Alcohol use in South Africa : findings from the first demographic and health survey (1998)

Objective This study formed part of the 1998 South African Demographic and Health Survey, which included questions assessing the extent of alcohol use, risky drinking and alcohol problems among South Africans to obtain up-to-date baseline estimates of consumption and risky drinking and to inform intervention efforts. Method A two-stage random sample of 13,826 persons ages 15 or older (59% women) was included in the survey. Alcohol use was assessed through eight questions, including the CAGE questionnaire. Frequency analyses for different age groups, geographic setting, education level, population group and gender were calculated, as were odds ratios for these variables in relation to symptoms of alcohol problems. Results Current alcohol consumption was reported by 45% of the men and 17% of the women. White men (71%) were most likely and Asian women (9%) least likely to be current drinkers. Urban residents were more likely than nonurban dwellers to report current drinking. One third of the current drinkers reported risky drinking over weekends, and 28% of the men and 10% of the women scored above the cutoff level on the CAGE questionnaire. Symptoms of alcohol problems were significantly associated with lower socioeconomic status, no school education in women and being older than 25 years of age. Conclusions A comprehensive strategy is required to address the high levels of risky drinking and reported symptoms of alcohol problems.

Some comparison on whole-proteome phylogeny of large dsDNA viruses based on dynamical language approach and feature frequency profiles method

There has been a growing interest in alignment-free methods for phylogenetic analysis using complete genome data. Among them, CVTree method, feature frequency profiles method and dynamical language approach were used to investigate the whole-proteome phylogeny of large dsDNA viruses. Using the data set of large dsDNA viruses from Gao and Qi (BMC Evol. Biol. 2007), the phylogenetic results based on the CVTree method and the dynamical language approach were compared in Yu et al. (BMC Evol. Biol. 2010). In this paper, we first apply dynamical language approach to the data set of large dsDNA viruses from Wu et al. (Proc. Natl. Acad. Sci. USA 2009) and compare our phylogenetic results with those based on the feature frequency profiles method. Then we construct the whole-proteome phylogeny of the larger dataset combining the above two data sets. According to the report of The International Committee on the Taxonomy of Viruses (ICTV), the trees from our analyses are in good agreement to the latest classification of large dsDNA viruses.