Engagement in cognitively stimulating activities has been considered to maintain or strengthen cognitive skills, thereby minimizing age-related cognitive decline. While the idea that there may be a modifiable behavior that could lower risk for cognitive decline is appealing and potentially empowering for older adults, research findings have not consistently supported the beneficial effects of engaging in cognitively stimulating tasks. Using observational studies of naturalistic cognitive activities, we report a series of mixed effects models that include baseline and change in cognitive activity predicting cognitive outcomes over up to 21 years in four longitudinal studies of aging. Consistent evidence was found for cross-sectional relationships between level of cognitive activity and cognitive test performance. Baseline activity at an earlier age did not, however, predict rate of decline later in life, thus not supporting the concept that engaging in cognitive activity at an earlier point in time increases one's ability to mitigate future age-related cognitive decline. In contrast, change in activity was associated with relative change in cognitive performance. Results therefore suggest that change in cognitive activity from one's previous level has at least a transitory association with cognitive performance measured at the same point in time.
With the rising proportion of older adults and increases in life expectancy [
A facet of this research that is relatively understudied involves examining the degree to which discrete types of everyday cognitive activity relate to change in specific cognitive domains over time. Most of the aforementioned trials incorporated training in multiple cognitive abilities and accordingly found support for cognitive training in general, but some reviews report less promising results for domain-specific training. Memory is frequently the targeted cognitive domain in many interventions, with training involving efforts to improve recall of newly learned information, including skills training, imagery, and mnemonic strategy use; however, meta-analyses reveal minimal efficacy for memory-focused techniques [
Despite the promising body of work that has accumulated in recent years, definitive conclusions regarding the benefits of cognitive activity are precluded by several methodological concerns [
Thus, the purpose of this study was to examine the effects of self-reported everyday cognitive activities and changes in these activities on changes in four domains of cognition (reasoning, fluency, memory, and semantic knowledge) in longitudinal models that incorporate data from the Origins of Variance in the Oldest-Old: Octogenarian Twins Study (Octo-Twin), the Long Beach Longitudinal Study (LBLS), the Seattle Longitudinal Study (SLS), and the Victoria Longitudinal Study (VLS). This investigation was part of a larger coordinated effort to examine the effects of lifestyle activities on cognitive function across multiple large-scale longitudinal studies of aging that formed the basis of a meeting of the Advanced Psychometrics Methods in Cognitive Aging Workshop. The aim of this workshop was to use a common analytic protocol across studies from the Integrative Analysis of Longitudinal Studies on Aging (IALSA [
These studies were specifically selected based on their collection of cognitive, physical, and social activity data along with a range of cognitive functioning measures over multiple occasions. While the cognitive activity and cognitive function variables are not always identical, the subsets of variables in each study were chosen based on the rationale that they tapped similar domains at the construct level; specifically, we chose measures thought to tap fluid reasoning (Gf, i.e., verbal reasoning, block design, and verbal fluency measures), short-term memory (Gsm, i.e., immediate recall of a verbally presented story or word list), and crystallized knowledge (Gc, i.e., measures of vocabulary and acquired knowledge [
We report a series of mixed effects models that included baseline and change in cognitive activity predicting cognitive function over up to 21 years of time in four large-scale longitudinal studies of older adults. Three of the four studies included in this analysis (LBLS, SLS, and VLS) specifically aimed to study healthy aging and only recruited community-dwelling older adults who were presumed to be cognitively normal at baseline. The fourth study, Octo-Twin, also included a largely cognitively normal sample of older adults, but those who did have dementia diagnoses at baseline (
Octo-Twin participant characteristics.
Year of testing | |||||
---|---|---|---|---|---|
Measure | Baseline | Year 2 | Year 4 | Year 6 | Year 8 |
( |
( |
( |
( |
( |
|
Retention from previous testing (%) | 82.2 | 76.8 | 75.9 | 70.8 | |
Age [M (SD)] | 83.3 (3.0) | 85.2 (2.8) | 86.9 (2.5) | 88.8 (2.5) | 90.7 (2.4) |
Education [M (SD)] | 7.2 (2.4) | 7.3 (2.4) | 7.3 (2.3) | 7.2 (2.1) | 7.2 (2.3) |
Sex, female [ |
369 (65) | 304 (65) | 235 (65) | 195 (71) | 144 (74) |
Reasoning [M (SD)] | 11.5 (7.1) | 11.4 (7.2) | 11.4 (7.1) | 10.8 (7.2) | 10.3 (7.3) |
Memory [M (SD)] | 9.6 (4.0) | 9.4 (4.2) | 9.2 (4.4) | 9.2 (4.7) | 9.0 (4.4) |
Semantic knowledge [M (SD)] | 28.1 (11.1) | 28.6 (11.2) | 27.5 (12.4) | 26.7 (13.0) | 26.2 (11.4) |
Cognitive activity [M (SD)] | 2.1 (1.7) | 1.7 (1.6) | 1.3 (1.4) | 1.2 (1.4) | 1.1 (1.3) |
Activity change [M (SD)] | — | −0.3 (1.3) | −0.6 (1.3) | −0.8 (1.5) | −1.1 (1.6) |
M: mean; SD: standard deviation. The theoretical ranges for each measure with a defined upper limit are as follows: reasoning = 0–42, Memory = 0–16, semantic knowledge = 0–44, and cognitive activity = 0–8.
