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Association of cognitive performance with overall, dosage, intensity, and domain physical activity in aging: NHANES 2011–2014

BMC Geriatrics volume 24, Article number: 910 (2024) Cite this article

Abstract

Background

The specific relationship between PA in detailed types and cognition is still unclear due to limited evidence. Our study aimed to investigate the relationship between cognitive performance and various aspects of physical activity, including overall activity, dosage, intensity levels [moderate physical activity (MPA), vigorous PA], and different domains of activity [occupational PA (OPA), transportation PA (TPA), and leisure-time PA (LTPA)] in older adults using data from the NHANES database.

Methods

This cross-sectional analysis used data from 2 cycles of NHANES (2011–2014). PA was determined through participants' self-reports using the Global Physical Activity Questionnaire (GPAQ). Cognitive performance was evaluated by the presence of psychometric mild cognitive impairment (p-MCI), identified based on a composite measure derived from three cognitive tests including the Consortium to Establish a Registry for Alzheimer's Disease (CERAD), the Animal Fluency test, and the Digit Symbol Substitution test (DSST). Logistic regression models were used to evaluate the association.

Results

A total of 2588 participants aged 60 years or older were included, with an average age of 69.4 years and 48% being male. In the fully adjusted model, compared to no PA, performing 300 min of PA, and MPA were associated with 44%, and 33% reductions in the prevalence of p-MCI, respectively. Additionally, engaging in 1–149 min/week [OR 0.56, 95% CI (0.33–0.92)] and ≥ 300 min/week [OR 0.66, 95% CI (0.44–0.96)] of OPA, as well as ≥ 300 min/week [OR 0.56, 95% CI (0.36–0.86)] of LTPA, were also associated with a lower prevalence of p-MCI. Additionally, engaging in a diverse range of PA had better outcomes.

Conclusions

Our results suggested a positive association between higher levels of PA and enhanced cognitive performance. Different intensities and domains of PA have varying impacts on cognition. Future exploration, such as objectively measured PA and longitudinal studies were needed to validate our conclusion.

Peer Review reports

Introduction

The twenty-first century is an era of an aging population. According to United Nations [1], currently, 12.3 percent of the world's population is aged 60 and older and is expected to rise to about 22 percent by 2050. Aging is often associated with a decline in cognitive abilities [2]. Cognition refers to the mental process of gaining knowledge and understanding through thought, experience, and the senses [3]. Cognitive decline among older adults is associated with various adverse outcomes. It can lead to reduced physical mobility, such as difficulty walking on uneven surfaces, poor balance, and an increased risk of falls as individuals may struggle with complex daily activities, and it can also lead to worse mental health outcomes such as an increased incidence of depression and anxiety [4,5,6,7]. Moreover, cognitive decline can significantly increase the risk of 30-day rehospitalization, is strongly associated with the incidence of frailty, and acts as a major contributor to mortality among the elderly [8,9,10]. The cost and care burdens can be quite substantial for families of individuals who experience cognitive impairment. On average, the paid costs for those who become cognitively impaired in the United States can exceed $280,000, and the value of unpaid care provided by families and friends is also significant [11].

Considering the significant health consequences and economic burden related to cognitive decline, effective interventions are of great importance. Physical activity (PA) has gained increasing attention recently, especially after the FINGER study demonstrated that multidomain interventions can prevent or slow down cognitive decline [12,13,14]. Existing literature has established a positive correlation between PA and improved cognition [15]. Therefore, current guidelines suggest engaging in at least 150–300 min of moderate-intensity activities (MPA) or 75–150 min of vigorous-intensity activities (VPA) per week, or an equivalent combination of both for gaining health consequences [16]. However, current recommendations and studies have some limitations. First, although PA guidelines recommend certain dosages for overall health improvements [16], the specific relationships between these recommended dosages and particular health outcomes have been investigated recently. For example, a study conducted by Fan et al. [17] using data from the National Health and Nutrition Examination Survey (NHANES) reported that any dosage of PA was linked to a lower risk of depressive symptoms. Similarly, another previous study [18] using data from the UK Biobank found that engaging in 150 to 300 min/week of MPA or more was significantly associated with decreased risk of all-cause mortality among hypertensive individuals. These findings suggest that PA dosage recommendations may vary depending on the specific condition. Given the high risk for cognitive decline among older adults, it is particularly important to clarify the relationship between the specific PA dosages and cognitive improvements in this population. Second, PA is a complex behavior that includes different intensities (i.e., moderate or vigorous) and domains [i.e., occupational PA (OPA), leisure-time PA (LTPA), and transportation-related PA (TPA)]. Significant differences exist between these intensities and domains, yet most current studies have primarily focused on total PA [19, 20], with limited research examining the impact of different PA domains. The results are inconsistent. For instance, a study from Norway [21] reported that a sustained engagement in occupations involving moderate to high levels of PA was associated with a higher risk of cognitive decline. In contrast, another study identified OPA as a protective factor against cognitive decline [22]. These mixed findings highlight the need for more research to clarify the specific effects of different types of PA on cognition.

Therefore, we aimed to investigate the association of cognitive performance with overall, dosage, intensity (MPA, and VPA), and domain PA (OPA, TPA, and LTPA) in aging.

