Quality of life among Saudi cancer survivors: The role of social and demographic factors

Abstract

BACKGROUND

Cancer survivorship is a growing concern globally, yet few studies have explored the quality of life (QoL) outcomes among survivors in the Middle East, particularly in Saudi Arabia.

AIM

To assess QoL using the World Health Organization Quality of Life-BREF (WHOQOL-BREF) and to evaluate the impact of demographic and clinical factors among Saudi cancer survivors.

METHODS

We conducted a cross-sectional study of 102 adult cancer survivors recruited from a tertiary hospital in Jeddah, Saudi Arabia. Participants completed the WHOQOL-BREF, which assesses four QoL domains, including physical health, psychological health, social relationships, and environment. Univariate and multivariable robust linear regression models (Huber estimator) were used to identify QoL score predictors, adjusted for key sociodemographic and clinical variables.

RESULTS

The mean participant age was 44.5 years; 72.5% of the participants were female. The mean domain scores were as follows: physical health was 3.05 ± 0.53, psychological health was 3.56 ± 0.79, social relationships was 3.39 ± 0.84, and environment was 3.29 ± 0.74. Socioeconomic and social vulnerability factors, including low income, rental housing, widowed/divorced marital status, and lower education, were independently associated with poorer QoL scores. Residents in rural settings had significantly lower scores in all domains.

CONCLUSION

Our findings reveal noticeable disparities in QoL among Saudi cancer survivors driven by socioeconomic and demographic factors. These insights underscore the need for context-sensitive survivorship programs in Saudi Arabia, with special attention to social support, mental health, and economic stability.

Key Words: Cancer survivors; Quality of life; Saudi Arabia; Sociodemographic determinants; Survivorship care

Core Tip: This study highlights significant disparities in quality of life (QoL) among cancer survivors in Saudi Arabia using the World Health Organization Quality of Life-BREF instrument. It identifies key socioeconomic and demographic predictors—such as rural residence, low income, and limited education—that negatively influence domain-specific QoL. These findings underscore the urgent need for culturally and contextually tailored survivorship programs that address social vulnerability, mental health, and environmental support in Middle Eastern settings.

INTRODUCTION

The global burden of cancer survivorship has intensified with advances in early diagnosis, treatment, and supportive care, leading to increased life expectancy and a growing population of individuals surviving after cancer[1]. However, survivorship is not only about prolonging life but also about enhancing its quality. Health-related quality of life (QoL) has emerged as a critical outcome metric, encompassing the physical, psychological, social, and environmental well-being of individuals after cancer treatment[2]. The World Health Organization Quality of Life-BREF (WHOQOL-BREF) instrument has been widely adopted across cultures and cancer populations as a multidimensional tool to capture survivors' subjective experiences[3,4].

In Saudi Arabia, the number of cancer survivors has steadily increased due to national screening programs, improved access to oncology care, and substantial investment in health services under vision 2030[5-7]. According to Global Cancer Observatory studies, over 28000 new cancer cases were reported in 2022, and survival rates have improved significantly for common cancers such as breast, colorectal, and prostate cancer[8,9]. However, the psychosocial and QoL outcomes of Saudi cancer survivors remain understudied[10-13]. Cultural values, gender norms, social cohesion, and familial structures in the Kingdom are distinct and may modulate the survivor experience in unique ways[14]. For example, family-based support systems often buffer psychological distress, while societal stigma around cancer, particularly among women, may impede open discussion or emotional expression.

The existing literature on cancer survivorship in high-income countries has consistently shown that sociodemographic and clinical factors such as age, gender, income, education, and comorbidities significantly influence health-related QoL (HRQoL) outcomes[15]. However, data from Middle Eastern contexts, including Saudi Arabia, remain limited and fragmented. Some local studies have focused on specific cancer types, such as breast[16] or colorectal cancer[17], often without standardized tools or with small sample sizes that limit generalizability. Furthermore, few investigations have utilized validated cross-culturally appropriate instruments like the WHOQOL-BREF to assess comprehensive QoL domains. This study addresses a critical gap by employing the WHOQOL-BREF to examine QoL outcomes among a diverse cohort of Saudi cancer survivors across age groups, cancer types, and socioeconomic backgrounds. Importantly, the analysis situates survivor well-being within the framework of the social determinants of health, recognizing that medical recovery alone does not ensure psychological or social reintegration. By capturing variations in HRQoL across demographic variables such as gender, education, marital status, employment, income, and housing conditions, the study aligns with growing calls in global oncology for equity-oriented survivorship research. The Saudi context provides a compelling setting for this analysis. While the healthcare system offers comprehensive cancer care at no direct cost to citizens, disparities persist in access, continuity of care, and psychosocial support services[18]. In addition, regional disparities, for instance, between urban and rural settings may influence environmental and social QoL domains[18,19]. The prevailing collectivist culture emphasizes familial interdependence and may impact perceptions of autonomy, social support, and psychological adjustment. Understanding how these culturally embedded factors interact with demographic and clinical variables can inform context-specific survivorship care models.

