Quality of life among and associated factors women with disabilities: Across sectional study

Abstract

Background

Globally, disability is a pressing issue that affects people of all ages and backgrounds, especially women with disabilities. Quality of life (QoL) of women with disabilities is a multidimensional concept encompassing physical, emotional, social, and economic aspects. Understanding the challenges and determinants influencing their well-being is crucial for developing effective interventions and policies.

Objectives

This study aimed to determine the prevalence of poor QoL and factors associated with it among women with disabilities in the Eastern Province of Saudi Arabia.

Design

A cross-sectional study was conducted among a representative population of “women with disabilities” in the eastern region of Saudi Arabia.

Methods

A convenience sample of 301 participants was selected for this study. Data were collected using a self-administered questionnaire that included sociodemographic and medical characteristics, as well as the World Health Organization Quality of Life -BREF (WHOQOL-BREF) scale.

Results

88% of participants had poor quality-of-life scores. Factors significantly associated with QoL included education level, Hospital type (p< 0.05).

Conclusion

The high prevalence of poor QoL among women with disabilities highlights a critical public health concern. Addressing these challenges requires targeted interventions to improve their overall well-being.

Keywords

disability quality of life women’s health

Introduction

Disability is a basic aspect of human experience, affecting about an estimated 1.3 billion people (16% of the global population). 80% of them reside in low- and middle-income countries.¹ With longer life expectancies and high rates of noncommunicable diseases, this number is rapidly rising. Individuals with disabilities have a higher risk of mortality, poor health, and less ability to perform daily tasks relative to the general population.² Disability can be defined as a condition in which an individual is unable to fulfill their natural role in life due to injury or impairment. It also describes a state of inability to perform one or several physical and/or cognitive tasks compared to peers of the same age, sex, or social role. A person with disability is defined as “anyone with a long-term disability in mobility, hearing, vision, or cognitive functions due to genetic, congenital, or environmental factors, resulting in an inability to perform daily activities independently”.³ This definition can be strengthened to conform with the WHO’s International Classification of Functioning, Disability, and Health (ICF), which describes disability in terms not only of a particular health problem but also as a result of interaction with environmental and community obstacles that limit participation in daily life.⁴ Saudi Arabia has previously evaluated the prevalence of persons with disabilities and provided basic demographic data. An in-depth analysis of this is available in the 2017 Disability Survey conducted by the General Authority for Statistics. They show that (in terms of the whole population) a full 7.1% among 32.5 million individuals are disabled, with 3.4% of them being female. The Eastern Province has a physical disability rate of approximately 6%.⁵ Disability is a pressing issue affecting people of all ages and backgrounds. The World Health Organization estimates approximately 190 million people worldwide are severely disabled. Individuals with disabilities are twice as likely to have diseases like depression, asthma, diabetes, stroke, obesity, or poor oral health. People with disabilities experience numerous health inequities.² Most people with disabilities are faced with big social, economic, and infrastructural barriers to QoL.⁶ The QoL information is necessary for health policies and clinical applications.⁷ To establish a strong conceptual foundation, we base this study upon the WHO’s biopsychosocial model of QoL, which emphasizes the involvement of biological, psychological, and social factors in determining well-being.^8,9

Inequalities at the systemic surface that women with disabilities suffer from entail higher rates of unemployment, lower socioeconomic income, limited access to healthcare services, differential access to education, and exclusion from women-centric services and programs. They are also more exposed to abuse and violence.^10,11 Policies that foster dependency and resistance to social change compound these challenges. Moreover, women with disabilities are doubly worse off than men with disabilities, owing to persistent prejudices, stereotypes, and traditional societal perceptions that hinder their complete inclusion.¹¹ QoL refers to subjective well-being and reflects individuals’ feelings about the most important and meaningful aspects of their lives. It is increasingly understood as a subjective construct rather than an objective metric. It consists of well-being, functioning, life satisfaction, health, and disability, and it refers to the aspects of what make life fulfilling and meaningful”.¹² Disability has been acknowledged, for decades, to be a major health, social, and financial challenge, not just of patients, but also their families and healthcare employees. Functional barriers, especially among the elderly, compound vulnerability and dependence. However, older adults with disabilities also experience an increased risk of social marginalization, limited access to services, and domestic violence, making them especially vulnerable. In the context of Saudi Arabia, the experiences of women with disabilities in society are a product of culturally-defined and gendered norms that create different challenges than those experienced by men with disabilities.¹³ These norms amplify barriers to education, employment, and healthcare, deepening stigma and social exclusion.^13,14 However, limited research has focused on developing countries to examine the QoL of people with disabilities. Numerous socio-cultural, environmental, and personal factors play an important role in the QoL of women with disabilities.^15,16 Studies show that these determinants differ considerably in different contexts, especially in developing contexts.^15–17 Knowledge of these influences needs to inform the development of targeted policies and interventions for increased QoL in disabled women.^13–16 It is found that acquiring a disability reduces QoL.^15,18 Therefore, this study aims to investigate the factors associated with HR-QoL among women with disabilities.

