Identifying developmental trajectories of worldwide road traffic accident death rates using a latent growth mixture modeling approach.
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ABSTRACT:
SUBMITTER: Salehi M
PROVIDER: S-EPMC6382161 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Background: Post-traumatic stress disorder (PTSD) occurs after exposure to actual or threatened death, serious injury, or sexual violence. Road traffic accident (RTA) is one of the traumatic experiences, which may result in PTSD. But treatment is mainly concentrated on physical health. This may be due to a lack of evidence in low-income countries. Aim: To determine the incidence level and identify risk factors of PTSD after RTA. Methods: Longitudinal panel study was done to assess the incidence of PTSD after RTA. The study was conducted in three orthopedic settings of Bahir Dar town Northwest, Ethiopia. The study was on 299 adult car accident survivors. PTSD Checklist (PCL) civilian version, Sheehan disability assessment scale, Patient Health Question (PHQ-2), and Alcohol Use Disorder Identification Test (AUDIT) were instruments to assess the outcome and associated factors. The generalized linear model with Poisson log-linear method was applied to identify associated factors. Ethical clearance was obtained from Bahir Dar University. Individuals with PTSD symptoms were linked to the psychiatric clinic. Result: One hundred thirty-nine (46.5%) participants had at least three extremely severe symptoms that fulfil criteria B, C, and D of Diagnostic Statistical Manual IV of PTSD. The most frequent severe symptoms were having repeated, disturbing memories, thoughts, or images. Two hundred ten (70.2%) participants reported the extreme impact of the accident on work or schooling and 156 (51.9%) reported extreme problems in social functioning. Alcohol dependence, hazardous alcohol consumption, and harmful use were reported by 7.9%, 15.1%, and 4.7% of the participants, respectively. In the final model witnessing death, severe sleep problem and severe impairment in family functioning were significantly associated with PTSD. Conclusion: Nearly half of RTA survivors develop PTSD. Clinicians need to link these patients to the psychiatry clinic. Special attention should be given to patients who witnessed death, with a serious disability, and previous psychiatric history.
| S-EPMC6659351 | biostudies-literature
Project description:Increased traffic volumes worldwide have resulted in an increased number of road accident injuries and mortalities. This global phenomenon motivated the United Nations (UN) to initiate a decade-long global road safety plan in 2010. In response, Saudi Arabia concurrently initiated a comprehensive road safety program, supported by detailed and comprehensive road safety data for the Eastern Province (EP) of Saudi Arabia. The contributed EP-Traffic-Mortality-and-Policy-Interventions Dataset provides multidimensional road safety data for 2010-2020 via two primary and five secondary data subsets. The first primary subset provides road accident mortality data. The five secondary data subsets reflect road accident mortalities at different time scales and administrative (provincial or governorate) levels. The second primary subset provides details of traffic safety policy interventions implemented during the same period. Researchers and policymakers can use this comprehensive dataset to study accident mortality patterns across various geospatial and time scales and analyze the effectiveness of policies intended to mitigate road accident mortalities.
| S-EPMC9363955 | biostudies-literature
Project description:BACKGROUND:Road traffic accident (RTA), an unexpected traumatic event, may not only lead to death and serious physical injuries, but also could put survivors at an increased risk for a wide range of psychiatric disorders, particularly acute stress disorder (ASD). Early assessment of trauma-related psychological responses is important because acute trauma responses in the early post-traumatic period are among the robust predictors of long-term mental health problems. However, estimates of the prevalence of ASD among RTA survivors varied considerably across studies. Therefore, this meta-analysis aimed to identify the pooled prevalence of ASD among RTA survivors. METHODS:A systematic literature search in the databases of PubMed, PsycINFO, PsycARTICLES, Embase and Web of Science was performed from their inception dates to December 2017. Subject headings were used to identify relevant articles, and the search strategy was adjusted across databases. Heterogeneity across studies was evaluated by Cochran's χ2 test and quantified by the I2 statistic. Subgroup analyses were performed to identify the pooled prevalence in relation to the country of study, instrument used to identify ASD, age, gender and traumatic brain injury. When significant heterogeneity was observed, the influence of some potential moderators was explored using meta-regression analyses. RESULTS:Thirteen eligible studies conducted in 8 countries were included. A total of 2989 RTA survivors were assessed, of which 287 were identified with ASD. The overall heterogeneity was high across studies (I2=96.8%, P < 0.001), and the pooled prevalence of ASD among RTA survivors was 15.81% (95% confidence interval: 8.27-25.14%). Subgroup analyses indicated that the prevalence of ASD among RTA survivors differed significantly with regard to the country of study, instrument used to identify ASD, age and gender (P < 0.05). Meta-regression analyses showed that mean age of participants and quality assessment score were significant moderators for heterogeneity (P < 0.05). CONCLUSIONS:Nearly one-sixth of RTA survivors suffer from ASD, indicating the need for regular assessment of early trauma responses among RTA survivors, as well as the importance of implementing early psychological interventions.