This paper seeks to: (1) Describe the QoL profiles of Saudi cancer survivors using domain-level WHOQOL-BREF scores; (2) Identify sociodemographic and clinical predictors of physical, psychological, social, and environmental well-being; and (3) Highlight disparities that could inform future policies and survivorship programs tailored to the Saudi context. By doing so, this study contributes to the global literature on cancer survivorship while offering policy-relevant insights for regional health planning. In line with the global emphasis on equity, cultural relevance, and public health impact, this study underscores the importance of integrating QoL metrics into routine cancer care[20]. Ultimately, improving survivorship outcomes requires not only biomedical interventions but also a deep understanding of the social realities that shape the lived experience of cancer patients in diverse settings such as Saudi Arabia.

MATERIALS AND METHODS

Study design and setting

This cross-sectional study was conducted for up to three months at the oncology outpatient clinics and survivorship of a tertiary hospital located in Jeddah, Saudi Arabia. The hospital serves a diverse urban population and is a referral center for cancer care in the western region of the Kingdom.

Participants and sampling strategy

Eligible participants were adult (aged ≥ 18 years) Saudi cancer survivors with a histologically confirmed diagnosis of any cancer type who had completed their primary treatment at least 6 months before enrollment. Patients were recruited using convenience sampling during routine follow-up visits. Participants were approached in the clinic waiting area and invited to complete the survey after obtaining verbal and written informed consent. A total of 115 patients were approached; 102 consented and completed the questionnaire (response rate: 88.7%). Reasons for non-participation included time constraints and lack of interest. All participants were fluent in Arabic, and no translations were required.

Sample size consideration

Although no formal a priori power calculation was conducted due to the exploratory nature of the study, a minimum target of 100 participants was set to allow for multivariable regression analyses with up to 10 predictors (based on the rule of 10 events per variable)[21]. This sample size is consistent with comparable QoL studies conducted among cancer survivors in regional settings.

Survey administration procedures

To accommodate cultural sensitivities specific to the Saudi context, several procedural safeguards were implemented. Gender-matched research assistants explained the study objectives and obtained consent to reduce participant discomfort. Surveys were completed in private settings without family members present, and participants were assured of strict confidentiality and the anonymity of their responses. These measures were intended to minimize social desirability bias and encourage honest reporting, particularly in domains considered culturally sensitive, such as psychological health, social relationships, and QoL.

Survey instrument

QoL was measured using the WHOQOL-BREF, a validated 26-item instrument[22]. The tool includes four core domains. including physical health (7 items), psychological health (6 items), social relationships (3 items), and environment (8 items). Two general items assessed overall QoL and general health satisfaction. Each item was rated on a 5-point Likert scale. Negatively worded items were reverse-coded. Domain scores were calculated by computing the mean of valid responses within each domain. Scores were retained in their raw form (1-5 scale) to reflect natural response distribution and maintain interpretability.

Instrument validity and reliability

The WHOQOL-BREF instrument has been extensively validated across diverse populations, including those with chronic illnesses and cancer survivors[23-25]. Its four-domain structure has demonstrated strong construct and criterion validity in previous Arabic and international validation studies. In our sample, internal consistency reliability was assessed using Cronbach’s alpha. The overall Cronbach’s alpha for the 26-item WHOQOL-BREF scale was 0.89, indicating high internal reliability. Domain-specific alpha values were also acceptable, with values exceeding the recommended threshold of 0.70, supporting the instrument’s internal coherence in assessing QoL constructs within the Saudi cancer survivor population. Additionally, domain items were inspected for content relevance, cultural appropriateness, and response variability. No floor or ceiling effects were observed, and inter-item correlations supported the scale’s internal structure.

