The spatial pattern of suicide in the US in relation to deprivation, fragmentation and rurality

Testing rurality as a moderator of associations between masculinity constructs, help-seeking, and firearm storage practices

INTRODUCTION

Self-reliance, emotional control, and honor ideology may prevent help-seeking when suicidal ideation emerges. Furthermore, these factors are associated with an increased likelihood of firearm ownership and unsecure storage, which could facilitate suicide attempts. The rurality of residence may impact these associations, as rural regions report increased independence, honor culture, and firearm prevalence. Therefore, this study examined how emotional control, self-reliance, and honor ideology relate to firearm storage and help-seeking for suicidal ideation, with rurality moderating these associations.

METHODS

Participants were 733 adults (63.6% female, 33.5% male, and 2.9% transgender/other) who reported past-month suicidal ideation. Analyses tested associations between emotional control, self-reliance, and honor ideology with help-seeking for suicidal ideation and firearm storage, with rurality moderating these associations.

RESULTS

The association of self-reliance and decreased help-seeking willingness for suicidal ideation was significant for those in non-urban areas. The association of emotional control and decreased help-seeking willingness for suicidal ideation was significant for those in urban areas. No variables predicted firearm storage.

CONCLUSIONS

Self-reliance and emotional control could be barriers for help-seeking regardless of gender identity that depend on rurality. Clinicians may target emotional control/self-reliance via strengths-based approaches with an emphasis on when these constructs could be maladaptive, as this could promote help-seeking.

The Spatio-Temporal Distribution of Suicide-related Emergency Calls in a European City: Age and Gender Patterns, and Neighborhood Influences

Objective: The aim of this study was to conduct a comprehensive spatio-temporal analysis of suicide-related emergency calls in the city of Valencia (Spain) over a six-year period. To this end we first examined age and gender patterns and, second, the influence of neighborhood characteristics on general and gender-specific spatio-temporal patterns of suicide-related emergency calls. Method: Geocoded data on suicide-related emergency calls between 2017 and 2022 (N = 10,030) were collected from the 112 emergency service in Valencia. Data were aggregated at the census block group level, used as a proxy for neighborhoods, and trimesters were considered as the temporal unit. Two set of analyses were performed: (1) demographic (age and gender) and temporal descriptive analyses and (2) general and gender-specific Bayesian spatio-temporal autoregressive models. Results: Descriptive analyses revealed a higher incidence of suicide-related emergency calls among females and an increase in calls among the 18-23 age group from 2020 onwards. The general spatio-temporal model showed higher levels of suicide-related emergency calls in neighborhoods characterized by lower education levels and population density, and higher residential mobility, aging population, and immigrant concentration. Relevant gender differences were also observed. A seasonal effect was noted, with a peak in calls during spring for females and summer for males. Conclusions: These findings highlight the need for comprehensive mental health targeted interventions and preventive strategies that account for gender-specific disparities, age-related vulnerabilities, and the specific characteristics of neighborhoods.

Area-level Measures of the Social Environment: Operationalization, Pitfalls, and Ways Forward

People's mental health is intertwined with the social environment in which they reside. This chapter explores approaches for quantifying the area-level social environment, focusing specifically on socioeconomic deprivation and social fragmentation. We discuss census data and administrative units, egocentric and ecometric approaches, neighborhood audits, social media data, and street view-based assessments. We close the chapter by discussing possible paths forward from associations between social environments and health to establishing causality, including longitudinal research designs and time-series social environmental indices.

Psychiatrist density and risk of suicide: a multilevel case-control study based on a national sample in Taiwan

AIM

No previous studies, to our knowledge, have investigated the association between psychiatrist density and suicide, accounting for individual- and area-level characteristics.

METHODS

We investigated all suicide cases in 2007-2017 identified from the national cause-of-death data files, with each suicide case matched to 10 controls by age and sex and each suicide case/control assigned to one of the 355 townships across Taiwan. Our primary outcome was the odds ratio (OR) of suicide and its 95% confidence interval (CI) estimated via multilevel models, which included both individual- and area-level characteristics. Townships with no psychiatrists were compared with the quartiles of townships with psychiatrists (density per 100,000 population): quartile 1 (Q1) (0.01-3.02); quartile 2 (Q2) (3.02-7.20); quartile 3 (Q3) (7.20-13.82); and quartile 4 (Q4) (>13.82).

RESULTS

A total of 40,930 suicide cases and 409,300 age- and sex-matched controls were included. We found that increased psychiatrist density was associated with decreased suicide risk (Q1: adjusted OR [aOR], 0.95 [95% CI, 0.90-1.01]; Q2: aOR, 0.90 [95% CI, 0.85-0.96]; Q3: aOR, 0.89 [95% CI, 0.83-0.94]; Q4: aOR, 0.89 [95% CI, 0.83-0.95]) after adjusting for individual-level characteristics (employment state, monthly income, physical comorbidities, and the diagnosis of psychiatric disorders) and area socioeconomic characteristics.

