Measuring The Impact Of Air Pollution On Health Care Costs


Short- and long-term air pollution exposure exacerbates and contributes to the development of numerous adverse health outcomes.19 For example, air pollutants such as particulate matter and ground-level ozone can exacerbate preexisting conditions and also contribute to increased incidence of disease, particularly respiratory (such as chronic bronchitis and asthma) and cardiovascular conditions.1 In turn, greater incidence of illness can increase mortality, health care use, and costs.1,10

The Environmental Benefits Mapping and Analysis Program–Community Edition (BenMAP-CE) is a tool historically used by the Environmental Protection Agency (EPA) to estimate the economic impact of a range of clinical outcomes due to air pollution, including the cost of a subset of impacts (hospital admissions and emergency department [ED] visits). Both morbidity and mortality outcomes are considered.1113 BenMAP-CE includes concentration-response parameters and unit economic values to quantify the air pollution–attributable cases of premature death. BenMAP-CE is preloaded with geographic-specific data on ground-level ozone and particulate matter. Users can also import data on the geographic values for other air pollutants.

BenMAP-CE is often used in the US to conduct various types of analyses in support of air quality regulations, such as the Regulatory Impact Analysis for Light-Duty Vehicle Greenhouse Gas Emission Standards14 and the Regulatory Impact Analysis for the Final Mercury and Air Toxics Standards.15 In addition to its extensive use by the EPA, BenMAP-CE is used widely by other agencies in analyses conducted both domestically and internationally.1619 In these analyses BenMAP-CE’s default configuration, described here, is often used.

Mortality is an important health outcome measure of the burden of air pollution. From an economic outcome perspective, lives lost matter greatly to the future productivity and growth of the economy. BenMAP-CE uses the value of a statistical life approach to estimate mortality costs.12 This approach measures the willingness of a group of people to pay to reduce the risk for premature death.12 Although previous research has shown the large mortality burden associated with air pollution,5,6,12 it is also important to quantify accurately the costs of health care associated with air pollution because they add to the financial burden of care paid by patients as well as by private and public insurers.

Based on air quality and population data, baseline rates of mortality and morbidity, concentration-response parameters, and unit economic values, BenMAP-CE quantifies the number and value of air pollution–attributable cases of premature death and disease (for example, hospital admissions for respiratory and cardiovascular conditions).13 To estimate health care costs, BenMAP-CE multiplies the estimated number of hospitalizations and ED visits attributed to an air pollutant by unit cost estimates. It also uses the same hospitalization data in its calculation of work loss as it does for health care costs (that is, hospital length-of-stay).12,20

The default BenMAP-CE configuration estimates the costs of the health outcome examined (that is, the hospital admission or ED visit), but not other health care costs that could be incurred before or after entry into the hospital. Therefore, absent from BenMAP-CE’s default calculations are the costs attributable to ambulatory care (including physician and clinic visits, prescription drugs, supplies, and home health care) that may also increase as a result of increased air pollution. The literature does not offer ways that meet BenMAP-CE standards to quantify the impact of air pollution on ambulatory visits. Nevertheless, a hospitalization (assuming patient survival) typically will necessitate additional follow-up outpatient visits regardless of the initiating event, whether or not it is related to air pollution.21,22 Although patients with severe symptoms may be hospitalized on bad air pollution days, on such days patients with mild respiratory symptoms may just seek ambulatory care.2123

The cost of such ambulatory care can be substantial. For instance, an analysis of the effect of asthma exacerbations using an employer claims database found that ambulatory care costs exceed hospital costs for patients with at least one asthma exacerbation.24 Analysis of data from the Medical Expenditure Panel Survey found that hospitalization costs from asthma are a small fraction of total health care costs.25 Similarly, analyses of Kaiser Permanente data found that inpatient costs among patients with cardiovascular disease account for less than half of their total costs.26 This literature suggests that by not accounting for the full chain of potential related ambulatory outcomes, BenMAP-CE computations may underestimate the morbidity costs of air pollution.

