What’s Known

Worldwide, the economic burden of asthma is immense. Due to gender bias in healthcare, it is recommended to develop gender-specific evidence-based guidelines.

What’s New

Laboratory and diagnostic tests pose substantial costs to male asthma patients. Regression coefficients of the structural equation modeling (SEM) predicted a significant association between severe asthma and indirect costs in the three distinct explanatory models (total, female, and male participants).

Introduction

Bronchial asthma is the most prevalent non-communicable disease worldwide with long-term social impact and immense economic burden. The higher the prevalence and years lived with disability (YLD) due to bronchial asthma, the lower the rate of healthy life expectancy (HALE). Such a negative correlation imposes a huge economic burden on society due to days lost from work/school, impairment-related productivity loss, and increased cost of medical care. ^{1 - 3} According to data published by the European Respiratory Society (ERS), the total economic burden of asthma in Europe in 2011 was approximately €33.9 billion, of which €14.4 billion was related to indirect costs (productivity loss due to absenteeism and presenteeism, and early retirement on health grounds). The remaining expenditure was related to medication costs and the cost of primary care. ⁴ Based on a pooled sample, in 2013, 7.3% of the population in the United States had asthma at a total cost of $81.9 billion. ⁵

The prerequisite for good public health policy decision-making in patients with asthma is a good understanding of the disease and access to accurate data. From the societal perspective, the latter portrays the scale, severity, and consequences of the disease. It also facilitates the development of a country-specific strategy to manage and control asthma. ^{5 , 6} In Iran, the prevalence of asthma in 2015-2016 was reported at 8.9% of the total population. ⁷ However, only a few studies provided an estimate of the social impact and economic burden of the disease; all based on self-administered questionnaires. ^{6 , 8 , 9}

Cost of illness (COI) studies, based on the incidence or prevalence of a disease, are an evaluation technique to identify and measure the direct, indirect, and intangible costs of the disease to society. It provides an approximation of the opportunity cost of lost resources due to illness. The method includes three phases (identification, measurement, and valuation of resources) to estimate the average cost imposed by an illness in a given period of time. ^{10 , 11}

Gender bias is reported in healthcare across the board, from health status to prescribing drugs, disease type, and even in medical research. ¹² For the sake of good practice, it is therefore important to develop gender-specific evidence-based guidelines. In this context, the present study aimed to evaluate direct medical and non-medical costs as well as indirect expenditures in patients with asthma. In addition, based on a method proposed in a previous study, ¹³ the effect of sex and asthma severity on direct and indirect costs was assessed.

Materials and Methods

Prevalence-based COI and longitudinal observational studies were conducted between 2017 and 2018 at various respiratory clinics in Tabriz (Iran). Patients diagnosed with asthma by a pulmonologist were recruited regardless of sex and age. The only inclusion criterion was the diagnosis of asthma according to the European Thoracic Society/American Thoracic Society (ERS/ATS) criteria. ¹⁴ Patients with any other respiratory disease or unwillingness to participate in the study were excluded. The sample size was calculated based on a minimum effect size of r=0.18 with α=0.05 for a targeted 90% power using G*Power software, version 3.1.2. ¹⁵ A sample size of 320 participants was estimated. However, considering 20% attrition probability and a design effect of 1.5, 621 patients were recruited. The recruited patients were grouped based on the severity of asthma, namely intermittent, mild persistent, moderate persistent, and severe persistent. ¹⁶ They were followed over one year period after which the total COI was estimated.

The study was approved by the Ethics Committee of Tabriz University of Medical Sciences, Tabriz, Iran (code: IR.TBZMED.REC.1397.801). Written informed consent was obtained from adult patients or parents of the participating children.

