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  Identifying counties vulnerable to diabetes from obesity prevalence in the United States: a spatiotemporal analysis

  Xiao Li, Amanda Staudt, Lung-Chang Chien

  21-11-2016

  https://doi.org/10.4081/gh.2016.439

  2875

  PDF: 1382

  APPENDIX: 502

  HTML: 1189
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  Diabetes prevalence in the state of Alabama: identifying the risk factors

  Kwaku Karikari Manu, Seth Appiah-Opoku

  31-03-2026

  https://doi.org/10.4081/gh.2026.1465

  715

  PDF: 251

  HTML: 11
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  Physical inactivity displays a mediator role in the association of diabetes and poverty: A spatiotemporal analysis

  Lung-Chang Chien, Xiao Li, Amanda Staudt

  03-11-2017

  https://doi.org/10.4081/gh.2017.528

  3040

  PDF: 1081

  HTML: 808

• Geospatial determinants of diabetes risk in Thailand: socioeconomic and health service factors

  Withaya Polnakoo, Wongsa Laohasiriwong, Kittipong Sornlorm

  01-07-2026

  https://doi.org/10.4081/gh.2026.1440

  174

  PDF: 70

  HTML: 3
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  Impact of walkability with regard to physical activity in the prevention of diabetes

  Carlos Mena, César Sepúlveda, Yony Ormazábal, Eduardo Fuentes, Iván Palomo

  03-11-2017

  https://doi.org/10.4081/gh.2017.595

  3856

  PDF: 1300

  HTML: 1091
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  Modelling geographical heterogeneity of diabetes prevalence and socio-economic and built environment determinants in Saudi City - Jeddah

  Abdulkader Murad, Fazlay Faruque, Ammar Naji, Alok Tiwari, Mansour Helmi, Ammar Dahlan

  16-05-2022

  https://doi.org/10.4081/gh.2022.1072

  2271

  PDF: 1113

  HTML: 166
• 

  Socio-spatial vulnerability index of type 2 diabetes mellitus in Mexico in 2020

  Enríque Ibarra-Zapata, Darío Gaytán-Hernández, Yolanda Terán-Figueroa, Verónica Gallegos-García, Carmen del Pilar Suárez-Rodríguez, Sergio Zarazúa Guzmán, Omar Parra Rodríguez

  27-01-2025

  https://doi.org/10.4081/gh.2025.1348

  4695

  PDF: 1661

  HTML: 276
• 

  Spatial association of socio-demographic, environmental factors and prevalence of diabetes mellitus in middle-aged and elderly people in Thailand

  Suparat Tappo, Wongsa Laohasiriwong, Nattapong Puttanapong

  29-11-2022

  https://doi.org/10.4081/gh.2022.1091

  2094

  PDF: 1202

  Appendix: 179

  HTML: 227
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  Spatiotemporal patterns of mortality associated with chronic non-communicable diseases and child malnutrition at the municipal level in Mexico

  José Mauricio Galeana-Pizaña, Leslie Verdeja-Vendrell, Lizbeth Ixchel Díaz-Trejo, Carlos Anzaldo, Daniela Figueroa, Aldo Daniel Jiménez-Ortega

  17-05-2022

  https://doi.org/10.4081/gh.2022.1087

  1855

  PDF: 1074

  Appendix: 209

  HTML: 77
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  A geospatial analysis of cardiometabolic diseases and their risk factors considering environmental features in a midsized city in Argentina

  Micaela Natalia Campero, Carlos Matías Scavuzzo, Veronica Andreo, María Sol Mileo, Micaela Belén Franzois, María Georgina Oberto, Carla Gonzalez Rodriguez, María Daniela Defagó

  23-10-2023

  https://doi.org/10.4081/gh.2023.1212

  1964

  PDF: 974

  HTML: 29
• 

  Spatiotemporal heterogeneity of SARS-CoV-2 diffusion at the city level using geographically weighted Poisson regression model: The case of Bologna, Italy

  Addisu Jember Zeleke, Rossella Miglio, Pierpaolo Palumbo, Paolo Tubertini, Lorenzo Chiari, Bologna MODELS4COVID Study Group of the University of Bologna and the National Institute for Nuclear Physics (INFN)

  01-12-2022

  https://doi.org/10.4081/gh.2022.1145

  1873

  PDF: 1005

  Appendix: 158

  HTML: 84
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  Spatial Bayesian semi-parametric Cox-Leroux modelling of stroke patient hospitalization: aspects on survival

