The daily movement pattern and physical activity in a Swedish cohort of heart failure patients

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University of Örebro Medical programme Bachelor’s thesis, 15 Hp January 2020

Author: Philip Ingemarsson Mentor Mats Börjesson Center for health and performance (CHP) at the Department of food and nutrition, and Sport science, Sahlgrenska University hospital

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Abstract

Introduction

In patients with heart failure (HF), routine physical activity (PA) has a negative correlation with future HF-specific hospitalization rate. Daily activity and exercise training are

recommended for patients with chronic HF. Nevertheless, only a few studies have objectively investigated the daily movement pattern in individuals with chronic HF, indicating that physical inactivity in patients with HF is common.

Aim

To present descriptive data on a cohort of patients with chronic heart failure, including the distribution and amount of physical activity and sedentary behavior pattern.

Material and methods

To objectively measure the daily movement pattern of HF patients, accelerometers were used. The participants were told to wear the device for 7 consecutive days. Out of 242 participants, valid accelerometer data was found in 132 patients, and complete data for 97 of those.

Result

In median, 24.9% of the daily time was spent in light intensity physical activity (LIPA) and 2.7% in moderate- and vigorous physical activity (MVPA). Patients post-acute myocardial infarction (AMI) and patients with high values of NT-proBNP spent significantly less time in MVPA than their counterparts. 44.7% fulfilled the PA recommendations of 30 min MVPA on most days of the week. The young group, post-AMI patients, and patients with high values of NT-proBNP fulfilled the recommendations to a lesser extent, although not significant. Conclusion

Of all patients, they spent only 2,7% of the day in MVPA. Patients with post-AMI and patients with high NT-proBNP levels were least physically active. In addition, less than half of the patients fulfilled the general PA recommendations. Furthermore, since the results show a significant difference between particular subgroups in PA activity, this study highlights the importance of evaluating the daily movement patterns in HF patients. Implementation of more methods to increase the PA in this patient group is necessary.

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Abbrevations

HF – Heart failure

HFrEF – Heart failure with reduced systolic left ventricular function HFpEF – Heart failure with preserved systolic left ventricular function PA – Physical activity

Peak VO2/VO2 max – maximum rate of oxygen consumption

NYHA classification – New York Heart Association functional classification MVPA – Moderate- and vigorous intensity physical activity

LIPA – Light intensity physical activity SED – Sedentary

MET – Metabolic equivalent of task

SCAPIS – Swedish CardioPulmonary bioImage Study ECG – Electrocardiography

KCCQ – Kansas City Cardiomyopathy Questionnaire Cpm – Counts per minute

VM – Vector magnitude TPA – total physical activity EF – ejection fraction

NT-proBNP – N-terminal pro-Brain Natriuretic Peptide MI – myocardial infarction

AMI – Acute myocardial infarction Dnr – Diarienumber

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Index

... 0

ABSTRACT ... 1

Introduction ... 1

Aim ... 1

Material and methods ... 1

Result ... 1

Conclusion ... 1

ABBREVATIONS ... 2

INTRODUCTION ... 4

AIM ... 6

MATERIAL AND METHODS ... 7

STUDY POPULATION ... 7

MEASUREMENT OF PHYSICAL ACTIVITY AND SEDENTARY BEHAVIOR... 8

OTHER MEASUREMENTS ... 9

OTHER ... 10

RESULTS ... 11

DISCUSSION ... 14

DAILY MOVEMENT PATTERN ... 15

FULFILLMENT OF RECOMMENDATION ... 17

STRENGTH AND LIMITATIONS ... 19

CONCLUSION ... 20

ACKNOWLEDGEMENTS ... 21

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Introduction

In high-income nations, heart failure (HF) is the most common diagnosis among patients aged 65 years or older [1]. In Sweden, the estimated prevalence is 2.2%, which is in line with other developed countries in the western world, and in 2010 the mean age for diagnosis was 77 ± 13 years [2,3].

Chronic HF is defined as a clinical syndrome characterized by symptoms such as fatigue, breathlessness and ankle swelling, that may be followed by signs as peripheral edema, pulmonary crackles and elevated jugular venous pressure. These symptoms and signs are caused by functional and/or structural cardiac abnormalities, resulting in higher than normal intracardiac pressures during stress or at rest and/or reduced cardiac output. Chronic HF may be present with reduced (HFrEF) or with preserved systolic left ventricular function (HFpEF) [3].

The etiology of heart failure is diverse. All states affecting the heart may eventually lead to HF. The by far most common cause of myocardial disease, responsible for initiation of HF in around 70% of patients, is coronary heart disease. Functional deterioration of the heart, caused by acute or chronic ischemia, damage or loss of the myocardium, development of atrial fibrillation or other tachyarrhythmias, and increased vascular resistance with

hypertension, are all major causes of HF. Cardiomyopathies accounts for 10% of the initiating causes and valve disease for another 10% [4,5]. Thus, common risk factors for developing HF are obesity, diabetes and hypertension, all of which are common in the western world [5]. From the first recorded diagnosis, the 5-year survival rate in Sweden is estimated to 48% and co-morbidity and hospitalizations are common [2]. However, many studies claim that these figures can be affected with physical activity (PA). The beneficial effects of regular PA on chronic HF have been extensively studied. Aerobic exercise, continuous and interval,

improves peak VO2 with a mean of 20% in HF [3,6,7] and improvements in walking distance during 6 minutes walking test can be seen [6]. Aerobic exercise improves cardiac function through elevated stroke volume, chronotropic response, peak heart rate resulting in increased cardiac output [4–7]. Endothelial dysfunction has been observed with aging and also in multiple chronic disease states, including chronic HF. Regular aerobic exercise has been found to result in a shear-stress-mediated improvement in endothelial function and hence

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improve vascular function [7,8]. The effects on the endothelial function improve the blood flow in metabolically active skeletal muscles, which also improves the function of the active muscle, and thus daily activities can be performed at a lower degree of maximum voluntary contraction. This theoretically results in reduced energy requirements for the heart [6,7]. Resistance or endurance PA also improves autonomic control and improves inflammatory state with decreased levels of inflammatory cytokines [4,6,7,9]. In patients with HF, routine PA has a negative correlation with future HF-specific hospitalization rates and has shown to improve health-related quality of life [3,4,6,10,11]. Reduced mortality rate has also been seen as an effect of PA [3–6,8,11].

