Concept: Alcoholic beverage
A rank based social norms model predicts that drinkers' judgements about their drinking will be based on the rank of their breath alcohol level amongst that of others in the immediate environment, rather than their actual breath alcohol level, with lower relative rank associated with greater feelings of safety. This study tested this hypothesis and examined how people judge their levels of drunkenness and the health consequences of their drinking whilst they are intoxicated in social drinking environments.
Alcoholic beverages are widely consumed. Depression, the most prevalent mental disorder worldwide, has been related to alcohol intake. We aimed to prospectively assess the association between alcohol intake and incident depression using repeated measurements of alcohol intake.
Alcohol consumption is known to be associated with risky sexual behaviours, but this relationship may be complex and bidirectional. We explored whether alcohol consumption leads to the consumer being rated as more attractive than sober individuals.
To quantify risk of overall cancer across all levels of alcohol consumption among women and men separately, with a focus on light to moderate drinking and never smokers; and assess the influence of drinking patterns on overall cancer risk.
High levels of alcohol consumption and increases in heavy episodic drinking (binge drinking) are a growing public concern, due to their association with increased risk of personal and societal harm. Alcohol consumption has been shown to be sensitive to factors such as price and availability. The aim of this study was to explore the influence of glass shape on the rate of consumption of alcoholic and non-alcoholic beverages.
We examined whether a sugary drink limit would still be effective if larger-sized drinks were converted into bundles of smaller-sized drinks.
to determine the impact of recently proposed age-specific alcohol consumption limits on the proportion and number of older people classified at risk of alcohol-related harm.
BACKGROUND: Various recommendations exist for total water intake (TWI), yet this is seldom reported in dietary surveys. Few studies have examined how real-life consumption patterns, including beverage type, variety and timing relate to TWI and energy intake (EI). METHODS: We analysed weighed dietary records from the National Diet and Nutrition Survey of 1724 British adults aged 19–64 years (2000/2001) to investigate beverage consumption patterns over 24 hrs and 7 days and associations with TWI and EI. TWI was calculated from the nutrient composition of each item of food and drink and compared with reference values. RESULTS: Mean TWI was 2.53 L (SD 0.86) for men and 2.03 L (SD 0.71) for women, close to the European Food Safety Authority “adequate Intake” (AI) of 2.5 L and 2 L, respectively. However, for 33% of men and 23% of women TWI was below AI and TWI:EI ratio was <1 g/kcal. Beverages accounted for 75% of TWI. Beverage variety was correlated with TWI (r 0.34) and more weakly with EI (r 0.16). Beverage consumption peaked at 0800 hrs (mainly hot beverages/ milk) and 2100 hrs (mainly alcohol). Total beverage consumption was higher at weekends, especially among men. Overall, beverages supplied 16% of EI (men 17%, women 14%), alcoholic drinks contributed 9% (men) and 5% (women), milk 5-6%, caloric soft drinks 2%, and fruit juice 1%.In multi-variable regression (adjusted for sex, age, body weight, smoking, dieting, activity level and mis-reporting), replacing 100 g of caloric beverages (milk, fruit juice, caloric soft drinks and alcohol) with 100 g non-caloric drinks (diet soft drinks, hot beverages and water) was associated with a reduction in EI of 15 kcal, or 34 kcal if food energy were unchanged. Using within-person data (deviations from 7-day mean) each 100 g change in caloric beverages was associated with 29 kcal change in EI or 35 kcal if food energy were constant. By comparison the calculated energy content of caloric drinks consumed was 47 kcal/100 g. CONCLUSIONS: TWI and beverage consumption are closely related, and some individuals appeared to have low TWI. Compensation for energy from beverages may occur but is partial. A better understanding of interactions between drinking and eating habits and their impact on water and energy balance would give a firmer basis to dietary recommendations.
The most common technique used to detect ochratoxin A (OTA) in food matrices is based on extraction, clean-up, and chromatography detection. Different clean-up cartridges, such as immunoaffinity columns (IAC), molecular imprinting polymers (MIP), Mycosep™ 229, Mycospin™, and Oasis® HLB (Hydrophilic Lipophilic balance) as solid phase extraction were tested to optimize the purification for red wine, beer, roasted coffee and chili. Recovery, reproducibility, reproducibility, limit of detection (LOD) and limit of quantification (LOQ) were calculated for each clean-up method. IAC demonstrated to be suitable for OTA analysis in wine and beer with recovery rate >90%, as well as Mycosep™ for wine and chili. On the contrary, MIP columns were the most appropriate to clean up coffee. A total of 120 samples (30 wines, 30 beers, 30 roasted coffee, 30 chili) marketed in Italy were analyzed, by applying the developed clean-up methods. Twenty-seven out of 120 samples analyzed (22.7%: two wines, five beers, eight coffees, and 12 chili) resulted positive to OTA. A higher incidence of OTA was found in chili (40.0%) more than wine (6.6%), beers (16.6%) and coffee (26.6%). Moreover, OTA concentration in chili was the highest detected, reaching 47.8 µg/kg. Furthermore, three samples (2.5%), two wines and one chili, exceeded the European threshold.
It is unclear whether consumption of low-calorie beverages (LCB) leads to compensatory consumption of sweet foods, thus reducing benefits for weight control or diet quality. This analysis investigated associations between beverage consumption and energy intake and diet quality of adults in the UK National Diet and Nutrition Survey (NDNS) (2008-2011; n = 1590), classified into: (a) non-consumers of soft drinks (NC); (b) LCB consumers; © sugar-sweetened beverage (SSB) consumers; or (d) consumers of both beverages (BB), based on 4-day dietary records. Within-person data on beverage consumption on different days assessed the impact on energy intake. LCB consumers and NC consumed less energy and non-milk extrinsic sugars than other groups. Micronutrient intakes and food choices suggested higher dietary quality in NC/LCB consumers compared with SSB/BB consumers. Within individuals on different days, consumption of SSB, milk, juice, and alcohol were all associated with increased energy intake, while LCB and tea, coffee or water were associated with no change; or reduced energy intake when substituted for caloric beverages. Results indicate that NC and LCB consumers tend to have higher quality diets compared with SSB or BB consumers and do not compensate for sugar or energy deficits by consuming more sugary foods.