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Assessment of the Possible Association of Air Pollutants PM10, O3, NO2 With an Increase in Cardiovascular, Respiratory, and Diabetes Mortality in Panama City: A 2003 to 2013 Data Analysis.

ABSTRACT: In recent years, Panama has experienced a marked economic growth, and this, in turn, has been associated with rapid urban development and degradation of air quality. This study is the first evaluation done in Panama on the association between air pollution and mortality. Our objective was to assess the possible association between monthly levels of PM10, O3, and NO2, and cardiovascular, respiratory, and diabetes mortality, as well as the seasonal variation of mortality in Panama City, Panama.The study was conducted in Panama City, using air pollution data from January 2003 to December 2013. We utilized a Poisson regression model based on generalized linear models, to evaluate the association between PM10, NO2, and O3 exposure and mortality from diabetes, cardiovascular, and respiratory diseases. The sample size for PM10, NO2, and O2 was 132, 132, and 108 monthly averages, respectively.We found that levels of PM10, O3, and NO2 were associated with increases in cardiovascular, respiratory, and diabetes mortality. For PM10 levels ? 40??g/m3, we found an increase in cardiovascular mortality of 9.7% (CI 5.8-13.6%), and an increase of 12.6% (CI 0.2-24.2%) in respiratory mortality. For O3 levels ? 20??g/m3 we found an increase of 32.4% (IC 14.6-52.9) in respiratory mortality, after a 2-month lag period following exposure in the 65 to <74 year-old age group. For NO2 levels ?20??g/m3 we found an increase in respiratory mortality of 11.2% (IC 1.9-21.3), after a 2-month lag period following exposure among those aged between 65 and <74 years.There could be an association between the air pollution in Panama City and an increase in cardiovascular, respiratory, and diabetes mortality. This study confirms the urgent need to improve the measurement frequency of air pollutants in Panama.

SUBMITTER: Zuniga J

PROVIDER: S-EPMC4718270 | biostudies-literature | 2016 Jan

REPOSITORIES: biostudies-literature

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Assessment of the Possible Association of Air Pollutants PM10, O3, NO2 With an Increase in Cardiovascular, Respiratory, and Diabetes Mortality in Panama City: A 2003 to 2013 Data Analysis.

Zúñiga Julio J Tarajia Musharaf M Herrera Víctor V Urriola Wilfredo W Gómez Beatriz B Motta Jorge J

Medicine 20160101 2

In recent years, Panama has experienced a marked economic growth, and this, in turn, has been associated with rapid urban development and degradation of air quality. This study is the first evaluation done in Panama on the association between air pollution and mortality. Our objective was to assess the possible association between monthly levels of PM10, O3, and NO2, and cardiovascular, respiratory, and diabetes mortality, as well as the seasonal variation of mortality in Panama City, Panama.The ...[more]

PMID: 26765444

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Project description:IntroductionAir pollution represents a serious threat to health on a global scale, being responsible for a large portion of the global burden of disease from environmental factors. Current evidence about the association between air pollution exposure and Diabetes Mellitus (DM) is still controversial. We aimed to evaluate the association between area-level ambient air pollution and self-reported DM in a large population sample in Italy.Materials and methodsWe extracted information about self-reported and physician diagnosed DM, risk factors and socio-economic status from 12 surveys conducted nationwide between 1999 and 2013. We obtained annual averaged air pollution levels for the years 2003, 2005, 2007 and 2010 from the AMS-MINNI national integrated model, which simulates the dispersion and transformation of pollutants. The original maps, with a resolution of 4 x 4 km2, were normalized and aggregated at the municipality class of each Italian region, in order to match the survey data. We fit logistic regression models with a hierarchical structure to estimate the relationship between PM10, PM2.5, NO2 and O3 four-years mean levels and the risk of being affected by DM.ResultsWe included 376,157 individuals aged more than 45 years. There were 39,969 cases of DM, with an average regional prevalence of 9.8% and a positive geographical North-to-South gradient, opposite to that of pollutants' concentrations. For each 10 μg/m3 increase, the resulting ORs were 1.04 (95% CI 1.01-1.07) for PM10, 1.04 (95% CI 1.02-1.07) for PM2.5, 1.03 (95% CI 1.01-1.05) for NO2 and 1.06 (95% CI 1.01-1.11) for O3, after accounting for relevant individual risk factors. The associations were robust to adjustment for other pollutants in two-pollutant models tested (ozone plus each other pollutant).ConclusionsWe observed a significant positive association between each examined pollutant and prevalent DM. Risk estimates were consistent with current evidence, and robust to sensitivity analysis. Our study adds evidence about the effects of air pollution on diabetes and suggests a possible role of ozone as an independent factor associated with the development of DM. Such relationship is of great interest for public health and deserves further investigation.