| S-EPMC5998549 | biostudies-literature
Project description:Road traffic accident (RTA) victims also suffer from different types of injuries and disabilities, which can affect their quality of life. They usually face with various physical, mental, and social problems. Most traffic accident victims had difficulty to return to normal life.This study aimed to understand the experiences of return to normal life in RTA victims.This qualitative study with content analysis approach was conducted on 18 Iranian patients with disability in the upper or lower limbs caused by traffic accidents, who had passed a time between 3 months till 2 years. A purposeful sampling method was applied until reaching data saturation. Data were collected using semi-structured interviews. Afterwards, the gathered data were analyzed through conventional content analysis.By analyzing 498 primary codes, four main categories, including supportive needs, adaptation to the new situation, seeking information, and transition from functional limitation, were extracted from traffic accident victims' experiences of reintegration to normal life.The results of this study may help policy-makers to take steps toward health promotion and recovery of RTA victims. Considering the results of this study, it is a need for further research to investigate RTAs victims' needs for reintegration to home and community. Access to training and supportive facilities like strong therapeutic, nursing and social support, and the possibility to participate in self-care activities is essential for reintegration to community in RTA victims.
| S-EPMC4893411 | biostudies-other
Project description:Although previous reports have documented mean-level declines in personality disorder (PD) symptoms over time, little is known about whether personality pathology sometimes emerges among nonsymptomatic adults, or whether rates of change differ qualitatively among symptomatic persons. Our study sought to characterize heterogeneity in the longitudinal course of PD symptoms with the goal of testing for and describing latent trajectories. Participants were 250 young adults selected into two groups using a PD screening measure: those who met diagnostic criteria for a DSM-III-R PD (PPD, n = 129), and those with few PD symptoms (NoPD, n = 121). PD symptoms were assessed three times over a 4-year study using semistructured interviews. Total PD symptom counts and symptoms of each DSM-III-R PD were analyzed using growth mixture modeling. In the NoPD group, latent trajectories were characterized by stable, minor symptoms; the rapid or gradual remission of subclinical symptoms; or the emergence of symptoms of avoidant, obsessive-compulsive, or paranoid PD. In the PPD group, three latent trajectories were evident: rapid symptom remission, slow symptom decline, or a relative absence of symptoms. Rapid remission of PD symptoms was associated with fewer comorbid disorders, lower Negative Emotionality, and greater Positive Emotionality and Constraint, whereas emergent personality dysfunction was associated with comorbid PD symptoms and lower Positive Emotionality. In most cases, symptom change for one PD was associated with concomitant changes in other PDs, depressive symptoms, and anxiety. These results indicate that the longitudinal course of PD symptoms is heterogeneous, with distinct trajectories evident for both symptomatic and nonsymptomatic individuals. The prognosis of PD symptoms may be informed by an assessment of personality and comorbid psychopathology.
