Summary: Older adults who have higher levels of education, embark on more social activities and stay cognitively active have a slower rate of cognitive decline than those who engage in less self-maintenance and social activities.
Source: University of Alberta
University of Alberta neuroscientists have identified different factors for maintaining healthy memory and for avoiding memory decline in those over age 55, according to a new study. The results have implications for the prevention of Alzheimer’s disease through targeted early intervention efforts.
Memory decline is one of the first signs of cognitive and neurodegenerative diseases, such as Alzheimer’s disease. Understanding and designing interventions for memory decline is critical for efforts toward preventing or delaying these illnesses.
“We found different risk factors for stable memory and for rapidly declining memory,” said Peggy McFall, lead author and research associate in the Department of Psychology. “It may be possible to use these factors to improve outcomes for older adults.”
McFall, who conducted the study in collaboration with Professor Roger Dixon, used machine learning to analyze data from a longitudinal study based in Edmonton, Alberta.
The study found that adults with healthy memory were more likely to be female, educated, and engage in more social activities, such as hosting a dinner party, and novel cognitive activities, such as using a computer or learning a second language. For adults age 55 to 75, healthy memory was associated with lower heart rate, higher body mass index, more self-maintenance activities, and living companions. Adults over 75 had faster gait and fewer depressive symptoms.
Those with declining memory tended to engage in fewer new cognitive activities. Younger adults, age 55 to 75, younger, had higher heart rates, and engaged in fewer self-maintenance activities, while adults over age 75 had slower gait and engaged in fewer social activities.
“These modifiable risk and protective factors may be converted to potential intervention targets for the dual purpose of promoting healthy memory aging or preventing or delaying accelerated decline, impairment, and perhaps dementia,” said McFall. For instance, clinicians might target specific groups with an intervention to increase new cognitive activities among men or improve mobility for those over age 75.
About this neuroscience research article
Source: University of Alberta Media Contacts: Katie Willis – University of Alberta Image Source: The image is in the public domain.
Modifiable Risk Factors Discriminate Memory Trajectories in Non-Demented Aging: Precision Factors and Targets for Promoting Healthier Brain Aging and Preventing Dementia?
Background: Non-demented cognitive aging trajectories are characterized by vast level and slope differences and a spectrum of outcomes, including dementia.
Objective: The goal of AD risk management (and its corollary, promoting healthy brain aging) is aided by two converging objectives: 1) classifying dynamic distributions of non-demented cognitive trajectories, and 2) identifying modifiable risk-elevating and risk-reducing factors that discriminate stable or normal trajectory patterns from declining or pre-impairment patterns.
Method: Using latent class growth analysis we classified three episodic memory aging trajectories for n = 882 older adults (baseline Mage=71.6, SD=8.9, range = 53-95, female=66%): Stable (SMA; above-average level, sustained slope), Normal (NMA; average level, moderately declining slope), and Declining (DMA; below average level, substantially declining slope). Using random forest analyses, we simultaneously assessed 17 risk/protective factors from non-modifiable demographic, functional, psychological, and lifestyle domains. Within two age strata (Young-Old, Old-Old), three pairwise prediction analyses identified important discriminating factors.
Results: Prediction analyses revealed that different modifiable risk predictors, both shared and unique across age strata, discriminated SMA (i.e., education, depressive symptoms, living status, body mass index, heart rate, social activity) and DMA (i.e., lifestyle activities [cognitive, self-maintenance, social], grip strength, heart rate, gait) groups.
Conclusion: Memory trajectory analyses produced empirical classes varying in level and slope. Prediction analyses revealed different predictors of SMA and DMA that also varied by age strata. Precision approaches for promoting healthier memory aging—and delaying memory impairment—may identify modifiable factors that constitute specific targets for intervention in the differential context of age and non-demented trajectory patterns.