Recidivism and Neighborhood Governance

2018 ◽  
Vol 56 (4) ◽  
pp. 1263-1292
Author(s):  
Michael Craw ◽  
Tusty ten Bensel

Recent research on recidivism emphasizes the importance of neighborhoods to successful prisoner reentry. This research analyzes two ways in which institutions of neighborhood governance affect reentry. First, offenders in neighborhoods with institutions supporting social control may have more success in reintegrating into the community. Second, neighborhood institutions may create barriers to entry for ex-offenders more likely to reoffend. To test this, we combine Arkansas Department of Corrections data on offenders returning to Little Rock between 2004 and 2014 with geocoded data on neighborhood and homeowner associations. We analyze this data using Cox proportional hazards and two-stage residual inclusion models of recidivism hazard. We find that a significant relationship exists between recidivism hazard and neighborhood governance, but that this is attributable to nonrandom assignment of ex-offenders to neighborhoods rather than the role neighborhood organizations play in facilitating reentry.

2017 ◽  
Vol 55 (2) ◽  
pp. 501-529 ◽  
Author(s):  
Michael Craw

The relationship between neighborhood racial composition and property values is generally explained as a consequence of White household exit from racially and ethnically mixed neighborhoods. But some neighborhoods offer opportunities for households to exercise voice in response to neighborhood change rather than exit. This article argues that differences across neighborhoods in how they are governed play a significant role in mediating the relationship between property values and neighborhood racial and ethnic composition. Using geocoded data on sales of detached single family homes in Little Rock from 2000 to 2014, this article finds that neighborhood associations tend to increase the effect of the size of a neighborhood’s Black population on property values. At the same time, homeowner associations tend to reduce the effect of neighborhood Black population on property values.


Crisis ◽  
2018 ◽  
Vol 39 (1) ◽  
pp. 27-36 ◽  
Author(s):  
Kuan-Ying Lee ◽  
Chung-Yi Li ◽  
Kun-Chia Chang ◽  
Tsung-Hsueh Lu ◽  
Ying-Yeh Chen

Abstract. Background: We investigated the age at exposure to parental suicide and the risk of subsequent suicide completion in young people. The impact of parental and offspring sex was also examined. Method: Using a cohort study design, we linked Taiwan's Birth Registry (1978–1997) with Taiwan's Death Registry (1985–2009) and identified 40,249 children who had experienced maternal suicide (n = 14,431), paternal suicide (n = 26,887), or the suicide of both parents (n = 281). Each exposed child was matched to 10 children of the same sex and birth year whose parents were still alive. This yielded a total of 398,081 children for our non-exposed cohort. A Cox proportional hazards model was used to compare the suicide risk of the exposed and non-exposed groups. Results: Compared with the non-exposed group, offspring who were exposed to parental suicide were 3.91 times (95% confidence interval [CI] = 3.10–4.92 more likely to die by suicide after adjusting for baseline characteristics. The risk of suicide seemed to be lower in older male offspring (HR = 3.94, 95% CI = 2.57–6.06), but higher in older female offspring (HR = 5.30, 95% CI = 3.05–9.22). Stratified analyses based on parental sex revealed similar patterns as the combined analysis. Limitations: As only register-­based data were used, we were not able to explore the impact of variables not contained in the data set, such as the role of mental illness. Conclusion: Our findings suggest a prominent elevation in the risk of suicide among offspring who lost their parents to suicide. The risk elevation differed according to the sex of the afflicted offspring as well as to their age at exposure.


2020 ◽  
Vol 132 (4) ◽  
pp. 998-1005 ◽  
Author(s):  
Haihui Jiang ◽  
Yong Cui ◽  
Xiang Liu ◽  
Xiaohui Ren ◽  
Mingxiao Li ◽  
...  

