Discrepancy in Fluid and Crystallized Intelligence: An Early Cognitive Marker of Dementia from the LASI-DAD Cohort - Swati Bajpai; Ashish Dutt Upadhayay; Joyita Banerjee; Avinash Chakrawarthy; Prashun Chatterjee; Jinkook Lee; Aparajit Ballav Dey (Dementia and Geriatric Cognitive Disorders Extra, 2022)
Background: Cognitive aging is a complex phenomenon, which comprises various cognitive skills, broadly categorized into fluid and crystallized intelligence. Crystallized intelligence (gc) tends to be maintained, as opposed to fluid intelligence (gf), which tends to decline rapidly with age. The association of the two with cognitive decline remains a matter of conjecture requiring further research. Aim: The aim of the study was to identify the variables of gc and gf from a population data of Longitudinal Aging Study in India-Diagnostic Assessment of Dementia (LASI-DAD) study and investigate its relationship with the onset of cognitive impairment using discrepancy analysis against neuropsychological tests. Methods: This analysis of data from LASI-DAD study was carried out on a sample of 3,223 participants. They were assessed on extensive thirteen cognitive tests and one subjective test of cognition. Standardized score was used for discrepancy analysis. Fluid ability minus crystallized ability was used to assess the cognitive impairment. Any statistical significance with the score difference >0.99 SD was defined as a presence of cognitive decline. Hindi Mental Status Examination (HMSE) and the Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) were used as gold standard. Results: With increased discrepancy score, each cognitive parameter score declined which was found to be statistically significant. In HMSE (Normal = 25.81 ± 3.39; Impaired = 23.17 ± 3.54; p = <0.001), there was a drop of 2 point scores in identifying cognitive impairment in the population sample as per the gold standard. A similar trend was evident in other neurocognitive domains as well. Conclusion: Crystallized-fluid intelligence discrepancy analysis has a strong potential in predicting the onset of cognitive decline ahead of time, facilitating early intervention.