The eleventh seminar in the CLOSER Longitudinal Methodology Series featured a talk from Meena Kumari. Meena Kumari is Professor of Biological and Social Epidemiology at ISER, University of Essex, and Honorary Professor in the Department of Epidemiology and Public Health, UCL. Meena investigated methodological considerations in the analysis of the biomarker data available in the CLOSER studies.
About the CLOSER Longitudinal Methodology Series
The aim of the series is to highlight methodological innovations and expertise and in turn facilitate and encourage future collaborations and new research.
Professor Meena Kumari
Methodological considerations in the analysis of the biomarker data available in CLOSER
Collection of biological data is routine and commonplace in medical research settings that include patients and volunteers. However, the methods used to collect these data in these settings may not be appropriate to the collection of biological or clinical data from population representative studies and alternative methods are used to collect these data. Biological samples have been collected from participants of the CLOSER studies using two modes of data collection; invitation of participants to a clinic and immediate processing of blood sample or visiting participants in their home and postage of the sample. However it is not clear how mode of collection impacts biomarker measurements in blood samples. Further it is not clear whether this difference in mode of collection impacts analyses of associations of the social environment with biomarker data. Harmonisation of biomarker data across the CLOSER studies requires an understanding of whether mode of collection impacts measurement properties.
Here we describe the comparison of a variety of biomarkers measured from samples collected in the home and in the clinic using data from Whitehall II participants that were invited to both settings. Further we will describe the influence of the home visit protocol on biomarker measurements. This talk with discuss whether failure to take these factors into account influences associations using an example of biosocial research with data from Understanding Society.