Table 2.

Linear regression models with well-being predicting HbA1c as outcome^a

	Model 1 Demographics			Model 2 +Health Factors			Model 3 +Negative Affect
	B(SE)	β	p	B(SE)	β	p	B(SE)	β	p
Age	.014(.002)	.39	<.001	.013(.002)	.36	<.001	.013(.002)	.36	<.001
Gender (1=Female)	−.003(.004)	−.04	.39	.002(.004)	.02	.69	.002(.004)	.02	.68
Education (years)	.001(.002)	.04	.51	.002(.002)	.05	.31	.002(.002)	.05	.31
BMI				.004(.002)	.11	.021	.004(.002)	.11	.024
Current Smokingb				.001(.004)	.01	.77	.001(.004)	.01	.76
Alcohol (drinks/wk)				.000(.002)	−.01	.89	.000(.002)	−.01	.88
Exerciseb				.001(.001)	.03	.52	.001(.001)	.03	.53
Healthy eating index				−.003(.002)	−.07	.15	−.003(.002)	−.07	.15
Subjective sleep quality				−.001(.002)	−.02	.59	−.001(.002)	−.02	.63
Chronic Conditions				.000(.002)	−.01	.77	.000(.002)	−.01	.86
Anti-diabetic Medication useb				.097(.009)	.45	<.001	.097(.009)	.45	<.001
Negative Affect							.001(.002)	−.01	.84
Eudaimonic Well-being
Personal Growth	−.003(.002)	−.10	.058	−.001(.002)	−.02	.65	−.001(.002)	−.02	.61
Purpose in Life	−.005(.002)	−.14	.005	−.004(.002)	−.10	.021	−.004(.002)	−.11	.018
Ikigaib	−.006(.004)	−.08	.13	−.005(.004)	−.06	.16	−.005(.004)	−.07	.16
Hedonic Well-being
Positive Affect	.001(.002)	.04	.41	.002(.002)	.05	.26	.002(.002)	.06	.25
Life Satisfaction	−.001(.001)	−.04	.45	−.001(.001)	−.04	.66	−.001(.001)	−.02	.66
Interdependent Well-being
Gratitude	−.002(.002)	−.05	.32	.000(.002)	.00	.97	−.000(.002)	.00	.99
Peaceful Disengagement	.005(.002)	.13	.009	.005(.002)	.13	.003	.005(.002)	.13	.003
Adjustment	.001(.002)	.02	.73	.000(.002)	.00	.94	.000(.002)	.01	.91

Note. HbA1c and alcohol were log10 transformed. All continuous predictor variables are z-scored.

^aEach psychological well-being variable was entered in a separate model.

^b1=yes.