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Cultural resources and health among Asian Americans: results from the National Latino and Asian American Study

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Cultural resources and health among Asian Americans: results from the National Latino and Asian American Study

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Content CULTURAL RESOURCES AND HEALTH AMONG ASIAN AMERICANS:
RESULTS FROM THE NATIONAL LATINO AND ASIAN AMERICAN STUDY
by
Diana Ray Letourneau
A Dissertation Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(SOCIAL WORK)
March 2014
Copyright 2014 Diana Ray Letourneau
Dedication
This dissertation is dedicated to my family, new and old. They have provided me support,
encouragement, and grounding through the many rough points that arose during this journey. They
helped me keep my eyes on the prize and continue my trek. They have inspired me through their own
hard work, compassion, and steadfast ability to make their own goals come to fruition. My husband,
Brian, whom I met when the prospect of a PhD program was just a twinkle in my eye, has had
inexplicably unwavering confidence in me, which sustained me through many moments of doubt and
frustration. And, of course, my mom, without whose steady encouragement I probably wouldn't have
made it through my 5
th
grade heritage report, let alone a dissertation. Mom, I think you can finally be
relieved of your duty of quelling my anxiety about grades. Words can't express my appreciation for
your unshakable belief in me and my work.
I also would like to dedicate this dissertation to my community of doctoral students, who have
shared the many ups and downs that go along with the freedoms and challenges of PhD program life.
My close friends in the cohorts ahead of mine shed a guiding light through the labyrinthine tunnels of
higher learning, with vital insights provided like a trail of breadcrumbs, exactly when I needed them. I
also greatly value the relationships I've developed with members of cohorts arriving after mine, which
have helped me keep a fresh perspective. And of course, I cannot overlook the deep connections I have
built with the folks of my own cohort, who provided a sense of camaraderie without which I really
cannot imagine finishing this program! You five have helped me recognize that all the small steps
we've taken together – although sometimes feeling like we were standing in place – really can add up
to something great.
Lastly, I would like to dedicate this study to those I sincerely hope it might benefit. So many
ii
people are still standing on the fringes of society, with needs unrecognized and strengths unsupported.
Through this work and throughout my career, I hope to do my small part to help facilitate voices being
heard, communities advancing their causes, and opportunities for well-being and success to be
increasingly shared by all.
iii
Acknowledgments
I would like to thank the many people and entities that supported this effort.
First, I give my deepest appreciation to my mentor and committee chair, Dr. Karen Lincoln,
who has seen me through years of growth, learning, and development in just about every aspect of my
life. Her scholarly guidance has been indispensable, as I formulated (and re-formulated) conceptual
models, grappled with new analytic approaches, and struggled to make sense of the occasional
seemingly incomprehensible result. She was always just an email away, easing my doubts and
confusion with her discerning insights. Dr. Lincoln has also helped me give life to my burgeoning
career aspirations and my lifelong goals. She has truly led by example, and coached me in the art of
overcoming setbacks and re-interpreting situations that feel like failures into lessons and opportunities.
She has acted as my advocate, helped me make the most of professional development opportunities,
and made sure I stayed on track. I really cannot thank you enough, Dr. Lincoln, for all your support and
wisdom, which have culminated in the completion of this dissertation and will stick with me forever. I
feel incredibly fortunate to have had you as a mentor.
To my internal committee member, Dr. William Vega, I would like to express sincere gratitude
for the many astute insights, questions, and contributions you made as I developed my ideas from
tutorial papers, to a qualifying exam, and finally, this dissertation project. Your deep familiarity with
the concepts that went into my work helped me distill my abstract ideas into feasible, understandable
(and hopefully publishable) products. It has been truly inspiring to work with someone who has had
such a tremendous research career dedicated to reducing health disparities. Thank you, Dr. Vega.
To my external committee member, Dr. Cleopatra Abdou Kamperveen, I am deeply grateful for
the kind support and insightful suggestions provided during our work together, both within and outside
of my dissertation meetings. Your eye-opening manuscripts on the value of cultural resources among
populations for whom poor health was expected sparked my interest in applying similar concepts to
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another population with surprising health outcomes (Asian Americans). And your affirmational words
of wisdom are always so reassuring, I do believe you are an honorary social worker. Thank you for
joining and being such a strong team player on my committee, Cleopatra.
I would also like to recognize the other faculty members I had the opportunity to work with
during the course of my doctoral studies. Dr. Kristin Ferguson, thank you for instilling in me a strong
sense of the value of research in social work intervention, and the importance of keeping the
communities we study close to our hearts. To Dr. Eric Rice, I so appreciate the way you welcomed me
to your research team, encouraged my (sometimes atypical) scholarly interests and aspirations, and put
in a kind word on my behalf when it was needed. Dr. Bruce Jansson, your enlightening policy textbook
captivated me as an MSW student, and I am still amazed and humbled that I had the opportunity to take
your doctoral seminar and collaborate with you on a subsequent text; thank you for that wonderful
opportunity, and good luck opening the minds of social workers for years to come.
I would also like to acknowledge the team of researchers who conceived of, implemented, and
published the National Latino and Asian American Study, on which this dissertation is based. I have
especially deep gratitude for the groundbreaking efforts of Dr. David Takeuchi and Dr. Margarita
Alegría, the principal investigators of the project.
Lastly, I wish to thank the institutions that provided funding to support this dissertation. My
sincere appreciation goes to the USC Graduate School for awarding me the Provost's Fellowship and
Oakley Endowed Fellowship, which allowed me to dedicate full-time attention to my research. I also
thank the Roybal Institute on Aging for providing a summer research award that helped to support this
project. Finally, I thank the School of Social Work PhD Program for its ongoing support, both
administrative and financial.
v
Table of Contents
Dedication ii
Acknowledgments iv
List of Tables viii
List of Figures ix
Abstract x
Chapter One: Introduction and Overview of the Three Studies 1
Rationale and Theoretical Background 4
Structure of the Dissertation 15
References 18
Chapter Two (Study 1): Testing the Cultural Resource Hypothesis among Asian Americans
Introduction 27
Methods 35
Results 38
Discussion 41
References 58
Chapter Three (Study 2): The Impacts of Duration of Residence in the U.S. on Asian American Health:
Do Cultural Resources Mediate Health Decline?
Introduction 67
Methods 69
Results 72
Discussion 74
References 85
Chapter Four (Study 3): A Latent Class Analysis of Asian Americans, Health and Ethnic Identity
Introduction 94
Methods 97
Results 100
Discussion 103
References 116
vi
Chapter Five: Conclusions and Future Directions 122
Major Findings 123
Limitations 126
Implications for Theory 128
Implications for Policy and Practice 130
Implications for Research 133
Conclusions 135
References 137
vii
List of Tables
Table 2.1. Descriptive Characteristics of Asian Americans in the National Latino and Asian
American Study 52

Table 2.2. Correlations between Predictor and Outcome Variables 53
Table 2.3. Regression Analyses Predicting Self-Rated Mental Health 54
Table 2.4. Logistic Regression Analyses Predicting Mental Health Disorder 55
Table 2.5. Regression Analyses Predicting Self-Rated Physical Health 56
Table 2.6. Logistic Regression Analyses Predicting Physical Health Problem 57
Table 3.1. Descriptive Characteristics of Asian Americans in the National Latino and Asian
American Study 80
Table 3.2 Logistic Regression Analyses Predicting Mental Health Disorder (Interaction) 81
Table 3.3. Logistic Regression Analyses Predicting Physical Health Problem (Interaction) 82
Table 4.1. Fit Statistic Comparisons of Latent Class Analysis Models based on Health and
Sociodemographic Characteristics 112
Table 4.2. Four-class Latent Class Analysis Model of Conditional Probabilities, by Class 113
Table 4.3. Odds Ratio Results of Latent Class Logistic Regression Model 114
viii

List of Figures
Figure 3.1. Mental Health Disorder Predicted by the Interaction of Ethnic Identity and
Duration of Residence in the U.S. among Asian Americans 83
Figure 3.2. Physical Health Problem Predicted by the Interaction of Native Language Proficiency and
Duration of Residence in the U.S. among Asian Americans 83
Figure 3.3. Physical Health Problem Predicted by the Interaction of Ethnic Identity and Duration
of Residence in the U.S. among Vietnamese Americans 84
Figure 4.1. Class Composition 115
Figure 4.2. Ethnic Group Composition, by Class 115
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CULTURAL RESOURCES AND HEALTH Ray-Letourneau
Abstract
The primary aim of this study is to improve our understanding of Asian American health. In
spite of numerous research studies indicating a high degree of variability in the health status of Asian
Americans, overgeneralizations and stereotypes such as the “model minority myth” continue to obscure
diversity and give the impression that Asian Americans as a whole are successful and healthy.
However, some ethnic and sociodemographic sub-groups of Asian Americans are indeed at higher risk
of health problems than others. Thus, it is important to better understand the risk and protective factors
that contribute to health among this large and growing segment of the U.S. population.
The “immigrant paradox” is often used to explain heterogeneity in health outcomes among
Asian Americans. This perspective posits that new immigrants have superior health status compared to
those with longer-term residence or those who are U.S.-born. However, over time this health advantage
tends to deteriorate, such that the health status of long-term immigrants and subsequent generations
tends to converge to that of their U.S.-born counterparts. It is unclear whether there exist any mediators
of the relationship between time in the U.S. and health status. This dissertation study aims to fill this
gap in the literature by exploring whether cultural resources benefit the health of Asian Americans and
tests whether maintenance of these resources are protective against the deleterious effects of long-term
residence of immigrants in the U.S.. The overarching goal of this study is to explore heterogeneity
among Asian Americans while also improving our understanding of the impact of cultural resources on
health.
Using data from the National Latino and Asian American Survey (NLAAS), the first nationally
representative sample of Asian Americans, and the cultural resource hypothesis as a conceptual
framework, this dissertation examines the effects of three cultural resources – ethnic identity, native
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CULTURAL RESOURCES AND HEALTH Ray-Letourneau
language proficiency, and religious service attendance – on mental and physical health outcomes.
Particular attention is paid to the possible moderating effects of cultural resources on duration of
residency, as Asian Americans who reside in the U.S. for longer duration have an increased risk of
health problems. The cultural resource hypothesis has been employed in the past to explain health
outcomes among other disadvantaged groups, but has never before been applied to Asian Americans.
The dissertation is presented in a multiple manuscript format, with three chapters comprising
three distinct but related empirical studies. Study 1 (Chapter 2) explores the impact of ethnic identity,
native language proficiency, and religious service attendance on mental and physical health, stratified
by ethnic group (Chinese, Filipino, Vietnamese). Findings from Study 1 indicate that native language
proficiency and ethnic identity are associated with better health for at least one ethnic group, providing
initial support for the cultural resource hypothesis among Asian Americans. Study 2 (Chapter 3)
examines the moderating role of cultural resources in the relationship between longer duration of
residence and mental and physical health. Results reveal that ethnic identity and native language
proficiency moderate the effects of length of residency in the U.S. on mental and physical health,
respectively, with the stronger protective effects found among Asian Americans who have lived in the
U.S. for longer periods of time. Study 3 (Chapter 4) uses latent class analysis to empirically identify
risk profiles of health among Asian Americans. Four classes or profiles of health were identified,
revealing four sociodemographically distinct risk profiles. Additional analyses indicated that ethnic
identity predicts class membership, differentiating those with a “good health” profile from those with
an “excellent health” profile.
In sum, findings from this dissertation illustrate the potential of cultural resources as protective
factors for health and extend the cultural resource hypothesis to include Asian Americans. Instead of
accepting health declines among immigrant populations over time as inevitable, it is important to
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CULTURAL RESOURCES AND HEALTH Ray-Letourneau
consider heterogeneity among Asian Americans, and understand that longer duration of residence in the
U.S. does not always result in poor health outcomes. Social workers and other helping professionals
can work to create policies and programs that facilitate maintenance of cultural resources as part of a
larger effort to improve health among Asian Americans. In this way, health disparities found among
certain Asian American sub-groups can be minimized and long-term health and well-being can be
improved among this large and growing population.
