Influencing Indicators and Spatial Variation of Diabetes Mellitus Prevalence in Shandong, China: A Framework for Using Data‐Driven and Spatial Methods-Reference-Cited by-同舟云学术

Influencing Indicators and Spatial Variation of Diabetes Mellitus Prevalence in Shandong, China: A Framework for Using Data‐Driven and Spatial Methods

Published:2021-03 Issue:3 Volume:5 Page:
ISSN:2471-1403
Container-title:GeoHealth
language:en
Short-container-title:Geohealth

Author:

Li Yizhuo¹,Fei Teng¹^ORCID,Wang Jian²,Nicholas Stephen³⁴⁵,Li Jun¹,Xu Lizheng⁶,Huang Yanran⁶,Li Hanqi¹

Affiliation:

1. School of Resource and Environmental Sciences Wuhan University Wuhan China

2. Research Center of Health Economics and Management Dong Fureng Institute of Economic and Social Development Wuhan University Beijing China

3. Top Education Institute Sydney NSW Australia

4. Newcastle Business School University of Newcastle Newcastle NSW Australia

5. School of Management and School of Economics Tianjin Normal University Tianjin China

6. School of Public Health Center for Health Economics Experiment and Public Policy Shandong University Key Laboratory of Health Economics and Policy Research NHFPC (Shandong University) Jinan China

Publisher

American Geophysical Union (AGU)

Subject

Health, Toxicology and Mutagenesis,Management, Monitoring, Policy and Law,Public Health, Environmental and Occupational Health,Pollution,Waste Management and Disposal,Water Science and Technology,Epidemiology,Global and Planetary Change

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1029/2020GH000320

Reference74 articles.

1. What accounts for ‘England's green and pleasant land’? A panel data analysis of mental health and land cover types in rural England

2. Partitioning the variation among spatial, temporal and environmental components in a multivariate data set

3. Local Indicators of Spatial Association-LISA

4. Socioeconomic Position and Health among Persons with Diabetes Mellitus: A Conceptual Framework and Review of the Literature

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