Examining factors contributing to mortality in Saudi Arabia: proposing effective healthcare management approaches

Abstract

Background

Non-communicable diseases (NCDs) are the leading cause of death globally, with their prevalence rising in Saudi Arabia due to unhealthy lifestyles and increased life expectancy. This study investigates the primary causes of mortality in Saudi Arabia, which include cardiovascular diseases, cancers, diabetes, and chronic respiratory diseases, and proposes healthcare management strategies to improve mortality outcomes, reduce preventable deaths, and enhance healthcare delivery.

Methods

Secondary quantitative data from the General Authority for Statistics (GASTAT) and the World Health Organization (WHO) from 2015 to 2022 were analyzed. These years were selected based on data availability, completeness, and consistency to ensure a comprehensive assessment of mortality trends and non-communicable diseases. Data points were excluded if they were incomplete, inconsistent, or lacked proper classification.The study analyzed key variables, including age, gender, and specific causes of death related to non-communicable diseases. Mortality rates and non-communicable diseases were examined using descriptive statistics, correlation analysis, and linear regression. IBM SPSS Statistics version 27 was used for analysis, while Microsoft Excel facilitated data visualization.

Results

The findings indicate that non-communicable diseases (NCDs) are the leading causes of mortality in Saudi Arabia, with ischemic heart disease being the most prevalent. The mean mortality rate for ischemic heart disease was higher in males (133.25 per 100,000, 95% CI: 132.88–133.62) than females (87.84 per 100,000, 95% CI: 87.58–88.10). Stroke mortality rates were comparable between genders, while neoplasms, kidney disease, and diabetes mellitus had lower but notable contributions. Males consistently exhibited higher mortality rates over five years (mean: 102.20 per 1,000) compared to females (81.88 per 1,000). Regression analysis confirmed a significant association between NCDs and mortality (β = -0.917, R² = 0.841, p < 0.001), emphasizing the need for targeted public health interventions.

Conclusion

The high mortality rates from ischemic heart disease, stroke, and other NCDs, particularly among males, highlight the need for targeted interventions. Gender-specific public health campaigns, early detection programs for high-risk individuals, and stronger preventive policies are essential to reducing mortality and improving healthcare outcomes in Saudi Arabia.

Background

Non-communicable diseases (NCDs) are chronic conditions arising from genetic, physiological, environmental, and behavioral factors, contributing to 74% of global deaths [1]. In Saudi Arabia, NCDs are the leading cause of mortality, accounting for 73% of total deaths, closely aligning with global trends [2]. The primary contributors include cardiovascular diseases, cancers, diabetes, and chronic respiratory diseases, with a premature mortality probability (death between ages 30 and 70) of 18.6% [2].

Over the past two decades, urbanization, lifestyle changes, and increased life expectancy have significantly contributed to the growing burden of NCDs in Saudi Arabia [3]. The proportion of NCD-related deaths increased from 65% in 2000 to 73% in 2016 [2], largely driven by modifiable risk factors such as tobacco use, unhealthy diets, physical inactivity, and obesity [4]. These factors are closely linked to metabolic disorders, including high blood glucose, hypertension, and abnormal lipid profiles, which further elevate NCD morbidity and mortality.

Key risk factors driving NCDs in Saudi Arabia

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Unhealthy Diet and Obesity:

Dietary patterns in Saudi Arabia have shifted towards high consumption of processed foods and sugary drinks, with 94% of the population failing to meet recommended fruit and vegetable intake [5]. As a result, obesity prevalence reached 28% in 2016, significantly contributing to rising diabetes and cardiovascular disease cases [2].

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Physical Inactivity:

Sedentary behavior is widespread, with 58% of adults not meeting WHO’s recommended physical activity levels [2]. This is exacerbated by reliance on motorized transportation, limited recreational exercise, and prolonged screen time [6].

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Tobacco Use:

19.8% of the Saudi population uses tobacco products, posing a major risk for lung diseases, cancers, and cardiovascular disorders [7]. Despite anti-smoking regulations, smoking remains a persistent public health challenge [8, 9].

If these risk factors remain unchanged, projections indicate that by 2050, the disability-adjusted life years (DALYs) per 100,000 people will increase from 3,550 to 8,628 for women and from 5,073 to 12,198 for men [10]. However, modifying these risk factors, such as reducing smoking, improving diet, and increasing physical activity, could lower the NCD burden by 4.9% by 2050 [10].