Data Collection

Costs were estimated using the bottom-up and human capital approaches. The three phases of identification, measurement, and valuation of resources were used to estimate the average cost imposed by the illness. ¹⁰ To this end, the Persian version of the work productivity and activity impairment in patients with asthma (WPAI-AQ) questionnaire was used. The reliability and validity of the Persian version of the questionnaire were already confirmed in a previous study. ¹⁷ The questionnaire includes 34 items divided into three sections. The first section includes items related to demographic and anthropometric variables, such as socioeconomic, smoking, and insurance status. The second section covers asthma severity such as grade and symptoms. Finally, the third section includes items related to direct medical and non-medical costs as well as indirect expenditures. Direct medical costs include the actual costs to patients and those covered by insurance companies, e.g., physician office visits, radiology, laboratory, and diagnostic tests (spirometry, oximetry), prescription medication, emergency visits, and hospitalization. Depending on the type of health care insurance, 30%-70% of the costs are covered by insurance companies. Non-medical costs include payments by patients for travel, lodging, and transportation. In addition, indirect costs were also addressed in the WPAI-AQ questionnaire and covered the costs related to the effect of the disease on the quality of life due to impairment, productivity loss due to activity impairment, and days lost from work/school.

The participants were instructed by an expert on how to complete the self-report WPAI-AQ questionnaire. They were requested to complete the questionnaire quarterly for one year, either in one of the clinics or through a telephone interview.

Cost Calculation

Based on the data published by the International Monetary Fund (IMF), gross domestic product (local currency unit) (GDP-LCU) was divided by active population to calculate indirect costs, which is a key parameter for policymakers in developing health strategies. ^{18 - 20}

Mathematical Model and Variables

Structural equation modeling (SEM) was used to determine the predictive relationships between latent and observed variables. SEM encompasses a measurement model and a structural model. It can be used for confirmatory models, as it provides model-fit information on the consistency of the hypothesized conceptual model data to find a causal relationship between variables and theoretical structures. ^{21 - 23} Accordingly, we examined the relationship of direct and indirect costs (latent variables) with the corresponding indicators (observed variables). Indicators included medical and non-medical costs (direct costs), days lost from work/school, impairment-related productivity loss (indirect costs), the stage of asthma, and the sex of the participants.

Statistical Analysis

Quantitative data were expressed as mean with 95% confidence interval (CI). The unpaired t test was used to examine the difference between male and female patients in terms of asthma severity. The analysis of variance (ANOVA) was used to compare asthma severity between the patients.

To develop the model, normal distribution of univariate and multivariate variables was initially examined using Kolmogorov-Smirnov and Mardia’s tests with skewness and kurtosis indices, respectively. Then, bivariate correlation and confirmatory factor analysis (CFA) were performed. SEM was used as the theoretical structure. The missing data ranged from 1.81% to 13.21%, for which the maximum likelihood method was used. ²⁴ To assess the relationship between variables, 5% significance level, the goodness of fit, comparative fit index (CFI) (cutoff≥0.95), root mean square error of approximation (RMSEA) (cutoff≤0.06), and standardized root mean square residual (SRMR) (cutoff≤0.08) were used. The data from SEM were presented using the regression coefficient β with 95% CI. Data were analyzed using Stata software, version 15.0 (StataCorp LLC, College Station, TX, USA). P<0.05 was considered statistically significant.

Results

Baseline characteristics of the patients are presented in table 1. More than 70% of the patients were in the category of mild (47.5%) and moderate persistent (28.9%) asthma. Furthermore, 60% of the patients were non-smokers, and more than 80% exhibited diurnal variation in asthma. While 84.3% of patients had public health insurance, only 16.4% had private insurance contracts.

The estimated direct costs at baseline between male and female patients showed a significant difference in costs for radiology (P=0.006), laboratory (P=0.028), and diagnostic (P=0.017) tests. Based on the one-year follow-up data, there was a significant difference between the costs covered by the patients and insurance companies for laboratory (P=0.012) and diagnostic (P=0.027) tests. However, except for the laboratory costs, there was no significant difference in the costs covered by insurance companies between male and female patients (table 2).

The results showed that asthma exacerbation was directly related to a significantly higher mean expenditure per patient (e.g., medical visits, radiology, diagnostic tests, and medications). The one-year follow-up data showed a significant variation in the number of physician office visits and medication costs (table 3). However, no significant difference was found in expenditure by the insurance companies for housewives.

Indirect cost analysis was performed for both sexes. As shown in table 4, the cost of lost productivity at work at both one week and one-year follow-up was higher in male than female patients. For both sexes, the highest indirect costs were impairment-related productivity followed by the lost productive time.

