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        "resumen" => "<span class="elsevierStyleSectionTitle">Objetivo</span><p class="elsevierStyleSimplePara elsevierViewall">Comparar la utilidad de 2 m&#233;todos anal&#237;ticos multivariados&#44; el an&#225;lisis como casos y controles &#40;CC&#41; y como casos y controles anidados &#40;CCa&#41; en una cohorte&#44; para identificar los factores asociados al inicio del consumo de cannabis&#46;</p> <span class="elsevierStyleSectionTitle">M&#233;todos</span><p class="elsevierStyleSimplePara elsevierViewall">Estudio longitudinal con una muestra de 1&#46;056 alumnos de primer curso de Educaci&#243;n Secundaria Obligatoria &#40;ESO&#41;&#44; seguidos anualmente hasta cuarto de ESO&#46; En el an&#225;lisis como CC se consideraron casos los que declararon&#44; en el cuarto a&#241;o&#44; haber consumido cannabis y controles los que no hab&#237;an consumido nunca&#44; estimando modelos de regresi&#243;n log&#237;stica &#40;RL&#41;&#46; En el an&#225;lisis como CCa&#44; se compararon los casos de cada a&#241;o de seguimiento con una muestra aleatoria de controles de riesgo en ese mismo a&#241;o&#44; estimando modelos de RL condicional&#46;</p> <span class="elsevierStyleSectionTitle">Resultados</span><p class="elsevierStyleSimplePara elsevierViewall">En el an&#225;lisis como CC&#44; se identificaron 6 variables en los chicos y 9 en las chicas en los modelos bivariados&#44; y 3 en los chicos y 4 en las chicas en los multivariados&#46; En el an&#225;lisis como CCa se obtuvieron 17 variables en los modelos bivariados y 4 en los multivariados&#44; tanto en los chicos como en las chicas&#46; Los estimadores del an&#225;lisis como CC ten&#237;an 1&#44;2 veces m&#225;s variabilidad&#46;</p> <span class="elsevierStyleSectionTitle">Conclusiones</span><p class="elsevierStyleSimplePara elsevierViewall">El an&#225;lisis como CCa permiti&#243; identificar un mayor n&#250;mero de factores asociados al consumo de cannabis y los estimadores fueron m&#225;s precisos&#46; El CCa puede ser una alternativa m&#225;s eficiente frente al an&#225;lisis como CC&#46;</p>"
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        "titulo" => "Abstract"
        "resumen" => "<span class="elsevierStyleSectionTitle">Objective</span><p class="elsevierStyleSimplePara elsevierViewall">To compare the utility of two multivariate analytic methods&#44; case-control &#40;CC&#41; analysis and nested case-control &#40;NCC&#41; analysis in a cohort&#44; to identify the factors associated with the onset of cannabis use&#46;</p> <span class="elsevierStyleSectionTitle">Methods</span><p class="elsevierStyleSimplePara elsevierViewall">A longitudinal cohort study of a sample of secondary school students &#40;n &#61; 1&#44;056&#41; in the first year of secondary school was carried out&#46; Participating students were followed-up annually until the fourth year of secondary school&#46; In the CC analysis&#44; students in the fourth year who reported having consumed cannabis at some time were considered cases and those who had never consumed cannabis were considered controls&#46; Logistic regression &#40;LR&#41; models were estimated&#46; In the NCC analysis&#44; cases in each year of follow-up were compared with a random sample of controls at risk in the same year and conditional LR models were estimated&#46; I</p> <span class="elsevierStyleSectionTitle">Results</span><p class="elsevierStyleSimplePara elsevierViewall">In the CC analysis&#44; 6 variables in boys and 9 variables in girls in bivariate models and 3 variables in boys and 4 variables in girls in multivariate models were identified&#46; In the NCC analysis&#44; 17 variables in univariate models and 4 in multivariate models were obtained in both boys and girls&#46; The estimators of the CC analysis showed an average of 1&#46;2-fold more variability&#46;</p> <span class="elsevierStyleSectionTitle">Conclusions</span><p class="elsevierStyleSimplePara elsevierViewall">A higher number of factors associated with cannabis use were identified in the NCC analysis and the estimators were more precise&#46; NCC could be a more efficient option than CC analysis&#46;</p>"
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Vol. 21. Núm. 6.
Páginas 515-524 (noviembre - diciembre 2007)
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Vol. 21. Núm. 6.
Páginas 515-524 (noviembre - diciembre 2007)
Nota metodológica
Open Access
Comparación de dos métodos para identificar los factores asociados al inicio del consumo de cannabis en un estudio de cohortes
Comparison of two methods to identify factors associated with the onset of cannabis use in a cohort study
Visitas
1040
Mònica Guxensa,b,c, Manel Nebota,c,d,
Autor para correspondencia
mnebot@aspb.es