| S-EPMC3570677 | biostudies-literature
Project description:Identifying children who are at-risk for developmental delay, so that these children can have access to interventions as early as possible, is an important and challenging problem in developmental research. This research aimed to identify latent subgroups of children with developmental delay, by modelling and clustering developmental milestones. The main objectives were to (a) create a developmental profile for each child by modelling milestone achievements, from birth to three years of age, across multiple domains of development, and (b) cluster the profiles to identify groups of children who show similar deviations from typical development. The ensemble methodology used in this research consisted of three components: (1) Bayesian sequential updating was used to model the achievement of milestones, which allows for updated predictions of development to be made in real time; (2) a measure was created that indicated how far away each child deviated from typical development for each functional domain, by calculating the area between each child's obtained sequence of posterior means and a sequence of posterior means representing typical development; and (3) Dirichlet process mixture modelling was used to cluster the obtained areas. The data used were 348 binary developmental milestone measurements, collected from birth to three years of age, from a small community sample of young children (N = 79). The model identified nine latent groups of children with similar features, ranging from no delays in all functional domains, to large delays in all domains. The performance of the Dirichlet process mixture model was validated with two simulation studies.
| S-EPMC7266333 | biostudies-literature
Project description:BackgroundGlobally, road traffic accidents are the leading causes of death among young people in general, and the main cause of death among young people aged 15-29 years. Recently, in Ethiopia, the number of road traffic accidents has been increasing. The study aimed to identify the potential factors associated with the number of human deaths by road traffic accidents in the Oromia Regional State, Ethiopia.MethodsWe used data obtained from the Oromia region traffic police office recorded on daily basis road traffic accidents from July 2016 up to July 2017. Count regression models were was used to analyses the factors associated with the number of human deaths from road traffic accidents.ResultsAge of the driver's 31-50 years (AOR = 0.289, 95%CI: 0.175, 0.479) and higher than 50 years old (AOR = 0.311, 95%CI: 0.129, 0.751), driver's years of experience 5-10 years (AOR = 0.014, 95%CI: 0.007, 0.027), and more than 10 years (AOR = 0.101, 95%CI: 0.057, 0.176), automobile vehicle type (AOR = 8.642, 95%CI: 2.7644, 27.023), vehicle years of service 5-10 years (AOR = 2.484, 95%CI: 1.194, 5.169), and more than 10 years (AOR = 2.639, 95%CI: 1.268, 5.497), vehicle upside down accidents (AOR = 5.560, 95%CI: 2.506, 12.336), turning illegal position (AOR = 0.454, 95%CI: 0.226, 0.913), residential areas (AOR = 108.506, 95%CI: 13.725, 857.798), and working areas (AOR = 129.606, 95%CI: 16.448, 1021.263) were significant associated number of human deaths per road traffic accident factors in the study area.ConclusionHuman deaths per road traffic accidents occurred due to the younger age of the driver, driver's lack of sufficient experience, vehicle serviced for long years, driving on a wet road, driving in the afternoon, driving near/around residential places and vehicle to driver's relation. Thus, the regional traffic police should give special attention to younger drivers, less experienced drivers, old vehicles, driving near residential areas, driving automobiles, and driving in the afternoon to control traffic system to reduce the number of human deaths pear road traffic accident.
| S-EPMC8133474 | biostudies-literature
Project description:ObjectivesDespite much focus on the health impact of road traffic injury (RTI) on life, there is a lack of knowledge of the dynamic process of return to work following RTI and its related factors. The aim of this study was to identify longitudinal patterns of sickness absence (SA) following RTI, to examine the patterns' interplay with health-related quality of life (HRQoL) and to determine if there are differences, regarding the patterns and interplay, according to injury severity.DesignA register-based prospective cohort study.SettingAdministrative data on RTI in Sweden from the Swedish Traffic Accident Data Acquisition System (STRADA) and Swedish Social Insurance data.ParticipantsIndividuals suffering an RTI (total n=4761) were identified in STRADA between 1 January 2007 and 31 December 2009. A total of 903 of these met the inclusion criteria for the current study and were included.Primary and secondary outcome measuresThe primary outcome measure was SA following RTI. The secondary outcome measure was HRQoL.ResultsThree distinct patterns of SA were identified; 'Stable', 'Quick decrease' and 'Gradual decrease'. The patterns differed in the number of initial SA days and the rate of reduction of SA days. After 3 years, all three patterns had almost the same level of SA. Higher injury severity and a higher number of SA days had a negative interplay with HRQoL. Participants who initially had a higher number of SA days were more likely to report a low HRQoL, indicating that people with a slower return to work are more vulnerable.ConclusionThe study highlights the heterogeneity of return to work after an RTI. People with a more severe injury and slower pace of return to work seem to be more vulnerable with regards to HRQoL loss following RTI.
