Healthy Days, Health Satisfaction and Satisfaction with the Overall Quality of Life

• Published in: Social indicators research Vol. 59; no. 3; pp. 321 - 338
• Main Authors: Michalos, Alex C., Zumbo, Bruno D.
• Format: Journal Article
• Language: English
• Published: Dordrecht Kluwer Academic Publishers 01.09.2002; Springer; Springer Nature B.V
• Subjects: Correlation; Disease control; Health; Health Conditions; Health status; Health surveys; History, theory and methodology; Life Satisfaction; Mental Health; Methodology; Physical Health; Preventive medicine; Public health; Quality of Life; Questionnaires; Raw Scores; Research methods; Satisfaction; Significance level; Social indicators; Social research; Sociology; Statistical analysis; Statistical variance; Structural Equation Models; Surveillance; Surveys; U.S.A; United States of America; Variables; Variance; United States Of America; Measurement; Behaviour; Quantitative research; Health; Social Indicator; Satisfaction; Perception; Statistics
• ISSN: 0303-8300; 1573-0921
• DOI: 10.1023/A:1019601213926

In this note we report results of 6 surveys using the United States Centers for Disease Control and Prevention indicators of health status, taken from the Behavioral Risk Factor Surveillance System. Generally speaking, we found that the CDC healthy days variables could play a useful role in survey research aimed at assessing the impact of measured health status on people's satisfaction with their own health and with the overall quality of their lives. More precisely, using stepwise regressions we found: (1) The three healthy days variables explained from 16 to 27 percent of the variance in General Health scores. The limited activity days variable remained as a significant predictor in only one of the six regressions and the not good physical health days variable was most influential in every sample. (2) The three healthy days variables explained from 19 to 32 percent of the variance in health satisfaction scores, and the not good physical health days variable was again most influential in every sample. (3) The three healthy days variables explained from 12 to 39 percent of the variance in quality-of-life satisfaction scores, with the not good mental health variable most influential in every sample. (4) The four CDC variables together explained from 40 to 55 percent of the variance in health satisfaction scores, with the General Health variable always dominating the set of predictors by a fairly wide margin. (5) The four CDC variables together explained from 17 to 28 percent of the variance in quality-of-life satisfaction scores, with the General Health variable most influential in three samples and the not good mental health variable most influential in the other three. (6) When the four CDC variables plus the health satisfaction variable were used as potential predictors, we were able to explain from 29 to 40 percent of the variance in quality-of-life satisfaction scores. In every sample, the General Health and limited activity days variables had no significant impact. (7) Using structural equation modeling, we found General Health does not have a direct effect on satisfaction with the overall quality of life but rather only an indirect effect through health satisfaction. The General Health, not good physical health, and not good mental health days variables account for 51% of the variation in health satisfaction, and health satisfaction, not good physical health and not good mental health days variables account for 30% of the variation in satisfaction with the overall quality of life.