Because of all the positive effects of training on HF patients, daily activity and exercise training are recommended for all with chronic, stable HF. No evidence suggesting limited training for particular subgroups of HF patients exist (NYHA class, etiology, medication etc.) [5,11]. The national exercise recommendations for HF patients in NYHA I-III, in Sweden are: aerobic exercise, continuous or interval, 3-5 days a week (40-90% of VO2max, during 30-60 minutes per session) and sometimes muscle strengthening exercise 2-3 days a week is included [6]. These recommendations are largely the same as those for healthy, non-HF individuals in Sweden [12], and also elsewhere the world [13,14].

Although the evidence is consistent with that physical exercise is beneficial for patients with chronic HF, only a few studies have objectively investigated the daily movement pattern and fulfillment of PA recommendations in individuals with chronic HF. Previous studies indicate that physical inactivity in patients with symptomatic HF is common and that fulfillment of PA recommendations may be low [4,15–19].

By using an PA assessment tool that is objective (e.g. accelerometers), it is possible to capture different aspects of the patients’ daily movement pattern, including distribution and volume of both sedentary time and activity time throughout the day [20]. In a study that compared self-reported and accelerometer measured PA data in HF patients, the subjects engaged in <1 minute of moderate- and vigorous intensity PA (MVPA) a day (>3.0 METs (metabolic

equivalent of task)) and none met the national guidelines of ≥150min/week. Using self-report, 38% of the HF patients met the PA recommendations [16]. A study using only self-reported data described relatively high PA levels and fulfillment of recommendations [21].

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An American study on 204 HF subjects, with an average age of 60 ± 11.5 years, using accelerometers reported 10.2 ± 10.5 minutes of MVPA per day and only 12.6 % met the national recommendations [15]. One resembling study describes similar results of high sedentary time and low levels of MVPA [18]. Current data, measured with accelerometers, also report that whites, men, low NYHA class, subjects with better physical function and high self-efficacy have higher levels of PA [15,18,22,23], and that PA in HF patients is lower than in the healthy population [24]. Previous studies show no clear results whether ejection

fraction (EF) affects the level of PA in HF patients or not [15,18].

However, no studies using accelerometers (a measuring tool described in more detail in the section “measurement of physical activity and sedentary behavior”) have been done on Swedish HF patients. Furthermore, detailed data regarding the distribution and amount of the different aspects of patterns in daily movement are lacking. This is important in this target population since physical inactivity contributes to progression of the disease [4]. In addition, the proportion of HF patients reaching the national recommended levels of PA in Sweden is unknown, and also if the daily movement patterns in HF patients differ from that in the healthy population.

Aim

The aim of the present study was to present descriptive data on urban, 34-75 years old

Swedish women and men with chronic heart failure, including the distribution and amount of physical activity and sedentary behavior pattern. Analysis of fulfillment of national PA recommendations in this cohort was also included. This is an important knowledge since inactivity results in negative outcome in this patient group.

The second aim was to analyze potential variations of PA in subgroups, with regard to age, sex, EF, NT-proBNP and post-AMI.

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Material and Methods

Study population

This study was a descriptive cross-sectional, cohort study, conducted at the Sahlgrenska University Hospital in Gothenburg, Sweden. Initially, patients eligible for inclusion in the study were 18 to 55 years at time for diagnosis with HF at the Sahlgrenska university hospital, between 1997-2016. Subjects over 55 years of age by the time of diagnosis and patients living outside the catchment area were not included. Totally 1367 patients were entered in this part of the study. All data were extracted from the medical records and entered into a database. When entering the data into the database the personal identity numbers were exchanged with codes. The code list was kept confidential in a locked cabinet with only access by the few people working with this study. Patient data was handled according to GDPR.

In the second part of data collection, patients alive from the database without drug abuse or muscle dystrophy affecting the myocardium, and were willing to participate, were called to an appointment.

Figure 1. A flowchart describing the selection of study population and loss of participants. From the original database

with 1367 HF patients, 242 subjects agreed to participate in the study. Of those, 132 had valid accelerometer data and were included in the analysis. When analyzing PA data together with information about EF, post-AMI and smoking habits, 97 patients were used.

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During this visit the patients’ blood pressure, weight, length, and waist circumference were measured, an ECG was performed and blood samples were taken. The patients also filled out the Kansas City Cardiomyopathy Questionnaire (KCCQ) and drug information was obtained. A population sample of 242 patients, aged 34-74 years, were willing to participate in the present study. Out of these, 172 (71%) individuals were men and 70 (29%) were women. Valid accelerometer data was found in 132 subjects. Information about EF, post-AMI and smoking habits were collected from the original database, but possible to extract only for 176 of the initial 242 participants. Out of these 176 patients, 97 had valid accelerometer data. Therefore, analyzes made with these variables (EF, post-AMI, smoking habits) only include 97 participants. The rest of the analyzes include all patient with valid accelerometer data (n=132) (figure 1).