OBJECTIVEThe aim of this study was to investigate the relationship between extent of resection (EOR) and survival in terms of clinical, molecular, and radiological factors in high-grade astrocytoma (HGA).METHODSClinical and radiological data from 585 cases of molecularly defined HGA were reviewed. In each case, the EOR was evaluated twice: once according to contrast-enhanced T1-weighted images (CE-T1WI) and once according to fluid attenuated inversion recovery (FLAIR) images. The ratio of the volume of the region of abnormality in CE-T1WI to that in FLAIR images (VFLAIR/VCE-T1WI) was calculated and a receiver operating characteristic curve was used to determine the optimal cutoff value for that ratio. Univariate and multivariate analyses were performed to identify the prognostic value of each factor.RESULTSBoth the EOR evaluated from CE-T1WI and the EOR evaluated from FLAIR could divide the whole cohort into 4 subgroups with different survival outcomes (p < 0.001). Cases were stratified into 2 subtypes based on VFLAIR/VCE-T1WIwith a cutoff of 10: a proliferation-dominant subtype and a diffusion-dominant subtype. Kaplan-Meier analysis showed a significant survival advantage for the proliferation-dominant subtype (p < 0.0001). The prognostic implication has been further confirmed in the Cox proportional hazards model (HR 1.105, 95% CI 1.078–1.134, p < 0.0001). The survival of patients with proliferation-dominant HGA was significantly prolonged in association with extensive resection of the FLAIR abnormality region beyond contrast-enhancing tumor (p = 0.03), while no survival benefit was observed in association with the extensive resection in the diffusion-dominant subtype (p=0.86).CONCLUSIONSVFLAIR/VCE-T1WIis an important classifier that could divide the HGA into 2 subtypes with distinct invasive features. Patients with proliferation-dominant HGA can benefit from extensive resection of the FLAIR abnormality region, which provides the theoretical basis for a personalized resection strategy.


Author(s):  
Alejandro Márquez-Salinas ◽  
Carlos A Fermín-Martínez ◽  
Neftalí Eduardo Antonio-Villa ◽  
Arsenio Vargas-Vázquez ◽  
Enrique C. Guerra ◽  
...  

Abstract Background Chronological age (CA) is a predictor of adverse COVID-19 outcomes; however, CA alone does not capture individual responses to SARS-CoV-2 infection. Here, we evaluated the influence of aging metrics PhenoAge and PhenoAgeAccel to predict adverse COVID-19 outcomes. Furthermore, we sought to model adaptive metabolic and inflammatory responses to severe SARS-CoV-2 infection using individual PhenoAge components. Methods In this retrospective cohort study, we assessed cases admitted to a COVID-19 reference center in Mexico City. PhenoAge and PhenoAgeAccel were estimated using laboratory values at admission. Cox proportional hazards models were fitted to estimate risk for COVID-19 lethality and adverse outcomes (ICU admission, intubation, or death). To explore reproducible patterns which model adaptive responses to SARS-CoV-2 infection, we used k-means clustering using PhenoAge components. Results We included 1068 subjects of whom 222 presented critical illness and 218 died. PhenoAge was a better predictor of adverse outcomes and lethality compared to CA and SpO2 and its predictive capacity was sustained for all age groups. Patients with responses associated to PhenoAgeAccel&gt;0 had higher risk of death and critical illness compared to those with lower values (log-rank p&lt;0.001). Using unsupervised clustering we identified four adaptive responses to SARS-CoV-2 infection: 1) Inflammaging associated with CA, 2) metabolic dysfunction associated with cardio-metabolic comorbidities, 3) unfavorable hematological response, and 4) response associated with favorable outcomes. Conclusions Adaptive responses related to accelerated aging metrics are linked to adverse COVID-19 outcomes and have unique and distinguishable features. PhenoAge is a better predictor of adverse outcomes compared to CA.


Risks ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 103
Author(s):  
Morne Joubert ◽  
Tanja Verster ◽  
Helgard Raubenheimer ◽  
Willem D. Schutte

Survival analysis is one of the techniques that could be used to predict loss given default (LGD) for regulatory capital (Basel) purposes. When using survival analysis to model LGD, a proposed methodology is the default weighted survival analysis (DWSA) method. This paper is aimed at adapting the DWSA method (used to model Basel LGD) to estimate the LGD for International Financial Reporting Standard (IFRS) 9 impairment requirements. The DWSA methodology allows for over recoveries, default weighting and negative cashflows. For IFRS 9, this methodology should be adapted, as the estimated LGD is a function of in the expected credit losses (ECL). Our proposed IFRS 9 LGD methodology makes use of survival analysis to estimate the LGD. The Cox proportional hazards model allows for a baseline survival curve to be adjusted to produce survival curves for different segments of the portfolio. The forward-looking LGD values are adjusted for different macro-economic scenarios and the ECL is calculated for each scenario. These ECL values are probability weighted to produce a final ECL estimate. We illustrate our proposed IFRS 9 LGD methodology and ECL estimation on a dataset from a retail portfolio of a South African bank.


