Cargando…

The Montreal Cognitive Assessment: Normative Data from a Large Swedish Population-Based Cohort

BACKGROUND: The Montreal Cognitive Assessment (MoCA) has a high sensitivity for detecting cognitive dysfunction. Swedish normative data does not exist and international norms are often derived from populations where cognitive impairment has not been screened for and not been thoroughly assessed to e...

Descripción completa

Detalles Bibliográficos
Autores principales: Borland, Emma, Nägga, Katarina, Nilsson, Peter M., Minthon, Lennart, Nilsson, Erik D., Palmqvist, Sebastian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: IOS Press 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5545909/
https://www.ncbi.nlm.nih.gov/pubmed/28697562
http://dx.doi.org/10.3233/JAD-170203
_version_ 1783255503875342336
author Borland, Emma
Nägga, Katarina
Nilsson, Peter M.
Minthon, Lennart
Nilsson, Erik D.
Palmqvist, Sebastian
author_facet Borland, Emma
Nägga, Katarina
Nilsson, Peter M.
Minthon, Lennart
Nilsson, Erik D.
Palmqvist, Sebastian
author_sort Borland, Emma
collection PubMed
description BACKGROUND: The Montreal Cognitive Assessment (MoCA) has a high sensitivity for detecting cognitive dysfunction. Swedish normative data does not exist and international norms are often derived from populations where cognitive impairment has not been screened for and not been thoroughly assessed to exclude subjects with dementia or mild cognitive impairment. OBJECTIVE: To establish norms for MoCA and develop a regression-based norm calculator based on a large, well-examined cohort. METHODS: MoCA was administered on 860 randomly selected elderly people from a population-based cohort from the EPIC study. Cognitive dysfunction was screened for and further assessed at a memory clinic. After excluding cognitively impaired participants, normative data was derived from 758 people, aged 65–85. RESULTS: MoCA cut-offs (–1 to –2 standard deviations) for cognitive impairment ranged from <25 to <21 for the lowest educated and <26 to <24 for the highest educated, depending on age group. Significant predictors for MoCA score were age, sex and level of education. CONCLUSION: We present detailed normative MoCA data and cut-offs according to the DSM-5 criteria for cognitive impairment based on a large population-based cohort of elderly individuals, screened and thoroughly investigated to rule out cognitive impairment. Level of education, sex, and age should be taken in account when evaluating MoCA score, which is facilitated by our online regression-based calculator that provide percentile and z-score for a subject’s MoCA score.
format Online
Article
Text
id pubmed-5545909
institution National Center for Biotechnology Information
language English
publishDate 2017
publisher IOS Press
record_format MEDLINE/PubMed
spelling pubmed-55459092017-08-16 The Montreal Cognitive Assessment: Normative Data from a Large Swedish Population-Based Cohort Borland, Emma Nägga, Katarina Nilsson, Peter M. Minthon, Lennart Nilsson, Erik D. Palmqvist, Sebastian J Alzheimers Dis Research Article BACKGROUND: The Montreal Cognitive Assessment (MoCA) has a high sensitivity for detecting cognitive dysfunction. Swedish normative data does not exist and international norms are often derived from populations where cognitive impairment has not been screened for and not been thoroughly assessed to exclude subjects with dementia or mild cognitive impairment. OBJECTIVE: To establish norms for MoCA and develop a regression-based norm calculator based on a large, well-examined cohort. METHODS: MoCA was administered on 860 randomly selected elderly people from a population-based cohort from the EPIC study. Cognitive dysfunction was screened for and further assessed at a memory clinic. After excluding cognitively impaired participants, normative data was derived from 758 people, aged 65–85. RESULTS: MoCA cut-offs (–1 to –2 standard deviations) for cognitive impairment ranged from <25 to <21 for the lowest educated and <26 to <24 for the highest educated, depending on age group. Significant predictors for MoCA score were age, sex and level of education. CONCLUSION: We present detailed normative MoCA data and cut-offs according to the DSM-5 criteria for cognitive impairment based on a large population-based cohort of elderly individuals, screened and thoroughly investigated to rule out cognitive impairment. Level of education, sex, and age should be taken in account when evaluating MoCA score, which is facilitated by our online regression-based calculator that provide percentile and z-score for a subject’s MoCA score. IOS Press 2017-07-29 /pmc/articles/PMC5545909/ /pubmed/28697562 http://dx.doi.org/10.3233/JAD-170203 Text en © 2017 – IOS Press and the authors. All rights reserved https://creativecommons.org/licenses/by-nc/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution Non-Commercial (CC BY-NC 4.0) License (https://creativecommons.org/licenses/by-nc/4.0/) , which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Borland, Emma
Nägga, Katarina
Nilsson, Peter M.
Minthon, Lennart
Nilsson, Erik D.
Palmqvist, Sebastian
The Montreal Cognitive Assessment: Normative Data from a Large Swedish Population-Based Cohort
title The Montreal Cognitive Assessment: Normative Data from a Large Swedish Population-Based Cohort
title_full The Montreal Cognitive Assessment: Normative Data from a Large Swedish Population-Based Cohort
title_fullStr The Montreal Cognitive Assessment: Normative Data from a Large Swedish Population-Based Cohort
title_full_unstemmed The Montreal Cognitive Assessment: Normative Data from a Large Swedish Population-Based Cohort
title_short The Montreal Cognitive Assessment: Normative Data from a Large Swedish Population-Based Cohort
title_sort montreal cognitive assessment: normative data from a large swedish population-based cohort
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5545909/
https://www.ncbi.nlm.nih.gov/pubmed/28697562
http://dx.doi.org/10.3233/JAD-170203
work_keys_str_mv AT borlandemma themontrealcognitiveassessmentnormativedatafromalargeswedishpopulationbasedcohort
AT naggakatarina themontrealcognitiveassessmentnormativedatafromalargeswedishpopulationbasedcohort
AT nilssonpeterm themontrealcognitiveassessmentnormativedatafromalargeswedishpopulationbasedcohort
AT minthonlennart themontrealcognitiveassessmentnormativedatafromalargeswedishpopulationbasedcohort
AT nilssonerikd themontrealcognitiveassessmentnormativedatafromalargeswedishpopulationbasedcohort
AT palmqvistsebastian themontrealcognitiveassessmentnormativedatafromalargeswedishpopulationbasedcohort
AT borlandemma montrealcognitiveassessmentnormativedatafromalargeswedishpopulationbasedcohort
AT naggakatarina montrealcognitiveassessmentnormativedatafromalargeswedishpopulationbasedcohort
AT nilssonpeterm montrealcognitiveassessmentnormativedatafromalargeswedishpopulationbasedcohort
AT minthonlennart montrealcognitiveassessmentnormativedatafromalargeswedishpopulationbasedcohort
AT nilssonerikd montrealcognitiveassessmentnormativedatafromalargeswedishpopulationbasedcohort
AT palmqvistsebastian montrealcognitiveassessmentnormativedatafromalargeswedishpopulationbasedcohort