Abstract
Background
Low gait speed has been linked with impaired mood, cognition, and quality of life (QOL) in older adults. We examined whether low gait speed was associated with impaired mood, cognition, and QOL among older adults with atrial fibrillation (AF).
Methods and Results
Participants (n=1185) had a diagnosis of AF, aged ≥65 years, CHA 2 DS 2 VASc ≥2 and had no contraindications to anticoagulation. Participants completed a 15‐foot walk test, and low gait speed was categorized using cutoffs from the Fried Frailty Index. Participants self‐reported measures of depressive symptoms (Patient Health Questionnaire 9 ≥10), anxiety symptoms (Generalized Anxiety Disorder 7 ≥10), cognitive impairment (Montreal Cognitive Assessment ≤23), and potentially impaired Atrial Fibrillation Effect Quality‐of‐Life Questionnaire <80. Participants were on average aged 75.3 (SD: 7.0) years, 48.0% were women, and 85.5% were non‐Hispanic white; 85.6% were taking an oral anticoagulant, 26.1% had low gait speed, 8.4% had elevated depressive symptoms, 5.7% had elevated anxiety symptoms, 41.1% were cognitively impaired, and 41.6% had potentially impaired AF‐related QOL. Participants with low gait speed were significantly more likely to have elevated depressive symptoms (adjusted odds ratio: 2.1, 95% CI: 1.3–3.4), elevated anxiety symptoms (adjusted odds ratio: 2.2, 95% CI: 1.2–3.9), and cognitive impairment (adjusted odds ratio: 1.5, 95% CI: 1.1–2.1). Impaired AF‐related QOL did not differ by gait speed after adjustment for clinical characteristics (adjusted odds ratio: 1.1, 95% CI: 0.8–1.5).
Conclusions
Twenty‐six percent of older adults with AF had low gait speed, and low gait speed was associated with impaired mood and cognition. Further research is needed to determine whether declines in gait speed lead to impaired mood and cognition or whether these conditions develop concurrently.
Keywords: anxiety, atrial fibrillation, cognition, depression, quality of life
Subject Categories: Atrial Fibrillation, Epidemiology, Quality and Outcomes
Clinical Perspective
What Is New?
We found that 26% of older adults with atrial fibrillation had low gait speed.
Low gait speed was associated with elevated symptoms of depression and anxiety and cognitive impairment.
What Are the Clinical Implications?
Older adults with atrial fibrillation who are identified as having low gait speed may benefit from screening for depression, anxiety, or cognitive impairment and referrals for mental health care.
Introduction
Atrial fibrillation is the most common sustained arrhythmia in older adults and is associated with an increased risk of stroke. Adults with atrial fibrillation have been found to have lower quality of life and cardiac performance and higher rates of cardiac comorbidities such as coronary disease, heart failure, and hypertension.1, 2 Frailty is common among older adults, and gait speed is one of its predominant components.3, 4, 5 Atrial fibrillation relates to reduced exercise capacity, cardiac output, frailty, cognition, and vascular function, all of which may contribute to an observed decrease in gait speed.6
Gait speed has been used to predict factors such as depression, anxiety, cognition, and quality of life, which relate to the functional status of older adults.7, 8, 9, 10 Gait speed has been studied in community‐dwelling older adults,7, 10 patients undergoing cardiac surgery,11 and in patients with chronic stroke, incomplete spinal cord injury, hip fracture, multiple sclerosis, Parkinson disease, Huntington disease, Alzheimer disease, and dementia.12 Gait speed is commonly measured from a walk test, and although there are many published walk test procedures, the processes are generally simple to administer and require only a timer and flat surface.10, 12 Walk test protocols include either time (eg, 6 minutes) or distance (eg, 4–10 m)10, 12; the Fried Frailty Index includes a 15‐foot walk test.3 Published cutoffs for low versus normal gait speed are also variable, but the most commonly used cutoffs are between 0.8 and 1 m/s, where gait speeds below this range are considered low gait speed.13, 14 Using gait speed as an easy and accurate diagnostic tool could have meaningful clinical implications.4
Patients experiencing depression or sadness have significantly lower gait speeds than those without mood disorders,15 and this relationship has also been observed in older adults.16 Gait speed also relates to general anxiety, balance‐, and fall‐related anxiety in older adults.9, 17 Similarly, those with low gait speed (eg, <0.83 m/s,11 <1.0 m/s7) are more likely to have morbidity and adverse clinical outcomes.
While low gait speed has been linked with mood, cognitive impairment, and quality of life in community‐dwelling older adults and older adults undergoing cardiac surgery, little is known about the relationship between low gait speed and these outcomes in older adults with atrial fibrillation, an important question given that low gait speed is common in this population.6, 7, 9, 11, 15, 16, 17 In this study, we examined the association between low gait speed and elevated depressive symptoms, elevated symptoms of anxiety, cognition, and atrial fibrillation‐related quality of life in a cohort of older adults with atrial fibrillation. We hypothesized that patients with low gait speed will be more likely to have elevated depressive symptoms, elevated symptoms of anxiety, and more cognitive impairment, and have lower atrial fibrillation quality of life as compared with patients with gait speeds in the normal range.
