Global Association of Air Pollution and Cardiorespiratory Diseases: A Systematic Review, Meta-Analysis, and Investigation of Modifier Variables

Abstract

Background: Little is known about the health risks of air pollution and cardiorespiratory diseases, globally, across regions and populations, which may differ because of external factors.

Objectives: We systematically reviewed the evidence on the association between air pollution and cardiorespiratory diseases (hospital admissions and mortality), including variability by energy, transportation, socioeconomic status, and air quality.

Search methods: We conducted a literature search (PubMed and Web of Science) for studies published between 2006 and May 11, 2016.

Selection criteria: We included studies if they met all of the following criteria: (1) considered at least 1 of these air pollutants: carbon monoxide, sulfur dioxide, nitrogen dioxide, ozone, or particulate matter (PM_2.5 or PM₁₀); (2) reported risk for hospital admissions, mortality, or both; (3) presented individual results for respiratory diseases, cardiovascular diseases, or both; (4) considered the age groups younger than 5 years, older than 65 years, or all ages; and (5) did not segregate the analysis by gender.

Data collection and analysis: We extracted data from each study, including location, health outcome, and risk estimates. We performed a meta-analysis to estimate the overall effect and to account for both within- and between-study heterogeneity. Then, we applied a model selection (least absolute shrinkage and selection operator) to assess the modifier variables, and, lastly, we performed meta-regression analyses to evaluate the modifier variables contributing to heterogeneity among studies.

Main results: We assessed 2183 studies, of which we selected 529 for in-depth review, and 70 articles fulfilled our study inclusion criteria. The 70 studies selected for meta-analysis encompass more than 30 million events across 28 countries. We found positive associations between cardiorespiratory diseases and different air pollutants. For example, when we considered only the association between PM_2.5 and respiratory diseases ( Figure 1 , we observed a risk equal to 2.7% (95% confidence interval = 0.9%, 7.7%). Our results showed statistical significance in the test of moderators for all pollutants, suggesting that the modifier variables influence the average cardiorespiratory disease risk and may explain the varying effects of air pollution.

Conclusions: Variables related to aspects of energy, transportation, and socioeconomic status may explain the varying effect size of the association between air pollution and cardiorespiratory diseases. Public Health Implications. Our study provides a transferable model to estimate the health effects of air pollutants to support the creation of environmental health public policies for national and international intervention.

FIGURE 1—

Global Association Between Air Pollution (Fine Particulate Matter ≤ 2.5 µm) and Health

FIGURE 2—

Global Association Between Air Pollution and Health Stratified by Age, Health Outcome, and Diseases, for (a) Carbon Monoxide, (b) Nitrogen Dioxide, (c) Ozone, (d) PM₁₀, (e) PM_2.5, and (f) Sulphur Dioxide: Studies Published Between 2006 and May 11, 2016 Note. PM₁₀ = fine particulate matter of ≤ 10 µm; PM_2.5 = fine particulate matter of ≤ 2.5 µm. Because most of the studies reported results for more than 1 category of pollutant, health outcome, disease, or age, “n” here represents the number of reports, and not the number of studies. Red circle = hospital admissions; blue circle = mortality; black circle = there is no report; whiskers = 95% confidence interval.

FIGURE 3—

Cardiorespiratory Disease Risk (%) Attributable to Exposure to Particulate Air Pollutants and Distribution of Significant Modifier Variables by Country, in Studies Published Between 2006 and May 11, 2016 Note. Biofuels = consumption of biofuels, 1000 barrels per day/100 000 people; Clean Elect. = clean electricity production, %; Cooking = percentage of population using solid fuels as main cooking fuel; Educ. = education, mean years of schooling; Elect. = total electricity net consumption, annual billion kWh per 100 000 people; Gas = consumption of motor gasoline, 1000 barrels per day/100 000 people; PM₁₀ = fine particulate matter of ≤ 10 µm; PM_2.5 = fine particulate matter of ≤ 2.5 µm; Pop. = population density; Smoking = prevalence of smoking, %; Urban Pop. = urban population, %. We selected the modifier variables shown here on the basis of the modifiers that presented significant coefficients (Appendix H, available as a supplement to the online version of this article at http://www.ajph.org). We calculated the mean value for each modifier variable by considering the study period stated in the literature. According to our selection criteria, there are no studies reporting risk for the specific particulate and country (—). Green color scheme represents the range values of each modifier variable, for which dark green is the highest value. Red color scheme represents the range values of each health variable (cardiorespiratory disease risk), for which dark red is the highest value.