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

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.

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

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.

Nyckelord: osteoporos, livskvalitet, fysisk träning, postmenopausala kvinnor,

ryggradsfrakturer

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.

Table of Contents 1. Introduction ......................................................................................................... 1

1.1 Osteoporosis as a Public Health concern ..................................................................... 1 1.2 Development of Osteoporosis; the Effect of Physical Exercise and Lifestyle ................. 2 1.3 Osteoporosis and Quality of Life ................................................................................. 4

2. Aim of the Study ................................................................................................... 7

3. Research Questions .............................................................................................. 7

4.Methods ................................................................................................................ 8 4.1 Study Design .............................................................................................................. 8 4.2 Selection Criteria ........................................................................................................ 8 4.3 Data Collection and Questionnaire ............................................................................. 8 4.4 Conducting the study ............................................................................................... 14 4.5 Data Analysis ........................................................................................................... 15 4.6 Ethical considerations .............................................................................................. 15

4. Results ............................................................................................................... 17

6. Discussion .......................................................................................................... 22 6.1 Discussion of Results ................................................................................................ 22 6.2 Discussion of Methods ............................................................................................. 26 6.3 Future Research ....................................................................................................... 29

7. Conclusions ........................................................................................................ 30

8. References.......................................................................................................... 31

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,

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

measures of prevention of osteoporosis; these strategies may also help to speed up the

healing of fractures. This thesis was based on a collaborative research trial between the

University of Bologna, health care practitioners, and osteoporosis patients. During the

present study, I have concluded that cooperation among researchers and patients to

prevent the impact of fragility fractures, such as comorbidities, needs to become a top

priority for health authorities. Osteoporosis is currently a hot topic, and how it affects

different markers of quality of life is what mostly made me consider to investigate this

subject. While the pandemic of COVID-19 is going on, another pandemic of osteoporosis

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

disorder (Cosman et al., 2014; Lentle et al., 2007). The presence of vertebral fractures,

i.e. fractures localized to the vertebrae of the spine, is widely recognized as an indication

of osteoporosis. These fractures negatively influence physical function, leading to limited

mobility (Borgström et al., 2005; Recknor et al., 2013; Koevska et al., 2019). As reviewed

by Madureira et al. (2012), vertebral fractures may reduce quality of life through lumbar

back pain and comorbidities, such as reduced functions of the heart, lungs and urinary

system. The European Prospective Osteoporosis Study found that incidence rates of

vertebral fractures were higher in Sweden than in any other European country (Felsenberg

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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

is crucial for individuals with fractures. As explained by Sinaki (2012), exercise may be

helpful to manage osteoporosis, but could even be harmful to individuals with vertebral

fracture, if not conducted properly. Spine-flexing activities, including twisting and

bending of the spine, such as in yoga or Pilates, have been shown to cause vertebral

fractures and should be avoided (Sinaki., 2013).

Overall, the population in modern society is successively becoming more sedentary

(Owen et al., 2020). Some risk factors for morbidity include physical inactivity, such as

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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

9

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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11

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

© EuroQol Research Foundation. Reproduced by permission of EuroQol Research Foundation.

EQ-5DTM 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

generating the EQ-5D index, which is a measure of the level of health of the studied

population. All the values or weights attached to the markers were based on societal

standards of the country-specific version. That is, the average population of a country has

given values for VAS-valuation or time-trade-off. The EQ-5D index value ranges from -

0.171 to 1. An individual with a score of 0 was considered to be dead, whereas an

individual with a score of 1 experienced the best possible health. To calculate the index,

the appropriate country values can be deducted from the value of full health, which is

11111. The calculation of quality-adjusted life years is applied through this index and

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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

15

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

research involving human subjects must be given the permission by an ethics committee.

According to the United Nations Declaration of Human Rights, all individuals have the

right to integrity (Swedish Research Council, 2017). Some women did not want to be part

of the Exercise Group, for different reasons. Therefore, the patients included in the

Exercise Group, voluntarily opted to take part in the physical exercise program. Freedom

of choice is an important ethical aspect. The fact that patients freely could choose to

participate in the program could have had a positive effect on their willingness to adhere

to the exercise program. It also meant that the osteoporosis patients were not randomly

16

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).

17

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).

18

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 (%)

19

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

CONTROLGROUP

n = 18

EXERCISE GROUP n = 22

CONTROLGROUP 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

CONTROLGROUP

EXERCISE GROUP

CONTROLGROUP

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

1Medians and ranges are presented with p values from an independent sample of a Mann-Whitney U 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)

3Mean (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 (%)

20

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).

21

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 (%)

22

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.

23

(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

was evaluated in this study. The effect of exercise on the overall quality of life was not

conclusive, in part due to the small sample size in combination with the blunt EQ-5D-3L

instrument, which together generated a large standard error. The EQ-5D index value

tended to increase at the end of the intervention period (after six months), which indicated

that physical exercise could have slightly improved the quality of life for women with

osteoporosis. At the end of the study, it appeared as if the Exercise Group had improved

their performance of Usual Activities, from 2.0 to 1.0 (p = 0.083). These results were not

significant. However, a similar study demonstrated significant improvement of quality of

24

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.

25

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

osteoporosis or low bone mass (Martin, M., 2014). It is important to select a physical

exercise program, which is safe and adapted to osteoporosis patients to prevent vertebral

fractures and improve their physical performance and quality of life.

Osteoporosis affects both the relationship with friends and family; thus, social support is

crucial. Health care systems need to pay attention, not only to bone fragility but to

psychological, social and environmental factors, which are all associated with quality of

life (Gold, 1996). As mentioned in the Introduction, the health values in EQ-5D-3L are

country-specific. Therefore, Jung et al. (2017) have obtained results based on the Korean

26

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)

27

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

groups instead of two, including a group that combined physical exercise with modalities

of magnetic- and interferential current therapy (for pain reduction) every weekday for 3

weeks. The participants were younger (mean age was 60) than in the present study. Age

could have affected the quality of life in osteoporosis patients and incidence of vertebral

fractures (ibid; Gold et al., 2019; Felsenberg et al., 2002). The randomized design,

younger participants and a longer exercise program with pain-reducing magnetic-and

interferential therapy; could be reasons why the exercise program by Koevska et al.

(2019) resulted in significant improvement.

28

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

29

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

of life, through the application of both QUALEFFO-41 and EQ-5D-5L, could be

an option. The answers of a questionnaire have subjective elements. The use of

more than one tool can contribute to a deeper understanding of the analyze of the

studied population.

30

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.

31

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