The results showed significantly higher costs due to days lost from work/school. We also found a direct relationship between the cost of impairment-related productivity loss and asthma severity in both male and female patients. However, at one-year follow-up, costs due to days lost from work/school were significantly higher in male patients (table 5).

A multivariate causal analysis was performed on three distinct explanatory models, namely male participants, female participants, and total participants. These were analyzed in terms of direct and indirect costs (latent variables), the corresponding indicators, asthma severity, and the sex of the participants (observed variables). SEM was then performed separately for each of the three models. The final fit indices for the total explanatory model based on pre-defined cutoffs were CFI=0.98, RMSEA=0.03, and SRMR=0.06. ²⁵ Unstandardized regression weights were used in the confirmatory model (measurement) between two latent variables and the corresponding observed indicators. The results showed a significant and good discriminant predictive relationship between direct costs and medical costs for the three models; total participants (P=0.032), female participants (P=0.023), and male participants (P<0.001). Similarly, between indirect costs and the cost of impairment-related productivity loss, these values were P<0.001, P=0.023, and P<0.001, respectively (table 6). In terms of the confirmatory model (structural), a significant predictive relationship was found between severe asthma and indirect costs in the model for total participants (P<0.001), female participants (P=0.011), and male participants (P<0.006) (table 6).

The results also showed a positive correlation between two latent variables (direct and indirect costs) in the model for total participants (r=0.243, P<0.001), female participants (r=0.176, P=0.001), and male participants (r=0.303, P<0.001). As depicted in figure 1, the links for standardized coefficients had similar associations as the unstandardized coefficients.

Figure 1. The results of structural equation modeling showing standardized regression weights for the predicated costs. DC: Direct costs; IC: Indirect costs; Med: Medical costs; Non-Med: Non-medical costs; WPIC: Work productivity impairment costs; AbsT: Absent time; Mild: Mild persistent asthma; Moderate: Moderate persistent asthma; Severe: Severe persistent asthma. Thick lines represent P≤0.05 and thin lines represent weak relationships. Total model fit indices CFI (0.98), RMSEA (0.03), and SRMR (0.06).

Discussion

The findings of the present study indicated that direct costs related to laboratory and diagnostic tests, both at baseline and one-year follow-up, were significantly higher in males than female patients with asthma. Similarly, the costs of medication and physician office visits increased significantly with asthma exacerbation. These findings were in line with other studies in Iran and the United States. ^{5 , 6 , 8 , 26} In contrast, a systematic review reported that direct costs were higher in female patients as a result of inadequate medication, improper use of the inhaler device, or the presence of comorbidity. ²⁷ The difference in the results could be attributed to various parameters. For example, the prevalence of severe asthma is slightly higher in men (58.3%) than in women. Besides, it seems that female patients can cope better with the treatment than male patients. Consequently, they have less severe asthma exacerbations resulting in improved clinical management and reduced health-related costs. ^{28 , 29} Nonetheless, the evidence does not support the role of sex on variables affecting direct costs. ²⁸

A previous study projected the economic burden of asthma in the United States and estimated an additional direct cost of $1,056 by 2038, compared to 2019, in patients with uncontrolled versus controlled asthma. ³⁰ Based on our results, the total annual direct costs for each patient with asthma were estimated at $432, of which 90% was related to medical and 10% to non-medical costs. The increase in direct costs could be attributed to severe cases requiring more emergency drugs, systematic use of corticosteroids, visits to emergency departments, and hospitalization. ^{5 , 30}

Our results on indirect costs showed that the cost of productivity loss at work was higher in male than female patients with asthma. Over 60% of the indirect costs were related to productivity loss due to impairment. Our findings may seem to be an overestimate, however, inaccuracies in other studies resulted in an underestimation of direct costs of asthma. ³¹ We address this potential inaccuracy by using the Persian version of the WPAI-AQ questionnaire, which allowed a detailed assessment of presenteeism and absenteeism on weekly basis. ¹⁷ As a result, our estimation of the indirect costs appears to be more realistic than other studies conducted in Iran. ^{5 , 6} However, in line with previous studies, we found that the cost due to days lost from work in men with severe asthma was significantly high. ^{6 , 32}

