Correlations between particulate matter pollutant factors and morbimortality in Romania-a study with focus on...

Atmospheric pollution greatly impacts public health, since accumulating scientific data found credible evidence between pollutant exposure and various causes of morbimortality. In the 42 counties of Romania some pollutant substances and particles are monitored trough 152 stations. The study focuses on particulate matter (PM₁₀ and PM_2.5) data analysis in correlation with public health statistics. Spearman tests were used to correlate contemporaneous yearly average PM values to morbidity and mortality and showed a statistically significant weak positive correlation between PM₁₀ and PM_2.5 average yearly concentrations (μg/m3) and morbidities for lung cancer (LC) (r = 0.211, p < 0.001; r = 0.166, p = 0.022, respectively) and asthma (r = 0.264, p < 0.001; r = 0.31, p < 0.001, respectively). For mortalities, PM_2.5 showed a positive weak correlation with congenital and chromosomal anomalies (CCA) (r = 0.21, p = 0.004) while PM₁₀ showed weaker positive correlations with multiple mortality causes (tuberculosis, CCA, early childhood mortalities (< 27 days, < 1 year and < 5 years). Other correlation results involving morbidities or mortalities from other causes were not reliable due to the high impact of SARS-Cov2 pandemic on hospital admissions and deaths but also on data reporting. The Welch 2-sample T-test performed for the comparison of the most (Gorj, 30.03 μg/m³) and least (Harghita, 16.80 μg/m³) PM₁₀ polluted counties showed an increase in LC (p = 0.002) and asthma (p = 0.279) admissions for the polluted county. The 3-year exposure window emerged as a predictor for morbidity for lung cancer and asthma using single and dual linear regression models. For asthma, the fine fraction (PM_2.5) remained the primary independent driver, adding 5.28 admissions per 100,000 inhabitants for every increase with 1 μg/m³. For lung cancer, the coarse particle fraction exhibited the strongest independent effect on hospitalizations, adding 2.85 admissions per 100,000 inhabitants for every unit increase in concentration. Based on the results of the linear regression models, avoidable burden maps for morbidity from lung cancer and asthma were built, which can be useful tools for adapting public health and environmental policies on the dynamic of the PM concentrations in time and space.