In a similar vein, although the BenMAP-CE configuration considers only hospitalizations with cardiovascular or respiratory disease coded as a primary diagnosis, recent research has found that air pollution is also associated with hospitalizations in addition to those considered in BenMAP-CE. This is because air pollution can cause harm beyond these acute conditions to affect chronic conditions, “potentially affecting every organ in the body. It can cause, complicate, or exacerbate many adverse health conditions.”27 Similarly, there is evidence air pollution is a carcinogen linked to lung cancer.28,29 Another study found that many conditions that are neither respiratory nor cardiovascular related (for example, septicemia and anemia) are also exacerbated by air pollution.30

The objective of this article is to provide a more complete estimate of the health care costs associated with morbidity resulting from air pollution. Specifically, the analysis here makes no changes to the inner workings of BenMAP-CE. Rather, this study more completely estimates the economic impact of air pollution on morbidity outcomes. Specifically, it considers the increased costs of both ambulatory care and “other hospitalizations” (with a secondary diagnosis code of cardiovascular or respiratory disease or with diagnosis codes for any non-respiratory- or non-cardiovascular-related condition).

Study Data And Methods

To demonstrate the effect of including additional categories of health care resource use (that is, ambulatory care and other hospitalizations) on the monetary costs of air pollution, this analysis considers the two main disease categories for adults in the default BenMAP-CE configuration: all respiratory (ages 65–99) and all cardiovascular (ages 18–64 and 65–99) patients. To estimate costs of additional outcomes not included in BenMAP-CE, we compared the use of health care resources and costs of patients in a year in which they had a respiratory or cardiovascular hospitalization (2016) with those in the preceding year (2015), during which the same patients did not have any such hospitalizations. The ratio of the cost of care components (for example, ambulatory care) not included in BenMAP-CE to the cost of hospital care that was included in BenMAP-CE is an estimate of the extent of the additional costs relative to included costs. The cost per event of air pollution and non–air pollution health care are assumed to be the same.

Data Source

We analyzed data from the OptumHealth Reporting and Insights Administrative Claims Database, which contains administrative claims for approximately twenty million privately insured people covered by eighty-four large US employers from 1999 through the first quarter of 2017. This is an opportunistic database of participating employers. Although not representative of the US population, it and other commercial claims databases have been used extensively in health outcomes analyses.31,32 As described here (see Study Results), hospital lengths-of-stay and unit cost data measures in the employer database are similar to those used in BenMAP-CE analyses. The study database contains complete medical and pharmaceutical claims, along with enrollment information, for beneficiaries younger than age sixty-five as well as those ages sixty-five and older who have employer-paid Medicare supplemental insurance. The study database is deidentified and is fully compliant with the requirements of the Health Insurance Portability and Affordability Act.

Study Population

Patients with at least one 2016 inpatient stay or ED claim with a primary diagnosis of a respiratory or cardiovascular condition considered by BenMAP-CE (as defined by International Classification of Diseases, Ninth Revision, or Statistical Classification of Diseases and Related Health Problems, Tenth Revision, diagnosis codes, henceforth termed BenMAP-CE-specified conditions) were identified in the study database. Inclusion criteria specified that patients in the respiratory and cardiovascular cohorts must not have had a hospitalization for these conditions in 2015 (the baseline period). All patients were also required to have continuous non–health maintenance organization insurance coverage during the full calendar years of 2015 through 2016, to ensure the completeness of the cost information. Online appendix exhibit A1 illustrates the selection of patients in the analytic sample.33 The final sample of patients having a hospitalization for these conditions in 2016 but not 2015 included 11,694 patients in the respiratory cohort, 19,191 patients in the cardiovascular cohort ages 18–64, and 14,354 patients in the cardiovascular cohort ages 65 and older.

Analysis

The analysis first considered the comparability of the mean length of hospital stay and mean unit cost of hospitalization between BenMAP-CE results and those using the study database. Then the analysis measured increases in care (and costs) that occurred when patients went from having no hospitalizations in 2015 for respiratory or cardiovascular care to having such a hospitalization in 2016. This methodology allows patients to serve as their own controls to determine the impact of a hospitalization on ambulatory care costs.

To compute the costs of health care included by BenMAP-CE, we summed annual costs (that is, total charges of providers, following BenMAP-CE’s approach) for hospitalizations in 2016 that had a primary diagnosis of cardiovascular or respiratory disease for each cohort. All costs during these hospitalizations were attributed to the given condition. This definition is consistent with BenMAP-CE’s methodology and represents those costs included in BenMAP-CE analyses.

