Two-Stage Negative Binomial and Overdispersed Poisson Models for Clustered Developmental Toxicity Data with Random Cluster Size

1998 ◽  
Vol 3 (1) ◽  
pp. 75 ◽  
Author(s):  
Thomas R. Ten Have ◽  
Vernon M. Chinchilli
2015 ◽  
Vol 34 (2_suppl) ◽  
pp. 70S-83S
Author(s):  
Wilbur Johnson ◽  
Bart Heldreth ◽  
Wilma F. Bergfeld ◽  
Donald V. Belsito ◽  
Ronald A. Hill ◽  
...  

The Cosmetic Ingredient Review (CIR) Expert Panel (Panel) reviewed the safety of alkyl polyethylene glycol (PEG) sulfosuccinates, which function in cosmetics mostly as surfactants/cleansing agents. Although these ingredients may cause ocular and skin irritation, dermal penetration is unlikely because of the substantial polarity and molecular size of these ingredients. The Panel considered the negative oral carcinogenicity and reproductive and developmental toxicity data on chemically related laureths (PEG lauryl ethers) and negative repeated dose toxicity and skin sensitization data on disodium laureth sulfosuccinate supported the safety of these alkyl PEG sulfosuccinates in cosmetic products, but. The CIR Expert Panel concluded that the alkyl PEG sulfosuccinates are safe in the present practices of use and concentration when formulated to be nonirritating.


2001 ◽  
Vol 20 (2_suppl) ◽  
pp. 1-11

Arnica Montana Extract is an extract of dried flowerheads of the plant, Arnica montana. Arnica Montana is a generic term used to describe a plant material derived from the dried flowers, roots, or rhizomes of A. montana. Common names for A. montana include leopard's bane, mountain tobacco, mountain snuff, and wolf's bane. Two techniques for preparing Arnica Montana Extract are hydroalcoholic maceration and gentle disintegration in soybean oil. Propylene glycol and butylene glycol extractions were also reported. The composition of these extracts can include fatty acids, especially palmitic, linoleic, myristic, and linolenic acids, essential oil, triterpenic alcohols, sesquiterpene lactones, sugars, phytosterols, phenol acids, tannins, choline, inulin, phulin, arnicin, flavonoids, carotenoids, coumarins, and heavy metals. The components present in these extracts are dependent on where the plant is grown. Arnica Montana Extract was reported to be used in almost 100 cosmetic formulations across a wide range of product types, whereas Arnica Montana was reported only once. Extractions of Arnica Montana were tested and found not toxic in acute toxicity tests in rabbits, mice, and rats; they were not irritating, sensitizing, or phototoxic to mouse or guinea pig skin; and they did not produce significant ocular irritation. In an Ames test, an extract of A. montana was mutagenic, possibly related to the flavenoid content of the extract. No carcinogenicity or reproductive/developmental toxicity data were available. Clinical tests of extractions failed to elicit irritation or sensitization, yet Arnica dermatitis, a delayed type IV allergy, is reported in individuals who handle arnica flowers and may be caused by sesquiterpene lactones found in the flowers. Ingestion of A. montana–containing products has induced severe gastroenteritis, nervousness, accelerated heart rate, muscular weakness, and death. Absent any basis for concluding that data on one member of a botanical ingredient group can be extrapolated to another in the group, or to the same ingredient extracted differently, these data were not considered sufficient to assess the safety of these ingredients. Additional data needs include current concentration of use data; function in cosmetics; ultraviolet (UV) absorption data—if absorption occurs in the UVA or UVB range, photosensitization data are needed; gross pathology and histopathology in skin and other major organ systems associated with repeated dermal exposures; dermal reproductive/developmental toxicity data; inhalation toxicity data, especially addressing the concentration, amount delivered, and particle size; and genotoxicity testing in a mammalian system; if positive, a 2-year dermal carcinogenicity assay performed using National Toxicology Program (NTP) methods is needed. Until these data are available, it is concluded that the available data are insufficient to support the safety of these ingredients in cosmetic formulations.


