Medium-to-High Late-Life Physical Activity Is Associated with Lower Risk of Incident Dementia: The Shanghai Aging Study

Abstract

Background:

There is significant evidence that physical activity has profound effects on the neurochemistry and plasticity of the brain and may prevent cognitive decline.

Objective:

This study aimed to determine the association between physical activity and incident dementia among older Chinese adults.

Methods:

In the prospective phase of the Shanghai Aging Study, 1,648 community-dwellers aged 60 years or older were followed for an average of 5 years. Their physical activity was assessed based on questionnaires. The physical activities were further transformed into metabolic equivalent values. A consensus diagnosis of incident dementia was ascertained based on medical, neurological, and neuropsychological data and the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition.

Results:

We identified 166 incident dementia cases; the incidence rate was 19.4 per 1000 person-years. A multivariate Cox regression model indicated that compared to low levels of physical activity, medium-to-high levels of physical activity were associated with a reduced risk of dementia (hazard ratio, 95% confidence interval = 0.62, 0.44–0.89) after adjusting for age, sex, years of education, apolipoprotein E ɛ4, and other confounders.

Conclusion:

Our findings demonstrate that medium-to-high level of physical activity is protective against dementia in older adults.

Keywords

Chinese cognition cohort studies dementia incidence physical activity

INTRODUCTION

The number of people living with dementia worldwide in 2015 was estimated at 47 million and is set to increase to 75 million and 135 million in 2030 and 2050, respectively [1]. China is aging much faster than other low- and medium-income countries. With a reported national dementia prevalence of 6%, there are an estimated 7.4 million people currently living with dementia in China [2, 3]. Due to the absence of effective treatments, it is important to identify potentially modifiable risk factors to delay the onset or reduce the risk of developing dementia.

There is substantial evidence that physical activity has profound effects on the neurochemistry and plasticity of the brain and may prevent cognitive decline [4 –7]. Epidemiological evidence involved quite a few observational studies [8 –21]. Consistent results were found in studies with relatively short follow-up periods, suggesting a protective effect of physical activity for cognitive decline and dementia [8–12 , 21]. However, studies with long-term follow-up periods reported inconsistent conclusions [10 , 19]. Possible reasons for this difference may be different target populations, study designs, sample sizes, measurements, types of physical activity, and end points or outcomes (e.g., dementia types or neuro-psychological assessments). Regardless, physical activity is known to have an inverse association with cardiovascular disease, hypertension, diabetes, and obesity, each contributing to cognitive impairment [8 , 23]. The current study aimed to determine the association between physical activity and incident dementia among older Chinese adults through the prospective phase of the Shanghai Aging Study.

METHODS

Study design and participants

Between 2010 and 2011, permanent residents aged 60 years or older who were willing to participate were consecutively enrolled based on a government-maintained residents list of the Jingansi community in central Shanghai. A clinical interview appointment (either at Huashan Hospital or at the participants’ homes) was made. Participants were excluded if they were deceased; had severe mental retardation or schizophrenia on their medical record; and/or were visually, hearing, or verbally impaired and were not capable of accomplishing the neuropsychological evaluation. A detailed description of the design and procedure of the Shanghai Aging Study has been previously published elsewhere [3].

This study was approved by the Medical Ethics Committee of Huashan Hospital, Fudan University, Shanghai, China. Written informed consent was obtained from all participants and/or their legal guardians.

Characteristics and apolipoprotein E genotype

At baseline, the demographic characteristics of the participants were collected via an interviewer-administered questionnaire, including age, sex, years of formal education, cigarette smoking status, and alcohol consumption. Cigarette smoking status was defined if the participant had smoked daily within the past month. Alcohol consumption was defined if the participant had at least one serving of alcohol weekly during the past year [24]. Medical histories, such as hypertension and diabetes (type II), were recorded and further confirmed based on the participants’ medical records. Height and weight were measured by research nurses. Their body mass index (BMI) was then calculated as weight in kilograms (kg) divided by height in meters (m) squared. Obesity was defined as BMI ≥27.5 kg/m² based on the World Health Organization (WHO)’s definition for Asian populations [25].

The apolipoprotein E (APOE) ɛ4 allele is recognized as major genetic risk factor for sporadic late-onset Alzheimer’s disease. DNA was extracted from the blood or saliva samples of each participant to conduct APOE genotyping using the Taqman SNP method [26]. The presence of at least one ɛ4 allele designated the participant as APOE ɛ4 positive.