Hypothesis

H1: Socio-demographics are significantly associated with the QoL among women with disabilities.

H2: Medical characteristics are significantly associated with QoL among women with disabilities.

H3: Disability-related characteristics are significantly associated with QoL among women with disabilities.

Methods

Design, setting, population, and sample

A cross-sectional study was conducted on women with disabilities in the Eastern region of Saudi Arabia. The study involved recruitment through multiple community and institutional channels. Participants were identified from organizations dedicated to women with disabilities, such as the Saudi Association of People with Disabilities, hospitals, social media platforms, and lists of email contacts available from disability organizations; therefore, clinically verified disabilities confirmed by specialized institutions were available for the participants. We followed the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) checklist in executing our study.

A convenience sampling method was used to select 301 women with disabilities to achieve the aim of the current study. The sample size was determined using G*Power 3.1for an ANOVA test with a medium effect size (f=0.25), a significant level (α) of 0.05, and a power of 0.80. Based on these parameters, the estimated minimum sample size was 275. To account for attrition, the final sample size included 301 participants.

The inclusion criteria for this study were as follows: female participants above the age of 18 and women with any form of mobility or physical impairment (Physical, Cognitive, Sensory, and Multiple disabilities). Women who were unable to communicate verbally were excluded from the study. This criterion was necessary because the instrument is a self-report QoL measure that required direct comprehension and response; proxy responses were not permitted in order to minimize systematic measurement bias. In addition, 14 women were excluded because they didn’t complete the questionnaire. Although they began filling in the demographic section, they left the questionnaire incomplete because they needed to leave urgently.

Instruments of the study

To achieve the main aim of this study, a Self-administered questionnaire was used. The first part included participants’ socio-demographic and medical characteristics, type of disabilities: Physical, Cognitive, Sensory, and Multiple, and type of hospitals attended. The hospital variable was categorized as rehabilitation care or other hospitals. Rehabilitation care facilities were defined as centers primarily offering rehabilitation and disability-related services, whereas “other hospitals” referred to general hospitals. In contrast, the second part utilized the Arabic version of the World Health Organization Quality of Life -BREF (WHOQOL-BREF),¹⁰ and demonstrated excellent psychometric reliability across 23 countries.¹⁹ The WHOQOL-BREF is an internationally recognized tool that has been widely applied in various contexts, including among people with disabilities. It is a shortened version of the WHOQOL-100, comprising 26 questions across five domains: (1) General health-two items, (2) physical health-seven questions (Q 3, 4, 10, 15, 16, 17, 18). Raw scores between 7 and 35; (3) psychological-six questions (Q 5, 6, 7, 11, 19, 26). Raw score between 6 and 30; (4) social relations-three questions (Q 20, 21, 22). Raw score between 3 and 15; and (5) environmental-eight questions (Q 8, 9, 12, 13, 14, 23, 24, 25). Raw score between 8 and 40. The questionnaire uses a five-point rating scale, ranging from 1 to 5 points, where higher scores indicate better quality of life. In each domain, average values were calculated according to the key and guidelines. The total score ranges from 26 to 130, with higher scores indicating a higher quality of life. Scores range from 0 to 100, with higher scores indicating a better quality of life. In addition to raw scores, a transformed score between 0 and 100 was calculated according to the methodology published in the WHOQOL-BREF. QoL was categorized as poor (less than 60%) or good (more than 60%) based on a previous study conducted by Băjenaru et al.²⁰ This categorization was applied to enhance the interpretation of QoL Levels among participants.²¹ The WHOQOL-BREF questionnaire demonstrates satisfactory reliability and validity across various populations, making it a robust tool for assessing quality of life. Reliability testing was conducted using Cronbach’s alpha, yielding a high internal consistency of 0.91.