Cancers ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 842
Author(s):  
Masaki Kaibori ◽  
Hideyuki Matsushima ◽  
Morihiko Ishizaki ◽  
Hisashi Kosaka ◽  
Kosuke Matsui ◽  
...  

This retrospective study recorded pertinent baseline geriatric assessment variables to identify risk factors for recurrence-free survival (RFS) and overall survival (OS) after hepatectomy in 100 consecutive patients aged ≥70 years with hepatocellular carcinoma. Patients had geriatric assessments of cognition, nutritional and functional statuses, and comorbidity burden, both preoperatively and at six months postoperatively. The rate of change in each score between preoperative and postoperative assessments was calculated by subtracting the preoperative score from the score at six months postoperatively, then dividing by the score at six months postoperatively. Patients with score change ≥0 comprised the maintenance group, while patients with score change <0 comprised the reduction group. The change in Geriatric 8 (G8) score at six months postoperatively was the most significant predictive factor for RFS and OS among the tested geriatric assessments. Five-year RFS rates were 43.4% vs. 6.7% (maintenance vs. reduction group; HR, 0.19; 95%CI, 0.11–0.31; p < 0.001). Five-year OS rates were 73.8% vs. 17.8% (HR, 0.12; 95%CI, 0.06–0.25; p < 0.001). Multivariate Cox proportional hazards analysis showed that perioperative maintenance of G8 score was an independent prognostic indicator for both RFS and OS. Perioperative changes in G8 scores can help forecast postoperative long-term outcomes in these patients.


2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
I.D Poveda Pinedo ◽  
I Marco Clement ◽  
O Gonzalez ◽  
I Ponz ◽  
A.M Iniesta ◽  
...  

Abstract Background Previous parameters such as peak VO2, VE/VCO2 slope and OUES have been described to be prognostic in heart failure (HF). The aim of this study was to identify further prognostic factors of cardiopulmonary exercise testing (CPET) in HF patients. Methods A retrospective analysis of HF patients who underwent CPET from January to November 2019 in a single centre was performed. PETCO2 gradient was defined by the difference between final PETCO2 and baseline PETCO2. HF events were defined as decompensated HF requiring hospital admission or IV diuretics, or decompensated HF resulting in death. Results A total of 64 HF patients were assessed by CPET, HF events occurred in 8 (12.5%) patients. Baseline characteristics are shown in table 1. Patients having HF events had a negative PETCO2 gradient while patients not having events showed a positive PETCO2 gradient (−1.5 [IQR −4.8, 2.3] vs 3 [IQR 1, 5] mmHg; p=0.004). A multivariate Cox proportional-hazards regression analysis revealed that PETCO2 gradient was an independent predictor of HF events (HR 0.74, 95% CI [0.61–0.89]; p=0.002). Kaplan-Meier curves showed a significantly higher incidence of HF events in patients having negative gradients, p=0.002 (figure 1). Conclusion PETCO2 gradient was demonstrated to be a prognostic parameter of CPET in HF patients in our study. Patients having negative gradients had worse outcomes by having more HF events. Time to first event, decompensated heart Funding Acknowledgement Type of funding source: None


2021 ◽  
pp. 000486742110096
Author(s):  
Oleguer Plana-Ripoll ◽  
Patsy Di Prinzio ◽  
John J McGrath ◽  
Preben B Mortensen ◽  
Vera A Morgan

Introduction: An association between schizophrenia and urbanicity has long been observed, with studies in many countries, including several from Denmark, reporting that individuals born/raised in densely populated urban settings have an increased risk of developing schizophrenia compared to those born/raised in rural settings. However, these findings have not been replicated in all studies. In particular, a Western Australian study showed a gradient in the opposite direction which disappeared after adjustment for covariates. Given the different findings for Denmark and Western Australia, our aim was to investigate the relationship between schizophrenia and urbanicity in these two regions to determine which factors may be influencing the relationship. Methods: We used population-based cohorts of children born alive between 1980 and 2001 in Western Australia ( N = 428,784) and Denmark ( N = 1,357,874). Children were categorised according to the level of urbanicity of their mother’s residence at time of birth and followed-up through to 30 June 2015. Linkage to State-based registers provided information on schizophrenia diagnosis and a range of covariates. Rates of being diagnosed with schizophrenia for each category of urbanicity were estimated using Cox proportional hazards models adjusted for covariates. Results: During follow-up, 1618 (0.4%) children in Western Australia and 11,875 (0.9%) children in Denmark were diagnosed with schizophrenia. In Western Australia, those born in the most remote areas did not experience lower rates of schizophrenia than those born in the most urban areas (hazard ratio = 1.02 [95% confidence interval: 0.81, 1.29]), unlike their Danish counterparts (hazard ratio = 0.62 [95% confidence interval: 0.58, 0.66]). However, when the Western Australian cohort was restricted to children of non-Aboriginal Indigenous status, results were consistent with Danish findings (hazard ratio = 0.46 [95% confidence interval: 0.29, 0.72]). Discussion: Our study highlights the potential for disadvantaged subgroups to mask the contribution of urban-related risk factors to risk of schizophrenia and the importance of stratified analysis in such cases.


