| Literature DB >> 29202828 |
Philippe Grandjean1,2, Martine Bellanger3.
Abstract
Calculation of costs and the Burden of Disease (BoD) is useful in developing resource allocation and prioritization strategies in public and environmental health. While useful, the Disability-Adjusted Life Year (DALY) metric disregards subclinical dysfunctions, adheres to stringent causal criteria, and is hampered by gaps in environmental exposure data, especially from industrializing countries. For these reasons, a recently calculated environmental BoD of 5.18% of the total DALYs is likely underestimated. We combined and extended cost calculations for exposures to environmental chemicals, including neurotoxicants, air pollution, and endocrine disrupting chemicals, where sufficient data were available to determine dose-dependent adverse effects. Environmental exposure information allowed cost estimates for the U.S. and the EU, for OECD countries, though less comprehensive for industrializing countries. As a complement to these health economic estimations, we used attributable risk valuations from expert elicitations to as a third approach to assessing the environmental BoD. For comparison of the different estimates, we used country-specific monetary values of each DALY. The main limitation of DALY calculations is that they are available for few environmental chemicals and primarily based on mortality and impact and duration of clinical morbidity, while less serious conditions are mostly disregarded. Our economic estimates based on available exposure information and dose-response data on environmental risk factors need to be seen in conjunction with other assessments of the total cost for these environmental risk factors, as our estimate overlaps only slightly with the previously estimated environmental DALY costs and crude calculations relying on attributable risks for environmental risk factors. The three approaches complement one another and suggest that environmental chemical exposures contribute costs that may exceed 10% of the global domestic product and that current DALY calculations substantially underestimate the economic costs associated with preventable environmental risk factors. By including toxicological and epidemiological information and data on exposure distributions, more representative results can be obtained from utilizing health economic analyses of the adverse effects associated with environmental chemicals.Entities:
Keywords: Attributable risk; Burden of illness; Lead; Mercury; Neurotoxicity; Pesticides
Mesh:
Substances:
Year: 2017 PMID: 29202828 PMCID: PMC5715994 DOI: 10.1186/s12940-017-0340-3
Source DB: PubMed Journal: Environ Health ISSN: 1476-069X Impact factor: 5.984
Fig. 1For individual environmental risks, the costs of exposure-dependent adverse effects can be estimated using health economics methods, and they can then be compared to costs associated with the estimated disease burden in terms of disability adjusted life years
Estimates of economic costs associated with lead and other neurotoxicant exposure
| Risk factor | Adverse consequences | Context | Economic cost ($billions) | % GDP | % of Global GDP |
|---|---|---|---|---|---|
| Lead exposure | Cognitive deficits | LMICs [ | 1040 [775.5–1237] | 5.20 [3.9–6.2] | 1.68 [1.25–1.99] |
| U.S. [ | 54.0 [47.5–64.3] | 0.37 [0.33–0.44] | 0.09 [0.08–0.1] | ||
