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Abstract

Objective:

This study examined associations between physical activity (PA) and neuropsychiatric symptoms (NPS) in older adults free of dementia.

Methods:

This cross-sectional study included 3,222 individuals ≥70 years of age (1,655 men; mean±SD age=79.2±5.6; cognitively unimpaired, N=2,723; mild cognitive impairment, N=499) from the population-based Mayo Clinic Study of Aging. PA (taken as a presumed predictor) in midlife (i.e., when participants were 50–65 years of age) and late life (i.e., the year prior to assessment) was assessed with a self-reported, validated questionnaire; PA intensity and frequency were used to calculate composite scores. NPS (taken as presumed outcomes) were assessed with the Neuropsychiatric Inventory Questionnaire, Beck Depression Inventory (BDI-II), and Beck Anxiety Inventory (BAI). Regression analyses included midlife and late-life PA in each model, which were adjusted for age, sex, education, apolipoprotein E ɛ4 status, and medical comorbidity.

Results:

Higher late-life PA was associated with lower odds of having apathy (OR=0.89, 95% CI=0.84–0.93), appetite changes (OR=0.92, 95% CI=0.87–0.98), nighttime disturbances (OR=0.95, 95% CI=0.91–0.99), depression (OR=0.94, 95% CI=0.90–0.97), irritability (OR=0.93, 95% CI=0.89–0.97), clinical depression (OR=0.92, 95% CI=0.88–0.97), and clinical anxiety (OR=0.90, 95% CI=0.86–0.94), as well as lower BDI-II (β estimate=−0.042, 95% CI=−0.051 to −0.033) and BAI (β estimate=−0.030, 95% CI=−0.040 to −0.021) scores. Higher midlife PA was associated only with higher BDI-II scores (β estimate=0.011, 95% CI=0.004 to 0.019). Sex modified the associations between PA and NPS.

Conclusions:

Late-life PA was associated with a lower likelihood of clinical depression or anxiety and subclinical NPS. These findings need to be confirmed in a cohort study.
Physical activity has numerous beneficial effects on general and mental health across the lifespan. In older adults, engaging in physical activity is associated with lower risk of developing cognitive impairment and dementia (17). Therefore, physical activity has been recommended as one of few promising, nonpharmacological treatments to potentially preserve cognitive function in older adults.
Neuropsychiatric symptoms are common in older adults, even in community-dwelling individuals (8). We and others have reported that neuropsychiatric symptoms are a risk factor for cognitive decline (911) and are associated with abnormalities in neuroimaging biomarkers for Alzheimer’s disease in older adults free of dementia (12, 13).
A recent review that included observational and interventional studies showed that physical activity may have beneficial effects on depression and sleep disturbances in patients with Alzheimer’s disease, but there is limited evidence for effects on other neuropsychiatric symptoms, such as agitation, apathy, or anxiety (14). In addition, little is known as to whether physical activity is associated with different neuropsychiatric symptoms in older community-dwelling adults free of dementia.
Therefore, the aim of this cross-sectional study was to examine associations between self-reported physical activity carried out in midlife and late life and self- and informant-reported neuropsychiatric symptoms in a sample of community-dwelling older adults who were either cognitively unimpaired or had mild cognitive impairment (MCI). We hypothesized that physical activity would be associated with a lower likelihood of having neuropsychiatric symptoms and lower scores on continuous measures of neuropsychiatric symptoms.

Methods

Study Sample and Design

This study was conducted in the setting of the ongoing population-based Mayo Clinic Study of Aging in Olmsted County, Minnesota (15). We included 3,222 individuals (1,655 men) ≥70 years of age who were either cognitively unimpaired (N=2,723) or had MCI (N=499). Data were available from all participants on self-reported physical activity carried out in midlife and late life, self-reported or informant-observed presence or absence of neuropsychiatric symptoms, and covariates (e.g., age, sex, education). The protocols used in the Mayo Clinic Study of Aging have been approved by the institutional review boards of the Mayo Clinic and Olmsted Medical Center in Rochester, Minnesota. All participants provided written informed consent. The data used in the analyses were collected between April 2006 and March 2020.

