ABSTRACT
Background and Aims
Air pollution refers to the presence of one or more pollutants or compounds in outdoor or indoor air in concentrations and durations that can harm human health, plants, animals, or possessions, or lead to undue disruption of a person's ability to enjoy their life or belongings comfortably. This study examines the economic burden of diseases caused by air pollution in Iran, highlighting the financial impacts on the healthcare system and the broader economy.
Methods
This descriptive cross‐sectional study, conducted in Iran in 2022, employed an incidence‐based approach to estimate the economic burden of air pollution‐related diseases from a societal perspective. The analysis involved calculating direct costs using the top‐down method and indirect costs through the human capital approach.
Results
The average direct medical costs of diseases caused by air pollution per patient were $4485.55. The average direct non‐medical cost per patient was estimated at $758.11. Notably, the cost of accompaniment accounted for the highest proportion among direct non‐medical costs, with an average cost of $292.21 per patient. The average indirect cost per patient was estimated at $1713.03.
Conclusion
The fight against air pollution‐related diseases is not just a public health issue but also an economic necessity. By tackling this challenge proactively, societies can pave the way for cleaner, healthier, and more prosperous futures.
Keywords: air pollution, direct cost, indirect cost, Iran
1. Introduction
Air pollution and its associated impacts have attracted significant attention from researchers in recent years. It is recognized as one of the primary contributors to environmental degradation and ranks as the leading environmental risk factor in terms of disease burden [1]. Prolonged exposure to polluted air has profoundly adverse effects on human health. In addition to contributing to premature mortality, air pollution plays a major role in the development of various health conditions, including cardiovascular diseases, bronchitis, respiratory disorders, and certain types of cancer [2]. Cancer is a leading cause of mortality worldwide [3].
Air pollution stems from a range of harmful environmental agents, including particulate matter (both coarse and fine), nitrogen oxides, ozone, sulfur dioxide, and black carbon. Among these, fine particulate matter with a diameter of less than 2.5 microns (PM2.5) is particularly hazardous. Due to its small size, PM2.5 can penetrate deep into the lungs, reaching the alveoli and causing serious health issues [4]. According to data from the Global Burden of Disease (GBD) study, long‐term exposure to PM2.5 was the fifth leading risk factor for premature death in 2015, contributing to 4.2 million deaths and 103.1 million disability‐adjusted life years (DALYs) worldwide. This represents 7.6% of total global deaths and 4.2% of global DALYs [5].
In 2019, 99% of the global population lived in areas that failed to meet the World Health Organization's (WHO) Air Quality Guidelines. The combined effects of outdoor and indoor air pollution have been linked to approximately 6.7 million premature deaths annually [6]. Data from the GBD study highlights environmental air pollution as a major contributor to the global disease burden, particularly in low‐ and middle‐income countries, with South and East Asia being the most affected regions [7]. Among these, China and India consistently rank among the highest in pollution levels and associated mortality. In 2019 alone, air pollution was responsible for an estimated 1.67 million deaths in India, accounting for 17.8% of the country's total mortality [8].
Although air pollution poses a global threat, its effects are unevenly distributed, even among BRICS countries—Brazil, Russia, India, China, and South Africa—despite their similar economic and demographic profiles [9]. This inequality highlights the varying degrees of exposure and susceptibility to health risks from air pollution across different regions and populations within these nations. Recognizing these disparities is essential for crafting targeted strategies and policies to reduce the environmental and health‐related consequences of air pollution. Although air pollution is a common global issue, its impacts are not distributed evenly—even among countries with comparable levels of development [10].
In these countries, reducing air pollution levels could significantly alleviate the burden of diseases such as stroke, heart disease, lung cancer, and both chronic and acute respiratory illnesses, including asthma. According to the WHO, in 2019, premature deaths caused by environmental air pollution were primarily due to ischemic heart disease and stroke (37%), chronic obstructive pulmonary disease (COPD) (18%), lower respiratory infections (23%), and respiratory tract cancers (11%) [6]. Taking into account the disabilities and challenges faced by patients that result in higher hospitalization rates, there is growing concern about the substantial economic burden on the healthcare system, which categorizes heart disease as an expensive condition in various countries [11].
