Approximately 67% of patients with heart failure (HF) experience chronic noncardiac pain that further complicates their disease management.1 Comorbid depression is estimated to impact 22% to 42% of patients with HF and poses additional threats to effective pain management.2 When depression is combined with HF and pain, patients are even less able to follow recommendations, treatment plans, and self-care behaviors, and length of time to treat chronic pain and depression is extended.3 Increasing physical activity levels among patients with HF and depression holds many opportunities to facilitate health and well-being by improving HF, pain, and depression symptoms.4 However, Butchart et al5 report that only 23% of patients with HF reported using exercise as a pain management strategy. Most (70%) use rest or sedentary activities to decrease their pain. Sedentary activities exacerbate HF and depression problems further because increased muscle wasting occurs when daily physical activity decreases.1
Chronic pain and depression often occur together.3,6 A considerable body of literature supports the coexistence and bidirectional relationship between chronic pain and depression that demands concurrent treatment to achieve optimal outcomes for each condition.3,6–9 However, little attention has been paid to this relationship in patients with HF who are at a much higher risk for adverse health outcomes. Given low exercise participation rates and the many barriers that discourage exercise, an essential first step is to assess current physical activity levels and examine how pain and depression may further influence engagement in exercise programs.10 The purposes of this article are to describe self-reported physical activity and exercise levels of depressed patients with HF and to determine the relationships of pain intensity, pain interference, total activity time, and sitting time with depression.
This analysis uses cross-sectional data as a secondary analysis from a larger clinical trial that was enrolling 219 participants. This study complies with the Declaration of Helsinki, the institutional review board at a midwestern university approved the protocol, and informed consent was obtained from participants. Inclusion criteria that were used in this analysis include age of 55+ years, diagnosis of heart failure, a score of 10+ on the Beck Depression Inventory (BDI), and a score of 70 or lower on the physical impairment subscale of the Rand Medical Outcomes Study. Exclusion criteria included currently participating in psychotherapy, other significant psychiatric diagnoses, suicidal ideation, cognitive impairment, awaiting transplant, residence in a long-term care facility, or significant hearing impairment.
The International Physical Activity Questionnaire (IPAQ) is an internationally used, open-access instrument that has well-defined scoring protocols for rating physical activity levels as both a continuous variable and a categorical variable.11 The instructions direct participants to only count physical activities that are at least 10 minutes in length. Compared with other self-report physical activity measures, the IPAQ has been shown to have equally acceptable validity (0.33) for assessing different domains of exercise and physical activity.12 Reliability is reported to be acceptable (α = .81).13
The BDI-II was used to assess level of depression. The BDI-II contains 21 questions that are scored on a scale of 0 to 3, for a total score range of 0 to 63. The inventory has well-established cut points related to depression severity (mild, 10–20; moderate, 21–30; and severe, >30), and a score of 10 is widely accepted for screening.14
The Brief Pain Inventory Short Form (BPI-SF) was used to assess pain intensity and interference. The BPI-SF assesses intensity of pain and extent that pain interferes with social and physical function.15 Scores for the 4 intensity items and 7 interference items are averaged to derive a single score value each for pain intensity and pain interference. The 15-item BPI-SF has shown consistent validity and reliability for many conditions.
The Charlson Comorbidity Index was used to evaluate the effects of comorbidities based on the International Classification of Diseases diagnostic codes. Each comorbidity has an associated weight, based on the adjusted risk of mortality or resource use. The sum of all the weights results in a single comorbidity score for a patient, with higher scores indicating greater comorbidity burden.16 Charlson scores presented here are in addition to heart failure.
A demographic and health-related questionnaire was used to collect data on age, gender, race, ethnicity, marital status, income level, health insurance for medical expenses, employment status, educational level, veteran status, smoking status, and antidepressant use. New York Heart Association (NYHA) classification was assessed from a medical record review.
Data were analyzed using SAS (version 9.3; SAS Institute Inc, Cary, North Carolina). Continuous data were summarized as means and standard deviations for variables that were normally distributed and medians and interquartile ranges for variables that were not normally distributed. Categorical data were summarized as frequencies. Participants' times spent sitting in low, moderate, and vigorous activities were summarized in minutes. Pairwise relationships between time spent performing physical activities (total activity time) and pain (intensity and interference) among depressed participants with HF were examined. Because of the level of skewness in the data, Spearman correlations were used to examine relationships among continuous variables in regression models.
Regression analyses were conducted to determine which demographic and health-related variables were most influential in predicting pain intensity, pain interference, depression, total activity time, and sitting time. Demographic and health-related variables were summarized, categorized, and used in the model selection analyses, with the final model chosen by Akaike information criterion (AIC). The AIC is a measure of penalized fit that takes into account the amount of variability explained and penalizes for each additional parameter in the model.17 This helps determine the set of predictors that adequately describe the data while keeping the model as parsimonious as possible. The modeling method provides a means for unbiased model selection because AIC looks at model fit, not significance levels.