Existing national policies and programs

To combat NCDs, the Ministry of Health (MOH) has implemented several national policies and programs, including:

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Nutrition Policy:

Saudi Arabia has adopted WHO’s Global Action Plan for NCD Prevention, introducing measures such as taxation on sugary beverages, banning trans fats, and reducing salt consumption to promote healthier eating habits [7, 11,12,13].

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Physical Activity Promotion:

Various awareness campaigns and educational initiatives have been launched to increase physical activity, yet sedentary behavior remains a key challenge [6, 14].

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Tobacco Control Policy:

The MOH has enforced anti-smoking laws, including restrictions on tobacco advertising, public smoking bans, and taxation on tobacco products [8, 9].

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Chronic Disease Management Programs:

The MOH has developed targeted programs for major NCDs, including diabetes, cardiovascular disease, and obesity, focusing on early detection, prevention, and patient-centered care models [15].

Saudi Arabia has also initiated multisectoral collaborations, such as the RASHAKA program, a school-based intervention for childhood obesity that has successfully reduced students’ BMI levels over two years [16]. Additionally, the Chronic Care Model (CCM) has been implemented in primary healthcare centers, integrating self-management support, electronic health records, and interdisciplinary care teams to improve NCD management [17, 18].

Despite existing national policies and initiatives, including the Nutrition Policy, Physical Activity Policy, and Tobacco Control Programs, Saudi Arabia continues to experience a rising burden of NCD-related mortality [15]. While previous studies have examined individual risk factors, comprehensive assessments of mortality trends and their underlying causes remain limited. Additionally, there is a lack of integrated strategies for addressing disparities across age and gender groups.

This study aims to fill this research gap by analyzing the leading causes of mortality in Saudi Arabia, identifying high-risk populations, and proposing evidence-based healthcare management strategies. Understanding these trends is essential for developing targeted interventions to reduce preventable deaths and improve healthcare service delivery.

Methods

Data collection

The data used for this study were secondary quantitative datasets retrieved from two main sources: the General Authority for Statistics (GASTAT) and the World Health Organization (WHO). The datasets from GASTAT covered the period from 2017 to 2022. They were primarily derived from the Civil Registration and Vital Statistics (CRVS) system, which compiles data from death certificates issued by healthcare providers. These datasets included age-specific and gender-specific mortality rates and demographic data such as population size and distribution across age groups. Additionally, household health surveys conducted by GASTAT supplemented the data, capturing mortality events occurring outside healthcare facilities. The WHO datasets spanned the period from 2015 to 2019 and provided detailed information on the leading causes of death, including non-communicable diseases (NCDs). This data, primarily sourced from global health databases and reports, included gender-specific mortality rates attributed to NCDs and aligned with the International Classification of Diseases (ICD) standards for coding causes of death. The selection of different time frames (2015–2019 for WHO data and 2017–2022 for GASTAT data) was based on data availability and relevance to the study objectives:

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WHO data (2015–2019) was selected because it represents the most comprehensive and internationally standardized dataset on cause-specific mortality, particularly for NCD-related deaths. These data ensure comparability across different years and regions, which is crucial for analyzing trends in disease burden.

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GASTAT data (2017–2022) was chosen due to its recency and national specificity, providing the latest demographic and mortality statistics for the Saudi population. These data offer a more updated representation of general mortality trends, allowing for a contemporary analysis of overall mortality rates.

While the datasets cover partially overlapping but different timeframes, this approach allows for a robust comparison of long-term trends in NCD mortality while ensuring the inclusion of the most recent national mortality data available.

Study population

The study includes the entire Saudi Arabian population, encompassing both Saudi nationals and non-Saudi residents. Given the national representativeness of the datasets, the findings provide valuable insights into mortality patterns and trends across the country.

Variables

The primary variables examined in this study are:

1. 1.

Causes of Death: Categorized into the leading causes of death in Saudi Arabia, including ischemic heart disease, stroke, neoplasms, kidney diseases, and diabetes mellitus.

2. 2.

Number of Deaths: This represents the total number of deaths related to each cause for each year and gender.

3. 3.

Year: Specifies the year associated with each cause of death for both genders.

4. 4.

Gender: Categorized as Male and Female, enabling the analysis of mortality rates by gender.

5. 5.

