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.

MutateX: an automated pipeline for in silico saturation mutagenesis of protein structures and structural ensembles.

Mutations, which result in amino acid substitutions, influence the stability of proteins and their binding to biomolecules. A molecular understanding of the effects of protein mutations is both of biotechnological and medical relevance. Empirical free energy functions that quickly estimate the free energy change upon mutation (ΔΔG) can be exploited for systematic screenings of proteins and protein complexes. In silico saturation mutagenesis can guide the design of new experiments or rationalize the consequences of known mutations. Often software such as FoldX, while fast and reliable, lack the necessary automation features to apply them in a high-throughput manner. We introduce MutateX, a software to automate the prediction of ΔΔGs associated with the systematic mutation of each residue within a protein, or protein complex to all other possible residue types, using the FoldX energy function. MutateX also supports ΔΔG calculations over protein ensembles, upon post-translational modifications and in multimeric assemblies. At the heart of MutateX lies an automated pipeline engine that handles input preparation, parallelization and outputs publication-ready figures. We illustrate the MutateX protocol applied to different case studies. The results of the high-throughput scan provided by our tools can help in different applications, such as the analysis of disease-associated mutations, to complement experimental deep mutational scans, or assist the design of variants for industrial applications. MutateX is a collection of Python tools that relies on open-source libraries. It is available free of charge under the GNU General Public License from https://github.com/ELELAB/mutatex.

The Spatial Overlap of Police Calls Reporting Street-Level and Behind-Closed-Doors Crime: A Bayesian Modeling Approach.

Traditionally, intimate-partner violence has been considered a special type of crime that occurs behind closed doors, with different characteristics from street-level crime. The aim of this study is to analyze the spatial overlap of police calls reporting street-level and behind-closed-doors crime. We analyzed geocoded police calls in the 552 census-block groups of the city of Valencia, Spain, related to street-level crime (N = 26,624) and to intimate-partner violence against women (N = 11,673). A Bayesian joint model was run to analyze the spatial overlap. In addition, two Bayesian hierarchical models controlled for different neighborhood characteristics to analyze the relative risks. Results showed that 66.5% of the total between-area variation in risk of reporting street-level crime was captured by a shared spatial component, while for reporting IPVAW the shared component was 91.1%. The log relative risks showed a correlation of 0.53, with 73.6% of the census-block groups having either low or high values in both outcomes, and 26.4% of the areas with mismatched risks. Maps of the shared component and the relative risks are shown to detect spatial differences. These results suggest that although there are some spatial differences between police calls reporting street-level and behind-closed-doors crime, there is also a shared distribution that should be considered to inform better-targeted police interventions.

AMBRA1 regulates cyclin D to guard S-phase entry and genomic integrity.

Mammalian development, adult tissue homeostasis and the avoidance of severe diseases including cancer require a properly orchestrated cell cycle, as well as error-free genome maintenance. The key cell-fate decision to replicate the genome is controlled by two major signalling pathways that act in parallel-the MYC pathway and the cyclin D-cyclin-dependent kinase (CDK)-retinoblastoma protein (RB) pathway1,2. Both MYC and the cyclin D-CDK-RB axis are commonly deregulated in cancer, and this is associated with increased genomic instability. The autophagic tumour-suppressor protein AMBRA1 has been linked to the control of cell proliferation, but the underlying molecular mechanisms remain poorly understood. Here we show that AMBRA1 is an upstream master regulator of the transition from G1 to S phase and thereby prevents replication stress. Using a combination of cell and molecular approaches and in vivo models, we reveal that AMBRA1 regulates the abundance of D-type cyclins by mediating their degradation. Furthermore, by controlling the transition from G1 to S phase, AMBRA1 helps to maintain genomic integrity during DNA replication, which counteracts developmental abnormalities and tumour growth. Finally, we identify the CHK1 kinase as a potential therapeutic target in AMBRA1-deficient tumours. These results advance our understanding of the control of replication-phase entry and genomic integrity, and identify the AMBRA1-cyclin D pathway as a crucial cell-cycle-regulatory mechanism that is deeply interconnected with genomic stability in embryonic development and tumorigenesis.

Chronic high risk of intimate partner violence against women in disadvantaged neighborhoods: An eight-year space-time analysis.