Improving air quality—particularly in heavily polluted regions like China and India—is essential to reduce mortality associated with PM2.5 exposure. Demographic and epidemiological projections suggest that, to maintain the current PM2.5‐related mortality rate (deaths per 100,000 people annually), average PM2.5 concentrations should be reduced by 20%–30% over the next 15 years. In the long term, implementing effective strategies to improve air quality in the world's most polluted areas could prevent hundreds of thousands of premature deaths each year [12].
Air pollution has become a significant public health and societal concern in urban environments because of its severe effects on human well‐being. The World Bank reports that over 7 million premature deaths annually are attributed to air pollution‐related illnesses, representing 12.5% of total deaths worldwide [13].
In Iran—a developing country—air pollution levels have gradually increased since industrialization began in the 1970s. Over the past two decades, major cities such as Tehran, Mashhad, Tabriz, Isfahan, Ahvaz, and Arak have experienced alarmingly high levels of air pollution [14]. According to World Bank estimates, the health and economic costs of air pollution in Tehran alone amount to approximately $2.6 billion annually [15]. In 2019, the mortality rate attributable to environmental air pollution in Iran was reported at 40.74 deaths per 100,000 people [16]. The GBD study further estimated that the mortality rate due to ambient particulate matter pollution in Iran stood at 52.49 per 100,000 individuals—close to the global average of 53.52 [5]. A study by Bayat et al. [17] attributed 7146 deaths in adults over the age of 25 in Tehran to PM2.5 pollution, with ischemic heart disease, stroke, lower respiratory infections, COPD, and lung cancer identified as the leading causes of death.
Consequently, air pollutants have had a significant impact on public health, contributing to a wide range of diseases and resulting in substantial healthcare expenditures and economic losses. According to the World Bank, diseases related to urban air pollution cause annual damage equivalent to $260 million, or approximately 0.023% of Iran's gross domestic product (GDP). The World Bank further estimates that mortality linked to urban air pollution costs around 5.1 trillion rials annually, with disease prevalence and disease‐related damages costing approximately 4.1 trillion and 2.1 trillion rials, respectively [18]. Moreover, research conducted in 2013 indicated that air pollution was responsible for 14% of stroke‐related deaths in Iran. The total annual economic cost of air pollution was estimated at $1.81 billion, or 14.429 trillion rials—equivalent to 1.6% of the country's GDP [19].
Given the upward trend in air pollution and its considerable impact on mortality and chronic diseases, a deeper understanding of pollution‐related illnesses and their role in public health outcomes is essential. Equally important is the investigation of strategies to control pollutant emissions. In light of the significant economic and health implications, this study aims to identify and assess the direct and indirect costs of air pollution‐related diseases in Iran during the 2021 period. The findings will provide valuable insights into the economic burden of air pollution, offering policymakers and stakeholders evidence to inform the development of effective interventions.
By quantifying the economic impact of air pollution‐related diseases, this study contributes to the existing body of literature and provides a foundation for evidence‐based policymaking. Ultimately, the results can guide sustainable development initiatives, air quality improvement programs, and efforts to protect public health and economic well‐being in Iran.
2. Methods
2.1. Study Design and Setting
This study employed a cross‐sectional descriptive design to assess the economic burden of diseases resulting from air pollution in the metropolis of Mashhad, Iran, during the year 2022.
Mashhad, Iran's second‐largest city and the capital of Razavi Khorasan Province, is renowned for its rich historical, cultural, and religious significance. As a major religious destination attracting millions of pilgrims annually, the city also faces serious environmental challenges, the chief of which is air pollution. The primary sources of air pollution in Mashhad include industrial activities, vehicular emissions, and unfavorable meteorological conditions. Rapid population growth and urban expansion in recent years have further deteriorated the city's environmental quality, resulting in a marked decline in air quality. This has had substantial adverse effects on public health, particularly among vulnerable groups such as the elderly and individuals with cardiovascular and respiratory conditions. Consequently, air pollution has emerged as a critical environmental concern in Mashhad, necessitating urgent attention in public policy and health intervention strategies.
