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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
The Test Your Memory cognitive screening tool: sociodemographic and cardiometabolic risk correlates in a
Efstathios Papachristou1, Sheena E Ramsay1, Olia Papacosta1
1Department of Primary Care and Population Health, UCL, London, UK.
Insights
Cognitive impairment in older adults is linked to lower socioeconomic status, obesity, and poor health. These factors, identified by the Test Your Memory (TYM) tool, align with known risks for mild cognitive impairment (MCI) and Alzheimer's disease.
Area of Science:
- Gerontology
- Neuroscience
- Epidemiology
Background:
- Cognitive impairment is a growing concern in aging populations.
- Identifying correlates of cognitive decline is crucial for early intervention.
Purpose of the Study:
- To investigate the association between Test Your Memory (TYM)-defined cognitive impairment groups and sociodemographic/cardiometabolic factors.
- To compare these correlates in normal cognitive aging, mild cognitive impairment (MCI), and severe cognitive impairment (SCI) groups.
Main Methods:
- Analysis of 1570 British men (aged 71-92) from the British Regional Heart Study cohort.
- Comparison of sociodemographic and cardiometabolic factors based on TYM scores defining normal, MCI, and SCI categories.
Main Results:
- Severe cognitive impairment (SCI) was associated with lower socioeconomic position, slower walking speed, mobility problems, poorer self-reported health, obesity, and impaired lung function.
- Mild cognitive impairment (MCI) showed a similar, though weaker, pattern of associations.
Conclusions:
- Sociodemographic, lifestyle, adiposity, lung function, and overall health factors are associated with late-life cognitive impairments.
- The identified correlates for TYM-defined MCI and SCI groups align with established risk profiles for MCI and Alzheimer's disease.
Objective:
This study aimed to examine the association of Test Your Memory (TYM)-defined cognitive impairment groups with known sociodemographic and cardiometabolic correlates of cognitive impairment in a population-based study of older adults.
Methods:
Participants were members of the British Regional Heart Study, a cohort across 24 British towns initiated in 1978-1980. Data stemmed from 1570 British men examined in 2010-2012, aged 71-92 years. Sociodemographic and cardiometabolic factors were compared between participants defined as having TYM scores in the normal cognitive ageing, mild cognitive impairment (MCI) and severe cognitive impairment (SCI) groups, defined as ≥46 (45 if ≥80 years of age), ≥33 and <33, respectively.
Results:
Among 1570 men, 636 (41%) were classified in the MCI and 133 (8%) in the SCI groups. Compared with participants in the normal cognitive ageing category, individuals with SCI were characterized primarily by lower socio-economic position (odds ratio (OR) = 6.15, 95% confidence interval (CI) 4.00-9.46), slower average walking speed (OR = 3.36, 95% CI 2.21-5.10), mobility problems (OR = 4.61, 95% CI 3.04-6.97), poorer self-reported overall health (OR = 2.63, 95% CI 1.79-3.87), obesity (OR = 2.59, 95% CI 1.72-3.91) and impaired lung function (OR = 2.25, 95% CI 1.47-3.45). A similar albeit slightly weaker pattern was observed for participants with MCI.
Conclusion:
Sociodemographic and lifestyle factors as well as adiposity measures, lung function and poor overall health are associated with cognitive impairments in late life. The correlates of cognitive abilities in the MCI and SCI groups, as defined by the TYM, resemble the risk profile for MCI and Alzheimer's disease outlined in current epidemiological models.
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