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CULTURAL RESOURCES AND HEALTH Ray-Letourneau
Chapter One:
Introduction and Overview of the Three Studies
Nearly 16 million Asian Americans reside in the U.S., comprising 5.1% of the U.S. population
(U.S. Census Bureau, 2012). However, these figures are continuing to climb steadily, with the number
of Asian Americans projected to double by 2060 when Asian Americans will account for over eight
percent of the nation's population (U.S. Census Bureau, 2012). While some subpopulations of Asian
Americans seem to have a health advantage over the average U.S. resident, a high degree of
heterogeneity exists among Asian Americans such that certain groups (i.e., Southeast Asians and
refugees) have higher-than-average rates of some health conditions. Adding to this complexity (i.e.,
variations in health status among Asians), individuals' country of origin and amount of time spent
residing in the U.S. both tend to affect health outcomes in nuanced ways.
Most Asian Americans either moved to the U.S. from abroad or had parents or grandparents
who did. Empirical research on immigrant populations has uncovered an “epidemiological paradox”
phenomenon, which states that although immigrants often arrive in the U.S. with better mental and
physical health status than their U.S.-born counterparts, over time, the protective effects of foreign-
born status diminish, resulting in an overall increase in physical and mental health problems with
longer duration in the U.S. (Frisbie, 2001; Zhang, 2009). However, some individuals defy this overall
trend; there exists a great deal of heterogeneity in the health status of Asian Americans, but much less is
known about contributors to health among this group in comparison to other racial groups (Takeuchi,
Zane, Hong, et al., 2007). Because Asian Americans comprise a large and growing segment of the U.S.
population, it is increasingly important to understand the sociodemographic correlates of health and the
protective factors that might improve health in order to better meet the health and social service needs
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of this diverse group.
Empirical studies of Asian American health offer equivocal and often contradictory findings
with regards to differences in risk, prevalence, and persistence of health problems, depending on the
analytical methods employed, the health outcome chosen, the covariates accounted for in the models,
and the subgroup of Asian Americans under study (Leu, 2011; Takeuchi, 2007; Yip, 2008). But with the
recent advent of large-scale studies that produce nationally representative data, the risk and protective
factors that contribute to Asian American health can be examined with increasing specificity, so that
inconsistent results reported in the past can now be explained.
As part of an effort to explain divergent health outcomes of Asian Americans over time in the
U.S., this dissertation study will draw from the cultural resource hypothesis proposed by Abdou and
colleagues (i.e., 2010, 2012), which posits that nonmaterial resources derived from culture can buffer
the negative health effects of stressors related to ethnic minority status (Abdou et al., 2010). While this
body of work has indicated the beneficial nature of cultural resources for a number of health outcomes
among low-income and ethnic minority populations, the subjects of the studies came mostly from
European American, African American, and Latino backgrounds. Therefore, the results are not
generalizable to Asian Americans, and the current study seeks to fill this gap in the literature.
Prior research findings indicate that certain aspects of Asian culture are beneficial to health
(Juang, 2009; Kitayama, 2010; Miyamoto, 2011; Triandis, 1988), but systematic investigations of
cultural contributors to Asian American health guided by a priori reasoning are still critically needed
(Takeuchi, Gong, & Gee, 2012). This dissertation study will help to elucidate the mechanisms by which
sociodemographic position influences health, employing a promising theory – the cultural resource
hypothesis – to explain health outcomes among Asian Americans. The cultural resources included in
this study are ethnic identity, religious participation, and native language proficiency, as these reflect
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both internal and external domains of culture (Chia & Costigan, 2006). Since “certain aspects of culture
might be less vulnerable to erosion than others” (Sue, Mak, & Sue, 1998), the current study will also
investigate the interaction of each cultural resource with duration of time lived in the U.S. with respect
to health outcomes.
The specific research questions addressed by the three studies described in this dissertation are listed
below, along with the statistical method utilized to address the question:
1. How do internal and external cultural resources contribute to physical and mental health among
Asian American adults, accounting for relevant sociodemographic attributes? (First-order
multiple linear and logistic regression analyses)
2. To what extent do cultural resources moderate the relationship between duration of time in the
U.S. and health? (Second-order logistic regression analyses)
3. Can risk profiles of health be empirically identified among a heterogeneous sample of Asian
Americans? If so, what is the composition of these profiles in terms of sociodemographic
makeup? (Latent class analysis)
3b. Is an individual's level of ethnic identity associated with their class
membership? (Multiple regression analysis)
The overall aim addressed by these research questions is to improve our understanding of the
relationships among sociodemographic factors, cultural resources and physical and mental health status
among Asian Americans, a large but under-studied population.
Extant literature contains a number of conceptual, theoretical, and methodological limitations
that the current study seeks to address. First, by distinguishing between internal and external domains
of culture (further described below), this research will provide conceptual clarity regarding the specific
mechanisms by which culture affects health. Second, application of the cultural resource hypothesis
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CULTURAL RESOURCES AND HEALTH Ray-Letourneau
brings a theoretical framework to the study of Asian American health, which has heretofore been
lacking in a priori reasoning. Third, by relying solely on “variable-oriented” frameworks, empirical
studies of Asian American health are limited in the extent to which they reflect the full heterogeneity
found among Asian Americans in the U.S. Employing a “person-oriented” framework (Bergman &
Magnusson, 1997) through the latent class analysis to be conducted in Study 3, this dissertation will
address this gap by providing detailed profiles of Asian Americans, including their health status.
Finally, while most studies examine contributors to either mental health or physical health, the present
study includes both types of health outcomes, in order to examine whether the associations found
among sociodemographics, cultural resources and health vary by type of health outcome under study.
Therefore, the current dissertation study contributes to the development of a conceptual
foundation by empirically testing several models that potentially explain the relationships among
sociodemographics, cultural resources, and physical and mental health among Asian Americans. The
ultimate goal of this work is to present findings that will be useful for developing more responsive and
culturally appropriate health and social service delivery systems that can improve services among this
large and growing segment of the U.S. population.
Rationale and Theoretical Background
The Changing Health Service Landscape in the U.S.
National health expenditures, which were about $2.6 trillion in 2010, are projected to rise to
about $4.6 trillion in 2020 (Centers for Medicare and Medicaid Services, 2011). As the nation
undergoes changes in national health insurance coverage policies which are projected to bring coverage
to an additional 30 million people by 2022 (CBO, 2012), there is increasing pressure on health care
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CULTURAL RESOURCES AND HEALTH Ray-Letourneau
institutions to provide high-quality, low-cost, and culturally appropriate health services to an
increasingly diverse patient population. The United States is projected to become a “majority-minority”
nation by 2043 (U.S. Census Bureau, 2012). Already, at least four states and a host of cities have
become pluralities, with no single racial group comprising over fifty percent of the population (Frey,
2009). In order to respond to the shifting health and social service needs represented by demographic
change, increased attention must be paid to the causes of and contributors to physical and mental health
problems among racial and ethnic minority populations.
Ethnic minority status has long been considered a risk factor for poor health outcomes in the
United States (Abdou, 2010; Chen, 2006; Flores, 1999, 2008; Read, 2005; Uehara, 1994; Williams,
1999). A mounting stockpile of evidence has demonstrated that certain ethnic minority groups
experience systematic disparities in health on a number of fronts, most notably life expectancy, infant
mortality, cancer, asthma, diabetes, and certain mental health disorders (Canino, 2009; Chow, 2003;
Ward, 2004; National Center for Health Statistics, 2008). Health disparities are defined as preventable
differences in the burden of disease that are experienced by socially disadvantaged populations (CDC,
2008). Even when prevalence rates for some racial and ethnic groups are similar to that of non-
Hispanic Whites, the severity, persistence, and amount of disability associated with the disease or
condition are often worse for racial and ethnic minority individuals than for Whites (Breslau, 2005;
Williams, 2007). Furthermore, minority individuals often experience multiple disparities in access to
care, including barriers such as lack of transportation, health insurance coverage, and access to
receptive, culturally and linguistically compatible service providers (Alegría, 2008; Chow, 2003;
Flores, 2008). Health care utilization rates of minority populations are therefore often lower than those
of Whites (Chow, 2003; Flores, 2008). Accordingly, public health workers, researchers, advocates, and
officials have undertaken efforts to reduce such health status, access, and treatment disparities, even
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including the elimination of health disparities as one of the overarching goals of Healthy People 2020
(U.S. Department of Health and Human Services, 2010).
Asian Americans and Health
Asian Americans account for 5.1% of the total U.S. population, or 15.9 million individuals
(U.S. Census Bureau, 2012). This group experienced a 43% growth rate between the 2000 and 2010
Censuses, which was more than any other major race group (Hoeffel, Rastogi, Kim, & Shahid, 2012).
The Asian American population is projected to double over the next fifty years, amounting to 34.4
million people and comprising 8.2% of the U.S. population by 2060 (U.S. Census Bureau, 2012).
Despite the group's size, much remains unknown about Asian Americans in comparison to other racial
and ethnic groups (Takeuchi, Gong, & Gee, 2012). Lack of scientific literature, misinformation, and
stereotypes about Asian Americans persist to this day, obfuscating the true diversity of experiences and
resulting in Asian Americans being identified as the racial group with whom the most Americans feel
the least in common (Gee, Ro, Shariff-Marco, & Chae, 2009; GSS, 2000).
Having insufficient scientific data about a population group as substantial as Asian Americans is
particularly troubling with regards to their health. Until very recently, there was a dearth of
methodologically rigorous, generalizable data regarding the health and health care of Asian Americans
(Takeuchi, 2007; Kim, 2010). Studies typically included smaller, geographically defined samples or
only specific ethnic groups, and thus were not generalizable to the national Asian American population.
These early studies often resulted in inconclusive, mixed, and contradictory findings. However, the
advent of the first national epidemiological survey of Asian Americans – the National Latino and Asian
American Study (NLAAS) – has allowed for the conduct of methodologically sound empirical
research. This research has already made impressive contributions to the literature on ethnic minority
health and has helped to dispel many myths and stereotypes that had permeated the discourse around
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Asian Americans. For example, contrary to the “model-minority” myth (Gee, Ro, Shariff-Marco, &
Chae, 2009) purporting that Asian Americans have overcome the barriers of minority status and have
attained superior educational, occupational, financial, and health outcomes compared to other racial
groups, recent research shows that some subgroups of Asian Americans are actually at higher risk of
certain health issues than their White counterparts. For instance, Asian/Pacific Islander men have lower
five-year cancer survival rates than non-Hispanic Whites (Ward et al., 2010). Asian American children
are more likely to have poor/fair health than are White children (Chen, Martin, & Matthews, 2006).
Finally, prevalence rates for lifetime- and 12-month mental disorder are lower among Whites, African
Americans and Latinos (Breslau, Kendler, Su, Gaxiola-Aguilar, & Kessler, 2005) than among Asian
Americans (Takeuchi, Zane, Hong, et al., 2007).
The great diversity among Asian Americans results in specific ethnic groups having
differentiated health risk profiles (Kim, 2010; Kim, 2012). Those originating from Southeast Asia, for
example, have high levels of depression, Post-Traumatic Stress Disorder, Hepatitis B, Tuberculosis,
and liver, lung, and cervical cancer compared to other Asian ethnic groups (Chu, 2011; McCracken,
2007; Takada, 1998). Some have attributed Southeast Asians' increased prevalence rates to the higher
proportion of refugees and individuals who experienced “repeated exposure to catastrophic
environmental stressors” including torture, combat, witnessing the death of loved ones, and harsh
refugee camp conditions (Chu & Sue, 2011, p. 4; see also Kinzie, 1990; Takada, 1998; Westermeyer,
1988). Others have teased out the heterogeneity in health outcomes among Asian Americans by
differentiating between “structural factors,” such as ethnicity, generational status, and socioeconomic
status, and “intermediary factors” including lack of insurance, discrimination, and limited English-
language proficiency, that pose risk factors for Asian American health (Kim, Chen, & Spencer, 2012).
