Effect of Behavioral Factors on Severity of Female Pattern Hair Loss: An Ordinal Logistic Regression Analysis

Yi, Yanhua; Li, Xiaoqiang; Jia, James; Guy Didier, Djakaya Ngondi; Qiu, Jun; Fu, Jile; Mao, Xiaoyan; Miao, Yong; Hu, Zhiqi

doi:10.7150/ijms.45979



Theranostics

International Journal of Biological Sciences

Nanotheranostics

Journal of Cancer

Journal of Genomics

Global reach, higher impact

Full Text | PDF

Int J Med Sci 2020; 17(11):1584-1588. doi:10.7150/ijms.45979 This issue Cite

Research Paper

Effect of Behavioral Factors on Severity of Female Pattern Hair Loss: An Ordinal Logistic Regression Analysis

Yanhua Yi^#, Xiaoqiang Li^#, James Jia, Djakaya Ngondi Guy Didier, Jun Qiu, Jile Fu, Xiaoyan Mao, Yong Miao^✉, Zhiqi Hu^✉

Department of Plastic and Aesthetic Surgery, Nanfang Hospital of Southern Medical University, Guangzhou, Guangdong 510515, China.
#These authors contributed equally to this study.

Citation:

Yi Y, Li X, Jia J, Guy Didier DN, Qiu J, Fu J, Mao X, Miao Y, Hu Z. Effect of Behavioral Factors on Severity of Female Pattern Hair Loss: An Ordinal Logistic Regression Analysis. Int J Med Sci 2020; 17(11):1584-1588. doi:10.7150/ijms.45979. https://www.medsci.org/v17p1584.htm

Other styles

Abstract

Background: Female pattern hair loss (FPHL) is one of the most common types of hair loss with complex genetic predisposition. A frontal pattern hair loss with ponytail hairstyle is pervasively seen among young Chinese women. The purpose of this study is to investigate the association between the severity of FPHL and behavioral factors which include dietary, and sleep habits, and to test the hypothesis on whether ponytail hairstyle is an independent factor that increases the risks of being more severe on the FPHL scale.

Methods: A cross-sectional survey was performed with a structured questionnaire in this study. The severity of FPHL was graded according to basic and specific (BASP) classifications. Ordinal logistic regression analysis was performed to investigate the factors related to the severity of FPHL.

Results: 1,825 participants with different severities of FPHL completed the questionnaire. Ordinal logistic regression analysis revealed that the age group between thirty and forty years (OR:2.03, 95% CI: 1.56,2. 65), insufficient time with poor quality (OR:1.30, 95% CI: 1.05,1.62), presence of alcohol consumption (OR:2.15, 95% CI: 1.14,4.42), ponytail hairstyles (OR:2.03, 95% CI: 1.40,2.96), and oily scalps (OR:2.00, 95% CI: 1.65,2.43) were risk factors which increased the odds of being in the more severe type of FPHL, compared to the age group that ranged from eighteen to thirty years, sufficient sleep with good quality, without alcohol consumption, ponytail hairstyles, and oily scalps.

Conclusion: Avoiding alcohol consumption and ponytail hairstyles, in combination with proper control of scalp oil, improve sleep quality with sufficient time may help prevent FPHL from deteriorating to the more severe type.

Keywords: Female pattern hair loss (FPHL), alcohol consumption, alopecia, traction, China

Citation styles

APA

Yi, Y., Li, X., Jia, J., Guy Didier, D.N., Qiu, J., Fu, J., Mao, X., Miao, Y., Hu, Z. (2020). Effect of Behavioral Factors on Severity of Female Pattern Hair Loss: An Ordinal Logistic Regression Analysis. International Journal of Medical Sciences, 17(11), 1584-1588. https://doi.org/10.7150/ijms.45979.

ACS

Yi, Y.; Li, X.; Jia, J.; Guy Didier, D.N.; Qiu, J.; Fu, J.; Mao, X.; Miao, Y.; Hu, Z. Effect of Behavioral Factors on Severity of Female Pattern Hair Loss: An Ordinal Logistic Regression Analysis. Int. J. Med. Sci. 2020, 17 (11), 1584-1588. DOI: 10.7150/ijms.45979.

NLM

CSE

Yi Y, Li X, Jia J, Guy Didier DN, Qiu J, Fu J, Mao X, Miao Y, Hu Z. 2020. Effect of Behavioral Factors on Severity of Female Pattern Hair Loss: An Ordinal Logistic Regression Analysis. Int J Med Sci. 17(11):1584-1588.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/). See http://ivyspring.com/terms for full terms and conditions.