Neurocognitive Evaluation

Participants underwent a face-to-face evaluation that included a neurological examination, a study coordinator visit, and neuropsychological testing (15). The neurological evaluation comprised a neurological history review, administration of the Short Test of Mental Status (16), and a neurological examination. The study coordinator met with the participant and a study partner to collect sociodemographic data and ask questions about the participant’s memory, neuropsychiatric symptoms, and activities of daily living. Neuropsychological testing was administered by a psychometrist to assess performance in four cognitive domains: memory (Auditory Verbal Learning Test [17]; logical memory and visual reproduction subtests of the Wechsler Memory Scale–Revised [18]), language (Boston Naming Test [19]; category fluency [20]), visuospatial skills (picture completion and block design subtests of the Wechsler Adult Intelligence Scale–Revised [21]), and attention and executive function (Trail Making Test [22]; digit symbol substitution subtest of the Wechsler Adult Intelligence Scale–Revised [21]). An expert consensus panel of physicians, study coordinators, and neuropsychologists reviewed the results for each participant and determined whether a participant had cognitive impairment. Individuals were classified as cognitively unimpaired based on normative data from a different sample in this community (23, 24). Individuals were classified as having MCI based on the revised Mayo Clinic criteria for MCI (25, 26): cognitive concern expressed by a physician, informant, participant, or study coordinator; impairment in one or more cognitive domains (memory, attention and executive function, language, or visuospatial skills); essentially normal functional activities; and absence of dementia. Participants with MCI had a Clinical Dementia Rating score of 0 or 0.5; however, the final diagnosis of MCI was based on all available data. Participants with dementia were excluded from this study.

Measurement of Physical Activity

Physical activity data were collected with a self-report questionnaire (27). The questionnaire was derived from two validated instruments: the 1985 National Health Interview Survey and the Minnesota Heart Survey intensity codes (28, 29). Participants were asked about engagement in physical activity and exercise in midlife (i.e., between the ages of 50 and 65 years) and late life (i.e., over the past year). Three levels of physical activity and exercise intensity were distinguished by providing examples for each level: light physical activity (e.g., laundry, vacuuming, making beds, or dusting), moderate physical activity (e.g., scrubbing floors, washing windows, gardening, or raking leaves), heavy physical activity (e.g., carrying heavy objects, heavy digging, pushing a mower, or hard manual labor), light physical exercise (e.g., leisurely walking or slow dancing), moderate physical exercise (e.g., hiking or swimming), and vigorous physical exercise (e.g., jogging or playing singles tennis). Participants were also asked to indicate the frequency at which they carried out these activities: ≤ once per month, two to three times per month, one to two times per week, three to four times per week, five to six times per week, and daily. For the purpose of this study, we calculated a composite score by summing the number of days per week that an individual engaged in light, moderate, and vigorous physical activity and exercise and dividing the total by 2 to get an overall score. This was done separately for midlife and late life. The scores could range from 0 to 21, and higher scores indicated higher levels of overall activity (referred to as “physical activity” throughout this article). Previous research has shown that the physical activity questionnaire used in the Mayo Clinic Study of Aging has moderate to good internal consistency; test-retest correlation coefficients range from 0.33 for vigorous activity to 0.50 for moderate activity (27).

Measurement of Neuropsychiatric Symptoms

Neuropsychiatric symptoms were assessed with the Neuropsychiatric Inventory Questionnaire (NPI-Q) (30). The NPI-Q was administered as a structured interview to an informant, such as the spouse of a participant, by a study coordinator to assess the presence or absence of 12 emotional behaviors (i.e., depression, anxiety, apathy, agitation, delusions, hallucinations, euphoria, disinhibition, irritability, aberrant motor behavior, sleep or nighttime disturbances, and eating or appetite changes). In addition, we assessed self-reported depression and anxiety using the Beck Depression Inventory (BDI-II) (31) and Beck Anxiety Inventory (BAI) (32), respectively. The BDI-II measures common symptoms of depression, such as feelings of guilt or loss of interest, over the past 2 weeks. The BAI measures common anxiety symptoms, such as nervousness or fear of losing control, over the past week. Both inventories have been validated and consist of 21 items. The severity of each item is rated on a Likert-type scale ranging from 0 to 3 points, resulting in a total score that can range from 0 to 63 points. Higher scores indicate higher levels of depressive and anxiety symptom severity. For our analyses, we used BDI-II and BAI total scores as continuous measures, and we used BDI-II scores ≥13 (indicating clinical depression) and BAI scores ≥10 (indicating clinical anxiety) as categorical measures.

Assessment of Confounding Variables

In addition to traditional confounders (i.e., age, sex, and education), we also adjusted the statistical analyses for apolipoprotein E (APOE) ε4 genotype status, which was determined by using standard methods, and medical comorbidity, which was assessed with the weighted Charlson Index (33). This index includes the following conditions: myocardial infarction, congestive heart failure, peripheral vascular disease, cerebrovascular disease, dementia, chronic pulmonary disease, ulcer, mild liver disease, diabetes, diabetes with organ damage, hemiplegia, moderate or severe renal disease, moderate or severe liver disease, metastatic solid tumor, AIDS, rheumatologic disease, and other cancers.

