Spatial analysis of suicide mortality in Québec: spatial clustering and area factor correlates

Socioeconomic Determinants of Health: Remoteness From Care

Remoteness from care remains a major challenge to equitable provision of health services worldwide. Beyond the difficulties associated with geographically and climatically rugged terrain, there are also socioeconomic, cultural, and technological challenges associated with remote residence. The objective of this review is to examine the factors whereby remoteness can be associated with sociodemographic disadvantage in health care and describe some of the methodologies for measurement and analysis of remoteness, with examples from the literature, particularly focusing on Canada. As surrogates for remoteness, simple measurements of direct distance or travel time may correlate well with more complex measures and can be performed relative to specific health care services of interest (for example, tertiary obstetric service). These metrics may also be measured, as general proxies for service availability, to various sizes of population centres. More complex measures of remoteness may also incorporate modes of available transport and availability of specific services into an index such as the Canadian Index of Remoteness. As an important independent predictor of health, remoteness requires careful predictive modelling because of potential complex nonlinear relationships, edge effects created by health system zone boundaries, and covariance with other sociodemographic factors and Indigenous population proportions. To combat disadvantage caused by remoteness, innovation in health service delivery, policy, and technology is required. Health-resource allocation must be adequate, and innovative technological advances-such as remote monitoring, expert clinical support, and artificial intelligence algorithms-must be supported by development of appropriate technological infrastructure, targeting remote regions. With these, the barriers to equitable health imposed by remoteness can be overcome.

Spatial, geographic, and demographic factors associated with adolescent and youth suicide: a systematic review study

Background

Suicide is a public health issue and a main cause of mortality among adolescents and the youth worldwide, particularly in developing countries.

Objectives

The present research is a systematic review aiming to investigate the spatial, geographical, and demographic factors related to suicide among adolescents and the youth.

Methods

In this systematic review, two researchers examined PsycINFO, Web of Science, Scopus, and PubMed databases on December 7th, 2022 with no time limits from the beginning of publication until 2022 to identify the primary studies on spatial and geographic analysis on adolescent and youth suicides. Once duplicate studies were identified and removed, the titles and abstracts of studies were examined and irrelevant studies were also removed. Finally, 22 studies were reviewed based on the inclusion criteria.

Results

Our findings show that suicide rates are generally higher among men, residents of rural and less densely populated regions, coastal and mountainous regions, natives, 15-29 age group, less privileged populations with social fragmentation, unemployed, divorced or lonely people, those who live in single parent families, people with mental health issues, and those with low levels of education.

Conclusions

Stronger evidence supports the effects of geographic and demographic variables on youth and adolescent suicide rates as compared with spatial variables. These findings suggest that policy makers take spatial and demographic factors into consideration when health systems allocate resources for suicide prevention, and that national policymakers integrate demographic and geographic variables into health service programs.

Systematic Review Registration

https://www.crd.york.ac.uk/prospero/, identifier CRD42023430994.

Spatiotemporal clustering of suicide attempt in Kermanshah, West-Iran

Background

A suicide attempt is a major societal problem because it imposes high costs on societies worldwide. This paper analyses the spatiotemporal clustering of suicide attempt in Kermanshah, Iran from 2006-14.

Methods

This study draws on 18,333 individuals (7,234 males and 11,097 females) who attempted suicide across the Kermanshah province. Data was collected from the records of individuals registered in hospitals across the Kermanshah province between 2006 and 2014. Mean Center, Standard Deviational Ellipse (SDE), Moran's I and Kernel Density Estimation (KDE) in Arc/GIS10.6 software were used for the analysis of the spatial distribution of suicide attempt, while the chi-squared test in SPSS was used to examine the different demographic variables between groups within/outside spatial clusters of suicide.

Results

The results show that a total of 18,331 suicide attempts (39.46% male and 60.53% female) were reported between 2006 and 2014 in the Kermanshah province. The spatial pattern of suicide attempts was clustered in 16 clusters (6 high clusters and 10 low clusters) and statistically significant differences were found within and outside the hotspots of suicide attempts. Most hot spots were formed in and around cities. Younger people were at a greater risk. The rate of suicide attempts reduced in illiterate people and increased in people with university degrees. Unmarried people were associated with a higher risk of suicide attempt than was married status for both males and females.

