Determinants of dental user groups among an elderly, low-income population.
OBJECTIVE
We test whether or not there are differences for selected variables among five dental user groups and one nondental group within an elderly, low-income population.


METHODS
We used ten years of Medicare Part B claims data from the Cincinnati Health Department for all clinic users 62 years of age and older who participated in the Municipal Health Services Program.


METHODS
A polychotomous logistic regression model determined the ability to differentiate between the groups for each of the selected variables, controlling for race. Next, a polychotomous stepwise logistic regression was used in finding a multivariate model for determining dental user group membership. Logistic regression was used to ascertain which variables were discriminators between any two types of dental users.


RESULTS
Mean number of medical visits, mean number of prescriptions filled, and race are determinants of group membership, with the nondental group having more medical visits and more likely to be white. Although year of birth cohort is statistically significant in determining dental user types, the direction of effect is not constant across the comparisons. However, the relative risk for being in the two complete denture groups, compared to both compliant subgroups, increases with each older cohort.


CONCLUSIONS
Higher levels of medical use may "crowd out" dental use, even when it is without user cost, either because the medical problems are treated as a higher priority, or because dealing with medical needs leaves too little perceived time or energy to seek dental care. Even in a low-income population seeking dental care, there appears to be a birth cohort effect with a decline in the younger elderly who require two complete dentures.
Kuthy
R A
RA
Ohio State University College of Dentistry, Columbus 43210-1241, USA.
Strayer
M S
MS
Caswell
R J
RJ
D000368:Aged; D016321:Dental Care for Aged / Q000191:economics / Q000706:statistics & numerical data*; D003824:Denture, Complete / Q000706:statistics & numerical data; D003829:Denture, Partial / Q000706:statistics & numerical data; D005260:Female; D017048:Health Care Costs / Q000706:statistics & numerical data; D006801:Humans; D016015:Logistic Models; D008297:Male; D016345:Medicare Part B / Q000706:statistics & numerical data*; D008875:Middle Aged; D009820:Ohio; D010349:Patient Compliance; D011203:Poverty / Q000191:economics / Q000706:statistics & numerical data; D012306:Risk; D014481:United States; D014505:Urban Population