How Does Crime-Specific Victimization Impact Fear of Crime in Urban China? The Role of Neighborhood Characteristics

Past research has failed to find consistent relationships between criminal victimization and fear of crime. Except for neighborhood disorder and crime rate, few studies have examined whether other neighborhood conditions matter the victimization—fear relationship. Using survey data in Guangzhou neighborhoods, the present analysis employs multinomial logistic regression models to examine whether neighborhood characteristics moderate the relationship between violent victimization and fear of violence, and between burglary victimization and fear of burglary, separately. Some aspects of the neighborhood environment do differentially influence victims’ and non-victims’ fear levels. Besides verifying the interaction effect of neighborhood disorder and victimization, the present study finds that neighborhood policing alleviates the harmful effect of violent victimization on fear, while collective efficacy fosters the harmful effect of burglary victimization on fear. This paper underscores the significance of the social context of urban China in explaining the interplay of neighborhood characteristics and victimization on fear of crime.

Adverse Neighborhood Environments and Health Behaviors among Older Americans

Maintaining healthy lifestyle, including healthy diet and physical activity, in adverse neighborhood environments may be more difficult for older adults because of changes linked to aging, which make them more vulnerable to their environments. This study aims to investigate the association of neighborhood disorder with diet quality and physical activity in a national sample of older Americans. For this study, we used data from the Health and Retirement Study. Neighborhood disorders include vandalism, boarded houses, abandoned cars, demolished houses, trash, litter, or junk, poorly kept communal areas, homeless people, prostitution, winos or junkies, and drug use or drug dealing near residents’ housing unit (range: 0-11). Diet quality and physical activity were assessed using the Healthy Eating Index 2015 (HEI-2015; range:0-100) and the metabolic (MET) equivalent activity points (range: 0-31 in this sample). Ordinary least squares regression models were estimated to examine an association between neighborhood disorder, diet quality, and physical activity. Neighborhood disorder was associated with poor diet and physical inactivity. For one additional negative neighborhood feature, HEI-2015 scores and MET-equivalent activity points decreased by 0.55 (95% CI: -1.09. -0.01) and 0.69 (95% CI: -1.05, -0.33). Findings of this study suggest that older adults living in adverse neighborhoods are at a greater risk of poor diet and physical inactivity, which are important risk factors for poor health and chronic diseases. Promoting neighborhood environments and perceived neighborhood safety would increase access to health food, encourage healthy diet and physical activity, and support healthy aging.

Housing Cost Burden and Well-Being in Older Adults Moderated by Neighborhood Cohesion and Disorder

Although aging in the community promotes well-being in older adults, contextual factors (e.g., housing cost burden, neighborhood cohesion, neighborhood disorder) may impact this relationship. Identifying such risk factors represents a first step toward improving older adult well-being. NHATS data (Rounds 5–8) were used to answer two research questions (RQs). RQ1: “Is housing cost burden significantly associated with well-being?” RQ2: “Is this association further moderated by neighborhood cohesion and neighborhood disorder?” Participants were 18,311 adults ≥ 65 years old. Well-being was assessed by summing 11 commonly identified indicators. Two items were merged to assess housing cost burden (categories: “no burden,” “no money for utilities,” “no money for rent,” and “no money for utilities or rent”). Neighborhood cohesion and disorder were combined (categories: “no cohesion, no disorder,” “yes cohesion, no disorder,” “no cohesion, yes disorder,” and “yes cohesion, yes disorder”). Both RQs were assessed through a random coefficient model controlling for established covariates. RQ1 results revealed that, compared to “no burden,” “no money for utilities or rent” (B = −1.22, p = .003) and “no money for rent” (B = −1.50, p = .007) were significantly associated with well-being. RQ2 results revealed that “no cohesion, no disorder” significantly moderated the association between “no money for utilities or rent” and well-being (B = −2.44, p = .011). These results indicate that increased housing cost burden is associated with decreased well-being, especially for those reporting no neighborhood cohesion. Future research should examine neighborhood-level protective factors promoting cohesion for older adults to support well-being.