Measurement of physical activity and sedentary behavior

To be able to compare the present study with the SCAPIS-pilot study (described in the section “other”), most of criteria, thresholds and methods used for assessing PA are the same as in the SCAPIS-pilot study [25,26].

Specifically, to objectively measure the daily movement pattern of HF patients, Axivity AX3 accelerometers (Axivity Ltd., Newcastle upon Tyne, UK.) were used. An objective record of the frequency, duration and intensity of the subject’s movements were provided, by recording accelerations in the participant’s movement. The data was summarized in units called counts. The Axivity AX3 accelerometer is a lightweight (11 g) and small (23 x 32.5 x 7.6 mm)

electronic device. The participants were told to wear the device for 7 consecutive days, all day long (except during water activities), in an elastic belt on the right hip [25]. In order to

distinguish between sleep and sedentary time, the patients had to write in diaries what times they were sleeping.

For initialization and data extraction of the sensor, the OmGUI software (Axivity Ltd., Newcastle upon Tyne, UK) was used. The data was initialized to record with a sample rate of 50 Hz and raw data was then extracted and resampled to 30 Hz. Using MATLAB R2018b (MathWorks, Natick, MA, USA), the data was then processed to ActiGraph counts with an epoch length of 60 seconds [27].

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Data processing

600 minutes of valid daily monitor wear, on at least 4 days, was set as a minimum

requirement for the data to be included [28]. 60 continuous minutes without movement (0 counts per minute (cpm)), with allowance of counts between 0-200 for a maximum of 2 minutes, was defined as non-wear time [26]. To get wear time, non-wear time was subtracted from 24 hours.

The 60-s data from all three axes was combined into a vector magnitude (VM) [26]. The daily movement pattern and PA is given in percentage of the day spent in particular intensity-specific categories [15,25]. Sedentary behavior was defined as absence of, or very low registrations <200 cpm [29], cpm between 200 and 2689 recognized as light intensity physical activity (LIPA), and cpm ≥2690 defined as moderate- and vigorous intensity physical activity (MVPA) [30]. Furthermore, time spent in LIPA, MVPA and mean counts per minute is presented [30]. Mean cpm to express total physical activity (TPA) for the triaxial analysis was calculated as the mean of the VM epochs, including non-wear time. Fulfilment of MVPA recommendations was also analyzed. Swedish national guidelines for PA are currently recommending at least 150 minutes a week of MVPA. The activity should preferably be spread out on most of the days of the week (5 out of 7) and performed in bouts of at least 10 minutes [12]. Because this is rather complex to catch, we defined the amount of the study population meeting the recommendations, as follows:

Accumulating 150 minutes of MVPA per week, and/or accumulating 30 minutes of MVPA per day on at least 5 out of 7 days of the week.

Other measurements

BMI (body mass index) was calculated by dividing weight (kg) by square height (m^2). Age was categorized into a young (34-58 years) and an old (59-74 years) age group, based on the median. From the database with HF patients stored at Östra hospital, information about ejection fraction (EF) and potential previous myocardial infarction (post-MI), were collected. Also, information about the patients’ smoking habits was extracted from the database. EF was dichotomized into EF <40% and EF ≥40% and NT-proBNP was dichotomized, into low (≤400 ng/L), and high (>400 ng/L) level groups, based on median.

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Statistical analysis

Descriptive data is mainly presented as median with 25th – 75th percentile (Q1-Q3) and as proportions, since most of the variables were skewed.

To compare sex differences in descriptive data, independent Mann-Whitney U-test was used. The same test was also used to compare variations in percentage of time per day spent in different PA intensity levels between age, sex, EF-groups, if patients had had AMI or not, and NT-proBNP-levels. Chi-square independence test was used to compare fulfillment of PA recommendations between subgroups.

The level of significance was set at p<0.05 for all analyses. Statistical analyses were performed with SPSS (IBM Corp. Released 2019. IBM SPSS Statistics for Macintosh, Version 26.0. Armonk, NY: IBM Corp.).

Ethics

PA data were collected with accelerometers, which means very little discomfort for the patient, but may, on the contrary, have positive effects.

All information about the patients were stored in a database, with codes assigned to the patients instead of personal number. Thus, the data was anonymously stored to ensure that no tracking was possible. This was done to protect the participants.

In 2012-12-20, Dnr 856-12, the Ethics board of Gothenburg (“Regionala

etikprövningsnämnden Göteborg”) approved collection of the original database, from which the study population and some of the data in this study were retrieved. This present study was approved by the Ethics board of Gothenburg (“Regionala etikprövningsnämnden Göteborg”) in 2016-06-28, Dnr T606-16.

Other

When the result was analyzed, the figures was put in context to the results of the SCAPIS-pilot study. The SCAPIS-SCAPIS-pilot study presented descriptive data on healthy, urban, Swedish women and men aged 50-64 years, regarding distribution and amount of sedentary and PA

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behavior patterns, estimated with accelerometer [25]. Therefore, it is feasible to discuss the results in this study in comparison to the SCAPIS-pilot study.

Results

Of the 242 subjects participating in the study, 132 patients had valid accelerometer data and were therefore included in the analysis.

To be able to distinguish between sleep time and sedentary time the participants wrote the times they were sleeping in a diary. Unfortunately, the subject information about sleep in the diaries did not match the accelerometers’ objective assessment of the same. Thus, sleep time was impossible to discriminate from sedentary time and sedentary time could thus not be analyzed in this present study. The results will therefore only focus on PA and fulfillment of recommendations.

Out of the 132 patients with valid data, 38 subjects (28.8%) were women. The median (Q1-Q3) age overall was 59 (54.25-63.75) years, with a total range of 34-74 years. 74.2% of the subjects were classified as overweight or obese. 23% were smokers and another 13.4% former smokers. In total, 15.5% of the population had previously had AMI, 28.1% had low EF (<40%) and 26.8% had high NT-proBNP value (>400 ng/L). Table 1 gives further details of the study population with regard to sex.

