INTRODUCTION
Chronic diseases are a leading cause of disability and mortality worldwide, significantly impacting individuals’ quality of life and posing substantial challenges to healthcare systems (World Health Organization, 2018). In Saudi Arabia, the prevalence of chronic conditions such as diabetes, hypertension, and asthma has been rising, reflecting broader global trends of increased chronic disease burden (Alhowaish, 2021; AlQuaiz et al., 2022). These diseases often coexist, leading to multimorbidity, which further exacerbates disability and complicates disease management (Barnett et al., 2012). There has been a discernible rise in the incidence of chronic illnesses in Saudi Arabia. A health report [MOH (2019), Saudi Arabia] states that 54% of adults will have at least one chronic illness by 2023. In particular, it is reported that the prevalence rates of hypertension and diabetes are 29% and 25%, respectively (Hazazi and Wilson, 2022). Around 71% of deaths worldwide are caused by chronic illnesses, with cancer, respiratory conditions, and cardiovascular diseases being the main culprits. According to data from the World Health Organization (2018), 422 million adults worldwide have diabetes, and approximately 1.5 billion people worldwide suffer from hypertension (Hazazi and Wilson, 2022).
Disability resulting from chronic diseases is a growing public health concern, as it affects individuals’ ability to perform daily activities and participate in social and economic life. Research has shown that chronic conditions are closely associated with various levels of disability, contributing to functional limitations and reduced mobility (Marengoni et al., 2011). Moreover, disability is not evenly distributed across populations; sociodemographic factors such as gender, education, and income level significantly influence the prevalence and severity of disability (Mitra et al., 2011; Adams et al., 2013).
The relationship between chronic diseases and mental health, particularly depression, is also well-documented. Individuals with chronic conditions are at a higher risk of developing depressive symptoms due to the continuous psychological and physical stress associated with managing their illnesses (Egede, 2007; Gonzalez et al., 2008). Depression, in turn, can negatively impact the management and progression of chronic diseases, creating a vicious cycle that further deteriorates health outcomes (Katon, 2011).
In Saudi Arabia, the intersection of chronic diseases, disability, and depression presents a unique challenge, given the country’s specific socio-cultural and economic context. While previous studies have explored the prevalence and impact of chronic diseases and mental health issues in Saudi Arabia, there is limited research on the comprehensive interplay between these factors and how they collectively affect the population’s health and well-being (AlQuaiz et al., 2022).
This study aims to fill this gap by examining the relationships between chronic diseases, disability, and depression among Saudi Arabian patients. By conducting a cross-sectional survey in Riyadh, Saudi Arabia, this research seeks to provide a detailed understanding of how these factors interact and influence each other. The insights gained from this study can inform healthcare policies and interventions aimed at improving the quality of life and health outcomes for patients with chronic diseases in Saudi Arabia.
MATERIALS AND METHODS
Research design, participants, and settings
From March to May 2024, this study was conducted in Riyadh, Saudi Arabia, to investigate the relationship between chronic illnesses, disability, and depression. Saudi residents aged 18 years and above with at least one chronic disease who agreed to participate in the study were eligible. Participants were selected from a variety of settings, including disability centers, hospitals, health clinics, community gatherings, charity events, and health camps. They were invited to take online surveys using QR code-accessed Google Forms. Participants had the choice of completing the survey alone or with help from an attendant. Interviewers were present to answer any questions that arose during the survey process. The study’s objectives and informed consent were stated at the beginning of the form, and participants had the option of participating or declining, making participation entirely voluntary. Participants were assured of the confidentiality of their data and the anonymity of the study outcomes. Those who were unable to read were given an oral explanation of the contents of the informed consent form. An institutional review board of AlMaarefa University (IRB24-024/02) granted ethical approval for the research project.
Sample size
Utilizing the online sample size calculator available at http://www.raosoft.com/samplesize.html, we arrived at 377 as the sample size for our study with a 95% confidence level and a 5% margin of error. In total, 381 people took part in our study.
