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UNIVERSITY OF ZIMBABWE

Faculty of Medicine

College of Health Sciences

DEPARTMENT OF NURSING SCIENCE

A study to determine the relationship between

prevalence of late stage diagnosis of cervical cancer and

number of comorbid illnesses in women aged 65 years

and above in Zimbabwe.

Submitted by Yvonne Kagura in partial fulfilment of the

Masters in Nursing Science Degree Program

June 2015

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ABSTRACT

The elderly are currently the fastest growing population worldwide. Illnesses arising

with advancing age, like hypertension, diabetes mellitus, dementia, Alzheimer’s and vascular

disorders are complicating cervical cancer diagnosis in elderly women. This descriptive,

correlational study was done to explore the relationship between prevalence of late stage

diagnosis of cervical cancer and number of comorbidities in women aged 65 years and above

in Zimbabwe guided by Betty Neuman’s Systems Model. Non-probability sampling was used

to recruit and interview 68 women aged 65 years and above with cervical cancer from

Parirenyatwa Hospital and Spilhause Clinic at Harare Hospital. Data analysis was done using

the Statistical Package for Social Sciences (SPSS), The Pearson’s Correlation coefficient and

simple regression to describe demographic characteristics and dependent and independent

variables. Study findings indicated that the average number of comorbidities suffered by

elderly women before late stage cervical cancer diagnosis was 2.03 with a mean comorbidity

score of 9.03 out of 38 using a modified Charleson Comorbidity Index. The prevalence of

late stage diagnosis was 0.661. Pearson’s correlation coefficient showed a positive and

significant relationship between prevalence of late stage diagnosis of cervical cancer and

number of comorbidities (r = .431, p < 0.01). This result means that the higher the number of

comorbidities in elderly women, the later the stage of presentation with cervical cancer.

There is need to focus early screening of cervical cancer efforts on elderly women to promote

early detection and treatment. The effect of the independent variable is indicated by

significant R² = 0.186 (b = 0.289). This result explains that the number of comorbidities

suffered before cervical cancer diagnosis causes 18.6% of the prevalence of late stage

diagnosis of cervical cancer. Further research is needed to clarify other factors leading to late

stage diagnosis of cervical cancer in elderly women aged 65 years and above in Zimbabwe.

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ACKNOWLEDGEMENTS

I would like to thank my supervisor, Dr H. Zvinavashe, Mrs Nyamakura my mentor

and the whole nursing science department staff for their support during the time this study

was conducted. My gratitude also goes to Professor Rusakaniko, Mr V. Chikwasha and Mrs

M. Kaiyo-Utete from the Department of Medicine for their assistance in data entry and

analysis.

I am thankful to the respective clinical directors at Parirenyatwa Hospital and

Spilhause Clinic for granting permission to carry out the study and the sisters-in-charge of the

various departments from where the research participants were selected from, for ensuring a

peaceful and quiet environment. Special mention goes to the participants without whose

permission; this study would not have been done.

I am grateful to my parents, my brothers Albert and Kudzie, and wonderful sisters

who are all too numerous to mention but were nevertheless psychologically and financially

supportive during the course of this study. God bless you all.

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TABLE OF CONTENTS ABSTRACT ............................................................................................................................... 2

ACKNOWLEDGEMENTS ....................................................................................................... 3

TABLE OF CONTENTS ........................................................................................................... 4

LIST OF FIGURES ................................................................................................................... 7

LIST OF TABLES ..................................................................................................................... 8

LIST OF APPENDICES ............................................................................................................ 9

CHAPTER 1 ............................................................................................................................ 10

BACKGROUND AND ORGANISING FRAMEWORK ................................................... 10

1.1. Introduction ............................................................................................................... 10

1.2. Background ................................................................................................................ 10

1.3. Problem statement ..................................................................................................... 14

1.4. Purpose of the study .................................................................................................. 17

1.5. Research Objectives .................................................................................................. 17

1.6. Research Questions.................................................................................................... 17

1.7. Significance to nursing .............................................................................................. 17

1.8. Theoretical framework .............................................................................................. 19

1.9. Conceptual definition of terms .................................................................................. 23

1.1.0. Summary ................................................................................................................. 24

CHAPTER 2 ............................................................................................................................ 25

LITERATURE REVIEW ..................................................................................................... 25

2.1. Introduction ............................................................................................................... 25

2.2. The cervix .................................................................................................................. 25

2.3. Cervical cancer .......................................................................................................... 26

2.4. Staging ....................................................................................................................... 27

Late stage presentation of cervical cancer............................................................................ 30

2.5. Comorbidity ............................................................................................................... 31

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2.6. Cervical cancer and comorbidity ............................................................................... 35

The Comorbidity Index .................................................................................................... 37

Theoretical framework ..................................................................................................... 39

2.7. Summary .................................................................................................................... 39

CHAPTER 3 ............................................................................................................................ 40

METHODS........................................................................................................................... 40

3.1. Introduction ............................................................................................................... 40

3.2. Research design ......................................................................................................... 40

3.3. Sampling Plan ............................................................................................................ 41

3.4. Study site ................................................................................................................... 41

3.5. Target population ....................................................................................................... 42

3.6. Accessible Population................................................................................................ 42

3.7. Sampling Criteria ....................................................................................................... 42

3.8. Sample Size ............................................................................................................... 43

3.9. Sampling Procedure ................................................................................................... 44

3.1.0. Variables ................................................................................................................. 46

3.1.1. Instrument ............................................................................................................... 47

3.1.2. Validity ................................................................................................................... 47

3.1.3. Reliability ............................................................................................................... 48

3.1.4. Data collection plan ................................................................................................ 48

3.1.5. Data collection procedure ....................................................................................... 49

3.1.6. Human Rights Consideration .................................................................................. 49

3.1.7. Pilot study ............................................................................................................... 50

3.1.8. Data Analysis Plan.................................................................................................. 50

Chapter 4 .................................................................................................................................. 51

Results .................................................................................................................................. 51

4.1. Demographic data ...................................................................................................... 51

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4.2. Cervical cancer .......................................................................................................... 58

4.3. Comorbidity ............................................................................................................... 59

4.4. Correlation ..................................................................................................................... 68

4.5. Regression analysis (n = 68) ......................................................................................... 69

Chapter 5 .................................................................................................................................. 70

Discussion of findings .......................................................................................................... 70

5.1. Demographic data ...................................................................................................... 70

5.2. Late stage cervical cancer diagnosis .......................................................................... 72

5.3. Comorbidity ............................................................................................................... 73

5.4. Study limitations ........................................................................................................ 74

5.5. Recommendations ..................................................................................................... 75

References ............................................................................................................................ 78

APPENDIX I: English Consent form .................................................................................. 83

APPENDIX II: Shona Consent Form .................................................................................. 85

APPENDIX I11: English Interview Guide .......................................................................... 88

APPENDIX 1V: Shona Interview Guide ............................................................................. 92

APPENDIX V: PERMISSION LETTERS .......................................................................... 96

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LIST OF FIGURES

Fig 1: Adaptation of Betty Neuman Systems Model ........................................................................ 23

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LIST OF TABLES

Table 2.0: The FIGO Clinical Staging for Cancer of the Cervix ...................................................... 29

Table 2.1: Modified Charleson Comorbidity Index .......................................................................... 38

Table 4.1.Demographic data (1): Age in years ................................................................................. 52

Demographic data (2): Age when married .................................................................................... 53

Demographic data (3): Number of children .................................................................................. 54

Demographic data (4): .................................................................................................................. 56

Demographic data (5): .................................................................................................................. 57

Table 4.2.1. Diagnosis ...................................................................................................................... 59

Table 4.2.2. Awareness ..................................................................................................................... 61

Table 4.3.0. Comorbidities ................................................................................................................ 62

Table 4.3.1. Comorbidities in elderly women with cervical cancer in Zimbabwe ........................... 63

Table 4.3.1. Score of comorbidities before cancer............................... Error! Bookmark not defined.

Table 4.3.2. Score of comorbidities after the cancer diagnosis......................................................... 65

Table 4.3.3. Total comorbidity score ................................................................................................ 64

Table 4.3.4. Comorbidity scoring summary ..................................................................................... 66

4.4. Correlation ................................................................................................................................. 68

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LIST OF APPENDICES APPENDIX I: English Consent form ............................................................................................... 83

APPENDIX II: Shona Consent Form ............................................................................................... 85

APPENDIX I11: English Interview Guide ....................................................................................... 88

APPENDIX 1V: Shona Interview Guide .......................................................................................... 92

APPENDIX V: PERMISSION LETTERS ....................................................................................... 96

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CHAPTER 1

BACKGROUND AND ORGANISING FRAMEWORK

1.1. Introduction

Cancer is a major cause of morbidity and mortality in Zimbabwe with over 5000 new

diagnoses being made and over 1000 deaths per year National Cancer registry, 2014). The

number of people developing cancer is expected to increase due to an increasing aging

population, HIV and AIDS, and unhealthy lifestyle choices in the population (National

Cancer Prevention and Control Strategy, 2014-2018). Cervical cancer is the number 1 cancer

among women in Zimbabwe, with an estimated 1 855 cases diagnosed and 1 286 deaths

recorded annually due to the disease (National Cancer Registry Annual Report, 2013).

Cervical cancer contributed 19% of all cancer deaths in 2007 (Chokunonga et al, 2010).

Cervical cancer is highly preventable with proper screening and early treatment (Alliance for

Cervical Cancer Prevention, 2014). The average elderly woman in Zimbabwe is living with at

least 1 or 2 chronic illnesses and is prone to frequent contact with the health care provider,

yet there is reduced screening of cervical cancer in these women leading to late diagnosis of

cervical cancer (Nhongo, 2014). It is worthwhile to discover the effect of comorbidity on

prevalence of late stage cervical cancer diagnosis in elderly women in Zimbabwe.

1.2. Background

The elderly are the fastest growing population today. Latest statistics from the Global

Cancer Network (GLOBOCAN) indicate that there were 506 million people aged 65 years

and older in 2008, a number expected to increase to 1.3 billion by 2040 worldwide including

the developing countries (GLOBOCAN, 2012). In the majority of countries, women

constitute 55% of the elderly population with 65% of them aged 80 years and above

(Nhongo, 2014). According to the 2012 population census in Zimbabwe, 758 000 people are

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elderly, which is 6% of the entire population (Zimbabwe National Statistical Agency, 2014).

This increased population ageing is occurring due to several reasons some of which are cited

by Nhongo as declining fertility rates (from 4.5 children per woman in 1994 to 2.7 in 2002),

increased average life expectancy worldwide projecting from 45 years in 1945 to 69 years in

2000 and to an expected 73 years in 2050. In addition, there is improved nutrition, lifestyle

and healthcare in general.

However, with the adoption of cancer causing lifestyles like smoking and fast foods,

the effects of which are evident in the elderly, more elderly people are now living with

malignant conditions which will eventually transition into end of life stages requiring

palliative care and straining an already exhausted health care system especially in poor

resource countries (Jemal et al., 2011).Cancer incidence increases exponentially with

advancing age (Berger, 2006).According to GLOBOCAN, there were about 12.7 million

cancer cases and 7.6 million cancer deaths worldwide in 2008, and approximately 56% of the

cases and 64% deaths occurring in developing countries (Ferlay et al., 2010).Cervical cancer

is the third most commonly diagnosed cancer and the fourth leading cause of female cancer

deaths worldwide (Jemal et al., 2011; WHO, 2014). It accounted for 9% of the total new

cancer cases and 8% of the total cancer deaths among females in 2008 with more than 85% of

these cases and deaths occurring in developing countries (Ferlay et al, 2010; WHO, 2014).

The highest incidence rates are in Eastern, Western and Southern Africa as well as South-

Central Asia and South America (Jemal et al., 2011). In 2011, there were an estimated 249

632 women living with cervical cancer in the United States (Howlader et al, 2013).

According to the American Cancer Association, cervical cancer represents 0.7% of all new

cancer cases in 2014 and 0.7% of all cancer deaths of which more than 15% of the cases are

found in women aged 65 years and above. Records from the national cancer registry have the

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prevalence of cervical cancer in Zimbabwe at 33.5% with 15.6% of that being in elderly

women aged 65 years and above (Zimbabwe National Cancer Registry, 2014).

Early stage cervical cancer can develop over a number of years (between 5-35 years)

without initial symptoms to accompany it (Cancer Association of Zimbabwe, 2014). Cervical

cancer is highly preventable with proper screening and early treatment (Alliance for Cervical

Cancer Prevention, 2014). Qualitative screening techniques in developing countries include

visual inspection using Lugol’s iodine or acetic acid and testing for human papillomavirus

(HPV) DNA in cervical cell samples (Sherris, Withet & Kleine, 2009). This is associated

with about 50% reduction in risk of developing advanced cervical cancer according to a

clinical trial done in rural India (Sankaranarayan et al., 2009). A study done in America found

that cervical cancer screening in women aged 55-79 years is associated with a 77-79%

reduction in cervical cancer incidence (Rustagi et al., 2014). A case only analysis of

Sweden’s cervical cancer screening registry found that women aged 66 years and above

experienced a 36% increase in long term survival if their cancers were detected by screening

rather than clinically. Despite increasingly widespread use of Papanicoloau (Pap) smears,

almost half of all women with invasive cervical cancer are diagnosed at a late stage (Ferrante,

Gonzalez, Roetzheim, Pal & Woodard, 2013). Little is known about factors associated with

late stage diagnosis of cervical cancer. The study by Ferrante et al. (2013) found that women

who are elderly, unmarried and without insurance are more likely to be diagnosed at a late

stage.

