Latent Profiles Based on Combined Risk Factors for Cognitive Decline in European Older Adults: A Retrospective Study Based on the SHARE HCAP Project

<b>Background/Objectives</b>: Cognitive decline is common in ageing, ranging from mild to severe manifestations. Although several modifiable risk factors have been identified, they are typically examined individually. This study aimed to identify latent profiles based on combinations of dementia risk factors and to quantify the associations with cognitive impairment in a European population of older adults. <b>Methods</b>: Based on the SHARE HCAP project, we conducted a retrospective longitudinal study by linking individual data from wave 6 (2015) and wave 9 (2021-2022). The sample included 2685 individuals aged 50+. The study outcome was cognitive status, assessed using standardised neurological tests and questionnaire and categorised as normal cognition, mild cognitive impairment (MCI), or severe cognitive impairment (SCI). The exposures included clinical, psychosocial, and lifestyle variables. Latent Class Analysis (LCA) was applied to identify distinct profiles, and multinomial logistic regression models were carried out to estimate associations between latent profiles and cognitive status, expressed as odds ratios (ORs) with 95% confidence intervals (CI). <b>Results</b>: The study sample included 2326 participants, of whom 25.1% with MCI and 9.4% with SCI. Through LCA, we identified four profiles: <i>Low-risk</i>, <i>Combined Cluster</i>, <i>Inactive Behaviour</i>, and <i>Cardiometabolic Risk</i>. Compared with the <i>Low-risk</i> profile, the odds of MCI were significantly higher for <i>Combined Cluster</i> profile (OR = 3.11; 95% CI: 2.38-4.06) and CR (OR = 1.44; 95% CI: 1.07-1.93). For SCI, elevated odds were observed for <i>Combined Cluster</i> (OR = 7.30; 95% CI: 4.47-11.92), <i>Cardiometabolic Risk</i> (OR = 2.31; 95% CI: 1.31-4.05), and <i>Inactive Behaviour</i> (OR = 1.87; 95% CI: 1.01-3.48). <b>Conclusions</b>: Four latent profiles were identified, each showing distinct associations with MCI and SCI. The <i>Combined Cluster</i>-characterised by poor mental health, limited physical activity, and hypertension-showed the highest odds of cognitive impairment. Public health strategies should prioritise integrated actions against these risk factors.

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Journal
Neurology International
Published
2025-10-14
DOI
https://doi.org/10.3390/neurolint17100172
Primary Topic
Dementia and Cognitive Impairment Research
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article
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article

Latent Profiles Based on Combined Risk Factors for Cognitive Decline in European Older Adults: A Retrospective Study Based on the SHARE HCAP Project

Paola Bertuccio, Lorenzo Blandi, Anna Odone, Giacomo Pietro Vigezzi et al.
Neurology International
Dementia and Cognitive Impairment Research
article

Latent Profiles Based on Combined Risk Factors for Cognitive Decline in European Older Adults: A Retrospective Study Based on the SHARE HCAP Project

Paola Bertuccio, Lorenzo Blandi, Anna Odone, Giacomo Pietro Vigezzi, Johnnatas Mikael Lopes, Riccardo Vecchio
article en

Abstract

<b>Background/Objectives</b>: Cognitive decline is common in ageing, ranging from mild to severe manifestations. Although several modifiable risk factors have been identified, they are typically examined individually. This study aimed to identify latent profiles based on combinations of dementia risk factors and to quantify the associations with cognitive impairment in a European population of older adults. <b>Methods</b>: Based on the SHARE HCAP project, we conducted a retrospective longitudinal study by linking individual data from wave 6 (2015) and wave 9 (2021-2022). The sample included 2685 individuals aged 50+. The study outcome was cognitive status, assessed using standardised neurological tests and questionnaire and categorised as normal cognition, mild cognitive impairment (MCI), or severe cognitive impairment (SCI). The exposures included clinical, psychosocial, and lifestyle variables. Latent Class Analysis (LCA) was applied to identify distinct profiles, and multinomial logistic regression models were carried out to estimate associations between latent profiles and cognitive status, expressed as odds ratios (ORs) with 95% confidence intervals (CI). <b>Results</b>: The study sample included 2326 participants, of whom 25.1% with MCI and 9.4% with SCI. Through LCA, we identified four profiles: <i>Low-risk</i>, <i>Combined Cluster</i>, <i>Inactive Behaviour</i>, and <i>Cardiometabolic Risk</i>. Compared with the <i>Low-risk</i> profile, the odds of MCI were significantly higher for <i>Combined Cluster</i> profile (OR = 3.11; 95% CI: 2.38-4.06) and CR (OR = 1.44; 95% CI: 1.07-1.93). For SCI, elevated odds were observed for <i>Combined Cluster</i> (OR = 7.30; 95% CI: 4.47-11.92), <i>Cardiometabolic Risk</i> (OR = 2.31; 95% CI: 1.31-4.05), and <i>Inactive Behaviour</i> (OR = 1.87; 95% CI: 1.01-3.48). <b>Conclusions</b>: Four latent profiles were identified, each showing distinct associations with MCI and SCI. The <i>Combined Cluster</i>-characterised by poor mental health, limited physical activity, and hypertension-showed the highest odds of cognitive impairment. Public health strategies should prioritise integrated actions against these risk factors.

Neurology InternationalVol. 17(10)
Vita-Salute San Raffaele University (IT), University of Pavia (IT), Istituti Clinici Scientifici Maugeri (IT), Policlinico San Matteo Fondazione (IT), Istituti di Ricovero e Cura a Carattere Scientifico (IT), Universidade Federal do Vale do São Francisco (BR)
Openalex Percentile: Top 65%
Dementia and Cognitive Impairment Research
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