Table 1. Characteristics of the study population data with regard to gender.

Study population Men (n = 94) Women (n = 38) Age (years) 59.0 (55.0-64.0) 58.5 (51.0-62.0) Weight (kg) 88 (82.0-99.0) 70.5 (65.0-75.0)# Height (cm) 179.0 (172.0-183.0) 166.5 (161-169.5)# Waist (cm) 105.0 (98.0-114.0) 92.0 (86.0-101.0)# BMI (kg/m^2) 28.2 (25.6-32.0) 25.7 (24.2-29.3)#

BMI ≥25 (% of study population) 80.9 57.9

Regular/Daily smokera (% of study

population) 24.6 21.4

NT-proBNP (ng/L) 120.0 (54.0-308.0) 248.5 (86.5-807.0)#

EFb (%) 50.0 (35.0-59.5) 54.5 (40.0-60.0)

Data presented as median (Q1-Q3) or percent of study population.

#Significant gender difference (p<0.05, independent Mann-Whitney U-test). a24 values for men and 10 values for women are missing.

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Median wear time of the accelerometer for all participants was 87% (80-91%), with no significant difference between subgroups. The patients in this study (all subgroups) spent in median 24.9% (20.7-30.5%) of their daily time in LIPA and 2.7% (1.4-4.2%) in MVPA (Table 2). No difference was found regarding time spent in different PA intensity levels between gender. The younger age group was more physically active, both regarding LIPA and MVPA, but no statistical significance was discovered (p=0.08). Similar situation was seen for the EF subgroups, with patients having EF ≥40% as being more physically active.

Nevertheless, no major discrepancy between EF groups in time spent in different PA intensity levels was found. The patients who had suffered an AMI in the past spent less time in both LIPA and MVPA than the group with no previous cases of AMI, with the difference in time spent in MVPA between the groups was significantly different (p=0.042). A similar

relationship was detected with the NT-proBNP groups; patients with a value higher than 400 ng/L spent significantly less time in MVPA than the patients with NT-proBNP levels lower than or equal to 400 ng/L (p=0.039). Less difference between the groups was found regarding

Table 2. Daily movement pattern in percent of the day in different intensity levels, and in minutes per day, presented for subgroups and all patients.

LIPAx (%) LIPA (min/day) MVPAxx (%) MVPA (min/day)

All 24.9 (20.7-30.5) 359.2 (298.1-438.7) 2.7 (1.4-4.2) 38.6 (20.6-59.8) Gender Men 25.1 (20.6-30.6) 361.8 (297.2-440.3) 2.7 (1.8-4.3) 39.4 (25.6-62.0) Women 24.8 (21.3-30.3) 357.0 (306.3-436.6) 2.6 (1.1-3.5) 36.9 (15.6-50.9) Age (years) 34 – 58 25.2 (21.3-30.1) 363.3 (306.9-439.8) 2.9 (2.0-4.3) 42.0 (29.0-61.4) 59 – 74 23.8 (19.8-29.9) 343.4 (285.0-430.5) 2.4 (1.2-3.5) 34.6 (17.1-50.4) EF (%)a <40 25.2 (21.4-31.2) 363.3 (307.6-449.1) 2.6 (1.4-5.1) 37.3 (20.0-73) ≥40 26.6 (19.4-31.5) 383.3 (278.6-453.1) 2.9 (1.7-4.3) 42.4 (24.8-62.0) Post-AMIb Yes 23.1 (19.4-29.7) 332.8 (278.6-427.0) 2.0 (0.7-3.3) 29.0 (9.5-46.9) No 26.4 (20.7-31.0) 380.8 (297.6-446.4) 3.0 (1.9-5.0)* 42.8 (27.3-72.3)* NT-proBNP (ng/L) ≤400 25.2 (21.3-30.6) 363.3 (307.4-440.3) 2.9 (2.0-3.9) 42.0 (18.1-56.9) >400 23.7 (19.4-28.4) 340.9 (279.4-408.9) 1.7 (0.6-3.5)# 24.4 (8.4-50.9)#

Data presented as median (Q1-Q3) of individual means.

*Significant difference between Post-AMI groups, p<0.05 (independent Mann-Whitney U-test) #Significant difference between NT-proBNP groups, p<0.05 (independent Mann-Whitney U-test)

an=89, out of 132 participants

bn=97, out of 132 participants

xLIPA – Light intensity physical activity

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time spent in LIPA. TPA, in median, for all the patients was 387.5 (265.8-490.0) cpm, with no significant differences between subgroups.

Of the two requirements for fulfillment of national recommendations, 150 minutes of MVPA per week and 30 minutes of MVPA per day on most days of the week, the latter is the

criterion that corresponds most closely to the national guidelines for PA. The number of patients reaching 30 minutes per day on most days of the week is therefore of more interest. For the entire study population, the median time of daily MVPA was 38.6 (20.6-59.8) minutes. Thus, 75.0% of the patients accumulated at least 150 minutes of MVPA per week, but only 44.7% reached 30 minutes of MVPA per day on most days of the week (Table 3). Men had higher percentage of fulfillment than women. Also, patients with high EF showed greater fulfillment of recommendation number one than the patients with low EF (78% vs 72%), and patients who had gone through an episode of AMI reached the recommendations of 150 minutes/week in a lesser extent than those who had no previous episode of AMI (60% vs 79%). Even though there was a distinction between these subgroups, no significant difference

Table 3. Fulfillment of MVPA recommendations in all participants and in different subgroups, given in percent (%).