Conclusion

The results of this study could help public health practitioners and policymakers in Iran prioritize resources and target efforts for suicide attempt prevention.

The application of spatial analysis to understanding the association between area-level socio-economic factors and suicide: a systematic review

BACKGROUND

Little is known about what impact the use of different spatial methodological approaches may have on understanding the relationship between area-level socio-economic factors and suicide.

METHODS

In this systematic review, we searched PubMed, Embase, CINAHL and PsycInfo for original empirical studies examining the relationship between socio-economic factors and suicide with a spatial lens, published up to January 22, 2022. Data on applied spatial methods, indicators of socio-economic factors, and risk of suicide related to socio-economic factors were extracted. The protocol for this systematic review was registered with PROSPERO (CRD42021251387).

RESULTS

A systematic search yielded 6290 potentially relevant results; 58 studies met the inclusion criteria for review. Of the 58 included studies, more than half of the studies (n = 34; 58.6%) used methods that accounted for spatial effects in analyses of the association between socio-economic factors and suicide or examined spatial autocorrelation, while 24 (41.4%) studies applied univariate and multivariate models without considering spatial effects. Bayesian hierarchical models and spatial regression models were commonly used approaches to correct for spatial effects. The risk of suicide relating to socio-economic factors varied greatly by local areas and between studies using various socio-economic indicators. Areas with higher deprivation, higher unemployment, lower income, and lower education level were more likely to have higher suicide risk. There was no significant difference in results between studies using conventional versus spatial statistic methods.

CONCLUSION

An increasing number of studies have applied spatial methods, including Bayesian spatial models and spatial regression models, to explore the relationship between area-level socio-economic factors and suicide. This review of spatial studies provided further evidence that area-level socio-economic factors are generally inversely associated with suicide risk, with or without accounting for spatial autocorrelation.

Quantitative Methods to Detect Suicide and Self-Harm Clusters: A Systematic Review

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.

Exploring multiple pathways and mediation effects of urban environmental factors for suicide prevention

Public health is threatened by air pollution and high temperature, especially in urban areas and areas impacted by climate change. Well-designed urban forms have co-benefits on promoting human health and mediating atmospheric environment-related threats (e.g., high temperature and air pollution). Previous studies overlooked these mediating effects of urban form on suicide mortality. This study used partial least squares modeling and countywide data in Taiwan to identify the crucial influences and pathways of urban environment, socioeconomic status, and diseases on suicide mortality. The model considered the impact of the characteristics of urban form (i.e., urban development intensity, land mix, and urban sprawl), urban industrial status (i.e., industrial level), urban greening (i.e., green coverage), disease (i.e., important diseases morbidity of human immunodeficiency virus [HIV], cerebrovascular disease [CVD], chronic liver disease and cirrhosis [CLDC], nephritis, nephrotic syndrome and nephrosis [NNSN], malignant tumor [MT]), socioeconomic status (i.e., income level and aging population rate), and the atmospheric environment (i.e., air pollution and high temperature) on suicide mortality. Optimizing land mix and minimizing urban development intensity and urban sprawl have been found to reduce suicide mortality. The mediating effect of urban form on suicide mortality originated from air pollution and high temperature, and mediating air pollution was greater than high temperature. Furthermore, industrial level, important diseases (HIV, CVD, CLDC, NNSN, and MT) morbidity, an aging population rate, air pollution, and high temperature were associated with an increase in suicide mortality, whereas green coverage and income level were associated with a reduction in suicide rates. The findings demonstrate that appropriate urban policy and urban planning may lower suicide mortality, be useful strategies for suicide prevention, and be a foundation for building a healthy city. Moreover, this study provides clarity on the complex relationship of suicide and the urban environment while identifying crucial factors.

