Korean J Adult Nurs.  2015 Jun;27(3):273-282. 10.7475/kjan.2015.27.3.273.

Predictors of Self-care Behaviors among Elderly with Hypertension using Quantile Regression Method

Affiliations
  • 1College of Nursing, Keimyung University, Daegu, Korea.
  • 2Department of Nursing, Pukyong National University, Busan, Korea. euna-pak@hanmail.net

Abstract

PURPOSE
The objective of this study was to identify the predictors of self-care behaviors among elderly patients with hypertension using quantile regression method.
METHODS
A total of 253 elderly patients diagnosed with hypertension was recruited via 3 different medical clinics for the study. The quantile regression and a liner regression was conducted using Stata 12.0 program by analyzing predictors of self-care behaviors.
RESULTS
In the ordinary least square, self-efficacy, period of disease, and education level explained 42% of the variance in self-care activities. In the quantile regression, affecting predictors of self-care behaviors were self-efficacy for all quantiles, the period of disease for from 60% quantile to 90% quantile, education level for 20%, 30%, and 50% quantiles, economic status for 10%, 50%, and 60% quantiles, age for 10%, 70% quantiles, fatigue for 10% quantile, knowledge about hypertension for 10% and 20% quantiles, and depression for 30% and 40% quantiles.
CONCLUSION
The affecting predictors of self-care behaviors among elderly with hypertension were different from the level of self-care behaviors. These results indicated the significance in assessing predictors according to the level of self-care behaviors when clinical nurses examine the patients' health behaviors and plan any intervention strategies. Specially, education level and knowledge about hypertension were the significant predictors of self-care activities for low quantiles. Clinical nurses may promote self-care activities of the given population though health education programs.


MeSH Terms

Aged*
Depression
Education
Fatigue
Health Behavior
Health Education
Humans
Hypertension*
Self Care*

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