在泰国COVID-19大流行期间估计过度死亡率的性别差异
Wiraporn Pothisiri1, Orawan Prasitsiriphon2, Jutarat Apakupakul3
1College of Population Studies, Chulalongkorn University, Bangkok, Thailand.
BMC public health
|October 2, 2023
概括
在COVID-19大流行期间,泰国存在过度死亡率的性别不平等. 分析显示,不同年龄组和地区的性别差距不同,特别是在老年人和曼谷.
科学领域:
- 流行病学 流行病学
- 公共卫生 公共卫生
- 人口统计学 人口统计学
背景情况:
- 在COVID-19大流行期间,性别不平等导致过度死亡的研究有限.
- 这项研究通过分析泰国过度全因死亡率的性别差异来解决这一差距.
研究的目的:
- 在COVID-19大流行期间,分析泰国超过全因死亡率的性别不平等模式.
- 检查这些年龄段和地理位置之间的差异的变化.
主要方法:
- 利用泰国 (2010-2021) 所有原因死亡和人口的数据.
- 采用季节性自回归集成移动平均 (SARIMA) 模型来估计过度死亡率 (2020-2021年).
- 使用年龄标准化率测量性别差异过度死亡率.
主要成果:
- 泰国估计所有原因的过度死亡率为1,032,921人,COVID-19的死亡人数是官方数据的1.64倍.
- 观察到波动的过度死亡率模式,显著的性别差异在2020年4月 (女性) 和2021年8月 (男性) 达到顶峰.
- 80岁以上的年龄组显示出最大的性别差距;曼谷在第四波峰值期间经历了最高的差异.
结论:
- 证实了在泰国流行病期间,跨年龄组和地区的过度死亡率存在性别不平等.
- 强调需要更多地关注死亡率中的性别差异.
- 呼吁采取有针对性的干预措施,以解决已确定的基于性别的死亡率不平等问题.
更多相关视频
相关概念视频
Bias in Epidemiological Studies
339
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:
339
Parametric Survival Analysis: Weibull and Exponential Methods
468
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...
468
Comparing the Survival Analysis of Two or More Groups
218
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...
218
Panic Disorder
129
Panic disorder is an anxiety disorder characterized by recurrent and sudden minutes-long episodes of intense fear, known as panic attacks. These attacks may feel like heart attacks and often happen without warning or a specific cause. They can include symptoms such as rapid heart rate, shortness of breath, chest pain, trembling, sweating, dizziness, and a sense of helplessness. During a panic attack, individuals may feel as though they are experiencing a heart attack or are in a...
129
Relative Risk
208
Relative risk (RR) is a statistical measure commonly used in epidemiology to compare the likelihood of a particular event occurring between two groups. This metric is important for evaluating the relationship between exposure to a specific risk factor and the probability of a particular outcome. It plays a crucial role in medical research, public health studies, and risk assessment. Relative risk quantifies how much more (or less) likely an event is to occur in an exposed group compared to an...
208
Truncation in Survival Analysis
233
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...
233