We conducted a small-area ecological longitudinal study to analyze neighborhood contextual influences on the spatio-temporal variations in intimate partner violence against women (IPVAW) risk in a southern European city over an eight-year period. We used geocoded data of IPVAW cases with associated protection orders (n = 5867) in the city of Valencia, Spain (2011-2018). The city's 552 census block groups were used as the neighborhood units. Neighborhood-level covariates were: income, education, immigrant concentration, residential instability, alcohol outlet density, and criminality. We used a Bayesian autoregressive approach to spatio-temporal disease mapping. Neighborhoods with low levels of income and education and high levels of residential mobility and criminality had higher relative risk of IPVAW. Spatial patterns of high risk of IPVAW persisted over time during the eight-year period analyzed. Areas of stable low risk and with increasing or decreasing risk were also identified. Our findings link neighborhood disadvantage to the existence and persistence over time of spatial inequalities in IPVAW risk, showing that high risk of IPVAW can become chronic in disadvantaged neighborhoods. Our analytic approach provides specific risk estimates at the small-area level that are informative for intervention purposes, and can be useful to assess the effectiveness of prevention efforts in reducing IPVAW.

Disadvantaged neighborhoods and the spatial overlap of substantiated and unsubstantiated child maltreatment referrals.

BACKGROUND: Considerable debate exists on whether the substantiation decision is a reliable measure for rates of maltreatment. Studies have shown that risks among children victims of maltreatment versus children investigated but unsubstantiated are similar. OBJECTIVE: This paper aims to respond to two research questions: (1) Do most child maltreatment referrals, substantiated and unsubstantiated, come from the same neighborhoods? (2) Do substantiated and unsubstantiated referrals share the same neighborhood risk factors? PARTICIPANTS AND SETTINGS: We used geocoded data from substantiated (n = 1799) and unsubstantiated (n = 1638) child maltreatment referrals in Valencia, Spain (2004-2015). As the neighborhood proxy, we used 552 Census block groups. Neighborhood characteristics analyzed were: socioeconomic status, immigration concentration, residential instability, and public disorder and crime. METHODS: To study the geographical overlap of child maltreatment referrals, a Bayesian joint modeling approach was used. To analyze the influence of neighborhood-level characteristics on risk, we used a Bayesian random-effects modeling approach. RESULTS: For substantiated child maltreatment referrals, 90 % of the total between-area variation in risk is captured by the shared component, while for unsubstantiated child maltreatment referrals, the shared component was 88 %. The correlation between substantiated and unsubstantiated risks of child maltreatment referrals was .80. These risks were higher in neighborhoods with low levels of socioeconomic status, higher immigrant concentration, public disorder and crime. CONCLUSIONS: Child maltreatment referrals, regardless of whether substantiated or unsubstantiated, overlap in the same disadvantaged neighborhoods. This suggests that in these neighborhoods, families are at a higher risk of being investigated by child protective services suggesting a potential reporting bias.

Opioid prescription rates and risk for substantiated child abuse and neglect: A Bayesian spatiotemporal analysis.

OBJECTIVES: To determine the association between opioid prescribing rates and substantiated abuse and neglect across Tennessee counties during an 11-year period. METHODS: We adopted a Bayesian spatiotemporal approach to determine the association between opioid prescribing and rates of substantiated child abuse and neglect over and above environmental and population-level covariates. Annual county-level data for Tennessee (2006-2016) included rates of substantiated child abuse and neglect, rates of drug and non-drug crime incidents, racial and Hispanic composition, per capita income, child poverty and teen birth rates, and vacant housing. RESULTS: Higher opioid prescribing rates were associated with greater risk for substantiated child abuse and neglect across Tennessee counties. Risk for substantiated child abuse and neglect was positively associated with vacant housing, child poverty, teen birth rates, and rates of both drug and non-drug criminal incidents - including stimulant arrests. Risk for substantiated child abuse and neglect was negatively associated with percentages of African Americans. CONCLUSIONS: Results underscore the importance of opioid prescribing and crime rates as independent determinants of spatial and temporal variation in risk for substantiated child abuse and neglect. Policies that regulate and reduce opioid prescribing have the potential to reduce risk for child abuse and neglect.

Child maltreatment and alcohol outlets in Spain: Does the country drinking culture matters?

BACKGROUND: Alcohol outlet density has been linked to rates of substantiated maltreatment both cross-sectionally and over time. Most of these studies have been conducted in Anglo-Saxon countries, especially in the U.S., but other countries, where alcohol outlets and alcohol consumption may have different social meanings, are clearly underrepresented in the literature. OBJECTIVE: The aim of this study was to analyze whether alcohol outlet density is associated with neighborhood-level child maltreatment risk in a South-European city. PARTICIPANTS AND SETTING: A longitudinal study was conducted in the city of Valencia (Spain). As spatial units, we used 552 census block groups. Family units with child maltreatment protection measures from 2004 to 2015 were geocoded (n = 1799). METHODS: A Bayesian spatio-temporal autoregression model was conducted to model the outcome variable. RESULTS: Results indicated that, once controlled for other neighborhood-level characteristics, the influence of off-premise density and restaurant/cafe density were not relevant, while bar density showed a negative relationship with child maltreatment risk. Spatially lagged alcohol outlet variables were also not relevant in the model. CONCLUSIONS: Our results suggest the importance of taking into account the cultural influences on the relationship between alcohol outlets and child maltreatment risk. Future cross-cultural research is needed for better understanding this relationship.

