Meta-analysis of Value of Statistical Life Estimates

2017 ◽  
Vol 6 (1) ◽  
pp. 110-120 ◽  
Author(s):  
Agamoni Majumder ◽  
S. Madheswaran
Keyword(s):  
Wage Differential ◽  
Meta Analysis ◽  
Policy Instrument ◽  
Value Of Statistical Life ◽  
Mortality Risks ◽  
Statistical Life ◽  
Compensating Wage Differential ◽  
Health Related ◽  
Emerging Issues ◽  
Hedonic Wage

Value of Statistical Life (VSL) is one of the most debatable areas in economics. However, VSL is frequently used as a policy instrument for evaluating various safety, health and environmental regulations. Policymakers have to undertake the difficult task of assigning monetary value to the reduction of various health and mortality risks while analyzing safety policies. Compensating wage differential (CWD) for job risks acts as a reference point for valuing mortality risks while VSL serves as a basis to analyze these benefits of risk reduction policies. However, it has been observed in the recent past that VSL estimates vary substantially across various studies. Therefore, it has become necessary for researchers and policymakers to understand the source of this variation in order to aid policymaking. This paper attempts to bring together some of the emerging issues in VSL literature and presents a meta-analysis that is based on 34 observations from 30 hedonic wage-based VSL studies. The results of this meta-analysis show that certain emerging areas in VSL literature such as worker’s compensation benefits, age and long-term health-related job risk require more emphasis and further examination.

scholarly journals Groundwater Arsenic-Attributable Cardiovascular Disease (CVD) Mortality Risks in India

Water ◽  
2021 ◽  
Vol 13 (16) ◽  
pp. 2232
Author(s):  
Ruohan Wu ◽  
Lingqian Xu ◽  
David A. Polya
Keyword(s):  
Chronic Exposure ◽  
Population Attributable Fraction ◽  
Attributable Fraction ◽  
Value Of Statistical Life ◽  
Mortality Risks ◽  
Statistical Life ◽  
Exposure Pathway ◽  
Groundwater Arsenic ◽  
Cvd Mortality ◽  
High Arsenic

Cardiovascular diseases (CVDs) have been recognized as the most serious non-carcinogenic detrimental health outcome arising from chronic exposure to arsenic. Drinking arsenic contaminated groundwaters is a critical and common exposure pathway for arsenic, notably in India and other countries in the circum-Himalayan region. Notwithstanding this, there has hitherto been a dearth of data on the likely impacts of this exposure on CVD in India. In this study, CVD mortality risks arising from drinking groundwater with high arsenic (>10 μg/L) in India and its constituent states, territories, and districts were quantified using the population-attributable fraction (PAF) approach. Using a novel pseudo-contouring approach, we estimate that between 58 and 64 million people are exposed to arsenic exceeding 10 μg/L in groundwater-derived drinking water in India. On an all-India basis, we estimate that 0.3–0.6% of CVD mortality is attributable to exposure to high arsenic groundwaters, corresponding to annual avoidable premature CVD-related deaths attributable to chronic exposure to groundwater arsenic in India of between around 6500 and 13,000. Based on the reported reduction in life of 12 to 28 years per death due to heart disease, we calculate value of statistical life (VSL) based annual costs to India of arsenic-attributable CVD mortality of between USD 750 million and USD 3400 million.

scholarly journals The value of statistical life in road safety: a meta-analysis

2003 ◽  
Vol 35 (6) ◽  
pp. 973-986 ◽  
Author(s):  
Arianne de Blaeij ◽  
Raymond J.G.M Florax ◽  
Piet Rietveld ◽  
Erik Verhoef
Keyword(s):  
Road Safety ◽  
Meta Analysis ◽  
Value Of Statistical Life ◽  
Statistical Life

Impact of early childhood caries on oral health‐related quality of life: a systematic review and meta‐analysis

2021 ◽  
Author(s):  
Carlos Zaror ◽  
Andrea Matamala‐Santander ◽  
Montse Ferrer ◽  
Fernando Rivera‐Mendoza ◽  
Gerardo Espinoza‐Espinoza ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Systematic Review ◽  
Early Childhood ◽  
Oral Health ◽  
Early Childhood Caries ◽  
Meta Analysis ◽  
Health Related Quality ◽  
Related Quality ◽  
Health Related

scholarly journals A heart failure phenotype stratified model for predicting 1-year mortality in patients admitted with acute heart failure: results from an individual participant data meta-analysis of four prospective European cohorts

BMC Medicine ◽  
2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Yuntao Chen ◽  
Adriaan A. Voors ◽  
Tiny Jaarsma ◽  
Chim C. Lang ◽  
Iziah E. Sama ◽  
...  
Keyword(s):  
Heart Failure ◽  
Clinical Decision Making ◽  
Cox Model ◽  
Meta Analysis ◽  
Prognostic Index ◽  
Individual Participant Data ◽  
Mortality Risks ◽  
Baseline Mortality ◽  
Individual Participant ◽  
Stratified Model

Abstract Background Prognostic models developed in general cohorts with a mixture of heart failure (HF) phenotypes, though more widely applicable, are also likely to yield larger prediction errors in settings where the HF phenotypes have substantially different baseline mortality rates or different predictor-outcome associations. This study sought to use individual participant data meta-analysis to develop an HF phenotype stratified model for predicting 1-year mortality in patients admitted with acute HF. Methods Four prospective European cohorts were used to develop an HF phenotype stratified model. Cox model with two rounds of backward elimination was used to derive the prognostic index. Weibull model was used to obtain the baseline hazard functions. The internal-external cross-validation (IECV) approach was used to evaluate the generalizability of the developed model in terms of discrimination and calibration. Results 3577 acute HF patients were included, of which 2368 were classified as having HF with reduced ejection fraction (EF) (HFrEF; EF < 40%), 588 as having HF with midrange EF (HFmrEF; EF 40–49%), and 621 as having HF with preserved EF (HFpEF; EF ≥ 50%). A total of 11 readily available variables built up the prognostic index. For four of these predictor variables, namely systolic blood pressure, serum creatinine, myocardial infarction, and diabetes, the effect differed across the three HF phenotypes. With a weighted IECV-adjusted AUC of 0.79 (0.74–0.83) for HFrEF, 0.74 (0.70–0.79) for HFmrEF, and 0.74 (0.71–0.77) for HFpEF, the model showed excellent discrimination. Moreover, there was a good agreement between the average observed and predicted 1-year mortality risks, especially after recalibration of the baseline mortality risks. Conclusions Our HF phenotype stratified model showed excellent generalizability across four European cohorts and may provide a useful tool in HF phenotype-specific clinical decision-making.

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