Childhood Drinking and Depressive Symptom Level Predict Harmful Personality Change

Personality traits in children predict numerous life outcomes. Although traits are generally stable, if there is personality change in youth, it could affect subsequent behavior in important ways. We found that the trait of urgency, the tendency to act impulsively when highly emotional, increases for some youth in early adolescence. This increase can be predicted from the behavior of young children: alcohol consumption and depressive symptom level in elementary school children (fifth grade) predicted increases in urgency 18 months later. Urgency, in turn, predicted increases in a wide range of maladaptive behaviors another 30 months later, at the end of the first year of high school. The mechanism by which early drinking behavior and depressive symptoms predict personality is not yet clear and merits future research; notably, the findings are consistent with mechanisms proposed by personality change theory and urgency theory

Nineteenth-century Ship-based Catches of Gray Whales, Eschrichtius robustus, in the Eastern North Pacific

The 19th century commercial ship-based fishery for gray whales, Eschrichtius robustus, in the eastern North Pacific began in 1846 and continued until the mid 1870’s in southern areas and the 1880’s in the north. Henderson identified three periods in the southern part of the fishery: Initial, 1846–1854; Bonanza, 1855–1865; and Declining, 1866–1874. The largest catches were made by “lagoon whaling” in or immediately outside the whale population’s main wintering areas in Mexico—Magdalena Bay, Scammon’s Lagoon, and San Ignacio Lagoon. Large catches were also made by “coastal” or “alongshore” whaling where the whalers attacked animals as they migrated along the coast. Gray whales were also hunted to a limited extent on their feeding grounds in the Bering and Chukchi Seas in summer. Using all available sources, we identified 657 visits by whaling vessels to the Mexican whaling grounds during the gray whale breeding and calving seasons between 1846 and 1874. We then estimated the total number of such visits in which the whalers engaged in gray whaling. We also read logbooks from a sample of known visits to estimate catch per visit and the rate at which struck animals were lost. This resulted in an overall estimate of 5,269 gray whales (SE = 223.4) landed by the ship-based fleet (including both American and foreign vessels) in the Mexican whaling grounds from 1846 to 1874. Our “best” estimate of the number of gray whales removed from the eastern North Pacific (i.e. catch plus hunting loss) lies somewhere between 6,124 and 8,021, depending on assumptions about survival of struck-but-lost whales. Our estimates can be compared to those by Henderson (1984), who estimated that 5,542–5,507 gray whales were secured and processed by ship-based whalers between 1846 and 1874; Scammon (1874), who believed the total kill over the same period (of eastern gray whales by all whalers in all areas) did not exceed 10,800; and Best (1987), who estimated the total landed catch of gray whales (eastern and western) by American ship-based whalers at 2,665 or 3,013 (method-dependent) from 1850 to 1879. Our new estimates are not high enough to resolve apparent inconsistencies between the catch history and estimates of historical abundance based on genetic variability. We suggest several lines of further research that may help resolve these inconsistencies

Problematic alcohol use and sexting as risk factors for sexual assault among college women

Sexual assault is a major public health concern and college women are four times more likely to experience sexual assault than any other group. We investigated whether sexting is a mechanism by which alcohol use increases risk for college women to be targeted for sexual assault. We hypothesized that sexting would mediate the relationship between problem drinking and sexual assault, such that drinking (T1 = beginning fall semester) would contribute to increased sexting (T2 = end fall semester), and in turn increase the risk of being targeted for sexual assault (T3 = end spring semester). Results: Among 332 undergraduate women (M(SD)age = 19.15(1.69), 76.9% Caucasian), sexting (T2) predicted sexual assault (T3; b = 3.98, p = .05), controlling for baseline sexual assault (b = 0.82, p < .01). Further, sexting (T2) mediated the relationship between problem drinking (T1) and sexual assault (T3) (b = 0.04, CI[.004,.12]). Conclusion: Findings suggest that sexting is one mechanism through which drinking increases the risk of college women being targeted for sexual assault

Insights From Whaling Logbooks on Whales, Dolphins, and Whaling in the Gulf of Mexico

Whaling voyage logbooks provide a unique window into historical marine animal distribution and relative numbers. The Gulf of Mexico was among the regions visited by American commercial whalers beginning in the late 1700s, and possibly as early as the 1760s. For more than a century, they hunted sperm whales (Physeter macrocephalus) and blackfish (usually probably short-finned pilot whales; Globicephala macrorhynchus) in the Gulf. An ongoing study of global whaling history has allowed us to offer some insights on characteristics and trends of the Gulf fishery and on cetacean populations in the Gulf. We examined 53 voyage logbooks that included some whaling in the Gulf. Using the information from those logbooks and other sources, we identified 204 different voyages that included one or more ‘‘vessel-seasons’’ of whaling in the Gulf (total of 214 vessel-seasons) between 1788 and 1877. More than three-quarters (76%) of the 186 voyages for which the rig type is known were by brigs or schooners; they sailed primarily from the Massachusetts ports of New Bedford and Nantucket initially and Provincetown in later years. The whaling took place mainly in deep portions of the Gulf and in the first 7 mo of the calendar year (i.e., from Jan. through July). The sperm whales hunted in the Gulf tended to be small and were usually taken from schools, suggesting that they were mostly juveniles and females. Observations (and occasionally catches) of other cetaceans besides sperm whales and blackfish are mentioned in the logbooks—mainly ‘‘finbacks’’ (Balaenoptera sp.), killer whales (Orcinus orca), and ‘‘porpoises’’ (various small delphinids)

