Dataset Information

Class-Specific Incidence of All-Cause Dementia and Alzheimer's Disease: A Latent Class Approach.

ABSTRACT: Identifying preclinical Alzheimer's disease (AD) is an important step toward developing approaches to early treatment and dementia prevention. We applied latent class analysis (LCA) to 10 baseline neuropsychological assessments for 1,345 participants from Einstein Aging Study. Time-to-event models for all-cause dementia and AD were run examining events in 4-year intervals. Five classes were identified: Mixed-Domain Impairment (n = 107), Memory-Specific Impairment (n = 457), Average (n = 539), Frontal Impairment (n = 118), and Superior Cognition (n = 124). Compared to the Average class, the Mixed-Domain Impairment and Memory-Specific Impairment classes were at higher risk of incident all-cause dementia and AD in the first 4 years from baseline, while the Frontal Impairment class was associated with higher risk between 4 and 8 years of follow-up. LCA identified classes which differ in cross-sectional cognitive patterns and in risk of dementia over specific follow-up intervals.

SUBMITTER: Zammit AR

PROVIDER: S-EPMC6329008 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Class-Specific Incidence of All-Cause Dementia and Alzheimer's Disease: A Latent Class Approach.

Zammit Andrea R AR Hall Charles B CB Katz Mindy J MJ Muniz-Terrera Graciela G Ezzati Ali A Bennett David A DA Lipton Richard B RB

Journal of Alzheimer's disease : JAD 20180101 1

Identifying preclinical Alzheimer's disease (AD) is an important step toward developing approaches to early treatment and dementia prevention. We applied latent class analysis (LCA) to 10 baseline neuropsychological assessments for 1,345 participants from Einstein Aging Study. Time-to-event models for all-cause dementia and AD were run examining events in 4-year intervals. Five classes were identified: Mixed-Domain Impairment (n = 107), Memory-Specific Impairment (n = 457), Average (n = 539), Fr ...[more]

PMID: 30282367

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Project description:ObjectiveIn the absence of adequate nationally-representative empirical evidence on multimorbidity, the existing healthcare delivery system is not adequately oriented to cater to the growing needs of the older adult population. Therefore, the present study identifies frequently occurring multimorbidity patterns among older adults in India. Further, the study examines the linkages between the identified patterns and socioeconomic, demographic, lifestyle and anthropometric correlates.DesignThe present findings rest on a large nationally-representative sample from a cross-sectional study.Setting and participantsThe study used data on 58 975 older adults (45 years and older) from the Longitudinal Ageing Study in India, 2017-2018.Primary and secondary outcome measuresThe study incorporated a list of 16 non-communicable diseases to identify commonly occurring patterns using latent class analysis. The study employed multinomial logistic regression models to assess the association between identified disease patterns with unit-level socioeconomic, demographic, lifestyle and anthropometric characteristics.ResultsThe present study demonstrates that older adults in the country can be segmented into six patterns: 'relatively healthy', 'hypertension', 'gastrointestinal disorders-hypertension-musculoskeletal disorders', 'musculoskeletal disorders-hypertension-asthma', 'metabolic disorders' and 'complex cardiometabolic disorders'. Additionally, socioeconomic, demographic, lifestyle and anthropometric factors are significantly associated with one or more identified disease patterns.ConclusionsThe identified classes 'hypertension', 'metabolic disorders' and 'complex cardiometabolic disorders' reflect three stages of cardiometabolic morbidity with hypertension as the first and 'complex cardiometabolic disorders' as the last stage of disease progression. This underscores the need for effective prevention strategies for high-risk hypertension group. Also, targeted interventions are essential to reduce the burden on the high-risk population and provide equitable health services at the community level.

Project description:Background Cardiovascular risk factors co-occur with one another, and little is known about the extent of their clustering and risk of Alzheimer disease (AD). We identify groups of cardiovascular risk factors in cognitively normal individuals and investigate between-group differences in incident AD and death. Methods and Results Cognitively normal individuals were recruited from the National Alzheimer's Coordinator Center. A latent class analysis was conducted with hypertension, hypercholesterolemia, heart condition, stroke, smoking history, diabetes, and high body mass index. Between-group differences in the incidence of AD, mortality, and mortality-adjusted AD were investigated. This study included 12 412 cognitively normal individuals (average follow-up, 65 months). Three groups were identified: (1) low probabilities of cardiovascular risk factors (reference; N=5398 [43%]), (2) hypertension and hypercholesterolemia (vascular-dominant; N=5721 [46%]), and (3) hypertension, hypercholesterolemia, diabetes, and high body mass index (vascular-metabolic; N=1293 [10%]). Both vascular groups were significantly older, had more men, were slightly less educated, and were slightly more cognitively impaired than the reference group (all P<0.05). However, only the vascular-metabolic group had a significantly younger age of death compared with the reference group (84.3 versus 88.7 years, P<0.001). Only the vascular-dominant group had a greater incidence of AD (odds ratio [OR], 1.30; P<0.001) compared with the reference group. Mortality was greater in the vascular-dominant (OR, 3.26; P<0.001) and vascular-metabolic groups (OR, 1.84; P=0.02). Mortality-adjusted AD was greater in the vascular-dominant (OR, 1.54; P=0.02) and vascular-metabolic groups (OR, 1.46; P=0.04). Conclusions Three distinct cardiovascular risk factor groups were identified in cognitively normal elderly individuals. Only the vascular-dominant group was associated with a greater incidence of AD. Selective mortality may contribute to the attenuated association between the vascular-metabolic group and incident AD.

Dataset Information

Class-Specific Incidence of All-Cause Dementia and Alzheimer's Disease: A Latent Class Approach.

Publications

Class-Specific Incidence of All-Cause Dementia and Alzheimer's Disease: A Latent Class Approach.

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