1
|
Yeung CY, Men VY, Guo Y, Yip PSF. Spatial-temporal analysis of suicide clusters for suicide prevention in Hong Kong: a territory-wide study using 2014-2018 Hong Kong Coroner's Court reports. THE LANCET REGIONAL HEALTH. WESTERN PACIFIC 2023; 39:100820. [PMID: 37927995 PMCID: PMC10625019 DOI: 10.1016/j.lanwpc.2023.100820] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Revised: 05/07/2023] [Accepted: 05/25/2023] [Indexed: 11/07/2023]
Abstract
Background This study aimed to (i) identify high-risk suicide-methods clusters, based on location of residence and suicide incidence; and (ii) compare the characteristics of cases and spatial units inside and outside clusters. Methods Suicide data of 4672 cases was obtained from the Coroner's Court reports in Hong Kong (2014-2018). Monthly aggregated suicide numbers based on location of residence, and suicide incidence, were obtained in small tertiary planning units (STPUs). Community-level characteristics and population of STPUs were retrieved from 2016 Census. Retrospective space-time analyses were performed to identify locations with elevated suicide rates over specific time periods, i.e., spatial-temporal clusters. Clusters were evaluated for overall suicide (any method), as well as jumping, hanging, and charcoal burning methods, in location of residence and suicide incidence. Bi-variate analysis was performed to compare the characteristics of cases, and spatial units, inside and outside the clusters. Findings Suicide clusters involving jumping and charcoal burning were identified, but no hanging clusters were found. The within-cluster distribution of types of housing was different from that of outside. For most of the overall suicide and suicide by jumping clusters, spatial units within the clusters were more socially disadvantaged compared to those outside. Interpretation Clusters varied by suicide methods, location of residence and location of incidence. The findings highlighted the need for consistent and concerted support from different stakeholders within suicide clusters, to ensure appropriate design, implementation and sustainability of effective suicide prevention programs. Funding General Research Fund (37000320) and seed fund from the University of Hong Kong (104006710).
Collapse
Affiliation(s)
- Cheuk Yui Yeung
- Department of Social Work and Social Administration, The University of Hong Kong, Hong Kong SAR, China
- University of Rochester Medical Center, Rochester, USA
| | - Vera Yu Men
- Sunnybrook Research Institute, The University of Toronto, Toronto, Canada
- Hong Kong Jockey Club Centre for Suicide Research and Prevention, The University of Hong Kong, Hong Kong SAR, China
| | - Yingqi Guo
- Department of Social Work, Hong Kong Baptist University, Hong Kong SAR, China
- Department of Geography (Joint), Hong Kong Baptist University, Hong Kong SAR, China
- Smart Society Lab, Hong Kong Baptist University, Hong Kong SAR, China
| | - Paul Siu Fai Yip
- Department of Social Work and Social Administration, The University of Hong Kong, Hong Kong SAR, China
- Hong Kong Jockey Club Centre for Suicide Research and Prevention, The University of Hong Kong, Hong Kong SAR, China
| |
Collapse
|
2
|
Lu FW, Conway E, Liang YL, Chen YY, Gunnell D, Chang SS. Space-time self-harm and suicide clusters in two cities in Taiwan. Epidemiol Psychiatr Sci 2023; 32:e37. [PMID: 37258458 DOI: 10.1017/s2045796023000513] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 06/02/2023] Open
Abstract
AIMS Suicidal acts may cluster in time and space and lead to community concerns about further imitative suicidal episodes. Although suicide clusters have been researched in previous studies, less is known about the clustering of non-fatal suicidal behaviour (self-harm). Furthermore, most previous studies used crude temporal and spatial information, e.g., numbers aggregated by month and residence area, for cluster detection analysis. This study aimed to (i) identify space-time clusters of self-harm and suicide using daily incidence data and exact address and (ii) investigate the characteristics of cluster-related suicidal acts. METHODS Data on emergency department presentations for self-harm and suicide deaths in Taipei City and New Taipei City, Taiwan, were used in this study. In all-age and age-specific analyses, self-harm and suicide clusters were identified using space-time permutation scan statistics. A cut-off of 0.10 for the p value was used to identify possible clusters. Logistic regression was used to investigate the characteristics associated with cluster-related episodes. RESULTS A total of 5,291 self-harm episodes and 1,406 suicides in Taipei City (2004-2006) and 20,531 self-harm episodes and 2,329 suicides in New Taipei City (2012-2016) were included in the analysis. In the two cities, two self-harm clusters (n [number of self-harm