County-level socioeconomic and crime risk factors for substantiated child abuse and neglect.

Rates of substantiated child abuse and neglect vary significantly across counties. Despite strong cross-sectional support for links between social-contextual characteristics and abuse and neglect, few longitudinal studies have tested relations between these risk factors and substantiated rates of abuse/neglect. The goal of this study was to identify county-level socioeconomic and crime factors associated with substantiated abuse/neglect rates over 13 years (2004-2016). Annual county-level data for Tennessee, obtained from the KIDS COUNT Data Center, included rates of substantiated child abuse and neglect, children's race and ethnicity, births to unmarried women, teen birth rate, children in families receiving Supplemental Nutrition Assistance Program (SNAP) benefits, and children in families receiving Temporary Assistance for Needy Families. Annual county-level crime report data, obtained from the Tennessee Incident Based Reporting System, included sexual offenses, non-sexual assaults, stalking incidents, thefts, property damage, and drug-related offenses. Bayesian spatio-temporal models indicated that substantiated child abuse and neglect rates were independently and positively associated with teen birth rates, percentages of births to unmarried mothers, drug-related offenses, and percentages of children receiving SNAP benefits. In contrast, substantiated child abuse and neglect rates were negatively associated with percentages of African-American youth. The findings highlighted distinct demographic, socioeconomic, and crime factors associated with substantiated child abuse and neglect rates and have the potential to enhance identification of high-risk counties that could benefit from targeted abuse and neglect prevention efforts.

Toward mechanistic models for genotype-phenotype correlations in phenylketonuria using protein stability calculations.

Phenylketonuria (PKU) is a genetic disorder caused by variants in the gene encoding phenylalanine hydroxylase (PAH), resulting in accumulation of phenylalanine to neurotoxic levels. Here, we analyzed the cellular stability, localization, and interaction with wild-type PAH of 20 selected PKU-linked PAH protein missense variants. Several were present at reduced levels in human cells, and the levels increased in the presence of a proteasome inhibitor, indicating that proteins are proteasome targets. We found that all the tested PAH variants retained their ability to associate with wild-type PAH, and none formed aggregates, suggesting that they are only mildly destabilized in structure. In all cases, PAH variants were stabilized by the cofactor tetrahydrobiopterin (BH4 ), a molecule known to alleviate symptoms in certain PKU patients. Biophysical calculations on all possible single-site missense variants using the full-length structure of PAH revealed a strong correlation between the predicted protein stability and the observed stability in cells. This observation rationalizes previously observed correlations between predicted loss of protein destabilization and disease severity, a correlation that we also observed using new calculations. We thus propose that many disease-linked PAH variants are structurally destabilized, which in turn leads to proteasomal degradation and insufficient amounts of cellular PAH protein.

Connecting Child Maltreatment Risk With Crime and Neighborhood Disadvantage Across Time and Place: A Bayesian Spatiotemporal Analysis.

Child maltreatment is a major public health problem. Although maltreatment rates vary over time and are influenced by neighborhood characteristics, the unique effects of crime and disadvantage on risk are not well understood. This study utilized a Bayesian spatiotemporal approach to examine risk factors for substantiated child abuse and neglect over a 9-year period across zip codes in Davidson County, TN. Risk of child sexual and physical abuse decreased from 2008 to 2016. In contrast, risk of child neglect increased from 2011 to 2014, followed by a rapid decrease in risk. Whereas higher percentages of families living in poverty were associated with higher risk of all maltreatment subtypes, higher unemployment rates were uniquely associated with risk of child neglect. Crime rates were positively associated with risk of child physical and sexual abuse but not neglect. Results have implications for tailoring prevention strategies according to geographic area and maltreatment subtype.

The university campus environment as a protective factor for intimate partner violence against women: An exploratory study.

Some neighborhood characteristics linked to social disorganization theory have been related to intimate partner violence against women (IPVAW). The study of other neighborhood-level factors that may influence IPVAW risk, however, has received less attention. The aim of this study is to analyze the influence of university campuses on IPVAW risk. To conduct the study, IPVAW cases from 2011 to 2013 in the city of Valencia, Spain, were geocoded (n = 1,623). Census block groups were used as the neighborhood analysis unit. Distance between each census block group and the nearest university campus was measured. A Bayesian spatial model adjusted for census block group-level characteristics was performed. Results showed that the distance from a university campus was associated with an approximate 7% increase in IPVAW risk per kilometer. These results suggest that university campuses integrated in the city are related to IPVAW risk. Further research is needed to explain the mechanisms involved.