Methods
Study Design, Participants, and Data Collection
The data that support the findings of this study are available from SAGE‐AF (Systematic Assessment of Geriatric Elements in Atrial Fibrillation) study principal investigators upon reasonable request (david.mcmanus@umassmemorial.org and j.saczynski@northeastern.edu).
Data for the current study are from the SAGE‐AF study, an ongoing prospective cohort study of older adults >65 years with atrial fibrillation (AF). SAGE‐AF enrolled a cohort of 1244 older adults with atrial fibrillation that received care at a clinical site in Central Massachusetts (University of Massachusetts Memorial Health Care [UMMHC] internal medicine, UMMHC cardiology, UMMHC electrophysiology, or Heart Rhythm Associates of Central MA), Eastern Massachusetts (Boston University cardiology), or Central Georgia (Family Health Center or Georgia Arrhythmia Consultants). Potential participants were screened before their upcoming clinic visit, and eligible participants received an invitation to participate 1 week before this appointment. Eligibility criteria for SAGE‐AF included having a scheduled ambulatory care visit at 1 of the study practices; having AF (participants were considered to have a history of AF if the arrhythmia was present on an ECG or Holter monitor or if AF was noted in any clinic note or hospital record); being aged ≥65 years; having a CHA2DS2VASC risk score ≥2. Participants were not eligible for enrollment if they had documentation of an absolute contraindication to oral anticoagulants (ie, large esophageal varices, recent major surgery within the past 72 hours, recent major bleeding in the past 3 months, arteriovenous malformation or aneurysm, planned invasive procedure with high risk for uncontrollable bleeding [eg, open surgical procedure], decompensated liver disease, significant thrombocytopenia [ie, platelet count <50k], or documented hypersensitivity/allergic reaction to oral anticoagulation); had an indication for oral anticoagulants other than AF (ie, mechanical heart valve in the mitral position); did not demonstrate capacity to provide informed consent as assessed by a capacity instrument that combines direct questions about their understanding of study participation with interviewer observations of the patient18; did not speak English; had a planned invasive procedure with high risk for uncontrollable bleeding; were pregnant; were prisoners; were unwilling or unable to participate in planned 1‐ and 2‐year follow‐up visits at their study sites. Data were collected through a comprehensive baseline geriatric assessment, structured interview, and abstraction of electronic medical records. All participants provided written informed consent. SAGE‐AF was approved by the Institutional Review Boards at each study site.
At baseline, participants completed a 60‐minute in‐person assessment visit that included physical examination and a survey completed via paper or iPad. Trained research staff abstracted clinical, demographic, treatment, and laboratory characteristics from participants’ electronic medical records.
Assessment of Gait Speed
At baseline, participants completed a self‐paced 15‐foot walk test following the procedures of the Fried Frailty Index3 as part of the comprehensive assessment of geriatric elements. Staff instructed participants to stop at the beginning of a hallway located in an indoor, private research center, and the hallway was marked to indicate where participants should start and stop the 15‐foot walk. Study staff were available throughout the test to provide balance or gait support as needed. Staff timed the walk test and calculated gait speed. Gait speed was dichotomized (low versus normal) according to cutoffs for low gait speed in the Fried Frailty Index.3 This score stratifies walk time by sex and height, such that men with a height ≤173 cm had low gait speed if their time to walk 15 feet (walk time) was ≥7 seconds, men with a height >173 cm had low gait speed if their walk time was ≥6 seconds, women with a height ≤159 cm had low gait speed if their walk time was ≥7 seconds, and women with a height >159 cm had low gait speed if their walk time was ≥6 seconds.3 These cutoffs are equivalent to paces of 0.76 m/s (6 seconds) and 0.65 m/s (7 seconds). We conducted a sensitivity analysis in which we categorized low gait speed as a walking pace of <0.83 m/s for all participants, an alternative cutoff for slow gait speed also commonly used in the literature.14
Outcome Measures
As part of the baseline interview, participants completed measures of depressive symptoms, symptoms of anxiety, cognitive impairment, and atrial fibrillation quality of life. Depressive symptoms were assessed using the Patient Health Questionnaire‐9. This 9‐item questionnaire asks participants to self‐report the frequency with which they have experienced depressive symptoms over the past 2 weeks. Response options for this questionnaire include “not at all,” “several days,” “more than half the days,” or “nearly every day.” Symptoms of depression were calculated from the sum of responses, with a potential range of 0 to 27 (higher scores indicate more severe depressive symptoms).19 We used a cutoff of ≥10 to indicate moderate/severe depression.19