Methods

Participants

This cross-sectional analysis used data from 2 cycles of NHANES (2011–2012, 2013–2014). The NHANES was conducted by the Centers for Disease Control and Prevention (CDC) in the United States, collecting information from participants on topics including health, demographics, socioeconomic status, and dietary patterns. A complex, multistage stratified cluster sampling method was used in NHANES to ensure a representative sample of the civilian, noninstitutionalized U.S. population. All study protocols were approved by the National Centers for Health Statistics Ethics Review Board, and all participants provided written informed consent (https://www.cdc.gov/nchs/nhanes/irba98.htm).

Measures

PA

Participants self-reported their PA using the Global Physical Activity Questionnaire (GPAQ) [23]. The GPAQ assessed three PA domains (i.e., occupational, transportation, and leisure-time PA), along with their intensity (vigorous or moderate). OPA is work-related activities such as household chores, and harvesting food. Transportation activities including walking and bicycling are regarded as TPA. LTPA involves sports, fitness, and recreational activities. Participants reported both vigorous and moderate PA done during work (OPA) and in their leisure time (LTPA) in a typical week. VPA requires hard physical effort, resulting in significantly elevated breathing or heart rate, and MPA would cause a slight increase in breathing or heart rate.

Based on participants’ self-reported data, we calculated both moderate occupational PA (MOPA) and vigorous occupational PA (VOPA) weekly. Following NHANES guidelines, we doubled VOPA to convert it into MOPA equivalents, thus deriving the total OPA [24]. The same approach generated calculations for moderate leisure-time PA (MLTPA), vigorous leisure-time PA (VLTPA), and total leisure-time PA (LTPA). We calculated the total MPA by summing MOPA, MLTPA, and TPA. Similarly, total VPA was determined by adding together VOPA and VLTPA. PA was the sum of MPA, and VPA. According to the 2018 PA guidelines [16], which recommend a minimum of 150–300 min per week of moderate-intensity or 75–150 min of vigorous-intensity activities, or an equivalent combination of both. All variables related to moderate-intensity PA, including total PA, total MPA, OPA, MOPA, LTPA, MLTPA, and TPA, were further categorized into four groups: 0 min/week, 1–149 min/week, 150–299 min/week, and ≥ 300 min/week. Similarly, variables related to vigorous-intensity PA, such as total VPA, VOPA, and VLTPA, were divided into 0 min/week, 1–74 min/week, 75–149 min/week, and ≥ 150 min/week [17, 25]. Using the calculated MOPA, VOPA, MLTPA, VLTPA, and TPA, we determined the number of activity types for which each participant met the recommended levels. Participants were then categorized into groups based on achieving the recommended levels in 1, 2, or ≥ 3 types of PA. This categorization enabled us to investigate more effective combinations of PA.

Cognitive tests

Cognitive function in NHANES participants was evaluated using three tests: the word learning and recall modules from the Consortium to Establish a Registry for Alzheimer's Disease (CERAD), the Animal Fluency test, and the Digit Symbol Substitution test (DSST). To represent each participant’s overall cognitive performance, we summed, standardized and normed individual test scores. Psychometric mild cognitive impairment (p-MCI) was defined as having total composite scores that are less than 1 SD below the mean to reflect the clinical significance of cognitive tests [26].

Covariates

Covariates considered include sociodemographic characteristics: sex, age (60–69 years, 70–79 years, and 80 + years), race (Mexican American, Other Hispanic, Non-Hispanic White, Non-Hispanic Black, Non-Hispanic Asian and Other race), education (less than 9th grade, 9-11th grade, high school graduate, some college or associate of arts degree, and college graduate or above), marital (yes or no), family income to poverty ratios (< 1, 1–1.99, 2–3.99, and ≥ 4), and occupation (yes or no). In addition, lifestyle variables [smoking status, Alcohol intake, and body mass index (BMI)] are also included in covariates. Individuals who have smoked fewer than 100 cigarettes in their lifetime are defined as “Never smokers”, those who have smoked 100 or more cigarettes in their lifetime but currently do not smoke are defined as “Former smokers”, and the rest are classified as “Current smokers” [27]. Alcohol intake is categorized into "Non-drinker", "1 to < 5 drinks/month", "5 to < 10 drinks/month", and "10 + drinks/month" [28]. Given that clinical characteristics are associated with PA and cognitive function, medical conditions including diabetes, hypertension, heart disease (i.e., congestive heart failure, coronary heart disease, angina, and heart attack), stroke, respiratory disease (i.e., asthma, emphysema, and chronic bronchitis), and cancer are also considered.

Statistical analysis

Categorical variables are presented as frequency (%). After dividing participants into not p-MCI and p-MCI, participants’ characteristics were compared using Chi-squared test. Logistic regression models were used to evaluate the association between overall, intensity, and domain PA and the risk of p-MCI (yes or no). Four models were used in all analyses. Model 1 was an unadjusted model. Model 2 was adjusted for age and sex. Model 3 included the model 2 variables plus race, education, marital, PIR, smoking, alcohol, BMI, and occupation. Model 4 included the model 3 variables plus diabetes, hypertension, stroke, heart disease, respiratory disease, and cancer. Model 5 was introduced to examine the dependency relationship of cognitive benefits between intensities of PA (i.e., MPA, and VPA), and domains of PA (i.e., OPA, TPA, LTPA). More specific types of PA (i.e., MLTPA, VLTPA, MOPA, VOPA) were not explored in Model 5 due to the limited sample size. Additionally, to explore the dose–response relationship between PA and cognition, a trend analysis was conducted using PA as an ordinal variable. Adjusted odds ratios (ORs) and their 95% confidence intervals (CIs) were calculated to assess the relationship between each PA category and the presence of p-MCI. All data manipulations, analyses, and visualizations were performed using R (version 4.3.1) and R Studio (version 2023.12.0.369). A two-sided p < 0.05 was considered statistically significant.

