泰国地区级社会经济贫困指数的发展:基于人口普查的方法论研究
Witchakorn Ruamtawee1, Mathuros Tipayamongkholgul2, Kanitta Bundhamcharoen3
1Faculty of Medicine Vajira Hospital, Navamindradhiraj University, Bangkok, Thailand.
Health research policy and systems
|January 17, 2026
概括
泰国地区级社会经济贫困指数 (TSDI) 通过人口普查数据确定贫困地区. 这种经过验证的工具有助于针对公共卫生干预措施,了解社会不平等的影响.
科学领域:
- 公共卫生 公共卫生
- 健康的社会经济决定因素
- 地理空间分析是什么
背景情况:
- 区域一级的社会经济贫困严重影响健康差异和生活质量.
- 识别贫困地区对于公平的资源分配和公共卫生倡议至关重要.
- 现有的措施可能无法捕捉到泰国细微的地区级社会经济格局.
研究的目的:
- 开发和验证泰国地区级社会经济贫困指数 (TSDI).
- 使用全国人口普查数据创建全国范围的地区级索引.
- 确定泰国各个地区社会经济贫困的具体层面.
主要方法:
- 一项方法性的横截面研究,利用2010年泰国全国人口普查 (遍布928个地区的6300多万个人) 的20%分层随机样本.
- 根据范围审查和相对贫困理论框架,选择贫困领域和指标.
- 主要组件分析 (PCA) 的应用,用于构建一个复合索引,可通过合乐谱映射可视化.
主要成果:
- 该TSDI包括6个主要组成部分 (解释73.82%的差异),来自29个指标,代表整体贫困,住房,人口,劳动力,拥挤和供水.
- 空间分析确定了北方,东北下部和南部地区严重贫困的重要集群.
- 中部 (包括曼谷) 和东部沿海地区的贫困程度较低.
结论:
- 泰国社会经济贫困指数 (TSDI) 是一种新的,经过验证的工具,它提供了一个全面的,空间显式的泰国社会经济贫困的衡量标准.
- 该指数为有针对性的公共卫生干预和明智的资源分配提供了关键数据.
- TSDI促进了研究将社会不平等与健康和发展结果联系在一起的途径.
相关概念视频
Ordinal Level of Measurement
32.0K
The way a set of data is measured is called its level of measurement. Correct statistical procedures depend on a researcher being familiar with levels of measurement. For analysis, data are classified into four levels of measurement—nominal, ordinal, interval, and ratio.
Data measured using an ordinal scale are similar to nominal scale data, but there is one major difference. The ordinal scale data can be ordered. An example of ordinal scale data is a list of the top five national parks...
Data measured using an ordinal scale are similar to nominal scale data, but there is one major difference. The ordinal scale data can be ordered. An example of ordinal scale data is a list of the top five national parks...
32.0K
Statistical Methods for Analyzing Epidemiological Data
900
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:
900
Cross-Sectional Research
12.4K
In cross-sectional research, a researcher compares multiple segments of the population at the same time. If they were interested in people's dietary habits, the researcher might directly compare different groups of people by age. Instead of following a group of people for 20 years to see how their dietary habits changed from decade to decade, the researcher would study a group of 20-year-old individuals and compare them to a group of 30-year-old individuals and a group of 40-year-old...
12.4K
Stratified Sampling Method
14.5K
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...
14.5K
Thematic Layering in GIS
335
In the past, planning projects such as schools or public facilities required extensive manual effort to gather and compile data. Information such as property boundaries, soil characteristics, road networks, zoning regulations, and flood zones had to be sourced individually from courthouses, utility providers, and registry offices. Assembling these datasets into a coherent format often took several months, delaying project timelines.The introduction of Geographic Information Systems (GIS)...
335
Levels of Use of a GIS
367
Geographic Information Systems (GIS) operate across three levels of application, each representing an increasing degree of complexity: data management, analysis, and prediction. These levels reflect the expanding functionality and versatility of GIS technology in handling spatial data for diverse purposes.Data ManagementAt its foundational level, GIS serves as a tool for data management, enabling the input, storage, retrieval, and organization of spatial data. This level is often employed in...
367

