Obesity and low Body Mass Index (BMI) have both been found to be risk factors for dementia. There have been no studies to our knowledge that have examined the relationship between BMI classification and cognitive function using a large Canadian database such as the CLSA. Our study objectives were: 1) To determine the cross-sectional association between BMI classification and cognitive performance using baseline data from the CLSA and 2) To determine whether 3-year changes in BMI between Baseline and Follow-Up 1 were associated with changes in memory performance. We found that normal BMI was associated with significantly better memory performance compared to underweight, overweight and to all three classifications of obesity. Being underweight and obesity class III were associated with significantly higher odds of meeting criteria for mild cognitive impairment (MCI) compared to normal BMI. Being underweight was associated with highest rates of MCI (20% compared to 4% for normal BMI). No association was demonstrated between change in BMI and change in cognitive performance at 3-year follow-up. In conclusion, this study provides further support that maintaining a normal BMI is protective with regards to cognitive function among older adults. Being underweight was associated with the highest rates of MCI stressing the importance of adequate nutrition.
Dr. Nadine Akbar is currently a Research Chair in Community Connection at Humber River Health and an Assistant Professor in Health Services Research, through the Institute of Health Policy, Management and Evaluation at the University of Toronto. She is currently leading a research program at Humber River Health focused on addressing the needs of marginalized communities, including older adults experiencing barriers due to social determinants of health, predominately from the Northwestern Toronto region. Her previous academic training is in psychology and rehabilitation sciences with a focus on assessment and rehabilitation of cognitive dysfunction and fatigue in neurological populations, particularly multiple sclerosis (MS).
