In 1 study, older populations had statistically higher particulate matter—associated risk estimates than younger populations for total and stroke deaths but not for respiratory or cardiovascular deaths Of the 26 studies that investigated whether age modifies particulate matter—associated hospitalizations, risk estimates were statistically higher for older populations than for younger populations in 4 studies and lower in 1 study, with no statistically significant evidence of effect modification in the remaining 21 studies.
Figure 2 provides meta-analysis results for age from 30 pairs of estimates from 23 studies that used individual-level data. Other studies that used individual-level data were excluded from meta-analysis because of differences in study designs e.
Solid points represent results for younger populations; open points represent results for older populations. Risks for older populations were 0.
The remaining 26 pairs of estimates from 19 studies resulted in 0. Overall estimates adjusted for publication bias were increases of 0. By using these results, we found risk estimates to be 0. We concluded that there is strong evidence that the risk of death associated with short-term particulate matter exposure is higher in older populations than in younger populations. No statistically significant associations were reported in the 9 studies that examined effect modification by race 31 , 33 , 42— Thus, we concluded that these studies present no evidence of effect modification by race; however, the investigation of race was limited.
All studies were conducted in the United States. In all cases, race was categorized simplistically, such as percent African American 45 or nonwhite The most commonly studied SES indicator was education, which generally was based on educational attainment. Two of the 10 mortality studies 30 , 49 with individual-level data on education and 1 of the 6 mortality studies 50 with community-level data on education found higher particulate matter—associated risks with lower educational level; the remaining studies found no statistically significant evidence of effect modification.
One study examined whether the risk of hospitalization was affected by educational level and found no such evidence when using community-level data Income level was examined for particulate matter—associated death risk estimates in 8 studies with community-level data e.
For the 3 studies examining community-level income data and hospitalization risk, 1 found higher risk in lower income communities 54 , whereas the remaining studies did not find evidence of effect modification 51 , Poverty was examined only as a community-level variable in 3 mortality studies 44 , 56 , 57 and 4 hospitalization studies 48 , 55 , 58 , One study found lower SES to be associated with lower particulate matter—associated hospitalization risk; during the warm season, risk estimates were lower in communities in 36 US cities with higher proportions of persons over 65 years of age living in poverty Overall, we found no evidence of effect modification by poverty, although no studies examined individual-level poverty data.
Effect modification for particulate matter—associated death by employment status was analyzed in 7 mortality studies and no hospitalization studies. Based on individual-level data, risk estimates were higher for those with lower employment status, for unemployed persons compared with white-collar employees 30 , and for blue-collar workers or never employed persons compared with white-collar workers Risk estimates were higher for communities with higher unemployment rates in 2 studies 5 , 40 but not in a third community-level study We found that age is the most consistent effect modifier of the association between short-term exposure to particulate matter and death and hospitalization, with older persons experiencing higher risks.
Our analysis of age compared risks for older and younger populations; however, the very young may also be susceptible. Children could face higher risks because their biological systems are under development, they breathe more air per body weight than do adults, and they typically spend more time outdoors. Exposures to PM 2. Future work could investigate whether particulate matter risks are modified for infants and children. A recent review discussed potential reasons for effect modification by sex on respiratory outcomes associated with exposure to PM 2.
Exposures related to occupation, cooking, physical activity, smoking status, and personal care products vary by sex. Men and women differ in dermal absorption, lung function, and absorption of gases through the respiratory system. Hormonal changes can affect relationships between dose and effective dose. A recent review found that most studies of adults observed stronger air pollution risks in women than in men and recommended more research to identify the relevant pathways, noting that differences between sexes differ by society Although our analysis did not provide evidence that race modifies particulate matter—associated risks, the identified studies are limited.
All studies used simplistic race categorizations e. Great Britain, Canada, and the United States have revised their census surveys to include multirace choices Researchers have noted that hypotheses on health disparities by race are largely characterized by 3 mechanisms 69 , which could be extrapolated to differences in particulate matter—associated health risks by race. The first is a biological mechanism of genetic susceptibility to disease by race.
Because racial groups are based not only on genetics but also on social and community relationships, this explanation is unlikely to fully explain differences by race. The second mechanism is race as an indicator of SES.
Race and SES can be correlated, challenging efforts to disentangle their effects; however, this pathway also is unlikely to fully explain health differences because race is not a fully adequate SES surrogate.