(1) 150 min/week (2) 30 min/day on most days of the week*

All 75.0 44.7 Gender Men 77.7 45.7 Women 68.4 42.1 Age (years) 34 – 58 86.4 52.5 59 – 74 65.8# 38.4 EF (%)a <40 72.0 48.0 ≥40 78.1 48.4 Post-AMIb Yes 60.0 33.3 No 79.3 52.4 NT-proBNP (ng/L) ≤400 83.9 47.3 >400 52.9## 35.3

*At least 5 out of 7 days. For participants with less than 7 valid days, the requirement is at least 4 out of 6 day, 4 out of 5 days, or 3 out of 4 days.

#Significant difference between age groups, p<0.05 (Chi-Square independence test).

##Significant difference between NT-proBNP groups, p<0.05 (Chi-Square independence test).

an=89, out of 132 participants.

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was identified. Fulfillment of 150 min/week recommendations was significantly different between the age groups, with 65.8% of the patients in the older group reaching the requirements while 86.4 % of the younger patients fulfilled these recommendations (p=0.006). Strong statistical significance was also found between the NT-proBNP groups regarding fulfillment of 150 min/week of MVPA. The group with lower levels of NT-proBNP had higher fulfillment of these recommendations than the group with high values (p<0.001).

Fulfillment of the recommendation of 30 min/day of MVPA on most days of the week, in a better way reflects the actual fulfillment of national PA guidelines, as the activity has to be spread out on several days of the week. The percentage of the study population reaching this goal was much lower for all the patients (44.7%) compared to the recommendation of 150 min/week of MVPA. Since this criterion is a better value of fulfillment of national

recommendation guidelines, the results show that 44.7%, rather than 75%, are reaching the national PA goal. Although lower percentage of fulfillment, similar patterns of difference as for the recommendations of 150 min/week between the subgroups, were found, with the exception that both EF groups had almost exactly the same percentage of fulfillment of 30 min/day on most days of the week (48.0% vs 48.4%). Men and younger patients fulfilled the recommendations to a greater extent. The number of post-AMI patients reaching the goal was smaller than those with no previous AMI episode (33.3% vs 52.4%) and patients with high values of NT-proBNP had lower fulfillment numbers than those with a low value (35.3% vs 47.3%). Although differences, no statistically significant difference between the subgroups was detected for the recommendations of at least 30 min of MVPA per day on most days of the week.

Discussion

A main finding in this study was that fulfillment of the national recommendations of PA for the whole study population was low. Not even half of the patients (44.7%) reached 30 minutes of MVPA on most days of the week. Another main finding was that NT-proBNP level and whether the patients had previously had AMI or not, was associated with how physically active the patient was.

As previously stated, sedentary behavior pattern was not possible to interpret, due to mismatch between the subjective description and the objective measurement of sleep time.

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Hence, the goal to describe sedentary behavior among chronic HF patients could not be fulfilled.

Daily movement pattern

Only a few studies have objectively assessed PA among HF patients with accelerometers. Variations in wear time, age groups, various cut-points for different PA intensity levels and diverse accelerometer models and settings complicate comparison to prior studies.

In the present study, we found that, in median, 24.9% of the day was spent in LIPA and 2.7% was spent in MVPA. TPA was 387.5 cpm. Our results are much higher, in terms of PA, than reported by Pozehl et al [15]. Importantly, we found no considerable difference in movement pattern between genders. Previous studies have reported higher activity levels in men [15,19], but another study was consistent with ours in finding no gender difference [18].

Time spent in MVPA was in this study discovered to significantly be associated with NT-proBNP values and it was also found that a patients PA level varies depending on if the patients had previously had an episode of AMI or not. The high-level BNP-group only spent 1.9% of the day in MVPA while the low-level group spent 2.9% of the day in MVPA. Also, the fulfillment of the national recommendations of 150 min/week in MVPA was significantly lower in the high-level NT-proBNP-group (52.9% vs 83.9%). This may be explained by a more severe disease in those with higher values of NT-proBNP, and hence are more limited being physically active. Even if the high-level group did not have very high NT-proBNP values (range 403-35000 ng/L) the very limited MVPA compared with recommended, shows that patients with HF, also without high neurohormonal activation, have very limited PA. Further, patients with no previous event of AMI were more physically active, and fulfilled the PA recommendations to a greater extent than the patients with an episode of AMI in the past. Probably, these patients had habits of being inactive already before the AMI, and have not changed their behavior after that. To the best of our knowledge, there are no earlier studies investigating MVPA with correlation to NT-proBNP and AMI, and thus, the results showing an association between these parameters and PA are novel findings.

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The present study showed some correlation between percentage of EF and PA, but the difference between the two EF-groups was not significant. This is consistent with previous studies available, who examine EF and PA in HF patients, showing quite diverse results whether EF percentage affects PA pattern or not [15,18,31]. Probably, since the results of different studies vary, the association between EF and PA is relatively modest. More research is necessary on this parameter.

Even though the method and the material used in this study was mostly the same as in the SCAPIS-pilot study, comparison between the two studies is complicated. First of all, in the SCAPIS-pilot study the patients were told to not wear the accelerometer during night time [26]. In this study, the patients were told to wear the devise even during sleep and to note sleep time in a diary. Thus, sleep is included in wear time in this study, but excluded in the SCAPIS-pilot study. There are studies reporting that if the participant wear the accelerometer for a long time, the wear time will increase even more, because they remember to use it [32]. Therefore, wearing the accelerometer during sleep may increase the wear time, in some cases. The SCAPIS-pilot study also used different accelerometer models and uniaxial analysis. Studies comparing triaxial (used in this study) and uniaxial (used in SCAPIS-pilot study) analysis indicates that PA values become higher when using triaxial accelerometer analysis [33]. To further notice is that the SCAPIS-pilot study had a population with an age range from 50 to 65 [25], while this study had a range from 34 to 74. Still, the median age was very similar. Most medians of the descriptive facts about the study population (e.g. age, BMI, weight), except from smoking habits, were the same in the two studies [25]. If comparison is still to be made, the study population in SCAPIS-pilot spent in median 21.0% of the day in LIPA and 2.3% of the day in MVPA (in the SCAPIS-pilot study, data is presented as percent of wear time, while in this present study data is presented in percent of the day. Therefore, the SCAPIS-pilot data is converted to percent of the day here) [25]. That is lower than the results of this study (24.9% LIPA, 2.7% MVPA), indicating that the study population of the present study had a more active daily movement pattern than the population in the SCAPIS-pilot study.

