title: Predictors of adherence with self-care guidelines among persons with type 2 diabetes: results from a logistic regression tree analysis.
abstract: Type 2 diabetes is known to contribute to health disparities in the U.S. and failure to adhere to recommended self-care behaviors is a contributing factor. Intervention programs face difficulties as a result of patient diversity and limited resources. With data from the 2005 Behavioral Risk Factor Surveillance System, this study employs a logistic regression tree algorithm to identify characteristics of sub-populations with type 2 diabetes according to their reported frequency of adherence to four recommended diabetes self-care behaviors including blood glucose monitoring, foot examination, eye examination and HbA1c testing. Using Andersen's health behavior model, need factors appear to dominate the definition of which sub-groups were at greatest risk for low as well as high adherence. Findings demonstrate the utility of easily interpreted tree diagrams to design specific culturally appropriate intervention programs targeting sub-populations of diabetes patients who need to improve their self-care behaviors. Limitations and contributions of the study are discussed.
authors.affiliation: Scripps Gerontology Center, Miami University, Oxford, OH, 45056, USA, yamasht@muohio.edu.
authors.forename: Takashi
authors.initials: T
authors.lastname: Yamashita
authors.forename: Cary S
authors.initials: CS
authors.lastname: Kart
authors.forename: Douglas A
authors.initials: DA
authors.lastname: Noe
mesh_terms: D040343:Behavioral Risk Factor Surveillance System; D003924:Diabetes Mellitus, Type 2 / Q000523:psychology*; D005260:Female; D015438:Health Behavior; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D010349:Patient Compliance / Q000523:psychology* / Q000706:statistics & numerical data; D012648:Self Care / Q000523:psychology* / Q000592:standards