Results

Characteristics of Participants

A total of 19,931 participants participated in the NHANES during 2011–2014. Our study included 2588 participants after exclusions (Fig. 1). Table 1 shows the sociodemographic, lifestyle, and clinical characteristics of the study population, categorized by the presence of p-MCI, which was identified in 436 participants. Study participants were primarily 60–69 years (55%), female (52%), non-Hispanic white (49%), having some college or associate of arts degree (29%), and married (55%). 49% of participants were never smokers, and the most common alcohol consumption category was 1 to < 5 drinks per month (48%). Clinically, hypertension was reported by more than half of the participants. 37% and 35% of participants reached the recommended PA and TPA, respectively, while only 18% of participants reached the recommended LTPA.

Fig. 1
figure 1

Flow diagram of the included survey participants

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Table 1 Sample characteristics (adults aged ≥ 60 years): NHANES, 2011–2014
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Association between overall, intensity PA and cognitive performance

Figure 2 illustrates the findings from our logistic regression analysis, adjusted for all considered potential confounders, to evaluate the association between the levels of overall PA, MPA, and VPA with the presence of p-MCI. In model 4 (detailed in supplementary files), the analysis revealed that participants engaging in higher levels of PA (≥ 300 min/week) had a lower risk of p-MCI compared to those with lower PA levels (1–74 min/week, and 75–149 min/week). The analysis indicated a dose–response relationship for both overall PA [OR(CI) 0.79 (0.56–1.12) vs. 0.77 (0.51–1.15) vs. 0.56 (0.40–0.76)] and MPA [OR(CI) 0.85 (0.60–1.19) vs. 0.68 (0.45–1.01) vs. 0.63 (0.45–0.86)]. Specifically, participating in 300 min of PA and MPA weekly was associated with 44% reduction and 37% reduction in the prevalence of p-MCI, respectively. Performing VPA at 300 min/week was associated with a lower risk of p-MCI [OR 0.54, 95% CI (0.32–0.89)]. In model 5 (shown in Fig. 2), VPA was included as a confounder in the analysis of the association between MPA and cognition. While minor changes were observed, these changes did not affect the significance of the results [OR 0.67 95% CI (0.48–0.93)]. Conversely, when MPA was introduced as a confounder in the analysis of the association between VPA and cognition, the cognitive benefits of VPA became non-significant [OR 0.62, 95% CI (0.36–1.03)].

Fig. 2
figure 2

Multivariable OR for p-MCI based on the dosage of PA. PA: physical activity; OR: odds ratio; CI: confidence interval. All ORs were adjusted for age, sex, race, education, marital, PIR, smoking, alcohol, BMI, occupation, diabetes, hypertension, stroke, heart disease, respiratory disease, cancer and MPA or VPA

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Association between domain PA and cognitive performance

Table 2 presents the associations between OPA, LTPA, TPA, and the number of types meeting recommended activity levels with the prevalence of p-MCI across four different models. The findings across these models remained consistent, suggesting stable associations. In model 4, adjusted for all considered confounders, indicated that compared to individuals with no PA, those engaging in 1–149 min/week [OR 0.56, 95% CI (0.33–0.91)] and ≥ 300 min/week [OR 0.63, 95% CI (0.42–0.91)] of OPA, as well as ≥ 300 min/week [OR 0.54, 95% CI (0.35–0.81)] of LTPA, were associated with a lower prevalence of p-MCI. Model 5 was also introduced to explore the dependency relationship between different domains of PA. In this model, each PA domain was treated as a confounder for the others, and the results showed no significant changes. The trend analysis demonstrated a dose–response relationship between LTPA and cognition (P = 0.026). However, TPA did not show a statistically significant association with p-MCI prevalence. In addition, model 4 revealed a dose–response relationship, showing a significant reduction in p-MCI prevalence among individuals who met recommended activity levels in at least three types of activities [OR(CI) 0.73 (0.55–0.98) vs. 0.71 (0.44–1.13) vs. 0.42 (0.17–0.89)], compared to those not meeting any recommendations.

Table 2 Multivariable OR for p-MCI based on the dosage of PA
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Association between various PA types and cognitive performance

The detailed associations between various PA types and cognitive performance across four models were presented in supplementary files. In addition to the associations between intensity, domain PA, and cognition mentioned in previous sections. We further examined the association between activity levels in various types (MOPA, VOPA, MLTPA, and VLTPA) and p-MCI prevalence. In model 4, no statistically significant associations were observed between specific types of PA and p-MCI prevalence, except for MLTPA. Individuals engaging in 300 min/week of MLTPA experienced a 40% reduction in the prevalence of MCI. A dose–response relationship was also identified, as indicated by the P for trend analysis (P = 0.031).

Discussion

Main findings

In this cross-sectional study using data from the nationally representative NHANES survey, we had four main findings. First, we observed dose–response associations between PA and MPA with the prevalence p-MCI, suggesting that PA may be a modifiable factor influencing cognitive health. Second, engaging in at least 300 min/week of PA, and MPA was significantly associated with a lower prevalence of p-MCI. Third, higher levels of OPA and LTPA, but not TPA, were associated with better cognitive performance. Fourth, meeting the recommended activity levels in at least three different types of physical activities was notably associated with enhanced cognitive performance, suggesting a beneficial impact of diverse PA on cognitive health.