A prevalence‐based approach was employed from a societal perspective to assess the economic impact of air pollution‐related illnesses. This method enables a comprehensive evaluation of the health‐related economic burden at the population level, offering valuable insights for policymakers and stakeholders.
2.2. Sample Selection
The study population comprised 3832 patients diagnosed with air pollution‐related diseases, specifically including various cardiovascular and respiratory conditions. Participants were identified through diagnostic codes recorded in their medical records, ensuring a systematic and standardized approach to case selection. Data collection was conducted over a 92‐day period during the year, specifically targeting days when the air pollution index exceeded 100—classified as “crisis days.” These days were selected to capture periods of heightened air pollution, during which acute health effects are more likely to occur.
A cross‐sectional descriptive design was chosen for this study due to its appropriateness in estimating the economic burden of disease within a defined population at a specific point in time. This design facilitates the assessment of health‐related costs associated with air pollution exposure during periods of elevated risk, such as days with high pollution levels. A prevalence‐based approach—commonly employed in health economics—was used to quantify the current burden of existing disease cases, rather than tracking new incidences over time. Given the availability of health and hospital data corresponding to designated “crisis days,” during which the air quality index exceeded 100, this approach was both practical and methodologically sound for estimating direct and indirect costs from a societal perspective. Moreover, it aligns with previous burden‐of‐disease research that has linked pollution exposure to adverse health outcomes in urban environments.
2.2.1. Types of Costs
In this method, costs are categorized into three main groups, including the following: direct medical costs, direct non‐medical costs, and indirect costs (resulting from lost productivity).
Direct medical costs: These costs encompassed a range of medical services, including medical visits, consultations, medications, radiology, laboratory tests, CT scans, sonography, electrocardiograms (ECGs), MRIs, nursing services, and hospital accommodation expenses. Initially, the average direct cost of each patient was estimated through a survey study, and we extracted direct medical cost data from patients' hospital records.
Direct non‐medical costs: Direct non‐medical costs included expenses related to companionship, home care, transportation, and time allocated by companions for patient care. Study participants or their companions provided these cost estimates through telephone interviews, using a questionnaire designed for this purpose.
The questionnaire for determining direct costs consisted of three main sections: The first section pertained to demographic information, including age, gender, marital status, education, occupation, place of residence, head of household, and insurance coverage. The second section addressed direct medical costs, including home care, time required for medical visits and medication purchases (in hours), and transportation within and outside the city, accommodation, and companionship. The third section of non‐medical direct costs encompassed daily wage rates, days of absence from work or sick leave (in days) for both the patient and the accompanying person, and the duration of hospitalization (in days). This questionnaire was designed based on previous studies, and its validity was confirmed through interviews with epidemiologists, health economists, and specialized medical experts. A pilot study was conducted, and based on its results, the questionnaire underwent revision.
Indirect costs: Indirect costs refer to productivity losses resulting from both disability and premature death. To estimate the reduction in productivity due to disability, the total number of hospitalization days for all patients was multiplied by the average daily wage. Information on work absenteeism was obtained through expert interviews and patient file reviews. For cost calculations, the 2022 minimum daily wage for unemployed individuals and the average wage for employed individuals were used. Additionally, the absenteeism costs of patient companions were included, based on the minimum daily wage rate.
The estimation of direct and indirect costs was adapted from previous studies on the economic burden of both communicable and non‐communicable diseases. These methodologies typically include calculations of out‐of‐pocket medical expenses, ancillary healthcare‐related costs, and indirect costs such as loss of productivity, absenteeism, and income loss at the household level [20, 21].
2.3. Data Analysis
To calculate the average direct medical cost of each patient, the amount of service use was multiplied by the tariff or price of that service in 2022.