2013 ◽  
Vol 41 ◽  
pp. 16
Author(s):  
Jane Stewart ◽  
Aldert H. Piersma ◽  
Peter T. Theunissen ◽  
Greg D. Cappon ◽  
Sonja Beken

2019 ◽  
Vol 12 (1) ◽  
pp. 68-77
Author(s):  
Ronald Fisa ◽  
Chola Nakazwe ◽  
Charles Michelo ◽  
Patrick Musonda

Background: According to the World Health Organization (WHO), 1.24 million people die annually on the world’s roads, with 20-50 million sustaining non-fatal injuries. More than 85% (1.05 million) of the global deaths due to injuries occur in the developing world. Road traffic deaths and injuries are a major but neglected public health challenge that requires concerted efforts for effective and sustainable prevention. The objectives of the study were to estimate the incidence rate of death from RTAs, to determine factors associated with serious and fatal Road Traffic Accidents (RTAs) and to determine which of the poisson models fit the count data better. Methods: Data was collected from Zambia Police (ZP), Traffic Division on accidents that occurred on the Great North Road (GNR) highway between Lusaka and Kapiri-Mposhi in Zambia from January 1, 2010 to December 31, 2016. Results from standard Poisson regression were compared to those obtained using the Negative Binomial (NB), Zero-Truncated Negative Binomial (ZTNB) and the Zero-Truncated Poisson (ZTP) regression models. Diagnostic tests were used to determine the best fit model. The data was analysed using STATA software, version 14.0 SE (Stata Corporation, College Station, TX, USA). Results: A total of 1, 023 RTAs were analysed in which 1, 212 people died. Of these deaths, 82 (7%) were Juveniles and 1, 130 (93%) were adults. Cause of accident such as pedestrians crossing the road accounted for 30% (310/1,023) while 29% (295/1,023) were as a result of driver’s excessive speed. The study revealed that driving in the early hours of the day (1AM-6AM) as compared to driving in the night (7PM-12AM) had a significant increase in the incidence rate of death from RTAs, Incidence Rate Ratio (IRR) of 2.1, (95% CI={1.01-4.41}), p-value=0.048. Results further showed that public transport as compared to private transport had an increased incidence rate of death from RTAs (IRR=5.65, 95% CI={2.97-10.73}), p-value<0.0001. The two competing models were the ZTP and the ZTNB. The ZTP had AIC=1304.55, BIC= 1336.55, whereas the ZTNB had AIC=742.25 and BIC=819.69. This indicated that the ZTNB with smaller AIC and BIC was the best fit model for the data. Conclusion: There is a reduced incidence of dying if one is using a private vehicle as compared to a public vehicle. Driving in the early hours of the day (1AM and 6AM) had an increased incidence of death from RTAs. This study suggests that when dealing with counts in which there are a few zeros observed such as in serious and fatal RTAs, ZTNB fits the data well as compared to other models.


2019 ◽  
Vol 11 (11) ◽  
pp. 3176 ◽  
Author(s):  
António Lobo ◽  
Sara Ferreira ◽  
Isabel Iglesias ◽  
António Couto

Most previous studies show that inclement weather increases the risk of road users being involved in a traffic crash. However, some authors have demonstrated a little or even an opposite effect, observed both on crash frequency and severity. In urban roads, where a greater number of conflict points and heavier traffic represent a higher exposure to risk, the potential increase of crash risk caused by adverse weather deserves a special attention. This study investigates the impact of meteorological conditions on the frequency of road crashes in urban environment, using the city of Porto, Portugal as a case study. The weather effects were analyzed for different types of crashes: single-vehicle, multi-vehicle, property-damage-only, and injury crashes. The methodology is based on negative binomial and Poisson models with random parameters, considering the influence of daily precipitation and mean temperature, as well as the lagged effects of the precipitation accumulated during the previous month. The results show that rainy days are more prone to the occurrence of road crashes, although the past precipitation may attenuate such effect. Temperatures below 10 °C are associated with higher crash frequencies, complying with the impacts of precipitation in the context of the Portuguese climate characteristics.


2006 ◽  
Vol 92 (1) ◽  
pp. 329-334 ◽  
Author(s):  
Daniel L. Hunt ◽  
Chin-Shang Li

2018 ◽  
Vol 28 (5) ◽  
pp. 1540-1551
Author(s):  
Maengseok Noh ◽  
Youngjo Lee

Poisson models are widely used for statistical inference on count data. However, zero-inflation or zero-deflation with either overdispersion or underdispersion could occur. Currently, there is no available model for count data, that allows excessive occurrence of zeros along with underdispersion in non-zero counts, even though there have been reported necessity of such models. Furthermore, given an excessive zero rate, we need a model that allows a larger degree of overdispersion than existing models. In this paper, we use a random-effect model to produce a general statistical model for accommodating such phenomenon occurring in real data analyses.


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