FIT & STRONG! PLUS: DESCRIPTIVE DEMOGRAPHIC AND RISK CHARACTERISTICS IN A COMPARATIVE EFFECTIVENESS TRIAL FOR OLDER AFRICAN-AMERICAN ADULTS WITH OSTEOARTHRITIS

M. L Fitzgibbon^1,2,3, L. Tussing-Humphreys^1,3,4, L. Schiffer³, R. Smith-Ray^3,5, A.D. Demott^3,6, M. Martinez^3,6, M.L. Berbaum^1,3, G.M. Huber7, S.L. Hughes^3,6

1. University of Illinois Cancer Center, Chicago, IL 60612; 2. Department of Pediatrics, University of Illinois at Chicago, Chicago, IL 60612; 3. Institute for Health Research and Policy, School of Public Health, University of Illinois at Chicago, Chicago, IL, 60608; 4. Department of Medicine, University of Illinois at Chicago, Chicago, IL 60612; 5. Health Analytics, Research and Reporting, Walgreen Co., Deerfield, IL, 60015; 6. Center for Research on Health and Aging, University of Illinois at Chicago, Chicago, IL 60608; 7. Physical Therapy and Human Movement Sciences, Northwestern University, Chicago, IL, 60611

Corresponding Author: Marian L. Fitzgibbon, PhD, University of Illinois at Chicago, 486 Westside Research Office Building, 1747 W. Roosevelt Rd., Chicago, IL, 60608, Email: mlf@uic.edu, Phone: 312-996-0146

J Aging Res Clin Practice 2018;7:9-16
Published online February 19, 2018, http://dx.doi.org/10.14283/jarcp.2018.3

Abstract

Objectives: The prevalence of osteoarthritis (OA) has increased in the US. We report on a comparative effectiveness trial that compares Fit & Strong!, an existing evidence-based physical activity (PA) program, to Fit & Strong! Plus, which combines the Fit & Strong! intervention with a weight management intervention. Methods: Participants included 413 overweight/obese (BMI 25-50 kg/m²) adults with lower extremity (LE) OA. The majority of the sample was African-American and female. Both interventions met 3 times weekly for 8 weeks. Primary measures included diet and weight. Results: The baseline mean BMI for all participants was 34.8 kg/m², percentage of calories from fat was high, and self-reported PA was low. Discussion: This sample of overweight/obese African-American adults had lifestyle patterns at baseline that were less than healthful, and there were differences between self-report and performance-based measures as a function of age.

Key words: Weight management, obesity, older adults, physical activity.

Purpose

Arthritis and related rheumatic conditions, including osteoarthritis (OA), affect approximately 50 million or 22% of the adult United States (US) population (1), and the majority of affected individuals are older adults. African Americans with OA have higher rates of inactivity and functional limitations than non-Hispanic whites (2-4), and African-American women with OA have approximately twice the rate of disability compared to non-Hispanic whites (5). Risk factors for OA include genetics, female sex, and obesity (6), and obesity is a strong risk factor for the incidence and progression of knee OA (7, 8). Unfortunately, the prevalence of obesity has increased significantly since the 1980s, with African-American women ≥ 60 years having the highest rates compared to non-Hispanic white women (57.5% vs. 38.2%) (9-13).
Obese individuals who have OA are usually advised to lose weight (14-16). Several studies support the combination of physical activity (PA) and weight management as central to the reduction of knee pain and limitations in mobility (17, 18), and several randomized controlled trials (RCTs) have tested the combined impact of modest weight loss with regular moderate PA compared to either PA or diet/weight management alone (17, 19-22). These studies highlight a need to test relatively simple, easily replicable evidence-based programs that combine both PA and weight management for adults with OA and to test these interventions with disadvantaged populations that have consistently higher rates of OA and obesity, such as African-American women (1, 23). To address this need, our team developed and is testing Fit & Strong! Plus.
Fit & Strong! Plus combines interventions from two successful RCTs that have shown improvements in PA (Fit & Strong!) and weight management (the Obesity Reduction Black Intervention Trial, ORBIT) (24-26). The Fit & Strong! intervention and its evidence base are described in detail elsewhere (27-29). ORBIT is a 6-month weight loss and PA intervention targeting African-American women that was successful in reducing weight by 3.0 kg in the intervention group, on average (25). In 2012, we received funding to test the comparative effectiveness of customary Fit & Strong! vs. the new Fit & Strong! Plus version using an RCT. The details of the trial design are published elsewhere (30).

Methods

Design

The Fit & Strong! Plus trial is a randomized comparative effectiveness trial that is testing whether Fit & Strong! Plus produces significantly better results than standard Fit & Strong! on weight, dietary intake, PA, physical performance, OA-associated symptoms of LE pain and stiffness, anxiety / depression, and self-efficacy for weight loss and exercise among overweight / obese adults with OA. The project was approved by the Institutional Review Board at the University of Illinois at Chicago (UIC), and all participants gave written informed consent. The trial is registered at clinicaltrials.gov (NCT03180008).

Setting

Both interventions were conducted at local community sites.

Subjects

Participants were randomly assigned to Fit & Strong! (n = 210) or Fit & Strong! Plus (n = 203) and are being followed for 18 months.

