Knight et al., 2018. Olfactory Identification and Episodic Memory in Older Adults

Knight, J. E., Bennett, D. A., & Piccinin, A. M. (2018). Variability and Coupling of Olfactory Identification and Episodic Memory in Older Adults. The Journals of Gerontology: Series B. DOI: 10.1093/geronb/gby058. 

Year: 
2018
Status: 
complete
Presentation Citations: 

Knight, J. E., & Piccinin, A. M. (2018, April). Poster. Foreshadowing Alzheimer’s: Variability and Coupling of Olfaction and Cognition. In D. Burgoyne & R. Gooding (Eds.), Research Now: Contemporary Writing in the Disciplines. Broadview Press.

Knight, J. E., & Piccinin, A. M. (2017, July). Foreshadowing Alzheimer’s: Variability and Coupling of Olfaction and Cognition. Poster presented at 21st IAGG World Congress of Gerontology and Geriatrics (IAGG), San Francisco, USA.

Knight, J. E., & Piccinin, A. M. (2016, November). Olfaction as a Predictor of Alzheimer’s Disease Pathology in Old Age: A Growth Curve Analysis. Poster presented at Gerontological Society of America (GSA) Scientific Meeting, New Orleans, USA

Knight, J. E., & Piccinin, A. M. (2016, July). Olfaction as a Risk Factor for Dementia, Mortality and Stroke. Poster presented at Alzheimer’s International Conference (AAIC), Toronto, CA.

Abstract: 

Objectives: To determine whether assessment-to-assessment fluctuations in episodic memory (EM) reflect fluctuations in olfaction over time.

Methods: Within-person coupled variation in EM and the Brief Smell Identification Test (BSIT) was examined in 565 participants aged 58–106 with autopsy data from the Rush Memory and Aging Project. A growth model for up to 15 years of EM data, with BSIT as time-varying covariate, was estimated accounting for main effects of sex, education, ε4 allele, and Alzheimer’s disease (AD) pathology, BSIT and time-varying BSIT, as well as the interaction between AD pathology and time-varying BSIT.

Results: Individuals with higher BSIT scores (b = .01, standard error [SE] = .004, p = .009) had slower declines in EM. High AD pathology (b = −.06, SE = .02, p = .001) was associated with more rapid declines in EM. The association between time-specific fluctuations in EM and BSIT differed by level of AD pathology (b = .08, SE = .034, p = .028), with a higher EM–BSIT association at higher levels of pathology. Discussion: BSIT and EM fluctuate together over measurement occasions, particularly for individuals with AD pathology. Repeated intraindividual measurements provide information that could lead to early detection and inexpensive monitoring of accumulating AD pathology.

Muniz-Terrera et al., 2011. Joint Modeling of Longitudinal Change and Survival

Muniz-Terrera, G., Piccinin, A. M., Johansson, B., Matthews, F., & Hofer, S. M. (2011). Joint modeling of longitudinal change and survival: An investigation of the association between change in memory scores and death. GeroPsych: The Journal of Gerontopsychology and Geriatric Psychiatry, 24(4), 177-185.

Year: 
2011
Status: 
complete
Abstract: 

Joint longitudinal-survival models are useful when repeated measures and event time data are available and possibly associated. The application of this joint model in aging research is relatively rare, albeit particularly useful, when there is the potential for nonrandom dropout. In this article we illustrate the method and discuss some issues that may arise when fitting joint models of this type. Using prose recall scores from the Swedish OCTO-Twin Longitudinal Study of Aging, we fitted a joint longitudinal-survival model to investigate the association between risk of mortality and individual differences in rates of change in memory. A model describing change in memory scores as following an accelerating decline trajectory and a Weibull survival model was identified as the best fitting. This model adjusted for random effects representing individual variation in initial memory performance and change in rate of decline as linking terms between the longitudinal and survival models. Memory performance and change in rate of memory decline were significant predictors of proximity to death. Joint longitudinal-survival models permit researchers to gain a better understanding of the association between change functions and risk of particular events, such as disease diagnosis or death. Careful consideration of computational issues may be required because of the complexities of joint modeling methodologies.

