The associations between sedentary behavior and cognition in a population cohort of older adults

Abstract

Background

Sedentary behavior is common in older adulthood and is associated with poor health outcomes. Less is known about how sedentary behavior relates to cognition in older adulthood and how it relates to increased risk for cognitive decline associated with Alzheimer's disease (AD).

Objective

We sought to examine these associations in a large, population-based cohort of community-dwelling older adults residing in a Rust Belt region of the United States.

Methods

A subset of the population-based Monongahela–Youghiogheny Healthy Aging Team (MYHAT) participants (n = 193) completed 7 days of wrist-accelerometry following comprehensive neuropsychological assessment. Cross-sectional linear regression models related sedentary time to domains of cognition. Models were adjusted by age, sex, education, and APOE4 carrier status and moderate to vigorous physical activity (MVPA). The interaction between sedentary behavior and APOE4 genotype on cognition was also examined.

Results

Greater sedentary behavior was associated with worse executive function (β = −0.06, p = 0.01) and memory (β = −0.06, p = 0.05) performance. These results were attenuated when adjusting for MVPA. No significant interactions between sedentary time and APOE4 carrier status were observed, although estimation results applying the delta method on regression coefficients suggested the associations were stronger in APOE4 non-carriers when compared to APOE4 carriers.

Conclusions

Higher levels of sedentary behavior were associated with worse performance in cognitive domains implicated in AD. Public health initiatives and precision-based medicine approaches to reduce sedentary behavior in a population-based cohort of older adults may be important AD prevention measures. Results support the importance of reducing sedentary time.

Keywords

Alzheimer’s disease cognition older adult population study sedentary

Introduction

Sedentary behavior in older adulthood is a common and modifiable health factor, with the average older adult in the US spending about 10 h daily being sedentary.¹ More than 10 h of sedentary time per day in older adulthood has been linked to an increased risk for dementia.² Given the impact of sedentary behavior on risk for poor health outcomes in aging,^3,4 there has been recent interest in examining the impacts of sedentary behavior on specific cognitive domains.

The current evidence linking sedentary behavior to cognition is mixed. Some studies find that greater sedentary behavior is associated with worse global cognition.⁵ Prior literature that has examined the association between sedentary behavior and specific cognitive domains point to an association with executive function^6,7 and memory.⁸ Other work has shown that greater sedentary behavior predicted worse processing speed and language (confrontation naming) over a 7-year follow-up period.⁹ Other literature shows no impact of sedentary behavior on cognition^10–12; however, many studies vary in their measurement of these constructs, which could contribute to inconsistent findings. Prior work in this area often rely on self-report, which has been shown to underestimate sedentary behavior compared to objective device-based measurements.¹³ In addition, sedentary behavior, while interrelated to physical activity, may also be an independent risk factor for dementia¹⁴; however, many studies do not adjust for total physical activity when examining how sedentary behavior relates to cognition, which does not allow for the independent risk of sedentary behavior to be accounted for.¹⁴ Therefore, examining how objectively measured sedentary behavior relates to specific cognitive domains, while also considering physical activity, would better our understanding of gaps in the current literature.

The mechanisms underlying sedentary behavior and changes in cognition are poorly understood. Evidence suggests that greater sedentary behavior is related to neurodegeneration, including medial temporal lobe thinning,¹⁵ white matter atrophy¹⁶ and hyperintensities.¹⁷ Greater sedentary time may also lead to cognitive decline through cerebral and systemic vascular dysfunction, increases in inflammation, and reduction in synaptic plasticity.¹⁸ The potential downstream effects of these cascades are myriad but may include increased risk for development of Alzheimer's disease (AD). It is also likely that common comorbidities in older adulthood (e.g., heart problems, low mood, mobility issues) may have a bidirectional relationship with sedentariness.^19,20 More research is needed to understand the biological mechanisms underlying sedentary behavior and risk for AD.

This study leverages a well-characterized population cohort of older adults with 7 days of wrist accelerometry data with objective measurement of sedentary behavior to examine associations with cognitive domains measured via a comprehensive neuropsychological assessment. We hypothesize that greater sedentary behavior will be related to worse cognitive performance above and beyond level of physical activity, specifically in domains also impacted by AD (i.e., memory, executive functions). We also hypothesize that APOE4 carrier status will influence this association, such that the effects of more sedentary time will be worse for cognition among APOE4 carriers.