Interventions

Both Fit & Strong! and Fit & Strong! Plus are conducted in 90-minute sessions 3 times per week over an 8-week period. The first 60 minutes of both interventions consist of stretching, low-impact aerobics, and strengthening exercises with a consistent focus on lower extremity muscles. The interventions diverge in the 30-minute health education component at the end of the session. The health education component of Fit & Strong is designed to build self-efficacy (SE) related to managing pain and OA symptoms through PA, while Fit & Strong! Plus also incorporates SE for dietary weight management behaviors.

Measures

Anthropometrics: Height was measured using a portable stadiometer (Seca, United Kingdom), and weight was measured using a calibrated digital scale (Tanita Worldwide). Both height and weight were measured twice. If the two measurements were > 0.5 cm or > 0.2 kg apart, a third measurement was taken, and the mean of the two closest measurements was used. BMI was calculated as weight (kg) divided by height (m) squared. To assess body composition change, we measured waist circumference twice using a Gulick 150-centimeter anthropometric tape (Country Technology, Inc.; Gays Mills, WI, USA). If the two waist measurements were > 1 cm apart, a third measurement was taken, and the mean of the two closest measurements was used.

Dietary intake

We used the Block 2005 Food Frequency Questionnaire (FFQ) to assess dietary intake. The FFQ, which inquires about approximately 110 food items, was designed to estimate habitual intake of an array of nutrients and food groups (31). Using data from the FFQ, participants’ diet quality was calculated using the Healthy Eating Index-2010 (HEI) (32), which measures adherence to the 2010 Dietary Guidelines for Americans (DGA).

Physical Activity

PA was assessed using the Physical Activity Scale for the Elderly (PASE) (33), a valid and reliable self-report measure for older adults, with a higher score indicating greater self-reported physical activity.

Performance measures

Lower extremity (LE) strength was measured using the 30-second Chair Stand, which tests the number of full stands from a seated position a person can complete in 30 seconds with folded arms (34). Mobility was assessed using the 6-minute Walk Test, which measures functional exercise capacity (35-37).

OA Symptoms

The Western Ontario and McMaster Universities Arthritis Index (WOMAC) was used to assess OA symptoms of stiffness and pain in the hip and knee joints during daily activities and the degree to which physical functioning is affected by arthritis.

Depression and anxiety

These outcomes were measured using the GERI-AIMS, a version of the Arthritis Impact Measurement Scale that was adapted for use with an elderly population (38).

Self Efficacy

We assessed weight-related SE using the Weight Efficacy Lifestyle Questionnaire (WEL), a 20-item measure that assesses confidence to manage eating in an array of situations (39).

Statistical Analyses

We tested for differences in participant characteristics between randomization groups at baseline using t-tests for most continuous variables, Wilcoxon rank tests for income and number of chronic conditions, and chi-square tests for categorical variables. We also examined differences in anthropometrics, diet, physical activity, performance measures, WOMAC OA index, anxiety/depression, and self-efficacy by age (<70 vs ≥ 70 years) using t-tests and chi-square tests. We explored associations with diet quality, PA, and physical performance using linear regression models with multiple covariates. SAS v 9.4 was used for all analyses.

Primary Results

This study met its target recruitment goal of 400 subjects. We randomized 413 individuals: 203 to standard Fit & Strong! and 210 to Fit & Strong! Plus. Table 1 reflects the baseline demographic characteristics. As we anticipated in designing the study, our sample was primarily African-American and representative of the racial and ethnic distribution of older adults in the neighborhoods surrounding the participating Chicago Park District sites. As measured by the Block 2005 FFQ, participants reported a mean energy intake of 1579 (SD = 710) calories, the mean percentage of calories from fat was 39.9 (SD = 6.9%), and the mean HEI total score was 66.3 out of a possible 100, which is in the “needs improvement” range, but is consistent with the HEI-2010 total score reported by the USDA for a nationally representative sample of adults that were 65 years and older (https://www.cnpp.usda.gov/sites/default/files/healthy_eating_index/HEI89-90report.pdf; https://www.cnpp.usda.gov/sites/default/files/healthy_eating_index/HEI-2010-During-2011-2012-Oct21-2016.pdf).

Table 1
Participant characteristics at baseline

a. N=345 for income, N=411 for waist. For diet data, N=400; records with estimated energy <500 or >5000 were excluded from the analysis (N=13: 6 in F&S Plus, 7 in F&S). N=409 for physical activity score and 6-minute walk, and N=412 for chair stands; b. Percentage of participants reporting each type of insurance; some participants reported more than one type of insurance; c. Chronic conditions: Number of self-reported conditions currently affecting health (of 17): arthritis, high BP, heart disease, mental illness, diabetes, cancer, alcohol or drug abuse, lung disease, kidney disease, liver disease, stomach disease, blood disease, stroke or other neurologic problems, vascular disease, vision problems, hearing problems, thyroid; d. A higher score indicates greater physical activity; e. A higher score indicates greater difficulties due to OA; f. A higher score indicates greater anxiety/depression; g .A higher score indicates greater self-efficacy.

