Hostname: page-component-cd9895bd7-hc48f Total loading time: 0 Render date: 2024-12-27T14:18:57.367Z Has data issue: false hasContentIssue false

Identifying life course mechanisms and pathways that influence cognitive health among Asian and Latina/o/x older adults

Published online by Cambridge University Press:  13 September 2022

Lauren L. Brown*
Affiliation:
Department of Health Management and Policy, San Diego State University School of Public Health, San Diego, CA, USA
Catherine García*
Affiliation:
Department of Human Development and Family Science, Aging Studies Institute, Center for Aging and Policy Studies, Lerner Center for Public Health Promotion and Population Health, Syracuse University, Syracuse, NY, USA

Abstract

Type
Commentary
Copyright
© International Psychogeriatric Association 2022

Population aging and the increase of adults migrating at older ages have led to rapid growth in the foreign-born population aged 65 years and older (hereafter, older adults) in the USA (Mizoguchi et al., Reference Mizoguchi2019). In 2020, an estimated 14.3% of the older adult population were foreign-born. U.S. Census estimates show that the foreign-born population will increase to 20.5% by 2040 and 23.3% by 2060. These demographic changes are concerning since mounting evidence indicates that foreign-born adults are more likely to develop dementia than their U.S.-born counterparts and may spend more of their older adult years living with this condition (Garcia et al., Reference Garcia2019). Additionally, racial/ethnic minorities are projected to comprise 44.9% of U.S. older adults by 2060 and will include a large proportion of individuals affected by Alzheimer’s disease or related conditions (U.S. Census Bureau, 2018). These demographic changes underscore the challenges related to who will care for the growing number of older adults with dementia, given the relative decline of younger adults in the decades ahead (Aranda et al., Reference Aranda2021). Thus, the rapid increases in the diverse aging population suggest that there is an urgent need to understand the risks that immigration, nativity status, and racial stratification impose that influence late-life cognition, including the physiological and psychological mechanisms that play a critical role in health across the lifespan and generations.

In the 2022 Alzheimer’s Disease-Related Dementias (ADRD) Summit, one of the priority foci emphasized for health equity in ADRD included identifying life course and multi-level mechanisms and pathways that produce ADRD inequities (González and Zissimopoulos, Reference González and Zissimopoulos2022). Life course perspectives emphasize that health and health-related outcomes are shaped by biological, environmental, and social factors (whether independently, cumulatively, or interactively) across the life course and generations (Kuh et al., Reference Kuh2003). For example, previous studies of older immigrant health in the USA have emphasized the importance of biological and historical timing in the migration process that differentiate immigrant experiences, such as health selectivity at the time of migration and acculturation since arrival (Montes de Oca et al., Reference Montes de Oca2011). Supplementary to the life course perspective, multi-level approaches consider how place-based effects (e.g. local economic, service, social, natural, and policy environments) are fundamental causes of health and health disparities (Browning et al., Reference Browning, Cagney, Boetnner, Shanahan, Mortimer and Kirkpatrick Johnson2016). Indeed, racism and race-based residential segregation have shaped how material and flexible resources that matter for health has been historically and presently allocated to sustain and undergird racial/ethnic inequities in the USA (Williams and Collins, Reference Williams and Collins2001).

However, often overlooked in most research is that racial/ethnic minorities and immigrants in the USA are heterogeneous and diverse in terms of their sociodemographic characteristics, motivations to migrate (among foreign-born populations), and acculturation experiences that are nested within systemic and structural contexts (e.g. historical, environmental, and geographic contexts). These factors can potentially influence modifiable risk factors for dementia, including education, hypertension, hearing impairment, smoking, obesity, depression, physical inactivity, diabetes, and low social contact (Livingston et al., Reference Livingston2020).