Total annual costs were then summed for 2015 and 2016 for each cohort. These costs included all-cause ambulatory care (outpatient visits, home health care, other care, and prescription medications for any reason). The study also included other hospitalizations with cardiovascular or respiratory disease coded as a secondary diagnosis, as well as any non-respiratory- or non-cardiovascular-related conditions. These other hospitalizations are important to consider because air pollution can exacerbate many non-respiratory- or non-cardiovascular-related conditions, as mentioned above. The difference in costs between 2016 and 2015 represents the added costs that patients had in a year in which they had a hospitalization with a primary diagnosis for a cardiovascular or respiratory condition relative to a year in which they did not. These incremental (additional) costs are not included in the default BenMAP-CE configuration.

For each of the three cohorts, the ratio of incremental costs relative to health care costs included by BenMAP-CE was calculated. For patients with cardiovascular disease, a single weighted cost ratio was also calculated using the two cardiovascular cohort sizes as weights.

Work-Loss And Utilization Analyses

Work-loss costs were calculated by cohort, following the EPA’s methodology of estimating work-loss days using BenMAP-CE, as the product of median daily wage and mean length of hospitalization stay as reported in BenMAP-CE. The analysis estimated the total number of added work-loss days in 2016 that were due to incremental ambulatory care and other hospitalizations. As in work-loss analyses elsewhere, each day of incremental hospitalization accounted for one day of work loss.31,32 Each ambulatory visit accounted for one day of work loss per visit. Additional work-loss costs were estimated as the number of added days of hospital/ambulatory use multiplied by the BenMAP-CE reported median daily wage. Similar to the health care cost analysis, the ratio of incremental work-loss costs relative to BenMAP-CE-included costs were calculated for each cohort.

In addition to cost measures, health care use constitutes a substantial patient outcome that imposes a large emotional and time burden on patients. Therefore, results are reported on the number of visits and days for which patients received health care that are not included in BenMAP-CE.

Limitations

A limitation of this research is the absence of measures of health care costs associated with actual, local changes in particulate matter. It would be useful to extend the research of Yaguang Wei and colleagues regarding the roles of geography, patient demographics, treatment patterns, and timing of air pollution events on the use and cost of both hospital and ambulatory care.30 Wei and colleagues’ research found that air pollution leads to cost increases in inpatient and postacute care costs and mortality;30 similar findings are reported by Tatyana Deryugina and colleagues.8 Other temporal factors such as recent increases in air pollution associated with changes in climate and outbreaks of new diseases (for example, coronavirus disease 2019 [COVID-19])34 also should be considered. Because this study is based on administrative claims data for a commercially insured population, results might not be generalizable to other groups (for example, Medicare and Medicaid patients). Work-loss costs are another area where the chain of costs could be broadened from that in BenMAP-CE; for example, days missed from work while recuperating from a hospitalization were not accounted for in the tool.

Study Results

Because the analysis here relies on an employer-sponsored claims database, not the Healthcare Cost and Utilization Project (hospital discharge abstract database) used in BenMAP-CE,35 hospital lengths-of-stay and unit cost data for the research sample were compared with BenMAP-CE estimates. Appendix exhibit A2 shows that measures in the employer database are similar to those used in BenMAP-CE analyses.33 For example, average lengths-of-stay for cardiovascular patients younger than age sixty-five were 4.12 days in BenMAP-CE12 and 3.97 days in the study data (appendix exhibit A2).33 Average hospital costs were $45,65912 and $43,337 (in 2015 dollars), respectively.

Cost Of Additional Care

The extent and cost of additional ambulatory care use was substantial. Among patients with no hospitalization in 2015 and a respiratory hospitalization in 2016, the average number of ambulatory care visits increased from 20.7 visits in 2015 to 26.0 visits in 2016 (exhibit 1). That is, for respiratory patients there was an increase of 25.6 percent in the average number of ambulatory care visits associated with a hospitalization. An even larger increase in the average number of ambulatory care visits occurred for cardiovascular patients (44.0 percent for patients younger than age sixty-five and 33.0 percent for patients ages sixty-five and older). Likewise, other hospitalizations not included in the BenMAP-CE calculation also increased substantially (76.0 percent for respiratory patients, 64.3 percent for cardiovascular patients younger than age sixty-five, and 118.8 percent for cardiovascular patients ages sixty-five and older).

