Global Economic Cost of Deaths Attributable to Ambient Air Pollution: Disproportionate Burden on the Ageing Population
Notice bibliographique
Résumé
Summary Background The health impacts of ambient air pollution impose large costs on society. While all people are exposed to air pollution, older individuals tend to be disproportionally affected. As a result, there is growing concern about the public health impacts of air pollution as many countries undergo rapid population ageing. We investigated the spatial and temporal variation in the health economic cost of deaths attributable to ambient air pollution, and its interaction with population ageing from 2000 to 2016 at global and regional levels. Methods We developed an age-adjusted measure of the value of a statistical life year (VSLY) to estimate the health economic cost attributable to ambient PM 2.5 pollution using the Global Burden of Disease 2017 data and country-level socioeconomic information. First, we estimated the global age- and cause-specific mortality and years of life lost (YLL) attributable to PM 2.5 pollution using the global exposure mortality model (GEMM) and global estimates of exposure derived from ground monitoring, satellite retrievals and chemical transport model simulations at 0.1° × 0.1° (~11 km at the equator) resolution. Second, for each year between 2000 and 2016, we translated the YLL within each age-group into a health-related economic cost using a country-specific, age-adjusted measure of VSLY. Third, we decomposed the major driving factors that contributed to the temporal change in health costs related to PM 2.5 . Finally, we conducted a sensitivity test to analyze the variability of the estimated health costs to four alternative valuation measures. We identified the uncertainty intervals (UIs) from 1000 draws of the parameters and exposure-response functions by age, cause, country and year. All economic values are reported in 2011 purchasing-power-parity-adjusted US dollars. Findings Globally, 8.42 million (95% UI: 6.50, 10.52) deaths and 163.68 million (116.03, 219.44) YLL were attributable to ambient PM 2.5 in 2016. The average attributable mortality for the older population was 12 times higher than for those younger than 60 years old. In 2016, the global health economic cost of ambient PM 2.5 pollution for the older population was US$2.40 trillion (1.89, 2.93) accounting for 59% of the cost for the total population. The health cost for the older population alone was equivalent to 2.1% (1.7%, 2.6%) of global gross domestic product (GDP) in 2016. While the economic cost per capita for the older population was US$2739 (2160, 3345) in 2016, the cost per capita for the younger population was only US$268 (205, 335). From 2000 to 2016, the annual global health economic cost for the total population increased from US$2.37 trillion (1.88, 2.87) to US$4.09 trillion (3.19, 5.05). Decomposing the factors that contributed to the rise in health economic costs, we found that increases in GDP per capita, population ageing, population growth, age-specific mortality reduction, and PM 2.5 exposure changed the total health economic cost by 77%, 21.2%, 15.6%, -41.1% and -0.2%, respectively. Compared to using an age-invariant VSLY or an age-invariant value of a statistical life (VSL), the estimates of the older population’s share of the total health economic cost using an age-adjusted VSLY was 2 and 18 percentage points lower, respectively.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».