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Association of Anthropometric Indices with Menstrual Abnormality among Nursing Students of Nepal: A Cross-Sectional Study
INTRODUCTION: Obesity has been reported to be linked with menstrual abnormalities including abnormality in cycle length, duration, and period blood loss. However, which anthropometric parameter is a better marker of menstrual abnormality is yet unknown. This study aims to explore the association of...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8956380/ https://www.ncbi.nlm.nih.gov/pubmed/35342646 http://dx.doi.org/10.1155/2022/6755436 |
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author | Amgain, Kapil Subedi, Prativa Yadav, Gopal Kumar Neupane, Sujana Khadka, Sitaram Sapkota, Shubha Devi |
author_facet | Amgain, Kapil Subedi, Prativa Yadav, Gopal Kumar Neupane, Sujana Khadka, Sitaram Sapkota, Shubha Devi |
author_sort | Amgain, Kapil |
collection | PubMed |
description | INTRODUCTION: Obesity has been reported to be linked with menstrual abnormalities including abnormality in cycle length, duration, and period blood loss. However, which anthropometric parameter is a better marker of menstrual abnormality is yet unknown. This study aims to explore the association of BMI, waist-hip ratio (WHR), and waist-height ratio (WHtR) with menstrual abnormalities. METHODS: This was a cross-sectional study conducted among 240 nursing students on two nursing campuses of Nepal. Demographic and menstrual characteristics related data were collected from the participants via the face-to-face interview technique followed by anthropometric measurements. Binary logistic regression was used to study the association of BMI, WHR, and WHtR with menstrual characteristics. Univariable and multivariable regression models were calculated at 95% confidence interval and a P value of 0.05 using a Statistical Package for Social Sciences, IBM SPSS® v21 (IBM, Armonk, New York). RESULTS: Out of 240 participants, 52 participants (21.67%) were underweight (<18.5 kg/m(2)), and 47 participants (19.58%) were either overweight (≥23 kg/m(2)) or obese (≥25 kg/m(2)). Overweight and obese BMI was associated with abnormality in menstrual cycle length (AOR = 4.24; 95% CI = 1.77–10.17), duration of the menstrual period (AOR = 2.52; 95% CI = 1.09–5.81), and periodic menstrual blood loss (AOR = 9.04; 95% CI = 3.55–23.01). Increase in WHtR (>0.5) was associated with abnormal cycle length (AOR = 3.09; 95% CI = 1.09–8.80) and abnormal period duration (AOR = 3.05; 95% CI = 1.10–8.44). An increase in WHR (>0.8) was associated with abnormal cyclical menstrual blood loss (AOR = 4.93; 95% CI = 1.55–15.71). CONCLUSIONS: Obesity predisposes to menstrual irregularities. BMI is a better predictor of menstrual irregularity as the increase in BMI is associated with abnormality in menstrual cycle length, period duration, and blood loss. Increased WHR was associated with periodic blood loss only. Increased WHtR was associated with abnormal cycle length and period duration, but not menstrual blood loss. |
format | Online Article Text |
id | pubmed-8956380 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-89563802022-03-26 Association of Anthropometric Indices with Menstrual Abnormality among Nursing Students of Nepal: A Cross-Sectional Study Amgain, Kapil Subedi, Prativa Yadav, Gopal Kumar Neupane, Sujana Khadka, Sitaram Sapkota, Shubha Devi J Obes Research Article INTRODUCTION: Obesity has been reported to be linked with menstrual abnormalities including abnormality in cycle length, duration, and period blood loss. However, which anthropometric parameter is a better marker of menstrual abnormality is yet unknown. This study aims to explore the association of BMI, waist-hip ratio (WHR), and waist-height ratio (WHtR) with menstrual abnormalities. METHODS: This was a cross-sectional study conducted among 240 nursing students on two nursing campuses of Nepal. Demographic and menstrual characteristics related data were collected from the participants via the face-to-face interview technique followed by anthropometric measurements. Binary logistic regression was used to study the association of BMI, WHR, and WHtR with menstrual characteristics. Univariable and multivariable regression models were calculated at 95% confidence interval and a P value of 0.05 using a Statistical Package for Social Sciences, IBM SPSS® v21 (IBM, Armonk, New York). RESULTS: Out of 240 participants, 52 participants (21.67%) were underweight (<18.5 kg/m(2)), and 47 participants (19.58%) were either overweight (≥23 kg/m(2)) or obese (≥25 kg/m(2)). Overweight and obese BMI was associated with abnormality in menstrual cycle length (AOR = 4.24; 95% CI = 1.77–10.17), duration of the menstrual period (AOR = 2.52; 95% CI = 1.09–5.81), and periodic menstrual blood loss (AOR = 9.04; 95% CI = 3.55–23.01). Increase in WHtR (>0.5) was associated with abnormal cycle length (AOR = 3.09; 95% CI = 1.09–8.80) and abnormal period duration (AOR = 3.05; 95% CI = 1.10–8.44). An increase in WHR (>0.8) was associated with abnormal cyclical menstrual blood loss (AOR = 4.93; 95% CI = 1.55–15.71). CONCLUSIONS: Obesity predisposes to menstrual irregularities. BMI is a better predictor of menstrual irregularity as the increase in BMI is associated with abnormality in menstrual cycle length, period duration, and blood loss. Increased WHR was associated with periodic blood loss only. Increased WHtR was associated with abnormal cycle length and period duration, but not menstrual blood loss. Hindawi 2022-03-18 /pmc/articles/PMC8956380/ /pubmed/35342646 http://dx.doi.org/10.1155/2022/6755436 Text en Copyright © 2022 Kapil Amgain et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Amgain, Kapil Subedi, Prativa Yadav, Gopal Kumar Neupane, Sujana Khadka, Sitaram Sapkota, Shubha Devi Association of Anthropometric Indices with Menstrual Abnormality among Nursing Students of Nepal: A Cross-Sectional Study |
title | Association of Anthropometric Indices with Menstrual Abnormality among Nursing Students of Nepal: A Cross-Sectional Study |
title_full | Association of Anthropometric Indices with Menstrual Abnormality among Nursing Students of Nepal: A Cross-Sectional Study |
title_fullStr | Association of Anthropometric Indices with Menstrual Abnormality among Nursing Students of Nepal: A Cross-Sectional Study |
title_full_unstemmed | Association of Anthropometric Indices with Menstrual Abnormality among Nursing Students of Nepal: A Cross-Sectional Study |
title_short | Association of Anthropometric Indices with Menstrual Abnormality among Nursing Students of Nepal: A Cross-Sectional Study |
title_sort | association of anthropometric indices with menstrual abnormality among nursing students of nepal: a cross-sectional study |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8956380/ https://www.ncbi.nlm.nih.gov/pubmed/35342646 http://dx.doi.org/10.1155/2022/6755436 |
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