Keywords

Physical activity; Exercise; Cognitive decline; Cognitive function; Middle-aged

Introduction

As individuals age, neurodegenerative diseases become more extensive, which may lead to cognitive decline, which results in complex issues for individuals, families, and the healthcare system. Increasing age is known to be associated with cognitive decline through decreased neurotrophic factor expression and neurogenesis in the brain [1]. Substance use and current health status may also affect cognition over time [1-4].

For example, tobacco and alcohol use negatively impact many aspects of health, including brain function, which could contribute to cognitive decline and lower levels of cognitive function [3,5]. In addition, stress can counteract neuroprctive influences, leading greater risk for cognitive decline [1,4], and excess sleep could be a symptom of certain disorders, such as depression, that are associated with increased cognitive decline [6].

Indeed, lower levels of depressive symptoms are associated with greater neuroprotective effects [1], and the absence of diabetes, stroke, or heart attack tend to be associated with greater mental functioning in older adults [6].Aside from age, inactivity is identified as the predominant risk factor for many disease processes [1], which include physical, as well as cognitive and neurologic decline. Deficits in cognitive and neurologic function could potentially be prevented or slowed with health promotion and physical activity [4].

Many studies have shown that those who are physically active experience lower rates of cognitive decline [2,7,8]. IGF-1, a factor associated with neurogenesis, presents with diminished levels in elderly with poor cognitive performance. Exercise is known to accelerate cognitive function and increase IGF-1 levels, which can subsequently improve cognitive performance. Exercise also increases VEGF, which is known to be neurogenic and neuroprotective [1]. Both increased leisure-time activity and vigorous physical activity may help reduce the risk of cognitive decline in postmenopausal females [2,3].

While there is strong evidence supporting the beneficial effects of physical activity on cognition [1,4], there are limited findings for females ages 55 to 64 [9] and in postmenopausal women [2].

There are also inconsistent findings addressing the type and intensity of physical activity that would be most beneficial for cognitive decline [3,4,6,9]. This study aims to assess the relationship between varying levels of physical activity and cognitive decline for females ages 55 to 64.

Methods

Design

This cross-sectional analysis used 2015 data from the Behavioral Risk Factor Surveillance System (BRFSS) conducted by the Centers for Disease Control and Prevention (CDC) regarding health-related risk behaviors, chronic health conditions, and use of preventive services [10]. BRFSS collects data in all 50 states as well as the District of Columbia and three U.S. territories, and completes more than 400,000 interviews annually. This study was given exempt status by The University of North Texas Health Science Center.

Sample

The population included females ages 55 to 64 in Connecticut (N=1623), Montana (N=829), and Oregon (N=638). These states were chosen for their higher proportions of active females in the target age range based on prevalence data available through BRFSS [10].

Data

The outcome, cognitive decline, was measured as yes/no to having “serious difficulty concentrating, remembering, or making decisions.” The factor of interest, physical activity levels, was measured in BRFSS with questions asking about weekly physical activities and time spent in activities.

Based on weekly minutes of moderate activity (or vigorous equivalent), BRFSS categories for levels of physical activity include the following: “inactive,” defined as 0 minutes/week; “insufficiently active,” defined as 11 to 149 minutes/week; “active,” defined as 150 to 300 minutes/week; and “highly active,” defined as greater than 300 minutes/week. Control variables included health and demographic factors.

Number of health conditions was measured as the number of lifetime diagnoses of any of the following: hypertension, hyperlipidemia, myocardial infarction, coronary heart disease, stroke, skin cancer, cancer, chronic obstructive pulmonary disease (COPD), arthritis, depression, renal disease, diabetes, and asthma. Numerical results were categorized as 0, 1, 2, or 3 or more. Due low percentages in categories across states, health conditions was dichotomized as “0-2 health conditions” versus “3 or more health conditions” for adjusted analyses. Mental health was measured quantitatively as number of days of poor mental health attributed to “stress, depression, or problems with emotions” in the past 30 days. Due to severe skew across all states, this variable was then dichotomized at the mode in all states (mode=30) as “30 days of good mental health in the past 30 days” versus “less than 30 days of good mental health in the past 30 days.” Tobacco use was categorized as “current smoker” versus “non-smoker.” Alcohol use was measured as yes/no to any alcohol consumption in the past 30 days.

Due to small percentages in various categories across states, race/ethnicity was categorized as “White, non-Hispanic” versus “Other.” Education level was measured as “graduated college or technical school” versus “did not graduate college or technical school.” Marital status was categorized as “married” versus “not married.” Variable categories and descriptive statistics by state are shown in Table 1.

Table 1: Descriptive statistics by state.

Analysis

Frequency distributions by state were used to describe the sample and determine any issues with the distribution of variables. Multiple logistic regression analysis by state was used to assess the relationship between cognitive decline and levels of physical activity after controlling for health and demographic factors. We chose to analyze data separately by state to assess patterns in relations among variables across similar samples. As such, a similar result in two or three (out of three states) was considered reliable evidence for a relationship.

Any observations with missing data for any of the variables were excluded from the multivariable analysis. Adjusted results by state are shown in Table 2. All analyses were conducted in R (version 3.3.3, © 2017 The R Foundation for Statistical Computing).

Table 2: Results of logistic regression analysis by state, ref =referent group; AOR= adjusted odds ratio; 95% CI= 95% confidence interval; Bolded results are significant (AORs with 95% CI that do NOT include 1.0 are significant).

