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. 2014 Jul 30;9:30. doi: 10.1186/1747-597X-9-30

Table 2.

Negative binomial regression on number of barriers to treatment in Mexico, 2011

Variable IRR SE p 95% C.I.
Traveling to U.S.a
0.992
0.164
0.961
0.717, 1.373
Transnationala
1.015
0.143
0.917
0.770, 1.337
Drug dependence
1.937
0.249
0.000
1.504, 2.494
Traveling to U.S. x femaleb
0.311
0.115
0.002
0.150, 0.643
Transnational x femaleb
0.656
0.172
0.109
0.392, 1.099
Drug dependence x femaleb
1.084
0.610
0.886
0.358, 3.276
Female
1.014
0.173
0.935
0.725, 1.417
Age
0.993
0.005
0.875
0.983, 1.003
Less than High school
1.085
0.155
0.986
0.818, 1.437
Region c
 
 
 
 
North central
1.657
0.381
0.028
1.055, 2.602
Northwest
1.618
0.383
0.043
1.016, 2.576
Northeast
2.522
0.557
0.000
1.634, 3.892
West
3.364
0.794
0.000
2.116, 5.348
Central
1.989
0.409
0.001
1.327, 2.980
South central
2.386
0.625
0.001
1.426, 3.992
South 2.008 0.667 0.036 1.046, 3.857

Note. CI, confidence interval; IRR, incidence rate ratio; SE, standard error. IRRs can be interpreted as the estimated rate ratio for a 1-unit increase in the independent variable, given the other variables are held constant in the model. For example, compared to non-dependent, individuals reporting drug dependence are associated with an increased ratio for number of barriers of IRR = 1.937, while holding all other variables in the model constant. The corresponding p-value is less than 0.001.

aMexicans who have not visited the United States was reference category.

bInteraction term.

cMexico City was reference category.

*p < .05, **p < .01, ***p < .001.