Age Group: Age-specific mortality rates were directly obtained from GASTAT, categorized into predefined age cohorts, allowing for an analysis of mortality trends across different population segments. Age-specific mortality rates were used as reported in GASTAT datasets, without additional age standardization. The analysis directly reflects the mortality patterns within each age group, providing insights into the distribution of deaths across different demographic segments in Saudi Arabia.

6. 6.

Population Size: Annual population estimates from GASTAT were used to calculate age- and gender-specific mortality rates, ensuring demographic adjustments in the analysis.

These variables facilitate an in-depth analysis of mortality rates and their underlying causes, specifically focusing on gender and temporal trends.

Analytical approach

Data were analyzed using descriptive and inferential statistical methods. IBM SPSS Statistics version 27 is employed for statistical computations, and Microsoft Excel for data visualization. The main analytical methods used include:

1. 1.

Descriptive Statistics were applied, including mean, standard deviation, median, proportions, and frequency distributions. They were employed to analyze mortality rates and identify the primary causes of death, categorized by gender and year, providing measures of central tendency, variability, and percentage contributions to total mortality.

2. 2.

Correlation Analysis was applied through Spearman’s rank correlation to evaluate the non-linear relationship between the “Cause of Death” and “Mortality Rate” variables using a two-tailed significance test. This method was selected over Pearson’s correlation because it does not assume a linear relationship or normally distributed data, making it more appropriate for analyzing mortality trends. Given the potential non-linear associations between mortality rates and causes of death, as well as the ordinal nature of some variables, Spearman’s correlation provides a more robust measure of association in this context.

3. 3.

Regression Analysis was incorporated through a linear regression model. It was utilized to investigate the impact of “Cause of Death” (independent variable) on “Mortality Rate” (dependent variable), with regression coefficients, adjusted R-squared, standard errors, t-values, and p-values calculated to assess the magnitude, direction, and significance of the association.

4. 4.

Data visualization was performed using Microsoft Excel, including bar charts to compare mortality rates across years, age groups, genders, and leading causes of death, and line graphs to illustrate temporal trends and patterns in mortality rates for both genders and different causes of death.

Results

The results highlight the leading causes of mortality in Saudi Arabia, with a particular focus on non-communicable diseases (NCDs) as the primary contributors. The analysis examines age- and gender-specific mortality trends, identifies key fluctuations in death rates, and explores statistical associations between cause of death and overall mortality to inform healthcare management strategies.

Mortality Trends by Age Group (GASTAT Data: 2018–2022)

Mortality rates varied across age groups, as shown in Fig. 1. Among the observed trends, the 5–9 age group consistently exhibits the lowest mortality rates, experiencing a notable decline from 2018 to 2019. On the other hand, the 65 + age group demonstrates the highest mortality rates, reaching a peak in 2021 before a subsequent decrease in 2022. Noteworthy fluctuations are observed in the 35–39 and 55–59 age groups, with mortality rates peaking in 2021 and 2019, respectively. The 50–54 age group also experience a substantial increase in mortality rates in 2021. Overall, these trends underscore the importance of age-specific considerations in understanding mortality patterns and informing targeted healthcare interventions.

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Mortality Trends by Gender (GASTAT Data: 2017–2021)

The data in Table 1 reveals distinct patterns in mortality rates among adult females and males per 1,000 population over the five years. The mortality rate for adult females exhibited a relatively stable trend between 2017 and 2019, with 79.41 in 2017, 79.49 in 2018, and 81.36 in 2019. This was followed by an increase to 88.31 in 2020 before decreasing slightly to 80.84 in 2021. In contrast, adult males consistently experienced higher mortality rates, starting at 100.02 in 2017, increasing to 101.80 in 2018, peaking at 108.38 in 2020, and declining to 99.91 in 2021. The mean mortality rate over the five years was 81.88 for females and 102.20 for males. The standard deviation for both groups remained within a narrow range with an SD = 3.69 for females and an SD = 3.53 for males, indicating that the data points were closely distributed around the respective means. These findings underscore the differences in mortality rates between adult females and males. These findings suggest the need for gender-focused health interventions, particularly for conditions disproportionately affecting males.

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Leading Causes of Death by Gender (WHO Data: 2015–2019)

Descriptive statistics for the leading causes of death in Saudi Arabia for females and males between the years 2015 and 2019 are presented in Table 2. The table provides the mean mortality rates, standard deviations, and 95% confidence intervals for the five-year span, highlighting the burden of non-communicable diseases (NCDs) as the primary contributors to mortality.