Asian Americans also experience problems with access to and utilization of health services at
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higher rates than other ethnic groups (Abe-Kim, 2007; Flores, 2008; Huang, 2011; Kim & Keefe, 2010;
Takada, 1998). Asian/Pacific Islander children tend to have fewer physician visits and more problems
obtaining specialty health care when they need it than White children (Flores & Tomany-Korman,
2008). Asian American patients rate their health plan coverage and medical care satisfaction lower than
all other racial and ethnic groups in the U.S. (Haviland, Morales, Reise, & Hays, 2003). Finally, Asian
Americans are less likely than Whites to report positive interactions with their regular doctors (Ngo-
Metzger, Legedza, & Phillips, 2004).
Asian Americans and Mental Health. While the above section discussed issues that pertain to
overall health status, including both physical and mental dimensions of health, some additional points
related solely to the psychological, emotional, and mental aspects of health warrant further explication.
First, the health differences mentioned regarding overall health among Asian Americans
certainly pertain to mental health outcomes as well. Results from the NLAAS indicate that Asian
Americans have mental disorder prevalence rates of 17.3% (lifetime) and 9.19% (12-month) (Takeuchi,
Zane, Hong, et al., 2007). These rates are higher than those of the Whites, African Americans, and
Latinos in the National Comorbidity Study (Breslau et al., 2005). Also, higher rates of suicide and
suicidal ideation have been found among elderly Asian Americans, when compared to the elderly of
other racial groups (Bartels, 2002; Yang, 2007). Among college students, Asian Americans report
higher levels of depression and social anxiety than their White counterparts (Okazaki, 1997). Asian
Americans are less likely to seek and utilize mental health care than other racial groups (Abe-Kim,
2007; Appel, 2011; Chu & Sue, 2011; Flores, 2008; Kearney, 2005; Kim, 2011; Matsuoka, 1997; U.S.
DHHS, 2001; Wang, 2005; Zhang, 1998). While 54% of the general population with a probable mental
disorder utilize specialty mental health services, only 28% of comparable Asian Americans do (Wang et
al., 2005). Furthermore, Asian/Pacific Islander children have the highest adjusted odds of having no
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mental health care, when compared to Latino, African American, Native American, multiracial, and
White children (Flores & Tomany-Korman, 2008).
Secondly, empirical examination of Asian American mental health is subject to different results
depending on what type of assessment method is administered (Chu & Sue, 2011). While self-reported
measures of depression indicated higher depression rates among Asian compared to White Americans,
a diagnostic interview yielded no differences between the two groups (Lam, Pepper, & Ryabchenko,
2004). Similarly, U.S.-born Asians demonstrated significantly poorer health than their foreign-born
counterparts when objective measures were used (Kim, Chen, & Spencer, 2012). However, subjective
(self-rated) measures of physical and mental health showed the opposite trend, with those born in the
U.S. having better self-rated health than immigrants (Kim, Chen, & Spencer, 2012). Others have noted
similar patterns whereby differences in health between American and Japanese residents vary by the
objectivity of the measure (Miyamoto & Ryff, 2011). Therefore, both subjective and objective
measures of health should be used in order to comprehensively examine the nuanced mechanisms by
which sociodemographic and cultural factors influence health among Asian Americans.
Third, great heterogeneity has been found within the Asian American population with regards to
mental health. Subgroups originating from particular regions, such as Southeast Asia, have much higher
rates of certain disorders than those from other regions. One study found that Cambodian prevalence
rates of past-year PTSD were as high as 62 percent, while depression rates were 51 percent (Marshall,
Schell, Elliott, Berthold, & Chun, 2005). Meanwhile, those from South Asia (including India, Pakistan,
Bangladesh, and others) had lower rates of affective, anxiety, and substance abuse/dependence
disorders than Asian Americans in general (Masood, Okazaki, Takeuchi, 2009). There is heterogeneity
in terms of mental health service utilization as well, with those born in the U.S. reporting higher rates
of service use than their immigrant counterparts (Abe-Kim et al., 2007).
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In sum, due to problems with the validity of measures, great diversity of Asian ethnic groups,
and conflicting data regarding prevalence rates (Chu & Sue, 2011), uncovering heterogeneity in
profiles of Asian American mental health remains an integral part of an effort to better understand and
serve this large and growing group.
Health changes over time in the U.S. One of the most salient and consistent findings with
regard to the health of ethnic minority populations that are largely foreign-born (i.e., Latinos and Asian
Americans) is that despite the many stressors associated with the process of moving to a new country –
leaving loved ones, customs, and perhaps even one's profession behind and acclimating to a new and
different society – immigrants tend to arrive in the U.S. with better physical and mental health than
their native-born counterparts. This phenomenon is called the “immigrant paradox,” “epidemiological
paradox” and “healthy immigrant effect” and has been documented among a host of populations from a
variety of countries of origin (Alegría, 2004; 2007; Caplan, 2007; Chen, 2006; Gong, 2006; Lincoln,
2007; Kimbro, 2012; Markides, 1986; Mossakowski, 2003, 2007; Rumbaut, 1996; Suárez-Orozco,
2008; Takeuchi, 2002; Vega, 1991). However, over time, this health advantage tends to diminish such
that long-term residents and those in the second, third, and later generations have health status
generally comparable to the U.S. average (Alegría, 2007; Finch, 2003; Frisbie, 2001; Rumbaut 1997a,
1997b; Zhang, 2009).
A number of reasons have been put forward to help explain the downturn in immigrant
outcomes with longer duration in the U.S. (Gong, 2006; Portes, 2006). Along the lines of the
assimilation perspective, some assert that immigrants tend to change their beliefs, values, and lifestyles
in order to adapt themselves to the host culture, and that these changes have an effect on health
behavior as well as health outcomes (Ma et al., 2004). Others propose that over time, foreign-born
residents in the U.S. have increasing exposure to societal stressors such as discrimination, which in turn
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erode health status over time (Caplan, 2007; Gee, 2002; Gong, 2006; Landale, 1999; Noh, 2003;
Portes, 1984). Lastly, it is possible that after growing up in a social context in which one was part of the
racial majority, moving into a “minority” status can be psychologically jarring, especially when
migrating into a racially stratified society such as the United States (Mossakowski, 2007).
Regardless of the source of the health declines found among immigrants, factors that counteract
this decline need to be identified. Rather than being viewed as inevitable, this health decline is simply
an “average” experience; there are many individuals who defy the trend by maintaining good health
over time in the U.S. and it is important to determine what might help to sustain the health of these
individuals. Exploring how differences in sociodemographic factors contribute to different risk profiles
of health is one task in the larger goal of understanding and working to improve Asian American health
outcomes. A second task is bringing theory to bear on the hypotheses and research questions that are
involved in these analyses. A recent paper published by the investigators who led the Asian American
portion of the NLAAS study states:
One major issue is that we lack a theory of heterogeneity. It is clear that heterogeneity exists. An
endemic issue with many studies of Asian Americans is that often there is no a priori for saying
how groups should differ, beyond saying that they will differ...Accordingly, the field should
move beyond documenting heterogeneity to developing more specific theories about which
differences may influence different health outcomes. (Takeuchi, Gong, & Gee, 2012, p. 126).
It is in this vein that the cultural resource hypothesis will be utilized as an explanatory mechanism that
connects sociodemographic factors and physical and mental health status in this dissertation study.
Cultural Resources and Health
Culture, defined as something that is learned, shared, and transmitted across generations, which
is reflected in a group's values, beliefs, norms, behaviors, communication, and social roles, can have
both direct and indirect effects on health (Rosal, 2009; Kreuter, 2006). The presence of cultural
resources has been posited as one way to explain the sometimes unexpected positive health outcomes
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CULTURAL RESOURCES AND HEALTH Ray-Letourneau
among groups that could be considered as occupying a disadvantaged social status, such as ethnic
minorities and those living in poverty (Abdou, 2010, 2012; Campos, 2008). According to Abdou et al.
(2010), “nonmaterial resources derived from culture can buffer the negative health effects of limited
material resources and even ethnic minority status” (p. 396). In their study, the cultural resource of
“communalism” was associated with better prenatal emotional health and physiology among African
American women and women of lower socioeconomic backgrounds (Abdou et al., 2010). A subsequent
study demonstrated that the cultural resource of maternal “familism” is not only associated with
improved birth outcomes, but also with the child's health status three years after birth (Abdou,
Dominguez, & Myers, 2012). Interactive effects of cultural resources with ethnicity and socioeconomic
status were also found, indicating that cultural resources play a unique role in the health of women
from marginalized backgrounds (Abdou et al., 2010). As such, cultural resources seem to be a plausible
link between sociodemographic factors and the health differences found among ethnic minority
populations. However, to the author's knowledge, the cultural resource hypothesis has not yet been
empirically tested among Asian Americans.
Research findings suggest that aspects of Asian culture are associated with improved health
(Juang, 2009; Kitayama, 2010; Miyamoto, 2011; Triandis, 1988). For example, the “middle way”
emotional style that is prevalent in East Asia, as opposed to the style prone to emotional extremes that
is more prominent in the U.S., is associated with improved health status (Miyamoto & Ryff, 2011).
Meanwhile, the Asian cultural value of collectivism, which emphasizes group goals and collective
sharing, is beneficial to mental health, at least in certain contexts (Mossakowski, 2007; Triandis, 1988).
Health advantages are found among Japanese individuals who report higher levels of relational
harmony (Kitayama, Karasawa, Curhan, Ryff, & Markus, 2010). Chinese American adolescents
exhibiting greater filial piety – as demonstrated by higher levels of family obligation attitudes and
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CULTURAL RESOURCES AND HEALTH Ray-Letourneau
behaviors – have lower risk for depressive symptoms (Juang & Cookston, 2009). In sum, a compelling
body of work is suggestive of the health-benefiting nature of cultural values and behaviors. However,
the specific cultural resources that influence health, as well as the mechanisms by which they do so,
remain unclear. Experts in this field have called for more systematic study of cultural and social
phenomena as contributors to Asian American health (Takeuchi, Gong, & Gee, 2012).
In an effort to apply systematic thinking to the study of Asian American health, this study will
employ a typology to differentiate important aspects of culture. Chia and Costigan (2006) provide a
typology that distinguishes between “internal” and “external” domains of culture. By their delineation,
the “internal domain” of culture refers to psychological aspects of a person's orientation toward their
cultural group; for example, a feeling of identification with one's own ethnic group (Chia & Costigan,
2006). Meanwhile, the “external domain” pertains to behavioral aspects of a person's cultural
orientation, including language use and participation in cultural traditions such as religious services
(Chia & Costigan, 2006). This differentiation seems pertinent and useful as a means to advance the
systematic study of cultural resources; therefore both internal and external domains of culture will be
investigated as contributors to Asian American health in this dissertation study.
Internal resources. Ethnic identity. Although the concept of ethnic identity is multidimensional
and has undergone changing definitions over the years (Mossakowski, 2003, 2007; Phinney, 1990,
2007; Sue, 1998, Yip, 2008), many researchers cite Tajfel (1981), who defined it as: “that part of an
individual's self-concept which derives from his knowledge of his membership of a social group (or
groups) together with the value and emotional significance attached to that membership” (p. 255).
Having stronger ethnic identity is protective against depression (Mossakowski, 2003) and
psychological distress (Yip, Gee, & Takeuchi, 2008) among Asian Americans. Ethnic identity may
operate by buffering the stressful effects of racial discrimination (Yip, Gee, & Takeuchi, 2008) and is
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CULTURAL RESOURCES AND HEALTH Ray-Letourneau
an important coping resource for racial/ethnic minorities (Mossakowski, 2003). Ethnic identity is a
construct of particular relevance to Asian Americans because of the Asian cultural orientation toward
interdependence and collectivism mentioned above. Due to their interdependent self-construals, Asian
Americans are more likely than other racial groups to be influenced by the situational context and
fellow in-group members in defining their identities (Sue, Mak, & Sue, 1998).
External resources. Religious participation. Connection to religious groups, institutions, and
practices can help to maintain traditional culture as well as promote ethnic identity and positive
outcomes among immigrants and Asian Americans (Bankston III, 1995; Chen, 2002; Min, 1992).
