ArticleInternational journal of public health2015
Deprivation and suicide mortality across 424 neighborhoods in Seoul, South Korea: a Bayesian spatial analysis.
Article in International journal of public health, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
19 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The application of spatial analysis to understanding the association between area-level socio-economic factors and suicide: a systematic review.Social psychiatry and psychiatric epidemiology · 2023Pooled it
- A Moderated Mediation Analysis of Timely EMS Activation and Bystander CPR in the Association Between Regional Deprivation and Outcomes Following Out-of-Hospital Cardiac Arrest.Healthcare (Basel, Switzerland) · 2026Article
- Neighborhood Deprivation and Suicide Among Adolescent and Young Adult Cancer Patients.Cancer medicine · 2025Article
- Article
- The Spatio-Temporal Distribution of Suicide-related Emergency Calls in a European City: Age and Gender Patterns, and Neighborhood Influences.Psychosocial intervention · 2024Article
- Article
- The relative importance of macro versus micro geographical scale in explaining suicide variation in Seoul, South Korea 2014-2016.PloS one · 2022Article
- Spatial distribution of neighborhood-level housing prices and its association with all-cause mortality in Seoul, Korea (2013-2018): A spatial panel data analysis.SSM - population health · 2021Article
- Socially-isolated neighborhoods and the risk of all-cause mortality among nursing home residents in the United States: A multilevel study.Preventive medicine reports · 2021Article
- Life Expectancy in Areas around Subway Stations in the Seoul Metropolitan Area in Korea, 2008-2017.Journal of Korean medical science · 2020Article
- Use of the National Health Information Database for Estimating Town-Level Mortality in Korea: Comparison with the National Administrative Data, 2014-2017.Journal of Korean medical science · 2019Article
- Suicidal thoughts in low-income adolescents: a longitudinal analysis.International journal of public health · 2019Article
- What calls for service tell us about suicide: A 7-year spatio-temporal analysis of neighborhood correlates of suicide-related calls.Scientific reports · 2018Article
- Income-related inequality in completed suicide across the provinces of Iran.Epidemiology and health · 2018Article
- Comparison of Baseline Characteristics between Community-based and Hospital-based Suicidal Ideators and Its Implications for Tailoring Strategies for Suicide Prevention: Korean Cohort for the Model Predicting a Suicide and Suicide-related Behavior.Journal of Korean medical science · 2017Article
- Spatiotemporal Suicide Risk in Germany: A Longitudinal Study 2007-11.Scientific reports · 2017Article
- Spatio-Temporal Analysis of Suicide-Related Emergency Calls.International journal of environmental research and public health · 2017Article
- Income Differences in Smoking Prevalences in 245 Districts of South Korea: Patterns by Area Deprivation and Urbanity, 2008-2014.Journal of preventive medicine and public health = Yebang Uihakhoe chi · 2017Article
- Suicide mortality among youth in southern Brazil: a spatiotemporal evaluation of socioeconomic vulnerability.Revista brasileira de psiquiatria (Sao Paulo, Brazil : 1999)Observational
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesA neighborhood-level analysis of mortality from suicide would be informative in developing targeted approaches to reducing suicide. This study aims to examine the association of community characteristics with suicide in the 424 neighborhoods of Seoul, South Korea.
methodsNeighborhood-level mortality and population data (2005-2011) were obtained to calculate age-standardized suicide rates. Eight community characteristics and their associated deprivation index were employed as determinants of suicide rates. The Bayesian hierarchical model with mixed effects for neighborhoods was used to fit age-standardized suicide rates and other covariates with consideration of spatial correlations.
resultsSuicide rates for 424 neighborhoods were between 7.32 and 71.09 per 100,000. Ninety-nine percent of 424 neighborhoods recorded greater suicide rates than the Organization for Economic Cooperation and Development member countries' average. A stepwise relationship between area deprivation and suicide was found. Neighborhood-level indicators for lack of social support (residents living alone and the divorced or separated) and socioeconomic disadvantages (low educational attainment) were positively associated with suicide mortality after controlling for other covariates.
conclusionsFinding from this study could be used to identify priority areas and to develop community-based programs for preventing suicide in Seoul, South Korea.
Indexed as
Identifiers
26022192What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.