2008
DOI: 10.1038/sj.ki.5002650
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Confounding: What it is and how to deal with it

Abstract: As confounding obscures the 'real' effect of an exposure on outcome, investigators performing etiological studies do their utmost best to prevent or control confounding. Unfortunately, in this process, errors are frequently made. This paper explains that to be a potential confounder, a variable needs to satisfy all three of the following criteria: (1) it must have an association with the disease, that is, it should be a risk factor for the disease; (2) it must be associated with the exposure, that is, it must … Show more

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Cited by 359 publications
(259 citation statements)
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“…The independent relationship between eGFR, FGF-23, and ADMA in this cohort was investigated by introducing into the same linear regression model all variables that met criteria to be confounders, 47 46 The relationship between intact FGF-23 and the incidence rate of renal events was investigated by Kaplan-Meier survival analysis and by univariate and multiple Cox regression models. In the survival analysis, patients who died (n=42) were censored at the date of death.…”
Section: Southern Italy Cohortmentioning
confidence: 99%
See 1 more Smart Citation
“…The independent relationship between eGFR, FGF-23, and ADMA in this cohort was investigated by introducing into the same linear regression model all variables that met criteria to be confounders, 47 46 The relationship between intact FGF-23 and the incidence rate of renal events was investigated by Kaplan-Meier survival analysis and by univariate and multiple Cox regression models. In the survival analysis, patients who died (n=42) were censored at the date of death.…”
Section: Southern Italy Cohortmentioning
confidence: 99%
“…In the multiple Cox regression model we included intact FGF-23, ADMA, and eGFR and all variables that met criteria to be confounders. 47 We also tested the full list of variables considered above in a saturated model. The Cox regression model did not violate the proportional hazards assumption.…”
Section: Southern Italy Cohortmentioning
confidence: 99%
“…We adjusted the models for factors fulfilling criteria for confounding, obtaining adjusted eGFRs. 10 Potential confounders were sex, age, country, and working in a for-profit center. A 2-sided P Ͻ 0.05 was considered statistically significant.…”
Section: Data Processing and Analysismentioning
confidence: 99%
“…Second, we investigated the predictive power of serum IL-6 in the prospective cohort study. In both logistic and survival analyses, we considered variables that met criteria to be confounders (i.e., variables related [P#0.10] to both the exposure under investigation [serum IL-6 levels below/above the median value] and history of CVD or incident fatal and nonfatal CV events, which are not an effect of the exposure and are not in the causal pathway between the exposure and outcome) (34). Tested covariates included traditional risk factors (age, sex, smoking, diabetes and glucose, cholesterol, and BP), factors specific to CKD (hemoglobin, albumin, eGFR, and urinary protein), antihypertensive treatment, body mass index, and CRP.…”
Section: Statistical Analysesmentioning
confidence: 99%