Nutrients ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 1034
Author(s):  
Vincenza Gianfredi ◽  
Annemarie Koster ◽  
Anna Odone ◽  
Andrea Amerio ◽  
Carlo Signorelli ◽  
...  

Our aim was to assess the association between a priori defined dietary patterns and incident depressive symptoms. We used data from The Maastricht Study, a population-based cohort study (n = 2646, mean (SD) age 59.9 (8.0) years, 49.5% women; 15,188 person-years of follow-up). Level of adherence to the Dutch Healthy Diet (DHD), Mediterranean Diet, and Dietary Approaches To Stop Hypertension (DASH) were derived from a validated Food Frequency Questionnaire. Depressive symptoms were assessed at baseline and annually over seven-year-follow-up (using the 9-item Patient Health Questionnaire). We used Cox proportional hazards regression analyses to assess the association between dietary patterns and depressive symptoms. One standard deviation (SD) higher adherence in the DHD and DASH was associated with a lower hazard ratio (HR) of depressive symptoms with HRs (95%CI) of 0.78 (0.69–0.89) and 0.87 (0.77–0.98), respectively, after adjustment for sociodemographic and cardiovascular risk factors. After further adjustment for lifestyle factors, the HR per one SD higher DHD was 0.83 (0.73–0.96), whereas adherence to Mediterranean and DASH diets was not associated with incident depressive symptoms. Higher adherence to the DHD lowered risk of incident depressive symptoms. Adherence to healthy diet could be an effective non-pharmacological preventive measure to reduce the incidence of depression.


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Maryam Farhadian ◽  
Sahar Dehdar Karsidani ◽  
Azadeh Mozayanimonfared ◽  
Hossein Mahjub

Abstract Background Due to the limited number of studies with long term follow-up of patients undergoing Percutaneous Coronary Intervention (PCI), we investigated the occurrence of Major Adverse Cardiac and Cerebrovascular Events (MACCE) during 10 years of follow-up after coronary angioplasty using Random Survival Forest (RSF) and Cox proportional hazards models. Methods The current retrospective cohort study was performed on 220 patients (69 women and 151 men) undergoing coronary angioplasty from March 2009 to March 2012 in Farchshian Medical Center in Hamadan city, Iran. Survival time (month) as the response variable was considered from the date of angioplasty to the main endpoint or the end of the follow-up period (September 2019). To identify the factors influencing the occurrence of MACCE, the performance of Cox and RSF models were investigated in terms of C index, Integrated Brier Score (IBS) and prediction error criteria. Results Ninety-six patients (43.7%) experienced MACCE by the end of the follow-up period, and the median survival time was estimated to be 98 months. Survival decreased from 99% during the first year to 39% at 10 years' follow-up. By applying the Cox model, the predictors were identified as follows: age (HR = 1.03, 95% CI 1.01–1.05), diabetes (HR = 2.17, 95% CI 1.29–3.66), smoking (HR = 2.41, 95% CI 1.46–3.98), and stent length (HR = 1.74, 95% CI 1.11–2.75). The predictive performance was slightly better by the RSF model (IBS of 0.124 vs. 0.135, C index of 0.648 vs. 0.626 and out-of-bag error rate of 0.352 vs. 0.374 for RSF). In addition to age, diabetes, smoking, and stent length, RSF also included coronary artery disease (acute or chronic) and hyperlipidemia as the most important variables. Conclusion Machine-learning prediction models such as RSF showed better performance than the Cox proportional hazards model for the prediction of MACCE during long-term follow-up after PCI.


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