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Lancet. 2020 Oct 17;396(10258):1223-1249. doi: 10.1016/S0140-6736(20)30752-2.
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Health-care spending attributable to modifiable risk factors in the USA: an economic attribution analysis.美国可改变风险因素导致的医疗保健支出:经济归因分析。
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PLoS One. 2020 Sep 11;15(9):e0238565. doi: 10.1371/journal.pone.0238565. eCollection 2020.
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Comparative analysis of the economic burdens of physical inactivity in Hungary between 2005 and 2017.2005 年至 2017 年匈牙利身体活动不足的经济负担比较分析。
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[Trends in excess male mortality in the working age population in a region with the highest mortality rates in Poland].[波兰死亡率最高地区劳动年龄人口男性超额死亡率趋势]
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8
Production losses associated with premature mortality in 28 European Union countries.28 个欧盟国家因过早死亡导致的生产损失。
J Glob Health. 2019 Dec;9(2):020418. doi: 10.7189/jogh.09.020418.
9
Production Losses Associated with Alcohol-Attributable Mortality in the European Union.与欧盟酒精相关死亡率相关的生产损失。
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Effects of behavioural risk factors on high-cost users of healthcare: a population-based study.行为风险因素对医疗保健高消费人群的影响:基于人群的研究。
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波兰因可改变的健康风险因素导致的死亡造成的生产损失。

Production losses due to mortality associated with modifiable health risk factors in Poland.

机构信息

Department of Health Economics, Nicolaus Copernicus University in Toruń, Toruń, Poland.

Department of Analyses and Strategies, Ministry of Health, Warsaw, Poland.

出版信息

Eur J Health Econ. 2022 Feb;23(1):33-45. doi: 10.1007/s10198-021-01345-6. Epub 2021 Jul 8.

DOI:10.1007/s10198-021-01345-6
PMID:34236544
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8882090/
Abstract

BACKGROUND

Epidemiological burden of modifiable mortality risk factors is recognized in literature; however, less is known on the economic losses due to a range of such risks.

AIM

To estimate production losses (indirect cost) of mortality associated with risk factors as classified in Global Burden of Disease 2019 Study in Poland in years 2000, 2010, and 2017.

METHODS

We relied on the human capital method and societal perspective and used sex-, age-, region-, and risk-specific data on mortality due to modifiable risk factors and a set of socio-economic measures.

RESULTS

The production losses due to mortality attributable to all investigated risk factors accounted for 19.6-21.0 billion PLN (Polish zloty; 2017 exchange rate: 1€ = 4.26 PLN) and 1.44-2.45% of gross domestic product, depending on year. Behavioural factors were the most important contributor to overall burden (16.7-18.2 billion PLN), followed by metabolic factors (6.8-7.6 billion PLN) and environmental and occupational factors (3.0-3.5 billion PLN). Of disaggregated risks, alcohol and tobacco, high systolic blood pressure, and dietary risks proved to lead to the highest losses. Cost per death was greatest for child and maternal malnutrition, followed by intimate partner violence and childhood sexual abuse and bullying. Moreover, a notable regional variation of indirect cost was identified with losses ranging from 1.21 to 1.81% of regional gross domestic product in 2017.

CONCLUSION

Our findings provide economically hierarchised list of modifiable risk factors and they contribute to inform policy-makers in prioritizing programmes to improve health.

摘要

背景

文献中已认识到可改变的死亡风险因素的流行病学负担;然而,对于一系列此类风险导致的经济损失知之甚少。

目的

评估 2000 年、2010 年和 2017 年波兰全球疾病负担研究中分类的风险因素相关死亡的生产损失(间接成本)。

方法

我们依赖人力资本法和社会视角,使用性别、年龄、地区和风险特异性的可改变风险因素死亡率数据以及一系列社会经济措施。

结果

归因于所有调查风险因素的死亡率导致的生产损失占 196-210 亿波兰兹罗提(波兰货币;2017 年汇率:1 欧元=4.26 波兰兹罗提),占国内生产总值的 1.44%-2.45%,取决于年份。行为因素是总负担的最重要贡献者(167-182 亿波兰兹罗提),其次是代谢因素(68-76 亿波兰兹罗提)和环境与职业因素(30-35 亿波兰兹罗提)。在细分风险中,酒精和烟草、高血压和饮食风险导致的损失最大。每例死亡的成本最高的是儿童和孕产妇营养不良,其次是亲密伴侣暴力、儿童性虐待和欺凌。此外,还发现间接成本存在显著的地区差异,2017 年的损失范围占地区国内生产总值的 1.21%-1.81%。

结论

我们的研究结果提供了可改变风险因素的经济分层清单,有助于为决策者提供优先改善健康的方案。