Methods

Study cohort

The Monongahela–Youghiogheny Healthy Aging Team (MYHAT) is an ongoing, population-based study cohort of mild cognitive impairment drawn from a Rust Belt region in southwestern Pennsylvania, USA. MYHAT participants undergo study visits annually. Study recruitment occurred during two periods (2006–2008 and 2016–2019) using age-stratified random sampling from publicly available voter registration lists. Individuals were excluded if, at study entry, they were under 65 years old, did not reside in one of the designated areas, lived in long-term care, had severe hearing or vision impairments preventing neuropsychological testing, or lacked the capacity to provide informed consent, or, at study entry, already had substantial cognitive impairment evidenced by age-education- adjusted Mini-Mental State Exam scores <21.²¹ This study was approved by the University of Pittsburgh Institutional Review Board and written consent was obtained from all participants.

Accelerometry

Participants were asked to wear a triaxial accelerometer (ActiGraph GT3X, Actigraph, Pensacola, USA) on their non-dominant wrist for 24 h per day over 7 consecutive days (device set to 80 Hz sampling rate). Accelerometry data began collection in 2021 and ended in 2025. Raw accelerometry data were downloaded and exported using ActiLife software (Actigraph, Pensacola, USA) and processed in R software using the GGIR package (version 2.4-0, https://cran.r-project.org/web/packages/GGIR/).²² GGIR auto-calibrated the data according to local gravity, censored abnormally high accelerations, and identified non-wear time following previously validated algorithms.^23–25 Accelerations related to movement were then quantified over 5-s epochs using the Euclidian Norm Minus One ( $ENMO = \sqrt{x^{2} + y^{2} + z^{2}} - 1 g$ ), with negative values rounded to zero. Final values were expressed in milligravity units (mg), which describe units of acceleration and is a common unit to express accelerometry metrics captured in three directions (i.e., the x, y, z planes).

Cut points for older adults activity thresholds for wrist accelerometry variables in community-dwelling older adults were calculated as follows: (1) sedentary behavior ≤49 mg, (2) light physical activity (LPA) 50–99 mg, and (3) moderate-to-vigorous physical activity (MVPA) ≥ 100 mg.^26–28 Sleep periods were detected by GGIR by using algorithms that discriminate sleep from wakefulness and inactivity periods, and then sleep periods are excluded from quantifications of sedentary behavior and physical activity. The 24 h continuity of activity level was calculated daily for all participants over the 7 day span. A valid wear day was defined as ≥10 h of wear time.²⁹ GGIR uses an algorithm that identifies non-wear time by detecting patterns in the raw acceleration signals. Participants with fewer than 4 valid days of data were excluded.³⁰ Average minutes per day spent in sedentary behavior was calculated for each participant.

Neuropsychological assessment and cognitive status

At baseline and each annual visit, a comprehensive battery of neuropsychological tests was administered to evaluate cognitive functioning across five cognitive domains including attention/psychomotor speed, executive functions, memory, language, and visuospatial functions. Composite Z-scores were developed by averaging baseline-referenced Z-scores within each domain, as described in detail elsewhere.^31,32 Cross-sectional neuropsychological assessment data collected at the same cycle as the accelerometry data was utilized for the present study. The Clinical Dementia Rating^® (CDR) Scale³³ was used for to classify participants’ cognitive status as Cognitively Unimpaired (CU; CDR = 0) and Mild Cognitive Impairment (MCI; CDR = 0.5) diagnostic categories. Participants with Dementia (CDR> = 1) were excluded.

APOE4 genotyping

Apolipoprotein E (APOE4) genotyping was conducted using blood or saliva samples as previously described.³⁴ For the current analysis, participants were grouped into APOE4 carrier (E4/E4, E4/E3, E4/E2) versus non-carrier E4 (E3/E3, E2/E3) status.

Analyses

Demographic, health, and neuropsychological characteristics were summarized as mean ± standard deviation (SD) for normally distributed continuous variables, median (interquartile range: Q1, Q3) for non-normal continuous variables, and frequency (percentage) for categorical variables. Characteristics were reported overall and by cognitive status, with group comparisons conducted using two-sample t-tests, Wilcoxon rank-sum tests, chi-squared tests, or Fisher's exact tests, as appropriate. Linear regression models were fitted to examine the association between sedentary time (average minutes per day) and each cross-sectional neuropsychological domain score (one score per model), adjusting for age, sex, education, and APOE4 carrier status (carrier versus non-carrier). Models were repeated with the addition of moderate-to-vigorous physical activity (MVPA) as a covariate, dichotomized based on recommended guidelines (<150, ≥150 min per week),³⁵ to assess the independent contribution of sedentary behavior to outcomes. To evaluate potential effect modification by APOE4 status, an interaction term between sedentary time and APOE4 status was included in additional models. As an exploratory analysis, we estimated the stratified effect sedentary time on neuropsychological outcomes in each model for APOE4 non-carriers and carriers using Delta methods.³⁶ Statistical significance was set a priori as p < 0.05. All analyses were conducted using R 4.2.2 (https://www.r-project.org). A false discovery rate (FDR) procedure was applied to account for multiple comparisons.³⁷