LBLS participant characteristics.
Year of testing | ||||
---|---|---|---|---|
Measure | Baseline | Year 3 | Year 6 | Year 9 |
( |
( |
( |
( |
|
Retention from previous testing (%) | 52.0 | 49.3 | 70.1 | |
Age [M (SD)] | 73.7 (9.2) | 75.4 (8.7) | 75.1 (8.0) | 76.1 (7.1) |
Education [M (SD)] | 13.7 (3.0) | 13.9 (2.8) | 14.2 (2.7) | 14.2 (2.7) |
Sex, female [ |
285 (51) | 146 (50) | 70 (49) | 51 (51) |
Reasoning [M (SD)] | 22.3 (11.7) | 23.9 (11.5) | 25.4 (11.6) | 25.2 (11.1) |
Fluency [M (SD)] | 32.4 (11.6) | 33.7 (11.1) | 33.3 (13.3) | 34.4 (11.7) |
Memory [M (SD)] | 11.4 (4.0) | 11.6 (4.3) | 11.6 (4.5) | 11.2 (4.6) |
Semantic knowledge [M (SD)] | 38.5 (10.3) | 39.5 (9.6) | 40.7 (9.0) | 39.7 (9.8) |
Cognitive activity [M (SD)] | 2.5 (1.3) | 2.8 (1.4) | 2.7 (1.3) | 2.6 (1.3) |
Activity change [M (SD)] | — | 0.2 (1.3) | 0.2 (1.4) | −0.2 (1.3) |
M: mean; SD: standard deviation. The theoretical ranges for each measure with a defined upper limit are as follows: education = 0–20, reasoning = 0–30, memory = 0–20, semantic knowledge = 0–36, and cognitive activity = 0–6.
SLS participant characteristics.
Year of testing | ||||
---|---|---|---|---|
Measure | Baseline | Year 7 | Year 14 | Year 21 |
( |
( |
( |
( |
|
Retention from previous testing (%) | 56.4 | 47.7 | 40.8 | |
Age [M (SD)] | 67.1 (8.2) | 72.9 (7.3) | 77.9 (6.4) | 81.8 (4.9) |
Education [M (SD)] | 14.6 (2.9) | 14.7 (2.8) | 14.8 (2.7) | 14.8 (2.8) |
Sex, female [ |
859 (52) | 502 (54) | 255 (57) | 108 (60) |
Reasoning [M (SD)] | 15.6 (5.8) | 15.2 (5.6) | 14.3 (5.5) | 14.0 (5.3) |
Fluency [M (SD)] | 38.6 (12.8) | 37.5 (13.1) | 36.7 (12.7) | 38.8 (14.5) |
Memory [M (SD)] | 12.5 (4.0) | 12.0 (4.1) | 11.5 (4.2) | 11.6 (4.0) |
Semantic knowledge [M (SD)] | 25.0 (6.7) | 25.3 (6.6) | 25.8 (6.2) | 25.8 (5.9) |
Cognitive activity [M (SD)] | 2.4 (1.2) | 2.5 (1.2) | 2.5 (1.2) | 2.3 (1.2) |
Activity change [M (SD)] | — | −0.1 (1.1) | −0.2 (1.1) | −0.5 (1.3) |
M: mean; SD: standard deviation. The theoretical ranges for each measure with a defined upper limit are as follows: education = 0–20, reasoning = 0–30, memory = 0–20, semantic knowledge = 0–36, and cognitive activity = 0–5.
VLS participant characteristics.
