Cargando…
Menstrual patterns and disorders among Chinese women of reproductive age: A cross-sectional study based on mobile application data
Menstruation is an important indicator of women's health. Identification of abnormal menstrual patterns in adolescence may improve early diagnosis of potential health concerns in adulthood. This study aimed to evaluate menstrual patterns and disorders of Chinese women of reproductive age based...
Autores principales: | , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Lippincott Williams & Wilkins
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8078451/ https://www.ncbi.nlm.nih.gov/pubmed/33879662 http://dx.doi.org/10.1097/MD.0000000000025329 |
_version_ | 1783685064400306176 |
---|---|
author | Mao, Lele Xi, Sisi Bai, Wenpei Yao, Chen Zhou, Yingfang Chen, Xing Sun, Yu |
author_facet | Mao, Lele Xi, Sisi Bai, Wenpei Yao, Chen Zhou, Yingfang Chen, Xing Sun, Yu |
author_sort | Mao, Lele |
collection | PubMed |
description | Menstruation is an important indicator of women's health. Identification of abnormal menstrual patterns in adolescence may improve early diagnosis of potential health concerns in adulthood. This study aimed to evaluate menstrual patterns and disorders of Chinese women of reproductive age based on an APP. From December 2015 to January 2016, a cross-sectional study was conducted. We utilized a mobile application (APP) to collect information about participants’ age at menarche, length of menstruation, duration of menstruation, amount of menstrual flow, regularity of menstrual cycle, prevalence of abnormal uterine bleeding and dysmenorrhoea. A total of 156,055 women (25,716 from the questionnaire survey and 130,000 from the mobile APP users) participated in the study. The average age of the subjects was 26.32 ± 6.97 years (median age, 25 years). Mean age at menarche was 13.08 ± 1.87 years; average length of menstrual cycle, 30.9 ± 4.28 days (median 30 days); and average duration of menstruation, 5.01 ± 1.13 days (median 5 days). Women with irregular menstrual cycles accounted for 36.41%. Women aged < 18 years and > 30 years were more likely to experience irregular menstrual cycles. The prevalence of secondary amenorrhoea was 4.07%. More than 20% of women reported abnormal menstrual flow. About 20.11% of women had abnormal uterine bleeding, and 77.65% had dysmenorrhoea. A hot compress was the most commonly used approach to ameliorate dysmenorrhoea. Women with low education and low income and those with high education and high income tended to have menstrual problems. A mobile APP as a survey tool has the advantages of large sample size, low cost, and high efficiency. The use of a mobile APP is an emerging approach for collecting big data in the field of health research. The results showed that the prevalence of menstrual disorders among Chinese reproductive women was high. Healthcare providers should educate girls and their caregivers about menstrual physiology, normal menstrual pattern, and reproductive health to prevent long-term diseases. |
format | Online Article Text |
id | pubmed-8078451 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Lippincott Williams & Wilkins |
record_format | MEDLINE/PubMed |
spelling | pubmed-80784512021-04-28 Menstrual patterns and disorders among Chinese women of reproductive age: A cross-sectional study based on mobile application data Mao, Lele Xi, Sisi Bai, Wenpei Yao, Chen Zhou, Yingfang Chen, Xing Sun, Yu Medicine (Baltimore) 5600 Menstruation is an important indicator of women's health. Identification of abnormal menstrual patterns in adolescence may improve early diagnosis of potential health concerns in adulthood. This study aimed to evaluate menstrual patterns and disorders of Chinese women of reproductive age based on an APP. From December 2015 to January 2016, a cross-sectional study was conducted. We utilized a mobile application (APP) to collect information about participants’ age at menarche, length of menstruation, duration of menstruation, amount of menstrual flow, regularity of menstrual cycle, prevalence of abnormal uterine bleeding and dysmenorrhoea. A