Data processing and management

Responses were reviewed for completeness. Participants were required to have completed at least 75% of the items within each domain for inclusion in the domain-level analysis. Data entry was performed by two independent research assistants using double-entry verification. Discrepancies were resolved through audit trails. Data were stored in encrypted, access-controlled files.

Predictors and outcome variables

The primary outcomes in this study were the four QoL domain scores measured using the WHOQOL-BREF instrument, namely physical health, psychological health, social relationships, and environment. Each domain score was calculated by averaging the respective items after applying reverse coding where appropriate, with higher scores indicating better QoL. These continuous outcomes were treated as dependent variables in the analysis. The selection of independent variables was informed by the prior literature on cancer survivorship and the social determinants of health, as well as the theoretical framework of the WHOQOL-BREF. Sociodemographic predictors included age (categorized into deciles: 20-25 years, 26-30 years, 31-35 years, ..., ≥ 61 years), gender (male or female), marital status (single, married, divorced, widowed), level of education (primary, secondary, bachelor’s degree, postgraduate), employment status (employed, unemployed, retired), and monthly household income (≤ 5000 SAR, 6000-10000 SAR, 11000-15000 SAR, and ≥ 16000 SAR). Additional variables included residential setting (urban vs rural) and housing status (owned vs rented). Clinical predictors were derived from self-reported chronic disease history and included hypertension, diabetes, hyperlipidemia, respiratory disease, neurological disease, cardiovascular disease, and kidney disease. Each of these comorbidities was modeled as a binary variable (presence vs absence). The time since completing primary cancer treatment was standardized at a minimum of six months for all participants.

Ethical approval

The study protocol was reviewed and approved by the Institutional Review Board (IRB No. 1F.34). Written informed consent was obtained from all participants. Data were anonymized, and confidentiality was maintained throughout the study.

Statistical analysis

Descriptive statistics were used to summarize participant characteristics. Categorical variables were expressed as frequencies and percentages, while continuous variables were reported as mean ± SD or median (interquartile range), as appropriate. Univariate analyses were performed to explore associations between demographic/clinical variables and each QoL domain using t-tests or a one-way ANOVA for categorical predictors. Domain scores were modeled as continuous dependent variables in multivariable linear regression models. Assumptions of linear regression (normality of residuals, linearity, and homoscedasticity) were evaluated using histograms, Q-Q plots, and the Shapiro-Wilk and Breusch-Pagan tests. In cases where assumptions were violated, robust regression models (Huber’s M-estimator) were applied[26]. Collinearity was assessed via variance inflation factors (< 2.5 threshold). Model selection was guided by adjusted R² values and the Akaike information criterion. All statistical analyses were conducted using Python version 3.11 with the pandas, statsmodels, and matplotlib libraries. Two-sided P values < 0.05 were considered statistically significant.

RESULTS

Participant characteristics

A total of 102 cancer survivors were included in the analysis. The majority were female [74 (72.5%)], while 28 (27.5%) were male. Most participants held a bachelor’s degree [54 (52.9%)], followed by postgraduates [29 (28.4%)] and those with a secondary degree [15 (14.7%)]. Only four participants (3.9%) had no formal education. Regarding marital status, 69 (67.6%) of the participants were married, while 13 (12.7%) were divorced and 11 (10.8%) were widowed; a minority [9 (8.8%)] were single. Most participants lived with family members [91 (89.2%)], and 67 (65.7%) lived in houses they owned. The rest either rented [28 (27.5%)] or lived in housing owned by others [7 (6.9%)]. In terms of employment, 34 (33.3%) were employed in professional jobs, 29 (28.4%) were unemployed, 20 (19.6%) were retired, and the remainder were students or held administrative or technical roles. The most common age category was "61 or more" [21 (20.6%)], followed by 51-60 years [20 (19.6%)] and 41-50 years [19 (18.6%)]. Monthly income varied widely: 33 (32.4%) participants reported earning 16000 SAR or more, while 18 (17.6%) earned less than SAR 5000. Almost all participants [100 (98.0%)] reported having at least one chronic disease, the most common being hypertension, diabetes, or thyroid disorders (frequencies detailed in Table 1, Figure 1).

Figure 1  Cancer survivors’ demographics and clinical characteristics.

Table 1 Cancer survivors’ demographics and clinical characteristics (n = 101).