A Longitudinal Study of the Reciprocal Relationship Between Ever Smoking and Urgency in Early Adolescence

Background—Among early adolescents in the United States (U.S.), the prevalence of cigarette smoking is at its lowest level in recent decades. Nonetheless, given the risks of smoking in early development, it remains critically important to study both risk factors for smoking and risks from smoking. This longitudinal study with U.S. early adolescents examines smoking initiation and tests a model of reciprocal prediction between ever smoking and the personality trait of urgency (i.e., mood-based impulsivity), a trait that increases risk for multiple forms of dysfunction. Methods—Participants (n=1906; 90% 10–11 years old, 50% female, 39% racial minorities at baseline) completed questionnaires 1–2 times per year starting in 5th grade and ending in 9th grade. Structural equation modeling allowed tests of bidirectional relationships between ever smoking and urgency controlling for pubertal status and negative affect at each wave. Results—Incidence of ever smoking increased from 5% to 27% over time, with current smoking around 5% at the last wave. Urgency at each wave predicted ever smoking at the next wave above and beyond covariates and prior smoking (all p \u3c .01). Likewise, with one exception, ever smoking predicted an increase in urgency at the subsequent wave above and beyond covariates and prior urgency (all p \u3c .05). Conclusion—Results show that risk for smoking increases with higher levels of urgency and urgency increases secondary to engagement in smoking. Future work should therefore explore urgency as a point of prevention for smoking and smoking cessation as a means to mitigate mood-based impulsivity

Socioeconomic inequalities in survival and provision of neonatal care: population based study of very preterm infants

Objectives To assess socioeconomic inequalities in survival and provision of neonatal care among very preterm infants

Validity of self-reported smoking status: comparison of patients admitted to hospital with acute coronary syndrome and the general population

Many studies rely on self-reported smoking status. We hypothesized that patients with acute coronary syndrome (ACS), a smoking-related condition, would be more prone to misclassify themselves as ex-smokers, because of pressure to quit. We compared patients admitted with ACS with a general population survey conducted in the same country at a similar time. We determined whether ACS patients who classified themselves as ex-smokers (n = 635) were more likely to have cotinine levels suggestive of smoking deception than self-reported ex-smokers in the general population (n = 289). On univariate analysis, the percentage of smoking deceivers was similar among ACS patients and the general population (11% vs. 12%, p = .530). Following adjustment for age, sex and exposure to environmental tobacco smoke, ACS patients were significantly more likely to misclassify themselves (adjusted OR = 14.06, 95% CI 2.13-93.01, p = .006). There was an interaction with age whereby the probability of misclassification fell significantly with increasing age in the ACS group (adjusted OR = 0.95, 95% CI 0.93-0.97, p&lt;.001), but not in the general population. Overall, smoking deception was more common among ACS patients than the general population. Studies comparing patients with cardiovascular disease and healthy individuals risk introducing bias if they rely solely on self-reported smoking status. Biochemical confirmation should be undertaken in such studies

Nature of socioeconomic inequalities in neonatal mortality: population based study

Objective To investigate time trends in socioeconomic inequalities in cause specific neonatal mortality in order to assess changing patterns in mortality due to different causes, particularly prematurity, and identify key areas of focus for future intervention strategies

Identification and Analysis of Behavioral Phenotypes in Autism Spectrum Disorder via Unsupervised Machine Learning

Background and objective: Autism spectrum disorder (ASD) is a heterogeneous disorder. Research has explored potential ASD subgroups with preliminary evidence supporting the existence of behaviorally and genetically distinct subgroups; however, research has yet to leverage machine learning to identify phenotypes on a scale large enough to robustly examine treatment response across such subgroups. The purpose of the present study was to apply Gaussian Mixture Models and Hierarchical Clustering to identify behavioral phenotypes of ASD and examine treatment response across the learned phenotypes. Materials and methods: The present study included a sample of children with ASD (N = 2400), the largest of its kind to date. Unsupervised machine learning was applied to model ASD subgroups as well as their taxonomic relationships. Retrospective treatment data were available for a portion of the sample (n =1034). Treatment response was examined within each subgroup via regression. Results: The application of a Gaussian Mixture Model revealed 16 subgroups. Further examination of the subgroups through Hierarchical Agglomerative Clustering suggested 2 overlying behavioral phenotypes with unique deficit profiles each composed of subgroups that differed in severity of those deficits. Furthermore, differentiated response to treatment was found across subtypes, with a substantially higher amount of variance accounted for due to the homogenization effect of the clustering. Discussion: The high amount of variance explained by the regression models indicates that clustering provides a basis for homogenization, and thus an opportunity to tailor treatment based on cluster memberships. These findings have significant implications on prognosis and targeted treatment of ASD, and pave the way for personalized intervention based on unsupervised machine learning