季节性死亡率及其对意大利寿命空间不平等的影响
Isabella Marinetti1,2, Dmitri A Jdanov3, Domantas Jasilionis3,4,5
1Max Planck Institute for Demographic Research, Rostock, Germany. marinetti@demogr.mpg.de.
European journal of population = Revue europeenne de demographie
|October 30, 2025
概括
季节性死亡率显著影响意大利的预期寿命 (e0) 和地区差异. 消除过度的季节性死亡可能会使空间不平等减少11.2%,特别是在南部地区.
科学领域:
- 人口统计学 人口统计学
- 公共卫生 公共卫生
- 流行病学 流行病学
背景情况:
- 季节性死亡率波动影响国家预期寿命,但它们在区域不平等中的作用未得到充分研究.
- 了解这些空间差异对于制定有针对性的卫生政策来减少死亡率差异至关重要.
研究的目的:
- 量化季节性过度死亡率对意大利地区预期寿命 (e0) 和不平等水平的影响.
- 分析区域对这些不平等的贡献,并确定受影响最严重的地区.
主要方法:
- 利用来自意大利国家统计局 (2005-2019) 的每月死亡数据,按性别和年龄分别分布在20个地区.
- 通过将观察到的e0与最低可实现水平进行比较,评估了季节性损失.
- 量化季节性对e0不平等的影响,通过比较带有和没有过度季节性死亡率的标准偏差,使用分解分析.
主要成果:
- 季节性过度死亡率导致意大利各地区的平均生命损失为1.4年.
- 影响在南部和岛屿地区 (坎帕尼亚,西西里) 最为明显,特别是由于冬季死亡率.
- 消除过度的季节性死亡率可以将e0的空间不平等减少11.2%,过度的冬季死亡率占 -7.5%.
结论:
- 季节性过度死亡率对意大利预期寿命的区域不平等有很大影响.
- 坎帕尼亚和西西里等南部地区显示出最大的脆弱性和对空间死亡率变化的贡献.
- 针对季节性死亡,特别是冬季死亡的有针对性的干预措施对于减少区域健康差异至关重要.
相关概念视频
01:22Applications of Life Tables
321
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...
321
01:29Bias in Epidemiological Studies
1.3K
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:
1.3K
01:22Life Tables
488
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,...
488
01:20Actuarial Approach
283
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,...
283
01:21Causality in Epidemiology
1.5K
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...
1.5K
00:57Population Growth
27.8K
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.
27.8K