Rural-Urban Differences in Suicide Mortality: An Observational Study in Newfoundland and Labrador, Canada: Différences de la Mortalité Par Suicide en Milieu Rural-Urbain: Une Étude Observationnelle à Terre-Neuve et Labrador, Canada

BACKGROUND

Suicide rates are higher in rural compared to urban areas. Although this pattern appears to be driven by higher rates among men, there is limited evidence about the characteristics of rural people who die by suicide in Canada. The objective of this study was to examine the demographics, manner of death, and social and clinical antecedents of people who died by suicide in rural areas compared to urban areas.

METHODS

We conducted an observational study of all suicide deaths that occurred among Newfoundland and Labrador residents between 1997 and 2016 using a linked data set derived from a comprehensive review of provincial medical examiner records. We used t tests and χ² to assess associations between rural/urban status and variables related to demographics, circumstances, and manner of death, as well as social and medical history. Logistic regression was utilized to assess the independent contribution of any variable found to be significant in univariate analysis.

RESULTS

Rural people who died by suicide accounted for 54.8% of all deaths over a 20-year period. Overall, 81.6% of people who died were male. Compared to urban, rural people who died by suicide were younger, more likely to use firearms or hanging, and had a higher mean blood alcohol content at the time of death (27.69 vs. 22.95 mmol/L). Rural people were also less likely to have had a known history of a prior suicide attempt, psychiatric disorder, alcohol or substance abuse, or chronic pain.

DISCUSSION

The demographic and clinical differences between rural and urban people who died by suicide underscore the need for suicide prevention approaches that account for place-based differences. A key challenge for suicide prevention in rural communities is to ensure that interventions are developed and implemented in a manner that fits local contexts.

Community social determinants and health outcomes drive availability of patient-centered medical homes

The collaborative design of America's patient-centered medical homes places these practices at the forefront of emerging efforts to address longstanding inequities in the quality of primary care experienced among socially and economically marginalized populations. We assessed the geographic distribution of the country's medical homes and assessed whether they are appearing within communities that face greater burdens of disease and social vulnerability. We assessed overlapping spatial clusters of mental and physical health surveys; health behaviors, including alcohol-impaired driving deaths and drug overdose deaths; as well as premature mortality with clusters of medical home saturation and community socioeconomic characteristics. Overlapping spatial clusters were assessed using odds ratios and marginal effects models, producing four different scenarios of resource need and resource availability. All analyses were conducted using county-level data for the contiguous US states. Counties having lower uninsured rates and lower poverty rates were the most consistent indicators of medical home availability. Overall, the analyses indicated that medical homes are more likely to emerge within communities that have more favorable health and socioeconomic conditions to begin with. These findings suggest that intersecting the spatial footprints of medical homes in relation to health and socioeconomic data can provide crucial information for policy makers and payers invested in narrowing the gaps between clinic availability and the communities that experience the brunt of health and social inequalities.

Life Expectancy in Areas around Subway Stations in the Seoul Metropolitan Area in Korea, 2008-2017

BACKGROUND

This study aimed to calculate life expectancy in the areas around 614 subway stations on 23 subway lines in the Seoul metropolitan area of Korea from 2008 to 2017.

METHODS

We used the National Health Information Database provided by the National Health Insurance Service, which covers the whole population of Korea. The analysis was conducted on the level of the smallest administrative units within a 200-m radius of each subway station. Life expectancy was calculated by constructing an abridged life table using the number of population and deaths in each area and 5-year age groups (0, 1-4, …, 85+) during the whole study period.

RESULTS

The median life expectancy in the areas around 614 subway stations was 82.9 years (interquartile range, 2.2 years; minimum, 77.6 years; maximum, 87.4 years). The life expectancy of areas around subway stations located in Seoul was higher than those in Incheon and Gyeonggi-do, but variation within the region was observed. Significant differences were observed between some adjacent subway stations. In Incheon and Gyeonggi-do, substantially higher life expectancy was found around subway stations in newly developed urban areas, and lower life expectancy was found in central Incheon and suburbs in Gyeonggi-do.

CONCLUSION

When using areas around subway stations as the unit of analysis, variation in life expectancy in the Seoul metropolitan area was observed. This approach may reduce the stigma associated with presenting health inequalities at the level of the smallest administrative units and foster public awareness of health inequalities.

