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van Nie-Visser, NC; Meijers, J; Schols, J; Lohrmann, C; Bartholomeyczik, S; Spreeuwenberg, M; Halfens, R.
Which characteristics of nursing home residents influence differences in malnutrition prevalence? An international comparison of The Netherlands, Germany and Austria.
Br J Nutr. 2014; 111(6):1129-1136 [OPEN ACCESS]
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Autor/innen der Med Uni Graz:
Lohrmann Christa

Dimensions Citations:

Plum Analytics:
Prevalence rates of malnutrition vary considerably internationally, partly due to differences in measurement methodology and instruments. In the present study, the same measurement methodology and instruments were used in The Netherlands, Germany and Austria. The aim of the present study was to investigate whether resident characteristics influence possible differences in malnutrition prevalence between countries. The study followed a cross-sectional, multi-centre design that measured malnutrition in nursing home residents from The Netherlands, Germany and Austria. Resident data were gathered using a standardised questionnaire. Malnutrition was operationalised using BMI, unintentional weight loss and nutritional intake. Data were analysed using an association model. The prevalence rates of malnutrition in The Netherlands, Germany and Austria were 18·3, 20·1 and 22·5 %, respectively. The multivariate generalised estimating equation (GEE) logistic regression analysis showed that sex, age, care dependency, the mean number of diseases and some specific diseases were influencing factors for whether the resident was malnourished or not. The OR of malnutrition in the three countries declined after including the influencing factors resulting from the multivariate GEE analysis. The present study reveals that differences in the prevalence rates of malnutrition in nursing homes in The Netherlands, Germany and Austria are influenced by different resident characteristics. Since other country-related factors could also play an important role in influencing differences in the prevalence rates of malnutrition between the countries (structural and process factors of malnutrition care policy). We recommend the investigation of these factors in future studies.
Find related publications in this database (using NLM MeSH Indexing)
Aged -
Aged, 80 and over -
Aged, 80 and over - epidemiology
Cross-Sectional Studies -
Female -
Female - epidemiology
Health Status -
Homes for the Aged -
Humans -
Length of Stay -
Logistic Models -
Male -
Malnutrition - diagnosis Malnutrition - epidemiology
Malnutrition - epidemiology
Nursing Homes -
Odds Ratio -
Questionnaires -
Sex Factors -

Find related publications in this database (Keywords)
Resident characteristics
Nursing homes
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