Elsevier

Science of The Total Environment

Volumes 527–528, 15 September 2015, Pages 413-419
Science of The Total Environment

Cost saving potential in cardiovascular hospital costs due to reduction in air pollution

https://doi.org/10.1016/j.scitotenv.2015.04.104Get rights and content

Highlights

  • Improved methodology chain to estimate potential hospital cost savings for Belgium

  • PM2.5&10, NO2 are significantly associated with cardiovascular emergency admissions.

  • Ischemic heart disease and heart rhythm disturbances are significant subcategories.

  • 10% reduction in air pollution exposure averts at least €14 M/year on hospital costs.

  • Achieving WHO guidelines results in minimum €51 M/year on averted hospital costs.

Abstract

Objective

We describe a methodological framework to estimate potential cost savings in Belgium for a decrease in cardiovascular emergency admissions (ischemic heart disease (IHD), heart rhythm disturbances (HRD), and heart failure) due to a reduction in air pollution.

Methods

Hospital discharge data on emergency admissions from an academic hospital were used to identify cases, derive risk functions, and estimate hospital costs. Risk functions were derived with case-crossover analyses with weekly average PM10, PM2.5, and NO2 exposures. The risk functions were subsequently used in a micro-costing analysis approach. Annual hospital cost savings for Belgium were estimated for two scenarios on the decrease of air pollution: 1) 10% reduction in each of the pollutants and 2) reduction towards annual WHO guidelines.

Results

Emergency admissions for IHD and HRD were significantly associated with PM10, PM2.5, and NO2 exposures the week before admission. The estimated risk reduction for IHD admissions was 2.44% [95% confidence interval (CI): 0.33%–4.50%], 2.34% [95% CI: 0.62%–4.03%], and 3.93% [95% CI: 1.14%–6.65%] for a 10% reduction in PM10, PM2.5, and NO2 respectively. For Belgium, the associated annual cost savings were estimated at €5.2 million, €5.0 million, and €8.4 million respectively. For HRD, admission risk could be reduced by 2.16% [95% CI: 0.14%–4.15%], 2.08% [95% CI: 0.42%–3.70%], and 3.46% [95% CI: 0.84%–6.01%] for a 10% reduction in PM10, PM2.5, and NO2 respectively. This corresponds with a potential annual hospital cost saving in Belgium of €3.7 million, €3.6 million, and €5.9 million respectively. If WHO annual guidelines for PM10 and PM2.5 are met, more than triple these amounts would be saved.

Discussion

This study demonstrates that a model chain of case-crossover and micro-costing analyses can be applied in order to obtain estimates on the impact of air pollution on hospital costs.

Introduction

After the famous Meuse Valley fog in 1930, the Belgian pathologist Firket was one of the first scientists to demonstrate the harmful effects of air pollution on public health (Firket, 1936, in Nemery et al., 2001). Eighty-five years later, significant improvement has been made in the scientific knowledge regarding the effects of air pollutants on the respiratory and cardiovascular system. Numerous epidemiological studies and reviews have demonstrated an association between cardiovascular diseases and acute and chronic exposures to Particulate Matter (PM) with an aerodynamic diameter < 10 μm (PM10) or < 2.5 μm (PM2.5) (Hansen et al., 2012, Rückerl et al., 2011, Brook et al., 2010) and Nitrogen Dioxide (NO2) (Carracedo-Martínez et al., 2010, Shah et al., 2013).

Several international studies and reviews have shown evidence that lowering air pollution exposure leads to less adverse health effects (e.g. Burnett et al., 2014, Pope et al., 2008, Wellenius et al., 2006, WHO Regional office for Europe, 2013). In an era in which the importance of sustainable development and its impact on environment and public health gains more and more recognition worldwide, this outcome forced policy makers to tackle the problem of air pollution. These days, more stringent air quality standards than ever before are applied in the United States (National ambient air quality standards (US EPA, 2015, March 9)), the European Union (Council Directive, 2008/50/EC; The Clean Air Policy Package (European Commission, 2013)) and other countries. Although Belgium still remains one of the most polluted regions in Europe concerning particulate air pollution, it performs relatively well in keeping its air pollution exposure below the European Union air quality guidelines. Despite this observation, adverse health effects still occur at exposure levels well below these guidelines (Beelen et al., 2014). Moreover, the air pollution guidelines published by the World Health Organization (WHO) are stricter and therefore more protective towards public health than the European Union standards (WHO, 2005).

The economic implications of air pollution-related illnesses for society are inevitable but are often overlooked and/or underestimated by policy makers (Landrigan, 2012, Guo et al., 2010, Pervin et al., 2008). However, reductions in air pollution exposure, at every level, are expected to result in a reduction in total external costs. From this perspective, economic data are needed for the debate on priority settings in public health.

In the current study, the aim was to estimate the total averted hospital costs (one component in the total societal cost calculation) in Belgium attributable to a decrease in cardiovascular emergency admissions associated with a short-term reduction in PM10, PM2.5, and NO2. Two reduction scenarios were considered. First, we analyzed the impact of a 10% reduction in short-term air pollution exposure for the study population and extrapolated the effects to a national level. In a second scenario, we assume a reduction of the pollutants towards the levels of the WHO-guidelines and calculate the impact at national level for Belgium. Case-crossover analyses were used (Maclure, 1991) to estimate the impact of air pollutants on emergency admissions for ischemic heart diseases, heart rhythm disturbances, and heart failure. The derived risk functions were used in a hospital cost analysis.

