Evaluation of confounding in epidemiologic studies assessing alcohol consumption on the risk of ischemic heart disease

Abstract

Background: Among different investigators studying the same exposures and outcomes, there may be a lack of consensus about potential confounders that should be considered as matching, adjustment, or stratification variables in observational studies. Concerns have been raised that confounding factors may affect the results obtained for the alcohol-ischemic heart disease relationship, as well as their consistency and reproducibility across different studies. Therefore, we assessed how confounders are defined, operationalized, and discussed across individual studies evaluating the impact of alcohol on ischemic heart disease risk. Methods: For observational studies included in a recent alcohol-ischemic heart disease meta-analysis, we identified all variables adjusted, matched, or stratified for in the largest reported multivariate model (i.e. potential confounders). We recorded how the variables were measured and grouped them into higher-level confounder domains. Abstracts and Discussion sections were then assessed to determine whether authors considered confounding when interpreting their study findings. Results: 85 of 87 (97.7%) studies reported multivariate analyses for an alcohol-ischemic heart disease relationship. The most common higher-level confounder domains included were smoking (79, 92.9%), age (74, 87.1%), and BMI, height, and/or weight (57, 67.1%). However, no two models adjusted, matched, or stratified for the same higherlevel confounder domains. Most (74/87, 85.1%) articles mentioned or alluded to "confounding" in their Abstract or Discussion sections, but only one stated that their main findings were likely to be affected by residual confounding. There were five (5/87, 5.7%) authors that explicitly asked for caution when interpreting results. Conclusion: There is large variation in the confounders considered across observational studies evaluating the impact of alcohol on ischemic heart disease risk and almost all studies spuriously ignore or eventually dismiss confounding in their conclusions. Given that study results and interpretations may be affected by the mix of potential confounders included within multivariate models, efforts are necessary to standardize approaches for selecting and accounting for confounders in observational studies.

Association between patterns of alcohol consumption (beverage type, frequency and consumption with food) and risk of adverse health outcomes: a prospective cohort study

“…In our study, all-cause mortality models were adjusted for 10 covariates, liver cirrhosis models were adjusted for 11 covariates and cardiovascular events models were adjusted for 14 covariates [38]. The models in our study were adjusted for the effect of major determinants of health and well-being to minimise the risk of residual confounding [39]; however, it still remains a possibility.…”

Reaction Time and Visual Memory in Connection to Alcohol Use In Schizophrenia and Schizoaffective Disorder

“…Study findings suggesting positive association between alcohol and cognition could be attributed by unmeasured or residual confounding factors [85,86] like: smoking [87], drink type [88], drink pattern [89], personality [87,90], intelligence [76,91,92], educational attainment [93,94], potential abstainer errors [95,96,97,98], reverse causality bias [99], recall error [100] within person temporal variation [101,102], ascertainment of diseases [103] and sociability effect of alcohol [104]. Study findings suggesting positive association between alcohol and cognition could be attributed by poor motivation [105,106,107].…”

Reaction Time and Visual Memory in Connection with Alcohol Use in Schizophrenia and Schizoaffective Disorder

“…Study findings suggesting a positive association between alcohol use and cognition could be attributed to unmeasured or residual confounding factors [79,80], such as smoking [81], drink types [82], drinking patterns [83], personality [81,84], intelligence [70,85,86], educational attainment [87,88], potential abstainer errors [89][90][91][92], reverse causality bias [93], recall error [94], within-person temporal variation [95,96], ascertainment of diseases [97], and the sociability effect of alcohol [98]. Study findings suggesting a positive association between alcohol use and cognition could be attributed to poor motivation [99][100][101].…”