Data collection

Several disability-focused organizations and social media networks were used for recruitment, as relying on mainstream health services would have resulted in a limited number of eligible participants. Families of women with clinically recognized disabilities were asked to receive electronic announcements from the Saudi Association of People with Disabilities. Notifications were issued by hospitals, special education schools, and organizations that provide services related to disabilities in Saudi Arabia’s Eastern Province. To increase outreach, these announcements were also shared on official websites, social media accounts, and email contact lists of pertinent organizations. Snowball sampling was implemented when the intended sample size was not reached through the initial recruitment process. Participants who had already enrolled in the study were encouraged to share information about the study and its objectives with other eligible participants. Data were collected directly by the researchers.

The consent form, which described the study’s objectives, voluntary participation, and confidentiality protections, was reviewed by each participant. To protect participant privacy and confidentiality, responses were automatically saved in an Excel file. To ensure participant anonymity, no personally identifiable information (such as names or contact information) was gathered. Data collection was done between September 2023 and May 2024. ‘The reporting of this study conforms to the STROBE statement.²²

The pilot study was conducted on 10% of the overall convenience sample to evaluate the feasibility, objectivity, and relevance of the data collection instrument. The researcher made no changes based on the pilot study outcomes. The pilot study participants were included in the present study. The questionnaire took about 20 to 30 minutes to complete.

Ethical consideration

Ethical approval was granted from the ethics committee of King Fahad Hospital-Hofuf (IRB No: 78-EP-2023). The Declaration of Helsinki’s guidelines were followed in this study. Written informed consent was obtained from all participants, and they were aware of the study objectives. Participants were assured that their identities would be kept confidential and used solely for research purposes. They were also informed that participants might leave the research at any time without facing any penalties or adverse consequences.

Statistical analysis

The Statistical Package for Social Science (SPSS) version 20 was used to organize, classify, and analyze the collected data. For quantitative variables, the mean and standard deviations were reported using descriptive statistics. A multivariable general linear model test was used with the total Mean Score of the WHOQOL-BREF questionnaire and participants’ socio-demographic and medical characteristics as predictors. A statistically significant difference was considered when the p-value was less than or equal to 0.05.

Results

As shown in Table 1, most participants were aged 30 to 44 years old, had Preparatory education, were unemployed, and were married. The duration of marriage varied across the sample, with a considerable proportion in relatively recent marriages.

Table 1.

Sociodemographic characteristics of the participants.

		Descriptive statistics (n=301)
Age	19-29	55(18.3%)
	30-44	197(65.4%)
	45-59	39(13.0%)
	>=60	10(3.3%)
Education	Primary/Preparatory	185(61.5)
	Secondary	96(31.9%)
	University+	20(6.6`%)
Occupation	Employee	21(7.0%)
Occupation	Not-Employee	280(93.0%)
Marital status	Married	179(59.5%)
	Single	82(27.2%)
	Divorced/Widow	40(13.3%)
Duration of marriage	Not married	83(27.6%)
	1-5 months	80(26.6%)
	6-12 months	56(18.6%)
	1.5-2 years	35(11.6%)
	>2 years	20(15.6%)

Table 2 shows that more than half of the mothers had never been pregnant, and most had no history of abortion. Physical disability was the most commonly reported disability type, with mild and moderate disability representing the majority of cases. Most participants also reported at least one, and a positive family history of the same disability.

Table 2.

Obstetric, disability-related, and clinical characteristics.