Interpretation of results

Association between overall, intensity PA and cognitive performance

The relationship between PA and cognitive function has been explored in several previous studies. Hamer, M. et al. [19] examined the association in the English Longitudinal Study of Ageing, finding that PA was associated with the preservation of cognitive function. Similarly, Wang et al. [20], using NHANES data, observed that high levels of PA were inversely associated with the incidence of cognitive impairment, corresponding to a 20% reduction in risk. In a cross-sectional study [29] with a sample size of 31,464 participants in India, it was found that frequently physically active older men and women had increases in cognitive function scores by 0.98 and 1.32 points, respectively, compared to less active older adults. These results were consistent with our findings.

The potential mechanisms by which PA enhances cognitive performance are as follows. Firstly, regular PA would increase cerebral blood flow by decreasing blood pressure, reducing plasma levels of low-density lipoproteins, inhibiting platelet aggregability, activating the brain, or enhancing cerebral metabolic demands [30]. Secondly, the neuroprotective effects of PA may be attributed to its role in enhancing the release of brain-derived neurotrophic factors (BDNF), which are crucial for brain health [31, 32]. Thirdly, PA may also exert an indirect effect on other modifiable factors related to cognitive function, including depression, and diabetes [33, 34]. Lastly, PA may decrease brain atrophy through higher levels of aerobic fitness and induce functional network changes [35, 36].

According to the 2018 PA guidelines [16], at least 150–300 min/week of MPA, or 75–150 min/week of VPA, or an equivalent combination of both was required for substantial health benefits. In addition, the guidelines suggest that engaging in PA beyond the equivalent of 300 min/week of MPA may offer additional health benefits. In our study, individuals who engage in more than 300 min/week of either PA or MPA showed a lower risk of developing p-MCI compared to those who did not engage in any intensity of PA. Another important finding in this result section is that in model 5, after introducing MPA as a confounder in the analysis of the relationship between VPA and cognition, the cognitive benefits of VPA became non-significant. The reason was that MPA and VPA were not independent of each other.

Association between domain PA and cognitive performance

Several studies have investigated the association between domain-specific PA and cognitive function. A French randomized controlled trial [37] explored the relationship between LTPA, housework PA, and gardening PA with cognitive performance, finding that higher levels of LTPA were associated with better function. Similarly, a meta-analysis of 93 original studies also observed that LTPA was positively associated with mental health [38]. These findings were in agreement with our results, revealing that engaging in LTPA for at least 300 min/week was significantly associated with a reduced risk of developing p-MCI. Possible explanations for this phenomenon were as follows. The 2020 Lancet Commission identified social isolation in older adults as one of the risk factors for dementia [39]. In our study, LTPA, defined as activities involving sports and fitness includes sports such as basketball or football that require social interaction with others, thereby improving cognitive performance [40, 41]. Additionally, individuals who had higher cognitive function tended to choose LTPA because they knew the importance of PA in promoting health [38]. Apart from that, previous studies [42, 43] showed that compared with PA with no choice, PA involving choice such as LTPA was connected to enjoyment and satisfaction, which were positively correlated with cognitive function [44].

Individuals engaging in 1–149 min/week and ≥ 300 min/week of OPA were more likely to experience improved cognitive performance in our study. The reason why the cognitive benefits of 150–299 min/week was not detected might be the limited sample size (N = 108) along with a large number of confounders. OPA refers to the time people spend doing work, which includes physical exertion alongside added mental demands. Higher mental demands in the workplace were observed to have a longitudinal association with enhanced cognitive performance among the aging [45, 46], and this could be explained by the concept of cognitive reserve and use-it-or-lose-it-hypothesis. Cognitive reverse suggested that individuals with it were able to maintain cognitive function through compensatory approaches, thereby mitigating the adverse effects of dementia pathology on cognition [45, 47]. Furthermore, use-it-or-lose-it-hypothesis stated that keeping mentally active would help prevent age-related mental decline [48, 49]. The association between OPA and cognitive performance was proved in previous studies. A cross-sectional survey found that moderate to high levels of work-related PA were beneficial for enhancing cognitive function in older adults [22]. A study using data from the HUNT4 70 + study concluded that working in a job with moderate or high PA regularly was connected to a higher risk of developing MCI [21]. TPA referred to walking or bicycling in our study, and it was categorized as MPA. Only TPA demonstrated no association with cognitive performance may be due to its simplicity [38].

The number of types of PA achieving the recommendation was also explored in our study, and we found that having more than or equal to three types of PA that met the recommendation is associated with a 58% reduction in the prevalence of MCI. This observation may indicate a positive correlation between a diverse range of PA and improved cognitive performance, a conclusion that aligned with findings from previous studies [50]. The evolutionary theory of adaptation may partly explain this phenomenon. It proposed that survival depended on the ability to adapt to new situations. In line with this, mental stimulation through exposure to enriched environments was also beneficial for the brain, thereby improving cognitive function [51, 52]. However, this conclusion should be treated with caution because, in our study, individuals meeting the recommendation in a greater variety of PA may be related to them engaging in more PA overall. Therefore, the amount of physical activity is an important confounder.

