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2024-11-11

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Why Do Only Some Cohort Studies Find Health Benefits From Low-Volume Alcohol Use? A Systematic Review and Meta-Analysis of Study Characteristics That May Bias Mortality Risk Estimates (www.jsad.com)

submitted 3 months ago by ArcticDagger@feddit.dk to c/science@lemmy.world

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From the article:

As predicted, studies with younger cohorts and separating former and occasional drinkers from abstainers estimated similar mortality risk for low-volume drinkers (RR = 0.98, 95% CI [0.87, 1.11]) as abstainers. Studies not meeting these quality criteria estimated significantly lower risk for low-volume drinkers (RR = 0.84, [0.79, 0.89]). In exploratory analyses, studies controlling for smoking and/or socioeconomic status had significantly reduced mortality risks for low-volume drinkers. However, mean RR estimates for low-volume drinkers in nonsmoking cohorts were above 1.0 (RR = 1.16, [0.91, 1.41]).

Studies with life-time selection biases may create misleading positive health associations. These biases pervade the field of alcohol epidemiology and can confuse communications about health risks. Future research should investigate whether smoking status mediates, moderates, or confounds alcohol-mortality risk relationships.

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[–] cashmaggot@piefed.social 1 points 3 months ago

They seemingly tend to crop out gender, socio-economic standings, and ethnicity all of which can alter the data. Although they're not used I believe due to scope and variability. It is also noted there are external influences which could in theory "fudge" the data. At least as far as I see it. There also seems to be a tie to smoking and alcohol which perhaps links the two risky behaviors together. An abstaining of one, leading to an abstaining in the other. Which leads in part to what others are saying about other health issues not being tracked or noted.

But ultimately I would say addiction, as a disease, is quite abstract. And it's very social in nature. And that many cultures spread it through coming-of-age rituals. Which makes it difficult to villainize. But also difficult to "pin down" when an activity reaches an unhealthy level. Also people lie. So all of this could lead to fudged data as well.