To further explore the relationships, each key variable was used as the dependent variable in the regression analysis. Multiple linear regression was performed with pain interference, intensity, depression, and total activity time. To meet the normality assumption, only those reporting pain were included for pain interference and intensity variables. Depression level and total activity time were log transformed. Sitting time was dichotomized (<8 or ≥8 hours a day) and analyzed using logistic regression.
A total of 61 participants with heart failure completed the IPAQ and BPI-SF questionnaires. The sample characteristics are displayed in Table 1. The participants had a mean (SD) age of 67 (8.8) years; were male (75%), white (92%), non-Hispanic (95%), and married (53%); had an NYHA classification of III (60%); and had a moderate level of depression symptoms (48%). A summary of variables from the BPI-SF, IPAQ, and BDI-II can be found in Table 2. The pain scores were moderate, with a median pain intensity score of 4.0 and a median pain interference score of 4.4 (both on a 0–10 scale). A median of 365 minutes per week was spent performing any physical activity. A median of 60 minutes per week was spent performing light physical activity. A median of 210 minutes a week was spent performing moderate activities.
Five different regression models were developed and tested for the following variables: pain intensity and pain interference with those participants who reported pain, total activity time, depression, and sitting time (Table 3). For the pain intensity analysis, patients in NYHA classification of III to IV were more likely to report higher levels of pain compared with those with an NYHA category II (P = .054). In the pain interference analysis, women were more likely to have higher pain interference than men (P = .02). In the depression analysis, only sitting time was chosen, and that model was not statistically significant (P = .0595). In the total activity time analysis, only minutes sitting was found to be statistically significant (P < .001). In the sitting time analysis, age and NYHA were statistically significant (Ps = .004 and .003, respectively). For every year increase in age, the odds of being the higher sitting time group are estimated to increase by 18%, controlling for all the other variables in the model. Those participants who were in NYHA class III to IV were estimated to have 20 times higher odds of being in the higher sitting time group than those in the NYHA class II.
Depressed participants with HF reported less than an hour per day of being physically active. Alosco et al18 reported that depression was an independent predictor of low physical activity levels in HF, with 587 minutes per day spent being sedentary, which is higher than the median sitting time of 420 minutes per day we report. Moderate activity was 8 minutes per day, which is lower than the median of 210 minutes per week (30 minutes per day) in this study.18 An explanation for the differences might be due to the type of measurement. Johansson et al19 found that accelerometers counted higher levels of light-intensity activity and lower levels of moderate activity than was self-reported, suggesting that participants felt they were “working” at a higher intensity than the objective measure reported.20
Depressed patients with HF would be expected to spend less time being active. However, the difference of 52 minutes per day in this sample compared with reports of 6.1 to 7.2 hours per day in the general population19,21 indicates how inactive depressed patients with HF are. Light activity levels were very low (median of 1 hour per week) when compared with the general population of 2.8 to 3 hours per day.19,21 Moderate-intensity activity was also very low, with a median time of 30 minutes per day compared with 2.1 hours per day.21
Sitting time in this study (7 hours per day) was higher than reported for adults in the general population (4.7 hours per day) but consistent with trends that adults spend more time sitting as they age.22 The related finding that minutes sitting was the only predictor chosen in the AIC model for depression provides support for activity engagement and is consistent other studies that report an association between sitting time and depression.23 Sitting time is an important public health concern because research consistently shows that increased sitting produces worse health outcomes even in those who exercise regularly.23 At the same time, decreasing sitting time by as little as 1 hour per day has the potential to decrease the risk of mortality by 5%,24 suggesting that interventions to reduce sitting time may have additional important outcomes in all sedentary populations.
Our results indicating that gender is a significant predictor of pain interference in those with HF and depression, with women reporting higher levels of pain interference, supports similar pain findings in other populations.25–27 Although there is a debate about gender differences in pain within the scientific community, women seem to be more sensitive to pain than men.26 In turn, special consideration of pain experiences among women with HF and depression is needed in clinical practice.
The generalizability of these data to other populations is limited by the small sample size and lack of minority participation. Self-reported measures of physical activity may lead to overestimating the actual amount of time spent exercising20 and may have been complicated by HF symptoms in this population. The description of moderate activity being “physical activities make you breathe somewhat harder than normal” may have been misleading.
Discussion of current levels of activities is an important starting point in HF care and treatment, for making small but meaningful changes that may enhance symptom management. Further research is needed to determine how best to increase time spent being active while decreasing sitting time and how much of an increase is necessary to have a meaningful decrease in pain and depressive symptoms in this population.
- Clinicians need to assess general activity and sitting time.
- Develop a plan with small changes to increase activity
- Follow up with patients to reassess activity levels
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Keywords:Copyright © 2017 Wolters Kluwer Health, Inc. All rights reserved
depression; heart failure; pain; physical activity