Sixty percent of Zimbabwe’s women risk dying from cervical cancer (Chigariro,

2014). Detection is usually late after presentation of uncontrolled or abnormal bleeding and

pain in the 3rd

and 4th

stage when the cancer has already spread to nearby tissue surrounding

the cervix (Cancer Association of Zimbabwe, 2014). Reasons for late diagnosis are lack of

awareness, low risk self-perception, inadequate financial resources, general myths

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surrounding promiscuity, belief that cancer is caused by witchcraft thus delaying in seeking

health care and belief that the excision of cancerous masses result in death (Chigariro &

Nyemba, 2014).

Comorbidities play an important role in survival of women with cervical cancer

(Hatch, Samper-Tement, Zang, Yong-Fang & Freeman, 2014). Patients with comorbid

conditions have greater odds of late stage diagnosis of cancer (Gonzalez, Ferrante, Van

Durme, Naazneen & Roetzheim, 2013). Comorbidity generally increases with advancing age

and may be the reason behind age-related differences in cancer diagnosis, treatment and

outcome. Cancer stage at diagnosis determines treatment options and has strong influence on

length of survival (The American Cancer Association, 2014). The 5 year survival for

localised cervical cancer is 90.9% (Surveillance Epidemiology and End Results Program

[SEER], 2014). Regional or distant stage which occurs when the cancer has spread to other

parts of the body is presented by 53% of the cases and survival rate is low (SEER, 2014). In

developing countries like Zimbabwe, limited access to effective screening means that the

disease is often not identified until it is further advanced and clinical symptoms develop.

Treatment prospects are poor in such cases resulting in higher mortality rate from cervical

cancer in these countries (WHO, 2014). Findings from a study done by Berger (2006) in

America indicated that cancer screening decreases among the elderly and is particularly

deficient among those with comorbid conditions. A survey done by Nhongo in 2014 in

Zimbabwe indicated that more than 75% of rural elderly women are not considered for

cervical cancer screening as they come into clinics or hospitals for any health concern.

Screening efforts in Zimbabwe have focused on the 15-49 year age group as it is considered

the one at highest risk of contracting cervical cancer from the risky lifestyles undertaken

including early onset of sexual activity and douching (Nhongo, 2014). This has resulted in

side-lining of the older age groups who then present with late stage cervical cancer later

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whilst they are now burdened with other comorbid illnesses like hypertension, diabetes,

cardiac failure or other malignancies like breast cancer as this research sought to find out.

Museveni & Tshuma did a cohort study in 198 people with malignant conditions including

colorectal, prostate, breast and lung cancer which indicated that survival rate was

considerably reduced in patients with comorbidities scoring 6 or higher on the Charleson

comorbidity scale (Museveni & Tshuma, 2002). The Zimbabwe National Health Policy does

look at elderly people as deserving of free medical attention but sadly, there is little

implementation in terms of cancer treatment as all ages are expected to fork out large

amounts of money and therefore treatment is unaffordable. There is little research done on

elderly people with cervical cancer and comorbidities and this researcher aimed at adding to

the body of knowledge already existing as the elderly population rises each year.

1.3. Problem statement

Globally cancer is the third leading cause of death and 12 million new cancer cases and 7.6

million cancer related deaths were recorded worldwide in 2008 (WHO, 2014). These figures

are projected to increase to 26 million cases and 17 million deaths by 20130 (WHO, 2014).

Cancer is an emerging public health problem in Africa. According to the International

Agency for Research on Cancer (IARC), about 681,000 new cancer cases and 512,400 cancer

deaths occurred in 2008 in Africa. These numbers are projected to nearly double (1.28

million new cancer cases and 970,000 cancer deaths) by 2030 simply due to the aging and

growth of the population, with the potential to be even higher because of the adoption of

behaviours associated with western lifestyles, such as smoking, unhealthy diet, and physical

inactivity.

There is an increase in elderly women with cervical cancer in the developing world. It is the

leading cancer among women in Zimbabwe (National Cancer Prevention and Control

Strategy, 2014 - 2018). The total number of new cancer cases recorded among Zimbabweans

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in 2012 was 6 107 comprising 2 621 (42.9%) males and 3 486 (57.1%) females. The five

most common cancers among Zimbabwean black women were cervical cancer (33.5%),

breast (11.7%), Kaposi sarcoma (8.9%), eye (6.5%) and non-Hodgkin lymphoma (4.9%)

(National Cancer Prevention and Control Strategy 2014 – 2018).

With the Human Immuno-deficiency Virus (HIV) pandemic leaving orphans and ill spouses,

it is increasingly befalling the elderly to care for them thus leaving little to no time for self-

care, thus forfeiting early and regular cervical cancer screening. According to Ward (2011)

who did a research on the elderly in rural Zimbabwe, he postulated that they were so

encumbered with subsistence farming and sourcing funds for medication for their orphaned

grandchildren and ill children that there are little funds left for themselves and their health.

For those with relatives abroad life becomes a bit easier but then comes the fear factor; fear

of drug-drug interactions, fear of unknown side-effects due to lack of knowledge and fear of

polypharmacy, the elderly who are on treatment for other chronic illnesses believe that they

are taking enough medication already and do not need to add more perceived strain to their

bodies (Chigariro & Nhongo, 2014). In low resource settings like Zimbabwe, unavailability

of the required drugs and memory loss from the normal ageing process add to the resulting

non-adherence leading to development of complications which keep adding to the vicious

cycle of health resource strain. The 2015 National Budget has set aside 13.1 million for the

ministry of health for direct health care with a special mention to the fight against HIV and

AIDS, TB and malaria (Chinamasa, 2014).Whilst the scourge of these illnesses is real there is

need to recognise cancer and especially cervical cancer as a potential pandemic if left

unchecked. It will be a major drain on health resources as most cases are treated in their late

stages thus requiring more aggressive but futile intervention resulting in unprecedented and

unnecessary marginal utilities. Reasons for late cervical cancer diagnosis are cited as lack of

awareness, low risk self-perception and inadequate financial resources (Chigariro, 2014).

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Major barriers to early diagnosis also include general myths surrounding promiscuity, belief

that cancer is caused by witchcraft in case of traditionalists or that it represents possession by

demonic spirits in case of Christians and belief that excision of the cancerous tumour results

in death (Nyemba, 2014).Despite improved screening methods, most women present late with

3rd

and 4th

stage clinical symptoms when the cancer has spread to other tissues and expensive

palliative care is required. Also most of the resources on cervical cancer programs have been

focused on younger women whilst keeping the elderly in the side-lines. Reduced parity and

HIV/AIDS killing more of the younger generation means that there are more elderly people

in the economically productive population of Zimbabwe which has seen the retirement age

moving beyond 65 years. This researcher postulated that comorbidities arise as ageing

advances. In addition to polypharmacy which is confounded by drug-drug interactions, non-

adherence, and unavailability and non- affordability of overall treatment, there is under

reporting of symptoms and delayed treatment of cervical cancer. As comorbidity increases,

there is a tendency to focus more on them by the patients themselves and their health care

providers resulting in non-referral for early screening of cervical cancer. A study done in

America indicated that cancer screening decreases among the elderly and is particularly

deficient among those with comorbid conditions (Berger, 2006).In Zimbabwe, survival rate is

particularly reduced in patients suffering from malignant conditions with added

comorbidities. No studies have been done to assess effect of comorbidity in elderly women

with cervical cancer therefore this researcher sought to establish the relationship between

number of comorbid conditions suffered by elderly women in Zimbabwe and stage at which

cervical cancer is diagnosed.

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1.4. Purpose of the study

The purpose of this study was to determine the relationship between prevalence of

late stage diagnosis of cervical cancer and number of comorbidities in women aged 65 years

and above in Zimbabwe.

1.5. Research Objectives

The objectives of the research were:

1. To determine the prevalence of late stage diagnosis of cervical cancer in women aged

65 years and above in Zimbabwe.

2. To ascertain the number of comorbid illnesses suffered by women aged 65 years and

above presenting with late stage cervical cancer in Zimbabwe.

3. To establish the relationship between prevalence of late stage diagnosis of cervical

cancer and number of comorbidities in women aged 65 years and above in Zimbabwe.

1.6. Research Questions

1. What is the prevalence of late stage diagnosis of cervical cancer in women aged 65

years and above in Zimbabwe?

2. What is the number of comorbid illnesses suffered by women with late stage cervical

cancer aged 65 years and above in Zimbabwe?

3. What is the relationship between prevalence of late stage diagnosis of cervical cancer

and number of comorbidities?

1.7. Significance to nursing

Cervical cancer is fast becoming a pandemic in Zimbabwe. The majority of cases are

late diagnosis cases, reasons which were attributed to low risk self-perception, lack of

financial resources and myths surrounding cancer in general by Chigariro and Nyemba in

2014. No studies have been done to find out the effect of comorbidities on prevalence of late

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stage cervical cancer diagnosis which is relevant in order to assist health care workers to

focus more on identified problem areas. It has been proven in India and America that geriatric

patients are referred less frequently for cervical cancer screening, meaning that only when

clinical symptoms manifest are they diagnosed. By then the cancer will have spread to other

organs, leading to expensive palliative care for the health-care institution and the patient and

loss of economically viable manpower. In less developed countries like Zimbabwe, the

referral may be even lesser than previously determined due to economic challenges. In 2014,

a survey done by Nyemba in rural Zimbabwe indicated that more than 75% of elderly women

are not screened for cervical cancer in the clinics or hospitals they would have attended for

other health concerns. Elderly women suffering from other chronic illnesses will refrain from

early screening and even delay treatment should they recognise symptoms due to reluctance

to become a burden to already strained funds.

Multi-parity has been cited as a predisposing factor to development of cervical cancer

(WHO, 2014). Findings from this study are of interest to women of child-bearing age and

their health as they impact on their life as they grow older. At a time that the Zimbabwe

National Health Research Agenda Strategy is vouching for reduction in maternal and child

deaths, findings from this research will ensure early screening of cervical cancer and prevent

the death of pivotal dependent carers which are the elderly women.

Stakeholders investing in women’s health should know the outcome of this study as it

brings out results of efforts put in place to combat cervical cancer. Also new areas of

investment are revealed, like providing Pap smear kits to every health institution in the

country and more focus on geriatric oncology. Investments in nursing curriculum

development are necessary to address evolving societal changes especially in geriatric

nursing.

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Establishing a relationship between prevalence of late stage diagnosis of cervical

cancer and number of comorbidities is essential for nursing practice, nursing education as

well as nursing research. In nursing practice, clinicians will be interested to know whether

frequent contact with elderly women with chronic conditions delays referral for early

screening of cervical cancer as more focus is put on other conditions. The frequent contact

needs to be put to maximum use and actually help in increasing awareness of cervical cancer

screening leading to early diagnosis.

Nurse educators interested in curriculum adjustment in issues involving the elderly,

chronic conditions and malignancies as the elderly population continues to increase will be

given these results. The pap smear is a basic test for screening cervical cancer that can be

taught from neophyte nurses to advanced clinical practitioners so that it can be offered on a

regular basis in all health care settings including walk-in clinics. Nurse researchers will need

to identify areas of further scientific enquiry in order to establish evidence-based findings

which support or refute existing evidence and further advance the evolving profession of

geriatric nursing. They can then advocate for a more comprehensive health assessment

package for women with comorbid conditions which include regular pap smears along with

their usual blood pressure, blood sugar or cholesterol checks. Nurse Managers need to

advocate for more funding for their budget in order to provide palliative care and to educate

the community in a more aggressive manner to combat late diagnosis of cervical cancer.

They can also attract funding into installing cervical cancer screening equipment in their

respective health institutions to cater for all women clinicians come into contact with.

1.8. Theoretical framework

A framework is an abstract and logical structure of meaning that guides the

development of a study and enables the researcher to link study findings and nursing’s body

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of knowledge (Burns & Grove, 2009). The Betty Neuman’s Systems model was used as the

theoretical framework for this study.

Theoretical frameworks in nursing are based on the nursing meta-paradigm which

Fawcett (1989) describes as person, environment, health and nursing.

Neuman, views a client as an open system which is composed of five variables. These

include physiological, psychological, socio-cultural, spiritual and developmental and are

surrounded by lines of defence and resistance which attempt to combat the effect of stressors.

The environment is viewed as a source of stressors and provides resources for managing the

same stressors (Neuman, 2011). Stressors can be intrapersonal, occurring within the

individual including feelings such as anger or fear. Interpersonal stressors occur between the

individual and others including health care providers, support groups, relatives and any other

people they come in contact with whilst extra-personal stressors occur outside the individual

like a job, financial pressures and comorbid illnesses. Neuman states that health or wellness is

a state in which all parts and sub-parts are in harmony or a steady state with the whole of the

person. Optimum wellness occurs when all needs are met. Illness conversely is a state of

insufficiency or instability. She therefore implies that health is on a continuum with wellness

at one end and extreme variables from wellness up to death at the other end of the continuum.

The term reconstitution is used to describe the process of adaptation to stressors.

Nursing is described as a unique profession that is concerned with all variables

affecting an individual’s response to stressors (Neuman, 2011). The goal of nursing is to

maintain, regain or attain client system stability. Neuman then goes ahead to describe the

nursing process which contains three basic parts namely the nursing diagnosis, nursing goal

and nursing outcome as an intervention at any point when a stressor is suspected, detected or

identified. Intervention before a reaction to a stressor occurs is described as a primary

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intervention while intervention after a reaction has occurred is termed secondary intervention.

