A neurodegenerative disorder that progresses toward complete incapacitation and death, Alzheimer's Disease (AD) affects 5.8 million people in the United States and 50 million worldwide, with incurred costs in 2021 of $355 billion in the U.S. (Alzheimer's Association, 2021). With no effective treatment to prevent or modify the course of the disease in sight, AD is an immense burden on our economy, patients, and caregivers (Alzheimer's Association, 2014, Alzheimer's Association, 2021; Brookmeyer et al., 1998; Sloane et al., 2002). The literature on AD and related dementia (ADRD) shows constant and adverse health disparities as well as research disparities across racial and ethnic groups (Chin et al., 2011; Faison et al., 2007; Raman et al., 2021). Like most complex diseases, the AD literature has a strong basis in European ancestry (Kunkle et al., 2019; Raman et al., 2021) and there are substantial disparities in minority participation in AD studies. Despite this fact, older racial/ethnic minority populations are growing faster than their non-Hispanic white counterparts and will comprise 42 % of the older adult population by 2050. The number of Asian Americans who are 65 years old and older will increase by 352 %, and comprise 21 % of the total Asian American population by 2060 (National Asian Pacific Center of Aging (NAPCA), 2013). Participation of Asian Americans in the ADRD interventional trials is very low (i.e., <1 %) (Faison et al., 2007; Raman et al., 2021).

Investigations of AD in Asian American populations are woefully inadequate. Achieving health equity, eliminating disparities, and improving the health of all groups is the primary goal of Healthy People 2020. The availability of reliable data is imperative to the attainment of this goal (U.S. Department of Health and Human Services, 2018). However, in the publication of Healthy People 2020, as in most other national health reports, dementia data about Asian Americans is absent. Ironically, these aspects of Asian American data may have led many in western science to conclude that health disparities among Asian Americans are not a serious problem because there are no data or evidence to prove otherwise. There is a need for developing sampling methods that are responsive to ethnic and sociocultural diversity among study population and to generalize scientific findings for Asian Americans (Lee et al., 2013).

The health-related data of Asian Americans are confounded by several factors (Barnes & Bennett, 2002; Pew Research Center, 2021a): rapid population growth due to the influx of immigrants, diversity within the existing Asian American subgroups, and methodological issues. However, these factors have not been carefully incorporated into research methodology, especially population-based studies, thereby either omitting data, or collapsing it into “other” categories resulting in misrepresenting the health status of Asian American groups. Thus, little or no accurate population-based data on Asian Americans exist to clearly identify their unique health problems related to AD and dementia. Lee and Baik (2011) have pointed out the perils of the application of Eurocentric textbook research methods in sampling coverage, selection, and nonresponse in studies related to Asian Americans. There are several factors related to the omission of Asian Americans including 1) a myth that Asian Americans are a model minority group; 2) the masking of aggregated data for all Asian Americans or the data is collapsed into the category of “Others”; 3) questions raised about the generalizability of findings because Asian Americans only comprise a small minority of the population and are not represented among the larger number of people overall; and 4) methodological barriers including the small number of Asian Americans in ethnic enclaves, language barriers, the low level of contact by Asian Americans with the healthcare system, and geographical dispersion (Grill et al., 2017; Lee et al., 2013; Rabinowitz & Gallagher-Thompson, 2010).

Older Asian Americans show certain characteristics that make them different from other ethnic groups, including language, health beliefs, health attitudes and social networks (Dong et al., 2010; HUGO Pan-Asian SNP Consortium et al., 2009; Lee et al., 2010; Lee, Fawcett, Kim and Yang, 2016, Lee, Fawcett, Yang and Hann, 2012, Lee, Lee, Kim, Hontz and Warner, 2007). These characteristics may act as either facilitators or barriers to participate in ADRC research. Thus, the Asian Cohort for Alzheimer's disease (ACAD) is designed to address these factors in the recruitment and engagement of hard-to-reach Asian ancestry older adult populations. To our knowledge, this is the first large AD genetic cohort for Asians in the U.S. and Canada to focus on Chinese, Korean, and Vietnamese ancestries. This article only reports on studying Korean Americans. Korean Americans are difficult to locate, and accurate, comprehensive lists of Korean Americans do not exist. >70 % of Korean Americans adults are immigrants, many of whom face the task of developing networks and social relations in their new environment with members of their ethnic group and with the mainstream population (Min, 2011; Pew Research Center, 2021b). Targeted-Korean American community studies have shown that good sample coverage can be achieved through well-planned recruitment in concentrated, targeted areas or in Korean American community locations where group members can be found (Hwang et al., 2021; Kim et al., 2015; Lee et al., 2007).

The purpose of this article is to report on our innovative strategies to enlarge the recruitment pool of Korean immigrant elderly populations and to share how we develop a Geographic Information System (GIS) to assess the geographic, socio-linguistic distribution of the study population who are known to be hard to reach. GIS has the ability to enhance the visual perception of data by mapping layers of data information and its relationship to the location of the population. The use of GIS techniques in public health studies has developed significantly in recent years (Disse et al., 2018; Ha, 2018; Ha & Wanyun, 2019; Sancar & Tabrizi, 2017; Solis-Paredes et al., 2017). Many public health researchers have found that visualization of spatial distribution of health-related events of target populations and construction of advanced health indicators are the two primary applications of GIS data/methods in health-related studies (Jia et al., 2017).