Year of testing | |||||||
---|---|---|---|---|---|---|---|
Measure | Baseline | Year 3 | Year 6 | Year 9 | Year 12 | Year 15 | Year 18 |
|
|
|
|
|
|
|
|
Retention from previous testing (%)a | — | 73 | 79 | 72 | 69 | 72 | 57 |
Age [M (SD)] | 68.8 (6.8) | 71.4 (6.7) | 73.7 (6.5) | 76.6 (6.0) | 79.3 (5.2) | 82.2 (4.6) | 85.1 (3.6) |
Years of education at baseline [M (SD)] | 14.9 (3.3) | 15.4 (3.2) | 15.7 (3.1) | 15.8 (3.1) | 15.8 (3.1) | 15.2 (3.1) | 14.8 (2.8) |
Sex, female [ |
642 (63.5) | 459 (62.6) | 353 (61.0) | 256 (61.4) | 177 (61.9) | 60 (65.9) | 35 (67.3) |
Reasoning [M (SD)]b | 11.1 (4.6) | 11.6 (4.2) | 10.3 (4.7) | 10.3 (4.6) | 9.9 (4.6) | 7.5 (4.7) | 6.5 (4.2) |
Fluency [M (SD)] | 17.5 (4.4) | 17.9 (4.4) | 17.7 (4.4) | 17.2 (4.8) | 16.3 (4.9) | 14.7 (5.8) | 13.8 (5.4) |
Memory [M (SD)]c | 13.7 (5.9) | 14.6 (6.0) | 14.7 (6.1) | 14.8 (6.4) | 11.8 (5.5) | 13.0 (6.3) | — |
Semantic knowledge [M (SD)] | 43.6 (7.5) | 44.6 (6.3) | 44.3 (6.0) | 44.2 (5.9) | 43.6 (5.7) | 42.7 (7.1) | 42.6 (6.6) |
Cognitive activity [M (SD)] | |||||||
Communication | 0.1 (0.8) | 0.1 (0.8) | 0.0 (0.8) | −0.1 (0.8) | −0.2 (0.8) | −0.4 (0.8) | −0.4 (0.7) |
Computation | 0.1 (0.8) | 0.0 (0.8) | 0.0 (0.8) | 0.0 (0.8) | −0.1 (0.8) | −0.3 (0.7) | −0.5 (0.7) |
Conundrums | 0.0 (0.8) | 0.0 (0.8) | 0.0 (0.8) | 0.0 (0.8) | 0.0 (0.8) | −0.2 (0.9) | −0.2 (0.8) |
Activity change [M (SD)] | |||||||
Communication | — | 0.0 (0.5) | −0.2 (0.6) | −0.3 (0.6) | −0.4 (0.6) | −0.5 (0.6) | −0.6 (0.5) |
Computation | — | −0.1 (0.6) | −0.2 (0.6) | −0.3 (0.6) | −0.4 (0.7) | −0.4 (0.7) | −0.5 (0.8) |
Conundrums | — | 0.0 (0.6) | −0.1 (0.6) | −0.1 (0.7) | −0.2 (0.6) | −0.3 (0.8) | −0.4 (0.7) |
M: mean; SD: standard deviation. The theoretical ranges for each measure with a defined upper limit are as follows: reasoning 0–20, memory 0–30, and semantic knowledge 0–54. The cognitive activity scores are on a normal metric with means of approximately 0 and SD of approximately 0.8.
aThe 1986 cohort was followed for up to 18 years and the 1993 cohort for up to 12.
bThe reasoning measure was not given until year 6 for the 1986 cohort.
cThe memory measure was not given in year 18.
The Octo-Twin study is based on the oldest cohort of the Swedish Twin Registry and includes 702 participants aged 80 years and older at the time of the first examination. All individuals with a dementia diagnosis at baseline were excluded from the analyses (
The cognitive activity measure was based on self-report of engagement in six cognitively stimulating activities including playing games (e.g., chess and bridge), completing crossword puzzles, reading literature, writing, conducting genealogical research, or any otherdocumentation,studies, or other mentally demanding activity (e.g., handicraft), each rated dichotomously as “no” (0) or “yes” (1). Participants were also asked if they “train their memory or keep their mind active” rated as “no” (0), “yes, to a certain degree” (1), or “yes, definitely” (2). A composite score for cognitive activity was created by summing responses across items (range = 0–8). Change in cognitive activity was computed by subtracting the cognitive activity score at baseline from all subsequent activity scores.
The LBLS was started in 1978 in Long Beach, California, with participants recruited from the Family Health Plan Health Maintenance Organization (HMO) who were primarily from Long Beach and Orange Counties. Panel 1 included 583 individuals aged 28–36 or 55–87. The ethnic composition of the older group (98% Caucasian) was similar to the 65+ population for the area based on the 1970 census. Panel 2, initiated in 1992, included 633 contacted from the same HMO (64 were excluded due to frank dementia, serious sensory, or neurological problems). In order to include the same measures as those in the Seattle Longitudinal Study, LBLS Panel 1 (
Demographic information and descriptive statistics for the sample are presented in Table
The cognitive activity measure was derived from a modified version of the Life Complexity Scale (LCS), originally developed for the Seattle Longitudinal Study [
The SLS was initiated in 1956 in Seattle, Washington, and includes eight samples recruited from a local HMO at seven-year intervals and followed longitudinally every seven years (total
The cognitive activity measure was derived by summing dichotomized test responses to five cognitive activity items (reading, educational activities, music, writing, and cultural activities) from a modified version of the Life Complexity Scale [
The VLS was begun in the 1986 in Victoria, British Columbia, and consists of three cohorts started in 1986, 1992, and 2001, respectively, followed longitudinally at 3-year intervals. Longitudinal data used in this study were from Samples 1 (baseline
The cognitive activity measure included a subset of items from the VLS Activity Lifestyle Questionnaire [
The current analysis was conducted as part of a larger effort to examine the effects of lifestyle activities on cognitive function using the same analytic approach across studies from the Integrative Analysis of Longitudinal Studies on Aging (IALSA) network [
An initial 19-term model included the following terms: (1) baseline age, (2) sex, (3) education, (4) baseline activity, (5) baseline activity × age, (6) baseline activity × sex, (7) baseline activity × education, (8) individually defined time since baseline, (9) time × baseline age, (10) time × sex, (11) time × education, (12) time × baseline activity, (13) time × baseline activity × baseline age, (14) time × baseline activity × sex, (15) time × baseline activity × education, (16) change in activity from baseline (activity change), (17) activity change × baseline age, (18) activity change × sex, and (19) activity change × education. This full model was evaluated in each study data set independently, and terms that were not significant in any of the four studies were dropped in order to present a parsimonious set of results that retained the fullest set of parameters found in any study. This process eliminated 7 of the 19 terms, including all 3-way interactions, and four of the 2-way interactions, including the interactions between activity change and age, sex, or education, as well as the interaction between baseline activity level and sex. This resulted in a final model that included 12 terms summarized in Table
Mixed effects model summaries across four studies with baseline cognitive activity and activity change predicting four cognitive outcomes.