The mean score on the PASE (33) was 97.2 (SD = 61.3), which is lower than the mean scores of 169.3 (SD = 88.2) reported by Skou and colleagues (40) and 131.4 (SD = 71.1) by Martin and colleagues (41) in work with older adult samples. Participants had a low mean score of 8.7 (SD = 3.6) on the 30-second chair stand as well as a low mean score of 356.3 meters (SD = 97.1) on the six-minute walk test. On the WOMAC, participants had a mean of 5.6 (SD = 4.0) on the pain subscale, 3.2 (SD = 1.7) on the stiffness subscale and 18.0 (SD = 12.9) on the physical functioning subscale, indicating a moderate amount of OA-related impairment at baseline. The mean score for anxiety/depression measured by the GERI-AIMS was low at 2.5 (SD = 1.7). Mean overall score on weight-related self-efficacy was 134.1 (SD = 32.9), which is higher than reported for other samples of overweight/obese non-Hispanic white samples (5, 42). Mean self-efficacy for exercise was also relatively high: 7.6 (SD=2.0) on a 1-10 scale.

Differences by Age

As shown in Table 2, we tested for differences between younger (60-69 years) and older (≥ 70 years) participants on a number of measures. Younger participants had a higher mean BMI (35.3 vs. 33.6 kg/m2, p = .003), and 23% of younger participants had Class III obesity (≥ 40 kg/m2) compared to 12% of older participants. Consistent with their lower BMI, older participants also scored significantly higher on the HEI (mean=68.4 vs. 65.4, p = .009) and consumed more fiber (10.6 vs. 9.6 g/1000 kcal, p = .02). Mean scores on the self-reported WOMAC showed that younger participants perceived more OA-related impairment than older participants. This was evident across the pain (6.1 vs. 4.6, p < .001), stiffness (3.3 vs. 2.7, p = .002), and physical functioning subscales (19.1 vs. 15.6, p = .01). However, on the performance-based six-minute walk, younger participants had a better mean score than older participants (363.9 m vs. 338.8 m, p = .02).

Table 2
Participant characteristics at baseline by age

a. Ns differ for some variables due to missing data; see Table 1; b. From t-tests with pooled variance for continuous variables and chi-square tests for categorical variables; c. A higher score indicates greater difficulties due to OA; d. A higher score indicates greater physical activity; e. A higher score indicates greater anxiety/depression; f. A higher score indicates greater self-efficacy.

Finally, we used linear regression models with multiple covariates to explore possible predictors of diet quality, PA, and performance measures at baseline (Table 3). The chosen predictors explained a relatively small percentage of the variance for the HEI-2010 (R2=0.06) and self-reported PA (R2=0.07), somewhat more for chair stands in 30 seconds (R2=0.12) and a substantial percentage for six-minute walk distance (R2=0.29). None of the selected predictors were significantly associated with the HEI-2010 score at baseline. However, increased age was associated with lower self-reported PA (b=-1.69, p = .002), a shorter 6-minute walk distance (b=-3.38, p < .001), and fewer chair stands in 30 seconds (b=-0.08, p = .01). A higher BMI predicted a shorter 6-minute walk distance (b=-4.70, p < .001) and fewer chair stands (-0.08, p =.02). Married participants had higher self-reported PA (b=18.44, p=.009), but did not have significantly higher performance scores. A higher score on the WOMAC (more severe OA symptoms) predicted a shorter 6-minute walk distance (b=-1.16, p < .001) and fewer chair stands (b=-0.04, p < .001).

Table 3
Predictors of diet quality, physical activity, and performance measures

From linear regression models with diet and physical activity variables as the dependent variable and the variables shown as independent variables. For diet data, N=400; records with estimated energy <500 or >5000 were excluded from the analysis (N=13: 6 in F&S Plus, 7 in F&S). Due to missing data, N=409 for physical activity score and 6-minute walk; a. A higher score indicates greater physical activity; b. A higher score indicates greater difficulties due to OA; c. A higher score indicates greater anxiety/depression; d. A higher score indicates greater self-efficacy.

