Background Recent studies have reported associations between particulate air pollution and daily mortality rates. Population-based, cross-sectional studies of metropolitan areas in the United States have also found associations between particulate air pollution and annual mortality rates, but these studies have been criticized, in part because they did not directly control for cigarette smoking and other health risks. Methods In this prospective cohort study, we estimated the effects of air pollution on mortality, while controlling for individual risk factors. Survival analysis, including Cox proportional-hazards regression modeling, was conducted with data from a 14-to-16-year mortality follow-up of 8111 adults in six U.S. cities. Results Mortality rates were most strongly associated with cigarette smoking. After adjusting for smoking and other risk factors, we observed statistically significant and robust associations between air pollution and mortality. The adjusted mortality-rate ratio for the most po...

An Association between Air Pollution and Mortality in Six U.S. Cities

Efforts to understand and mitigate the health effects of particulate matter (PM) air pollution have a rich and interesting history. This review focuses on six substantial lines of research that have been pursued since 1997 that have helped elucidate our understanding about the effects of PM on human health. There has been substantial progress in the evaluation of PM health effects at different time-scales of exposure and in the exploration of the shape of the concentration-response function. There has also been emerging evidence of PM-related cardiovascular health effects and growing knowledge regarding interconnected general pathophysiological pathways that link PM exposure with cardiopulmonary morbidity and mortality. Despite important gaps in scientific knowledge and continued reasons for some skepticism, a comprehensive evaluation of the research findings provides persuasive evidence that exposure to fine particulate air pollution has adverse effects on cardiopulmonary health. Although much of this research has been motivated by environmental public health policy, these results have important scientific, medical, and public health implications that are broader than debates over legally mandated air quality standards.

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Health effects of fine particulate air pollution: lines that connect

Air pollution and health.

This review is written with the goal of informing public health concerns related to nanoscience, while raising awareness of nanomaterials toxicity among scientists and manufacturers handling them. We show that humans have always been exposed to nanoparticles and dust from natural sources and human activities, the recent development of industry and combustion-based engine transportation profoundly increasing anthropogenic nanoparticulate pollution. The key to understanding the toxicity of nanoparticles is that their minute size, smaller than cells and cellular organelles, allows them to penetrate these basic biological structures, disrupting their normal function. Among diseases associated with nanoparticles are asthma, bronchitis, lung cancer, neurodegenerative diseases (such as Parkinson`s and Alzheimer`s diseases), Crohn`s disease, colon cancer. Nanoparticles that enter the circulatory system are related to occurrence of arteriosclerosis, and blood clots, arrhythmia, heart diseases, and ultimately cardiac death. We show that possible adverse effects of nanoparticles on human health depend on individual factors such as genetics and existing disease, as well as exposure, and nanoparticle chemistry, size, shape, and agglomeration state. The faster we will understand their causes and mechanisms, the more likely we are to find cures for diseases associated with nanoparticle exposure. We foresee a future with better-informed, and hopefully more cautious manipulation of engineered nanomaterials, as well as the development of laws and policies for safely managing all aspects of nanomaterial manufacturing, industrial and commercial use, and recycling.

Nanomaterials and nanoparticles: Sources and toxicity

This review is presented as a common foundation for scientists interested in nanoparticles, their origin, activity, and biological toxicity. It is written with the goal of rationalizing and informing public health concerns related to this sometimes-strange new science of “nano,” while raising awareness of nanomaterials’ toxicity among scientists and manufacturers handling them. We show that humans have always been exposed to tiny particles via dust storms, volcanic ash, and other natural processes, and that our bodily systems are well adapted to protect us from these potentially harmful intruders. The reticuloendothelial system, in particular, actively neutralizes and eliminates foreign matter in the body, including viruses and nonbiological particles. Particles originating from human activities have existed for millennia, e.g., smoke from combustion and lint from garments, but the recent development of industry and combustion-based engine transportation has profoundly increased anthropogenic particulate pollution. Significantly, technological advancement has also changed the character of particulate pollution, increasing the proportion of nanometer-sized particles-“nanoparticles”-and expanding the variety of chemical compositions. Recent epidemiological studies have shown a strong correlation between particulate air pollution levels, respiratory and cardiovascular diseases, various cancers, and mortality. Adverse effects of nanoparticles on human health depend on individual factors such as genetics and existing disease, as well as exposure, and nanoparticle chemistry, size, shape, agglomeration state, and electromagnetic properties. Animal and human studies show that inhaled nanoparticles are less efficiently removed than larger particles by the macrophage clearance mechanisms in the lungs, causing lung damage, and that nanoparticles can translocate through the circulatory, lymphatic, and nervous systems to many tissues and organs, including the brain. The key to understanding the toxicity of nanoparticles is that their minute size, smaller than cells and cellular organelles, allows them to penetrate these basic biological structures, disrupting their normal function. Examples of toxic effects include tissue inflammation, and altered cellular redox balance toward oxidation, causing abnormal function or cell death. The manipulation of matter at the scale of atoms, “nanotechnology,” is creating many new materials with characteristics not always easily predicted from current knowledge. Within the nearly limitless diversity of these materials, some happen to be toxic to biological systems, others are relatively benign, while others confer health benefits. Some of these materials have desirable characteristics for industrial applications, as nanostructured materials often exhibit beneficial properties, from UV absorbance in sunscreen to oil-less lubrication of motors. A rational science-based approach is needed to minimize harm caused by these materials, while supporting continued study and appropriate industrial development. As current knowledge of the toxicology of “bulk” materials may not suffice in reliably predicting toxic forms of nanoparticles, ongoing and expanded study of “nanotoxicity” will be necessary. For nanotechnologies with clearly associated health risks, intelligent design of materials and devices is needed to derive the benefits of these new technologies while limiting adverse health impacts. Human exposure to toxic nanoparticles can be reduced through identifying creation-exposure pathways of toxins, a study that may someday soon unravel the mysteries of diseases such as Parkinson’s and Alzheimer’s. Reduction in fossil fuel combustion would have a large impact on global human exposure to nanoparticles, as would limiting deforestation and desertification. While nanotoxicity is a relatively new concept to science, this review reveals the result of life’s long history of evolution in the presence of nanoparticles, and how the human body, in particular, has adapted to defend itself against nanoparticulate intruders.

