在41个亚洲国家的新生儿,婴儿和5岁以下儿童死亡率 (2000-2022) 的贝叶斯空间时间建模:一个人口级观测研究
Siddikur Rahman1, Abu Bokkor Shiddik2
1Department of Statistics, Begum Rokeya University, Rangpur, Bangladesh siddikur@brur.ac.bd.
BMJ open
|February 26, 2026
概括
由于疫苗接种覆盖率增加和女性识字率提高,亚洲的儿童死亡率显著下降. 有针对性的新生儿干预对于进一步进步和实现可持续发展目标3.2至关重要.
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:
- 儿童死亡率仍然是亚洲的一个重大公共卫生问题.
- 这项研究分析了该地区5岁以下,婴儿和新生儿死亡率的趋势和决定因素.
研究的目的:
- 检查亚洲儿童死亡率的时空趋势.
- 确定关键决定因素,空间风险模式,并预测到2030年的死亡率.
主要方法:
- 利用来自41个亚洲国家 (2000-2022) 的26个指标的国家数据.
- 采用一个等级化的贝叶斯空间时间模型与集成嵌套拉普拉斯近似.
- 使用DIC,WAIC,R2,RMSE和MAE等标准指标评估模型性能.
主要成果:
- 年龄在5岁以下的死亡率从每1000个活产婴儿的46.73下降到18.53.
- 在儿童死亡率和疫苗接种覆盖率 (红疹,DTP,HepB,轮状病毒),女性识字率和预期寿命之间发现了强烈的负相关性.
- 确定阿富汗,孟加拉国和缅甸是5岁以下死亡率高风险的热点;新生儿死亡率在孟加拉国,印度尼西亚和阿塞拜疆达到顶峰.
结论:
- 免疫接种和母亲教育对于降低儿童死亡率至关重要.
- 有针对性的新生儿干预措施是必要的,以提高儿童存活率.
- 白盒建模方法支持数据驱动的政策,以实现公平的儿童生存率,与可持续发展目标3.2保持一致.
相关概念视频
Statistical Methods for Analyzing Epidemiological Data
1.1K
Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
1.1K
Causality in Epidemiology
1.8K
Causality or causation is a fundamental concept in epidemiology, vital for understanding the relationships between various factors and health outcomes. Despite its importance, there's no single, universally accepted definition of causality within the discipline. Drawing from a systematic review, causality in epidemiology encompasses several definitions, including production, necessary and sufficient, sufficient-component, counterfactual, and probabilistic models. Each has its strengths and...
1.8K
Population Growth
29.0K
Population size is dynamic, increasing with birth rates and immigration, and decreasing with death rates and emigration. In ideal conditions with unlimited resources, populations can increase exponentially, which plots as a J-shaped growth rate curve of population size against time. This type of curve is characteristic of newly-introduced invasive species, or populations that have suffered catastrophic declines and are rebounding.
29.0K
Bias in Epidemiological Studies
1.4K
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:
1.4K
Applications of Life Tables
390
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...
390
Steps in Outbreak Investigation
644
In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
644


