Alcohol-related blackouts among college students: impact of low level of response to alcohol, ethnicity, sex, and environmental characteristics

Objective: To explore how a genetically-influenced characteristic (the level of response to alcohol [LR]), ethnicity, and sex relate to environmental and attitudinal characteristics (peer drinking [PEER], drinking to cope [COPE], and alcohol expectancies [EXPECT]) regarding future alcohol-related blackouts (ARBs). Methods: Structural equation models (SEMs) were used to evaluate how baseline variables related to ARB patterns in 462 college students over 55 weeks. Data were extracted from a longitudinal study of heavy drinking and its consequences at a U.S. university. Results: In the SEM analysis, female sex and Asian ethnicity directly predicted future ARBs (beta weights 0.10 and -0.11, respectively), while all other variables had indirect impacts on ARBs through alcohol quantities (beta weights ~ 0.23 for European American ethnicity and low LR, 0.21 for cannabis use and COPE, and 0.44 for PEER). Alcohol quantities then related to ARBs with beta = 0.44. The SEM explained 23% of the variance. Conclusion: These data may be useful in identifying college students who are more likely to experience future ARBs over a 1-year period. They enhance our understanding of whether the relationships of predictors to ARBs are direct or mediated through baseline drinking patterns, information that may be useful in prevention strategies for ARBs

A new approach for developing comprehensive agricultural drought index using satellite-derived biophysical parameters and factor analysis method

The accurate assessment of drought and its monitoring is highly depending on the selection of appropriate indices. Despite the availability of countless drought indices, due to variability in environmental properties, a single universally drought index has not been presented yet. In this study, a new approach for developing comprehensive agricultural drought index from satellite-derived biophysical parameters is presented. Therefore, the potential of satellite-derived biophysical parameters for improved understanding of the water status of pistachio (Pistachio vera L.) crop grown in a semiarid area is evaluated. Exploratory factor analysis with principal component extraction method is performed to select the most in?uential parameters from seven biophysical parameters including surface temperature (Ts), surface albedo (a), leaf area index (LAI), soil heat ?ux (Go), soil-adjusted vegetation index (SAVI), normalized difference vegetation index (NDVI), and net radiation (Rn). Ts and Gowere found as the most effective parameters by this method. However, Ts, LAI, a, and SAVI that accounts for 99.6 % of the total variance of seven inputs were selected to model a new biophysical water stress index (BPWSI). The values of BPWSI were stretched independently and compared with the range of actual evapotranspiration estimated through well-known METRIC (mapping evapotranspiration at high resolution with internal calibration) energy balance model. The results showed that BPWSI can be ef?ciently used for the prediction of the pistachio water status (RMSE of 0.52, 0.31, and 0.48 mm/day on three image dates of April 28, July 17, and August 2, 2010). The study con?rmed that crop water status is accounted by several satellite-based biophysical parameters rather than single parameter