8 |
| Enterprise staff | 60 | 23.3 |
| Others | 47 | 18.2 |
| Marital Status | ||
| Married | 186 | 72.1 |
| Unmarried | 72 | 27.9 |
| Education | ||
| Middle school and lower | 56 | 21.7 |
| High/Secondary School | 55 | 21.3 |
| College/University | 131 | 50.8 |
| Master and above | 16 | 6.2 |
| Monthly income (Chinese Yuan ¥) | ||
| <1500 | 19 | 7.4 |
| 1500–3000 | 69 | 26.7 |
| 3001–4500 | 86 | 33.3 |
| 4501–6000 | 56 | 21.7 |
| >6000 | 28 | 10.9 |
| Medical insurance | ||
| Urban basic medical insurance | 178 | 69.0 |
| Free medical insurance | 15 | 5.8 |
| New cooperative medical scheme | 47 | 18.2 |
| Commercial medical insurance | 11 | 4.3 |
| No medical insurance | 7 | 2.7 |
Figure 2Respondent’s medical treatment choice.
Figure 3Type of illness for self-medication.
The reason and source of knowledge for self-medication.
| Variables | Frequency | Percentage |
|---|---|---|
| The reason of self-medication * | ||
| High medical costs | 39 | 15.1 |
| Save the trouble of seeing a doctor | 58 | 22.5 |
| Mild disease | 117 | 45.4 |
| No time to see the doctor | 30 | 11.6 |
| Other reasons | 14 | 5.4 |
| | ||
| Medication knowledge sources * | ||
| Advice from others or peers | 71 | 27.7 |
| Internet | 49 | 19.1 |
| Newspaper and magazine | 5 | 2.0 |
| Past experience | 131 | 51.2 |
| | ||
Notes: * p < 0.05 and a chi-square test were conducted to test categorical difference. # The sample size is 256 because of 2 missing values.
Adverse drug reaction and whether the instructions were read or not (person (%)).
| Variable | Read Instruction | Not Read Instruction | Total |
|---|---|---|---|
| Adverse drug reaction * | |||
| Yes | 31 (15.1) | 15 (28.3) | 46 (17.8) |
| No | 174 (84.9) | 38 (71.7) | 212 (82.2) |
| Total | 205 (100) | 53 (100) | 258 (100) |
Note: * p < 0.05 and a chi-square (X2) test were conducted to test categorical difference.
The situation of reading instructions in different education level (person (%)).
| Variable | Read Instruction | Not Read Instruction | Total |
|---|---|---|---|
| Education level * | |||
| Junior high school or below | 27 (48.2) | 29 (51.8) | 56 (100) |
| High school, secondary school | 44 (80.0) | 11 (20.0) | 55 (100) |
| Training certificate, bachelor or higher | 134 (91.2) | 13 (8.8) | 147 (100) |
| Total | 205 (79.5) | 53 (20.5) | 258 (100) |
Note: * p < 0.05 and a chi-square test were conducted to test categorical difference.
Multivariable logistic regression analyses on influencing factors of self-medication.
| Independent Variable (N = 258) | Wald | OR | (95% CI) | |||
|---|---|---|---|---|---|---|
| Age | −0.14 | 0.22 | 0.44 | 0.51 | 0.87 | (0.57, 1.32) |
| Gender (male/female) | −0.21 | 0.27 | 0.63 | 0.43 | 0.81 | (0.48, 1.37) |
| Employment (employed/unemployed) | −0.03 | 0.06 | 0.32 | 0.58 | 0.97 | (0.86, 1.09) |
| Marital status (yes/no) | −0.26 | 0.13 | 4.24 | 0.04 | 0.78 | (0.60, 0.99) |
| Education (high school or lower/college, bachelor or higher) | 0.32 | 0.18 | 3.04 | 0.08 | 1.37 | (0.96, 1.96) |
| Income (≤6000/>6000) | 0.04 | 0.13 | 0.10 | 0.75 | 1.04 | (0.81, 1.34) |
| Medical Insurance (yes/no) | −0.50 | 0.81 | 0.37 | 0.54 | 0.61 | (0.12, 3.02) |
| Distance to medical units (<4 miles/≥4 miles) | −0.15 | 0.11 | 1.96 | −0.15 | 0.86 | (0.69, 1.06) |
| Severity of disease (severe, common/mild) | −0.63 | 0.24 | 6.65 | 0.01 | 0.53 ** | (0.33, 0.86) |
| Length of illness (<7 days/≥7 days) | 0.46 | 0.16 | 8.78 | 0.00 | 1.59 ** | (1.17, 2.16) |
| Constant | 1.89 | 1.65 | 1.32 | 0.25 | 6.65 |
Notes: SE is standard error; Log likelihood = 355.428; Log likelihood X2 = 26.504; Cox & Snell pseudo R2 = 0.098; ** p < 0.01.