Análisis de la relación del PM10 con las enfermedades respiratorias en la población urbana de Mexicali, Baja California: Un estudio de series de tiempo

Abstract

Mexicali is the third most contaminated city of the country, the second by particles smaller than 10 micrometers in diameter (PM10), the mean annual standards (50 µg/m3) are continuously surpassed. Its North American counterpart, the Imperial Valley is in the same geographic area but slightly higher levels of particulate matter. Associated with PM10, Imperial reports the highest child asthma index in California, the same holds for Mexicali related to Baja California. The primary source for PM10 are of natural origin, dust and pollen primarily; the anthropogenic sources are gaining importance due to an accelerated growth in this bi-national basin. The recently built thermoelectric plants are an indication of this and its implied ecological impact is a source of concern taking into account the already diminished quality of air. Very few published documents focus on health or Mexicali’s environment, they report data on PM10 or respiratory illness, including asthma but are few those doing simultaneous analysis on both. This leads to erroneous environmental decisions an insufficient clarity to establish directives and/or policies to improve the environmental health in the borders of atmospheric basin. A model based on Poisson regression was studied in order to gain knowledge relating the impact that PM10 may have on the primary respiratory diseases under the influence of Temperature and Relative Humidity on the Mexicali/Imperial border corridor. Six-time series were analyzed, those from PM10 were taken from Environmental Monitoring Stations in Mexicali, those for asthma, acute respiratory infections and pneumonia were obtained from public health centers under the supervision of the State of Baja California in a lapse of four years, from 1997 to 2000. The primary source of pollution for PM10 is identified and their relative percentage contributing to the total. Dispersion graphs and cross-correlation coefficients were also obtained for respiratory illness incidence and those time series relating the environmental markers including PM10.