Background/Objectives: 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. Methods: 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). Results: The study sample included 2326 participants, of whom 25.1% with MCI and 9.4% with SCI. Through LCA, we identified four profiles: Low-risk, Combined Cluster, Inactive Behaviour, and Cardiometabolic Risk. Compared with the Low-risk profile, the odds of MCI were significantly higher for Combined Cluster 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 Combined Cluster (OR = 7.30; 95% CI: 4.47–11.92), Cardiometabolic Risk (OR = 2.31; 95% CI: 1.31–4.05), and Inactive Behaviour (OR = 1.87; 95% CI: 1.01–3.48). Conclusions: Four latent profiles were identified, each showing distinct associations with MCI and SCI. The Combined Cluster—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.

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

Bertuccio, Paola;Vecchio, Riccardo;Vigezzi, Giacomo Pietro;Blandi, Lorenzo;Odone, Anna
2025-01-01

Abstract

Background/Objectives: 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. Methods: 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). Results: The study sample included 2326 participants, of whom 25.1% with MCI and 9.4% with SCI. Through LCA, we identified four profiles: Low-risk, Combined Cluster, Inactive Behaviour, and Cardiometabolic Risk. Compared with the Low-risk profile, the odds of MCI were significantly higher for Combined Cluster 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 Combined Cluster (OR = 7.30; 95% CI: 4.47–11.92), Cardiometabolic Risk (OR = 2.31; 95% CI: 1.31–4.05), and Inactive Behaviour (OR = 1.87; 95% CI: 1.01–3.48). Conclusions: Four latent profiles were identified, each showing distinct associations with MCI and SCI. The Combined Cluster—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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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11571/1533235
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