Zahodne et al., 2011. Education Does Not Slow Cognitive Decline with Aging: 12-Year Evidence from the Victoria Longitudinal Study

Zahodne, L.B., Glymour, M.M., Sparks, C., Bontempo, D., Dixon, R.A., MacDonald, S.W.S., & Manly, J.J. (2011). Education does not slow cognitive decline with aging: 12-year evidence from the Victoria Longitudinal Study. Journal of the International Neuropsychological Society, 17(6), 1039-1046

Year: 
2011
Status: 
complete
Abstract: 

Although the relationship between education and cognitive status is well-known, evidence regarding whether education moderates the trajectory of cognitive change in late life is conflicting. Early studies suggested that higher levels of education attenuate cognitive decline. More recent studies using improved longitudinal methods have not found that education moderates decline. Fewer studies have explored whether education exerts different effects on longitudinal changes within different cognitive domains. In the present study, we analyzed data from 1014 participants in the Victoria Longitudinal Study to examine the effects of education on composite scores reflecting verbal processing speed, working memory, verbal fluency, and verbal episodic memory. Using linear growth models adjusted for age at enrollment (range, 54–95 years) and gender, we found that years of education (range, 6–20 years) was strongly related to cognitive level in all domains, particularly verbal fluency. However, education was not related to rates of change over time for any cognitive domain. Results were similar in individuals older or younger than 70 at baseline, and when education was dichotomized to reflect high or low attainment. In this large longitudinal cohort, education was related to cognitive performance but unrelated to cognitive decline, supporting the hypothesis of passive cognitive reserve with aging. (JINS, 2011, 17, 1039–1046)

Clouston & Denier, 2017. Mental retirement and health selection: Analyses from the U.S. Health and Retirement Study

Clouston, S. A., & Denier, N. (2017). Mental retirement and health selection: Analyses from the US Health and Retirement Study. Social Science & Medicine, 178, 78-86.

Year: 
2017
Status: 
complete
Abstract: 

Background: Research has recently suggested that retirement may decrease cognitive engagement, resulting in cognitive aging. Few studies have systematically documented whether or how selectivity into retirement shapes the relationship between retirement and cognitive aging.

Methods: We draw on data from the Health and Retirement Study (1998–2012) to examine the relationship between cognition and retirement for 18,575 labor force participants. Longitudinal regression discontinuity modeling was used to examine performance and decline in episodic memory. Models differentiated three forms of selection bias: indirect and direct selection as well as reverse causation. To further interrogate the disuse hypothesis, we adjust for confounding from health and socioeconomic sources.

Results: Results revealed that individuals who retired over the course of the panel were substantially different in terms of health, wealth and cognition when compared to those who remained employed. However, accounting for observed selection biases, significant associations were found linking longer retirement with more rapid cognitive decline.

Discussion: This study examined respondents who were in the labor force at baseline and transitioned into retirement. Analyses suggested that those who retired over the course of the panel had worse overall functioning, but also experienced more rapid declines after retirement that increased the rate of aging by two-fold, resulting in yearly losses of 3.7% (95% CI = [3.5, 4.0]) of one standard deviation in functioning attributable to retirement. Results are supportive of the view that retirement is associated with more rapid cognitive aging.

Cadar et al., 2017. An International Evaluation of Cognitive Reserve and Memory Changes in Early Old Age in 10 European Countries.

Cadar, D., Robitaille, A., Clouston, S., Hofer, S. M., Piccinin, A. M., & Muniz-Terrera, G. (2017). An international evaluation of cognitive reserve and memory changes in early old age in 10 European countries. Neuroepidemiology, 48(1-2), 9-20.

Year: 
2017
Status: 
complete
Abstract: 

Background: Cognitive reserve was postulated to explain individual differences in susceptibility to ageing, offering apparent protection to those with higher education. We investigated the association between education and change in memory in early old age. 

Methods: Immediate and delayed memory scores from over 10,000 individuals aged 65 years and older, from 10 countries of the Survey of Health, Ageing and Retirement in Europe, were modeled as a function of time in the study over an 8-year period, fitting independent latent growth models. Education was used as a marker of cognitive reserve and evaluated in association with memory performance and rate of change, while accounting for income, general health, smoking, body mass index, gender, and baseline age. 

Results: In most countries, more educated individuals performed better on both memory tests at baseline, compared to those less educated. However, education was not protective against faster decline, except for in Spain for both immediate and delayed recall (0.007 [SE = 0.003] and 0.006 [SE = 0.002]), and Switzerland for immediate recall (0.006 [SE = 0.003]). Interestingly, highly educated Italian respondents had slightly faster declines in immediate recall (-0.006 [SE = 0.003]). 

Conclusions: We found weak evidence of a protective effect of education on memory change in most European samples, although there was a positive association with memory performance at individuals' baseline assessment.