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Notably, ischemic heart disease remains the leading cause of death, with males exhibiting a significantly higher mean mortality rate 133.25 per 100,000 population compared to females 87.84 per 100,000 population. The 95% confidence intervals for ischemic heart disease were 87.58–88.10 for females and 132.88–133.62 for males, indicating a consistent and significantly higher mortality rate among males. The low standard deviations 0.30 for females and 0.42 for males further suggest a stable pattern in mortality rates over the study period.

For stroke, the mean mortality rates are comparable between females 50.38 per 100,000 population and males 49.54 per 100,000 population. The confidence intervals for females were 49.93–50.83, while for males, they were 48.86–50.22. Despite this similarity, the slightly higher standard deviation for males 0.78 compared to females 0.51 suggests greater variability in mortality rates among males.

Neoplasm-related mortality rates were lower overall, with females having a mean mortality rate of 37.48 per 100,000 (95% CI: 36.74–38.22) and males 33.55 per 100,000 (95% CI: 32.52–34.58). Similarly, for kidney disease, males showed a mean mortality rate of 25.63 per 100,000 (95% CI: 25.43–25.83), slightly lower than females at 27.24 per 100,000 (95% CI: 26.78–27.70).

Diabetes mellitus exhibited the lowest mortality rates, with males having a mean rate of 11.84 per 100,000 (95% CI: 11.53–12.15) compared to females at 9.86 per 100,000 (95% CI: 9.73–9.99). The low standard deviations for both genders across kidney disease and diabetes mortality rates indicate less variability in the data.

Figure 2 shows that according to WHO, the primary causes of death in Saudi Arabia from the year 2015 to 2019 are ischemic heart disease, stroke, neoplasms, kidney disease, and diabetes mellitus. The graph shows that ischemic heart disease is the leading cause with (220) deaths per 100,000. It is followed by stroke (100), neoplasms (70), kidney disease (52), and diabetes mellitus, with (21) deaths per 100,000 population.

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Statistical associations between cause of death and mortality rates

Table 3 presents Spearman’s rank correlation analysis results between two variables, “Death Cause” and “Mortality,” using a dataset of 25 data points. The analysis aimed to assess the relationship between causes of death and mortality rates within the dataset. The Spearman’s rho coefficient of approximately −0.981 suggests a strong negative correlation between “Death Cause” and “Mortality,” indicating that as the values of “Death Cause” change, the corresponding values of “Mortality” tend to change in the opposite direction. This shows that certain causes of death are associated with higher mortality rates while others are associated with lower mortality rates.

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The highly statistically significant p-value (0.000) indicates that the observed correlation is not due to random chance, indicating that the negative correlation is real and not a result of random fluctuations. This negative correlation could have important implications for understanding the relationship between specific causes of death and mortality rates, indicating that specific causes of death correlate with higher mortality rates. In comparison, others may be associated with lower mortality rates.

In Table 4 The regression analysis (Model 1) explores the relationship between the independent variable “Cause of Death” and the dependent variable “Mortality Rate.” The negative correlation coefficient (−0.917) indicates a strong inverse relationship between the cause of death and mortality rate. The coefficient of determination (R Square) suggests that approximately 84.1% of the variability in mortality rates can be explained by the cause of death. The adjusted R Square, accounting for model complexity, remains high at 0.834. The standard error of the estimate is 28.49313, reflecting the average deviation of observed values from predicted values. The model includes a constant term and emphasizes the significance of the cause of death as a predictor. Overall, the analysis provides valuable insights into the impact of the cause of death on mortality rates.

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The Coefficients Table outlines the relationships and significance of the variables in the regression model. The constant term (intercept) has a coefficient of 226.788, with a standard error of 13.364 and a highly significant t-value of 16.969 (p < 0.001), indicating that it contributes significantly to the model. The coefficient for “Death Cause” is −44.510, suggesting that there is an associated decrease in mortality rates for each unit change in the cause of death. This relationship is supported by a substantial standardized coefficient (Beta) of −0.917 and a highly significant t-value of −11.046 (p < 0.001). These results underscore the robust and negative association between the cause of death and mortality rates. In practical terms, this means that different causes of death considerably impact mortality, and the model provides a strong basis for predicting mortality rates based on the cause of death.