| EU [ | 60.6 [53.7–72.2] | 0.36 [0.32–0.43] | 0.1 [0.09–0.12] | ||
| Total (sum) | 1154 [876.7–1373.5] | 2.47 [1.88–2.94] | 1.83 [1.39–2.18] | ||
| Intellectual disability only | World (WHO) [ | 16 [10–40] | <0.01 | <0.01 | |
| World (GDB) [ | 246 [154–615] | 0.4 [0.24–1] | 0.4 [0.24–1] | ||
| Neurotoxicity total | World (WHO) [ | 5 [3.15–12.6] | <0.01 | <0.01 | |
| World (GBD) [ | 283 [177–708] | 0.45 [0.27–1.1] | 0.45 [0.27–1.1] | ||
| Methylmercury | Cognitive deficits | U.S. [ | 4·8 [4.2–5.7] | 0.03 [0.026–0.04] | <0.01 |
| EU [ | 10.8 [9,6–11.2] | 0.06 [0.053–0.062] | <0.01 | ||
| Sum | 15.6 [13.8–16.9] | 0.05 [0.044–0.54] | <0.01 | ||
| Organophosphate pesticides | Cognitive deficits | U.S. [ | 44.7 [14.6–59.5] | 0.30 [0.1–0.4] | 0.07 [0.2–0.09] |
| EU [ | 194 [62–259] | 1.14 [0.37–1.52] | 0.31 [0.09–0.4] | ||
| Sum | 248.7 [76.6–318.5] | 0.8 [0.25–1.02] | 0.38 [0.11–0.49] | ||
| Polybrominated diphenyl ethers | Cognitive deficits | U.S. [ | 266 [133–367] | 1.8 [0.9–2.5] | 0.4 [0.2–0.6] |
| EU [ | 12·6 [2.08–29.4] | 0.07 [0.011–0.16] | 0.02 [0.003–0.05] | ||
| Sum | 278.6 [135.08–396.4] | 0.9 [0.43–1.28] | 0.42 [0.23–0.65] |
Estimates of economic costs associated with air pollution
| Adverse consequence | Context | Economic cost ($billions) | % GDP | % of Global GDP |
|---|---|---|---|---|
| Asthma | U.S. [ | 2.33 [0.728–2.5] | 0.02 [0.006–0.021] | <0.01 |
| EU [ | 1.70 [0.568–1.98] | 0.01 [0.003–0.012] | <0.01 | |
| EU city children [ | 0.151 [0.03–0.3]a | <0.01 | <0.01 | |
| Preterm birth | U.S. [ | 4.3 [2.06–8.22] | <0.01 | <0.01 |
| Cardiovascular | EU [ | 37.24 [24.47–49.83]a | 0.22 [0.14–0.29] | 0.06 |
| All health impacts | OECD countries [ | 500 [300–1250] | 1.2 [0.7–2.8] | 0.8 [0.5–2] |
| China [ | 483 [300–1200] | 8 [5–20] | 0.8 [0.5–2] | |
| India [ | 120 [74–300] | 7 [4–17] | 0.2 [0.1–5] | |
| Sum (OECD, China, India) | 1100 [700–2760] | 2.2 [1.3–5.4] | 1.8 [1.1–4.4] | |
| World (WHO) [ | 1177 [736–2942] | 1.9 [1.1–4.6] | 1.9 [1.1–4.6] | |
| World (GBD) [ | 1083 [677–2709] | 1.7 [1.1–4.3] | 1.7 [1.1–4.3] |
Base case estimates are presented along with range [low/high end estimates] from sensitivity analysis or 95 CIa. All estimates are given in $2010, a 1.33 rate change € /$ is used, and for estimates prior to 2010, inflated adjustments are made. OECD estimates are based on DALYs reported for OECD countries (High Income Countries, HICs), China (Upper Middle Income Country, UMIC), & India (Lower Middle Income Country, LMIC). Our estimates of DALYs for OECD, WHO and GBD are based on Value of Life Year (VOLY) [50] adjusted to $2010 PPP and for inflation and then adjusted per income group levels from World Bank GNI per capita in $ppp2010. For consistency we valued OECD DALY estimates based on VOLY instead of using Value of Statistical Life Year (VSL) for mortality costs (additional 10% for morbidity included) as reported in OECD [100]
Environmental burdens of disease in terms of DALYs, economic value, and percent of GDP for major health outcomes based on attributable risks derived by WHO [29]a
| Disease | DALYs (% fraction of total burden of disease in DALYs) | Environmental AF (%) | DALYs due to environmental risk factors | Economic cost ($billions) | % of Global GDP |
|---|---|---|---|---|---|
|
| |||||
| Asthma | 25,202,418 (0.9) | 44 (26–53) | 11,055,150 | 200 [124–500] | 0.3 [0.2–0.8] |
