24 June 2019 In Diabetes

BACKGROUND: Previous studies identified conflicting results about the effects of wine intake on glucose parameters and the risk of cardiovascular diseases in type 2 diabetes mellitus (T2DM). The present study further investigated the association between wine digestion and these outcomes in T2DM patients.

MATERIAL AND METHODS: A search of PubMed, Embase, and Scopus databases (up to November 2018) was performed for randomized interventional trials which evaluated the effect of wine on blood pressure (BP), glucose parameters and lipid profiles in T2DM people. We used a variety of tests: fixed and random effects models, Q Cochrane test and I index, Egger and Begg tests, forest plots, and sensitivity analysis in our study.

RESULTS: A total of 9 randomized interventional studies were included in this meta-analysis. Overall, significant association between wine intake with diastolic BP (weighted mean difference [WMD] = 0.10; 95% confidence interval [95% CI]: -0.01 to 0.20, P = .03 I = 13%) and total cholesterol (TC) (WMD = 0.16, 95% CI: 0.02-0.31, P = .03, I = 6%), whereas no noticeable differences in glucose parameters, systolic BP, low-density lipoprotein cholesterol (LDLC), triglyceride (TG) and high-density lipoprotein cholesterol (HDLC) were identified between wine and controls groups (fasting glucose [FG],WMD = -0.00, 95% CI: -0.58 to 0.58; fasting insulin [FI], -0.22, -2.09 to 1.65; HbAc1%, -0.16, -0.40 to 0.07; systolic blood pressure, 0.12, -0.05 to 0.28; LDLC, -0.02, -0.25 to 0.21; TG, -0.34, -1.31 to 0.64; HDLC, 0.22, -0.08 to 0.53].

CONCLUSION: This meta-analysis revealed that moderate wine consumption among T2DM patients could reduce the level of diastolic blood pressure and TC, but not glucose parameters and other cardiovascular risk factors.

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 Drinking & Eating Patterns

Reduction of excessive alcohol consumption still remains a significant challenge to the actions in the scope of public health of European citizens. The aim of this study is to present the prevalence of alcohol consumption and to estimate the occurrence of risky drinking among college students from the Polish, Slovak, Romanian, and Ukrainian parts of the Carpathian Euroregion, taking social contexts into account. The consumption of alcohol was estimated on the basis of the respondents' statements regarding the quantity and frequency of their consumption of beer, wine, and vodka. The study included people from the first year of undergraduate studies. The analysis used the Chi-square independence test and odds ratios (ORs). There were significant differences in the frequency of alcohol consumption, as well as the individual types consumed, among the respondents from the analyzed countries. Of the examined college students, 70% admit to occasional drinking. The pattern of dangerous alcohol consumption occurs in the case of approximately every seventh person. Risky drinking occurs with much greater frequency among male students rather than their female counterparts. In Romania, a very small percentage of female students engage in risky drinking. The analysis did not show statistically significant differences in the frequency of risky drinking between countries. The coexistence of other adverse health behaviors, such as smoking and alcohol abuse, was confirmed.

 

Reference/Source 

Zadarko-Domaradzka,M.; Barabasz,Z.; Sobolewski,M.; Niziol-Babiarz,E.; Penar-Zadarko,B.; Szybisty,A.; Zadarko,E.

Alcohol Consumption and Risky Drinking Patterns among College Students from Selected Countries of the Carpathian Euroregion

Biomed.Res.Int. 2018

22 February 2019 In General Health

BACKGROUND: Unhealthy alcohol use (UAU) is one of the major causes of preventable morbidity, mortality, and associated behavioral risks worldwide. Although mobile health (mHealth) interventions can provide consumers with an effective means for self-control of UAU in a timely, ubiquitous, and cost-effective manner, to date, there is a lack of understanding about different health outcomes brought by such interventions. The core components of these interventions are also unclear.

OBJECTIVE: This study aimed to systematically review and synthesize the research evidence about the efficacy of mHealth interventions on various health outcomes for consumer self-control of UAU and to identify the core components to achieve these outcomes.

METHODS: We systematically searched 7 electronic interdisciplinary databases: Scopus, PubMed, PubMed Central, CINAHL Plus with full text, MEDLINE with full text, PsycINFO, and PsycARTICLES. Search terms and Medical Subject Headings "mHealth," "text message," "SMS," "App," "IVR," "self-control," "self-regulation," "alcohol*," and "intervention" were used individually or in combination to identify peer-reviewed publications in English from 2008 to 2017. We screened titles and abstracts and assessed full-text papers as per inclusion and exclusion criteria. Data were extracted from the included papers according to the Consolidated Standards of Reporting Trials-EHEALTH checklist (V 1.6.1) by 2 authors independently. Data quality was assessed by the Mixed Methods Appraisal Tool. Data synthesis and analyses were conducted following the procedures for qualitative content analysis. Statistical testing was also conducted to test differences among groups of studies. RESULTS: In total, 19 studies were included in the review. Of these 19 studies, 12 (63%) mHealth interventions brought significant positive outcomes in improving participants' health as measured by behavioral (n=11), physiological (n=1), and cognitive indicators (n=1). No significant health outcome was reported in 6 studies (6/19, 32%). Surprisingly, a significant negative outcome was reported for the male participants in the intervention arm in 1 study (1/19, 5%), but no change was found for the female participants. In total, 5 core components reported in the mHealth interventions for consumer self-control of UAU were context, theoretical base, delivery mode, content, and implementation procedure. However, sound evidence is yet to be generated about the role of each component for mHealth success. The health outcomes were similar regardless of types of UAU, deployment setting, with or without nonmobile cointervention, and with or without theory.

CONCLUSIONS: Most studies reported mHealth interventions for self-control of UAU appeared to be improving behavior, especially the ones delivered by short message service and interactive voice response systems. Further studies are needed to gather sound evidence about the effects of mHealth interventions on improving physiological and cognitive outcomes as well as the optimal design of these interventions, their implementation, and effects in supporting self-control of UAU.

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