Postmenopausal Women with Osteoporosis: The Effect of Physical Exercise on Markers Linked to Quality of Life

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FACULTY OF HEALTH AND OCCUPATIONAL STUDIES

Department of Public Health and Sport Science

Postmenopausal Women with Osteoporosis

The Effect of Physical Exercise on Markers Linked to Quality of Life

Henrik Gustafsson

2021

Student thesis, Bachelor level, 15 Credits Public Health

Health Promotion through Sustainable Development Research Methods in Public Health II and Thesis writing 30 Credits

FHG800

Supervisors: Francesca Maffei, Sandra A.I. Wright, and Sofia Marini Head Advisor in the Subject Area of Public Health: Anne-Sofie Hiswåls

Examiner: Gloria Macassa

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Gustafsson, H. (2020). Postmenopausal women with osteoporosis – The effect of physical exercise on markers linked to quality of life. Bachelor thesis in Public Health Science.

Department of Public Health and Sport Science. University of Gävle, Sweden.

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Abstract

This study has aimed to evaluate how osteoporosis affects the quality of life in postmenopausal women and to assess the influence of physical exercise on markers for quality of life in osteoporosis patients. The EQ-5D questionnaire was applied for evaluation of the markers: Mobility, Self-care, Usual Activities, Pain/Discomfort and Anxiety/Depression. In collaboration with the University of Bologna, a 6-month exercise trial of women aged 60-75 with osteoporotic vertebral fractures was analyzed. These osteoporosis patients were divided into two groups; an exercise group and a control group.

Markers linked to quality of life were compared for the women with osteoporosis with those of an average female Italian population of similar age. Markers for quality of life, specifically: Mobility, Usual Activities, Pain/Discomfort and Anxiety/Depression were significantly lower in the Italian osteoporosis patients than in the average population.

Exercise slightly improved Mobility and Usual Activities for the osteoporosis patients, but the results did not reach statistical significance.

Keywords: osteoporosis, quality of life, physical exercise, postmenopausal women, vertebral fractures

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Sammanfattning

Denna studie har syftat till att undersöka hur osteoporos påverkar livskvaliteten hos postmenopausala kvinnor (dvs. efter klimakteriet) och att bedöma påverkan av fysisk tränings på markörer för livskvalitet hos osteoporospatienter.

Frågeformuläret EQ-5D användes för utvärdering av markörerna: rörlighet, egenvård, vardagsaktiviteter, smärta/obehag och oro/nedstämdhet. I samarbete med universitet i Bologna analyserades en 6 månaders träningsstudie av kvinnor i åldrarna 60-75 år med osteoporotiska ryggradsfrakturer. Dessa osteoporospatienter delades in i två grupper; en träningsgrupp och en kontrollgrupp. Markörer kopplade till livskvalitet jämfördes för kvinnor med osteoporos och kvinnor från en italiensk genomsnittspopulation i liknande ålder. Markörer för livskvalitet, särskilt: rörlighet, vardagsaktiviteter, smärta/obehag och oro/nedstämdhet var signifikant lägre hos de italienska osteoporospatienterna jämfört med genomsnittspopulationen. Träning förbättrade rörlighet och vardagsaktiviteter något för osteoporospatienterna, men resultaten nådde inte statistisk signifikans.

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Acknowledgements

Support, patience and extraordinary supervision – without those components, this thesis would not have been possible to realize. I would like to express my deepest appreciation to Professor Sandra A. I. Wright, for teaching me valuable research skills. You have generously given your time, even when you had other commitments simultaneously. I am also grateful to you for introducing me to Professor Francesca Maffei, at the University of Bologna. Thanks are due to Prof. Maffei, for her endless patience during all our Zoom meetings throughout the unusual 2020 year, and for introducing me to the subject of osteoporosis. I hope I will be able to visit the university campus one day. I would like to express my sincere gratitude to Sofia Marini and for generously sharing the data and for valuable suggestions on this thesis. I am honored that I could take part in your study. My sincere appreciation also goes to Laura Dallolio, for sharing the data and for appreciating my contribution of analyzing the data. Although not formally my supervisor, Professor Niclas Olofsson patiently and generously introduced me to statistics and supported me throughout the data collection. The information became clearer as I evaluated and processed the data and you made me aware of the complexity of statistics.

I am also owing gratitude to Mia Mårdberg, at the University of Gävle Writing Center, and librarian Karin Meyer Lundén for replying to my questions. I would also like to acknowledge the support of Christina Edin and Marie-Louise Holmberg. I truly appreciate the support I have got from Professor Yuko Okubo, at the University of California, Berkeley and Stefanie Lazer at the American Psychological Association, for giving me comprehensive guidance on questions regarding references. I am also thankful to the physical therapists; Margaret Martin, in Ottawa, for letting me use her video material, and my brother Alex for putting up with inquires. Kaisori Bellach has been there by my side with her sincere support even her time was limited. Thank you for your helpful advice, as always. A special thanks goes to my girlfriend for being patient and supportive during the thesis project, and to my family for their support and encouragement throughout my studies.

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Preface

During this thesis work, I have understood that the concept of quality of life is complex, i.e. that it can refer to different things, depending on the personal values of an individual.

Although its immediate connotation appears to be related to health, quality of life may, in fact, not necessarily always indicate the same as what we consider as "healthy".

Osteoporosis affects physical as well as psychological health. To feel neglected may perhaps be conceived as even worse to the individual than the physical trauma of a fracture that osteoporosis often leads to, and there could be countless unrecorded data on the psychological costs of the disease.

While searching the literature, it did not take long to understand that patients with osteoporotic fractures have not been prioritized, which Cosman et al., (2014) highlighted, by stating that in the U.S., many individuals with osteoporotic fractures do not get a diagnosis or have received proper therapies. In Sweden, vertebral fractures caused more morbidity than hip fractures up to age 75 (Kanis et al. 2004). Despite the high prevalence of osteoporotic fractures, Swedish physicians reported that the national health care system ordered staff to set low priority to osteoporosis. Consequently, only about 14% of the patients received bone-specific aid after a fracture (Salminen et al., 2019). This indicates that the problem could worsen and lead to side effects, such as repeated fractures. The women in this study have had one or several fractures due to osteoporosis. In fact, a major risk factor for obtaining a fracture is existing, previous fractures (Cipriani et al., 2018).

These may lead to chronic pain, and in some cases, fatality. For instance, several studies reported a higher risk for mortality in patients with vertebral fractures (Cauley et al., 2000;

Hallberg et al., 2004); it was even nine times higher than in the general population, according to a Polish review by Haczynski and Jakimiuk (2001). In the present study, the effect of osteoporosis on quality of life was investigated.

With the burden on society that osteoporosis causes, bone health investment is essential and should also be prioritized, due to the risk of comorbidities after a fracture. It may require health policy planners to be rationally open-minded, since immediate evidence seldom occurs, for example from exercise trials. Research on long-term effects of physical exercise and awareness of the influence of diet and drugs on exercise may be suitable for future measures, as reviewed by Benedetti et al. (2018). In the present thesis,

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the influence of exercise on markers linked to quality of life was investigated. A positive aspect of physical exercise is that it can be carried out at home, without posing an economic burden on the patient (Koevska et al., 2019). Accordingly, physical exercise is excellent for disease prevention, also for those with limited financial means, being of help to the public health and the individual. Thus, it is important that funding is made available for these types of studies and that future research in osteoporosis is encouraged.