To estimate indirect costs, the potential reduction in productivity due to disability was calculated by multiplying the average days of hospitalization by the number of patients by the average daily wage. In addition, by using the estimation of incidence and prevalence, the total number of days absent from work of patients was predicted in 2022. Then, the number of days absent from work was multiplied by the average daily wage in 2022, and the cost of absenteeism due to illnesses attributed to air pollution (ischemic heart disease, lung cancer, and COPD) was estimated. The employment rate was extracted from the available data from the statistics center and previous studies. While the unemployed are seemingly unpaid, given that they are still engaged in daily tasks (such as housekeeping), the 2022 minimum rate approved by the Ministry of Labor was considered for them. For working people, the average wage rate of the country's employees in 2022 is considered. Since one of the family members usually accompanies the patient to the treatment centers, the cost of the absence of the patient's companions from the workplace was also calculated. But for these companions, similar to unemployed people, the minimum daily wage was considered.
Total direct and indirect costs were collected to estimate the total cost of each patient. Then the total cost of each patient was multiplied by the number of studied samples, and the economic burden of the entire studied sample was estimated. To facilitate cost comparisons in the study, it was converted using the Purchasing Power Parity index to US dollars in 2022. Data analysis was done using Excel 2016 and Stata 16 software.
2.4. Ethical Considerations
This cross‐sectional study was conducted in accordance with the ethical standards of the relevant institutional ethics committee. Informed consent was obtained from all participants before their inclusion in the study.
3. Results
Table 1 summarizes the demographic characteristics of the 3832 study participants. Of these individuals, 1533 (40%) were female, while 2299 (60%) were male. Notably, 3793 patients were covered by health insurance, while 39 patients did not have health insurance coverage. Among those insured, 67% were the heads of their households. The average age of the participants was 62.35 years, with their length of hospitalization varying from 1 to 15 days.
Table 1.
Demographic characteristics of study participants.
| Variable | Number (%) |
|---|---|
| Gender | |
| Female | 1533 (40%) |
| Male | 2299 (60%) |
| Household head | |
| Yes | 2567 (67%) |
| No | 1265 (33%) |
| Insurance | |
| Yes | 3793 (99%) |
| No | 39 (1%) |
| Age | |
| Mean (standard deviation) | 62.35 (8.54) |
| Average length of stay | |
| Mean (standard deviation) | 4.8 (4.33) |
Table 2 presents the direct medical costs associated with air pollution‐related diseases, categorized by medical service type and sector (governmental vs. private). The costs are denoted in dollars, and the percentage represents the proportion of each service's cost relative to the total direct medical costs within each sector.
Table 2.
Direct medical costs by medical service and sector (governmental vs. private).
| Service type | Governmental | Private | Cost ($) | % |
|---|---|---|---|---|
| Operating room technical | 182.96 | 1280.75 | 512.3 | 11 |
| CCU hoteling | 202.37 | 607.1 | 323.78 | 7 |
| ICU hoteling | 255.48 | 1277.38 | 562.05 | 13 |
| Regular hoteling | 157.18 | 471.54 | 251.49 | 6 |
| Surgeon | 458.17 | 2290.83 | 1007.96 | 23 |
| Surgical assistance | 33.63 | 168.13 | 73.98 | 2 |
| Anesthesia | 47.29 | 47.29 | 47.29 | 1 |
| Drugs | 242.66 | 242.66 | 242.66 | 5 |
| Medical consumables | 906.34 | 906.34 | 906.34 | 20 |
| Laboratory | 84.23 | 336.9 | 160.03 | 4 |
| Imaging | 35.84 | 143.36 | 68.1 | 2 |
| ECG | 18.48 | 73.94 | 35.12 | 1 |
| Nursing services | 32.6 | 130.4 | 61.94 | 1 |
| Doctor's visit | 31.56 | 220.92 | 88.37 | 2 |
| Counseling visit | 12.91 | 90.35 | 36.14 | 1 |
| Other medical procedures | 35.86 | 179.3 | 78.89 | 2 |
| Other cost | 7.66 | 30.65 | 14.56 | 0 |
| Total | 2752.87 | 8528.48 | 4485.55 | 100 |
These results illustrate the distribution of direct medical costs across various healthcare services and sectors. Further interpretation and policy implications can be drawn from these findings.
