在津巴布韦的女性中,模拟性首次亮相的时间,使用地质增量离散时间生存方法
Alphonce Bere1, Innocent Maposa2,3, Zvifadzo Matsena-Zingoni4
1Department of Mathematical and Computational Sciences, University of Venda, Thohoyandou, South Africa.
BMC women's health
|March 25, 2025
概括
津巴布韦的早期性行为与低教育和财富有关. 干预措施应集中在马塔贝莱兰北部和南部省份的高风险群体,以减少未成年人怀孕和相关的健康风险.
科学领域:
- 公共卫生 公共卫生
- 人口统计学 人口统计学
- 流行病学 流行病学
背景情况:
- 早期的性行为带来重大健康风险,包括性传播感染,艾滋病毒,心理健康问题和怀孕并发症.
- 津巴布韦面临着高频率的未成年人怀孕,这表明青少年早期性行为是持续存在的问题.
- 这项研究调查了影响津巴布韦妇女早期性首秀时间的空间模式和社会人口因素.
研究的目的:
- 分析津巴布韦早期性活动的空间分布.
- 确定与津巴布韦妇女早期性行为相关的人口和社会经济决定因素.
- 为青少年性健康提供有针对性的公共卫生干预信息.
主要方法:
- 利用了2015年津巴布韦人口和健康调查 (ZDHS) 中的9,882名生育年龄的津巴布韦妇女的数据.
- 定义早期的性初恋是18岁之前的第一次性交.
- 采用完全贝叶斯地质增值离散时间生存模型,调整调查权重以考虑不平等的采样概率.
主要成果:
- 较高的教育水平 (小学,中学,高等) 与未受过教育的人相比,早期性初恋的几率明显较低.
- 家庭财富指数较高的女性的早期性初恋几率较低,而指数较低的女性与中等财富群体相比的几率更高.
- 在马塔贝莱兰北省和马塔贝莱兰南省确定了早期性行为首发的热点;居住地和出生年龄队列不是重要因素.
结论:
- 针对性的干预措施在Matabeleland North和Matabeleland South省份至关重要,以应对早期的性行为.
- 干预措施还应重点关注确定的高风险人口和社会经济群体.
- 在津巴布韦青少年中,应对早期的性行为是减轻负面健康后果的关键.
相关概念视频
01:15Assumptions of Survival Analysis
76
Survival models analyze the time until one or more events occur, such as death in biological organisms or failure in mechanical systems. These models are widely used across fields like medicine, biology, engineering, and public health to study time-to-event phenomena. To ensure accurate results, survival analysis relies on key assumptions and careful study design.
76
01:18Introduction To Survival Analysis
144
Survival analysis is a statistical method used to study time-to-event data, where the "event" might represent outcomes like death, disease relapse, system failure, or recovery. A unique feature of survival data is censoring, which occurs when the event of interest has not been observed for some individuals during the study period. This requires specialized techniques to handle incomplete data effectively.
The primary goal of survival analysis is to estimate survival time—the time...
The primary goal of survival analysis is to estimate survival time—the time...
144
01:09Censoring Survival Data
54
Survival analysis is a statistical method used to analyze time-to-event data, often employed in fields such as medicine, engineering, and social sciences. One of the key challenges in survival analysis is dealing with incomplete data, a phenomenon known as "censoring." Censoring occurs when the event of interest (such as death, relapse, or system failure) has not occurred for some individuals by the end of the study period or is otherwise unobservable, and it might have many different...
54
01:19Survival Tree
48
Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
Building a Survival Tree
Constructing a...
Building a Survival Tree
Constructing a...
48
01:09Truncation in Survival Analysis
141
Truncation in survival analysis refers to the exclusion of individuals or events from the dataset based on specific criteria related to the time of the event. This exclusion can happen in two primary forms: left truncation and right truncation.
Left truncation occurs when individuals who experienced the event of interest before a certain time are not included in the study. This is often due to a "delayed entry" into the study where only those who survive until a certain entry point are...
Left truncation occurs when individuals who experienced the event of interest before a certain time are not included in the study. This is often due to a "delayed entry" into the study where only those who survive until a certain entry point are...
141
01:20Comparing the Survival Analysis of Two or More Groups
107
Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
107