The United Nations General Assembly (2015) stated the importance of promoting physical and mental health in individuals with non-communicable diseases (NCDs), including osteoporosis. Recently, a report of NCDs showed a decrease in fracture assessment of osteoporosis patients in many countries during the COVID-19 pandemic (McCloskey et al., 2020). Early diagnosis is crucial since osteoporosis later can create a heavy burden on the public health systems. It should not be neglected due to the current challenges of a pandemic. Social distancing with people working or studying from home can lead to increasing sedentary behavior and this may lead to a second pandemic of osteoporosis. This may be a global problem but especially in the northern hemisphere during the cold season, with lack of natural vitamin D from the sun, which is needed for healthy bones.

As mentioned earlier, no symptoms appear for over half of the patients with vertebral fractures (Lentle et al., 2007). Therefore, not only the osteoporosis condition may go undiagnosed but a person with a fracture may also not receive medical care, which in turn may lead to personal trauma and a subsequent burden on the primary health care (Gold et al., 2019). This is costly also to the families of patients since it affects physical and mental health, which is socially and financially unsustainable. The costs for health care systems are massive when osteoporosis has set in. Thus, the public health system needs to cooperate with experts in osteoporosis to remain competent on strategies that are efficient, safe, feasible and effective, including physical therapy, as both primary and secondary

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is silently moving forward. Bone fragility is so common that almost everyone knows another person with osteoporosis, or someone that had a fracture. Therefore, we should ask ourselves why this may be, and what we can do. Health authorities need to implement efficient risk assessment of fractures to promote favorable choices of lifestyle, which could contribute to promoting quality of life.

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1. Introduction

1.1 Osteoporosis as a Public Health concern

Osteoporosis is defined as bone fragility or "porous bone”. It is a chronic, degenerative disease of the skeleton and a major public health problem that results in decreased bone strength, which can increase the risk of bone fracture (Hernlund et al., 2013; National Institute of Arthritis and Musculoskeletal and Skin Diseases, n.d.). Osteoporosis is especially prevalent among elderly women. A correlation between osteoporosis and the onset of menopause was observed already in the 1960s (Tella & Gallagher, 2014). Low estrogen levels after menopause are believed to cause bone loss and lead to osteoporosis (Agostini et al., 2018). Hundreds of millions of people are affected worldwide and the prevalence is increasing (Reginster & Burlet, 2006; Hernlund et al., 2013). In people who are 50 years of age and older, approximately one in two women and one in four men will have a fracture caused by osteoporosis (National Osteoporosis Foundation, 2020). A U.S.

survey of postmenopausal women from 2000 to 2011 showed that the annual cost due to hospitalization for osteoporotic fractures was higher than for breast cancer, myocardial infarction, or stroke (Singer et al., 2015). A report on the medical and economic burden in the European Union showed that around 22 million women and 5.5 million men had osteoporosis in 2010. It resulted in roughly 3.5 million fractures. The annual cost of fractures caused by osteoporosis was approximately EUR 37 billion and has been predicted to increase by 25% by 2025. However, most persons in Sweden who are affected by or at risk for an osteoporotic fracture do not receive proper treatment. Instead, fewer persons are receiving treatment than previously (Hernlund et al., 2013). Fractures appear after different levels of trauma but until a fracture occurs, osteoporosis is a silent

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et al., 2002). Moreover, osteoporosis and fractures are also issues in Southern Europe.

More than half of the Italian women over the age of 50 had osteoporosis, according to Cipriani et al. (2018).

Longevity and osteoporosis

Bone-related disorders can be understood through the prevalence of longevity in a population since bone mineral density (BMD) decreases with old age. Osteoporosis constitutes a global health problem, since the median age is increasing in the world, due to low fertility and increased longevity. Life expectancy is especially high in developed countries, and Europe has the oldest median age in the world. The fastest-growing population group is people over the age of 60. By 2050, in developed countries, the number of elderly is estimated to be twice as high as the number of children (United Nations, 2011). This gives an idea about how urbanized nations will be affected by bone fragility, due to aging populations. After all, quality of life is an important component of longevity and longevity affects the quality of life.

1.2 Development of Osteoporosis; the Effect of Physical Exercise and Lifestyle

Aging leads to a lower BMD (osteopenia) and muscular density (sarcopenia) (dos Santos Silva et al., 2019). High BMD is essential for preventing osteoporosis and it can depend on genetic predisposition, such as ethnicity (Whedon, 1984; Smith, 1985)^.Measuring bone density is part of the regular risk evaluation for preventing osteoporosis-related fractures (Cummings et al., 1993; Marshall et al., 1996). However, there is limited information regarding facture incident proportions in postmenopausal women with either low or regular BMD (Cranney et al., 2007).

Physical exercise is an effective way to build up bone mass, and it contributes to osteogenesis; the formation and maintenance of the bones, as reviewed by Benedetti et al. (2018). Findings suggest that physical exercise prevents osteoporosis through counteracting and slowing down the loss of bone from the lumbar vertebrae at the lower back spine (Krølner et al., 1983). In fact, exercise is believed to be the most fundamental non-pharmacological treatment for facilitating the healing of fall-related fractures and delaying the outbreak of osteoporosis (Agostini et al., 2018). Emphasis on exercise is of

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importance, since decreasing physical activity among elderly is a contributing factor as to why they are more prone to osteoporosis (ibid).

Physical exercise can improve overall quality of life. It may contribute to improving self- esteem and social life among women with osteoporosis, as seen in a Macedonian study (Koevska et al., 2019). There are different types of exercise that lead to vitalization.

Resistance strength training of the lower limbs strengthens the femoral neck. However, for patients with disorders of the spine (vertebrae), multicomponent exercises appear to be the most effective. These include a combination of "weight-bearing activities", such as Tai Chi, walking, jogging, and stair climbing with resistance and strength training with weights, as reviewed by Benedetti et al. (2018). Recommendations that has been proven helpful for women with vertebral fracture include exercises for strengthening the back, upper and lower extremities, combined with balance training and should be individually applied (Dusdal et al., 2011; Giangregorio et al., 2013). Evidence is limited regarding the effects of physical function on quality of life in patients with vertebral fractures, which was reviewed by Gibbs et al. (2019). As reported by Benedetti et al. (2018), there are three areas of physical exercise for osteoporosis patients:

1. Weight-bearing aerobic exercises 2. Strength and resistance exercise 3. Balance training

Exercises suited to individuals with vertebral fractures may consist of modified trunk and lower extremity muscle strengthening, exercises directed to correction of posture, challenging balance practices combined, and aerobic physical activity with moderate intensity, according to Gibbs et al. (2019). An important discrepancy has to be made about different types of physical exercise. Exercise may prevent osteoporosis but safe exercise

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the number of individuals older than 15 years of age, who are classified as moderately physically active for less than half an hour per week. Physical activity has predominantly decreased in high-income countries. In 2008, almost every second woman in high-income countries was considered physically inactive (World Health Organization, 2011). In any case, it is important to be physically active at all ages (Kannus, 1999).