| Chronic obstructive pulmonary disease | 92,376,604 (3.4) | 35 (20–48) | 32,280,160 | 400 [250–1000] | 0.6 [0.4–1.5] |
| Lower respiratory infections | 146,863,685 (5.4) | 35 (27–41) | 51,752,605 | 530 [330–1320] | 0.8 [0.5–2.1] |
|
| |||||
| Lung cancer | 38,535,303 (1.4) | 36 (17–52) | 13,902,105 | 285 [180–720] | 0.5 [0.3–1.1] |
| Other cancers | 185,421,704 (6.8) | 16 (7–41) | 31,047,781 | 715 [450–1800] | 1.1 [0.7–2.8] |
|
| |||||
| Ischemic heart diseases | 165,717,210 (6.0) | 35 (26–46) | 58,561,915 | 1065 [670–2660] | 1.8 [1.1–4.2] |
| Stroke | 141,348,082 (5.2) | 42 (24–53) | 58,985,984 | 843 [527–2108] | 1.3 [0.8–3.3] |
|
| |||||
| Childhood behavioral disorders | 6,208,771 (0.22) | 12 (3–36) | 742,156 | 12 [8–30] | 0.02 [0.01–0.05]]] |
|
| 258,327,866 | 4050 [2500–10,140] | 6.5 [4–15.8] | ||
aTotal DALYs, 2,743,857,491 (2012 values); Breakdown of DALYS for LMICs and HICs from WHO supplement [29]
Estimates of economic costs associated with EDC exposures in the EU [81] and the US [39]
| EDC | Adverse consequences | Context | Economic costs ($millions) | % GDP (2010) | % of Global GDP |
|---|---|---|---|---|---|
| Polybrominated diphenyl ethers (PBDEs) | Testicular cancer | US | 81.5 [24.8–109.3] | <0.01 | <0.01 |
| EU | 1100 [416–1100] | <0.01 | <0.01 | ||
| Cryptorchidism | US | 35.7 [NA - NA] | <0.01 | <0.01 | |
| EU | 172.6 [155.5–172.6] | <0.01 | <0.01 | ||
| Dichlorodiphenyl trichloroethane (DDE) | Childhood obesity | US | 29.6 [NA - 57.3] | <0.01 | <0.01 |
| EU | 32.7 [NA - 114.8] | <0.01 | <0.01 | ||
| Adult diabetes | US | 1800 [NA – 13,500] | <0.01 [NA - 0.08] | <0.01 | |
| EU | 1100 [NA – 22,065] | <0.01 [NA - 0.13] | <0.01 | ||
| Fibroids | US | 259 [NA - NA] | <0.01 | <0.01 | |
| EU | 216.8 [NA - NA] | <0.01 | <0.01 | ||
| Di-2-ethylhexyl phthalate | Adult obesity | US | 1700 [NA - NA] | 0.011 | <0.01 |
| EU | 20,800 [NA - NA] | 0.12 | <0.01 | ||
| Adult diabetes | US | 91.4 [NA - NA] | <0.01 | <0.01 | |
| EU | 807.2 [NA - NA] | <0.01 | <0.01 | ||
| Endometriosis | US | 47,000 [NA - NA] | 0.32 | <0.01 | |
| EU | 1700 [NA - NA] | 0.01 | <0.01 | ||
| Bisphenol A | Childhood obesity | US | 2400 [NA - NA] | 0.02 | <0.01 |
| EU | 2000 [NA - NA] | 0.02 | <0.01 | ||
| Benzyphtalates & butylphalates | Male infertility resulting in Increasesed ART | US | 2500 [NA - NA] | 0.02 | <0.01 |
| EU | 6300 [NA - NA] | 0.04 | 0.01 | ||
| Phtalates | Low testoterone and increased early mortality | US | 8800 [NA - NA] | 0.06 | 0.012 |
| EU | 10,600 [NA - NA] | 0.05 | 0.012 | ||
| Multiple exposures | Attention deficit hyperactivity disorder (ADHD) | US | 698 [568–1950] | <0.01 [<0.01–0.011] | <0.01 |
| EU | 3056 [1600–3800] | 0.014 [<0.01–0.017] | <0.01 | ||
| Autism | US | 1984 [803–4100] | 0.014 [<0.01–0.024] | <0.01 | |
| EU | 352 [105–530] | <0.01 | <0.01 | ||
| All compounds included | US | 340,000 [668–612,000] | 2.33 [<0.01–3.53] | 0.54 [<0.01 0.96] | |
| EU | 217,000 [110,049–359,239] | 1.2 [0.75–2.12] | 0.34 [0.17–0.57] | ||
| Sum | 557,000 [110,707–971,239] | 1.8 [0.3–3.07] | 0.88 [0.17–1.54] |
NA: Not available
Base case estimates are presented along with ranges [Low end and High end estimates] from sensitivity analyses, when available
All estimates are given in $2010, for EU a 1.33 rate change € /$ is used, and for estimates prior to 2010, inflated adjustments are made