Future research directions

Based on our results and previous discussions, the following research directions are suggested. Firstly, due to the limited sample size and conflicting findings from previous studies, the specific relationship between the level of OPA and cognitive benefits has not been clarified remains unclear and warrants further investigation. Secondly, identifying the optimal PA strategies should be another direction as our evidence only suggest that a combination of various PA types is more beneficial. Thirdly, whether VPA should be recommended for older adults still lacks sufficient evidence, particularly given the low sample size in the study. Fourthly, the assessment of NHANES is performed in non-gerontologic settings as part of a global survey, which presents challenges for routine health assessments. The GPAQ is used for PA evaluation; however, it is not specifically designed for older adults, and recall bias may be more pronounced in this population. Therefore, there is a need to improve assessment tools for PA in older adults. Additionally, future studies should incorporate objectively assessed PA using wearable fitness trackers to ensure the accuracy of PA measurements. Cognitive assessment also requires professional staff due to their complexity, highlighting the need for sufficient training when assessing cognition in older populations. Lastly, more rigorous study designs, such as cohort studies and Mendelian randomization, are needed to validate our findings and provide stronger causal evidence.

Clinical implications

In this section, we outline specific recommendations for clinical practice to assist healthcare professionals in integrating evidence into their routine care. The implications are categorized into immediate clinical implications and typical multidimensional geriatric management implications.

Immediate clinical implications

Regarding intensity PA, we summarized that traditionally, VPA is often considered less suitable for older adults. Therefore, engaging in more than 300 min/week of MPA may be a more appropriate and beneficial approach for improving cognition in older adults. Furthermore, regarding the clinical implications of domain PA, we concluded that participating in 300 min/week of LTPA, especially MLTPA, and OPA at any level, is recommended.

Typical multidimensional geriatric management implications

In the aging era, older adults face many health challenges such as chronic diseases, polypharmacy, and psychological health problems, influencing their quality of life [53]. Integrating PA into multidimensional geriatric management holds great promise due to its extensive benefits across physiological, psychological, and social domains, contributing to the overall health of older adults [54]. As discussed in previous section, PA enhances physiological health by increasing cerebral blood flow, boosting BDNF levels, and reducing brain atrophy. Moreover, LTPA supports psychological and social well-being by reducing social isolation, promoting social interaction, and providing older adults a sense of enjoyment and satisfaction. Additionally, Cognitive reserve and use-it-or-lose-it hypothesis mentioned in the OPA section further highlight the psychological benefits of PA. Enhancing older adults’ adherence to PA and integrating it into their daily lives should be carefully considered.

Strengths and limitations

Our study has several strengths. We explored the relationship between cognitive performance and PA comprehensively, examining not only total PA but also the intensity and domain-specific aspects of PA. Given PA’s complexity, clarifying the specific influences of different types of PA on cognition is crucial. We used data from 2 cycles of NHANES (2011–2012, 2013–2014), a representative survey of the civilian, noninstitutionalized U.S. population to ensure the generalization of our results. Apart from that, recognizing that cognitive function and PA were influenced by multiple factors, we employed different models to adjust for potential confounders (i.e., sociodemographic, lifestyle, and clinical factors) to reveal the real association between these variables, enhancing the study’s internal validity and credibility. Lastly, NAHNES used three cognitive tests including CERAD, the Animal Fluency test, and the DSST to assess the cognitive performance of participants. We identified populations with p-MCI based on these assessment results, assigning clinical significance to the cognitive assessment results. However, there were some limitations in our study. Firstly, PA was assessed using GPAQ, which was self-reported by participants, and influenced by participants’ subjective memories to underestimate or overestimate PA levels, thereby reducing accuracy. Secondly, owing to the cross-sectional study nature of NHANES, we only provided data at one point in time rather than capturing the stable levels or trajectories of PA, thereby finding the association between PA and cognitive performance rather than the causal relationship. Thirdly, we failed to explore the best PA strategy due to the relatively small sample size. Therefore, we only found that a wide variety of PA may be related to better cognitive performance. Additionally, the sample size of older adults engaging in VPA was limited, and the combination of a small sample size with a high number of confounding variables made the specific effects of VPA on cognition unclear. Similarly, this limitation also applies to OPA.

Conclusions

In conclusion, our results suggested a positive association between higher levels of PA and enhanced cognitive performance. Specifically, engaging in at least 300 min/week of MPA, LTPA, or OPA, as well as 1–149 min/week of OPA, and embracing a diverse range of PA, were all significantly correlated with improved cognitive function. Future exploration, such as objectively measured PA and longitudinal studies were needed to validate our conclusion.

Data availability

The datasets used and analyzed during the current study are available from the corresponding author on reasonable request.

Abbreviations

PA:

Physical activity

OPA:

Occupational physical activity

TPA:

Transportational physical activity

LTPA:

Leisure-time physical activity

MPA:

Moderate physical activity

VPA:

Vigorous physical activity

MOPA:

Moderate occupational physical activity

VOPA:

Vigorous occupational physical activity

MLTPA:

Moderate leisure-time physical activity

VLTPA:

Vigorous leisure-time physical activity

CERAD:

The consortium to establish a registry for Alzheimer's disease

DSST:

The digit symbol substitution test

p-MCI:

Psychometric mild cognitive impairment

GED:

General educational development

AA:

Associate of arts

PIR:

Family income to poverty ratios

BMI:

Body mass index

References

  1. Ageing. https://www.unfpa.org/ageing. Accessed 2 Jan 2024.

  2. Murman DL. The Impact of Age on Cognition. Semin Hear. 2015;36(3):111–21.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Dhakal A, Bobrin BD. Cognitive Deficits. In: StatPearls. Treasure Island (FL): StatPearls Publishing. Copyright © 2024, StatPearls Publishing LLC.; 2024. https://pubmed.ncbi.nlm.nih.gov/32644478/.