Results

Descriptive statistics

Table 1 lists descriptive statistics for females age 55-64 in Connecticut, Montana, and Oregon. Across states, few participants reported cognitive decline (10-14%), and only onefifth reported being inactive (18-29%), while twice as many reported being highly active (34-48%).

For current health status, about one-third of participants reported having three or more health conditions (33-42%) and the majority reported 30 days of good mental health in the past 30 days (57-66%).

For substance use, most participants were nonsmokers (81-87%) and about half reported consuming alcohol in the past 30 days (50-59%). For demographic factors, most participants reported their ethnicity/race as White (80-90%); almost half reported graduating college or technical school (38-48%); and the majorities were married (53-61%).

Adjusted statistics

The results of multiple logistic regression analysis by state for females ages 55 to 64 showed that after controlling for all other variables in the model, cognitive decline was not significantly related to levels of physical activity in any of the three states. However, cognitive decline was highly related to health conditions and mental health in all three states.

Across states, participants that reported 3 or more health conditions were about 4 to 5.5 times more likely to report cognitive decline, while those who reported having 30 days of good mental health in the past 30 days were about 7 to 11 times less likely to report cognitive decline. In addition, cognitive decline was related to substance use in two of three states. Those who reported consuming alcohol in the past 30 days were about 2 to 3 times less likely to report cognitive decline, while current smokers were about 3 to 3.5 times more likely to report cognitive decline.

Discussion

The purpose of this study was to assess the relationship between physical activity levels and cognitive decline in female ages 55 to 64. Across states, few participants reported cognitive decline (10-14%), and only one-fifth reported being inactive (18-29%), while twice as many reported being highly active (34-48%). The results of adjusted analysis indicated that there were no significant patterns in relations between physical activity and cognitive decline in any of the three states. These findings differed from previous research that showed physical activity to be a neuroprotective factor [1-4,7-9].

This discrepancy could be due to differences in measures or target populations. Prior research examined the effects of physical activity on cognitive functioning using cognitive assessments [1,4,6,9,11], whereas this study defined cognitive decline as self-reported “difficulty concentrating, remembering, or making decisions.”

In addition, this study examined females ages 55 to 64, whereas most previous research focused on the elderly [1,6-8,12]. The variables in this study were concurrent levels of cognitive decline and physical activity levels at one point in time; therefore, benefits of physical activity for cognitive decline may not be immediate.

The results of this study do, however, show that cognitive decline was consistently and moderately to highly rated to number of health conditions, mental health, and substance use in females ages 55 to 64. In this study, participants who reported having three or more conditions were more likely to report cognitive decline.Although prior research only examined the type of health condition as opposed to number of chronic conditions, the finding of cognitive decline being associated with chronic health conditions is consistent [1,3]. In addition, the results of this study indicated that women in the target population who reported good mental health were less likely to report cognitive decline, which is supported by prior research [1,6,12].

Interestingly for substance use, those who reported smoking were more likely to report cognitive decline, whereas those who reported alcohol consumption were less likely to report cognitive decline. The former finding for tobacco use is consistent with previous research, whereas the latter finding for alcohol use is not [2]. However, the variable for alcohol in this study simply measured any alcohol use in the past 30 days.

Limitations

Using 2015 data from the Behavioral Risk Factor Surveillance System (BRFSS) provided access to large sample sizes. However, the data is cross-sectional in nature so the results can only address concurrent relations and no temporal or casual relations can be determined from it.

In addition, the BRFSS data did not include certain variables that may be relevant to cognitive decline in this target population, including sleep [5] and onset of menopause and presence of Hormone Replacement Therapy (HRT) [4,11].

Because sleep and hormones may regulate the effect of physical activity on neurogenesis and, thus, on cognitive performance, future studies should include these variables as the findings related to them would be important in patient education and treatment.

Furthermore, the relationship between having multiple chronic health conditions and cognitive decline in this study could be related to participant medication use. Research shows that middle and older age adults tend to take multiple medications and many may take medications, such those with anticholinergic properties, that have adverse effects on cognitive functioning [13]. However, there was no data available for medication use in this study.

Conclusion

Because this was a population-based study, the findings may apply to females between the ages of 55 and 64 in primary care. For this target population, there may be a low prevalence of cognitive decline and moderate prevalence of physical activity. Although cognitive decline was not related to physical activity levels in this target population, providers should screen for cognitive decline in this target population when patients present with complaints or early signs of decreased cognitive functioning, and continue to educate patients on the benefits of physical activity, noting that any benefits may not be immediate for cognitive decline.

However, cognitive decline was consistently and moderately to highly related to number of health conditions, mental health status, and tobacco use. As such, females ages 55 to 64 presenting with cognitive decline symptoms should be screened for multiple health conditions, current mental health status, and tobacco use, and vice versa.

Providers should determine appropriate referrals for declining cognitive function; determine how well patients with multiple health conditions are managing them and help with management strategies; educate patients about the signs and symptoms of mental distress and provide resources for addressing mental health issues; and educate patients who smoke about the risks of tobacco use and encourage them to quit. Most importantly, primary care providers should concurrently monitor all comorbid conditions, including treatment regimens, compliance, and adverse medication side effects on cognitive functioning, to increase health outcomes for females ages 55 to 64.

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