Theoretical Foundations in Support of Small and Medium Towns

This theoretical review aims to create a comprehensive and systematic analysis based on previously published literature explaining how contemporary technological developments may promote new paths for small and medium-sized towns (SMTs) and their networking systems. Much has been said concerning the capacity of towns to absorb strategic knowledge, which is highly dependent on local governance systems. In this paper, five levels of multidisciplinary approaches will be addressed so as to pinpoint the theoretical grounds for the promotion and advocacy of small and medium-sized towns (SMTs) as major drivers of regional sustainability: agglomeration advantages and networking efficiencies—representing strict economic accounting of cost and benefits; clustering in a context of online environments, and its extension to open networking systems; sustainable innovation processes for SMTs, technology, and knowledge transfer in open innovation systems—both settings for discussions within the framing of new technological developments and artificial intelligence; knowledge and new technological developments with local spillovers—to be enhanced employing new educational programs and learning diffusion at advanced levels; the social functions of small and medium-sized towns—to be addressed in the areas of sociology, architecture, and planning.

Can We Develop a Risk Map for Suicide Rates? An Ecological Study in Portugal

Place of residence can influence suicide acts, beyond individual characteristics. The aim of this study was to identify areas with a greater risk of suicide, identify possible associations with ecological risk factors and develop a risk map of suicide in Portugal. Spatial scan statistic was used to identify critical areas and associations were analyzed through logistic regression models. The results indicate that the spatial distribution of suicides could be determined by a set of ecological risk factors, and that being a foreigner (OR 26.64; 95% CI 13.15-53.97), having no religion (OR 8.65; 95% CI 4.62-16.19) and having lower levels of education (OR 1.20; 95% CI 1.09-3.64) are associated with a higher risk of suicide in Portugal. Results indicate that local risk factors should be taken into account, in accordance to the priority Health Program in the Mental Health area of the Directorate-General for Health of Portugal.

Does Land Use and Landscape Contribute to Self-Harm? A Sustainability Cities Framework

Self-harm has become one of the leading causes of mortality in developed countries. The overall rate for suicide in Canada is 11.3 per 100,000 according to Statistics Canada in 2015. Between 2000 and 2007 the lowest rates of suicide in Canada were in Ontario, one of the most urbanized regions in Canada. However, the interaction between land use, landscape and self-harm has not been significantly studied for urban cores. It is thus of relevance to understand the impacts of land-use and landscape on suicidal behavior. This paper takes a spatial analytical approach to assess the occurrence of self-harm along one of the densest urban cores in the country: Toronto. Individual self-harm data was gathered by the National Ambulatory Care System (NACRS) and geocoded into census tract divisions. Toronto’s urban landscape is quantified at spatial level through the calculation of its land use at different levels: (i) land use type, (ii) sprawl metrics relating to (a) dispersion and (b) sprawl/mix incidence; (iii) fragmentation metrics of (a) urban fragmentation and (b) density and (iv) demographics of (a) income and (b) age. A stepwise regression is built to understand the most influential factors leading to self-harm from this selection generating an explanatory model.

The geography of suicide in older adults in Hong Kong: An ecological study

OBJECTIVES

The geography of suicide has been widely explored among the general population. However, little is known of the geographic variations in suicides among the older adults and their spatial correlates. This study aims to explore the spatial variations in the elderly suicide rates and their correlates in Hong Kong.

METHODS

Bayesian hierarchical models have been used to estimate smoothed standardized mortality ratios (2006-2015) on suicide in people aged 65 years or older in each geographic unit in Hong Kong. Their associations with the Social Vulnerability Index and the accessibility of eight types of services (ie, recreational services, rehabilitation services, food services, daily necessity services, community services, and transportation services) were further analyzed.