Study instrument
The questionnaire was developed using published literature. There were three sections in the questionnaire. Section I contained 10 items about sociodemographic traits (gender, age, marital status, educational level, region of location, nationality, employment status, income, number of chronic diseases, and name of chronic disease/s suffering). Section II included items for assessing disability, and Section III had items for measuring depression.
The World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0) (World Health Organization, 2012) is a self-report questionnaire designed by WHO to assess levels of disability and functional impairment. It investigates several aspects of life, including mobility, cognition, social interactions, and self-care. There are two versions: a long version (36 items) and a short version (12 items). The 12-item WHODAS 2.0 uses Likert-style scale questions to assess difficulty levels in functioning over the previous 30 days, ranging from “none” to “extreme.”
The scale assesses six domains: cognitive (items 3 and 6), mobility (items 1 and 7), self-care (items 8 and 9), relationships (items 10 and 11), life activities (item 2), and participation (items 4 and 5). Due to the scale’s one-dimensional structure and high internal consistency, simple scoring is sufficient to assess functional limitations (Üstün et al., 2010). The raw scores of each item, which range from 0 (no disability) to 48 (full disability), are added up to get the summary score.
In this study, we apply the widely used simple scoring method described by Younus et al. (2017) and Axelsson et al. (2017). The ratings for each item, which range from “none” (0) to “extreme” (4), add up to an average score that divides the status of disability into five categories: no disability (0-0.5), mild disability (0.51-1.5), moderate disability (1.51-2.5), severe disability (2.51-3.5), and extreme disability (3.51-4).
The Patient Health Questionnaire-9 (PHQ-9) was used to assess depression in Section III of the questionnaire (Asdaq et al., 2024). The PHQ-9 self-report questionnaire includes nine items on which participants rated their emotions over the previous 2 weeks. On a scale of 0-3, responses were scored (0 = not at all, 1 = several days, 2 = more than half the days, and 3 = nearly every day) to generate a total score that ranged from 0 to 27. According to earlier research (Kroenke et al., 2001), a cutoff score of 10 was used to categorize depression. A score of <10 denoted a non-depressive state, whereas a score of ≥10 indicated depression.
The research team used established models and published material to develop the questionnaire. Its validation was aided by specialists in the fields of public health, epidemiology, community pharmacy, internal medicine, and scientific research. The questionnaire was translated into Arabic using both forward and reverse translation methods with the help of multilingual specialists. The survey employed a bilingual (Arabic and English) questionnaire. As part of the pilot/pretest, 10 eligible participants were first given a questionnaire to see if any of the study questions needed more clarification. The reliability of the questionnaire was assessed using Cronbach’s alpha, and the result indicated that it was 0.801.
Statistical analysis
The collected data were entered into IBM’s statistical software, SPSS (version 25). The research sample’s sociodemographic features were first subjected to a univariate descriptive analysis, which was followed by a bivariate analysis employing the Pearson’s chi-squared test. The degree of disability was measured using WHODAS 2.0, and the factors influencing the emergence of disability were evaluated using regression analysis.
Regression analysis was used to determine the factors contributing to depression and disability in patients based on the number of chronic diseases they had. This statistical approach enabled researchers to identify and quantify the links between various chronic conditions and their effects on mental health and functional limitations. With a significance level set at a P-value of <0.05, the analysis shed light on how the number and severity of chronic diseases affected the study population’s levels of depression and disability by accounting for potential confounding variables. To increase the robustness and dependability of the results, bootstrapping was done in addition to regression analysis in the correlation analysis (Pearson correlation). To generate multiple simulated samples and estimate the sampling distribution of the correlation coefficients, bootstrapping entails resampling the data with replacement. The bootstrapping methodology and the analysis results offer insightful information for creating focused interventions that target the mental health and general well-being of patients with chronic illnesses.
