Unconditional and Conditional Standards Using Cognitive Function Curves for the Modified Mini-Mental State Exam: Cross-Sectional and Longitudinal Analyses in Older Chinese Adults in Singapore.

Published

Journal Article

OBJECTIVE: The conventional practice of assessing cognitive status and monitoring change over time in older adults using normative values of the Mini-Mental State Exam (MMSE) based on age bands is imprecise. Moreover, population-based normative data on changes in MMSE score over time are scarce and crude because they do not include age- and education-specific norms. This study aims to develop unconditional standards for assessing current cognitive status and conditional standards that take prior MMSE score into account for assessing longitudinal change, with percentile curves as smooth functions of age. METHODS: Cross-sectional and longitudinal data of a modified version of the MMSE for 2,026 older Chinese adults from the Singapore Longitudinal Aging Study, aged 55-84, in Singapore were used to estimate quantile regression coefficients and create unconditional standards and conditional standards. RESULTS: We presented MMSE percentile curves as a smooth function of age in education strata, for unconditional and conditional standards, based on quantile regression coefficient estimates. We found the 5th and 10th percentiles were more strongly associated with age and education than were higher percentiles. Model diagnostics demonstrated the accuracy of the standards. CONCLUSION: The development and use of unconditional and conditional standards should facilitate cognitive assessment in clinical practice and deserve further studies.

Full Text

Cited Authors

  • Cheung, YB; Xu, Y; Feng, L; Feng, L; Nyunt, MSZ; Chong, MS; Lim, WS; Lee, TS; Yap, P; Yap, KB; Ng, TP

Published Date

  • September 2015

Published In

Volume / Issue

  • 23 / 9

Start / End Page

  • 915 - 924

PubMed ID

  • 25260558

Pubmed Central ID

  • 25260558

Electronic International Standard Serial Number (EISSN)

  • 1545-7214

Digital Object Identifier (DOI)

  • 10.1016/j.jagp.2014.08.008

Language

  • eng

Conference Location

  • England