Scholarlink

Background <p>The cross-regional floating population in China has brought new challenges for tuberculosis prevention and control. Tuberculosis health Education for the floating population can significantly enhance their health awareness and reduce the prevalence of the disease. However, the current status of health education for the floating population is not adequately assessed, highlighting the urgent need to identify the key factors that restrict effective health education and to safeguard the health rights and interests of this group.</p> Methods <p>This study utilized the data of China’s migrant population from 2014 to 2017, combined with the China Statistical Yearbook and meteorological data, and conducted literature searches and collected relevant information on tuberculosis health education through databases such as Web of Science and PubMed. It identified the key factors influencing tuberculosis health education from four dimensions: social economy, population, health resources, and meteorological environment. Furthermore, the study also explored the relationships between these indicators and tuberculosis health education at the provincial and urban regional levels respectively. A spatial lag fixed effect model was determined to be the most appropriate analysis model based on Schwarz’s Bayesian Information Criterion and Akaike’s Information Criterion.</p> Results <p>The results indicated that at the provincial level a positive correlation between the proportion of the urban population and tuberculosis health education. Conversely, the medical doctors (per 1000 population) negatively correlated with local tuberculosis health education. Additionally, average annual temperature, precipitation, and SO<sub>2</sub> emissions showed positive correlations with tuberculosis health education. At the city level, the results were not statistically significant.</p> Conclusions <p>The health education regarding tuberculosis among China’s floating population demonstrates significant spatial clustering from 2014 to 2017. Key determinants identified include economic factors, healthcare resources, and environmental influences, which contribute not only at a local level but also through notable spatial spillover effects. It is essential to adopt targeted public health strategies to enhance interregional collaboration and optimize resource allocation for equitable tuberculosis control.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Spatial spillover effects and regional differences of tuberculosis health education levels among China’s floating population: a spatial lag model study (2014–2017)

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月25日

查看全文
  • YaJie Feng,
  • Lihan Zhang,
  • Junping Liu,
  • Weijian Song,
  • Juan Guan,
  • Yunkai Li,
  • Wei Liu,
  • Yanfu Wang,
  • Libo Liang

摘要

Background

The cross-regional floating population in China has brought new challenges for tuberculosis prevention and control. Tuberculosis health Education for the floating population can significantly enhance their health awareness and reduce the prevalence of the disease. However, the current status of health education for the floating population is not adequately assessed, highlighting the urgent need to identify the key factors that restrict effective health education and to safeguard the health rights and interests of this group.

Methods

This study utilized the data of China’s migrant population from 2014 to 2017, combined with the China Statistical Yearbook and meteorological data, and conducted literature searches and collected relevant information on tuberculosis health education through databases such as Web of Science and PubMed. It identified the key factors influencing tuberculosis health education from four dimensions: social economy, population, health resources, and meteorological environment. Furthermore, the study also explored the relationships between these indicators and tuberculosis health education at the provincial and urban regional levels respectively. A spatial lag fixed effect model was determined to be the most appropriate analysis model based on Schwarz’s Bayesian Information Criterion and Akaike’s Information Criterion.

Results

The results indicated that at the provincial level a positive correlation between the proportion of the urban population and tuberculosis health education. Conversely, the medical doctors (per 1000 population) negatively correlated with local tuberculosis health education. Additionally, average annual temperature, precipitation, and SO2 emissions showed positive correlations with tuberculosis health education. At the city level, the results were not statistically significant.

Conclusions

The health education regarding tuberculosis among China’s floating population demonstrates significant spatial clustering from 2014 to 2017. Key determinants identified include economic factors, healthcare resources, and environmental influences, which contribute not only at a local level but also through notable spatial spillover effects. It is essential to adopt targeted public health strategies to enhance interregional collaboration and optimize resource allocation for equitable tuberculosis control.