RESULTS
Sociodemographic characteristics of the participants
Table 1 shows the demographic characteristics of the study participants. Seventy-six percent (n = 269) of the participants, representing a range of age groups, were female. More than half of them were married (55%, n = 210), and a sizable percentage (72.7%, n = 277) had completed a degree or higher education. Most participants (65.1%, n = 248) were from the central region of Saudi Arabia, while 3.1% (n = 12) were from the western region. Almost half of the participants (48.8%, n = 186) were employed, while 25.7% (n = 98) reported no source of income. Saudi nationals make up most of the study cohort (86.4%, n = 329). In terms of health conditions, most participants (66.7%, n = 254) had a single chronic disease, 13.6% (n = 52) had two, and 19.7% (n = 75) were managing more than two chronic diseases.
Sociodemographic characteristics of the participants.
| Characteristics | Variables | Frequency | Percentage |
|---|---|---|---|
| Gender | Female | 269 | 70.6 |
| Male | 112 | 29.4 | |
| Age (years) | 18-25 | 106 | 27.8 |
| 26-35 | 92 | 24.1 | |
| 36-45 | 84 | 22.0 | |
| 46-55 | 61 | 16.0 | |
| >55 | 38 | 10.0 | |
| Marital status | Single | 147 | 38.6 |
| Married | 210 | 55.1 | |
| Widowed | 14 | 3.7 | |
| Divorced | 10 | 2.6 | |
| Education | Pre-primary and Primary | 13 | 3.4 |
| High school | 15 | 3.9 | |
| Secondary school | 76 | 19.9 | |
| Graduate | 161 | 42.3 | |
| Postgraduate and above | 116 | 30.4 | |
| Location | Eastern region or around it | 83 | 21.8 |
| Western region or around it | 12 | 3.1 | |
| Middle region or around it | 248 | 65.1 | |
| Southern region or around it | 15 | 3.9 | |
| Northern region or around it | 23 | 6.0 | |
| Nationality | Saudi | 329 | 86.4 |
| Non-Saudi | 52 | 13.6 | |
| Employment status | Employed | 186 | 48.8 |
| Unemployed | 85 | 22.3 | |
| Inactive | 23 | 6.0 | |
| Student | 87 | 22.8 | |
| Monthly family income (Saudi Riyals) | <5000 SAR | 70 | 18.4 |
| 5000-10,000 SAR | 62 | 16.3 | |
| 10,000-20,000 SAR | 79 | 20.7 | |
| >20,000 SAR | 72 | 18.9 | |
| No income | 98 | 25.7 | |
| Number of chronic disease(s) | 1 | 254 | 66.7 |
| 2 | 52 | 13.6 | |
| >2 | 75 | 19.7 |
Prevalence of chronic diseases
The study participants reported a range of common chronic diseases. Diabetes mellitus was the most prevalent, affecting 43.3% (n = 165) of the participants. Hypertension followed at 39.9% (n = 152), and bronchial asthma at 28.6% (n = 109). Additionally, 25.72% (n = 98) had cardiovascular issues, and 16.8% (n = 64) had osteoarticular diseases. Gastrointestinal diseases were reported by 14.17% (n = 54), while 13.12% (n = 50) had a thyroid disorder. Cancer was present in 10.23% (n = 39) of participants, mental health issues in 4.46% (n = 17), and strokes in 2.36% (n = 9). Less common were liver diseases (0.78%, n = 3) and renal diseases (0.52%, n = 2) (Fig. 1). These findings underscore the diverse health challenges within the study population and highlight the necessity for comprehensive management strategies.
A total of 762 chronic diseases were reported by the 381 participants. Of these, 254 diseases were reported by individuals with a single chronic condition, 104 by those with two, and 404 diseases were reported by 75 participants (19.7%) who had three or more chronic conditions.
Comparison of sociodemographic variables with the disability status
Table 2 compares sociodemographic characteristics with disability status in four categories: mild, moderate, severe, and extreme. In comparison to male participants, a significant majority of females experienced mild (78.1%, n = 132) and moderate (66.8%, n = 127) disability levels. Thus, in our study, gender and disability status have a significant relationship (P = 0.006). Although the number of participants with severe disabilities was small, a significant proportion of them had higher education levels (postgraduate and above), indicating that educational attainment has a significant impact on disability status (P = 0.001). Additionally, there was a significant correlation (P = 0.003) between income level and disability status, with participants with lower incomes showing higher levels of depression and disability.
