Skip to main content
. Author manuscript; available in PMC: 2013 Mar 14.
Published in final edited form as: J Pain. 2008 May 23;9(8):750–758. doi: 10.1016/j.jpain.2008.03.007

Table 4.

Model for tooth pain and pain impact

Variables Pain intensity
B (SE)		 Depression
B (SE)		 Eating
B (SE)		 Sleep difficulty
B (SE)
    Block1 - Block1 - Demographic and economic
Gender .570 (.222)** .357 (.308)* .650 (.273)* .962 (.314)*
Age .046 (.130) .855 (.184)** −.278 (.164) .464 (.189)
Dental Insurance −.304 (.287) −.859 (.337)* −.625 (.296)* −.599 (.309)
Financial status −.187 (.083)* −.410 (.133)** −.245 (.114)* −.559 (.201)**
Census tract income −.134 (.064)* −.336 (.100)** −.172 (.080)* −.354 (.091)**
    Block2 - Acculturation
Language −.441 (.121)** −.680 (.180)** −.129 (.148) −.506 (.175)**
Nativity .206 (.104)* −.107 (.154) .265 (.138) .292 (.148)*
Identification .074 (.107) −.205 (.147) .028 (.131) .097 (.155)

Note:

*

p≤.05,

**

p≤.01, n=746.

Positive coefficients for the acculturation factors should be interpreted to mean an increase in acculturation is associated with an increase in the value of the outcome variable.