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Review article

Cognitive Decline in Women or Brain Aging?

Gordana Rubeša


Full text: croatian pdf 97 Kb

page 227-232

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Full text: english pdf 97 Kb

page 227-227

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Abstract

Cognitive health enables each individual to have adequate insight into their abilities and a good adaptation of their cognitive, emotional and behavioral functions to various life events. Each individual does not maintain their cognitive health for the same length of time because the human brain ages at different rates in every individual. Some have a rapid cognitive decline, while others retain cognitive functions longer than is typical for their age. Even evolutionary theorists predicted that the female brain might be younger compared to male, and recent research suggests that this is due to lesser loss of cerebral blood flow after puberty, greater brain glycolysis during young adulthood, lesser loss of expression of genes related to protein synthesis during aging, and a significantly later peak of brain gene expression. Factors identified as exacerbating risk for aging and cognitive decline include depression, type-2 diabetes, midlife hypertension, midlife obesity, smoking in men but not women, physical inactivity and low educational attainment, early parental death, and chronic sleep disorders in middle age. Protective factors associated with a younger appearance of the brain are: years of education, physical exercise, practicing meditation, social activity, consumption of moderate amounts of alcohol, adequate diet (Mediterranean, Nordic, DASH and MIND), i.e. diet associated with a low proportion of fat and with the present beneficial micronutrients such as vitamin B, iron and many polyphenols. It has been proven in many studies that education is the greatest non-biological factor in the protection of cognitive decline in old age. A reliable biomarker of aging still does not exist, but recently multivariate methods have been developed to define statistical models of healthy brain aging. Thus, the chronological age of healthy individuals can be predicted using machine learning analysis of neuroimaging data.

Keywords

brain; aging; cognition; female

Hrčak ID:

328496

URI

https://hrcak.srce.hr/328496

Publication date:

27.2.2025.

Article data in other languages: croatian

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