Role of geographic characteristics in the spatial cluster detection of cancer: Evidence in South Korea, 1999-2013.

BACKGROUND: Identification of high-risk areas of cancer, referred to as spatial clusters, can inform targeted policies for cancer control. Although cancer cluster detection could be affected by various geographic characteristics including sociodemographic and environmental factors which impacts could also vary over time, studies accounting for such influence remain limited. This study aims to assess the role of geographic characteristics in the spatial cluster detection for lung and stomach cancer over an extended period. METHODS: We obtained sex-specific age-standardized incidence and mortality rates of lung and stomach cancer as well as geographic characteristics across 233 districts in South Korea for three five-year periods between 1999 and 2013. We classified geographic characteristics of each district into four categories: demography, socioeconomic status, behaviors, and physical environments. Specifically, we quantified physical environments using measures of greenness, concentrations of particulate matter and nitrogen dioxide, and air pollution emissions. Finally, we conducted cluster detection analyses using weighted normal spatial scan statistics with the residuals from multiple regression analyses performed with the four progressive sets of geographic attributes. RESULTS: We found that the size of clusters reduced as we progressively adjusted for geographic covariates. Among the four categories, physical environments had the greatest impact on the reduction or disappearance of clusters particularly for lung cancer consistently over time. Whereas older population affected a decrease of lung cancer clusters in the early period, the contribution of education was large in the recent period. The impact was less clear in stomach cancer than lung cancer. CONCLUSION: Our findings highlight the importance of geographic characteristics in explaining the existing cancer clusters and identifying new clusters, which jointly provides practical guidance to cancer control.

Primary health care patient satisfaction: Explanatory factors and geographic characteristics.

OBJECTIVE: To determine the factors that explain the levels of patient satisfaction and the role of geographical characteristics. DESIGN: Questionnaires to patients of Primary Health Care (PHC) units in Portugal Mainland distributed to each unit according to their size; codes were distributed to guarantee single responses; the questionnaire was anonymous and confidential. SETTING: Primary Health Care units in Portugal Mainland. PARTICIPANTS: Primary health care patients. INTERVENTION(S): None. MAIN OUTCOME MEASURE(S): Overall patient satisfaction. RESULTS: The main results indicate that the most significant dimension explaining overall patient satisfaction index is the satisfaction regarding general practitioner (GP) care, and the two other most significant explanatory variables of satisfaction are to be enrolled in a GP list and education. The bigger is the size of a PHC unit the lower is satisfaction. In rural areas, the level of satisfaction is higher than in urban areas. Comparing to the Lisbon metropolitan area, all other regions show a higher satisfaction in access dimension. CONCLUSIONS: These results contribute to the creation of strategic information relevant to the evaluation of the various models of Primary Health Care, to the commissioning and definition of health policies.

Analysis of impact of geographic characteristics on suicide rate and visualization of result with Geographic Information System.

AIM: The aim of our study was to understand the geographic characteristics of Japanese communities and the impact of these characteristics on suicide rates. METHODS: We calculated the standardized mortality ratio from suicide statistics of 3318 municipalities from 1972 to 2002. Correlation analysis, multi-regression analysis and generalized additive model were used to find the relation between topographic and climatic variables and suicide rate. We visualized the relation between geographic characteristics and suicide rate on the map of Wakayama Prefecture, using the Geographic Information System. RESULTS: Our study showed that the geographic characteristics of each community are related with its suicide rate. The strongest factor among the geographic characteristics to increase the suicide rate was the slope of the habitable land. CONCLUSIONS: It is necessary to take the characteristics of each community into consideration when we work out measures of suicide prevention. Visualization of the findings on the local map should be helpful to promote understanding of problems and to share the information among various parties in charge of suicide prevention.

Geographic modeling and simulation systems for geographic research in the new era: Some thoughts on their development and construction.

Regionality, comprehensiveness, and complexity are regarded as the basic characteristics of geography. The exploration of their core connotations is an essential way to achieve breakthroughs in geography in the new era. This paper focuses on the important method in geographic research: Geographic modeling and simulation. First, we clarify the research requirements of the said three characteristics of geography and its potential to address geo-problems in the new era. Then, the supporting capabilities of the existing geographic modeling and simulation systems for geographic research are summarized from three perspectives: Model resources, modeling processes, and operational architecture. Finally, we discern avenues for future research of geographic modeling and simulation systems for the study of regional, comprehensive and complex characteristics of geography. Based on these analyses, we propose implementation architecture of geographic modeling and simulation systems and discuss the module composition and functional realization, which could provide theoretical and technical support for geographic modeling and simulation systems to better serve the development of geography in the new era.

Studying Healthcare Affordability during an Economic Recession: The Case of Greece.

The significant deterioration of economic prosperity in Greece during the economic crisis decreased patients' ability to pay. Thus, the objective of this study is to determine the factors affecting healthcare affordability in Greece during an economic recession. This study used data from the European Union Statistics on Income and Living Conditions (EU-SILC) 2016. The sample consisted of 18,255 households. Healthcare affordability was regressed on geographic characteristics as well as several variables that refer to the households' financial condition. Region of residence, ability to make ends meet, and capacity to cope with unexpected financial expenses were found to be statistically significant. Using sample sizes of 1000 and 1096 adults, respectively, the European Quality of Life Surveys (EQLS) of 2007 and 2016 were also used as data sources. Economic crisis was expressed with a dummy variable: (1) 0: 2007, and (2) 1: 2016. Difficulty in responding to healthcare costs was regressed on survey year and several demographic, socioeconomic, and health characteristics, revealing that individuals were more likely to face difficulties in responding to healthcare costs during the economic crisis. These results confirm the mechanism on the basis of which economic crises affect healthcare access: primarily through the effects of demand-side barriers.

The Measles Vaccination Narrative in Twitter: A Quantitative Analysis.

BACKGROUND: The emergence of social media is providing an alternative avenue for information exchange and opinion formation on health-related issues. Collective discourse in such media leads to the formation of a complex narrative, conveying public views and perceptions. OBJECTIVE: This paper presents a study of Twitter narrative regarding vaccination in the aftermath of the 2015 measles outbreak, both in terms of its cyber and physical characteristics. We aimed to contribute to the analysis of the data, as well as presenting a quantitative interdisciplinary approach to analyze such open-source data in the context of health narratives. METHODS: We collected 669,136 tweets referring to vaccination from February 1 to March 9, 2015. These tweets were analyzed to identify key terms, connections among such terms, retweet patterns, the structure of the narrative, and connections to the geographical space. RESULTS: The data analysis captures the anatomy of the themes and relations that make up the discussion about vaccination in Twitter. The results highlight the higher impact of stories contributed by news organizations compared to direct tweets by health organizations in communicating health-related information. They also capture the structure of the antivaccination narrative and its terms of reference. Analysis also revealed the relationship between community engagement in Twitter and state policies regarding child vaccination. Residents of Vermont and Oregon, the two states with the highest rates of non-medical exemption from school-entry vaccines nationwide, are leading the social media discussion in terms of participation. CONCLUSIONS: The interdisciplinary study of health-related debates in social media across the cyber-physical debate nexus leads to a greater understanding of public concerns, views, and responses to health-related issues. Further coalescing such capabilities shows promise towards advancing health communication, thus supporting the design of more effective strategies that take into account the complex and evolving public views of health issues.