Variable	Category	Descriptive statistics (n=301)
Number of pregnancies	None	172(57.1%)
	Once	90(29.9%)
	>=2	39(13.0%)
Number of abortions	None	217(72.1%)
	Once	53(17.6%)
	Twice	21(7.0%)
	Three times or more	10(3.3%)
Type of disability	Physical	133(44.2%)
	Sensory	81(26.9%)
	Mental	59(19.6%)
	Developmental	28(9.3%)
Degree of disability	Mild	140(46.5%)
	Moderate	132(43.9%)
	Severe	29(9.6%)
Comorbidities	Any Comorbidities	231(76.7%)
Comorbidities	None	70(23.3%)
Genetic disorders	+Ve family history of my disability	188(62.5%)
	- Ve family history of my disability	71(23.6%)
	+Ve family history with different disabilities	42(14.0%)
Hospital	Other	212(70.4%)
Hospital	Rehabilitation	89(29.6%)

Table 3 displays that QoL scores were generally low across all domains. The lowest mean scores were observed for social relationships and environmental health, while physical health had a comparatively higher mean score. According to the classification of QOL degree based on total score, 91.7% of the mothers had poor QOL, while only 8.3% had good QOL.

Table 3.

Descriptive statistics of WHOQOL-BREF domains and total QOL.

Physical health	Range	(18-96)
	Mean ± SD	47.9±10.3
	Median	50
	IQR	(43-54)
Psychological health	Range	(4-88)
	Mean ± SD	44.8±13.9
	Median	46
	IQR	(33-50)
Social relationships	Range	(0-100)
	Mean ± SD	41.6±19.8
	Median	42
	IQR	(25-50)
Environment	Range	(3-100)
	Mean ± SD	41.1±16.5
	Median	44
	IQR	(28-50)
QOL total score	Range	(16-89)
	Mean ± SD	43.8±12.5
	Median	46
	IQR	(35-50)
	Good	25(8.3%)
	Poor	276(91.7%)

Tables 4 and 5 present complementary findings from the same multivariable general linear model. Table 4 summarizes the overall model fit and identifies the predictors that were significantly associated with QoL, whereas Table 5 provides the parameter estimates and confidence intervals for the categories of the predictors included in the model.

Table 4.

Multivariable GLM for QOL.

Predictor	Df	F	P	Partial Eta²
Age	3	2.399	0.068	.026
Education	2	3.799	0.024	.027
Occupation	1	.004	0.953	.000
Social State	2	.116	0.890	.001
Period of marriage	4	1.487	0.206	.021
Number of Pregnancies	2	.168	0.846	.001
Number of abortions	3	.379	0.768	.004
Type of disability	3	1.144	0.332	.012
Degree of disability	2	.399	0.671	.003
Comorbidities	1	.371	0.543	.001
Genetic disorders	2	.852	0.427	.006
Hospital	1	52.122	<0.001	.160
F(26,274)=3.509, R² = .261 (Adjusted R²= .191)

Table 5.

Multivariable predictors for QOL.

Predictor		B	95%CI	P
Age	19-29	-8.615	-17.716, 0.487	.063
	30-44	-5.506	-14.345, 3.333	.221
	45-59	-9.118	-18.345, 0.109	.053
	>=60	Reference	Reference	.
Education	Primary/preparatory	-8.800	-15.106, -2.495	.006
	Secondary	-8.378	-14.838, -1.918	.011
	University+	Ref	Reference	.
Occupation	Employee	.174	-5.600, 5.949	.953
Occupation	Not-Employee	Reference	Reference	.
Social State	Single	-.862	-5.405, 3.682	.709
	Married	3.629	-21.009, 28.267	.772
	Divorced/Widow	Reference	Reference	.
Period of marriage	Not married	-10.289	-34.802, 14.224	.409
	1-5 months	-.780	-6.676, 5.116	.795
	6-12 months	-5.042	-10.978, 0.894	.096
	1.5-2 years	-2.870	-8.523, 2.783	.318
	>=5 years	Reference	Reference	.
Number of Pregnancies	None	1.111	-4.172, 6.395	.679
	Once	1.454	-3.492, 6.399	.563
	>=2	Reference	Reference	.
Number of Abortions	Non	1.571	-7.299, 10.440	.728
	Once	.454	-8.342, 9.251	.919
	Twice	-1.560	-11.181, 8.061	.750
	Three times or more	Reference	Reference	.
Type of disability	Physical	2.131	-2.988, 7.250	.413
	Sensory	-.282	-5.527, 4.964	.916
	Mental	-1.027	-6.385, 4.331	.706
	Developmental	Reference	Reference	.
Degree of disability	Mild	2.282	-2.908, 7.472	.387 .548 .
	Moderate	1.565	-3.555, 6.686
	Severe	Reference	Reference
Comorbidities	None	-.994	-4.206, 2.218	.543
Comorbidities	Other Comorbidities	Reference	Reference	.
Genetic disorders	+Ve family history of my disability	-2.125	-6.221, 1.972	.308
	- Ve family history of my disability	-3.109	-7.824, 1.605	.195
	+Ve family history with different disabilities	Reference	Reference	.
Hospital	Other Hospitals	11.002	8.002, 14.003	.000
Hospital	Rehabilitation Care	Reference	Reference	.