CONCLUSIONS

The psychiatrist density-suicide association suggests an effect of increased availability of psychiatric services on preventing suicide. Suicide prevention strategies could usefully focus on enhancing local access to psychiatric services.

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

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).

The association between social fragmentation and deaths attributable to alcohol, drug use, and suicide: Longitudinal evidence from a population-based sample of Canadian adults

BACKGROUND

Social fragmentation has been theorized and empirically associated with suicide in prior research. However, less is known about whether social fragmentation is associated with deaths attributed to alcohol use or drug use. This research examined the association between social fragmentation and risk for deaths attributable to alcohol use, drug use, and suicide (collectively known as deaths of despair) among Canadian adults.

METHODS

A weighted sample representing 15,324,645 Canadians within 288 census divisions between 2006 and 2019 was used. Mortality data from the Canadian Vital Statistics Database (alcoholic liver disease, drug use, and suicide) was linked with census division socioeconomic data from the 2006 Canadian census using the Canadian Census Health and Environment Cohorts. Social fragmentation at the census division was created based on the Congdon Index. Cox-proportional hazard regression with survey weights and the sandwich estimator were used to account for clustering of individuals (level-1) nested within census divisions (level-2).

RESULTS

After adjusting for individual and census division confounders, social fragmentation was positively associated with all-cause mortality (HR = 1.04; 95% CI: 1.02, 1.07), suicide (HR = 1.09; 95%CI: 1.01, 1.18), drug overdose related mortality (HR = 1.13; 95%CI: 1.03, 1.24), and deaths of despair (HR = 1.10; 95% CI: 1.04, 1.16), and not significantly associated with alcohol related liver disease (HR = 1.06; 95% CI: 0.91, 1.23).

CONCLUSION

Social fragmentation is associated with an increased hazard of deaths of despair among Canadian adults. Efforts to improve social cohesion in areas that are highly socially fragmented need to be evaluated.

Longitudinal associations of neighbourhood environmental exposures with mental health problems during adolescence: Findings from the TRAILS study

BACKGROUND

Cross-sectional studies have found associations between neighbourhood environments and adolescent mental health, but the few longitudinal studies mainly focused on single exposure-based analyses and rarely assessed the mental health associations with environmental changes.

OBJECTIVES

We assessed longitudinal within- and between-person associations of multiple neighbourhood time-varying physical and social environmental exposures with externalising and internalising problems throughout adolescence.

METHODS

We used four waves of TRAILS (Tracking Adolescents' Individual Lives Survey) data on self-reported externalising and internalising problems at ages 11, 13, 16, and 19 among 2,135 adolescents in the Netherlands. We measured residence-based time-varying environmental exposures, including green space, air pollution (fine particulate matter (PM2.5)), noise, deprivation, and social fragmentation. We fitted random-effect within-between regression models to assess the environment-mental health associations.

RESULTS

At the within-person level, an interquartile range (IQR) increase in PM2.5 was associated with a 0.056 IQR (95% CI: 0.014, 0.099) increase in externalising problems, while an IQR social fragmentation increase was associated with a 0.010 IQR (95% CI: -0.020, -0.001) decrease in externalising problems. Stratification revealed that the association with PM2.5 was significant only for movers, whereas the association with social fragmentation remained only for non-movers. At the between-person level, an IQR higher noise was associated with a 0.100 IQR (95% CI: 0.031, 0.169) more externalising problems, while higher deprivation (β = 0.080; 95% CI: 0.022, 0.138) and lower fragmentation (β = -0.073; 95% CI: -0.128, -0.018) were associated with more internalising problems. We also observed positive between-person associations between PM2.5, noise, and internalising problems, but both associations were unstable due to the high PM2.5-noise correlation. Further, we observed a non-linear between-person PM2.5-externalising problems association turning positive when PM2.5 > 15 µg/m3. Null associations were found for green space.

CONCLUSION

Our findings suggested that air pollution, noise, and neighbourhood deprivation are risk factors for adolescent mental health. Not only exposure levels but also exposure changes matter for adolescent mental health.

County-level estimates of suicide mortality in the USA: a modelling study

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.

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.

[Geographies of suicide in Argentina: a spatial ecological study during 1999-2003 and 2008-2012 periods]

OBJECTIVE

The aim of this study was to describe the geographical distribution and the role of sociodemographic factors on mortality by suicides, according to sex and age groups, in Argentina during the periods 1999-2003 and 2008-2012.

METHODS

The role of sociodemographic factors on mortality by suicides and their geographical distribution were analyzed by means of multiple spatial regressions. Three independent variables were included: an index of social fragmentation, a poverty index and population density, as an indicator of the level of rurality.

