title: Targeting risk for unmet need: not enough help versus no help at all.
abstract: OBJECTIVE
  This study examined factors associated with unmet need for care among persons aged 18 and older who need help with daily living tasks. The analysis focused on two types of unmet need: not enough (or inadequate) help and no help at all.
  
  
  METHODS
  The authors used multinomial logistic regression to examine differences between persons with long-term care needs who (a) had all their needs met; (b) received inadequate help; and (c) received no help at all. Data were from the Adult Followback to the National Health Interview Survey on Disability (NHIS-D) for 1994 and 1995.
  
  
  RESULTS
  The determinants of inadequate care versus no care differed with respect to age, gender, level of impairment, and insurance status. Whereas age and gender were important in determining inadequate care, insurance coverage and availability of social support were key factors related to a situation of no care.
  
  
  CONCLUSIONS
  The present study demonstrates that the characteristics of groups reporting inadequate care versus no care, and the factors associated with these situations, are quite different. Nevertheless, the most important demographic risk factors for both types of unmet need mirror demographic groups currently on the increase in the U.S. population.
authors.affiliation: Population Studies and Training Center, Brown University, Providence, RI 02812, USA.
authors.forename: J C
authors.initials: JC
authors.lastname: Lima
authors.forename: S M
authors.initials: SM
authors.lastname: Allen
mesh_terms: D000203:Activities of Daily Living / Q000145:classification*; D000293:Adolescent; D000328:Adult; D000368:Aged; D004185:Disability Evaluation; D006233:Persons with Disabilities / Q000706:statistics & numerical data*; D005260:Female; D006801:Humans; D019458:Insurance Coverage / Q000706:statistics & numerical data; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D020380:Needs Assessment / Q000706:statistics & numerical data*; D012307:Risk Factors; D014481:United States / Q000453:epidemiology