Prediction of risk of depressive symptoms in menopausal women based on hot flash and sweating symptoms: a multicentre study

Yanwei Zheng,1 Yibei Zhou,1 Jiangshan Hu,1 Jieping Zhu,2 Qi Hua,3 Minfang Tao1 1Department of Gynecology and Obstetrics, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, 2Department of Gynecology and Obstetrics, Shanghai Sixth People’s Hospital East Branch, 3Dep...

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Autores principales: Zheng YW, Zhou YB, Hu JS, Zhu JP, Hua Q, Tao MF
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Publicado: Dove Medical Press 2017
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spelling oai:doaj.org-article:5d3d5ac03a534939a0a7b2b7fac155cc2021-12-02T02:41:52ZPrediction of risk of depressive symptoms in menopausal women based on hot flash and sweating symptoms: a multicentre study1178-1998https://doaj.org/article/5d3d5ac03a534939a0a7b2b7fac155cc2017-11-01T00:00:00Zhttps://www.dovepress.com/prediction-of-risk-of-depressive-symptoms-in-menopausal-women-based-on-peer-reviewed-article-CIAhttps://doaj.org/toc/1178-1998Yanwei Zheng,1 Yibei Zhou,1 Jiangshan Hu,1 Jieping Zhu,2 Qi Hua,3 Minfang Tao1 1Department of Gynecology and Obstetrics, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, 2Department of Gynecology and Obstetrics, Shanghai Sixth People’s Hospital East Branch, 3Department of Gynecology and Obstetrics, International Peace Maternal and Child Health Hospital of the China Welfare Institute, Shanghai, People’s Republic of China Objective: The present study aimed to develop a symptom-based (namely, hot flashes and sweating) scoring system for predicting the risk of depressive symptoms in menopausal women via a multicentre cross-sectional survey. Methods: The data examined in the present study were obtained from 1,004 women aged 40–60 years who underwent physical examination at A Hospital. The basic information was obtained using a questionnaire-based survey. A self-rating depression scale was used to obtain the depressive symptom scores, while the Kupperman Menopausal Index was used to obtain the scores for the frequency of hot flashes and sweating. A logistic regression model was also established. The resulting β coefficient was employed to calculate and predict the risk of depressive symptoms in these women and a risk scoring system was established. The scoring system was validated using samples from 2 other centers (validation sample 1: B Hospital, 440 women; validation sample 2: C Hospital, 247 women). Results: The scoring system developed to predict the risk of depressive symptoms in menopausal women was based on hot flash and sweating symptoms and associated with menopausal status, hot flash scores, education level (high school education and below) and being diabetic. The scoring system yielded a total score of 0–54 points. For women in the study sample, the area under the curve (AUC) of depressive symptom risk score was 0.750 (95% CI, 0.708–0.793). Validation sample 1 had an AUC of 0.731 (95% CI, 0.667–0.794), while validation sample 2 had an AUC of 0.744 (95% CI, 0.669–0.820). The optimal cut-off score to assess depressive symptoms in women participating in the present study was 31 points. The sensitivity and specificity for predicting depressive symptoms in the study sample were 0.667 and 0.701, respectively. In contrast, the sensitivity was 0.840 in validation sample 1 and 0.879 in validation sample 2. Conclusion: The hot flash and sweating symptom-based scoring system developed to predict the risk of depressive symptoms in menopausal women relies on non-laboratory survey data. The system is simple, practical, and convenient to use. For Chinese huge population of menopausal women, the scoring system should be considered a reliable screening tool for depressive symptoms. Keywords: menopause, depressive symptoms, hot flash, sweatingZheng YWZhou YBHu JSZhu JPHua QTao MFDove Medical Pressarticlemenopausedepressive symptomshot flash and sweatingGeriatricsRC952-954.6ENClinical Interventions in Aging, Vol Volume 12, Pp 1993-2001 (2017)
institution DOAJ
collection DOAJ
language EN
topic menopause
depressive symptoms
hot flash and sweating
