Context Matters: Assessing the Association Between Area Deprivation and the Severity of Injury and Types of Domestic Violence Victimization Among Women

The impact of social determinants of health on feminicide in the second-largest state of the Brazilian Amazon: a spatial epidemiological analysis

INTRODUCTION

Despite global advancements in gender equality and legal frameworks, feminicide remains a persistent issue worldwide. Spatial analysis is a powerful tool to use in obtaining evidence-based recommendations for more effective policies to fight it. In Brazil the state of Pará was highlighted with the sixth highest increase in the feminicide rate between 2019 and 2022. In this study, we spatially analyzed feminicide rates in Pará, from 2016 to 2021, employing spatial distribution and autocorrelation, spatio-temporal, and geographically weighted regression (GWR) techniques.

METHODS

Annual number of feminicide incidents from all municipalities in Pará were provided by Secretariat of Intelligence and Criminal Analysis of Pará. Municipalities crude feminicide rates were calculated and analyzed using spatial distribution and spatial autocorrelation (Getis-Ord G analysis) to identify areas with a high burden of feminicide. Spatio-temporal risk analysis was employed to assess the influences of policies and social factors on feminicide trends over space and time. GWR was used to evaluate the influence of social determinants of health in the spatial variability of feminicide rates.

RESULTS

During the study period, feminicide rates expanded spatially in Pará, with municipalities in Belem metropolitan area and in the northeast, southeast and southwest mesoregions of Pará being the most affected. Between 2016 and 2018, there was a hotspot cluster (neighbor municipalities sharing high feminicide rates) located in southwest and southeast of Pará. From 2019 to 2021, this hotspot contracted, and a new one appeared in the northeast. The spatio-temporal risk zone comprised municipalities situated in the northeast, southeast, and southwest mesoregions of Pará from 2018 to 2021. The spatial variability of feminicide was promoted by the "high school pass rate," the "youth homicide rate," and "primary healthcare services coverage."

CONCLUSION

Our findings highlight the need for policy interventions, including increased investment in women's shelters, expanded access to legal and psychological support for victims of gender-based violence, and the integration of gender equality education into school.

Neighborhood disadvantage and pain-related experiences in a pain psychology clinic: The mediating roles of pain catastrophizing and pain-related fear

This study investigated the relationship between neighborhood disadvantage, measured by the Area Deprivation Index (ADI), and pain-related variables in a pain psychology clinic. We also examined the sequential mediating roles of pain catastrophizing and pain-related fear on these relationships. Participants (N = 509) completed questionnaires assessing usual pain intensity, fatigue, emotional distress, and interference with daily activities. The mean ADI score was 32.57 (SD = 22.65), with scores ranging from 1 to 100. Linear regression analysis, adjusting for age and gender, revealed that higher ADI (i.e., less advantage) was significantly associated with higher scores on pain-related variables (pain intensity: B = 0.026, p < .001; fatigue: B = 0.018, p < .001; emotional distress: B = 0.020, p < .001; interference with daily activities: B = 0.014, p = .006). Sequential mediation analysis revealed pain catastrophizing and pain-related fear mediated these relationships, with significant indirect effects for fatigue (B = 0.001, 95% CI [0.000, 0.002]) and interference with daily activities (B = 0.001, 95% CI [0.001, 0.003]) - but not pain intensity or emotional distress. Pain catastrophizing alone mediated neighborhood disadvantage-pain relationship for all variables. The results suggest that neighborhood disadvantage is associated with higher scores on pain-related experiences and that consistent with the fear avoidance model, pain catastrophizing and pain-related fear may play a role in these relationships for fatigue and interference with daily activities. These findings underscore that neighborhood disadvantage is associated with worse pain-related experiences and highlight the importance of considering neighborhood factors in chronic pain management. PERSPECTIVE: This study identifies potential pathways linking neighborhood disadvantage to chronic pain variables, highlighting the roles of pain catastrophizing and pain-related fear. The findings underscore the need for a holistic approach to pain management that recognizes both individual cognitive-emotional factors and the broader social context in which pain occurs.