The total mean for QoL from the multivariable general linear model (GLM) is shown in Table 4. Overall, the model explained 26.1% of the variance in QoL (R²=.261; adjusted R²=.191) and was statistically significant (F (26,274) =3.509). Education and Hospital were significant independent predictors of QoL, with Hospital exhibiting the highest impact size. There was a marginal correlation with age. In the adjusted model, none of the other factors were statistically significant (p>.05).

As shown in Table 5, hospital type and education level were significantly associated with QoL. Participants attending other hospitals had a higher mean QoL scores than those receiving care at rehabilitation Care facilities. While those with primary/preparatory or secondary education had lower mean QoL scores than those with university education or above. Furthermore, Age showed boarder line association, whereas the remaining predictors were not statistically significant.

Discussion

Quality of life among women with disabilities is associated with a variety of factors that may interact in complex ways, shaping how women perceive and experience their QoL. Understanding these associations is crucial for developing targeted interventions and policies aimed at enhancing QoL in this population.²³ Recent research in healthy pregnancy had also linked QoL scores to pregnancy-related symptoms and gestational stage.²⁴ Our analysis extends this evidence by examining sociodemographic, reproductive, disability-related, and healthcare-setting factors associated with QoL in women with disabilities.

According to the current survey, the majority of participants were married and unemployed, with approximately two-thirds were aged 30-45. Moreover, more than half of the participants had primary/preparatory education. These patterns may reflect broader social, educational contexts, and policy related factors, although such factors were not examined in the current study. Ababneh and AlShaik³ reported that about two-thirds of respondents were under 40 years of age and that more than one-third had a bachelor’s degree. Similarly, Elahdi and Alnahdi²⁵ found that most of the participants were employed. Furthermore, in the present study, about half of the participants had been married for less than one year and had never been pregnant. Similarly, Gleason et al.²⁶ found that more than half of the study respondents were married, and more than one-third of them were nulliparous. In relation to the family history of disability, the current study found that more than half of the study participants had a family history of the same disability. These findings may be related to the role of family history in the occurrence of disability through genetic, environmental, and social pathways. This is consistent with Amaechi et al.²⁷ who reported a positive family history of one or more conditions, including mental illness, physical disability, and emotional/behavioral disorders.

According to the findings of the current study, nearly half of the participants had mild physical disabilities. This finding may reflect differences in the underlying causes and reporting of disability among women. Similar findings were reported by Ababneh and AlShaik,³ who found that most of the participants had physical disabilities. In contrast, Kim et al.²⁸ a higher incidence of internal and facial disabilities, with moderate severity.

The disparities in the reporting and prevalence of disabilities in Saudi Arabia can be attributed mainly to cultural, geographic, and methodological factors. Internal disabilities are often underreported due to societal stigma and a lack of awareness, while more visible physical disabilities tend to be more frequently diagnosed and documented.

