Nevin Manimala

J Safety Res. 2023 Sep;86:364-375. doi: 10.1016/j.jsr.2023.07.015. Epub 2023 Aug 4.

ABSTRACT

INTRODUCTION: The aim of this paper is to understand the causes of occupational accidents in Spain’s mining sector in order to propose action plans and improve future accident rates.

METHOD: This research analyzed a pool of data on 15,032 accidents occurring in the mining sector and reported to authorities between 2013 and 2018. Accidents are divided into three levels of severity: light, serious, and fatal. We study the influence of 12 variables on the accident severity rate in our sample.

RESULTS: The results show that accident severity is related to age, gender, nationality, length of service, economic activity, company size, accident location, days of injury leave, day of the week, deviation, injury, and specific Spanish region. This sector produces a high rate of serious accidents compared to all other sectors; has a male-dominated, older and experienced workforce; and employs mainly Spanish workers. Its activity is concentrated in larger companies and the work involves the use of heavy machinery and dangerous materials. We offer conclusions and future lines of research to help regulators, companies and workers to improve worker safety.

PMID:37718064 | DOI:10.1016/j.jsr.2023.07.015

J Safety Res. 2023 Sep;86:318-335. doi: 10.1016/j.jsr.2023.07.010. Epub 2023 Jul 26.

ABSTRACT

INTRODUCTION: In recent years, with the rapid development of university laboratory construction, frequent laboratory accidents have aroused widespread concern. There is an urgent need to improve laboratory safety management’s effectiveness further, enhance laboratory accident prevention ability, and reduce the occurrence of accidents.

METHOD: Based on the accident causation theory, this paper uses the accident analysis path of 24Model and the logical idea of WBA (Why-Because-Analysis) to statistically analyze the causative factors of 64 typical college laboratory fire and explosion accidents and find out the defects of current college laboratory management.

RESULTS: The study showed that unsafe human actions at the individual level were the most critical factors affecting laboratory safety management, with a high frequency of violations of experimental procedures (105 times) and managers’ failure to perform their supervisory duties (98 times); low safety awareness and insufficient safety knowledge among laboratory personnel were key factors triggering unsafe actions. At the organizational level, the lack of training programs (92 times) and the lack of systematic procedures (106 times) are the weaknesses of the laboratory safety management system in general in all universities; the lack of safety culture construction is the root cause of laboratory management deficiencies.

CONCLUSIONS: Based on the above statistical results, and taking into account the characteristics of university laboratories themselves, the root causes of poor safety are specifically analyzed and preventive measures are proposed in six areas to address the key causes of accidents.

PRACTICAL APPLICATIONS: The results of this study are essential for improving the ability to prevent accidents in flammable and explosive laboratories in universities.

PMID:37718060 | DOI:10.1016/j.jsr.2023.07.010

J Safety Res. 2023 Sep;86:253-261. doi: 10.1016/j.jsr.2023.07.004. Epub 2023 Jul 26.

ABSTRACT

INTRODUCTION: Nighttime crashes account for 74% of pedestrian fatalities in the United States, and reduced visibility is a significant cause of nighttime pedestrian crashes. Maintaining sufficient and uniform roadway lighting is an effective countermeasure to improve pedestrian visibility and prevent nighttime pedestrian crashes and injuries. Previous studies have not quantified the safety effects of roadway photometric patterns (i.e., average lighting level and uniformity) on nighttime pedestrian crashes on roadway segments.

METHOD: This study investigated the association between two roadway photometric criteria (horizontal illuminance mean representing average lighting level and horizontal illuminance standard deviation representing lighting uniformity) and nighttime pedestrian crash occurrence in Florida roadway segments. The matched case-control method was used to decouple the confounding effects between the illuminance mean and standard deviation. Statistically-significant crash modification factors (CMFs) were developed to quantify the safety effects of the mean and standard deviation of horizontal illuminance on nighttime pedestrian crashes.