Measurement of physical activity

At baseline, the participants were asked about the average time (daily or weekly) that they spent doing physical activities, such as walking or bicycling (Supplementary Table 1), during the past 12 months. Since most of the participants in our cohort have retired, current measurement represented the participants’ total physical activity. We assigned each activity a metabolic equivalent value (MET) based on the compendium of physical activities [27]. This was then multiplied by the reported time (hours/week) spent performing the activity resulting in the amount of physical activity per week (METs/week). One MET is defined as 1 kcal/kg/hour and is roughly equivalent to the energy cost of sitting quietly [27]. We categorized physical activity into two levels based on the tertile of the METs distribution: low level (approximately a third of the population): <10.5 METs/week; and medium-to-high level (approximately two-thirds of the population): ≥10.5 METs/week.

Neurological and neuropsychological assessments and diagnosis

At baseline, neurologists examined each participant’s motor responses and reflexes. Each participant was administered a battery of neuropsychological tests for global cognition, executive function, spatial construction function, memory, language, and attention. The battery contained the following: 1) the Mini-Mental State Examination [28]; 2) the Conflicting Instructions Task (Go/No Go Task) [29]; 3) the Stick Test [30]; 4) the Modified Common Objects Sorting Test [30]; 5) the Auditory Verbal Learning Test [31]; 6) the Modified Fuld Object Memory Evaluation [32]; 7) the Trail-making tests A and B [33]; and 8) the RMB (Chinese currency) test [34]. Participants with <6 years of education were given tests 1 to 4, 6, and 8. Participants with ≥6 years of education were given tests 1 to 5 and 7. Normative data and more details of these tests were reported elsewhere [35]. All tests were conducted in Chinese by study psychometrists within 90 minutes. Neurologists also administered the Clinical Dementia Rating (CDR) [36] and the Lawton and Brody Activity of Daily Living (ADL) [37] to elicit memory complaints and the ability to perform activities of daily living.

A panel of neurologists, neuropsychologists, and research coordinators reviewed the examinations for each participant at baseline and reached a consensus diagnosis for dementia using the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) [38]. Detailed diagnostic procedures have been reported elsewhere [3].

Follow-up procedure

From April 1, 2014 to December 31, 2016, dementia-free participants with valid physical activity measurements at baseline were scheduled to follow-up. Research coordinators contacted participants using their contact information provided at the beginning of the study. Cognitive functioning was evaluated again, using the same neuropsychological battery that was previously used. A consensus diagnosis of incident dementia was concluded by the same panel of experts, using the same diagnostic criteria as at baseline.

Statistical analysis

The mean with the standard deviation (SD) or median (Q1, Q3) and numbers with frequencies (%) were used to describe continuous and categorical variables, respectively. The student-test was used to analyze the differences between continuous variables. The Pearson’s chi-squared test was used to analyze the differences between categorical variables. For individuals with incident dementia, the timeframe for follow-up was defined as the difference between the date of diagnosis and the date of the baseline assessment, when physical activity was measured. For those who did not develop dementia, the follow-up time was defined as the difference between the date of the follow-up interview and the date of the baseline assessment, when physical activity was measured. The incidence of dementia was calculated as the number of new-onset cases divided by the cumulative person-years of follow-up. The cumulative incidence of dementia was estimated with the Kaplan-Meier product-limit method and compared using the log-rank test. Cox proportional hazards models were used to estimate the adjusted hazard ratios (HRs) with 95% confidence intervals (CIs) for the MET categories with incident dementia. Model 1 adjusted for age, sex, years of education, and APOE ɛ4. Model 2 further adjusted for cigarette smoking status, alcohol consumption, hypertension, diabetes, and BMI. Subgroup analysis was conducted using model 1.

The p values and 95% CIs were calculated using two-tailed methods and differences were statistically significant at p < 0.05. Data were analyzed using SAS 9.4 (SAS Institute Inc., Cary, NC, USA).

