Research Article - Onkologia i Radioterapia ( 2024) Volume 18, Issue 1

Quality of life and its associated factors among patients with cancer in Hilla city/Iraq

Saja Mohammed Hashim* and Shatha Saadi Mohammed
 
Department of Nursing, College of Nursing University of Babylon, Hillah, Iraq
 
*Corresponding Author:
Saja Mohammed Hashim, Department of Nursing, College of Nursing University of Babylon, Hillah, Iraq, Tel: 9652806704, Email: sajahashim768@gmail.com

Received: 10-Jun-2023, Manuscript No. OAR-22-102033; , Pre QC No. OAR-22-102033 (PQ); Editor assigned: 13-Jun-2023, Pre QC No. OAR-22-102033 (PQ); Reviewed: 28-Jun-2023, QC No. OAR-22-102033; Revised: 27-Dec-2023, Manuscript No. OAR-22-102033 (R); Published: 03-Jan-2024

Abstract

Objectives: Quality of life is an important measure for evaluating and predicting treatment for cancer patients. Patients with cancer are at increased risk of a poor quality of life during effective cancer treatment. This study aimed to assess quality of life and its associated factors among patients with cancer.

Methods: A descriptive correlational study conducted in Hill city during the period from November 9th 2022 to April 18th 2023. The study sample consist of 150 patients is selected according to non-probability sampling approach. The validity of the questionnaire was verified by experts and its reliability was verified through a pilot study. Data were collected through the interview and analyzed by applying descriptive and inferential statistical analysis.

Results: The results indicated that the average age of the participants is 51 among those who are female (84%), married (74%), elementary school graduated (36%), who are free business (32.7%) with enough to certain limit (53.3%). Over than half (53.3%) of the study participants were found to average quality of life. Quality of life are differs according to age, marital status, occupation, monthly income, duration of cancer and stages of cancer (p=.000).

Conclusion: Quality of life for cancer patients was generally average and was mostly influenced by demographic factors including age, marital status, occupation and monthly income as well as clinical aspects of cancer such as its length and stages of disease. Recruit ministries and social organizations to play a role in ensuring that cancer patients have access to adequate financial resources to meet their demands in order to minimize the negative effects of individual variables affecting their quality of life.

Keywords

Quality of life; Associated factors; Cancer; Female; Demographic

Introduction

In 2020, there will likely be 10.6 million cancer related deaths and 19.3 million new instances of the disease worldwide [1]. In actuality, 28.4 million more cases are predicted to arise by 2040. Even while overall survival and long term disease free survival are the main goals of cancer treatment, Health Related Quality of Life (HRQOL) is one of the main outcomes. Many cancer patients prefer to enhance their HRQOL over extending their life expectancy from their perspective and their present HRQOL may affect the future treatments they select [2]. Physicians regard HRQOL to be crucial for survival when determining a course of treatment for cancer patients [3]. Additionally, HRQOL may be used to define the course of supportive therapy for cancer patients or to forecast their prognosis [4]. Patients use the complex construct known as QOL to evaluate their current state of health. These elements comprise their cognitive, social, emotional and physical abilities as well as their symptoms and therapy-related adverse effects [5]. In actuality, chemotherapy for cancer patients requires repeated hospital stays for checkups, chemotherapy or other therapies [6]. Quality of Life (QoL) has emerged as a crucial metric for assessing the prognosis and course of treatment for cancer patients. During active cancer therapy, cancer patients are more likely to have low quality of life [7]. Therefore, thus aimed to assess quality of life and its associated factors among patients with cancer in Hill city/ Iraq.

Materials and Methods

Study design: The descriptive correlational study design technique was carried out in Hilla city/Iraq during the period from November 9th 2022 to April 16th 2023.