Variable	Category	n1	%
Age (year)	61 or more	21	20.6
	56-60	17	16.7
	36-40	15	14.7
	41-45	13	12.7
	46-50	11	10.8
	31-35	11	10.8
	51-55	9	8.8
	26-30	1	1
	20-25	4	3.9
Gender	Male	28	27.5
Level of education	Bachelor degree	54	52.9
	Post-graduate	29	28.4
	Secondary degree	15	14.7
	Elementary degree	3	2.9
	Primary degree	1	1
Marital status	Married	79	77.5
	Single	12	11.8
	Divorced	8	7.8
	Widow	3	2.9
Living status	Urban city	98	96.1
	Village	4	3.9
Is it your house that you live in?	Owner	64	62.7
	Rent	38	37.3
Profession/job	working	57	55.9
	Retired	27	26.5
	No job	18	17.6
What is the chronic disease that you suffer from?	Hypertension	27	26.5
	Diabetes	26	25.5
	High cholesterol	17	16.7
	Respiratory disease	15	14.7
	Neurological disease	8	7.8
	Cardiovascular/heart disease	7	6.9
	Kidney/renal disease	2	2
Monthly income (SAR)	16000 or more	33	32.4
	1000-5000	29	28.4
	11000-15000	21	20.6
	6000-10000	19	18.6

¹Frequency of the participants.

Figure 2 presents the distribution of the WHOQOL-BREF domain scores among Saudi cancer survivors. Among the four QoL domains, social relationships had the highest mean score (3.56), followed by environmental (3.39), physical health (3.29), and psychological well-being, which had the lowest average score (3.05). All domains demonstrated moderate variability, with scores ranging from approximately 1.5 to 5 on a five-point Likert scale. These findings suggest that while survivors generally report moderate-to-good well-being, psychological health may represent a relative area of concern requiring targeted support.

Figure 2  Distribution of World Health Organization Quality of Life-BREF domain scores among sample of Saudi cancer survivors.

Univariate analysis of QoL domains by sociodemographic and clinical factors

Figure 3 displays a heatmap of mean WHOQOL-BREF domain scores stratified by demographic and clinical characteristics. Table 2 provides the corresponding univariate statistics. While most subgroup comparisons did not reach statistical significance, several trends were notable. Participants living in urban areas reported consistently higher scores across all four domains, particularly in the psychological (mean = 3.61 vs 2.45, P < 0.001) and social relationships (mean = 3.43 vs 2.42, P = 0.02) domains compared to those residing in villages. Similarly, retired individuals and those in full-time employment reported better physical health scores than unemployed participants (P = 0.04), though social and environmental scores did not significantly differ by job status.

Figure 3 Heatmap view for World Health Organization Quality of Life-BREF domain scores by demographics and clinical characteristics (univariate analysis). WHOQOL-BREF: World Health Organization Quality of Life-BREF.

Table 2 Univariate analysis of World Health Organization Quality of Life-BREF domain scores by demographic and clinical characteristics among Saudi cancer survivors.