Religious participation facilitates immigrant adolescents' positive adaptation to American society
(Bankston III & Zhou, 1995). Minority religious groups can serve to integrate young people into the
dominant society, both through teaching of norms that affirm compliance with the dominant society and
by increasing minority solidarity, which often leads to upward mobility in mainstream society
(Bankston III & Zhou, 1995). Religious participation is also associated with health, though this line of
research has primarily been conducted among White Americans, with comparatively few studies
conducted on racial and ethnic minority populations (Ellison, 2010; Lincoln, 2003). Attending
religious services improves mental health outcomes such as depression (Ellison, 1995), and is
particularly beneficial for the mental health of those who are medically compromised and/or poor
(Cummings, 2003; Kilbourne, 2011; Wink, 2005). Religious service attendance also improves physical
health, reducing all-cause mortality among the medically ill (Schnall et al., 2010).
Maintenance of native language proficiency is deeply tied to cultural identity among Asian
Americans (Lee, 2002; Kang, 2012). Asian immigrants who maintain native language proficiency in
addition to gaining proficiency in English have a health advantage over immigrants who are English-
dominant (Schachter, Kimbro, & Gorman, 2012).
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CULTURAL RESOURCES AND HEALTH Ray-Letourneau
Ethnic identity, religious participation, and maintenance of native language are therefore each
independently associated with improved adaptation to the U.S. context. However, how each of these
resources affects health among Asian Americans over time remains unclear, thus forming the central
research question of Study 2.
Structure of the Dissertation
This dissertation is presented in a multiple manuscript format as three separate but related
studies (each further described below). The objective of this format is to produce distinct studies that
are to be of publication quality, which can be disseminated in an expeditious fashion. The data for the
empirical studies come from the National Latino and Asian American Study (NLAAS), the first
nationally representative epidemiological study of Asian Americans. The NLAAS employed a multi-
frame, stratified area probability sampling design, representative of Asian and Latino individuals 18 or
older in the non-institutionalized population of the 50 United States. The data were collected using a
complex sampling design during 2002-2003; details of the NLAAS protocol and sampling methods
have been previously documented (Alegría, 2004a, 2004b; Heeringa, 2004; Pennell, 2004).
The analytical sample for this dissertation study is comprised of the 2,095 Asian American
respondents who were recruited as part of the broader NLAAS study. All participants were interviewed
either face-to-face or via telephone by trained bilingual interviewers, using computer-assisted
interviewing software (mean duration=2.6 hours). Respondents could choose to be interviewed in
English, Mandarin, Cantonese, Tagalog, or Vietnamese. Informed consent was written and signed by
the respondent and was verified by the interviewer. The study procedures were approved by the Internal
Review Boards of the University of Washington, University of Michigan, and Cambridge Health
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CULTURAL RESOURCES AND HEALTH Ray-Letourneau
Alliance.
This first chapter serves as a brief introduction to and overview of the three studies in the
dissertation. Chapter 2 (Study 1) will present the results of descriptive, correlational, and first-order
regression analyses that will be employed to examine the influence of the three proposed cultural
resources on subjective and objective measures of physical and mental health, taking sociodemographic
characteristics and survey design corrections into account. To address research question 2, regarding
the extent to which cultural resources moderate the relationship between duration of time in the U.S.
and mental health, Chapter 3 (Study 2) will employ second-order regression analyses. Specifically,
interaction terms between “duration of residence in the U.S.” and each of the cultural resource
variables will be utilized in logistic regression models predicting objective measures of mental and
physical health. In Chapter 4 (Study 3), latent class analysis (LCA) will be conducted to address
research question 3, regarding identifying health risk profiles among a heterogeneous sample of Asian
Americans. By using a “person-oriented” (Bergman & Magnusson, 1997) as opposed to a “variable-
oriented” framework, it may be possible to identify latent classes of people based on their reported
characteristics, which will help to elucidate the heterogeneity in health profiles among Asian American
populations. The LCA will include the following variables: physical health, gender, age, ethnic group,
household income, educational attainment, and duration of residence in U.S.. The classes resulting
from the LCA will then be used in a regression analysis to examine how different levels of ethnic
identity predict class membership, in response to research question 3b. Chapter 5 will serve as a
concluding chapter to integrate the findings from chapters two through four and discuss their collective
implications.
In addition to filling the conceptual, theoretical, and methodological gaps in the scientific
literature mentioned above, this dissertation study will contribute to the knowledge base regarding
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CULTURAL RESOURCES AND HEALTH Ray-Letourneau
Asian American physical and mental health by helping to unravel the complex mechanisms that lead to
divergent health outcomes of this large and growing, diverse segment of the U.S. populace. It is hoped
that by identifying malleable risk and protective factors, the general decline in health status that occurs
over time in the U.S. might be averted, benefiting both individuals and society as a whole.
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CULTURAL RESOURCES AND HEALTH Ray-Letourneau
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Chapter 2 (Study 1):
Testing the Cultural Resource Hypothesis among Asian Americans
Asian Americans account for over 5% of the total U.S. population. Their numbers are projected
to double over the next fifty years so that by 2060, approximately 34 million Asian Americans will be
living in the U.S. (U.S. Census Bureau, 2012). Despite the group's size, much remains unknown about
the health profile of Asian Americans compared to other racial and ethnic groups. Thus, both the
scientific community and the general public remain insufficiently informed about the health and well-
being of Asian Americans (Takeuchi, Gong, & Gee, 2012). This is particularly troubling given that the
nation's annual health expenditures are projected to rise to about $4.6 trillion by 2020 (Centers for
Medicare and Medicaid Services, 2011). Demographic shifts have led to increasingly diverse patient
populations and pressure on health systems to provide effective, efficient, and culturally competent
care.
Early attempts to understand the breadth and depth of health problems among Asian Americans
were plagued with methodological limitations such as small sample sizes, geographically defined
samples, and single-ethnic-group focus, resulting in a lack of generalizability and equivocal findings
(Leu, 2011; Takeuchi, 2007; Yip, 2008). With the advent of the first national epidemiological survey of
Asian Americans – the National Latino and Asian American Study (NLAAS) – many of these
limitations have been overcome and articles examining Asian American health have flourished. Recent
research has shown, for example, that contrary to the “model-minority” myth, purporting that Asian
Americans attain superior educational, occupational, and health outcomes compared to other racial
groups (McBride, 1996; Yee, 2009), many Asian Americans have a high risk of developing certain
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health problems. For example, Asian American men have lower cancer survival rates (Ward et al.,
2010) and children have worse overall health status (Chen, Martin, & Matthews, 2006) than their white
counterparts. Moreover, some research findings indicate higher rates of mental disorder among Asian
American adults (Takeuchi et al., 2007) than those reported for whites, African Americans and Latinos
(Breslau, Kendler, Su, Gaxiola-Aguilar, & Kessler, 2005).
The great diversity among Asian Americans results in specific ethnic groups having
differentiated health risk profiles (Kim, 2010; Kim, 2012). Some subgroups of Asian Americans, such
as those from Southeast Asia, have higher prevalence of depression, Post-Traumatic Stress Disorder,
Hepatitis B, Tuberculosis, and liver, lung, and cervical cancer than members of other Asian ethnic
groups (Chu, 2011; McCracken, 2007; Takada, 1998). Many studies explore reasons for the great
variability found in Asian American health prevalence rates. The explanation that has probably received
the most attention is the “epidemiological paradox” or “immigrant health paradox,” which states that
although immigrants often arrive in the U.S. with better mental and physical health status than their
U.S.-born counterparts, over time, the protective effects of foreign-born status diminish, resulting in an
overall increase in health problems with longer duration in the U.S. (Frisbie, 2001; Zhang, 2009). Even
very recent studies continue the line of inquiry about whether the paradox exists and if so, what
contributes to it (Dolly, de Castro, Martin, Duran, & Takeuchi, 2012). However, the causes and
contributors to health in such a diverse population remain undetermined. Explanatory mechanisms are
still needed in order to develop more responsive and culturally appropriate health and social service
delivery systems that better address the needs of this large and growing segment of the U.S. population.
Therefore, this study will attempt to elucidate the mechanisms that contribute to heterogeneous Asian
American health outcomes, based on the theoretical and empirical literature presented below.
Specifically, it will apply the cultural resource hypothesis (Abdou, 2010, 2012; Campos, 2008), a
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promising theory that has not yet been tested among Asian Americans, to investigate whether one
cultural resource from the internal domain of culture, ethnic identity, and two from the external domain
of culture, native language proficiency and religious service attendance, affect mental and physical
health problems among a nationally representative sample of Asian American adults.
Asian American Mental Health
Over 17% of Asian Americans have had a mental health disorder in their lifetime (Takeuchi et
al., 2007). However, a great deal of variability exists among this diverse population, with prevalence
rates being affected by factors such as ethnic group and amount of exposure to U.S. society. Lifetime
prevalence rates of mental disorder are lower for Filipino and Vietnamese ethnic groups (17% and
14%, respectively) than those for Chinese and Asians from other ethnic backgrounds (both 18%)
(Takeuchi et al., 2007). Asian Americans who arrived in the U.S. recently have lower prevalence rates
(13%) than both long-term residents (17%) and those born in the U.S. (25%) (Takeuchi et al., 2007).
Within the Asian American population, some sociodemographic groups are at higher risk of
certain mental health disorders than their non-Asian counterparts. Among older adults, Asians have
higher rates of suicide and suicidal ideation than older adults of other racial groups (Bartels, 2002;
Yang, 2007). Asian American college students report higher levels of depression and social anxiety
than their white counterparts (Okazaki, 1997). Some Southeast Asians have very high rates of specific
mental health disorders: 62% of Cambodians meet criteria for past-year Post Traumatic Stress Disorder
and 51% meet criteria for depression (Marshall, Schell, Elliott, Berthold, & Chun, 2005).
Differences in mental health status are compounded by ethnic disparities in access and
utilization of mental health services. Health disparities – preventable differences in the burden of
disease that are experienced by socially disadvantaged populations (CDC, 2008) – affect Asian
Americans on a number of fronts. Extensive research has demonstrated that Asian Americans are less
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likely to seek and utilize mental health care than other racial groups (Abe-Kim, 2007; Appel, 2011;
Chu, 2011; Flores, 2008; Kearney, 2005; Kim, 2011; Matsuoka, 1997; U.S. DHHS, 2001; Wang, 2005;
Zhang, 1998). While 54% of the general population with a probable mental disorder utilize specialty
mental health services, only 28% of comparable Asian Americans do (Wang et al., 2005). Furthermore,
Asian/Pacific Islander children have the highest adjusted odds of having no mental health care,
compared to Latino, African American, Native American, multiracial, and white children (Flores &
Tomany-Korman, 2008). Finally, Asian Americans born outside the U.S. have much lower rates of
service use than their U.S.-born counterparts (Abe-Kim et al., 2007).
Asian American Physical Health
On average, Asian American adults report having 1.31 out of the 10 chronic health conditions
assessed using the World Mental Health Composite International Diagnostic Interview (CIDI) (Kim,
Chen, & Spencer, 2012). However, the great diversity found among Asian Americans leads to
heterogeneous health outcomes (Frisbie, 2001; Gee, 2009; Gong, 2006; Kim, 2012; Takeuchi, 2012).
Mortality from cardiovascular disease is fairly high (320 per 10,000) among men of South Asian
descent, but much lower among those of Chinese descent (107 per 10,000) (Yusuf, Reddy, Ounpuu, &
Anand, 2001). Sociodemographic factors such as older age, higher levels of education, and being
female, Filipino, or born in the U.S. are all associated with increased health problems among this
population (Kim, Chen, & Spencer, 2012). Social stressors such as experiencing discrimination
increase Asian Americans' likelihood of chronic health conditions (Kim et al., 2012) as well as other
physical health problems (Gee, 2009; Hahm, 2010; Mereish, 2011).
Although Asian Americans are often thought of as a “model minority,” having fewer health
concerns than white or other ethnic groups, Asian incidence rates for many physical health issues are
comparable to, or worse than, those of their non-Asian counterparts (McBride, Morioka-Douglas, &
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Yeo, 1996). Asian American/Pacific Islanders (AAPIs) have higher incidence rates than all other ethnic
groups for stomach and liver cancers (Ward et al., 2004) and Asian Americans experience higher
mortality than non-Hispanic whites from these cancers (McCracken et al., 2007). Asian American men
also have lower five-year cancer survival rates than non-Hispanic whites (Ward et al., 2004). A higher
proportion of AAPIs engage in very little leisure-time physical activity (39.1%), compared to whites
(34.8%) (Barnes, Adams, & Powell-Griner, 2008). Some Asian descent groups, such as Filipinos and
Asian Indians, have similar rates of overweight and obesity as their white counterparts (Barnes et al.,
2008). Finally, Asian Americans experience problems with access to health services at higher rates than
other ethnic groups (Abe-Kim, 2007; Flores, 2008; Huang, 2011; Kim, 2010; Takada, 1998).