Exhibit 1 Annual and incremental health care resource use: respiratory and cardiovascular patients in the US with no condition-specific hospitalizations in 2015 and with at least one condition-specific hospitalization in 2016

All-cause health care resource use per patient-year
Respiratory patients ages 65+ (n = 11,694) Cardiovascular patients ages <65 (n = 19,191) Cardiovascular patients ages 65+ (n = 14,354)
2015 2016 Incremental 2015 2016 Incremental 2015 2016 Incremental
Ambulatory visitsa 20.7 26.0 5.3 13.4 19.3 5.9 20.6 27.4 6.8
Other hospitalization daysb 2.5 4.4 1.9 1.4 2.3 0.9 1.6 3.5 1.9

For respiratory patients, the annual per patient costs (in 2016 dollars) of BenMAP-CE-included care averaged $52,336; the total cost of the additional services was $22,621 (exhibit 2). The calculation implies that including the costs of additional services would increase the health care costs measured by BenMAP-CE by 43.2 percent for respiratory patients. Similar calculations for cardiovascular patients found that including the additional services would increase the cost of health care by 41.7 percent for patients younger than age sixty-five and 35.1 percent for patients ages sixty-five and older relative to what BenMAP-CE includes.

Exhibit 2 Annual and incremental health care costs: respiratory and cardiovascular patients in the US with no condition-specific hospitalizations in 2015 and with at least one condition-specific hospitalization in 2016

Health care costs per patient-year (2016 US $)
Respiratory patients ages 65+
Cardiovascular patients ages <65
Cardiovascular patients ages 65+
2015
2016
Incremental
2015
2016
Incremental
2015
2016
Incremental
[A1] Condition hospitalization (primary) 0 52,336 52,336 0 55,170 55,170 0 61,282 61,282
[A2] Condition hospitalization (secondary)a 1,282 2,785 1,503 2,015 4,015 2,000 2,539 5,461 2,922
[A3] Other hospitalization 10,690 17,927 7,238 6,616 11,532 4,916 4,680 8,756 4,077
[B] All-cause ambulatoryb 27,323 41,203 13,880 24,836 40,912 16,075 24,190 38,728 14,538
Total 39,295 114,251 74,957 33,467 111,629 78,161 31,408 114,226 82,819

Work Loss

A similar analysis conducted for work loss, shown in appendix exhibit A3,33 found that costs not included in BenMAP-CE were 85 percent of included costs for the BenMAP-CE categories for respiratory patients, 138 percent for cardiovascular patients younger than age sixty-five, and 119 percent for cardiovascular patients ages sixty-five and older. Although the added work-loss costs were proportionally much larger than for additional health care costs, on a dollar basis the added work-loss costs were much smaller.

With these additional health care and work-loss costs combined into a total cost measure, shown in appendix exhibit A4,33 the additional total costs would exceed included BenMAP-CE costs by more than 40 percent (44.4 percent for respiratory patients, 43.1 percent for cardiovascular patients younger than age sixty-five, and 36.8 percent cardiovascular patients ages sixty-five and older. Exhibit 3 shows these differences in dollar terms.

Exhibit 3 Incremental per patient annual health care and work-loss costs in the US, by condition

Exhibit 3
SOURCES Environmental Protection Agency. BenMAP-CE user’s manual (see note 12 in text); authors’ analysis of data from the OptumHealth Reporting and Insights Administrative Claims Database. NOTES Annual costs include both Environmental Benefits Mapping and Analysis Program–Community Edition (BenMAP-CE) included costs and additional costs, accounting for both health care and work-loss costs. BenMAP-CE health care and work loss includes inpatient or emergency department visits with a primary diagnosis code for the given condition, as well as associated work loss. Additional health care and work loss includes incremental hospitalization visits without a primary diagnosis code for the given condition and other all-cause ambulatory care (for example, outpatient, home health agency), as well as associated work loss and incremental costs of all prescription medications. Calculations are in exhibit 2 and appendix exhibit A3 (see note 33 in text).

Sensitivity Analyses

Several sensitivity analyses were conducted. One sensitivity analysis, shown in appendix exhibit A5,33 considered the impact of excluding hospitalizations with a secondary diagnosis of cardiovascular or respiratory disease from the analysis. After the exclusion of such hospitalizations, BenMAP-CE health care costs still would increase by approximately 36 percent (that is, 36 cents added for every dollar included in BenMAP-CE estimates). Similarly, this study included other hospitalizations (nonrespiratory and noncardiovascular) that were not directly attributable to cardiovascular or respiratory disease; after the removal of such hospitalizations, BenMAP-CE health care costs would increase by up to 31 percent.

