Spousal concordance for overall health risk status and preventive service compliance.
OBJECTIVE
In this study we examined spousal concordance for two aggregate measures of health risk status and compliance with preventive service recommendations among 9620 pairs of cohabitating, opposite-sex married couples.


METHODS
Health risk appraisals were the primary data source to measure two outcome variables. Health risk status was compiled from 12 health risks and categorized into three levels (low-, medium-, and high-risk status). Overall preventive service compliance status was estimated by seven age-sex specific preventive service recommendations and dichotomized into lower and higher compliance status. For each of the husband and wife populations, we conducted proportional odds models and logistic regression models to assess spousal concordance for the two aggregate measures respectively. All models were adjusted for household income, one's characteristics (age, race, education, disease burden), and the same set of characteristics and the corresponding outcome variable from the spouse.


RESULTS
A positive correlation within spousal pairs was statistically significant for both health risk status and compliance status (p < .001) based on multivariate modeling. The odds ratios were similar in magnitude for the two spouse populations.


CONCLUSIONS
The analyses showed spousal concordance for aggregate measures of health behaviors. This study also provides some evidence for dominance of husband's education.
Pai
Chih-Wen
CW
University of Michigan Hospitals, Ann Arbor, MI 48109-5485, USA. cwpai@umich.edu <cwpai@umich.edu>
Godboldo-Brooks
Ambyr
A
Edington
Dee W
DW
D000328:Adult; D000367:Age Factors; D004522:Educational Status; D005260:Female; D006304:Health Status; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D016017:Odds Ratio; D010349:Patient Compliance / Q000706:statistics & numerical data*; D011314:Preventive Health Services / Q000706:statistics & numerical data*; D044469:Racial Groups; D012307:Risk Factors; D012959:Socioeconomic Factors; D018454:Spouses / Q000706:statistics & numerical data*; D055815:Young Adult