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Uwak I, Olson N, Fuentes A, Moriarty M, Pulczinski J, Lam J, Xu X, Taylor BD, Taiwo S, Koehler K, Foster M, Chiu WA, Johnson NM. Application of the navigation guide systematic review methodology to evaluate prenatal exposure to particulate matter air pollution and infant birth weight. ENVIRONMENT INTERNATIONAL 2021; 148:106378. [PMID: 33508708 PMCID: PMC7879710 DOI: 10.1016/j.envint.2021.106378] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/03/2020] [Revised: 12/11/2020] [Accepted: 01/04/2021] [Indexed: 05/04/2023]
Abstract
Low birth weight is an important risk factor for many co-morbidities both in early life as well as in adulthood. Numerous studies report associations between prenatal exposure to particulate matter (PM) air pollution and low birth weight. Previous systematic reviews and meta-analyses report varying effect sizes and significant heterogeneity between studies, but did not systematically evaluate the quality of individual studies or the overall body of evidence. We conducted a new systematic review to determine how prenatal exposure to PM2.5, PM10, and coarse PM (PM2.5-10) by trimester and across pregnancy affects infant birth weight. Using the Navigation Guide methodology, we developed and applied a systematic review protocol [CRD42017058805] that included a comprehensive search of the epidemiological literature, risk of bias (ROB) determination, meta-analysis, and evidence evaluation, all using pre-established criteria. In total, 53 studies met our inclusion criteria, which included evaluation of birth weight as a continuous variable. For PM2.5 and PM10, we restricted meta-analyses to studies determined overall as "low" or "probably low" ROB; none of the studies evaluating coarse PM were rated as "low" or "probably low" risk of bias, so all studies were used. For PM2.5, we observed that for every 10 µg/m3 increase in exposure to PM2.5 in the 2nd or 3rd trimester, respectively, there was an associated 5.69 g decrease (I2: 68%, 95% CI: -10.58, -0.79) or 10.67 g decrease in birth weight (I2: 84%, 95% CI: -20.91, -0.43). Over the entire pregnancy, for every 10 µg/m3 increase in PM2.5 exposure, there was an associated 27.55 g decrease in birth weight (I2: 94%, 95% CI: -48.45, -6.65). However, the quality of evidence for PM2.5 was rated as "low" due to imprecision and/or unexplained heterogeneity among different studies. For PM10, we observed that for every 10 µg/m3 increase in exposure in the 3rd trimester or the entire pregnancy, there was a 6.57 g decrease (I2: 0%, 95% CI: -10.66, -2.48) or 8.65 g decrease in birth weight (I2: 84%, 95% CI: -16.83, -0.48), respectively. The quality of evidence for PM10 was rated as "moderate," as heterogeneity was either absent or could be explained. The quality of evidence for coarse PM was rated as very low/low (for risk of bias and imprecision). Overall, while evidence for PM2.5 and course PM was inadequate primarily due to heterogeneity and risk of bias, respectively, our results support the existence of an inverse association between prenatal PM10 exposure and low birth weight.
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Affiliation(s)
- Inyang Uwak
- Department of Environmental and Occupational Health. Texas A&M University, College Station, TX, USA
| | - Natalie Olson
- Department of Veterinary Integrative Biosciences. Texas A&M University, College Station, TX, USA
| | - Angelica Fuentes
- Department of Veterinary Integrative Biosciences. Texas A&M University, College Station, TX, USA
| | - Megan Moriarty
- Department of Environmental and Occupational Health. Texas A&M University, College Station, TX, USA
| | - Jairus Pulczinski
- Department of Environmental Health and Engineering. Johns Hopkins University, Baltimore, MD, USA
| | - Juleen Lam
- Department of Health Sciences, California State University, East Bay, Hayward, CA USA
| | - Xiaohui Xu
- Department of Epidemiology and Biostatistics. Texas A&M University, College Station, TX, USA
| | - Brandie D Taylor
- Department of Epidemiology and Biostatistics. Temple University, Philadelphia, PA, USA
| | - Samuel Taiwo
- Department of Environmental and Occupational Health. Texas A&M University, College Station, TX, USA
| | - Kirsten Koehler
- Department of Environmental Health and Engineering. Johns Hopkins University, Baltimore, MD, USA
| | - Margaret Foster
- Medical Sciences Library. Texas A&M University, College Station, TX, USA
| | - Weihsueh A Chiu
- Department of Veterinary Integrative Biosciences. Texas A&M University, College Station, TX, USA
| | - Natalie M Johnson
- Department of Environmental and Occupational Health. Texas A&M University, College Station, TX, USA.
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Monthly-Term Associations Between Air Pollutants and Respiratory Morbidity in South Brazil 2013-2016: A Multi-City, Time-Series Analysis. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2019; 16:ijerph16203787. [PMID: 31600878 PMCID: PMC6843508 DOI: 10.3390/ijerph16203787] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/25/2019] [Revised: 09/18/2019] [Accepted: 09/24/2019] [Indexed: 11/17/2022]
Abstract
Most air pollution research conducted in Brazil has focused on assessing the daily-term effects of pollutants, but little is known about the health effects of air pollutants at an intermediate time term. The objective of this study was to determine the monthly-term association between air pollution and respiratory morbidity in five cities in South Brazil. An ecological time-series study was performed using the municipality as the unit of observation in five cities in South Brazil (Gravataí, Triunfo, Esteio, Canoas, and Charqueadas) between 2013 and 2016. Data for hospital admissions was obtained from the records of the Hospital Information Service. Air pollution data, including PM10, SO2, CO, NO2, and O3 (µg/m3) were obtained from the environmental government agency in Rio Grande do Sul State. Panel multivariable Poisson regression models were adjusted for monthly counts of respiratory hospitalizations. An increase of 10 μg/m3 in the monthly average concentration of PM10 was associated with an increase of respiratory hospitalizations in all age groups, with the maximum effect on the population aged between 16 and 59 years (IRR: Incidence rate ratio 2.04 (95% CI: Confidence interval = 1.97–2.12)). For NO2 and SO2, stronger intermediate-term effects were found in children aged between 6 and 15 years, while for O3 higher effects were found in children under 1 year. This is the first multi-city study conducted in South Brazil to account for intermediate-term effects of air pollutants on respiratory health.
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