Discussion

OA is a leading cause of pain and disability among older adults in the US (43). The primary aim of this comparative effectiveness trial is to assess whether Fit & Strong! Plus is more successful than Standard Fit & Strong! for producing positive dietary changes at post-intervention (2 months) and producing a 5% or greater weight loss at 6 months that is maintained at 18 months among older adults who both have OA and are overweight or obese. The secondary aim is to assess whether Fit & Strong! Plus will produce superior outcomes for this population in self-reported PA and physical performance, lower extremity (LE) pain, stiffness, function, anxiety/depression, and self-efficacy at 2 months that are maintained at 6, 12, and 18 months.
Dietary intake is a central aspect of weight management, and high fat consumption is a key contributor to the obesity epidemic (44, 45). Overall, participants in our study consumed more than the recommended amount of fat and less than the recommended amount of fiber (46). Although clinical guidelines recommend PA as a central tenet of treating OA, PA in this population is low, with less than 50% meeting current recommended activity levels (47-49). In addition, a number of articles demonstrate that African Americans are less likely to meet PA guidelines than non-Hispanic whites (50, 51), and that African-American women, in particular, are among those reporting the lowest levels of PA (52-54).
We also administered the performance-based six-minute walk test. The mean score in our sample was 356.3 meters, which was lower than reports from other samples comprising individuals with OA (55).
Measuring lower body strength is vital when evaluating the functional performance of older adults with OA (34, 56) The 30-second chair stand test provides a reliable and valid indication of lower body strength and function (57). In our study, the mean score on this test was 8.7 (SD = 3.6), which is lower than the 13.1 reported in another study of healthy older adults (mean = 70.5 years) (34), and importantly, it was also lower than a score of 10.0 reported in a study of older adults (mean = 56.3 years) with OA(55).
Overall, OA-related pain and functional limitations are known to be higher among African Americans compared to non-Hispanic whites (58, 59). On the WOMAC, we observed both commonalities and differences between our sample and other older adult samples. For example, pain and physical function scores were 6.5 and 24.2 in the Messier IDEA trial respectively (20), compared to our scores of 5.6 and 18.0. Wilcox and colleagues (55) reported lower scores than our sample on the pain subscale (4.6-4.9), but higher scores on the stiffness subscale (5.1-5.5 vs. 3.2 in our sample). A prior study of customary Fit & Strong! that included approximately 47% African Americans (42) reported similar scores on the pain and stiffness subscales but a higher score on physical function (42).
The differences between our older and younger participants are striking for the WOMAC. On all subscales, younger participants (60-69 years) reported more pain, stiffness, and disability than older participants (≥70 years). This could reflect societal changes in how people think about their health, with younger groups of older adults having higher expectations for their health [60].
Limitations. The current study has several limitations. It is limited to individuals who are overweight and obese (BMI = 25-50 kg/m²) and will not provide information on how Fit & Strong! Plus could benefit those with a BMI < 25 or > 50. We also did not clinically confirm OA, but instead used self-reported LE pain and stiffness. Additionally, our sample consisted of primarily lower-income adults with a median income of $25,000.
Conclusions. This study adds to the limited literature on combined PA and diet and weight management studies with older African-American adults with OA. Our results highlight some differences in self-reported versus performance-based functioning in our study sample at baseline and also documents differences between younger and older individuals within our older adult sample. Our findings regarding increased BMI and poorer self-reported function agree with findings from several recent longitudinal studies on aging that document disturbing trends of increased disability related to overweight/obesity in younger cohorts of aging adults (61, 62). These findings illustrate the need for additional research and ongoing refinement of interventions for this population that is both high-risk and growing rapidly.

Author’s Note

This project is supported by Grant Number R01AG039374 from the National Institute on Aging. Additional support was provided by the American Cancer Society of Illinois grant (#261775) and American Cancer Society Mentored Research Scholar grant MRSG014-025-01-CNE) to Dr. Lisa Tussing-Humphreys. The content of this manuscript is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute on Aging or National Institutes of Health. We wish to thank Colleen Lammel and the supportive staff at the Chicago Park Districts. We would also like to thank Mirjana Antonic for her administrative support and the study participants for giving their time generously to the project.

Conflict of Interests: The authors declare that there are no conflicts of interest.

Ethical standards: All authors in this manuscript declare that they have no conflicting interest

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PHYSICAL ACTIVITY IN HOSPITALIZED OLD MEDICAL PATIENTS; HOW ACTIVE ARE THEY, AND WHAT

M. Holst, P.L. Hansen, L.A. Pedersen, S. Paulsen, C.D. Valentinsen, M. Kohler

Aalborg University Hospital, Aalborg, Denmark, mette.holst@rn.dk

Corresponding Author: Mette Holst, Aalborg University Hospital, Aalborg, Denmark, mette.holst@rn.dk

Abstract

Objective: To examine how physically active Danish old medical patients are during hospitalization and to achieve knowledge of motivation and barriers to physical activity. Background: Functional decline in frail old patients during hospitalization is an important clinical problem with potential long-lasting undesirable outcomes and complications. Design: A mixed methods study including qualitative and quantitative methods. Methods: Patients >60 years of age were recruited at two medical departments during one week. Three SenseWear armband monitors were used for quantitative monitoring of physical activity. Semi Structured interviews were used for qualitative data. Results: The study comprised 13 patients, five female and eight male, mean age 73 (SD 9); BMI 19.4-32.1, mean 25.2 (SD 3.7). Only 11 patients completed 24-hours of SenseWear armband monitoring. Half of the participants walked less than 50 steps a day. The majority were bedridden 9 to 15 hours a day. Five of 11 patients had very low activity score. Four patients were moderately active for 19-38 minutes. Five patients sleep less than 6,3 hours, mean 9 (SD 3.3). Lying down was recorded for a mean of 11 hours (SD 4). Factors motivating to physical activity were: Praise and recognition from the staff, experienced boredom, continued ability to perform Activities of Daily Living. Barriers: Symptoms of illness, fear of falling, lack of meaningful activities, inadequate facilities and staff’s lack of focus. Organisational routines such as waiting for physical examinations and rounds, were barriers for patients to get out of bed. Conclusion: Old medical patients were very inactive during hospitalization. Motivation for physical activity was continued ADL abilities, boredom and staff interest, however often hindered by organizational barriers, lack of meaningful activities and focus from staff.

Key words: Old, patients, physical activity, hospitalization, ADL, bed rest, steps, MET, nurses, organization.

