Either your web browser doesn't support Javascript or it is currently turned off. In the latter case, please turn on Javascript support in your web browser and reload this page. Language: English Portuguese. Ecological study of time series. The independent variables were the concentration of fine particulate, estimated by a mathematical model, temperature and relative air humidity, controlled by short and long-term trends. Generalized additive model of Poisson regression was used.
Relative risks, proportional attributable risk PAR and excess hospitalizations and their respective costs by the population attributable fraction PAF were calculated. The mean concentration, estimated by the mathematical model, was For boys, there was no significant association; for girls a relative risk of up to 1. Significant effect in daily hospitalizations due to respiratory diseases related to exposure to fine particulate matter was noted for girls, suggesting the need for stratification by sex in further studies.
Foram internadas 1. In addition to known factors - such as low birth weight, lack of breastfeeding, overcrowded household, and presence of smokers -, exposure to air pollutants is also associated with hospitalizations for respiratory diseases, especially pneumonia.
Particulate matter is a mixture of liquid and solid particles suspended in the air, whose composition and size depend on the emission source. Air pollutants are usually quantified in measuring stations of state environmental agencies. However, not all states have environmental agencies, including Mato Grosso. The model estimates PM 2. Recently, different responses to exposure to air pollutants according to the gender of adult subjects have been revealed. Studies suggest that health responses to air pollution could differ between women and men, and between girls and boys, but it is not yet clear whether the response observed is a result of biological differences related to gender or differences in activity patterns, co-exposure, or even accuracy in exposure measurement.
Possibly, these differences consist of some combination of two factors - exposure patterns and biological response. Data on PM 2. We created a time-series from January 1, to December 31, and recovered data on hospitalizations from November and December by researching information from January and February We carried out a descriptive analysis of these variables and, due to a difference in the effect of exposure over the days, we used a lag of up to seven days lag 0 to lag 7.