Because not every ambulatory visit is associated with a full day missed from work as computed earlier, a sensitivity analysis also was conducted counting the visit as a half-day (rather than a full-day) loss. This calculation still yields additional work-loss costs of 54 percent of BenMAP-CE costs for respiratory patients, 78 percent for cardiovascular patients younger than age sixty-five, and 72 percent for cardiovascular patients ages sixty-five and older (appendix exhibit A6).33 Because work-loss cost as measured here is small relative to health care costs, the change in additional total (work-loss plus health care) costs is approximately 1 percentage point, as computed from appendix exhibit A7.33

Discussion

For each dollar of health care costs captured by the BenMAP-CE tool that the EPA has used to calculate the outcomes of air pollution, a more complete accounting described here would include approximately 40 additional cents. These results suggest that because air pollution costs are underestimated, the health care benefits associated with reducing air pollution may be substantially larger than previously estimated.

These results also suggest that policy analyses using the BenMAP-CE model may substantially underestimate the health care benefits of reductions in air pollution. For instance, in the Regulatory Impact Analysis for the Final Mercury and Air Toxics Standards, the EPA used BenMAP-CE to estimate the annual benefits associated with the reductions in respiratory and cardiovascular hospitalizations due to the Final Mercury and Air Toxics Standards and found these benefits to be $10 million for respiratory and $30 million for cardiovascular (in 2007 dollars).15 Results estimated here suggest that these benefits would be approximately 40 percent higher after ambulatory and other care was considered. Another EPA study of the Clean Air Act36 found that a more complete accounting of health care costs would lead to greater reductions in the annual costs of respiratory and cardiovascular hospitalizations by up to $488 million for respiratory and $809 million for cardiovascular hospitalizations (in 2006 dollars). Similarly, BenMAP-CE-based analyses conducted both domestically and internationally have not considered the potential full chain of costs.1619

Beyond economic considerations, avoided air pollution–related physician visits and hospitalizations are desirable patient outcomes. In addition to the health care costs of ambulatory care, there is a burden to the patient and family members (in time, emotional stress, and so on) from additional visits. For example, every patient hospitalized for respiratory care, as noted earlier, also averages five additional ambulatory care visits not included in the BenMAP-CE tool. Extrapolating this analysis suggests that consideration of the full chain of outcomes in the Regulatory Impact Analysis for the Final Mercury and Air Toxics Standards could result in 3,142 avoided respiratory and 8,491 avoided cardiovascular ambulatory care visits.

Conclusion

Although the estimates reported here can be refined, this research finds that the health care cost benefits associated with reducing air pollution may be much larger than previously estimated. Further improvements in methods and data will yield more complete measures of the economic impacts and patient outcomes of air pollution at both the patient and payer levels. In today’s environment, where current health care costs are a focus of much debate and individual concern, further research on the full range of air pollution–induced health care costs is warranted.

ACKNOWLEDGMENTS

Analysis Group entirely and solely supported the performing of this research and writing of this article by its employees. No external funding was involved. The authors acknowledge the comments of Noam Kirson, who is also an Analysis Group employee.