Statistical Analysis

Descriptive statistics were calculated and are presented as mean values with standard deviations or as frequencies and percentages, depending on whether a variable was continuous or categorical. Because the direction of causality is unknown in cross-sectional studies, we arbitrarily assigned engagement in physical activity as a presumed predictor (independent variable) and considered the presence of neuropsychiatric symptoms as the outcome of interest (dependent variable) for the analyses. We ran logistic regression analyses to examine the association between engagement in physical activity in midlife and late life and clinical depression (indicated by BDI-II scores ≥13), clinical anxiety (indicated by BAI scores ≥10), and the presence of neuropsychiatric symptoms assessed by the NPI-Q (categorical measures). Because of the low prevalence of some neuropsychiatric symptoms in our population-based sample free of dementia, we focused on only seven of the 12 items on the NPI-Q: depression, anxiety, apathy, agitation, irritability, nighttime disturbances, and appetite changes. For the logistic regression models, we computed odds ratios, 95% confidence intervals, and p values. We also conducted linear regression analyses to examine associations between engagement in physical activity in midlife and late life and continuous BDI-II and BAI total scores. Because of the right-skewed distributions of the continuous BDI-II and BAI scores in our data set, we added 1 point and log-transformed the scores (1 point needed to be added before the log transformation because a log of 0 is mathematically undefined and many participants had a value of 0 for these variables). For the linear models, we computed β estimates, 95% CIs, and p values. We adjusted all models for age, sex, education, APOE ε4 carrier status, and medical comorbidity. To adjust physical activity in midlife for physical activity in late life and vice versa, we included the two physical activity composite scores, i.e., midlife and late-life scores, in all models. Finally, we calculated models that included a sex interaction term to explore whether sex modifies the association between physical activity in midlife and late life and neuropsychiatric symptoms. All analyses were conducted with the conventional two-tailed alpha level of 0.05 and performed with SAS, version 9.4, and R, version 3.6.2.

