Improving Alzheimer’s Disease and Related Dementias Population-Based Research Data Capacity for All through Nationally Representative Hybrid Sampling.

University Of Michigan At Ann Arbor, Ann Arbor MI

Investigators

Abstract

Two of the strategic research directions of the National Institute on Aging (NIA) are: 1) improving understanding of Alzheimer’s Disease and Related Dementias (ADRD) and 2) understanding heterogeneity of health conditions to improve the health of all older adult populations. Achieving these goals requires data across subpopulations, particularly groups associated with races, ethnicities and languages, the aging U.S. population is projected to be more heterogenous on these dimensions. Unfortunately, national aging research data are absent beyond (mostly White) Latinos, non-Latino Whites, and non-Latino Blacks who are fluent in English or Spanish. Collecting research data under the traditional sampling framework is resource intensive and prohibitively so for granular subpopulations. In response to NOT-AG-21-033 that addresses this gap, this study aims to improve ADRD research data infrastructure by introducing Hybrid Sampling (HybS) for building a nationally representative panel of middle-age and older adults where all subpopulations are represented with an oversample of seven granular subpopulations (Afro Latino, non-Afro Latino, Chinese, Asian Indians, Filipinos, Koreans and Vietnamese) through the push-to-Web method. As an extension of address-based sampling (ABS) and respondent driven sampling (RDS), HybS starts from a probability sample of seeds and exploits existing social networks for participant recruitment through chain-referrals, capturing those who, otherwise, are difficult to reach, while maintaining the probability sampling principles. To do so, we apply the push-to-Web method that also offers an option of participating over phone to lower the costs and the constraints associated with the time, geography and interview language. Currently underrepresented groups (e.g., racial, ethnic and linguistic minorities) are particularly well suited for the push-to-Web HybS, as they are known to form tight in-group social networks and to access the Web at a high level. For managing such a panel survey, we will also develop a sample management system and make it publicly available. Capitalizing on the connectedness of participants, this study will measure social networks from multiple angles and examine the role of various social networks on ADRD risks and heterogeneities within. This study will collect data using the same methods across a wide range of subpopulations, which will eliminate methodological confounders in examining heterogeneities. Although rare, there are scientifically rigorous and well-established population-based data about minorities and aging research data. We will triangulate data from these existing studies with data from the proposed study’s panel through multiple frame estimation in order to improve its representation properties. By developing a practical data collection framework and providing tools to implement studies under this framework, outcomes of this study will enable the research community to address the needs for ADRD data on granular subpopulations. Resulting comprehensive research data will inform policy makers to develop nuanced ADRD prevention and intervention strategies, which further leads to improving conditions across subpopulations among older adults, an important goal of the NIA.