The Willingness to Intervene in Cases of Intimate Partner Violence Against Women (WI-IPVAW) Scale: Development and Validation of the Long and Short Versions.

Willingness to intervene when one becomes aware of a case of intimate partner violence against women (IPVAW) reflects the level of tolerance and acceptance of this type of violence in society. Increasing the likelihood of intervention to help victims of IPVAW is also a target for prevention strategies aiming to increase informal social control of IPVAW. In this study, we present the development and validation of the Willingness to Intervene in Cases of Intimate Partner Violence (WI-IPVAW) scale. We report data for both the long and short versions of the scale. We analyzed the latent structure, the reliability and validity of the WI-IPVAW across four samples (N = 1648). Factor analyses supported a bifactor model with a general non-specific factor expressing willingness to intervene in cases of IPVAW, and three specific factors reflecting different intervention preferences: a preference for setting the law enforcement process in motion ("calling the cops" factor), a preference for personal intervention ("personal involvement" factor), and a preference for non-intervention ("not my business" factor). Configural, metric, and partial scalar invariance across genders were supported. Two short versions of the scale, with nine and six items, respectively, were constructed on the base of quantitative and qualitative criteria. The long and short versions of the WI-IPVAW demonstrated both high reliability and construct validity, as they were strongly related to the acceptability of IPVAW, victim-blaming attitudes, perceived severity of IPVAW, and hostile sexism. These results confirm that both the long and short versions of the WI-IPVAW scale are psychometrically sound instruments to analyze willingness to intervene in cases of IPVAW in different settings and with different research needs (e.g., long versions for clinical and research settings, and short versions for large population surveys). The WI-IPVAW is also useful for assessing prevention policies and public education campaigns design to promote a more responsive social environment in cases of IPVAW, thus contributing to deter and reduce this major social and public health problem.

Neighborhood characteristics and violence behind closed doors: The spatial overlap of child maltreatment and intimate partner violence.

In this study, we analyze first whether there is a common spatial distribution of child maltreatment (CM) and intimate partner violence (IPV), and second, whether the risks of CM and IPV are influenced by the same neighborhood characteristics, and if these risks spatially overlap. To this end we used geocoded data of CM referrals (N = 588) and IPV incidents (N = 1450) in the city of Valencia (Spain). As neighborhood proxies, we used 552 census block groups. Neighborhood characteristics analyzed at the aggregated level (census block groups) were: Neighborhood concentrated disadvantage (neighborhood economic status, neighborhood education level, and policing activity), immigrant concentration, and residential instability. A Bayesian joint modeling approach was used to examine the spatial distribution of CM and IPV, and a Bayesian random-effects modeling approach was used to analyze the influence of neighborhood-level characteristics on small-area variations of CM and IPV risks. For CM, 98% of the total between-area variation in risk was captured by a shared spatial component, while for IPV the shared component was 77%. The risks of CM and IPV were higher in neighborhoods characterized by lower levels of economic status and education, and higher levels of policing activity, immigrant concentration, and residential instability. The correlation between the log relative risk of CM and IPV was .85. Most census block groups had either low or high risks in both outcomes (with only 10.5% of the areas with mismatched risks). These results show that certain neighborhood characteristics are associated with an increase in the risk of family violence, regardless of whether this violence is against children or against intimate partners. Identifying these high-risk areas can inform a more integrated community-level response to both types of family violence. Future research should consider a community-level approach to address both types of family violence, as opposed to individual-level intervention addressing each type of violence separately.

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.

Mapping child maltreatment risk: a 12-year spatio-temporal analysis of neighborhood influences.

