Table 4.

Hierarchical multiple regression analysis for variables predicting wellbeing and happiness.

Variable	Well-Being				Happiness
	b	β	t	R2	b	β	t	R2
Model 1				0.035				0.087 ***
Age	0.067	0.063	1.139		−0.466	−0.181	−3.352 ***
Sex	−0.860	−0.065	−1.228		−0.143	−0.098	−1.893
Lives with relatives	1.815	0.138	2.435 **		5.447	0.170	3.085 ***
Education	0.078	0.009	0.160		0.331	0.016	0.285
Income	1.148	0.082	1.395		−1.156	−0.034	−0.593
Model 2				0.171 ***				0.260 ***
Age	0.161	0.153	2.793 **		−0.221	−0.086	−1.663
Sex	−0.509	−0.039	−0.760		−1.800	−0.056	−1.167
Lives with relatives	1.273	0.097	1.732		2.689	0.084	1.590
Education	−0.763	−0.088	−1.573		−1.183	−0.056	−1.059
Income	1.154	0.082	1.488		−0.947	−0.028	−0.530
Health	0.125	0.191	3.395 ***		0.218	0.137	2.568 **
Social integration	0.190	0.120	2.083 *		1.007	0.260	4.790 ***
Activity level	0.467	0.065	1.146 *		3.803	0.216	4.056 ***
Leisure activities	0.228	0.143	2.159		0.269	0.069	1.107
Functional skills	0.005	0.002	0.041		−0.220	−0.044	−0.776
Environmental quality	0.623	0.137	2.712 **		0.752	0.068	1.424
Model Summary	Well-Being				Happiness
	R		R2	F	R		R2	F
Model 1	0.186 a		0.035	2.473 *	0.295 b		0.087	6.568 ***
Model 2	0.414 a		0.171	6.359 ***	0.510 b		0.260	10.845 ***

Notes. ^a Dependent variable: Well-Being. ^b Dependent variable: Happiness. * p < 0.05; ** p < 0.01; *** p < 0.001.