| S-EPMC6677943 | biostudies-literature
Project description:ObjectivesEvery day, an average of 3,400 deaths and tens of millions of injuries occur as a result of traffic accidents. This study aims to model and validate road traffic injury (RTI) times series, specifically considering gender.Study designTime trend studies of monthly road traffic injuries (RTI) in Iran from March 2005 to February 2016, as well as those of males and females from March 2009 to February 2016 were performed.MethodsThe seasonal auto-regressive integrated moving average method (SARIMA) was employed to predict RTI time series. The final model was selected from various SARIMA models based on the Akaike information criterion (AIC) and the Bayesian information criterion (BIC). To examine whether the residuals were white noise, the Ljung-Box (LB) test and residuals plots were used for un-correlation, and the zero mean and stationarity, respectively. Additionally, smoothing methods were utilized to validate the SARIMA models for fitting and out-of-range prediction of the time series models under study. The sample auto-correlation function (ACF) and the partial autocorrelation function (PACF) with 20 lags were employed to determine the order of models and to ascertain if the residuals of the model were uncorrelated.ResultsBased on the obtained results, SARIMA (2,1,0)(0,1,1)12, SARIMA (0,1,1)(0,1,1)12, SARIMA (1,1,1)(0,0,1)12, and SARIMA (2,0,0)(1,0,0)12 were chosen for the time series including incidence rates of total road traffic injuries (IRTI), IRTI of males, females, and males-to-females, respectively. The AIC values were -87.57, 413.38, -732.91, and -85.32, respectively. The LB test for the residuals of the time series models of (0.539) IRTI, (0.3) IRTI of males, (0.23) females, and (0.237) males-to-females indicated that residuals were uncorrelated. Furthermore, prediction values for the next 24 months (2016 to 2018) showed no decline in the incidence rate of male and female traffic injuries. Results of the predictions using exponential smoothing methods indicated out-of-range prediction validity of the SARIMA models.ConclusionThis study exemplified the high efficiency of SARIMA models in predicting road traffic injuries (RTIs). Based on observations, the IRTI mean in Iran was 35.57 in 2016. The predicted values of the IRTI for 2016-2018 by the SARIMA model showed no decreasing trend. During the studied period, the observed values of IRTI for males were two to three times the female values. Thus, prediction of RTI can provide a useful tool for traffic safety policymaking by simulating interrupted time series when applying new traffic enforcement interventions and regulations in the future. Additionally, IRTI analysis of males and females showed that men had a non-increasing trend but higher incidence of traffic injuries, whereas the IRTI for women revealed an increasing trend from 2009 to 2012 with a lower incidence of injuries. This growth could be attributed to the impact of increased outdoor activities of women and the increased number of issued driving licenses in the period of 2009-2012.
| S-EPMC6508924 | biostudies-literature
Project description:The analysis of traffic accident data is crucial to address numerous concerns, such as understanding contributing factors in an accident's chain-of-events, identifying hotspots, and informing policy decisions about road safety management. The majority of statistical models employed for analyzing traffic accident data are logically count regression models (commonly Poisson regression) since a count - like the number of accidents - is used as the response. However, features of the observed data frequently do not make the Poisson distribution a tenable assumption. For example, observed data rarely demonstrate an equal mean and variance and often times possess excess zeros. Sometimes, data may have heterogeneous structure consisting of a mixture of populations, rather than a single population. In such data analyses, mixtures-of-Poisson-regression models can be used. In this study, the number of injuries resulting from casualties of traffic accidents registered by the General Directorate of Security (Turkey, 2005-2014) are modeled using a novel mixture distribution with two components: a Poisson and zero-truncated-Poisson distribution. Such a model differs from existing mixture models in literature where the components are either all Poisson distributions or all zero-truncated Poisson distributions. The proposed model is compared with the Poisson regression model via simulation and in the analysis of the traffic data.
| S-EPMC9042158 | biostudies-literature