five

Underlying data set.

收藏
Figshare2023-07-19 更新2026-04-28 收录
下载链接:
https://figshare.com/articles/dataset/Underlying_data_set_/23711648
下载链接
链接失效反馈
官方服务:
资源简介:
BackgroundOver the previous few decades, significant progress has been made in reducing newborn mortality, but the worldwide scale of the problem remains high. A considerable number of newborn death and difficulties owing to neonatal danger signs could be avoided if mothers sought appropriate health care for common neonatal risk indications, according to a number of studies presently underway in Ethiopia. The aim of this study is to assess health care seeking behavior of mothers’ in related to neonatal danger signs.MethodA community-based cross-sectional study was conducted among 410 participants in Wolaita Sodo, From October 1 to October 30, 2019. To collect data, structured interviewer administered questionnaire was used. Data was coded, cleaned, recoded and entered in to epi-data version 3.1 and transported to SPSS window version 21 for analysis. Multivariable logistic regression was carried out and p-value of less than or equal to 0.05 was considered statistically significant.ResultA total of 410 mothers participated in this study, 110 (47.6%) mothers preferred health intuition for their neonate. Husband educational status (AOR = 2.4, 95% CI = 1.1, 5.5), communication media (AOR = 4.3, 95% CI = 2.4, 7.5), place of residence (AOR = 3.5, 95% C.I = 1.9, 6.7), ANC follow up (AOR = 2.8, 95% CI = 1.4, 5.8), and PNC follow (AOR = 1.7, 95% CI = 1.1, 3.1) were all factors that significantly associated with health care seeking practice neonatal dander signs.ConclusionOverall, there was a low degree of health-seeking practice. The educational status of the mother’s husband, communication media, residence, ANC follow-up, and PNC follow-up all predicted the mothers’ health-care seeking behavior. The study also identifies the Wolaita Zone and Sodo town health offices, the health development army, one to five local community organizations with and health extension workers as key contributors.
创建时间:
2023-07-19
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作