基于诺莫格拉姆模型的过度妊娠体重增加的风险预测:中国的一项前性观察研究
Linyan He1, Xihong Zhou1, Jiajun Tang2
1Clinical Nursing Teaching and Research Section, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China.
概括
一个新的模型预测了中国孕妇的过度妊娠体重增加,识别了妊娠前肥胖和不健康的饮食习惯等危险因素. 这种工具有助于早期干预,以改善母亲和婴儿健康结果.
科学领域:
- 产科和妇科 产科和妇科
- 公共卫生 公共卫生
- 生殖医学 生殖医学
背景情况:
- 过度妊娠体重增加 (EGWG) 对母亲和婴儿构成重大全球健康风险.
- 早期识别和干预对于管理EGWG流行率至关重要.
- 中国目前缺乏有效的工具来预测EGWG风险.
研究的目的:
- 在中国孕妇中开发EGWG的风险预测模型.
- 为早期识别高风险个体创建一个查工具.
- 为 EGWG 预防提供有针对性的干预信息.
主要方法:
- 用物流回归分析来构建风险预测模型.
- 使用R4.3.1软件开发了一个名图,用于可视化.
- 模型性能通过Hosmer-Lemeshow测试,ROC曲线,校准图表和k折交叉验证进行评估.
主要成果:
- 在研究人群中,EGWG的患病率为50.32%.
- 确定的关键风险因素包括怀孕前的超重/肥胖,屏幕时间饮食,大量摄入含糖食物/饮料以及对身体形象的担忧.
- 保护因素包括更高的平价,对体重管理的动机,以及定期的中等强度体育活动.
结论:
- 开发的nomogram模型显示了对EGWG风险的良好歧视和校准.
- 这种工具为早期识别危险怀孕提供了宝贵的基础.
- 这些发现支持精确的干预措施,以减轻EGWG和改善母婴健康.
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