Estimate annual and seasonal PM1, PM2.5 and PM10 concentrations using land use regression model

Miri, Mohammad; Ghassoun, Yahya; Dovlatabadi, Afshin; Ebrahimnejad, Ali; Löwner, Marc-Oliver

doi:10.1016/j.ecoenv.2019.02.070

Cited by 72 publications

(27 citation statements)

References 51 publications

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“…The median (IQR) of pre-pregnancy BMI was 21.2 (5.9) kg/m 2 . The median (IQR) of FBG, 1-h and 2-h glucose concentrations were 69 (8), 112 (35), and 100 (26), mg/dL, respectively. The median (IQR) of proximity to major roads and total street length in 100, 300 and 500 m buffers were 321 (388), 905 (257), 7756 (2035) and 20,704 (6292) meters, respectively.…”

Section: Resultsmentioning

confidence: 99%

“…The PMs data were estimated based on annual mean concentrations before pregnancy. The details of developed models have been described in detail elsewhere [26]. Briefly, the PM 1 , PM 2.5 , and PM 10 concentrations were measured using 26 air pollution monitoring stations installed in the different microenvironments.…”

Section: Exposure Assessment Ambient Particulate Mattermentioning

confidence: 99%

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Preconception air pollution exposure and glucose tolerance in healthy pregnant women in a middle-income country

et al. 2020

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Background Preconception exposure to air pollution has been associated with glucose tolerance during pregnancy. However, the evidence in low and middle-income countries (LMICs) is under debate yet. Therefore, this study aimed to assess the relationship between exposure to ambient particulate matter (PM) and traffic indicators with glucose tolerance in healthy pregnant women in Sabzevar, Iran (2019). Methods Two-hundred and fifty healthy pregnant women with singleton pregnancies and 24–26 weeks of gestations participated in our study. Land use regression (LUR) models were applied to estimate the annual mean of PM1, PM2.5 and PM10 at the residential address. Traffic indicators, including proximity of women to major roads as well as total streets length in 100, 300 and 500 m buffers around the home were calculated using the street map of Sabzevar. The oral glucose tolerance test (OGTT) was used to assess glucose tolerance during pregnancy. Multiple linear regression adjusted for relevant covariates was used to estimate the association of fasting blood glucose (FBG), 1-h and 2-h post-load glucose with PMs and traffic indicators. Results Exposure to PM1, PM2.5 and PM10 was significantly associated with higher FBG concentration. Higher total streets length in a 100 m buffer was associated with higher FBG and 1-h glucose concentrations. An interquartile range (IQR) increase in proximity to major roads was associated with a decrease of − 3.29 mg/dL (95% confidence interval (CI): − 4.35, − 2.23, P-value < 0.01) in FBG level and − 3.65 mg/dL (95% CI, − 7.01, − 0.28, P-value = 0.03) decrease in 1-h post-load glucose. Conclusion We found that higher preconception exposure to air pollution was associated with higher FBG and 1-h glucose concentrations during pregnancy.

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Section: Resultsmentioning

confidence: 99%

Section: Exposure Assessment Ambient Particulate Mattermentioning

confidence: 99%

Preconception air pollution exposure and glucose tolerance in healthy pregnant women in a middle-income country

et al. 2020

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“…The developed land use regression (LUR) models for Sabzevar were applied to estimate the preconception exposure to ambient PMs (i.e., PM 1 , PM 2.5 , and PM 10 ) and exposure to PMs during entire pregnancy at residential address. The details of developed models have been described in detail elsewhere [21]. Brie y, the PM , PM 2.5 , and PM 10 concentrations were measured using 26 air pollution monitoring stations installed in different parts of the study area.…”

Section: Population Settingmentioning

confidence: 99%

Preconception air pollution exposure and glucose tolerance in healthy pregnant women in a middle income country

Zareie

Gohari

Haghighi

et al. 2020

Preprint

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Background: The effect of preconception exposure to air pollution on glucose tolerance during pregnancy in developing and middle-income countries is under debate yet. Therefore, this study aimed to assess the relationship between exposure to ambient particulate matter (PM) and traffic indicators with glucose tolerance in healthy pregnant women in Sabzevar, Iran (2019). Methods: Accordingly, 250 healthy pregnant women with singleton pregnancies of 24-26 weeks of gestations were participated in our study. Land use regression (LUR) models were applied to estimate the annual mean of PM1, PM2.5 and PM10 at residential address. Traffic indicators, including distance from home to the nearest major road (DHMR) as well as total streets length in 100, 300 and 500m buffers around the home (TSL-100, 300 and 500) were calculated using the street map of Sabzevar. Oral glucose tolerance test (OGTT) was used to assess glucose tolerance during pregnancy. Multiple linear regression adjusted for relevant covariates was used to estimate the association of fasting blood glucose (FBG), 1-h and 2-h post-load glucose with PMs and traffic indicators. Results: Exposure to PM1, PM2.5 and PM10 was significantly associated with higher FBG concentration. Higher TSL-100 was associated with higher FBG and 1-h glucose concentrations. Each one interquartile range (IQR) increase in DHMR the levels of FBG and 1-h post-load glucose were decreased -3.42 mg/dL (95% confidence interval (CI): -4.47, -2.37, P-value < 0.01) and -4.65 mg/dL (95% CI: -8.03, -1.26, P-value < 0.01), respectively. Conclusion: We found higher preconception exposure to air pollution and exposure to air pollution during pregnancy were negatively associated with glucose tolerance during pregnancy in a middle income country.

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“…For example, Li et al (2011) discussed the application of moderate resolution imaging spectroradiometer in air quality research in parts of Asia, and analyse the AOT and PM10 concentrations in surface layer of China and Thailand from 2001 to 2019 by using simple multiple regression model. Miri et al (2019) used the land use regression model to analyse the spatial pattern of annual and seasonal concentrations of PM1, PM2.5 and PM10 in Sabzewal. In the same year, Stafoggia et al (2019) used the land-use random forest model to estimate the daily concentrations of PM10 and PM2.5 in Italy from 2013 to 2015, and analyse the spatial distribution of PM2.5 and PM10 annual average concentrations.…”

Section: Introductionmentioning

confidence: 99%

Temporal and Spatial Variation Characteristics of PM2.5 Concentration in “2+26” Cities

Liang

Jing

Wang

et al. 2020

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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In recent years, air pollution is still a serious problem in China. Therefore, the government has further strengthened the pollution control measures for the Beijing-Tianjin-Hebei (BTH) air pollution transmission channel cities ("2+26" cities). This study used realtime PM2.5 monitoring data from 176 air quality monitoring sites in "2+26" cities from 2015 to 2018. The temporal and spatial evolution characteristics of PM2.5 concentration in "2+26" cities were analysis by statistical analysis and Kriging interpolation method.This contribution has been peer-reviewed. https://doi.org/10.5194/isprs-archives-XLII-3-W10-995-2020 | © Authors 2020. CC BY 4.0 License. 995

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Estimate annual and seasonal PM1, PM2.5 and PM10 concentrations using land use regression model

Cited by 72 publications

References 51 publications

Preconception air pollution exposure and glucose tolerance in healthy pregnant women in a middle-income country

Preconception air pollution exposure and glucose tolerance in healthy pregnant women in a middle-income country

Preconception air pollution exposure and glucose tolerance in healthy pregnant women in a middle income country

Temporal and Spatial Variation Characteristics of PM2.5 Concentration in “2+26” Cities

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