Cultural Resources
Culture is defined as something that is learned, shared, and transmitted across generations,
which is reflected in a group's values, beliefs, norms, behaviors, communication, and social roles.
Culture can have both direct and indirect effects on health (Rosal, 2009; Kreuter, 2006). The “cultural
resource hypothesis” has been posited as one way to explain the sometimes unexpected positive health
outcomes among groups that would otherwise be considered disadvantaged, such as ethnic minorities
and those living in poverty (Abdou, 2010, 2012; Campos, 2008). For example, children born into
families with low socioeconomic position (SEP) are at higher risk of low birthweight and childhood
asthma (Abdou, Parker Dominguez, & Myers, 2012). However, the cultural resource of maternal
familism reduces the risk of poor health outcomes, especially among those with the lowest SEP (Abdou
et al., 2012). Similarly, the cultural resource of communalism benefits maternal emotional and
physiological health among African American women and women of lower socioeconomic
backgrounds (Abdou et al., 2010). The authors note the “intriguing possibility that cultural resources
may help to buffer status-based stressors, thereby minimizing ethnic and socioeconomic inequalities in
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health and well-being” (Abdou et al., 2010, p. 402).
Cultural resources provide a plausible link between sociodemographic factors and the health
differences reported among ethnic minority and disadvantaged populations. However, research
examining the role of cultural influences on health among Asian Americans is scant. Aspects of Asian
culture such as an emphasis on collectivism (Mossakowski, 2007; Triandis, 1988), interdependence
(Kitayama, Karasawa, Curhan, Ryff, & Markus, 2010), and filial piety (Juang & Cookston, 2009)
benefit certain health outcomes among specific Asian ethnic groups. But this research often lacks a
priori reasoning and systematic methods, which are sorely needed when examining cultural and social
influences on health (Takeuchi et al., 2012).
In an effort to be more systematic, it is helpful to draw distinctions between different domains
of culture. Using Chia and Costigan's (2006) typology of cultural domains, the “internal domain” of
culture refers to psychological aspects of a person's orientation toward their cultural group; for
example, a feeling of identification with one's own ethnic group. Meanwhile, the “external domain”
pertains to behavioral aspects of a person's cultural orientation, including language use and
participation in cultural traditions such as religious services (Chia & Costigan, 2006). This
differentiation is pertinent and useful as a means to advance the systematic study of cultural resources.
Ethnic Identity. Ethnic identity has been described as “that part of an individual's self-concept
which derives from his knowledge of his membership of a social group (or groups) together with the
value and emotional significance attached to that membership” (Tajfel, 1981, p. 255). Ethnic identity is
a construct of particular relevance to Asian Americans because of the Asian cultural orientation toward
interdependence and collectivism mentioned above. Due to their interdependent self-construals, “Asian
Americans are more likely to be influenced by the situational context and their in-group members in
defining their identities” (Sue, Mak, & Sue, 1998). Asian American health has been linked to ethnic
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identity in a limited number of studies. Study findings show that ethnic identity is protective against
depression (Mossakowski, 2003) and psychological distress (Yip, Gee, & Takeuchi, 2008) among
Asian Americans. Ethnic identity buffers the stressful effects of racial discrimination on mental health,
at least for certain age groups (Yip et al., 2008), and is described as “a coping resource for racial/ethnic
minorities that should not be overlooked” (Mossakowski, 2003, p. 318).
Religion and Asian Americans. Connection to religious groups, institutions, and practices
helps to maintain Asian culture as well as promote ethnic identity and positive outcomes among
immigrants and their families (Bankston, 1995; Chen, 2002; Min, 1992). Religious participation among
immigrant adolescents facilitates their positive adaptation to American society, in part by enhancing
their sense of solidarity with others to who they feel similar (Bankston & Zhou, 1995). Although few
studies have examined the effects of religious participation on health among racial and ethnic minority
populations (Ellison, 2010; Lincoln, 2003), research shows that among white populations, attendance at
religious services improves mental health outcomes such as depression (Ellison, 1995). Religious
participation is particularly beneficial for the mental health of those who are elderly, medically
compromised, and/or poor (Braam, 2001; Cummings, 2003; Kilbourne, 2011). Physical health
outcomes such as mortality are also benefited by more frequent attendance at religious services,
especially among the medically ill (Schnall et al., 2010).
Studies of older adults in Asia also suggest the health-promoting nature of religious
participation. Risk of dying is significantly lower for elders who engage in religious practices (Zeng,
Gu, & George, 2011). Participating in social activities like religious groups prevents depression among
older adults in Taiwan, even after controlling for the effects of aging, demographic differences, and
health status (Chiao, Weng, & Botticello, 2011). Religious participants in Taiwan also have lower
anxiety and better quality of life than their non-religious counterparts (Huang, Hsu, & Chen, 2012).
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Subjective vs. Objective Measures of Health
To get a full and complete picture of a person's health and well-being, it is helpful to consider
both objective and subjective indicators of health status. Research studies employ subjective or self-
rated assessments of health for a number of reasons. First, their more global and overarching nature can
capture aspects of health beyond what objective measures can tell us (Gorman & Sivaganesan, 2007).
Self-rated health is also strongly associated with health status (Gold, 1996; Singh-Manoux, 2006) and
mortality (Idler & Benyamini, 1997). Its reliability in predicting morbidity has been demonstrated
across a number of ethnic groups (Chandola & Jenkinson, 2000). However, the appropriateness of self-
rated health measures as markers of true mental or physical health status remains under debate
(Johnston, Propper, & Shields, 2007). Health disparities research is particularly prone to questioning
the validity of self-reported health measures since some studies indicate that certain ethnic groups,
including Asian immigrants, tend to avoid giving extreme ratings on health questionnaires (Iwata,
2000; Iwata, 1995), complicating efforts at comparison across groups. However, others have disputed
this claim, finding no systematic differences in self-rated health response distributions between native-
born and foreign-born Asian Americans (Erosheva, Walton, & Takeuchi, 2007). Still, health differences
between groups can vary, depending on the objectivity of the measure (Miyamoto & Ryff, 2011). For
example, objective measures indicate that Asian Americans born in the U.S. have poorer health than
their immigrant counterparts, but subjective measures indicate that the opposite is true (Kim et al.,
2012).
Some known contributors to health, such as income, influence subjective measures of health
more strongly than objective measures (Johnston, 2007; Sturm, 2002). By the same logic, it is possible
that one type of measure is more susceptible to the influence of cultural resources than the other. Even
though objective measures of health might be considered more important due to their effects on public
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health and medical care systems, subjective measures of health might be more important for people's
quality of life and overall sense of well-being (Gold, 1996; Idler, 1997). Therefore, it is important to
include both types of measures of health in studies of physical and mental health.
Focus of the Present Study
The aim of the current study is to better understand the relationships among sociodemographic
factors, cultural resources and health status among Asian Americans. Specifically, the cultural resources
of ethnic identity, native language proficiency, and religious service attendance will be examined as
possible explanatory factors between sociodeomographic position and Asian American mental and
physical health outcomes. Findings have the potential to inform the development of more responsive
and culturally appropriate health and social service delivery systems for this large and growing segment
of the U.S. population.
Methods
Data for this analysis come from the National Latino and Asian American Study (NLAAS), the
first nationally representative epidemiological study of Asian Americans. The NLAAS employed a
multiframe, stratified area probability sampling design, representative of Asian and Latino individuals
aged 18 and older in the non-institutionalized population of the contiguous United States. Details of the
NLAAS protocol and sampling methods have been previously documented (Alegría, 2004a, 2004b;
Heeringa, 2004; Pennell, 2004). Weighting corrections were developed to take into account the joint
probabilities for selection under the complex sampling design.
The analytic sample contains the 2,095 Asian American respondents who were recruited as part
of the broader NLAAS study during 2002-2003. All participants were interviewed either face-to-face or
via telephone by trained bilingual interviewers, using computer-assisted interviewing software (mean
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CULTURAL RESOURCES AND HEALTH Ray-Letourneau
duration = 2.6 hours). Respondents could choose to be interviewed in English, Mandarin, Cantonese,
Tagalog, or Vietnamese. Informed consent was written and signed by the respondent and was verified
by the interviewer. The study procedures were approved by the Internal Review Boards of the
University of Washington, University of Michigan, and Cambridge Health Alliance. The present study
is exempt according to Institutional Review Board guidelines because it utilizes secondary analyses of
existing de-identified data.
Measures
Dependent Variables. Self-rated mental health (SRMH) was assessed by respondents' self-report of
their overall mental health on a five-point scale (1 = “poor” through 5 = “excellent”). SRMH predicts
medical care usage (Rohrer, 2004) and mental health service use (Kim et al., 2011). Mental health
disorder (MHD) was a composite of 11 International Classification of Diseases (ICD) disorders in three
major groups (depressive, anxiety, and substance use). Respondents were classified as having a
disorder if they met criteria for any of the following diagnoses: major depressive disorder or
dysthymia; panic disorder, generalized anxiety disorder or post-traumatic stress disorder; alcohol abuse
or dependence and drug abuse or dependence. Responses were dichotomized so that 0 = no disorder
and 1 = 1 or more disorder. Self-rated physical health (SRPH) was assessed by respondents' self-report
of their overall physical health on a five-point scale (1 = “poor” through 5 = “excellent”). Self-rated
health is a consistent predictor of mortality (Idler & Benyamini, 1997). The meaning of self-rated
health has been validated among different ethnic groups and the construct has been associated with
morbidity across ethnic groups (Chandola, 2000; Erosheva, 2007). Finally, physical health problem
(PHP) was assessed using the World Health Composite International Diagnostic Interview (CIDI). The
composite measure included cardiovascular and respiratory conditions, pain, diabetes, cancer, and
epilepsy, among others. The number of chronic health problems in the NLAAS Asian American sample
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CULTURAL RESOURCES AND HEALTH Ray-Letourneau
ranged from 0 to 10 (Kim et al., 2012). Responses were dichotomized so that 0 = no health problem
and 1 = 1 or more problems.
Independent Variables. Ethnic identity was measured by the question “How close do you feel, in your
ideas and feelings about things, to other people of the same racial and ethnic descent?” (Félix-Ortiz,
Newcomb, & Myers, 1994). Responses ranged from 1 = “not at all” through 4 = “very close.” Native
language proficiency was measured by the question “How well do you speak Mandarin/Cantonese/
Tagalog/ Vietnamese/Other Asian language?” Responses ranged from 1 = “poor” through 4 =
“excellent.” Religious attendance was measured by the question “How often do you usually attend
religious services?” Response options were 1= “more than once a week,” 2 = “about once a week,” 3 =
“one to three times a month,” 4 = “less than once a month,” 5 = “never.” The item was reverse-coded
so that higher scores reflect more frequent religious attendance.
Sociodemographic characteristics included gender (self-identified, 0 = male; 1 = female); age
(measured continuously); ethnicity (categorized into four groups: Chinese, Filipino, Vietnamese, and
Other Asian; Chinese is referent); educational attainment (measured continuously); income (income-to-
needs ratio, calculated by dividing 12-month household income by the federal poverty threshold for the
corresponding household size and composition, based on the 2000 U.S. Census [Chen & Takeuchi,
2011]); and duration of residence in the U.S (1 = less than 5 years, 2 = 5-10 years, 3 = 11-20 years, 4 =
20+ years, 5 = entire life).
