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Predictors of nursing home admission in the older population in Belgium: a longitudinal follow-up of health interview survey participants
BACKGROUND: This study examines predictors of nursing home admission (NHA) in Belgium in order to contribute to a better planning of the future demand for nursing home (NH) services and health care resources. METHODS: Data derived from the Belgian 2013 health interview survey were linked at individu...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9585772/ https://www.ncbi.nlm.nih.gov/pubmed/36266620 http://dx.doi.org/10.1186/s12877-022-03496-4 |
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author | Berete, Finaba Demarest, Stefaan Charafeddine, Rana De Ridder, Karin Vanoverloop, Johan Van Oyen, Herman Bruyère, Olivier Van der Heyden, Johan |
author_facet | Berete, Finaba Demarest, Stefaan Charafeddine, Rana De Ridder, Karin Vanoverloop, Johan Van Oyen, Herman Bruyère, Olivier Van der Heyden, Johan |
author_sort | Berete, Finaba |
collection | PubMed |
description | BACKGROUND: This study examines predictors of nursing home admission (NHA) in Belgium in order to contribute to a better planning of the future demand for nursing home (NH) services and health care resources. METHODS: Data derived from the Belgian 2013 health interview survey were linked at individual level with health insurance data (2012 tot 2018). Only community dwelling participants, aged ≥65 years at the time of the survey were included in this study (n = 1930). Participants were followed until NHA, death or end of study period, i.e., December 31, 2018. The risk of NHA was calculated using a competing risk analysis. RESULTS: Over the follow-up period (median 5.29 years), 226 individuals were admitted to a NH and 268 died without admission to a NH. The overall cumulative risk of NHA was 1.4, 5.7 and 13.1% at respectively 1 year, 3 years and end of follow-up period. After multivariable adjustment, higher age, low educational attainment, living alone and use of home care services were significantly associated with a higher risk of NHA. A number of need factors (e.g., history of falls, suffering from urinary incontinence, depression or Alzheimer’s disease) were also significantly associated with a higher risk of NHA. On the contrary, being female, having multimorbidity and increased contacts with health care providers were significantly associated with a decreased risk of NHA. Perceived health and limitations were both significant determinants of NHA, but perceived health was an effect modifier on limitations and vice versa. CONCLUSIONS: Our findings pinpoint important predictors of NHA in older adults, and offer possibilities of prevention to avoid or delay NHA for this population. Practical implications include prevention of falls, management of urinary incontinence at home and appropriate and timely management of limitations, depression and Alzheimer’s disease. Focus should also be on people living alone to provide more timely contacts with health care providers. Further investigation of predictors of NHA should include contextual factors such as the availability of nursing-home beds, hospital beds, physicians and waiting lists for NHA. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12877-022-03496-4. |
format | Online Article Text |
id | pubmed-9585772 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-95857722022-10-22 Predictors of nursing home admission in the older population in Belgium: a longitudinal follow-up of health interview survey participants Berete, Finaba Demarest, Stefaan Charafeddine, Rana De Ridder, Karin Vanoverloop, Johan Van Oyen, Herman Bruyère, Olivier Van der Heyden, Johan BMC Geriatr Research BACKGROUND: This study examines predictors of nursing home admission (NHA) in Belgium in order to contribute to a better planning of the future demand for nursing home (NH) services and health care resources. METHODS: Data derived from the Belgian 2013 health interview survey were linked at individual level with health insurance data (2012 tot 2018). Only community dwelling participants, aged ≥65 years at the time of the survey were included in this study (n = 1930). Participants were followed until NHA, death or end of study period, i.e., December 31, 2018. The risk of NHA was calculated using a competing risk analysis. RESULTS: Over the follow-up period (median 5.29 years), 226 individuals were admitted to a NH and 268 died without admission to a NH. The overall cumulative risk of NHA was 1.4, 5.7 and 13.1% at respectively 1 year, 3 years and end of follow-up period. After multivariable adjustment, higher age, low educational attainment, living alone and use of home care services were significantly associated with a higher risk of NHA. A number of need factors (e.g., history of falls, suffering from urinary incontinence, depression or Alzheimer’s disease) were also significantly associated with a higher risk of NHA. On the contrary, being female, having multimorbidity and increased contacts with health care providers were significantly associated with a decreased risk of NHA. Perceived health and limitations were both significant determinants of NHA, but perceived health was an effect modifier on limitations and vice versa. CONCLUSIONS: Our findings pinpoint important predictors of NHA in older adults, and offer possibilities of prevention to avoid or delay NHA for this population. Practical implications include prevention of falls, management of urinary incontinence at home and appropriate and timely management of limitations, depression and Alzheimer’s disease. Focus should also be on people living alone to provide more timely contacts with health care providers. Further investigation of predictors of NHA should include contextual factors such as the availability of nursing-home beds, hospital beds, physicians and waiting lists for NHA. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12877-022-03496-4. BioMed Central 2022-10-20 /pmc/articles/PMC9585772/ /pubmed/36266620 http://dx.doi.org/10.1186/s12877-022-03496-4 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Berete, Finaba Demarest, Stefaan Charafeddine, Rana De Ridder, Karin Vanoverloop, Johan Van Oyen, Herman Bruyère, Olivier Van der Heyden, Johan Predictors of nursing home admission in the older population in Belgium: a longitudinal follow-up of health interview survey participants |
title | Predictors of nursing home admission in the older population in Belgium: a longitudinal follow-up of health interview survey participants |
title_full | Predictors of nursing home admission in the older population in Belgium: a longitudinal follow-up of health interview survey participants |
title_fullStr | Predictors of nursing home admission in the older population in Belgium: a longitudinal follow-up of health interview survey participants |
title_full_unstemmed | Predictors of nursing home admission in the older population in Belgium: a longitudinal follow-up of health interview survey participants |
title_short | Predictors of nursing home admission in the older population in Belgium: a longitudinal follow-up of health interview survey participants |
title_sort | predictors of nursing home admission in the older population in belgium: a longitudinal follow-up of health interview survey participants |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9585772/ https://www.ncbi.nlm.nih.gov/pubmed/36266620 http://dx.doi.org/10.1186/s12877-022-03496-4 |
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