Comparison of sociodemographic characteristics with the status of disability.
| Characteristics | Variables | Status of disability, n (%) | P-value | |||
|---|---|---|---|---|---|---|
| Mild disability | Moderate disability | Severe disability | Extreme disability | |||
| Gender | Female | 132 (78.1) | 127 (66.8) | 9 (45) | 1 (50) | 0.006 |
| Male | 37 (21.9) | 63 (33.2) | 11 (55) | 1 (50) | ||
| Age (years) | 18-25 | 52 (30.8) | 53 (27.9) | 1 (5) | 0 | 0.181 |
| 26-35 | 38 (22.5) | 51 (26.8) | 3 (15) | 0 | ||
| 36-45 | 38 (22.5) | 38 (20) | 7 (35) | 1 (50) | ||
| 46-55 | 26 (15.4) | 30 (15.8) | 5 (25) | 0 | ||
| >55 | 15 (8.9) | 18 (9.5) | 4 (20) | 1 (50) | ||
| Marital status | Single | 69 (40.8) | 76 (40) | 2 (10) | 0 | 0.236 |
| Married | 90 (53.3) | 102 (53.7) | 16 (80) | 2 (100) | ||
| Widowed | 5 (3.0) | 7 (3.7) | 2 (10) | 0 | ||
| Divorced | 5 (3.0) | 5 (2.6) | 0 | 0 | ||
| Education | Pre-primary and Primary | 4 (2.4) | 5 (2.6) | 3 (15) | 1 (50) | 0.001 |
| High school | 6 (3.6) | 7 (3.7) | 2 (10) | 0 | ||
| Secondary school | 35 (20.7) | 40 (21.1) | 0 | 1 (50) | ||
| Graduate | 81 (47.9) | 78 (41.1) | 2 (10) | 0 | ||
| Postgraduate and above | 43 (25.4) | 60 (31.6) | 13 (65) | 0 | ||
| Location | Eastern region or around it | 46 (27.2) | 33 (17.4) | 4 (20) | 0 | 0.403 |
| Western region or around it | 5 (3) | 6 (3.2) | 1 (5) | 0 | ||
| Middle region or around it | 103 (60.9) | 131(68.9) | 13 (65) | 1 (50) | ||
| Southern region or around it | 6 (3.6) | 8 (4.2) | 1 (5) | 0 | ||
| Northern region or around it | 9 (5.3) | 12 (6.3) | 1 (5) | 1 (50) | ||
| Nationality | Saudi | 150 (88.8) | 162 (85.3) | 17(85) | 0 | 0.003 |
| Non-Saudi | 19 (11.2) | 28 (14.7) | 3 (15) | 2 (100) | ||
| Employment status | A. Employed | 81 (47.9) | 90 (47.4) | 15 (75) | 0 | 0.030 |
| B. Unemployed | 43 (25.4) | 38 (20) | 3 (15) | 1 (50) | ||
| C. Inactive | 11 (6.5) | 10 (5.3) | 1 (5) | 1 (50) | ||
| D. Student | 34 (20.1) | 52 (27.4) | 1 (5) | 0 | ||
| Income status | A. <5000 SAR | 33 (19.5) | 33 (17.4) | 4 (20) | 0 | 0.003 |
| B. 5000-10,000 SAR | 31 (18.3) | 31 (16.3) | 0 (0) | 0 | ||
| C. 10,000-20,000 SAR | 42 (24.9) | 33 (17.4) | 3 (15) | 1 (50) | ||
| D. >20,000 SAR | 21 (12.4) | 40 (21.1) | 11 (55) | 0 | ||
| E. No income | 42 (24.9) | 53 (27.9) | 2 (10) | 1 (50) | ||
| Number of chronic disease(s) | 1 | 144 (85.2) | 107 (56.3) | 3 (15) | 0 | 0.001 |
| 2 | 16 (9.5) | 33 (17.4) | 3 (15) | 0 | ||
| >2 | 9 (5.3) | 50 (26.3) | 14 (70) | 2 (100) | ||
Bold font indicate significant difference, where P-values of <0.05, <0.01, and <0.001 indicate a significant, very significant, and extremely significant difference, respectively, based on the Chi-Square Test.