RESULTS

We successfully followed up with 1648 participants; their baseline characteristics are shown in Table 1. The participants’ mean age was 71 years old and most of them received higher education. Half of the participants had hypertension and the prevalence of other chronic diseases was approximately 10%. Participants with ≥10.5 METs/week were younger (p < 0.001), more likely to be male (p < 0.001), had a lower prevalence of hypertension (p = 0.038), had a better baseline MMSE (p < 0.001), and had a better follow-up MMSE (p < 0.001). During a median 5.3-year follow-up, 166 cases of incident dementia were identified, with an incidence rate of 19.4 per 1000 person-years (95% CI: 16.4–22.3). The incidence rates for participants with <10.5 METs/week and ≥10.5 METs/week were 30.0 (95% CI: 24.0–35.9) and 12.8 (95% CI: 9.8–15.9) per 1000 person-years, respectively (Table 1). As shown in Fig. 1, there were later-onset and less dementia cases in participants with ≥10.5 METs/week (log-rank p < 0.001).

Table 1

Baseline characteristics and cognition at follow-up of study participants

		Physical activity
	Total (n = 1648)	Low <10.5 METs/week (n = 641)	Medium-to-high ≥10.5 METs/week (n = 1007)	p ^*
Baseline
METs/week, median (Q1,Q3)	21.0 (9.8, 34.9)	6.5 (0.0, 10.0)	31.5 (21.0, 44.8)
Age, y, mean±SD	71.5±7.4	73.3±7.8	70.3±6.9	<0.001
Male, n (%)	750 (45.5)	234 (36.5)	516 (51.2)	<0.001
Education, y, mean±SD	11.9±4.0	11.7±4.1	12.0±4.0	0.101
APOEɛ4+, n (%)	257 (16.7)	106 (18.4)	151 (15.6)	0.162
Cigarette smoking status, n (%)	169 (10.3)	67 (10.5)	102 (10.1)	0.833
Alcohol consumption, n (%)	149 (9.0)	42 (6.6)	107 (10.6)	0.005
Body mass index, mean±SD	24.6±3.5	24.6±3.6	24.6±3.4	0.804
Hypertension, n (%)	891 (54.1)	367 (57.3)	524 (52.0)	0.038
Diabetes, n (%)	221 (13.4)	90 (14.0)	131 (13.0)	0.549
MMSE, mean±SD	28.2±2.1	27.9±2.2	28.3±1.9	<0.001
Follow-up
MMSE, mean±SD	26.6±4.2	25.9±4.8	27.1±3.7	<0.001
Incident dementia, n (%)	166 (10.1)	98 (15.3)	68 (6.8)	<0.001
Dementia incidence, 1000 person-years (95% CI)	19.4 (16.4, 22.3)	30.0 (24.0, 35.9)	12.8 (9.8, 15.9)	<0.001

MET, metabolic equivalent value; Q1 and Q3, first quartile and third quartile; SD, standard deviation; APOE, apolipoprotein E; MMSE, Mini-Mental State Examination. ^*Comparison between groups with low and medium-to-high level of physical activity.

Fig.1

Cumulative incidence of dementia by METs categories during follow-up.

In the Cox regression model 1, participants with ≥10.5 METs/week were inversely associated with the likelihood of being diagnosed with dementia during the follow-up (HR = 0.60, 95% CI 0.42–0.85). After adjustment for further confounders, HR remained at 0.62 (95% CI: 0.44–0.89), compared to participants with <10.5 METs/week (Table 2). As shown in the subgroup analysis, participating in ≥10.5 METs/week was associated with a lower risk for dementia in: females (HR 0.59, 95% CI 0.37–0.95), individuals ≥71 years (HR 0.60, 95% CI 0.41–0.87), those who are APOE ɛ4 negative (HR 0.53, 95% CI 0.36–0.79), individuals who do not smoke cigarettes (HR 0.56, 95% CI 0.38–0.82) or consume alcohol (HR 0.62, 95% CI 0.43–0.89), those with hypertension (HR 0.53, 95% CI 0.34–0.81), and those without diabetes (HR 0.65, 95% CI 0.44–0.96) or obesity (HR 0.52, 95% CI 0.35–0.78) (Fig. 2).

Fig.2

Subgroup analysis for the association between physical activity and incident dementia. Diamonds indicate point estimates of hazard ratios, and bars indicate 95% confidence intervals. Hazard ratios (95% confidence intervals) were adjusted for age, sex, years of education, and APOE ɛ4.