Octo-Twin | LBLS | SLS | VLS | |||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Reasoning | Communication | Computation | Conundrums | |||||||||||||||
|
SE |
|
|
SE |
|
|
SE |
|
|
SE |
|
|
SE |
|
|
SE |
| |
Intercept | 11.17 | 0.64 | <0.001 | 20.98 | 0.58 | <0.001 | 14.83 | 0.18 | <0.001 | 9.60 | 0.58 | <0.001 | 9.06 | 0.56 | <0.001 | 9.64 | 0.57 | <0.001 |
Age | −0.32 | 0.10 | 0.002 | −0.60 | 0.05 | <0.001 | −0.35 | 0.01 | <0.001 | −0.25 | 0.02 | <0.001 | −0.22 | 0.02 | <0.001 | −0.24 | 0.02 | <0.001 |
Sex | 0.10 | 0.59 | 0.862 | 2.58 | 0.82 | 0.002 | 1.40 | 0.24 | <0.001 | −0.12 | 0.31 | 0.700 | 0.42 | 0.31 | 0.170 | −0.19 | −0.19 | 0.300 |
Education | 0.39 | 0.14 | 0.015 | 1.24 | 0.15 | <0.001 | 0.48 | 0.05 | <0.001 | 0.29 | 0.05 | <0.001 | 0.25 | 0.05 | <0.001 | 0.32 | 0.05 | <0.001 |
Activity | 1.46 | 0.18 | <0.001 | 0.02 | 0.33 | 0.956 | 0.34 | 0.11 | 0.001 | 0.45 | 0.20 | 0.024 | 1.24 | 0.19 | <0.001 | 0.94 | 0.19 | <0.001 |
Age × activity | 0.05 | 0.06 | 0.389 | 0.09 | 0.04 | 0.020 | 0.01 | 0.01 | 0.286 | 0.00 | 0.02 | 0.876 | 0.04 | 0.02 | 0.078 | 0.02 | 0.02 | 0.447 |
Education × activity | −0.05 | 0.06 | 0.453 | 0.04 | 0.10 | 0.702 | −0.05 | 0.03 | 0.168 | −0.12 | 0.05 | 0.020 | 0.00 | 0.05 | 0.923 | 0.05 | 0.05 | 0.404 |
Time | −0.45 | 0.09 | <0.001 | −0.50 | 0.08 | <0.001 | −0.25 | 0.02 | <0.001 | −0.24 | 0.03 | <0.001 | −0.25 | 0.03 | <0.001 | −0.25 | 0.03 | <0.001 |
Age × time | −0.02 | 0.02 | 0.274 | −0.03 | 0.01 | 0.000 | −0.01 | 0.00 | <0.001 | −0.01 | 0.00 | <0.001 | −0.01 | 0.00 | <0.001 | −0.01 | 0.00 | <0.001 |
Sex × time | 0.09 | 0.10 | 0.367 | 0.07 | 0.11 | 0.536 | 0.01 | 0.02 | 0.545 | 0.02 | 0.03 | 0.598 | 0.04 | 0.03 | 0.232 | 0.01 | 0.03 | 0.643 |
Education × time | 0.03 | 0.02 | 0.224 | −0.06 | 0.02 | 0.008 | −0.01 | 0.00 | 0.092 | −0.01 | 0.01 | 0.091 | −0.01 | 0.00 | 0.061 | −0.01 | 0.00 | 0.138 |
Activity × time | 0.02 | 0.03 | 0.595 | 0.05 | 0.05 | 0.337 | 0.01 | 0.01 | 0.173 | 0.03 | 0.02 | 0.145 | 0.05 | 0.02 | 0.025 | −0.01 | 0.02 | 0.692 |
Activity change | 0.41 | 0.13 | 0.002 | 0.28 | 0.20 | 0.164 | 0.24 | 0.09 | 0.006 | 0.38 | 0.14 | 0.005 | 0.49 | 0.13 | <0.001 | 0.23 | 0.12 | 0.059 |
| ||||||||||||||||||
— | LBLS | SLS | VLS | |||||||||||||||
Fluency | Communication | Computation | Conundrums | |||||||||||||||
|
SE |
|
|
SE |
|
|
SE |
|
|
SE |
|
|
SE |
| ||||
| ||||||||||||||||||
Intercept | 30.94 | 0.66 | <0.001 | 36.46 | 0.46 | <0.001 | 11.68 | 0.53 | <0.001 | 11.28 | 0.55 | <0.001 | 11.73 | 0.53 | <0.001 | |||
Age | −0.31 | 0.05 | <0.001 | −0.34 | 0.04 | <0.001 | −0.08 | 0.02 | 0.001 | −0.08 | 0.02 | 0.002 | −0.07 | 0.02 | 0.006 | |||
Sex | 3.42 | 0.93 | <0.001 | 2.88 | 0.61 | <0.001 | 0.63 | 0.34 | 0.065 | 1.02 | 0.36 | 0.005 | 0.54 | 0.34 | 0.115 | |||
Education | 0.88 | 0.17 | <0.001 | 1.17 | 0.11 | <0.001 | 0.47 | 0.05 | <0.001 | 0.58 | 0.05 | <0.001 | 0.60 | 0.05 | <0.001 | |||
Activity | 1.14 | 0.37 | 0.002 | 1.03 | 0.27 | 0.001 | 1.80 | 0.22 | <0.001 | 0.81 | 0.22 | <0.001 | 1.68 | 0.21 | <0.001 | |||