episodes or suicide deaths in the cluster] = 4 and 8 in Taipei City), four suicide clusters (n = 3 in Taipei City and n = 4, 11 and 4 in New Taipei City) and two self-harm and suicide combined clusters (n = 4 in Taipei City and n = 8 in New Taipei City) were identified. Space-time clusters of self-harm, suicide, and self-harm and suicide combined accounted for 0.05%, 0.59%, and 0.08% of the respective groups of suicidal acts. Cluster-related episodes of self-harm and suicide were more likely to be male (adjusted odds ratio [aOR] = 2.22, 95% confidence interval [CI] 1.26, 3.89) and young people aged 10-29 years (aOR = 2.72, 95% CI 1.43, 5.21) than their cluster-unrelated counterparts. CONCLUSIONS Space-time clusters of self-harm, suicide, and self-harm and suicide combined accounted for a relatively small proportion of suicidal acts and were associated with some sex/age characteristics. Focusing on suicide deaths alone may underestimate the size of some clusters and/or lead to some clusters being overlooked. Future research could consider combining self-harm and suicide data and use social connection information to investigate possible clusters of suicidal acts.
Collapse
Affiliation(s)
- Fang-Wen Lu
- Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan
- Institute of Health Behaviors and Community Sciences, College of Public Health, National Taiwan University, Taipei, Taiwan
| | - Erica Conway
- Institute of Health Behaviors and Community Sciences, College of Public Health, National Taiwan University, Taipei, Taiwan
- Global Health Program, College of Public Health, National Taiwan University, Taipei, Taiwan
| | - Ya-Lun Liang
- Institute of Health Behaviors and Community Sciences, College of Public Health, National Taiwan University, Taipei, Taiwan
| | - Ying-Yeh Chen
- Taipei City Psychiatric Centre, Taipei City Hospital, Taipei, Taiwan
- Institute of Public Health and Department of Public Health, National Yang-Ming Chiao Tung University, Taipei, Taiwan
| | - David Gunnell
- Centre for Academic Mental Health, Population Health Sciences, University of Bristol, Bristol, UK
- National Institute of Health Research Biomedical Research Centre, University Hospitals Bristol and Weston National Health Service Foundation Trust, Bristol, UK
| | - Shu-Sen Chang
- Institute of Health Behaviors and Community Sciences, College of Public Health, National Taiwan University, Taipei, Taiwan
- Global Health Program, College of Public Health, National Taiwan University, Taipei, Taiwan
- Psychiatric Research Center, Wan Fang Hospital, Taipei Medical University, Taipei, Taiwan
| |
Collapse
|
3
|
Roca-Barceló A, Crabbe H, Close R, Fahie H, Leonardi GS, Piel FB. Spatial and temporal trends and risk factors for intentional carbon monoxide poisoning hospitalizations in England between 2002 and 2016. J Affect Disord 2023; 329:168-175. [PMID: 36841308 DOI: 10.1016/j.jad.2023.02.036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Revised: 02/06/2023] [Accepted: 02/09/2023] [Indexed: 02/27/2023]
Abstract
INTRODUCTION Suicide and mental health disorders are a recognized increasing public concern. Most suicide prevention rely on evidence from mortality data, although suicide attempts are a better predictor for completed suicides. Understanding spatio-temporal patterns and demographic profiles of people at risk can improve suicide prevention schemes, including for carbon monoxide (CO) poisoning, a common method for gas-related suicides. OBJECTIVE Describe spatio-temporal patterns of intentional CO poisoning hospitalization rates in England between 2002 and 2016, and identify population sub-groups at risk. METHODS We used NHS Digital's Hospital Episode Statistics (HES) routinely collected data on hospital admissions for intentional CO poisoning. We estimated age-standardised rates (ASR) by year, gender and residential small-area characteristics, including rural/urban, deprivation and ethnic composition. Temporal trends were assessed through linear regression and joinpoint regression analysis. Regional differences were explored. RESULTS On average, we identified 178 hospital admissions for intentional CO poisoning per year. The ASR decreased substantially over the study period, particularly among males (average annual percent change of -7.8 % (95 % CI: -11.0; -4.6)), in comparison to 3.9 % (95%CI, -6.4; -1.4) among females. Most admissions (81 %) occurred in males. White men aged 35-44 years were particularly at risk. The ASR in London (0.08/100,000) was almost six times lower than in the South-West (0.47/100,000). CONCLUSIONS This study provides novel insights into attempted suicides by intentional CO poisoning. Further prevention interventions, targeting sub-groups at risk (i.e. white men in their 30s/40s), need to be developed and implemented to reduce the burden of suicides and of CO poisoning.