Area deprivation index and social vulnerability index in Milwaukee County: Impact on hospital outcomes after traumatic injuries

BACKGROUND

Predisposing factors for traumatic injuries are complex and variable. Neighborhood environments may influence injury mechanism or outcomes. The Social Vulnerability Index (SVI) identifies areas at risk for emergencies; Area Deprivation Index (ADI) measures socioeconomic disadvantage. The objective was to assess the impact of SVI or ADI on hospital length of stay (LOS) and mortality for injured patients to determine whether SVI or ADI indicated areas where injury prevention may be most impactful.

METHODS

Adult patients who resided in Milwaukee County and were treated for injuries from 2015 to 2022 at a level I trauma center were included. Patients' addresses were geocoded and merged with 2020 state-level SVI and ADI measures. SVI ranks census tracts 0-100 from least to most vulnerable. ADI ranks census block groups 1-10 from least to most disadvantaged. ADI and SVI rankings were converted to deciles. Statistical analyses included descriptive statistics, chi-square tests, and regression models for LOS and in-hospital mortality, adjusted for either SVI or ADI within separate models, age, sex, race or ethnicity, mechanism of injury (MOI), injury severity score (ISS).

RESULTS

14,542 patients were included; 63 % were male. Mean total hospital LOS was 6.4 ± 9.8 days, and in-hospital mortalities occurred in 5.2 % of patients. Based on SVI and ADI, 5,280 (36 %) patients resided in high vulnerability areas and 5,576 (39 %) lived in highly disadvantaged areas, respectively. After adjusting for patient factors, SVI deciles #6, 9, 10 were associated with increased hospital LOS, and SVI decile #5 was associated with in-hospital mortality (OR = 2.22, 95 %CI:1.06-4.63; p = 0.034). When adjusted for ADI, the 7th-10th deciles were associated with increased hospital LOS. Greater age and ISS were associated with increased hospital LOS and mortality when adjusted for SVI and ADI.

CONCLUSIONS

SVI and ADI identified a similar proportion of patients in high vulnerability or disadvantaged areas. Higher SVI and ADI deciles were associated with longer hospital LOS, and only the 5th SVI decile was associated with in-hospital mortality. Highly disadvantaged or vulnerable areas may have a longer LOS, but SVI and ADI have limited influence on trauma mortality. Continued research on neighborhood and community factors and trauma outcomes is needed.

Your neighborhood matters: an ecological social determinant study of the relationship between residential racial segregation and the risk of firearm fatalities

BACKGROUND

Firearm fatalities are a major public health concern, claiming the lives of 40,000 Americans each year. While firearm fatalities have pervasive effects, it is unclear how social determinants of health (SDOH) such as residential racial segregation, income inequality, and community resilience impact firearm fatalities. This study investigates the relationships between these SDOH and the likelihood of firearm fatalities.

METHODS

County-level SDOH data from the Agency for Health Care Research and Quality for 2019 were analyzed, covering 72 Wisconsin counties. The dependent variable was the number of firearm fatalities in each county, used as a continuous variable. The independent variable was residential racial segregation (Dissimilarity Index), defined as the degree to which non-White and White residents were distributed across counties, ranging from 0 (complete integration) to 100 (complete segregation), and higher values indicate greater residential segregation (categorized as low, moderate, and high). Covariates were income inequality ranging from zero (perfect equality) to one (perfect inequality) categorized as low, moderate, and high, community resilience risk factors (low, moderate, and high risks), and rural-urban classifications. Descriptive/summary statistics, unadjusted and adjusted negative binomial regression adjusting for population weight, were performed using STATA/MPv.17.0; P-values ≤ 0.05 were considered statistically significant. ArcMap was used for Geographic Information System analysis.

RESULTS

In 2019, there were 802 firearm fatalities. The adjusted model demonstrates that the risk of firearm fatalities was higher in areas with high residential racial segregation compared to low-segregated areas (IRR.:1.26, 95% CI:1.04-1.52) and higher in areas with high-income inequality compared to areas with low-income inequality (IRR.:1.18, 95% CI:1.00-1.40). Compared to areas with low-risk community resilience, the risk of firearm fatalities was higher in areas with moderate (IRR.:0.61, 95% CI:0.48-0.78), and in areas with high risk (IRR.:0.53, 95% CI:0.41-0.68). GIS analysis demonstrated that areas with high racial segregation also have high rates of firearm fatalities.

CONCLUSION

Areas with high residential racial segregation have a high rate of firearm fatalities. With high income inequality and low community resilience, the likelihood of firearm fatalities increases.