RESULTS: The results show that if the average lighting level on a roadway segment is increased from a low illuminance mean (<0.2 foot-candle [fc]) to a medium illuminance mean [0.2 fc, 0.5 fc], a medium-high illuminance mean (0.5 fc, 1.0 fc], and a high illuminance mean (>1.0 fc), the relative likelihood of nighttime pedestrian crashes on midblock segments in Florida tends to be reduced by 77.5% (CMF = 0.225), 81.2% (CMF = 0.188), and 85.5% (CMF = 0.145), respectively.

PRACTICAL APPLICATIONS: A poor uniformity (illuminance standard deviation ≥ 0.52 fc) is likely to increase the relative likelihood of nighttime pedestrian crashes on midblock segments in Florida by 80.3% (CMF = 1.803) compared to good uniformity (illuminance standard deviation < 0.52 fc).

PMID:37718053 | DOI:10.1016/j.jsr.2023.07.004

J Safety Res. 2023 Sep;86:245-252. doi: 10.1016/j.jsr.2023.07.003. Epub 2023 Jul 31.

ABSTRACT

BACKGROUND: Differences in social and environmental factors can contribute to disparities in fatal injury rates. The purpose of this study was to examine the relationship between social and environmental factors and unintentional fatal injury across counties in the United States and how this relationship varies by geography.

METHODS: County-level vital statistics on age-adjusted unintentional fatal injury rates for 2015-2019 were linked with county-level data from the 2018 Social Vulnerability Index (SVI), a dataset identifying socially vulnerable communities. We conducted linear regression to examine the association between SVI and unintentional fatal injury, overall and by Census region/division. We mapped county-level data for SVI and unintentional fatal injury rates in bivariate choropleth maps using quartiles.

RESULTS: SVI was positively associated with unintentional fatal injury (β = 18.29, p < 0.001) across U.S. counties. The geographic distribution of SVI and unintentional fatal injury rates varied spatially and substantially for U.S. counties, with counties in the South and West regions having the greatest levels of SVI and rates of unintentional fatal injury.

CONCLUSIONS: Our findings demonstrate that the social vulnerability of counties is associated with unintentional fatal injury rates. Modification of the SVI for injury research could include additional social determinants and exclude variables not applicable to injuries. A modified SVI could inform unintentional injury prevention strategies by prioritizing efforts in areas with high levels of social vulnerability.

PRACTICAL APPLICATIONS: This study is the first step in combining the SVI and injury mortality data to provide researchers with an index to investigate upstream factors related to injury.

PMID:37718052 | DOI:10.1016/j.jsr.2023.07.003

J Safety Res. 2023 Sep;86:21-29. doi: 10.1016/j.jsr.2023.06.004. Epub 2023 Jun 14.

ABSTRACT

PROBLEM: Fatal injuries in the agriculture, forestry, and fishing sector (AgFF) outweigh those across all sectors in the United States. Transportation-related injuries are among the top contributors to these fatal events. However, traditional occupational injury surveillance systems may not completely capture crashes involving farm vehicles and logging trucks, specifically nonfatal events.

METHODS: The study aimed to develop an integrated database of AgFF-related motor-vehicle crashes for the southwest (Arkansas, Louisiana, New Mexico, Oklahoma, and Texas) and to use these data to conduct surveillance and research. Lessons learned during the pursuit of these aims were cataloged. Activities centered around the conduct of traditional statistical and geospatial analyses of structured data fields and natural language processing of free-text crash narratives.

RESULTS: The structured crash data in each state include fields that allowed farm vehicles or equipment and logging trucks to be identified. The variable definitions and coding were not consistent across states but could be harmonized. All states recorded data fields pertaining to person, vehicle, and crash/environmental factors. Structured data supported the construction of crash severity models and geospatial analyses. Law enforcement provided additional details on crash causation in free-text narratives. Crash narratives contained sufficient text to support viable machine learning models for farm vehicle or equipment crashes, but not for logging truck narratives.

