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Fine particulate matter and polycystic ovarian morphology
BACKGROUND: Polycystic ovary morphology (PCOM) is an ultrasonographic finding that can be present in women with ovulatory disorder and oligomenorrhea due to hypothalamic, pituitary, and ovarian dysfunction. While air pollution has emerged as a possible disrupter of hormone homeostasis, limited resea...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8855564/ https://www.ncbi.nlm.nih.gov/pubmed/35180862 http://dx.doi.org/10.1186/s12940-022-00835-1 |
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author | Fruh, Victoria Cheng, Jay Jojo Aschengrau, Ann Mahalingaiah, Shruthi Lane, Kevin J. |
author_facet | Fruh, Victoria Cheng, Jay Jojo Aschengrau, Ann Mahalingaiah, Shruthi Lane, Kevin J. |
author_sort | Fruh, Victoria |
collection | PubMed |
description | BACKGROUND: Polycystic ovary morphology (PCOM) is an ultrasonographic finding that can be present in women with ovulatory disorder and oligomenorrhea due to hypothalamic, pituitary, and ovarian dysfunction. While air pollution has emerged as a possible disrupter of hormone homeostasis, limited research has been conducted on the association between air pollution and PCOM. METHODS: We conducted a longitudinal cohort study using electronic medical records data of 5,492 women with normal ovaries at the first ultrasound that underwent a repeated pelvic ultrasound examination during the study period (2004–2016) at Boston Medical Center. Machine learning text algorithms classified PCOM by ultrasound. We used geocoded home address to determine the ambient annual average PM(2.5) exposures and categorized into tertiles of exposure. We used Cox Proportional Hazards models on complete data (n = 3,994), adjusting for covariates, and additionally stratified by race/ethnicity and body mass index (BMI). RESULTS: Cumulative exposure to PM(2.5) during the study ranged from 4.9 to 17.5 µg/m(3) (mean = 10.0 μg/m(3)). On average, women were 31 years old and 58% were Black/African American. Hazard ratios and 95% confidence intervals (CI) comparing the second and third PM(2.5) exposure tertile vs. the reference tertile were 1.12 (0.88, 1.43) and 0.89 (0.62, 1.28), respectively. No appreciable differences were observed across race/ethnicity. Among women with BMI ≥ 30 kg/m(2), we observed weak inverse associations with PCOM for the second (HR: 0.93, 95% CI: 0.66, 1.33) and third tertiles (HR: 0.89, 95% CI: 0.50, 1.57). CONCLUSIONS: In this study of reproductive-aged women, we observed little association between PM(2.5) concentrations and PCOM incidence. No dose response relationships were observed nor were estimates appreciably different across race/ethnicity within this clinically sourced cohort. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12940-022-00835-1. |
format | Online Article Text |
id | pubmed-8855564 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-88555642022-02-23 Fine particulate matter and polycystic ovarian morphology Fruh, Victoria Cheng, Jay Jojo Aschengrau, Ann Mahalingaiah, Shruthi Lane, Kevin J. Environ Health Research BACKGROUND: Polycystic ovary morphology (PCOM) is an ultrasonographic finding that can be present in women with ovulatory disorder and oligomenorrhea due to hypothalamic, pituitary, and ovarian dysfunction. While air pollution has emerged as a possible disrupter of hormone homeostasis, limited research has been conducted on the association between air pollution and PCOM. METHODS: We conducted a longitudinal cohort study using electronic medical records data of 5,492 women with normal ovaries at the first ultrasound that underwent a repeated pelvic ultrasound examination during the study period (2004–2016) at Boston Medical Center. Machine learning text algorithms classified PCOM by ultrasound. We used geocoded home address to determine the ambient annual average PM(2.5) exposures and categorized into tertiles of exposure. We used Cox Proportional Hazards models on complete data (n = 3,994), adjusting for covariates, and additionally stratified by race/ethnicity and body mass index (BMI). RESULTS: Cumulative exposure to PM(2.5) during the study ranged from 4.9 to 17.5 µg/m(3) (mean = 10.0 μg/m(3)). On average, women were 31 years old and 58% were Black/African American. Hazard ratios and 95% confidence intervals (CI) comparing the second and third PM(2.5) exposure tertile vs. the reference tertile were 1.12 (0.88, 1.43) and 0.89 (0.62, 1.28), respectively. No appreciable differences were observed across race/ethnicity. Among women with BMI ≥ 30 kg/m(2), we observed weak inverse associations with PCOM for the second (HR: 0.93, 95% CI: 0.66, 1.33) and third tertiles (HR: 0.89, 95% CI: 0.50, 1.57). CONCLUSIONS: In this study of reproductive-aged women, we observed little association between PM(2.5) concentrations and PCOM incidence. No dose response relationships were observed nor were estimates appreciably different across race/ethnicity within this clinically sourced cohort. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12940-022-00835-1. BioMed Central 2022-02-18 /pmc/articles/PMC8855564/ /pubmed/35180862 http://dx.doi.org/10.1186/s12940-022-00835-1 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Fruh, Victoria Cheng, Jay Jojo Aschengrau, Ann Mahalingaiah, Shruthi Lane, Kevin J. Fine particulate matter and polycystic ovarian morphology |
title | Fine particulate matter and polycystic ovarian morphology |
title_full | Fine particulate matter and polycystic ovarian morphology |
title_fullStr | Fine particulate matter and polycystic ovarian morphology |
title_full_unstemmed | Fine particulate matter and polycystic ovarian morphology |
title_short | Fine particulate matter and polycystic ovarian morphology |
title_sort | fine particulate matter and polycystic ovarian morphology |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8855564/ https://www.ncbi.nlm.nih.gov/pubmed/35180862 http://dx.doi.org/10.1186/s12940-022-00835-1 |
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