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Y. Rabinowitz1,2, R. Ravona-Springer2,3,4, A. Heymann3,5, E. Moshier6, Y. Berman4, J. Schwartz4, M. Sano7, D. Aisenberg1, M. Schnaider-Beeri4,7


1. Department of Gerontological Clinical Psychology, Ruppin Academic Center, Israel; 2. Memory Clinic, Sheba Medical Center, Tel HaShomer, Israel; 3. Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel; 4. The Joseph Sagol Neuroscience Center, Sheba Medical Center, Israel; 5. Maccabi Healthcare Services, Tel Aviv, Israel; 6. Institute for Health Care Delivery Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA; 7. Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA

Corresponding Author: Yaacov Rabinowitz, Israel, Akiva 22, Ra’anana, Israel, 972-54-5421240,, ORCID ID:

J Prev Alz Dis 2023;
Published online March 16, 2023,



Background: Physical activity is associated with slower cognitive decline in old age. Type 2 diabetes (T2d) is a risk factor for dementia and cognitive decline. Physical activity protects against several T2d complications. Yet, little is known about the contribution of physical activity to cognitive health among the elderly with T2d.
Objectives: To examine the association between physical activity and cognitive decline in older adults with T2d. Design: This is a prospective longitudinal study using data from the Israel Diabetes and Cognitive Decline (IDCD) study. Setting: ICDC study (N=1,213), is a population-based cohort of adults over the age of 65, diagnosed with type 2 diabetes, who were cognitively normal at baseline and followed up every 18 months.
Participants: Participants with at least one follow-up assessment who were in the same physical activity group consistently and had complete demographic data.
Measurements: Physical activity was measured using Minnesota Leisure Time Activity Questionnaire, cognitive functioning was measured using a broad neuropsychological assessment measuring Executive Functioning, Attention/Working Memory, Semantic Categorization and Episodic Memory.
Results: Participants were classified into physical activity groups based on self-reported physical activity at baseline and all follow ups: “active” – participation in recreational physical activity (n=286); “non-active”- the only physical activity was walking from place to place (n=93) and “sedentary” (n=19). Linear mixed effects models were applied to adjust for key demographic and cardiovascular risk factors. Participants were 72.4 (SD 4.6) years old, had 13.3 (SD 3.6) years of education, and 163 (41%) were female. In the fully adjusted model, compared to the non-active group the active group had significantly slower rate of decline in Global Cognition (p=0.005), Executive Functioning (p=.014), and Attention/Working Memory (p=.01). There were no significant group differences for Semantic Categorization (p=.17) and Episodic Memory (p=.88).
Conclusions: Among initially cognitively normal and independent older adults with T2d, a physically active lifestyle was associated with a slower rate of cognitive decline. Future research should examine whether promoting physical activity may prevent or delay onset of dementia in this high-risk population.

Key words: Cognitive decline, dementia, physical activity, type 2 diabetes.



Owing to the increase in longevity in many countries, there is a burgeoning interest in preventing cognitive decline associated with aging and in reducing the risk for age-related neurological disorders, such as Alzheimer’s disease (1). Physical activity has been shown to have many benefits for health and well-being across the life span (2). An increasing body of evidence supports the role of physical activity as a means to maintain cognitive functioning and decrease the risk of cognitive decline and dementia (3–6). Associations have been found between midlife and late life physical activity with better cognitive outcomes (7) and there are suggestions that in addition to the benefits that physical activity may confer to cognitive health in the short-term, it may also benefit memory in the long-term (8, 9).
Type 2 diabetes is a well-established risk factor for dementia and cognitive decline (9, 10). Research investigating the relationship of physical activity with cognition in type 2 diabetes is primarily cross sectional (11), with limited longitudinal research (12), and consistently suggests a protective effect. Associations are found with global cognition but also with specific cognitive domains, primarily executive function (13) and episodic memory (14) possibly indicating that physical activity affects differentially brain regions underlying cognition.
We examined the associations of physical activity with longitudinal decline in global cognition and in specific cognitive domains in a population-based cohort of initially cognitively normal, independent older adults with type 2 diabetes, adjusting for a broad range of potential confounders.