1.3 Osteoporosis and Quality of Life

Health-related quality of life, or simply quality of life, defines the well-being of an individual. It includes environmental and financial aspects in addition to the general health status of a person. The term has been relevant since 1948, after the humanitarian tragedies of World War II, when the World Health Organization defined health as more than the absence of disease. It has been a widely used term in the MEDLINE database since the 1970s, as reviewed by Testa and Simonson (1996). To have a sense of coherence is necessary for quality of life in osteoporosis patients. A study found social support and socioeconomic factors to speed recovery and decrease mortality after hip fracture. Over time, this treatment also had positive effects such as pain relief, shorter hospitalization, and improved quality of life (Auais et al., 2019). Social support was mentioned as an important factor for physical function also by Kerr et al. (2017). Conversely, disability may restrict participation in society.

Instruments for measuring health-related quality of life

Quality of life cannot be clinically measured, since it is a subjective experience.

Therefore, self-assessment through measurement scales are often used. Even though quality of life is commonly associated with social sciences, it is of relevance for clinical studies, for example in estimating the cost-effectiveness of medical interventions (Testa

& Simonson, 1996). Since quality of life is multidimensional, the instruments need to include several dimensions (Lydick et al., 1997). Many different questionnaires exist to measure the quality of life in osteoporotic patients through patient-reported outcome. Two of the most commonly used are the EQ-5D and the QUALEFFO-41. EQ-5D is a generic health-related quality of life questionnaire, while QUALEFFO-41 is a disease-specific questionnaire for measuring the quality of life in patients with vertebral fractures (van Schoor et al., 2006).

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The EuroQol Group, a global research organization, has developed the EQ-5D, a standardized questionnaire for the measurement of health-related quality of life (Rabin &

de Charro, 2001). Markers used to measure the effect of osteoporosis on quality of life include Mobility, Self-care, Usual Activities, Anxiety/Depression and Pain/Discomfort, which all contribute to physical functions, psycho-social state, and well-being. The EQ- 5D is available in three versions: EQ-5D-3L, EQ-5D-5L and the EQ-5D-Y. A list of

terminology is accessible via the EuroQol website:

https://euroqol.org/support/terminology/ (Brooks et al., 2020). The EQ-5D is utilized in clinical settings, clinical trials and population studies worldwide. The EQ-5D-3L is translated into 180 different languages. Each of the adapted versions comes with a translation protocol that conforms to the International guidelines, which guarantee that these are equal to the original version in English, as stated in the EQ-5D-3L User Guide (EuroQol Research Foundation, 2018).

The effect of vertebral fractures on quality of life

Vertebral fractures can cause chronic pain and disability, which reduce the quality of life even after healing (Hallberg et al., 2004; Suzuki et al., 2010; Jung et al., 2017; Gold et al., 2019). A fracture leads to a lower quality of life through impaired social and physical function in postmenopausal women with osteoporosis (Fechtenbaum et al., 2005). After a fracture, increased fear of falling is common in the affected individual. Fear of falling and dependency on others after a fracture often makes the patient more inactive, which increases the osteoporotic condition. In fact, fear of falling has a serious impact on the quality of life in women with osteoporosis (Lydick et al., 1996). This sequence of events manifests itself as a vicious circle, depicted in Figure 1 (Kerr et al., 2017).

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Figure 1. The vicious circle of deterioration during osteoporosis. The figure is adapted from the original by Kerr et al. (2017).

Figure 1 shows how the different aspects of osteoporosis affect each other. Decreased physical performance may lead to loss of bone and muscle, which in turn may lead to fractures; and fractures are usually painful. The pain is likely to cause a decline in physical performance – and that is where everything started. The result is a vicious circle, which affects the quality of life of the osteoporosis patient.

After a fracture, the osteoporosis patient may have a reduction or absence of ability to perform daily tasks, i.e. Usual Activities. Some examples include the ability to shower, pick up things, manage to get up from chairs or seats, etc. This is often due to decreased Mobility and Pain/Discomfort, but also fear of falling, which may present itself as Anxiety/Depression. Self-care may thus be even more difficult after a fracture for the elderly. Self-care is defined as the ability to take care of ones personal hygiene and independently sustaining oneself (Brooks et al., 2003). As seen in Figure 1, fractures have an impact both physically and psychologically – it has an especially large negative psychosocial impact. The consequences of a fracture are worse for the elderly, because of the likelihood of social isolation and because of a general deterioration in physical health (Kerr et al., 2017). Markers used to measure the effect of osteoporosis on quality of life are listed in the middle of Figure 1. These markers are important for planning integrated therapeutic strategies for the treatment of individuals affected by osteoporosis (Rabin & de Charro, 2001; Marini et al., 2019). To ultimately break the vicious circle

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(Fig 1), and prevent and counteract osteoporosis, a regular physical exercise routine may serve as a final solution (Kannus et al., 1995).

The present study focuses on postmenopausal women, since they are particularly prone to osteoporosis and affected by it, to such a degree that osteoporosis in these women represents a serious global public health problem. There is evidence to suggest that physical exercise may help women to obtain a better quality of life, even if they start exercising later in life (Choi, 2013).

2. Aim of the Study

To investigate the impact of physical exercise on health and wellbeing and to evaluate markers linked to quality of life among Italian postmenopausal women with osteoporosis and a history of vertebral fractures.

3. Research Questions

• How can osteoporosis interfere with quality of life among Italian postmenopausal women?

• Can physical exercise influence markers linked to quality of life (Mobility, Usual Activities, Self-care, Pain/Discomfort and Anxiety/Depression) among osteoporotic patients?

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4.Methods

4.1 Study Design

The research was part of a quasi-experimental controlled 6-month trial, with non-random assignment. The study was non-randomized, because the selection of participants was based on voluntary participation in the exercise program. Forty women participated in the study. The studied population was classified into two groups: Adapted Physical Exercise Group (22 subjects) and a Control Group (18 subjects). The Control Group did not change their lifestyle during the six months. The Exercise Group however, followed a specific, regular exercise program, adapted for persons suffering from osteoporosis (Marini et al., 2019).

Perceived quality of life among the participating women at the beginning of the exercise study was compared to that of an average Italian population. The population consisted of individuals of similar age and gender (Table 1).

4.2 Selection Criteria

To be included in the study, the participants had to be 60- to 75-year-old postmenopausal females from the city of Bologna, Italy. The studied population was recruited by the Internal Medicine Unit at Sant'Orsola Malpighi University Hospital in Bologna during daily outpatient activity. All of the participating women lived at home. They had confirmed osteoporosis, verified by dual-energy X-ray absorptiometry (DXA), and a history of at least one vertebral fracture. Most of them followed drug therapy for osteoporosis. The pharmacological administration was constant throughout the study.

This thesis is utilizing some data from of a large study that never were analyzed or published previously. They form the basis for the present thesis.

