Spatial analysis of the relationship between out-of-pocket expenditure and socioeconomic status in South Korea
Submitted: 25 November 2022
Accepted: 15 March 2023
Published: 25 May 2023
Accepted: 15 March 2023
Abstract Views: 767
PDF: 435
HTML: 21
HTML: 21
Publisher's note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
Similar Articles
- Chunhui Liu, Xiaodi Su, Zhaoxuan Dong, Xingyu Liu, Chunxia Qiu, Understanding COVID-19: comparison of spatio-temporal analysis methods used to study epidemic spread patterns in the United States , Geospatial Health: Vol. 18 No. 1 (2023)
- Lung-Chang Chien, Xiao Li, Amanda Staudt, Physical inactivity displays a mediator role in the association of diabetes and poverty: A spatiotemporal analysis , Geospatial Health: Vol. 12 No. 2 (2017)
- Ciro José Jardim de Figueiredo, Caroline Maria de Miranda Mota, Amanda Gadelha Ferreira Rosa, Arthur Pimentel Gomes de Souza, Simone Maria da Silva Lima, Vulnerability to COVID-19 in Pernambuco, Brazil: A geospatial evaluation supported by multiple-criteria decision aid methodology , Geospatial Health: Vol. 17 No. s1 (2022): Special issue on COVID-19
- I Gede Nyoman Mindra Jaya, Anna Chadidjah, Farah Kristiani, Gumgum Darmawan, Jane Christine Princidy, Does mobility restriction significantly control infectious disease transmission? Accounting for non-stationarity in the impact of COVID-19 based on Bayesian spatially varying coefficient models , Geospatial Health: Vol. 18 No. 1 (2023)
- Marcus Matheus Quadros Santos, Bianca Alessandra Gomes do Carmo, Taymara Barbosa Rodrigues, Bruna Rafaela Leite Dias, Cleyton Abreu Martins, Glenda Roberta Oliveira Naiff Ferreira, Andressa Tavares Parente, Cíntia Yollete Urbano Pauxis Aben-Atha, Sandra Helena Isse Polaro, Eliã Pinheiro Botelho, Spatial variability of mother-to-child human immunodeficiency virus transmission in a province in the Brazilian Rainforest: An ecological study , Geospatial Health: Vol. 17 No. 2 (2022)
- Juan Adrian Wiranata, Herindita Puspitaningtyas, Susanna Hilda Hutajulu, Jajah Fachiroh, Nungki Anggorowati, Guardian Yoki Sanjaya, Lutfan Lazuardi, Patumrat Sripan, Temporal and spatial analyses of colorectal cancer incidence in Yogyakarta, Indonesia: a cross-sectional study , Geospatial Health: Vol. 18 No. 1 (2023)
- Gayani Shashikala Amarasinghe, Thilini Chanchala Agampodi, Vasana Mendis, Suneth Buddhika Agampodi, The geo-spatial perspective of biological, social and environmental determinants of early pregnancy anaemia in rural Sri Lanka: Need for context-specific approaches on prevention , Geospatial Health: Vol. 17 No. 2 (2022)
- Gianluca Boo, Stefan Leyk, Sara Irina Fabrikant, Andreas Pospischil, Ramona Graf, Assessing effects of structural zeros on models of canine cancer incidence: a case study of the Swiss Canine Cancer Registry , Geospatial Health: Vol. 12 No. 1 (2017)
- Benn Sartorius, Kurt Sartorius, How much incident lung cancer was missed globally in 2012? An ecological country-level study , Geospatial Health: Vol. 11 No. 2 (2016)
- Yi Huang, Chen Li, Xianjing Lu, Yue Wang, The geographic environment and the frequency of falling: a study of mortality outcomes in elderly people in China , Geospatial Health: Vol. 18 No. 1 (2023)
You may also start an advanced similarity search for this article.