Tertiary intervention is appropriate only when reconstitution has occurred. This study focuses

on the four central concepts as defined by Neuman.

Betty Neuman’s System Model was chosen because of its open characteristics. The

major client variables which influence the individual’s observable reaction are going to be

considered. This study proposed that comorbidity influences stage at which cervical cancer is

diagnosed in elderly women aged 65 years or above leading to a health outcome on a

continuum with optimal wellness on one end as early diagnosis late diagnosis on the other

end. Comorbidity is part of the environmental stressors that have an influence on the

diagnosis of cervical cancer and is placed in the reaction phase. The environment is a source

of stress for the client’s system in the cancer patient. The patient with comorbidities might be

able to have early diagnosis of cervical cancer due to constant or frequent contact with health

care providers but may also not be able to do so due to overwhelming stressors which come

with comorbid illness including drug-drug interactions, non-adherence, availability and

affordability of treatment. Patients who are overwhelmed are unable to adapt to stressors

effectively leading to late stage diagnosis of cervical cancer and thus tertiary intervention.

The model was adapted to guide the nursing care of elderly women with chronic

illnesses on the continuum of care from early and regular screening to palliative treatment of

late presenters. The diagram illustrates the interaction of stressors from the extra-personal

(environmental), intra-personal and inter-personal stressors which eventually lead to the

diagnosis of cervical cancer. Early or late diagnosis will depend on the nursing intervention s

applied at the 3 different level of stress.

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CLIENT SYSTEM

Lines of defence

Intra-personal

stressors –

genetics and

repeated HPV

infections

Inter-

personal

stressors –

lifestyle e.g.

diet and

exercise

Extra-personal

stressors –

environment,

carcinogens

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Fig 1: Adaptation of Betty Neuman Systems Model

In clients with chronic illnesses, the role of the medical-surgical nurse is to provide

education on risk factors of developing cervical cancer, assess client scores on the risk factor

scale and encourage early screening to promote early detection and treatment. Clients who

are fully alert and are on treatment for other chronic illnesses must be fully aware of the

implications of constant cervical screening and must have at least undergone cervical

screening once a year. The medical-surgical nurse requires a body of knowledge to impart to

the client and to make observations, understanding the events and conditions and possible

courses of actions which will be beneficial to the client (Orem, 1991).

In terms of environmental stressors the nurse is mainly an advocate for safer

environment. With interpersonal stressors the nurse includes health education and in terms of

intra-personal stressors, clinical intervention is a key component.

1.9. Conceptual definition of terms

A conceptual definition provides a variable with an abstract of theoretical meaning

and it is reached through concept analysis (Burns & Grove, 2009). The following definitions

will be used in this study:

Client – synonymous with the term patient is used interchangeably in this study to mean an

elderly woman aged 65 years and above with cervical cancer.

Cancer – a malignant, autonomous and uncontrolled growth of cells and tissues forming

tumours.

Cervical cancer – a tumour of the cervix caused by the human papillomavirus (HPV).

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Comorbidity – a chronic illness or illnesses being suffered from in conjunction with the

cervical cancer in the elderly woman.

Condition – a state of unwellness, also synonymous with the term: illness. Will be used

interchangeably in this study.

Staging – classification of the cervical cancer according to histology.

Human papillomavirus – a most common sexually transmitted infection causing cervical

cancer if persistent.

Late stage presentation – stage 3 and 4 of cervical cancer.

Prevalence of late stage presentation of cervical cancer – percentage or fraction of elderly

women aged 65 years and above presenting with stage 4 cervical cancer in Zimbabwe.

Stressors – include intra-, inter-and extra-personal stressors that affect the client system

directly or indirectly.

Reconstitution – the nursing system put in place to ensure

Palliative care – end of life care for patients with stage 3 and 4 cervical cancer. Tab these

1.1.0. Summary

Cervical cancer is the fourth leading cause of all cancer deaths worldwide and the

number one cancer in females in Zimbabwe. With increasing age comes a host of chronic

illnesses which elderly women have to deal with as comorbidity generally increases with

advancing age. Cancer stage at diagnosis determines treatment options and has influence on

length of survival. Betty Neuman’s Systems Model was modified to illustrate the effect of

stressors on the continuum of care for elderly women from early and regular screening of

cervical cancer to those presenting with late stage symptoms requiring palliative care. There

is an urgent need therefore to determine the relationship between comorbidity and diagnosis

25

of cervical cancer in elderly women aged 65 years and above in Zimbabwe in order to adjust

the nursing care accordingly.

CHAPTER 2

LITERATURE REVIEW

This chapter looks at literature review concerning the independent and dependent

variables. This was a study to determine the relationship between late stage cervical cancer

diagnosis and number of comorbidities in women aged 65 years and above in Zimbabwe.

2.1. Introduction

Polit & Hungler (2008) defined literature review as a critical summary of findings on

a topic of interest generally prepared to put a research problem in perspective. Literature

review in nursing serves a number of purposes in the research process one of which is to refer

to scientific sources that are important in providing the in-depth knowledge that is needed to

make changes in education, practice and research and to assist the researcher in finding out

what is already known about an existing problem. The purpose of literature review in this

study was to identify, scrutinise, summarise and integrate previous work done globally,

regionally and locally on cervical cancer and comorbidity among elderly women presenting

with late stage cervical cancer in order to answer the posed research questions.

2.2. The cervix

The cervix constitutes the lower third of the uterus. In a non-pregnant fertile woman,

it is 3cm long and 2.5cm wide (Berek, 2011). The ectocervix is the lower part of the cervix

whilst the endocervix forms the upper two thirds. The ectocervix is lined by stratified,

squamous epithelium and the cervical canal by the columnar epithelium which is thinner and

more fragile (Berek, 2011). The area where the 2 types of epithelia meet forms the squamo-

26

columnar junction (SCJ). The cervix undergoes striking changes from birth to menopause

(Shaw, 2003).

From birth up to pre-puberty, the original SCJ remains intact. At puberty the cervix

grows in size in response to oestrogen. As the woman becomes more fertile, squamous

metaplasia occurs giving rise to a second SCJ, called the transformation zone, located

between the original and the new SCJ, cells of which are particularly vulnerable to persistent

HPV infection. It is here that most squamous cell carcinoma develops (WHO, 2014).

As women advance in age and the effects of oestrogen lessen and the cervix shrinks.

In post-menopausal women, the new SCJ and a variable portion of the metaplastic epithelium

of the transformation zone retreat into the cervical canal (Berek, 2011).

2.3. Cervical cancer

Cancer results from malignant, autonomous and uncontrolled growth of cells and

tissues forming tumours which invade surrounding normal tissue competing for nutrients and

oxygen thus destroying them (Tortora, 2012). Cervical cancer is caused by persistent

infection with cancer-causing HPV types 16 and 18(WHO, 2014). These types are

responsible for 70% of all cervical cancer cases throughout the world. The virus exclusively

pervades epithelium, produces new viral particles thus causing genetic damage and tumour

formation (Crosbie, Einstein, Franceschi & Kitchener, 2013). Ninety percent of cervical

cancers are squamous cell cancers and the other 10% are adenocarcinomas beginning in the

glandular columnar layers of the endocervix (WHO, 2014). Cervical precancer is a distinct

change in the epithelial cells of the transformation zone where cells start developing in an

abnormal fashion in the presence of persistent HPV infection (Crosbie et. al., 2013). This

precursor stage, stage 0, can last years before becoming invasive cancer; providing ample

opportunity for detection and treatment. Cervical cancer screening in Zimbabwe is aiming at

27

the 15-49 age group who may be in stage 0 so that they do not present later in life when they

are older and the cancer is at an advanced stage. In women, during puberty and pregnancy,

the transformation zone of the ectocervix is enlarged and exposure to HPV at these

vulnerable times facilitates infection (Basu et. al., 2011; WHO, 2014). This may explain the

association between squamous cell cervical cancer and early sexual activity, young age at

first birth and a history of multiple pregnancies. Behaviours that can also increase the risk of

HPV infection (and thus cervical cancer) include having multiple partners and having

partners with multiple partners (Gyenwali, Pariyar & Onta, 2013). This study aimed at

screening elderly women age 65 years and above with cervical cancer for all the above-

mentioned risk factors.

Conditions leading to HPV infection are not well understood but risk factors that play

a role include HPV type, oncogenicity or cancer-causing strength; immune status: those

living with HIV are more likely to have persistent HPV infection and a more rapid

progression from pre-cancer to invasive cancer; co-infection with other sexually transmitted

illnesses such as herpes simplex, Chlamydia and gonorrhoea; parity and young age at birth;

tobacco smoking and lastly use of oral contraceptives for over 5 years (WHO, 2014).

2.4. Staging

Cervical cancer is a progressive disease that is staged according to histology

(McCance & Huether, 2006).It is a process that can take weeks or months depending on

diagnostics done (Chitsike, 2015). Classification is done on a continuum from cervical

intraepithelial neoplasia or cervical dysplasia to cervical carcinoma in situ to invasive

carcinoma. Initially, there is cervical dysplasia. The patient is asymptomatic and only a pap

smear can detect changes in cell characteristics. Eventually, there is progression to invasive

cancer and this can take place over a period of 10-12 years (Gyenwali, Pariyar & Onta,

2013).

28

Four routes are taken by the invasive cancer progressing within the cervix. Spread

occurs from a tiny focus of microinvasive cancer until it covers the entire cervix and

enlarging to 8cm or more in diameter (WHO, 2014). Direct spread then occurs, downwards to

the vagina, upwards to the uterus, sideways into the tissues supporting the uterus in the pelvis

and ureters, backwards to the rectum and forwards to the bladder. Thirdly, there are lymph

node metastases which at first, are confined to the pelvis and then later up to the aorta.

Cervical cancer cells fourthly spread through the blood stream and lymphatic system to

develop distant metastases in the liver, bone, lung and brain producing symptoms related to

these regions. Patients are staged using the International Federation of Gynaecology and

Obstetrics (FIGO) clinical classification which remains the gold standard (WHO, 2014) and

is illustrated in Table 2.0. In addition to a clinical examination, use is made of radiological

investigations, which include a chest radiograph, a pelvic and abdominal ultrasound,

computed tomography (CT) and magnetic resonance imaging (MRI) to aid in the staging

process (Sauer, Simonds, Van der Merwe & Hatingh, 2013).

29

Table 2.0: The FIGO Clinical Staging for Cancer of the Cervix

Stage Characteristics

0 Cancer in situ, intraepithelial carcinoma, earliest stage of cancer,

cancer confined to its original site.

1

1A

1B

1A1

1A2

1B1

1B2

Carcinoma confined to cervix (extension to corpus disregarded)

Earliest form of stage 1, very small amount of cancer visible only

under the microscope

Area of invasion is < 3mm deep and < 7mm wide.

Area of invasion is between 3-5mm deep and < 7mm wide

Includes cancers that can be seen without a microscope and cancers

that can be seen only with a microscope that have spread deeper than

5mm into connective tissue of the cervix and are wider than 7mm.

A 1B cancer that is no larger than 4cm

A 1B cancer that is larger than 4cm

11

11A

11B

Cancer has spread beyond the cervix to the upper part of the vagina

but does not involve the lower third of the vagina.

Cancer has spread beyond the cervix to the upper 2/3 of the vagina.

Cancer has spread to the tissue next to the cervix (parametrical

tissue).

111

111A

111B

Cancer has spread to the lower part of the vagina or the pelvic wall;

cancer may be blocking the ureters

Cancer has spread to the lower third of the vagina but not the pelvic

wall

Cancer extends to the pelvic wall. Bocks urine flow to the bladder

from both ureters.

1V

1VA

1VB

Most advanced stage of cervical cancer, cancer has spread to other

parts of the body

Cancer has spread to the bladder or rectum, which are organs close

to the cervix

Cancer has spread to distant organs beyond the pelvic area such as

the lungs.

Adapted with permission from McCance & Huether (2006), 5th

edition, page 795.

30

2.4.1. Late stage presentation of cervical cancer

According to the Zimbabwe Ministry of Health, most women present late with

cervical cancer, in stage 3 and 4 (Zimbabwe National Cancer Strategy, 2014). The prevalence

of cervical cancer in women in Zimbabwe was 33.4% in 2009 with 15.6% being in elderly

women aged 65 years and above. A study done by Ferrante et al in 2009 indicated that older

patients in Florida had a 10.9% more likelihood of being diagnosed in the 3rd

0r 4th

stage of

cervical cancer than their younger counterparts. In India, a study done to assess screening

behaviours showed that elderly women in rural India were the least regularly screened and

presented with late clinical symptoms of cervical cancer (Gynewali, 2013).

Late stage presentation means that the focus of health resources is expended

fruitlessly. The current early cervical cancer screening drive has been focused on the 15-49

year age group whilst neglecting the elderly. Little research has been done in Zimbabwe

about the elderly and the researcher feels that more should be done to this vulnerable group.

We are in the age where people are striving to stay younger for longer but eventually old age

catches up with everyone. A survey done in 2011 in Europe about all research done

concerning late presentation of disease and co-infection related factors found that less than

2% of the studies concerned the elderly (Sangha et al, 2011). African literature is even

scantier. This research seeks to close that gap and pose questions for researchers to branch

more into geriatric research.

31

2.5. Comorbidity

Comorbidity is defined in relation to a specific index condition, as any distinct

additional entity or illness that has existed or may occur during the clinical course of a patient

who has the index disease under study (Valderas, Starfield, Sibbald, Salisbury & Roland,

2009). The question of which condition should be designated the index varies in relation to

the research question, the disease that prompted a particular episode of care, or of the

specialty of the attending physician. In this study, the index condition is cervical cancer.

