Living alone is associated with adverse outcomes after acute coronary syndromes (ACS). One potential mediator of the relation between partner status and outcomes after ACS is physical activity. To evaluate the association of partner status with physical activity after ACS, data from 107 participants enrolled in the Prescription Use, Lifestyle, and Stress Evaluation (PULSE) study, a prospective observational study of post-ACS patients, were analyzed. Accelerometers were used to measure physical activity after hospital discharge. The primary outcome measure was a maximum 10 hours of daytime activity 1 month after discharge. One month after discharge from ACS hospitalizations, participants without a partner or spouse exhibited 24.4% lower daytime activity than those with a partner or spouse (p = 0.003). After controlling for age, gender, body mass index, Charlson co-morbidity index, and traditional psychosocial and clinical cardiovascular correlates of post-ACS physical activity, partner status remained an independent predictor of post-ACS physical activity (20.5% lower daytime activity among those without a partner or spouse, p = 0.008). In conclusion, in this study of accelerometer-measured physical activity after an ACS hospitalization, those without a partner or spouse exhibit significantly less physical activity than those with a partner or spouse 1 month after discharge from the hospital. Low physical activity may be an important mediator of the prognosis associated with partner status after ACS.
Living alone is an important risk factor for adverse events after acute coronary syndromes (ACS). However, the mechanism underlying this relation is not well understood. One proposed mediator of the relation between living alone and post-ACS adverse events is physical activity. Previous studies have shown that a low level of physical activity is associated with increased risk for recurrent cardiovascular events and increased risk for mortality after myocardial infarction (MI). However, previous studies that have examined the relation between post-ACS physical activity and prognosis have relied on self-reported physical activity, which is limited by recall bias and correlates only moderately well with objective assessments of physical activity. In contrast, accelerometers provide a more accurate representation of day-to-day physical activity and better predict adverse events. Therefore, to determine if physical activity is associated with partner status, a preliminary step toward determining if physical activity mediates the association of living alone with increased risk for adverse post-ACS events, we evaluated the relation between partner status and post-ACS physical activity as measured by continuously worn accelerometers using data from the Prescription Use, Lifestyle, and Stress Evaluation (PULSE) study.
Methods
Participants were hospitalized patients with ACS enrolled in PULSE, a prospective cohort study of the prognostic risk conferred by depression at the time of ACS. Five hundred patients with unstable angina or acute ST-segment elevation or non–ST-segment elevation MIs at Columbia University Medical Center were recruited from February 1, 2009 to June 30, 2010, <1 week after their hospitalization. Participants returned for a follow-up visit 1 month later. Excluded from analyses were 225 participants who were not approached or did not agree to wear the accelerometers, 105 participants who did not return the accelerometers, and 61 participants who were not adherent to accelerometer use during the study. Two patients who underwent coronary artery bypass surgery and balloon aortic valvuloplasty were also excluded, because the invasiveness of these procedures may confound the association between any predictor and level of post-ACS physical activity. The present analysis thus included 107 PULSE participants treated with percutaneous coronary intervention or medical therapy for ACS during the index hospitalization. The institutional review board of Columbia University Medical Center approved this study, and all participants provided informed consent.
Participants were provided with Actical (Respironics, Inc., Bend, Oregon) accelerometers before discharge or were mailed the devices after discharge from their ACS hospitalization. They were instructed to wear the devices on the nondominant wrist continuously (including during sleep) and to return the devices at the 1-month postdischarge follow-up visit. The Actical is a small, wristwatch-like, omnidirectional accelerometer that provides real-time ambulatory monitoring and quantification of activity levels. Data were monitored continuously and recorded in 1-minute epochs, resulting in an activity count for each minute of the day. To be included in the present analyses, participants were required to have worn the device for ≥5 days within 45 days of their discharge from the hospital. Accelerometer nonadherence, evaluated for each day, was defined as >4 hours of total inactivity recorded by the device during daytime hours (6 am to 10 pm ). Data for nonadherent days were excluded from the analysis. The following measures of activity from 6 am to 10 pm were then derived. M10h, a measure of a participant’s overall daytime activity, was the total activity count of the most active 10 hours in the day (which need not be 10 consecutive hours). This measure was previously used in a study of patients with chronic heart failure to summarize overall activity.
At baseline, a trained research assistant interviewed participants. Age, gender, ethnicity (Hispanic vs non-Hispanic), race (white vs black vs other), and partner status (presence or absence of a partner or spouse) were determined by patient self-report. Systematic medical chart extraction was performed to ascertain history of cardiovascular diseases (angina, MI, stroke, peripheral arterial disease, heart failure, and New York Heart Association heart failure class), cardiovascular procedures (percutaneous transluminal coronary angioplasty [PTCA] and coronary artery bypass grafting), and history of other chronic medical conditions (respiratory diseases, liver diseases, rheumatologic diseases, and stomach ulcers). The Global Registry of Acute Coronary Events (GRACE) risk score was used to calculate 6-month post-ACS mortality risk, and the Charlson co-morbidity index was used to assess severity of medical co-morbidities. The left ventricular ejection fraction was assessed using echocardiography, ventriculography, or nuclear stress testing. ACS type (unstable angina, ST-segment elevation MI, non–ST-segment elevation MI) was determined from chart review by study cardiologists according to standard criteria. Treatment strategy (PTCA or medical therapy) and length of hospitalization for index ACS event were obtained by chart review.
