SUCCESSFUL AGING IN PATHOLOGICAL AGING HOW TO

Factors throughout early and middle life, including educational and occupational attainments, etc., are usually nonmodifiable for older adults. From the lifespan perspective, the aforementioned factors are divided into two types. In addition, multiple aspects of the geriatric lifestyle are potential influencing factors, such as diet and sleep quality. The maintenance of abundant leisure activities was shown to be beneficial to cognitive function. Poor physical and mental health conditions were recognized as influencing factors of pathological cognitive aging the issue of whether intact health conditions positively affect SCA remains unresolved. High educational attainment is one of the most commonly identified variables associated with SCA, but studies have yielded mixed results on its effect on cognitive decline. In contrast, a longitudinal study of episodic memory found that the female sex was a predictor of membership in the maintainer group. In addition to advanced age, the female sex represents a strong risk factor for Alzheimer’s disease.

įactors that influence cognitive aging heterogeneity and distinguish pathological and successful cognitive aging have been reported previously, although not as extensively. Since pathological and successful cognitive aging are located at opposite ends of the cognitive aging spectrum, studies aiming to identify how they are influenced by multiple factors differently are very important for both disease prevention and the promotion of successful aging.

SUCCESSFUL AGING IN PATHOLOGICAL AGING HOW TO

How to define SCA remains debated, but well-preserved age-sensitive cognitive functions, like episodic memory and executive function, are often-measured domains. Prior studies used various definitions of SCA, including top memory performers defined using cross-sectional data, successful cognitive ager and memory maintainers defined using longitudinal data, and superager defined by generational comparison (older adults vs. This heterogeneity is remarkably observed in cognitive aging: compared with steady cognitive changes in normal aging, accelerated cognitive decline is usually a characteristic of pathological cognitive aging in the form of mild cognitive impairment (MCI) and eventually dementia on the other end of the spectrum, older adults maintaining superior cognitive performance compared with their peers are commonly referred to as exhibiting successful cognitive aging (SCA). The way we age is mainly decided by the quality of early-life development, the degree of middle-life maintenance, and the pace of late-life degeneration therefore, aging heterogeneity is substantially influenced by various factors in lifespan experiences. This study clarifies the important rankings of behavioral characteristics of cognitive aging, and the relationship that ECR has a long-lasting effect on LLA and finally on cognition, providing efficient guidance for older adults to improve their cognitive function and new evidence to explain the heterogeneity of cognitive aging. Results of this large-sample community-based study suggest it is important for older adults to have an abundant ECR for SCA, and to keep a high level of LLA to prevent cognitive impairment. By SEM analyses, we firstly found that LLA partially mediated the relationship between ECR and cognition and further multi-group SEM analyses showed ECR played a more direct role in the SCA group than in the MCI group: in the SCA group, only the direct effect of ECR on cognition was significant, and in the MCI group, direct effects between ECR, LLA and cognition were all significant. The level of education, age, mental activity, and occupational attainment were the top four important factors that explained 31.6% of cognitive variability. We found that abundant early-life cognitive reserve (ECR, including the level of education and occupational attainment) and reduced late-life leisure activity (LLA, including mental, physical, and social activities) were distinct characteristics of SCA and MCI, respectively. Analyses of variance, regression models with the Shapley value algorithm, and structural equation model (SEM) analyses were conducted to determine specific influencing factors and to evaluate their relative importance and interacting relationships in altering cognitive performance. MethodsĪ group of community-dwelling older adults ( N = 1347, aged 70-88 years) in Beijing was recruited in this cross-sectional study, and a sub-cohort was further divided into successful cognitive aging (SCA, N = 154), mild cognitive impairment (MCI, N = 256), and cognitively normal control (CNC, N = 173) groups. However, multi-domain behavioral factors that characterize the difference between successful and pathological cognitive aging are not clear yet. The identification of factors that specifically influence pathological and successful cognitive aging is a prerequisite for implementing disease prevention and promoting successful aging.

Successful aging in pathological aging