Results

Participant characteristics

Of the participants who agreed to participate and completed one week of accelerometry, 209 participants had properly activated devices that captured data. Five participants were excluded for less four consecutive device wear days, one participant was excluded for a dementia diagnosis, one participant was excluded for missing cognitive diagnosis information, and nine others were excluded for missing covariate information (i.e., APOE4 status). Participants then included 193 older adults (76 ± 7 years old, 33% with highest education level of high school or below, 64% female, 95% White/non-Hispanic). Most participants (86%) were cognitively unimpaired (CDR=0) at the time of accelerometry assessment baseline. A majority of the sample (70%) reported hypertension. Like many population-based samples, 17% of participants were APOE4 carriers (E4/E4, E4/E3, E4/E2; n = 34).

A little over half (57%) of participants met the Center for Disease Control (CDC) recommended guidelines of at least 150 min of MVPA per week.³⁵ Average sedentary time was 841 min per day (∼14 h). See Table 1 for additional details.

Table 1.

Participant characteristics.

	Total N = 193	Cognitively Unimpaired (CDR=0) N = 166	MCI (CDR=0.5) N = 27	p ^b
Demographic and Health Characteristics (mean ± SD)
Age, y	76 ± 7	76 ± 6	78 ± 8	0.64
Age, y, median (Q1, Q3)	74 (72, 80)	74 (72, 83)	74 (71, 80)
Sex, female, n (%)	123 (64%)	106 (65%)	17 (63%)	0.99
Race, white, n (%)	183 (95%)	157 (95%)	26 (96%)	0.99
Education,^a >High School, n (%)	130 (67%)	113 (68%)	17 (63%)	0.76
Average sedentary time, min/day	842 ± 119	830 ± 115	917 ± 113	<0.001
Self-report hypertension, n (%) (2 missing)	134 (70%)	117 (71%)	17 (65%)	0.57
Self-report diabetes, n (%) (1 missing)	59 (31%)	48 (29%)	11 (41%)	0.22
APOE ε4 status, carriers, n (%)	34 (17%)	28 (16%)	6 (22%)	0.72
APOE E2/E4, carriers, n (%)	2 (1%)	1 (1%)	1 (4%)	0.26
APOE E3/E4, carriers, n (%)	28 (15%)	23 (14%)	5 (18%)	0.56
APOE E4/E4, carriers, n (%)	4 (2%)	4 (2%)	0 (0%)	1
APOE ε4 status, non-carriers, n (%)	159 (82%)	138 (83%)	21 (78%)	0.69
APOE E2/E3, carriers, n (%)	24 (12%)	22 (13%)	2 (7%)	0.54
APOE E3/E3, carriers, n (%)	135 (70%)	116 (70%)	19 (70%)	0.99
MVPA time, minutes/day	36.92 ± 32.95	40.11 ± 33.82	17.30 ± 17.20	0.0001
MVPA time, ≥150 min/day, n (%)	109 (57%)	103 (62%)	6 (22%)	0.0003
Neuropsychological Outcomes (mean ± SD)
Attention Composite	0.02 ± 0.68	0.06 ± 0.69	−0.24 ± 0.59	0.02
Executive Composite	0.07 ± 0.65	0.11 ± 0.65	−0.14 ± 0.67	0.10
Language Composite	0.16 ± 0.68	0.19 ± 0.70	−0.04 ± 0.53	0.03
Visuospatial Composite	0.08 ± 0.82	0.16 ± 0.79	−0.34 ± 0.92	0.02
Memory Composite	0.53 ± 0.88	0.65 ± 0.82	−0.24 ± 0.84	<0.0001

APOE4: Apolipoprotein E4 allele; MCI: mild cognitive impairment; MVPA: moderate to vigorous activity; SD: standard deviation.