Discussion

This study investigated the primary factors contributing to mortality in Saudi Arabia and proposed effective healthcare management strategies to reduce mortality, prevent avoidable deaths, and optimize healthcare delivery. The findings highlight that adults aged 65 years and older exhibit the highest mortality rates, primarily due to the prevalence of chronic diseases in this age group [19]. Non-communicable diseases (NCDs), including ischemic heart disease, stroke, neoplasms, kidney diseases, and diabetes mellitus, were identified as the leading causes of mortality. Gender disparities were observed, with males consistently exhibiting higher mortality rates than females. Additionally, the findings indicate a strong negative correlation between causes of death (NCDs) and mortality rates, suggesting that as the ranking of causes of death changes, mortality rates tend to shift in the opposite direction. This implies that while certain NCDs contribute significantly to overall mortality, others have a comparatively lower impact. The negative correlation may also reflect advancements in NCD management, for example, Saudi Arabia’s tobacco control policies have contributed to a reduction in smoking-related diseases, while initiatives such as the National Diabetes Prevention Program and the RASHAKA Program have helped mitigate key NCD risk factors like obesity and physical inactivity [20,21,22,23,24].

This phenomenon can be attributed to progress in reducing risk factors and efficiently controlling non-communicable diseases among the population. Research has shown that public health interventions can reduce mortality rates associated with diseases such as cancer, diabetes, and cardiovascular disease. However, the results can differ based on the circumstances and the type of programs [25]. For instance, the outcomes of different cancer prevention and screening methods varied significantly, depending on the specific kind of cancer [26]. Nevertheless, programs can potentially enhance results and reduce medical expenses by motivating individuals with chronic illnesses to adhere to their outpatient treatment and attend scheduled sessions [27].

Correlations and implications

The findings indicate that risk factors for NCDs, including physical inactivity, obesity, unhealthy diets, diabetes, and hypertension, are significant contributors to mortality in Saudi Arabia [28]. Approximately two-thirds of the population have low levels of physical activity, half are obese, and one-quarter have diabetes. These risk factors strongly correlate with high mortality rates from cardiovascular diseases (CVD), particularly ischemic heart disease and stroke [28].

The results also show that ischemic heart disease emerged as the leading cause of mortality, with males experiencing significantly higher rates than females. Several biological, behavioral, and sociocultural factors contribute to this disparity. Biologically, men have a higher baseline cardiovascular risk due to differences in sex hormones, with testosterone being linked to higher blood pressure and unfavorable lipid profiles, increasing susceptibility to cardiovascular disease (CVD) [29]. Conversely, estrogen in females provides a protective effect against CVD by promoting better lipid metabolism and vascular function, potentially delaying the onset of heart disease [29].

Behavioral factors also play a significant role in gender-based mortality differences. Males in Saudi Arabia have higher rates of smoking and physical inactivity, both of which are major risk factors for CVD, lung disease, and metabolic disorders [28, 30]. The 2019 Global Adult Tobacco Survey reported that 19.8% of Saudi males use tobacco, compared to only 3.4% of females [31]. Similarly, dietary habits differ between genders, with men consuming higher amounts of processed and high-fat foods, which contribute to obesity and metabolic syndrome [32].

Additionally, health-seeking behaviors differ between genders, with men being less likely to engage in preventive healthcare, attend regular screenings, or seek medical attention early in disease progression, leading to delayed diagnosis and poorer health outcomes [33].

Furthermore, obesity and diabetes exacerbate the risk of acute coronary syndromes and heart failure, with Saudi patients developing these conditions nearly a decade earlier than those in industrialized nations [34, 35]. The early onset of these conditions contributes to prolonged exposure to complications and increased mortality. Patients with diabetes have a 2 to 4 times higher risk of developing cardiovascular disease (CVD) compared to the general population [36], and Saudi Arabia ranks in the top 10 nations in terms of diabetes prevalence, as reported by the International Diabetes Federation Diabetes Atlas (8th edition) [37]. A study found that the total occurrence of obesity was extremely high in Saudi Arabia [38]. Highlighting the ineffectiveness of obesity prevention measures in the monarchy. Furthermore, certain risk factors have been associated with the rising incidence of obesity in the nation, such as a sedentary lifestyle and a growing tendency to calorie consumption [28].