RESULTS

The results suggested that compared with the simple "inner-city high suicide rate and suburban low" pattern in the Western studies and the "central low suicide rate and peripheral high" pattern in the Asian studies, the spatial variations of elderly suicides in Hong Kong exhibit a much more complicated pattern. In Hong Kong, higher elderly suicide clusters were found in both the lower-density areas located in the New Territories and in some inner-city areas. The spatial variations of suicide in the older adults cannot be explained by the Social Vulnerability Index. Instead, service provision such as recreational services, daily necessity resources, and community centers played a more significant role in affecting suicides in the older adults.

CONCLUSIONS

Strengthening public services, providing more public spaces and activities, and making good use of the community resources might be key and efficient strategies in elderly suicide prevention in Hong Kong. Key points The spatial variations of elderly suicides in Hong Kong show a much more complicated pattern compared with the simple "inner-city high suicide rate and suburban low" pattern in the Western countries and the "central low suicide rate and peripheral high" pattern in some of the Asian countries. In Hong Kong, suicide rates in the city centers were not higher than the average in the city. Clusters of higher suicide rates were mainly found in the New Territories, which is somewhat disconnected from the city and, in some inner-city neighborhoods, with high-density population. The spatial variations of suicide in the older adults in Hong Kong cannot be explained by the neighborhood Social Vulnerability Index as in the existing literature. Neighborhood service provision such as recreational services, daily necessity resources, and community centers played a significant role in affecting suicides in the older adults in Hong Kong.

Suicide mortality among youth in southern Brazil: a spatiotemporal evaluation of socioeconomic vulnerability

Objective:

To conduct a geospatial analysis of suicide deaths among young people in the state of Paraná, southern Brazil, and evaluate their association with socioeconomic and spatial determinants.

Methods:

Data were obtained from the Mortality Information System and the Brazilian Institute of Geography and Statistics. Data on suicide mortality rates (SMR) were extracted for three age groups (15-19, 20-24, and 25-29 years) from two 5-year periods (1998-2002 and 2008-2012). Geospatial data were analyzed through exploratory spatial data analysis. We applied Bayesian networks algorithms to explore the network structure of the socioeconomic predictors of SMR.

Results:

We observed spatial dependency in SMR in both periods, revealing geospatial clusters of high SMR. Our results show that socioeconomic deprivation at the municipality level was an important determinant of suicide in the youth population in Paraná, and significantly influenced the formation of high-risk SMR clusters.

Conclusion:

While youth suicide is multifactorial, there are predictable geospatial and sociodemographic factors associated with high SMR among municipalities in Paraná. Suicide among youth aged 15-29 occurs in geographic clusters which are associated with socioeconomic deprivation. Rural settings with poor infrastructure and development also correlate with increased SMR clusters.

Spatial Clustering of Suicide and Associated Community Characteristics, Idaho, 2010-2014

Introduction

In 2015, Idaho had the fifth highest suicide rate in the United States. Little is known about the characteristics of areas in Idaho with high suicide rates. To aid suicide prevention efforts in the state, we sought to identify and characterize spatial clusters of suicide.

Methods

We obtained population data from the 2010 US Census and the 2010–2014 American Community Survey, analyzed data on suicides from death certificates, and used a discrete Poisson model in SaTScan to identify spatial clusters of suicide. We used logistic regression to examine associations between suicide clustering and population characteristics.

Results

We found 2 clusters of suicide during 2010–2014 that accounted for 70 (4.7%) of 1,501 suicides in Idaho. Areas within clusters were positively associated with the following population characteristics: median age ≤31.1 years versus >31.1 years (multivariable-adjusted odds ratio [aOR] = 2.4; 95% confidence interval [CI], 1.04–5.6), >53% female vs ≤53% female (aOR = 2.7; 95% CI, 1.3–5.8; P = .01), >1% American Indian/Alaska Native vs ≤1% American Indian/Alaska Native (aOR = 2.9; 95% CI, 1.4–6.3), and >30% never married vs ≤30% never married (aOR = 3.4; 95% CI, 1.5–8.0; P = .004).

Conclusion

Idaho suicide prevention programs should consider using results to target prevention efforts to communities with disproportionately high suicide rates.

Spatial analysis of the relative risk of suicide for Virginia counties incorporating uncertainty of variable estimates

PURPOSE

This research aimed to identify significantly elevated areas of risk for suicide in Virginia adjusting for risk factors and risk factor uncertainty.

