Columbia University, NYU, and Ichan School of Medicine at Mt. Sinai, New York, NY; Health Investment & Financing, New York, NY.
Health, Nutrition and Population Global Practice of the World Bank, Washington, DC; Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.
Ann Glob Health. 2016 Sep-Oct;82(5):711-721. doi: 10.1016/j.aogh.2016.12.003.
The research done for this paper is part of the background analysis undertaken to support the work of the Global Commission on Pollution, Health and Development, an initiative of The Lancet, the Global Alliance on Health and Pollution, and the Icahn School of Medicine at Mount Sinai. The paper expands on areas where the current literature has gaps in knowledge related to the health care cost of pollution.
This study aims to generate an initial estimate of total tangible health care expenditure attributable to man-made pollution affecting air, soil and water.
We use two methodologies to establish an upper and lower bounds for pollution related health expenditure. Key data points in both models include (a) burden-of-disease (BoD) at the national level in different countries attributable to pollution; and (b) the total cost of health care at the national level in different countries using standard national health accounts expenditure data.
Depending on which determinist model we apply, annual expenditures range from US$630 billion (upper bound) to US$240 billion (lower bound) or approximately three to nine percent of global spending on health care in 2013 (the reference year for the analysis). Although only 14 percent of global total for pollution related health care spending is in lower- and middle-income countries (LMICs) in our primary (lower bound) model, the relative share of spending for pollution related illness is substantial, especially in very low-income countries. Cancer, chronic respiratory and cardio/cerebrovascular illnesses account for the largest health care spending items linked to pollution even in LMICs.
These conditions have historically received less attention by national governments, international public health organizations and development/financial agencies than infectious disease and maternal/child health sectors. Other studies posit that intangible costs associated with environmental pollution include lower productivity and reduced income - components which our models do not attempt to capture. The financial and health impacts are substantial even when we exclude intangible costs, yet it is likely that in many LMICs poor households simply forgo medical treatment and lose household income as a result of man-made environmental degradation.
When evaluating the value of public health or environmental programs which prevent or limit pollution-related illness, policy makers should consider the health benefits, the tangible cost offsets (estimated in our models) and the opportunity costs.
本文的研究工作是支持全球污染、健康与发展委员会（The Lancet、全球健康与污染联盟和西奈山伊坎医学院的倡议）工作的背景分析的一部分。本文扩展了当前文献在与污染导致的医疗保健成本相关的知识方面存在差距的领域。
本研究旨在初步估算因人为污染空气、土壤和水而导致的有形医疗保健总支出。
我们使用两种方法来确定污染相关健康支出的上限和下限。两个模型中的关键数据点包括：（a）不同国家归因于污染的疾病负担（BoD）；以及（b）不同国家使用标准国家卫生账户支出数据的国家一级医疗保健总支出。
根据我们应用的哪种决定论模型，每年的支出范围从 6300 亿美元（上限）到 2400 亿美元（下限），或约占 2013 年（分析的参考年份）全球医疗保健支出的三到九分之一。尽管我们的主要（下限）模型中，与污染相关的医疗保健支出仅占全球总支出的 14%，但污染相关疾病的支出相对份额很大，尤其是在非常低收入国家。即使在中低收入国家（LMICs），癌症、慢性呼吸道和心血管/脑血管疾病也占与污染相关的最大医疗保健支出项目。
与传染病和母婴/儿童健康部门相比，这些疾病在历史上受到国家政府、国际公共卫生组织和发展/金融机构的关注较少。其他研究认为，与环境污染相关的无形成本包括生产力下降和收入减少——我们的模型没有试图捕捉到这些因素。即使我们排除了无形成本，其财务和健康影响也是巨大的，但在许多中低收入国家，贫困家庭可能只是因为人为的环境退化而放弃医疗和失去家庭收入。
在评估预防或限制与污染相关的疾病的公共卫生或环境计划的价值时，政策制定者应考虑健康效益、有形成本抵消（我们的模型中估计）和机会成本。