4.3 Data Collection and Questionnaire

The collection of data was based on patient-reported outcomes through the EQ-5D-3L questionnaire, since the study that provided the data applied this version (EuroQol

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Research Foundation, 2018; Marini et al., 2019). Included were questions regarding five markers related to quality of life: Mobility, Self-care, Usual Activities, Pain/Discomfort and Anxiety/Depression. There was also a visual analog scale; EQ VAS, where each woman could indicate her self-assessed overall state of health.

The EQ-5D-3L questionnaire estimates the state of health in three ways: 1) by the EQ- 5D-3L descriptive system of five dimensions (markers) linked to quality of life at three levels, 2) by the EQ VAS (scale measuring overall quality of life), 3) by the EQ-5D index value (EuroQol Research Foundation, 2018).

The EuroQol Research Foundation has provided the following demo version (sample) of the EQ-5D-3L questionnaire seen on the next page:

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Figure 2. The EQ-5D-3L questionnaire (sample version) shown for illustrating purposes.

EQ-5D^TM is a trade mark of the EuroQol Research Foundation. Reproduction of this version is not allowed. For reproduction, use or modification of the EQ-5D (any version), please register your study by using the online EQ registration page: www.euroqol.org.

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1. Application of the EQ-5D-3L to estimate the state of health

The questionnaires, which were in paper format, were given to the osteoporosis patients.

The patients were asked to tick one of three boxes next to each of the five markers linked to quality of life. There were three levels to choose from when assessing health: 1. no problem, 2. some problems, 3. extreme problems.

When these levels were combined with the markers for quality of life, a distinctive health state for each individual was created.

The EQ-5D-3L has 5 dimensions (markers) with 3 levels. The five markers create a code of five numbers from the chosen levels of 1, 2, 3. For example, a health state of 12231 would indicate no perceived problems with Mobility, some with Self-care and Usual Activities, extreme problems with Pain/Discomfort and none with Anxiety/Depression.

On the other hand, 11111 would indicate no perceived problems with any of the five markers (EuroQol Research Foundation, 2018). Each patient received a personal health profile, created by treatments and visits. The distribution of the responses of each marker were recorded in a table and percentages were calculated. The five number digits also contributed to a summary EQ-5D index, which is described below.

2. Imagined and self-assessed state of health through a visual analog scale The EQ VAS allowed the osteoporosis patients to estimate their self-rated health by placing a cross on a scale of 0 to 100, where 0 meant "worst imaginable health" and 100 meant "best imaginable health (Marini et al., 2019; Rabin & de Charro, 2001). The percentage estimated health level was recorded by each patient as a number in a box on the same page (The EuroQol Research Foundation, 2018).

3. The summary EQ-5D index value

Summarized data from (step one) are automatically created by the program, thus

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used for economic assessment in health interventions (EuroQol Research Foundation, 2018).

4.4 Conducting the study

This study was carried out in collaboration with the Department for Life Quality Studies (Rimini Campus) and the Department of Biomedical and Neuromotor Science (Bologna Campus) of the University of Bologna in the framework of an Erasmus+ mobility.

The data were kindly provided by Francesca Maffei, Sofia Marini and Laura Dallolio through a pilot study conducted by the University of Bologna (Department of Biomedical and Neuromotor Sciences and Department for Life Quality Studies), in co-operation with the Bologna University Hospital Authority St. Orsola-Malpighi Polyclinic in Bologna.

The pilot study, among the outcome assessments, applied the EQ-5D-3L questionnaire for the data collection relatively to the health-related quality of life domain, and therefore the present thesis applied the same method using the data collected but not yet described by Marini et al. study (2019). The participants completed the questionnaire at the beginning and the end of the study. The answers for the two-time points were called pre- intervention and post-intervention, respectively. The data were collected by trained and blinded assessors, with the supervision of Sofia Marini and the research team. However, the study could not be considered randomized, since the patients participated in the exercise program on a voluntary basis. All the participants in the study confirmed at the outset in writing their informed consent to participate in the study (Marini et al., 2019).

The participants of the Control Group were recommended to proceed with their current lifestyle. The Exercise Group participated in a one-hour long training session twice a week, administered at specific gym, by graduates with Master of Science Degrees in Sciences and Techniques of Preventive and Adapted Physical Activity of the University of Bologna. Each training session started with a 15 minutes’ warm-up of cardio- respiratory conditioning, coordination and mobility exercises and balance training. The larger part of the session was based on weight-free strengthening exercises and finally, every session ended with a ten-minute cool-down. Exercises that could lead to vertebral fractures were deliberately excluded from the training program, particularly those related to spinal flexion and twist. Simple materials, such as elastic bands, mats and sponge balls

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were used at every session. The exercise intervention lasted for a period of six months (Marini et al., 2019).

4.5 Data Analysis

The average Italian population, which consisted of 247 women in the age range of 65 to 74 years old was chosen as a reference population for comparison to the osteoporosis patients. The data of the average Italian population were extracted from the book: Self- Reported Population Health: An International Perspective based on EQ-5D (Szende et al., 2014, pp. 101-105). The parametric, two proportion Z-test was used to analyze EQ- 5D questionnaires regarding quality of life comparisons between the osteoporosis patients and the average Italian population. The Z-test allows you to compare two proportions to see if they are the same. The null hypothesis (H0) for the test was that proportions were the same for the average population as for the osteoporosis patients.

Since the sample size of the participants in the exercise program was small and not normally distributed, a non-parametric Wilcoxon Signed-Rank test was used when comparing the Exercise group with the Control group, before and after the intervention.

Lastly, a Mann-Whitney U test was used, to compare independent samples of the Exercise Group to those of the Control Group. Results with p values lower than 0.05 were considered significant. The analysis was carried out through the IBM SPSS Statistics software (IBM Corporation, 2016).

4.6 Ethical considerations

In 2004, an act about the research involving human subjects passed legislation. All

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distributed over the two groups (Marini et al., 2019). The Independent Ethics Committee, Azienda Ospedaliera di Bologna, Policlinico S. Orsola-Malpighi approved the study (ref.

143/2014/U/Sper; Marini et al., 2019).

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4. Results

A group of osteoporosis patients consisting of 40 postmenopausal women was compared to a similar group of the average Italian population with regard to their perception of quality of life. The objective was to determine if osteoporosis could affect markers linked to quality of life. The EQ-5D index value was significantly lower for the osteoporosis patients, which indicated that osteoporosis had a negative impact on the experienced quality of life. The markers that significantly differed across the two populations were:

Mobility, Usual Activities, Pain/Discomfort and Anxiety/Depression. Self-care was the only marker that did not significantly differ between the osteoporosis patients and the average Italian population (Table 1).

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Table 1.

Markers for quality of life at start of the study - a comparison between Italian osteoporosis patients and a gender and age-controlled average Italian population.