Perceived Neighborhood Disorder, Social Cohesion, and Depressive Symptoms among Spousal Caregivers

Most prior research on caregivers’ mental health focused on individual or household factors, we know much less about the influence of neighborhood factors on mental health of spousal caregivers. The current study fills the gap in our knowledge by examining the association of neighborhood characteristics (i.e., perceived neighborhood disorder and neighborhood social cohesion) and depressive symptoms among spousal caregivers. We used data from 2006 to 2016 waves of the Health and Retirement Study, which includes 2,362 spousal caregivers. Negative binomial regression models were estimated to examine the association of perceived neighborhood disorder and neighborhood social cohesion with depressive symptoms. A greater perceived neighborhood disorder was associated with higher CES-D scores, which indicates more depressive symptoms. On the other hand, a higher level of neighborhood social cohesion was associated with lower CES-D scores. When they were included in the same model, the association between neighborhood disorder and depression disappeared, while respondents who reported higher levels of neighborhood social cohesion continue to exhibit lower CES-D scores than those lived in less cohesive neighborhoods. This study highlights the importance of neighborhood contexts in understanding caregivers’ well-being. Findings of this study suggest that neighborhood social cohesion may attenuate the negative effects of neighborhood disorder. Therefore, enhancing positive characteristics of the neighborhood may promote well-being of spousal caregivers.

Evaluating Community Factors Associated With Individually Held Intimate Partner Violence Beliefs Across 51 Countries

Globally, one in three women will experience intimate partner violence (IPV) within her lifetime. IPV attitudes are highly predictive of IPV. While a wealth of literature on risk factors related to IPV exist, an overarching critique in the field is the lack of studies examining risk factors across the socioecological framework. Using data from multiple administrative and individual surveys, this study fills a gap in the literature by evaluating the effect of meso-influences on physical IPV attitudes (i.e., permissibility of a man beating his wife) while accounting for known micro- and macro-risk factors in 64,466 individuals across 51 low-, middle- and high-income countries. Mixed-effects modeling was used to evaluate factors and identify comparative contributions of each factor representing the socio-ecological levels. We tested five multivariate logistic models. The final model indicated that greater perceived neighborhood disorder and less perceived neighborhood security were associated with physical IPV attitudes, while individual endorsement of interpersonal violence, belief in corporal punishment of children, holding greater patriarchal beliefs, being male, being separated from a significant partner, reporting greater household hunger and nationally lower levels of female literacy were associated with beliefs that IPV is acceptable. Overall, the findings of this study support that IPV is a complex behavior, influenced by factors across socio-ecological domains. However, data on neighborhood structural factors (i.e., exosystem) would help unpack the mechanisms between macro-, meso- and micro-level factors and may be important for protecting women from violence.

Pathways between objective and perceived neighborhood factors among Black breast cancer survivors

Background Mounting evidence supports associations between objective neighborhood disorder, perceived neighborhood disorder, and health, yet alternative explanations involving socioeconomic and neighborhood social cohesion have been understudied. We tested pathways between objective and perceived neighborhood disorder, perceived neighborhood social cohesion, and socioeconomic factors within a longitudinal cohort. Methods Demographic and socioeconomic information before diagnosis was obtained at interviews conducted approximately 10 months post-diagnosis from participants in the Women’s Circle of Health Follow-up Study – a cohort of breast cancer survivors self-identifying as African American or Black women (n = 310). Neighborhood perceptions were obtained during follow-up interviews conducted approximately 24 months after diagnosis. Objective neighborhood disorder was from 9 items audited across 23,276 locations using Google Street View and scored to estimate disorder values at each participant’s residential address at diagnosis. Census tract socioeconomic and demographic composition covariates were from the 2010 U.S. Census and American Community Survey. Pathways to perceived neighborhood disorder were built using structural equation modelling. Model fit was assessed from the comparative fit index and root mean square error approximation and associations were reported as standardized coefficients and 95% confidence intervals. Results Higher perceived neighborhood disorder was associated with higher objective neighborhood disorder (β = 0.20, 95% CI: 0.06, 0.33), lower neighborhood social cohesion, and lower individual-level socioeconomic factors (final model root mean square error approximation 0.043 (90% CI: 0.013, 0.068)). Perceived neighborhood social cohesion was associated with individual-level socioeconomic factors and objective neighborhood disorder (β = − 0.11, 95% CI: − 0.24, 0.02). Conclusion Objective neighborhood disorder might be related to perceived disorder directly and indirectly through perceptions of neighborhood social cohesion.