Addressing these risk factors through targeted interventions, such as promoting physical activity, encouraging healthier dietary habits, and improving diabetes management, is critical to reducing the burden of CVD and other NCDs. Public health initiatives must prioritize modifiable behaviors to significantly reduce mortality rates.

Comparison to Global Trends

The findings align with global trends, as NCDs account for 74% of deaths worldwide, according to the World Health Organization (WHO) [1]. Similar to global patterns, cardiovascular diseases, cancers, diabetes, and chronic respiratory diseases are the major contributors to mortality in Saudi Arabia. However, Saudi Arabia faces unique challenges, such as the earlier onset of CVD and its complications, attributed to the higher prevalence of diabetes, obesity, and physical inactivity. Comparisons to high-income countries such as Finland and Canada provide valuable benchmarks for improving Saudi initiatives. For instance, Finland’s population-wide strategies targeting smoking cessation, dietary improvements, and physical activity significantly reduced CVD mortality [39], while Canada’s comprehensive tobacco control policies and public education campaigns achieved similar outcomes [40].

Government initiatives

The Saudi government has implemented significant reforms under the Saudi Vision 2030 initiative, including the National Transformation Program, to improve healthcare quality and efficiency [28]. Specific measures targeting cardiovascular diseases (CVD) and other non-communicable diseases (NCDs) include the Saudi Guideline for Tobacco [20], the Obesity Control & Prevention Strategy 2030 [21], the RASHAKA Program promoting physical activity [22], the Saudi Hypertension Guideline [23], and the KSA National Strategy for Diet and Physical Activity [24]. Additionally, efforts to improve urban walkability through the City Humanization Initiative aim to encourage healthier lifestyles among the population [41].

These programs align with the World Heart Federation’s roadmap to reduce premature mortality from CVD by at least 25% by 2025 [42]. By benchmarking against successful international approaches, such as Finland’s North Karelia Project, which focused on population-wide interventions like smoking cessation, dietary improvements, and increased physical activity [39], and Canada’s integration of community-based interventions and tobacco control policies [40], Saudi Arabia can further strengthen its initiatives. Expanding preventive healthcare access, implementing stricter regulations on unhealthy food and beverages, and enhancing public awareness campaigns could support the country’s goals of reducing CVD mortality and achieving Vision 2030 objectives.

Challenges and recommendations

In Saudi Arabia, non-communicable diseases constitute the predominant disease burden [43]. The annual economic burden due to non-communicable diseases in Saudi Arabia is quantified at US$24.4 billion, with direct charges constituting 45% of this financial burden [44]. The strategic prioritization of healthcare expenditure in Saudi Arabia towards augmenting primary and preventive care is underscored by the pursuit of optimal efficiency and value for money. Primary Health Care Centers (PHCs) are critical in managing NCDs, yet their readiness to implement reforms requires further evaluation [45]. Specialized chronic disease clinics and the introduction of Electronic Health Records (EHRs) have improved care delivery; however, current EHR systems lack full functionality, such as providing patients complete access to their health information. Additionally, PHCs need enhanced resources to support nutrition and physical activity counseling [46]. Financial barriers can also hinder effective chronic disease management [47, 48]. Despite the Saudi government providing free healthcare to its citizens, the current funding model faces significant challenges in ensuring financial sustainability. The system is under immense pressure because of the rising costs associated with managing NCDs and the increasing demand for healthcare due to population growth and aging.

Reforms are being implemented as part of Saudi Vision 2030, emphasizing the introduction of private health insurance to alleviate the financial burden on the public healthcare system. However, the current private health insurance model focuses primarily on treatment rather than prevention, limiting its effectiveness in addressing NCDs comprehensively [49].

Saudi Arabia could adopt successful strategies from other high-income countries to address these challenges. For instance, France exempts individuals with chronic conditions from co-payments, ensuring financial accessibility [50]. Germany caps out-of-pocket healthcare costs at 1% of annual income for patients with chronic illnesses [51]. Implementing similar financial protections in Saudi Arabia, such as capped expenses or targeted subsidies, could enhance healthcare equity and improve outcomes for patients with NCDs. These measures would also align with Vision 2030’s goals of promoting health equity and improving population health outcomes.

Study Limitations

The study faced limitations due to the lack of comprehensive WHO data on mortality causes in Saudi Arabia beyond 2020. This gap restricts the ability to analyze recent trends and assess the impact of recently implemented public health initiatives.

