scholarly journals Should Central Obesity Be an Optional or Essential Component of the Metabolic Syndrome?: Ischemic heart disease risk in the Singapore Cardiovascular Cohort Study

Diabetes Care ◽  
2007 ◽  
Vol 30 (2) ◽  
pp. 343-347 ◽  
Author(s):  
J. Lee ◽  
S. Ma ◽  
D. Heng ◽  
C.-E. Tan ◽  
S.-K. Chew ◽  
...  
Keyword(s):  
Metabolic Syndrome ◽  
Cohort Study ◽  
Heart Disease ◽  
Ischemic Heart Disease ◽  
Central Obesity ◽  
Disease Risk ◽  
Ischemic Heart ◽  
The Metabolic Syndrome ◽  
Ischemic Heart Disease Risk ◽  
Heart Disease Risk

scholarly journals The Effect of Elevated Body Mass Index on Ischemic Heart Disease Risk: Causal Estimates from a Mendelian Randomisation Approach

PLoS Medicine ◽  
2012 ◽  
Vol 9 (5) ◽  
pp. e1001212 ◽  
Author(s):  
Børge G. Nordestgaard ◽  
Tom M. Palmer ◽  
Marianne Benn ◽  
Jeppe Zacho ◽  
Anne Tybjærg-Hansen ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Heart Disease ◽  
Ischemic Heart Disease ◽  
Body Mass ◽  
Disease Risk ◽  
Ischemic Heart ◽  
Mendelian Randomisation ◽  
Elevated Body Mass Index ◽  
Ischemic Heart Disease Risk ◽  
Heart Disease Risk

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

2020 ◽  
Author(s):  
Joshua D Wallach ◽  
Stylianos Serghiou ◽  
Lingzhi Chu ◽  
Alexander C Egilman ◽  
Vasilis Vasiliou ◽  
...  
Keyword(s):  
Heart Disease ◽  
Ischemic Heart Disease ◽  
Observational Studies ◽  
Disease Risk ◽  
Meta Analysis ◽  
Epidemiologic Studies ◽  
Ischemic Heart ◽  
Ischemic Heart Disease Risk ◽  
Study Results ◽  
Heart Disease Risk

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 alcohol and 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 higher-level 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 alcohol and 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.

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