Results

The study included 3,222 individuals (N=1,655 men) ≥70 years of age (mean±SD=79.2±5.6); 2,723 of these individuals were cognitively unimpaired, and 499 individuals had MCI. The mean midlife physical activity score was 8.93±4.63, and the mean late-life score was 6.54±3.90. The presence of neuropsychiatric symptoms ranged from 12% for depression to 3% for agitation; 7% of participants had clinical depression (i.e., BDI-II score ≥13), and 7% had clinical anxiety (i.e., BAI score ≥10). Women had significantly fewer years of education; lower body mass index; lower Charlson index scores; lower frequency of cognitive impairment; lower frequency of agitation, apathy, appetite or eating changes, nighttime disturbances, and irritability; and higher BAI total scores. The demographic and other characteristics of the study sample are shown in Table 1.
TABLE 1. Characteristics of 3,222 individuals ≥70 years of age participating in the Mayo Clinic Study of Aginga
 Total (N=3,222)Women (N=1,567)Men (N=1,655)
MeasureMeanSDMissing NMeanSDMissing NMeanSDMissing N
Age79.225.5879.345.7479.115.42
Education (years)14.082.8513.752.3914.383.20
Body mass index28.035.086427.775.633028.284.4734
Charlson index score4.163.473.683.284.623.58
Midlife PA score (0–21)8.934.638.924.188.935.03
Late-life PA score (0–21)6.543.906.423.606.674.15
BDI-II total score4.834.58174.764.44154.904.702
BAI total score2.743.8753.003.8932.493.832
 N%Missing NN%Missing NN%Missing N
APOE ɛ4 carrier855274102644527
Race         
 White3,185991,553991,63299
 More than one14040101
 Asian903060
 Black604020
 Other or unknown803050
Ethnicity         
 Not Hispanic or Latino3,205991,557991,648100
 Hispanic or Latino604020
 Unknown or not disclosed1106050
English as first language3,1109741,5059621,605972
Cognitive status         
 Cognitively unimpaired2,723851,368871,35582
 Mild cognitive impairment499151991330018
NPI-Q-assessed NPS         
 Agitation953257342155614102
 Anxiety1826257937155896102
 Apathy or indifference18862577151551178102
 Appetite or eating change1395258534156866102
 Nighttime disturbances227967173745915411212
 Depression or dysphoria361122581621115619913102
 Irritability or lability263925798715516511102
BDI-II score ≥132147179161512372
BAI score ≥10218751167310262
a
APOE=apolipoprotein E; BAI=Beck Anxiety Inventory; BAI score ≥10=clinical anxiety; BDI-II=Beck Depression Inventory–II; BDI-II score ≥13=clinical depression; NPI-Q=Neuropsychiatric Inventory Questionnaire; NPS=neuropsychiatric symptoms; PA=physical activity. The following NPI-Q-assessed neuropsychiatric symptoms were not included in the analyses due to low frequency: delusions (N=24, 1%), disinhibition (N=55, 2%), euphoria or elation (N=20, 1%), hallucinations (N=9, 0%), and motor behavior (N=29, 1%).
Logistic regression analyses revealed statistically significant inverse associations between engagement in late-life physical activity and the presence of neuropsychiatric symptoms: each one-unit increase in late-life physical activity was associated with lower odds of having apathy (OR=0.89, 95% CI=0.84–0.93, p<0.001), appetite or eating changes (OR=0.92, 95%=0.87–0.98, p=0.006), sleep or nighttime disturbances (OR=0.95, 95% CI=0.91–0.99, p=0.024), depression (OR=0.94, 95% CI=0.90–0.97, p<0.001), irritability (OR=0.93, 95% CI=0.89–0.97, p=0.001), clinical depression (OR=0.92, 95% CI=0.88–0.97, p=0.001), and clinical anxiety (OR=0.90, 95% CI=0.86–0.94, p<0.001). We did not observe any significant associations between midlife physical activity and neuropsychiatric symptoms. The logistic regression models of the associations between midlife and late-life physical activity and neuropsychiatric symptoms are shown in Table 2.
TABLE 2. Logistic regression results showing associations between engagement in physical activity and neuropsychiatric symptomsa
MeasureNEventsMidlife physical activityLate-life physical activity
OR95% CIpOR95% CIp
Neuropsychiatric symptom        
 Agitation2,965951.000.95, 1.050.9760.930.87, 1.000.051
 Anxiety2,9651820.980.94, 1.020.4021.000.95, 1.050.972
 Apathy2,9651881.030.99, 1.070.1050.890.84, 0.93<0.001*
 Appetite2,9641391.020.97, 1.060.4480.920.87, 0.980.006*
 Nighttime disturbances2,5512271.010.98, 1.050.5290.950.91, 0.990.024*
 Depression2,9643611.010.98, 1.040.5340.940.90, 0.97<0.001*
 Irritability2,9652631.010.98, 1.040.5540.930.89, 0.970.001*
BDI-II score ≥133,2052141.010.98, 1.050.4440.920.88, 0.970.001*
BAI score ≥103,2172181.020.99, 1.060.1820.900.86, 0.94<0.001*
a
BAI=Beck Anxiety Inventory, with scores ≥10 indicating clinical anxiety; BDI-II=Beck Depression Inventory–II, with scores ≥13 indicating clinical depression. Models were adjusted for age, sex, education, apolipoprotein E ɛ4 status, and medical comorbidity. Levels of physical activity in both midlife and late life were included in each model.
* Indicates a significant p value.
Linear regression analyses showed that higher levels of late-life physical activity were associated with less depressive and anxiety symptom severity as indicated by lower BDI-II (β estimate=−0.042, 95% CI=−0.051 to −0.033, p<0.001) and BAI (β estimate=−0.030, 95% CI=−0.040 to −0.021, p<0.001) total scores. Higher levels of midlife physical activity were associated with higher BDI-II total scores (β estimate=0.011, 95% CI=0.004 to 0.019, p=0.004). Because the BDI-II and BAI scores were log-transformed, we can approximately interpret the results in terms of percentages: each one-unit increase in late-life physical activity was associated with an approximately 4.2% decrease in BDI-II score, on average. The linear regression models of the associations between midlife and late-life physical activity and BDI-II and BAI scores are shown in Table 3.
TABLE 3. Linear regression results showing associations between engagement in physical activity and BDI-II and BAI total scoresa
  Midlife physical activityLate-life physical activity
NPSNβ estimate95% CIpβ estimate95% CIp
BDI-II3,2050.0110.004, 0.0190.004*−0.042−0.051, −0.033<0.001*
BAI3,2170.007−0.001, 0.0150.084−0.030−0.040, −0.021<0.001*
a
BAI, Beck Anxiety Inventory; BDI-II, Beck Depression Inventory–II; NPS=neuropsychiatric symptoms. Models were adjusted for age, sex, education, apolipoprotein E ɛ4 status, and medical comorbidity. Levels of physical activity in both midlife and late life were included in each model. For each BDI-II and BAI score, 1 point was added for log transformation.
* Indicates a significant p value.
To examine whether sex modifies the association between midlife and late-life physical activity and neuropsychiatric symptoms, we ran models that included an interaction term with sex. We observed two statistically significant interactions; these interactions included physical activity in midlife predicting the presence of anxiety and physical activity in late life predicting clinical anxiety. Thus, we stratified these analyses by sex and found that higher levels of midlife physical activity were statistically significantly associated with lower odds of the presence of anxiety in women (OR=0.92, 95% CI=0.86–0.98, p=0.013) but not in men (OR=1.03, 95% CI=0.98–1.08, p=0.299). Similarly, higher levels of late-life physical activity were associated with lower odds of clinical anxiety in women (OR=0.84, 95% CI=0.78–0.90, p<0.001) but not in men (OR=0.97, 95% CI=0.90–1.03, p=0.284).