Table 3 illustrates the direct non‐medical costs associated with air pollution‐related diseases. The average direct non‐medical cost per patient was estimated at $758.11. Notably, the cost of accompaniment accounted for the highest proportion among direct non‐medical costs, with an average cost of $292.21 per patient.
Table 3.
Direct non‐medical costs.
| Cost type | Cost ($) | % |
|---|---|---|
| Accompaniment | 292.21 | 39 |
| Transportation | 199.92 | 26 |
| Accommodation | 133.45 | 18 |
| Home care | 76.88 | 10 |
| Time | 55.65 | 7 |
| Total | 758.11 | 100 |
Based on Table 3, the average direct non‐medical cost per patient was approximately $758.11.
Table 4 presents the indirect costs per patient associated with air pollution‐related diseases. These costs include the cost of lost productivity due to patient absence from work, premature death, and accompanying the patient. The average indirect cost per patient was estimated at $1713.03.
Table 4.
Indirect costs per patient.
| Cost type | Cost ($) |
|---|---|
| Cost of lost productivity – Absence from work | 1103.44 |
| Cost of lost productivity – Premature death | 194.14 |
| Cost of lost productivity – Accompaniment | 415.45 |
| Total indirect cost per patient | 1713.03 |
Based on the findings presented in Table 5, the average direct medical cost of air pollution‐related diseases was $4485.55, the average direct non‐medical cost was $758.11, and the average indirect cost was $1713.03. The estimated economic burden in the studied sample was $388,670,307.
Table 5.
Economic burden of air pollution‐related diseases.
| Direct medical cost | Indirect cost | Direct non‐medical cost | Total cost | Economic burden ($) |
|---|---|---|---|---|
| 4485.55 | 1713.03 | 758.11 | 6956.69 | 388,670,307 |
Based on the examination of the number of patients on clean days (8277 patients for 273 days) and critical days (3832 patients for 92 days), it was found that 37.5% of them are attributed to air pollution among all patients with diagnostic codes under study. Considering that the total number of patients with diagnostic codes under study in the country was 148,986, therefore, the number of patients attributed to air pollution in Iran is 55,870 patients.
4. Discussion
The findings of this study underscore the substantial economic burden posed by air pollution‐related diseases in Iran. Air pollution remains a critical environmental challenge with far‐reaching implications for both public health and economic sustainability. Accurately understanding the associated economic costs is essential for policymakers, healthcare providers, and the broader community to develop effective mitigation strategies.
The demographic profile of the study participants provides valuable context. With an average age of 62 years among those affected, the results highlight the heightened vulnerability of older adults to the adverse health effects of air pollution. Furthermore, while the majority of participants were insured, the findings raise important questions regarding healthcare access for uninsured populations, pointing to potential inequities in treatment availability and financial protection.
Direct medical costs represent a significant share of the overall economic burden. The observed variations in costs across different healthcare services and sectors, as detailed in Table 2, emphasize the need for more efficient resource allocation and the implementation of cost‐effective healthcare interventions. Notably, the higher expenses associated with private healthcare services may impose a greater financial strain on patients and their families, reinforcing the importance of public health initiatives aimed at reducing air pollution exposure and associated disease incidence.
Direct non‐medical costs, outlined in Table 3, also contribute meaningfully to the total economic impact. Among these, the cost of patient accompaniment—including transportation, lodging, and home care—is particularly significant. These non‐medical expenses reflect the broader socioeconomic consequences of air pollution, affecting not only the patients but also their caregivers and households.
Indirect costs, presented in Table 4, include productivity losses due to patient absenteeism, premature mortality, and time spent accompanying patients. These costs extend beyond the healthcare system, with broader societal implications for economic productivity and labor force stability. Collectively, the results illustrate how air pollution imposes a multifaceted economic burden that compromises both public health and national economic resilience.
The estimated economic burden of air pollution‐related diseases in the studied sample is considerable, totaling $388,670,307. Extrapolating these findings to the national level, it is estimated that approximately 55,870 patients in Iran are affected by air pollution‐related diseases, signaling a substantial economic challenge at the national scale.
