Representativeness of the LifeLines Cohort Study

Abstract

BackgroundLifeLines is a large prospective population-based three generation cohort study in the north of the Netherlands. Different recruitment strategies were adopted: recruitment of an index population via general practitioners, subsequent inclusion of their family members, and online self-registration. Our aim was to investigate the representativeness of the adult study population at baseline and to evaluate differences in the study population according to recruitment strategy.MethodsDemographic characteristics of the LifeLines study population, recruited between 2006–2013, were compared with the total adult population in the north of the Netherlands as registered in the Dutch population register. Socioeconomic characteristics, lifestyle, chronic diseases, and general health were further compared with participants of the Permanent Survey of Living Conditions within the region (2005–2011, N = 6,093). Differences according to recruitment strategy were assessed.ResultsCompared with the population of the north of the Netherlands, LifeLines participants were more often female, middle aged, married, living in a semi-urban place and Dutch native. Adjusted for differences in demographic composition, in LifeLines a smaller proportion had a low educational attainment (5% versus 14%) or had ever smoked (54% versus 66%). Differences in the prevalence of various chronic diseases and low general health scores were mostly smaller than 3%. The age profiles of the three recruitment groups differed due to age related inclusion criteria of the recruitment groups. Other differences according to recruitment strategy were small.ConclusionsOur results suggest that, adjusted for differences in demographic composition, the LifeLines adult study population is broadly representative for the adult population of the north of the Netherlands. The recruitment strategy had a minor effect on the level of representativeness. These findings indicate that the risk of selection bias is low and that risk estimates in LifeLines can be generalized to the general population.

The Lifelines Cohort Study: a data source available for studying informal caregivers’ experiences and the outcomes of informal caregiving

“…In addition, the healthrelated quality of life of the 965 informal caregivers in Lifelines ICAS was generally good. This good health may be related to the overrepresentation of middle-aged individuals in the Lifelines Cohort Study, which in turn can be explained by the recruitment strategy used in the Lifelines Cohort Study (index population aged 25-49 years) [17]. After adjusting for demographic status, the characteristics of the adult Lifelines participants were broadly representative of the adult population in the north of the Netherlands [17].…”

“…The cohort profile of Lifelines has been described elsewhere [16,17]. Briefly, Lifelines employs a broad range of investigative procedures to assess the biomedical, socio-demographic, behavioural, physical and psychological factors that contribute to the health and disease of the general population, with a special focus on multimorbidity and complex genetics [15,16].…”

Genome-Wide Association Scan of Serum Urea in European Populations Identifies Two Novel Loci

“…Additionally, there was the option to self-register. The recruitment and data collection, as well as the representativeness of the data have been described in detail elsewhere [19,20]. Of the 165,729 participants, 15,368 presumably unrelated, oldest members of their respective families, were genotyped (details Genotyping, Quality Control, and Imputation A total of 15,368 individuals of the Lifelines Cohort Study were genotyped using the Illumina HumanCytoSNP-12 array and called using GenomeStudio (San Diego, CA, USA).…”

Missing heritability: is the gap closing? An analysis of 32 complex traits in the Lifelines Cohort Study

“…Lifelines not only provides an indepth characterization of the biomedical, socio-demographic, behavioral, physical and psychological factors that contribute to health and disease in the general population, it also employs a broad disease-and organ-overriding phenotypic characterization of its participants allowing it to validly address questions concerning the multi-morbidity that occurs with ageing, rather than focusing on single-disease conditions. Its representativeness for the population in the Northern Netherlands was recently shown 5 and the age-related multi-morbidity was documented. 6 Thus, Lifelines is particularly suited to investigate causes of morbidity across disease domains.…”