Discussion

Engagement in physical activity in late life was associated with a lower likelihood of having neuropsychiatric symptoms in our sample of community-dwelling older adults free of dementia. In line with our hypothesis, we observed significant inverse associations between late-life physical activity and apathy, appetite or eating changes, sleep or nighttime disturbances, depression, and irritability (all assessed by the NPI-Q), as well as associations with clinical depression and anxiety (assessed by the BDI-II and BAI, respectively). Because it is not possible to infer cause and effect based on our cross-sectional study design, there are two potential explanations for our findings: engaging in physical activity in late life may decrease the risk of having neuropsychiatric symptoms, and participants who have neuropsychiatric symptoms may be less likely to engage in late-life physical activity.
For women, there were significant associations between higher levels of midlife physical activity and a lower likelihood of the presence of anxiety and higher levels of late-life physical activity and a lower likelihood of having clinical anxiety; these associations did not hold for men. These findings may indicate that the associations between physical activity and anxiety are modified by sex; more research is needed to examine the potential impact of sex on the associations between physical activity and neuropsychiatric symptoms.
Furthermore, there was a significant association between higher levels of midlife physical activity and higher BDI-II scores. We conducted additional analyses to further explore this association (data not shown) and found that particularly vigorous midlife physical exercise in women was associated with higher depressive symptom severity. In this study, as noted above, midlife was defined as 50 to 65 years of age, which coincides with menopause and associated mood changes. We and others have reported that menopause is associated with depression (34). Some women might be using vigorous physical exercise as a nonpharmacological way of dealing with depressive symptoms associated with physiological changes in midlife. Future studies are warranted to explore the potentially different associations between midlife and late life physical activity with neuropsychiatric symptoms by accounting for potential sex effects. In addition, future research should investigate the potential impact of social determinants of health factors on the association between physical activity and neuropsychiatric symptoms.
Overall, the findings from our study are in line with previous research. For example, investigators from the Netherlands have reported that adults >60 years of age with depression were less physically active than peers without depression based on cross-sectional data (35). In addition, a recent review concluded that there is an inverse relationship between physical activity and depression in older adults, although it was acknowledged that the dose-response relationship between physical activity and depression, as well as the potentially different effects of various types of physical activity, remain unknown (36). Another review of clinical trials and cohort studies also showed that aerobic and resistance training are effective in decreasing symptoms of depression in older adults (37). On the basis of these findings, it has been postulated that physical activity may affect biological and psychosocial processes that are implicated in the pathophysiology of depression. For example, physical activity may have effects on neuroplasticity (e.g., increased hippocampal neurogenesis), inflammation, oxidative stress, the endocrine system (e.g., cortisol), self-esteem, social support, and self-efficacy (38, 39).
With regard to anxiety symptoms, a recent review of 24 prospective studies revealed a potentially protective effect of physical activity on anxiety symptoms and disorders (40). Similar to the aforementioned review on depression, the authors concluded that the data were not sufficient to make conclusions about the dose-response relationship between physical activity and lower anxiety symptoms; furthermore, the use of different methods to assess physical activity may limit the comparability of studies. Evidence of physical activity reducing neuropsychiatric symptoms can also be drawn from interventional research. For example, a home-based, 6-month physical activity program was effective in reducing depression and anxiety, particularly in persons with elevated anxiety and depressive symptoms at baseline (41). In addition, there is a rather large body of research on the associations between physical activity and sleep. For example, a randomized controlled trial showed that a 4-week, low-impact walking intervention was associated with better sleep quality in healthy adults (42). Furthermore, a longitudinal study derived from the Wisconsin Sleep Cohort showed that an intermediate level of physical activity, defined as 500–1,500 metabolic-equivalent-of-task minutes per week, was associated with a lower risk of short sleep times (43). Furthermore, investigators from Spain reported that higher levels of objectively measured physical activity were associated with better subjective sleep quality and quantity (44).
In our study, we did not examine the association between changes in physical activity levels between midlife and late life and neuropsychiatric symptoms. However, this potential association may be interesting with regard to the linear model predicting BDI-II scores, as midlife physical activity was not statistically significant for any other model, and the result that higher levels of midlife physical activity were associated with higher BDI-II scores seems counterintuitive. Based on the model we report in Table 3, we can say that participants with low midlife and high late-life physical activity will have the lowest BDI-II scores, and those with high midlife and low late-life physical activity will have the highest BDI-II scores, on average. In an additional analysis (data not shown), we created a four-level physical activity variable by using median splits of the midlife and late-life activity data: low in midlife and low in late life, high in midlife and low in late life, low in midlife and high in late life, and high in midlife and high in late life. Using the participants with low activity in both midlife and late-life periods as the reference, those who went from high to low levels of activity were not statistically different from those who always had low levels of activity; those who went from low to high levels of activity had the lowest BDI-II scores (β estimate=−0.258, 95% CI=−0.351 to −0.166, p≤0.001); and those who maintained high levels of activity also had lower BDI-II scores (β estimate=−0.220, 95% CI=−0.289 to −0.151, p≤0.001). Although these results were not completely consistent across models, it seems likely that a change from high levels of midlife physical activity to low levels of late-life physical activity would be associated with a greater likelihood or severity of neuropsychiatric symptoms.
The strengths of our study are the large sample size and the rigorous assessment of self-reported and informant-observed neuropsychiatric symptoms. In addition, we focused on both midlife and late-life physical activity as presumed predictor variables. To our knowledge, our study is one of the few that has examined the association between engaging in physical activity in different periods of life and the presence of neuropsychiatric symptoms. Furthermore, we examined potential sex interactions, given that previous research indicated that the association between physical activity and neuropsychiatric symptoms may be moderated by sex (42). Finally, to adjust physical activity in midlife for physical activity in late life and vice versa, we included physical activity composite scores from both time periods in all models. We made this adjustment because it is likely that physical activity habits in late life are influenced by those in midlife. The main limitations of our research pertain to the cross-sectional study design, which does not allow for drawing conclusions about cause and effect in the associations between physical activity and neuropsychiatric symptoms. Furthermore, physical activity was assessed with a self-report questionnaire, which may be prone to recall bias, and reliability was only low to moderate. Thus, use of body-worn sensors should be considered in future research to ensure objective assessments of physical activity and overcome the risk of bias from self-reported data. In addition, we did not differentiate between physical activity and exercise in the composite score, and we did not weigh the scores on the basis of degree of intensity. However, as noted above, we conducted additional analyses by including the three exercise intensities (i.e., light, moderate, and vigorous physical exercise in midlife and in late life) separately in the models to further clarify rather unexpected findings (e.g., when we observed a significant association between higher levels of midlife physical activity and higher BDI-II scores). Furthermore, we did not adjust our analyses for multiple comparisons, which may have increased the possibility of a type I error. However, when considering a Bonferroni correction for our analyses, the alpha significance level would be 0.006 (i.e., 0.05/9) because we had a total of nine neuropsychiatric symptoms per predictor (i.e., levels of midlife and late-life physical activity) in Table 2. In this situation, six out of the seven significant p values for the association between late-life physical activity and neuropsychiatric symptoms would have remained significant, and none of our major conclusions would have been affected by the correction. As expected in our population-based sample, the numbers of participants with depression and anxiety as measured by the BDI-II and BAI were low, and this may have influenced the conclusions. Finally, our sample is relatively highly educated, and 99% of the study participants were White. However, it has been shown that data from Olmsted County are generalizable to the U.S. population of Minnesota and the upper Midwest (45). Nevertheless, the data may not be generalizable to minority populations such as non-White race or ethnicities. This lack of cultural and linguistic sensitivity may have also had an impact on the study findings. Thus, we acknowledge that future studies in populations with more racial and ethnic diversity are needed to confirm our findings.