Symptoms of anxiety were assessed using the Generalized Anxiety Disorder‐7 Scale. This 7‐item scale asks participants to self‐report the frequency with which they have experienced symptoms of anxiety over the past 2 weeks. Response options for this scale include “not at all,” “several days,” “over half the days,” or “nearly every day.” Symptoms of anxiety were calculated from the sum of responses, with a potential range of 0 to 21 (higher scores indicate more severe symptoms of anxiety). We used a cutoff of ≥10 to indicate moderate/severe anxiety.20
Cognitive impairment was assessed using the Montreal Cognitive Assessment Battery.21 This 30‐item battery includes an assessment of participants’ visuospatial/executive skills, naming skills, memory, attention, language, abstraction skills, delayed recall, and orientation. Cognitive impairment was calculated from the sum of correct responses, with a potential range of 0 to 30 (higher scores indicate better cognitive functioning). We used a cutoff of ≤23 to indicate cognitive impairment.22
Atrial fibrillation quality of life was assessed using the Atrial Fibrillation Effect Quality‐of‐Life (AFEQT) Questionnaire.23 This 20‐item questionnaire asks participants to self‐report the extent to which atrial fibrillation has affected their quality of life in the past month, and there are individual subscales for symptoms, daily activities, and treatment concern. Response options for this questionnaire include “not at all bothered OR I did not have this symptom,” “hardly bothered,” “a little bothered,” “moderately bothered,” “quite a bit bothered,” “very bothered,” or “extremely bothered.” Atrial fibrillation quality of life was calculated according to the following formula: 100−[(sum of severity for all questions answered)−(number of questions answered)×100]/[(total number questions answered)×6],24 with a potential range of 0 to 100 (higher scores indicate better quality of life). We categorized atrial fibrillation‐related quality of life as potentially impaired (<80) versus not impaired (≥80). A score of 80 indicates that on average patients responded that they were not at all or hardly bothered (or not/hardly limited, or experienced no/hardly any difficulty) by the symptoms, daily activities, and treatment concerns queried on the AFEQT, and roughly equals the mean AFEQT scores in patients with atrial fibrillation who maintained sinus rhythm 3 months after ablation.25 We also examined atrial fibrillation quality of life as a continuous variable, with lower scores representing worse atrial fibrillation quality of life.
Potential Confounders
Participants reported their race/ethnicity, education level, marital status, living situation, number of falls in the past 6 months, and use of a walking aid during the baseline interview. Age, sex, type of atrial fibrillation, current medications (eg, oral anticoagulants, beta blockers, calcium channel blockers), and medical history (eg, type 2 diabetes mellitus, heart failure, chronic obstructive pulmonary disease) were abstracted from participants’ medical records.
Statistical Analysis
First, we reported descriptive statistics by gait speed. We presented frequency and percentages for categorical variables. We used chi‐squared tests to assess differences among demographic and clinical characteristics by gait speed. Then, we estimated crude and adjusted odds ratios (ORs) and 95% CIs for elevated depressive symptoms, elevated symptoms of anxiety, cognitive impairment, and potentially impaired atrial fibrillation‐related quality of life in relationship to gait speed (low versus normal) using logistic regression models. Demographic and clinical characteristics that differed by gait speed were included in adjusted models. We present models adjusted for demographic characteristics and also models adjusted for demographic and clinical characteristics. We additionally included study site (Massachusetts versus Georgia) in adjusted regression models to control for additional confounding by other differences between sites. We also examined continuous AF quality of life scores in relationship to gait speed using linear regression models and the model‐building strategy outlined above. Finally, we conducted a sensitivity analysis using an alternative definition of low gait speed (<0.83 m/s).14 P<0.05 was considered statistically significant. All statistical analyses were conducted using SAS software version 9.4 (SAS Institute Inc, Cary, NC).
Results
Of the 1244 older adults with atrial fibrillation enrolled in SAGE‐AF, we excluded participants who did not complete the walk test (n=41). Of the 1203 participants with information on gait speed, we excluded participants missing information about any of the variables used in the analysis (n=1 race/ethnicity, n=18 education), resulting in an analytic sample of 1185 older adults with AF.
Participants were on average 75.3 (SD: 7.0) years old, 48.0% women, 85.5% non‐Hispanic white (Table 1). Most patients (59.6%) had paroxysmal AF, 25.0% had persistent AF, and 5.7% had permanent AF. The majority (85.6%) were taking an oral anticoagulant. A quarter (26.1%; n=309) had low gait speed. Characteristics of the sample in relationship to gait speed are shown in Table 1.
Table 1.