Collapse
Affiliation(s)
- Aina Roca-Barceló
- Small Area Health Statistics Unit, Medical Research Council (MRC) Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom
| | - Helen Crabbe
- Environmental Epidemiology Group, UK Health Security Agency, Radiation, Chemical and Environmental Hazards Directorate, Chilton, Oxon, United Kingdom; National Institute of Health Research (NIHR) Health Protection Research Unit (HPRU) in Environmental Exposures & Health, Imperial College London, London, United Kingdom
| | - Rebecca Close
- Environmental Epidemiology Group, UK Health Security Agency, Radiation, Chemical and Environmental Hazards Directorate, Chilton, Oxon, United Kingdom; National Institute of Health Research (NIHR) Health Protection Research Unit (HPRU) in Environmental Exposures & Health, Imperial College London, London, United Kingdom
| | - Helena Fahie
- Specialty Registrar in Public Health, Oxford School of Public Health, Health Education England, United Kingdom
| | - Giovanni S Leonardi
- Environmental Epidemiology Group, UK Health Security Agency, Radiation, Chemical and Environmental Hazards Directorate, Chilton, Oxon, United Kingdom; National Institute of Health Research (NIHR) Health Protection Research Unit (HPRU) in Environmental Exposures & Health, Imperial College London, London, United Kingdom
| | - Frédéric B Piel
- Small Area Health Statistics Unit, Medical Research Council (MRC) Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom; National Institute of Health Research (NIHR) Health Protection Research Unit (HPRU) in Environmental Exposures & Health, Imperial College London, London, United Kingdom; National Institute of Health Research (NIHR) Health Protection Research Unit (HPRU) in Chemical & Radiation Threats & Hazards, Imperial College London, London, United Kingdom.
| |
Collapse
|
4
|
Steelesmith DL, Lindstrom MR, Le HTK, Root ED, Campo JV, Fontanella CA. Spatiotemporal Patterns of Deaths of Despair Across the U.S., 2000-2019. Am J Prev Med 2023:S0749-3797(23)00093-4. [PMID: 36964010 DOI: 10.1016/j.amepre.2023.02.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/17/2022] [Revised: 02/08/2023] [Accepted: 02/12/2023] [Indexed: 03/26/2023]
Abstract
INTRODUCTION Deaths of despair (i.e., suicide, drug/alcohol overdose, and chronic liver disease and cirrhosis) have been increasing over the past 2 decades. However, no large-scale studies have examined geographic patterns of deaths of despair in the U.S. This ecologic study identifies geographic and temporal patterns of individual and co-occurring clusters of deaths of despair. METHODS All individuals aged ≥10 years who died in the U.S. between 2000 and 2019 and resided within the 48 contiguous states and Washington, District of Columbia were included (N=2,171,105). Causes of death were limited to deaths of despair, namely suicide, drug/alcohol overdose, and chronic liver disease and cirrhosis. Univariate and multivariate space-time scan statistics were used to identify individual and co-occurring clusters with excess risk of deaths of despair. County-level RRs account for heterogeneity within each cluster. Analyses were conducted from late 2021 to early 2022. RESULTS Six suicide clusters, 4 overdose clusters, 9 liver disease clusters, and 3 co-occurring clusters of all 3 types of deaths were identified. A large portion of the western U.S., southeastern U.S., and Appalachia/rust belt were contained within the co-occurring clusters. The co-occurring clusters had average county RRs ranging from 1.17 (p<0.001) in the southeastern U.S. to 4.90 (p<0.001) in the western U.S. CONCLUSIONS Findings support identifying and targeting risk factors common to all types of deaths of despair when planning public health interventions. Resources and policies that address all deaths of despair simultaneously may be beneficial for the areas contained within the co-occurring high-risk clusters.