Conclusions

Our study suggests that being physically active in late life is associated with lower neuropsychiatric symptomatology. Particularly in light of the recent COVID-19 pandemic, which may have had a negative impact on emotional health, it is critical to highlight and further examine the potential beneficial effects of physical activity on emotional health. Our findings should be considered preliminary until confirmed by a prospective cohort study.

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Information & Authors

Information

Published In

Go to The Journal of Neuropsychiatry and Clinical Neurosciences
Go to The Journal of Neuropsychiatry and Clinical Neurosciences
The Journal of Neuropsychiatry and Clinical Neurosciences
Pages: 133 - 140
PubMed: 36464975

History

Received: 4 April 2022
Revision received: 3 August 2022
Accepted: 16 September 2022
Published online: 5 December 2022
Published in print: Spring 2023

Keywords

  1. Physical Activity
  2. Lifestyle
  3. Neuropsychiatric Symptoms
  4. Geriatric Neuropsychiatry
  5. Depression
  6. Anxiety

Authors

Details

Janina Krell-Roesch, Ph.D.
Institute of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany (Krell-Roesch, Bezold, Trautwein, Barisch-Fritz, Jekauc, Woll); Department of Quantitative Health Sciences (Krell-Roesch, Syrjanen, Kremers, Vassilaki), Department of Psychiatry and Psychology (Fields), and Department of Neurology (Scharf, Knopman, Petersen), Mayo Clinic, Rochester, Minn.; International Clinical Research Center, St. Anne University Hospital, Brno, Czech Republic (Stokin); Department of Neurology, Barrow Neurological Institute, Phoenix (Geda).
Jeremy A. Syrjanen, M.S.
Institute of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany (Krell-Roesch, Bezold, Trautwein, Barisch-Fritz, Jekauc, Woll); Department of Quantitative Health Sciences (Krell-Roesch, Syrjanen, Kremers, Vassilaki), Department of Psychiatry and Psychology (Fields), and Department of Neurology (Scharf, Knopman, Petersen), Mayo Clinic, Rochester, Minn.; International Clinical Research Center, St. Anne University Hospital, Brno, Czech Republic (Stokin); Department of Neurology, Barrow Neurological Institute, Phoenix (Geda).
Jelena Bezold, M.Sc.
Institute of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany (Krell-Roesch, Bezold, Trautwein, Barisch-Fritz, Jekauc, Woll); Department of Quantitative Health Sciences (Krell-Roesch, Syrjanen, Kremers, Vassilaki), Department of Psychiatry and Psychology (Fields), and Department of Neurology (Scharf, Knopman, Petersen), Mayo Clinic, Rochester, Minn.; International Clinical Research Center, St. Anne University Hospital, Brno, Czech Republic (Stokin); Department of Neurology, Barrow Neurological Institute, Phoenix (Geda).
Sandra Trautwein, Ph.D.
Institute of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany (Krell-Roesch, Bezold, Trautwein, Barisch-Fritz, Jekauc, Woll); Department of Quantitative Health Sciences (Krell-Roesch, Syrjanen, Kremers, Vassilaki), Department of Psychiatry and Psychology (Fields), and Department of Neurology (Scharf, Knopman, Petersen), Mayo Clinic, Rochester, Minn.; International Clinical Research Center, St. Anne University Hospital, Brno, Czech Republic (Stokin); Department of Neurology, Barrow Neurological Institute, Phoenix (Geda).
Bettina Barisch-Fritz, Ph.D.
Institute of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany (Krell-Roesch, Bezold, Trautwein, Barisch-Fritz, Jekauc, Woll); Department of Quantitative Health Sciences (Krell-Roesch, Syrjanen, Kremers, Vassilaki), Department of Psychiatry and Psychology (Fields), and Department of Neurology (Scharf, Knopman, Petersen), Mayo Clinic, Rochester, Minn.; International Clinical Research Center, St. Anne University Hospital, Brno, Czech Republic (Stokin); Department of Neurology, Barrow Neurological Institute, Phoenix (Geda).
Walter K. Kremers, Ph.D.
Institute of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany (Krell-Roesch, Bezold, Trautwein, Barisch-Fritz, Jekauc, Woll); Department of Quantitative Health Sciences (Krell-Roesch, Syrjanen, Kremers, Vassilaki), Department of Psychiatry and Psychology (Fields), and Department of Neurology (Scharf, Knopman, Petersen), Mayo Clinic, Rochester, Minn.; International Clinical Research Center, St. Anne University Hospital, Brno, Czech Republic (Stokin); Department of Neurology, Barrow Neurological Institute, Phoenix (Geda).
Julie A. Fields, Ph.D., L.P.
Institute of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany (Krell-Roesch, Bezold, Trautwein, Barisch-Fritz, Jekauc, Woll); Department of Quantitative Health Sciences (Krell-Roesch, Syrjanen, Kremers, Vassilaki), Department of Psychiatry and Psychology (Fields), and Department of Neurology (Scharf, Knopman, Petersen), Mayo Clinic, Rochester, Minn.; International Clinical Research Center, St. Anne University Hospital, Brno, Czech Republic (Stokin); Department of Neurology, Barrow Neurological Institute, Phoenix (Geda).
