General Health

Moderate wine drinkers have a lower risk to die from any cause (lower total  mortality risk) than those who abstain or drink heavily. This widely accepted association is known as the J-curve. This J-curve is attributable to the beneficial effect on cardiovascular health which compensates the negative effects of some cancers resulting in a lower risk to die from any possible cause. The relative risk of dying is lowest among light to moderate drinkers and increased among abstainers. However, the risk increases dramatically with each drink above moderation. Thus, while one or two glasses can be considered “good for your health”, drinking more than what guidelines suggest will not provide more benefits, only more harm.

 

If consumed in excess, alcoholic beverages increase the exposure to a wide range of risk factors whereby the risk rises with the amount of alcohol consumed. Thus, it is crucial to prevent abusive consumption. Alcohol abuse is associated with a range of long-term chronic diseases that reduce the quality of life. These include hypertension, cardiovascular problems, cirrhosis of the liver, alcohol dependence, various forms of cancer, alcohol-related brain damage and a range of other problems. Not only the amount of alcohol but also the drinking patterns are important. Findings from a meta analysis support results from other studies that binge drinking is detrimental to heart health. The authors concluded that it is best for drinkers to avoid binge drinking -- not only because of the possible heart effects, but also because of more immediate risks, like accidents and violence.

 

In addition to health issues resulting from excessive alcohol consumption, there are social consequences, both for the drinker and for others in the community. The consequences include harm to family members (including children), to friends and colleagues as well as to bystanders and strangers.

 

The above summary provides an overview of the topic, for more details and specific questions, please refer to the articles in the database.

 

 

BACKGROUND: Previous studies exploring usual alcohol consumption and falls risk were scarce in China. In addition, the dose-response relationship has not been explored so far. This study aims to estimate the association between usual alcohol consumption and risk of falls among middle-aged and older Chinese adults based on data from the China Health and Retirement Longitudinal Study (CHARLS), which is representative of the population of the entire country. METHODS: Baseline survey data in 2015 and follow-up data in 2018 in CHARLS were utilized. Alcohol consumption was calculated in grams per day (gr/day) according to self-reported drinking data and categorized accordingly to The Dietary Guidelines for Chinese Residents (DGC) 2016. Fall was obtained from self-reported information. Multivariable logistic regression analyses were…
We aimed to investigate whether alcohol intake contributes to lung function levels and which beverage type may have an effect. We investigated 3742 participants from the Wuhai-Zhuhai Cohort and 12,526 participants from the Dongfeng-Tongji Cohort, and they were followed up for 3 and 5 years, respectively. Information on the type and daily amount of alcohol intake was collected through face-to-face interviews. Lung function was measured by trained physicians using electronic spirometers. Compared with nondrinkers, moderate alcohol intake was significantly associated with a 70.03 and 74.92 mL increase in FEV1 and FVC, respectively (P < 0.05), after adjusting for covariates. With regard to beverage type, red wine was associated with a 105.31 and 98.91 mL increase in FEV1 and FVC, respectively…
Alcohol consumption is associated with the development of cardiovascular diseases, cancer, and liver disease. The biological mechanisms are still largely unclear. Here, we aimed to use an agnostic approach to identify phenotypes mediating the effect of alcohol on various diseases. METHODS: We performed an agnostic association analysis between alcohol consumption (red and white wine, beer/cider, fortified wine, and spirits) with over 7800 phenotypes from the UK biobank comprising 223,728 participants. We performed Mendelian randomisation analysis to infer causality. We additionally performed a Phenome-wide association analysis and a mediation analysis between alcohol consumption as exposure, phenotypes in a causal relationship with alcohol consumption as mediators, and various diseases as the outcome. RESULTS: Of 45 phenotypes in association with alcohol consumption, 20…
AIMS: The Tromso Study 1979-1980 collected information on alcohol (beer, wine and spirits) consumption frequency and inebriation frequency, and the oldest male participants (aged 50-54 years) were followed for all-cause mortality. This study aimed to identify the impact of habitual alcohol consumption in mid-life on reaching up to 90 years of age. RESULTS: Among the study sample of 778, a total of 120 (15.4%) men reached the age of 90. The most common reported alcohol consumption frequency was 'never or a few times a year', and 18.9% of those in this group reached 90 compared with 11.9% of those who reported a more frequent beer consumption. Fifty per cent survival in these groups was 80.5 and 76.9 years, respectively. The…
Alcohol's impact on telomere length, a proposed marker of biological aging, is unclear. We performed the largest observational study to date (in n = 245,354 UK Biobank participants) and compared findings with Mendelian randomization (MR) estimates. Two-sample MR used data from 472,174 participants in a recent genome-wide association study (GWAS) of telomere length. Genetic variants were selected on the basis of associations with alcohol consumption (n = 941,280) and alcohol use disorder (AUD) (n = 57,564 cases). Non-linear MR employed UK Biobank individual data. MR analyses suggested a causal relationship between alcohol traits, more strongly for AUD, and telomere length. Higher genetically-predicted AUD (inverse variance-weighted (IVW) beta = -0.06, 95% confidence interval (CI): -0.10 to -0.02, p = 0.001) was…
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