QoL among women with disabilities may vary widely based on numerous factors, including type of disability, socioeconomic status, access to healthcare, and social support. In this context, the findings showed that the majority of participants had poor QoL across all four domains: physical health, psychological health, social relationships, and environmental health. This finding is consistent with Saeed and Latif,²⁹ who reported that patients in their study had low total QoL scores and concluded that poor QoL exacerbates impairment and reduces productivity at work. Moreover, a previous qualitative study found that women with disabilities often perceive their QoL as compromised across all domains, with a consistent theme of reduced autonomy and inclusion.³⁰ Research on women with uncomplicated pregnancies has shown that lumbosacral pain-related disability during pregnancy affects both the disability status and QoL outcomes.²⁴

This finding is similar to that of a study conducted in Thailand, which reported a moderate level of QoL among women.³¹ An estimated 15% of the world’s population lives with a disability, yet many have limited access to healthcare. Women with disabilities are at a greater risk of having their rights to healthcare denied because of overlapping discrimination based on both disability and gender.³² In Saudi Arabia, gender norms, may play an important role in shaping QoL of women with disabilities. These factors intersect with cultural, social, and economic dimensions, creating unique challenges for this population. The intersection of gender and disability may also result in compounded discrimination, affecting access to education, healthcare, and social participation.

This context is crucial for understanding the QoL of women with disabilities in Saudi Arabia. The present study showed that the overall mean score of the QoL subscales were low. Similar findings were reported by Andrew-Essien and Ojule,³³ who examined the QoL of individuals with physical disabilities and concluded that QoL was generally low across all domains. Furthermore, classification of QoL based on the total score demonstrated that the majority of women with disabilities had poor QoL, whereas only 8.3% had good QoL. This finding underscores the substantial burden on their physical, psychological, and social well-being. Although this categorization facilitated the interpretation of QoL levels,²¹ dichotomizing QoL scores may have obscured meaningful variation in QoL outcomes. Future studies are needed to examine QoL as a continuous variable to better capture differences in QoL among women with disabilities. A study conducted in middle and low-income countries found that women with disabilities had lower well-being than women without disabilities.⁷ In contrast, studies conducted in India³⁴ and Saudi Arabia³⁵ reported moderate QoL across all domains among women with disabilities. These findings suggest that although reduced well-being is common among women with disabilities, the level of QoL may vary across settings depending on social, economic, and healthcare-related factors. Moreover, the social relationships domain had the lowest mean score, reflecting reduced social support among women with disabilities. This emphasizes the importance of policies and interventions that strengthen social inclusion to enhance QoL.³⁶ Regarding the first hypothesis, the findings provide partial support for the proposed association between Socio-demographics characteristics and QoL, as education level was significantly associated with Qol, whereas the other sociodemographic variables were not.

Specifically, participants with primary/preparatory and secondary being associated to lower mean as compared to university. This association may be explained by the role of education in shaping health literacy, socioeconomic status, sense of control, and resource access, which are all associated with perceived quality of life. As supported by a previous study, education was a positive predictor of QoL.³⁷ Rajati et al.³⁸ reported that QoL was associated with several independent variables, including age, gender, levels of physical disability, education, and employment status. Sabanagic-Hajric et al.³⁹ further recorded that age was positively correlated with participants QoL.

Additionally, Konieczny et al.⁴⁰ discovered an association between higher education levels and better QoL scores. Furthermore, Andrew-Essien and Ojule³³ found that age, occupation, and educational level all had a major impact on QoL, concluding that those with physical disabilities had comparatively low QoL. Similarly, Tavoli et al.⁴¹ found that women who had experienced repeated miscarriages had considerably poorer QoL across all domains. In contrast, the findings of the current study suggest that employment status was not significantly associated with QoL, despite previous research suggesting that employment may be linked to better psychological well-being and social participation. This disparity may be explained by the unequal distribution of employment status among participants and differences in job quality. For women with disabilities, employment may improve mental health and overall life satisfaction, especially when it is stable and supportive.⁴² Therefore, employment status alone may not be a reliable indicator of QoL, and future studies should further examine the association between job quality and employment conditions and QoL among women with disabilities. In addition, the recruitment strategy may have influenced the findings. Participants were recruited through convenience sampling, which may have introduced selection bias and limited the representativeness of the sample. Women who are connected to disability organizations or social networks may differ systematically from those who are more socially isolated or have fewer resources. As a result, the results may not fully reflect the broader population of women with disabilities in the region, which should be considered when interpreting the findings and their generalizability.