Comorbid health problems are classified in terms of their relevance to clinical management.

For example, ischemic heart disease, cardiovascular risk factors (hypertension, hyper-

cholesterolemia), and diabetes are commonly managed within the same cardiovascular clinics

in primary care because they share important aspects of disease management (Valderas et al.

2009). Drawing together patients who have similar clinical management needs is efficient,

but runs the risk of interaction in relation to diagnosis, prognosis, treatment, and management

(including self-management) or outcomes. Even for the same pair of comorbid conditions

(e.g., diabetes and chronic pulmonary disease), some interventions can be antagonistic (e.g.

the effect of hypoglycaemic drugs and corticosteroids on blood glucose), others may be

agonistic (physical activity), and others may be neutral. Improved understanding of such

interactions among comorbid diseases is important to improving clinical care by promoting

early detection and treatment.

Understanding patterns and identifying common clusters of chronic diseases may help

policymakers, researchers, and clinicians to understand the needs of the care process better

and potentially save both provider and patient time and cost. However, only limited research

has been conducted in this area, and ambiguity remains as those limited previous studies used

different approaches to identify common clusters and findings may vary with approaches.

This study seeks to identify comorbid illnesses suffered by elderly women presenting with

32

late stage cervical cancer in Zimbabwe. A study in Australia estimated the prevalence of

common chronic diseases and examined co-occurrence of diseases using four approaches: (i)

identification of the most occurring pairs and triplets of comorbid diseases; performing (ii)

cluster analysis of diseases, (iii) principal component analysis, and (iv) latent class analysis

(Islam M.M., Valderas J.M., Yen L., Dawda P., Jowsey T., et al., 2014). Data were collected

using a questionnaire mailed to a cross-sectional sample of senior Australians, with 4574

responses. Eighty-two percent of respondents reported having at least one chronic disease and

over 52% reported having at least two chronic diseases. Respondents suffering from any

chronic diseases had an average of 2.4 comorbid diseases. Female respondents reported a

significantly higher number of diseases than male respondents. Of those respondents aged

over 75 years, 93% experienced at least one chronic disease and 73% more than one chronic

disease. Overall, 27% reported at least three chronic diseases, 11% at least four and 3% at

least five diseases. High blood pressure (HBP) (43.1%), arthritis (32.2%) and cancer (17.9%)

were three most prevalent diseases (Islam et al., 2014).

Three defined groups of chronic diseases were identified, asthma, bronchitis, arthritis,

osteoporosis and depression forming 1 group; high blood pressure and diabetes forming the

second and cancer, with heart disease and stroke either making a third group or attaching

themselves to different groups. The consistency of the findings suggests there is co-

occurrence of diseases beyond chance, and patterns of co-occurrence are important for

clinicians, patients, policymakers and researchers.

The National Institute on Aging (NIA) Geriatrics and Clinical Gerontology (GCG)

Program in Europe convened an interdisciplinary Task Force on Comorbidity to foster the

development of a research agenda on the multiple concurrent health problems that often

occur in older persons (Yancik R., Ershler W., Satariano W., Hazzard W., Cohen H. J., &

Ferrucci J., 2009).The risk of developing concomitant chronic illnesses and physiological

33

limitations escalates with aging. Diabetes, respiratory diseases, cancer, cardiovascular

problems, arthritis, hypertension, and certain other chronic conditions are more common in

older than in younger persons (Karlamangla A., Tinetti M., Guralnik J., Studenski S., Wetle

T., Reuben D., 2007). As a consequence, a new diagnosis of any common chronic health

condition is likely to be made in the context of pre-existing health problems.

A study done in England reviewed literature relating to comorbidity and dementia

(Bunn et al., 2014). Findings noted that comorbidity amongst patients with dementia

represented complex challenges in their primary and secondary care. Certain comorbid

conditions exacerbate the progression of dementia for example, they found out that cognitive

decline is accelerated in elderly patients with type 2 diabetes mellitus (Bunn et al., 2014).

Cervical cancer is a defining illness of acquired immune-deficiency syndrome (AIDS)

in patients with HIV (WHO, 2014). Immunocompromised women have a higher prevalence

of persistent infection with multiple high risk HPV types increasing susceptibility leads to a

stronger risk of developing precancer and cancer at younger ages. The degree of immune-

suppression increases risk of developing invasive disease up to 10 years earlier than in

uninfected women (WHO, 2014). They also have more frequent presentation with advanced

disease and a smaller chance of survival for 5 years (WHO, 2014).

As the elderly population expands, many diseases that predominantly affect older

people are also on the increase (Berger et. al., 2006). Many conditions that affect the elderly

are occurring in combination thereby complicating care of any single condition. The

incidence of cancer in those over 65 years is 10 times greater than in those younger and

cancer death rate is 16 times higher as well(Berger et. al., 2006). Since patients are likely to

acquire an increasing number of maladies with increasing age, strategies to prevent, screen or

prevent cancer and the need for physicians and caretakers to have expertise in both oncology

34

and geriatrics. A new approach established at the Case Western Reserve University uses a

Cancer-Aging Linked Database (CALD) for patients in the state of Ohio (Berger et. al.,

2006). The CALD accesses and merges information from a series of databases including the

Ohio Cancer Incidence Surveillance System (as cancer is a reportable disease in Ohio), the

Ohio death certificate file, Census block data and Long term care minimum data set amongst

others. Using the CALD, they were able to identify the following comorbidities in patients

aged 65 years and above with breast, prostate and colorectal cancers respectively: geriatric

syndromes such as incontinence, depression and dementia as well as disabilities leading to

functional impairment. The preliminary findings indicate that geriatric syndromes such as

depression and dementia are associated with late stage diagnosis of breast cancer. Also of

interest is the observation that older patients with breast cancer are less likely to be

recommended for therapy. These results clearly indicate that health care providers involved

in care of the elderly must be made aware of these disparities to more effectively orient their

cancer screening and treatment strategies (Berger et. al., 2006).

A study in Cleveland and Florida conducted to ascertain the impact of comorbidity on

cancer screening and prevention (Berger et. al., 2006) indicate that cancer screening

decreases among the elderly in general and is particularly deficient among those with

comorbid health problems. However, age was found to be a greater predictor than

comorbidity for health care providers not referring elderly patients for screening. In

Zimbabwe, for elderly women aged 65 years and above with cervical cancer, some are living

with hypertension, diabetes mellitus, arthritis, gout and HIV among another comorbid

conditions in rural areas (Ward, 2011). The elderly population in Zimbabwe especially in the

rural setting are already living with debilitating illness such as chronic backache and the

burden of taking care of orphaned grandchildren and sick children due to the AIDS

35

pandemic. These women present with late stage diagnosis of cervical cancer and reduced

survival rate due to comorbidities (Tshuma, 2002).

According to the World Health Organisation (2014), cervical cancer is the number

one cancer among women in Zimbabwe; with an estimated 1855 new cases and 1 280 deaths

due to the disease annually (WHO, 2014). Figures from the Zimbabwe National Cancer

Registry indicate the highest incidence of cervical cancer to be in women aged 65 years and

above. Of the 680 cases attended in 2006, 107 of them were 65 years and above, placing their

incidence at 15.6% out of the 32.5% total for all women in Zimbabwe (ZNCR, 2010).

A social study done in 2009 by Chinhamora & Trent linked multiple comorbidities in

the elderly population of Zimbabwe with a lesser tendency to seek professional healthcare for

serious or life-threatening conditions like cancer and cardiac anomalies. The recent economic

meltdown posed a threat especially to women’s health. They neglected themselves in favour

of their children or other family members and viewed general annual check-up as an

unaffordable luxury (Chinhamora, 2009).

2.6. Cervical cancer and comorbidity

Cervical cancer is a common malignancy in developing countries, in particular those

with a high prevalence of human papillomavirus and human immunodeficiency virus

(HIV).The incidence rate in black women is 11.2 per 100 000, exceeds the rate in white

women which is 7.3 per 100 000 and mortality risks for black women continue to be two

times higher than for white women (McCance & Huether, 2006). According to the South

African National Cancer Registry’s 2001 published report, cervical cancer was the third most

common malignancy (16%) after breast cancer (19%) and basal cell carcinoma of the skin

(17%) in female patients, and the most common malignancy in black African women (31%)

(Sauer, et. al., 2013).

36

A study done in Denmark in 2014 found large variations in cancer awareness

between individuals of different socioeconomic status supporting findings from previous

studies which show that people of low economic status are less aware of cancer symptoms

than their counterparts of higher economic status leading to late diagnosis (Hvidberg,

Fischer-Pederson, Nielsen-Wulff & Vedstead, 2014). Also supported by a study done by

Gyenwali in India in 2013. Poor socioeconomic status was linked to heavy burden of

comorbid conditions which demand polypharmacy and place financial constraints leading to

women bypassing cervical cancer screening and waiting for clinical manifestations to occur

of which the cancer would be advanced to stage 1V at that time.

Another study done in India revealed that economic constraints prioritises women

towards social responsibilities and self-neglect towards their health issues (Singh & Badaya,

2012). The most untouched population is in the rural areas, availability of facilities there

would increase compliance to cervical cancer screening (Singh & Badaya, 2012).

The Eve Appeal Survey carried out in England in 2010 was a study to ascertain

awareness of cervical cancer in women. Women aged 60 years and above were more able to

recognise clinical symptoms such as persistent bleeding post-menopause but cited fear of the

unknown as a barrier to seeking early cervical screening in the absence of those clinical

symptoms.

In Zimbabwe, cervical cancer screening is widespread but hardly offered to the

elderly woman with the regular check-up package due to health worker misconception,

reluctance for the invasive screening technique and focus on other comorbidities (Tshuma,

2002; Trent, 2009).A study done by Chipfuwa in 2012 indicated that the most focus of

cervical cancer screening was on the 15-49 year age group showing that the elderly are

neglected in cancer research but they are important members of our society. This study was

37

done to establish awareness and compliance in Zimbabwean women about early cervical

cancer screening.

The Comorbidity Index

The Charleson Comorbidity Index is used to measure or predict prognosis and quality

of life in patients living with co-existing conditions. It was used successfully by Fadem in

2013 to predict or estimate the prognosis of elderly patients on dialysis by scoring the

comorbidities and estimating remaining survival rate. It has been modified for the purpose of

this research as illustrated in Table 2.1. A scoring system based on the quality or nature of

comorbidities was used in tailoring it to suit the Zimbabwean population according to the

chronic illnesses commonly found in the population. This researcher hypothesizes that elderly

women often present at health care institutions with late stage cervical cancer and most of

them suffer from a number of other diseases which could have developed either before or

after the cervical cancer diagnosis. The scoring system was used as a comparison system

against actual number of comorbidities to rule out gravity of the illnesses as the actual

contributor to late stage diagnosis of cervical cancer.

38

Table 2.1: Modified Charleson Comorbidity Index

A score of 1 is added for every decade >60 years of age to account for the normal aging

process.

Score Condition

3 Myocardial infarction

Congestive cardiac failure

Peripheral vascular disease

CVA

Dementia

Depression

Anxiety disorders

Sleeping disorders

Chronic Pulmonary Disease

Connective tissue disease

Alzheimer’s

Osteoporosis

Backache

Eye disorders(cataracts)

Peptic Ulcer Disease

Mild liver disease

DM (uncomplicated)

Hypertension

Arthritis

4 Hemiplegia

Moderate or severe renal disease

DM (with end-organ damage)

Tumour without metastasis

Leukaemia

Lymphoma

HIV on ART

5 Moderate to severe liver disease

Hepatitis

6 Metastatic solid tumour

AIDS

39

Theoretical framework

Betty Neuman’s Systems Model has been used in this study as a framework guide.

This conceptual framework is an open systems model, fitting well with the wholistic concept

of optimising a dynamic, yet stable interrelationship of mind, body and spirit of the client in a

constantly changing environment and society (Neuman, 1989).

White, Richter & Fry (1992), examined the impact of potential stressors, coping

strategies and perceived social support in the psychological adaptation of women with

diabetes mellitus using Betty Neuman’s model. Diabetes mellitus was selected as the

prototype of a chronic illness because of its prevalence as a chronic disease and the necessity

for significant lifestyle changes. In this study, cervical cancer is the prototype, studied in a

complex context of comorbidity adding to external stressors leading to delayed screening and

late stage diagnosis of cervical cancer.

A study done by Ladd in 1999 also used Betty Neuman’s Systems Model to study the

effect of social support on the psychological adaptation of an individual receiving an

alternative form of nutritional therapy in cancer patients. An interesting finding was that the

coexistence of 2 or more diseases in the same individual affects clinical care of the index

condition. One other major clinical question is whether there would be a common aetiological

pathway which then ties the index condition to external and internal stressors (Piccirillo &

Feinstein, 1996).

2.7. Summary

There have been various studies undertaken locally, regionally and internationally

concerning cervical cancer in women but none have focused on whether comorbidity plays a

role in diagnosis of cervical cancer in elderly women which is what this researcher has sought

to find out.

40

CHAPTER 3

METHODS

3.1. Introduction

Research methods incorporate all procedures that are used to pursue knowledge

(Burns & Grove, 2009). This study examined the relationship between prevalence of late

stage diagnosis of cervical cancer and number of comorbid conditions in women aged 65

years and above in Zimbabwe. This chapter will address the research design, setting,

sampling procedure, sample size, variables, development of research study instrument, data

collection plan, ethical issues and data analysis.