Demographic and Clinical Characteristics of Older Adults With Atrial Fibrillation, Overall Sample and in Relationship to Gait Speed, SAGE‐AF 2016 to 2018, N (%)
| Total Sample (N=1185) | Low Gait Speed (n=309) | Normal Gait Speed (n=876) | P Value | |
|---|---|---|---|---|
| Age | ||||
| 65 to 74 y | 605 (51.1) | 105 (34.0) | 500 (57.1) | <0.0001 |
| 75 to 84 y | 433 (36.5) | 131 (42.4) | 302 (34.5) | |
| 85 y | 147 (12.4) | 73 (23.6) | 74 (8.5) | |
| Women | 569 (48.0) | 190 (61.5) | 379 (43.3) | <0.0001 |
| Non‐Hispanic white | 1013 (85.5) | 229 (74.1) | 784 (89.5) | <0.0001 |
| Education | ||||
| High school, GED, or less | 97 (8.2) | 45 (14.6) | 52 (5.9) | <0.0001 |
| Some college, trade school | 575 (48.5) | 181 (58.6) | 394 (45.0) | |
| College/some graduate coursework | 187 (15.8) | 33 (10.7) | 154 (17.6) | |
| Graduate degree | 326 (27.5) | 50 (16.2) | 276 (31.5) | |
| Weight status | ||||
| Underweight | 12 (1.0) | 4 (1.3) | 8 (0.9) | 0.0138 |
| Normal weight | 223 (18.8) | 67 (21.7) | 156 (17.8) | |
| Overweight | 415 (35.0) | 85 (27.5) | 330 (37.7) | |
| Obese | 535 (45.2) | 153 (49.5) | 382 (43.6) | |
| Type of atrial fibrillation | ||||
| Paroxysmal | 706 (59.6) | 178 (57.6) | 528 (60.3) | 0.4535 |
| Persistent/long‐standing persistent | 296 (25.0) | 86 (27.8) | 210 (24.0) | |
| Permanent | 67 (5.6) | 19 (6.2) | 48 (5.5) | |
| Other/unknown | 116 (9.8) | 26 (8.4) | 90 (10.3) | |
| Medication use | ||||
| OAC | 1014 (85.6) | 270 (87.4) | 744 (84.9) | 0.2926 |
| Beta blocker | 754 (63.6) | 218 (70.6) | 536 (61.2) | 0.0033 |
| Calcium channel blocker | 369 (31.1) | 93 (30.1) | 276 (31.5) | 0.6454 |
| Type of anticoagulant among OAC users (n=1014) | ||||
| Warfarin | 566 (55.8) | 150 (55.6) | 416 (55.9) | 0.9191 |
| Other anticoagulant | 448 (44.2) | 120 (44.4) | 328 (44.1) | |
| Prior implantable cardiac device | 392 (33.1) | 153 (49.5) | 239 (27.3) | <0.0001 |
| Medical history | ||||
| Anemia | 362 (30.6) | 123 (39.8) | 239 (27.3) | <0.0001 |
| Major bleeding | 229 (19.3) | 78 (25.2) | 151 (17.2) | 0.0022 |
| Stroke | 109 (9.2) | 42 (13.6) | 67 (7.7) | 0.0019 |
| Renal disease | 327 (27.6) | 114 (36.9) | 213 (24.3) | <0.0001 |
| Chronic obstructive pulmonary disorder | 291 (24.6) | 97 (31.4) | 194 (22.2) | 0.0012 |
| Type 2 diabetes mellitus | 322 (27.2) | 119 (38.5) | 203 (23.2) | <0.0001 |
| Myocardial infarction | 233 (19.7) | 78 (25.2) | 155 (17.7) | 0.0041 |
| Peripheral vascular disease | 164 (13.8) | 58 (18.8) | 106 (12.1) | 0.0035 |
| Heart failure | 429 (36.2) | 177 (57.3) | 252 (28.8) | <0.0001 |
OAC indicates oral anticoagulants, SAGE‐AF, Systematic Assessment of Geriatric Elements in Atrial Fibrillation.
Overall, 8.4% of participants had elevated depressive symptoms, 5.7% had elevated anxiety symptoms, and 41.1% were cognitively impaired. Average atrial fibrillation‐related quality of life was 80.2 (SD: 17.9), and 41.6% had potentially impaired atrial fibrillation‐related quality of life.
Participants with low gait speed were more likely to have elevated depressive symptoms (16.5% versus 5.6%; adjusted OR: 2.1, 95% CI: 1.3–3.4), elevated anxiety symptoms (10.7% versus 3.9%; adjusted OR: 2.2, 95% CI: 1.2–3.9), cognitive impairment (59.9% versus 34.5%; adjusted OR: 1.5, 95% CI: 1.1–2.1; Figure and Table 2). While potentially impaired atrial fibrillation‐related quality of life differed by gait speed in crude models and after adjustment for demographics (50.3% versus 35.5%; crude OR: 1.6; 95% CI: 1.2–2.1; adjusted OR: 1.4, 95% CI: 1.1–1.9; Figure and Table 2), the proportion of patients with impaired atrial fibrillation‐related quality of life did not differ by gait speed after adjusting for clinical characteristics (adjusted OR: 1.1; 95% CI: 0.8–1.5; Table 2).
Figure 1.