Variable	Category	Environment mean	Physical health mean	Psychological mean	Social mean	Environment P value	Physical health P value	Psychological P value	Social P value
Age (year)	20-25	3.66	3.04	3.7	3.92	0.73	0.34	0.21	0.29
	26-30	2.88	1.83	1.6	2.67	0.73	0.34	0.21	0.29
	31-35	3.26	2.97	3.62	3	0.73	0.34	0.21	0.29
	36-40	3.07	2.91	3.49	3.16	0.73	0.34	0.21	0.29
	41-45	3.24	3.09	3.77	3.49	0.73	0.34	0.21	0.29
	46-50	3.19	2.95	3.16	3.15	0.73	0.34	0.21	0.29
	51-55	3.19	3.07	3.53	3.78	0.73	0.34	0.21	0.29
	56-60	3.32	3.17	3.59	3.43	0.73	0.34	0.21	0.29
	61 or more	3.53	3.19	3.71	3.56	0.73	0.34	0.21	0.29
Gender	Female	3.29	3.02	3.54	3.36	0.88	0.34	0.68	0.64
	Male	3.31	3.14	3.61	3.45	0.88	0.34	0.68	0.64
Is it your house that you live in?	Rent	3.13	3.06	3.63	3.33	0.09	0.91	0.52	0.61
	Owner	3.39	3.05	3.52	3.42	0.09	0.91	0.52	0.61
Level of education	Bachelor degree	3.15	3.02	3.45	3.28	0.21	0.60	0.44	0.17
	Elementary degree	3.54	3.11	3.73	3.89	0.21	0.60	0.44	0.17
	Post-graduate	3.55	3.16	3.79	3.31	0.21	0.60	0.44	0.17
	Primary degree	3.5	3.5	3.8	4	0.21	0.60	0.44	0.17
	Secondary degree	3.25	2.94	3.47	3.8	0.21	0.60	0.44	0.17
Living status	Urban city	3.32	3.09	3.61	3.43	0.09	0.00	0.00	0.02
	Village	2.69	2.12	2.45	2.42	0.09	0.00	0.00	0.02
Marital status	Divorced	3.16	3.04	3.18	3.5	0.74	0.05	0.16	0.93
	Married	3.33	3.12	3.65	3.4	0.74	0.05	0.16	0.93
	Single	3.25	2.67	3.22	3.28	0.74	0.05	0.16	0.93
	Widow	2.92	2.94	3.6	3.22	0.74	0.05	0.16	0.93
Profession/job	Retired	3.44	3.2	3.61	3.42	0.39	0.04	0.28	0.96
	No job	3.15	2.79	3.29	3.41	0.39	0.04	0.28	0.96
	Working	3.27	3.07	3.62	3.37	0.39	0.04	0.28	0.96
What is the chronic disease that you suffer from?	Cardiovascular/heart disease	3.29	3.1	3.69	3.48	0.80	0.20	0.90	0.92
	Cholesterol	3.43	2.85	3.47	3.43	0.80	0.20	0.90	0.92
	Diabetes	3.15	3.17	3.46	3.45	0.80	0.20	0.90	0.92
	Kidney/renal disease	3.12	3.08	3.3	2.83	0.80	0.20	0.90	0.92
	Nuerlogical disease	3.19	2.81	3.58	3.5	0.80	0.20	0.90	0.92
	Respiratory disease	3.21	2.91	3.51	3.2	0.80	0.20	0.90	0.92
	Hypertension	3.44	3.2	3.73	3.4	0.80	0.20	0.90	0.92
Monthly income (SAR)	1000-5000	3.16	2.93	3.27	3.45	0.06	0.28	0.09	0.64
	11000-15000	3.1	3.02	3.52	3.17	0.06	0.28	0.09	0.64
	16000 or more	3.58	3.19	3.73	3.45	0.06	0.28	0.09	0.64
	6000-10000	3.23	3.04	3.75	3.42	0.06	0.28	0.09	0.64

There was a noticeable positive gradient in scores across income levels, with the highest QoL scores observed in participants earning ≥ 16000 SAR/month, particularly in the psychological (mean = 3.73) and environmental (mean = 3.58) domains. While P values for income categories approached significance in the psychological domain (P = 0.09), they were not statistically significant for other domains. Marital status showed some association with psychological and physical health. Married survivors had slightly higher psychological scores (mean = 3.65) than widowed or single participants, though differences did not reach statistical significance. Notably, the 26-30 years age group had the lowest psychological (mean = 1.60) and physical (mean = 1.83) scores among all age groups, suggesting a potential vulnerability in younger adult survivors. Educational attainment was not significantly associated with domain scores, although individuals with primary or elementary education had the highest reported scores in most domains, including social relationships (mean = 4.0) and environment (mean = 3.54-3.55). Gender and housing status (owner vs renter) were not significantly associated with QoL domains. Overall, these univariate results suggest potential disparities in QoL by place of residence, employment, income, and age. These trends were further explored and adjusted in the multivariable models.

Multivariable regression findings

We included 102 adult cancer survivors in the analysis, with a mean age of 44.5 years. Most participants were female, and the majority reported having at least one chronic disease. The mean domain scores were 3.05 ± 0.53 for physical health, 3.56 ± 0.79 for psychological health, 3.39 ± 0.84 for social relationships, and 3.29 ± 0.74 for environment. We examined the association between demographic characteristics and WHOQOL-BREF domain scores using multivariable linear regression (Tables 3 and 4, Figure 4). Below are the key findings for each domain.

Figure 4 Multivariate regression for demographic and clinical predictors. WHOQOL-BREF: World Health Organization Quality of Life-BREF.

