Análise espacial de óbitos por acidentes de trânsito, antes e após a Lei Seca, nas microrregiões do estado de São Paulo

Nunes, Marcela Neves; Nascimento, Luiz Fernando Costa

doi:10.1590/s0104-42302012000600013

Cited by 10 publications

(4 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The majority of studies were concerned with road traffic injuries ( n = 36) (Chakravarthy et al 2010; Cinnamon et al 2011; DiMaggio 2015; Dissanayake et al 2009; Durkin et al 2005; Eksler and Lassarre 2008; Eksler et al 2008; Erdogan 2009; Haynes et al 2005; Haynes et al 2008; Hijar et al 2003; Hosking et al 2013; Hu et al 2008; Huff et al 2012; Jones et al 2008; La Torre et al 2007; Lassarre and Thomas 2005; Lateef 2011; Lawrence et al 2015; Mohan et al 2015; Morency and Cloutier 2006; Nagata et al 2011; Nunes and Nascimento 2012; Nunn and Newby 2015; Paulozzi 2006; Poulos et al 2012; Razzak et al 2011; Schuurman et al 2009; Silva et al 2011; Slaughter et al 2014; Spoerri et al 2011; Statter et al 2011; Sukhai et al 2009; Unni et al 2012; Weiner and Tepas 2009; Yan-Hong et al 2006). Other studies considered falls ( n = 11) (Bamzar and Ceccato 2015; Chan et al 2012; de Pina et al 2008; Dey et al 2010; Lai et al 2009a; Lai et al 2009b; Lai et al 2011; Morency et al 2012; Towne et al 2015; Turner et al 2009; Yiannakoulias et al 2003), burns ( n = 9) (Edelman et al 2010; Fouillet et al 2006; Goltsman et al 2014; Harlan et al 2013; Heng et al 2015; Mian et al 2014; Niekerk et al 2006; Stylianou et al 2015; Williams et al 2003), drowning ( n = 4) (Dai et al 2013; Maples and Tiefenbacher 2009; Sharif et al 2012; Shenoi et al 2015), occupational ( n = 2) (Breslin et al 2007; Forst et al 2015), aviation-related ( n = 2) (Grabowski et al 2002a, 2002b), poisoning ( n = 1) (Nkhoma et al 2004), natural disaster ( n = 1) (Peek-Asa et al 2000) and dog-bite ...…”

Section: Resultsmentioning

confidence: 99%

An overview of geospatial methods used in unintentional injury epidemiology

et al. 2016

View full text Add to dashboard Cite

BackgroundInjuries are a leading cause of death and disability around the world. Injury incidence is often associated with socio-economic and physical environmental factors. The application of geospatial methods has been recognised as important to gain greater understanding of the complex nature of injury and the associated diverse range of geographically-diverse risk factors. Therefore, the aim of this paper is to provide an overview of geospatial methods applied in unintentional injury epidemiological studies.MethodsNine electronic databases were searched for papers published in 2000–2015, inclusive. Included were papers reporting unintentional injuries using geospatial methods for one or more categories of spatial epidemiological methods (mapping; clustering/cluster detection; and ecological analysis). Results describe the included injury cause categories, types of data and details relating to the applied geospatial methods.ResultsFrom over 6,000 articles, 67 studies met all inclusion criteria. The major categories of injury data reported with geospatial methods were road traffic (n = 36), falls (n = 11), burns (n = 9), drowning (n = 4), and others (n = 7). Grouped by categories, mapping was the most frequently used method, with 62 (93%) studies applying this approach independently or in conjunction with other geospatial methods. Clustering/cluster detection methods were less common, applied in 27 (40%) studies. Three studies (4%) applied spatial regression methods (one study using a conditional autoregressive model and two studies using geographically weighted regression) to examine the relationship between injury incidence (drowning, road deaths) with aggregated data in relation to explanatory factors (socio-economic and environmental).ConclusionThe number of studies using geospatial methods to investigate unintentional injuries has increased over recent years. While the majority of studies have focused on road traffic injuries, other injury cause categories, particularly falls and burns, have also demonstrated the application of these methods. Geospatial investigations of injury have largely been limited to mapping of data to visualise spatial structures. Use of more sophisticated approaches will help to understand a broader range of spatial risk factors, which remain under-explored when using traditional epidemiological approaches.Electronic supplementary materialThe online version of this article (doi:10.1186/s40621-016-0097-0) contains supplementary material, which is available to authorized users.