Study sample: The study sample included in present study are patients with cancer is selected according to non-probability sampling approach with a total of (150) who are attended babylon oncology center in babylon province for the purpose of receiving care was chosen based on a set of criteria include: 1)Those who are diagnosed any types of cancer, 2) Who were diagnosed with cancer for more than 6 months, 3) Who are different age groups and 4) Volunteer to participate in the study after his consent.

Study instrument: This questionnaire consists of two parts include the followings.

Part I: Patients characteristics include age, gender, marital status, education level, occupation, monthly income, residents, Cancer type, duration, staging and comorbidities.

Part II: The WHOQoL is a 26 items instrument with four domains: Social relationships, environmental health, psychological health and physical health. The scale included five levels: 1 for very poor, 2 for poor, 3 for moderate, 4 for good and 5 for very good. As a result, points might be earned between 26 to 130. The higher average is what is meant by a high quality of life. Cronbach alpha in the most recent data was 0.89, indicating an acceptable level.

Data collection: The researcher conducted interviews with the participants, gave them a copy of the questionnaire, answered their questions about it, persuaded them to participate, and expressed gratitude for their participation. Individual interviewers conducted each interview for 15 to 20 minutes after completing the crucial stages that have to be part of the study design.

Statistical analysis: The IBM SPSS 20.0 program was used for all of the analyses that follow. The continuous variables were defined using the mean and standard deviation, whereas the discrete variables were categorized using numbers and percentages (No. and %) (SD and mean). ANOVA was used to predict the differences between study variables. To illustrate statistical significance, p.05 was utilized.

Results

Findings reveal participant characteristics, with the mean age being 51 (SD=12.8) for those who are female (84%), married (74%), have completed primary school education (36%), are free-to-run their own businesses (32.7%) with enough to a particular limit (53.3%), and live in cities (60%) (Table 1).

SDVs Classification No. %
Age <20 2 1.3
20-29 7 4.7
30-39 13 8.7
40-49 38 25.3
50-59 29 19.3
60 and older 61 40.7
51 ± 12.8    
Gender Male 24 16
Female 126 84
Marital status Single 2 1.3
Married 111 74
Divorced 2 1.3
Widowed 35 23.3
Education level Illiterate 23 15.3
Read and write 19 12.7
Elementary 54 36
Middle school 33 22
High school 5 3.3
College 16 10.7
Occupation Employed 32 21.3
Free business 49 32.7
Retired 27 18
Unemployment 42 28
Monthly income Enough 18 12
Enough to certain limit 80 53.3
Not enough 52 34.7
Residents Urban 90 60
Rural 60 40

Tab. 1. Socio demographic characteristics.

Findings show participants clinical data, the most common type of cancer among studied sample were breast cancer (65.3%), most of the participants were diagnosed with cancer 1-3 years ago (74%), more than half of participants in the stage II metastasis (40%), chemotherapy were the most common type of treatment (71.3%), one-third were no associated comorbidities (Tables 2 and 3).

Clinical data Classification No. %
Type of CA Digestive system and liver 29 19.3
Kidney and urinary system 9 6
Breast 98 65.3
Reproductive system 7 4.7
Blood and lymphatic system 3 2
Bone 2 1.3
Skin 2 1.3
Duration of CA <1 year 18 12
1-3 years 111 74
>3 years 21 14
Stage of CA I 51 34
II 60 40
III 26 17.3
IV 13 8.7
Type of Treatment Chemotherapy 107 71.3
Radiotherapy 5 3.3
Both 38 25.3
Comorbidities No 100 66.7
Diabetes 6 4
Hypertension 29 19.3
Heart diseases 2 1.3
Kidney disease 6 4
Liver disease 2 1.3
Digestive system diseases 4 2.7
Asthma 1 0.7

Tab. 2. Clinical characteristics.