RESULTS

Social fragmentation and suicide were directly related in men 10-59 years old and women 10-29 years old during 1999-2003. During 2008-2012, the risk of suicide was higher in areas of low population density, except for women aged 10-29 years.

CONCLUSIONS

The results obtained in this study support the hypothesis of social fragmentation as a phenomenon associated with the risk of suicide in departments of Argentina, but also support the hypothesis of an increased risk of suicide in rural areas. Suicide prevention measures could focus on policies that promote social integration, especially in the young population, as well as greater cohesion of rural areas.

The differential impacts of social deprivation and social fragmentation on suicides: A lesson from Hong Kong

INTRODUCTION

Little research has conducted to examine the association between social deprivation and social fragmentation, overall and method-specific suicide risk, and how these associations may change over time. This study investigated the association between social deprivation and social fragmentation with overall and method-specific suicide in Hong Kong from 1999 to 2018.

METHODS

Suicide death data of each small tertiary planning unit (STPU) was obtained from the Census and Statistics Department of Hong Kong. Socio-economic characteristics in STPU level were obtained from Census and Bi-census. Exploratory principal component analysis was used to construct the social deprivation (SDI) and social fragmentation indices (SFI) based on the socio-economic characteristics. Bayesian hierarchical modelling was conducted to explore the association between SDI and SFI with overall and method-specific suicide over time, controlling for population density and male-to-female ratio.

RESULTS

Higher risk of suicide was generally observed around Kowloon Peninsula and some parts in the Northern, Northwestern and Southwestern areas depending on methods. The effect of SDI and SFI on suicide risk varied by years and methods. In 2014-2018, for every 10% increase in SDI, the suicide risk for overall, jumping, hanging, and charcoal burning elevated by 22% (95%Crl = 10%-37%), 26% (95%Crl = 12%-41%), 31% (95%Crl = 14%-51%), and 21% (95%Crl = 4%-42%) respectively.

CONCLUSION

Spatial variations and effects of SDI and SFI on overall and method-specific suicide risks varied by different periods. SDI was observed to be a stronger factor in the recent years. Situations should be monitored, and interventions should be implemented and adjusted accordingly to the changes.

Associations between social fragmentation, socioeconomic deprivation and suicide risk across 1887 municipalities in Japan, 2009-2017: a spatial analysis using the Bayesian hierarchical model

OBJECTIVE

Previous studies have indicated that spatial variation in suicide mortality is associated with area-specific socioeconomic characteristics, such as socioeconomic deprivation and social fragmentation. However, most of these studies have been conducted in the West and findings from Asian countries are limited. This study aims to investigate associations between socioeconomic characteristics and suicide mortality rates across 1887 municipalities in Japan between 2009 and 2017. We also assessed these associations by gender and age group.

METHODS

Suicide data were obtained from the suicide statistics of the Ministry of Health, Labour and Welfare in Japan and included information on the number of suicides by gender, age and municipality location. Social fragmentation, socioeconomic deprivation and urbanicity were used as socioeconomic characteristics in this study and were created from survey data obtained from the 2010 census. Bayesian hierarchical models were used to examine associations between socioeconomic characteristics and suicide risk.

RESULTS

Suicide rates were significantly higher in municipalities with higher levels of deprivation, with a rate ratio of 1.13 (95% credible interval: 1.10 to 1.17) in the highest quartile compared with the lowest. Higher levels of urbanicity had significantly lower suicide rates, with a rate ratio of 0.79 (95% credible interval: 0.77 to 0.82) in the highest quartile compared with the lowest. However, associations between exposures and suicide varied considerably by gender and age. Among both men and women aged 0-39 years, fragmentation was significantly associated with suicide, with rate ratios of 1.07 and 1.15 for men and women, respectively, in the highest quartile compared with the lowest.

CONCLUSION

Suicide prevention in Japan should particularly focus on areas with high levels of deprivation or low levels of urbanicity. Furthermore, young Japanese people residing in the most fragmented municipalities were also at high risk of suicide, and appropriate measures need to be taken.