Significant differences are highlighted in bold (p ≤ 0.05)

MARKER FOR QUALITY OF LIFE (3 levels for health evaluation by EQ-5D-3L¹)

OSTEOPOROSIS PATIENTS n = 40 n (%)

AVERAGE ITALIAN POPULATION

n = 247

n (%) p value

MOBILITY 1. NO PROBLEM 2. SOME PROBLEMS 3. CONFINED TO BED

25 (62.5) 15 (37.5) 0 (0.0)

175 (68.5) 71 (31.2) 1 (0.3)

0.720 0.001 0.690 SELF-CARE

1. NO PROBLEM 2. SOME PROBLEMS 3. UNABLE TO WASH OR DRESS

35 (87.5) 5 (12.5) 0 (0.0

220 (88.1) 24 (10.9) 3 (1.0)

0.770 0.590 0.480 USUAL ACTIVITES³

1. NO PROBLEM 2. SOME PROBLEMS 3. UNABLE TO PERFORM

22 (55.0) 18 (45.0) 0 (0.0)

187 (73.8) 54 (23.9) 6 (2.3)

0.006 0.002 0.320 PAIN/DISCOMFORT

1. NO PROBLEM

2. MODERATE PROBLEMS 3. EXTREME

8 (20.0) 31 (77.5) 1 (2.5)

114 (44.6) 117 (48.1) 16 (7.3)

0.002 0.001 0.320 ANXIETY/DEPRESSION

1. NO PROBLEM

2. MODERATE PROBLEMS 3. EXTREME PROBLEMS

22 (55,0) 16 (40,0) 2 (5.0)

200 (79,7) 43 (18,8) 4 (1.5)

0.001 0.001 0.170

PARAMETER

OSTEOPOROSIS PATIENTS MEAN (SE)

AVERAGE ITALIAN POPULATION

MEAN (SE) p value EQ-5D INDEX⁴ 0.607 (0.049) 0.783 (0.015) 0.001

EQ VAS SCORE⁵ 67.8 (2.6) 65.3 (1.5) 0.410

1EQ-5D-3L; Descriptive system of the markers linked to quality of life with 3 levels of self-experienced health, where 1 is no problem, 2 signifies some- or moderate problems and 3 indicates extreme problems (Rabin & de Charro, 2001).

2A two proportion Z-test was used to compare the two populations and obtain a probability of results (p value)

3Ability to participate in leisure activities, work, studies, housework, etc. It does not include the use of public transportation, car, bicycle, etc. (Brooks et al., 2003)

4Mean (SE) score of the EQ-5D composes the EQ-5D index value, in which the levels are: 1 (full health), 0 (a state as in being dead) and below 0, a state worse than being dead (ibid; EuroQol Research Foundation 2018; Patrick et al., 1994)

5Mean score for EQ VAS (%)

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The second part of the study consisted of an evaluation of an intervention within the group of the same 40 postmenopausal women, which were affected by osteoporosis and living in Bologna, Italy. The study assessed the effect of physical exercise on markers of quality of life among these patients (Table 2).

Table 2.

Inter-group comparison of 40 osteoporosis patients between an exercise group and a control group, pre- and post-intervention

MARKER FOR QUALITY OF LIFE

EXERCISE GROUP n = 22

CONTROL GROUP n = 18

EXERCISE GROUP n = 22

CONTROL GROUP n = 18

Pre-intervention Post-intervention

Median (range) p value¹ Median (range) p value MOBILITY 1.5 (1) 1.0 (1) 0.096 1.0 (1) 1.0 (1) 1.000

SELF-CARE 1.0 (0) 1.0 (1) 0.180 1.0 (1) 1.0 (1) 0.968 USUAL

ACTIVITES² 2.0 (1) 1.0 (1) 0.262 1.0 (1) 1.0 (1) 0.199 PAIN/

DISCOMFORT 2.0 (2) 2.0 (2) 0.697 2.0 (1) 2.0 (1) 0.717 ANXIETY/

DEPRESSION 2.0 (2) 2.0 (2) 0.199 2.0 (1) 2.0 (1) 0.132 EXERCISE

GROUP

CONTROL

GROUP EXERCISE

GROUP CONTROL GROUP

PARAMETER Mean (SE) p value Mean (SE) p value EQ-5D INDEX 0.53 (1.46) 0.68 (0.81) 0.095 0.62 (0.92) 0.74 (0.81) 0.694 EQ VAS 68 (70) 72 (60) 0.251 70 (75) 70 (70) 0.381

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Table 2 shows a comparison between the Exercise Group and the Control Group at the beginning (pre) and the end of (post) intervention. The Mann-Whitney U test showed that the Exercise Group experienced more problems with Mobility than the Control Group at the beginning of the study. At the end of the intervention, the Exercise Group showed the same value as the Control Group for Mobility.

The Exercise Group also experienced more problems in performing Usual Activities at the beginning of the intervention compared to the Control Group. At the end of the intervention, the Exercise Group showed the same value as the Control Group for Usual Activities.

Comparisons within each of the groups

The Exercise Group and the Control Group were also compared internally over time, in the beginning and at the end of the intervention, to see how physical exercise could have affected the markers linked to quality of life.The Exercise Group tended to experience fewer problems with Mobility post-intervention as compared to pre-intervention. The Exercise Group also tended to experience an improvement in performing Usual Activities post-intervention, as compared to pre-intervention. However, the differences observed did not reach statistical significance (Table 3).

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Table 3.

Intra-group comparison of 40 osteoporosis patients within an exercise group and a control group through repeated measures, pre and post intervention

MARKER FOR QUALITY OF LIFE

EXERCISE GROUP n = 22

CONTROL GROUP n = 18

Median (range) Median (range

Pre Post p value¹ Pre Post p value

MOBILITY 1.5 (1) 1.0 (1) 0.096 1.0 (1) 1.0 (1) 1.000

SELF-CARE 1.0 (1) 1.0 (1) 0.180 1.0 (1) 1.0(1) 1.000 USUAL

ACTIVITES² 2.0 (1) 1.0 (1) 0.257 1.0 (1) 1.0(1) 0.083 PAIN/

DISCOMFORT 2.0 (2) 2.0 (2) 0.608 2.0 (1) 2.0 (1) 0.564 ANXIETY/

DEPRESSION 2.0 (2) 2.0 (2) 0.317 2.0 (1) 2.0 (1) 0.317

PARAMETER

EXERCISE GROUP CONTROL GROUP

Mean (SE) p value Mean (SE) p value

EQ-5D

INDEX 0.53 (1.4) 0.64 (0.92) 0.224 0.68 (0.81) 0.74 (0.81) 0.694

EQ VAS 68 (70) 70 (75) 0.126 72 (60) 70 (70) 0.503

1Medians and ranges are presented with p values of a Wilcoxon paired repeated measures test

2Ability to participate in leisure activities, work, studies, housework etc. It does not include usage of public transportation, car, bicycle etc. (Brooks et al., 2003)

3 Mean (SE) score of the EQ-5D composes the EQ-5D index value, in which the levels are: 1 (full health), 0 (a state as in being dead) and below 0, a state worse than being dead (ibid; EuroQol Research

Foundation 2018; Patrick et al., 1994)

4 Mean score for EQ VAS (%)

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6. Discussion

6.1 Discussion of Results

The results showed that the osteoporosis patients experienced an overall lower quality of life than the average Italian population. Osteoporosis seemed to cause lower quality of life particularly as regards Mobility, Usual Activities, Pain/Discomfort and Anxiety/Depression. These findings agree with studies of others (Gold et al., 2019, Silverman et al., 2001). For example, a Korean study of 196 osteoporosis patients reported similar trends for markers linked to quality of life (Jung et al., 2017). Just as in the present study, it examined the impact of osteoporotic vertebral fractures on quality of life, through the EQ-5D questionnaire. A comparison to a reference population was also made, which concluded that osteoporosis significantly reduced quality of life.

