Normalized Mini-Mental State Examination for Assessing Cognitive Change in Population-Based Brain Aging Studies

被引:74
作者
Philipps, Viviane [1 ,2 ]
Amieva, Helene [1 ,2 ]
Andrieu, Sandrine [3 ,4 ,5 ]
Dufouil, Carole [1 ,2 ]
Berr, Claudine [6 ,7 ]
Dartigues, Jean-Francois [1 ,2 ]
Jacqmin-Gadda, Helene [1 ,2 ]
Proust-Lima, Cecile [1 ,2 ]
机构
[1] INSERM U897, FR-33076 Bordeaux, France
[2] Bordeaux Univ, Bordeaux, France
[3] Univ Toulouse 3, F-31062 Toulouse, France
[4] Univ Hosp Toulouse, Dept Epidemiol & Publ Hlth, Toulouse, France
[5] INSERM UMR 1027, Toulouse, France
[6] INSERM U1061, Montpellier, France
[7] Univ Montpellier I, Montpellier, France
关键词
Dementia; Cognition; Curvilinearity; Epidemiologic methods; Longitudinal studies; Mini-Mental State Examination; LATENT PROCESS; MODEL;
D O I
10.1159/000365637
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
Background: The Mini-Mental State Examination (MMSE) is widely used in population-based longitudinal studies to quantify cognitive change. However, its poor metrological properties, mainly ceiling/floor effects and varying sensitivity to change, have largely restricted its usefulness. We propose a normalizing transformation that corrects these properties, and makes possible the use of standard statistical methods to analyze change in MMSE scores. Methods: The normalizing transformation designed to correct at best the metrological properties of MMSE was estimated and validated on two population-based studies (n = 4,889, 20-year follow-up) by cross-validation. The transformation was also validated on two external studies with heterogeneous samples mixing normal and pathological aging, and samples including only demented subjects. Results:The normalizing transformation provided correct inference in contrast with models analyzing the change in crude MMSE that most often lead to biased estimates of risk factors and incorrect conclusions. Conclusions: Cognitive change can be easily and properly assessed with the normalized MMSE using standard statistical methods such as linear (mixed) models. (C) 2014 S. Karger AG, Basel
引用
收藏
页码:15 / 25
页数:11
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