However, there are probably many reasons for this outcome. In addition to all the aspects previously mentioned about why it is difficult to compare the results, one possible explanation is selection bias. The participants in this study were derived from an already existing cohort, where those who volunteered to participate were possibly selected in terms of PA-behavior.

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They represent a selected more active subgroup, most certainly. They also may have been extra motivated to be physically active when they participated in the study. The study

population in SCAPIS-pilot was randomly selected. Therefore, drawing conclusions from this comparison should be done with caution.

Fulfillment of recommendation

Two different versions of the national guidelines were set as requirements to fulfill the PA recommendations. The recommendation of 150 min/week of MVPA was more often met compared with the recommendation of 30 minutes of MVPA/day on most days of the week (75% vs 44.7%). Since the recommendation of 30 minutes per day on most days of the week better reflects the national PA guidelines, as the PA must be spread out over several days, 44.7% fulfillment of recommendations is the main result of the two numbers presented in this study.

The percentage of patients fulfilling the 150 min/week criterion in this study is higher than obtained in previous studies evaluating the fulfillment of these recommendations among HF patients [15,16]. The percentage of fulfillment is also higher than in the SCAPIS-pilot study, where 72.5% of the healthy study population reached this goal [25]. Furthermore, also when comparing fulfillment of 30 min per day on most days of the week, the number of participants reaching the recommendations in this study is higher than in the SCAPIS-pilot study (44.7% in this study, compared to 35.3% in SCAPIS-pilot) [25]. Once again, it is difficult to compare the results in this study to the results in the SCAPIS-pilot study due to the reasons pointed out earlier. Additionally, it is very complex to evaluate fulfillment of national PA

recommendations with accelerometers in general. Therefore, these numbers are difficult to apply to the reality and also to conclude whether the HF patients in this cohort actually had higher fulfillment of recommendations than the healthy cohort in the SCAPIS-pilot study. However, we know for certain that, despite probable selection bias, still a minority of the study population fulfilled the criteria.

Although higher figures than earlier findings, a large proportion of the patients did not reach the recommended levels of PA. Interestingly, even though not significant (probably due to the low number of participants), patients with a previous episode of AMI did not fulfill the

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alarmingly and may indicate that these patients did not start to increase their PA even after an infarction. Increased PA the year after an MI is associated with decreased mortality and is thus an important change of lifestyle [34]. This also indicates that the clinics have to become better at informing the patients about, and emphasize the importance of PA. Thus, this is highly clinically relevant findings.

No difference between EF groups were found for the second recommendation (30 min of MVPA per day on most days of the week), indicating that preserved systolic function or not does not have such a great impact on the daily movement pattern.

The young group and the group with low levels of NT-proBNP fulfilled the recommendations of 150 min per week to a significantly greater extent than the old group and the group with high NT-proBNP levels. The difference was also noticeable for fulfillment of

recommendation number 2, even though not significant. So, it seems like older individuals and patients with high NT-proBNP values have, in high extent, difficulties in being physically active enough to reach the national recommendations. This is probably associated with a more advanced disease or ageing itself in these subgroups, leading to difficulties in being physically active.

Although one should be careful in drawing conclusions from this study, it is obvious that the fulfillment of the recommendations in this population is low. Furthermore, it seems like patients with more advanced HF and post-AMI HF tend to be more physically inactive. This indicates that the healthcare has to continue working with getting patients to activate themselves. More energy and emphasis need to be put into this. Thus, this is a highly important clinical finding. Especially since there are reports indicating that PA levels may decrease further in the future [35]. Powerful and effective methods in the society and

healthcare that increase the levels of movement, both among healthy individuals and patients, need to be implemented. An example of such a method is PA on prescription (PAP). A model used in Sweden, shown to improve the level of movement in patients [36]. This could be one way to increase PA levels in HF patients.

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Strength and limitations

A strength with the present study was that all the PA data was objectively assessed with accelerometers, rather than subjective evaluation. Thus, the accelerometer provides a valid estimate of the daily movement pattern. Furthermore, systemic bias was reduced by collecting PA data throughout the year, and thus diminish the impact of seasonal variability. At the same time, gathering data at different times increase the risk of systematic errors. For example, a possible scenario could be that the majority of the PA data from the group with low NT-proBNP levels was collected in the summer, while the majority of PA data from the high-level group was collected in the winter. Thus, the outcome will be affected, since we can assume that the level of movement and PA is higher during summer time for most patients. Another weakness with this study is the limited number of participants, especially in the groups with EF, AMI and smoking habits. The dropout rate was relatively high and so also the number of subjects without valid accelerometer data. The low number of patients increase the risk of findings being random. Moreover, as stated before, the patients in this study were selected because they fitted the requirements and wanted to participate. Likely, those who wanted to participate may have felt motivated to be more active when they got to be part of a study. This causes selection bias and may affect the outcome. In addition, there was a skewed distribution between men and women.