Participants’ symptoms of depression were ascertained at baseline on the basis of their self-reported responses to the 21-item Beck Depression Inventory. Symptoms of anxiety were assessed by participants’ self-reported responses to the anxiety subscale of the Hospital Anxiety and Depression Scale. Anergia (lack of energy) was assessed using a validated anergia assessment tool. Perceived social support was assessed using the Enhancing Recovery in Coronary Heart Disease Patients (ENRICHD) Social Support Index on the basis of the responses to 7 items shown to be predictive of outcomes in heart disease and scored according to standard methods. To be categorized as having low perceived social support, participants had to have either (1) a score ≤3 on any 2 items in combination with a total score ≤18 or (2) a score ≤2 on any 2 items, as has been previously published.
Demographic, psychosocial, and clinical factors are presented as proportions, mean ± SD, or median (interquartile range [IQR]). The primary outcome variable was estimated daytime activity level (M10h) on the 30th day after discharge from ACS hospitalization, derived from a multilevel growth curve model designed to leverage the accelerometer data from the entire postdischarge period and account for missing data and outliers. The distribution of M10h was positively skewed; preliminary analyses indicated that the optimal Box-Cox transformation was the natural log transformation, and thus this transformation was used for all analyses. Multilevel growth curve models were used to model within-person trajectories of daytime physical activity during the first 45 days after discharge. Preliminary analyses demonstrated that the optimal model specification included linear and quadratic terms for postdischarge day (time), with these terms and the intercept treated as random effects. With appropriate scaling of time, the within-subject intercepts represent the estimated activity level on the 30th day after discharge. Using this growth curve model as a base, partner status and all other covariates were individually added to the model to assess their bivariate associations with estimated physical activity (M10h) on day 30. Subtracting 1 from the exponentiated parameter estimate for each covariate (and its 95% confidence limits) yielded the percentage difference in activity associated with a 1-unit difference in the covariate. Subsequent models were estimated to assess the independent association of partner status with day 30 activity after adjusting for demographic, psychosocial, and clinical predictors. Because age was the most powerful predictor of activity in bivariate analyses, the relationship of all other covariates with post-ACS activity was evaluated in age-adjusted models. Those covariates that demonstrated an age-adjusted association with activity at a significance level of p <0.15 were included in a fully adjusted multivariate model. To confirm that the inclusion of participants with small numbers of accelerometer days did not have an undue influence of the results, analyses were repeated after restricting the data set to participants with ≥15 days of accelerometer wear time (n = 72). All analyses were performed in SAS version 9.2 (SAS Institute Inc., Cary, North Carolina). A p value ≤0.05 was considered statistically significant.
Results
Demographic, psychosocial, and clinical characteristics of participants are listed in Table 1 . The median accelerometer wear time for participants was 23 days (IQR 10 to 33). The median age was 63 years (IQR 55 to 71), and there were more male (65%) than female participants. Participants of Hispanic ethnicity constituted 36% of the cohort, and 20% were black. Overall, 57% of ACS events were unstable angina, 25% were non-ST-segment elevation MIs, and 18% were ST-segment elevation MIs. Most participants (77%) were treated with PTCA during hospitalization for their index ACS events, and the median length of index hospitalization was 3 days (IQR 2 to 5). Most participants had histories of chronic anginal symptoms (57%), while relatively few participants had histories of symptomatic congestive heart failure (5% with New York Heart Association class III or IV symptoms). The prevalence of previous MI was 28%. The median Beck Depression Inventory score was 9 (IQR 4 to 13), and 37% of participants met criteria for the syndrome of anergia. Most participants reported not having partners or spouses (58%).