DISCUSSION: Crash records can help to fill research and surveillance gaps in AgFF in the southwest region. This supports traffic safety’s evolution to the current Safe System paradigm. There is a conceptual linkage between the Safe System and Total Worker Health approaches, providing a bridge between traffic safety and occupational health.

PRACTICAL APPLICATIONS: Despite limitations, crash records can be an important component of injury surveillance for events involving AgFF vehicles. They also can be used to inform the selection and evaluation of traffic countermeasures and behavioral interventions.

PMID:37718049 | DOI:10.1016/j.jsr.2023.06.004

J Safety Res. 2023 Sep;86:164-173. doi: 10.1016/j.jsr.2023.05.007. Epub 2023 May 19.

ABSTRACT

INTRODUCTION: The role of real-time data capture (via telematics technology) is gathering prominence as a strategy to provide feedback to young drivers about important road safety issues.

METHOD: A naturalistic driving study was undertaken to determine whether providing personalized feedback (via a smartphone app) to young provisional drivers aged 17-20 years living in metropolitan and regional Western Australia (WA) reduced their risky driving behavior compared to a control group who did not receive feedback. Speeding over the posted speed limit, harsh decelerations (braking), harsh accelerations and overall driving performance, were recorded continuously using the smartphone app during the 11-week study. Four separate Generalised Estimating Equations (GEE) linear regression models were undertaken after accounting for relevant confounders including driving exposure to determine the difference between the intervention and control group for the 4 driving outcomes obtained from the smartphone app.

RESULTS: The study found that there was no significant change in overall driving scores between the intervention and control groups (p = 0.35). However, the overall driving score significantly improved by 0.19 points for young provisional drivers who lived in regional areas compared to those in the metropolitan area (p = 0.05) after adjusting for potential confounders. There was also no significant change in harsh braking scores (p = 0.46) and harsh acceleration scores between the intervention and control groups (p = 0.26) However, harsh acceleration scores improved by 0.37 points for females compared to males (p = 0.04). Lastly, there was no significant change in speed scores between the control and intervention groups (p = 0.72). However, the speed scores of participants who lived in regional WA improved by 0.22 points compared to those in the metropolitan area (p = 0.02). Furthermore, for every 1,000 km travelled, speed scores worsened by -0.08 points (p < 0.01) regardless of group.

CONCLUSIONS: The study did not find any statistical difference in the driving outcomes examined; however the treatment effects for feedback were consistently in the expected positive direction. Young drivers in regional WA also improved their speeding scores and overall driving performance scores compared to young drivers in the metropolitan area. Females, also significantly improved their harsh deceleration scores compared to males, regardless of group allocation. These results highlight the use of smartphone telematics as an opportunity to not only enhance the safety of provisional young drivers but also provide data-informed decision making and policy development.

PMID:37718043 | DOI:10.1016/j.jsr.2023.05.007

J Safety Res. 2023 Sep;86:118-126. doi: 10.1016/j.jsr.2023.05.004. Epub 2023 May 18.

ABSTRACT

INTRODUCTION: The civil construction industry (CCI) is one of the most dangerous sectors for occupational accidents. Studies conducted in several countries show that occupational accidents involving falls from height are the main cause of deaths in recent years.

METHOD: This article analyzed the combinations of causal factors with the highest likelihood of accidents involving falls from height in construction to assist in decision-making. The methodology was divided into four stages: accident collection and sample definition; accident analysis; probability determination; and obtaining the theoretical curve of an accident probability distribution. The methodology was applied to reports of fatal fall-from-height accidents that occurred in the United States between 1997 and 2020.

RESULTS: The results show that among the accidents analyzed, the highest probability of fatality is when a roofer aged between 31 and 44 years performs their activity on a roof between 10:00 and 11:59 am. It is also noted that the three causal factors most present in the accidents were: organizational process (97.7%); poor management of worker resources (96.6%); and organizational climate (95.4%). From the probability distribution curve, 68% of the fatal accidents occurred after reaching between 18 and 34 causal factors present in the HFACS method categories.