This table presents the characteristics of the study population (N = 193) included in the regression analyses, grouped by MCI status. MCI was defined as a Clinical Dementia Rating (CDR) score of 0.5. Continuous variables were summarized as mean ± standard deviation (SD); for skewed distributions, median (Q1, Q3) is also presented. Categorical variables are presented as frequency and percentages: n (%).

Education > high school was defined as any education beyond high school.

p-values represent the comparison between the cognitively unimpaired (i.e., non-MCI) and the MCI groups. For continuous variables, the p values were derived from two sample t-tests or Wilcoxon rank-sum tests; while for categorical variables, the p values were derived from chi-squared tests or Fishers’ exact tests, as appropriate. A significance level of 0.05 was used and significant values are bolded.

Sedentary behavior and cognition

Adjusting for age, sex, education and APOE4 carrier status, greater sedentary time was cross-sectionally associated with worse executive function (β = −0.06, p = 0.01), and memory (β = −0.06, p = 0.05) performance (Figure 1). No significant associations were observed with attention, language, or visuospatial functioning (all p-values >0.08). After applying FDR correction for the multiple comparisons across all of the five neuropsychological domains, only the association between greater sedentary time and worse executive function remained statistically significant (β = −0.06, FDR-p = 0.05; Table 2).

Figure 1.

Sedentary time is cross-sectionally associated with attention, executive function, and memory. Association between sedentary time and neuropsychological domain scores for (A) executive function and (B) memory adjusting for age, sex, education, and APOE4 carrier status.

Table 2.

Sedentary time associations with cognition.

Model: Outcome ∼ Sedentary Time + APOE4 + Age (in years) + Sex + Education
Neuropsychological Outcomes	β	SE	95% CI (β)		N	t	p	Adjusted p^a
Neuropsychological Outcomes	β	SE	Lower	Upper	N	t	p	Adjusted p^a
Attention Composite	−0.0447	0.0253	−0.0942	−0.0048	193	−1.7682	0.08	0.13
Executive Composite	−0.0617	0.0236	−0.1080	−0.0154	193	−2.6136	0.001	0.05
Language Composite	−0.0232	0.0249	−0.0721	0.0256	192	−0.9320	0.35	0.40
Memory Composite	−0.0636	0.0321	−0.1266	−0.0006	192	−1.9796	0.05	0.12
Visuospatial Composite	−0.0276	0.0328	−0.0919	0.0368	167	−0.8396	0.40	0.40

Model: Outcome ∼ Sedentary Time + APOE4 + Age (in years) + Sex + Education + MVPA
Neuropsychological Outcomes	β	SE	95% CI (β)		N	t	p	Adjusted p^a
Neuropsychological Outcomes	β	SE	Lower	Upper	N	t	p	Adjusted p^a
Attention Composite	−0.0351	0.0295	−0.0930	0.0228	193	−1.1884	0.24	0.44
Executive Composite	−0.0362	0.0274	−0.0899	0.0175	193	−1.3216	0.19	0.44
Language Composite	0.0061	0.0289	−0.0506	0.0627	192	0.2104	0.83	0.83
Memory Composite	−0.0418	0.0375	−0.1152	0.0317	192	−1.1141	0.27	0.44
Visuospatial Composite	−0.0143	0.0390	−0.0907	0.0620	167	−0.3675	0.71	0.83

SE: standard error; CI: confidence interval; N: number of observations; APOE4: apolipoprotein E4 allele; MVPA: moderate to vigorous activity; p value <0.05 indicates significant result at a significance level of 0.05.

This table shows the estimation results of regression models to determine the cross-sectional effect of sedentary time on each neuropsychological outcome, adjusting to age (in years), sex (female versus male), education attainment, and APOE4 status (carrier versus non-carrier), either without or with additional adjustment to MVPA (≥150 versus <150 min per week). The β coefficient represents the estimated effect of sedentary time. Significant p values are indicated in bold.

The adjusted p values were calculated by the Benjamini-Hochberg procedure to control for the false discovery rate (FDR) in multiple comparison across all the five analyzed neuropsychological outcomes.

With additional adjustment for MVPA, all previously significant associations were attenuated, and sedentary time was not associated with any cognitive domain (all p values >0.19, all FDR-adjusted p values >0.44). See Table 2 and Figure 2 for more details.

Figure 2.

Interval plot (mean with 95% confidence intervals plotted) for coefficient estimates of sedentary time on each neuropsychological outcome, with and without adjustment for MVPA.

