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Published in: BMC Geriatrics 1/2012

Open Access 01-12-2012 | Research article

Examining the influence of gender, education, social class and birth cohort on MMSE tracking over time: a population-based prospective cohort study

Authors: Fiona Matthews, Riccardo Marioni, Carol Brayne, Medical Research Council Cognitive Function and Ageing Study

Published in: BMC Geriatrics | Issue 1/2012

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Abstract

Background

Whilst many studies have analysed predictors of longitudinal cognitive decline, few have described their impact on population distributions of cognition by age cohort. The aim of this paper was to examine whether gender, education, social class and birth cohort affect how mean population cognition changes with age.

Methods

The Medical Research Council Cognitive Function and Ageing Study (MRC CFAS) is a multi-centre population based longitudinal study of 13,004 individuals in England and Wales. Using ten years of follow-up data, mean Mini-mental State Examination (MMSE) scores were modelled by age and birth cohort adjusting for non-random drop-out. The model included terms to estimate cohort effects. Results are presented for five year age bands between 65–95 years.

Results

At a population level, women show greater change in MMSE scores with age than men. Populations with lower education level and manual work also show similar effects. More recent birth cohorts have slightly higher scores.

Conclusion

Longitudinal data can allow examination of population patterns by gender, educational level, social class and cohort. Each of these major socio-demographic factors shows some effect on whole population change in MMSE with age.
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Metadata
Title
Examining the influence of gender, education, social class and birth cohort on MMSE tracking over time: a population-based prospective cohort study
Authors
Fiona Matthews
Riccardo Marioni
Carol Brayne
Medical Research Council Cognitive Function and Ageing Study
Publication date
01-12-2012
Publisher
BioMed Central
Published in
BMC Geriatrics / Issue 1/2012
Electronic ISSN: 1471-2318
DOI
https://doi.org/10.1186/1471-2318-12-45

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