Data Analytic Strategy
First, descriptive statistics were examined for the full sample and then stratified by ethnic
group. The Rao-Scott chi-square test was used to assess whether differences observed between ethnic
groups were significant. Second, bivariate correlations were examined for multicollinearity and
preliminary associations among all study variables. Lastly, hierarchical multivariate regression analyses
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CULTURAL RESOURCES AND HEALTH Ray-Letourneau
were conducted to examine the relative contributions of sociodemographic factors and cultural
resources to mental and physical health. Linear regression models were conducted for continuous
outcome measures (SRMH and SRPH) and logistic regression models were conducted for categorical
outcome measures (MHD and PHP). Regression analyses were executed in two steps; the seven
sociodemographic variables were entered first, followed by the three cultural resource variables. Model
fit indices were used to examine improvement in fit between the first and second steps of the analysis
(R-square for linear models, Wald chi-square for logistic models). All analyses were performed using
SAS 9.2, using the “survey” command to take into account the sample's complex survey design,
including weight, cluster, and strata.
Results
Table 2.1 displays the distribution of sociodemographic, cultural resource, and health variables
for the full sample of Asian Americans, indicating that more than half (53%) were female, over three-
fourths (81%) were 54 years old or less, and nearly one-quarter (23%) were born in the U.S. About
one-quarter (26%) of respondents were born outside of the U.S. and arrived within the past 10 years,
while about half (51%) arrived over 10 years prior. Over two-thirds (67%) have more than a high
school education and a similar proportion (68%) have an income level at least three times above the
national poverty line. In terms of cultural resources, 84% report a high level of ethnic identity, 32%
report attending religious services at least weekly, and 64% report a “good” or “excellent” level of
native language proficiency. Nine percent of respondents rate their mental health as poor or fair and
11% endorse at least one diagnosable mental health disorder. Finally, 16% of respondents rate their
physical health as poor or fair, with 58% endorsing at least one physical health problem.
The results are also stratified by ethnic group (Table 2.1), demonstrating that the distributions of
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sociodemographic factors, cultural resources, and health vary considerably between Asian subgroups.
Significant ethnic group differences were found for a number of variables: age, years in U.S.,
education, income, self-rated mental and physical health, and physical health problem. The
distributions of the three cultural resources also varied by ethnic group; with the highest level of ethnic
identity and native language proficiency reported by Vietnamese adults, and the highest level of weekly
religious attendance reported by the Filipino adults.
Bivariate associations among study variables (Table 2.2) were in the low to moderate range (+/-
0.002 - 0.608). The strongest correlations were between the two subjective health measures (SRPH and
SRMH, r = 0.608) and between Years in U.S. and native language proficiency (r = -0.572). Among the
cultural resource variables, the associations were positive and significant but relatively low (0.073 to
0.295). Regression analyses predicting subjective and objective measures of mental and physical health
are summarized in Tables 2.3-2.6, and significant findings are described below.
Self-rated Mental Health
Table 3 illustrates results of analysis for self-rated mental health. Findings indicate that the full
model accounted for 14% of the variance in SRMH among the full sample of Asian Americans.
Regarding the association between the three cultural resources and SRMH, religious attendance
( β=0.09, p<.001) and native language proficiency ( β=0.06, p<.05) were associated with SRMH, such
that those who reported more frequent church attendance and were more proficient in their native
language had better self-reported mental health. Among Chinese adults specifically, more frequent
church attendance was associated with higher SRMH ( β=0.11, p<.05). Among Filipino and Vietnamese
adults, those with high levels of native language proficiency reported better SRMH ( β=0.11, p<.001,
and β=0.31, p<.001, respectively).
For the full sample, female gender ( β= -0.20, p<.01) and older age ( β= -0.01, p<.001) were
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CULTURAL RESOURCES AND HEALTH Ray-Letourneau
associated with worse SRMH, whereas higher income ( β=0.02, p<.05) and education ( β=0.04, p<.01)
were associated with better SRMH. Being Vietnamese ( β=0.14, p<.05), Filipino ( β=0.40, p<.001), or
“Other Asian” ( β=0.47, p<.001) had beneficial effects on SRMH, in comparison to being Chinese.
Mental Health Disorder
Table 4 illustrates results of analysis for mental health disorder. Findings indicate that the Wald
chi-square for the full sample of Asian Americans was 30.78 for the baseline model and 50.37 for the
final model, indicating an improvement in model fit. Native language proficiency (OR = 0.84, 95% CI=
0.72, 0.99) was associated with lower odds of MHD in the full sample and among Chinese adults (OR
= 0.73, 95% CI= 0.58, 0.91). Ethnic identity was associated with lower odds of MHD, but only among
Filipino adults (OR = 0.64, 95% CI= 0.47, 0.88).
Older age was associated with lower odds of MHD (OR = 0.98, 95% CI= 0.97, 0.99) and longer
duration of residence in the U.S. increased the odds of MHD for the full sample (OR = 1.28, 95% CI=
1.12, 1.46).
Self-rated Physical Health
Results from the full model estimating self-rated physical health indicate that the
sociodemographic and cultural resource variables accounted for 10% of the variance in SRPH among
the full sample of Asian Americans. None of the cultural resources were associated with SRPH in the
multivariate model among the full sample; however, native language proficiency was associated with
higher SRPH among Filipino ( β=0.09, p<.05) and Vietnamese ( β=0.34, p<.001) respondents.
For the full sample, female gender ( β= -0.13, p<.05) and older age ( β= -0.01, p<.001) were
associated with lower SRPH while higher income ( β=0.02, p<.01) and being Filipino ( β=0.31, p<.001)
or “Other Asian” ( β=0.38, p<.001) were associated with higher SRPH.
Physical Health Problem
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CULTURAL RESOURCES AND HEALTH Ray-Letourneau
Table 6 displays that the Wald chi-square increased from 206.54 in the baseline model to 269.53
in the final model, indicating an improvement in model fit. Native language proficiency (OR = 0.83,
95% CI= 0.76, 0.91) exerted a protective effect on PHP among all Asian Americans. The effect was
particularly strong among Vietnamese respondents (OR = 0.65, 95% CI= 0.50, 0.87). More frequent
religious attendance was associated with an increased risk of PHP (full sample OR = 1.09, 95% CI =
1.00, 1.19; Vietnamese OR = 1.22, CI = 1.08, 1.38).
Age (OR = 1.04, 95% CI= 1.04, 1.05) and duration of residence in the U.S. (OR = 1.28, 95% CI
= 1.18, 1.39) increased the risk for PHP among the full sample. Respondents in the “Other Asian”
group had lower odds of PHP compared to Chinese, Filipino, and Vietnamese respondents (OR = 0.75,
95% CI = 0.57, 0.98).
Discussion
This study is the first to examine the association between cultural resources and multiple
measures of physical and mental health among a nationally representative sample of Asian Americans.
Findings that cultural resources were associated with mental and physical health provide support for the
“cultural resource hypothesis” and demonstrate important sources of heterogeneity within Asian
Americans. Studies indicate that health status is largely determined by one's material resources and
background, such as income, educational attainment, and racial/ethnic background (Anderson, 1995;
Braveman, 2006; Kawachi, 2005; Lincoln, 2010; Phelan, 2005; Ward, 2004; Williams, 1999, 2007;
Zsembik, 2001). However, Abdou and colleagues suggest that nonmaterial resources, such as those
deriving from culture can “buffer the negative health effects of limited material resources and even
ethnic minority status” (Abdou et al., 2010 p. 396).
Findings of this study indicated that higher proficiency in one's native language was associated
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with better physical and mental health among all Asian Americans. This finding is aligned with those of
others indicating the beneficial health effects of maintaining native language proficiency (Portes, 2002,
2006; Yee, 2009). Among immigrants to the U.S., continued use of their language of origin facilitates
preservation of cultural identity and worldview (García, 2003; Kang, 2012; Lee, 2002). Losing these
aspects of cultural life can lead to depressive symptoms as well as other adjustment and health
problems (DuBois, 2002; Rumbaut, 1997a, 1997b; Wong, 2012). Furthermore, since more than half of
elderly Asian Americans are not conversant in English (McBride, Morioka-Douglas, & Yeo, 1996),
they are at high risk of linguistic and social isolation if younger generations in their families and
communities do not speak the elder's language of origin (Ho, 2010; Kang, 2009; Yee, 2009). Linguistic
isolation is a major contributor to poor health outcomes and access to health services (Kwok, 2011; Yu,
2009). Family cohesion, facilitated by intergenerational communication, can also act as a protective
barrier to insulate immigrant families from the harmful effects of adjusting to a new society that may
be experienced as antagonistic, challenging, or discriminatory (Finch, 2003; Lee, 2009; National
Institute on Drug Abuse [NIDA], 1993; Schachter, 2012; Walton, 2010; Yee, 2009). Among younger
immigrants, maintaining proficiency in a native language helps to preserve key elements of the culture
of origin, which in turn can provide “a cognitive reference point to guide their successful integration”
(Portes & Rumbaut, 2006, p. 350). Thus, the mechanisms by which native language proficiency
benefits immigrant health are many, and may vary by one's age and family composition.
For Asian Americans born in the U.S., learning the native language of their first-generation
predecessors helps to facilitate intergenerational communication, making it easier for parents to guide
and support their children (Portes, 2006; Yee, 2009). Maintenance of strong family support systems is
much more difficult when the second and third generations abandon their parents' language and culture,
which can lead to loss of parental control over their children (Portes & Rumbaut, 2006). Family
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conflict is lower and family solidarity is higher when teens can speak the native language of their
predecessors (Portes & Hao, 2002). Among young adults and adolescents, self esteem, educational
aspirations, academic performance, and family socioeconomic status are all benefited by maintenance
of native language (Portes, 2002; Portes, 2006; Yee, 2009). For adults, employability is enhanced by
having strong bilingual language skills, especially as the economy becomes increasingly globalized
(Portes & Rumbaut, 2006). Since family cohesion, psychosocial adjustment, and socioeconomic
success are all associated with improved mental and physical health, it is not surprising that
maintaining native language proficiency improves health status among Asian Americans.
Consistent with prior literature, ethnic identity predicted lower levels of mental health disorder,
but only among Filipino respondents. One potential explanation for this finding is the transnational
nature of the immigrant experience. In an ethnographic study of Filipino Americans, Espiritu (2003)
described transnationalism as “the processes by which immigrant groups forge and sustain strong
sentimental and material links with their countries of origin – as a disruptive strategy...to resist their
differential inclusion in the United States as subordinate residents and citizens” (2003, p. 70).
Therefore, even though Filipinos are at risk of health problems related to their experience of
discrimination and other types of unfair treatment in the U.S. (Gee et al., 2006), it is possible that many
maintain transnational families and social networks in ways that may offset their negative experiences
and improve their mental health and overall well-being. Several studies among the general population
and among Asians, specifically, document the health restorative and protective nature of social
networks on health (Alegría, 2004a; Gorman, 2007; House, 1988; Yoshikawa, 2004) and mental health
(Bearman, 2004; Lee, 2004; Rice, 2012; Tata, 1994; Yeh, 2003).
Another way in which ethnic identity may result in improved mental health is through
intentional creation of ethnic residential communities, which offer an alternative to segregated
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neighborhoods that “maintain white privilege” (Espiritu, 2003, p. 98). Filipinos often live in “distinct
areas” that can be classified as “ethnic neighborhoods,” which are sometimes urban but are
increasingly found in the suburbs of major cities (Logan, Zhang & Alba, 2002). Contrary to patterns
found among other immigrant groups, the fewer economic constraints Filipinos face, the more likely
they are to choose to live in an ethnic group neighborhood (Logan, Zhang & Alba, 2002). Living
alongside fellow Filipinos and maintaining ethnic solidarity can “challenge [the] discriminatory
practices” of white neighborhoods and allow for immigrants to “provide crucial social sustenance and
financial support to each other” (Espiritu, 2003, p. 98). In this way, feelings of social cohesion and
support act as the links between ethnic identity and improved mental health status among Filipino
Americans.
Attendance at religious services had mixed effects – it was protective for self-rated mental
health but a risk factor for physical health problems among Asian Americans. These results are aligned
with previous findings indicating that religious involvement can be both beneficial and harmful to
health, depending on the context and population under investigation (Ellison, 1990, 1995; Trevino,
2007).