| Variable | Value |
|---|---|
| Age (yrs) | 63 (55–71) |
| Men | 70 (65%) |
| Body mass index (kg/m 2 ) | 28.2 (25.7–31.2) |
| Hispanic | 39 (36%) |
| Black | 21 (20%) |
| Charlson co-morbidity index | 1 (0–2) |
| Chronic lung disease | 12 (11%) |
| ACS | |
| Unstable angina pectoris | 61 (57%) |
| Non–ST-segment elevation MI | 27 (25%) |
| ST-segment elevation MI | 19 (18%) |
| Characteristics of ACS hospitalization | |
| Treated with PTCA | 82 (77%) |
| Length of hospital stay (days) | 3 (2–5) |
| GRACE risk score | 65 (84–106) |
| Left ventricular ejection fraction (%) | 53 (45–58) |
| Left ventricular ejection fraction <40% | 9 (8%) |
| History of cardiovascular diseases and related procedures | |
| MI | 30 (28%) |
| PTCA | 46 (43%) |
| Coronary artery bypass grafting | 16 (15%) |
| Stroke | 4 (4%) |
| Peripheral arterial disease | 5 (5%) |
| Congestive heart failure | 10 (9%) |
| New York Heart Association class III/IV | 5 (5%) |
| History of chronic angina pectoris | 61 (57%) |
| Psychosocial symptoms and social support | |
| Partner status | |
| Partner or spouse | 45 (42%) |
| No partner or spouse | 62 (58%) |
| Depression symptom severity | |
| Beck Depression Inventory score | 9 (4–13) |
| Anergia | 38 (37%) |
| Hospital Anxiety and Depression Scale, anxiety subscale | 3 (1–6) |
| Low perceived social support | 12 (11%) |
Those living without partners or spouse were 24% less active on day 30 after discharge for ACS than those living with partners or spouses (p = 0.003). Patients with anergia were 20% less active than patients without anergia. Patients who underwent PTCA during the index hospitalization exhibited 26% higher post-ACS physical activity compared with patients who did not receive PTCA. Statistically significant clinical predictors of lower levels of physical activity included GRACE risk score (6% decrease in activity per 10-point increase in GRACE risk score), history of stroke (38% decreased activity in patients with histories of stroke), and length of index hospitalization (6% decreased activity per day of hospitalization). Older age and higher Charlson co-morbidity scores were also associated with lower levels of physical activity. Low perceived social support as estimated by the ENRICHD Social Support Index was not associated with post-ACS activity (p = 0.84). The unadjusted effects of demographic, clinical, and psychosocial factors on day 30 physical activity after ACS are listed in Table 2 .
| Variable | % Difference in Activity (95% Confidence Limits) | p Value |
|---|---|---|
| Age (per 10-yr increase) | −15% (−21%, −9%) | <0.0001 |
| Male gender | 16% (−4%, 41%) | 0.13 |
| Body mass index | −1% (−3%, 1%) | 0.26 |
| Hispanic | −9% (−24%, 11%) | 0.36 |
| Black | −16% (−33%, 7%) | 0.16 |
| Charlson co-morbidity index | −8% (−12%, −2%) | 0.01 |
| Chronic lung disease | −16% (−37%, 12%) | 0.24 |
| ACS | ||
| ST-segment elevation MI | Reference | 0.59 |
| Non–ST-segment elevation MI | −7% (−29%, 23%) | |
| Unstable angina | −12% (−31%, 13%) | |
| Index ACS hospitalization | ||
| Treated with PTCA | 26% (2%, 55%) | 0.04 |
| Length of hospital stay | −6% (−8%, −3%) | <0.0001 |
| GRACE risk score (per 10-point increase) | −6% (−9%, −3%) | <0.0001 |
| Left ventricular ejection fraction (per 10% increase) | −0.03% (−8%, 9%) | 0.99 |
| Left ventricular ejection fraction <40% | −2% (−29%, 36%) | 0.92 |
| History of cardiovascular diseases and related procedures | ||
| MI | −13% (−29%, 6%) | 0.17 |
| PTCA | 4% (−13%, 26%) | 0.66 |
| Coronary artery bypass grafting | −9% (−30%, 18%) | 0.46 |
| Stroke | −38% (−62%, −0.4%) | 0.051 |
| Peripheral arterial disease | −33% (−57%, 4%) | 0.07 |
| Congestive heart failure | −6% (−31%, 29%) | 0.71 |
| New York Heart Association class III/IV | −2% (−48%, 19%) | 0.26 |
| History of chronic angina | −4% (−21%, 15%) | 0.65 |
| Psychosocial symptoms and social support | ||
| Beck Depression Inventory score (per 5-point increase) | −5% (−10%, 1%) | 0.12 |
| Beck Depression Inventory score >10 | −9% (−24%, 10%) | 0.32 |
| Anergia | −20% (−34%, −3%) | 0.03 |
| Hospital Anxiety and Depression Scale, anxiety subscale (per 1-point increase) | 1% (−2%, 4%) | 0.43 |
| No partner or spouse | −24% (−37%, −10%) | 0.003 |
| Low perceived social support | −3% (−28%, 30%) | 0.84 |
Partner status remained a significant predictor of post-ACS activity after adjusting for age, gender, body mass index, Charlson co-morbidity score, Beck Depression Inventory score, the presence of anergia, history of stroke, history of peripheral arterial disease, treatment with PTCA during ACS hospitalization, and length of index hospitalization ( Table 3 ). In the fully adjusted model, patients without partners or spouses were 20.5% less active than those living with partners or spouses (p = 0.008). Age and length of index hospitalization were also inversely associated with post-ACS activity after multivariate adjustment ( Table 3 ). Results were similar after the exclusion of 35 participants with <15 days of accelerometer wear time (data not presented).