Furthermore, participants with two or more chronic diseases reported significantly higher disability levels (P = 0.001). Employment status (P = 0.030) and nationality (P = 0.003) were two other significant variables associated with disability status among the participants. These findings highlight the complex relationship between sociodemographic variables and disability status, highlighting the need for specialized interventions to address differences in disability outcomes across various populations.
Determination of factors that influence the disability status by regression analysis
Table 3 shows that gender [P = 0.032, Beta = 0.100, 95% confidence interval (CI) = 0.011-0.257], nationality (P = 0.015, Beta = 0.115, 95% CI = 0.041-0.368), employment status (P = 0.046, Beta = 0.109, 95% CI = 0.022-0.055), and the presence of multiple chronic diseases (P = 0.000, Beta = 0.456, 95% CI = 0.272-0.422) are the factors that significantly influence the development of disability in patients with chronic illnesses. Collinearity statistics show that predictor variables have minimal multicollinearity: tolerance levels are high for gender (0.942), region (0.921), nationality (0.933), income (0.945), and chronic diseases (0.809), indicating that there is no redundancy or strong correlation. Therefore, each independent variable makes a unique contribution to changes in the disability status.
Linear regression analysis to determine the factors that influence the development of disability.
| Characteristics of the participants | Standardized coefficients (Beta) | P-value | 95% CI for Beta | Collinearity statistics | ||
|---|---|---|---|---|---|---|
| Lower bound | Upper bound | Tolerance | VIF | |||
| Gender | 0.100 | 0.032* | 0.011 | 0.257 | 0.942 | 1.062 |
| Age | 0.015 | 0.815 | 0.052 | 0.066 | 0.496 | 2.016 |
| Marital status | 0.003 | 0.964 | 0.113 | 0.119 | 0.497 | 2.011 |
| Education | 0.007 | 0.889 | 0.058 | 0.067 | 0.791 | 1.265 |
| Regions | 0.085 | 0.072 | 0.005 | 0.104 | 0.921 | 1.086 |
| Nationality | 0.115 | 0.015* | 0.041 | 0.368 | 0.933 | 1.072 |
| Employment | 0.109 | 0.046* | 0.001 | 0.109 | 0.688 | 1.453 |
| Income | 0.039 | 0.400 | 0.022 | 0.055 | 0.945 | 1.059 |
| Number of chronic diseases | 0.456 | 0.000* | 0.272 | 0.422 | 0.809 | 1.237 |
Abbreviations: CI, confidence interval; VIF, variance inflation factor.
*P-value < 0.05.
Correlation between disability status, depression, and number of chronic diseases
The Pearson correlation analyzing the correlations between depression, the number of chronic diseases, and disability are shown in Table 4. The number of chronic illnesses and disability status showed the strongest positive correlation, with a significant increase in disability being observed as the number of chronic illnesses among participants increased (P < 0.01). Our study found a significant correlation (P < 0.05) between increased depression and higher levels of disability among participants. However, while there was a linear and positive relationship between depression and the number of chronic diseases, it was not statistically significant.
Pearson correlation between the number of chronic diseases, status of disability, and depression.
| Correlations | Disability | Depression | Number of chronic diseases | |||
|---|---|---|---|---|---|---|
| Disability | Pearson correlation | 1 | 0.118 a | 0.588 b | ||
| Sig. (2-tailed) | - | 0.021 | 0.000 | |||
| Bootstrap c | 95% CI | Lower | 1 | 0.026 | 0.506 | |
| Upper | 1 | 0.205 | 0.669 | |||
| Depression | Pearson correlation | 0.118 a | 1 | 0.089 | ||
| Sig. (2-tailed) | 0.021 | - | 0.083 | |||
| Bootstrap c | 95% CI | Lower | 0.026 | 1 | −0.002 | |
| Upper | 0.205 | 1 | 0.180 | |||
| Number of chronic diseases | Pearson correlation | 0.588 b | 0.089 | 1 | ||
| Sig. (2-tailed) | 0.000 | 0.083 | - | |||
| Bootstrap c | 95% CI | Lower | 0.506 | −0.002 | 1 | |
| Upper | 0.669 | 0.180 | 1 | |||
Abbreviation: CI, confidence interval.