Regarding Mobility, a greater proportion of the osteoporosis patients in the present study experienced some problems (37.5%) as compared to the average Italian population (31.2%). The impact of osteoporosis on the Mobility marker was also significant in the Korean study (Jung et al., 2017). Other studies confirm these results; Silverman et al., 2001) reported significantly lower physical function in postmenopausal women with osteoporotic vertebral fractures; A Norwegian study showed that pain caused by vertebral fractures mainly affected Mobility through decreased walking speed (Stanghelle et al., 2019). Not only Pain/Discomfort due to a fracture would make it difficult to walk, but also the psychological impact from the fear of falling, which can lead to the belief that one small mistake can cause a new fracture. This may in turn lead to social isolation and a sedentary lifestyle. Thus, it will decrease Mobility further and similarly affect Usual Activities; both events render the patient less independent. In the present study, almost half (45%) of the osteoporosis patients reported some problems in performing Usual Activities, which agrees with findings by Jung et al. (2017). Moreover, there was a higher percentage of osteoporosis patients that experienced Pain/Discomfort as compared to the average Italian population. Only 20% of the patients reported no Pain/Discomfort. Studies on vertebral fractures agree with these results. An Australian study of persons with low bone mass (osteoporosis and/or osteopenia), reported Pain/Discomfort as the marker that was most negatively affected (Gandham et al., 2019). Numerous studies have reported the correlation between vertebral fractures and pain, as reviewed by Silverman et al.

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(2001) and Koevska et al. (2019). Osteoporosis is generally not painful, but it increases the risk of obtaining a fracture. During a fracture acute pain may occur, which can cause persistent Pain/Discomfort (National Health Service, 2019). In the present study, all the patients were affected by vertebral fractures, which may have resulted in chronic pain.

Consequently, Pain/Discomfort significantly affected their quality of life, as seen in Table 1. The individual that has suffered a personal trauma and ensuing Pain/Discomfort may become more careful, due to fear of falling, thus getting habituated to avoiding Usual Activities, which also lowers his/her Mobility. A low self-confidence in physical ability and changed body image may cause depression, thus possibly resulting in a change in Anxiety/Depression. Depression can cause social isolation, which leads to further depression and lack of motivation, which in turn can result in the avoidance of physical exercise, and further loss of bone strength ensues (Kerr et al., 2017). A slight negative trend for Anxiety/Depression was seen in the osteoporosis patients as compared to the average Italian population, which agrees with the Korean study, in which a significantly larger proportion of osteoporosis patients experienced Anxiety/Depression as compared to the reference population (Jung et al., 2017). The psycho-social impact of osteoporosis, which results in Anxiety/Depression has been thoroughly reviewed (Gold, 1996;

Silverman et al., 2001; Kerr et al., 2017). As described by Gold (1996), vertebral fractures cause psychological disorders, such as anxiety, depression or bad self-esteem. These complex issues are difficult to differentiate by using the EQ-5D-3L, which measures Anxiety/Depression as a single marker. In the present study, Self-care was the only marker that was not significantly affected by osteoporosis, which agreed with the results of Gandham et al. (2019). The reasons for this will be addressed in the section entitled:

Discussion of Methods.

An exercise program, which had specifically been adapted for women with osteoporosis

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life in osteoporosis patients specifically regarding physical function and social activities (Koevska et al., 2019). Physical exercise has a positive effect on muscle tone, balance and agility; which facilitate Mobility and Usual Activities, which include social activities.

Bone strength can be enhanced through physical exercise, although it is not always visible by DXA-measurement of the bone (Polidoulis et al., 2012). Exercise did not significantly improve Pain/Discomfort in the present study. A possible reason for that could be that Pain/Discomfort may have been present throughout the study. This will be further discussed in the Discussion of Methods.

All of the osteoporosis patients in the exercise program had been affected by one or multiple vertebral fractures (Marini et al., 2019). As already mentioned and according to several studies, these have an exceptionally negative impact on quality of life (Gold, 1996; Begerow et al., 1999; Silverman et al., 2001; Lips & van Schoor, 2005; Borgström et al., 2005; Jung et al., 2017; Gibbs et al., 2019; Gold et al., 2019; Koevska et al., 2019).

Swedish researchers found that after two years, a hip fracture affected some markers linked to quality of life, whereas a vertebral fracture affected quality of life in all areas (Hallberg et al., 2004). In the present study, comorbidities were present in over 90% of the patients (Marini et al., 2019). A hypothesis is that these consequences for quality of life and physical function may explain the results of low quality of life among the osteoporosis patients (Table 1) and the non-significant effect on quality of life through physical exercise, even though a slightly positive trend was visible (Table 2). Morbidity of vertebral fractures must be considered by those who design an exercise program.

Marini et al. (2019) provided a safe program for the patients. However, there could be confounding effects; the present study used a generic questionnaire, which could have led to difficulty in assessing osteoporosis-specific factors within each marker, since theses factors could have been overlooked. Taking into account that the exercise had to be relatively mild to avoid injuries and the limited time given; twice a week for six months, the exercise program was perhaps not long enough to see clear results, particularly for Pain/Discomfort or Anxiety/Depression, which were significantly affected by osteoporosis (Table 1). The effects on quality of life may have been too subtle to be detected within six months. Also, patients with vertebral fractures have general difficulties to exercise, according to Silverman (1992). In other words, vertebral fractures may have such a negative impact on all markers that it may be difficult to obtain significant results. Nevertheless, there were slightly positive effects of physical exercise, which may in part have been due to the safety precautions taken.

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Studies have so far gathered little evidence for physical exercise being beneficial to patients with vertebral fractures (Gibbs et al., 2019). A therapeutic exercise review of nine studies showed improvement in strength and balance, but results for pain and quality of life were inconsistent (Dusdal et al., 2011). During the past ten years, systematic reviews of physical exercise have confirmed certain benefits in specific markers such as pain, but not consistently evident results for the overall improvement of quality of life.

The conclusion was that more evidence is required (Gibbs et al., 2019). The effects of physical exercise after a vertebral fracture were only analyzed in seven trials, according to Giangregorio et al. (2013) i.e. the first edition of the review by Gibbs et al. (2019). The studies above had limitations, such as lack of long-term follow-up, bias and small sample sizes (ibid). Similarly, the present study of postmenopausal women with osteoporosis had similar drawbacks. To be able to prescribe exercise for patients with vertebral fractures, a review study by Giangregorio et al. (2013) concluded that a randomized trial of high quality is required. The Too Fit to Fracture expert panel, including clicicians and researchers from Australia, Canada, Finland and the U.S., recommended safe exercise and professional consultation for osteoporosis patients with vertebral fractures, since negative effects may outweigh the positive for those with multiple fractures, pain, etc., such as in the present study (Giangregorio et al., 2014; Marini et al. 2019).

