Air pollution spikes drive unnecessary antibiotic use, fueling resistance

Invisible Threats in the Air: Linking Pollution to Antibiotic Misuse

In a recent study published in the journal JAMA Network Open, researchers investigated the associations between short-term ambient air pollution exposure and antimicrobial drug consumption.

Study Details

The study employed ecological time series analysis to evaluate if transient exposure to particulate matter of 10 microns (PM₁₀), 2.5 microns (PM_2.5), and nitrogen dioxide (NO₂) could result in patients seeking primary care for respiratory tract distress, subsequently leading to the prescription of antimicrobial pharmacological interventions.

The findings confirmed that air pollution exposure routinely triggers acute respiratory symptoms. However, the study revealed differences in the timing of these effects depending on the type of pollutant, with PM10 and NO2 causing immediate spikes in healthcare consultations, while PM2.5 showed a delayed impact.

Unfortunately, primary healthcare providers often misdiagnose these symptoms as bacterial infections and prescribe antimicrobial drugs to counter their effects, resulting in significantly heightened defined daily dose (DDD) consumption of prescription therapeutics. This delay in response, particularly to PM2.5, highlights the potential for ongoing exposure to exacerbate conditions before symptoms become severe enough to warrant medical attention.

These findings may highlight a hidden driver of antimicrobial drug resistance in bacterial pathogens, informing policy decisions on air pollution and emphasizing the need for in-depth diagnostic tests for patients suffering from respiratory ailments.

Background

Air pollution is one of the most prevalent public health concerns in today’s industrialized world. The World Health Organization (WHO) estimates that more than 95% of humans are exposed to unhealthy concentrations of air pollutants annually.

Primary Air Pollutants and Health Risks

The primary air pollutant triggers of respiratory tract distress include suspended particulate matter (10 microns [PM₁₀], 2.5 microns [PM_2.5]) and prolonged exposure to inorganic oxides (e.g., nitrogen dioxide [NO₂], ozone [O₃], and oxides of sulfur) of which NO₂ is the most frequently encountered.

These pollutants are commonly associated with increased risk or exacerbation of stroke, heart disease, cancers, and respiratory tract distress. The study also identified notable differences across various cities in Catalonia, indicating that local factors may influence the degree of impact these pollutants have on respiratory health. Unfortunately, primary partitioners often misdiagnose the latter condition as bacterial infections.

Antimicrobial Resistance: A Global Threat

The WHO has named antimicrobial resistance as one of the 10 greatest global public threats facing humanity. It has been estimated that in 2019, 4.95 million deaths were associated with infections caused by multidrug-resistant bacteria. Moreover, mortality attributable to antimicrobial resistance is expected to reach 10 million deaths per year by 2050.

Misdiagnoses and erroneous use of antimicrobial interventions against air pollutant-induced respiratory distress have been hypothesized as significant drivers of antimicrobial resistance in common pathogens. Still, this notion has never been formally tested within a scientific framework.

About the Study

The present study (titled ‘ONAIR’) was a 2-stage cross-sectional investigation leveraging ecological time series analysis to assess the relationship between transient air pollution exposure and the subsequent consumption of antimicrobial agents.

Study data was acquired between June 2012 and December 2019 from the Public Data Analysis for Health Research and Innovation Program (health data) and the Atmospheric Pollution Monitoring and Forecasting Network of the Catalan government (air quality data) and included the 11 most populous cities from Catalonia, Spain.

Participants’ data was anonymously collected with ‘service area’ (primary healthcare) as the cohort identifier. Ten μg/m³ surges in daily mean values of PM₁₀, PM_2.5, and NO₂ were recorded as ‘day 0′, and medical health records were perused for data on antimicrobial drugs dispensed/prescribed (for suspected respiratory disease) in the following 30 days. Variables of interest included participants’ age, sex, social income, adjusted morbidity groups, and body mass index (BMI).

Quasi-Poisson generalized linear models (GLMs) were used to compute defined daily doses (DDDs) of prescription antimicrobials within the study period. The study’s design also incorporated adjustments for potential confounders such as temperature and relative humidity, ensuring a robust analysis of the pollution-antimicrobial use relationship. Between-city heterogeneity was estimated using the Higgins I2 estimator and the Cochran Q test. Outcomes were reported as relative risks (RRs).

Study Findings

The study revealed that the final sample cohort size was 1,983,333 individuals (55% female, 48 years median age) who consumed 8,421,404 antimicrobial courses (12.26 DDDs/1000).