Findings revealed the importance of religious services attendance for self-rated mental health
among Asian Americans, particularly for Chinese adults. Participation in religious activities has long
been an important means of coping with the traumas of migration, the difficulty of acclimating to an
unfamiliar environment, and the exclusionism often faced by immigrants in their new host societies
(Chen, 2002; Portes, 2006). Being part of a religious community benefits Asian American health by
facilitating adjustment into the host society (Bankston & Zhou, 1995). Religious participation improves
adjustment by increasing feelings of minority solidarity, integrating members into the dominant society,
and facilitating upward mobility (Bankston & Zhou 1995, p. 532). Furthermore, religious involvement
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CULTURAL RESOURCES AND HEALTH Ray-Letourneau
moderates the effects of anxiety and depression on quality of life (Huang, Hsu, & Chan, 2012) and
improves subjective well-being (Ellison & Day, 1990), all of which contribute to health. The particular
aspect of religious participation included in the present study – attendance at religious services – may
affect health through multiple pathways: via increased social support, adherence to guidelines
restricting unhealthy behaviors (e.g., drinking alcohol, smoking), having a sense of meaning or purpose
in one's life, or gaining psychosocial resources to help one cope with life stress (Koenig, 2009, Zeng,
2011).
The association between the frequency of religious service attendance and self-rated mental
health among Chinese adults only, was not particularly surprising given the specific sociopolitical
contexts that faced Chinese immigrants before and after their migration experiences. The two dominant
religions in China, Buddhism and Daoism, emphasize understanding of the world and attunement to the
natural order, respectively (Zeng, Gu, & George, 2011). Prayer and worship are often practiced
privately, and the public weekly religious services that characterize Western religions are not typical in
China (Melton, 2001; Yang, 2001; Zeng, 2011). While the proportion of individuals practicing Western
religions such as Christianity in China is fairly low, around 5%, the proportion of Chinese Americans
who do so is much greater, around 31% (Pew Research Center, 2012a). In this sense Chinese
Americans are distinct from the other major Asian ethnic groups living in the U.S, whose proportions
of religious affiliation generally reflect the religious composition of their country of origin (Pew
Research Center, 2012a). For example, about 90 percent of Filipinos and Filipino Americans report a
Christian affiliation (including Catholicism), whether they live in the U.S. or the Philippines (Abad,
2001; Pew Research Center, 2012a).
Two processes contribute to the overrepresentation of Christians among Chinese Americans
when compared to Chinese individuals in China. First, a process of self-selection may occur: Christians
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CULTURAL RESOURCES AND HEALTH Ray-Letourneau
living in China may be more likely than their non-Christian counterparts to decide to move to the
United States, where they become part of the religious majority (Pew Research Center, 2012a; Connor,
2012). A disproportionate number of Christians from countries around the world choose to migrate to
the U.S., which is the world's top destination for Christian migrants (Connor, 2012). Second, a process
of religious conversion or “religious switching” is common among immigrant individuals (Pew
Research Center, 2012a, 2012b), especially among those emigrating from China (Yang, 1998). A far
greater proportion of Chinese Americans (43%) report “religious switching” than do Filipino
Americans (26%) or Vietnamese Americans (22%) (Pew Research Center, 2012b).
The reasons for the “wave” of Chinese conversions to Christianity should be viewed within the
broader historical context of dramatic social, political and cultural changes taking place over decades in
China (Yang, 1998, p. 253). In an ethnographic study examining religious conversion among Chinese
Americans, Yang (1998) delineated the sociopolitical processes described by the study participants that
led to an “unprecedented openness toward Christian proselytization” (p. 247). First, a series of events,
including wars, social turmoil, natural disasters, and political campaigns, occurred in China during the
19
th
and 20
th
centuries. These cumulative events, though national in scale, created repeated personal
crises in peoples' lives and often resulted in “unwilling migration” to “strange” places, where life
remained a struggle (p. 249). Migrants' sense of “unrootedness” served to intensify their spiritual needs,
and after experiencing the failure of socialist experiments, many became more open to the belief
systems of Western democracies (p. 249). The promise of “permanence or eternity in the heavenly
world” was a particularly desirable attribute of Christianity to those who had experienced repeated
migrations and traumas (p. 249). At the same time, a process of “coerced modernization” in China
resulted in a fundamental interruption of cultural traditions, leaving many searching for alternate
meaning systems (p. 251). As Chinese individuals in both China and the U.S. became increasingly open
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CULTURAL RESOURCES AND HEALTH Ray-Letourneau
to Christian values, evangelical organizations responded by intensifying their recruitment of Chinese
individuals. Their efforts met with success, largely because Chinese immigrants recognized
conservative Christianity's compatibility with traditional Chinese and Confucian values (i.e., familism,
asceticism, and authoritarian power structure). Though religious conversion among Chinese Americans
was rare during the 1980s, it became a frequent occurrence following the 1989 Tiananmen Square
incident, after which many exiled political dissidents and Chinese scholars studying abroad converted
to Christianity (p. 250). Living in a fast-changing, chaotic world and faced with post-migration
uncertainty, the absolute love and eternal life after death promised by evangelical Christianity was
attractive to many Chinese Americans. Conservative Christianity also met needs for social group
belonging, moral education of children (p. 252), and a distinctive Chinese Christian identity (p. 254).
Therefore, the beneficial effects of religious attendance on self-rated mental health found in the present
study can be interpreted, in part, as Chinese respondents' subjective reactions to the resolution of the
quest for social inclusion and spiritual sustenance. Notably, self-rated mental health was the only
outcome out of the four that was associated with religious participation among Chinese respondents,
indicating that this cultural resource may be more of a benefit to one's subjective state than one's
objective health status.
The singular finding that ran counter to predicted effects of this study was the positive
association between religious attendance and physical health problems, among the full sample of Asian
Americans and among Vietnamese adults. Though not aligned with the cultural resource hypothesis, the
result is consistent with previous findings (e.g., Gorman & Sivaganesan, 2007). Due to the cross-
sectional nature of the data, a temporal direction of causality among the variables cannot be presumed.
Therefore, it is quite possible that the association between religious attendance and poorer health is
indicative of respondents who seek out religious support in times of hardship and pain. In fact, religious
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CULTURAL RESOURCES AND HEALTH Ray-Letourneau
coping is a common reaction to sickness, pain, and disability for many Americans (Gall, 2009; Trevino,
2010; Vallurupalli, 2012; Williams, 2011), including those of Asian descent (Ashing, 2003; Chiu, 2005;
Kwon, 2004; Villero, 2013). Along the same lines, the association between religious attendance and
self-rated mental health could also be a function of the cross-sectional nature of the data: Chinese
respondents who rate their mental health favorably may be more likely to choose to attend religious
meetings and ceremonies. Since there are fewer expectations about regular group participation in
Chinese belief systems compared to Western religions (Liu, 2011; Zeng, 2011), public participation
may be seen as optional or voluntary as part of one's spiritual life and therefore many individuals
engage in home-based rather than temple-based worship activities (Zeng, 2011).
This study examined three types of cultural resources and their effects on Asian American
health. Findings provided some support for the cultural resource hypothesis, specifically among
Filipino and Chinese adults. One of the benefits of taking into account ethnic heterogeneity and
multiple measures of physical and mental health is that differences across groups can be revealed. This
study makes a methodological contribution to the literature on Asian American health by
disaggregating the data by ethnic group, thereby uncovering heterogeneity regarding contributors to
health that otherwise would have been obscured. Thus, the beneficial effects of ethnic identify, native
language proficiency and religious attendance were not the same for all physical and mental health
outcomes nor for all ethnic groups considered. For example, by running separate models for each of the
three largest ethnic groups in the NLAAS data set, it became apparent that the protective effect of
religious attendance on self-rated mental health among the full sample was driven by a strong effect
found among Chinese adults. The effect was not significant among Filipino or Vietnamese adults,
revealing an important distinction between groups. In addition, the finding that religious attendance
was associated with poorer physical health status among the full sample was driven by a strong effect
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CULTURAL RESOURCES AND HEALTH Ray-Letourneau
found among Vietnamese adults. Therefore, it appears that certain cultural resources play more
prominent roles in the health outcomes of specific groups of people, a finding that underscores the
substantial heterogeneity found among Asian Americans.
Despite these strengths, findings from this study should be considered within the context of its
limitations. First, each of the cultural resources was measured by a single-item indicator. While prior
literature supports the inclusion of these constructs as individual items (Alegria, 2004b; Leu, 2011;
Schachter, 2012; Yip, 2008;), it is possible that multiple-item scales would account for the fuller
complexity of each construct and produce more reliable estimates. For example, in the present study
ethnic identity had relevance only for the Filipino group. It is possible that had ethnic identity been
measured differently, for example with a multiple-item scale including items regarding how much time
the respondent prefers to spend with people of the same racial/ethnic descent and how closely they
identify with others of the same descent (Chen & Takeuchi, 2011), its fuller complexity would have
uncovered associations with health for the other ethnic groups. However, when a three-item version of
the variable was used in related analyses (not shown), the results were not substantially different from
those that utilized the single-item measure. Another potential limitation of this study is that the
variables included only constitute a small subset of constructs that could be viewed as cultural
resources. Further research is needed to determine what aspects of cultural life are most related to
health outcomes, and how they might best be operationalized in scientific study. For example,
constructs such as communalism and familism, cultural resources that contribute to health among low-
income white, Latina and African American women (Abdou, 2010; 2012), may have relevance for
Asian American adults as well. Moreover, this study investigated the three largest Asian ethnic groups
represented in the U.S. – Chinese, Filipino, and Vietnamese. Asian Americans from all other countries
were aggregated into a single “Other” group. To further tease out heterogeneity among this diverse
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CULTURAL RESOURCES AND HEALTH Ray-Letourneau
population, it would be helpful to have larger samples to further stratify the sample into smaller
components, such as Indians, Koreans, and Japanese. Finally, the cross-sectional nature of the NLAAS
data employed in this study preclude discussion of temporality or causality in the relationships found
among the variables. Therefore, as alluded to above, it is entirely possible that presence of certain
health statuses might predispose some people to increase their religious participation, for example,
instead of the reverse order predicted by the cultural resource hypothesis. However, prior longitudinal
research supports the present ordering, with religious coping and religious participation impacting
subsequent health (Trevino et al., 2007) and mortality (Zeng, 2011), respectively. Also, in the context of
health-promotion programs and interventions, the direction of effects is less important than the fact that
an association exists at all. For example, since findings revealed that native language proficiency was
beneficial for health outcome for a number of Asian ethnic groups, native language use can be
promoted in policies and programs intended for Asian populations without concerning ourselves with
the temporal order.
Despite these limitations, this study is the first to examine the cultural resource hypothesis
among a nationally representative sample of Asian Americans. The findings underscore the importance
of both internal and external dimensions of culture in shaping health outcomes, and suggest that
encouraging specific cultural practices among Asian American groups can supplement the repertoire of
strategies currently employed by medical and social service providers for health promotion. When
found to serve protective functions among at-risk and minority populations, these cultural resources can
be protected and enhanced, with the ultimate goal of reducing health disparities. The findings indicate
that programs designed to foster cultural resources (i.e., intergenerational socializing groups that
promote native language use or neighborhood action committees that incorporate participants'
expressions of ethnic identity) may improve health among Asian Americans. The present examination
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CULTURAL RESOURCES AND HEALTH Ray-Letourneau
of cultural resources provides a more nuanced understanding of heterogeneity among this diverse
population. While more systematic empirical work is needed to determine which cultural resources are
both health-promoting and amenable to change, the present study highlights the benefits to be gained
from programs that help Asian Americans capitalize on cultural resources, which can be an asset to
their physical and mental health.
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52
Table 2.1.
