Are there non-linear relationships between alcohol consumption and long-term health?: a systematic review of observational studies employing approaches to improve causal inference

Abstract

Background Research has long found ‘J-shaped’ relationships between alcohol consumption and certain health outcomes, indicating a protective effect of moderate consumption. However, methodological limitations in most studies hinder causal inference. This review aimed to identify all observational studies employing improved approaches to mitigate confounding in characterizing alcohol–long-term health relationships, and to qualitatively synthesize their findings. Methods Eligible studies met the above description, were longitudinal (with pre-defined exceptions), discretized alcohol consumption, and were conducted with human populations. MEDLINE, PsycINFO, Embase and SCOPUS were searched in May 2020, yielding 16 published manuscripts reporting on cancer, diabetes, dementia, mental health, cardiovascular health, mortality, HIV seroconversion, and musculoskeletal health. Risk of bias of cohort studies was evaluated using the Newcastle-Ottawa Scale, and a recently developed tool was used for Mendelian Randomization studies. Results A variety of functional forms were found, including reverse J/J-shaped relationships for prostate cancer and related mortality, dementia risk, mental health, and certain lipids. However, most outcomes were only evaluated by a single study, and few studies provided information on the role of alcohol consumption pattern. Conclusions More research employing enhanced causal inference methods is urgently required to accurately characterize alcohol–long-term health relationships. Those studies that have been conducted find a variety of linear and non-linear functional forms, with results tending to be discrepant even within specific health outcomes. Trial registration PROSPERO registration number CRD42020185861.

Do MAFLD Patients with Harmful Alcohol Consumption Have a Different Dietary Intake?

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Is low‐level alcohol consumption really health‐protective? A critical review of approaches to promote causal inference and recent applications

“…Both MR and G‐methods, as well as other causal inference methods discussed elsewhere (see Visontay et al., 2022), have unique advantages for promoting causal inference from observational data, as well as unique weaknesses. The G‐methods can elucidate causal relationships, but if the model is misspecificied, then estimates will still be biased.…”

The association between alcohol consumption and all‐cause mortality: An umbrella review of systematic reviews using lifetime abstainers or low‐volume drinkers as a reference group

“…Five systematic reviews met the inclusion criteria [1,2,[21][22][23], of which four reviews contained a meta-analysis [1,2,21,23] (Table 1).…”

“…These reviews ranged in size from 1 to 87 included primary cohort studies, from 14 787 to 3 998 626 included participants and from 30 406 to 367 103 deaths from any cause. In the one review without a meta-analysis, one relevant primary study was captured, which was a twin study not captured by other reviews [22].…”

“…According to the ROBIS classification, four of the five included reviews had high risk of bias, and one review had low risk of bias (Table 2). Reviews were classified at high risk of bias because of the following reasons: one review searched only a single electronic database [1], one review did not specify literature search terms [21], three reviews did not specify that at least two reviewers performed study selection and/or data collection and/or risk of bias assessment for all articles [1,21,22], three reviews did not perform a risk of bias or methodological quality assessment [1,21,23] and one review did not address publication bias [21].…”