Introduction

Functional decline in frail old patients during hospitalization is an important clinical problem with potential long-lasting undesirable outcomes and complications. Sedentary older medical patients are at risk of developing complications during and after hospitalization, and it is therefore important to know to which extent these patients are actually inactive in hospitals, and what motivates patients to active behavior.

Age related decrease in physical fitness and function is commonly seen in older people due to the normal process of aging, where a reduction of muscle strength in both upper and lower limbs as well as changes in body-composition is seen (1).

Functional decline and any accompanying dependence of daily assistance, has important implications for the individual older person. Muscle strength generally decreases with approximately 1.5% annually from 60-80 years in both men and women, while the explosive muscle strength decreases by around 3.5% annually (2). The explosive muscle strength is a measure of how fast a muscle or muscle group can develop maximum power. The ability to quickly develop maximal force is needed to stave off decline, to rise and for walking on stairs. With the loss of explosive muscle power comes reduced ability to cope with activities of daily living (ADL) (3, 4). With profound physical inactivity, such as bed rest during disease, loss of muscle strength in the old occurs after only one day. Functional decline in frail old patients during hospitalization is an important clinical problem with potential long-lasting undesirable outcomes and complications, including nosocomial infections, falls and pressure ulcers. The older medical patients are particularly at risk of developing complications during and after hospitalization, due to physical inactivity and prolonged immobilization (5, 6). This is furthermore important for the high number of readmissions in this patient group (7-11). Functional decline has been strongly related to patients’ age and preadmission activities of daily living status (12, 13). Patients with shorter stays seemed to be more physically active during hospital stay, than patients with longer lengths of stay (14).

Two recent reviews showed that early physical rehabilitation care for acute hospitalized old adults leads to functional benefits (10, 15). Another recent nurse driven mobility intervention study, showed that older adults maintained or improved functional status and reduced length of stay (16). Other studies however contradict these findings, as physical training did not sufficiently improve physical function (17, 18).

In Denmark, as well as in many other well-established countries, there is an actual overall demographic transition, with an increase in the old population, and chronic diseases. This transition leads to a need for an increased focus on the wellbeing of the old population, including focus on the maintenance of physical function and ADL, during hospitalization (13).

Despite the fact that international studies indicate that an increased focus on physical activity during hospitalization including can reduce hospitalizations and the number of readmissions, there is limited knowledge about the extent to which hospitalized old medical patients are actually physically active (19-21).

The motivation for old hospitalized patients to be physically active has been sought in an American study. This study found that motivating factors included avoiding complications to prolonged bed rest, promoting a sense of well-being, promoting functional recovery, and being asked to exercise. Barriers against physical activity included symptoms of illness, institutional barriers, and fear of injury (22). Thus it seems relevant to examine the activity level of Danish old medical patient’s during hospitalization, as well as finding factors that are important for achieving an acceptable level of activity.

The aim of this pilot study was to:

I. Examine how physically active Danish old medical patients <60 years of age are during hospitalization

II. To achieve knowledge of motivation and barriers to physical activity in the same patients.

Methods

With regard to the two aims of the study, two methods were used in the same sample of patients.

As this was a pilot study, recruiting patients for one week only, the sample of patients were those who could be included within the week in question. Therefore no sample size or data-satiety was considered. Three SenseWear Armband monitors were available, and used to measure daily steps and Metabolic Equivalent of Task (MET) for 24 hours in each participant. Semi Structured interviews were used to investigate motivation and barriers.

The setting

Patients were recruited at two medical departments in a university hospital with 900 beds. The departments were a hematology department, where patients are admitted for diagnostics, treatment and care of hematological diseases, and department for kidney disease, where patients are admitted for acute and chronic kidney diseases. Both departments furthermore have an acute intake of patients with internal medical diseases, i.e. pneumonia, sepsis, and vertigo. The specialty patients are mainly younger patients, especially on the hematology department, and the internal medical patients are most often old patients with complex illness and multiple diseases. Combining these factors, the choice fell on including patients <60 in both departments, instead of having different inclusion criteria between the two departments. Patient bed rooms in both departments, had room for two patients.

Sample and inclusion

Patients were recruited at two medical departments during one week. Inclusion was therefore cross sectional, regarding all patients <60 years of age, who were hospitalized within the two departments during the actual week. On every morning of the week, a list was made of patients who met the criteria: 60 years of age or older, ability to walk with or without a walker and not going to be discharged within the next two days. This was important, since the activity monitoring lasted 24 hours, and time was needed to inform patients in a reasonable timely manner, so they had time to consider participation and ask questions before inclusion. The investigators went through the lists from both departments, and found patients suitable for inclusion. Secondly, the patients were discussed in collaboration with the nurse in charge of the patient in focus. This was in order to be certain of the patient’s ability to carry through an interview session, due to physical and psychological strength and cognitive abilities. Finally, in this pilot study, we strived for a selection of participants which was not distinctly homogenous. Thus, the aim was to include male and female participants, with a broad variation within older age.

Preparation of the patient

When patients were found relevant for inclusion, they were informed orally and in writing about the study. The patients were asked to “act as usual” wearing the armband, and just do as they would have done otherwise. If the patient decided to participate, an agreement was made about time and a setting.

