The Factors Related to Protein-Energy Malnutrition of Institutionalized Residents

• Main Authors: Yi-Ching Chen, 陳怡靜
• Other Authors: Li-Chan Lin
• Format: Others
• Language: zh-TW
• Published: 1999
• Online Access: http://ndltd.ncl.edu.tw/handle/40000234073072821257

碩士 === 國立陽明大學 === 臨床護理研究所 === 87 === The purpose of this study was to investigate the factors related to protein-energy malnutrition on residents in institutions. Subjects were sampled from six intermediate care facilities. Of the 138 residents consenting to participate this study, 105 completed the biochemical data collection necessary for acceptance as valid subjects. Descriptive analysis, one-way ANOVA, Pearson product moment correlation, multiple regression and logistic regression were used for data analysis. The research results revealed the prevalent rate of protein-energy malnutrition at 21.9%, which consisted of 15.2% energy malnutrition, 5.7% protein malnutrition, and 1% mixed type malnutrition.Body mass index(BMI) had a significantly negative correlation with cancer, pressure sore presence, method of feeding and dental status, but had a significantly positive correlation with endocrine-metabolism drugs, cognitive status, self-care ability and feeding ability. Serum albumin concentration had a significant negative correlation with cancer, pressure sores, method of feeding, antibiotics, swallowing ability and dental status, and a significant positive correlation with education level, duration of institutionalization, cognitive status, self-care ability, feeding ability, licensure status of institutions and professional nursing manpower. Malnutrition had a significant positive correlation with cerebral vascular accident, cancer, pressure sore, method of feeding and antibiotics, and a negative correlation with education level, duration of institutionalization, cognitive status, self-care ability, feeding ability, dental status, licensure status of institutions and professional nursing manpower. In multiple regression, BMI and albumin were used as dependent variables, with educational level, cerebral vessel accident, cancer, pressure sore, way of feeding, antibiotics, institutionalized duration, cognitive status, self-care ability, feeding ability, dental status, licensure status of institutions and nursing manpower used as predictors. The research results for the above models yielded a 25.7% explained variance for BMI, and 50.2% explained variance for albumin. In logistic regression, the above predictors were also used to predict malnutrition, but only cancer had significant prediction. To improve institutionalized care, periodically assessing residents'' nutritional status is needed. Further studies are needed to develop practical methods to reduce the rate of malnutrition in institutions.