Assessing the representativeness of population-sampled health surveys through linkage to administrative data on alcohol-related outcomes

Am J Epidemiol. 2014 Nov 1;180(9):941-8. doi: 10.1093/aje/kwu207. Epub 2014 Sep 16.


Health surveys are an important resource for monitoring population health, but selective nonresponse may impede valid inference. This study aimed to assess nonresponse bias in a population-sampled health survey in Scotland, with a focus on alcohol-related outcomes. Nonresponse bias was assessed by examining whether rates of alcohol-related harm (i.e., hospitalization or death) and all-cause mortality among respondents to the Scottish Health Surveys (from 1995 to 2010) were equivalent to those in the general population, and whether the extent of any bias varied according to sociodemographic attributes or over time. Data from consenting respondents (aged 20-64 years) to 6 Scottish Health Surveys were confidentially linked to death and hospitalization records and compared with general population counterparts. Directly age-standardized incidence rates of alcohol-related harm and all-cause mortality were lower among Scottish Health Survey respondents compared with the general population. For all years combined, the survey-to-population rate ratios were 0.69 (95% confidence interval: 0.61, 0.76) for the incidence of alcohol-related harm and 0.89 (95% confidence interval: 0.83, 0.96) for all-cause mortality. Bias was more pronounced among persons residing in more deprived areas; limited evidence was found for regional or temporal variation. This suggests that corresponding underestimation of population rates of alcohol consumption is likely to be socially patterned.

Keywords: Scotland; alcohol-related harm; bias; health surveys; nonresponse; record linkage.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Alcohol Drinking / adverse effects*
  • Alcohol Drinking / epidemiology
  • Alcohol Drinking / mortality
  • Bias*
  • Cross-Sectional Studies
  • Female
  • Health Surveys*
  • Humans
  • Male
  • Middle Aged
  • Models, Statistical*
  • Poisson Distribution
  • Risk Factors
  • Scotland / epidemiology
  • Socioeconomic Factors
  • State Medicine
  • Young Adult