  Aswi Aswi, Bobby Poerwanto, Nurussyariah Hammado, Nurwan Nurwan, Oktaviana Oktaviana, Siti Djawijah, Susanna Cramb

  21-07-2025

  https://doi.org/10.4081/gh.2025.1380

  1038

  PDF: 454

  HTML: 44

• Healthcare-seeking behavior and spatial variation of internal migrants with chronic diseases: a nationwide empirical study in China

  Dan Li, Dawei Gao, Masaaki Yamada, Chuangbin Chen, Liuchun Xiang, Haisong Nie

  28-05-2024

  https://doi.org/10.4081/gh.2024.1255

  3039

  PDF: 832

  HTML: 110
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  Comparison of complete and spatial sampling frames for estimation of the prevalence of hypertension and diabetes mellitus

  Vasna Joshua, Kamaraj Pattabi, Yuvaraj Jeyaraman, Prabhdeep Kaur, Tarun Bhatnagar, Suresh Arunachalam, Sabarinathan Ramasamy, Venkateshprabhu Janagaraj, Manoj V Murhekar

  30-11-2022

  https://doi.org/10.4081/gh.2022.1097

  2469

  PDF: 1000

  HTML: 130

• Spatial associations between chronic kidney disease and socio-economic factors in Thailand

  Juree Sansuk, Kittipong Sornlorm

  30-01-2024

  https://doi.org/10.4081/gh.2024.1246

  6601

  PDF: 1168

  HTML: 1145
• 

  Spatial analysis for the epidemiological study of cardiovascular diseases: A systematic literature search

  Carlos Mena, Cesar Sepúlveda, Eduardo Fuentes, Yony Ormazábal, Iván Palomo

  07-05-2018

  https://doi.org/10.4081/gh.2018.587

  5632

  PDF: 2786

  HTML: 815
• 

  Smartphone-assisted spatial data collection improves geographic information quality: pilot study using a birth records dataset

  Xiaohui Xu, Hui Hu, Sandie Ha, Daikwon Han

  23-11-2016

  https://doi.org/10.4081/gh.2016.482

  2995

  PDF: 1117

  HTML: 819

• Geospatial epidemiology of coronary artery disease treated with percutaneous coronary intervention in Crete, Greece

  Evangelos Melidoniotis, Kleomenis Kalogeropoulos, Andreas Tsatsaris, Michail Zografakis-Sfakianakis, George Lazopoulos, Nikolaos Tzanakis, Ioannis Anastasiou, Emmanouil Skalidis

  16-05-2024

  https://doi.org/10.4081/gh.2024.1251

  2600

  PDF: 764

  HTML: 62

• Spatial pattern analysis of the impact of community food environments on foetal macrosomia, preterm births and low birth weight

  Micaela Natalia Campero, Carlos Matías Scavuzzo, Carlos Marcelo Scavuzzo, María Dolores Román

  07-05-2024

  https://doi.org/10.4081/gh.2024.1249

  1289

  PDF: 802

  Supplementary Materials: 175

  HTML: 72
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  Effects of geographical factors on reference values of the thyroid stimulating hormone in healthy adults in China and its clinical significance

  Xinrui Pang, Miao Ge, Congxia Wang, Jinwei He

  06-05-2022

  https://doi.org/10.4081/gh.2022.1030

  1345

  PDF: 687

  HTML: 303
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  Understanding the spatial non-stationarity in the relationships between malaria incidence and environmental risk factors using Geographically Weighted Random Forest: A case study in Rwanda

  Gilbert Nduwayezu, Pengxiang Zhao, Clarisse Kagoyire, Lina Eklund, Jean Pierre Bizimana, Petter Pilesjo, Ali Mansourian

  25-05-2023

  https://doi.org/10.4081/gh.2023.1184

  3465

  PDF: 1793

  HTML: 218
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  The geographic environment and the frequency of falling: a study of mortality outcomes in elderly people in China

  Yi Huang, Chen Li, Xianjing Lu, Yue Wang

  25-05-2023

  https://doi.org/10.4081/gh.2023.1180

  1107

  PDF: 652

  HTML: 20
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  Risk areas for hepatitis A, B and C in the municipality of Maringá, Paraná State, Brazil 2007-2010

  Valéria Miranda Avanzi, Udelysses Janete Veltrini Fonzar, Eraldo Schunk Silva, Jorge Juarez Vieira Teixeira, Dennis Armando Bertolini

  08-05-2018

  https://doi.org/10.4081/gh.2018.607

  2078

  PDF: 872

  HTML: 154