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Aplicación de grafos acíclicos dirigidos en la evaluación de un set mínimo de ajuste de confusores: un complemento al modelamiento estadístico en estudios epidemiológicos observacionales / Directed acyclic graphs in statistical modelling of epidemiological studies
Werlinger, Fabiola; Cáceres, Dante D.
  • Werlinger, Fabiola; Universidad de Chile. Facultad de Odontología. Centro de Epidemiología y Vigilancia de las Enfermedades Orales. Santiago. CL
  • Cáceres, Dante D; Universidad de Chile. Escuela de Salud Pública. Programa de Salud Ambiental. Santiago. CL
Rev. méd. Chile ; 146(7): 907-913, jul. 2018. tab, graf
Article in Spanish | LILACS | ID: biblio-961477
ABSTRACT

Background:

Confusion in observational epidemiological studies distorts the relationship between exposure and event. "Step by step" regression models, diverts the decision to a statistical algorithm with little causal basis. Directed Acyclic Graphs (DAGs), qualitatively and visually assess the confusion. They can complement the decision on confounder control during statistical modeling.

Aim:

To evaluate the minimum set of confounders to be controlled in a cause-effect relationship with the use of "step-by-step regression" and DAGs, in a study of arsenic exposure. Material and

Methods:

We worked with data from Cáceres et al., 2010 in 66 individuals from northern Chile. The interindividual variability in the urinary excretion of dimethyl arsenic acid attributable to the GSTT1 polymorphism was estimated. A causal DAG was constructed using DAGitty v2.3 with the list of variables. A multiple linear regression model with the step-by-step backwards methodology was carried out.

Results:

The causal diagram included 12 non-causal open pathways. The minimum adjustment set corresponded to the variables "sex", "body mass index" and "fish and seafood ingest". Confusion retention of the multivariate model included normal and overweight status, gender and the interaction between "water intake" and GSTT1.

Conclusions:

The use of DAG prior to the modeling would allow a more comprehensive, coherent and biologically plausible analysis of causal relationships in public health.
Subject(s)


Full text: Available Index: LILACS (Americas) Main subject: Epidemiologic Studies / Confounding Factors, Epidemiologic / Regression Analysis Type of study: Diagnostic study / Observational study / Prognostic study Limits: Humans Country/Region as subject: South America / Chile Language: Spanish Journal: Rev. méd. Chile Journal subject: Medicine Year: 2018 Type: Article Affiliation country: Chile Institution/Affiliation country: Universidad de Chile/CL

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Full text: Available Index: LILACS (Americas) Main subject: Epidemiologic Studies / Confounding Factors, Epidemiologic / Regression Analysis Type of study: Diagnostic study / Observational study / Prognostic study Limits: Humans Country/Region as subject: South America / Chile Language: Spanish Journal: Rev. méd. Chile Journal subject: Medicine Year: 2018 Type: Article Affiliation country: Chile Institution/Affiliation country: Universidad de Chile/CL