  4. Bierman EJ, Comijs HC, Rijmen F, Jonker C, Beekman AT. Anxiety symptoms and cognitive performance in later life: results from the longitudinal aging study Amsterdam. Aging Ment Health. 2008;12(4):517–23.

    Article  PubMed  Google Scholar 

  5. Brodaty H, Heffernan M, Draper B, Reppermund S, Kochan NA, Slavin MJ, Trollor JN, Sachdev PS. Neuropsychiatric symptoms in older people with and without cognitive impairment. J Alzheimers Dis. 2012;31(2):411–20.

    Article  PubMed  Google Scholar 

  6. Bunce D, Batterham PJ, Mackinnon AJ, Christensen H. Depression, anxiety and cognition in community-dwelling adults aged 70 years and over. J Psychiatr Res. 2012;46(12):1662–6.

    Article  PubMed  Google Scholar 

  7. Gray M, Gills JL, Glenn JM, Vincenzo JL, Walter CS, Madero EN, Hall A, Fuseya N, Bott NT. Cognitive decline negatively impacts physical function. Exp Gerontol. 2021;143:111164.

    Article  PubMed  Google Scholar 

  8. Kewcharoen J, Trongtorsak A, Kanitsoraphan C, Prasitlumkum N, Mekritthikrai R, Techorueangwiwat C, Limpruttidham N, Rattanawong P. Cognitive impairment and 30-day rehospitalization rate in patients with acute heart failure: A systematic review and meta-analysis. Indian Heart J. 2019;71(1):52–9.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Yuan L, Zhang X, Guo N, Li Z, Lv D, Wang H, Jin J, Wen X, Zhao S, Xu T, et al. Prevalence of cognitive impairment in Chinese older inpatients and its relationship with 1-year adverse health outcomes: a multi-center cohort study. BMC Geriatr. 2021;21(1):595.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Duan J, Lv YB, Gao X, Zhou JH, Kraus VB, Zeng Y, Su H, Shi XM. Association of cognitive impairment and elderly mortality: differences between two cohorts ascertained 6-years apart in China. BMC Geriatr. 2020;20(1):29.

    Article  PubMed  PubMed Central  Google Scholar 

  11. The Risk and Costs of Severe Cognitive Impairment at Older Ages: Key Findings from our Literature Review and Projection Analyses ASPE RESEARCH BRIEF. https://aspe.hhs.gov/reports/risk-costs-severe-cognitive-impairment-older-ages-key-findings-our-literature-review-projection-0. Accessed 2 Jan 2024.

  12. Li S, Wang P, Cai Z, Jiang W, Xin X, Wang X, Zhou X. Correlates of physical activity levels, muscle strength, working memory, and cognitive function in older adults. Front Aging Neurosci. 2023;15:1283864.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Xu X, Xu Y, Shi R. Association between obesity, physical activity, and cognitive decline in Chinese middle and old-aged adults: a mediation analysis. BMC Geriatr. 2024;24(1):54.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Kivipelto M, Solomon A, Ahtiluoto S, Ngandu T, Lehtisalo J, Antikainen R, Bäckman L, Hänninen T, Jula A, Laatikainen T, et al. The Finnish Geriatric Intervention Study to Prevent Cognitive Impairment and Disability (FINGER): study design and progress. Alzheimers Dement. 2013;9(6):657–65.

    Article  PubMed  Google Scholar 

  15. Groot C, Hooghiemstra AM, Raijmakers PG, van Berckel BN, Scheltens P, Scherder EJ, van der Flier WM, Ossenkoppele R. The effect of physical activity on cognitive function in patients with dementia: A meta-analysis of randomized control trials. Ageing Res Rev. 2016;25:13–23.

    Article  PubMed  CAS  Google Scholar 

  16. Piercy KL, Troiano RP, Ballard RM, Carlson SA, Fulton JE, Galuska DA, George SM, Olson RD. The Physical Activity Guidelines for Americans. JAMA. 2018;320(19):2020–8.

    Article  PubMed  PubMed Central  Google Scholar 

  17. He F, Li Y, Hu Z, Zhang H. Association of domain-specific physical activity with depressive symptoms: A population-based study. Eur Psychiatry. 2022;66(1):e5.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Xiang B, Zhou Y, Wu X, Zhou X. Association of Device-Measured Physical Activity With Cardiovascular Outcomes in Individuals With Hypertension. Hypertension. 2023;80(11):2455–63.

    Article  PubMed  CAS  Google Scholar 

  19. Hamer M, Muniz Terrera G, Demakakos P. Physical activity and trajectories in cognitive function: English Longitudinal Study of Ageing. J Epidemiol Community Health. 2018;72(6):477–83.

    Article  PubMed  Google Scholar 

  20. Wang N, Wang L, Wang J, Chen R, Shi M, Liu H, Xu X. Effects of physical activity and depressive symptoms on cognitive function in older adults: National Health and Nutrition Examination Survey. Neurol Sci. 2024;45(1):299–308.

