26 February 2019 In Drinking & Eating Patterns

Background: Alcohol-induced hangover constitutes a significant, yet understudied, global hazard and a large socio-economic burden. Old folk wisdoms such as "Beer before wine and you'll feel fine; wine before beer and you'll feel queer" exist in many languages. However, whether these concepts in fact reduce hangover severity is unclear.

Objectives: The aim of this study was to investigate the influence of the combination and order of beer and wine consumption on hangover intensity. Methods: In this multiarm, parallel randomized controlled matched-triplet crossover open-label interventional trial, participants were matched into triplets and randomly assigned according to age, gender, body composition, alcohol drinking habits, and hangover frequency. Study group 1 consumed beer up to a breath alcohol concentration (BrAC) >/=0.05% and then wine to BrAC >/=0.11% (vice versa for study group 2). Control group subjects consumed either only beer or only wine. On a second intervention day (crossover) >/=1 wk later, study-group subjects were switched to the opposite drinking order. Control-group subjects who drank only beer on the first intervention received only wine on the second study day (and vice versa). Primary endpoint was hangover severity assessed by Acute Hangover Scale rating on the day following each intervention. Secondary endpoints were factors associated with hangover intensity.

Results: Ninety participants aged 19-40 y (mean age 23.9), 50% female, were included (study group 1 n = 31, study group 2 n = 31, controls n = 28). Neither type nor order of consumed alcoholic beverages significantly affected hangover intensity (P > 0.05). Multivariate regression analyses revealed perceived drunkenness and vomiting as the strongest predictors for hangover intensity.

Conclusions: Our findings dispel the traditional myths "Grape or grain but never the twain" and "Beer before wine and you'll feel fine; wine before beer and you'll feel queer" regarding moderate-to-severe alcohol intoxication, whereas subjective signs of progressive intoxication were confirmed as accurate predictors of hangover severity. This trial was prospectively registered at the Witten/Herdecke University Ethics Committee as 140/2016 and retrospectively registered at the German Clinical Trials Register as DRKS00015285

 

Reference/Source

Kochling,J.; Geis,B.; Wirth,S.; Hensel,K.O.

Grape or grain but never the twain? A randomized controlled multiarm matched-triplet crossover trial of beer and wine

Am.J Clin.Nutr, 2019, 109,2: 345-352.

26 February 2019 In Cancer

PURPOSE: Breast cancer (BC) risk prediction allows systematic identification of individuals at highest and lowest risk. We extend the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) risk model to incorporate the effects of polygenic risk scores (PRS) and other risk factors (RFs).

METHODS: BOADICEA incorporates the effects of truncating variants in BRCA1, BRCA2, PALB2, CHEK2, and ATM; a PRS based on 313 single-nucleotide polymorphisms (SNPs) explaining 20% of BC polygenic variance; a residual polygenic component accounting for other genetic/familial effects; known lifestyle/hormonal/reproductive RFs; and mammographic density, while allowing for missing information.

RESULTS: Among all factors considered, the predicted UK BC risk distribution is widest for the PRS, followed by mammographic density. The highest BC risk stratification is achieved when all genetic and lifestyle/hormonal/reproductive/anthropomorphic factors are considered jointly. With all factors, the predicted lifetime risks for women in the UK population vary from 2.8% for the 1st percentile to 30.6% for the 99th percentile, with 14.7% of women predicted to have a lifetime risk of >/=17-<30% (moderate risk according to National Institute for Health and Care Excellence [NICE] guidelines) and 1.1% a lifetime risk of >/=30% (high risk).

CONCLUSION: This comprehensive model should enable high levels of BC risk stratification in the general population and women with family history, and facilitate individualized, informed decision-making on prevention therapies and screening.

22 February 2019 In Liver Disease

OBJECTIVE: To evaluate the longitudinal relationship between repeated measures of alcohol consumption and risk of developing fatty liver.

PATIENTS AND METHODS: This study includes 5407 men and women from a British population-based cohort, the Whitehall II study of civil servants, who self-reported alcohol consumption by questionnaire over approximately 30 years (1985-1989 through to 2012-2013). Drinking typologies during midlife were linked to measures of fatty liver (the fatty liver index, FLI) when participants were in older age (age range 60-84 years) and adjusted for age, socio-economic position, ethnicity, and smoking.

RESULTS: Those who consistently drank heavily had two-fold higher odds of increased FLI compared to stable low-risk moderate drinkers after adjustment for covariates (men: OR = 2.04, 95%CI = 1.53-2.74; women: OR = 2.24, 95%CI = 1.08-4.55). Former drinkers also had an increased FLI compared to low-risk drinkers (men: OR = 2.09, 95%CI = 1.55-2.85; women: OR = 1.68, 95%CI = 1.08-2.67). There were non-significant differences in FLI between non-drinkers and stable low-risk drinkers. Among women, there was no increased risk for current heavy drinkers in cross sectional analyses.

CONCLUSION: Drinking habits among adults during midlife affect the development of fatty liver, and sustained heavy drinking is associated with an increased FLI compared to stable low-risk drinkers. After the exclusion of former drinkers, there was no difference between non-drinkers and low-risk drinkers, which does not support a protective effect on fatty liver from low-risk drinking. Cross-sectional analyses among women did not find an increased risk of heavy drinking compared to low-risk drinkers, thus highlighting the need to take a longitudinal approach.

22 February 2019 In General Health

BACKGROUND: Prevention aiming at smoking, alcohol consumption, and BMI could potentially bring large gains in life expectancy (LE) and health expectancy measures such as Healthy Life Years (HLY) and Life Expectancy in Good Perceived Health (LEGPH) in the European Union. However, the potential gains might differ by region.

METHODS: A Sullivan life table model was applied for 27 European countries to calculate the impact of alternative scenarios of lifestyle behavior on life and health expectancy. Results were then pooled over countries to present the potential gains in HLY and LEGPH for four European regions.

RESULTS: Simulations show that up to 4 years of extra health expectancy can be gained by getting all countries to the healthiest levels of lifestyle observed in EU countries. This is more than the 2 years to be gained in life expectancy. Generally, Eastern Europe has the lowest LE, HLY, and LEGPH. Even though the largest gains in LEPGH and HLY can also be made in Eastern Europe, the gap in LE, HLY, and LEGPH can only in a small part be closed by changing smoking, alcohol consumption, and BMI.

CONCLUSION: Based on the current data, up to 4 years of good health could be gained by adopting lifestyle as seen in the best-performing countries. Only a part of the lagging health expectancy of Eastern Europe can potentially be solved by improvements in lifestyle involving smoking and BMI. Before it is definitely concluded that lifestyle policy for alcohol use is of relatively little importance compared to smoking or BMI, as our findings suggest, better data should be gathered in all European countries concerning alcohol use and the odds ratios of overconsumption of alcohol.

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