Table 4. Analysis of the zero-inflated negative binomial model for the relationship between cancer rate and migratory status, adjusted for sociodemographic variables, including additive and interaction effects. Chile, 2012.

Variable		Coefficient	PR	95%CI	p
Negative binomial model (counting)

Migratory status	Immigrant	0.969	2,6	1.77–3.93	0.000
	Chilean		1
Age	Age	0.033	1.0	1.02–1.05	0.000
	Age	0.0001	1.0	0.99–1.00	0.343
Sex	Woman	0.095	1.1	0.92–1.32	0.308
	Man		1
Health insurance	FONASA	0.388	1.5	1.08–2.01	0.014
	ISAPRE	1.071	2.9	2.15–3.96	0.000
	Other	1.568	4.8	3.51–6.56	0.000
	No insurance
Intersection	Immigrant-FONASA	-2.547	0.8	0.05–0.14	0.000
	Immigrant-ISAPRE	-1.073	0.3	0.20–0.59	0.000
	Immigrant-other	-1.055	0.3	0.17–0.72	0.005
Constant		-7.633	0.001	0.0003–0.0007	0.000

Logistic model (excess zeros)

Migratory status	Immigrant	20.92	1.22x10⁹	0	0.995
	Chilean		1
Age	Age	-0.05	0.9	0.91–0.98	0.004
Sex	Woman	0.2	1.2	0.39–3.80	0.73
	Man		1
Health insurance	Public	-0.13	0.9	0.14–5.47	0.889
	Private	0.4	1.5	0.31–7.24	0.619
	Other	2.24	9.4	1.58–55.92	0.014
	No insurance		1
Constant		-20.82	0.0	0	0.995

PRR: Prevalence Rate Ratio

In(α) = -0.882 (IC95% -1.120 – -0.644), p = 0.000

Log pseudolikelihood: p = 0.000

Test Vuong: z = 1.70; p = 0.0442