For example, in the United States during —, more than 9 million blacks or African Americans Some have proposed a more multifaceted third mechanism of race and class as separate influences, with potential interactions e. SES could modify particulate matter—associated health risks through differences in access to health care, baseline health status, occupational exposures, and nutrition. Studies investigating multiple SES indicators generally had consistent within-study results.
For example, evidence of effect modification was identified for all of the SES indicators considered in several mortality studies e. No associations were observed for any of the multiple indicators considered in other studies e.
However, this was not true in all cases e. Furthermore, although evidence for effect modification by lower SES was generally consistent within a given study, some studies found such evidence, some did not, and 1 study found the opposite result i. Evidence on effect modification by SES has been limited by the use of community-level data.
Health is associated with individual characteristics, as well as the community in which a person lives 71 , although few studies have evaluated SES by using individual-level data. The indicators discussed here do not fully represent true SES. Limitations stem from the reliability of each indicator's measurement, the inability to capture lifetime history of SES, unmeasured assets e. The use of occupational data to gauge SES can affect estimates differently by sex because women have less heterogeneity in occupations than men Although SES indicators are generally correlated, this correlation can vary by population, including among races within an area Relationships between SES and access to medical care differ by region e.
Some SES indicators are more associated with overall health status than others. There is some evidence that economic indicators such as income have stronger associations with health than do indicators based on occupation or education 75 , 76 , and that SES is more related to health in some areas than in others The potential effect modifiers examined here are not independent of each other or of other potential modifiers. Levels of physical activity change with age and differ by sex and age 77 , Smoking rates are often higher for men e.
Studies are needed on effect modification within the complex system of multiple social, economic, and environmental factors, which may vary across regions in terms of the direction and level of effect modification and their relationships with each other e. Regarding our categories of degree of evidence, results such as weak or no evidence of effect modification reflect the current scientific evidence, although modification may indeed exist.
Limitations of this study include problems inherent in the designation of results as statistically significant 80—82 and in publication bias 83 , 84 , under which results e. Thus, results from studies that did not find evidence of effect modification may be underrepresented in the literature. In fact, the results of our meta-analyses indicate publication bias. Further, many studies that did not find statistically significant evidence did find higher risks for some groups than for others.
Our methodology was designed to allow the manageable review and presentation of papers; however, studies without statistically significant results should not be interpreted as definitive evidence of the absence of effect modification.
Most studies were designed to investigate hypotheses other than effect modification, so a study designed to address effect modification specifically may differ from those used e.
Although we focused on selected effect modifiers, the identified studies considered many other effect modifiers, primarily addressing season, weather, location, pollution, and health status. Effect modification was examined with respect to season and weather e. Pollutants as effect modifiers were studied by using long-term levels of copollutants e. Health status was evaluated with individual-level data for comorbidities, such as causes of previous hospitalizations or concurrent conditions, smoking status, dietary intakes, and community-level, age-standardized death rates.
Other potential effect modifiers considered include individual-level data on housing type e. Although we summarized evidence for several key modifiers, a multitude of other individual and environmental factors may modify particulate matter—associated health risks.
A better understanding of vulnerability and susceptibility and, more generally, of effect modification, can provide evidence on which to base the targeting of local air quality efforts to specific populations. It can also inform our understanding of biological mechanisms e. Future efforts are needed to further investigate effect modification and the suggestive evidence summarized here. To the degree feasible, researchers should address factors that may modify air pollution estimates and incorporate them into analyses.
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Sign In or Create an Account. Sign In. Advanced Search. Search Menu. Article Navigation. Close mobile search navigation Article Navigation. Volume Article Contents Abstract. Bell , Michelle L. Oxford Academic. Antonella Zanobetti. Francesca Dominici. Cite Cite Michelle L. Select Format Select format. Permissions Icon Permissions. Abstract Although there is strong evidence that short-term exposure to particulate matter is associated with health risks, less is known about whether some subpopulations face higher risks.
Figure 1. Open in new tab Download slide. Figure 2. An estimate of the global burden of anthropogenic ozone and fine particulate matter on premature human mortality using atmospheric modeling. Google Scholar Crossref. Search ADS. Fine particulate air pollution and hospital admission for cardiovascular and respiratory diseases. Google Scholar PubMed.
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Research on human beings has been slow to observe that the subjects recruited are susceptible, especially so if research is done in less developed countries. By mislabelling them as vulnerable--a characteristic they share with all humans--sponsors avoid registering the deprivation these people suffer, and the ethical obligation to offer them remedial help.
The distinction between vulnerability and susceptibility also marks the difference between being intact but fragile--vulnerable--and being injured and predisposed to compound additional harm--susceptible.
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