Collapse
Affiliation(s)
- Danielle L Steelesmith
- Center for Suicide Prevention and Research, The Abigail Wexner Research Institute at Nationwide Children's Hospital, Columbus, Ohio.
| | | | - Huyen T K Le
- Department of Geography, The Ohio State University, Columbus, Ohio
| | | | - John V Campo
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Cynthia A Fontanella
- Center for Suicide Prevention and Research, The Abigail Wexner Research Institute at Nationwide Children's Hospital, Columbus, Ohio; Department of Psychiatry and Behavioral Health, College of Medicine, The Ohio State University Wexner Medical Center, Columbus, Ohio
| |
Collapse
|
5
|
Kandula S, Martinez-Alés G, Rutherford C, Gimbrone C, Olfson M, Gould MS, Keyes KM, Shaman J. County-level estimates of suicide mortality in the USA: a modelling study. Lancet Public Health 2023; 8:e184-e193. [PMID: 36702142 PMCID: PMC9990589 DOI: 10.1016/s2468-2667(22)00290-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Revised: 10/11/2022] [Accepted: 10/31/2022] [Indexed: 01/25/2023]
Abstract
BACKGROUND Suicide is one of the leading causes of death in the USA and population risk prediction models can inform decisions on the type, location, and timing of public health interventions. We aimed to develop a prediction model to estimate county-level suicide risk in the USA using population characteristics. METHODS We obtained data on all deaths by suicide reported to the National Vital Statistics System between Jan 1, 2005, and Dec 31, 2019, and age, sex, race, and county of residence of the decedents were extracted to calculate baseline risk. We also obtained county-level annual measures of socioeconomic predictors of suicide risk (unemployment, weekly wage, poverty prevalence, median household income, and population density) and state-level prevalence of major depressive disorder and firearm ownership from US public sources. We applied conditional autoregressive models, which account for spatiotemporal autocorrelation in response and predictors, to estimate county-level suicide risk. FINDINGS Estimates derived from conditional autoregressive models were more accurate than from models not adjusted for spatiotemporal autocorrelation. Inclusion of suicide risk and protective covariates further reduced errors. Suicide risk was estimated to increase with each SD increase in firearm ownership (2·8% [95% credible interval (CrI) 1·8 to 3·9]), prevalence of major depressive episode (1·0% [0·4 to 1·5]), and unemployment rate (2·8% [1·9 to 3·8]). Conversely, risk was estimated to decrease by 4·3% (-5·1 to -3·2) for each SD increase in median household income and by 4·3% (-5·8 to -2·5) for each SD increase in population density. An increase in the heterogeneity in county-specific suicide risk was also observed during the study period. INTERPRETATION Area-level characteristics and the conditional autoregressive models can estimate population-level suicide risk. Availability of near real-time situational data are necessary for the translation of these models into a surveillance setting. Monitoring changes in population-level risk of suicide could help public health agencies select and deploy targeted interventions quickly. FUNDING US National Institute of Mental Health.
Collapse
Affiliation(s)
- Sasikiran Kandula
- Department of Environmental Health Sciences, Columbia University, New York, NY, USA.
