Mild Cognitive Impairment and modifiable risk factors among Lebanese older adults in primary care
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Updated: Oct 20, 2025

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Georges Assaf1, Jamil El Khoury2, Sarah Jawhar1
1Department of Family Medicine, American University of Beirut Medical Center, Beirut, Lebanon.
Objective:
Mild Cognitive Impairment (MCI) is an intermediate state between normal cognition and dementia. Identification of MCI and associated risk factors is important for early intervention. This study investigated the prevalence of MCI among Lebanese older adults and associated risk factors in primary care.
Methods:
For this cross-sectional study, 337 adults aged 60 years and older met inclusion criteria and were recruited at a primary care clinic associated with a tertiary medical center in Beirut, Lebanon. The validated Arabic version of the Montreal Cognitive Assessment, the 5-item Geriatric Depression Scale, and the Lawton Instrumental Activities of Daily Living Scale were administered. Data about sociodemographic, behavioral, and clinical characteristics was obtained.
Results:
There was no difference in the mean age between those with normal cognition and those with MCI (mean age 70.38 ± 7.4 and 72.12 ± 7.6 years, respectively). The prevalence of MCI was 14.8% (50 out of 337), 42% were males and 58% were women. Participants having more than 12 years of education (OR = 0.297; CI = 0.112-0.788; P = 0.015) were less likely to have MCI. Participants with history of smoking (OR = 2.599; CI = 1.266-5.339; P = 0.012) or at risk of depression (OR = 2.847; CI = 1.392-5.819; P = 0.004) were more likely to have MCI.
Conclusion:
Identification of patients with history of smoking and at risk of depression may serve as an opportunity to offer intensive counseling and targeted treatment to delay the onset or progression of MCI to Alzheimer's disease.
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