NOTES

  • 1 Kampa M , Castanas E . Human health effects of air pollution. Environ Pollut. 2008;151(2):362–
    7. Crossref, Medline, Google Scholar
  • 2 Chay KY , Greenstone M . The impact of air pollution on infant mortality: evidence from geographic variation in pollution shocks induced by a recession. Q J Econ. 2003;118(3):1121–
    67. Crossref, Google Scholar
  • 3 Knittel CR , Miller DL , Sanders NJ . Caution, drivers! Children present: traffic, pollution, and infant health. Rev Econ Stat. 2016;98(2):350–
    66. Crossref, Google Scholar
  • 4 Schlenker W , Walker WR . Airports, air pollution, and contemporaneous health. Rev Econ Stud. 2016;83(2):768–
    809. Crossref, Google Scholar
  • 5 Dockery DW , Pope CA . Acute respiratory effects of particulate air pollution. Annu Rev Public Health. 1994;15(1):107–
    32. Crossref, Medline, Google Scholar
  • 6 Pope CA , Dockery DW . Health effects of fine particulate air pollution: lines that connect. J Air Waste Manag Assoc. 2006;56(6):709–
    42. Crossref, Medline, Google Scholar
  • 7 Pope CA , Ezzati M , Dockery DW . Fine-particulate air pollution and life expectancy in the United States. N Engl J Med. 2009;360(4):376–
    86. Crossref, Medline, Google Scholar
  • 8 Deryugina T , Heutel G , Miller NH , Molitor D , Reif J . The mortality and medical costs of air pollution: evidence from changes in wind direction. Am Econ Rev. 2019;109(12):4178–
    219. Crossref, Medline, Google Scholar
  • 9 Seaton A , MacNee W , Donaldson K , Godden D . Particulate air pollution and acute health effects. Lancet. 1995;345(8943):176–
    8. Crossref, Medline, Google Scholar
  • 10 Stafoggia M , Samoli E , Alessandrini E , Cadum E , Ostro B , Berti G et al. Short-term associations between fine and coarse particulate matter and hospitalizations in Southern Europe: results from the MED-PARTICLES project. Environ Health Perspect. 2013;121(9):1026–
    33. Crossref, Medline, Google Scholar
  • 11 Environmental Protection Agency. Environmental Benefits Mapping and Analysis Program—Community Edition (BenMAP-CE) [Internet]. Washington (DC): EPA; 2019 [cited 2020 Sep 23]. Available from: https://www.epa.gov/benmap Google Scholar
  • 12 Environmental Protection Agency. Environmental Benefits Mapping and Analysis Program–Community Edition (BenMAP-CE): User’s manual [Internet]. Washington (DC): EPA; 2018 [cited 2020 Oct 15]. Available from: https://www.epa.gov/sites/production/files/2015-04/documents/benmap-ce_user_manual_march_2015.pdf Google Scholar
  • 13 Sacks JD , Lloyd JM , Zhu Y , Anderton J , Jang CJ , Hubbell B et al. The Environmental Benefits Mapping and Analysis Program—Community Edition (BenMAP-CE): a tool to estimate the health and economic benefits of reducing air pollution. Environ Model Softw. 2018;104:118–
    29. Crossref, Medline, Google Scholar
  • 14 Environmental Protection Agency. Joint Technical Support Document: final rulemaking for 2017–2025 light-duty vehicle greenhouse gas emission standards and corporate average fuel economy standards [Internet]. Washington (DC): EPA, Office of Transportation and Air Quality; 2012 [cited 2020 Oct 15]. Available from: https://nepis.epa.gov/Exe/ZyPDF.cgi/P100F1E5.PDF?Dockey=P100F1E5.PDF Google Scholar
  • 15 Environmental Protection Agency. Regulatory impact analysis for the final mercury and air toxics standards [Internet]. Research Triangle Park (NC): EPA, Office of Air Quality Planning and Standards, Health and Environmental Impacts Division; 2011 [cited 2020 Oct 15]. Available from: https://www.epa.gov/sites/production/files/2015-11/documents/matsriafinal.pdf Google Scholar
  • 16 Nowak DJ , Hirabayashi S , Bodine A , Hoehn R . Modeled PM2.5 removal by trees in ten U.S. cities and associated health effects. Environ Pollut. 2013;178:395–
    402. Crossref, Medline, Google Scholar
  • 17 Kheirbek I , Wheeler K , Walters S , Kass D , Matte T . PM2.5 and ozone health impacts and disparities in New York City: sensitivity to spatial and temporal resolution. Air Qual Atmos Health. 2013;6(2):473–
    86. Crossref, Medline, Google Scholar
  • 18 Bae HJ , Park J . Health benefits of improving air quality in the rapidly aging Korean society. Sci Total Environ. 2009;407(23):5971–
    7. Crossref, Medline, Google Scholar
