The influence of locus of control on self-rated health in context of chronic disease: a structural equation modeling approach in a cross sectional study

Table 3 Logistic regressions: Associations between background variables, locus of control, disease burden and self-rated health

	Variables	Nagelkerke r²	B	S.E.	OR	95% CI	P-value
Model 1		0.02
Background	Gender^a		.199	.207	1.220	0.81 to 1.83	0.337
	Age		-.015	.012	.985	0.96 to 1.01	0.199
	Education level		.151	.129	1.163	0.90 to 1.50	0.243
Model 2		0.09
MHLC^b	Internal		.082	.023	1.085	1.04 to 1.14	0.000
	Chance		-.061	.026	.940	0.89 to 0.99	0.017
	Powerful others		-.066	.023	.936	0.90 to 0.98	0.004
Model 3		0.19
Background	Gender^a		.243	.245	1.275	0.79 to 2.06	0.321
	Age		-.007	.014	.993	0.97 to 1.02	0.625
	Education level		.182	.151	1.200	0.89 to 1.61	0.230
MHLC^b	Internal		.063	.025	1.065	1.01 to 1.12	0.012
	Chance		-.038	.029	.963	0.91 to 1.02	0.188
	Powerful others		-.056	.025	.945	0.90 to 1.00	0.026
Diseases	Disease burden		-.416	.080	.660	0.56 to 0.77	0.000

^aMen = 1, women = 2.
^bMultidimensional health locus of control in index-form, ranging from 6 to 36.
Odds ratio (OR), standard error (S.E.) and confidence interval (CI) for the logistic regressions.

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