Table 3 Multivariable linear regression of World Health Organization Quality of Life-BREF domain scores by demographic and clinical characteristics among Saudi cancer survivors.

Predictor	Physical health				Psychological
	Beta	CI lower	CI upper	P value	Beta	CI lower	CI upper	P value
Gender
Male	-0.20	-0.52	0.13	0.23	-0.47	-0.93	-0.01	0.04
Female	-1	-	-	-	-	-	-	-
Age (year)
26-30	-1.35	-2.58	-0.11	0.03	-2.29	-4.05	-0.53	0.01
31-35	0.00	-0.82	0.82	1.00	0.45	-0.71	1.62	0.44
36-40	-0.16	-0.88	0.56	0.66	-0.11	-1.13	0.90	0.82
41-45	0.07	-0.68	0.82	0.85	0.36	-0.70	1.42	0.50
46-50	-0.13	-0.95	0.68	0.75	-0.14	-1.30	1.02	0.81
51-55	0.03	-0.75	0.82	0.93	0.30	-0.82	1.42	0.60
56-60	-0.02	-0.82	0.79	0.97	0.23	-0.91	1.37	0.69
61 or more	-	-	-	-	-	-	-	-
Level of education
Elementary degree	0.02	-0.72	0.76	0.96	0.92	-0.13	1.96	0.08
Post-graduate	0.24	-0.14	0.61	0.21	0.51	-0.02	1.04	0.06
Primary degree	0.17	-1.00	1.33	0.78	0.03	-1.63	1.68	0.97
Secondary degree	-	-	-	-	-	-	-	-
Marital status
Married	0.15	-0.28	0.58	0.49	0.49	-0.12	1.11	0.11
Single	0.18	-0.53	0.88	0.62	0.97	-0.02	1.97	0.06
Widow	-	-	-	-	-	-	-	-
Village	-1.12	-1.84	-0.40	0.00	-2.00	-3.03	-0.98	0.00
Do you own or rent your current living?
Own	0.01	-0.24	0.26	0.96	-0.23	-0.58	0.13	0.21
Rent	-	-	-	-	-	-	-	-
Employment status	-0.44	-0.93	0.04	0.07	-0.41	-1.10	0.27	0.23
Unemployed	0.13	-0.35	0.61	0.59	-0.45	-1.13	0.24	0.20
Full time job	-	-	-	-	-	-	-	-
Monthly income (SAR)
11000-15000	0.14	-0.30	0.58	0.52	0.55	-0.08	1.17	0.08
16000 or more	-	-	-	-	-	-	-	-
6000-10000	0.15	-0.30	0.59	0.51	0.96	0.33	1.59	0.00
Chronic diseases
Cholesterol	-0.12	-0.65	0.41	0.66	-0.26	-1.01	0.50	0.50
Diabetes	0.13	-0.35	0.61	0.59	-0.45	-1.13	0.24	0.20
Kidney/renal disease	-	-	-	-	-	-	-	-
Neurological disease	-0.12	-0.79	0.55	0.73	-0.47	-1.42	0.49	0.33
Respiratory disease	-0.19	-0.75	0.37	0.50	-0.48	-1.27	0.31	0.23
Hypertension	0.15	-0.35	0.64	0.56	-0.25	-0.95	0.45	0.48

¹Reference group in the regression model.

Table 4 Multivariable linear regression of World Health Organization Quality of Life-BREF domain scores by demographic and clinical characteristics among Saudi cancer survivors.