One more thing to keep in mind while analyzing the results, is that the accelerometer is not a perfects tool for PA measurement. Inability to distinguish between standing and sitting is one limitation [25]. Additionally, measuring the fulfillment of national recommendations is rather complex. A good thing to do would be to adjust some part of the national PA

recommendations to fit accelerometer measurement, since the use of accelerometers increases. This could facilitate evaluation of fulfillment of the recommendations. Furthermore, when doing many statistical tests, one may have to adjust the statistical

significance level. That is not done in this study, and is hence something to remember when drawing conclusions from the results.

Thus, even if this study used objective measurement methods to investigate the daily

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Since the study is based on a limited cohort, one should be careful with applying the results to other HF patients in Sweden and elsewhere.

Conclusion

The main findings of this study were that only 2.7% of the day for all patients was spent in MVPA, and HF patients who had previously had an episode of AMI and patients with high NT-proBNP levels spent significantly less time in MVPA than patients with no earlier AMI episode and with low levels of NT-proBNP. In addition, a minority of the study population (44.7%) fulfilled the PA recommendations of 30 minutes of MVPA per day on most days of the week.

Unfortunately, sedentary time was not possible to analyze, and thus no result was presented on this parameter. Therefore, sedentary behavior of HF patients should be included in future research.

Furthermore, since the results show a significant difference between particular subgroups in PA activity, this study highlights the importance of evaluating the daily movement patterns in HF patients. Implementation of more methods to increase the PA in this patient group, and to increase the patients’ own will to stay physically active, is necessary.

Thus, further research about the daily movement pattern and sedentary behavior of HF patients is needed. This is crucial to be able to treat the patients in an optimized way.

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Acknowledgements

Thanks to everyone at Forskningsenheten, Östra hospital of Gothenburg, for making me feel so welcome. A special thanks to Sven-Eric Hägelind for helping me with the data sampling of the HF patients and all the work you did for making it easier for me.

Also, a great thanks to everybody at CHP for being so kind and giving me a pleasant time. Thanks to Daniel Arvidsson, Magdalena Karczewska-Lindinger and especially Jonatan

Fridolfsson for all your support during the whole time, whenever I needed help. You made the writing easier and encouraged me.

Last but not least, I will say thank you very much to Mats Börjesson for having me and letting me do this project with you, for including me in the original project, in the physical activity group at CHP, and helping me overcome the obstacles throughout the project. Your passion for public health, PA and medicine is very inspiring.

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References

1. Braunwald E. The war against heart failure: the Lancet lecture. The Lancet 2015; 385:812–24.

2. Zarrinkoub R, Wettermark B, Wändell P, Mejhert M, Szulkin R, Ljunggren G, et al. The epidemiology of heart failure, based on data for 2.1 million inhabitants in Sweden. Eur J Heart Fail 2013; 15:995–1002.

3. Ponikowski P, Voors AA, Anker SD, Bueno H, Cleland JGF, Coats AJS, et al. 2016 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure: The Task Force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC)Developed with the special contribution of the Heart Failure Association (HFA) of the ESC. Eur Heart J 2016; 37:2129–200.

4. Dickstein K, m. fl. ESC guidelines for the diagnosis and treatment of acute and chronic heart failure 2008: the Task Force for the diagnosis and treatment of acute and... - PubMed - NCBI. Eur J Heart Fail 2008; :933–89.

5. Authors/Task Force Members, Graham I, Atar D, Borch-Johnsen K, Boysen G, Burell G, et al. European guidelines on cardiovascular disease prevention in clinical practice: executive summary: Fourth Joint Task Force of the European Society of Cardiology and Other Societies on Cardiovascular Disease Prevention in Clinical Practice (Constituted by representatives of nine societies and by invited experts). Eur Heart J 2007; 28:2375–414. 6. Borland M, Schaufelberger M, Cider Å. Fysisk aktivitet vid kronisk hjärtsvikt [Internet]. In: FYSS 2017: fysisk aktivitet i sjukdomsprevention och sjukdomsbehandling. 3rd ed. Stockholm: Läkartidningen förlag AB; 2016 [cited 2019 Jun 5]. p. 1–14. Available from: http://www.fyss.se/wp-content/uploads/2018/01/Kronisk-hj%C3%A4rtsvikt.pdf

7. Whellan DJ, O’Connor CM, Lee KL, Keteyian SJ, Cooper LS, Ellis SJ, et al. Heart failure and a controlled trial investigating outcomes of exercise training (HF-ACTION): design and rationale. Am Heart J 2007; 153:201–11.

8. Warburton DER. Health benefits of physical activity: the evidence. Can Med Assoc J 2006; 174:801–9.

9. Healy GN, Matthews CE, Dunstan DW, Winkler EAH, Owen N. Sedentary time and cardio-metabolic biomarkers in US adults: NHANES 2003–06. Eur Heart J 2011;

32:590–7.

10. Taylor RS, Long L, Mordi IR, Madsen MT, Davies EJ, Dalal H, et al. Exercise-Based Rehabilitation for Heart Failure. JACC Heart Fail 2019; 7:691–705.

11. Piepoli MF, Conraads V, Corrà U, Dickstein K, Francis DP, Jaarsma T, et al. Exercise training in heart failure: from theory to practice. A consensus document of the Heart Failure Association and the European Association for Cardiovascular Prevention and

Rehabilitation. Eur J Heart Fail 2011; 13:347–57.

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sjukdomsprevention och sjukdomsbehandling [Internet]. 2011 [cited 2019 Nov 5]; Available from: http://www.fyss.se/rekommendationer-for-fysisk-aktivitet/

13. Haskell WL, Lee I-M, Pate RR, Powell KE, Blair SN, Franklin BA, et al. Physical activity and public health: updated recommendation for adults from the American College of Sports Medicine and the American Heart Association. Circulation 2007;

116:1081–93.