Spatial and space-time clusters of suicides in the contiguous USA (2000-2019)

The present study investigates the spatiotemporal variations in suicide mortality and tests associations between several covariates and suicides for the years 2000-2019 in the contiguous USA. The epidemiological disease surveillance software (SaTScan^TM) was used to identify spatiotemporal variations in suicide mortality rates and to test for significant spatial and space-time clusters with elevated relative suicide risk. The analysis was done with age-adjusted suicide mortality counts data from the Centers for Disease Control (CDC) with (International Classification of Diseases) ICD-10 codes. Specifically, data with codes ICD-10 codes X60-X84.9 and Y87.0, plus ICD-10 113 codes from the CDC, was used. Fourteen significant spatial clusters and five significant space-time clusters of suicide in the contiguous USA were found, including nine significant bivariate spatial clusters of suicide deaths and opioid deaths. Based on these data, there exist significant and non-random suicide mortality clusters after adjusting for multiple covariates or risk factors. The covariates studied provide evidence to develop a better understanding of possible associations in geographical areas where the suicide mortality rates are higher than expected. In addition, there is a significant association between several of the studied risk factors and suicide mortality. While most suicide clusters are also opioid clusters, there exist some clusters with high opioid deaths that are not suicide clusters. These results have the potential to provide a scientific framework that is based on surveillance, allowing health agencies to intervene and reduce elevated rates of suicides in selected counties in the U.S. The study is limited due to the resolution of the data at the county level, and some covariate data was unavailable for the entire period of the study.

[Intra-urban differentials of suicide: the role of social fragmentation in Argentina]

El suicidio constituye una de las principales causas de muerte por lesiones en Argentina y existen pocos estudios que analicen las variaciones geográficas intra-urbanas en países en desarrollo. El objetivo de este estudio fue analizar la relación entre el suicidio y el nivel socioeconómico y la fragmentación social en áreas pequeñas de la Ciudad Autónoma de Buenos Aires (CABA) durante el período 2011-2015. Se realizó un estudio ecológico utilizando datos sobre registros de suicidio en población residente de la CABA disponibles en el Ministerio de Seguridad de la Nación. Se llevó a cabo una regresión múltiple espacial para poner a prueba la relación entre el suicidio e indicadores de nivel socioeconómico y de fragmentación social por área. El riesgo de suicidio estuvo asociado positivamente a mayores índices de fragmentación social, mientras no mostró relación con el índice de pobreza. Los resultados de este estudio apoyan la hipótesis de fragmentación social como un factor asociado positivamente al aumento del suicidio a nivel intra-urbano en ciudades de países en desarrollo.

Analysing spatial and temporal dynamics of suicide in South Korea: An application of the dynamic spatial panel data model

This study examines the relationship between the suicide mortality rate and structural covariates in South Korea from 2008 to 2017 under Durkheim's theory of suicide. It applies the dynamic spatial panel data model to explore both spatial and temporal aspects of the suicide phenomena recognising statistical limitations in previous suicide research based on either cross-sectional or longitudinal methodology. The results demonstrate that the suicide mortality rates in South Korea are spatially and temporally dependent on those of neighbouring units or its own time-lagged suicide mortality rates. Moreover, this study estimates that the divorce rate, unemployment rate and land price index, which are assumed to be proxies of social integration and regulation, significantly impact the suicide mortality rates. The results imply that deteriorating socioeconomic conditions are risk factors for the suicide mortality rate and suggests implementing policies to alleviate the high level of social disintegration caused by Korea's deteriorating socioeconomic conditions.

Longitudinal exposure assessments of neighbourhood effects in health research: What can be learned from people's residential histories?

Health research into neighbourhood effects has generally examined neighbourhoods cross-sectionally, ignoring the fact that neighbourhood exposures might accumulate over people's lives and affect health outcomes later in life. Using longitudinal Dutch register data with complete 15-year residential address histories, we examined whether health effects of neighbourhood socioeconomic characteristics differ between cumulative and current exposures. We illustrated these differences between exposure assessments using suicide mortality among middle-aged adults. All suicides aged 40-64 years between 2012 and 2016 were matched with 10 random controls in a nested case-control design. We measured neighbourhood exposures longitudinally for circular buffers around residential addresses at the current address and through three accumulative measures, each incorporating the residential address history with increasing detail. Covariate-adjusted conditional logistic regressions were used to assess associations between suicide and neighbourhood social fragmentation, population density and unemployment rate. Our results showed that total and male suicide mortality was significantly lower in highly fragmented neighbourhoods when using accumulative exposures, but not when using the current residential address. However, we observed few differences in coefficients between exposures assessments for neighbourhood urbanicity and unemployment rate. None of the neighbourhood characteristics showed evidence that detailed cumulative exposures were a stronger predictor of suicide compared to more crude measures. Our findings provide little evidence that socioeconomic neighbourhood characteristics measured cumulatively along people's residential histories are stronger predictors of suicide mortality than cross-sectional exposures.

US Firearm-Related Mortality: National, State, And Population Trends, 1999-2017

Nationwide firearm-related mortality rates increased in 2015-17 after remaining relatively stable in 1999-2014. Recent increases are reflected across most states and demographics to varying degrees, which suggests a worsening epidemic of firearm mortality that is geographically and demographically broad. In both time periods the fractions of firearm deaths due to suicide and homicide remained consistent.

