NIMLAS Background

Longitudinal studies of the population near, through and after the retirement stage, such as the Health and Retirement Study (HRS), play an important role in aging research because they provide data from a life course perspective, allowing researchers to make population-level causal inference. Because such data collection is a social interaction between researchers and the population, the methods employed to collect data in these studies need to accommodate societal changes. The aging population in the U.S. is experiencing rapid changes. First, its racial, ethnic, and linguistic composition is being shifted by the growing Hispanic and Asian American populations. Second, the reliance of this aging population on new mobile and video technologies has been accelerated by the COVID-19 pandemic. At the same time, the research environment for population-based data collection has also evolved, with an increased availability of administrative records that can be integrated with survey data and the increased use of modern devices for collecting anthropometric and biomarker data that can complement traditional, self-report survey data. Researchers can capitalize on these naturally occurring trends and shape methodological innovations for future longitudinal studies. For example, as the population has become accustomed to communicating via electronic devices during the COVID-19 pandemic, population-based studies have transitioned from using one interview mode to mixing modes, including web-based data collection and virtual interviewing. Unfortunately, the methodological research on optimal data collection approaches for aging populations that has been performed to date has several critical shortcomings: there is a notable lack of data on minority subgroups, optimal approaches to obtaining consent for administrative record linkage and biomarker data collection are unknown, methods for combatting increasing rates of attrition are needed, and there is an absence of methodological research on the use of new technologies for data collection.

NIMLAS is a network of internationally-renowned methodological and substantive experts who are actively researching the benefits of new data collection methodologies in response to these societal developments. The network will meet regularly to shape methodological innovations specifically for the measurement of aging populations and design studies that will produce evidence-based best practices for this type of longitudinal measurement. There are a large number of influential longitudinal studies of aging in the field at present that would stand to benefit from this type of coordinated, rigorous methodological investigation of more efficient approaches to collecting longitudinal measures from (and for) aging populations. Via a coordinated international program of training, consulting, thematic working group meetings, and pilot research projects, NIMLAS aims to set the agenda for methodological research on longitudinal studies of aging and protect NIA investments in population-representative longitudinal studies.

NIMLAS is being supported by an R24 award from NIA (grant number 1R24AG077012).