14. Division AGD of HPH. Australia’s Physical Activity and Sedentary Behaviour Guidelines and the Australian 24-Hour Movement Guidelines [Internet]. [cited 2019 Nov 6]; Available from: https://www1.health.gov.au/internet/main/publishing.nsf/Content/health-pubhlth-strateg-phys-act-guidelines

15. Pozehl BJ, Mcguire R, Duncan K, Hertzog M, Deka P, Norman J, et al. Accelerometer-Measured Daily Activity Levels and Related Factors in Patients With Heart Failure. J Cardiovasc Nurs 2018; 33:329–35.

16. Yates BC, Pozehl B, Kupzyk K, Epstein CM, Deka P. Are Heart Failure and Coronary Artery Bypass Surgery Patients Meeting Physical Activity Guidelines? Rehabil Nurs Off J Assoc Rehabil Nurses 2017; 42:119–24.

17. van der Wal MHL, Jaarsma T, Moser DK, Veeger NJGM, van Gilst WH, van Veldhuisen DJ. Compliance in heart failure patients: the importance of knowledge and beliefs. Eur Heart J 2006; 27:434–40.

18. Dontje ML, van der Wal MHL, Stolk RP, Brügemann J, Jaarsma T, Wijtvliet PEPJ, et al. Daily Physical Activity in Stable Heart Failure Patients. J Cardiovasc Nurs 2014; 29:218.

19. Garet M, Barthélémy JC, Degache F, Costes F, Da-Costa A, Isaaz K, et al. A questionnaire-based assessment of daily physical activity in heart failure. Eur J Heart Fail 2004; 6:577–84.

20. Ainsworth B. The Current State of Physical Activity Assessment Tools. Prog Cardiovasc Dis 2015; :9.

21. Klompstra L, Jaarsma T, Stromberg A. Physical activity in patients with heart failure: barriers and motivations with special focus on sex differences. Patient Prefer Adherence 2015; :1603.

22. Jehn M, Schmidt-Trucksäss A, Schuster T, Weis M, Hanssen H, Halle M, et al. Daily walking performance as an independent predictor of advanced heart failure: Prediction of exercise capacity in chronic heart failure. Am Heart J 2009; 157:292–8.

23. Witham MD, Argo IS, Johnston DW, Struthers AD, McMurdo MET. Predictors of exercise capacity and everyday activity in older heart failure patients. Eur J Heart Fail 2006; 8:203–7.

24. Hoodless DJ, Stainer K, Savic N, Batin P, Hawkins M, Cowley AJ. Reduced customary activity in chronic heart failure: assessment with a new shoe-mounted pedometer. Int J Cardiol 1994; 43:39–42.

(25)

25. Ekblom-Bak E, Olsson G, Ekblom Ö, Ekblom B, Bergström G, Börjesson M. The Daily Movement Pattern and Fulfilment of Physical Activity Recommendations in Swedish Middle-Aged Adults: The SCAPIS Pilot Study. PLOS ONE 2015; :15.

26. Ekblom Ö, Ekblom-Bak E, Rosengren A, Hallsten M, Bergström G, Börjesson M. Cardiorespiratory Fitness, Sedentary Behaviour and Physical Activity Are Independently Associated with the Metabolic Syndrome, Results from the SCAPIS Pilot Study. PloS One 2015; 10:e0131586.

27. Brønd JC, Andersen LB, Arvidsson D. Generating ActiGraph Counts from Raw Acceleration Recorded by an Alternative Monitor. Med Sci Sports Exerc 2017; 49:2351–60. 28. Trost SG, McIver KL, Pate RR. Conducting accelerometer-based activity assessments in field-based research. Med Sci Sports Exerc 2005; 37:S531-543.

29. Aguilar-Farías N, Brown WJ, Peeters GMEEG. ActiGraph GT3X+ cut-points for identifying sedentary behaviour in older adults in free-living environments. J Sci Med Sport 2014; 17:293–9.

30. Sasaki JE, John D, Freedson PS. Validation and comparison of ActiGraph activity monitors. J Sci Med Sport 2011; 14:411–6.

31. Jehn M, Schmidt-Trucksäss A, Hanssen H, Schuster T, Halle M, Koehler F. Association of physical activity and prognostic parameters in elderly patients with heart failure. J Aging Phys Act 2011; 19:1–15.

32. for the ISCOLE Research Group, Tudor-Locke C, Barreira TV, Schuna JM, Mire EF, Chaput J-P, et al. Improving wear time compliance with a 24-hour waist-worn accelerometer protocol in the International Study of Childhood Obesity, Lifestyle and the Environment (ISCOLE). Int J Behav Nutr Phys Act 2015; 12:11.

33. Sagelv EH, Ekelund U, Pedersen S, Brage S, Hansen BH, Johansson J, et al. Physical activity levels in adults and elderly from triaxial and uniaxial accelerometry. The Tromsø Study. PloS One 2019; 14:e0225670.

34. Ekblom O, Ek A, Cider Å, Hambraeus K, Börjesson M. Increased Physical Activity Post-Myocardial Infarction Is Related to Reduced Mortality: Results From the SWEDEHEART Registry. J Am Heart Assoc 2018; 7:e010108.

35. Ng SW, Popkin BM. Time use and physical activity: a shift away from movement across the globe. Obes Rev Off J Int Assoc Study Obes 2012; 13:659–80. 36. Kallings LV, Leijon M, Hellénius M-L, Ståhle A. Physical activity on

prescription in primary health care: a follow-up of physical activity level and quality of life. Scand J Med Sci Sports 2008; 18:154–61.

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