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Impact of some types of mass gatherings on current suicide risk in an urban population: statistical and negative binominal regression analysis of time series.

ABSTRACT: BACKGROUND:Many studies have investigated the impact of a wide range of social events on suicide-related behaviour. However, these studies have predominantly examined national events. The aim of this study is to provide a statistical evaluation of the relationship between mass gatherings in some relatively small urban sub-populations and the general suicide rates of a major city. METHODS:The data were gathered in the Ukrainian city of Dnipropetrovsk, with a population of 1 million people, in 2005-2010. Suicide attempts, suicides, and the total amount of suicide-related behaviours were registered daily for each sex. Bivariate and multivariate statistical analysis, including negative binomial regression, were applied to assess the risk of suicide-related behaviour in the city's general population for 7 days before and after 427 mass gatherings, such as concerts, football games, and non-regular mass events organized by the Orthodox Church and new religious movements. RESULTS:The bivariate and multivariate statistical analyses found significant changes in some suicide-related behaviour rates in the city's population after certain kinds of mass gatherings. In particular, we observed an increased relative risk (RR) of male suicide-related behaviour after a home defeat of the local football team (RR?=?1.32, p?=?0.047; regression coefficient beta?=?0.371, p?=?0.002), and an increased risk of male suicides (RR?=?1.29, p?=?0.006; beta =0.255, p?=?0.002), male suicide-related behaviour (RR?=?1.25, p?=?0.019; beta =0.251, p?

SUBMITTER: Usenko VS

PROVIDER: S-EPMC4021406 | biostudies-literature | 2014 Apr

REPOSITORIES: biostudies-literature

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Impact of some types of mass gatherings on current suicide risk in an urban population: statistical and negative binominal regression analysis of time series.

Usenko Vasiliy S VS Svirin Sergey N SN Shchekaturov Yan N YN Ponarin Eduard D ED

BMC public health 20140404

<h4>Background</h4>Many studies have investigated the impact of a wide range of social events on suicide-related behaviour. However, these studies have predominantly examined national events. The aim of this study is to provide a statistical evaluation of the relationship between mass gatherings in some relatively small urban sub-populations and the general suicide rates of a major city.<h4>Methods</h4>The data were gathered in the Ukrainian city of Dnipropetrovsk, with a population of 1 million ...[more]

PMID: 24708574

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Project description:Although regression models play a central role in the analysis of medical research projects, there still exist many misconceptions on various aspects of modeling leading to faulty analyses. Indeed, the rapidly developing statistical methodology and its recent advances in regression modeling do not seem to be adequately reflected in many medical publications. This problem of knowledge transfer from statistical research to application was identified by some medical journals, which have published series of statistical tutorials and (shorter) papers mainly addressing medical researchers. The aim of this review was to assess the current level of knowledge with regard to regression modeling contained in such statistical papers. We searched for target series by a request to international statistical experts. We identified 23 series including 57 topic-relevant articles. Within each article, two independent raters analyzed the content by investigating 44 predefined aspects on regression modeling. We assessed to what extent the aspects were explained and if examples, software advices, and recommendations for or against specific methods were given. Most series (21/23) included at least one article on multivariable regression. Logistic regression was the most frequently described regression type (19/23), followed by linear regression (18/23), Cox regression and survival models (12/23) and Poisson regression (3/23). Most general aspects on regression modeling, e.g. model assumptions, reporting and interpretation of regression results, were covered. We did not find many misconceptions or misleading recommendations, but we identified relevant gaps, in particular with respect to addressing nonlinear effects of continuous predictors, model specification and variable selection. Specific recommendations on software were rarely given. Statistical guidance should be developed for nonlinear effects, model specification and variable selection to better support medical researchers who perform or interpret regression analyses.

Project description:BackgroundMass gathering (MG) events may cause delayed emergency responses via various mechanisms and strain the resources of local emergency services. Therefore, preparedness, including adequate pre-planning and sufficient resourcing during MG events, is vital. The aim of this retrospective register study was to investigate the impact of MG events on the workload of rescue and emergency medical service (EMS) personnel during events to enable more precise and sufficient deployment of these authorities' operative resources.MethodsThe data from Finland covered of 25,124 EMS and rescue service missions during a three-year period (2015-2017), including data from nine MG events and reference material for the same weekdays two weeks before and after the event. The data were analysed through statistical and geospatial analyses.ResultsOur findings showed that missions increased in most events included in this study. Analysis of the missions' reasons showed that the categories of violence, traffic accidents and other accidents and injuries increased during events, with violence-related missions showing the highest relative risk (RR 1.87, 95% CI 1.43-2.44). In the four-grade (A-D) urgency grading, the analysis showed an increase in category C missions and a decrease in non-urgent category D missions. The analysis indicated an increase in missions during the evening and night-time. The geospatial analysis revealed dense hotspots of missions in the vicinity of the event area.ConclusionThe workload for EMS and rescue service personnel increases during MG events. Most of the increase is allocated to EMS staff, peaking in evening and night hours. The geospatial analysis showed hotspots of missions on the outskirts of the actual event area during events; thus, the workload can also increase for those authority resources that are not directly allocated to the event. Detailed information regarding workloads is valuable for the authorities that are responsible for resource planning and preparedness for MG events. Replicating the study internationally would improve the methodology for the future.

Dataset Information

Impact of some types of mass gatherings on current suicide risk in an urban population: statistical and negative binominal regression analysis of time series.

Publications

Impact of some types of mass gatherings on current suicide risk in an urban population: statistical and negative binominal regression analysis of time series.

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