    Article  PubMed  Google Scholar 

  21. Zotcheva E, Bratsberg B, Strand BH, Jugessur A, Engdahl BL, Bowen C, Selbæk G, Kohler HP, Harris JR, Weiss J, et al. Trajectories of occupational physical activity and risk of later-life mild cognitive impairment and dementia: the HUNT4 70+ study. Lancet Reg Health Eur. 2023;34: 100721.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Liu Y, Hou X, Tang Z, Zhang H, Liu J. The effect of different types of physical activity on cognitive reaction time in older adults in China. Front Public Health. 2022;10:1051308.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Cleland CL, Hunter RF, Kee F, Cupples ME, Sallis JF, Tully MA. Validity of the Global Physical Activity Questionnaire (GPAQ) in assessing levels and change in moderate-vigorous physical activity and sedentary behaviour. BMC Public Health. 2014;14(1):1255.

  24. Divney AA, Murillo R, Rodriguez F, Mirzayi CA, Tsui EK, Echeverria SE. Diabetes Prevalence by Leisure-, Transportation-, and Occupation-Based Physical Activity Among Racially/Ethnically Diverse U.S. Adults. Diabetes Care. 2019;42(7):1241–7.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Kim D, Vazquez-Montesino LM, Li AA, Cholankeril G, Ahmed A. Inadequate Physical Activity and Sedentary Behavior Are Independent Predictors of Nonalcoholic Fatty Liver Disease. Hepatology. 2020;72(5):1556–68.

    Article  PubMed  CAS  Google Scholar 

  26. Smagula SF, Zhang G, Gujral S, Covassin N, Li J, Taylor WD, Reynolds CF 3rd, Krafty RT. Association of 24-Hour Activity Pattern Phenotypes With Depression Symptoms and Cognitive Performance in Aging. JAMA Psychiat. 2022;79(10):1023–31.

    Article  Google Scholar 

  27. Zhou L. Association of vitamin B2 intake with cognitive performance in older adults: a cross-sectional study. J Transl Med. 2023;21(1):870.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  28. Christensen K, Gleason CE, Mares JA. Dietary carotenoids and cognitive function among US adults, NHANES 2011–2014. Nutr Neurosci. 2020;23(7):554–62.

    Article  PubMed  CAS  Google Scholar 

  29. Kumar M, Srivastava S, Muhammad T. Relationship between physical activity and cognitive functioning among older Indian adults. Sci Rep. 2022;12(1):2725.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  30. Rogers RL, Meyer JS, Mortel KF. After reaching retirement age physical activity sustains cerebral perfusion and cognition. J Am Geriatr Soc. 1990;38(2):123–8.

    Article  PubMed  CAS  Google Scholar 

  31. Loprinzi PD, Frith E. A brief primer on the mediational role of BDNF in the exercise-memory link. Clin Physiol Funct Imaging. 2019;39(1):9–14.

    Article  PubMed  Google Scholar 

  32. Nascimento CM, Pereira JR, de Andrade LP, Garuffi M, Talib LL, Forlenza OV, Cancela JM, Cominetti MR, Stella F. Physical exercise in MCI elderly promotes reduction of pro-inflammatory cytokines and improvements on cognition and BDNF peripheral levels. Curr Alzheimer Res. 2014;11(8):799–805.

    Article  PubMed  Google Scholar 

  33. Brown BM, Peiffer JJ, Martins RN. Multiple effects of physical activity on molecular and cognitive signs of brain aging: can exercise slow neurodegeneration and delay Alzheimer’s disease? Mol Psychiatry. 2013;18(8):864–74.

    Article  PubMed  CAS  Google Scholar 

  34. Jensen CS, Hasselbalch SG, Waldemar G, Simonsen AH. Biochemical Markers of Physical Exercise on Mild Cognitive Impairment and Dementia: Systematic Review and Perspectives. Front Neurol. 2015;6:187.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Bugg JM, Head D. Exercise moderates age-related atrophy of the medial temporal lobe. Neurobiol Aging. 2011;32(3):506–14.

    Article  PubMed  Google Scholar 

  36. Colcombe SJ, Erickson KI, Raz N, Webb AG, Cohen NJ, McAuley E, Kramer AF. Aerobic fitness reduces brain tissue loss in aging humans. J Gerontol A Biol Sci Med Sci. 2003;58(2):176–80.

    Article  PubMed  Google Scholar 

  37. de Souto BP, Andrieu S, Rolland Y, Vellas B. Physical activity domains and cognitive function over three years in older adults with subjective memory complaints: Secondary analysis from the MAPT trial. J Sci Med Sport. 2018;21(1):52–7.

    Article  Google Scholar 

  38. White RL, Babic MJ, Parker PD, Lubans DR, Astell-Burt T, Lonsdale C. Domain-Specific Physical Activity and Mental Health: A Meta-analysis. Am J Prev Med. 2017;52(5):653–66.

    Article  PubMed  Google Scholar 

  39. Livingston G, Huntley J, Sommerlad A, Ames D, Ballard C, Banerjee S, Brayne C, Burns A, Cohen-Mansfield J, Cooper C, et al. Dementia prevention, intervention, and care: 2020 report of the Lancet Commission. Lancet. 2020;396(10248):413–46.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Iizuka A, Suzuki H, Ogawa S, Kobayashi-Cuya KE, Kobayashi M, Inagaki H, Sugiyama M, Awata S, Takebayashi T, Fujiwara Y. Does social interaction influence the effect of cognitive intervention program? A randomized controlled trial using Go game. Int J Geriatr Psychiatry. 2019;34(2):324–32.