The studies conducted by Lu et al. [22], Pandey et al. [23], Xu et al. [24], Han et al. [25], Li et al. [26], and Liao et al. [27] provide valuable insights into the multifaceted impacts of air pollution on health and the economy, reinforcing the urgent need for comprehensive policies to address this critical issue. Recent studies have increasingly emphasized the economic dimensions of air pollution, alongside its well‐established health effects, further underlining the importance of prioritizing air quality improvement.
The study by Lu et al. evaluated the main pollutants (SO2, NO2, O3, and PM10) from 2010 to 2013 and found that air pollution led to high mortality, with the highest number of deaths occurring in 2013. The economic burden associated with health complications resulting from air pollution was calculated to be between US$14.8 and US$25.3 billion, equivalent to 1.4%–2.3% of the region's GDP. Urban areas showed higher mortality rates from air pollution than rural areas. The study calls for stricter pollution control policies to reduce health impacts and economic losses [22].
One of the most notable studies, implemented based on the framework of the GBD Study 2019, examines the broad health and economic consequences of air pollution at the state level in India. The findings revealed that in 2019, approximately 1.67 million premature deaths were attributed to air pollution, accounting for 17.8% of all deaths in the country. The majority of these deaths were due to exposure to ambient particulate matter and household air pollution. From an economic perspective, the losses due to premature deaths and morbidity associated with air pollution in India were estimated at $36.8 billion in 2019, which represents 1.36% of the country's GDP. The economic loss as a percentage of state GDP varied significantly, with the highest losses observed in states with lower per capita GDP, such as Uttar Pradesh, Bihar, Rajasthan, Madhya Pradesh, and Chhattisgarh. Additionally, Delhi experienced the largest individual economic burden stemming from air pollution [23].
Xu et al. demonstrated a declining trend in economic health losses related to PM2.5 pollution in Beijing, attributing it to improved air quality measures. From 2013 to 2018, the economic loss caused by fine particulate matter pollution in Beijing, Tianjin, and Hebei showed a decreasing trend year by year. The health economic losses in Beijing during these years were 3.815, 4.177, 4.090, 3.818, 2.567, and 2.031 billion yuan, respectively. In 2013, Hebei Province recorded the highest health‐related economic loss due to air pollution, reaching 13.719 billion yuan, which represented 0.51% of its GDP. In comparison, the lowest loss was observed in Tianjin in 2018, where the economic impact was 10.0 billion yuan, equivalent to 0.05% of the region's GDP. Other health economic losses in Hebei over the years were 11.850, 7.423, 7.216, 6.499, and 4.124 billion yuan [24].
Han et al. extended our understanding of the economic losses attributable to environmental pollutants in developing regions. This study, which estimates the health effects of major pollutants (PM10, SO2, and NO2) from 2011 to 2016, found significant mortality due to air pollution, with total short‐term all‐cause mortality reaching 48,098. The economic loss from these health effects was estimated at 40,555 million yuan, accounting for 2.86% of the region's GDP. Urbanization, industrialization, and residents' income were identified as key factors driving air pollution‐related health damage. The study concludes that the health burden from air pollution in rapidly developing regions is considerable and calls for stricter regulations to mitigate these effects. Their study revealed that air pollution led to a significant health burden, constituting 2.86% of the region's GDP. The findings emphasize the importance of socioeconomic factors in shaping the health and economic impacts of air pollution [25].
Li et al. highlighted the substantial health and economic toll of PM2.5 pollution in China. The study estimated 1.06 million PM2.5‐related deaths, accounting for 10.9% of all deaths in the country, with stroke and ischemic heart disease being the leading causes. The economic losses amounted to 0.95% of the GDP in 2016, underscoring the urgency of air quality improvement. The economic losses were estimated at 705.93 billion yuan, or 0.95% of the GDP in 2016. There were significant spatial variations in the health burden and economic loss, mainly in regions with higher PM2.5 levels or population density [26].
Finally, Liao et al. provided crucial insights into the health and economic implications of PM2.5 pollution in Gansu Province. Their findings revealed that PM2.5 pollution led to significant health endpoints and economic losses, equivalent to 5.93% to 6.45% of the region's GDP. Urbanization and industrialization were identified as key factors driving these economic losses [27].
