Literature DB >> 26056935

Does rising crime lead to increasing distress? Longitudinal analysis of a natural experiment with dynamic objective neighbourhood measures.

Thomas Astell-Burt1, Xiaoqi Feng2, Gregory S Kolt3, Bin Jalaludin4.   

Abstract

Identifying 'neighbourhood effects' to support widespread beliefs that where we live matters for our health remains a major challenge due to the reliance upon observational data. In this study we reassess the issue of local crime rates and psychological distress by applying unobserved ('fixed') effects models to a sample of participants who remain in the same neighbourhoods throughout the study. Baseline data was extracted from the 45 and Up Study between 2006 and 2008 and followed up as part of the Social Economic and Environmental Factors (SEEF) Study between 2009 and 2010. Kessler 10 scores were recorded for 25,545 men and 29,299 women reported valid outcomes. Annual crime rates per 1000 (including non-domestic violence, malicious damage, break and enter, and stealing, theft and robbery) from 2006 to 2010 inclusive were linked to the person-level data. Change in exposure to crime among participants in this study, therefore, occurs as a result of a change in the local crime rate, rather than a process of neighbourhood selection. Gender stratified unobserved effects logistic regression adjusting for sources of time-varying confounding (age, income, employment, couple status and physical functioning) indicated that an increase in the risk of experiencing psychological distress was generally associated with an increase in the level of neighbourhood crime. Effect sizes were particularly high for women, especially for an increase in malicious damage (Odds Ratio Tertile 3 vs Tertile 1 2.40, 95% Confidence Interval 1.88, 3.05), which may indicate that damage to local built environment is an important pathway linking neighbourhood crime with psychological distress. No statistically significant association was detected for an increase in non-domestic violence, although the effect was in the hypothesised direction. In summary, the application of unobserved effects models to analyse data that takes into account the temporally dynamic characteristics of where people live warrants further investigation.
Copyright © 2015 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Confounding; Crime; Health selective migration; Longitudinal study; Mental health; Neighbourhood; Reverse causation; Unobserved effects models

Mesh:

Year:  2015        PMID: 26056935     DOI: 10.1016/j.socscimed.2015.05.014

Source DB:  PubMed          Journal:  Soc Sci Med        ISSN: 0277-9536            Impact factor:   4.634


  22 in total

1.  Acute Changes in Community Violence and Increases in Hospital Visits and Deaths From Stress-responsive Diseases.

Authors:  Jennifer Ahern; Ellicott C Matthay; Dana E Goin; Kriszta Farkas; Kara E Rudolph
Journal:  Epidemiology       Date:  2018-09       Impact factor: 4.822

2.  Exposure to Community Violence and Self-harm in California: A Multilevel, Population-based, Case-Control Study.

Authors:  Ellicott C Matthay; Kriszta Farkas; Jennifer Skeem; Jennifer Ahern
Journal:  Epidemiology       Date:  2018-09       Impact factor: 4.822

3.  Neighborhood Factors as Predictors of Poor Sleep in the Sueño Ancillary Study of the Hispanic Community Health Study/Study of Latinos.

Authors:  Guido Simonelli; Katherine A Dudley; Jia Weng; Linda C Gallo; Krista Perreira; Neomi A Shah; Carmela Alcantara; Phyllis C Zee; Alberto R Ramos; Maria M Llabre; Daniela Sotres-Alvarez; Rui Wang; Sanjay R Patel
Journal:  Sleep       Date:  2017-01-01       Impact factor: 5.849

4.  Racial and ethnic differences in associations of community violence with self-harm: a population-based case-control study.

Authors:  Ellicott C Matthay; Kriszta Farkas; Jennifer Ahern
Journal:  Ann Epidemiol       Date:  2019-04-18       Impact factor: 3.797

5.  Experiences of Community Violence Among Adults with Chronic Conditions: Qualitative Findings from Chicago.

Authors:  Elizabeth L Tung; Tyrone A Johnson; Yolanda O'Neal; Althera M Steenes; Graciela Caraballo; Monica E Peek
Journal:  J Gen Intern Med       Date:  2018-08-03       Impact factor: 5.128

6.  The Power of Place: Social Network Characteristics, Perceived Neighborhood Features, and Psychological Distress Among African Americans in the Historic Hill District in Pittsburgh, Pennsylvania.

Authors:  Karen R Flórez; Madhumita Bonnie Ghosh-Dastidar; Robin Beckman; Kayla de la Haye; Obidiugwu Kenrik Duru; Ana F Abraído-Lanza; Tamara Dubowitz
Journal:  Am J Community Psychol       Date:  2016-09-09

7.  Moving to opportunity and mental health: Exploring the spatial context of neighborhood effects.

Authors:  Corina Graif; Mariana C Arcaya; Ana V Diez Roux
Journal:  Soc Sci Med       Date:  2016-05-25       Impact factor: 4.634

8.  Violent crime, police presence and poor sleep in two low-income urban predominantly Black American neighbourhoods.

Authors:  Andrea S Richardson; Wendy M Troxel; Madhumita Ghosh-Dastidar; Gerald P Hunter; Robin Beckman; Rebecca Collins; Stephanie Brooks Holliday; Alvin Nugroho; Lauren Hale; Daniel J Buysse; Matthew P Buman; Tamara Dubowitz
Journal:  J Epidemiol Community Health       Date:  2020-08-26       Impact factor: 3.710

9.  Large-scale investment in green space as an intervention for physical activity, mental and cardiometabolic health: study protocol for a quasi-experimental evaluation of a natural experiment.

Authors:  Thomas Astell-Burt; Xiaoqi Feng; Gregory S Kolt
Journal:  BMJ Open       Date:  2016-04-06       Impact factor: 2.692

10.  Getting Bigger, Quicker? Gendered Socioeconomic Trajectories in Body Mass Index across the Adult Lifecourse: A Longitudinal Study of 21,403 Australians.

Authors:  Xiaoqi Feng; Andrew Wilson
Journal:  PLoS One       Date:  2015-10-23       Impact factor: 3.240

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