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While there is considerable empirical evidence that social disorganization is positively associated with crime rates in urban areas, the empirical literature on rural social disorganization and crime faces three crucial limitations: inconsistent results, reliance on official crime statistics and the failure to test the full model. We overcome the two latter limitations via the British Crime Survey. Using data from respondents living in rural areas of 318 postcode sectors, we employed weighted least squares regression to estimate the effects of (1) the exogenous sources of social disorganization on our intervening measures of community organization and (2) all variables on victimization rates. This represents the first test of the full social disorganization model in the literature on rural crime and we find very little support for it. Our results suggest a reassessment of the conclusions drawn about how social disorganization and crime are related in rural communities. Adapted from the source document.

While there is considerable empirical evidence that social disorganization is positively associated with crime rates in urban areas, the empirical literature on rural social disorganization and crime faces three crucial limitations: inconsistent results, reliance on official crime statistics and the failure to test the full model. We overcome the two latter limitations via the British Crime Survey. Using data from respondents living in rural areas of 318 postcode sectors, we employed weighted least squares regression to estimate the effects of (1) the exogenous sources of social disorganization on our intervening measures of community organization and (2) all variables on victimization rates. This represents the first test of the full social disorganization model in the literature on rural crime and we find very little support for it. Our results suggest a reassessment of the conclusions drawn about how social disorganization and crime are related in rural communities.

Objective. To study the association between social disorganization and youth violence rates in rural communities. Method. We employed rural Missouri counties (N = 106) as units of analysis, measured serious violent victimization data via hospital records, and the same measures of social disorganization as Osgood and Chambers (2000). Controlling for spatial autocorrelation, the negative binomial estimator was used to estimate the effects of social disorganization on youth violence rates. Results. Unlike Osgood and Chambers, we found only one of five social disorganization measures, the proportion of female-headed households, to be associated with rural youth violent victimization rates. Conclusion. Although most research on social disorganization theory has been undertaken on urban areas, a highly cited Osgood and Chambers (2000) study appeared to extend the generalizeability of social disorganization as an explanation of the distribution of youth violence to rural areas. Our results suggest otherwise. We provide several methodological and theoretical reasons why it may be too early to draw strong conclusions about the generalizeability of social disorganization to crime rates in rural communities.

Research has found an aggregate association between heavy drinking and suicide rates in general, and in Russia specifically. Alcohol is one of the most serious drug problems facing Russian youth, yet the aggregate alcohol-suicide association has not been tested for this population. Aggregate mortality data for Russian regions (n = 78) for the year 2000 were used to measure youth (age 10–19) suicides and a proxy for societal heavy drinking. We employed the negative binomial estimator to test the heavy societal drinking-youth suicide hypothesis, controlling for other structural factors thought to influence suicide rates. The results showed a positive and significant association between the two for overall, male, and female rates. These results are consistent with studies of alcohol and suicide in Russia, suggesting youth suicide rates are influenced by levels of heavy drinking among youth and those close to them.

Between the 1980s and 2000s, the USA experienced wide swings in violence rates. These swings were not experienced equally across urban, suburban, and rural areas. We employed UCR and NCS/NCVS data to compare aggravated assaults rates in rural, suburban, and urban areas between 1988 and 2005. As expected, urban aggravated assault rates tended to remain the highest. However, the crime decline was much greater for urban relative to suburban and rural areas. Further, NCS/NCVS rates were not always higher than UCR rates for a given time and location. In the latter years, UCR–NCVS rate ratios were close to one for suburban and rural areas but remained about 1.5–2.0 in urban areas. This urban–nonurban difference has implications for testing criminological theories in non-urban areas.

The goal of this dissertation is to improve our understanding of violence in rural communities by addressing substantive and methodological gaps in the literature. I do this by comparing rural, suburban, and urban areas on three components of violence: trends, demographic explanations for trends, and measurement. Specifically, I addressed the following questions: (1) How do Uniform Crime Reporting Program (UCR) and National Crime Victimization Survey (NCVS) aggravated assault trends compare by rural, suburban, and urban location? (2) Do demographic changes in the population account for changes in aggravated assault trends in rural, suburban, and urban communities? (3) Are the same factors associated with police notification and emergency room treatment among victims of serious assaults, and are these associations moderated by rural, suburban, and urban location? The findings suggest the UCR and NCS/NCVS consistently show substantial rural and non-rural differences in violent crime trend patterns, demographic explanations for trends vary by rural and non-rural area, and there are few rural and non-rural differences in victim and incident characteristics associated with violent crime data sources. First, the UCR and NCS/NCVS exhibit similar aggravated assault rate patterns: non-rural rates decreased from the mid-1990s to the mid-2000s while rural rates increased slightly (UCR) or decreased more slowly (NCS/NCVS). Second, despite rural areas experiencing much smaller rate decreases from 1993 to 2005 than non-rural areas, demographic changes contributed much more to rate changes in rural compared to non-rural areas. Third, analyses reveal few victim and incident characteristics associated with victim emergency room treatment; many associated with police notification; and few associations moderated by rural, suburban, and urban location. In general, incident factors are associated with police notification more often than victim emergency room treatment. The methods used to address these questions and the results of the analyses provide important implications for future research. Particular attention should focus on the utilization of both the UCR and NCVS; accounting for demographic composition in violence studies within and between rural, suburban, and urban areas; and the role of sample selection bias in criminological research that utilizes police and/or emergency room data.

Various theories about drugs such as ACE inhibitors or angiotensin II receptor blockers (ARBs) in relation to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and clinical outcomes of COVID-19 are circulating in both mainstream media and medical literature. These are based on the fact that ACE2 facilitates SARS-CoV-2 cell invasion via binding of a viral spike protein to ACE2. However, the effect of ACE inhibitors, ARBs and other drugs on ACE2 is unclear and all theories are based on conflicting evidence mainly from animal studies. Therefore, clinical evidence is urgently needed. The aim of this study is to investigate the relationship between use of these drugs on clinical outcome of patients with COVID-19. Patients will be included from several hospitals in Europe. Data will be collected in a user-friendly database (Digitalis) on an external server. Analyses will be adjusted for sex, age and presence of cardiovascular disease, hypertension and diabetes. These results will enable more rational choices for randomised controlled trials for preventive and therapeutic strategies in COVID-19.