Geriatrics
RC952-954.6
spellingShingle menopause
depressive symptoms
hot flash and sweating
Geriatrics
RC952-954.6
Zheng YW
Zhou YB
Hu JS
Zhu JP
Hua Q
Tao MF
Prediction of risk of depressive symptoms in menopausal women based on hot flash and sweating symptoms: a multicentre study
description Yanwei Zheng,1 Yibei Zhou,1 Jiangshan Hu,1 Jieping Zhu,2 Qi Hua,3 Minfang Tao1 1Department of Gynecology and Obstetrics, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, 2Department of Gynecology and Obstetrics, Shanghai Sixth People’s Hospital East Branch, 3Department of Gynecology and Obstetrics, International Peace Maternal and Child Health Hospital of the China Welfare Institute, Shanghai, People’s Republic of China Objective: The present study aimed to develop a symptom-based (namely, hot flashes and sweating) scoring system for predicting the risk of depressive symptoms in menopausal women via a multicentre cross-sectional survey. Methods: The data examined in the present study were obtained from 1,004 women aged 40–60 years who underwent physical examination at A Hospital. The basic information was obtained using a questionnaire-based survey. A self-rating depression scale was used to obtain the depressive symptom scores, while the Kupperman Menopausal Index was used to obtain the scores for the frequency of hot flashes and sweating. A logistic regression model was also established. The resulting β coefficient was employed to calculate and predict the risk of depressive symptoms in these women and a risk scoring system was established. The scoring system was validated using samples from 2 other centers (validation sample 1: B Hospital, 440 women; validation sample 2: C Hospital, 247 women). Results: The scoring system developed to predict the risk of depressive symptoms in menopausal women was based on hot flash and sweating symptoms and associated with menopausal status, hot flash scores, education level (high school education and below) and being diabetic. The scoring system yielded a total score of 0–54 points. For women in the study sample, the area under the curve (AUC) of depressive symptom risk score was 0.750 (95% CI, 0.708–0.793). Validation sample 1 had an AUC of 0.731 (95% CI, 0.667–0.794), while validation sample 2 had an AUC of 0.744 (95% CI, 0.669–0.820). The optimal cut-off score to assess depressive symptoms in women participating in the present study was 31 points. The sensitivity and specificity for predicting depressive symptoms in the study sample were 0.667 and 0.701, respectively. In contrast, the sensitivity was 0.840 in validation sample 1 and 0.879 in validation sample 2. Conclusion: The hot flash and sweating symptom-based scoring system developed to predict the risk of depressive symptoms in menopausal women relies on non-laboratory survey data. The system is simple, practical, and convenient to use. For Chinese huge population of menopausal women, the scoring system should be considered a reliable screening tool for depressive symptoms. Keywords: menopause, depressive symptoms, hot flash, sweating
format article
author Zheng YW
Zhou YB
Hu JS
Zhu JP
Hua Q
Tao MF
author_facet Zheng YW
Zhou YB
Hu JS
Zhu JP
Hua Q
Tao MF
author_sort Zheng YW
title Prediction of risk of depressive symptoms in menopausal women based on hot flash and sweating symptoms: a multicentre study
title_short Prediction of risk of depressive symptoms in menopausal women based on hot flash and sweating symptoms: a multicentre study
title_full Prediction of risk of depressive symptoms in menopausal women based on hot flash and sweating symptoms: a multicentre study
title_fullStr Prediction of risk of depressive symptoms in menopausal women based on hot flash and sweating symptoms: a multicentre study
title_full_unstemmed Prediction of risk of depressive symptoms in menopausal women based on hot flash and sweating symptoms: a multicentre study
title_sort prediction of risk of depressive symptoms in menopausal women based on hot flash and sweating symptoms: a multicentre study
publisher Dove Medical Press
publishDate 2017
url https://doaj.org/article/5d3d5ac03a534939a0a7b2b7fac155cc
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