Table 1.
Perceived characteristics of the visited pharmacies and respondent pharmacy staff and factors associated with non-prescription dispensing of antibiotics at community pharmacies in Shenyang.
| Variables | Total Number | Nonprescription Antibiotic Dispensing | Multiple Logistic Regression | |||
|---|---|---|---|---|---|---|
| n(%) | Yes, n(%) | No n(%) | OR | 95%CI | p-Value | |
| Case | ||||||
| Adult case | 74(50.3) | 72(97.3) | 2(2.7) | ref | ||
| Pediatric case | 73(49.7) | 58(79.5) | 15(20.5) | 0.099 | 0.020–0.505 | 0.005 |
| Pharmacy characteristics | ||||||
| Socioeconomic 1 | ||||||
| Low socioeconomic level | 96(65.3) | 85(88.3) | 11(11.7) | ref | ||
| High socioeconomic level | 51(34.7) | 45(88.2) | 6(11.8) | 0.814 | 0.225–2.943 | 0.753 |
| Type | ||||||
| Independent | 18(12.2) | 18(100) | 0(0) | ref | ||
| Chain | 129(87.8) | 112(86.8) | 17(13.2) | 0.000 | 0.000– | 0.998 |
| Area | ||||||
| Suburb district | 43(39.3) | 40(93.0) | 3(7.0) | ref | ||
| Urban district | 104(60.7) | 90(86.5) | 14(13.5) | 0.892 | 0.204–3.914 | 0.881 |
| Distribution | ||||||
| Community center | 112(76.2) | 103(91.9) | 9(8.1) | ref | ||
| Medical center | 17(11.6) | 13(76.4) | 4(23.6) | 0.317 | 0.069–1.463 | 0.141 |
| Shopping center | 18(12.2) | 14(77.8) | 4(22.2) | 0.370 | 0.078–1.765 | 0.212 |
| Size 2 | ||||||
| Small (<100 m2) | 68(46.3) | 60(88.2) | 8(11.8) | ref | ||
| Medium (100–300 m2) | 70(47.6) | 61(87.1) | 9(13.9) | 1.479 | 0.446–4.906 | 0.522 |
| Larger (≥300 m2) | 9(6.1) | 9(100) | 0(0) | 1.841E8 | 0.000– | 0.999 |
| Staff characteristics | ||||||
| Gender | ||||||
| Female | 144(97.9) | 127(88.2) | 17(11.8) | ref | ||
| Male | 3(2.1) | 3(100) | 0(0) | 8.938E8 | 0.000– | 0.999 |
| Ages (years) | ||||||
| >50 | 6(4.1) | 5(83.3) | 1(16.7) | ref | ||
| 30–50 | 96(65.3) | 86(89.6) | 10(10.4) | 10.613 | 0.313–359.761 | 0.189 |
| ≤30 | 45(30.6) | 39(86.7) | 6(13.3) | 16.852 | 0.439–647.711 | 0.129 |
Note: The estimated odds ratios with 95% CI were obtained from the multivariate binary logistic regressions and all the independent variables with random intercepts were analyzed jointly in the regression model. 1 Socioeconomic: According to the gross domestic product (GDP) statistics, we categorize these districts with GDP higher than the average level into the high socioeconomic status region and the others into the low socioeconomic status region. Pharmacy characteristics of low/high socioeconomic level means a pharmacy in the low/high socioeconomic status region. 2 Size: According to the Good Supply Practice, the area of the community pharmacy’s place of business in the main urban district of the state (city) level shall not be less than 100 square meters. Our pharmacy visits were in major district of the city of Shenyang. Therefore, the area less than 100 square meters is classified as a small pharmacy. OR=odds ratios; CI= confidence interval.