Margaret Martin, Physical Therapist, referred to an exercise trial by Sinaki and Mikkelsen (1984) that investigated suitable exercises for the spine (vertebrae) among a group of postmenopausal women. Some of these women complained about back pain and were examined by DXA. The screenings showed that a larger proportion of those who performed flexion exercises had fractures (89%) compared to those who performed extension exercises (16%). This shows that caution needs to be taken for patients with vertebral fractures. According to Martin, physical trainers may ordinate exercise for spine-problems that is good for the average population but not for persons with

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population norm, while the present study used the Italian one. The present study evaluated how osteoporosis interferes with the markers linked to the quality of life by using previously unevaluated data and identified a possible of trend in some of these markers regarding the positive effect of physical exercise, with almost half a unit (i.e. from 1.5 to 1.0). However, the results were not statistically significant.

6.2 Discussion of Methods

In order to evaluate the methods and possible flaws, it was necessary to find comparable studies, i.e. those with an exercise program, similar inclusion criteria and study design.

Exercise studies for osteoporosis patients are rare (Marini et al., 2019). The present study was mainly compared to a quality of life study, by Jung et al. (2017), and a similar physical exercise study involving osteoporotic women, by Koevska et al. (2019).

These two studies applied two different questionnaires: EQ-5D and QUALEFFO-41, respectively. The pilot study by Marini et al. (2019) and the present thesis utilized the EQ-5D-3L. The EQ-5D was assumed to be an appropriate instrument for the present study as it is associated with the assessment of quality of life, related to osteoporotic spinal dysfunctions and back pain (Jung et al 2017). As mentioned earlier, the QUALEFFO-41 is specific for measuring quality of life in patients with vertebral fractures, while the EQ- 5D is a generic quality-of-life questionnaire. Because the more detailed questionnaire of QUALEFFO-41 includes 41 questions instead of 5, as is the case for the EQ-5D-3L questionnaire, difficulties arose in comparing the results of the current study with those of the exercise study by Koevska et al. (2019). The EQ-5D-5L, a newer version of the questionnaire, was used by Jung et al. (2017). The EQ-5D-3L is supposed to cover a category of problems within only five markers and provides only three answer options.

Patients may therefore find it confusing, or simply tick boxes only because they are supposed to. This may also be a source of error for the results obtained in the EQ VAS.

According to Kerr et al. (2017), clinical trials seldom estimate patient-reported outcomes, and in case they do, they only include a small number of markers. This results in difficulty in observing significant changes resulting from the treatment.

The short time-span was another possible limitation, aside from the shortcomings of the questionnaire. The exercise program lasted for six months, which Jung et al. (2017)

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referred to as the required time for a vertebral fracture to heal. Even so, severe pain would have been present for up to one year after a fracture had healed. According to Huang et al. (1996), back pain may last for up to four years after a vertebral fracture. The time since a fracture occurred seemed to affect quality of life more than the number of fractures, as interpreted by Begerow et al. (1999), who found that the pain started to decrease within two years. The longer duration of the exercise program in the study by Koevska et al.

(2019) may have produced a clearer effect of physical exercise than the exercise study in the present thesis. It had more participants (92) who also exercised three times a week, instead of twice a week, as in the present study. Unfortunately, the time period that had elapsed since the last fracture of the patients in this study was not recorded (Marini, pers.

comm). The short duration of the intervention may be a reason why physical exercise did not significantly improve the overall quality of life, nor influence the specific markers:

Pain/Discomfort, Anxiety/Depression and Self-care in the present study.

A possible selection bias could also have occurred, since participation in the exercise program was non-randomized. The two groups were supposed to be randomized, but all patients did not want to join the Exercise Group (Marini et al., 2019). The participants in the Exercise Group generally experienced lower health and physical fitness at the beginning of the program, which could have led to an emphasis on adjustments to meet the ability of each patient. Due to the risk of injuries, the study focused on feasibility and safety with weight-free strengthening exercises, which could have led to a limited physical challenge. There were no injuries during the study, so the program was safe. The results obtained with the EQ-5D questionnaire did not detect any influence of the exercise program on perceived quality of life.

The design of the study by Koevska et al. (2019) was randomized and single-blinded, thus, it had a superior design in preventing manipulation or bias. It consisted of three

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The low number of participants in the exercise program of the present study could have been due to difficulties in enrolling osteoporosis patients on a voluntary basis. Few participants may have resulted in a large standard error, which could have caused the absence of significant results. Moreover, some change in the markers for quality of life in osteoporosis patients, through participation in the exercise program, may not have been possible to detect. For example, self-esteem is a contributing factor to life satisfaction and a higher quality of life. Physical improvement could have led to feelings of confidence and self-esteem among these patients (Marini et al., 2019). The study by Koevska et al. (2019), which applied a detailed questionnaire, did observe improved social life, which highlighted the involvement of social factors. The social aspect of exercise is also important to the quality of life (Marini et al., 2019; Kendler et al., 2015).

Moreover, sense of coherence has been proven useful as a tool to improve quality of life after osteoporotic fractures, as seen in the study by Begerow et al. (1999). Sense of coherence is defined as an individual’s ability to stay healthy through stress management and health promotion (Antonovsky, 1987). Therefore, it may contribute to quality of life through improvement of self-reliability and Self-Care.

Regarding Self-care, there were no significant results in the population study (Table 1), nor in the exercise study (Table 2 & 3). The Italian women in the present study did not experience considerable problems with Self-care. Similarly, none of the Australian women in the study by Gandham et al. (2019) experienced Self-care problems. Just as in the present study, these community dwelling women were reasonably mobile and lived in a large metropolitan area. Even though the osteoporosis patients in the present study had suffered vertebral fractures that were assumed to be painful, they were in fact ambulating and lived at home (Marini et al., 2019). Feelings of uneasiness caused by pain does not necessarily render a person incapable of Self-care. Vertebral fractures are not homogenous, and the levels of pain may vary. The pain is usually most severe during the first six weeks after a fracture, after which it gradually declines. In other cases, the pain may initially be mild, and then intensify after 6-16 weeks (Lyritis et al., 1989; Silverman, 1992). Moreover, the Australian women were to have had a maximum of 150 minutes of self-reported exercise per week prior to the study, in order to be included (Gandham et al., 2019). Just as in the present study, these women were reasonably mobile. A conclusion can thus be drawn that the inclusion criteria could have influenced Self-care.

Regarding the exercise study, the Exercise Group tended to have lower initial Mobility

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as compared to the Control Group. It could also have been a factor as to why the persons in the Exercise Group opted to participate in the exercise program. By engaging in physical exercise, they could "catch up" in Mobility. Moreover, a decrease in Mobility can affect Self-care, so since Mobility improved from exercise, it could also explain why osteoporosis did not affect Self-care among the exercising women in this study.

6.3 Future Research

Despite the short duration, the results of the present study were promising and can be a starting point to design future research, taking into account the following considerations:

• A longer period is needed for exercise studies to detect changes in the overall quality of life and markers related to the quality of life. This would include a long-term randomized exercise trial with a follow-up for at least 12 months, as suggested by Gibbs et al., (2019).

