弥合差距:加拿大和美国免疫计划的混合方法分析,以提高儿童疫苗接种中的种族平等
Frances R Gellert1, Carmen Gonzalez2, Ali H Mokdad3
1Population Health Initiative, University of Washington, Seattle, Washington, United States.
Vaccine
|May 14, 2025
概括
儿童免疫接种的种族差异在加拿大和美国仍然存在. 解决这些问题需要社区参与和战略,以克服疫苗公平的系统和个人障碍.
科学领域:
- 公共卫生 公共卫生
- 健康 公平 卫生 公平
- 免疫接种实践 免疫接种实践
背景情况:
- 儿童免疫接种的种族差异是一个重大的公共卫生问题.
- 以前的美国研究突出了不平等现象,需要进行跨背景的比较.
- 了解这些差异对于加强公共卫生实践和促进公平至关重要.
研究的目的:
- 为了比较过去十年来加拿大和美国在儿童免疫接种方面的种族差异.
- 确定有弹性,跨背景的干预措施,以促进疫苗接种中的种族平等.
- 通过分析加拿大和美国免疫环境的相似之处和差异来加强公共卫生实践.
主要方法:
- 采用了比较混合方法方法,分析了加拿大三个人口最多的省份的数据.
- 量化方法包括对疫苗覆盖率数据的审查,对人口统计和免疫率的生态分析.
- 定性方法包括对各个行业的33个关键告密者进行采访.
主要成果:
- 在监测种族差异方面存在挑战,因为种族和种族分类数据有限.
- 加拿大的儿童疫苗接种率低于美国,黑人和土著儿童的疫苗接种率最低.
- 障碍包括:有限的医疗保健准入,健康的社会决定因素,不信任和分散的系统;有效的干预侧重于建立信任和社区参与.
结论:
- 儿童疫苗接种范围的种族不平等在加拿大和美国都存在.
- 解决这些差异需要策略,让社区参与并促进机构.
- 必须解决疫苗接种的系统和个体障碍,以实现公平的免疫率.
相关概念视频
01:25Statistical Methods for Analyzing Epidemiological Data
244
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:
244
01:25Strategies for Assessing and Addressing Confounding
70
Confounding is a critical issue in epidemiological studies, often leading to misleading conclusions about associations between exposures and outcomes. It occurs when the relationship between the exposure and the outcome is mixed with the effects of other factors that influence the outcome. Given that, addressing confounding is of high importance for drawing accurate inferences in research.
Confounding can be addressed at both the design phase of a study and through analytical methods after data...
Confounding can be addressed at both the design phase of a study and through analytical methods after data...
70
01:13Randomized Experiments
6.6K
The randomization process involves assigning study participants randomly to experimental or control groups based on their probability of being equally assigned. Randomization is meant to eliminate selection bias and balance known and unknown confounding factors so that the control group is similar to the treatment group as much as possible. A computer program and a random number generator can be used to assign participants to groups in a way that minimizes bias.
Simple randomization
Simple...
Simple randomization
Simple...
6.6K
01:51Vaccinations
43.1K
Overview
43.1K
01:16Stratified Sampling Method
11.7K
Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a stratified sample, divide the population into groups called strata and then take a...
To choose a stratified sample, divide the population into groups called strata and then take a...
11.7K
01:23Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
106
Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
106