METHODS

We fit three Bayesian hierarchical spatial models for relative risk of suicide adjusting for risk factors and considering different random effects. We compared models with and without incorporating parameter estimates' margin of error (MOE) from the American Community Survey and identified counties with significantly elevated risk and highly significantly elevated risk for suicide.

RESULTS

Incorporating MOEs and using a mixing parameter between unstructured and spatially structured random effects achieved the best model fit. Fifty-two counties had significantly elevated risk and 18 had highly significantly elevated risk of suicide. Models without MOEs underestimated relative risk and over-identified counties with elevated risk.

CONCLUSIONS

Accounting for uncertainty in parameter estimates achieved better model fit. Efficient allocation of resources for suicide prevention can be attained by targeting clusters of counties with elevated risk.

Does Walkability Contribute to Geographic Variation in Psychosocial Distress? A Spatial Analysis of 91,142 Members of the 45 and Up Study in Sydney, Australia

Walkability describes the capacity of the built environment to promote walking, and has been proposed as a potential focus for community-level mental health planning. We evaluated this possibility by examining the contribution of area-level walkability to variation in psychosocial distress in a population cohort at spatial scales comparable to those used for regional planning in Sydney, Australia. Data on psychosocial distress were analysed for 91,142 respondents to the 45 and Up Study baseline survey between January 2006 and April 2009. We fit conditional auto regression models at the postal area level to obtain smoothed “disease maps” for psychosocial distress, and assess its association with area-level walkability after adjusting for individual- and area-level factors. Prevalence of psychosocial distress was 7.8%; similar for low (7.9%), low-medium (7.9%), medium-high (8.0%), and high (7.4%) walkability areas; and decreased with reducing postal area socioeconomic disadvantage: 12.2% (most), 9.3%, 7.5%, 5.9%, and 4.7% (least). Unadjusted disease maps indicated strong geographic clustering of psychosocial distress with 99.0% of excess prevalence due to unobserved and spatially structured factors, which was reduced to 55.3% in fully adjusted maps. Spatial and unstructured variance decreased by 97.3% and 39.8% after adjusting for individual-level factors, and another 2.3% and 4.2% with the inclusions of area-level factors. Excess prevalence of psychosocial distress in postal areas was attenuated in adjusted models but remained spatially structured. Postal area prevalence of high psychosocial distress is geographically clustered in Sydney, but is unrelated to postal area walkability. Area-level socioeconomic disadvantage makes a small contribution to this spatial structure; however, community-level mental health planning will likely deliver greatest benefits by focusing on individual-level contributors to disease burden and inequality associated with psychosocial distress.

Mapping suicide mortality in Ohio: A spatial epidemiological analysis of suicide clusters and area level correlates

Previous studies have investigated spatial patterning and associations of area characteristics with suicide rates in Western and Asian countries, but few have been conducted in the United States. This ecological study aims to identify high-risk clusters of suicide in Ohio and assess area level correlates of these clusters. We estimated spatially smoothed standardized mortality ratios (SMR) using Bayesian conditional autoregressive models (CAR) for the period 2004 to 2013. Spatial and spatio-temporal scan statistics were used to detect high-risk clusters of suicide at the census tract level (N=2952). Logistic regression models were used to examine the association between area level correlates and suicide clusters. Nine statistically significant (p<0.05) high-risk spatial clusters and two space-time clusters were identified. We also identified several significant spatial clusters by method of suicide. The risk of suicide was up to 2.1 times higher in high-risk clusters than in areas outside of the clusters (relative risks ranged from 1.22 to 2.14 (p<0.01)). In the multivariate model, factors strongly associated with area suicide rates were socio-economic deprivation and lower provider densities. Efforts to reduce poverty and improve access to health and mental health medical services on the community level represent potentially important suicide prevention strategies.

Urban-Rural Differences in Suicide in the State of Maryland: The Role of Firearms

OBJECTIVES

To assess whether the use of firearms explains rural-urban differences in suicide rates.