  • 19 Boldo E , Linares C , Lumbreras J , Borge R , Narros A , García-Pérez J et al. Health impact assessment of a reduction in ambient PM(2.5) levels in Spain. Environ Int. 2011;37(2):342–
    8. Crossref, Medline, Google Scholar
  • 20 Environmental Protection Agency. How BenMAP-CE estimates the health and economic effects of air pollution [Internet]. Washington (DC): EPA; 2018 [cited 2020 Sep 23]. Available from: https://www.epa.gov/benmap/how-benmap-ce-estimates-health-and-economic-effects-air-pollution Google Scholar
  • 21 Burra TA , Moineddin R , Agha MM , Glazier RH . Social disadvantage, air pollution, and asthma physician visits in Toronto, Canada. Environ Res. 2009;109(5):567–
    74. Crossref, Medline, Google Scholar
  • 22 Tam WW , Wong TW , Ng L , Wong SY , Kung KK , Wong AH . Association between air pollution and general outpatient clinic consultations for upper respiratory tract infections in Hong Kong. PLoS One. 2014;9(1):e86913. Crossref, Medline, Google Scholar
  • 23 Li R , Jiang N , Liu Q , Huang J , Guo X , Liu F et al. Impact of air pollutants on outpatient visits for acute respiratory outcomes. Int J Environ Res Public Health. 2017;14(1):47. Crossref, Google Scholar
  • 24 Ivanova JI , Bergman R , Birnbaum HG , Colice GL , Silverman RA , McLaurin K . Effect of asthma exacerbations on health care costs among asthmatic patients with moderate and severe persistent asthma. J Allergy Clin Immunol. 2012;129(5):1229–
    35. Crossref, Medline, Google Scholar
  • 25 Nurmagambetov T , Kuwahara R , Garbe P . The economic burden of asthma in the United States, 2008–2013. Ann Am Thorac Soc. 2018;15(3):348–
    56. Crossref, Medline, Google Scholar
  • 26 Nichols GA , Bell TJ , Pedula KL , O’Keeffe-Rosetti M . Medical care costs among patients with established cardiovascular disease. Am J Manag Care. 2010;16(3):e86–
    93. Medline, Google Scholar
  • 27 Schraufnagel DE , Balmes JR , Cowl CT , De Matteis S , Jung S-H , Mortimer K et al. Air pollution and noncommunicable diseases: a review by the Forum of International Respiratory Societies’ Environmental Committee, Part 1: the damaging effects of air pollution. Chest. 2019;155(2):409–
    16. Crossref, Medline, Google Scholar
  • 28 World Health Organization. Air pollution [Internet]. Geneva: WHO; [cited 2020 Sep 23]. Available from: https://www.who.int/health-topics/air-pollution Google Scholar
  • 29 Loomis D , Huang W , Chen G . The International Agency for Research on Cancer (IARC) evaluation of the carcinogenicity of outdoor air pollution: focus on China. Chin J Cancer. 2014;33(4):189–
    96. Crossref, Medline, Google Scholar
  • 30 Wei YD , Dominici F , Schwartz JD . The dangers of air pollution for human health. The BMJ Opinion [blog on the Internet]. 2019 Nov 28 [cited 2020 Sep 23]. Available from: https://blogs.bmj.com/bmj/2019/11/28/yaguang-wei-the-dangers-of-air-pollution-for-human-health/ Google Scholar
  • 31 Rice JB , Desai U , Cummings AKG , Birnbaum HG , Skornicki M , Parsons N . Burden of venous leg ulcers in the United States. J Med Econ. 2014;17(5):347–
    56. Crossref, Medline, Google Scholar
  • 32 Zhou Z , Fan Y , Thomason D , Tang W , Liu X , Zhou Z-Y et al. Economic burden of illness among commercially insured patients with systemic sclerosis with interstitial lung disease in the USA: a claims data analysis. Adv Ther. 2019;36(5):1100–
    13. Crossref, Medline, Google Scholar
  • 33 To access the appendix, click on the Details tab of the article online.
  • 34 Wu X , Nethery RC , Sabath BM , Braun D , Dominici F . Exposure to air pollution and COVID-19 mortality in the United States: a nationwide cross-sectional study [Internet]. medRxiv [serial on the Internet]. 2020 Apr 27 [cited 2020 Sep 23]. Available from: https://www.medrxiv.org/content/10.1101/2020.04.05.20054502v2 Google Scholar
  • 35 Agency for Healthcare Research and Quality. Overview of the National (Nationwide) Inpatient Sample (NIS) [Internet]. Rockville (MD): AHRQ, Healthcare Cost and Utilization Project; 2019 [cited 2020 Sep 23]. Available from: https://www.hcup-us.ahrq.gov/nisoverview.jsp Google Scholar
  • 36 Environmental Protection Agency, Office of Air and Radiation. The benefits and costs of the Clean Air Act from 1990 to 2020. Research Triangle Park (NC): EPA; 2011 Mar. Google Scholar

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