Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025
Identifying dementia risk profiles for targeted interventions: A latent class analysis of at-risk middle-aged Australians.
СтатьяРандомизированное исследованиеНазвание и аннотация: Перевод пока не подготовлен
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Sarwar Muhammad Rehan, Cross Amanda J, Godbee Kali, Geethadevi Gopisankar Mohanannair, Magin Parker, Tullipan Mary, Baker Amanda L, Bonevski Billie, Ward Stephanie A, Mahal Ajay, Versace Vincent, Bell J Simon, Mc Namara Kevin, O'Reilly Sharleen L, Thomas Dennis, Manias Elizabeth, Anstey Kaarin J, Varnfield Marlien, Jayasena Rajiv, Elliott Rohan A, Lee Cik Y, Hernan Andrea, van den Bosch Denise, Ferreira Catherine, George Johnson
Аннотация
INTRODUCTION: This study aimed to identify distinct dementia risk profiles in middle-aged adults with two or more potential dementia risk factors, to inform targeted prevention strategies.
METHODS: Cross-sectional analysis of baseline sociodemographic, clinical, and dementia-risk data from the HAPPI MIND trial. Dementia risk was assessed using the Australian National University Alzheimer's Disease Risk Index. Risk profiles were identified using latent class analysis (LCA).
RESULTS: Among 403 participants (mean age 56.4 ± 5.7 years, 62.5% female), the median number of dementia risk factors was 5.0; hyperlipidaemia (92.5%), low cognitive activity (72.5%), obesity (57.6%), and hypertension (52.7%) were the most prevalent. Several risk factors showed significant positive correlations. LCA identified three distinct classes: 1-High Cardiometabolic Burden; 2-High Behavioural and Psychosocial Risk; and 3-Low Risk with Healthy Behaviours.
DISCUSSION: The identified latent classes highlight heterogeneity of dementia risk profile in midlife. Tailored, multidomain interventions addressing each group's specific needs may improve dementia risk profiles and support broader health outcomes.
HIGHLIGHTS: Middle-aged Australians who participated in the HAPPI MIND dementia risk reduction trial had a median of five modifiable risk factors. Significant positive correlations were observed between behavioral and clinical risk factors, such as depression, along with poor diet, social isolation, and smoking. Latent class analysis revealed three distinct profiles: High Cardiometabolic Burden; High Behavioral and Psychosocial Risk; and Low Risk with Healthy Behaviors. The findings suggest there is a need for personalized, multidomain prevention strategies tailored to individual risk profiles in primary care.
METHODS: Cross-sectional analysis of baseline sociodemographic, clinical, and dementia-risk data from the HAPPI MIND trial. Dementia risk was assessed using the Australian National University Alzheimer's Disease Risk Index. Risk profiles were identified using latent class analysis (LCA).
RESULTS: Among 403 participants (mean age 56.4 ± 5.7 years, 62.5% female), the median number of dementia risk factors was 5.0; hyperlipidaemia (92.5%), low cognitive activity (72.5%), obesity (57.6%), and hypertension (52.7%) were the most prevalent. Several risk factors showed significant positive correlations. LCA identified three distinct classes: 1-High Cardiometabolic Burden; 2-High Behavioural and Psychosocial Risk; and 3-Low Risk with Healthy Behaviours.
DISCUSSION: The identified latent classes highlight heterogeneity of dementia risk profile in midlife. Tailored, multidomain interventions addressing each group's specific needs may improve dementia risk profiles and support broader health outcomes.
HIGHLIGHTS: Middle-aged Australians who participated in the HAPPI MIND dementia risk reduction trial had a median of five modifiable risk factors. Significant positive correlations were observed between behavioral and clinical risk factors, such as depression, along with poor diet, social isolation, and smoking. Latent class analysis revealed three distinct profiles: High Cardiometabolic Burden; High Behavioral and Psychosocial Risk; and Low Risk with Healthy Behaviors. The findings suggest there is a need for personalized, multidomain prevention strategies tailored to individual risk profiles in primary care.