Premium
Malnutrition in a home‐living older population: prevalence, incidence and risk factors. A prospective study
Author(s) -
Johansson Yvonne,
BachrachLindström Margareta,
Carstensen John,
Ek AnnaChristina
Publication year - 2009
Publication title -
journal of clinical nursing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.94
H-Index - 102
eISSN - 1365-2702
pISSN - 0962-1067
DOI - 10.1111/j.1365-2702.2008.02552.x
Subject(s) - malnutrition , medicine , anthropometry , depression (economics) , quality of life (healthcare) , geriatric depression scale , gerontology , incidence (geometry) , environmental health , activities of daily living , logistic regression , risk factor , cross sectional study , population , physical therapy , anxiety , psychiatry , nursing , depressive symptoms , physics , pathology , optics , economics , macroeconomics
Aims and objectives. To prospectively investigate and describe the prevalence and incidence of malnutrition among home‐living older people, related to demographic and medical factors, self‐perceived health and health‐related quality of life. Another aim was to find predictors for developing risk of malnutrition. Background. Risk factors for malnutrition have previously been identified as diseases, several medications, low functional status, symptoms of depression and inadequate nutrient intake. Most studies are cross‐sectionally performed at hospitals or in nursing care settings. Design. A prospective study with a sample of 579 home‐living older people, randomly selected from a local national register. Examinations were performed at baseline and yearly follow‐ups two to four times. Method. Questionnaires validated and tested for reliability, to detect risk of malnutrition (Mini Nutritional Assessment), symptoms of depression (Geriatric Depression Scale‐20), cognitive function (Mini Mental State Examination), health‐related quality of life (Nottingham Health Profile), well‐being (Philadelphia Geriatric Center Multilevel Assessment Instrument) self‐perceived health, demographic factors, anthropometry and biochemical examinations. Predictors were searched for through multiple logistic regression analysis with the MNA as dependent factor. Results. The prevalence of risk for malnutrition was 14·5%, according to the MNA. Two risk factors for malnutrition were lower handgrip strength and lower self‐perceived health. The incidence of risk for malnutrition at follow‐ups was between 7·6% and 16·2%. Predictors for developing malnutrition were higher age, lower self‐perceived health and more symptoms of depression. Men with symptoms of depression had a higher risk of developing malnutrition. Conclusion. Lower self‐perceived health had the highest power to predict risk for malnutrition, with increased number of depression symptoms and higher age as second and third predictors. Relevance to clinical practice. A regular and combined assessment using the Mini Nutrition Assessment, Geriatric Depression Scale‐20 and self‐perceived health as a base for identifying people in need, is one way to prevent the development of malnutrition.