The results presented by Meyer et al. (Reference Meyer2020) in International Psychogeriatrics are significant as they highlight how age at migration and generational status (e.g. second generation American - children of immigrants) are important structural and social determinants of older adult cognitive health in two large racial and ethnic minority populations in the USA – Asians and Latina/o/xs. Specifically, their findings suggest that age of migration and generational status among Asian and Latina/o/x older adults have differential domain-specific effects on cognitive function that get masked under the umbrella of global cognitive function. Their major finding is that foreign-born Asian and Latina/o/xs who migrated to the USA at older ages (aged ≥19 years) exhibited lower cognitive scores, particularly in semantic memory and executive function, relative to their U.S.-born counterparts, especially third generation Asians and Latina/o/xs, respectively. Meyer et al. highlight that semantic memory and executive function depend on accumulated knowledge, which is impacted by factors such as education. Accumulated knowledge is a form of an individual and/or group’s availability of flexible resources that can be used to maintain health (Phelan, et al., Reference Phelan, Link and Tehranifar2010). Another study published in International Psychogeriatrics underscores how more extended opportunities for individuals to engage in the learning process benefit cognitive reserve (Mohammad et al., Reference Mohammad2020). Mohammad et al.’s (Reference Mohammad2020) study demonstrates that respondents with “distributed education” exhibited higher scores in episodic memory and name recognition measures, suggesting that a respondent’s prolonged exposure to being involved in the learning process across the lifespan results in improved cognitive reserve. Thus, continuing education among foreign-born older adults in the USA may be an effective public health policy intervention to delay or slow cognitive decline, in addition to intervention strategies tailored based on education level and are culturally appropriate as highlighted recently by other researchers in International Psychogeriatrics (Radanovic, Reference Radanovic2020; Yuan et al., Reference Yuan2018). Taken together, researchers should consider potential life course and multi-level influences that influence cognitive health among foreign-born populations, including the cumulative exposures of having lived in their respective country of origin before arrival to the USA and their experiences once living in the USA. These considerations can generate additional hypotheses that link age at migration, generational status, and cognitive health that can be potentially tested.

While the Meyer et al. study expands on the determinants of cognitive health among two large racial/ethnic populations in the USA, we must consider the strengths and limitations of the population-based study they derive their findings. Meyer et al. used baseline data from the Kaiser Healthy Aging and Diverse Life Experiences (KHANDLE) Study, a life course cohort study of disparities in cognitive aging and ADRD in racially and ethnically diverse individuals aged 65 and over. The KHANDLE Study stands out from other dementia research studies in the USA by including a diverse sample and equal proportions of Asian, Black, Latina/o/x, and White individuals of varying educational backgrounds. This underscores KHANDLE as an important data contribution, given the continuous growth in the racial/ethnic diversity of the older adult population in the USA and the urgent public health burden of cognitive decline and ADRD. The findings from using the KHANDLE can provide vital information for research and clinical applications of cognitive tests, identifying individuals at higher risk for cognitive impairment and improving the health and well-being of individuals using culturally relevant and appropriate measures. However, given some of the limitations in KHANDLE’s sampling strategy, there is room for improvement in future data collection efforts to achieve data and health equity. Notably, the KHANDLE included participants with long-term access to integrated health care (i.e. usual care), which is not the norm for the general population, especially racial and ethnic minorities across the USA. Moreover, many populations disproportionately rely on acute illness care to meet basic and primary care needs, suggesting a missed opportunity for ADRD research recruitment efforts (Gilmore-Bykovskyi et al., Reference Gilmore-Bykovskyi2019). Another consideration is that the KHANDLE sample draws on individuals from urban areas in Northern California, which limits our understanding of diverse populations living in rural contexts (e.g. Native American/Alaskan Native populations), which are generally understudied in ADRD research. Nonetheless, Meyer et al. used the strengths of the KHANDLE to examine the factors related to cognitive health within Asian and Latina/o/xs, moving away from using White Americans as the “control group” (Whitfield and Baker-Thomas, Reference Whitfield and Baker-Thomas1999).

