Analysis of non-response bias in a mailed health survey

J Clin Epidemiol. 1997 Oct;50(10):1123-8. doi: 10.1016/s0895-4356(97)00166-2.

Abstract

The objective of this study was to identify characteristics of non-respondents and late respondents to a mailed health survey. Persons who returned and those who did not return the questionnaire were compared using health insurance data, which indicated their age, sex, and health care expenditures in the previous year. Insurance and questionnaire data were used to compare early and late survey respondents and to compare categories of non-respondents. Questions covered use of health services, health status, and sociodemographic characteristics. Participants were members of health insurance plans in Geneva, Switzerland, 19-45 years old (n = 1822). Respondents (n = 1424) and non-respondents (n = 398) were of similar age and sex. The proportion of persons who had health care expenditures greater than zero Swiss francs (SFr) was higher among respondents (75%) than among non-respondents (69%, p = 0.03). Among non-respondents, expenditures of persons who explicitly refused to participate (2378 SFr) were higher than expenditures of persons who moved out of Geneva (1085 SFr) or who failed to return the questionnaire (1592 SFr, p = .02). Among respondents, being born in a Switzerland, having completed elementary school, having generated health care expenditures, and reporting good physical health were independent predictors of early response. In conclusion, low response rates to mailed health surveys may result in overestimating the utilization of health services. However, non-respondents did not constitute a homogeneous group, and the strength and even direction of non-response bias depended on the mechanisms of non-response.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Female
  • Health Expenditures / statistics & numerical data*
  • Health Services / statistics & numerical data
  • Health Services Research
  • Health Status
  • Health Surveys*
  • Humans
  • Income
  • Insurance, Health / statistics & numerical data
  • Male
  • Middle Aged
  • Postal Service
  • Selection Bias*
  • Sex Factors
  • Surveys and Questionnaires
  • Switzerland