| | - Gonzalo Martinez-Alés
- Department of Epidemiology, Columbia University, New York, NY, USA; CAUSALab, Harvard T H Chan School of Public Health, Boston, MA, USA; Mental Health Network Biomedical Research Center, Madrid, Spain; Mental Health Research Group, Hospital La Paz Institute for Health Research, Madrid, Spain
| | | | | | - Mark Olfson
- Department of Epidemiology, Columbia University, New York, NY, USA; Department of Psychiatry, Columbia University, New York, NY, USA
| | - Madelyn S Gould
- Department of Epidemiology, Columbia University, New York, NY, USA; Department of Psychiatry, Columbia University, New York, NY, USA
| | | | - Jeffrey Shaman
- Department of Environmental Health Sciences, Columbia University, New York, NY, USA
| |
Collapse
|
6
|
Spatial analysis of mental health and suicide clustering among older adults in North Carolina: An exploratory analysis. SSM - MENTAL HEALTH 2022. [DOI: 10.1016/j.ssmmh.2022.100162] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
|
7
|
Platt JM, Pamplin JR, Gimbrone C, Rutherford C, Kandula S, Olfson M, Gould MS, Martínez-Alés G, Shaman J, Keyes K. Racial Disparities in Spatial and Temporal Youth Suicide Clusters. J Am Acad Child Adolesc Psychiatry 2022; 61:1131-1140.e5. [PMID: 35031449 PMCID: PMC9271532 DOI: 10.1016/j.jaac.2021.12.012] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/21/2021] [Revised: 12/20/2021] [Accepted: 01/04/2022] [Indexed: 11/23/2022]
Abstract
OBJECTIVE Deaths by suicide correlate both spatially and temporally, leading to suicide clusters. This study aimed to estimate racial patterns in suicide clusters since 2000. METHOD Data from the US National Vital Statistics System included all International Classification of Diseases, Tenth Revision (ICD-10)-coded suicide cases from 2000-2019 among American Indian/Alaska Native (AI/AN), Asian/Pacific Islander (A/PI), Black, or White youth and young adults, aged 5-34 years. We estimated age, period, and cohort (APC) trends and identified spatiotemporal clusters using the SaTScan space-time statistic, which identified lower- and higher-than-expected suicide rates (cold and hot clusters) in a prespecified area (150 km) and time interval (15 months). We also calculated the average proportion of deaths by suicide contained in clusters, to quantify the relative importance of spatiotemporal patterning as a driver of overall suicide rates. RESULTS From 2010-2019, suicide rates increased from between 37% among AI/AN (95% CI = 1.22, 1.55) to 81% among A/PI (95% CI = 1.65, 2.01) groups. Suicide clusters accounted for 0.8%-10.3% of all suicide deaths, across racial groups. Since 2000, the likelihood of detecting cluster increased over time, with considerable differences in the number of clusters in each racial group (4 among AI/AN to 72 among White youth). Among Black youth and young adults, 27 total clusters were identified. Hot clusters were concentrated in southeastern and mid-Atlantic counties. CONCLUSION Suicide rates and clusters in youth and young adults have increased in the past 2 decades, requiring attention from policy makers, clinicians, and caretakers. Racially distinct patterns highlight opportunities to tailor individual- and population-level prevention efforts to prevent suicide deaths in emerging high-risk groups.
Collapse
Affiliation(s)
| | - John R Pamplin
- Center for Urban Science and Progress, New York University, New York; Grossman School of Medicine, New York University, New York
| | | | | | | | - Mark Olfson
- Mailman School of Public Health, Columbia University, New York; Columbia University Irving Medical Center and New York State Psychiatric Institute, New York
| | - Madelyn S Gould
- Mailman School of Public Health, Columbia University, New York; Columbia University Irving Medical Center and New York State Psychiatric Institute, New York
| | | | - Jeffrey Shaman
- Mailman School of Public Health, Columbia University, New York
| | - Katherine Keyes
- Mailman School of Public Health, Columbia University, New York
| |
Collapse
|
8
|
Benson R, Rigby J, Brunsdon C, Cully G, Too LS, Arensman E. Quantitative Methods to Detect Suicide and Self-Harm Clusters: A Systematic Review. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19095313. [PMID: 35564710 PMCID: PMC9099648 DOI: 10.3390/ijerph19095313] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Revised: 04/20/2022] [Accepted: 04/23/2022] [Indexed: 11/16/2022]
Abstract
Suicide and self-harm clusters exist in various forms, including point, mass, and echo clusters. The early identification of clusters is important to mitigate contagion and allocate timely interventions. A systematic review was conducted to synthesize existing evidence of quantitative analyses of suicide and self-harm clusters. Electronic databases including Medline, Embase, Web of Science, and Scopus were searched from date of inception to December 2020 for studies that statistically analyzed the presence of suicide or self-harm clusters. Extracted data were narratively synthesized due to heterogeneity among the statistical methods applied. Of 7268 identified studies, 79 were eligible for narrative synthesis. Most studies quantitatively verified the presence of suicide and self-harm clusters based on the scale of the data and type of cluster. A Poisson-based scan statistical model was found to be effective in accurately detecting point and echo clusters. Mass clusters are typically detected by a time-series regression model, although limitations exist. Recently, the statistical analysis of suicide and self-harm clusters has progressed due to advances in quantitative methods and geospatial analytical techniques, most notably spatial scanning software. The application of such techniques to real-time surveillance data could effectively detect emerging clusters and provide timely intervention.