Prior health disparities research examining the important sociocultural factors contributing to cognitive health has tended to communicate the cognitive health of immigrant and racial/ethnic subgroups in the USA from a comparative framework. Factors like acculturation and language proficiency are often examined as predictors of cognitive health in immigrant subgroups – factors relevant for certain subgroups in the USA compared to the “gold standard” of health: White Americans. One of the most critical and trailblazing decisions Meyer et al. make is in choosing the inclusion criteria and comparison groups to examine the effect of immigration and immigrant status on late-life cognition. The Healthy Immigrant Effect, or the idea that those born outside of the USA are healthier and may have better health, despite having lower education, income, and wealth compared to their counterparts born in the USA, has been a popular idea in health disparities research that is not well understood in the context of cognitive outcomes. Meyer et al. point out that Asians and Latina/o/x groups are the largest growing immigrant groups in the USA that have very different patterns of migration that may impact cognitive health differently. Centering Asian and Latina/o/x immigrant groups in the USA allows the authors to test the hypothesis that the sociocultural differences in migration patterns contribute to the variation in cognitive function between Asian and Latina/o/x older adults – with no intention of centering or contrasting their cognitive health to that of their White American peers.

In the larger context, much of the literature on race/ethnic differences in cognitive function reads arguably similar: always surmising that cognitive function is lower and declines faster among minority subgroups in the USA despite the Mini-Mental State Exam (MMSE), a standard neuropsychological battery used to evaluate cognitive function (Folstein et al., Reference Folstein, Folstein and McHugh1975), is susceptible to bias when used to compare racially and ethnically diverse populations to Whites (Borson et al., Reference Borson2005). The racial/ethnic framing of U.S.-based health disparities research is especially pertinent for cognitive health outcomes since these outcomes are heavily linked to differences in age at migration, English proficiency, parental education, acculturation, discrimination, access to work, and other features of the sociopolitical climate; all of which tend to advantage European/White and English-speaking populations. Meyer et al.'s paper stands out in the health disparities and cognitive function literature by using the Spanish and English Neuropsychological Assessment Scales (SENAS), a battery of cognitive tests (verbal episodic memory, semantic memory, and executive functioning) that has been developed for comparisons of cognitive change across racial/ethnic and linguistically diverse groups (Mungas et al., Reference Mungas2004). Using the SENAS in this sample of Asian and Latina/o/x older adults, the authors find the impact of immigration differs in magnitude across cognitive domains and depends on the migration experience. The Healthy Immigrant Effect, or the idea that the longer one stays in the USA, the worse their health, is too polarizing of a concept to fully represent the disparities in cognitive health among the generations of Asian and Latina/o/x immigrants in the USA. The truth lies in the particularities of the immigration experience and the measure(s) of health used to represent cognitive function.

Overall, Meyer et al.’s study underscores the complementary and interdisciplinary approaches needed to fully understand the differences (and heterogeneity) present within the Asian and Latina/o/x older adult populations in the USA. As Whitfield and Baker-Thomas (Reference Whitfield and Baker-Thomas1999, p.77) point out, research on these within-group differences is important because (1) it allows the study of minority groups without anchoring their performance to another group (i.e., White Americans) and (2) understanding within-group variability allows for more effective policies to be implemented among minority groups. In our attempts to achieve health equity, underrepresented and minority groups must be centered on research and data-collection efforts to understand how structural, social, and environmental influences aging and cognitive health and how those patterns vary across culture and time.

Conflict of interest

None.

Description of authors’ roles

The authors, Lauren L. Brown and Catherine García, equally contributed to the manuscript, revised, read, and approved the submitted version.