Prevalence of elevated depressive symptoms, elevated anxiety symptoms, cognitive impairment, and impaired quality of life in relationships to gait speed among older adults with atrial fibrillation, SAGE‐AF (Systematic Assessment of Geriatric Elements in Atrial Fibrillation) 2016 to 2018.
Table 2.
Associations Between Low Gait Speed and Depressed Mood, Symptoms of Anxiety, Cognitive Impairment, and Impaired Quality of Life Among Older Patients With AF, SAGE‐AF 2016 to 2018
| Low Gait Speed, n (%) | Normal Gait Speed, n (%) | Crude OR (95% CI) | Adjusteda OR (95% CI) | Adjustedb OR (95% CI) | |
|---|---|---|---|---|---|
| Elevated depressive symptoms | 51 (16.5) | 49 (5.6) | 3.3 (2.2–5.1)c | 3.0 (1.9–4.7)c | 2.1 (1.3–3.4)c |
| Elevated symptoms of anxiety | 33 (10.7) | 34 (3.9) | 3.0 (1.8–4.9)c | 2.4 (1.4–4.1)c | 2.2 (1.2–3.9)c |
| Cognitive impairment | 185 (59.9) | 302 (34.5) | 2.8 (2.2–3.7)c | 1.7 (1.3–2.3)c | 1.5 (1.1–2.1)c |
| Potentially impaired AF‐related quality of life | 155 (50.2) | 338 (38.6) | 1.6 (1.2–2.1)c | 1.4 (1.1–1.9)c | 1.1 (0.8–1.5) |
AF indicates atrial fibrillation; OR, odds ratio; SAGE‐AF, Systematic Assessment of Geriatric Elements in Atrial Fibrillation.
Adjusted for age, sex, race/ethnicity, and education.
Adjusted for age, sex, race/ethnicity, education, body mass index categories, beta‐blocker use, prior implantable cardiac device, and medical history of anemia, major bleeding, stroke, renal disease, chronic obstructive pulmonary disorder, type 2 diabetes mellitus, myocardial infarction, peripheral vascular disease, and heart failure.
P<0.05.
Participants with low gait speed had lower atrial fibrillation‐related quality of life on average than participants without low gait speed in the crude and adjusted models (M [SD]: 75.6 [20.5] versus 81.9 [16.6]; crude β: −6.3, 95% CI: −8.6 to −4.0, P<0.0001; demographics‐adjusted β: −5.2, 95% CI: −7.6 to −2.8, P<0.0001; fully‐adjusted β: −3.4, 95% CI: −5.9 to −0.9, P=0.0073). Results from regression models that included study site as a covariate were nearly identical to the main findings, and outcomes did not differ by study site (data not shown). We conducted a sensitivity analysis using an alternate definition of low gait speed. Using this definition, 41.1% of the sample had low gait speed. Results examining elevated depressive symptoms, elevated anxiety symptoms, and cognitive impairment were similar to the main analysis (data not shown). However, patients with low gait speed were more likely to have impaired atrial fibrillation‐related quality of life than patients with normal gait speed after adjustment for demographic and clinical characteristics (adjusted OR: 1.3; 95% CI: 1.0–1.7, P=0.0463).
Discussion
In this study, a quarter of older adults with atrial fibrillation had low gait speed. Patients with low gait speed had significantly greater odds of having symptoms of depression, symptoms of anxiety, cognitive impairment, and potentially impaired atrial fibrillation‐related quality of life, in support of our hypotheses.
Our findings that patients with AF who have low gait speed were more likely to have elevated depressive symptoms is consistent with previous research.8, 15, 16 Depression is common among older adults, due in part to the increased functional decline and social isolation in this population.8, 26 While the direction of this relationship is unknown, our findings suggest there is a strong association between gait speed and symptoms of depression. Although there are many factors that can cause depression, studies have shown that clinically depressed individuals have distinct gait patterns, posture, and walking speed.15 Furthermore, gait is regulated by psychomotor skills, which are adversely affected by depression.27 These skills combine both physical and mental domains; therefore, it is possible that low gait speed may be predictive of psychological status.8 Future longitudinal studies could shed light on whether slowing gait speed leads to an increase in depressive symptomology, whether the development of depression results in lowered gait speed, or whether low gait speed and depression develop simultaneously.
We also found that patients with low gait speed were more likely to have elevated anxiety symptoms. Clinical anxiety has been shown to affect attention and working memory, and these domains are also involved in regulating gait.9, 28, 29, 30 One specific cause of anxiety in older adults is fear related to balance and falls, and studies have shown that increasing this type of anxiety results in a more cautious, restricted walking style.9, 26 Similar to our findings related to depressive symptoms, future longitudinal studies could elucidate the directionality of the observed association between low gait speed and elevated anxiety symptoms.
