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Table 4 Univariate and multivariate analysis of predictors for selected regulatory practices (n = 213)

From: The policy-practice gap: describing discordances between regulation on paper and real-life practices among specialized drug shops in Kenya

  Keeping prescription records Availability of a working refrigerator Displaying licenses in premises
Predictor variable n (%) Unadjusted OR (95% CI) p-value Adjusted OR (95% CI) p-value n (%) Unadjusted OR (95% CI) p-value Adjusted OR (95% CI) p-value n (%) Unadjusted OR (95% CI) p-value Adjusted OR (95% CI) p-value
District          
  Bungoma 42 (35) 1.09 (0.61-1.95) p = 0.800 1.31 (0.69-2.50) p = 0.400 13 (10) 0.82 (0.35-1.90) p = 0.600 0.86 (0.30-2.47) p = 0.700 66 (55) 0.89 (0.51-1.55) p = 0.700 0.95 (0.52-1.74) p = 0.900
Kakamega 30 (33) 12 (13) 53 (58)
Shop location          
  Urban 31 (50) 2.58 (1.37-4.86) p = 0.002 1.94 (0.97-3.88) p = 0.050 18 (28) 7.71 (2.86-20.77) p < 0.001 4.14 (1.39-12.27) p = 0.010 41 (63) 1.55 (0.84-2.85) p = 0.200 0.99 (0.50-1.97) p = 0.900
Rural 41 (28) 7 (5) 78 (53)
Licenses displayed in premises          
  Yes 49 (42) 2.19 (1.18-4.08) p = 0.010 1.35 (0.69-2.67) p = 0.300 23 (19) 10.66 (2.30-49.26) p < 0.001 4.02 (0.81-20.10) p = 0.090 - - -
No 22 (25) 2 (2) -
Pharmacy-qualified staff          
  Yes 49 (50) 3.71 (1.96-7.00) p < 0.001 2.70 (1.38-5.31) p = 0.004 23 (23) 16.94 (3.53-81.20) p < 0.001 6.21 (1.26-30.54) p = 0.020 69 (70) 2.95 (1.63-5.34) p < 0.001 1.95 (1.05-3.64) p = 0.030
No 23 (21) 2 (2) 50 (45)
Knows name of pharmacy law          
  Yes 35 (55) 3.52 (1.84-6.71) 001 1.98 (0.95-4.10) p = 0.060 21 (33) 17.70 (5.10-61.49) p < 0.001 4.91 (1.33-18.12) p = 0.010 51 (81) 4.94 (2.33-10.44) p < 0.001 3.63 (1.67-7.89) p < 0.001
  No 37 (26) 4 (3) 68 (46)
Inspection in the last year          
  Yes 62 (35) 1.05 (0.47-2.41) p = 0.900 -   2.09 (0.46-9.44) p = 0.300 - 105 (59) 1.72 (0.80-3.73) p = 0.200 1.33 (0.59-3.01) p = 0.500
No 10 (33) 23 (13) 14 (45)