aCorrelation is significant at the 0.05 level (2-tailed).
bCorrelation is significant at the 0.01 level (2-tailed).
cUnless otherwise noted, bootstrap results are based on 1000 bootstrap samples.
DISCUSSION
The findings from this study provide a comprehensive understanding of the interplay between chronic diseases, disability, and depression among Saudi Arabian patients. A direct association was observed between the number of chronic diseases and the level of disability experienced by the participants. Furthermore, a positive linear correlation was found between the level of disability and the intensity of depression experienced by them.
Sociodemographic characteristics and chronic disease prevalence
The demographic distribution of the participants, predominantly females (70.6%, n = 269), married (55%, n = 210), and well-educated (72% with at least a degree, n = 277), is reflective of broader societal trends where women and individuals with higher educational levels are more likely to participate in health research (Choi and DiNitto, 2014a, b; Lai and Tan, 2019a, b). The high prevalence of chronic diseases, such as diabetes mellitus (43.3%, n = 165), hypertension (39.9%, n = 152), and bronchial asthma (28.6%, n = 109), aligns with national health data, underscoring the substantial burden of chronic conditions in Saudi Arabia (Alhowaish, 2021; AlQuaiz et al., 2022).
Disability and sociodemographic correlations
The study revealed significant gender differences in disability levels, with females experiencing higher levels of mild and moderate disabilities compared to males (P = 0.006). This finding is consistent with global trends indicating higher disability rates among women, potentially due to biological, social, and behavioral factors that contribute to chronic disease development and progression (Mitra et al., 2011). Additionally, the correlation between higher education levels and severe disability status (P = 0.001) suggests that, although education is generally associated with better health outcomes, it may not fully protect against the disability risks posed by chronic diseases (Adams et al., 2013).
Income was another critical factor, with lower-income levels significantly associated with higher disability and depression rates (P = 0.003). This finding highlights the socioeconomic disparities in health outcomes and the necessity for targeted interventions to support lower-income populations, addressing both economic and health inequities (Marmot et al., 2008).
The findings from this study provide valuable insights into the interplay between chronic diseases, disability, and depression among Saudi Arabian patients. Cultural and sociodemographic factors in Saudi Arabia play a critical role in shaping these relationships. For instance, the demographic profile of the participants, predominantly females, married, and well-educated, reflects broader societal trends where women and individuals with higher educational levels are more likely to engage in health research (Choi and DiNitto, 2014a, b; Lai and Tan, 2019a, b).
In Saudi Arabia, cultural norms and gender roles significantly impact health outcomes and access to care. Women often face unique challenges related to chronic diseases and disability. For example, societal expectations and roles may limit women’s access to health services or restrict their ability to seek care outside the home (Al-Eissa et al., 2018). This may partly explain the observed higher levels of disability among female participants compared to their male counterparts.
Chronic diseases and disability
The study revealed a significant relationship between the number of chronic diseases and disability levels (P = 0.001). Participants with multiple chronic conditions reported significantly higher levels of disability, corroborating the well-documented association between multimorbidity and increased functional impairment (Barnett et al., 2012). The regression analysis further identified gender (P = 0.032), nationality (P = 0.015), employment status (P = 0.046), and the presence of multiple chronic diseases (P = 0.000) as significant predictors of disability. These findings suggest a multifaceted interplay of sociodemographic and health-related factors influencing disability outcomes (Alavudeen et al., 2020).
The data indicate that individuals with more than one chronic disease are at a heightened risk of experiencing severe disability. This aligns with existing literature that underscores the compounded impact of multiple chronic conditions on physical function, mobility, and overall quality of life (Marengoni et al., 2011). For instance, patients with both diabetes and hypertension may face greater challenges in managing their health, leading to more significant functional limitations and disability (Banerjee et al., 2010).
