Binary logistic regression analysis for GI medical conditions to predict risk factors.

Table 4: Binary logistic regression analysis for GI medical conditions to predict risk factors.

Binary logistic regression analysis	B	Sig.	Odd ratio	95% CI for OR
Binary logistic regression analysis	B	Sig.	Odd ratio	Lower	Upper
likelihood of having one or more GID^*
SRH/Excellent to good (Ref.)	2.05	0.000	7.79	3.56	17.01
ChE+NChE scale (higher is bad)	0.39	0.008	1.47	1.11	1.96
Arab vs. Chaldean (Ref)	0.93	0.004	2.53	1.34	4.80
Years in US [Lowest = 2 years, Highest = 46 years]	0.04	0.022	1.04	1.01	1.08
Likelihood of having one or more GI disease^*
ChE+NChE scale (higher is bad)	0.48	0.000	1.62	1.25	2.11
SRH/Excellent to good (Ref.)	0.91	0.008	2.47	1.27	4.83
Employed vs. Unemployed (Ref.)	0.85	0.020	2.34	1.15	4.77
Female vs. Male (Ref.)	0.75	0.028	2.12	1.08	4.14
Years in US [Lowest = 2 years, Highest = 46 years]	0.06	0.010	1.06	1.01	1.10
Likelihood of having one or more GI Functional disorders^*
ChE+NChE scale (higher is bad)	0.40	0.000	1.48	1.19	1.85
Age in year	-0.04	0.049	0.96	0.93	1.00
SRH/Excellent to good (Ref.)	0.62	0.039	1.87	1.03	3.38
Likelihood of having one or more GI Psychosomatic symptoms^*
SRH/Excellent to good (Ref.)	2.09	0.000	8.10	4.23	15.51
Female vs. Male (Ref.)	0.62	0.049	1.86	1.00	3.44
Single vs. Married (Ref.)	-0.78	0.056	0.46	0.20	1.02

Variables enter the equation in each of the four tests above were as follows: Ethnicity, age, gender, marital status, employment status, health insurance, years in US, smoking status, total of ChE+NChE and SRH.

Note: Only significant results were presented in each analysis.