Alcohol consumption, wealth and health - Authors' reply

No abstract available

Socioeconomic status as an effect modifier of alcohol consumption and harm: an analysis of linked cohort data

Background: Alcohol-related mortality and morbidity are higher in socioeconomically disadvantaged populations. It is unclear if elevated harm reflects differences in consumption, reverse causation or greater risk of harm following similar consumption. We investigated whether the harmful effects differed by socioeconomic status accounting for alcohol consumption and other health-related factors. Methods: Alcohol consumption (weekly units and binge drinking) data (n=50,236; 429,986 person-years of follow-up) were linked to deaths, hospitalisations and prescriptions. The primary outcome was alcohol-attributable hospitalisation/death. The relationship between alcohol attributable harm and socioeconomic status was investigated for four measures (education level, social class, household income and area-based deprivation) using Cox proportional hazards models. The potential for alcohol consumption and other risk factors mediating the social patterning was explored. Downward social selection for high-risk drinkers (reverse causation) was tested by comparing change in area deprivation over time. Findings: Low socioeconomic status was consistently associated with markedly elevated alcohol-attributable harms, including after adjustment for weekly consumption, binge drinking, body mass index and smoking. There was evidence of effect modification: for example, relative to light drinkers living in advantaged areas, the hazard ratio for excessive drinkers was 6.75 (95% CI 5.09-8.93) in advantaged and 11.06 (95% CI 8.53-14.35) in deprived areas. We found little support for downward social selection. Interpretation: Disadvantaged social groups experience greater alcohol-attributable harms compared to the advantaged for given levels of alcohol consumption, even after accounting for different drinking patterns, obesity and smoking status at the individual level

A Dynamic Model of Induction Generators for Wind Power Studies

This paper presents an induction generator model that can be used for simulations to investigate and evaluate the control strategies for variable speed operation of doubly fed induction generators driven by wind turbines in transient conditions. The model makes use of rotor reference frame

4-Eth­oxy­phenyl 4-[(meth­oxy­carbon­yl)­oxy]benzoate

In the title compound, C17H16O6, the two benzene rings form a dihedral angle of 54.95 (10)°. Only weak inter­molecular inter­actions are present in the crystal structure, viz. C—H⋯O hydrogen bonds and C—H⋯π inter­actions involving one of the benzene rings

Field evaluation of Musa germplasm for resistance against banana stem weevil, Odoiporus longicollis (Oliver) (Curculionidae: Coleoptera) in Kadapa district of Andhra Pradesh

Banana germplasm with 17 different accessions for resistance were screened against banana stem weevil, Odoiporous longicollis in Koduru region of Kadapa district (Andhra Pradesh). All the accessions had infestation of stem weevil but with varying percent infestation. The 17 accessions of germplasm had weevil infestation ranging from 10.0–100 percent in 2012 with maximum infestation of 100 percent in red banana (AAA genome) followed by Bontha selection-88.88 % (ABB), Karpuravalli-84.60% (AAB) and Ellakibale-64.7% (AB) and the lowest was inSugandhalu-10.00% (AAB). In the year 2013, the infestation was in the range of 13.00-90.40% and with respect to infestation levels in different accessions, and the trend remained same as the earlier year wherein the highest infestation was recorded in red banana-90.40% followed by Bontha selection with the damage of 83.50 %, Karpuravalli (79.80%), Ellakibale (70.00%) and least in Sugandhalu-13.0% (AAB). There was no correlation between number of adults observed and percent damage and similarly no relation can be drawn between percent infestation and height of oviposition, This implies that the infestation caused by the weevils varied in different genotypes and also this information will be further helpful in selecting the resistant germplasms for future