Collapse
Affiliation(s)
- Ruth Benson
- School of Public Health, College of Medicine and Health, University College Cork, Western Gateway Building, T12 XF62 Cork, Ireland; (G.C.); (E.A.)
- National Suicide Research Foundation, University College Cork, 4.28 Western Gateway Building, T12 XF62 Cork, Ireland
- Correspondence:
| | - Jan Rigby
- National Centre for Geocomputation, Maynooth University, W23 F2H6 Maynooth, Ireland; (J.R.); (C.B.)
| | - Christopher Brunsdon
- National Centre for Geocomputation, Maynooth University, W23 F2H6 Maynooth, Ireland; (J.R.); (C.B.)
| | - Grace Cully
- School of Public Health, College of Medicine and Health, University College Cork, Western Gateway Building, T12 XF62 Cork, Ireland; (G.C.); (E.A.)
- National Suicide Research Foundation, University College Cork, 4.28 Western Gateway Building, T12 XF62 Cork, Ireland
| | - Lay San Too
- Centre for Mental Health, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC 3053, Australia;
| | - Ella Arensman
- School of Public Health, College of Medicine and Health, University College Cork, Western Gateway Building, T12 XF62 Cork, Ireland; (G.C.); (E.A.)
- National Suicide Research Foundation, University College Cork, 4.28 Western Gateway Building, T12 XF62 Cork, Ireland
- Australian Institute for Suicide Research and Prevention, School of Applied Psychology, Griffith University, Brisbane, QLD 4122, Australia
| |
Collapse
|
9
|
Bommersbach TJ, Rosenheck RA, Everett AS. Suicide Hot Spots: Leveraging County-Level Data and Local Agencies to Target Prevention in High-Risk Areas. Public Health Rep 2021; 137:408-413. [PMID: 34011219 PMCID: PMC9109527 DOI: 10.1177/00333549211016606] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023] Open
Affiliation(s)
| | - Robert A. Rosenheck
- Department of Psychiatry, Yale University School of Medicine,
New Haven, CT, USA,US Department of Veterans Affairs, New England Mental Illness
Research, Education, and Clinical Center, West Haven, CT, USA
| | - Anita S. Everett
- Center for Mental Health Services, Substance Abuse and Mental
Health Services Administration, US Department of Health and Human Services,
Rockville, MD, USA,Anita S. Everett, MD, US Department of
Health and Human Services, Substance Abuse and Mental Health Services
Administration, Center for Mental Health Services, 5600 Fishers Ln, Rockville,
MD 20857, USA;
| |
Collapse
|
10
|
Keyes KM, Kandula S, Olfson M, Gould MS, Martínez-Alés G, Rutherford C, Shaman J. Suicide and the agent-host-environment triad: leveraging surveillance sources to inform prevention. Psychol Med 2021; 51:529-537. [PMID: 33663629 PMCID: PMC8020492 DOI: 10.1017/s003329172000536x] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/29/2020] [Revised: 12/14/2020] [Accepted: 01/06/2021] [Indexed: 12/11/2022]
Abstract
Suicide in the US has increased in the last decade, across virtually every age and demographic group. Parallel increases have occurred in non-fatal self-harm as well. Research on suicide across the world has consistently demonstrated that suicide shares many properties with a communicable disease, including person-to-person transmission and point-source outbreaks. This essay illustrates the communicable nature of suicide through analogy to basic infectious disease principles, including evidence for transmission and vulnerability through the agent-host-environment triad. We describe how mathematical modeling, a suite of epidemiological methods, which the COVID-19 pandemic has brought into renewed focus, can and should be applied to suicide in order to understand the dynamics of transmission and to forecast emerging risk areas. We describe how new and innovative sources of data, including social media and search engine data, can be used to augment traditional suicide surveillance, as well as the opportunities and challenges for modeling suicide as a communicable disease process in an effort to guide clinical and public health suicide prevention efforts.
