Normative data for older adults may be tainted by inadvertent inclusion of undiagnosed individuals at the very early stage of a neurodegenerative process. To avoid this pitfall, we developed norms for a cohort of older adults without MCI/dementia at 3-year follow-up.

A randomly selected sample of 1041 community-dwelling individuals (age ≥ 65) received a full neurological and neuropsychological examination on two occasions [mean interval = 3.1 (SD = 0.9) years].

Of these, 492 participants (Group 1; 65–87 years old) were without dementia on both evaluations (CDR=0 and MMSE ≥ 26); their baseline data were used for norms development. Group 2 (n = 202) met the aforementioned criteria only at baseline, but not at follow-up. Multiple linear regressions included demographic predictors for regression-based normative formulae and raw test scores as dependent variables for each test variable separately. Standardized scaled scores and stratified discrete norms were also calculated. Group 2 performed worse than Group 1 on most tests (p-values < .001–.021). Education was associated with all test scores, age with most, and sex effects were consistent with the literature.

We provide a model for developing sound normative data for widely used neuropsychological tests among older adults, untainted by potential early, undiagnosed cognitive impairment, reporting regression-based, scaled, and discrete norms for use in clinical settings to identify cognitive decline in older adults. Additionally, our co-norming of a variety of tests may enable intra-individual comparisons for diagnostic purposes. The present work addresses the challenge of developing robust normative data for neuropsychological tests in older adults.