We also found that patients with low gait speed were more likely to be cognitively impaired. As previously stated, walking requires attention, executive function, memory, and other cognitive demands. It is well documented that these domains, as well as global cognition, can be affected by age.29, 30 Like cognition, there can also be age‐related changes in gait, such as shortened stride length and slower walking speed. One explanation for our finding is that physical changes in gait, such as slower walking speed, are related to declines in the cognitive domains that regulate posture, balance, and other gait elements.9 Previous research has documented that neurologic disease can adversely affect gait, and that gait speed may also be related to worsening of these impairments.26 These results help explain our finding that patients with low gait speed had significantly greater odds of having cognitive impairment.
Finally, we found that patients with low gait speed were more likely to have potentially impaired atrial fibrillation‐related quality of life in crude models and after adjusting for demographic characteristics. However, after adjusting for clinical characteristics, impaired atrial fibrillation‐related quality of life did not differ by gait speed, suggesting that differences in impaired quality of life can be explained by differences in clinical burden between patients with low versus normal gait speed. When examining continuous AFEQT scores, we found that patients with low gait speed had lower AF‐related quality of life in both crude and adjusted models. To our knowledge, there is little known about the relationship between gait speed and disease‐specific, atrial fibrillation‐related quality of life; however, previous research in other cardiac populations and among older adults generally has shown that low gait speed is predictive of frailty, mortality, hospitalizations, and overall physical function, all of which relate to quality of life.11, 16, 31 Longitudinal studies are needed to examine whether low gait speed leads to impaired atrial fibrillation‐related quality of life, or whether other health conditions lead to both declines in gait speed and worsening of quality of life.
There is no standard cutoff in the literature to indicate impaired atrial fibrillation‐related quality of life as measured by the AFEQT. We defined impaired quality of life as an AFEQT score <80, a score similar to the mean AFEQT scores of 81.3 in a previous study of patients with atrial fibrillation who maintained sinus rhythm 3 months after ablation.25 A score of 80 indicates that on average patients responded that they were not at all or hardly bothered (or not/hardly limited, or experienced no/hardly any difficulty) by the symptoms, daily activities, and treatment concerns queried on the AFEQT. Future studies may wish to use this cutoff to examine which patients are more likely to report impaired atrial fibrillation‐related quality of life.
A major limitation of this work is the cross‐sectional nature of the data. For this reason, we are unable to determine the direction of the relationships between gait speed and our outcomes. There is evidence to suggest that there is a bidirectional association between depression and low gait speed. Studies have shown that depression can affect motor control, gait, and walking speed, and that low gait speed can also increase depressive symptoms.8, 15, 16 It is possible that some patients may have sought treatment with psychotherapy or pharmacotherapy and, therefore, did not score high on the depression or anxiety symptom scales. Furthermore, patients treated with antidepressants may have experienced weight gain or alterations to neural circuits, which may have contributed to altered gait speed.15 Future longitudinal studies may be able to shed light on whether use of antidepressants or other medications lead to declines in gait speed. However, the current study's findings suggest that low gait speed is often comorbid with elevated depressive symptoms, elevated anxiety symptoms, cognitive impairment, and potentially impaired AF‐related quality of life.
This work also has strengths. The SAGE‐AF cohort is geographically diverse, and participants were enrolled from cardiology, primary care, and electrophysiology clinics, resulting in a more generalizable sample of older adults with AF. The inclusive eligibility criteria allowed us to study patients who may have otherwise been excluded from clinical studies because of age, comorbidities, or other factors.
Conclusions
In conclusion, this study of older adults with atrial fibrillation found that low gait speed was associated with elevated depressive symptoms, elevated anxiety symptoms, and cognitive impairment. A major limitation of the current study is its cross‐sectional nature, especially given previous research that is inconsistent about the directionality of these associations. However, gait speed is easy to measure in the clinical setting and already commonly used as a screening criterion for some procedures (eg, transcatheter aortic valve replacement).32, 33 The current findings suggest that screening for depression, anxiety, cognitive impairment, or impaired AF‐related quality of life may be prudent in patients with AF identified as having low gait speed, and appropriate referrals be made for mental health care. If future prospective studies were to observe that patients whose gait speed declined subsequently developed adverse psychological and cognitive outcomes, then screening for declines in gait speed and either behavioral or physical activity interventions to prevent declines in gait speed could potentially have an impact on these outcomes, thus improving the lives of older adults with atrial fibrillation.
Sources of Funding
This work and SAGE‐AF were supported by National Institutes of Health (grant number R01HL126911). Additional support provided by National Institutes of Health (grants R01HL141434 [Dr McManus], R01HL137734 [Dr McManus], R01HL137794 [Dr McManus], and R01HL13660 [Dr McManus]). The sponsor did not have a role in study design, in collection, analysis or interpretation of data, in writing the report, or in the decision to submit the article for publication.
Disclosures
Dr McManus discloses equity stakes or consulting relationships with Flexcon, Bristol‐Myers Squibb, Boston Biomedical Associates, Pfizer, Samsung, and research support from Apple, Sanofi Aventis, Otsuka Pharmaceuticals, Philips Healthcare, Biotronik, Bristol Myers Squibb, Boehringher Ingelheim, and Pfizer. Dr McManus has inventor stake in Mobile Sense Technologies, LLC. The remaining authors have no disclosures to report.