Eugene L. Scharf, M.D.
Institute of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany (Krell-Roesch, Bezold, Trautwein, Barisch-Fritz, Jekauc, Woll); Department of Quantitative Health Sciences (Krell-Roesch, Syrjanen, Kremers, Vassilaki), Department of Psychiatry and Psychology (Fields), and Department of Neurology (Scharf, Knopman, Petersen), Mayo Clinic, Rochester, Minn.; International Clinical Research Center, St. Anne University Hospital, Brno, Czech Republic (Stokin); Department of Neurology, Barrow Neurological Institute, Phoenix (Geda).
David S. Knopman, M.D.
Institute of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany (Krell-Roesch, Bezold, Trautwein, Barisch-Fritz, Jekauc, Woll); Department of Quantitative Health Sciences (Krell-Roesch, Syrjanen, Kremers, Vassilaki), Department of Psychiatry and Psychology (Fields), and Department of Neurology (Scharf, Knopman, Petersen), Mayo Clinic, Rochester, Minn.; International Clinical Research Center, St. Anne University Hospital, Brno, Czech Republic (Stokin); Department of Neurology, Barrow Neurological Institute, Phoenix (Geda).
Gorazd B. Stokin, M.D., Ph.D.
Institute of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany (Krell-Roesch, Bezold, Trautwein, Barisch-Fritz, Jekauc, Woll); Department of Quantitative Health Sciences (Krell-Roesch, Syrjanen, Kremers, Vassilaki), Department of Psychiatry and Psychology (Fields), and Department of Neurology (Scharf, Knopman, Petersen), Mayo Clinic, Rochester, Minn.; International Clinical Research Center, St. Anne University Hospital, Brno, Czech Republic (Stokin); Department of Neurology, Barrow Neurological Institute, Phoenix (Geda).
Ronald C. Petersen, M.D., Ph.D.
Institute of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany (Krell-Roesch, Bezold, Trautwein, Barisch-Fritz, Jekauc, Woll); Department of Quantitative Health Sciences (Krell-Roesch, Syrjanen, Kremers, Vassilaki), Department of Psychiatry and Psychology (Fields), and Department of Neurology (Scharf, Knopman, Petersen), Mayo Clinic, Rochester, Minn.; International Clinical Research Center, St. Anne University Hospital, Brno, Czech Republic (Stokin); Department of Neurology, Barrow Neurological Institute, Phoenix (Geda).
Darko Jekauc, Ph.D.
Institute of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany (Krell-Roesch, Bezold, Trautwein, Barisch-Fritz, Jekauc, Woll); Department of Quantitative Health Sciences (Krell-Roesch, Syrjanen, Kremers, Vassilaki), Department of Psychiatry and Psychology (Fields), and Department of Neurology (Scharf, Knopman, Petersen), Mayo Clinic, Rochester, Minn.; International Clinical Research Center, St. Anne University Hospital, Brno, Czech Republic (Stokin); Department of Neurology, Barrow Neurological Institute, Phoenix (Geda).
Alexander Woll, Ph.D.
Institute of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany (Krell-Roesch, Bezold, Trautwein, Barisch-Fritz, Jekauc, Woll); Department of Quantitative Health Sciences (Krell-Roesch, Syrjanen, Kremers, Vassilaki), Department of Psychiatry and Psychology (Fields), and Department of Neurology (Scharf, Knopman, Petersen), Mayo Clinic, Rochester, Minn.; International Clinical Research Center, St. Anne University Hospital, Brno, Czech Republic (Stokin); Department of Neurology, Barrow Neurological Institute, Phoenix (Geda).
Maria Vassilaki, M.D., Ph.D.
Institute of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany (Krell-Roesch, Bezold, Trautwein, Barisch-Fritz, Jekauc, Woll); Department of Quantitative Health Sciences (Krell-Roesch, Syrjanen, Kremers, Vassilaki), Department of Psychiatry and Psychology (Fields), and Department of Neurology (Scharf, Knopman, Petersen), Mayo Clinic, Rochester, Minn.; International Clinical Research Center, St. Anne University Hospital, Brno, Czech Republic (Stokin); Department of Neurology, Barrow Neurological Institute, Phoenix (Geda).
Yonas E. Geda, M.D., M.Sc. [email protected]
Institute of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany (Krell-Roesch, Bezold, Trautwein, Barisch-Fritz, Jekauc, Woll); Department of Quantitative Health Sciences (Krell-Roesch, Syrjanen, Kremers, Vassilaki), Department of Psychiatry and Psychology (Fields), and Department of Neurology (Scharf, Knopman, Petersen), Mayo Clinic, Rochester, Minn.; International Clinical Research Center, St. Anne University Hospital, Brno, Czech Republic (Stokin); Department of Neurology, Barrow Neurological Institute, Phoenix (Geda).

