Department of Oncology, Shandong Cancer Hospital affiliated to Shandong University, Shandong Academy of Medical Sciences, Jinan City, Shandong Province, China.
Department of Nutrition and Food Hygiene, School of Public Health, Shandong University, Jinan City, Shandong Province, China.
Biosci Rep. 2020 Mar 27;40(3). doi: 10.1042/BSR20190919.
To identify the potential risk factors for acute mastitis during lactation comprehensively. Subsequently, to evaluate logistic regression model in predicting the risk of lactational mastitis in Chinese women by applying receiver operating characteristic (ROC) curve.
A case-control study among Chinese women enrolled 652 patients with mastitis and 581 healthy women with breastfeeding experience as control. The retrospective information was obtained by questionnaires that included medical history of pregnancy, delivery, puerperium and breastfeeding behaviors. Univariate analysis and multivariate logistic regression model were performed to investigate the relationship between these factors and the occurrence of lactational mastitis. Using ROC curve to evaluate the prognostic value of these selected indicators in the risk of acute mastitis.
The multivariate logistic regression analysis showed that the primiparity (P < 0.001), mastitis in previous breastfeeding (P < 0.001), nipple's heteroplasia (P < 0.001), cracked nipple (P < 0.001), breast trauma by external force (P = 0.002), lateral position (P = 0.007), breast pump (P = 0.039), nipple sucking (P = 0.007), sleep with sucking (P = 0.007), and tongue-tie (P = 0.013) were risk variables independently and significantly related with mastitis. While vaginal delivery (P = 0.015), clean nipple before breastfeeding (P = 0.015), first contact with child within 1 h (P = 0.027) were protective factors. The ROC analysis demonstrated that the area under the curve of model 2 was 0.8122 (95%CI = 0.7885-0.8360), which stated that the model presented a high sensitivity and specificity.
By means of collecting and summarizing the risk factors associated with the occurrence of breast mastitis in Chinese women, we established risk discriminant model to identify and warn the individuals susceptible to acute mastitis early, which will allow practitioners to provide appropriate management advice and effective individual care.
全面识别哺乳期急性乳腺炎的潜在危险因素。随后，通过应用受试者工作特征（ROC）曲线，评估逻辑回归模型在中国女性哺乳期乳腺炎风险预测中的作用。
采用病例对照研究，纳入 652 例乳腺炎患者和 581 例有母乳喂养史的健康对照妇女。通过问卷调查获得回顾性信息，内容包括妊娠、分娩、产褥期和母乳喂养行为的病史。采用单因素分析和多因素逻辑回归模型，探讨这些因素与哺乳期乳腺炎发生的关系。应用 ROC 曲线评估这些选定指标对急性乳腺炎风险的预测价值。
多因素逻辑回归分析显示，初产妇（P<0.001）、既往哺乳期乳腺炎（P<0.001）、乳头畸形（P<0.001）、乳头皲裂（P<0.001）、外力引起的乳房创伤（P=0.002）、侧卧位（P=0.007）、吸奶器（P=0.039）、乳头吸吮（P=0.007）、含乳睡眠（P=0.007）和舌系带过短（P=0.013）是与乳腺炎显著相关的独立危险因素。而阴道分娩（P=0.015）、母乳喂养前清洁乳头（P=0.015）、产后 1 h 内首次与婴儿接触（P=0.027）是保护因素。ROC 分析显示，模型 2 的曲线下面积为 0.8122（95%CI=0.7885-0.8360），表明该模型具有较高的灵敏度和特异性。
通过收集和总结与中国女性乳腺炎发生相关的危险因素，我们建立了风险判别模型，以早期识别和预警易患急性乳腺炎的个体，从而使临床医生能够提供适当的管理建议和有效的个体护理。