Acknowledgments
All authors had access to the data and had a role in writing the manuscript.
(J Am Heart Assoc. 2019;8:e013212 DOI: 10.1161/JAHA.119.013212.)
References
- 1. Go AS, Hylek EM, Phillips KA, Chang Y, Henault LE, Selby JV, Singer DE. Prevalence of diagnosed atrial fibrillation in adults: national implications for rhythm management and stroke prevention: the anticoagulation and risk factors in atrial fibrillation (ATRIA) study. J Am Med Assoc. 2001;285:2370–2375. [DOI] [PubMed] [Google Scholar]
- 2. Wolf PA, Abbott RD, Kannel WB. Atrial fibrillation as an independent risk factor for stroke: the Framingham Study. Stroke. 1991;22:983–988. [DOI] [PubMed] [Google Scholar]
- 3. Fried LP, Tangen CM, Walston J, Newman AB, Hirsch C, Gottdiener J, Seeman T, Tracy R, Kop WJ, Burke G, McBurnie MA; Group CHSCR . Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci. 2001;56:M146–M156. [DOI] [PubMed] [Google Scholar]
- 4. Bieniek J, Wilczynski K, Szewieczek J. Fried frailty phenotype assessment components as applied to geriatric inpatients. Clin Interv Aging. 2016;11:453–459. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5. Schwenk M, Howe C, Saleh A, Mohler J, Grewal G, Armstrong D, Najafi B. Frailty and technology: a systematic review of gait analysis in those with frailty. Gerontology. 2014;60:79–89. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6. Donoghue OA, Nansen S, Dooley C, De Rooji S, Van Der Welde N, Kenny RA. Atrial fibrillation is associated with impaired mobility in community‐dwelling older adults. J Am Med Dir Assoc. 2014;15:929–933. [DOI] [PubMed] [Google Scholar]
- 7. Abellan Van Kan G, Rolland Y, Andrieu S, Bauer J, Beauchet O, Bonnefoy M, Cesari M, Donni L, Gillette‐Guyonnet S, Inzitari M, Nourhashemi F, Onder G, Ritz P, Salva A, Visser M, Vellas B. Gait speed at usual pace as a predictor of adverse outcomes in community‐dwelling older people an International Academy on Nutrition and Aging (IANA) Task Force. J Nutr Health Aging. 2009;13:881–889. [DOI] [PubMed] [Google Scholar]
- 8. Biderman A, Cwikel J, Fried AV, Galinsky D. Depression and falls among community dwelling elderly people: a search for common risk factors. J Epidemiol Community Health. 2002;56:631–636. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9. Gage WH, Sleik RJ, Polych MA, McKenzie NC, Brown LA. The allocation of attention during locomotion is altered by anxiety. Exp Brain Res. 2003;150:385–394. [DOI] [PubMed] [Google Scholar]
- 10. Kim H‐J, Park I, Lee HJ, Lee O. The reliability and validity of gait speed with different walking pace and distances against general health, physical function, and chronic disease in aged adults. J Exerc Nutrition Biochem. 2016;20:46–50. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11. Afilalo J, Eisenberg MJ, Morin J‐F, Bergman H, Monette J, Noiseux N, Perrault LP, Alexander KP, Langlois Y, Dendukuri N, Chamoun P, Kasparian G, Robichaud S, Gharacholou SM, Boivin J‐F. Gait speed as an incremental predictor of mortality and major morbidity in elderly patients undergoing cardiac surgery. J Am Coll Cardiol. 2010;56:1668–1676. [DOI] [PubMed] [Google Scholar]
- 12. Middleton A, Fritz SL, Lusardi M. Walking speed: the functional vital sign. J Aging Phys Act. 2015;23:314–322. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13. Castell M‐V, Sanchez M, Julian R, Queipo R, Martin S, Otero A. Frailty prevalence and slow walking speed in persons age 65 and older: implications for primary care. BMC Fam Pract. 2013;14:1–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14. Afilalo J, Alexander KP, Mack MJ, Maurer MS, Green P, Allen LA, Pompa JJ, Ferruucci L, Forman DE. Frailty assessment in the cardiovascular care of older adults. J Am Coll Cardiol. 2014;63:747–762. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15. Michalak J, Troje NF, Fischer J, Vollmar P, Heidenreich T, Schulte D. Embodiment of sadness and depression‐gait patterns associated with dysphoric mood. Psychosom Med. 2009;71:580–587. [DOI] [PubMed] [Google Scholar]
- 16. Buchner DM, Cress EM, Esselman PC, Margherita AJ, de Lateur BJ, Campbell AJ, Wagner EH. Factors associated with changes in gait speed in older adults. J Gerontol A Biol Sci Med Sci. 1996;51:M297–M302. [DOI] [PubMed] [Google Scholar]