Activity monitoring

Activity was measured by The SenseWear™ Armband (SWA) (BodyMedia, Inc. Pittsburgh, PA) for 24 hours in each patient. The SenseWear Armband is a type of accelerometer. An accelerometer is designed to carry out the objective measurement of physical activity by the movement patterns(11). The SenseWear Armband is worn on the upper left arm, and is completely harmless to the patient. It measures different parameters of activity. One is Metabolic Equivalent of Task (MET). MET is a standard parameter that is independent of time, weight and gender. MET describes the body’s ability to burn calories, 1 MET is equivalent to 1 kcal/kg/hour. An average person has a MET of 1.0 (0.9-1.1) when resting, reflecting the person’s resting metabolic rate (REE). Obese people generally have a lower MET, while bodybuilders and athletes with a higher musclemass pr. BMI, often have a higher MET. The program works with a fixed threshold of 3 MET for physical activity and therefore records all activity where MET is 3 or more. A MET 1,5-3 is equivalent of an ordinary persons walking speed. The armband also measures the patient’s average total energy expenditure (TEE). This measurement reflects the patient’s resting energy expenditure (REE) and the patient’s active energy consumption (AEE). The SenseWear Armband measures the duration of sleep and how much the patient is lying down, furthermore the relationship between duration of sleep and duration of lying down (RSE) is measured. RSE is considered normal if it is 0.8. Finally the armband measures step count.

SenseWear Armband has been validated for use in the activity measurements in healthy people, mainly regarding physical activity in weight loss programs(23). However it is also used in the clinic at Aalborg University Hospital at Centre for Nutrition and Bowel Disease as well as at Manchester University Hospital for evaluation of energy expenditure in patients with short bowel syndrome.

Motivation and barriers to physical activity

The methods used for interviews were inspired by two Danish qualitative methodology experts. The interviews was carried out as a qualitative research interview from a phenomenological and hermeneutical theory of science approach, where the aim is to better understand the studied problems, which can be used to generate new hypotheses and interpretations of reality(24).

Planning, executing and processing the interviews is based on the basis of Steiner Kvale`s seven phases: 1. Thematisation: Aim, subjects, what and why. 2. Design: What components does the study design consist off, making sure that you can obtain the knowledge you want to reach with the investigation. 3. Interview: interviews conducted from interview guides and thoughtful perspectives on the knowledge seeked. 4. Transcription: The interview material is made ready for the analysis phase. 5. Analysis: Based on the study’s purpose, subject and collected data , the method of analysis is desided with regard to providing the best analysis results. 6. Verification: The interviews are analyzed and discussed for generalizability, reliability and validity. 7. Reporting: Communicating results and findings. (25).

The interviews were undertaken as a conversation between interviewer and participant. The interviews took place either in the patients’ bed room, or in an office inside the unit. The patients were given the opportunity to decide whether they preferred to carry through the interview in bed, or sitting in a chair.

Ethical considerations

Prior to inclusion, the patients were given written and oral information about the SenseWear monitoring, and about the interview. The participants were informed that they at any time before or during the interview could withdraw from participation. The study was conducted according to the rules of the Helsinki Declaration of 2002. The study was put forward to the local ethic committee, which found that the study was not within claim of notification. .

Analysis I

Data from SenseWear Armband were analyzed in the statistical program SPSS 1.0. Medians and standard deviations for patient’s activity were calculated.

Analysis II

Data were analysed using a qualitative content and constant comparative method. Meaningful data were compared within the single interview, and between interviews. Inclusions continued until data-satiety was achieved in clear and stable patters, that did not change with adding more interviews. The interviews were recorded. Subsequently interviews were transcribed by interviewers and re-read for understanding. The interviews were then coded into units of meaning to the research question.

Results

Demographics

The study comprised 13 patients, five female and eight male, mean age 73 (SD 9); BMI 19.4-32.1, mean 25.2 (SD 3.7). Due to one sudden discharge and one transferral to other department, only 11 patients fulfilled the 24 hours of SenseWear armband monitoring. Since the two patients had already been interviewed, they remained included in the study. Ten patients were interviewed about motivation and barriers for physical activity during hospitalization. Three patients withdrew from this part due to feeling ill, and having to be present at sudden physical examinations. Table 1 shows demographic information and the distribution of data in the study.

Table 1 Demographic information and distribution of data

Of the included patients, only two patients received help for daily activities in own home. One of these patients had daily help for activities, including getting dressed, cleaning, cooking and grocery shopping, on a daily basis at home, prior to this hospitalization. One other patient had community help for housecleaning every two weeks. The remaining patients found themselves active, and of good health, prior to this disease and hospitalization.

How physically active

The included patients, in general, had very low activity rate regarding steps taken during the day, with a median of 46 steps, as shown in table 2.

Table 2 Distribution of number of daily steps

The patients (n=11) lie down in their bed between nine and 15 hours a day, mean 11 hours (SD 3 hours 53 min). Mean time of sleep was nine hours ( SD 3 hours 25 min). Five of the included patients, however were registered for sleeping less than 6 hours and 22 minutes.

Levels of activity: Five of the included patients were active (walking or more) less than 19 minutes during the 24 hours, due to the monitoring. Four patients were recorded for “moderate activity” for between 19 and 38 minutes.

