Latent profile analysis of impaired cognitive function and attribution among community-dwelling ol-der adults with mild cognitive impairment
Objective To explore the potential categories and associated factors of mild cognitive impairment(MCI)in community-dwelling older adults.Methods A total of 393 community-dwelling older adults with MCI in Huzhou City were selected through multistage random sampling from January to July 2022.The survey was conducted by the general information questionnaire,Montreal cognitive assessment(MoCA),Pittsburgh sleep quality index(PSQI)and 15-item geriatric depression scale(GDS-15).Latent profile analysis(LAP)was applied to explore latent categories based on the characteristics of cognitive im-pairment,and Logistic regression analysis was performed to examine the factors associated with these MCI categories.The statistical software was SPSS 26.0.Results The community-dwelling older adults with MCI was categorized into four subgroups:generalized mildly impaired subgroup,mixed impaired with visuospatial executive dysfunction subgroup,narrative memory dysfunction impaired subgroup,and high-risk severely im-paired subgroup,with corresponding MoCA scores of(23.10±0.96),(21.87±0.92),(20.43±0.93),(19.00±0.00),PSQI scores of(6.00(4.00)),(7.00(6.00)),(7.00(6.00)),(10.00(3.00)),and GDS-15 scores of(4.00(4.00)),(4.00(5.00)),(6.00(5.00)),(8.00(3.00)),respectively.Logis-tic regression analysis revealed that compared to generalized mildly impaired subgroup,gender,age,exercise habits,sleep quality,depressive symptoms,chronic disease count,and medication count significantly affected other three subgroups,with female,older age,and never/irregular exercise as common risk factors.Poor sleep quality and depressive symptoms could positively predict mixed impaired with visuospatial executive dysfunc-tion subgroup and narrative memory dysfunction impaired subgroup(B=0.82,OR=2.27,95％CI=1.26-4.08;B=1.12,OR=3.06,95％CI=1.36-6.91).Additionally,poor sleep quality,depressive symptoms,chronic disease and medication count could significantly predict high-risk severely impaired subgroup(B=4.13,OR=62.32,95％CI=1.71-＞999.99;B=3.31,OR=27.49,95％CI=1.37-549.99;B=1.20,OR=3.32,95％CI=1.06-10.41 and B=0.80,OR=2.22,95％CI=1.04-4.71).Conclusion Four latent MCI categories are identified among community-dwelling older adults,and each category was characterized by unique cog-nitive impairment features and factors.Healthcare professionals are advised to customize assessments and management strategies according to these specific characteristics to effectively slow cognitive decline.
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