This study might be valuable for policy makers, as the estimated risk functions contribute to the quantification of air pollution related cardiovascular diseases and the hospital cost calculations might guide subsequent cost-benefit analyses.

Section snippets

Emergency admissions

Hospital discharge data on emergency admissions from January 1st 2007 until July 1st 2012 were obtained from UZ Brussels (University Hospital Brussels, Belgium). UZ Brussels is an academic general hospital founded by the Vrije Universiteit Brussel in 1977. The hospital has 721 beds and admits approximately 30,000 patients a year. The emergency department is open 24 h a day treating approximately 65,000 patients a year.

Patients at interest were identified with the following primary discharge

Sample

In total, 4663 patients were identified in the registry database. 47 patients were excluded because of invalid or missing zip code. One patient with an extreme length of stay of more than 500 days and four patients without hospitalization overnight were excluded from the analyses. Depending on the temperature criterion, the number of control days per case ranged from 0 to 22. On average, each case had 7.9 control days. The 219 (4.7%) cases without control days were not included in the analysis. A

Discussion

This study provides a direct insight in the avoidable marginal external costs for society for acute hospital care due to air pollution. We estimated that only a 10% decrease in weekly average PM10 exposure results in 2.16% less emergency hospitalizations for heart rhythm disturbances and 2.44% less emergency hospitalizations for ischemic heart disease. In Belgium, this would result in 3,701,648€ and 5,195,520€ saved hospital costs in one year for these two diseases respectively. The estimates

Acknowledgment

This research has been supported by a research fund of the Vrije Universiteit Brussel (Grant number: IRP DEFIS 42028). There are no competing interests. We would like to express our gratitude to Dr. Karen Pien for her valuable help in the data extraction and Kasper Cockx for his work regarding the development of the maps in the supplementary data section.

References (45)

  • J. Barber et al.

    Analysis of cost data in randomized trials: an application of the non-parametric bootstrap

    Stat. Med.

    (2000)
  • R.D. Brook et al.

    Particulate matter air pollution and cardiovascular disease: an update to the scientific statement from the American Heart Association

    Circulation

    (2010)
  • R.T. Burnett et al.

    An integrated risk function for estimating the global burden of disease attributable to ambient Fine Particulate Matter exposure

    Environ. Health Perspect.

    (2014)
  • E. Carracedo-Martínez et al.

    Case-crossover analysis of air pollution health effects: a systematic review of methodology and application

    Environ. Health Perspect.

    (2010)
  • I. Cleemput et al.

    Belgian Guidelines for Economic Evaluations and Budget Impact Analyses: Second Edition

    (2012)
  • Council Directive

    2008/50/EC on Ambient Air Quality and Cleaner Air for Europe

    (2008)
  • B. Efron et al.

    An Introduction to the Bootstrap

    (1993)
  • European Commission

    Annexes to the Proposal for a Directive of the European Parliament and of the Council on the Reduction of National Emissions of Certain Atmospheric Pollutants and Amending Directive 2003/35/EC

    (2013)
  • J. Firket

    Fog along the Meuse Valley

    Trans. Faraday Soc.

    (1936)
  • J.S. Haukoos et al.

    Advanced statistics: bootstrapping confidence intervals for statistics with “difficult” distributions

    Acad. Emerg. Med.

    (2005)
  • M.M. Huynen et al.

    The impact of heat waves and cold spells on mortality rates in the Dutch population

    Environ. Health Perspect.

    (2001)
  • L. Jacobs et al.

    Air pollution-related prothrombotic changes in persons with diabetes

    Environ. Health Perspect.

    (2010)
  • Cited by (24)

    • Rerouting urban construction transport flows to avoid air pollution hotspots

      2023, Transportation Research Part D: Transport and Environment
    • Differential effects of fine and coarse particulate matter on hospitalizations for ischemic heart disease: A population-based time-series analysis in Southwestern China

      2020, Atmospheric Environment
      Citation Excerpt :

      Further scientific and regulatory interest focusing on those components of the particle fraction that are likely to be more toxic, is needed. Previous epidemiology studies that separately investigated the effect of PM2.5 or PMC on IHD hospitalizations in the USA (Dominici et al., 2006; Powell et al., 2015), Belgium (Devos et al., 2015), Taiwan (Chen et al., 2015), Beijing (Xie et al., 2015), and Shanghai (Xu et al., 2017), showed the potential impact of different fractions of PM on IHD hospitalizations. For example, single-city studies in Shanghai and Beijing found that a 10 μg/m3 increment in PM2.5 coincided with an increase in IHD hospitalizations of 0.25% (95% CI: 0.10%, 0.39%) and 0.27% (95% CI: 0.21%, 0.33%), respectively (Xie et al., 2015; Xu et al., 2017).

    • A dynamic approach to measure the impact of freight transport on air quality in cities

      2019, Journal of Cleaner Production
      Citation Excerpt :

      Different overviews in the literature illustrate large ranges in dose-response functions (Cesaroni et al., 2013; Faustini et al., 2014; Hoek et al., 2013). As a result, Devos et al. (2015a; 2015b) note the importance of the location variable, suggesting the use of locally applicable dose-response functions where possible. Ignoring this variable could lead to incorrect results and affect decision making (for example, in cost-benefit analyses).

    View all citing articles on Scopus
    View full text