APOE4 × sedentary behavior on cognition

No significant overall interactions between sedentary time and APOE4 carrier status were observed overall (all p values >0.25, all FDR-adjusted p values >0.67; Table 3), and results remained non-significant after additional adjustment for MVPA (all p values >0.27; all FDR-adjusted p values >0.65; Table 3).

Table 3.

Sedentary time × APOE4 associations with cognition.

Model: Outcome ∼ Sedentary Time + APOE4 + Age (in years) + Sex + Education + Sedentary Time × APOE4
Neuropsychological Outcomes	β (Sedentary Time × APOE4)	SE	95% CI (β)		N	t	p	Adjusted p^a
Neuropsychological Outcomes	β (Sedentary Time × APOE4)	SE	Lower	Upper	N	t	p	Adjusted p^a
Attention Composite	−0.0836	0.0725	−0.2258	0.0586	193	−1.1522	0.25	0.67
Executive Composite	0.0369	0.0680	−0.0964	0.1702	193	0.5427	0.59	0.74
Language Composite	0.0087	0.0720	−0.1323	0.1497	192	0.1212	0.90	0.90
Memory Composite	−0.1027	0.0924	−0.2837	0.0784	192	−1.1116	0.27	0.67
Visuospatial Composite	0.0534	0.0885	−0.1200	0.2268	167	0.6035	0.55	0.74

Model: Outcome ∼ Sedentary Time + APOE4 + Age (in years) + Sex + Education + Sedentary Time × APOE4 + MVPA
Neuropsychological Outcomes	β (Sedentary Time × APOE4)	SE	95% CI (β)		N	t	p	Adjusted p^a
Neuropsychological Outcomes	β (Sedentary Time × APOE4)	SE	Lower	Upper	N	t	p	Adjusted p^a
Attention Composite	−0.0802	0.0730	−0.2232	0.0628	193	−1.0993	0.27	0.65
Executive Composite	0.0479	0.0678	−0.0851	0.1809	193	0.7061	0.48	0.65
Language Composite	0.0205	0.0716	−0.1200	0.1609	192	0.2855	0.78	0.78
Memory Composite	−0.0947	0.0927	−0.2763	0.0869	192	−1.0220	0.31	0.65
Visuospatial Composite	0.0570	0.0888	−0.1170	0.2311	167	0.6423	0.52	0.65

APOE4: apolipoprotein E4 allele; CI: confidence interval; MVPA: moderate to vigorous activity; N: number of observations; SE: standard error.

This table presents the results of regression models estimating the cross-sectional effect of sedentary time on each neuropsychological outcome, including an interaction item between sedentary time and APOE4 status. Models were adjusted for age (in years), sex (female versus male), education attainment, APOE4 status (carrier versus non-carrier), and the sedentary time×APOE4 interaction term, with and without additional adjustment for MVPA (≥150 versus <150 min per week). The β coefficient represents the estimated interaction effect between sedentary time (in hours) and APOE4 status. A significance level of 0.05 was used; and statistically significant p values are shown in bold.

Adjusted p values were calculated by the Benjamini-Hochberg procedure to control the false discovery rate (FDR) across the five neuropsychological outcomes.

Among APOE4 non-carriers, greater sedentary time was significantly associated with worse executive function (β = −0.07, p = 0.01), after adjusting for all covariates (see Supplemental Table 1). This association remained significant after FDR correction for multiple comparisons (FDR-p = 0.05). However, the effect was attenuated with additional adjustment for MVPA. In contrast, among APOE4 carriers, no significant associations were found between sedentary time and any neuropsychological domain (all p-values >0.08; all FDR-adjusted p values >0.21; Supplemental Table 2).

Discussion

In a population cohort of community-dwelling older adults free of dementia, we examined how objectively measured sedentary behavior related to domain-specific aspects of cognition. We found that greater sedentary behavior was associated with worse performance in executive function and memory. However, these associations were attenuated when accounting for intensity of physical activity. In addition, there were no significant overall interactions on the association between sedentary behavior and cognition by APOE4 carrier status. Overall, these findings suggest that greater sedentary behavior may be a risk factor for AD.

