华南预防医学 ›› 2021, Vol. 47 ›› Issue (7): 829-833.doi: 10.12183/j.scjpm.2021.0829

• 论著 •    下一篇

分段线性回归分析在政策干预评价中的应用及SAS实现

夏晓燕, 何健荣, 沈松英, 魏雪灵, 于佳, 肖晚晴, 刘慧慧, 邱琇   

  1. 广州市妇女儿童医疗中心 广州医科大学,广东 广州 510623
  • 收稿日期:2020-12-24 出版日期:2021-07-20 发布日期:2021-08-06
  • 通讯作者: 邱琇,E-mail: xiu.qiu@bigcs.org
  • 作者简介:夏晓燕(1981—),女,硕士研究生,主治医师,从事妇幼流行病学研究
  • 基金资助:
    国家科技部重点研发计划(2016YFC1000304); 广州市卫生健康委员会(2019A031002)

The application of segmented linear regression in the evaluation of policy intervention and SAS implementation

XIA Xiao-yan, HE Jian-rong, SHEN Song-ying, WEI Xue-ling, YU Jia, XIAO Wan-qing, LIU Hui-hui, QIU Xiu   

  1. Guangzhou Women and Children’s Medical Center, Guangzhou Medical University, Guangzhou 510623, China
  • Received:2020-12-24 Online:2021-07-20 Published:2021-08-06

摘要: 目的 探讨中断时间序列设计分段线性回归分析在政策干预评价中的应用及SAS软件实现,为公共卫生政策研究人员提供方法学应用的参考与借鉴。方法 以二孩政策对剖宫产率的影响为例,采用SAS软件对2013年1月至2016年12月广州市Ⅳ类助产技术服务机构剖宫产率进行分段线性回归模型拟合,模型分析包括模型原理、SAS程序、自相关和协变量控制等。结果 分段线性回归分析表明,调整年龄和剖宫产史后,单独二孩政策和全面二孩政策的实施对广州市Ⅳ类助产技术服务机构剖宫产率水平和趋势的改变没有统计学意义(P>0.05)。结论 分段线性回归模型为评价政策干预的影响提供了有力工具,可以评价干预前后观测指标在水平和趋势上的改变,但该分析有一定的局限性,应用时要注意适用条件及其结果解释。

关键词: 中断时间序列, 分段线性回归, 政策影响, SAS软件

Abstract: Objective To explore the application of segmented linear regression of interrupted time series design in the evaluation of policy intervention and SAS implementation, and to provide reference for public health policy researchers in methodology application. Methods Taking the influence of the two-child policy on the cesarean section (CS) rates as an example, SAS software was used for the segmented linear regression model in the CS rates at Ⅳ-class maternity hospitals in Guangzhou between January 2013 to December 2016, including principle of the model, SAS program, controlling for autocorrelation and adjustment of covariates. Results The segmented linear regression analysis showed that there was no significant change in the level and trend of CS rate at Ⅳ-class maternity hospitals in Guangzhou both during the period of the selective two-child policy and the universal two-child policy after adjusting maternal age and the history of CS. Conclusion The segmented linear regression model is a powerful tool for evaluating the effects of policy by estimating the changes in the level and trend of observed indicators before and after the intervention, but attention should be paid to the applicable conditions and the interpretation of the results for its limitations.

Key words: Interrupted time series, Segmented linear regression, Effects of policy, SAS software

中图分类号: 

  • R173