Abstract

ABSTRACT Collecting biological data in representative surveys is becoming more common due to their potential to inform research and policy. Nevertheless, using nurses to collect these data can lead to unintended effects. In this paper, we investigate how nurses influence the non-response process by looking at five waves of data coming from two surveys in the UK: Understanding Society and the English Longitudinal Study of Ageing. We find that nurses explain between 5 and 14% of the variance in non-response to biological data collection. We also find that older nurses are more successful in obtaining cooperation and consent to biological data collection and nurses with more survey experience are more likely to successfully collect blood samples. Finally, we show that including nurse characteristics in non-response weighting models leads to modest changes in population estimates of biological markers.

Highlights

  • There is increasing interest in combining social data with objective physical and biological mea­ surements in surveys (Sakshaug et al, 2015)

  • We investigate how nurses influence the nonresponse process by looking at five waves of data coming from two surveys in the UK: Understanding Society and the English Longitudinal Study of Ageing

  • Such measures are collected in several large-scale surveys, such as the U.S Health and Retirement Study (HRS), the Survey of Health, Ageing and Retirement in Europe (SHARE), and the English Longitudinal Study of Ageing (ELSA)

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Summary

Introduction

There is increasing interest in combining social data with objective physical and biological mea­ surements (hereafter referred to as ‘biomeasures’) in surveys (Sakshaug et al, 2015). Household surveys that collect self-report data commonly supplement these data with an array of biomeasures, ranging from anthropometric measures (e.g. height/weight, waist circumference) and physical performance assessments (e.g. walking speed, grip strength) to biological specimens (e.g. blood, saliva). Depending on the costs and goals of the study, medically trained personnel, such as nurses, or non-medically trained lay interviewers are used to collect biomeasures in household surveys. Both actors play a critical role in the three stages of biomeasure participation. Interviewer characteristics (e.g. demo­ graphics, experience) can influence respondents’ likelihood of biomeasure participation (Korbmacher, 2014; Sakshaug et al, 2015).

Background
Data and methods
Statistical methods
Results
Conclusions and discussion
Notes on contributors

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