Collapse
Affiliation(s)
| | - Sasikiran Kandula
- Department of Environmental Health Sciences, Columbia University, New York, NY, USA
| | - Mark Olfson
- Department of Epidemiology, Columbia University, New York, NY, USA
- Department of Psychiatry, Columbia University, New York, NY, USA
| | - Madelyn S. Gould
- Department of Epidemiology, Columbia University, New York, NY, USA
- Department of Psychiatry, Columbia University, New York, NY, USA
| | - Gonzalo Martínez-Alés
- Department of Epidemiology, Columbia University, New York, NY, USA
- Universidad Autónoma de Madrid School of Medicine, Madrid, Spain
| | | | - Jeffrey Shaman
- Department of Environmental Health Sciences, Columbia University, New York, NY, USA
| |
Collapse
|
11
|
Understanding the characteristics and mechanisms underlying suicide clusters in Australian youth: a comparison of cluster detection methods. Epidemiol Psychiatr Sci 2020; 29:e151. [PMID: 32758330 PMCID: PMC7443820 DOI: 10.1017/s2045796020000645] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
Abstract
AIMS There is currently no gold-standard definition or method for identifying suicide clusters, resulting in considerable heterogeneity in the types of suicide clusters that are detected. This study sought to identify the characteristics, mechanisms and parameters of suicide clusters using three cluster detection methods. Specifically, the study aimed to: (1) determine the overlap in suicide clusters among each method, (2) compare the spatial and temporal parameters associated with different suicide clusters and (3) identify the demographic characteristics and rates of exposure to suicide among cluster and non-cluster members. METHODS Suicide data were obtained from the National Coronial Information System. N = 3027 Australians, aged 10-24 who died by suicide in 2006-2015 were included. Suicide clusters were determined using: (1) poisson scan statistics, (2) a systematic search of coronial inquests and (3) descriptive network analysis. These methods were chosen to operationalise three different definitions of suicide clusters, namely clusters that are: (1) statistically significant, (2) perceived to be significant and (3) characterised by social links among three or more suicide descendants. For each method, the demographic characteristics and rates of exposure to suicide were identified, in addition to the maximum duration of suicide clusters, the geospatial overlap between suicide clusters, and the overlap of individual cluster members. RESULTS Eight suicide clusters (69 suicides) were identified from the scan statistic, seven (40 suicides) from coronial inquests; and 11 (37 suicides) from the descriptive network analysis. Of the eight clusters detected using the scan statistic, two overlapped with clusters detected using the descriptive network analysis and one with clusters identified from coronial inquests. Of the seven clusters from coronial inquests, four overlapped with clusters from the descriptive network analysis and one with clusters from the scan statistic. Overall, 9.2% (12 suicides) of individuals were identified by more than one method. Prior exposure to suicide was 10.1% (N = 7) in clusters from the scan statistic, 32.5% (N = 13) in clusters from coronial inquest and 56.8% (N = 21) in clusters from the descriptive network analysis. CONCLUSION Each method identified markedly different suicide clusters. Evidence of social links between cluster members typically involved clusters detected using the descriptive network analysis. However, these data were limited to the availability information collected as part of the police and coroner investigation. Communities tasked with detecting and responding to suicide clusters may benefit from using the spatial and temporal parameters revealed in descriptive studies to inform analyses of suicide clusters using inferential methods.
Collapse
|
12
|
Pollock NJ. Place, the Built Environment, and Means Restriction in Suicide Prevention. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2019; 16:ijerph16224389. [PMID: 31717635 PMCID: PMC6888187 DOI: 10.3390/ijerph16224389] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 10/11/2019] [Revised: 11/05/2019] [Accepted: 11/08/2019] [Indexed: 01/19/2023]
Abstract
Restricting access to lethal means is a key public health intervention for preventing suicide. Means restriction research has often focused on suicide methods that are modifiable through legislation or policy interventions. However, some of the most common methods such as hanging may not be sensitive to regulation. The aims of this paper are to examine built environment and place-based approaches to means restriction in suicide prevention, and further consider the connections between place, the environment, and suicide methods. To increase knowledge about specific methods and mechanisms of injury in suicide deaths, higher resolution data for surveillance and epidemiology is required. Data that can be used to better discern patterns about specific locations and materials used in suicide and self-harm will support efforts to uncover new directions for prevention.
Collapse
Affiliation(s)
- Nathaniel J. Pollock
- School of Public Health, University of Alberta, Edmonton, AB T6G 2R3, Canada;
- Division of Community Health and Humanities, Faculty of Medicine, Memorial University, St. John’s, NL A1C 5S7, Canada
| |
Collapse
|