Correspondencia: Dr. Manel Nebot. Servei d’Avaluació i Mètodes d’Intervenció. Agència de Salut Pública de Barcelona. Pl. Lesseps, 1. 08015 Barcelona. España.
, Antònia Domingo-Salvanyc,e, Carles Arizaa,c
a Servei d’Avaluació i Mètodes d’Intervenció, Agència de Salut Pública de Barcelona; Barcelona, España
b Unitat Docent de Medicina Preventiva i Salut Pública IMAS-UPF-ASPB, Barcelona, España
c CIBER Epidemiología y Salud Pública (CIBERESP), España
d Departamento de Ciencias Experimentales y de la Salud, Universitat Pompeu Fabra, Barcelona, España
e Unitat de Recerca en Serveis Sanitaris, Institut Municipal d’Investigació Mèdica, Barcelona, España
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Información del artículo
Resumen
Objetivo

Comparar la utilidad de 2 métodos analíticos multivariados, el análisis como casos y controles (CC) y como casos y controles anidados (CCa) en una cohorte, para identificar los factores asociados al inicio del consumo de cannabis.

Métodos

Estudio longitudinal con una muestra de 1.056 alumnos de primer curso de Educación Secundaria Obligatoria (ESO), seguidos anualmente hasta cuarto de ESO. En el análisis como CC se consideraron casos los que declararon, en el cuarto año, haber consumido cannabis y controles los que no habían consumido nunca, estimando modelos de regresión logística (RL). En el análisis como CCa, se compararon los casos de cada año de seguimiento con una muestra aleatoria de controles de riesgo en ese mismo año, estimando modelos de RL condicional.

Resultados

En el análisis como CC, se identificaron 6 variables en los chicos y 9 en las chicas en los modelos bivariados, y 3 en los chicos y 4 en las chicas en los multivariados. En el análisis como CCa se obtuvieron 17 variables en los modelos bivariados y 4 en los multivariados, tanto en los chicos como en las chicas. Los estimadores del análisis como CC tenían 1,2 veces más variabilidad.

Conclusiones

El análisis como CCa permitió identificar un mayor número de factores asociados al consumo de cannabis y los estimadores fueron más precisos. El CCa puede ser una alternativa más eficiente frente al análisis como CC.

Palabras clave:
Estudio de cohortes
Casos y controles
Casos y controles anidados
Regresión logística
Regresión logística condicional
cannabis
Abstract
Objective

To compare the utility of two multivariate analytic methods, case-control (CC) analysis and nested case-control (NCC) analysis in a cohort, to identify the factors associated with the onset of cannabis use.

Methods

A longitudinal cohort study of a sample of secondary school students (n = 1,056) in the first year of secondary school was carried out. Participating students were followed-up annually until the fourth year of secondary school. In the CC analysis, students in the fourth year who reported having consumed cannabis at some time were considered cases and those who had never consumed cannabis were considered controls. Logistic regression (LR) models were estimated. In the NCC analysis, cases in each year of follow-up were compared with a random sample of controls at risk in the same year and conditional LR models were estimated. I

Results

In the CC analysis, 6 variables in boys and 9 variables in girls in bivariate models and 3 variables in boys and 4 variables in girls in multivariate models were identified. In the NCC analysis, 17 variables in univariate models and 4 in multivariate models were obtained in both boys and girls. The estimators of the CC analysis showed an average of 1.2-fold more variability.

Conclusions

A higher number of factors associated with cannabis use were identified in the NCC analysis and the estimators were more precise. NCC could be a more efficient option than CC analysis.

Key words:
Cohort study
Case-control
Nested case-control
Logistic regression
Conditional logistic regression
cannabis
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