Age × activity | 0.07 | 0.04 | 0.121 | 0.00 | 0.03 | 0.900 | 0.01 | 0.03 | 0.709 | 0.04 | 0.03 | 0.112 | 0.04 | 0.03 | 0.094 | |||
Education × activity | 0.05 | 0.11 | 0.651 | 0.00 | 0.08 | 0.995 | −0.12 | 0.06 | 0.042 | −0.04 | 0.05 | 0.489 | 0.03 | 0.06 | 0.659 | |||
Time | −0.22 | 0.11 | 0.052 | −0.42 | 0.04 | <0.001 | −0.11 | 0.03 | <0.001 | −0.13 | 0.03 | <0.001 | −0.13 | 0.03 | <0.001 | |||
Age × time | −0.02 | 0.01 | 0.015 | −0.02 | 0.00 | <0.001 | −0.01 | 0.00 | 0.001 | −0.01 | 0.00 | 0.001 | −0.01 | 0.00 | 0.001 | |||
Sex × time | −0.17 | 0.15 | 0.252 | 0.11 | 0.05 | 0.025 | 0.07 | 0.04 | 0.058 | 0.08 | 0.04 | 0.050 | 0.07 | 0.04 | 0.078 | |||
Education × time | 0.01 | 0.03 | 0.778 | −0.01 | 0.01 | 0.105 | 0.00 | 0.01 | 0.823 | 0.00 | 0.01 | 0.955 | 0.00 | 0.01 | 0.954 | |||
Activity × time | −0.06 | 0.07 | 0.350 | 0.02 | 0.02 | 0.324 | 0.00 | 0.03 | 0.868 | 0.02 | 0.03 | 0.448 | 0.01 | 0.03 | 0.793 | |||
Activity change | 0.49 | 0.30 | 0.097 | 0.50 | 0.20 | 0.012 | 0.76 | 0.18 | <0.001 | 0.68 | 0.18 | <0.001 | 0.48 | 0.16 | 0.003 | |||
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Octo-Twin | LBLS | SLS | VLS | |||||||||||||||
Memory | Communication | Computation | Conundrums | |||||||||||||||
|
SE |
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|
SE |
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|
SE |
|
|
SE |
|
|
SE |
|
|
SE |
| |
| ||||||||||||||||||
Intercept | 8.84 | 0.29 | <0.001 | 10.73 | 0.21 | <0.001 | 11.68 | 0.13 | <0.001 | 17.37 | 0.41 | <0.001 | 17.06 | 0.40 | <0.001 | 17.51 | 0.41 | <0.001 |
Age | −0.18 | 0.06 | 0.001 | −0.20 | 0.02 | <0.001 | −0.18 | 0.01 | <0.001 | −0.19 | 0.02 | <0.001 | −0.17 | 0.02 | <0.001 | −0.18 | 0.02 | <0.001 |
Sex | 0.91 | 0.99 | 0.006 | 1.41 | 0.30 | <0.001 | 1.40 | 0.18 | <0.001 | 1.58 | 0.26 | <0.001 | 2.13 | 0.27 | <0.001 | 1.50 | 0.26 | <0.001 |
Education | 0.35 | 0.07 | <0.001 | 0.25 | 0.05 | <0.001 | 0.26 | 0.03 | <0.001 | 0.23 | 0.04 | <0.001 | 0.25 | 0.04 | <0.001 | 0.30 | 0.04 | <0.001 |
Activity | 0.59 | 0.10 | <0.001 | 0.17 | 0.12 | 0.142 | 0.41 | 0.08 | <0.001 | 0.96 | 0.17 | <0.001 | 1.17 | 0.16 | <0.001 | 0.85 | 0.16 | <0.001 |
Age × activity | −0.01 | 0.04 | 0.930 | 0.00 | 0.01 | 0.776 | 0.00 | 0.01 | 0.901 | 0.07 | 0.02 | <0.001 | 0.06 | 0.02 | 0.002 | 0.06 | 0.02 | 0.002 |
Education × activity | −0.02 | 0.04 | 0.663 | 0.04 | 0.04 | 0.247 | 0.00 | 0.02 | 0.948 | −0.07 | 0.04 | 0.127 | −0.02 | 0.04 | 0.658 | −0.04 | 0.05 | 0.345 |
Time | −0.27 | 0.07 | <0.001 | −0.17 | 0.05 | 0.001 | −0.17 | 0.01 | <0.001 | −0.26 | 0.03 | <0.001 | −0.26 | 0.03 | <0.001 | −0.28 | 0.03 | <0.001 |
Age × time | 0.00 | 0.02 | 0.947 | 0.00 | 0.00 | 0.627 | −0.01 | 0.00 | <0.001 | −0.01 | 0.00 | <0.001 | −0.01 | 0.00 | <0.001 | −0.01 | 0.00 | <0.001 |
Sex × time | 0.06 | 0.08 | 0.465 | −0.03 | 0.07 | 0.705 | 0.03 | 0.02 | 0.112 | −0.01 | 0.03 | 0.783 | −0.01 | 0.03 | 0.736 | −0.01 | 0.03 | 0.660 |