    Article  PubMed  Google Scholar 

  41. Zhaoyang R, Scott SB, Martire LM, Sliwinski MJ. Daily social interactions related to daily performance on mobile cognitive tests among older adults. PLoS ONE. 2021;16(8): e0256583.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  42. Lubans DR, Smith JJ, Morgan PJ, Beauchamp MR, Miller A, Lonsdale C, Parker P, Dally K. Mediators of Psychological Well-being in Adolescent Boys. J Adolesc Health. 2016;58(2):230–6.

    Article  PubMed  Google Scholar 

  43. Parfitt G, Rose EA, Burgess WM. The psychological and physiological responses of sedentary individuals to prescribed and preferred intensity exercise. Br J Health Psychol. 2006;11(Pt 1):39–53.

    Article  PubMed  Google Scholar 

  44. Shi X, He X, Pan D, Qiao H, Li J. Happiness, depression, physical activity and cognition among the middle and old-aged population in China: a conditional process analysis. PeerJ. 2022;10: e13673.

    Article  PubMed  PubMed Central  Google Scholar 

  45. Boots EA, Schultz SA, Almeida RP, Oh JM, Koscik RL, Dowling MN, Gallagher CL, Carlsson CM, Rowley HA, Bendlin BB, et al. Occupational Complexity and Cognitive Reserve in a Middle-Aged Cohort at Risk for Alzheimer’s Disease. Arch Clin Neuropsychol. 2015;30(7):634–42.

    Article  PubMed  PubMed Central  Google Scholar 

  46. Fisher GG, Stachowski A, Infurna FJ, Faul JD, Grosch J, Tetrick LE. Mental work demands, retirement, and longitudinal trajectories of cognitive functioning. J Occup Health Psychol. 2014;19(2):231–42.

    Article  PubMed  PubMed Central  Google Scholar 

  47. Stern Y. What is cognitive reserve? Theory and research application of the reserve concept. J Int Neuropsychol Soc. 2002;8(3):448–60.

    Article  PubMed  Google Scholar 

  48. Hultsch DF, Hertzog C, Small BJ, Dixon RA. Use it or lose it: engaged lifestyle as a buffer of cognitive decline in aging? Psychol Aging. 1999;14(2):245–63.

    Article  PubMed  CAS  Google Scholar 

  49. Salthouse TA. Mental Exercise and Mental Aging: Evaluating the Validity of the “Use It or Lose It” Hypothesis. Perspect Psychol Sci. 2006;1(1):68–87.

    Article  PubMed  Google Scholar 

  50. Lee S, Charles ST, Almeida DM. Change Is Good for the Brain: Activity Diversity and Cognitive Functioning Across Adulthood. J Gerontol B Psychol Sci Soc Sci. 2021;76(6):1036–48.

    Article  PubMed  Google Scholar 

  51. Kolarik BS, Stark SM, Stark CEL. Enriching Hippocampal Memory Function in Older Adults Through Real-World Exploration. Front Aging Neurosci. 2020;12:158.

    Article  PubMed  PubMed Central  Google Scholar 

  52. Pang TY, Hannan AJ. Enhancement of cognitive function in models of brain disease through environmental enrichment and physical activity. Neuropharmacology. 2013;64:515–28.

    Article  PubMed  CAS  Google Scholar 

  53. Rony MKK, Parvin MR, Wahiduzzaman M, Akter K, Ullah M. Challenges and Advancements in the Health-Related Quality of Life of Older People. Advances in Public Health. 2024;2024(1):8839631.

    Google Scholar 

  54. Baldelli G, De Santi M, De Felice F, Brandi G. Physical activity interventions to improve the quality of life of older adults living in residential care facilities: a systematic review. Geriatr Nurs. 2021;42(4):806–15.

    Article  PubMed  Google Scholar 

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Acknowledgements

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Funding

This study was funded by the Non-Profit Central Research Institute Fund of Chinese Academy of Medical Sciences (Grant NO. 2023-RC320-01).

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Authors and Affiliations

  1. Chinese Academy of Medical Sciences, Peking Union Medical College School of Nursing, Beijing, China

    Si-Jia Li, Hao-Ming Ma, Ao-Qi Wang, Runyuan Pei, Xing-Yi Tang, Guang-Nan Liu, You Zhou & Mei-Hua Piao

  2. Department of Nursing, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), No. 9 9th Street, Qiantang District, Hangzhou, Zhejiang, China

    You Zhou

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  1. Si-Jia Li
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Contributions

S-J.L. was responsible for Conceptualization, Methodology, Writing the original draft, as well as Reviewing and Editing the manuscript. H-M.M. contributed to Conceptualization, Methodology, and Data curation. A-Q.W. worked on Software, Data curation, and Formal Analysis. R-Y.P. was involved in Methodology, Software, and Data curation. X–Y.T. contributed to Reviewing and Editing the manuscript. G-N.L. focused on Conceptualization. Y.Z. handled Methodology, Formal Analysis, Supervision, and was involved in Reviewing and Editing the manuscript. M-H.P. was responsible for Conceptualization, Methodology, Formal Analysis, Supervision, as well as Reviewing and Editing the manuscript. All authors reviewed the manuscript.

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Correspondence to You Zhou or Mei-Hua Piao.

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Li, SJ., Ma, HM., Wang, AQ. et al. Association of cognitive performance with overall, dosage, intensity, and domain physical activity in aging: NHANES 2011–2014. BMC Geriatr 24, 910 (2024). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12877-024-05503-2

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Keywords

BMC Geriatrics

ISSN: 1471-2318

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