A few recent economic surveys of Iranian patients with asthma reported that medical costs remained constant and that the highest indirect costs were related to days lost from work/school. ^{6 , 27} It is noteworthy that in these surveys, absenteeism from work/school was the only question about indirect costs. In our study, we found that indirect costs were about 70%-80% of the direct costs irrespective of asthma severity. In addition, the cost of impairment-related productivity loss at work, which is about 70%-90% of the indirect cost related to asthma severity and sex, could be explained by the limitations of the health system in Iran. For example, the lack of a well-developed primary healthcare system for asthma, high costs associated with asthma (e.g., medications), and low-income individuals. These are indicative of suboptimal asthma control and poor health-related quality of life. On the other hand, because of the need for a monthly salary, patients with asthma must attend work (presenteeism) despite the intangible costs of the disease, which in turn negatively affect their productivity. ^{5 , 27 , 30} We observed the same situation for asthma severity, although the associated direct and indirect costs were roughly the same. The cost of days lost due to severe asthma was reported to be a significant proportion of indirect costs. ^{4 , 26}

The prevalence of asthma in Iran is about 8.9%. Considering the 83 million population, this amounts to 7,400,000 patients and is equivalent to $3.2 billion in direct costs and $2.5 billion in indirect costs due to days lost from work or impairment-related productivity loss. A previous study on the economic burden of asthma in Greece estimated the cost of treatment per patient at €895 ($1,054), of which 90% were medical, 6% non-medical, and 4% indirect costs. Medical and non-medical costs represented 90% and 10% of the total annual direct costs, respectively. ⁴ In the United States, the annual cost for all patients with asthma due to loss of income and productivity during 2008-2013 were estimated at $120 (days lost from work) and $89 (days lost from school), respectively. ^{3 , 5} In comparison, our results showed different percentages for the direct and indirect costs. The difference could be explained by the lack of a comprehensive medical referral system for such patients in Iran, which can result in poor prevention, diagnosis, treatment, and health care utilization; leading to increased morbidity. In addition, increased asthma exacerbation resulted in days lost from work/school and impairment-related productivity/activity loss at work/school. Another explanation may be the clarity of the questions in the WPAI-AQ, which allowed patients to fully understand the questions and provide clear answers. Last but not least, the cost estimation method could also be the source of the differences. We used GDP-LCU and active population to estimate indirect costs, which allows extrapolation of the estimates to the whole country.

The results of our study on patients with private health insurance showed that insurance companies almost fully covered the cost of hospitalization and almost 80% of medications. Furthermore, the results of SEM for the three groups (male, female, and all participants) indicated significant relationships between indirect costs and productivity loss due to impairment and asthma severity. Our results are in line with a previous study reporting that severe persistent asthma is associated with a greater percentage (28%) of impairment than mild-to-moderate persistent asthma. ¹⁵

The main limitation of the study is related to the estimation of costs covered by insurance companies. Since these companies offer various insurance contracts for the payment of incurred claims, we used annual insurance premiums to estimate the costs. Therefore, we could not accurately estimate the indirect costs covered by the insurance companies. Since no figures were available, we estimated medication costs based on insurance claims by the patients, which may contain certain inaccuracies. In addition, the sample size included a limited number of children. Another limitation is related to national currency fluctuations due to economic conditions.

Conclusion

The cost of asthma, particularly severe asthma, is significant for Iranian patients and society as a whole. The cost of laboratory and diagnostic testing was the highest in male patients. The highest cost was related to physician office visits and medication and was correlated with asthma severity. Overall, the cost of medication (by the patients) and hospitalization (by insurance companies) accounted for the largest portion of the total medical costs. Indirect costs due to days lost from work were predominantly high in male patients, whereas the cost of productivity loss due to impairment increased in line with asthma severity. Our findings provide a set of indicators to develop strategies for improving systemic health assessments (in particular for asthma phenotypes), preventing acute asthma exacerbations, and reducing the effect of environmental factors to effectively manage the economic burden on Iranian asthma patients.

Acknowledgment

The study was financially supported by the Non-Communicable Disease Center of the Ministry of Health and Medical Education (number: 530000-87) and approved by the Tuberculosis and Lung Disease Center and Tabriz University of Medical Sciences. We would like to thank the patients and their families for their contribution during the follow-up period.

