Elsevier

Archives of Gerontology and Geriatrics

Volume 90, September–October 2020, 104137
Archives of Gerontology and Geriatrics

Cognitive reserve and depression predict subjective reports of successful aging

https://doi.org/10.1016/j.archger.2020.104137Get rights and content

Highlights

  • Improving successful aging (SA) could reduce risks for age-related declines.

  • We assessed self-report of function, cognition, depression and SA in older adults.

  • SA was best predicted by depression.

  • To lesser degree cognitive reserve also emerged as predictor of SA.

  • Interventions to lessen depression and promote cognitive reserve may improve SA.

Abstract

Background

With graying of western societies, successful aging is a hotly debated topic. Attaining successful aging brings benefits not only at the individual level, but also to society. To better understand successful aging, we conducted a study of older adults in the Republic of Slovenia.

Methods

We recruited 213 community-dwelling adults, age 65 years and older, who responded to the Successful Aging Inventory (SAI), Purpose of Life Questionnaire (PIL), Satisfaction with Life Scale (SWLS), Beck Depression Inventory (BDI), Cognitive Reserve Index, Functional Activities Questionnaire (FAQ), and Multiple Abilities Self-Report Questionnaire (MASQ).

Results

Responses to all scales were significantly correlated, which was taken into account when identifying covariates of latent successful aging in a structural equation model. Successful aging, as evaluated by the combination questionnaire responses, was most strongly associated with depression and marginally associated with cognitive reserve. Self-rated functional and cognitive capacities did not significantly explain individual differences in successful aging.

Discussion

In our study of community-dwelling, older Slovenes, self-rated depression emerged as a strong correlate of successful aging and, to a lesser degree, cognitive reserve. Future studies of interventions that aim to promote successful aging should consider the role of depression and cognitive reserve in the older adult’s experience of aging.

Introduction

As the graying population increases, interest in understanding how to attain “successful” aging (SA) has grown. Genetic predisposition determines merely 25–30 % of individual differences in longevity and the remaining majority of variance is attributed to lifestyle and health factors, many of which may be modifiable to promote SA (Eaton et al., 2012). Understanding the factors that underpin SA would result in dramatic social and economic benefits, with implications extending beyond the individual.

SA has been traditionally defined in terms of longevity, marked by cognitive maintenance and absence of chronic disease (Rowe & Kahn, 1997). The Rowe and Kahn model challenged the view that aging consists of unavoidable decline and suggests that age-related loss may be in part due to modifiable factors, and their model of SA later included maintaining physical functioning and actively engaging in life (Rowe & Kahn, 1997). Since the introduction of “successful aging” to gerontology parlance more than half a century ago (Havighurst, 1961), the definitions of SA have proliferated and become increasingly heterogeneous. For example, systematic review papers document 29 definitions in 2006 (Depp & Jeste, 2006) and 105 definitions a mere eight years later (Cosco, Prina, Perales, Stephan, & Brayne, 2013).

Soon after its introduction, the Rowe and Kahn model was subject to empirically-based critiques that called for its expansion. Proposed additions included subjective criteria (Coleman, 1992; Strawbridge, Wallhagen, & Cohen, 2002;), spirituality (Crowther, Parker, Achenbaum, Larimore, & Koenig, 2002), marital status and quality (Ko, Berg, Butner, Uchino, & Smith, 2007), positive as opposed to pathological health characteristics (Kaplan et al., 2008), resilience (Bowling & Iliffe, 2011; Nygren et al., 2005; Wagnild, 2003), leisure activity (Lee, Lan, & Yen, 2011), engagement and life satisfaction (Tze Pin et al., 2009).

Given the disparity between subjective experience and established objective criteria (Strawbridge et al., 2002), integration of the older adult’s own experience into SA definitions is important but often overlooked in empirical studies (Pruchno, Wilson-Genderson, Rose, & Cartwritght, 2010). The subjective experience of aging is often measured through interview (e.g., Reichstadt, Sengupta, Depp, Palinkas, & Jeste, 2010) or standardized questionnaires that elicit specific self-report based on operational definitions (e.g., Cosco, Stephen, & Brayne, 2015). When comparing objective and subjective measures, myriad domains have been proposed to be added to SA: emotional well-being and spirituality (Crowther et al., 2002; Lewis, 2011); comportment and acceptance of change (Rossen, Knafl, & Flood, 2008); self-acceptance and self-contentment (Reichstadt et al., 2010); self-care, accepting the aging process, and financial well-being (Hilton, Gonzalez, Saleh, Maitoza, & Anngela-Cole, 2012); and living with family and receiving emotional care (Hsu, 2007). With the introduction of new domains, including quality of life and relationships, self-report assessment is clearly warranted but subject to typical bias and unreliability (e.g., Ferri, James, & Pruchno, 2009; Mcdowell, 2010). The study of SA invites latent modeling approaches that specify multidimensional constructs, reflecting multiple indicators (Blanco-Molina, Pinazo-Hernandis, & Tomás, 2019; Cosco, Stephan, Brayne, & Muniz, 2017; Kok, Aartsen, Deeg, & Huisman, 2017; Pruchno et al., 2010), and that mitigate bias from the unreliability of individual measures.