Motivation and barriers to physical activity

The units of meaning identified in the interviews were clustered into the following significant themes, which are divided between motivation and barriers in the description. These are illustrated in Figure 1.

Motivation

Praise and recognition from the staff

Boredom

Awareness that physical activity is important for continued ability to perform activities of daily living

Self-determination

Praise and recognition from the staff

Patients found it very motivating when staff praised and recognised their effort to get out of bed. This was mentioned most often, if patients put on their own clothes and the effort thereby was more obvious. Recognition would keep patients from crawling back into bed.

Boredom

Boredom from just lying in bed was common and could make patients get up. One patient put it quite clear; (P7)»I do not want to lie in bed. I am bored simply“.

Awareness that physical activity is important for continued ability to perform activities of daily living:

Patients recognized that physical activity is important with regard to well-being, and especially for being able to go back to performing activities of daily living, as they did before this period of illness. One patient referred to physical well-being as; (P9) «I mean, we should not stay in a bed, we need to … The limbs prefer to be moved“. Others talked about physical abilities and psychological self-preservation as one whole; (P10) «I think… probably it’s a bit too “Sorry” if I do not get out of bed. It’s okay if you have to sleep. But it also has something to do with putting demands on yourself. For one must not come to a standstill. And once you go home .. there’s no dear mother. Then you only have yourself «. Another patient puts it this way; (P4)”I find it very important (to be active ..red), otherwise I won’t be able to do anything when I come home”.

Self-determination

The importance of self-determination and autonomy, and the relation to physical activity and being able to do things on their own decision, was obvious throughout the interviews, even though the grading of what was seen as autonomy was different within the patients; (P6) «I’m used to being in vigor, and fix things when they should be taken care of, and it gives a greater enjoyment of life». And; (P3)»Let me do something myself. I like to go out and wash myself and things like that».

Barriers

Organizational routines

The interviews often led to a need for the more concrete questions, as could be narrowed down to: Q: To what extent have you been out of bed, for instance, today? Patients had many responses to this, and most of them related to organizational issues; (P7) “I would, but “a little cuckoo came into the machinery”. I was supposed to have a scan at 10. Before then, I had to drink 1 ½ liters of water and wait for the porter. Then it was postponed until 3 o`clock, so now I can sit here and drink 1 ½ liters of water again». Most patients talked about the daily routines, which are also categorised as organizational in this interpretation; (P8) «Well, one needs to be here (at bedside. red) at rounds and so. I don’t know what time it is, so it’s no good, if I run around at the other end (of the department. red)“. And; (P9) “Yes, but not that much, because I expect a doctor to come”.

Lack of meaningful activities

More patients state that staff take over and do things for them, including bringing food and drinks. This attention is provided despite the fact, that these patients could easily fetch what they need themselves. This was problematized with the words; (P6) «You are well looked after, up to where ends meet. I’m used to doing everything myself, and all of a sudden you have to do nothing». The patient also describes that she, after her former hospitalization had lost energy, and was physically weaker after discharge. This is explained with the words; «Yes, but that was because, I didn’t keep going and all that. The only thing I did was to sit and knit». This patient signals that she is motivated to physical activity awareness, of what inactivity could mean for her well-being after discharge. But the staff’s well-meaning attention turns into a kind of barrier against physical activity. Lack of other meaningful activities besides walking up and down the corridor is requested. One patient says, that she has offered to help make coffee for the staff, and tidy the patient living room. Another patient has heard that some departments have a gym bike, so they could keep fit, and still “stick around”.

Staff help and individual focus

While some help was found too much and inappropriate as seen above, others found that lack of relevant help to be physical active is considered a barrier. One patient would rather go to the bathroom and wash herself with assistance for her safety and comfort, but finds she is not offered the relevant help, and therefore she does not dare to do so; (P4) “They could help just by standing beside me (bathroom red). Confidence alone, it means quite a lot. Especially, after I fell. I’m terrified of that».

One patient was fortunate to have had the presence of a physiotherapist. However he found that the therapy was not individually adjusted to his abilities, and were therefore useless; (P1) “They gave me this, so I can sit and strengthen my hands, but it is too easy, so bother – hell I won’t“.

Discussion

In this pilot study we investigated physical activity among old medical patients, and the motivation for as well as barriers against, being physically active during hospitalization. We monitored physical activity by SenseWear Armbands. By step count, patients were found to be generally very inactive, and indeed less active than recommended for the healthy population, in order to maintain functional abilities (9). Compared to former studies in other settings, patients in our setting were even more inactive. In the study by Brown et al, they monitored mobility levels in old patients during hospital stay. Like our results, they found that older hospitalized patients spent most of their time lying in bed, despite an ability to walk independently (20). Patients in the study by Fisher et al. were slightly more active, and took a mean number of 739 steps (range 89-1014) steps per day during their hospital stay. In the study by Fisher et al, however, the physical environment was designed to promote ambulation and provide incentive for patients to increase mobility and participate in activities during their hospital stay. In the present study, the lack of possibilities for meaningful activities was perceived as one of the main barriers. (14). Furthermore we find, that the reasons the patients in the present study are less active, can be that we found patients who were quite ill compared to those in other studies, and that the staffing in the two departments, including the focus on physical activity is low, as also advocated by patients. A comparison between resting time, low and moderate activity compared to steps taken on the day of monitoring, indicated that MET could be elevated due to metabolic changes related to disease rather than to physical activity/ or steps. Thereby, moderate activity as registered by SenseWear, might not be due to actual activity, but rather to metabolic disease activity.

