An Investigation on Modifiable and Nonmodifiable Estrogen Exposure and Gray Matter Volume in Healthy Older Women
Heather Kwan1,2, Cassandra Szoeke1,3, Ashleigh Parker1,2
1University of Victoria, Victoria, British Columbia, Canada.
Introduction:
It is projected that the global population of adults above age 60 years will surpass 2 billion by 2050. Age-related cognitive decline represents a prevalent issue and research has demonstrated that women are at greater risk than men. Changes in cognitive function with age are influenced by many factors and may include lifetime exposure to estrogen and the transition to menopause. While the exact relationship between estrogen and the aging brain is unclear, the hormonal changes in menopause have been associated with a decline in gray matter volume. However, some studies have demonstrated that the use of hormone therapy may mitigate some of the effects of cognitive decline.
Methods:
The current study used magnetic resonance imaging and voxel-based morphometry to examine the relationship between gray matter volume and endogenous lifetime estrogen exposure (e.g., reproductive period length or age of menopause - age of menarche in years) and differences in gray matter volume between women who used hormone therapy (N = 62, Mage = 70.97 [2.97], Medu = 12.43 [3.22]) and those who did not (N = 62, Mage = 70.14 [2.62], Medu = 12.81 [3.75]). It was hypothesized that higher lifetime estrogen exposure and use of hormone therapy would be correlated to greater gray matter volume. The data were retrieved from the Women's Healthy Ageing Project.
Results:
Results demonstrated no significant correlations between whole brain gray matter volume and lifetime estrogen exposure. There were no significant differences between groups based on hormone therapy use. However, there was a nonsignificant relationship that suggested that women who did not use hormone therapy had greater gray matter volume than those who did use it.
Discussion:
As the aging population continues to grow globally, it is essential to better understand the variables that influence trajectories of aging; especially for women, who are particularly at risk for age-related cognitive decline.
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