Notes

Send correspondence to Dr. Geda ([email protected]).

Competing Interests

Dr. Kremers receives research funding from Astra Zeneca, Biogen, and Roche. Dr. Knopman serves on a data safety monitoring board for the Dominantly Inherited Alzheimer Network (DIAN) study and is an investigator in clinical trials sponsored by Biogen, Lilly Pharmaceuticals, and the University of Southern California. Dr. Petersen consults for Roche, Merck, Genentech, Biogen, and GE Healthcare and receives royalties from Oxford University Press for the publication of Mild Cognitive Impairment. Dr. Vassilaki has received research funding from Roche and Biogen; she currently consults for Roche and has equity ownership in Abbott Laboratories, Amgen, Johnson and Johnson, and Medtronic. Dr. Geda receives funding from Roche and served on the Lundbeck advisory board. The other authors report no financial relationships with commercial interests.

Funding Information

Support for this research was provided by National Institute on Aging grants R01 AG057708, U01 AG006786, P50 AG016574, and R01 AG034676 and National Institute of Mental Health grant K01 MH068351. This project was also supported by the Robert Wood Johnson Foundation, the Robert H. and Clarice Smith and Abigail Van Buren Alzheimer’s Disease Research Program, the GHR Foundation, the Mayo Foundation for Medical Education and Research, the Arizona Alzheimer’s Consortium, the Barrow Neurological Foundation, and the Franke Global Neuroscience Center, Barrow Neurological Institute.

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