Education × time | 0.00 | 0.02 | 0.932 | 0.01 | 0.01 | 0.691 | 0.00 | 0.00 | 0.549 | 0.00 | 0.01 | 0.349 | 0.00 | 0.00 | 0.349 | −0.01 | 0.00 | 0.246 |
Activity × time | 0.03 | 0.02 | 0.231 | 0.04 | 0.03 | 0.216 | 0.00 | 0.01 | 0.827 | 0.01 | 0.02 | 0.708 | 0.00 | 0.02 | 0.923 | 0.03 | 0.02 | 0.164 |
Activity change | 0.35 | 0.09 | <0.001 | 0.25 | 0.12 | 0.039 | 0.25 | 0.07 | 0.001 | 0.71 | 0.13 | <0.001 | 0.78 | 0.12 | <0.001 | 0.18 | 0.12 | 0.126 |
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Semantic knowledge | Octo-Twin | LBLS | SLS | VLS | ||||||||||||||
Communication | Computation | Conundrums | ||||||||||||||||
|
SE |
|
|
SE |
|
|
SE |
|
|
SE |
|
|
SE |
|
|
SE |
| |
| ||||||||||||||||||
Intercept | 31.60 | 0.69 | <0.001 | 37.89 | 0.59 | <0.001 | 24.54 | 0.23 | <0.001 | 44.23 | 0.68 | <0.001 | 43.66 | 0.68 | <0.001 | 44.07 | 0.69 | <0.001 |
Age | −0.40 | 0.14 | 0.004 | −0.29 | 0.05 | <0.001 | 0.01 | 0.02 | 0.501 | 0.09 | 0.03 | 0.004 | 0.11 | 0.03 | <0.001 | 0.09 | 0.03 | 0.004 |
Sex | −5.17 | 0.85 | <0.001 | 1.60 | 0.84 | 0.056 | 0.12 | 0.31 | 0.688 | −0.07 | 0.44 | 0.865 | 0.68 | 0.46 | 0.137 | −0.18 | 0.45 | 0.687 |
Education | 1.60 | 0.20 | <0.001 | 0.95 | 0.15 | <0.001 | 0.99 | 0.06 | <0.001 | 0.58 | 0.07 | <0.001 | 0.65 | 0.07 | <0.001 | 0.72 | 0.07 | <0.001 |
Activity | 2.21 | 0.25 | <0.001 | 0.75 | 0.34 | 0.026 | 0.81 | 0.14 | <0.001 | 1.97 | 0.28 | <0.001 | 1.77 | 0.28 | <0.001 | 1.37 | 0.27 | <0.001 |
Age × activity | 0.03 | 0.09 | 0.737 | 0.05 | 0.04 | 0.199 | 0.02 | 0.02 | 0.277 | 0.05 | 0.03 | 0.113 | 0.06 | 0.03 | 0.074 | 0.07 | 0.03 | 0.039 |
Education × activity | −0.23 | 0.10 | 0.014 | −0.05 | 0.10 | 0.647 | −0.05 | 0.04 | 0.206 | −0.33 | 0.07 | <0.001 | −0.28 | 0.07 | <0.001 | −0.09 | 0.08 | 0.242 |
Time | −0.92 | 0.12 | <0.001 | −0.40 | 0.09 | <0.001 | −0.11 | 0.01 | <0.001 | 0.03 | <0.001 | −0.14 | 0.03 | <0.001 | −0.16 | 0.03 | <0.001 | |
Age × time | −0.05 | 0.03 | 0.064 | −0.03 | 0.01 | <0.001 | −0.01 | 0.00 | <0.001 | −0.01 | 0.00 | <0.001 | −0.01 | 0.00 | <0.001 | −0.01 | 0.00 | <0.001 |
Sex × time | 0.30 | 0.14 | 0.036 | 0.05 | 0.12 | 0.678 | 0.06 | 0.02 | 0.001 | 0.03 | 0.04 | 0.379 | 0.02 | 0.04 | 0.533 | 0.03 | 0.04 | 0.439 |
Education × time | 0.04 | 0.03 | 0.155 | −0.03 | 0.02 | 0.185 | 0.00 | 0.00 | 0.447 | 0.00 | 0.01 | 0.510 | 0.00 | 0.01 | 0.725 | 0.00 | 0.01 | 0.453 |
Activity × time | −0.02 | 0.04 | 0.571 | 0.03 | 0.05 | 0.627 | 0.01 | 0.01 | 0.069 | 0.02 | 0.02 | 0.442 | −0.01 | 0.02 | 0.773 | 0.01 | 0.02 | 0.524 |
Activity change | 0.47 | 0.17 | 0.005 | 0.44 | 0.20 | 0.027 | 0.26 | 0.07 | <0.001 | 0.49 | 0.15 | 0.001 | 0.53 | 0.14 | <0.001 | 0.49 | 0.13 | <0.001 |
Values represent model coefficients and their standard error. Across all studies, time was measured in years since baseline visit, and activity change was entered as a time-varying covariate. All other variables represent baseline measurements alone, in interaction with one another or in interaction with time.