Authors’ Contribution

All authors contributed to the study conception, design, and preparation of the manuscript. A. Sharifi, K. Ansarin, and AH. Jafari Rouhi participated in patient selection. E. Seyedrezazadeh was involved in data acquisition. E. Seyedrezazadeh, N. Gilani, M. Yousefi, and I. Dastan performed the statistical analysis and data interpretation.

Conflict of Interest

None declared.

References

1. Dalys GBD, Collaborators H. Global, regional, and national disability-adjusted life-years (DALYs) for 315 diseases and injuries and healthy life expectancy (HALE), 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015. Lancet. 2016; 388:1603-58. Publisher Full Text | DOI | PubMed
2. Lee LK, Ramakrishnan K, Safioti G, Ariely R, Schatz M. Asthma control is associated with economic outcomes, work productivity and health-related quality of life in patients with asthma. BMJ Open Respir Res. 2020; 7Publisher Full Text | DOI | PubMed
3. Mukherjee M, Stoddart A, Gupta RP, Nwaru BI, Farr A, Heaven M, et al. The epidemiology, healthcare and societal burden and costs of asthma in the UK and its member nations: analyses of standalone and linked national databases. BMC Med. 2016; 14:113. Publisher Full Text | DOI | PubMed
4. Vellopoulou K, Bakakos P, Loukides S, Maniadakis N, Kourlaba G. The Economic Burden of Asthma in Greece: A Cross-Sectional Study. Appl Health Econ Health Policy. 2019; 17:629-40. DOI | PubMed
5. Nurmagambetov T, Kuwahara R, Garbe P. The Economic Burden of Asthma in the United States, 2008-2013. Ann Am Thorac Soc. 2018; 15:348-56. DOI | PubMed
6. Sharifi L, Dashti R, Pourpak Z, Fazlollahi MR, Movahedi M, Chavoshzadeh Z, et al. Economic Burden of Pediatric Asthma: Annual Cost of Disease in Iran. Iran J Public Health. 2018; 47:256-63. Publisher Full Text | PubMed
7. Fazlollahi MR, Najmi M, Fallahnezhad M, Sabetkish N, Kazemnejad A, Bidad K, et al. The prevalence of asthma in Iranian adults: The first national survey and the most recent updates. Clin Respir J. 2018; 12:1872-81. DOI | PubMed
8. Sharifi L, Pourpak Z, Fazlollahi MR, Bokaie S, Moezzi HR, Kazemnejad A, et al. Asthma Economic Costs in Adult Asthmatic Patients in Tehran, Iran. Iran J Public Health. 2015; 44:1212-8. Publisher Full Text | PubMed
9. Rostamzadeh N, Akbari Sari A, Gharagozlou M. Direct Costs of Asthma in a Referral Public Children’s Hospital in Tehran, Iran. Iran J Allergy Asthma Immunol. 2018; 17:601-3. PubMed
10. Darba S, Safaei N, Mahboub-Ahari A, Nosratnejad S, Alizadeh G, Ameri H, et al. Direct and Indirect Costs Associated with Coronary Artery (Heart) Disease in Tabriz, Iran. Risk Manag Healthc Policy. 2020; 13:969-78. Publisher Full Text | DOI | PubMed
11. Jo C. Cost-of-illness studies: concepts, scopes, and methods. Clin Mol Hepatol. 2014; 20:327-37. Publisher Full Text | DOI | PubMed
12. Ruiz-Cantero MT, Blasco-Blasco M, Chilet-Rosell E, Peiro AM. Gender bias in therapeutic effort: from research to health care. Farm Hosp. 2020; 44:109-13. DOI | PubMed
13. Su R, Zhang Q, Liu Y, Tay L. Modeling congruence in organizational research with latent moderated structural equations. J Appl Psychol. 2019; 104:1404-33. DOI | PubMed