The impact of gun violence restraining order laws in the U.S. and firearm suicide among older adults: a longitudinal state-level analysis, 2012-2016

BACKGROUND

Older adults complete suicide at a disproportionately higher rate compared to the general population, with firearms the most common means of suicide. State gun laws may be a policy remedy. Less is known about Gun Violence Restricting Order (GVRO) laws, which allow for removal of firearms from people deemed to be a danger to themselves or others, and their effects on suicide rates among older adults. The purpose of this study was to examine the association of state firearm laws with the incidence of firearm, non-firearm-related, and total suicide among older adults, with a focus on GVRO laws.

METHODS

This is a longitudinal study of US states using data from 2012 to 2016. The outcome variables were firearm, non-firearm and total suicide rates among older adults. Predictor variables were [1] total number of gun laws to assess for impact of overall firearm legislation at the state level, and [2] GVRO laws.

RESULTS

The total number of firearm laws, as well as GVRO laws, were negatively associated with firearm-related suicide rate among older adults ages 55-64 and > 65 years-old (p < 0.001). There was a small but significant positive association of total number of firearm laws to non-firearm-related suicide rates and a negative association with total suicide rate. GVRO laws were not significantly associated with non-firearm-related suicide and were negatively associated with total suicide rate.

CONCLUSION

Stricter firearm legislation, as well as GVRO laws, are protective against firearm-relate suicides among older adults.

Relation between neighborhood socio-economic characteristics and social cohesion, social control, and collective efficacy: Findings from the Boston Neighborhood Study

Little is known about the determinants of collective efficacy, a neighborhood social process comprised of social cohesion and social control, which has shown to be beneficially associated with health. Our goal was to identify determinants of collective efficacy, social cohesion and social control. We used data collected from the Boston Neighborhood Survey, a cross-sectional survey conducted in 38 Boston neighborhoods in 2010 (n = 1710). We used multi-level logistic regression analyses to identify the relationship between the neighborhood-level characteristics and collective efficacy, social cohesion, and social control. High social fragmentation was associated with a decreased likelihood of reporting high collective efficacy (OR = 0.71, 95% CI = 0.54,0.95). and high social cohesion (OR = 0.63, 95% CI = 0.46, 0.86). High social fragmentation (OR = 0.80, 95% CI = 0.64, 0.99), and moderate economic deprivation (OR = 0.64, 95% CI = 0.47, 0.88) were associated with a decreased likelihood of reporting high social control, while high trust in police was associated with an increased likelihood in reporting high social control (OR = 1.86, 95% CI = 1.16, 3.00). Further research should be undertaken to better understand the direction of effect of these associations and how interventions to promote social processes can utilize these findings to improve health.

•

We tested the association between neighborhood characteristics and social processes.

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Social Fragmentation was associated with decreased odds for Social Cohesion.

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Trust in Police was associated with increased odds for Social Control.

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Social Fragmentation was associated with decreased odds for Collective Efficacy.

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Future work should be conducted to determine if these associations are causal.

Contextual Factors Associated With County-Level Suicide Rates in the United States, 1999 to 2016

IMPORTANCE

Understanding geographic and community-level factors associated with suicide can inform targeted suicide prevention efforts.

OBJECTIVES

To estimate suicide rates and trajectories, assess associated county-level contextual factors, and explore variation across the rural-urban continuum.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study included all individuals aged 25 to 64 years who died by suicide from January 1, 1999, to December 31, 2016, in the United States. Spatial analysis was used to map excess risk of suicide, and longitudinal random-effects models using negative binomial regression tested associations of contextual variables with suicide rates as well as interactions among county-level contextual variables. Data analyses were conducted between January 2019 and July 2019.

EXPOSURE

County of residence.

MAIN OUTCOMES AND MEASURES

Three-year county suicide rates during an 18-year period stratified by rural-urban location.

RESULTS

Between 1999 and 2016, 453 577 individuals aged 25 to 64 years died by suicide in the United States. Decedents were primarily male (349 082 [77.0%]) with 101 312 (22.3%) aged 25 to 34 years, 120 157 (26.5%) aged 35 to 44 years, 136 377 (30.1%) aged 45 to 54 years, and 95 771 (21.1%) aged 55 to 64 years. Suicide rates were higher and increased more rapidly in rural than in large metropolitan counties. The highest deprivation quartile was associated with higher suicide rates compared with the lowest deprivation quartile, especially in rural areas, although this association declined during the period studied (rural, 1999-2001: incidence rate ratio [IRR], 1.438; 95% CI, 1.319-1.568; P < .001; large metropolitan, 1999-2001: 1.208; 95% CI, 1.149-1.270; P < .001; rural, 2014-2016: IRR, 1.121; 95% CI, 1.032-1.219; P = .01; large metropolitan, 2014-2016: IRR, 0.942; 95% CI, 0.887-1.001; P = .06). The presence of more gun shops was associated with an increase in county-level suicide rates in all county types except the most rural (rural: IRR, 1.001; 95% CI, 0.999-1.004; P = .40; micropolitan: IRR, 1.005; 95% CI, 1.002-1.007; P < .001; small metropolitan: IRR, 1.010; 95% CI, 1.006-1.014; P < .001; large metropolitan: IRR, 1.012; 95% CI, 1.006-1.018; P < .001). High social capital was associated with lower suicide rates than low social capital (IRR, 0.917; 95% CI, 0.891-0.943; P < .001). High social fragmentation, an increasing percentage of the population without health insurance, and an increasing percentage of veterans in a county were associated with higher suicide rates (high social fragmentation: IRR, 1.077; 95% CI, 1.050-1.103; P < .001; percentage of population without health insurance: IRR, 1.005; 95% CI, 1.004-1.006; P < .001; percentage of veterans: IRR, 1.025; 95% CI, 1.021-1.028; P < .001).

