Evaluation of Environmental Contamination by Heavy Metals and Relationship with Cardiovascular Risk in a Population of Barcarena-PA.

Heavy metals are widely used to sustain the living standards of the modern world. Due to their prevalence, the risk of human exposure is an increasing threat to public health as they can cause negative health effects, such as cardiovascular diseases (CVDs). In this study, the objective was to evaluate clinical-epidemiological and biochemical parameters in relation to the overall risk score (ERG) of developing CVDs in 112 individuals aged 30 to 74 years living in the city of Barcarena-PA. The results of heavy metal contamination and biochemical parameters were applied in the ERG calculation. A significance level of p < 0.05 was adopted in the statistical tests. The values were high for chromium (Cr) (45.8%) and aluminum (Al) (98.6%). As for the ERG for CVDs, they obtained low risk (42%), medium risk (40%), and high risk (18%). In individuals with high ERG, a significant association was detected with increasing age group, in individuals ≥ 60 years (p < 0.0001). The relationship between concomitant Al and Cr intoxication and increased ERG was also significant (p = 0.0016). The probability of high cardiovascular risk among individuals contaminated by Al + Cr is higher than that of individuals contaminated by Al alone (p = 0.0074). Such evidence indicates that continuous environmental monitoring in the municipality of Barcarena is of extreme importance, since the population is in a situation of vulnerability in relation to their health.

Chemometrics Applied in the Development of a Water Quality Indicator System for the Brazilian Amazon.

The objective of this work was to develop a method to calculate the water quality index (WQI) using chemometric methods. The study was carried out at the Curuá-Una hydroelectric power plant in the state of Pará in the Brazilian Amazon. Eight collection stations in four periods (winter, intermediate I, summer, and intermediate II) and 29 parameters were selected. Multivariate analysis was applied to the results to verify the quality of the data and to select the most sensitive variables to be used as indicators for the WQI calculation. The 10 parameters selected were E h, dissolved oxygen, total dissolved solids, chlorophyll a, phosphate, Ba, Ca, Fe, Na, and Sn. The WQI proposed herein was effective in the classification of water quality for the periods analyzed.