14. nternational ERS/ATS guidelines on definition, evaluation and treatment of severe asthma. Kian Fan Chung, Sally E. Wenzel, Jan L. Brozek, Andrew Bush, Mario Castro, Peter J. Sterk, Ian M. Adcock, Eric D. Bateman, Elisabeth H. Bel, Eugene R. Bleecker, Louis-Philippe Boulet, Christopher Brightling, Pascal Chanez, Sven-Erik Dahlen, Ratko Djukanovic, Urs Frey, Mina Gaga, Peter Gibson, Qutayba Hamid, Nizar N. Jajour, Thais Mauad, Ronald L. Sorkness and W. Gerald Teague. Eur Respir J 2014; 43: 343-373. Eur Respir J. 2018; 52DOI | PubMed
15. Chen H, Blanc PD, Hayden ML, Bleecker ER, Chawla A, Lee JH, et al. Assessing productivity loss and activity impairment in severe or difficult-to-treat asthma. Value Health. 2008; 11:231-9. DOI | PubMed
16. National Asthma E, Prevention P. Expert Panel Report 3 (EPR-3): Guidelines for the Diagnosis and Management of Asthma-Summary Report 2007. J Allergy Clin Immunol. 2007; 120:S94-138. DOI | PubMed
17. Seyedrezazadeh E, Ansarin K, Sharifi A, Jafari Rouhi AH, Gilani N, Aftabi Y, et al. Validation of the Persian work productivity and activity impairment questionnaire in asthmatic patients. Expert Rev Respir Med. 2020; 14:757-62. DOI | PubMed
18. Sicras-Mainar A, Capel M, Navarro-Artieda R, Nuevo J, Orellana M, Resler G. Real-life retrospective observational study to determine the prevalence and economic burden of severe asthma in Spain. J Med Econ. 2020; 23:492-500. DOI | PubMed
19. Zhou ZY, Koerper MA, Johnson KA, Riske B, Baker JR, Ullman M, et al. Burden of illness: direct and indirect costs among persons with hemophilia A in the United States. J Med Econ. 2015; 18:457-65. DOI | PubMed
20. Quirce S, Melero C, Huerta A, Uria E, Cuesta M. Economic impact of severe asthma exacerbations in Spain: multicentre observational study. J Asthma. 2021; 58:207-12. DOI | PubMed
21. Hu Lt, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal. 1999; 6:1-55. DOI
22. Imai K, Keele L, Tingley D. A general approach to causal mediation analysis. Psychol Methods. 2010; 15:309-34. DOI | PubMed
23. McDonald RP. Measuring Latent Quantities. Psychometrika. 2011; 76:511-36. DOI | PubMed
24. Medeiros RA.Paper presented at: ; 2013.
25. Kline RB. Principles and practice of structural equation modeling. Guilford Publications: New York; 2015.
26. Settipane RA, Kreindler JL, Chung Y, Tkacz J. Evaluating direct costs and productivity losses of patients with asthma receiving GINA 4/5 therapy in the United States. Ann Allergy Asthma Immunol. 2019; 123:564-72. DOI | PubMed
27. Bahadori K, Doyle-Waters MM, Marra C, Lynd L, Alasaly K, Swiston J, et al. Economic burden of asthma: a systematic review. BMC Pulm Med. 2009; 9:24. Publisher Full Text | DOI | PubMed
28. Pignataro FS, Bonini M, Forgione A, Melandri S, Usmani OS. Asthma and gender: The female lung. Pharmacol Res. 2017; 119:384-90. DOI | PubMed
29. Varmaghani M, Rashidian A, Kebriaeezadeh A, Moradi-Lakeh M, Moin M, Ghasemian A, et al. National and sub-national prevalence, trend, and burden of asthma in Iran from 1990 to 2013; the study protocol. Arch Iran Med. 2014; 17:804-9. PubMed
30. Yaghoubi M, Adibi A, Safari A, FitzGerald JM, Sadatsafavi M. The Projected Economic and Health Burden of Uncontrolled Asthma in the United States. Am J Respir Crit Care Med. 2019; 200:1102-12. Publisher Full Text | DOI | PubMed
31. Birnbaum HG, Berger WE, Greenberg PE, Holland M, Auerbach R, Atkins KM, et al. Direct and indirect costs of asthma to an employer. J Allergy Clin Immunol. 2002; 109:264-70. DOI | PubMed
32. Statistical Centre of Iran. The results of the labor force census were published in the spring of 2018. 2018;1-15.