Examining the Association Between Massage Parlors and Neighborhood Crime

2018 ◽  
Vol 65 (11) ◽  
pp. 1537-1569 ◽  
Author(s):  
Jessica Huff ◽  
Danielle Wallace ◽  
Courtney Riggs ◽  
Charles M. Katz ◽  
David Choate
Keyword(s):  
Management System ◽  
Autoregressive Models ◽  
Physical Disorder ◽  
Record Management ◽  
Social Disorder ◽  
Neighborhood Crime ◽  
Spatial Autoregressive ◽  
Spatial Autoregressive Models ◽  
The Impact ◽  
User Review

Although massage parlors have been associated with illicit activities including prostitution, less is known about their association with neighborhood crime. Employing the Computer Automated Dispatch/Record Management System (CAD/RMS), online user review, licensing, Census, and zoning data, we examine the impact of massage parlors on crime in their surrounding neighborhoods. Using spatial autoregressive models, our results indicate the total number of massage parlors was associated with increased social disorder. The presence of illicit massage parlors in adjacent neighborhoods was associated with crime and physical disorder in the focal neighborhoods. This study has consequences for how police address crime associated with massage parlors. Specifically, the use of online user review forums could be an effective way to identify illicit massage parlors. Recommendations for policing and code enforcement are discussed.

scholarly journals Vulnerability of agriculture to climate change increases the risk of child malnutrition: Evidence from a large-scale observational study in India

PLoS ONE ◽  
2021 ◽  
Vol 16 (6) ◽  
pp. e0253637
Author(s):  
Bidhubhusan Mahapatra ◽  
Monika Walia ◽  
Chitiprolu Anantha Rama Rao ◽  
Bellapukonda Murali Krishna Raju ◽  
Niranjan Saggurti
Keyword(s):  
Climate Change ◽  
Food Security ◽  
Child Nutrition ◽  
Autoregressive Models ◽  
Child Malnutrition ◽  
Mixed Effect ◽  
Spatial Autoregressive ◽  
Micro Level ◽  
Spatial Autoregressive Models ◽  
The Impact

Introduction The impact of climate change on agriculture and food security has been examined quite thoroughly by researchers globally as well as in India. While existing studies provide evidence on how climate variability affects the food security and nutrition, research examining the extent of effect vulnerability of agriculture to climate change can have on nutrition in India are scarce. This study examined a) the association between the degree of vulnerability in agriculture to climate change and child nutrition at the micro-level b) spatial effect of climate vulnerability on child nutrition, and c) the geographical hotspots of both vulnerability in agriculture to climate change and child malnutrition. Methods The study used an index on vulnerability of agriculture to climate change and linked it to child malnutrition indicators (stunting, wasting, underweight and anaemia) from the National Family Health Survey 4 (2015–16). Mixed-effect and spatial autoregressive models were fitted to assess the direction and strength of the relationship between vulnerability and child malnutrition at macro and micro level. Spatial analyses examined the within-district and across-district spill-over effects of climate change vulnerability on child malnutrition. Results Both mixed-effect and spatial autoregressive models found that the degree of vulnerability was positively associated with malnutrition among children. Children residing in districts with a very high degree of vulnerability were more like to have malnutrition than those residing in districts with very low vulnerability. The analyses found that the odds of a child suffering from stunting increased by 32%, wasting by 42%, underweight by 45%, and anaemia by 63% if the child belonged to a district categorised as very highly vulnerable when compared to those categorised as very low. The spatial analysis also suggested a high level of clustering in the spatial distribution of vulnerability and malnutrition. Hotspots of child malnutrition and degree of vulnerability were mostly found to be clustered around western-central part of India. Conclusion Study highlights the consequences that vulnerability of agriculture to climate change can have on child nutrition. Strategies should be developed to mitigate the effect of climate change on areas where there is a clustering of vulnerability and child malnutrition.

scholarly journals Application of Hierarchical Spatial Autoregressive Models to Develop Land Value Maps in Urbanized Areas

2019 ◽  
Vol 8 (4) ◽  
pp. 195 ◽  
Author(s):  
Cellmer ◽  
Kobylińska ◽  
Bełej
Keyword(s):  
Linear Model ◽  
Empirical Studies ◽  
Hierarchical Linear Model ◽  
Autoregressive Models ◽  
Land Value ◽  
Property Market ◽  
Spatial Autoregressive ◽  
Urbanized Areas ◽  
Spatial Autoregressive Models ◽  
The Impact

This article aims at testing the possibilities of applying hierarchical spatial autoregressive models to create land value maps in urbanized areas. The use of HSAR (Hierarchical Spatial Autoregressive) models for spatial differentiation of prices in the property market supports the multilevel diagnosis of the structure of this phenomenon, taking into account the effect of spatial interactions. The article applies a two-level hierarchical spatial autoregressive model, which will permit the evaluation of interactions and control spatial heterogeneity at two levels of spatial aggregation (general and detailed). The results of the research include both the evaluation of the impact of location on prices (taking into account non-spatial factors) and the creation of the average land price map, taking into consideration the spatial structure of the city. In empirical studies, the HSAR model was compared with classic LM (Linear Model), HLM (Hierarchical Linear Model), and SAR (Spatial Autoregressive) models to perform comparative analyses of the results.

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