Table 2

Adjusted hazard ratios of incident dementia by METs categories in different Cox regression models

	Model 1^*		Model 2^†
Physical activity	HR (95% CI)	p	HR (95% CI)	p
Low
<10.5 METs/week	1.00		1.00
Medium-to-high
≥10.5 METs/week	0.60	0.004	0.62	0.009
	(0.42–0.85)		(0.44–0.89)

HR, hazard ratio; CI, confidence interval; MET, metabolic equivalent value. ^*Adjusted for age, sex, years of education, and APOE ɛ4. ^†Adjusted for age, sex, years of education, APOE ɛ4, cigarette smoking status, alcohol consumption, hypertension, diabetes, and body mass index.

DISCUSSION

Our study confirmed that in older Chinese adults, a medium-to-high level of physical activity was associated with a lower risk for incident dementia. After adjusting for potential confounders, the association remained significant. This effect was shown in several subgroups.

Although several longitudinal population surveys had been designed to examine the effect of physical activity on dementia among the Chinese population, their results were not convincing due to small sample sizes [39], short follow-up periods [20, 40], or unreliable assessments of cognitive performance [41]. There are several strengths in the current study. We assigned each physical activity with a MET value based on the compendium of physical activities, which enhanced the quantification and objectiveness of the physical activities. A consensus diagnosis of dementia was given by a panel of experts based on clinical, neuropsychological, and neurological assessments for every participant, both at baseline and follow-up. This was to obtain accurate information on the endpoint of dementia and to avoid under-reporting any incident dementia cases in the cohort.

Our results are consistent with most previous studies [8–12 , 18–21]. As for studies with long-term follow-up periods, the Cardiovascular Risk Factors, Aging and Dementia Study; the Hisayama Study; and the AGES—Reykjavik Study suggested that physical activity could reduce the long-term risk of dementia and Alzheimer’s disease [13–15 , 19]. Yet, in the Rotterdam Study, the inverse association between physical activity and dementia was confined to a follow-up period of up to 4 years [10]. The Whitehall II Cohort Study, however, failed to observe the inverse relationship between physical activity and the risk for dementia and cognitive decline [16]. Possible explanations for inconsistent findings might consider different measurements of physical activity (leisure-time physical activity versus total physical activity), periods of when the physical activity occurs in life (mid-life versus late-life), and types of physical activity (aerobic and mind-body versus stretching and toning exercises).

Over the past two decades, both animal and human studies have shown the capacity of exercise to benefit cognitive function [42]. Exercise improves memory and cognition [43, 44], facilitates functional recovery following brain injury [45], and counteracts the mental decline associated with aging [46]. Individuals with a more engaged and active lifestyle can endure more neuropathological changes (e.g., neurofibrillary tangles and senile plaques) before they suffer from the clinical symptoms of dementia [47]. Furthermore, physical activity is known to have an inverse association with cardiovascular disease, hypertension, diabetes, and obesity, each contributing to cognitive impairment [8 , 23]. These diseases may act as intermediate factors between physical activity and dementia. In addition, physical activity may be a surrogate for overall social activity and an active lifestyle, which are related to cognitive benefits and longer life expectancy [14].

The primary limitation of the current study, as well as most of previous studies, is the assessment of physical activity via questionnaire, which could induce recall bias. Second, the follow-up period in the current study was not long enough to generate any long-term results. The deterioration of one’s ability to engage in physical activity could be part of the pre-diagnostic phase of dementia. A longer follow-up period can provide a solution for such reverse causality. The relatively short follow-up time and the small number of incident dementia cases made this study underpowered in the association analysis for separate groups with medium-to-high levels of physical activity. Lastly, our findings may not be able to be extrapolated to the general population since the participants in our cohort were recruited from urban Shanghai, with better living conditions and lifestyles than other areas. However, in this way our findings are comparable to the results from western studies with participants who had similar characteristics.

CONCLUSION

Our findings demonstrate that medium-to-high level of physical activity is protective against dementia in older adults. Further studies are required to specify which types of physical activities are most beneficial and when, during a person’s lifespan, it should occur to maximize any potential protective effects.

Footnotes

ACKNOWLEDGMENTS

This work was supported by grants from Scientific Research Plan Project of Shanghai Science and Technology Committee [17411950701, 17411950106], National Natural Science Foundation of China [81773513], Shanghai Municipal Science and Technology Major Project (No. 2018SHZDZX01), ZHANGJIANG LAB, Tianqiao and Chrissy Chen Institute, and the State Key Laboratory of Neurobiology and Frontiers Center for Brain Science of Ministry of Education, Fudan University.

Authors’ disclosures available online ().

The supplementary material is available in the electronic version of this article: .

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