3.2. Research design

Research design is a blueprint for conducting the study that maximises control over

factors that may interfere with validity of findings (Burns & Grove, 2009). The descriptive,

correlational design was used to examine the relationship between late stage diagnosis of

cervical cancer and comorbidity in elderly women aged 65 years and above. It is a

retrospective study looking at medical records from previous hospital visits. The purpose of

this design was to guide the researcher in planning and implementing the study in the most

likely way to achieve the intended goal.

According to Polit & Hungler, descriptive, correlational study designs describe

relationships among variables rather than infer cause and effect. The variables under study

were prevalence of late stage diagnosis of cervical cancer as the dependent variable and

number of comorbidities as the independent variable. Descriptive research aims at observing,

describing and documenting aspects of a situation as it currently exists whilst correlational

research examines relationships among variables as they naturally occur (Polit & Hungler,

41

2008; Burns & Grove, 2009). Aspects of both descriptive and correlational research are

therefore combined. The research has no control over the independent variable but describes

rather how it is related to another. It is an efficient and useful method of collecting data in a

problem area in nursing over a short period of time. A quantitative, descriptive, correlational

study is appropriate for this study as the researcher seeks to describe the relationship between

number of comorbidities and prevalence of late stage diagnosis of cervical cancer in

Zimbabwe.

3.3. Sampling Plan

Sampling is a process of selecting a portion of the population as a representative of

the entire population (Polit & Beck, 2014). A sampling plan is a process of making the

selection (Burns & Grove, 2009). It describes the process for selecting the study site and

sample and specifies in advance how study participants are to be selected and how many are

to be included. The aim is to increase representativeness, decrease systematic bias and

determine sampling error. In this study, non-probability method of sampling is going to be

used. All patient records of women who are 65 years and above at Parirenyatwa Group of

Hospitals and Spilhause Clinic based at Harare Hospital who have cervical cancer were

reviewed in a process of convenience sampling as rate of patient attendance and time limit for

submission of study results did not correlate. A sample represents the entire population (Polit

& Beck, 2014). The element is the basic unit of a sample; in this study elements are referred

to as subjects as they are people, therefore sample will refer to elderly women aged 65 years

and above with cervical cancer with records at Parirenyatwa Hospital and Spilhause Clinic at

Harare Hospital.

3.4. Study site

Patients were selected from Parirenyatwa Radiography Department and Ward A6 and

at Spilhause Clinic at Harare Hospital. These are referral centres from council clinics,

42

provincial and district hospitals and private practitioners. The researcher also reviewed

patient records from the Parirenyatwa records department to confirm initial staging.

3.5. Target population

According to Burns & Grove (2009), a target population refers to all elements i.e.

individuals, objects or substances that meet the sample criteria for inclusion in a study. The

target population for this study were all cervical cancer patients aged 65 years and above in

Zimbabwe who were able to understand Shona or English.

3.6. Accessible Population

Accessible population is the aggregate of cases that meet the sampling criteria and are

accessible to the researcher (Polit & Hungler, 2008). One can generalise findings from

accessible population to the target population. The accessible population was the population

of elderly women with cervical cancer, attending Parirenyatwa Cancer Clinic and

radiotherapy clinic, Harare Hospital Spilhause clinic and with medical records at

Parirenyatwa Hospital.

3.7. Sampling Criteria

Sampling criteria is the essential characteristics of the target population (Burns &

Grove, 2009). Sampling criteria refers to inclusion and exclusion criteria which help to

control extraneous variables. It ensures homogeneity and provides a guideline for sample

recruitment. Inclusion criteria refer to specific characteristics the investigator wishes to

include in the study whereas exclusion criteria refer to characteristics not included in the

study.

3.7.1. Inclusion Criteria

The inclusion criteria included those subjects diagnosed with cervical cancer, whether

on treatment or recently diagnosed. The subjects should have been currently aged 65 years

43

and above and be able to communicate in English and Shona. Medical records had to be

available for elderly women diagnosed with cervical cancer dating back 2 years.

3.7.2. Exclusion Criteria

Exclusion criteria included those who could not communicate in English or Shona and those

aged below 65 years. The study also excluded those elderly women without a confirmed

diagnosis of cervical cancer and those not staged.

3.8. Sample Size

A sample is a fraction of the population that is selected for a study (Burns & Grove,

2009). The sample size is the minimum number of subjects needed to complete a study. It is

important to determine the sample size in order to yield adequate precision or power and is

calculated by considering significance level or alpha, then power and effect size (Burns &

Grove, 2009). The significance level is an index of how probable or reliable the study

findings are. The level of significance used in this study was 0.05, indicating the probability

that the relationship of the observed magnitude would be found by chance only 5 times out of

100 (Polit & Beck, 2014). The significance level will give the researcher an indication and

confidence that the findings are reliable.

According to Polit &Beck (2014), the effect size highlights the magnitude of the

differences between 2 groups or the magnitude of the relationship between 2 variables with

regard to some attribute of interest. It is a quantitative measure of the strength of a

phenomenon (Thalheimer & Cook, 2002). Sample based effect size estimates the strength or

magnitude of an apparent relationship (Kelly & Preacher, 2012). The effect size used in this

study was 0.50.

Polit &Beck (2014) defined power as the ability to detect existing relationships among

variables through use of a design. The power of .80 was used. The power assists the

44

researcher to avoid a type 2 error where conclusions can be made that there is no relationship

between the variables and yet a relationship actually exists. The sample size calculation was

based on the outcome: late stage diagnosis for cervical cancer. The sample outcome was

based on the proportion of women presenting late for cervical cancer diagnosis and using the

formula by A. Dobson: n = Z2pq⁄d

2

Where:

: p is the proportion of women aged 65 years and above presenting with cervical

cancer in Zimbabwe.

: q = (1-p)

: d is the precision which is presumed to be 5%

: Z is 1.96 based on a 95% confidence interval.

In this calculation, p was assumed to be 0.156 based on previous literature from the

Zimbabwe National Cancer Registry. Using the above formula, the sample size, n = 203.

Adjusting for a 75% response rate, the sample size was adjusted to 270. The researcher

utilised a sample of least 68, a quarter of the calculated sample size due to financial and time

constraints.

3.9. Sampling Procedure

The sampling procedure indicates how a group of people with whom to conduct a

study are selected. Non-probability sampling was used to recruit the study sample due to the

decreased number of elderly women being admitted in ward A6 or attending the Parirenyatwa

Hospital Radiography Department and Spilhause Clinic located at Harare Hospital Cancer

Clinics and the high death rate. Medical records dating back 2 years were reviewed. There is

no way to ensure that every member of the population is going to be selected thus introducing

45

a certain element of bias. Commonly used non-probability sampling methods are

convenience, quota and purposive sampling. In this study, convenience sampling was used to

select 68study participants (Polit & Beck, 2014). The interviews were carried out in Shona or

English with those subjects who met the inclusion criteria. An informed consent was sought

verbally after explaining the procedure and permission given to print names and hospital

numbers on the consent form in order to review medical records. A written consent was

obtained from the research sites heads of departments to recruit study participants and to

review medical records for elderly women with cervical cancer at the Records Department to

verify stage at diagnosis.

The investigator ensured privacy by using a counselling room and confidentiality by using a

coding system to label participant responses, real names and hospital numbers were only used

in order to retrieve medical records from the Parirenyatwa Database to confirm initial staging

and the record destroyed immediately after confirmation. The investigator visited the clinics

from 0700hrs weekdays, an hour before the actual clinic began in order to prepare stationery

and the counselling room. A list of potential subjects was drawn from the day’s Outpatients

Department Record book at the Radiography Department at Parirenyatwa and Spilhause

Clinic at Harare Hospital. The admission book and kardex were used in ward A6 at

Parirenyatwa and hospital notes for clarification. Medical records were reviewed from

1400hrs weekdays. Once candidates were identified, they were taken to the interview room

with the knowledge of the sister in charge of the clinic, made comfortable and introductions

made. Study purpose and approximate length of interview were explained to the subject. If it

was then established that the subject was competent and willing to participate, a verbal

informed consent was obtained and name printed on a written consent for records.

46

3.1.0. Variables

3.1.0.1. Conceptual and operational definitions

A conceptual definition provides a variable with a connotative meaning (Burns &

Grove, 2009). It refers to how the variable is defined. An operational definition describes

how the variable or concept will be measured in a study. The investigator was able to observe

the variables in their natural setting.

3.1.0.2. Demographic Variables

Demographic variables describe the characteristics or attributes of the sample (Burns

& Grove, 2003). These include, age, marital status, educational status, rural or urban

background and household type (whether nuclear or extended family). The rationale for using

demographic variable was that when the investigator completed the study, demographic

information would be analysed to provide a picture of the sample characteristics (Polit &

Beck, 2014). The demographic variable was measured by the demographic section devised by

the investigator.

3.1.0.3. Late stage cervical cancer

This is the dependent variable. Conceptually, cervical cancer has been defined as

autonomous and uncontrolled growth of cells of the cervix forming tumours which may

invade the tissues surrounding the cancer and cause metastases. Cervical cancer can be

diagnosed in its pre-cancer phase via a pap smear or may progress to stage IV where

metastasis has occurred and the cancer will have spread to distant organs beyond the pelvic

area such as the lungs and clinical manifestations of lungs damage then lead to late diagnosis

of the cervical cancer. Staging was measured from 1-4 with late stage cervical cancer being

stage 3 and 4.

47

3.1.0.4. Comorbidity

This is the independent variable. Comorbidity refers to other chronic illnesses subjects

will be suffering from besides cervical cancer which was the index condition. Comorbidity

was determined at time of diagnosis. Comorbid illnesses include hypertension, diabetes

mellitus, epilepsy, asthma, chronic obstructive pulmonary disease (COPD), arthritis, gout,

ulcers, chronic renal failure (CRF), backache, geriatric symptoms like dementia,

schizophrenia, depression and Alzheimer’s or Parkinsonism. Comorbidity will be

operationalised by measuring it with a comorbidity scale designed by the investigator based

on the Charleson Comorbidity Index to find out the number of comorbid illnesses in elderly

cervical cancer women. This index was used to devise a scoring system based on the quality

of the comorbid illness so that not only the number of illnesses is considered, but their weight

on survival as well. This has greater impact on whether comorbid illnesses affect the stage at

which cervical cancer is diagnosed.

3.1.1. Instrument

An instrument is a device or technique that an investigator uses to collect data, e.g.

questionnaire and observable schedules (Polit & Hungler, 2008). The instrument designed for

this study was an interview guide which consisted of a demographic data section, a cervical

cancer diagnosis section, and comorbidity scale section. This instrument was devised by the

investigator, translated into Shona then pretested at the cancer clinic at the Radiography

Department at Parirenyatwa Hospital to establish reliability and validity. It was used to

conduct a 30 minute interview with the participants.

3.1.2. Validity

Validity refers to the degree with which an instrument measures what it is intended to

measure (Burns & Grove, 2009). The instrument was translated into Shona and checked by

experts in the Nursing Science Department and consultants at the cancer clinic.

48

3.1.3. Reliability

Reliability refers to the degree of consistency and accuracy with which the instrument

measures what it is supposed to measure (Burns & Grove, 2009). To ensure reliability, the

instrument was pretested on 8 patients only due to time constraints. A research assistant was

used to test consistency of responses in 4 of the pilot participants if the interviewer was

different.

3.1.4. Data collection plan

Polit & Hungler (2008) explain that data collection should normally follow a pre-

established plan to minimise confusion, delays and mistakes. The investigator plan should

specify where, when and how data will be collected paying particular attention to human

rights consideration and the actual data collection procedure.

Approval for the study was sought and granted by the Joint Research and Ethics

Council of Parirenyatwa Group of Hospitals and the College of Health Sciences (JREC) after

submission of this proposal before data collection. Permission from the study site such as

Parirenyatwa Hospital and Spilhause at Harare Hospital were also obtained. Pre-testing of the

research instrument was done on 8 patients who were then excluded from the study. Non-

probability sampling used to recruit subjects. The clinic staff continued their usual schedule

and duties to minimise bias. Once a subject was selected, they were taken into a prepared

counselling room with adequate lighting, good ventilation and comfortable chairs. The

investigator made a self-introduction with the sister-in-charge present at initial contact only

and gave information to the subject to obtain an informed consent. A structured interview

was usually completed in 30 minutes or less using the interview guide whilst answers were

entered into a code book. Data collection took place from 1 – 28 May 2015.

49

3.1.5. Data collection procedure

After obtaining permission from JREC and the clinical director of Parirenyatwa

Group of Hospitals and Harare Hospital, the investigator visited the sites for familiarization

and to make prior arrangements for data collection. On interview days, the investigator was

introduced to the subjects by the sister in charge before proceeding to do face to face

interviews which lasted about 30 minutes. Data collected as well as written consent forms

were kept locked in a briefcase that the only investigator had access in order to maintain

privacy and confidentiality.

3.1.6. Human Rights Consideration

Protection of the rights of human subjects is of paramount importance and was

prioritised in this study by using the JREC template for informed consent which ensured that

all rights were observed. Permission to carry out the study was sought from the Nursing

Science Department, JREC and the clinical director of Parirenyatwa Group of Hospitals and

Spilhause Clinic at Harare Hospital to ensure that ethical requirements were met. The

subjects were informed of the purpose of the study, length of interview, potential benefits and

risks in a language they understood. Privacy and confidentiality was maintained by locking

up consents where subjects’ actual names were recorded and using a coding system

decipherable only by the investigator instead when recording responses to study questions.