Project description:The use of air sensor technology is increasing worldwide for a variety of applications, however, with significant variability in data quality. The United States Environmental Protection Agency held a workshop in July 2019 to deliberate possible performance targets for air sensors measuring particles with aerodynamic diameters of 10 μm or less (PM10), nitrogen dioxide (NO2), carbon monoxide (CO), and sulfur dioxide (SO2). These performance targets were discussed from the perspective of non-regulatory applications and with the sensors operating primarily in a stationary mode in outdoor environments. Attendees included representatives from multiple levels of government organizations, sensor developers, environmental nonprofits, international organizations, and academia. The workshop addressed the current lack of sensor technology requirements, discussed fit-for-purpose data quality needs, and debated transparency issues. This paper highlights the purpose and key outcomes of the workshop. While more information on performance and applications of sensors is available than in past years, the performance metrics, or parameters used to describe data quality, vary among the studies reports and there is a need for more clear and consistent approaches for evaluating sensor performance. Organizations worldwide are increasingly considering, or are in the process of developing, sensor performance targets and testing protocols. Workshop participants suggested that these new guidelines are highly desirable, would help improve data quality, and would give users more confidence in their data. Given the wide variety of uses for sensors and user backgrounds, as well as varied sensor design features (e.g., communication approaches, data tools, processing/adjustment algorithms and calibration procedures), the need for transparency was a key workshop theme. Suggestions for increasing transparency included documenting and sharing testing and performance data, detailing best practices, and sharing data processing and correction approaches.

Project description:Because of fast-paced industrialization, urbanization, and population growth in Indonesia, there are serious health issues in the country resulting from air pollution. This study uses geospatial modelling technologies, namely land-use regression (LUR), geographically weighted regression (GWR), and geographic and temporal weighted regression (GTWR) models, to assess variations in particulate matter (PM10) and nitrogen dioxide (NO2) concentrations in Surabaya City, Indonesia. This is the first study to implement spatiotemporal variability of air pollution concentrations in Surabaya City, Indonesia. To develop the prediction models, air pollution data collected from seven monitoring stations from 2010 to 2018 were used as dependent variables, while land-use/land cover allocations within a 250 m to 5000 m circular buffer range surrounding the monitoring stations were collected as independent variables. A supervised stepwise variable selection procedure was applied to identify the important predictor variables for developing the LUR, GWR, and GTWR models. The developed models of LUR, GWR, and GTWR accounted for 49%, 50%, and 51% of PM10 variations and 46%, 47%, and 48% of NO2 variations, respectively. The GTWR model performed better (R2 = 0.51 for PM10 and 0.48 for NO2) than the other two models (R2 = 0.49-0.50 for PM10 and 0.46-0.47 for NO2), LUR and GWR. In the PM10 model four predictor variables, public facility, industry and warehousing, paddy field, and normalized difference vegetation index (NDVI), were selected during the variable selection procedure. Meanwhile, paddy field, residential area, rainfall, and temperature played important roles in explaining NO2 variations. Because of biomass burning issues in South Asia, the paddy field, which has a positive correlation with PM10 and NO2, was selected as a predictor. By using long-term monitoring data to establish prediction models, this model may better depict PM10 and NO2 concentration variations within areas across Asia.

Project description:There are fewer longitudinal studies from China on symptoms as described for the sick building syndrome (SBS). Here, we performed a two-year prospective study and investigated associations between environmental parameters such as room temperature, relative air humidity (RH), carbon dioxide (CO2), nitrogen dioxide (NO2), sulphur dioxide (SO2), ozone (O3), particulate matter (PM10), and health outcomes including prevalence, incidence and remission of SBS symptoms in junior high schools in Taiyuan, China. Totally 2134 pupils participated at baseline, and 1325 stayed in the same classrooms during the study period (2010-2012). The prevalence of mucosal symptoms, general symptoms and symptoms improved when away from school (school-related symptoms) was 22.7%, 20.4% and 39.2%, respectively, at baseline, and the prevalence increased during follow-up (P<0.001). At baseline, both indoor and outdoor SO2 were found positively associated with prevalence of school-related symptoms. Indoor O3 was shown to be positively associated with prevalence of skin symptoms. At follow-up, indoor PM10 was found to be positively associated with new onset of skin, mucosal and general symptoms. CO2 and RH were positively associated with new onset of mucosal, general and school-related symptoms. Outdoor SO2 was positively associated with new onset of skin symptoms, while outdoor NO2 was positively associated with new onset of skin, general and mucosal symptoms. Outdoor PM10 was found to be positively associated with new onset of skin, general and mucosal symptoms as well as school-related symptoms. In conclusion, symptoms as described for SBS were commonly found in school children in Taiyuan City, China, and increased during the two-year follow-up period. Environmental pollution, including PM10, SO2 and NO2, could increase the prevalence and incidence of SBS and decrease the remission rate. Moreover, parental asthma and allergy (heredity) and pollen or pet allergy (atopy) can be risk factors for SBS.

Dataset Information

Assessment of the Possible Association of Air Pollutants PM10, O3, NO2 With an Increase in Cardiovascular, Respiratory, and Diabetes Mortality in Panama City: A 2003 to 2013 Data Analysis.

Publications

Assessment of the Possible Association of Air Pollutants PM10, O3, NO2 With an Increase in Cardiovascular, Respiratory, and Diabetes Mortality in Panama City: A 2003 to 2013 Data Analysis.

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