Background: This study aims to explore the risk factors inducing
bacterial vaginosis (BV) and establish a nomogram prediction model.
Methods: Single-factor analysis and multivariate logistic regression
were used to analyze the risk factors affecting the onset of BV. The selected
risk factors were incorporated into the R software to establish a nomogram
prediction model. The effectiveness of the proposed model was evaluated.
Results: The cleanliness of vaginal secretions above grade III accounted
for 90.86% (169/186) of the cases. Multivariate logistic regression analysis
showed that the use of nursing pads during non-menstrual periods, history of
miscarriage 1 time, self-vaginal douche, and frequency of sexual activity
5 time per week were identified as risk factors for the incidence of BV
(p 0.05). Using condoms as a method of contraception was identified
as a protective factor for the incidence of BV (p 0.05); A nomogram
prediction model was established based on the aforementioned risk factors, and
the area under the receiver operating characteristic (ROC) curve was 0.789 (95%
confidence interval (CI): 0.751–0.827), indicating that the nomogram had a good
degree of discrimination. The slope of the calibration curve was close to 1.
Decision curve analysis (DCA) shows that it has good clinical value.
Conclusions: The nomogram prediction model established based on BV risk
factors has good discrimination and high degree of consistency.