CONCLUSIONS AND RELEVANCE

This study found that suicide rates have increased across the nation and most rapidly in rural counties, which may be more sensitive to the impact of social deprivation than more metropolitan counties. Improving social connectedness, civic opportunities, and health insurance coverage as well as limiting access to lethal means have the potential to reduce suicide rates across the rural-urban continuum.

Subjective wellbeing, suicide and socioeconomic factors: an ecological analysis in Hong Kong

AIMS

There has recently been an increased interest in mental health indicators for the monitoring of population wellbeing, which is among the targets of Sustainable Development Goals adopted by the United Nations. Levels of subjective wellbeing and suicide rates have been proposed as indicators of population mental health, but prior research is limited.

METHODS

Data on individual happiness and life satisfaction were sourced from a population-based survey in Hong Kong (2011). Suicide data were extracted from Coroner's Court files (2005-2013). Area characteristic variables included local poverty rate and four factors derived from a factor analysis of 21 variables extracted from the 2011 census. The associations between mean happiness and life satisfaction scores and suicide rates were assessed using Pearson correlation coefficient at two area levels: 18 districts and 30 quantiles of large street blocks (LSBs; n = 1620). LSB is a small area unit with a higher level of within-unit homogeneity compared with districts. Partial correlations were used to control for area characteristics.

RESULTS

Happiness and life satisfaction demonstrated weak inverse associations with suicide rate at the district level (r = -0.32 and -0.36, respectively) but very strong associations at the LSB quantile level (r = -0.83 and -0.84, respectively). There were generally very weak or weak negative correlations across sex/age groups at the district level but generally moderate to strong correlations at the LSB quantile level. The associations were markedly attenuated or became null after controlling for area characteristics.

CONCLUSIONS

Subjective wellbeing is strongly associated with suicide at a small area level; socioeconomic factors can largely explain this association. Socioeconomic factors could play an important role in determining the wellbeing of the population, and this could inform policies aimed at enhancing population wellbeing.

What calls for service tell us about suicide: A 7-year spatio-temporal analysis of neighborhood correlates of suicide-related calls

Previous research has shown that neighborhood-level variables such as social deprivation, social fragmentation or rurality are related to suicide risk, but most of these studies have been conducted in the U.S. or northern European countries. The aim of this study was to analyze the spatio-temporal distribution of suicide in a southern European city (Valencia, Spain), and determine whether this distribution was related to a set of neighborhood-level characteristics. We used suicide-related calls for service as an indicator of suicide cases (n = 6,537), and analyzed the relationship of the outcome variable with several neighborhood-level variables: economic status, education level, population density, residential instability, one-person households, immigrant concentration, and population aging. A Bayesian autoregressive model was used to study the spatio-temporal distribution at the census block group level for a 7-year period (2010–2016). Results showed that neighborhoods with lower levels of education and population density, and higher levels of residential instability, one-person households, and an aging population had higher levels of suicide-related calls for service. Immigrant concentration and economic status did not make a relevant contribution to the model. These results could help to develop better-targeted community-level suicide prevention strategies.

Diving into the consumer nutrition environment: A Bayesian spatial factor analysis of neighborhood restaurant environment

Neighborhood restaurant environment (NRE) plays a vital role in shaping residents' eating behaviors. While NRE 'healthfulness' is a multi-facet concept, most studies evaluate it based only on restaurant type, thus largely ignoring variations of in-restaurant features. In the few studies that do account for such features, healthfulness scores are simply averaged over accessible restaurants, thereby concealing any uncertainty that attributed to neighborhoods' size or spatial correlation. To address these limitations, this paper presents a Bayesian Spatial Factor Analysis for assessing NRE healthfulness in the city of Kitchener, Canada. Several in-restaurant characteristics are included. By treating NRE healthfulness as a spatially correlated latent variable, the adopted modeling approach can: (i) identify specific indicators most relevant to NRE healthfulness, (ii) provide healthfulness estimates for neighborhoods without accessible restaurants, and (iii) readily quantify uncertainties in the healthfulness index. Implications of the analysis for intervention program development and community food planning are discussed.