Consistent with prior literature, greater sedentary behavior was related to worse memory^38–40 and executive function performance,⁴¹ which are typically the first domains to be impacted by AD.⁴² This is consistent with a recent study that found that greater sedentary behavior was cross-sectionally related to worse episodic memory in a community-dwelling cohort free of dementia at baseline.⁹ Changes in executive function in aging are often preceded by cardiovascular disease,^43,44 suggesting an additional concomitant pathway by which greater sedentary behavior may relate to worse cognition. Surprisingly, results were attenuated when adjusting for physical activity level based on CDC guidelines,³⁵ as evidence suggests that physical activity and sedentary behavior may be related but separate constructs.⁴⁵ However, only slightly more than half of the sample were meeting these guidelines, which is quite low. The average sedentary behavior time of the sample was 14 h, which is on the higher end,¹ suggesting that this population-based sample is overall less active than samples typically seen in self-selective volunteer and clinical research samples. In older adults who are very sedentary, meeting physical activity requirements may mitigate some cognitive risk associated with higher levels of sedentariness, and this may explain why our results were attenuated with the addition of MVPA in the model. More work is needed to disentangle the independent and interdependent effects of daily activity (sedentary time, physical activity, and sleep) on cognition in older adulthood.

While there was no overall interaction between sedentary time and APOE4 carrier status on cognition, greater sedentary time was associated with worse executive functioning in APOE4 non-carriers only. Given the very small number of APOE4 carriers in our sample, this analysis was exploratory and it is probable that we were not powered to find an overall interaction. Furthermore, the limited previous findings examining sedentary behavior and APOE4 carrier status have typically been mixed,^46,47 with some work even finding an effect of sedentary behavior on cognition in non-carriers only. Further replication in a larger group with more APOE4 carriers is needed to better understand these associations.

This study has several notable strengths including a large, well-characterized population cohort from an economically disadvantaged area. This provides a unique and important sample in which to address these associations. In addition, the use of device-based measurement of sedentary behavior adds rigor to the measurement of these constructs. Finally, the use of a comprehensive neuropsychological protocol allows for more specificity in examining how sedentary behavior relates to each domain of cognition, which provides information that global cognitive screenings would not be able to account for.

However, this study does have some limitations including limited racial/ethnic diversity and participants with mostly normal cognitive status across the sample, although this sample is more educationally and economically diverse than typical convenience or clinic-based samples. Furthermore, some evidence suggests that not all types of sedentary behavior are equal (e.g., watching TV versus reading, playing games),^48,49 and we were unable to account for what participants were doing while sedentary in this study. The cut points for activity levels in this study may vary from the cut-offs other studies use, which is important to consider. In addition, this study was cross-sectional, and further longitudinal cognitive follow-up of this cohort will allow us to ascertain directionality of effects. Nevertheless, this study makes an important contribution to our understanding of how sedentary behavior may relate to cognitive decline in older adults.

In conclusion, we found that greater sedentary time was related to worse executive function and memory performance in a sample of older adults from an economically disadvantaged area. This study has important public health implications. From a public health perspective, it might be important to consider messaging and interventions that target prolonged sedentary time and their precedents (e.g., mobility issues, frailty, depression, obesity, lack of walkability in neighborhood)⁵⁰ to promote cognitive health and AD prevention in a community setting. In addition, clinicians who work with older adults in the community might also consider assessing sedentary time (in addition to type, intensity, and duration of physical activity engaged in) when evaluating risk factors for AD. This study adds to the growing body of literature linking sedentary behavior to adverse health outcomes in aging.

Supplemental Material

sj-docx-1-alz-10.1177_13872877251410964 - Supplemental material for The associations between sedentary behavior and cognition in a population cohort of older adults

Supplemental material, sj-docx-1-alz-10.1177_13872877251410964 for The associations between sedentary behavior and cognition in a population cohort of older adults by Marissa A Gogniat, Yueting Wang, Chung-Chou H Chang, Joseph Storey, Erin Jacobsen, Isabella Wood, Amy Carper, M Ilyas Kamboh, Ann D Cohen, Mary Ganguli and Beth Snitz in Journal of Alzheimer's Disease

Footnotes

Acknowledgements

The authors would like to thank the staff and participants of MYHAT for their time and dedication to this research.

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The associations between sedentary behavior and cognition in a population cohort of older adults

Abstract

Background

Objective

Methods

Results

Conclusions

Keywords

Introduction

Methods

Study cohort

Accelerometry

Neuropsychological assessment and cognitive status

APOE4 genotyping

Analyses

Results

Participant characteristics

Sedentary behavior and cognition

APOE4 × sedentary behavior on cognition

Discussion

Supplemental Material

sj-docx-1-alz-10.1177_13872877251410964 - Supplemental material for The associations between sedentary behavior and cognition in a population cohort of older adults

Footnotes

Acknowledgements

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