References

Aranda, M. P. et al. (2021). Impact of dementia: health disparities, population trends, care interventions, and economic costs. Journal of the American Geriatrics Society, 69, 17741783. DOI 10.1111/jgs.17345.CrossRefGoogle ScholarPubMed
Borson, S. et al. (2005). Simplifying detection of cognitive impairment: comparison of the mini-cog and mini-mental state examination in a multiethnic sample: MINI-COG AND MMSE. Journal of the American Geriatrics Society, 53, 871874. DOI 10.1111/j.1532-5415.2005.53269.x.CrossRefGoogle Scholar
Browning, C. R., Cagney, K. A. and Boetnner, B. (2016). Neighborhood, place, and the life course. In: Shanahan, M. J., Mortimer, J. T. and Kirkpatrick Johnson, M. (Eds.), Handbook of the Life Course: Volume II (pp. 597620). New York: Springer.CrossRefGoogle Scholar
Folstein, M. F., Folstein, S. E. and McHugh, P. R. (1975). Mini-mental state. Journal of Psychiatric Research, 12, 189198. DOI 10.1016/0022-3956(75)90026-6.CrossRefGoogle ScholarPubMed
Garcia, M. A. et al. (2019). Racial/ethnic and nativity differences in cognitive life expectancies among older adults in the United States. The Gerontologist, 59, 281289. DOI 10.1093/geront/gnx142.CrossRefGoogle ScholarPubMed
Gilmore-Bykovskyi, A. L. et al. (2019). Recruitment and retention of underrepresented populations in Alzheimer’s disease research: a systematic review. Alzheimer’s & Dementia: Translational Research & Clinical Interventions, 5, 751770. DOI 10.1016/j.trci.2019.09.018.Google ScholarPubMed
González, H. and Zissimopoulos, J. (2022). Health equity in AD/ADRD. In: Alzheimer’s Disease-Related Dementias Summit 2022, 22 March. Available at: https://videocast.nih.gov/watch=45149 Google Scholar
Kuh, D. et al. (2003). Life course epidemiology. Journal of Epidemiology & Community Health, 57, 778783. DOI 10.1136/jech.57.10.778.CrossRefGoogle ScholarPubMed
Livingston, G. et al. (2020). Dementia prevention, intervention, and care: 2020 report of the lancet commission. The Lancet, 396, 413446. DOI 10.1016/S0140-6736(20)30367-6.CrossRefGoogle ScholarPubMed
Meyer, O. L. et al. (2020). Generation and age of immigration on later life cognitive performance in KHANDLE. International Psychogeriatrics, 112. DOI 10.1017/S1041610220003774.Google ScholarPubMed
Mizoguchi, N. et al. (2019). The Older Foreign-Born Population in the United States: 2012–2016. Washington, DC: U.S. Census Bureau. Available at: https://www.census.gov/content/dam/Census/library/publications/2019/acs/acs-42.pdf Google Scholar
Mohammad, N. et al. (2020). The effects of different proxies of cognitive reserve on episodic memory performance: aging study in Iran. International Psychogeriatrics, 32, 2534. DOI 10.1017/S1041610219001613.CrossRefGoogle ScholarPubMed
Montes de Oca, V. et al. (2011). The linkage of life course, migration, health, and aging: health in adults and elderly mexican migrants. Journal of Aging and Health, 23, 11161140. DOI 10.1177/0898264311422099.CrossRefGoogle Scholar
Mungas, D. et al. (2004). Spanish and English Neuropsychological Assessment Scales (SENAS): further development and psychometric characteristics. Psychological Assessment, 16, 347359. DOI 10.1037/1040-3590.16.4.347.CrossRefGoogle ScholarPubMed
Phelan, J. C., Link, B. G. and Tehranifar, P. (2010). Social conditions as fundamental causes of health inequalities: theory, evidence, and policy implications. Journal of Health and Social Behavior, 51, S28S40. DOI 10.1177/0022146510383498.CrossRefGoogle ScholarPubMed
Radanovic, M. (2020). Cognitive reserve: an evolving concept. International Psychogeriatrics, 32, 79. DOI 10.1017/S1041610219001947.CrossRefGoogle ScholarPubMed
U.S. Census Bureau (2018). Projected Race and Hispanic Origin: Projections for the United States, 2017–2060. Washington, DC: U.S. Census Bureau. Available at: https://www.census.gov/data/tables/2017/demo/popproj/2017-summary-tables.html; last accessed 26 June 2019.Google Scholar
Whitfield, K. E. and Baker-Thomas, T. (1999). Individual differences in aging minorities. The International Journal of Aging and Human Development, 48, 7379. DOI 10.2190/YGAQ-0D95-M0V4-820M.CrossRefGoogle ScholarPubMed
Williams, D. R. and Collins, C. (2001). Racial residential segregation: a fundamental cause of racial disparities in health. Public Health Reports, 116, 404416. DOI 10.1016/S0033-3549(04)50068-7.CrossRefGoogle ScholarPubMed
Yuan, M. et al. (2018). Associations between modifiable lifestyle factors and multidimensional cognitive health among community-dwelling old adults: stratified by educational level. International Psychogeriatrics, 30, 14651476. DOI 10.1017/S1041610217003076.CrossRefGoogle ScholarPubMed