Spatial clustering of fatal, and non-fatal, suicide in new South Wales, Australia: implications for evidence-based prevention

BACKGROUND

Rates of suicide appear to be increasing, indicating a critical need for more effective prevention initiatives. To increase the efficacy of future prevention initiatives, we examined the spatial distribution of suicide deaths and suicide attempts in New South Wales (NSW), Australia, to identify where high incidence 'suicide clusters' were occurring. Such clusters represent candidate regions where intervention is critically needed, and likely to have the greatest impact, thus providing an evidence-base for the targeted prioritisation of resources.

METHODS

Analysis is based on official suicide mortality statistics for NSW, provided by the Australian Bureau of Statistics, and hospital separations for non-fatal intentional self-harm, provided through the NSW Health Admitted Patient Data Collection at a Statistical Area 2 (SA2) geography. Geographical Information System (GIS) techniques were applied to detect suicide clusters occurring between 2005 and 2013 (aggregated), for persons aged over 5 years. The final dataset contained 5466 mortality and 86,017 non-fatal intentional self-harm cases.

RESULTS

In total, 25 Local Government Areas were identified as primary or secondary likely candidate regions for intervention. Together, these regions contained approximately 200 SA2 level suicide clusters, which represented 46% (n = 39,869) of hospital separations and 43% (n = 2330) of suicide deaths between 2005 and 2013. These clusters primarily converged on the Eastern coastal fringe of NSW.

CONCLUSIONS

Crude rates of suicide deaths and intentional self-harm differed at the Local Government Areas (LGA) level in NSW. There was a tendency for primary suicide clusters to occur within metropolitan and coastal regions, rather than rural areas. The findings demonstrate the importance of taking geographical variation of suicidal behaviour into account, prior to development and implementation of prevention initiatives, so that such initiatives can target key problem areas where they are likely to have maximal impact.

Spatio-Temporal Analysis of Suicide-Related Emergency Calls

Considerable effort has been devoted to incorporate temporal trends in disease mapping. In this line, this work describes the importance of including the effect of the seasonality in a particular setting related with suicides. In particular, the number of suicide-related emergency calls is modeled by means of an autoregressive approach to spatio-temporal disease mapping that allows for incorporating the possible interaction between both temporal and spatial effects. Results show the importance of including seasonality effect, as there are differences between the number of suicide-related emergency calls between the four seasons of each year.

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.

Do marginalized neighbourhoods have less healthy retail food environments? An analysis using Bayesian spatial latent factor and hurdle models

Background

Findings of whether marginalized neighbourhoods have less healthy retail food environments (RFE) are mixed across countries, in part because inconsistent approaches have been used to characterize RFE ‘healthfulness’ and marginalization, and researchers have used non-spatial statistical methods to respond to this ultimately spatial issue.

Methods

This study uses in-store features to categorize healthy and less healthy food outlets. Bayesian spatial hierarchical models are applied to explore the association between marginalization dimensions and RFE healthfulness (i.e., relative healthy food access that modelled via a probability distribution) at various geographical scales. Marginalization dimensions are derived from a spatial latent factor model. Zero-inflation occurring at the walkable-distance scale is accounted for with a spatial hurdle model.

Results

Neighbourhoods with higher residential instability, material deprivation, and population density are more likely to have access to healthy food outlets within a walkable distance from a binary ‘have’ or ‘not have’ access perspective. At the walkable distance scale however, materially deprived neighbourhoods are found to have less healthy RFE (lower relative healthy food access).

Conclusion

Food intervention programs should be developed for striking the balance between healthy and less healthy food access in the study region as well as improving opportunities for residents to buy and consume foods consistent with dietary recommendations.

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.

Neighbourhood social fragmentation and the mental health of children in poverty

Using data from 7,776 Millennium Cohort Study children in England, we examined the role of neighbourhood social fragmentation in trajectories of emotional/behavioural problems at ages three, five and seven, and in moderating the association of children's emotional/behavioural problems with neighbourhood poverty, family poverty and adverse family events. Allowing for key background characteristics, social fragmentation generally added little to explain child outcomes, but there were fewer conduct problems among children in poor neighbourhoods with less fragmentation. Surprisingly, in less fragmented neighbourhoods poor families tended to feel less safe and more distressed, which was associated with children's conduct problems.

The relationship between neighborhood socioeconomic characteristics and physical inactivity among adolescents living in Boston, Massachusetts

OBJECTIVES

We sought to determine whether the socioeconomic environment was associated with no participation in physical activity among adolescents in Boston, Massachusetts.

