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Effects of air pollution and factors meteorological on cardiovascular diseases in Presidente Prudente/SP

Grant number: 14/10581-3
Support Opportunities:Scholarships in Brazil - Scientific Initiation
Effective date (Start): July 01, 2014
Effective date (End): June 30, 2016
Field of knowledge:Health Sciences - Physiotherapy and Occupational Therapy
Principal Investigator:Dionei Ramos
Grantee:Iris Cristina Coripio
Host Institution: Faculdade de Ciências e Tecnologia (FCT). Universidade Estadual Paulista (UNESP). Campus de Presidente Prudente. Presidente Prudente , SP, Brazil

Abstract

Air pollution is associated with increasing morbimortality of individuals exposed in large urban centers. However, the cities of state of São Paulo, such as Presidente Prudente, has increased the fleet and the flow of vehicles and also have adjacent sugarcane mills as major sources of air pollution emissions, which can raise the concentration of air pollutants and the number of hospitalizations. However, there are few studies that assess the relationship between air pollution and hospital admissions for cardiovascular diseases in inner cities. Objectives: To investigate the effect of air pollution and meteorological factors on hospital admissions by cardiovascular diseases. Methodology: Daily data of hospital admissions by cardiovascular diseases (ICD10 - I00 to I99 ) will be obtained through the database SUS (SUS-DATE) of adults aged 45 to 79 years, residents in the city of Presidente Prudente / SP. Mean daily levels of air pollutants (PM10, NO2) and temperature data (T) and relative humidity (RH) will be obtained from CETESB (Companhia de Tecnologia de Saneamento Ambiental), which has a fixed station in the city cited. Statistics Analysis: Cardiovascular diseases will be considered dependent variables and daily mean levels of air pollutants as independent variables. The generalized additive regression model (GAM) will be used to assess the relationship between cardiovascular diseases, air pollution and meteorological factors. Finally, will be calculated the raise of hospital admissions in relation to interquartile difference of significant pollutants in the regression model.

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