https://avs.scitation.org/doi/pdf/10.1116/1.2815690

The relation between air pollution and mortality in London was examined for the winters of 1958-1972. The data exhibited a high degree of autocorrelation, requiring analyses using autoregressive models. There was a highly significant relation between mortality and either particulate matter or sulfur dioxide (after controlling for temperature and humidity), both overall and in each individual year. Graphic analysis revealed a nonlinear relation with no threshold, and a steeper exposure-response curve at lower air pollution levels. In models with both pollutants, particulate matter remained a significant predictor with about a 10% reduction in its estimated coefficients, while sulfur dioxide was insignificant, with a large drop in its estimated coefficient. The authors conclude that particulates are strongly associated with mortality rates in London, and the relation is likely causal.

Mortality and air pollution in London: a time series analysis

Dose-response curves for erythrocyte protoporphyrin vs blood lead: effects of iron status

The integrated exposure uptake biokinetic (IEUBK) model, recommended for use by the U.S. Environmental Protection Agency at residential Superfund sites to predict potential risks to children from lead exposure and to establish lead remediation levels, requires an interindividual geometric standard deviation (GSDi) as an essential input parameter. The GSDi quantifies the variability of blood lead concentrations for children exposed to similar environmental concentrations of lead. Estimates of potential risks are directly related to the GSDi, and therefore the GSDi directly impacts the scope of remediation at Superfund sites. Site-specific GSDi can be calculated for sites where blood lead and environmental lead have been measured. This paper uses data from blood and environmental lead studies conducted at the Bingham Creek and Sandy, Utah, Superfund sites to calculate GSDi using regression modeling, box modeling, and structural equation modeling. GSDis were calculated using various methods for treating values below the analytical method detection and quantitation limits. Treatment of nonquantifiable blood lead concentrations affected the GSDi more than the statistical method used to calculate the GSDi. For any given treatment, the different statistical methods produced similar GSDis. Because of the uncertainties associated with data in the blood lead studies, we recommend that a range of GSDis be used when analyzing site-specific risks associated with exposure to environmental lead instead of a single estimate. Because the different statistical methods produce similar GSDis, we recommend a simple procedure to calculate site-specific GSDi from a scientifically sound blood and environmental lead study.

Calculating the interindividual geometric standard deviation for use in the integrated exposure uptake biokinetic model for lead in children.

Although formal hypothesis tests provide a convenient framework for displaying the statistical results of empirical comparisons, standard tests should not be used without consideration of underlying measurement error structure. As part of the validation process, predictions of individual blood lead concentrations from models with site-specific input parameters are often compared with blood lead concentrations measured in field studies that also report lead concentrations in environmental media (soil, dust, water, paint) as surrogates for exposure. Measurements of these environmental media are subject to several sources of variability, including temporal and spatial sampling, sample preparation and chemical analysis, and data entry or recording. Adjustments for measurement error must be made before statistical tests can be used to empirically compare environmental data with model predictions. This report illustrates the effect of measurement error correction using a real dataset of child blood lead concentrations for an undisclosed midwestern community. We illustrate both the apparent failure of some standard regression tests and the success of adjustment of such tests for measurement error using the SIMEX (simulation-extrapolation) procedure. This procedure adds simulated measurement error to model predictions and then subtracts the total measurement error, analogous to the method of standard additions used by analytical chemists.

Some useful statistical methods for model validation.

Concentrations of size-resolved airborne particulate matter measured in Phoenix, Arizona in 1995-1996 indicate a strong linear relationship between the soil components of PM 2.5 and the intermodal PM concentration and similarly between the nonsoil components of PM 2.5 and the PM 1 concentration. Moreover, the ratio of PM 1 to intermodal PM varies considerably at all reported concentrations of PM 2.5 , and this variation appears to be systematically related to the proportion of PM 2.5 comprised of soil components.

https://www.tandfonline.com/doi/pdf/10.1080/02786820126854

Allan H. Marcus

Papers

Mortality and air pollution in London: a time series analysis

Dose-response curves for erythrocyte protoporphyrin vs blood lead: effects of iron status

Calculating the interindividual geometric standard deviation for use in the integrated exposure uptake biokinetic model for lead in children.

Some useful statistical methods for model validation.

PM 1 , Intermodal (PM 2.5-1 ) Mass, and the Soil Component of PM 2.5 in Phoenix, AZ, 1995-1996