METHODS

We performed a retrospective analysis on all 6196 well-characterized adult suicides in Maryland from 2003 through 2015. We computed rate ratios by using census data and then stratified by sex, with adjustment for age and race.

RESULTS

Suicide rates were higher in rural compared with urban counties. However, the higher rural suicide rates were limited to firearm suicides (incident rate ratio [IRR] = 1.66; 95% confidence interval [CI] = 1.20, 2.31). Nonfirearm suicide rates were not significantly higher in rural settings. Furthermore, 89% of firearm suicides occurred in men and the higher rural firearm suicide rate was limited to men (IRR = 1.36; 95% CI = 1.09, 1.69). Women were significantly less likely to complete suicide in rural areas (IRR = 0.63; 95% CI = 0.43, 0.94), regardless of method.

CONCLUSIONS

Male firearm use drives the increased rate of suicide in rural areas. The opposite associations between urbanicity and suicide in men and women may be driven by the male preference for firearms as a method for committing suicide.

Spatial Patterns and Neighborhood Characteristics of Overall Suicide Clusters in Florida From 2001 to 2010

INTRODUCTION

Although spatial examination of mortality and morbidity is becoming more common in health studies, the investigation of suicide death clusters within the neighborhood context is underutilized. The purpose of this ecological study is to detect high- and low-risk clusters of suicide deaths in Florida and determine which neighborhood characteristics distinguish clusters from non-clusters.

METHODS

The scan statistic method was used to detect overall clusters of completed suicides in Florida from 2001 to 2010. Regression analysis was used to investigate the association of neighborhood characteristics with identified clusters. All data synthesis and statistical analyses were conducted in 2015.

RESULTS

Twenty-four high-risk and 25 low-risk clusters were identified. The risk of suicide was up to 3.4 times higher in high-risk clusters than in areas outside of clusters (relative risk ranged from 1.36 to 3.44, p≤0.05). Low-risk clusters were associated with 30%-94% decreased risk of suicide (relative risk ranged from 0.06 to 0.70, p≤0.05). Areas with high levels of elderly concentration and household singularity were more likely to be in high-risk clusters, whereas areas with higher economic deprivation and residential density were more likely to be in low-risk clusters.

CONCLUSIONS

This study identified general suicide patterns across space in the state of Florida and described the characteristics of those areas.

Space-Time Cluster Analysis to Detect Innovative Clinical Practices: A Case Study of Aripiprazole in the Department of Veterans Affairs

OBJECTIVE

To identify space-time clusters of changes in prescribing aripiprazole for bipolar disorder among providers in the VA.

DATA SOURCES

VA administrative data from 2002 to 2010 were used to identify prescriptions of aripiprazole for bipolar disorder. Prescriber characteristics were obtained using the Personnel and Accounting Integrated Database.

STUDY DESIGN

We conducted a retrospective space-time cluster analysis using the space-time permutation statistic.

DATA EXTRACTION METHODS

All VA service users with a diagnosis of bipolar disorder were included in the patient population. Individuals with any schizophrenia spectrum diagnoses were excluded. We also identified all clinicians who wrote a prescription for any bipolar disorder medication.

PRINCIPAL FINDINGS

The study population included 32,630 prescribers. Of these, 8,643 wrote qualifying prescriptions. We identified three clusters of aripiprazole prescribing centered in Massachusetts, Ohio, and the Pacific Northwest. Clusters were associated with prescribing by VA-employed (vs. contracted) prescribers. Nurses with prescribing privileges were more likely to make a prescription for aripiprazole in cluster locations compared with psychiatrists. Primary care physicians were less likely.

CONCLUSIONS

Early prescribing of aripiprazole for bipolar disorder clustered geographically and was associated with prescriber subgroups. These methods support prospective surveillance of practice changes and identification of associated health system characteristics.

Railway suicide clusters: how common are they and what predicts them?

BACKGROUND

A growing number of studies have sought to detect clusters of all suicides, but few have sought to identify clusters of method-specific suicides.

