ABSTRACT
Objetivos: Demostrar que la obtención de una muestra nacional probabilística para un estudio longitudinal sobre envejecimiento en España está expuesta a sesgos de selección. Cuantificar las pérdidas que se producen al administrar el cuestionario en distintas fases. Métodos: Estudio transversal sobre población española no institucionalizada de 50 años o más de edad realizado entre 2010 y 2011. Por medio de regresiones logísticas multivariadas se comparan características de las secciones censales de residencia de los que acceden (n = 5813) o no (n = 7023) a formar parte del marco muestral, de los que acceden (n = 1677) o no (n = 2875) a participar en el estudio, y de los individuos que contestan (n = 1398) o no (n = 346) a un cuestionario presencial posterior a uno telefónico. Además, se estudian los motivos de las negativas. Resultados: La mala salud y la discapacidad son los motivos específicos más referidos para no formar parte del marco o no participar en el estudio (14,4% y 27,9%, respectivamente). En ambos casos, la negativa es más frecuente en las secciones censales de menor nivel socioeconómico o ubicadas en Cataluña, Guipúzcoa o Vizcaya. Los individuos mayores de 80 años responden con menos frecuencia al cuestionario presencial. En cada fase de recogida de información se pierde entre un 8,6% y un 18,4% de efectivos. Conclusiones: Un muestreo probabilístico en puntos de muestreo elegidos por conveniencia permitiría dedicar más recursos a aumentar las tasas de respuesta en los colectivos menos participativos. Se propone la concentración de las preguntas en un solo cuestionario más breve previo a la extracción de sangre
Objectives: To demonstrate that selection of a probabilistic sample at a national level for a study of aging in Spain is subject to selection bias. To quantify the losses produced after each phase of the administration of a questionnaire. Methods: We performed a cross-sectional study of the Spanish community-dwelling population aged 50 years or older between 2010 and 2011. Through multivariate logistic regressions, the characteristics of the census tract of the patients' residence were compared between those who agreed (n = 5,813) or refused (n = 7,023) to be included in the sampling frame and between those who agreed (n = 1,677) or refused (n = 2,875) to participate in the study. The individual characteristics of persons who responded (n = 1,398) or refused to respond (n = 346) to a face-to-face questionnaire administered after a telephone interview were also compared. In addition, the reasons for refusal were studied. Results: The most frequent specific reasons for refusing to be included in the sampling frame or to participate in the study were poor health and disability (14.4% and 27.9%, respectively). In both cases, refusal was more frequent in the census tracts of districts with a lower socioeconomic level or those located in Catalonia, Guipúzcoa or Biscay. Individuals older than 81 participated less frequently in the face-to-face questionnaire. Between 8.6% and 18.4% of participants were lost at each stage of information retrieval. Conclusion: Probabilistic sampling in sampling points chosen by the researchers would allow more resources to be devoted to increasing response rates among the groups who are less likely to participate. Questions should be concentrated in only one shorter questionnaire, administered before blood extraction (AU)
Subject(s)
Humans , Male , Female , Middle Aged , Aged , Aged, 80 and over , Aging , Health Surveys/statistics & numerical data , Health Status , Selection Bias , Refusal to Participate/statistics & numerical data , Cross-Sectional Studies , BiasABSTRACT
OBJECTIVES: To demonstrate that selection of a probabilistic sample at a national level for a study of aging in Spain is subject to selection bias. To quantify the losses produced after each phase of the administration of a questionnaire. METHODS: We performed a cross-sectional study of the Spanish community-dwelling population aged 50 years or older between 2010 and 2011. Through multivariate logistic regressions, the characteristics of the census tract of the patients' residence were compared between those who agreed (n = 5,813) or refused (n = 7,023) to be included in the sampling frame and between those who agreed (n = 1,677) or refused (n = 2,875) to participate in the study. The individual characteristics of persons who responded (n = 1,398) or refused to respond (n = 346) to a face-to-face questionnaire administered after a telephone interview were also compared. In addition, the reasons for refusal were studied. RESULTS: The most frequent specific reasons for refusing to be included in the sampling frame or to participate in the study were poor health and disability (14.4% and 27.9%, respectively). In both cases, refusal was more frequent in the census tracts of districts with a lower socioeconomic level or those located in Catalonia, Guipúzcoa or Biscay. Individuals older than 81 participated less frequently in the face-to-face questionnaire. Between 8.6% and 18.4% of participants were lost at each stage of information retrieval. CONCLUSION: Probabilistic sampling in sampling points chosen by the researchers would allow more resources to be devoted to increasing response rates among the groups who are less likely to participate. Questions should be concentrated in only one shorter questionnaire, administered before blood extraction.
