2002年至2018年,肯尼亚内罗毕非正式定居点五岁以下儿童死亡率的决定因素
Samuel Iddi1,2, Dennis Akeyo3, Richard E Sanya4
1Data Science and Evaluation Unit, African Population and Health Research Center, Nairobi, Kenya. siddi@aphrc.org.
BMC public health
|October 16, 2024
概括
在城市非正式定居点,儿童死亡率仍然很高. 接种疫苗和对母亲的支持等干预措施可以减少这些脆弱社区中五岁以下儿童的死亡.
科学领域:
- 全球健康 全球健康
- 儿科 儿科 儿科
- 人口统计学 人口统计学
背景情况:
- 儿童死亡率不成比例地影响低收入和中等收入国家,特别是在城市非正式定居点.
- 在这些特定的城市环境中,对死亡风险因素的研究有限.
- 本研究侧重于2002-2018年内罗毕非正式定居点5岁以下儿童死亡率.
研究的目的:
- 评估内罗毕城市非正式定居点五岁以下儿童死亡率.
- 确定导致五岁以下儿童死亡率的相关风险因素.
- 为有针对性的公共卫生干预提供证据.
主要方法:
- 利用了来自内罗毕城市卫生和人口监测系统 (NUHDSS) 的二次数据.
- 在生存分析中采用卡普兰-梅尔曲线.
- 应用了Cox比例危险模型与脆弱性术语来评估风险因素.
主要成果:
- 五岁以下儿童的总体生存率为96.8%,随着时间的推移呈现改善 (2002-2006年为82.6%,2012-2018年为98.4%).
- 在BCG疫苗接种儿童中观察到死亡风险降低.
- 与较低死亡率相关的因素包括单独怀孕和没有从事收入活动的母亲 (2007-2011).
结论:
- 在城市非正式定居点中,五岁以下儿童的死亡率仍然是一个重大问题.
- 有针对性的干预措施,包括疫苗接种和对母亲的社会经济支持,至关重要.
- 需要进一步努力,以减少这些高负担地区的儿童死亡率.
相关概念视频
01:22Applications of Life Tables
50
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...
50
01:22Life Tables
79
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,...
79
01:20Actuarial Approach
63
The actuarial approach, a statistical method originally developed for life insurance risk assessment, is widely used to calculate survival rates in clinical and population studies. This method accounts for participants lost to follow-up or those who die from causes unrelated to the study, ensuring a more accurate representation of survival probabilities.
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
63
01:15Assumptions of Survival Analysis
99
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.
99
01:24Kaplan-Meier Approach
103
The Kaplan-Meier estimator is a non-parametric method used to estimate the survival function from time-to-event data. In medical research, it is frequently employed to measure the proportion of patients surviving for a certain period after treatment. This estimator is fundamental in analyzing time-to-event data, making it indispensable in clinical trials, epidemiological studies, and reliability engineering. By estimating survival probabilities, researchers can evaluate treatment effectiveness,...
103
01:29Life Histories
17.8K
Overview
17.8K