Studies that have used multidimensional definitions have identified several early-life correlates of SA. SA is associated with high education, marriage, and no history of incarceration, as well as low incidence of chronic disease indicators (Pruchno et al., 2010). High socioeconomic status, occupational and educational attainment, and leisure activity are also indicators of cognitive reserve—the maintenance of function despite neurological damage—that is a prominent predictor of aging trajectory (Stern, 2009). The relation between subjective cognitive reserve and SA has not been thoroughly examined, but may provide additional insights into the older adult’s experience of aging. Sex differences in SA have been inconsistently observed: some reports identify women as having lower likelihood of SA (e.g., Pruchno et al., 2010) whereas others identify better outcomes among women (e.g., Maccora, Peters, & Anstey, 2018). Depression is negatively associated with SA and cognitive function, especially among women (Paulson, Bowen, & Lichtenberg, 2011; Vahia et al., 2010), and this may partially contribute to observed sex differences. Systematic studies of sex differences identified that income and education differentially predicted SA between Korean men and women (Park, Jang, & Kim, 2010) and poor access to infrastructural resources by Chilean women were predictive of unsuccessful aging (Rotarou & Sakellariou, 2019). Cross-cultural comparisons in SA are challenging due to differences in subjective criteria, socioeconomics and education (Jensen et al., 2018), and therefore studies of subjective SA in different cultures are necessary to inform a valid understanding of the world’s aging population.

The current study addresses the outlined limitations by examining individual differences in SA reflective of subjective psychosocial measures in a sample of older adults from Slovenia. SA was defined by self-reports of sociodemographic data, health status, and life satisfaction and meaning, which were combined as a latent construct. In a structural equation modeling framework, we tested the hypothesis that greater protective factors (cognitive reserve and functional and cognitive capacity) and lower risk factors (health status and depression) would predict high SA scores. Further, we examined possible differences between men and women in the correlates of SA.

Section snippets

Participants

A convenience sample of 213 adults, aged 60 years and older, who lived in Slovenia were enrolled in the study. Data were collected over a 10-month period, from November 2015 to August 2016. Older people who lived independently and who were able to communicate verbally in Slovene language were approached and invited to participate. We recruited participants through community agencies and programs for older adults—e.g., pensioners’ associations and Stari za stare. We recruited 222 adults who met

Sample univariate descriptions and bivariate correlations

The Pearson correlation coefficients between all scale self-evaluations are presented in Table 1. Testing possible group differences identified that the indicators of SA were comparable between men and women (all t = -0.50 – 0.18, all p’s > 0.25). Women (M = 67.74, SD = 5.54) were on average younger than men (M = 69.77, SD = 6.57) in this sample (t (210) = -2.17, p =  0.03). Women reported lower Functional Capacity (M = 10.5, SD = 2.4 vs. M = 11.4, SD = 3.3; t (205) = -2.10, p =  0.04) and

Discussion

The present study examined subjective evaluation of SA on a continuum and identified risk and protective factors that were associated with individual differences therein. Across older Slovenian individuals, high SA was associated with low depression ratings and a non-significant trend with high self-report of cognitive reserve. Although men in this sample reported higher depression symptoms than women, the linear relation with SA was similar between sexes. Self-evaluations of functional

Declaration of Competing Interest

The authors whose names are listed immediately below certify that they have NO affiliations with or involvement in any organization or entity with any financial interest (such as honoraria; educational grants; participation in speakers' bureaus; membership, employment, consultancies, stock ownership, or other equity interest; and expert testimony or patent-licensing arrangements), or non-financial interest (such as personal or professional relationships, affiliations, knowledge or beliefs) in

CRediT authorship contribution statement

Klara Golja: Conceptualization, Methodology, Data curation, Writing - original draft. Ana M. Daugherty: Formal analysis, Writing - review & editing. Voyko Kavcic: Conceptualization, Methodology, Visualization, Investigation, Supervision, Validation.

Acknowledgments

This research did not receive any financial support. The data, analyses and materials published in this manuscript will be made available upon written request to the corresponding author.

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