- 17. Hausdorff JM, Schweiger A, Herman T, Yogev‐Seligmann G, Giladi N. Dual‐task decrements in gait: contributing factors among healthy older adults. J Gerontol A Biol Sci Med Sci. 2008;63A:1335–1343. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18. Schmitt EM, Marcantonio ER, Alsop DC, Jones RN, Rogers SO, Fong TG, Metzger E, Inouye SK; SAGES Study Group . Novel risk markers and long‐term outcomes of delirium: the successful aging after elective surgery (SAGES) study design and methods. J Am Med Dir Assoc. 2012;13:818. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19. Kroenke K, Spitzer RL, Williams JB. The PHQ‐9: validity of a brief depression severity measure. J Gen Intern Med. 2001;16:606–613. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20. Spitzer RL, Kroenke K, Williams JB, Lowe B. A brief measure for assessing generalized anxiety disorder: the GAD‐7. Arch Intern Med. 2006;166:1092–1097. [DOI] [PubMed] [Google Scholar]
- 21. Nasreddine ZS, Phillips NA, Bedirian V, Charbonneau S, Whitehead V, Collin I, Cummings JL, Chertkow H. The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment. J Am Geriatr Soc. 2005;53:695–699. [DOI] [PubMed] [Google Scholar]
- 22. Saczynski JS, Inouye SK, Guess J, Jones RN, Fong TG, Nemeth E, Hodara A, Ngo L, Marcantonio ER. The Montreal Cognitive Assessment: creating a crosswalk with the Mini‐Mental State Examination. J Am Geriatr Soc. 2015;63:2370–2374. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23. Spertus J, Dorian P, Bubien R, Lewis S, Godejohn D, Reynolds MR, Lakkireddy DR, Wimmer AP, Bhandari A, Burk C. Development and validation of the atrial fibrillation effect on quality‐of‐life (AFEQT) questionnaire in patients with atrial fibrillation. Circ Arrhythm Electrophysiol. 2011;4:15–25. [DOI] [PubMed] [Google Scholar]
- 24. St. Jude Medical I . Atrial Fibrillation Effect on Quality‐of‐Life (AFEQT) questionnaire instruction and scoring manual. 2009.
- 25. Raine D, Langley P, Shepherd E, Lord S, Murray S, Murray A, Bourke JP. Effect of catheter ablation on quality of life in patients with atrial fibrillation and its correlation with arrhythmia outcome. Open Heart. 2015;2:e000302. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26. Rubenstein LZ, Josephson KR. Falls and their prevention in elderly people: what does the evidence show? Med Clin North Am. 2006;90:807–824. [DOI] [PubMed] [Google Scholar]
- 27. Seppala T, Linnoila M, Mattila MJ. Psychomotor skills in depressed out‐patients treated with L‐tryptophan, doxepin, or chlorimipramine. Ann Clin Res. 1978;10:214–221. [PubMed] [Google Scholar]
- 28. Eysenck MW, Calvo MG. Anxiety and performance: the processing efficiency theory. Cogn Emot. 1992;6:409–434. [Google Scholar]
- 29. Montero‐Odasso M, Speechley M, Chertkow H, Sarquis‐Adamson Y, Wells J, Borrie M, Vanderhaeghe L, Zou GY, Fraser S, Bherer L, Muir‐Hunter S. Donepezil for gait and falls in mild cognitive impairment. A randomized controlled trial. Eur J Neurol. 2019;26:651–659. [DOI] [PubMed] [Google Scholar]
- 30. Celsis P. Age‐related cognitive decline, mild cognitive impairment or preclinical Alzheimer's disease? Ann Med. 2000;32:6–14. [DOI] [PubMed] [Google Scholar]
- 31. Kojima G, Iliffe S, Jivraj S, Walters K. Association between frailty and quality of life among community‐dwelling older people: a systematic review and meta‐analysis. J Epidemiol Community Health. 2016;70:716–721. [DOI] [PubMed] [Google Scholar]
- 32. Afilalo J, Lauck S, Kim DH, Lefèvre T, Piazza N, Lachapelle K, Martucci G, Lamy A, Labinaz M, Peterson MD, Arora RC, Noiseux N, Rassi A, Palacios IF, Généreux P, Lindman BR, Asgar AW, Kim CA, Trnkus A, Morais JA, Langlois Y, Rudski LG, Morin JF, Popma JJ, Webb JG, Perrault LP. Frailty in older adults undergoing aortic valve replacement: the FRAILTY‐AVR study. J Am Coll Cardiol. 2017;70:689–700. [DOI] [PubMed] [Google Scholar]
- 33. Kim DH, Kim CA, Placide S, Lipsitz LA, Marcantonio ER. Preoperative frailty assessment and outcomes at 6 months or later in older adults undergoing cardiac surgical procedures: a systematic review. Ann Intern Med. 2016;165:650–660. [DOI] [PMC free article] [PubMed] [Google Scholar]