show abstract

Section: Resultsmentioning

confidence: 99%

An overview of geospatial methods used in unintentional injury epidemiology

et al. 2016

View full text Add to dashboard Cite

show abstract

“…O acesso facilitado à compra das bebidas alcoólicas, o baixo custo e a influência midiática contribuem para o aumento do consumo de álcool [20][21][22][23] e, consequentemente, para o aumento da ocorrência de acidentes automobilísticos associados com a presença de motoristas alcoolizados 12,13,19,20,23 .…”

Section: Discussionunclassified

Análise das causas dos acidentes automobilísticos nas rodovias federais da Bahia entre 2014 e 2017

Ribeiro¹,

Pimentel²,

Ribeiro³

et al. 2020

Rev. Med. (São Paulo)

View full text Add to dashboard Cite

Estimativas indicam que milhões de pessoas morrem por ano em decorrência de acidentes de trânsito. Por se tratar de um assunto tão sério que, muitas vezes é negligenciado pelas autoridades políticas, o presente estudo teve como objetivo analisar as principais causas dos acidentes automobilísticos nas rodovias federais da Bahia, considerada uma das regiões mais violentas quando o assunto é trânsito. Como material de investigação foi analisado o relatório de acidentes produzido pela Superintendência Regional da Bahia da Polícia Rodoviária Federal no período de 2014 e 2017. Os dados foram tabulados no Software Estatístico SPSS e analisados posteriormente. As causas foram agrupadas em categorias semelhantes. Os resultados mostram que, apesar do número de acidentes em 2017 ter reduzido quando comparado aos anos de 2014 e 2015, os acidentes tornaram-se mais graves na região e estiveram associados com uma maior porcentagem de óbitos. Os dados também indicam que os eventos em que havia ocorrido o consumo de álcool ou de substâncias psicotrópicas são mais graves e produzem um número maior de óbitos. Considerando as categorias apresentadas, a “atitudes imprudentes do condutor” foi a principal causa dos acidentes nas rodovias federais da Bahia no período analisado, principalmente, em decorrência do desrespeito às leis de trânsito.

show abstract

“…The implementation of preventive and corrective measures, based on studies using the Geographic Information System, provides spatial analysis through the surveillance of land transport accidents and allows the planning of preventive and protective measures for the affected populations in a timely manner 9,25 . In a spatial analysis study of deaths from traffic accidents in the micro-regions of the state of São Paulo, it is possible to identify the places with the highest mortality rates, allowing inspection actions to prevent accidents 26 . Therefore, the potential of studies that use data georeferencing in urban centers can be seen, in order to identify the critical points for health promotion and accident prevention interventions.…”

Section: Discussionmentioning

confidence: 99%

Spatial analysis of traffic accidents involving older adults in a city in the northeast of Brazil

Furtado

Bonfim

Fernandes

et al. 2020

Rev. bras. geriatr. gerontol.

View full text Add to dashboard Cite

Objective: to describe the epidemiological characteristics of traffic accidents involving older victims, responded to by the Mobile Emergency Service (or SAMU), and to analyze the spatial distribution of these events in the city of Olinda, Pernambuco, Brazil, from 2015 to 2018. Method: a composite cross-sectional study was performed, using SAMU service records as a data source. Descriptive statistics were applied, based on frequency distribution. For the mapping and detection of spatial clusters, the Kernel intensity estimator was used. Results: SAMU responded to 137 traffic accidents with older victims. The most affected age group were older adults aged 60 to 69 years (81; 59.1%), and there was a predominance of male victims (90; 65.7%). The day of the week when most accidents occurred was Wednesday (29; 21.25%), and the highest number of accidents occurred in the morning (46; 33.6%). As for the nature of the accident, accidents involving pedestrians (80; 58.4) predominated over collisions (57; 41.6%). The Kernel intensity estimator identified a significant focus in the Peixinhos neighborhood, with other foci distributed throughout the coastal area. Conclusion: the study identified the characteristics of older victims of traffic accidents and areas of greatest risk for their occurrence in the city studied. This information can be useful when planning environmental engineering measures to be carried out in the regions identified, in order to reduce the frequency of accidents and injuries.

show abstract

Análise espacial de óbitos por acidentes de trânsito, antes e após a Lei Seca, nas microrregiões do estado de São Paulo

Abstract: It was possible to identify the places with higher mortality rates, pointing out locations where enforcement actions should be reviewed.

Cited by 10 publications

References 15 publications

An overview of geospatial methods used in unintentional injury epidemiology

An overview of geospatial methods used in unintentional injury epidemiology

Análise das causas dos acidentes automobilísticos nas rodovias federais da Bahia entre 2014 e 2017

Spatial analysis of traffic accidents involving older adults in a city in the northeast of Brazil

Contact Info

Product

Resources

About