Zero-inflated Negative Binomial Analysis Research Articles

A Study of Over-Dispersed Household Victimizations in South Korea: Zero-Inflated Negative Binomial Analysis of Korean National Crime Victimization Survey

Analyzing the Korean Crime Victim Survey data with employing zero-inflated negative binomial (ZINB) regression, the current study aims to identify the effect of immunity from criminal victimization and the determinants of household victimization in South Korea. The results show that there is a significant immunity effect on the distribution of household victimizations. Furthermore, lack of considering an immune effect may result in a misleading conclusion. As main determinants of victimizations in South Korea, communal efforts are found to be important. Theoretical explanation and policy implications are discussed.

Impact of high risk drug use on hospitalization and mortality in older people with and without Alzheimer's disease: a national population cohort study.

BackgroundEvidence is lacking about outcomes associated with the cumulative use of anticholinergic and sedative drugs in people with Alzheimer’s disease (AD). This retrospective cohort study investigated the relationship between cumulative exposure to anticholinergic and sedative drugs and hospitalization and mortality in people with and without AD in Finland.MethodsCommunity-dwelling people aged 65 years and over, with AD on December 31st 2005 (n = 16,603) and individually matched (n = 16,603) comparison persons (age, sex, region of residence) were identified by the Social Insurance Institution of Finland. Drug utilization data were extracted from the Finnish National Prescription Register. Exposure to anticholinergic and sedative drugs was defined using the Drug Burden Index (DBI). Hospitalization and mortality data were extracted from national registers. Cox and zero-inflated negative binomial analyses were used to investigate the relationship between DBI and hospitalization and mortality over a one-year follow-up.ResultsIn total, 5.8% of people with AD and 3.7% without AD died during 2006. For every unit increase in DBI, the adjusted hazard ratio for mortality was 1.21 (95% confidence intervals [CI]: 1.09–1.33) among people with AD, and 1.37 (95%CI: 1.20–1.56) among people without AD. Overall, 44.3% of people with AD and 33.4% without AD were hospitalized. When using no DBI exposure as the reference group, the adjusted incidence rate ratio for length of hospital stay among high DBI group (≥1) in people with AD was 1.15 (95%CI: 1.05–1.26) and 1.63 (95%CI: 1.41–1.88) in people without AD.ConclusionThere is a dose-response relationship between cumulative anticholinergic and sedative drug use and hospitalization and mortality in people with and without AD.

Impact of demographic characteristics in pet ownership: Modeling animal count according to owners income and age

Pet owner characteristics such as age, gender, income/social class, marital status, rural/urban residence and household type have been shown to be associated with the number of owned pets. However, few studies to date have attempted to evaluate these associations in Brazil. Accordingly, the aim of this study was to evaluate the association between age and income of owners and the number of owned dogs and cats in a Brazilian urban center. Pinhais, metropolitan area of Curitiba, Southern Brazil, the seventh largest city in Brazil, was chosen for this study. Questionnaires were administered door-to-door between January and February 2007 and data were analyzed by zero-inflated negative binomial (ZINB) models. A total of 13,555 of 30,380 (44.62%) households were interviewed. The majority (62.43%) of households reported having one or more dogs, with one or two dogs being the most common (29.97% and 19.71%, respectively). Cat ownership per household was much lower (P=0.001) than dog ownership, with 90% of the households reported having no owned cats. ZINB analyses indicated that income is not associated with the number of both dogs and cats among households that have pets. However, households from higher income categories were more likely to have dogs (but not cats) when compared to the lowest income category (P<0.05), contradicting a common belief that the poorer the family, the more likely they have pets. Certain age categories were significantly associated with the number of dogs or cats in households that have pets. In addition, most age categories were significantly associated with having dogs and/or cats (P<0.05). In conclusion, our study has found that age but not household income is associated with the number of dogs or cats in households that have pets; higher income households were more likely to have dogs when compared to low-income households.