METHODS

We used cross-sectional data from 1878 urban adolescents living in 38 neighborhoods who participated in the 2008 Boston Youth Survey, a biennial survey of high school students (aged 14-19 years). We used multilevel multiple regression models to determine the association between neighborhood-level exposures of economic deprivation, social fragmentation, social cohesion, danger and disorder, and students' reports of no participation in physical activity in the previous week.

RESULTS

High social fragmentation within the residential neighborhood was associated with an increased likelihood of being inactive (odds ratio = 1.53; 95% confidence interval = 1.14, 2.05). No other neighborhood exposures were associated with physical inactivity.

CONCLUSIONS

Social fragmentation might be an important correlate of physical inactivity among youths living in urban settings. Interventions might be needed to assist youths living in unstable neighborhoods to be physically active.

Socio-environmental drivers and suicide in Australia: Bayesian spatial analysis

BACKGROUND

The impact of socio-environmental factors on suicide has been examined in many studies. Few of them, however, have explored these associations from a spatial perspective, especially in assessing the association between meteorological factors and suicide. This study examined the association of meteorological and socio-demographic factors with suicide across small areas over different time periods.

METHODS

Suicide, population and socio-demographic data (e.g., population of Aboriginal and Torres Strait Islanders (ATSI), and unemployment rate (UNE) at the Local Government Area (LGA) level were obtained from the Australian Bureau of Statistics for the period of 1986 to 2005. Information on meteorological factors (rainfall, temperature and humidity) was supplied by Australian Bureau of Meteorology. A Bayesian Conditional Autoregressive (CAR) Model was applied to explore the association of socio-demographic and meteorological factors with suicide across LGAs.

RESULTS

In Model I (socio-demographic factors), proportion of ATSI and UNE were positively associated with suicide from 1996 to 2000 (Relative Risk (RR)ATSI = 1.0107, 95% Credible Interval (CI): 1.0062-1.0151; RRUNE = 1.0187, 95% CI: 1.0060-1.0315), and from 2001 to 2005 (RRATSI = 1.0126, 95% CI: 1.0076-1.0176; RRUNE = 1.0198, 95% CI: 1.0041-1.0354). Socio-Economic Index for Area (SEIFA) and IND, however, had negative associations with suicide between 1986 and 1990 (RRSEIFA = 0.9983, 95% CI: 0.9971-0.9995; RRATSI = 0.9914, 95% CI: 0.9848-0.9980). Model II (meteorological factors): a 1°C higher yearly mean temperature across LGAs increased the suicide rate by an average by 2.27% (95% CI: 0.73%, 3.82%) in 1996-2000, and 3.24% (95% CI: 1.26%, 5.21%) in 2001-2005. The associations between socio-demographic factors and suicide in Model III (socio-demographic and meteorological factors) were similar to those in Model I; but, there is no substantive association between climate and suicide in Model III.

CONCLUSIONS

Proportion of Aboriginal and Torres Strait Islanders, unemployment and temperature appeared to be statistically associated with of suicide incidence across LGAs among all selected variables, especially in recent years. The results indicated that socio-demographic factors played more important roles than meteorological factors in the spatial pattern of suicide incidence.

Spatial clusters of suicide in Australia

BACKGROUND

Understanding the spatial distribution of suicide can inform the planning, implementation and evaluation of suicide prevention activity. This study explored spatial clusters of suicide in Australia, and investigated likely socio-demographic determinants of these clusters.

METHODS

National suicide and population data at a statistical local area (SLA) level were obtained from the Australian Bureau of Statistics for the period of 1999 to 2003. Standardised mortality ratios (SMR) were calculated at the SLA level, and Geographic Information System (GIS) techniques were applied to investigate the geographical distribution of suicides and detect clusters of high risk in Australia.

RESULTS

Male suicide incidence was relatively high in the northeast of Australia, and parts of the east coast, central and southeast inland, compared with the national average. Among the total male population and males aged 15 to 34, Mornington Shire had the whole or a part of primary high risk cluster for suicide, followed by the Bathurst-Melville area, one of the secondary clusters in the north coastal area of the Northern Territory. Other secondary clusters changed with the selection of cluster radius and age group. For males aged 35 to 54 years, only one cluster in the east of the country was identified. There was only one significant female suicide cluster near Melbourne while other SLAs had very few female suicide cases and were not identified as clusters. Male suicide clusters had a higher proportion of Indigenous population and lower median socio-economic index for area (SEIFA) than the national average, but their shapes changed with selection of maximum cluster radii setting.

CONCLUSION

This study found high suicide risk clusters at the SLA level in Australia, which appeared to be associated with lower median socio-economic status and higher proportion of Indigenous population. Future suicide prevention programs should focus on these high risk areas.