Scales Minimum Maximum M SD Score No. %
QOL related to general health (2Q) 2 6 3.82 1.12 Poor 51 34
Moderate 66 44
Good 33 22
QOL related to physical health (7Q) 7 20 15.35 2.5 Poor 3 2
Moderate 93 62
Good 54 36
QOL related to psychological health (6Q) 6 18 9.63 3.34 Poor 85 56.7
Moderate 53 35.3
Good 12 8
QOL related to environmental health (8Q) 8 22 12.7 4.57 Poor 72 48
Moderate 63 42
Good 15 10
QOL related to social relationship (3Q) 3 9 4.97 1.89 Poor 82 54.7
Moderate 54 36
Good 14 9.3
Overall QOL (Q26) 33 67 47.3 8.82 Poor 58 38.7
Moderate 80 53.3
Good 12 8
Findings indicated that the (53.3%) of cancer patients reported an average quality of life (M=47.3; SD=8.82). 

Tab. 3. Overall WHOQoL levels according to domains.

Findings indicated that the (53.3%) of cancer patients reported an average quality of life (M=47.3; SD=8.82).

Based on analysis of variance, findings indicate that there were significant differences in QOL between patients with respect to their age (p=.000), marital status (p=.000), occupation (p=.000), monthly income (p=.000), duration of cancer (p=.000) and stages of cancer (p=.000) (Table 4).

WHOQOL Source of variance Sum of squares d.f Mean square F-statistic Signature
Age Between groups 9.47 5 1.894 35.351 0
Within groups 7.715 144 0.054
Total 17.185 149
Gender Between groups 0.03 1 0.03 0.258 0.612
Within groups 17.155 148 0.116
Total 17.185 149
Marital status Between groups 7.171 3 2.39 34.854 0
Within groups 10.013 146 0.069
Total 17.185 149
Education level Between groups 0.39 5 0.078 0.669 0.648
Within groups 16.795 144 0.117
Total 17.185 149
Occupation Between groups 8.451 3 2.817 47.091 0
Within groups 8.734 146 0.06
Total 17.185 149
Income Between groups 6.13 2 3.065 40.762 0
Within groups 11.054 147 0.075
Total 17.185 149
Residents Between groups 0.138 1 0.138 1.2 0.275
Within groups 17.046 148 0.115
Total 17.185 149
Type of CA Between groups 0.425 7 0.061 0.512 0.824
Within groups 16.686 141 0.118
Total 17.111 148
Duration of CA Between groups 2.888 2 1.444 14.847 0
Within groups 14.297 147 0.097
Total 17.185 149
Stage of CA Between groups 8.783 3 2.928 50.881 0
Within groups 8.401 146 0.058
Total 17.185 149
Type of treatment Between groups 0.021 2 0.011 0.091 0.913
Within groups 17.09 146 0.117
Total 17.111 148
Comorbidities Between groups 0.895 7 0.128 1.112 0.359
Within groups 16.216 141 0.115
Total 17.111 148

Tab. 4. Statistical differences in quality of life with respect patients variables.

Discussion

For cancer patients, quality of life is a crucial indicator for assessing and forecasting their therapy. During effective cancer therapy, patients are more likely to experience a reduced quality of life. Compared to the normal population, cancer patients typically experience a lower quality of life. Only 8% of those we saw had good QOL, and the remainder 38.7% or 53.3% had poor or moderate QOL. These results, which were supported by previous research from India using the same QoL instrument, demonstrated that cancer patients' quality of life was less than ideal as a result of the numerous symptoms they faced. Interventions for the efficient management of symptoms are required in order to give patients a better sense of control over their condition and course of therapy as well as to raise their quality of Life (QOL) [8,9].

Because of the diverse demographic and social features, cancer patients' quality of life, whether it be bad or medium, is generally not regarded as being at its best. Gender, age, marital status, employment status and income are all factors that can affect a cancer patient's quality of life. Patients who are single or have little financial means should look into additional resources, and patients who are unemployed, female, old, or having radiotherapy to enhance their quality of life should receive special consideration [10]. The findings of this study emphasize the significance of supporting cancer patients in order to enhance the quality of life for cancer patients. Patients and their families will experience considerable financial hardships following the diagnosis of a chronic illness like cancer, which will lead to serious concerns about the price of medical care and treatment. As a result, financial assistance may enhance quality of life by easing patients' and their families' associated financial worries [11].