The right of the subject to withdraw from the study without any adverse effects was fully

explained. The principle of respect for human dignity encompasses peoples’ right to make

informed voluntary decision about their participation in the study (Polit & Hungler, 2008).

The signed consent forms and coded answers to the interview were kept locked by the

investigator and destroyed upon completion of the study to ensure that no information will be

linked to the subjects whatsoever.

50

3.1.7. Pilot study

A pilot study is frequently defined as a smaller version of a proposed study

undertaken to refine the methodology (Burns &Grove, 2008). This is done to assess the

clarity of the research study questions, time required to complete the questionnaire and the

extent to which the instrument answers the research study questions. Due to time and

financial constraints, an instrument pre-test was conducted on eight subjects who met the

inclusion criteria at the Radiography Department at Parirenyatwa Hospital. These were

excluded from the study. The pre-test assisted the researcher to become familiar with the

instrument and correct any foreseeable problems before the major study and use of a different

site could have been used to rule out bias. In this case, the pre-test was done on different days

to prevent repeating patients.

3.1.8. Data Analysis Plan

Data analysis is conducted to reduce, organise and give meaning to data (Burns &

Grove, 2009). After obtaining raw data, it was entered into a code book using the Statistical

Package for The Social Sciences (SPSS PC) which was then used to analyse that data.

Descriptive statistics were used to describe the sample characteristics, the dependent and the

independent variables. The Pearson’s correlational coefficient was computerised to show

whether there is a relationship between late stage cervical cancer diagnosis and number of

comorbidities in elderly women in Zimbabwe using a modified Charleson Comorbidity Index

and simple regression used to explain the relationship.

51

Chapter 4

Results

This section presents the results obtained from this study done to determine the

relationship between prevalence of late stage diagnosis of cervical cancer and number of

comorbidities in elderly women above 65 years in Zimbabwe.

4.1. Demographic data

Results from the demographic section are summarised as follows. Thirty-one women

(45.6%) were aged between 65-70 years, 17 (25%) aged between 71-75 years, 13 (19.1%)

between 76-80 years and 7 (10.3%) were aged above 80 years. The mean age was 72.57

years. On marital status, 6 (8.8%) women were single, 25 (36.8%) married, 9 (13.2%)

divorced and 28 (41.2%) were widowed. Of those who were married, 38 (55.9%) married in

their teens, 23 (33.8%) between the ages of 20-35 years and 1(1.5%) married beyond 35 years

of age. The mean age at marriage was 18.74. In terms of parity, 9 women (13.2%) were

nulliparous, 18 (26.5%) gave birth to 1-3 children, 23 (33.8%) had 4-6 children and 18

(26.5%) had more than 6 children. The mean parity was 4.66.

52

Table 4.1.Demographic data (1): Age in years (n=68)

Age in years Frequency Percentage

65 3 4.4

66 6 8.8

67 7 10.3

68 8 11.8

69 3 4.4

70 5 7.4

71 1 1.5

72 6 8.8

73 5 7.4

74 3 4.4

76 2 2.9

77 5 7.4

78 1 1.5

79 4 5.9

80 2 2.9

81 1 1.5

83 1 1.5

84 2 2.9

86 1 1.5

87 1 1.5

88 1 1.5

Total 68 100%

53

Demographic data (2): Age when married (n=68)

Age when married Frequency Percentage

12 1 1.5

13 4 5.9

14 8 11.8

15 6 8.8

16 8 11.8

17 4 5.9

18 5 7.4

19 2 2.9

20 2 2.9

21 3 4.4

22 4 5.9

23 6 8.8

24 3 4.4

25 2 2.9

27 1 1.5

28 1 1.5

30 1 1.5

36 1 1.5

Not applicable 6 8.8

Total 68 100%

54

Demographic data (3): Number of children (n=68)

Parity Frequency Percentage

0 9 13.2

1 1 1.5

2 9 13.2

3 10 14.7

4 8 11.8

5 9 13.2

6 4 5.9

7 3 4.4

8 5 7.4

9 3 4.4

10 3 4.4

11 1 1.5

12 1 1.5

13 2 2.9

Total 68 100%

55

Forty-five (66.2%) lived in the rural areas whilst 23 (33.8%) were urban dwellers. Two

women (2.9%) lived alone, 29 (42.6%) lived in a nuclear family with their husband, children

and/or grandchildren, 31 (45.6%) lived in an extended family with other relatives and 6

(8.8%) live with friends or workers.

Seventeen women (25%) had never worked, 18 (26.5%) were retired from

professional employment whilst 9 (13.2%) were still employed, 1 (1.5%) was informally

employed and 23 (33.8%) were farmers. In terms of education, 4 (5.9%) had none, 10

(14.7%) had below primary education, 22 (32.4%) were educated up to primary level, 19

(27.9%) up to secondary level and 13 (19.1%) up to tertiary level. Three women (4.4%) cited

no religious affiliation, 9 (13.2%) were traditionalists, 55 (80.9%) were Christians and 1

(1.5%) admitted to both traditional and Christian beliefs and practices.

For 10 women (14.7%), the nearest health care facility was less than 2 km from their

home, for 46 (67.6%), it was between 2-10 km and for 12 (17.6%), the distance was greater

than 10 km. In terms of usual health care provider, 3 women (4.4%) cited home based carers,

31 (45.6%) went to a clinic, 22(32.4%) went to a hospital, 11 (16.2%) went to a private

practitioner and 1 (1.5%) had none.

56

Demographic data (4): n = 68

Variable Frequency Percentage

Area lived

Rural

Urban

Total

45

23

68

66.2

33.8

100%

Family dynamics

Lives alone

Nuclear family

Extended family

Friends or workers

Total

2

29

31

6

68

2.9

42.6

45.6

8.8

100%

Occupation

Never worked

Retired

Professionally employed

Informal employment

Farmer

Total

17

18

9

1

23

68

25.0

26.5

13.2

1.5

33.8

100%

Level of education

None

Below primary schooling

Primary

Secondary

Tertiary

Total

4

10

22

19

13

68

5.9

14.7

32.4

27.9

19.1

100%

Religion

None

Traditional

Christianity

Both

Total

3

9

55

1

68

4.4

13.2

80.9

1.5

100%

57

Demographic data (5): n = 68

Variable Frequency Percentage

Nearest health care facility

< 2 km 10 14.7

2 – 10 km 46 67.7

>10 km 12 17.6

Total 68 100%

Usual health care provider

Home based carer 3 4.4

Clinic 31 45.6

Hospital 22 32.4

Private practitioner 11 16.2

None 1 1.5

Total 68 100%

58

4.2. Cervical cancer

4.2.0. Diagnosis

Results are summarised as follows: Eighteen women (26.5%) had been diagnosed less

than a year, 26 (38.2%) between 1-3 years and 24 (35.3%) greater than 2 years. The mean

duration of diagnosis was 1.09 years. Seven (10.3%) were diagnosed in Stage 1, 16 (23.5%)

in Stage 11, 26 (38.2%) in Stage 111 and 19 (27.9%) in Stage 1V. The mean stage was 2.84.

Sixty-three women (92.6%) were currently on treatment or had received treatment and 5

(7.4%) had no treatment. For those on treatment, the duration at the time when this study was

conducted was as follows: 4(5.9%) had weeks, 19 (27.9%) had months, 22 (32.4%) had years

of treatment and 18 (26.5%) had finished treatment. The mean duration of treatment was 2.01

years. In terms of treatment type, 8 women (11.8%) cited chemotherapy, 16 (23.5%)

radiotherapy, 7 (10.3%) cryotherapy, 3 (4.4%) traditional herbs, 6 (8.8%) had surgery and 23

(33.8%) had combined therapy. Those on combined therapy, 13 (56.5%) cited chemotherapy

and radiotherapy, 5 (21.7%) had chemotherapy then surgery, 4 (17.4%) had radiotherapy then

surgery and 1 (4.4%) was combining chemotherapy and traditional herbs from a registered

herbalist.

59

4.2.1. Awareness

Twenty-nine women (42.6%) were aware of the cervical cancer screening drive whilst

39 (57.4%) were not aware. Of those aware, 9 (13.2%) had been actually screened before

cervical cancer diagnosis, 8 of them (11.8%) more than annually and 1 (1.5%) annually.

Fifty-nine of the women (86.8%) were screened at diagnosis. Source of information for

cervical cancer screening awareness was directly from health care providers for 50 women

(73.5%), indirectly from peers, television or other source for 3 (4.4%) and 15 (22.1%) had

both as informants. These results are illustrated in table 4.3.0.

4.3. Comorbidity

A list of the comorbidities suffered by the women is listed in table 4.3.1. Fifty-four

women (79.4%) had comorbidities. Ten (14.7%) had 1 other chronic illness, 16 (23.5%) had

2 other illnesses, 19 (27.9%) had 3, 6 (8.8%) had 4 and 3 (4.4%) had 5 other illnesses. The

mean number of comorbidities was 2.03. The modified Charleson Comorbidity index showed

that 40 (74.1%) participants suffered from comorbidities before the cervical cancer diagnosis,

29 (53.7%) had them after the cervical cancer diagnosis and 13 (24.1%) had comorbidities

before and after the cervical cancer diagnosis. The scoring range was 0-38 sliding scale with

0 being no comorbidities and 38 being the largest number or most affected by other chronic

illnesses. Fourteen (26%) scored from 0-5 and 17 (31.5%) scored from 6-10 on comorbidities

before the cervical cancer diagnosis. The mean score before cervical cancer diagnosis was

5.16 out of 38. After the cervical cancer diagnosis 9 (16.7%) scored between 0-5, 10 (18.5%)

between 6-10 and 7 (13%) from 11-15. The mean score after the cervical cancer diagnosis

was 3.87 out of 38. The results are summarised in table 4.3.

Table 4.2.1. Diagnosis (n = 68)

60

Variable Frequency Percentage

Duration of diagnosis

< a year

1-3 years

>3 years

Total

18

26

24

68

26.5

38.2

35.3

100%

Stage at diagnosis

1

2

3

4

Total

7

16

26

19

68

10.3

23.5

38.2

28.0

100%

Treatment

Yes

No

Total

63

5

68

92.6

7.4

100%

Duration of treatment

Weeks

Months

Years

Finished treatment

Not treated

Total

4

19

22

18

5

68

5.9

27.9

32.4

26.5

7.4

100%

Type of treatment

Chemotherapy

Radiotherapy

Cryotherapy

Traditional herbs

Surgery

Combined treatment

Not treated

Total

8

16

7

3

6

23

5

68

11.8

23.5

10.3

4.4

8.8

33.8

7.4

100%

61

Table 4.2.2. Awareness (n=68)

Variable Frequency Percentage

Screening awareness before diagnosis

Yes

No

Total

29

39

68

42.6

57.4

100%

Actual screening before diagnosis

Yes

No

Total

9

59

68

13.2

86.8

100%

Screening frequency before diagnosis

>Annually

Annually

Stat (at diagnosis)

Total

8

1

59

68

11.8

1.5

86.8

100%

Source of information about screening

Direct

Indirect

Both

Total

50

3

15

68

73.5

4.4

22.1

100%

62

Table 4.3.0. Comorbidities

Variable Frequency Percentage

Comorbidity

Yes 54 79.4

No 14 20.6

Total 68 100%

Number of comorbidities

0 14 20.6

1 10 14.7

2 16 23.5

3 19 27.9

4 6 8.8

5 3 4.4

Total 68 100%

63

Table 4.3.1. Comorbidities in elderly women with cervical cancer in Zimbabwe

(n=68)

Comorbidity Before cervical cancer

diagnosis

After cervical cancer diagnosis

Hypertension

Diabetes mellitus

HIV/AIDS

Deep vein thrombosis

Ulcers

Schizophrenia

Breast cancer

Sleeping disorders

Arthritis

Heart failure

Renal failure

Vesicular-vaginal fistula

Backache

Liver disease

Dementia

Cataracts

Chronic pulmonary disease

Schizophrenia

Osteoporosis

Solid cancer (lungs, stomach)

Skin disorders

Depression

Cor-pulmonale

Hepatitis

21

15

5

5

4

4

3

3

3

3

2

2

2

2

1

1

1

1

1

1

1

0

0

0

4

5

2

0

2

5

2

2

2

6

8

0

2

4

0

0

0

0

0

7

0

1

1

1

64

Table 4.3.2. Comorbidity score before cervical cancer (n = 68. Mean = 9.03)

Score Frequency Percentage

0 14 20.6

3 3 4.4

4 4 5.9

5 2 2.9

6 4 5.9

7 1 1.5

8 8 11.8

9 5 7.4

10 1 1.5

11 8 11.8

12 2 2.9

13 1 1.5

14 4 5.9

15 2 2.9

17 2 2.9

18 3 4.4

19 1 1.5

20 1 1.5

21 1 1.5

28 1 1.5

31 1 1.5

Total 68 100%

65

Table 4.3.3. Score of comorbidities after the cancer diagnosis (n = 68. Mean = 3.87)

Score Frequency Percentage

0 39 57.4

3 1 1.5

4 6 8.8

5 2 2.9

6 3 4.4

7 3 4.4

8 1 1.5

9 2 2.9

10 1 1.5

11 1 1.5

12 2 2.9

13 1 1.5

14 1 1.5

15 2 2.9

18 1 1.5

20 1 1.5

21 1 1.5

Total 68 100%

66

Table 4.3.4. Comorbidity scoring summary (n=68.)