METHODS

Data on railway suicides occurring in Victoria, Australia, between 2001 and 2012 were obtained from the National Coronial Information System. We used the Poisson discrete scan statistic to identify railway suicides that occurred close together in space and/or time. We then used a case-control design to compare clustered railway suicides with non-clustered railway suicides on a range of individual and neighbourhood factors.

RESULTS

We detected four spatial clusters that accounted for 35% of all railway suicides. Railway suicides by individuals who were hospitalised for mental illness had nearly double the odds of being in a cluster compared with those individuals who had never been hospitalised (OR 1.80, 95% CI 1.02 to 3.18). Higher frequency train services were associated with increased odds of being in a cluster (OR 1.11, 95% CI 1.03 to 1.19). No other predictors were associated with being in a cluster.

CONCLUSIONS

Railway suicides that occur in clusters warrant particular attention because of the ripple effect they can have for communities and the risk that they may lead to copycat acts. Railway suicide prevention strategies should consider the fact that these suicides can occur in clusters, particularly among individuals who had previous hospitalisations for mental illness or live in areas with high-frequency train services.

Spatial transmission and meteorological determinants of tuberculosis incidence in Qinghai Province, China: a spatial clustering panel analysis

BACKGROUND

Tuberculosis (TB) is the notifiable infectious disease with the second highest incidence in the Qinghai province, a province with poor primary health care infrastructure. Understanding the spatial distribution of TB and related environmental factors is necessary for developing effective strategies to control and further eliminate TB.

METHODS

Our TB incidence data and meteorological data were extracted from the China Information System of Disease Control and Prevention and statistical yearbooks, respectively. We calculated the global and local Moran's I by using spatial autocorrelation analysis to detect the spatial clustering of TB incidence each year. A spatial panel data model was applied to examine the associations of meteorological factors with TB incidence after adjustment of spatial individual effects and spatial autocorrelation.

RESULTS

The Local Moran's I method detected 11 counties with a significantly high-high spatial clustering (average annual incidence: 294/100 000) and 17 counties with a significantly low-low spatial clustering (average annual incidence: 68/100 000) of TB annual incidence within the examined five-year period; the global Moran's I values ranged from 0.40 to 0.58 (all P-values < 0.05). The TB incidence was positively associated with the temperature, precipitation, and wind speed (all P-values < 0.05), which were confirmed by the spatial panel data model. Each 10 °C, 2 cm, and 1 m/s increase in temperature, precipitation, and wind speed associated with 9 % and 3 % decrements and a 7 % increment in the TB incidence, respectively.

CONCLUSIONS

High TB incidence areas were mainly concentrated in south-western Qinghai, while low TB incidence areas clustered in eastern and north-western Qinghai. Areas with low temperature and precipitation and with strong wind speeds tended to have higher TB incidences.

Individual and area-level factors correlated with death by suicide in older adults

OBJECTIVE

To determine the influence of individual and area-level characteristics associated with suicide in older adults.

METHOD

This study used two complementary data sources. The first used administrative data from the Quebec Coroner's office and included information on suicide deaths in older adults aged 65years and over who died by suicide between 2000 and 2005 (n=903 persons). The second data source, which was used to identify the control group, came from a longitudinal study on seniors' health that was conducted in Quebec between 2004 and 2005 (n=2493 persons). Logistic regression analyses were used to test for associations between suicide and individual and area-level level characteristics.

RESULTS

Suicide was associated with male gender, age, the presence of a physical and mental disorder and the use of health services. At the area-level level, suicide was associated with a higher population density, concentration of men, lower rates of education and higher rate of unemployment. Gender specific analyses also showed different patterns of associations on suicide risk.

CONCLUSIONS

Suicide in older adults is associated with area-level and individual characteristics. This suggests that policies targeting only one level of risk factors are less likely to significantly influence suicide among this population.

Deprivation and suicide mortality across 424 neighborhoods in Seoul, South Korea: a Bayesian spatial analysis

OBJECTIVES

A 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.

METHODS

Neighborhood-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.

RESULTS

Suicide 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.

CONCLUSIONS

Finding from this study could be used to identify priority areas and to develop community-based programs for preventing suicide in Seoul, South Korea.