There was a significant relationship between self-reported cognitive activity at baseline and baseline performance on tests of cognitive abilities across all measures and studies but the LBLS, which did not find this relationship in the reasoning and memory models. Overall, these findings suggest that participants who were more cognitively active at baseline tended to have better cognitive performance. One of the studies (VLS) included three distinct measures of cognitive activity—those involving Communication (e.g., writing), Computations (e.g., managing finances), and Conundrums (e.g., completing crossword puzzles)—enabling us to determine if specific cognitive activities were differentially related to the cognitive outcomes. While all three types of cognitive activities showed significant cross-sectional relationships with cognitive outcomes (all
Older age was associated with lower baseline performance across all studies on measures of reasoning, fluency, and memory. In contrast, the relationship between age and baseline performance on semantic knowledge measures was inconsistent, with LBLS and Octo-Twin results suggesting lower performance in older age, SLS showing no age differences, and VLS suggesting that older age was associated with better performance. Baseline associations between sex and cognitive performance showed a consistent relationship across studies for all memory outcomes, with women consistently performing higher than similar aged men. SLS and LBLS women additionally performed higher than men on reasoning and fluency measures. Across other cognitive outcomes, baseline associations between performance and sex were less consistent, with VLS women performing better on fluency in the Computations model and Octo-Twin women performing lower than men on semantic knowledge. Higher education was consistently associated with higher baseline cognitive performance across all studies and cognitive outcomes.
Two baseline covariate interaction terms were retained in the final model, and both showed inconsistent relationships across studies and outcome measures: the age by baseline cognitive activity interaction term was significant in the VLS memory models and the Conundrums/semantic knowledge model. There was a similarly significant interaction between baseline age and activity level in the LBLS reasoning model (
Across all studies and cognitive outcomes, there was, with one exception (VLS computation with reasoning), no evidence for baseline level of cognitive activity predicting change in cognitive outcomes over time. There was, however, a consistent positive relationship between change in cognitive activity from baseline and within person variability in cognitive outcomes across nearly all cognitive outcomes in all four studies. Specifically, after accounting for the expected linear within person trajectories, variation in cognitive activity was significantly related to variation in performance on all measures in all studies except reasoning and fluency in LBLS and reasoning and memory, in the case of Conundrums only, in VLS.
Within-person declines were seen over time across all studies and all cognitive outcomes except LBLS fluency. Older participants declined faster compared to younger participants on all VLS, SLS, and LBLS cognitive outcome measures except LBLS memory. Evidence for differential decline in older participants was not seen in Octo-Twin, which has a much narrower age range. Women declined less than men on fluency measures in the SLS and VLS Computations models and on semantic knowledge measures in the SLS and Octo-Twin study. Level of education was not a significant predictor of rate of cognitive decline in all but one study (LBLS) and one outcome measure (reasoning, coefficient = −0.06,
Our results provide compelling evidence across four longitudinal studies that changes in everyday cognitive activity level tracks with variation in multiple aspects of cognitive function. In three of the four studies (Octo-Twin, SLS, and VLS), participants reported engaging in fewer cognitive activities over time. In the fourth study (LBLS), participants endorsed a slight increase in average number of cognitive activities over time, which was likely due to differential retention of higher functioning individuals. While the overall trend was for participants to report slightly less cognitive activity at each follow-up visit in all but the LBLS sample, there was actually considerable variability in activity change scores, with some participants in each study reporting increased cognitive activity at follow-up visits relative to their baseline levels.
These results suggest that there is an increased risk of cognitive decline for individuals whose engagement in cognitive activities decreases over time relative to their baseline levels, and, conversely, the results suggest that increases in cognitive activity from baseline are associated with better than expected cognitive performance. Cognitive activity change appeared to most consistently track with variation in semantic knowledge, as the activity change term was significant in all six models. Strong evidence of activity change tracking with fluctuations in memory and fluency was also indicated, as five of six models had significant activity change terms in the memory models and in four of the five fluency models. Activity change was significantly related to variation in reasoning in four of the six models, making the models with reasoning outcomes the least consistent relative to models with the other cognitive outcomes. That two of the four inconsistent findings occurred in LBLS, which had the most similarity with SLS, in terms of both measures and sampling, suggests that some other factor, such as attrition, may be responsible for these differences. It is interesting to note, however, that the standard deviation of reported activity level did not differ from that of SLS. The lack of association with reasoning and memory for one of the three VLS activity variables (Conundrums) could be due to chance, although this finding may also suggest that changes in level of engagement on tasks involving problem solving are less related to changes in reasoning and memory function than they are to changes in fluency and semantic knowledge.