The current study's findings revealed that there are variations in people's quality of lives depending on their age groupings. Younger age groups benefited more from the variations; on the other hand, as people aged, their quality of life progressively declined. Aging, combined with sickness and therapy, has a detrimental impact on quality of life because of the advanced age and changes. These results are consistent with those from Saudi Arabia, which showed that cancer patients' quality of life declines with age for physiological reasons related to aging and treatment [12]. The gender of the patients in our study had no impact on their total QoL, despite the fact that females had lower mean QoL scores than males (p=.612). Similar findings from two more QoL studies of cancer patients have been published [13,14]. In contrast, female patients in these two investigations had worse physical, social and psychological life characteristics.

According to the analysis of variance, there were statistically significant changes in patients' quality of life depending on their marital status. Compared to unmarried, divorced, or bereaved people, married couples fared better. Compared to other marital statuses, married couples had a much higher quality of life, maybe as a result of social support. According to research from the USA and Israel, married patients have significantly higher quality of life [15,16].

The patients who performed free-business or who did not work (were unemployed) had the worst quality of life compared to those who were working or retired, it was noted that there were statistically significant differences in the quality of life according to the occupation of the patients. Perhaps this is a result of the poor economic conditions experienced by individuals who work for themselves and the social isolation experienced by those who are unemployed. These results are consistent with those from Turkey, which showed that breast cancer patients who were employed had a higher quality of life. Unemployed people may have lower quality of life due to their isolation from social life and lack of social support. Compared to other professions, government employees reported superior general well-being [17].

The current study's findings indicated that there are disparities in people's quality of life depending on their monthly income because those with low monthly incomes had lower quality of life. In other words, a general increase in monthly income can signal a rise in quality of life. The financial condition of cancer patients needs to be brought to the attention of decision-makers, cancer care providers, and social welfare networks. According to research from Iran and Kut and Babylon provinces in Iraq, there is a positive and significant relationship between socioeconomic position and Quality of Life (QoL) among cancer patients [18-20].

According to the results of the analysis of variance, there were statistically significant variations in patients' quality of life depending on the stage of their cancer. The quality of life is inversely correlated with the stage of cancer. This outcome makes sense. Every area of one's quality of life is impacted as the disease's severity worsens, including all physical and psychological symptoms, lethargy, and exhaustion. An Indian study that found that advanced stages of the disease wear down patients' Quality of Life (QOL) supports these findings [21].

According to this study, people with cancer have a lower quality of life in terms of psychological, social, and environmental factors. A crucial component of cancer care is cancer management. All medical personnel are responsible for ensuring that patients receive the proper instruction and care at the appropriate time. The development of strategies for the efficient management of symptoms and enhancement of QOL is required. The two primary problems are how to manage symptoms and how to help patients feel more in control of their condition and course of therapy.

Conclusion

Quality of life for cancer patients was generally average and was mostly influenced by demographic factors including age, marital status, occupation, and monthly income as well as clinical aspects of cancer such as its length and stages of disease. Recruit ministries and social organizations to play a role in ensuring that cancer patients have access to adequate financial resources to meet their demands in order to minimize the negative effects of individual variables affecting their quality of life.

References

Awards Nomination

Editors List

  • Ahmed Hussien Alshewered

    University of Basrah College of Medicine, Iraq

  • Sudhakar Tummala

    Department of Electronics and Communication Engineering SRM University – AP, Andhra Pradesh

     

     

     

  • Alphonse Laya

    Supervisor of Biochemistry Lab and PhD. students of Faculty of Science, Department of Chemistry and Department of Chemis

     

  • Fava Maria Giovanna

     

  • Manuprasad Avaronnan

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