Summary
It is often believed that communities with high crime rates tend to have many social and health-related problems. In addition to this, such communities have problems linked to adolescent development and weakened local institutions. As evidenced in Weisburd and White’s (2019) article, high-crime neighborhoods characterized by poverty tend to suffer more from health-related problems such as chronic diseases. In fact, crime levels in the neighborhood are one of the major risk factors as far as health problems are concerned. Despite this realization, the scholars noted that health outcomes had not been given the necessary attention: much focus is extended to situational context and crime. Overall, Weisburd and White’s aim in writing the article was to determine whether or not there is a direct relationship between health disparity and crime.
Current Study
In this current study, the authors used data obtained from the survey carried out in Baltimore, Maryland, to find out the relationship between crime and health disparity at a micro-geographic level. More specifically, the data comprises health outcomes such as depression, quality of life, post-traumatic stress disorders and history of a diagnosed disease. The calls for service recorded by the police further showed high crime levels in over 300 street segments. Some of these segments as highlighted in the article, include Cold, Cool, Drug, Violent and Combined Spots. The cold spots as discussed in the sample and data collection section, refer to the streets with less than three crime calls for drug or violent crime. The rest of the non-hot spot streets are categorized as cool spots.
Sample and Data Collection
The study depended more on the data from residential surveys collected between September 2013 and May, 2014. However, to achieve this, Weisburd and White (2019) utilized a multi-stage cluster sampling method as their preferred sampling strategy. This strategy is highly flexible as it allows researchers to choose the sample carefully. In fact, this method allowed them to start with a sample of 25,045 street segments which was further reduced to 4,630. Additionally, Weisburd and White (2019) used violent and drug crimes as the primary indicators of crime hot spots. It is this approach that allowed them to identify three categories of hot spots violent crime, drug crime and combined hot spots. After selecting the street segments for the sample, the team was required to undertake a pre-visit. This process was undertaken by a team of trained field researchers whose main task was to conduct a census of both the building and residency units. The findings helped them come up with a sampling frame for the residential survey
Health Measures and Data Analysis
The article incorporated several measures in the survey in order to establish whether or not individuals living in crime hot spots experienced adverse health problems compared to those in non-hot spot areas. Firstly, the survey integrated questions on different types of diseases, such as breast cancer, depression, diabetes and asthma. Secondly, health scales from RAND were used to assess the quality of health, specifically how health limits an individual’s ability to complete daily social and work activities (Weisburd and White, 2019). Items such as a lot, a little, or not at all were used in arriving at an informed decision with regard to daily activities. In addition to this, items such as all the time, most of the time, some of the time, or not at all were used in establishing a common pattern in both social and work activities.
The scholars as well adopted the mental health problems as a critical health measure. Here, the authors utilized two symptomology scales that allowed them to measure both the symptoms of depression and post-traumatic stress disorder (PTSD). The scale consisted of nine items to assess behaviors such as trouble concentrating and social withdrawal that is associated with depression. However, in an effort to obtain valid findings on PTSD, Weisburd and White (2019) relied on a screening scale based on the Diagnostic and Statistical Manual of Mental Disorders. Regarding data analysis, the authors performed a chi-square test based on the categorical level of variables assessed. The aim was to find significant health outcomes in different street segments.
Results
Weisburd and White presented their results in different categories and tables, with the first category being the health conditions the respondents were diagnosed with at some point in their life. While there were significant differences in high blood pressure, lung disease, and other types of cancer across the street segments, there was no major variation in diabetes, heart disease, arthritis, and breast cancer. More specifically, 35.8% of individuals living in combined hot spots reported being diagnosed with high blood pressure compared to 23.7% of those in cold spots. The second category comprised of findings from different health scales. According to Weisburd and White (2019), the individuals living in combined hot spots admitted that their health was either poor or very poor compared to those living in cod spots. For example, 7.3% of those residing reported their health as being poor compared to 2.7% of those in a cold spot.
The third category revolves around how health affects daily life with the findings showing the impact being greater among those living in high-crime streets. For instance, 1.1% of people living in cold spots noted that their health affected their ability to walk on blocks compared to 10.1% of those in combined hot spots. The last category consists of the findings on mental health measures. According to the findings, the majority of the respondents in crime hot spots reported significant mental health problems. For example, 23 percent of residents living in combined hot spots reported being diagnosed with depression in the past.
Discussion
The aim of this study was to determine whether or not there is a direct relationship between health disparity and crime at the micro-geographic level. Based on the findings, it is clear that residents of hot spots area are more likely to experience chronic diseases such as high blood pressure and lung diseases. Weisburd and White further added that the rates of these diseases are sometimes three times higher in crime hot spots compared to those living in areas with no crime. Similarly, the findings showed that the measures of health status and quality of health are low in areas with high crime rates. In fact, health problems, specifically lung cancer and diabetes, were found to hinder the ability of residents to perform their daily activities. Another essential point raised in the article is that mental health problems are high in areas with a high crime rate. One important thing, as evidenced throughout the study, is that crime levels vary from one street to another. Therefore, a major implication from this is that public health interventions should be offered in need, specifically at the micro-geographic level.
Reference
Weisburd, D., & White, C. 2019. “Hot Spots of Crime Are Not Just Hot Spots of Crime: Examining Health Outcomes at Street Segments”. Journal of Contemporary Criminal Justice, 35(2):142-160.