Experimental procedures

This is a prospective longitudinal study using data from the Israel Diabetes and Cognitive Decline (IDCD) study (N=1,213), a population-based cohort of adults over the age of 65, diagnosed with type 2 diabetes, who were cognitively normal at baseline. The study is a collaboration between the Icahn School of Medicine at Mount Sinai, New York, the Sheba Medical Center, Israel, and the Maccabi Health Services, Israel. The study is approved by all three IRBs and all participants signed informed consent.
The IDCD study methods have been described in detail elsewhere (10). Briefly, community-dwelling Israeli elderly individuals with T2D (65 years old) were recruited from the Maccabi Health Services diabetes registry. Participants had complete, demographic, and T2D-related characteristics data. Criteria for enrollment into the IDCD study were having T2D; having normal cognition on entry; being free of any neurological (e.g., Parkinson disease, stroke), major psychiatric (e.g., schizophrenia), or other diseases (e.g., alcohol or drug abuse) that might affect cognition; having an informant; being fluent in Hebrew; and living in the area of greater Tel Aviv (15).


Baseline assessments included medical, neurological, and psychiatric exams, a blood draw for APOE ε4 genotyping, basic demographic and anthropometric information (age, sex, years of education, weight, height). Blood measurements including HbA1c, total cholesterol, high density lipoprotein (HDL), low density lipoprotein (LDL), triglycerides and creatinine and T2D medication use were received from the Maccabi Diabetes Registry. Since Maccabi provided numerous measurements of each of these blood exams, we used the mean of all exams for each participant. In addition, assessments of daily living, functional assessments, a neuropsychological battery and assessments of physical activity were conducted (details below). Follow-up assessments were done at 18-month intervals. Participants who developed clinical dementia at follow-up were no longer followed.

Functional assessments

Activities of daily living (ADL) were assessed using the self-reported Barthel scale (eating, bathing, personal hygiene, dressing, bowel control, bladder control, toilet, transfer, walking, climbing stairs). The range of scores is 0-100, each item is rated as 0-unable, 1-needs help and 2-independent and the total score is multiplied by five. A score of 100 reflects full independence (16). Instrumental ADL (IADL) was assessed using the Lawton scale (using the phone, going to places, shopping, preparing meals, doing housework, doing the laundry, taking medications, doing financial chores). The range of scores is 0-16, each of the eight items is scored 0-unable, 1-needs assistance, 2-independent and a score of 16 reflects full independence (17).

Physical activity

Participation and extent of participation in various physical activities over the previous 2 weeks (18) was recorded using a modified version of the Minnesota Leisure Time Activity Questionnaire (19). The activities included in the scale are those most common among older adults such as swimming, jogging or pace-walking, dancing, spinning, or light exercise (yoga, Pilates etc.) (20). The scale was found to yield reliable results among older adult populations (18) and was used to categorize three different levels of PA (21). Certain activities have several forms of participation such as cross-country walking and walking as a means of transportation. Groups were a priori operationalized as follows: (1) physically active- participating in any sport or recreational activities including dancing, aerobics, ball or competitive sports, running, jogging, cross-country walking etc.; (2) not physically active- walking as a means of transportation (walking from place to place, walking at work etc.) but not partaking in any other physical activity; and (3) sedentary , not partaking in any sort of physical activity (not even walking as a means of transportation). Although the specific physical activity measures were recorded but the number of times a participant performed the activity in a week, or its intensity were not recorded. In addition, PA level was self-reported rather than directly measured. Thus, only participants who were consistently in the same physical activity group at all visits were included to more reliably reflect their level of physical activity.

Neuropsychological assessment

A broad neuropsychological assessment of 14 tests is detailed elsewhere (22) and covered four domains: Memory (Alzheimer’s Disease Assessment Scale [ADAS] (23), word list immediate recall, delayed recall, and recognition), Attention/Working memory (Diamond Cancellation, Digit Span forward and backward), Executive Functions (Trails Making Test A and B, Digit Symbol Substitution Test), and Semantic categorization (Similarities, Letter and Animal Fluency). Composite measures of the four cognitive domains were calculated at baseline by converting each test score to a z-score and then averaging the z-scores. For follow-up assessments, the baseline means and standard deviations were used for conversion. A global cognition measure was calculated by averaging the z-scores from all tests (10).

Statistical analyses

Descriptive data are reported as N (percent) or mean (standard deviation [SD]), as appropriate and t-tests and chi-square analyses compared characteristics of active vs. non-active physical activity. A linear mixed model was used to estimate the rates of change per month in global cognitive z-scores (and the four cognitive domain scores (Attention/Working Memory, Executive Function, Semantic Categorization and Episodic Memory)), comparing the physically active to the non-physically active groups. A random intercept with an unstructured covariance was assumed to account for the correlation among repeated measures made within a subject. Time of follow-up assessment, physical activity group and an interaction term between time and activity group was included in each model. Rates of change over time were compared between physical activity groups by testing whether the interaction term was equal to zero. Models were adjusted for key variables as follows: (1) demographics (age, sex and education), (2) cardiovascular risk factors (HbA1c, total cholesterol, creatinine, triglycerides, LDL and HDL), T2D medication use (as detailed in (24), ADL and BMI. Statistical analyses were conducted using SAS Version 9.4 (SAS Institute Inc., Cary, NC). All hypothesis testing were 2-sided with type 1 error rate fixed at 5% for determination of statistical significance.