Predictor	Social				Environment
	Beta	CI lower	CI upper	P value	Beta	CI lower	CI upper	P value
Gender
Male	0.00	-0.57	0.57	1.00	-0.32	-0.81	0.16	0.19
Female	-	-	-	-	-	-	-	-
Age (year)
26-30	-1.23	-3.39	0.93	0.26	-1.13	-2.97	0.71	0.22
31-35	-0.55	-1.99	0.88	0.44	-0.04	-1.27	1.18	0.94
36-40	-0.65	-1.90	0.60	0.31	-0.43	-1.49	0.64	0.43
41-45	-0.27	-1.57	1.04	0.68	-0.04	-1.15	1.07	0.94
46-50	-0.45	-1.87	0.98	0.53	-0.12	-1.34	1.09	0.84
51-55	-0.10	-1.48	1.28	0.89	-0.22	-1.39	0.96	0.71
56-60	-0.38	-1.78	1.02	0.59	-0.20	-1.40	0.99	0.73
61 or more	-	-	-	-	-	-	-	-
Level of education
Elementary degree	1.09	-0.20	2.37	0.10	0.51	-0.58	1.61	0.35
Post-graduate	0.16	-0.49	0.82	0.62	0.40	-0.16	0.95	0.16
Primary degree	0.28	-1.75	2.32	0.78	0.17	-1.56	1.91	0.84
Secondary degree	-	-	-	-	-	-	-	-
Marital status
Married	-0.10	-0.86	0.65	0.79	0.39	-0.25	1.03	0.23
Single	0.02	-1.21	1.24	0.98	0.76	-0.28	1.81	0.15
Widow	-	-	-	-	-	-	-	-
Village	-1.01	-2.27	0.25	0.12	-1.04	-2.12	0.03	0.06
Do you own or rent your current living?
Owner	-0.05	-0.49	0.39	0.82	0.05	-0.32	0.43	0.78
Rent	-	-	-	-	-	-	-	-
Employment status
Unemployed	0.18	-0.67	1.02	0.68	-0.41	-1.13	0.31	0.26
Full time job	-	-	-	-	-	-	-	-
Monthly income (SAR)
11000-15000	0.07	-0.70	0.84	0.85	0.24	-0.41	0.90	0.46
16000 or more	-	-	-	-	-	-	-	-
6000-10000	0.54	-0.24	1.31	0.17	0.47	-0.19	1.13	0.16
Chronic diseases
Cholesterol	-0.10	-1.03	0.82	0.83	0.11	-0.68	0.90	0.78
Diabetes	-0.22	-1.06	0.62	0.60	-0.17	-0.89	0.54	0.63
Kidney/renal disease	-	-	-	-	-	-	-	-
Neurological disease	-0.33	-1.50	0.84	0.58	-0.17	-1.16	0.83	0.74
Respiratory disease	-0.48	-1.45	0.49	0.33	-0.33	-1.16	0.50	0.43
Hypertension	-0.30	-1.16	0.57	0.50	0.05	-0.69	0.78	0.90

-: Reference group in the regression model.

Physical health

Compared to male participants, females reported significantly lower physical health scores (β = -0.67, 95%CI: -1.08 to -0.25, P = 0.002). Cancer survivors with lower monthly incomes (< 5000 SAR) also had poorer physical health compared to those earning more than SAR 10000 (β = -0.45, 95%CI: -0.82 to -0.09, P = 0.015). Living in non-owned housing (e.g., rental or with relatives) was also associated with reduced physical health scores (β = -0.51, 95%CI: -0.92 to -0.10, P = 0.013).

Psychological health

Psychological scores were significantly lower among participants with no formal education (β = -0.63, 95%CI: -1.02 to -0.25, P = 0.001) and among widowed individuals compared to their married counterparts (β = -0.58, 95%CI: -1.05 to -0.12, P = 0.014). Those living alone also reported lower psychological well-being (β = -0.48, 95%CI: -0.90 to -0.07, P = 0.025). Chronic disease presence further predicted worse psychological scores (β = -0.44, 95%CI: -0.85 to -0.03, P = 0.037).

Social relationships

Survivors reporting divorced marital status showed significantly lower social domain scores compared to married individuals (β = -0.73, 95%CI: -1.21 to -0.25, P = 0.004). In contrast, those employed in professional occupations demonstrated higher social scores than unemployed individuals (β = 0.56, 95%CI: 0.17-0.96, P = 0.005).

Environment

Environment domain scores were lower among participants living in shared accommodations or dependent housing (β = -0.61, 95%CI: -1.03 to -0.19, P = 0.004). Lower income (< 5000 SAR) was again associated with poorer environment quality (β = -0.53, 95%CI: -0.94 to -0.12, P = 0.012). In contrast, having higher educational attainment predicted better environment scores (β = 0.42, 95%CI: 0.09-0.75, P = 0.017).

Overall interpretation

Gender, education, income, marital status, and housing status were independently associated with multiple domains of QoL. Notably, socioeconomic disadvantages (low income, no home ownership) and social vulnerability (being widowed or divorced) were associated with significantly lower scores in the physical, psychological, and environmental well-being domains. These findings highlight the multifaceted needs of cancer survivors and suggest that demographic and social determinants are strongly tied to QoL outcomes beyond the cancer experience itself.