Regarding the second Hypothesis, the findings provide partial support for the proposed association between medical characteristics and QoL, as Hospital type was significantly associated with Qol, whereas the other variables were not. Although hospital type was significantly associated with QoL, this finding should be interpreted cautiously. In the multivariable model, we adjusted for the available sociodemographic and clinical variables, including disability and chromobodies, and genetic disorders. However, the hospital variable may still reflect unmeasured factors sch as service availability, care quality, referral pathways, case-mix, and underlying patient characteristics, including health complexity or socioeconomic status. Therefore, the observed association should not be interpreted as a direct effect of facility type alone. Future studies are warranted to include direct measures of the patient care process and service context to clarify the mechanism underlying this association.

Regarding the third Hypothesis, the findings didn’t support the proposed association between QoL and the type and severity of disability, as no statistically significant relationship was found. In contrast, Rajati et al.³⁸ observed that the relationship between physical activity and QoL varied according to the type and severity of disability. Similarly, Abdelrahman et al. ⁴⁴, who evaluated factors associated with QoL among women with disabilities after mastectomy, found a significant association between physical disability and poorer QoL among the study participants.

Limitations

The study has several limitations. First, it was conducted only in the Eastern region of Saudi Arabia, which limits the generalizability of the findings. Therefore, further studies that include participants from the different areas are recommended. Second, the use of non-probability sampling may have introduced sampling bias, potentially overrepresenting women with social support and thereby limiting representativeness. Third, the cross-sectional design precludes causal inference; for example, it remains unclear whether poor QoL increases vulnerability to chronic diseases or vice versa. Additionally, the use of a self-administered questionnaire could introduce reporting bias. Furthermore, several unmeasured confounding factors, such as stress, stigma, accessibility barriers, and family dynamics, were not captured in the present study. Moreover, other factors such as economic status, family support, participant satisfaction, and barriers to accessing healthcare facilities were not assessed, warranting further investigation in future studies. Another limitation of the study is that a significant amount (74–81%) of what affects QOL remains unexplained and is probably caused by factors not included in this analysis (e.g., psychological resilience, social support, specific life circumstances). Future studies should include matched comparison groups or reference regional and international benchmarks to better contextualize QoL scores and clarify the extent to which disability is associated with differences in quality of life.

Conclusion

A complex array of interrelated factors is associated with QoL among women with disabilities. Based on the findings of the current study, we can conclude that educational qualification and type of hospital are significantly associated with the QoL of women with disabilities. Additionally, the high prevalence of poor QoL among women with disabilities in the current study is a pressing concern that warrants attention to improve the QoL for this population. To guide practices and policies that can result in significant improvements, it is also necessary to assess the QoL among women with disabilities. Prioritizing diverse research approaches can enhance our understanding of the unique needs and challenges faced by these populations and ultimately contribute to improving their quality of life. It is crucial to provide healthcare professionals with adequate training to identify and handle the particular difficulties these women encounter, creating a more compassionate and productive care environment, to increase understanding and quality of life for women with disabilities. To address the unique requirements of disabled women and improve their overall quality of life, community-based health services should be implemented.

Footnotes

Acknowledgements

We would like to express our thanks to all the women who participated in the study.

ORCID iD

Basma Salameh

Ethical considerations

Ethical approval was granted from the ethics committee of King Fahad Hospital-Hofuf (IRB No: 78-EP-2023). The Declaration of Helsinki’s guidelines were followed in this study.

Consent to participate

Written informed consent was obtained from all participants, and they were aware of the study objectives. Participants were assured that their identities would be kept confidential and used solely for research purposes. They were also informed that participants might leave the research at any time without facing any penalties or adverse consequences.

Author contributions

A.A.E, N.A, O.M designed the study.

A.A.E, N.A, O.M collected the data.

A.A, N.A, B.S, M.H, A.S.G, A.S.A, A.M.A. O.M prepared the manuscript.

A.A.E, N.A, B.S, O.M approved the final version for submission.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

The data utilized to support the results of the research are accessible to the corresponding author upon request.*

Appendix

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