BACKGROUND: 'Place' matters in understanding prevalence variations and inequalities in child maltreatment risk. However, most studies examining ecological variations in child maltreatment risk fail to take into account the implications of the spatial and temporal dimensions of neighborhoods. In this study, we conduct a high-resolution small-area study to analyze the influence of neighborhood characteristics on the spatio-temporal epidemiology of child maltreatment risk. METHODS: We conducted a 12-year (2004-2015) small-area Bayesian spatio-temporal epidemiological study with all families with child maltreatment protection measures in the city of Valencia, Spain. As neighborhood units, we used 552 census block groups. Cases were geocoded using the family address. Neighborhood-level characteristics analyzed included three indicators of neighborhood disadvantage-neighborhood economic status, neighborhood education level, and levels of policing activity-, immigrant concentration, and residential instability. Bayesian spatio-temporal modelling and disease mapping methods were used to provide area-specific risk estimations. RESULTS: Results from a spatio-temporal autoregressive model showed that neighborhoods with low levels of economic and educational status, with high levels of policing activity, and high immigrant concentration had higher levels of substantiated child maltreatment risk. Disease mapping methods were used to analyze areas of excess risk. Results showed chronic spatial patterns of high child maltreatment risk during the years analyzed, as well as stability over time in areas of low risk. Areas with increased or decreased child maltreatment risk over the years were also observed. CONCLUSIONS: A spatio-temporal epidemiological approach to study the geographical patterns, trends over time, and the contextual determinants of child maltreatment risk can provide a useful method to inform policy and action. This method can offer a more accurate description of the problem, and help to inform more localized prevention and intervention strategies. This new approach can also contribute to an improved epidemiological surveillance system to detect ecological variations in risk, and to assess the effectiveness of the initiatives to reduce this risk.

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.

Validation of a Google Street View-Based Neighborhood Disorder Observational Scale.

Recently, there has been a growing interest in developing new tools to measure neighborhood features using the benefits of emerging technologies. This study aimed to assess the psychometric properties of a neighborhood disorder observational scale using Google Street View (GSV). Two groups of raters conducted virtual audits of neighborhood disorder on all census block groups (N = 92) in a district of the city of Valencia (Spain). Four different analyses were conducted to validate the instrument. First, inter-rater reliability was assessed through intraclass correlation coefficients, indicating moderated levels of agreement among raters. Second, confirmatory factor analyses were performed to test the latent structure of the scale. A bifactor solution was proposed, comprising a general factor (general neighborhood disorder) and two specific factors (physical disorder and physical decay). Third, the virtual audit scores were assessed with the physical audit scores, showing a positive relationship between both audit methods. In addition, correlations between the factor scores and socioeconomic and criminality indicators were assessed. Finally, we analyzed the spatial autocorrelation of the scale factors, and two fully Bayesian spatial regression models were run to study the influence of these factors on drug-related police interventions and interventions with young offenders. All these indicators showed an association with the general neighborhood disorder. Taking together, results suggest that the GSV-based neighborhood disorder scale is a reliable, concise, and valid instrument to assess neighborhood disorder using new technologies.

The Mutational Landscape of the Oncogenic MZF1 SCAN Domain in Cancer.

SCAN domains in zinc-finger transcription factors are crucial mediators of protein-protein interactions. Up to 240 SCAN-domain encoding genes have been identified throughout the human genome. These include cancer-related genes, such as the myeloid zinc finger 1 (MZF1), an oncogenic transcription factor involved in the progression of many solid cancers. The mechanisms by which SCAN homo- and heterodimers assemble and how they alter the transcriptional activity of zinc-finger transcription factors in cancer and other diseases remain to be investigated. Here, we provide the first description of the conformational ensemble of the MZF1 SCAN domain cross-validated against NMR experimental data, which are probes of structure and dynamics on different timescales. We investigated the protein-protein interaction network of MZF1 and how it is perturbed in different cancer types by the analyses of high-throughput proteomics and RNASeq data. Collectively, we integrated many computational approaches, ranging from simple empirical energy functions to all-atom microsecond molecular dynamics simulations and network analyses to unravel the effects of cancer-related substitutions in relation to MZF1 structure and interactions.

The Spatial Epidemiology of Intimate Partner Violence: Do Neighborhoods Matter?

We examined whether neighborhood-level characteristics influence spatial variations in the risk of intimate partner violence (IPV). Geocoded data on IPV cases with associated protection orders (n = 1,623) in the city of Valencia, Spain (2011-2013), were used for the analyses. Neighborhood units were 552 census block groups. Drawing from social disorganization theory, we explored 3 types of contextual influences: concentrated disadvantage, concentration of immigrants, and residential instability. A Bayesian spatial random-effects modeling approach was used to analyze influences of neighborhood-level characteristics on small-area variations in IPV risk. Disease mapping methods were also used to visualize areas of excess IPV risk. Results indicated that IPV risk was higher in physically disordered and decaying neighborhoods and in neighborhoods with low educational and economic status levels, high levels of public disorder and crime, and high concentrations of immigrants. Results also revealed spatially structured remaining variability in IPV risk that was not explained by the covariates. In this study, neighborhood concentrated disadvantage and immigrant concentration emerged as significant ecological risk factors explaining IPV. Addressing neighborhood-level risk factors should be considered for better targeting of IPV prevention.