Figure 1 presents a flow diagram of study sample. Of 818 participants with at least one follow-up assessment, 395 met a-priori inclusion criteria of being in the same physical activity group consistently and having complete demographic data. Using prespecified criteria 286 participants met criteria to be categorized as being in the active group, 90 in the non-active group and 19 in the sedentary group. Because of the small size of the sedentary group (n=19) which further diminished in the second-round of analysis to 8 subjects due to missing data on cardiovascular risk factors, they were combined with the non-active group. Supplementary tables provide the three-group analysis and render very similar results (Supplementary e-tables 1, 2).

Figure 1. Participant flow


Participants mean age was 72.4 (SD=4.43), 41% female, with a mean follow-up of 42 months (range 12-72). Physically active participants had lower BMI, more education, fewer participants with ADL impairment and longer follow-up time compared to non physically active participants. The groups did not differ on cognitive function at baseline or on any of the demographic, other cardiovascular risk factors or T2D medication use (Table 1).

Table 1. Patient Characteristics at Baseline

mean (SD) presented; * median [min-max] presented


Associations of physical activity with cognitive decline. Overall, as shown in Figure 2 and Table 2, the non-physically active group tended to decline faster over time compared to the physically active group. Since the partially and fully adjusted models had similar results, we describe here results from the fully adjusted model. Statistically significant differences were found for decline in Global Cognition (p=0.005), Executive Functioning (p=.014), and Attention/Working Memory (p=.01). There were no significant differences between the groups for Semantic Categorization (p=.17) and Episodic Memory (p=.88).

Figure 2. Estimated Cognitive trajectories for individuals in the high (black line) vs. low (red line)

PA group, adjusting for time in registry, sex, education, HbA1c, cholesterol, triglyceride, LDL, HDL, creatinine, BMI and ADL

Table 2. Longitudinal analysis of cognitive change persons remaining in same activity group activity (MMRM)- partially adjusted model+ (upper line) and fully adjusted model++ (lower line)

+Partially adjusted: Controlling for sex, education and age; ++Fully adjusted: Additionally controlling for HbA1c, Cholesterol, Triglyceride, LDL, HDL, T2d medication, Creatinine and BMI