• The safety of the exercise protocol plays a key role in the main intervention program for osteoporosis patients. In the present study, the safety aspect was taken into consideration when designing the exercise program. It showed the importance of including exercise to maximize strength and vitality of the spine, combined with balance training to prevent falls.

• The selection of an appropriate questionnaire for assessing quality of life in osteoporosis patients is important for interpreting the results. Quality of life is complex and may be defined differently according to the cultural habits or behavioral patterns within a country.

• Since every patient had vertebral fractures, an osteoporosis-specific questionnaire might have been more suitable, as mentioned by Lips & van Schoor (2005). A combination of specific and generic methods for evaluation of quality

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7. Conclusions

The overall results obtained in this study confirm that osteoporosis negatively affected quality of life for postmenopausal women. In particular, osteoporosis negatively affected the markers Mobility, Usual Activities, Pain/Discomfort and Anxiety/Depression in the studied population. Moreover, the exercise program seemed to improve some markers linked to quality of life, even if the results did not reach a statistical significance. On the basis of this evidence, it is possible to propose that health care systems consider the impact of osteoporosis on quality of life, since a vertebral fracture, a prevalent result of the disorder, is devastating to the individual. Evaluation of osteoporosis needs to be prioritized and supportive networks have to be established. This will contribute to social and economic sustainability.

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8. References

Agostini, D., Donati, S. Z., Lucertini, F., Annibalini, G., Gervasi, M., Ferri Marini, C., Piccoli, G., Stocchi, V., Barbieri, E., & Sestili, P. (2018). Muscle and bone health in postmenopausal women: Role of protein and vitamin D

supplementation combined with exercise training. Nutrients, 10(8), 1103.

https://doi.org/10.3390/nu10081103

Antonovsky, A. (1987) Unraveling the mystery of health: How people manage stress and stay well. Jossey-Bass.

Auais, M., Al-Zoubi, F., Matheson, A., Brown, K., Magaziner, J., & French, S. D.

(2019). Understanding the role of social factors in recovery after hip fractures: A structured scoping review. Health & Social Care in the Community, 27(6), 1375–1387. https://doi.org/10.1111/hsc.12830

Begerow, B., Pfeifer, M., Pospeschill, M., Scholz, M., Schlotthauer, T., Lazarescu, A., Pollaehne, W., & Minne, H. W. (1999). Time since vertebral fracture: An important variable concerning quality of life in patients with postmenopausal

(41)

Brooks, R., Rabin, R., & de Charro, F. (Eds.). (2003). The measurement and valuation of health status using EQ-5D: A European perspective. Dordrecht:

Springer

Brooks, R., Boye, K. S., & Slaap, B. (2020). EQ-5D: A plea for accurate nomenclature. Journal of Patient-Reported Outcomes, 4, 52.

https://doi.org/10.1186/s41687-020-00222-9

Borgström, F., Zethraeus, N., Johnell, O., Lidgren, L., Ponzer, S., Svensson, O., Abdon, P., Ornstein, E., Lunsjö, K., Thorngren, K. G., Sernbo, I., Rehnberg, C.,

& Jönsson, B. (2006). Costs and quality of life associated with osteoporosis- related fractures in Sweden. Osteoporosis International, 17(5), 637–650.

https://doi.org/10.1007/s00198-005-0015-8

Choi, M., Prieto-Merino, D., Dale, C., Nüesch, E., Amuzu, A., Bowling, A., Ebrahim, S., & Casas, J. P. (2013). Effect of changes in moderate or vigorous physical activity on changes in health-related quality of life of elderly British women over seven years. Quality of Life Research, 22(8), 2011–2020.

https://doi.org/10.1007/s11136-012-0332-2

Cauley, J. A., Thompson, D. E., Ensrud, K. C., Scott, J. C., & Black, D. (2000). Risk of mortality following clinical fractures. Osteoporosis International, 11(7), 556–561.

https://doi.org/10.1007/s001980070075

(42)

Cipriani, C., Pepe, J., Bertoldo, F., Bianchi, G., Cantatore, F. P., Corrado, A., Di Stefano, M., Frediani, B., Gatti, D., Giustina, A., Porcelli, T., Isaia, G., Rossini, M., Nieddu, L., Minisola, S., Girasole, G., & Pedrazzoni, M. (2018). The

epidemiology of osteoporosis in Italian postmenopausal women according to the National Bone Health Alliance (NBHA) diagnostic criteria: A multicenter cohort study. Journal of Endocrinological Investigation, 41(4), 431–438.

https://doi.org/10.1007/s40618-017-0761-4

Cosman, F., de Beur, S. J., LeBoff, M. S., Lewiecki, E. M., Tanner, B., Randall, S., Lindsay, R., & National Osteoporosis Foundation. (2014). Clinician's guide to prevention and treatment of osteoporosis. Osteoporosis International, 25(10), 2359–2381. https://doi.org/10.1007/s00198-014-2794-2

Cranney, A., Jamal, S. A., Tsang, J. F., Josse, R. G., & Leslie, W. D. (2007).

Low bone mineral density and fracture burden in postmenopausal women.

Canadian Medical Association Journal, 177(6), 575–580.

https://doi.org/10.1503/cmaj.070234

Cummings, S. R., Black, D. M., Nevitt, M. C., Browner, W., Cauley, J., Ensrud, K., Genant, H. K., Palermo, L., Scott, J., & Vogt, T. M. (1993). Bone density at

(43)

Dusdal, K., Grundmanis, J., Luttin, K., Ritchie, P., Rompre, C., Sidhu, R., &

Harris, S. R. (2011). Effects of therapeutic exercise for persons with osteoporotic vertebral fractures: A systematic review. Osteoporosis

International, 22(3), 755–769. https://doi.org/10.1007/s00198-010-1497-6

EuroQol Research Foundation. (2020). Terminology. EQ-5D.

https://euroqol.org/support/terminology

EuroQol Research Foundation. (2018). EQ-5D-3L User Guide: Basic Information on how to use the EQ-5D-3L Instrument (Version 6.0). EQ-5D.

https://euroqol.org/publications/user-guides

Fechtenbaum, J., Cropet, C., Kolta, S., Horlait, S., Orcel, P., & Roux, C. (2005).

The severity of vertebral fractures and health-related quality of life in

osteoporotic postmenopausal women. Osteoporosis International, 16(12), 2175–

2179. https://doi.org/10.1007/s00198-005-2023-0

Felsenberg et al. (2002). Incidence of vertebral fracture in Europe: Results from the European Prospective Osteoporosis Study (EPOS). Journal of Bone and Mineral Research, 17(4), 716–724. https://doi.org/10.1359/jbmr.2002.17.4.716

Gandham, A., McMillan, L. B., Ng, C. A., Humbert, L., Bonham, M. P., Zengin, A., Ebeling, P. R., & Scott, D. (2019). Associations of health-related quality of life, fear of falling and objective measures of physical function with bone health

Postmenopausal Women with Osteoporosis: The Effect of Physical Exercise on Markers Linked to Quality of Life

FACULTY OF HEALTH AND OCCUPATIONAL STUDIES