Association between exposure to fine particulate matter and adverse pregnancy outcomes in Kaunas

2016 ◽  
Vol 2016 (1) ◽  
Author(s):  
Audrius Dedele* ◽  
Regina Grazuleviciene ◽  
Jone Vencloviene ◽  
Aukse Miskinyte
2014 ◽  
Vol 22 (5) ◽  
pp. 3397-3399 ◽  
Author(s):  
Xiaoxia Zhu ◽  
Ying Liu ◽  
Yanyan Chen ◽  
Cijiang Yao ◽  
Zhen Che ◽  
...  

Author(s):  
Cezary Wojtyla ◽  
Karolina Zielinska ◽  
Paulina Wojtyla-Buciora ◽  
Grzegorz Panek

Air pollution is currently one of the greatest threats to global health. Polish cities are among the most heavily polluted in Europe. Due to air pollution 43,100 people die prematurely in Poland every year. However, these data do not take into account the health consequences of air pollution for unborn children. Thus, the aim of this study was to evaluate the effects of the fine particulate matter air pollution (less than 2.5 μm in diameter) on pregnancy outcomes. An analysis of pregnant women and their children was made using a questionnaire survey from a nationwide study conducted in 2017. Questionnaires from 1095 pregnant women and data from their medical records were collected. An analysis of air pollution in Poland was conducted using the air quality database maintained by the Chief Inspectorate for Environmental Protection in Poland. A higher concentration of PM2.5 was associated with a decrease in birth weight and a higher risk of low birthweight (i.e., <2500 g). We also observed lower APGAR scores. Thus, all possible efforts to reduce air pollution are critically needed.


2022 ◽  
Vol 21 (1) ◽  
Author(s):  
Mercedes A. Bravo ◽  
Marie Lynn Miranda

Abstract Background Previous studies observed associations between prenatal exposure to fine particulate matter (≤ 2.5 μm; PM2.5) and small-for-gestational-age (SGA) birth and lower birthweight percentile for gestational age. Few, if any, studies examine prenatal air pollution exposure and these pregnancy outcomes in neonates born to the same women. Here, we assess whether prenatal exposure to ambient fine particulate matter (PM2.5) is associated with small-for-gestational-age (SGA) birth or birthweight percentile for gestational age in a longitudinal setting. Methods Detailed birth record data were used to identify women who had singleton live births at least twice in North Carolina during 2002–2006 (n = 53,414 women, n = 109,929 births). Prenatal PM2.5 exposures were calculated using daily concentration estimates obtained from the US EPA Fused Air Quality Surface using Downscaling data archive. Associations between PM2.5 exposure and birthweight percentile and odds of SGA birth were calculated using linear and generalized mixed models, comparing successive pregnancies to the same woman. Odds ratios and associations were also estimated in models that did not account for siblings born to the same mother. Results Among NHW women, pregnancy-long PM2.5 exposure was associated with SGA (OR: 1.11 [1.06, 1.18]) and lower birthweight percentile (− 0.46 [− 0.74, − 0.17]). Trimester-specific PM2.5 was also associated with SGA and lower birthweight percentile. Among NHB women, statistically significant within-woman associations between PM2.5, SGA, and birthweight percentile were not observed. However, in models that did not account for births to the same mother, statistically significant associations were observed between some PM2.5 exposure windows and higher odds of SGA and lower birthweight percentile among NHB women. Conclusions Findings suggest that a woman is at greater risk of delivering an SGA or low birthweight percentile neonate when she has been exposed to higher PM2.5 levels. The within-woman comparison implemented here better controls for factors that may differ between women and potentially confound the relationship between PM2.5 exposure and pregnancy outcomes. This adds to the evidence that PM2.5 exposure may be causally related to SGA and birthweight percentile, even at concentrations close to or below National Ambient Air Quality Standards.


2014 ◽  
Vol 22 (5) ◽  
pp. 3383-3396 ◽  
Author(s):  
Xiaoxia Zhu ◽  
Ying Liu ◽  
Yanyan Chen ◽  
Cijiang Yao ◽  
Zhen Che ◽  
...  

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