Score range Number of

participants with

chronic illnesses

before cancer

diagnosis

Number of

participants with

chronic illnesses

after cancer

diagnosis

Number of

participants who had

chronic illnesses

before and after the

cancer diagnosis

0-10 - low

11-20 - moderate

>20– high

31

7

3

19

9

1

27

24

3

67

4.4. Relationship between prevalence of late stage cervical cancer diagnosis and number of

comorbidities

Table 4.4shows the results of the Pearson correlation analysis to establish if there was

a relationship between prevalence of late stage cervical cancer diagnosis in elderly women

and number of comorbidities. The correlation coefficient is 0.431 and significance is

0.01.The results show a positive correlation (r = .431, p = 0.01), which shows a strong

relationship between prevalence of late stage diagnosis and number of comorbidities. As

number of comorbidities increase, the later the stage of diagnosis of cervical cancer.

Table 4.4.1 shows the regression analysis. R² is 0.186. which when expressed as a

percentage is 18.6%.This result implies number of comorbidities accounts for 18.6% of the

variance in late stage diagnosis of cervical cancer which is the dependent variable. Other

factors are involved in affecting late stage diagnosis besides number of comorbidities. The

significant F-test (F = 15.062, p = 0.01) indicates a linear relationship and that R² is

significant. The T-test for the unstandardized regression coefficient (b = 0.289) and is

significant at 0.01. It represents a change in the dependent variable which is late stage

diagnosis for every unit change in number of comorbidities significant at the level of 0.01.

Summary

This chapter presented the results of the study undertaken using frequencies and

percentages presented in tables as descriptive statistics. Pearson’s correlation analysis was

used to test the relationship between prevalence of late stage diagnosis of cervical cancer and

number of comorbidities. The regression coefficient was then used to analyse the change in

the prevalence of late stage diagnosis of cervical cancer against change in number of

comorbidities.

68

4.4.0 Correlation (n = 68)

Pearson’s correlation matrix of late stage diagnosis of cervical cancer and number of

comorbidities (n = 68):

Y

1.000

X .431**

*p < 0.05 **p < 0.01 *** p < 0.001

Key

Y = Late stage diagnosis of cervical cancer

X = Number of comorbidities before cervical cancer diagnosis

69

4.5. Regression analysis (n = 68)

Variable B SEB BETA

X 2.251 0.184 0.431

Constant 12.211 0.075

R² 0.186

F = 15.062** 0

*p < 0.05 **p < 0.01 *** p < 0.001

Key

X = Independent variable

70

Chapter 5

Discussion of findings

5.1. Demographic data

The modal age group range was 65-70 years with the mean age at 72 years. Women

older than this could have been lost to follow up due to death or failure to honour review

dates. The commonest marital status was widowed followed by married women. This

supports findings by Gyenwali in India that women tend to look after themselves last after

taking care of everyone else. In this study’s demographic section, 42.6% of the participants

were from a nuclear family and 45.6% from an extended family thus having social support to

seek health treatment. This supports a study done by Mupepi et al (2011) to examine the

demographic factors influencing cervical cancer screening behaviours in Zimbabwe, results

indicated that younger women are more open to screening, and that older women need

support from their family.

One of the risk factors for development of cervical cancer is early sexual activity.

Fifty-five percent of the participants married in their teens commencing early sexual activity

and 60.5% had 4 or more children. Increased parity also increases the chances of developing

cervical cancer (WHO, 2014). The majority of women came from the rural areas where the

usual health care provider was on average 2-10 km away from home. Considering the aging

process and the burden of extended family that the elderly women has, this supports the

findings that 42.6% of the participants were aware of the cervical cancer screening drive but

unable to go for the actual screening process as only 13.2% of those aware were actually

screened before the cervical cancer diagnosis.

The official retirement age in Zimbabwe is 65 years (Zimbabwe Constitution, 2014).

Eighteen (26.5%) participants were retired from formal employment, 9 (13.2%) were still

71

formally employed and 33.8% were farmers as the country is a farming region. In a study by

Sagonda & Chamanga (2013), most employees who reach the retirement age continue in

formal employment and some branch out into unofficial employment to make ends meet.

They found that 69.3% of employees working in the public sector continue to do so beyond

65 years of age as well as 74.2% in other sectors due to various reasons, the most common of

which was backlog of paperwork followed by personal requests.

The findings of this study also show that literacy levels are high as 70.1% of

respondents had at least attained primary level education. More than 80% of participants

followed Christian beliefs and only 1.5% admitted to mixing both traditional and Christian

values. The traditional viewpoint has a large impact in Zimbabwe as treatment leans towards

herbs and away from hospital care due to traditional socialisation especially in elderly

patients. As 87% of those aware of cervical cancer screening were not actually screened, it

shows that level of education has little bearing on the screening drive. There is need to

disseminate information and offer a flexible cervical cancer screening package to elderly

women above 65 years of age to promote regular screening.

The usual health care provider is important in providing health education for early

cervical cancer screening. Only 1.5% of the participants had no usual heath care provider,

indicating that more than 90% of them had regular contact with health care workers. This is

supported by the finding that 73.5% of participants received screening information directly

from a health worker even though only a few them were actually screened. According to

studies done in America, physicians seldom refer elderly women for cervical cancer

screening using the assumption that it would not improve quality of life at that age. So

although most elderly women came in contact with health care workers, few of them were

referred for screening. In Zimbabwe, a lot of resources towards cervical cancer efforts have

been channelled to the 15-49 year age group whilst neglecting the elderly people (Chipfuwa,

72

2012). A survey done at the Visualisation and Acetic Testing screening clinic at Parirenyatwa

and Chinhoyi showed that 14 out of 23 health care providers did not refer elderly patients for

cervical cancer screening with 1 of the reasons being that they were perceived to now less

sexually active thereby at no risk of developing cervical cancer. This was part of a study to

assess knowledge levels about the cervical cancer screening package given to health care

workers (Chinhamora, 2009). Health care providers at VIAC centres verbalised that they

hardly refer elderly patients for cervical cancer screening as they perceive it to be a waste of

resources. There is a need for further research to find out other reasons for non-referral.

5.2. Late stage cervical cancer diagnosis

Respondents for the study had been diagnosed from 1999 – 2015. The duration of

diagnosis for 64.7% of respondents was within 3 years and 35.3% beyond 3 years.

Presentation by stage was normally distributed with most participants presenting at stage 111

(38.2%) and 27.9% presenting with stage 1V. Prevalence for late stage presentation was

0.661. The Zimbabwe National Cancer registry put the prevalence of cervical cancer

presentation at 0.154 in 2009; it stands to reason that the prevalence has increased since then

despite early detection awareness due to late stage presentation of patients. This supports

findings from a study done in Cleveland that more cancer causing lifestyles are affecting the

elderly now and leading to late diagnosis of cancers (Berger, 2011).

Fortunately, 92.6% of participants were on treatment, with 33.8% receiving combined

therapy. The most common combination was radiotherapy coupled with chemotherapy which

gave rise to a high development of comorbidities after cervical cancer diagnosis for these

elderly women.

73

5.3. Comorbidity

Fifty-four respondents (79.4%) suffered from comorbidities. From these, 35% had at

least 3 or more other chronic illnesses before the cervical cancer diagnosis. The average

number of comorbidities was 2.03. Hypertension and diabetes mellitus were the most

common comorbidities patients had before they were diagnosed with cervical cancer. After

diagnosis, respondents reported renal, heart and liver failure as the most common illnesses.

An interesting finding was that breast cancer occurred in 6% of respondents both before and

after cervical cancer diagnosis. Further research might be needed to find out if there is a link

between the 2.

The Pearson’s correlation coefficient showed a positive and significant relationship (r

= .431, p = 0.01) between prevalence of late stage presentation of cervical cancer and number

of comorbidities. Regression analysis showed a strong effect relationship (R² = 0.289). This

supported the hypothesis that the greater the number of comorbidities suffered by elderly

women, the later they presented with cervical cancer but at a smaller scale. Other factors are

also causing the late stage presentation in these elderly women. Other causes of late

presentation could be health-care provider lack of knowledge. This study showed that 45

(66.2%) of the participants hailed from the rural area. This could mean reduced accessibility

to health care facilities as well as delayed referral system.

Not much research has been done in Zimbabwe about the elderly in particular even

though we are all moving towards old age. According to Nhongo (2014), there are several

factors involved in the elderly who suffer from chronic illnesses. They are bombarded with

polypharmacy, fear of the unknown and drug-drug interactions of which they are then

reluctant to seek professional heath care therefore end up presenting with late symptoms.

Chigariro (2014), from the Cancer Association of Zimbabwe, postulated that elderly women

with cervical cancer are less likely to seek medical care as they are swamped with other

74

responsibilities. A study done by Ward in rural Zimbabwe in 2011 supported these findings

as he discovered that although heath care was within reach for the elderly woman, she was

bound to prioritise others first and she last especially when living with orphaned

grandchildren or with HIV/AIDS. In this study, there were 5 women who were on anti-

retroviral for years before the cervical cancer diagnosis and 2 who developed full blown

AIDS after the cervical cancer diagnosis.

The Eve Appeal study done in America in 2010 found out that although most elderly

women were aware of cervical cancer screening, few bothered to have it done due to fear of

the unknown (Singh & Badaya, 2012). There is a need to address fears of the elderly

population in particular if there is to be improved uptake of cervical cancer screening and

early detection in elderly patients, leading to early treatment.

Although figures from the Zimbabwe National Cancer Registry are available for

prevalence of cervical cancer in elderly women, there is need to define specific parameters on

the late diagnosis and to do studies specifically for the elderly.

5.4. Study limitations

A proper pilot study could not be done and the sample had to be quartered due to time

and financial constraints. The permission to carry out the study took 2 months to be granted

from JREC leaving little time for data collection and analysis. This led to use of a small

sample and bias as the pre-test of the study instrument had to be done at the same area as the

actual study. According to Polit & Hungler (2011), use of a different site in pre-testing or

piloting reduces the chance of a bias and increases validity and reliability of a research

instrument. There is a need to include reviewers in the ethical panel who are specific to

proposal review and not committed elsewhere in order to promote carrying out of timeous

research studies.

75

Most potential participants were not staged and therefore not eligible for the study.

There is need to identify ways of staging patients early on the diagnosis to monitor progress

and prevent delays in treatment.

5.5. Recommendations

Research

Further research needs to done in the area of cervical cancer screening uptake by elderly

women in Zimbabwe. Studies can also be done about the particular treatment combinations as there is

need for fine balance to prevent renal or liver failure from heavy chemotherapy agents especially with

the ageing process in effect.

Clinical practice

Rigorous patient follow-up measures need to be put in place so that patients are not

lost to follow up and to reduce time between contact with health care provider and treatment

commencement. Pap smears should be taught to all health care providers including

pharmacists and home based carers who must be able to perform cervical cancer screening at

the most basic level of contact so that elderly patients already saddled with other chronic

illnesses are not ferried from one carer to the next, which is not only tiring but time-

consuming as well. From this study, the most common comorbidity cluster was hypertension

and diabetes mellitus before diagnosis and renal failure with cardiac conditions after the

cervical cancer diagnosis. Elderly patients should be able to obtain BP, blood sugar,

cholesterol, weight and renal function tests together with pap smears at 1 place, be it a

pharmacy, clinic or mobile HBC team to promote early screening and treatment.

Education

Government efforts and foreign investors should aim at arming all women with

knowledge about their health and also make readily available and affordable cervical cancer

76

screening and treatment equipment; not focus on younger groups only. The nursing

curriculum should include a speciality in geriatric nursing in Zimbabwe to accommodate the

ever-increasing elderly population and keep up with international standards in care of the

elderly. As a nation. Zimbabwe is adopting cancer-causing lifestyles from the eastern and

western nations thus it follows that there is a surge of non-communicable diseases including

cancer in the new age pandemic.

Summary

This study presented a summary of findings, discussion and implications of the study

to medical-surgical nursing research, practice and education. Limitations and

recommendations were also discussed. The average number of comorbidities suffered before

the cervical cancer diagnosis in elderly women in Zimbabwe is 2.03 Number of comorbidities

in elderly women affect the way they interact with the health care system, discourages them

from seeking treatment for more serious conditions like cancer leading to presentation with

late stage symptoms.

The purpose of the study was to determine the relationship between prevalence of late

stage diagnosis of cervical cancer and number of comorbidities in elderly women aged 65

years and above in Zimbabwe. Betty Neuman’s Systems model was used to guide the study.

A number of environmental stressors affect the primary and secondary prevention of cervical

cancer in elderly women leading to tertiary prevention which leads to palliative care as the

disease will have progressed to stage 3 or 4. A quantitative, non-experimental, descriptive

correlational design was used to conduct the study. The design helped in the description of

variables and the relationship between them. Convenience sampling was used to select 68

participants from the Parirenyatwa Radiography department, ward A6 as well as Spilhause

clinic at Harare Hospital. Thirty minute structured interviews were conducted using an

interview guide. A power analysis of .80 and significance level of .05 were used to calculate

77

the sample size which was then quartered due to time and financial constraints. Power assists

in identification of relationships in populations, a positive, significant correlation was

identified between prevalence of late stage cervical cancer diagnosis and number of

comorbidities before the diagnosis (r = .431**, p < 0.01).

Regression analysis was used to predict the value of late stage cervical cancer

diagnosis based on the values of number of comorbidities. The R² of .186 supported that

number of comorbidities explains an 18.6% variance in late stage diagnosis of cervical

cancer. This indicates that there are other factors which actually contribute to late stage

diagnosis besides number of comorbidities. This alludes to further research.

