Attributable Risk to Assess the Health Impact of Air Pollution: Advances, Controversies, State of the Art and Future Needs
Abstract
:1. Aims and Definitions of the Health Impact Assessment and its Measurements
2. Health Impact Assessment of Air Pollution
2.1. Short-term Effects
- They involve larger populations and can recruit a larger number of cases, thus increasing the power of association;
- They can observe the same relationship under different circumstances, such as seasons, and in different populations thus making causality a more plausible interpretation of any possible association, providing that heterogeneity has been controlled for or assessed;
- Even a “weak” effect of air pollution on health will constitute an important public health problem, since a unique characteristic of air pollution exposure is its ubiquity for large populations.
- The researchers thereafter proposed a “Measurement error model for time-series studies of air pollution and mortality” which was a combination of the Berkson model; and the Bayesian hierarchical generalized additive model (GAM).The Berkson model [35] deals with the relationship between ambient concentration and personal exposure by comparing the two measurements to estimate the error between them. Although the Berkson error—unlike the misclassification—causes little or no bias in the association, the difference between the average personal exposure and the true ambient level has been identified as an important source of bias in log-linear models [36].The Bayesian hierarchical generalized additive model was the tool for modeling variability across the studies of the relationship between personal and ambient exposure concentrations. Two different approaches were available: a hierarchical multivariate regression with missing predictors for either continuous or categorical data [37].
- They included gaseous pollutants in subsequent studies on air pollution effects. This innovation was supported by using a hierarchical model to assess exposure-health outcome association which made it possible to estimate the independent effects of multiple pollutants in the presence of measurement error [38].
- They adopted a longer scale of mortality linked to short-term exposure which overcame the mortality displacement [39], and helped to introduce the long-term studies.
- They took into account the temporal structure of the exposure–response relationship which led to including effects of up to 5 days after exposure peak or harvesting. The distributed lag models played the major role in assessing the new exposure–response relationship of short-term effects [40,41]. Later, the study by Gasparrini and Leone [42] extended the definition of attributable risk within the framework of distributed lag models.
- They revised the frailty hypothesis—which restricted mortality to the frail people-by showing that larger effects occurred in frail people only at shorter time scales [43].
- The first approach overcame the limited capacity of the time-series so as to take account of spatial variation [47] and the introduction of Cox proportional hazards models in spatio-temporal analysis introduced the possibility of estimating results for different geographic levels, such as cities and states;
2.2. Long-term Effects
- A more comprehensive picture of the health effects of air pollution, which include cancer [58,59], metabolic diseases [60], maternal and birth outcomes [61,62], developmental effects [63], cognitive impairment [64] and central nervous system (CNS) diseases [65]. All these additional diseases have a progression that is consistent with cumulative exposure and progressive mechanisms of damage, such as chronic or degenerative diseases;
- An updated definition of “adverse health effects of air pollution” that includes asymptomatic signs of health deterioration, such as biological effects, altered biomarkers and reduced functions [66];
- The extension of exposure-lag-response models to allow for the health effects due to the protracted exposures to environmental factors [69].
2.3. Health Effects of Abatement in Air Pollution
3. When Scientific Evidence is clear enough to Promote Interventions
3.1. The Role of the Dose–Response Curve in Assessing a Causal Relationship between Air Pollution and Health Effects
3.2. The Adoption of New Analytic Perspectives and Statistical Methods to DirectlyAssess the Effects of Air Pollution Interventions on Air Quality and Health
- The first one, the “causal” health impact on mortality-among Medicare beneficiaries-in areas which exceeded the PM10 limits, was compared with the mortality rates among Medicare beneficiaries in areas where PM10 limits were not reached. The members of the first group were assumed to be randomly assigned to “treatment”, after testing their comparability with the second group (controls) for potential confounders by using the propensity-score method. In other words, this causal approach allows the consideration of mortality rates among controls as the mortality that might have occurred among cases had their area’s exposure been below the PM10 limit.
- The second case study examined the extent to which sulfur dioxide (SO2) affects emissions of SO2, nitrogen oxides (NO(x)), and carbon dioxide (CO2). The authors tested a range of scrubber technologies to reduce multiple gaseous pollutants (SO2, NO2 and CO2) in emissions and outdoor PM2.5 concentrations in areas where plants were either equipped with scrubbers or were not so equipped. The causal estimates were supported by applying principal stratification and causal mediation methods to assess the exposure, while a Bayesian nonparametric method was used to evaluate whether the effect on PM2.5 was really mediated by reducing gas emissions.
3.3. The Question of When the Scientific Evidence is Clear Enough, is still an Ongoing Discussion
4. Health Impact Assessment of Air Pollution to Evaluate Interventions of Exposure Reduction and the Effectiveness of Legislation
- The ban of coal sales in Dublin was followed by an important decrease in black smoke concentrations (70%); natural mortality decreased by 5.7%, respiratory mortality by 15.5% and cardiovascular mortality by 10.3% [110].
- Reducing the sulfur content in fuel in Hong Kong was followed by a substantial reduction in seasonal deaths during the first 12 months, followed by a peak death rate in the subsequent cool-season. It seemed that the intervention led to a significant decline in the annual trend of deaths from all causes (2.1%; p = 0.001), respiratory (3.9%; p = 0.0014) and cardiovascular (2.0%; p = 0.0214) diseases, but not from other causes. The average gain in life expectancy attendant upon the lower pollutant concentration was 20 to 41 days [111].
- Some measures to reduce traffic were implemented in more than one situation. The results in these cases are conclusive as regards neither exposures nor health effects.
- The first, appearing five years after the introduction of the CCS, showed a modest benefit in air pollution levels and life expectancy. The explanation given was that the greater reductions in air pollution in deprived areas have had only a small impact in counteracting the socioeconomic inequalities in exposure and mortality rates [114].
- The second study, published eight years after the introduction of the CCS, deals with the oxidative potential (OP) of PM as a parameter of traffic exposure. It shows a remarkable variation of OP between roadside and urban background locations, which was attributed to varying PM components. This result is consistent with the increased vehicle use throughout London in recent years and a decreased number of vehicles entering the CCS [115].
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
Note
References
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Faustini, A.; Davoli, M. Attributable Risk to Assess the Health Impact of Air Pollution: Advances, Controversies, State of the Art and Future Needs. Int. J. Environ. Res. Public Health 2020, 17, 4512. https://doi.org/10.3390/ijerph17124512
Faustini A, Davoli M. Attributable Risk to Assess the Health Impact of Air Pollution: Advances, Controversies, State of the Art and Future Needs. International Journal of Environmental Research and Public Health. 2020; 17(12):4512. https://doi.org/10.3390/ijerph17124512
Chicago/Turabian StyleFaustini, Annunziata, and Marina Davoli. 2020. "Attributable Risk to Assess the Health Impact of Air Pollution: Advances, Controversies, State of the Art and Future Needs" International Journal of Environmental Research and Public Health 17, no. 12: 4512. https://doi.org/10.3390/ijerph17124512
APA StyleFaustini, A., & Davoli, M. (2020). Attributable Risk to Assess the Health Impact of Air Pollution: Advances, Controversies, State of the Art and Future Needs. International Journal of Environmental Research and Public Health, 17(12), 4512. https://doi.org/10.3390/ijerph17124512