total of 156,055 women (25,716 from the questionnaire survey and 130,000 from the mobile APP users) participated in the study. The average age of the subjects was 26.32 ± 6.97 years (median age, 25 years). Mean age at menarche was 13.08 ± 1.87 years; average length of menstrual cycle, 30.9 ± 4.28 days (median 30 days); and average duration of menstruation, 5.01 ± 1.13 days (median 5 days). Women with irregular menstrual cycles accounted for 36.41%. Women aged < 18 years and > 30 years were more likely to experience irregular menstrual cycles. The prevalence of secondary amenorrhoea was 4.07%. More than 20% of women reported abnormal menstrual flow. About 20.11% of women had abnormal uterine bleeding, and 77.65% had dysmenorrhoea. A hot compress was the most commonly used approach to ameliorate dysmenorrhoea. Women with low education and low income and those with high education and high income tended to have menstrual problems. A mobile APP as a survey tool has the advantages of large sample size, low cost, and high efficiency. The use of a mobile APP is an emerging approach for collecting big data in the field of health research. The results showed that the prevalence of menstrual disorders among Chinese reproductive women was high. Healthcare providers should educate girls and their caregivers about menstrual physiology, normal menstrual pattern, and reproductive health to prevent long-term diseases. Lippincott Williams & Wilkins 2021-04-23 /pmc/articles/PMC8078451/ /pubmed/33879662 http://dx.doi.org/10.1097/MD.0000000000025329 Text en Copyright © 2021 the Author(s). Published by Wolters Kluwer Health, Inc. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial License 4.0 (CCBY-NC), where it is permissible to download, share, remix, transform, and buildup the work provided it is properly cited. The work cannot be used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc/4.0 (https://creativecommons.org/licenses/by-nc/4.0/) |
spellingShingle | 5600 Mao, Lele Xi, Sisi Bai, Wenpei Yao, Chen Zhou, Yingfang Chen, Xing Sun, Yu Menstrual patterns and disorders among Chinese women of reproductive age: A cross-sectional study based on mobile application data |
title | Menstrual patterns and disorders among Chinese women of reproductive age: A cross-sectional study based on mobile application data |
title_full | Menstrual patterns and disorders among Chinese women of reproductive age: A cross-sectional study based on mobile application data |
title_fullStr | Menstrual patterns and disorders among Chinese women of reproductive age: A cross-sectional study based on mobile application data |
title_full_unstemmed | Menstrual patterns and disorders among Chinese women of reproductive age: A cross-sectional study based on mobile application data |
title_short | Menstrual patterns and disorders among Chinese women of reproductive age: A cross-sectional study based on mobile application data |
title_sort | menstrual patterns and disorders among chinese women of reproductive age: a cross-sectional study based on mobile application data |
topic | 5600 |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8078451/ https://www.ncbi.nlm.nih.gov/pubmed/33879662 http://dx.doi.org/10.1097/MD.0000000000025329 |
work_keys_str_mv | AT maolele menstrualpatternsanddisordersamongchinesewomenofreproductiveageacrosssectionalstudybasedonmobileapplicationdata AT xisisi menstrualpatternsanddisordersamongchinesewomenofreproductiveageacrosssectionalstudybasedonmobileapplicationdata AT baiwenpei menstrualpatternsanddisordersamongchinesewomenofreproductiveageacrosssectionalstudybasedonmobileapplicationdata AT yaochen menstrualpatternsanddisordersamongchinesewomenofreproductiveageacrosssectionalstudybasedonmobileapplicationdata AT zhouyingfang menstrualpatternsanddisordersamongchinesewomenofreproductiveageacrosssectionalstudybasedonmobileapplicationdata AT chenxing menstrualpatternsanddisordersamongchinesewomenofreproductiveageacrosssectionalstudybasedonmobileapplicationdata AT sunyu menstrualpatternsanddisordersamongchinesewomenofreproductiveageacrosssectionalstudybasedonmobileapplicationdata |