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Characterization of polycystic ovary syndrome among Flo app users around the world
BACKGROUND: Polycystic ovary syndrome (PCOS) is a complex and multi-faceted endocrine disorder that affects 5–20% of women. Literature is limited regarding potentially differing PCOS phenotypes among women around the world. OBJECTIVE: To use Flo app technology to understand the multifaceted characte...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7927251/ https://www.ncbi.nlm.nih.gov/pubmed/33658043 http://dx.doi.org/10.1186/s12958-021-00719-y |
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author | Jain, Tarun Negris, Olivia Brown, Dannielle Galic, Isabel Salimgaraev, Rodion Zhaunova, Liudmila |
author_facet | Jain, Tarun Negris, Olivia Brown, Dannielle Galic, Isabel Salimgaraev, Rodion Zhaunova, Liudmila |
author_sort | Jain, Tarun |
collection | PubMed |
description | BACKGROUND: Polycystic ovary syndrome (PCOS) is a complex and multi-faceted endocrine disorder that affects 5–20% of women. Literature is limited regarding potentially differing PCOS phenotypes among women around the world. OBJECTIVE: To use Flo app technology to understand the multifaceted characteristics of PCOS across several countries and identify contributing risk factors to the development of this condition. STUDY DESIGN: Flo is a widely used female health and wellbeing app with period tracking functionality that provides a globally representative and medically unbiased perspective on PCOS symptomatology. A chatbot dialog on PCOS was subsequently administered on the Flo application (app) to users from 142 countries (with at least 100 respondents) who have the app running in English during September–October 2019. RESULTS: For analyses, we selected the five countries with the greatest number of respondents: US (n = 243,238), UK (n = 68,325), India (n = 40,092), Philippines (n = 35,131), and Australia (n = 29,926). Bloating was the most frequently reported symptom among PCOS-positive women and appeared to be the main predictor of PCOS in our model (odds ratio 3·76 [95% CI 3·60–3·94]; p < 0·0001). Additional top predictors of PCOS are high blood cholesterol and glucose levels. As BMI increased, the percentage of women who reported a physician-confirmed PCOS diagnosis also increased. However, women in India did not follow this trend. CONCLUSION: Our findings are based on the largest known PCOS dataset and indicate that symptoms are more complex than previously understood. The most frequently reported symptoms (bloating, facial hirsutism, irregular cycles, hyperpigmentation, and baldness) are broader than those included in the Rotterdam criteria. Future work should reevaluate and refine the criteria utilized in PCOS diagnosis. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12958-021-00719-y. |
format | Online Article Text |
id | pubmed-7927251 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-79272512021-03-03 Characterization of polycystic ovary syndrome among Flo app users around the world Jain, Tarun Negris, Olivia Brown, Dannielle Galic, Isabel Salimgaraev, Rodion Zhaunova, Liudmila Reprod Biol Endocrinol Research BACKGROUND: Polycystic ovary syndrome (PCOS) is a complex and multi-faceted endocrine disorder that affects 5–20% of women. Literature is limited regarding potentially differing PCOS phenotypes among women around the world. OBJECTIVE: To use Flo app technology to understand the multifaceted characteristics of PCOS across several countries and identify contributing risk factors to the development of this condition. STUDY DESIGN: Flo is a widely used female health and wellbeing app with period tracking functionality that provides a globally representative and medically unbiased perspective on PCOS symptomatology. A chatbot dialog on PCOS was subsequently administered on the Flo application (app) to users from 142 countries (with at least 100 respondents) who have the app running in English during September–October 2019. RESULTS: For analyses, we selected the five countries with the greatest number of respondents: US (n = 243,238), UK (n = 68,325), India (n = 40,092), Philippines (n = 35,131), and Australia (n = 29,926). Bloating was the most frequently reported symptom among PCOS-positive women and appeared to be the main predictor of PCOS in our model (odds ratio 3·76 [95% CI 3·60–3·94]; p < 0·0001). Additional top predictors of PCOS are high blood cholesterol and glucose levels. As BMI increased, the percentage of women who reported a physician-confirmed PCOS diagnosis also increased. However, women in India did not follow this trend. CONCLUSION: Our findings are based on the largest known PCOS dataset and indicate that symptoms are more complex than previously understood. The most frequently reported symptoms (bloating, facial hirsutism, irregular cycles, hyperpigmentation, and baldness) are broader than those included in the Rotterdam criteria. Future work should reevaluate and refine the criteria utilized in PCOS diagnosis. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12958-021-00719-y. BioMed Central 2021-03-03 /pmc/articles/PMC7927251/ /pubmed/33658043 http://dx.doi.org/10.1186/s12958-021-00719-y Text en © The Author(s) 2021 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/. The Creative Commons Public Domain Dedication waiver (http://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 Jain, Tarun Negris, Olivia Brown, Dannielle Galic, Isabel Salimgaraev, Rodion Zhaunova, Liudmila Characterization of polycystic ovary syndrome among Flo app users around the world |
title | Characterization of polycystic ovary syndrome among Flo app users around the world |
title_full | Characterization of polycystic ovary syndrome among Flo app users around the world |
title_fullStr | Characterization of polycystic ovary syndrome among Flo app users around the world |
title_full_unstemmed | Characterization of polycystic ovary syndrome among Flo app users around the world |
title_short | Characterization of polycystic ovary syndrome among Flo app users around the world |
title_sort | characterization of polycystic ovary syndrome among flo app users around the world |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7927251/ https://www.ncbi.nlm.nih.gov/pubmed/33658043 http://dx.doi.org/10.1186/s12958-021-00719-y |
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