Across studies, with the exception of VLS Computation with reasoning, there were no significant relationships between baseline cognitive activity and change in cognition over time, suggesting that level of cognitive activity at an earlier point in time is not related to subsequent cognitive decline. Thus, these results do not demonstrate that level of engagement in cognitively stimulating activities earlier in older adulthood can somehow increase one’s cognitive reserve or ability to maintain cognitive function in spite of age-related brain changes [
In terms of cross-sectional relationships, all studies provide evidence for activity/cognition relationships, and the VLS results allow us to conclude that level of engagement in cognitive activities involving what we termed “Conundrums” (e.g., playing chess, completing crossword puzzles) are most strongly and consistently related to concurrent function across cognitive domains, but evidence for relationships between engagement in activities involving Computations (e.g., balancing a check book) and Communication (e.g., writing letters) was also demonstrated. Thus, while the data do not provide particularly compelling evidence that engagement in one type of cognitively stimulating activity is preferable, activities involving novel information processing appear to be most related to concurrent cognitive function, a finding that is consistent with the extant literature [
The lack of evidence for cognitive activity level at baseline predicting cognitive decline over time in some respects may be interpreted as discouraging, as it implies that older adults who more frequently engage in cognitive activities may not be influencing the trajectory of their cognitive function in the coming years. However, across all studies, change in level of cognitive activity from baseline generally followed a normal distribution, with considerable portions of each sample reporting an increase in level of cognitive activity from baseline levels. The positive association between cognitive activity change and the cognitive outcomes across studies thus suggests that individuals who increase their cognitive activities may be effectively reducing age-related cognitive decline.
Our results demonstrate that older age is associated with faster decline, which supports the overall validity of our approach and suggests that we are detecting relevant change. The finding that education was not predictive of rate of cognitive decline with one exception (the LBLS reasoning model) suggests that education is not protective or predictive of a faster decline in normal aging. These multistudy results build upon findings from a recent paper using data from one of the studies (VLS) included in the current paper [
The current study has many strengths, including the large sample sizes and multinational representation in our study samples, which improves the generalizability of the findings. In addition, the inclusion of four separate studies with unique sample characteristics, methodologies for recruitment, different methods for measuring cognitive activity and cognitive function, and differing frequency and length of followup, all serve to minimize the likelihood that these findings are spurious. When results across such a coordinated analysis are inconsistent, any one of these differences between studies could be responsible for discrepancies and reflect a limitation of the design. For example, the inconsistencies in the relationships between baseline covariates and their interactions (e.g., sex and age with baseline activity level) highlight a weakness of our study design. Inconsistencies could also be attributable to the heterogeneity in the activity measures used across the four longitudinal studies, as the scales included different items with different response ratings, yielding restricted ranges of responses on some measures. It is also possible that the inconsistencies are due to differences in the cognitive outcomes used in the different studies, or any number of other differences in the methodologies across studies. However, it is important to note that when the model results demonstrate consistent patterns across studies despite variations in methodology, the heterogeneity of measures and sampling methods becomes a major strength of the multi-study approach, as there is improvement in the reliability of conclusions that can be drawn from the results, relative to the typical single-study design.
Perhaps the most obvious limitation inherent in the observational design of all studies included in this investigation is that conclusions implying causality cannot be inferred from these results. Specifically, while an increase in cognitive activity from baseline was associated with better than expected cognitive performance, and, conversely, activity decrease was associated with worse than expected performance, it is not possible to conclude that change in activity level was the cause for change in rate of cognitive decline. An alternative explanation is that decreases in level of cognitive activity from baseline levels observed in this study result from deteriorating cognitive functions rather than cause it. Put simply, this study design does not answer whether completing crossword puzzles reduces one’s risk of cognitive decline or if cognitive decline reduces the likelihood that one will complete crossword puzzles. In addition, this study does not address the protective effects of cognitive activity for incident dementia or Alzheimer’s disease. While there is a large body of the literature examining the beneficial effects of cognitive activity in reducing dementia risk (e.g., [
What these results impart, however, is that regardless of the causal mechanisms underlying these changes, the associations between cognitive activity and cognitive outcomes in this study are in directions that are intuitively and scientifically consistent with prior literature. This fact, coupled with the large-scale naturalistic, observational design of this study, lends credence to the burgeoning literature that directly examines the causal effect of cognitive activity on cognitive outcomes. Extension of this work in populations at great risk for dementia, or with individuals already diagnosed with neurodegenerative diseases, remains a worthwhile goal.
The research was supported in part by the Integrative Analysis of Longitudinal Studies of Aging (IALSA) research network (NIA AG026453, S. M. Hofer and A. M. Piccinin, PIs) and the