Study outcomes revealed a 10 μg/m³ increase in PM₁₀ significantly increased primary healthcare consultations between days 0-3 following exposure. Equivalent exposure to PM_2.5 was found to have a delayed effect, with consultations spiking at day 0 and then again between days 7-10. Nitrogen dioxide exposure only resulted in respiratory distress and primary healthcare consultations on the day of exposure (day 0).

The study further identified a “protective association” in the days following PM10 exposure, suggesting a possible temporary depletion of the most vulnerable individuals from the population at risk, which may lead to a temporary reduction in new cases immediately after the initial spike.

Meta-analysis reveals two potential hypotheses about the mode of action of these pollutants – direct and indirect. According to the direct hypothesis, exposure to air pollutants (day 0) causes respiratory tract distress (irritation), resulting in healthcare-seeking consultations.

In the indirect hypothesis, air pollutants may interfere with patients’ immune systems, triggering a decline in their normal immune responses, subsequently resulting in respiratory tract infections requiring medical attention (delayed responses at days 7-10). Study findings suggest that PM₁₀ and NO₂ follow the former hypothesis while PM_2.5 aligns with the latter.

Together, these findings highlight substantial increases in antimicrobial drug prescriptions/dispensations shortly following spikes in poor ambient air quality, emphasizing the role of air pollution in potentially unnecessary pharmacological interventions that may contribute to rapid increases in global antibiotic-resistant bacterial populations.

Additionally, the study underscores the importance of localized air quality improvements, as the effects varied across the different cities studied, suggesting that targeted interventions could be more effective in mitigating these risks. They underscore the need for air quality improvements and enhanced diagnostic tests capable of differentiating between pollutant-induced irritation and pathogen-induced respiratory tract infections.

Conclusions

The present study used a 2-phase long-term (7+ years) large cohort (almost 2 million participants) cross-sectional investigation utilizing ecological time series analysis to investigate the association between common air pollutants and antibiotic resistance in bacteria.

Study findings reveal that transient exposure to surges in poor air quality significantly increases respiratory tract distress, resulting in antimicrobial prescriptions despite the apparent lack of bacterial influence. They suggest a complex interaction between air pollution and healthcare practices, where immediate and delayed responses to pollutants can lead to the overuse of antimicrobials, particularly in urban populations.

The research underscores the need for intensive global efforts to curb poor air quality and cautions primary healthcare providers to exercise caution when prescribing pharmacological interventions against respiratory ailments.

SDGs, Targets, and Indicators

1. SDG 3: Good Health and Well-being

   • Target 3.3: By 2030, end the epidemics of AIDS, tuberculosis, malaria, and neglected tropical diseases and combat hepatitis, water-borne diseases, and other communicable diseases.
   • Indicator 3.3.2: Tuberculosis incidence per 100,000 population.
   • Indicator 3.3.5: Number of people requiring interventions against neglected tropical diseases.

2. SDG 6: Clean Water and Sanitation

   • Target 6.3: By 2030, improve water quality by reducing pollution, eliminating dumping, and minimizing release of hazardous chemicals and materials, halving the proportion of untreated wastewater, and increasing recycling and safe reuse globally.
   • Indicator 6.3.2: Proportion of bodies of water with good ambient water quality.

3. SDG 11: Sustainable Cities and Communities

   • Target 11.6: By 2030, reduce the adverse per capita environmental impact of cities, including by paying special attention to air quality and municipal and other waste management.
   • Indicator 11.6.2: Annual mean levels of fine particulate matter (e.g., PM2.5 and PM10) in cities (population-weighted).

4. SDG 13: Climate Action

   • Target 13.2: Integrate climate change measures into national policies, strategies, and planning.
   • Indicator 13.2.1: Number of countries that have integrated mitigation, adaptation, impact reduction, and early warning into primary, secondary, and tertiary curricula.

5. SDG 15: Life on Land

   • Target 15.1: By 2020, ensure the conservation, restoration, and sustainable use of terrestrial and inland freshwater ecosystems and their services, in particular forests, wetlands, mountains, and drylands, in line with obligations under international agreements.
   • Indicator 15.1.2: Proportion of important sites for terrestrial and freshwater biodiversity that are covered by protected areas, by ecosystem type.

Table: SDGs, Targets, and Indicators

Source: news-medical.net