These studies collectively emphasize the severe health and economic consequences of air pollution, with a particular focus on the role of PM2.5 pollution. Urgent measures are needed to reduce air pollution levels, transition to cleaner energy sources, and implement stricter regulations to safeguard public health and mitigate economic losses. These findings underscore the critical importance of addressing air pollution as a priority in environmental and public health policies.
These findings emphasize the urgency of comprehensive strategies to mitigate air pollution and its associated health and economic impacts. Policy measures aimed at reducing pollution sources, promoting clean energy alternatives, and enhancing public awareness can contribute to substantial cost savings in healthcare and improved overall well‐being. Furthermore, interventions to improve access to healthcare services and provide financial support to affected individuals and families may help alleviate the financial burden of air pollution‐related diseases.
4.1. Limitation
This study, while providing valuable insights into the economic burden of air pollution‐related health outcomes, has certain limitations. First, the analysis relies on secondary data and assumptions in exposure–response functions, which may not fully capture local variations in pollutant exposure or health response. Second, the study does not include indirect costs such as lost productivity, long‐term disability, or broader social impacts, potentially underestimating the full economic burden. Future research could benefit from incorporating more localized air quality and health data, using longitudinal methods, and exploring the economic benefits of specific policy interventions. Additionally, examining the combined effects of multiple pollutants and including vulnerable populations such as children and the elderly may yield a more comprehensive understanding of the health and economic impacts of air pollution.
5. Conclusion
This study quantifies the substantial economic burden imposed by air pollution‐related diseases in Iran. The findings highlight that direct medical costs, indirect costs, and non‐medical expenses collectively constitute a significant share of national economic losses. Comparative analysis with international studies reveals that the proportion of GDP lost due to air pollution in Iran aligns with or exceeds levels observed in other developing countries, underscoring the pervasive and transboundary nature of this public health threat.
Given the multispectral implications of air pollution, an integrated policy response is warranted, one that bridges environmental regulation, healthcare system strengthening, and socioeconomic support mechanisms. Interventions targeting emission source control, adoption of cleaner technologies, and public health risk communication are critical for mitigating both the health burden and the long‐term economic impacts.
Moreover, the evidence supports prioritizing vulnerable populations, particularly those with pre‐existing cardiopulmonary conditions, within air quality and health equity policies. Future studies should adopt longitudinal approaches, incorporate broader geographic and temporal scopes, and include co‐benefit assessments of mitigation strategies. In conclusion, addressing air pollution is not only a public health imperative but also a strategic economic investment towards sustainable national development.
Author Contributions
Nikta Shobeiri: methodology, validation, formal analysis. Amin Adel: investigation, software, formal analysis. Asma Rashki Kemmak: writing – original draft, methodology, data curation, supervision, resources.
Ethics Statement
This study was supported by Mashhad University of Medical Sciences (with ethical code IR.MUMS.REC.1402.102). All participants were fully informed about the objectives, methods, and potential risks of the study before enrollment and provided their written informed consent. Participation was entirely voluntary, and participants had the right to withdraw from the study at any time without any pressure or consequences. All personal information and collected data were treated confidentially and used solely for research purposes.
Consent
The authors have nothing to report.
Conflicts of Interest
The authors declare no conflicts of interest.
Transparency Statement
The lead author, Asma Rashki Kemmak, affirms that this manuscript is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that any discrepancies from the study as planned (and, if relevant, registered) have been explained.
Acknowledgments
The support provided by Mashhad University of Medical Sciences in conducting this study is highly acknowledged. The authors received no specific funding for this work.
Shobeiri N., Adel A., and Rashki Kemmak A., “Economic Burden of Diseases Caused by Air Pollution in Iran: A Cross‐Sectional Study,” Health Science Reports 8 (2025): 1‐8. 10.1002/hsr2.71229.
Data Availability Statement
Data sharing is not applicable to this article as no new data were created or analyzed in this study.
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Associated Data
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Data Availability Statement
Data sharing is not applicable to this article as no new data were created or analyzed in this study.
