Geographical Detectors‐Based Health Risk Assessment and its Application in the Neural Tube Defects Study of the Heshun Region, China

By Jinfeng Wang, Xinhu Li, George Christakos, Y. Liao, Tin Zhang, Xue Gu, Xiaoying Zheng. International Journal of Geographical Information Science, 2010

2,425 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Management, Monitoring, Policy and Law

View Paper: https://www.semanticscholar.org/paper/9c88008893dd6c396ff546b22fce127663c5540e

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

1. Shaojian Wang
2. Ming Zhang
3. Lei Jiang
4. Likang Tian
5. Yaobin Liu
6. Yongfu Li
7. Ping Luo
8. Chao Wu

In Management, Monitoring, Policy and Law

1. Likang Tian
2. Ping Luo
3. Chao Wu
4. Qingyun Du
5. Hualou Long
6. Xinyue Ye
7. Ming Zhang

Citations in the corpus

• Quantifying the spatial heterogeneity influences of natural and socioeconomic factors and their interactions on air pollution using the geographical detector method: A case study of the Yangtze River Economic Belt, China (2019, positive): “The method was originally used to detect disease risk area (Wang et al., 2010).”
• Spatial distribution characteristics and optimized reconstruction analysis of China’s rural settlements during the process of rapid urbanization (2016, methodology): “The model used is as follows (Wang et al., 2010; Yang et al., 2013a, 2013b): PD;U ¼ 1 1 ns2U Xm i¼1 nD;is 2 UD;i ; (5) where PD,U is the power determinant of each influencing factor in a rural settlements distribution, nD,i is the number of sub-regional samples, n is the number of samples in the…”
• Spatial effects of accessibility to parks on housing prices in Shenzhen, China (2017, methodology): “The GD is a spatial statistical method that can be used to analyse the effects of geographical spatial factors on human health (Wang et al., 2010), land use (Liang & Yang, 2016), and socioeconomics (Yansui & Ren, 2012).”
• Measuring urban sprawl and exploring the role planning plays: A shanghai case study (2017, positive): “Then, we adopt geographical detectors proposed by Wang et al. (2010) based on spatial variation analysis of the geographical strata to assess the impact of planning on urban sprawl.”
• Identifying the determinants of housing prices in China using spatial regression and the geographical detector technique (2017, methodology): “The presence of several significant determinants in relation to housing price necessitated the use of the geographical detector technique, a method proposed by Wang et al. (2010) which has been widely used in analyzing the effects of underlying factors on local disease risk.”
• Using the geographical detector technique to explore the impact of socioeconomic factors on PM2.5 concentrations in China (2019, methodology): “Proposed by Wang et al (2010), the basic idea of GDM is that, if the values of two variables tend to share the similar spatial distribution, these two variables are spatially correlated.”
• Statistical Modeling of Spatially Stratified Heterogeneous Data (2022, background): “We summarize findings from a pilot project investigating the factors associated with the geographical distribution of cases of Neural Tube Defects (NTD) in Heshun County, Shanxi Province (Wang et al. 2010b), which is an area with one of the highest NTD incidence rates in China.”