Table 2.

Prevalence rates ratios and 95% confidence intervals of the consumption of cocaine, marijuana, cigarette, alcohol risk of consumption of psychoactive substances associated with depression adjusted for age groups of Colombian workers

				CI 95%
	Estimator	Confusion effect percentage (%) (Eq. 10)	Standard error estimation	Lower limit	Upper limit	Comparison of the standard error of the models with MH (Eq. 11)	BIC
Lifetime cocaine consumption prevalence (prevalence = 1.8%)
PR MH (age adjusted)	2.913	13.08	0.7570	0.786	12.845
PR Negative Log-Binomial model	2.931	12.38	0.7185	0.717	11.985	5.358
PR Robust Negative Log-Binomial model	2.931	12.38	0.7144	0.723	11.889	5.963	-43,857.1
PR Cox/Poisson model	2.928	12.50	0.7161	0.720	11.918	5.711
PR Cox/ Poisson Robust model	2.928	12.50	0.7152	0.721	11.896	5.845	-43,787.03
PR Binomial regression	2.925	12.62	0.7128	0.722	11.851	6.201
PR Robust binomial regression	2.925	12.62	0.7160	0.719	11.903	5.726	-43,602.83
OR Age adjusted – logistic regression	2.965		0.7184	0.725	12.121
OR Age adjusted – Robust logistic regression	2.965		0.7198	0.723	12.155
Marijuana consumption prevalence (prevalence = 9.6%)
PR MH (age adjusted)	3.407	2.52	0.3121	1.848	6.281
PR Negative Log-Binomial model	3.444	1.42	0.3245	1.823	6.506	3.821
PR Robust Negative Log-Binomial model	3.444	1.42	0.3154	1.856	6.391	1.046	-45,899.8
PR Cox/Poisson model	3.440	1.54	0.3198	1.838	6.438	2.408
PR Cox/ Poisson Robust model	3.440	1.54	0.3159	1.852	6.389	1.203	-45,541.37
PR Binomial regression	3.435	1.69	0.3151	1.852	6.370	0.952
PR Robust binomial regression	3.435	1.69	0.3164	1.847	6.387	1.359	-44,534.91
OR Age adjusted – logistic regression	3.702		0.3246	1.959	6.995
OR Age adjusted – Robust logistic regression	3.702		0.3255	1.956	7.007
Cigarette consumption prevalence (prevalence = 21.3%)
PR MH (age adjusted)	2.209	17.38	0.1913	1.518	3.214
PR Negative Log-Binomial model	2.175	19.22	0.2091	1.443	3.276	8.513
PR Robust Negative Log-Binomial model	2.175	19.22	0.1919	1.493	3.167	0.313	-36,500.12
PR Cox/Poisson model	2.197	18.02	0.1991	1.487	3.247	3.918
Cox/Poisson Robust model	2.197	18.02	0.1901	1.863	3.190	0.631	-35,956.34
Binomial regression	2.225	16.54	0.1885	1.538	3.220	1.485
Robust binomial regression	2.225	16.54	0.1878	1.540	3.215	1.864	-34,252.81
OR Age adjusted – logistic regression	2.536		0.2105	1.679	3.831
OR Age adjusted – Robust logistic regression	2.536		0.2127	1.671	3.848
Lifetime alcohol consumption prevalence (prevalence = 85.7%)
PR MH (age adjusted)	1.241	1.13	0.0361	1.157	1.332
PR Negative Log-Binomial model	1.243	0.97	0.0872	1.048	1.475	58.601
PR Robust Negative Log-Binomial model	1.243	0.97	0.0360	1.158	1.334	0.278	-45,293.58
Cox/ Poisson model	1.242	1.05	0.0668	1.089	1.416	45.958
Cox/Poisson Robust model	1.242	1.05	0.0359	1.157	1.333	0.557	-44,885.75
Binomial regression	1.238	1.37	0.0449	1.153	1.329	19.599
Robust binomial regression	1.238	1.37	0.0450	1.153	1.329	19.778	-41,961.72
Age adjusted OR – logistic regression	2.810		0.1260	2.194	3.597
Age adjusted OR – Robust logistic regression	2.810		0.1248	2.199	3.589
Risk of consumption of psychoactive substances (prevalence = 96.1%)
PR MH (age adjusted)	1.086	0	0.0185	1.047	1.126
PR Negative Log-Binomial model	1.086	0	0.0793	0.930	1.269	76.671
PR Robust Negative Log-Binomial model	1.086	0	0.0186	1.047	1.127	0.538	-47,709.15
PR Cox/Poisson mode	1.086	0	0.0576	0.970	1.216	67.882
Cox/Poisson Robust model	1.086	0	0.0186	1.047	1.127	0.538	-47,583.75
PR Binomial regression	No converge
PR Robust binomial regression	No converge
OR Age adjusted OR – logistic regression	3.462		0.1857	2.406	4.982
OR Age adjusted – Robust logistic regression	3.462		0.1825	2.421	4.951

Models were controlled by grouped age for all cases. Results are shown for the models of negative log-binomial, Cox regression with constant time, log-Poisson, log-binomial compared with MH, and unconditional binary logistic regression model – OR value