Factors influencing participation rate in a baseline survey of a genetic cohort in Japan

J Epidemiol. 2010;20(1):40-5. doi: 10.2188/jea.je20090062. Epub 2009 Nov 7.

Abstract

Background: Although many studies have examined factors that influence the response to postal questionnaires, few have addressed baseline recruitment for cohort studies involving genetic analyses. The aim of this study was to describe the method used for a baseline survey, the Japan Multi-institutional Collaborative Cohort Study (J-MICC Study), in Saga Prefecture, and to examine the factors that might influence the recruitment of participants in such studies.

Methods: The Saga J-MICC Study is an ongoing population-based prospective cohort study of the genetic and environmental interactions associated with lifestyle-related disease. From 2005 through 2007, a total of 61 447 residents between the ages of 40 and 69 were invited by mail to participate in this study. The survey date and time were arranged by telephone.

Results: Among that population, 31 002 (50.5%) responded and 12 078 (19.7%) agreed to participate. A completed questionnaire and blood pressure and anthropometric data were collected from all participants; blood, DNA specimens, and accelerometer measures were obtained from the great majority of them. Female sex and older age were associated with a higher participation rate. In addition, the convenience of the survey location and the sending of a reminder significantly improved the participation rate (odds ratio, 1.3).

Conclusions: Our findings suggest that making the survey location as convenient as possible and sending a reminder can both substantially improve participation rate in population-based studies.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Age Factors
  • Aged
  • Blood Specimen Collection
  • Data Collection / methods*
  • Female
  • Genetic Research
  • Humans
  • Japan
  • Male
  • Middle Aged
  • Patient Acceptance of Health Care / statistics & numerical data*
  • Patient Selection*
  • Prospective Studies
  • Reminder Systems
  • Sex Factors