PMID:37718038 | DOI:10.1016/j.jsr.2023.05.004

Res Synth Methods. 2023 Sep 17. doi: 10.1002/jrsm.1668. Online ahead of print.

ABSTRACT

Conventional random-effects models in meta-analysis rely on large sample approximations instead of exact small sample results. While random-effects methods produce efficient estimates and confidence intervals for the summary effect have correct coverage when the number of studies is sufficiently large, we demonstrate that conventional methods result in confidence intervals that are not wide enough when the number of studies is small, depending not just on the configuration of sample sizes across studies, the degree of true heterogeneity and number of studies. We introduce two alternative variance estimators with better small sample properties, investigate degrees of freedom adjustments for computing confidence intervals, and study their effectiveness via simulation studies.

PMID:37717978 | DOI:10.1002/jrsm.1668

Saudi Med J. 2023 Sep;44(9):898-903. doi: 10.15537/smj.2023.44.9.20230441.

ABSTRACT

OBJECTIVES: To assess the specificity and sensitivity of prognostic biomarkers in individuals diagnosed with acute pulmonary embolism (PE).

METHODS: This study retrospectively enrolled 162 patients from the 741 patients who were hospitalized with acute PE and diagnosed using pulmonary computed tomography (CT) angiogram at 5 hospitals in Saudi Arabia between January 2015 and December 2019. Pulmonary embolism patients classified into survivor and non-survivor groups. Neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and red cell distribution width (RDW) were all recorded and were compared between the groups. The evaluation of mortality prediction, sensitivity, and specificity was carried out by employing receiver operating characteristic curves.

RESULTS: The variables NLR and RDW exhibited a statistically significant correlation with increased mortality and disease severity. A total of 8 patients among the 162 patients died. At the cut-off value of 5.5, NLR was showed an association with all-cause mortality, demonstrating a sensitivity of 75% and a specificity of 82%. At the cut-off value of 18.15, RDW was found to be significantly associated with all-cause mortality, displaying a sensitivity of 63% and a specificity of 88%.

CONCLUSION: Multiple parameters have been implicated in the mortality and severity of PE. Our study revealed a statistically significant association between NLR, RDW, and PE mortality. These tests are easily accessible and may provide insights into the mortality associated with PE.

PMID:37717976 | DOI:10.15537/smj.2023.44.9.20230441

Saudi Med J. 2023 Sep;44(9):864-869. doi: 10.15537/smj.2023.44.9.20230243.

ABSTRACT

OBJECTIVES: To investigate the positive effects of intraperitoneal administration of alpha-lipolic acid (ALA) and dexpanthenol (DXP) on wound healing after tracheal surgery in rats.

METHODS: The study was carried out at Necmettin Erbakan University, Konya, Turkey, from January 2014-2019. A total of 30 healthy and adult Sprague-Dawley type female rats were included in the study. For the experiment, rats were randomly divided into 3 groups: ALA group (n=10), DXP group (n=10), and control group (n=10). After trachea surgery, 100 mg/kg/day ALA was given to group ALA and 100 mg/kg/day intraperitoneal DXP to group DXP for 15 days, and the rats were sacrificed on the 21st day. The excised tracheal sections were evaluated and graded for inflammatory cell infiltration, angiogenesis, fibroblast proliferation, collagen deposition, and epithelial regeneration to evaluate wound healing.

RESULTS: Inflammation was found to be less in both the ALA and DXP groups. With the Mann-Whitney test, it was determined that inflammation was less in the ALA group than in the DXP group (C-D [p=0.097] and C-A [p=0.024]). On the other hand, no statistically significant difference was found in epithelial regeneration (p=0.574; >0.05), angiogenesis (p=0.174; >0.05), fibroblast proliferation, and collagen deposition (p=0.102; >0.05).

CONCLUSION: Alpha-lipolic acid injected intravenously after tracheal reconstruction in patients can prevent restenosis by reducing inflammation without adversely affecting wound healing.

PMID:37717974 | DOI:10.15537/smj.2023.44.9.20230243