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. Author manuscript; available in PMC: 2014 Sep 27.
Published in final edited form as: J Cross Cult Gerontol. 2013 Sep;28(3):251–266. doi: 10.1007/s10823-013-9202-9

Table 3.

GEE modeling coefficients predicting change in health status over 5 waves in the HEPESE by border/non-border residence

Any ADL Any IADL Diabetes Heart problems Stroke Hypertension Hip fracture Cancer
Total
 Border (1=yes) 1.52 (.000) 1.07 (.392) 1.14 (.189) 1.08 (.590) .966 (.810) 1.14 (.119) 1.18 (.450) .824 (.203)
 Model 2 1.43 (.000) 1.03 (.663) 1.10 (.336) 1.07 (.665) .917 (.540) 1.10 (.231) 1.20 (.382) .828 (.210)
 Model 3 1.43 (.000) 1.04 (.605) 1.09 (.371) 1.08 (.627) .911 (.522) 1.10 (.266) 1.19 (.405) .833 (.229)
 Model 4 1.46 (.000) 1.07 (.456) 1.14 (.222) 1.16 (.382) .997 (.983) 1.11 (.254) 1.27 (.255) .870 (.376)

all models adjusted for sex, age, marital status, income and nativity

Model 1 Adjusted for demographics

Model 2=Model 1+health behaviors

Model 3=Model 2+age at immigration

Model 4=Model 3+% poverty, % high school graduate, Mexican American density, % speak Spanish