In a population-based cohort of initially non-demented older adults with type 2 diabetes, we found that participation in any sporting or recreational activities (dancing, aerobics, ball or competitive sports, running, jogging, cross-country walking etc.), was associated with a slower rate of cognitive decline compared to physical activity that included only walking as a means of transportation, during a follow up of approximately 3 years. Significant differences between the two groups were found in Global Cognition, Executive Functions Participants and Attention/Working memory. Additional adjustments for key cardiovascular risk factors associated both with physical activity and with cognition did not alter the results, reflecting on their robustness. We chose a-priori to include in the analyses only those who reported the same physical activity category at all-time points, as this may more reliably reflect their level of physical activity. Our results possibly indicate that adopting a lifestyle that includes consistent physical activity may contribute to maintenance of cognitive health.
The results of the current study support previous research showing that more physical activity was associated with less cognitive decline among aging adults. A recent review of studies of studies on modifiable risk factors and prevention (9) identified six studies showing evidence of an association of physical activity and neuroprotection, one study that did not and no studies showing neurotoxicity or damage. Compared to those studies, the current study provides additional support for the potential role of physical exercise for neuroprotection. In this study we show similar results in older adults with type 2 diabetes, which are maintained after adjusting for type 2 diabetes related factors including duration of disease, HbA1c and T2D medication. Previous literature on type 2 diabetes has found that excess body weight, lack of physical activity and a general sedentary lifestyle are highly associated with incident type 2 diabetes, as well as with type 2 diabetes complications such as cardiovascular disease and diabetic neuropathy (25). Our study adds new evidence for the potential protective role of physical activity against cognitive decline, another growingly recognized complication of type 2 diabetes and is supportive of calls for more attention to prevention (26).
Potential underlying mechanisms for cognitive benefit from physical activity include preserving neuronal plasticity (27), increasing synapses and dendritic receptors (28), release of brain derived neurotrophic factor (BDNF) that aid in neuronal genesis and function (29) and improved cerebral blood flow (30). Type 2 diabetes has been associated with lower levels of plasma BDNF and interestingly, lower levels of BDNF are associated with greater insulin resistance (31) suggesting that in this population, physical activity may beneficially affect the brain through these two pathways (25, 31), as physical activity enhances insulin sensitivity (34).
Furthermore, physical activity has physiological effects that may be indirectly related to cognitive functions such as lowering cardiovascular risk, by increasing HDL cholesterol and glucose tolerance (32) and decreasing HbA1c. We adjusted for a broad range of cardiovascular risk factors, but this did not alter the results. Older adults with diabetes are often treated with medications for their comorbidities and to improve glycemic control (33), which may have masked their contribution to the associations of physical activity with cognitive decline.
Inflammation has been shown to be a critical component of the pathogenesis of Alzheimer’s disease (34) and is consistently higher in type 2 diabetes individuals (35). Physical activity beneficially affects the levels of inflammatory markers (36), specifically the levels of interleukin-6 (IL-6) and C-reactive protein (CRP) (37). To explore whether these inflammatory markers mediated the association of physical activity with cognition, we performed additional analyses adjusting for CRP and IL-6. Results remained essentially unchanged (data not shown) suggesting that other cytokines might be involved.
Previous research among type 2 diabetes participants consisted of controlled intervention studies with relatively small sample sizes and with very specific eligibility criteria impeding generalization of results to a broader population of diabetic elderly (11). The current study exploits the opportunity to examine a relatively large population based epidemiological longitudinal cohort while also adjusting for important key demographic and health related variables. Furthermore, an advantage of the current study was the measurement of physical activity at several time points which was not possible in other studies (12).
Strengths of this study include a well-validated (rather than self-reported) diagnoses of type 2 diabetes, a rich set of relevant long-term potential confounders, a longitudinal design, and assessment of different cognitive domains in addition to global cognition. A major limitation of this study is the lack of a non-diabetic control group thus we were not able to isolate the effects which could be associated with diabetes. Another major main limitation of the study is that it used a self-reported measure of physical activity based on a screening questionnaire rather than an in-depth assessment of physical activity or objectively measured tools such as fitness trackers that may allow more granular characterization of the activity. The analyses limited to participants who consistently reported the same level of activity attenuates this limitation. Furthermore, we may have underestimated the effects we found because the IDCD eligibility criteria excluded cognitively impaired individuals from the study at baseline, and by doing so created a bias for healthier individuals with a lower risk for cognitive decline. In keeping with much of the literature, physical activities appeared to have a neuroprotective effects on cognitive functioning, individuals in the preclinical stage of AD tended to have lower physical activity levels than the healthy elderly.
We chose to a-priori exclude physically impaired individuals from the analysis, possibly further limiting the effects of physical activity but ensuring that low levels of physical activity was primarily due to lifestyle rather than a physical limitation such as an amputated foot, neuropathy, or mobility disability, common in type 2 diabetes. Finally, since the IDCD study does not include non-diabetic participants, we cannot compare whether associations are stronger in diabetics compared to non-diabetics. A physical activity intervention study on previously sedentary adults with and without type 2 diabetes found improved cognitive scores only among the type 2 diabetes in the physical activity intervention group (14). Similar results were found in a randomized controlled study comparing aerobic exercise to stretching over 6-months in a sample of aging adults that met a 2-hour glucose intolerance, meeting criteria for newly diagnosis or pre-diabetes (38). Such results may indicate a particularly strong gain from physical activity in type 2 diabetic individuals.
Taken together with previous studies, this study supports the beneficial effects of physical activity on reducing risk of cognitive decline in older adults with type 2 diabetes. Our results also suggest that participating on a consistent basis in planned physical activity (i.e., our “active” group), is most beneficial and that walking as a mean of transportation (i.e., our “non-active” group) is less beneficial. Additional research is needed to test in large clinical trials, the effects of physical activity on reducing cognitive decline among the elderly and specifically those with type 2 diabetes, who are at high risk for cognitive decline and dementia. Future research might also focus on specific domains of physical activity on cognition, as various forms of physical activity, with different metabolic and physiological levels, may differentially affect cognitive activity and outcomes ultimately affecting different neurobiological pathways (39).


Conflicts of Interest: None of the authors have conflicts of interest to report.

Ethical standards: This study was reviewed and approved by the institutional review boards of Sheba Medical Center and MHS, Israel, and Icahn school of Medicine at Mount Sinai, NY. The participants provided written informed consent.





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