Additionally, cultural beliefs about illness and disability can influence the management and perception of chronic diseases. In Saudi Arabia, there is a cultural tendency to view chronic diseases through a lens of fatalism, where some individuals might perceive their conditions as predestined, which can affect their engagement with preventive care and management strategies (Al-Lawati, 2007). This perception might contribute to higher disability levels as patients might not actively seek or adhere to treatment plans.
Depression and chronic diseases
The study identified a significant correlation between higher levels of disability and increased depression (P = 0.021), underscoring the intertwined nature of physical and mental health (Moussavi et al., 2007). While the relationship between the number of chronic diseases and depression was positive, it was not statistically significant. This suggests that while chronic diseases contribute to depression, other factors such as social support, coping mechanisms, and individual resilience may also play crucial roles (Katon, 2011).
The findings highlight that patients with multiple chronic conditions are more likely to experience depressive symptoms. This is consistent with research indicating that the cumulative burden of managing multiple chronic illnesses can lead to increased psychological stress, reduced quality of life, and greater susceptibility to depression (Egede, 2007). For example, the daily management of conditions such as diabetes and asthma, which require constant monitoring and medication adherence, can significantly impact mental well-being, leading to feelings of hopelessness and depression (Gonzalez et al., 2008).
In Saudi Arabia, stigma associated with mental health issues can further complicate the situation. Cultural stigmatization of mental health conditions often leads to underreporting and under-treatment of depression, which may exacerbate the psychological impact of chronic diseases (Gater and Zaman, 2005). Social support structures and family dynamics also play a role. In Saudi society, familial support is crucial, yet the burden of caregiving can sometimes lead to increased stress and mental health issues among family members (Al-Jawad, 2013).
Implications for healthcare practice and policy
The results of this study underscore the urgent need for culturally sensitive, integrated, and multidisciplinary approaches to managing chronic diseases in Saudi Arabia. Healthcare policies should prioritize models of care that address both the physical and mental health needs of patients with chronic conditions, ensuring comprehensive support through accessible mental health services. Additionally, strengthening socioeconomic support systems is crucial to alleviating the financial burden on patients, particularly those from lower-income backgrounds, thereby enhancing their overall health outcomes (World Health Organization, 2016). By addressing both physical and mental health needs within an integrated care framework and tackling socioeconomic disparities through targeted interventions, healthcare systems can better manage the complexities of chronic diseases and improve patient outcomes.
Limitations and future research
The cross-sectional design of this study limits the ability to establish causal relationships. Longitudinal studies are needed to explore the temporal dynamics between chronic diseases, disability, and depression. Moreover, the reliance on self-reported data may introduce response biases, necessitating the inclusion of objective health assessments in future research to validate the findings.
CONCLUSION
In conclusion, this study offers critical insights into the substantial impact of chronic diseases on both disability and mental health among Saudi Arabian patients. The direct association between the number of chronic conditions and the level of disability highlights the compounded challenges faced by patients with multiple chronic illnesses. Additionally, the positive linear correlation between disability levels and the intensity of depression underscores the intertwined nature of physical and mental health.
To address these issues, it is essential to implement comprehensive policy changes aimed at improving health outcomes. First, increasing accessibility to integrated healthcare services, including mental health support, can facilitate early intervention and management of chronic diseases. Second, public health campaigns focused on preventive care, lifestyle modification, and health education can empower individuals to make informed health choices.
Furthermore, enhancing training programs for healthcare professionals in recognizing and treating mental health issues related to chronic diseases is crucial. Collaboration between governmental agencies, healthcare providers, and community organizations can create supportive environments that address the sociodemographic factors influencing health.
Investing in research to better understand the specific needs of chronic disease patients in Saudi Arabia will also be beneficial. This comprehensive approach has the potential to significantly improve the quality of life and overall health outcomes for this vulnerable population, ultimately fostering a healthier society.