Nurse effects on measurement error in household biosocial surveys

Alexandru Cernat, Joseph Sakshaug

Research output: Contribution to journalArticlepeer-review



Biosocial survey data are in high demand, yet little is known about the measurement quality of health measures collected by nurses in respondents’ homes. Our objective was to analyze the degree to which nurses influence measurement in anthropometric and physical performance indicators collected from respondents in two nationally-representative UK biosocial surveys.

The English Longitudinal Survey of Ageing and the UK Household Longitudinal Study – Understanding Society were used to analyze fourteen anthropometric and physical performance measures covering weight, height, pulse, grip strength, and lung capacity. Cross-classified multilevel models were used to estimate “nurse effects” on measurement error.

Overall, there is a medium effect of nurses on measurement. Across all measures collected in both studies, nurses explain around 13% of all measurement variation. Variation in specific measures range between approximately 2 and 25%. Grip strength and lung capacity are more heavily influenced by nurses than are height, weight, and pulse. Lastly, nurse characteristics explain only a very small proportion of nurse measurement variation.

Objective health measures collected by nurses in household biosocial surveys are susceptible to non-trivial amounts of measurement variation. Nurse ID numbers should be regularly included in biosocial data releases to allow researchers to account for this unnecessary source of variation. Further, researchers are advised to conduct sensitivity analyses using control variables that account for nurse variation to confirm whether their substantive findings are influenced by nurse measurement effects.
Original languageEnglish
Article number40
Pages (from-to)20-45
JournalBMC Medical Research Methodology
Issue number45
Early online date27 Feb 2020
Publication statusE-pub ahead of print - 27 Feb 2020


  • Biosocial surveys
  • Measurement error
  • Nurse effects
  • Anthropometric measures


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