Furthermore, the qualitative interviews indicated, that patients found themselves more active- or at least, wanting to be more active, than they actually were, seen by SenseWear monitoring. Only a few patients overcame the barriers and felt motivated to walk more steps, than just walking a bit around the patient bedroom, and for a few to fetch their own meals. Since this was a pilot study with only 13 patients, of which only 11 were monitored by SenseWear, the results should of course be considered with caution.

As seen in a former study, the encouragement and help from nurses to mobilize, helps motivate patients to be physically active (16). While one single study showed, that muscle strength did not decrease during hospitalization and 30 days after discharge in acutely admitted older medical patients, despite a low level of mobility during hospitalization (17). Other multidisciplinary intervention studies, focusing more on facilitating ADL, contrary to exercise programs aimed at improving functional outcomes”, showed, that at the time of discharge, patients who had participated in a multidisciplinary program or exercise program, improved more on physical functional tests and were less likely to be discharged to a nursing home, compared to patients receiving only usual care. In addition, multidisciplinary programs reduced the length of hospital stay significantly (15,18). In this study we did not investigate thoroughly the medical or social reasons that might impact the length of stay. The impact of staff was very central in our findings (Figure 1).

The patients in the present study found that relevant help and encouragement from staff would motivate them to get out of bed and be more active, and vise-versa, a barrier against physical activity when not provided. One patient felt unsafe out of bed, because of a former fall incidence, and was not offered relevant assistance. Therefore she was not likely to be physically active. This indicates, that dependencies of help, i.e the patient who was afraid of falling and therefore wished for help walking and staying in the bathroom with her, are not always provided, which may influence physical abilities and function, and have a negative impact on clinical outcome as length of stay and ADL function after discharge.

Another study showed that, unlike patients, the staff attributed low mobility among hospitalized older adults to lack of patient motivation (19). The same study found that lack of ambulatory devices, including meaningful activities, was a barrier against activity (19). In the same study they found, that lack of staff, patient clothing, disease symptoms and physical environment affected the old patient’s physical activity negatively. In the present study disease symptoms were only mentioned briefly by patients. Clothing was not directly mentioned as a barrier, however, motivation was found by staffs praise and recognition, when patients were actually out of bed, and praise was especially experienced, when patients were in own clothing. In general, the lack of individual focus towards physical activity, including mobilization, was seen as de-motivating.

The lack of staff, as seen as a barrier in the former study, might also be one of the reasons, for the lack of focus towards physical activity, especially mentioned regarding the nurses, but also, regarding lack of individually targeted care by the physiotherapist, as seen in the one fortunate patient, who was actually associated with such. Within the past couple of years, the hospital has been through a serious wielding, especially towards the staff caring for patients. With the shorter hospital stay, and increase in patient age and complexity, this might have influenced the focus to other than the core medical treatment.

Organizational issues were seen as serious barriers in this study. Patients did not find themselves able to leave the bed, in case they would miss the physician at rounds, and one patient had to spend the whole day close to a toilet and drinking water. Improved appointment systems, information and clarity about expectations between patients and staff, might improve the ability for patients to – at least- walk around the department, and maybe even use an exercise bike, as one of the patients suggested.

Methodological considerations: The study aimed to include only old patients. However there were not enough relevant patients during the week feasible for the study. As this was a pilot study only, we decided to include also patients a bit younger, however with chronic concurrent disease. During this study, it has become unclear whether SenseWear was actually able to correctly count the small short steps (toddle steps), that can possibly be taken of old ill patients. However, these short steps would anyhow not add significantly to the total MET activity score, as has been recommended for activity in the population(9). The inconstancy between bed rest and actual sleeping time indicates that SenseWear might have problems separating elevated back rest from lying down and sitting, and/or that patients may suffer from poor sleep quality. In our upcoming studies, we will include information about actual and concurrent disease, as well as body-composition and other physical function measurements.

Conclusion

Old medical patients in this study were very inactive. Reasons were organizational, lack of staff help and focus as well as lack of meaningful activities. Motivation for physical activity was found in self-preservation of continued functional abilities, help and recognition by staff, and meaningful activities.

Relevance to clinical practice

This study shows us that nurses can have important positive impact of the life threatening immobility in the hospitalized old patients. By giving attention and help to patients who need support towards the feeling of safety in being physically active, nurses can affect the most vulnerable patients’ action in a positive and self caring direction. Positive remarks, noticing and appraising the individual for getting out of bed and chair, takes a very little effort for nurses, thus means a very lot to the patients in this study, and may contribute to an improved quality of life, and clinical outcome.

Acknowledgements: The authors are thankful to patients and staff at department of hematology and department for kidney disease, at Aalborg University Hospital for kind and willing participation.

Funding: There was no funding to this study.

Conflict of interest: All authors declare no conflict of interest to this study.

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