24 June 2019 In Diabetes

BACKGROUND & AIMS: Alcohol consumption correlates with type 2 diabetes through its effects on insulin resistance, changes in alcohol metabolite levels, and anti-inflammatory effects. We aim to clarify association between frequency of alcohol consumption and risk of diabetes in Taiwanese population.

METHODS: The National Health Interview Survey (NHIS) in 2001, 2005, and 2009 selected a representative sample of Taiwan population using a multistage sampling design. Information was collected by standardized face to face interview. Study subjects were connected to the Taiwan National Health Insurance claims dataset and National Register of Deaths Dataset from 2000 to 2013. Kaplan-Meier curve with log rank test was employed to assess the influence of alcohol drinking on incidence of diabetes. Univariate and multivariate Cox proportional regression were used to recognize risk factors of diabetes.

RESULTS: A total of 43,000 participants were included (49.65% male; mean age, 41.79 +/- 16.31 years). During the 9-year follow-up period, 3650 incident diabetes cases were recognized. Kaplan-Meier curves comparing the four groups of alcohol consumption frequency showed significant differences (p < 0.01). After adjustment for potentially confounding variables, compared to social drinkers, the risks of diabetes were significantly higher for non-drinkers (adjusted hazard ratio [AHR] = 1.21; 95% confidence interval [CI], 1.09-1.34; p < 0.01), regular drinkers (AHR = 1.19; 95% CI, 1.06-1.35; p < 0.01), and heavy drinkers (AHR = 2.21, 95% CI, 1.56-3.13, p < 0.01).

CONCLUSIONS: Social drinkers have a significantly decreased risk of new-onset diabetes compared with non-, regular, and heavy drinkers.

03 June 2019 In Drinking Patterns

OBJECTIVE: A retrospective case-control study was conducted to evaluate whether frequent binge drinking between the age of 18 and 25 years was a risk factor for alcohol dependence in adulthood.

SETTING: The Department of Addictive Medicine and the Clinical Investigation Center of a university hospital in France.

PARTICIPANTS: Cases were alcohol-dependent patients between 25 and 45 years and diagnosed by a psychiatrist. Consecutive patients referred to the Department of Addictive Medicine of a university hospital between 1 January 2017 and 31 December 2017 for alcohol dependence were included in the study. Controls were non-alcohol-dependent adults, defined according to an Alcohol Use Disorders Identification Test score of less than 8, and were matched on age and sex with cases. Data on sociodemographics, behaviour and alcohol consumption were retrospectively collected for three life periods: before the age of 18 years; between the age of 18 and 25 years; and between the age of 25 and 45 years. Frequency of binge drinking between 18 and 25 years was categorised as frequent if more than twice a month, occasional if once a month and never if no binge drinking.

RESULTS: 166 adults between 25 and 45 years were included: 83 were alcohol-dependent and 83 were non-alcohol-dependent. The mean age was 34.6 years (SD: 5.1). Frequent binge drinking between 18 and 25 years occurred in 75.9% of cases and 41.0% of controls (p<0.0001). After multivariate analysis, frequent binge drinking between 18 and 25 years was a risk factor for alcohol dependence between 25 and 45 years: adjusted OR=2.83, 95% CI 1.10 to 7.25.

CONCLUSIONS: Frequent binge drinking between 18 and 25 years appears to be a risk factor for alcohol dependence in adulthood. Prevention measures for binge drinking during preadulthood, especially frequent binge drinking, should be implemented to prevent acute consequences as injury and death and long-term consequences as alcohol dependence.

TRIAL REGISTRATION NUMBER: NCT03204214; Results.

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.

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