78

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83

APPENDIX I: English Consent form

PARTICIPANT INFORMED CONSENT

PROTOCOL TITLE: A study to determine the relationship between prevalence of late stage

diagnosis of cervical cancer and number of comorbidities in elderly women aged 65 years

and above in Zimbabwe.

NAME OF RESEARCHER: Yvonne Kagura

PHONE: 0772 393 036

PROJECT DESCRIPTION: This is a study looking at elderly women in Zimbabwe suffering

from cervical cancer, whether diagnosed recently or over years. Comorbidities or concurrent

illnesses in these women will also be looked at to find out if they have any effect on

prevalence of late stage diagnosis of cervical cancer.

YOUR RIGHTS: Before you decide whether or not to volunteer for this study, you must

understand its purpose, how it may help you, the risks to you, and what is expected of you.

This process is called informed consent.

PURPOSE OF RESEARCH STUDY: The purpose of the study is to determine the effect of

comorbidity on prevalence of late stage cervical cancer diagnosis. The results will be used to

further knowledge of health care providers and implement health conscious programs for

elderly women who suffer from chronic illnesses including cervical cancer.

PROCEDURES INVOLVED IN THE STUDY: A 30 minute interview will be conducted

with you being asked questions relating to your condition and how you are living with it.

DISCOMFORTS AND RISKS: The structured interview will take at most 30 minutes of your

time and will take place in a quiet, comfortable and private place to protect your

confidentiality. All measures have been taken to ensure minimal risk to your health.

84

POTENTIAL BENEFITS: There are no financial benefits for participating in this study. You

will be allowed time to ask all the questions you wish to and clarification will be made. You

are free to call me anytime if you have any further enquiries.

Initials ___________

STUDY WITH DRAWAL: You may choose not to enter the study or withdraw from the

study at any time without loss of benefits entitled to you.

CONFIDENTIALITY OF RECORDS: Your name or hospital number will not appear on any

of the documents which may tie the information back to you. The answers you give in the

interview will be entered in a database and cannot be traced back to you so feel free to answer

all questions.

PROBLEMS/QUESTIONS: Please ask questions about this research or consent now. If you

have any question in future please ask or call me on the given telephone number -

0772393036.

AUTHORIZATION: I have read this paper about the study or it was read to me. I understand

the possible risks and benefits of this study. I know being in this study is voluntary. I choose

to be in this study: I know I can stop being in the study and I will not lose any benefits

entitled to me. I will get a copy of this consent form. (Initial all the previous pages of the

consent form)

___________________________________________________________________________

Client Signature Date

___________________________________________ Client Name (Printed)

___________________________________________________________________________

Researcher Signature Date

___________________________________________________________________________

Witness Signature Date

85

APPENDIX II: Shona Consent Form

GWARO REBVUMO

MUSORO WETSVAKURUDZO: Tsvakurudzo yehukama huri pakati pekurwara nezvirwere

zvimwewo nekunonoka kubatwa kwechirwere chegomarara remuromo wechibereko

muvanhukadzi vane makore makumi matanhatu nemashanu kana kudarika muno

muZimbabwe.

ZITA REMUTSVAKURUDZI: Yvonne Kagura

MBOZHANHARE: 0772 393 036

TSANANGUDZO YETSVAKURUDZO: Ino itsvakurudzo iri kutarisa madzimai ane makore

makumi matanhatu nemashanu kana kudarika vari muZimbabwe zvisinei kuti vachangobatwa

negomarara remuromo wechibereko, kana kuti vave nemakore. Zvimwe zvirwere zvinenge

zvichirwariwa nemadzimai aya zvichange zvichiongororwa kuti zvine chekuita here

nekunonoka kubatwa kwegomarara remuromo wechibereko.

KODZERO DZENYU: Munofanira kunzwisisa chikonzero nei tsvakurudzo iyi iri kuitwa,

ingakubatsirei sei, chii chamunotarisirwa kuita uye kuti pangave nenjodzi here kuutano

hwenyu musati mafunga kuti mupinde mutsvakurudzo iyi. Urwu ruzivo runokubatsirai kuita

sarudzo yakakwana.

CHIKONZERO CHETSVAKURUDZO: Tsvakurudzo ino inotarisa ukama huri pakati

pezvimwe zvirwere pakunonoka kubatwa kwegomarara remuromo wechibereko.

Zvichawanikwa mutsvakurudzo iyi zvichabatsira kuwedzera zivo kune vakoti kuti vawane

mabatsiro avangaite madzimai echikuru ane zvimwewo zvirwere pamusoro pegomarara

remuromo wechibereko.

86

ZVAMUNOTARISIRWA KUITA: Muchabvunzwa mibvunzo pamusoro pechirwere

chegomarara chamuinacho uye kuti muri kurarama sei nacho. Zvichatora minhasvu

isingadarike makumi matatu.

NJODZI DZINGATARISIRWE: Mibvunzo ichaita minhasvu makumi matatu bedzi.

Muchabvunzirwa munzvimbo yakahwanda, inochengetedza nhau dzeutano hwenyu. Njodzi

kuutano hwenyu ichange iri shoma chose.

ZVAMUNGATARISIRWE KUWANA: Hapana mari yamunotarisirwa Kuwana nekuda

kwekunge muri mutsvakurudzo iyi. Munobvumirwa kubvunza mibvunzo chero nguva kana

kuchaya nhare kuti munzwisise nezvetsvakurudzo kana chirwere chenyu.

Mavara ekutanga emazita enyu ___________

KUREGEDZA TSVAKURUDZO:Munokwanisa kurega kuenderera mberi netsvakurudzo iyi

chero nguva pasina njodzi ingakuwirei.

KUCHENGETEDZWA KWENHAU DZEHUTANO HWENYU: Zita kana nhamba

yemuchipatara hazvisi kuzonyorwa chero pai hapo. Saka hapana nhau dzeutano hwenyu

dzingaburitswe kunze kwemutsvakurudzi. Mhinduro dzamuchapa dzichaiswa mudatabase

saka hadzingazodzoki kwamuri saka pindurai makasungunuka.

MIBVUNZO: Bvunzai mibvunzo pamusoro petsvakurudzo iyi kana gwaro rino rebvumo

izvozvi. Makasununguka henyu kuzobvunza pamberi apo kana kuchaya nhare panhamba

dzinotevera - 0772393036.

BVUMO:Ndaverenga gwaro rino rebvumo kana kuti ndariverengerwa. Ndanzwisisa njodzi

yandingasangane nayo kana zvandingabatsirike nazvo. Ndinoziva kuti kuve kwangu

mutasvakurudzo iyi kuzvipira kuzere. Ndasarudza kunge ndiri mutsvakurudzo iyi pasina

kugombedzerwa, hapana zvingandiwire ndikarega ndiri pakati. Ndichawanawo kopi yegwaro

87

rebvumo iri. (Nyorai mavara ekutanga emazita enyu pa bepa rega-rega regwaro rino).

___________________________________________________________________________

Runyoro rwemurwereZuva

___________________________________________ Zita remurwere (Printed)

___________________________________________________________________________

Runyoro rwemutsvakurudzi Zuva

___________________________________________________________________________

Runyoro rwemuchuchisi Zuva

88

APPENDIX I11: English Interview Guide

INTERVIEW GUIDE_____________

Section A: Demographic Data

1. Age 65 – 70______

71 – 75______

76–80______

>80______

2. Marital status Single_______

Married______

Divorced_____

Widowed_____

3. Age at marriage Teen_________

20 – 35_______

>35__________

N/A______

4. Parity Nulliparous____

1 -3__________

4-6___________

>6____________

5. Area Lived Rural_________

Urban ________

6. Family dynamics Lives alone_____

Nuclear family___

Extended family__

Friends or workers__

7. Occupation Never worked______

Retired___________

Professionally employed______

Informal employment_________

Farmer__________

89

8. Level of education None____

Below primary level____

Primary level____

Secondary level___

Tertiary level_____

9. Religion None_____________

Traditionalist_______

Christian__________

Combine_______

10. Nearest health care facility <2km________

2 – 10km_____

>10km_______

11. Usual health care provider HBC (home based carers)____

Council clinic_________

Gvt or mission Hospital______

Private Practitioner______

None________

Section B: Cervical cancer

12. Year diagnosed

13. Duration of diagnosis <a year_________

1-3 years____

>3years_____

14. Stage at diagnosis 1____

11___

111___

1V__

90

15. Treatment Yes___

No____

16. Duration of treatment so far Weeks ________

Months_________

Years__________

Finished treatment (remission)

N/A

17. Type of treatment Chemotherapy only___

Radiotherapy only____

Cryotherapy only_____

Traditional herbs only___

Surgery only______

Brachytherapy only____

Combined (specify) ______

N/A_____

18. Cervical cancer screening awareness Yes______

No______

19. Screening before diagnosis Yes_____

No______

20. How often >Annually___

Annually__

Stat (at diagnosis) ________

21. Source of information(screening) Direct from health care provider__

Indirect from TV, radio, peers__

Both_____

91

Section C: Comorbidity

22. Any other illness Yes__

No___

23. Comorbidity scoring

Note: for each decade > 60 years of age, a score of 1 will be added.

Score Condition When diagnosed Treatment

Before Ca

cervix

After Ca

cervix

Yes No

3 Myocardial infarction

Congestive cardiac failure

Peripheral vascular disease

CVA

Dementia

Depression

Anxiety disorders

Sleeping disorders

Chronic Pulmonary Disease

Connective tissue disease

Alzheimer’s

Osteoporosis

Backache

Eye disorders(cataracts)

Peptic Ulcer Disease

Mild liver disease

DM (uncomplicated)

Hypertension

Arthritis

4 Hemiplegia

Moderate or severe renal

disease

DM (with end-organ damage)

Tumour without metastasis

Leukaemia

Lymphoma

HIV on ART

5 Moderate to severe liver

disease

Hepatitis

6 Metastatic solid tumour

AIDS

92

APPENDIX 1V: Shona Interview Guide

MIBVUNZO YENHAURIRANO_____________

Section A: Demographic Data

1. Makore ekuberekwa 65 – 70______

71 – 75______

76 – 80______

>80______

2. Kuwanikwa Kwete_______

Hongu______

Vakarambana_____

Chirikadzi_____

3. Makore ekuwanika Teen_________

20 – 35_______

>35__________

N/A____

4. Vana vakaberekwa Hapana____

1 -3__________

4-6___________

>6____________

5. Nzvimbo inogarwa Kumusha _________

Mudhorobha________

6. Mhando yemhuri yavanogara nayo Vega____

Vemumba mavo bedzi__

Hama dzimwewo__

Shamwari kana vashandi__

7. Basa Havana kumboshanda______

Vari pamudyandigere___________

Vanoshanda pakambani ______

Vnozvishandira_________

Murimi__________

8. Dzidzo Kwete____

93

Pazasi pepuraimari____

Vakasvika kupuraimari____

Vakasvika kusekondari___

Vakasvika kuUnivhesiti_____

9. Chinamato Havana_____________

Vanoita zvemidzimu_______

MuKristu__________

Vanosanganisa_____

10. Panorapwa pedyo zvakadii <2km________

2 – 10km_____

>10km_______

11. Kwavanosirapwa Varapi vekumba____

Kiriniki yekanzuru_________

Chipatara chehurumende kana misheni______

Chiremba akazvimirira______

Hakuna_____

Section B: Gomarara remuromo wechibereko

12. Gore rabatwa gomarara

13. Gomarara rabatwa nguvai Pazasi pegore_________

1-3 years____

>3years_____

14. Rakabatwa panhamba ipi 1____

11___

111___

1V___

94

15. Vari kurapwa Hongu___

Kwete____

16. Varapwa nguva yakareba sei Mavhiki ________

Mwedzi_________

Makore__________

Vakatopedza kurapwa_____

17. Vari kurapwa nei Chemotherapy chete___

Radiotherapy chete____

Cryotherapy chete_____

Traditional herbs chete____

Surgery chete_____

Brachytherapy chete___

Zvakasangana (ndezvipi) ______

N/A______

18. Ruzivo nezvekuongororwa gomarara Hongu______

Kwete______

19. Kuongororwa vasati vabatwa negomarara Hongu_____

Kwete______

20. Vakaongororwa kangani Pasi pegore___

Gore negore__

Kamwe chete________

21. Vakaudzwa nani nezvekuongororwa Nanamukoti__

Nevamwewo__

Vose vari pamusoro___

95

Section C: Comorbidity

22. Zvimwe zvirwere zvisiri gomarara Hongu__

Kwete___

23. Comorbidity scoring

Note: for each decade > 60 years of age, a score of 1 will be added.

Chibo

dzwa

Chirwere Chakabatwa riini Kurapwa

Before Ca

cervix

After Ca

cervix

Hon

gu

Kwe

te

3 Myocardial infarction

Congestive cardiac failure

Peripheral vascular disease

CVA

Dementia

Depression

Anxiety disorders

Sleeping disorders

Chronic Pulmonary Disease

Connective tissue disease

Alzheimer’s

Osteoporosis

Backache

Eye disorders(cataracts)

Peptic Ulcer Disease

Mild liver disease

DM (uncomplicated)

Hypertension

Arthritis

4 Hemiplegia

Moderate or severe renal

disease

DM (with end-organ damage)

Tumour without metastasis

Leukaemia

Lymphoma

HIV on ART

5 Moderate to severe liver

disease

Hepatitis

6 Metastatic solid tumour

AIDS

96

APPENDIX V: PERMISSION LETTERS