分析影响索马里已婚妇女第一次分娩年龄的因素:使用SDHS 2020的贝叶斯共享脆弱模型方法
Abdisalan Ahmed Osman1, Abdisalam Amin Esse2, Abdisalam Hassan Muse3
1Department of Statistics, Jigjiga University, P.O. Box 1020, Jigjiga, Ethiopia. abdisalanahmd@gmail.com.
BMC women's health
|July 14, 2025
概括
在索马里,晚年第一次结婚的年龄大大延迟了分娩. 社会人口和经济因素,特别是结婚年龄和教育程度,是第一个出生时间的关键决定因素,对母亲的健康至关重要.
科学领域:
- 生殖健康 生殖健康
- 人口统计学 人口统计学
- 孕产妇健康 孕产妇健康
背景情况:
- 索马里面临着一个分散的卫生系统和高的孕产妇死亡率.
- 了解第一个出生时的年龄决定因素对于可持续发展目标3至关重要.
- 早期生育对母亲和孩子的福祉构成重大风险.
研究的目的:
- 检查影响索马里第一个出生年龄的社会人口统计学,经济和健康因素.
- 确定针对性公共卫生干预措施的第一个出生时间的关键预测因素.
- 使用先进的统计方法,模拟出生时间的变化.
主要方法:
- 贝叶斯共享脆弱模型用于分析第一个出生时间.
- 使用DIC和WAIC的韦布尔,日志正常和日志后勤模型的比较.
- 分析因素,包括结婚时的年龄,居住地,教育程度,财富和避孕药的使用.
主要成果:
- 第一次结婚时的年龄是最强的预测因素,显著降低了第一个出生的危险 (HR=0.4636).
- 农村居住与延迟第一次分娩有关 (HR=0.9411).
- 贝叶斯逻辑逻辑加速失效时间 (AFT) 共享脆弱性模型提供了最合适的.
结论:
- 在第一次婚姻中晚年和高等教育是延迟分娩的关键预测因素.
- 社会人口和经济因素显著影响索马里的生殖时间.
- 针对早期生育的干预措施对于改善母亲和儿童健康结果至关重要.
相关概念视频
Factors Affecting Illness
4.4K
When a person's physical, emotional, intellectual, social development or spiritual functioning is compromised, this deviation from a healthy normal state is called illness. Illness creates stress that in turn harms individuals. Irritation, anger, denial, hopelessness, and fear are behavioral and emotional changes an individual experiences in the phases of illness. A variety of factors influence a person's health and well-being.
For instance, risk factors are connected to illness,...
For instance, risk factors are connected to illness,...
4.4K
Applications of Life Tables
125
Life tables are versatile across various fields, providing a quantitative basis for analyzing mortality and survival rates. Whether used by demographers, actuaries, epidemiologists, or sociologists, life tables offer valuable insights into the dynamics of life and death, facilitating informed decisions in public health, insurance, conservation, and beyond. Their broad applicability highlights the interconnectedness of demographic data with practical outcomes in everyday life and strategic...
125
Bias in Epidemiological Studies
695
Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:
695
Life Tables
199
A life table is a statistical tool that summarizes the mortality and survival patterns of a population, providing detailed insights into the likelihood of survival or death across different age intervals within a cohort. By organizing data on survival probabilities and mortality rates, life tables offer a clear snapshot of population dynamics over time. They are extensively used in demography, public health, actuarial science, and ecology to analyze life expectancy, design health interventions,...
199
Longitudinal Studies
248
Longitudinal studies are also widely used in other medical and social science fields. For instance, in cardiovascular research, they can monitor patients' health over decades to identify risk factors for heart disease, such as high cholesterol or smoking, and evaluate the long-term effectiveness of preventive measures. Similarly, in mental health studies, researchers might follow individuals from adolescence into adulthood to understand the development and progression of conditions like...
248
Parametric Survival Analysis: Weibull and Exponential Methods
622
Parametric survival analysis models survival data by assuming a specific probability distribution for the time until an event occurs. The Weibull and exponential distributions are two of the most commonly used methods in this context, due to their versatility and relatively straightforward application.
Weibull Distribution
The Weibull distribution is a flexible model used in parametric survival analysis. It can handle both increasing and decreasing hazard rates, depending on its shape parameter...
Weibull Distribution
The Weibull distribution is a flexible model used in parametric survival analysis. It can handle both increasing and decreasing hazard rates, depending on its shape parameter...
622


