Many epidemiological studies have used house characteristics associated with indoor sources as simplified proxies for personal nitrogen dioxide (NO2) exposure. Stove type and presence of a pilot light often been used as the two key characteristics, but significant overlaps have remained in the NO2 concentrations in the exposed and unexposed groups. This has contributed to inconsistencies in epidemiological findings, due to potential misclassification of exposure. In this study, other possible proxies were analyzed by cross-table analyses and were investigated in terms of improvements in both classification and predictive power. Adding building type to the above two proxies resulted in 0-5% of households with concentrations overlapping the observed range for the opposing stratum, compared with 22-42% for the two-proxy model. In spite of this performance, the predictive power of regression models for indoor NO2 was not improved by the addition of the third proxy, and the potential sample population was significantly limited. Using these analytical methods to choose descriptive proxies and evaluate the tradeoffs in their implementation can help epidemiological studies improve their designs and therefore optimize the robustness of their conclusions.
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http://dx.doi.org/10.1080/10473289.1998.10463717 | DOI Listing |
Ecotoxicol Environ Saf
January 2025
Department of Basic Education, University of Education, Winneba, Ghana.
Urbanization and industrialization have drastically increased ambient air pollution in urban areas globally from vehicle emissions, solid fuel combustion and industrial activities leading to some of the worst air quality conditions. Air pollution in Ghana causes approximately 28,000 premature deaths and disabilities annually, ranking as a leading cause of mortality and disability-adjusted life years. This study evaluated the annual concentrations of PM NO and O in the ambient air of 57 cities in Ghana for two decades using historical and forecasted data from satellite measurements.
View Article and Find Full Text PDFBMC Public Health
January 2025
Department of Prevention and Evaluation, Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany.
Background: Exposure to nitrogen dioxide (NO) is associated with an increased risk of cardiovascular, respiratory, and other diseases and health outcomes. Although NO emissions have decreased in Germany, concentrations currently observed still pose a threat to population health. The aim of this study is to estimate the environmental burden of disease (EBD) resulting from long-term NO exposure in Germany from 2010 to 2021.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Laboratoire d'Analyse et d'Architecture des Systèmes (LAAS), Université de Toulouse, CNRS, UPS, 7 Avenue du Colonel Roche, 31031 Toulouse, France.
The need for odor measurement and pollution source identification in various sectors (aeronautic, automobile, healthcare…) has increased in the last decade. Multisensor modules, such as electronic noses, seem to be a promising and inexpensive alternative to traditional sensors that were only sensitive to one gas at a time. However, the selectivity, the non-repetitiveness of their manufacture, and their drift remain major obstacles to the use of electronic noses.
View Article and Find Full Text PDFToxics
December 2024
Department of Public Health, University of Massachusetts Lowell, Lowell, MA 01854, USA.
Nitrogen dioxide (NO) and particulate matter of 2.5 microns (PM) are air pollutants that impact health, especially among vulnerable populations with respiratory disease. This study identifies factors influencing indoor NO and PM in low-income households of older adults with asthma who use gas stoves in Lowell, Massachusetts.
View Article and Find Full Text PDFToxics
December 2024
Medical Center for Neck and Low Back Pain, Xijing Hospital, Fourth Military Medical University, Xi'an 710000, China.
This study investigates the correlation between short-term exposure to nitrogen dioxide (NO) and hospitalization for chronic kidney disease (CKD) in Lanzhou, China. A distributed lag nonlinear model (DLNM) was employed to examine the relationship between changes in NO concentration and CKD hospitalizations. Subgroup analyses were conducted to assess the sensitivity of different populations to NO exposure.
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