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肯尼亚女性首次产前检查就诊时间及其预测因素:威布尔伽马共享脆弱模型(基于2022年肯尼亚人口与健康调查最新数据)

Time to first antenatal care visit and its predictors among women in Kenya: Weibull gamma shared frailty model (based on the recent 2022 KDHS data).

作者信息

Kase Bizunesh Fantahun, Seifu Beminate Lemma, Mare Kusse Urmale, Shibeshi Abdu Hailu, Asebe Hiwot Altaye, Gemeda Kebede, Asmare Zufan Alamrie, Asgedom Yordanos Sisay, Fente Bezawit Melak, Lombebo Afework Alemu, Tebeje Tsion Mulat

机构信息

Department of Public Health, College of Medicine and Health Sciences, Samara University, Samara, Ethiopia.

Department of Nursing, College of Medicine and Health Sciences, Samara University, Samara, Ethiopia.

出版信息

BMC Pregnancy Childbirth. 2025 Jan 22;25(1):50. doi: 10.1186/s12884-025-07178-y.

DOI:10.1186/s12884-025-07178-y
PMID:39844082
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11752801/
Abstract

BACKGROUND

The first trimester of pregnancy is critical for fetal development, making early antenatal care visits essential for timely check-ups and managing potential complications. However, delayed antenatal care initiation remains a public health challenge in sub-Saharan Africa, including Kenya. Therefore, this study aimed to assess and provide up-to-date information on time to first antenatal care visit and its predictors among women in Kenya, using data from the most recent 2022 Kenya Demographic and Health Survey (KDHS).

METHODS

This community-based cross-sectional study analyzed data from 19,530 birth histories in the 2022 Kenya Demographic and Health Survey (KDHS). The primary outcome was the timing of the first antenatal care (ANC) visit, classified as timely if it occurred in the first trimester. Shared frailty survival models were used to account for the hierarchical data structure and unobserved heterogeneity, with the Weibull gamma model identified as the best fit based on Information Criteria (AIC), and Bayesian Information Criteria (BIC). Variables with p < 0.2 entered multivariable analysis, and results were reported as Adjusted Hazard Ratios (AHR) with 95% Confidence Intervals (CI) using the Weibull gamma model.

RESULTS

The study found that the median time for the first antenatal care (ANC) visit in Kenya was four months. Significant predictors of ANC timing included women's age (35-49 years: AHR 0.83; 95% CI: 0.72-0.95), education level (higher: AHR 1.45; 95% CI: 1.17-1.78), media exposure (yes: AHR 1.21; 95% CI: 1.05-1.39), parity (four or more children: AHR 0.81; 95% CI: 0.72-0.91), wealth status (richest: AHR 2.00; 95% CI: 1.63-2.43), desire for more children (did not want more: AHR 0.64; 95% CI: 0.54-0.77), residence (rural: AHR 1.22; 95% CI: 1.07-1.39), and religion (Islam: AHR 0.76; 95% CI: 0.64-0.89).

CONCLUSION

The median time for the first ANC visit exceeds the World Health Organization's recommendation of initiating care within the first trimester. These findings underscore the need for targeted interventions to promote timely ANC, especially among women with limited media exposure, high parity, lower socioeconomic status, and specific religious followers.

摘要

背景

怀孕的头三个月对胎儿发育至关重要,因此早期产前检查对于及时进行检查和管理潜在并发症至关重要。然而,在撒哈拉以南非洲,包括肯尼亚,延迟开始产前护理仍然是一项公共卫生挑战。因此,本研究旨在利用2022年肯尼亚最新人口与健康调查(KDHS)的数据,评估并提供肯尼亚女性首次产前检查时间及其预测因素的最新信息。

方法

这项基于社区的横断面研究分析了2022年肯尼亚人口与健康调查(KDHS)中19530份生育史的数据。主要结果是首次产前检查(ANC)的时间,如果在孕早期进行则分类为及时。使用共享脆弱性生存模型来考虑分层数据结构和未观察到的异质性,基于信息准则(AIC)和贝叶斯信息准则(BIC),确定威布尔伽马模型为最佳拟合模型。p < 0.2的变量进入多变量分析,并使用威布尔伽马模型将结果报告为调整风险比(AHR)及95%置信区间(CI)。

结果

研究发现,肯尼亚首次产前检查(ANC)的中位时间为四个月。ANC时间的显著预测因素包括女性年龄(35 - 49岁:AHR 0.83;95% CI:0.72 - 0.95)、教育水平(较高:AHR 1.45;95% CI:1.17 - 1.78)、媒体接触情况(是:AHR 1.21;95% CI:1.05 - 1.39)、产次(四个或更多孩子:AHR 0.81;95% CI:0.72 - 0.91)、财富状况(最富有:AHR 2.00;95% CI:1.63 - 2.43)、生育更多孩子的意愿(不想要更多孩子:AHR 0.64;95% CI:0.54 - 0.77)、居住地(农村:AHR 1.22;95% CI:1.07 - 1.39)和宗教信仰(伊斯兰教:AHR 0.76;95% CI:0.64 - 0.89)。

结论

首次ANC检查的中位时间超过了世界卫生组织关于在孕早期开始护理的建议。这些发现强调了需要有针对性的干预措施来促进及时进行ANC检查,特别是在媒体接触有限、产次高、社会经济地位较低以及特定宗教信徒的女性中。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b1f5/11752801/d40903faca73/12884_2025_7178_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b1f5/11752801/6bbb4b657481/12884_2025_7178_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b1f5/11752801/d40903faca73/12884_2025_7178_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b1f5/11752801/6bbb4b657481/12884_2025_7178_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b1f5/11752801/d40903faca73/12884_2025_7178_Fig2_HTML.jpg

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