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Table 4 Multivariate analysis results of differences of key characteristics of 56,860 patients seeking medical cannabis certification by gender and age, with and without interaction

From: Medical cannabis use in the United States: a retrospective database study

 

Model without interaction between age and gender

Model with interaction between age and gender

Characteristic

Coefficient (95% CI)

p-value

Coefficient (95% CI)

p-value

Smoking Status

 Intercept

−0.890 (− 0.961, − 0.820)

< 0.001

−1.00 (−1.108, − 0.900)

< 0.001

 Age

− 0.014 (− 0.016, − 0.013)

< 0.001

− 0.012 (− 0.014, − 0.010)

< 0.001

 Gender (male)

0.110 (0.066, 0.153)

< 0.001

0.294 (0.163, 0.426)

< 0.001

 Interaction

NA

NA

− 0.004 (− 0.007, − 0.001)

0.004

Alcohol Consumption

 Intercept

−0.368 (− 0.424, − 0.311)

< 0.001

−0.220 (− 0.302, − 0.138)

< 0.001

 Age

0.002 (0.001, 0.003)

< 0.001

− 0.001 (− 0.003, 0.000)

0.108

 Gender (male)

− 0.066 (− 0.100, − 0.032)

< 0.001

−0.312 (− 0.417, − 0.207)

< 0.001

 Interaction

NA

NA

0.005 (0.003, 0.007)

< 0.001

Previous Cannabis Experience

 Intercept

0.904 (0.844, 0.964)

< 0.001

0.992 (0.905, 1.08)

< 0.001

 Age

−0.004 (− 0.006, − 0.003)

< 0.001

− 0.006 (− 0.008, − 0.005)

< 0.001

 Gender (male)

0.143 (0.107, 0.179)

< 0.001

− 0.005 (− 0.117, 0.107)

0.929

 Interaction

NA

NA

0.003 (0.001, 0.005)

0.006

History of Substance Abuse

 Intercept

−2.540 (−2.664, −2.418)

< 0.001

−2.284 (−2.475, −2.095)

< 0.001

 Age

−0.012 (− 0.015, − 0.010)

< 0.001

−0.018 (− 0.022, − 0.014)

< 0.001

 Gender (male)

0.361 (0.284, 0.439)

< 0.001

−0.019 (− 0.249, 0.212)

0.871

 Interaction

NA

NA

0.009 (0.004, 0.014)

0.001

Medication Usage

 Intercept

−1.014 (− 1.072, − 0.957)

< 0.001

−0.595 (− 0.677, − 0.513)

< 0.001

 Age

0.024 (0.023, 0.025)

< 0.001

0.015 (0.013, 0.017)

< 0.001

 Gender (male)

−0.607 (− 0.642, − 0.573)

< 0.001

− 1.336 (− 1.445, − 1.227)

< 0.001

 Interaction

NA

NA

0.016 (0.013, 0.018)

< 0.001

Average Number of Medications

 Intercept

0.236 (0.214, 0.259)

< 0.001

0.356 (0.324, 0.389)

< 0.001

 Age

0.011 (0.011, 0.012)

< 0.001

0.009 (0.008, 0.009)

< 0.001

 Gender (male)

−0.233 (− 0.247, − 0.220)

< 0.001

−0.432 (− 0.473, − 0.391)

< 0.001

 Interaction

NA

NA

0.004 (0.003, 0.005)

< 0.001

Average Number of Conditions

 Intercept

1.483 (1.469, 1.497)

< 0.001

1.507 (1.487, 1.527)

< 0.001

 Age

0.000 (0.000, 0.000)

0.423

−0.001 (− 0.001, 0.000)

0.003

 Gender (male)

−0.143 (− 0.151, − 0.135)

< 0.001

−0.183 (− 0.209, − 0.157)

< 0.001

 Interaction

NA

NA

0.001 (0.000, 0.001)

0.001

  1. Table 4 shows the results of regression analysis for age and gender as predictors for variables analyzed with univariate analysis in Tables 2 and 3 among 56,860 patients for whom gender was reported. Results are presented with and without an interaction between age and gender included in the model. The coefficient column represents the magnitude of effect and direction of the predictor variable; a negative coefficient for age suggests that younger patients are more likely to report the characteristic, and a negative coefficient for gender suggests that females are more likely to report the characteristic. CI confidence interval