Background: Research into dementia is needed in developing countries. Assessment of variations in disease frequency between regions might enhance our understanding of the disease, but methodological difficulties need to be addressed. We aimed to develop and test a culturally and educationally unbiased diagnostic instrument for dementia.
Methods: In a multicentre study, the 10/66 Dementia Research Group interviewed 2885 people aged 60 years and older in 25 centres, most in Universities, in India, China and southeast Asia, Latin America and the Caribbean, and Africa. 729 had dementia and three groups were free of dementia: 702 had depression, 694 had high education (as defined by each centre), and 760 had low education (as defined by each centre). Local clinicians diagnosed dementia and depression. An interviewer, masked to dementia diagnosis, administered the geriatric mental state, the community screening instrument for dementia, and the modified Consortium to Establish a Registry of Alzheimer's Disease (CERAD) ten-word list-learning task.
Findings: Each measure independently predicted a diagnosis of dementia. In an analysis of half the sample, an algorithm derived from all three measures gave better results than any individual measure. Applied to the other half of the sample, this algorithm identified 94% of dementia cases with false-positive rates of 15%, 3%, and 6% in the depression, high education, and low education groups, respectively.
Interpretation: Our algorithm is a sound basis for culturally and educationally sensitive dementia diagnosis in clinical and population-based research, supported by translations of its constituent measures into most languages used in the developing world.