Recommendations

Future research should utilize updated datasets from 2023 onward to further analyze the relationship between NCDs and mortality rates in Saudi Arabia. Additionally, evaluating the effectiveness of existing government initiatives and identifying gaps in healthcare delivery, particularly in primary and preventive care, is essential for achieving sustained improvements in health outcomes.

Conclusion

In conclusion, Various policy recommendations can be instituted to effectively manage healthcare and reduce mortality in Saudi Arabia. Healthcare promotion and preventive measures are essential in mitigating leading causes of death, particularly non-communicable diseases (NCDs). Implementing nationwide public health campaigns similar to Finland’s North Karelia Project and Canada’s ParticipACTION campaign can promote healthy dietary habits, physical activity, and tobacco cessation [39, 40]. Additionally, integrating mandatory health and wellness programs in schools and workplaces can foster lifelong preventive behaviors.

Age-specific and gender-specific interventions

Tailored age-specific and gender-specific interventions are essential to address the diverse health risks across populations. For older adults, strengthening geriatric healthcare services, increasing access to specialized screenings for chronic conditions, and expanding community-based rehabilitation programs can improve disease management and quality of life. For younger age groups, early health education, school-based obesity prevention programs, and adolescent mental health initiatives can help establish healthier behaviors from an early stage. Gender-specific interventions should target modifiable risk factors more prevalent in men and women. For example, cardiovascular health campaigns targeting high-risk male populations and expanded breast cancer screening and maternal health programs for women can ensure equitable healthcare access and improved health outcomes for both genders.

Strengthening primary healthcare and early detection programs

Early detection and screening programs should be expanded to target high-risk populations, with routine hypertension, diabetes, and obesity screenings integrated into primary healthcare services. Establishing mobile health clinics in rural and underserved areas can increase accessibility and enhance early diagnosis efforts. A national electronic health record (EHR) system should be developed to ensure real-time data sharing, enabling better chronic disease monitoring and follow-up care.

Expanding healthcare investment and health insurance contributions

Substantial governmental investment in medical research and innovation is needed to analyze disease trends, evaluate intervention effectiveness, and develop tailored prevention strategies. Increasing funding for artificial intelligence (AI)-driven predictive modeling can improve early detection and treatment personalization. Additionally, fostering academic-industry collaborations can drive advancements in pharmaceuticals, digital health solutions, and NCD prevention technologies.

Health insurance models must also evolve to prioritize preventive care rather than just treatment. Current private insurance schemes primarily focus on curative services, leaving preventive measures underfunded. Expanding insurance coverage to include routine screenings, lifestyle modification programs, and wellness incentives can reduce long-term healthcare costs while improving NCD outcomes. Learning from France’s exemption of chronic disease patients from co-payments and Germany’s capped out-of-pocket healthcare costs [52, 53], Saudi Arabia can introduce financial protections and incentives to encourage preventive healthcare utilization.

Implementing stronger regulatory and policy measures

Regulatory measures should be strengthened to improve food quality standards and limit unhealthy product availability. Imposing higher taxes on sugar-sweetened beverages, trans fats, and processed foods, while subsidizing nutritious alternatives, can incentivize healthier dietary choices. Additionally, stricter tobacco control policies, including higher taxation, expanded smoke-free zones, and aggressive anti-smoking awareness campaigns, are necessary to further reduce smoking-related mortality. Improving urban infrastructure for active transport, such as walkable city designs and dedicated cycling lanes, can also encourage physical activity and obesity prevention.

By implementing these comprehensive, evidence-based strategies, Saudi Arabia can effectively reduce NCD-related mortality, strengthen preventive healthcare, and align with the Saudi Vision 2030 health objectives.

Data availability

The datasets analyzed during the current study are available in The General Authority of Statistics. Mortality Rates in Saudi Arabia. Saudi Arabia Statistics. https://database.stats.gov.sa/home/indicator/544, and The World Health Organization. (Global Health Observatory Data: Leading Causes of Death. World Health Organization. https://www.who.int/data/gho/data/themes/mortality-and-global-health-estimates/ghe-leading-causes-of-death.

Abbreviations

NCD:

Non-communicable disease

GASTAT:

The General Authority for Statistics

WHO:

The World Health Organization

DALY:

Disability-adjusted life years

CCM:

Chronic Care Model

CVD:

Cardiovascular disease

PHC:

Primary Healthcare Center

MOH:

Ministry of Health

EHR:

Electronic Health Record

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