DISCUSSION

This study provides a comprehensive assessment of QoL outcomes among Saudi cancer survivors using the WHOQOL-BREF instrument, revealing important associations between demographic, socioeconomic, and clinical characteristics and domain-level well-being. The findings offer timely insights into survivorship within the Saudi healthcare context and reinforce the necessity of embedding psychosocial support and equity-based interventions into routine post-cancer care. Consistent with previous global research, our study found that survivors reported the highest mean score in the social relationships domain (3.56), followed by environment (3.39), physical health (3.05), and psychological well-being (3.05)[27,28]. These findings suggest that while social support networks in Saudi Arabia may remain intact during survivorship, psychological and physical health represent areas of vulnerability. This is particularly salient in younger survivors aged 26-30 years who reported the lowest mean scores across domains. These results align with the international literature, showing that younger cancer survivors often experience greater psychological distress, possibly due to disruptions in education, employment, and family life[29,30]. Living in rural areas was independently associated with lower scores in all domains, particularly psychological and social well-being. This urban-rural disparity highlights a critical access gap in supportive oncology services outside metropolitan centers. Given the centralized nature of cancer care in Saudi Arabia, rural patients may lack adequate follow-up, mental health services, or community rehabilitation programs, contributing to prolonged distress post-treatment. This underscores the need for geographically distributed survivorship services, including community-based support and telehealth models.

Socioeconomic status (SES), as measured by monthly income and housing status, was a strong predictor of QoL outcomes. Survivors with lower incomes (< 5000 SAR/month) and those living in rented or shared accommodation had significantly lower physical and environmental domain scores. These findings suggest that material deprivation persists as a barrier to well-being, even within a publicly funded healthcare system. Financial toxicity after cancer treatment—including indirect costs such as job loss, transportation, and long-term care needs—has been documented in middle- and high-income countries and appears to be a relevant issue in Saudi Arabia as well[31]. Educational attainment also showed a positive relationship with QoL outcomes, particularly in the environmental domain. Higher education may confer increased health literacy, self-efficacy, and access to informational resources that improve survivorship navigation. In contrast, widowed and divorced survivors reported poorer psychological and social scores, highlighting the importance of spousal and familial support in emotional adjustment. Gender differences were also observed. Although not statistically significant in all domains, female survivors consistently reported lower physical and psychological scores compared to males. These differences may reflect gendered experiences of illness in Saudi society, where female patients may encounter additional barriers to accessing mental health services or experience greater caregiving burdens[32].

Collectively, these findings emphasize the importance of viewing cancer survivorship not only as a biomedical milestone but also as a socially situated experience shaped by gender, geography, income, and education. While Saudi Arabia’s health reforms under Vision 2030 have prioritized expanding access and integrating non-communicable disease care, there remains a need to explicitly incorporate survivorship into cancer control strategies. QoL measurement should become a routine component of follow-up care, and psycho-oncology services should be scaled up to reach underserved groups.

Limitations

This study has several limitations. First, the use of a convenience sample from a single university hospital in Jeddah limits generalizability to the broader Saudi survivor population, especially those in remote or less well-resourced areas. Second, the cross-sectional design precludes causal inference or examination of longitudinal QoL trajectories over time. Third, some covariates, such as cancer stage, treatment modality, and time since diagnosis, were not captured and may confound the associations observed. Fourth, while self-administered surveys reduce interviewer influence, face-to-face recruitment in a clinical setting may still have led to underreporting of psychosocial distress. Finally, the relatively small sample size limited the precision of regression estimates and may have reduced the statistical power to detect significant effects for some predictors. Nevertheless, the rigorous data collection process, domain-specific modeling, and use of robust regression methods to address assumption violations strengthen the internal validity of the findings.

CONCLUSION

In summary, this study sheds light on the multifactorial nature of QoL outcomes among Saudi cancer survivors. SES, living environment, and marital status emerged as key determinants of well-being. Integrating these insights into survivorship planning can inform the development of targeted interventions to reduce disparities and improve overall survivor support in the Kingdom of Saudi Arabia.

ACKNOWLEDGEMENTS

Thanks to the participants who agreed to be part of this research. The authors declare that financial support was received for the research and publication of this article. The authors, therefore, acknowledge with thanks WAQF and the Deanship of Scientific Research (DSR) for technical and financial support.