Descriptive characteristics of Asian Americans in the National Latino and Asian American Study
Gender (Female)
1097 52.6 316 53.6 273 55.5 277 54.6
Age*
18-34 799 39.5 210 31.7 191 35.9 162 30.0
35-54 920 41.3 294 48.8 203 38.7 253 47.4
55-74 321 16.0 78 15.5 95 20.1 92 19.6
75+ 55 3.3 18 4.0 19 5.3 13 2.9
Years in U.S.*
10 or less 602 26.2 152 27.8 91 18.5 210 41.0
11 or more 1036 50.7 321 54.1 257 51.6 292 56.0
Native born 454 23.1 125 18.0 159 29.8 18 3.0
Education*
0-11 years 316 15.1 85 18.7 53 11.6 152 34.2
12 years 371 17.6 96 16.8 97 19.8 115 21.2
13-15 years 529 25.3 117 20.5 168 33.0 129 22.2
16+ years 878 42.0 302 44.0 190 35.6 123 22.4
Income*
Below poverty level 239 12.1 74 14.5 45 10.2 81 17.4
At poverty level 228 9.9 56 10.8 31 5.9 108 20.4
200% of poverty level 226 10.3 54 7.7 52 11.6 79 14.9
300%+ of poverty level 1402 67.7 416 67.0 380 72.3 252 47.3
Ethnic Identity*
Low 277 15.8 94 18.4 80 18.0 39 8.0
High 1806 84.2 502 81.6 425 82.0 477 92.0
Religious Attendance*
Less than weekly 1374 68.1 482 85.7 253 49.1 335 68.3
Weekly or more 682 31.9 100 14.3 249 50.9 181 31.7
Native Language Proficiency*
None to fair 703 35.9 197 32.6 234 46.0 94 16.4
Good or better 1386 64.1 402 67.4 271 54.0 425 83.6
Self-rated Mental Health*
Poor/fair 204 8.9 78 14.5 35 7.2 67 13.0
Good/excellent 1890 91.1 521 85.5 473 92.8 453 87.0
Self-rated Physical Health*
Poor/fair 354 15.8 133 22.6 58 11.8 119 23.7
Good/excellent 1741 84.2 467 77.4 450 88.2 401 76.3
210 10.5 68 11.2 54 10.7 37 7.1
1237 58.2 361 60.6 341 65.8 297 59.7
a = unweighted; b = weighted; c = presence of one or more
*Rao-Scott Chi-Square test of difference between groups is significant
Total sample
(n=2095)
Chinese
(n=600)
Filipino
(n=508)
Vietnamese
(n=520)
Freq
a
%
b
Freq
a
%
b
Freq
a
%
b
Freq
a
%
b
Mental Health Disorder
c
Physical Health Problem
c
*
CULTURAL RESOURCES AND HEALTH Ray-Letourneau
53
Table 2.2.
Correlations between predictor and outcome variables
12 34 567 89 10 11 12
--
2. Age -0.002 --
-0.040 0.098 *** --
4. Education -0.095 *** -0.233 *** 0.073 *** --
5. Income -0.075 *** -0.026 0.126 *** 0.323 *** --
-0.013 0.101 *** -0.219 *** -0.067 ** -0.052 * --
0.046 * 0.134 *** -0.015 0.053 * -0.020 0.084 *** --
0.043 * 0.109 *** -0.572 *** -0.002 -0.021 0.295 *** 0.073 *** --
9. SRMH -0.095 *** -0.179 *** 0.086 *** 0.213 *** 0.163 *** 0.009 0.110 *** -0.018 --
10. SRPH -0.055 * -0.208 *** 0.037 0.158 *** 0.161 *** 0.028 0.032 -0.011 0.608 *** --
11. MHD 0.032 -0.092 *** 0.108 *** 0.014 -0.017 -0.120 *** -0.018 -0.143 *** -0.157 *** -0.098 *** --
12. PHP 0.047 * 0.278 *** 0.153 *** -0.041 0.012 -0.043 0.093 *** -0.084 *** -0.128 *** -0.231 *** 0.100 *** --
Note: *p<.05. **p<.01. ***p<.001. a=male is referent.
1. Gender
a
3. Years in
U.S.
6. Ethnic
Identity
7. Religious
Attendance
8. Native
Language
Proficiency
CULTURAL RESOURCES AND HEALTH Ray-Letourneau
54
Table 2.3.
Regression analyses predicting Self-Rated Mental Health.
BSE B SE B SE B SE
Step 1
Intercept 3.30 *** 0.19 2.54 *** 0.26 3.37 *** 0.34 4.31 *** 0.31
-0.20 ** 0.06 -0.30 ** 0.11 0.05 0.09 -0.15 0.10
Age -0.01 *** 0.00 -0.01 0.00 0.00 * 0.00 -0.02 *** 0.00
Vietnamese 0.14 * 0.06 -- -- --
Filipino 0.40 *** 0.10 -- -- --
Other 0.47 *** 0.06 -- -- --
Years in U.S. 0.03 0.02 0.13 *** 0.04 -0.03 0.03 0.10 * 0.04
Education 0.04 ** 0.01 0.06 *** 0.02 0.06 *** 0.02 -0.01 0.02
Income 0.02 * 0.01 0.02 * 0.01 0.01 0.01 0.04 * 0.02
0.12 0.16 0.06 0.12
Step 2
Ethnic Identity -0.02 0.04 -0.08 0.08 -0.02 0.06 0.13 0.08
0.09 *** 0.02 0.11 * 0.04 0.06 0.05 0.01 0.04
0.06 * 0.02 0.01 0.05 0.11 *** 0.03 0.31 *** 0.07
0.14 0.18 0.10 0.17
Total sample
(n=2090)
Chinese
(n=597)
Filipino
(n=507)
Vietnamese
(n=519)
Gender
a
Ethnic Group
b
R
2
Religious
Attendance
Native Language
Proficiency
R
2
Note: *p<.05. **p<.01. ***p<.001. a=male is referent. b=Chinese is referent.
CULTURAL RESOURCES AND HEALTH Ray-Letourneau
55
Table 2.4.
Logistic regression analyses predicting Mental Health Disorder.
Chinese (n=598) Filipino (n=507) Vietnamese (n=519)
OR 95% CI OR 95% CI OR 95% CI OR 95% CI
Step 1
1.24 ( 0.81 , 1.90 ) 1.86 ( 0.99 , 3.47 ) 0.83 ( 0.48 , 1.43 ) 0.59 ( 0.23 , 1.52 )
Age 0.98 ( 0.97 , 0.99 ) 0.99 ( 0.96 , 1.02 ) 0.97 ( 0.95 , 1.00 ) 0.99 ( 0.96 , 1.02 )
Vietnamese 0.63 ( 0.39 , 1.01 ) -- -- -- -- -- --
Filipino 0.82 ( 0.52 , 1.29 ) -- -- -- -- -- --
Other 0.84 ( 0.52 , 1.34 ) -- -- -- -- -- --
Years in U.S. 1.28 ( 1.12 , 1.46 ) 1.45 ( 1.17 , 1.78 ) 1.46 ( 1.19 , 1.80 ) 1.32 ( 1.05 , 1.66 )
Education 0.99 ( 0.93 , 1.04 ) 0.97 ( 0.88 , 1.08 ) 0.97 ( 0.82 , 1.15 ) 1.03 ( 0.95 , 1.11 )
Income 0.98 ( 0.93 , 1.02 ) 0.93 ( 0.87 , 0.99 ) 1.06 ( 0.98 , 1.14 ) 1.00 ( 0.93 , 1.07 )
30.77 17.66 39.94 17.69
Step 2
Ethnic Identity 0.87 ( 0.69 , 1.09 ) 0.92 ( 0.71 , 1.18 ) 0.64 ( 0.47 , 0.88 ) 0.66 ( 0.38 , 1.15 )
1.05 ( 0.86 , 1.28 ) 1.09 ( 0.83 , 1.44 ) 0.95 ( 0.78 , 1.16 ) 0.82 ( 0.57 , 1.17 )
0.84 ( 0.72 , 0.99 ) 0.73 ( 0.58 , 0.91 ) 0.93 ( 0.78 , 1.10 ) 0.65 ( 0.41 , 1.01 )
50.37 56.68 84.08 124.07
Total sample
(n=2091)
Gender
a
Ethnic Group
b
Wald X
2
Religious
Attendance
Native Language
Proficiency
Wald X
2
Note: a=male is referent. b=Chinese is referent.
CULTURAL RESOURCES AND HEALTH Ray-Letourneau
56
Table 2.5.
Regression analyses predicting Self-Rated Physical Health.
BSE B SE B SE B SE
Step 1
Intercept 3.38 *** 0.18 2.71 *** 0.32 3.61 *** 0.24 4.21 *** 0.34
-0.13 * 0.06 -0.20 * 0.10 0.04 0.08 -0.17 0.11
Age -0.01 *** 0.00 -0.01 * 0.00 -0.01 *** 0.00 -0.02 *** 0.00
Vietnamese 0.13 0.08 -- -- --
Filipino 0.31 *** 0.09 -- -- --
Other 0.38 *** 0.08 -- -- --
Years in U.S. 0.02 0.02 0.12 ** 0.04 -0.08 ** 0.02 0.03 0.05
Education 0.02 0.01 0.04 * 0.02 0.03 0.02 -0.02 0.02
Income 0.02 ** 0.01 0.02 * 0.01 0.04 *** 0.01 0.05 * 0.02
0.09 0.12 0.10 0.10
Step 2
Ethnic Identity 0.04 0.04 0.03 0.08 -0.02 0.06 0.14 0.07
0.02 0.03 0.06 0.04 -0.06 0.03 0.04 0.05
0.01 0.03 -0.06 0.04 0.09 * 0.04 0.34 *** 0.06
0.10 0.12 0.12 0.17
Total sample
(n=2091)
Chinese
(n=598)
Filipino
(n=507)
Vietnamese
(n=519)
Gender
a
Ethnic Group
b
R
2
Religious
Attendance
Native Language
Proficiency
R
2
Note: *p<.05. **p<.01. ***p<.001. a=male is referent. b=Chinese is referent.
CULTURAL RESOURCES AND HEALTH Ray-Letourneau
57
Table 2.6.
Logistic regression analyses predicting Physical Health Problem.
Total sample (n=2091) Chinese (n=598) Filipino (n=507) Vietnamese (n=519)
OR 95% CI OR 95% CI OR 95% CI OR 95% CI
Step 1
1.25 ( 1.00 , 1.55 ) 1.09 ( 0.85 , 1.39 ) 1.25 ( 0.84 , 1.87 ) 1.36 ( 0.84 , 2.21 )
Age 1.04 ( 1.04 , 1.05 ) 1.05 ( 1.03 , 1.06 ) 1.05 ( 1.04 , 1.07 ) 1.04 ( 1.02 , 1.06 )
Vietnamese 1.01 ( 0.77 , 1.33 ) -- -- -- -- -- --
Filipino 1.14 ( 0.83 , 1.57 ) -- -- -- -- -- --
Other 0.75 ( 0.57 , 0.98 ) -- -- -- -- -- --
Years in U.S. 1.28 ( 1.18 , 1.39 ) 1.32 ( 1.13 , 1.54 ) 1.13 ( 0.96 , 1.32 ) 1.03 ( 0.84 , 1.27 )
Education 1.02 ( 0.99 , 1.05 ) 1.01 ( 0.95 , 1.07 ) 1.09 ( 1.03 , 1.15 ) 1.05 ( 1.00 , 1.11 )
Income 0.99 ( 0.97 , 1.02 ) 1.01 ( 0.98 , 1.04 ) 1.01 ( 0.96 , 1.06 ) 0.98 ( 0.91 , 1.05 )
206.54 68.21 78.78 45.41
Step 2
Ethnic Identity 0.95 ( 0.81 , 1.12 ) 1.11 ( 0.78 , 1.58 ) 0.95 ( 0.79 , 1.13 ) 0.76 ( 0.55 , 1.05 )
1.09 ( 1.00 , 1.19 ) 1.12 ( 0.94 , 1.34 ) 0.98 ( 0.82 , 1.16 ) 1.22 ( 1.08 , 1.38 )
0.83 ( 0.76 , 0.91 ) 0.90 ( 0.75 , 1.08 ) 0.95 ( 0.80 , 1.13 ) 0.65 ( 0.50 , 0.87 )
269.53 101.48 81.67 79.26
Gender
a
Ethnic Group
b
Wald X
2
Religious
Attendance
Native Language
Proficiency
Wald X
2
Note: a=male is referent. b=Chinese is referent.
CULTURAL RESOURCES AND HEALTH Ray-Letourneau
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CHAPTER 3 (Study 2):
The Impact of Duration of Residence in the U.S. on Asian American Health:
Do Cultural Resources Mediate Health Decline?
Despite the many stressors associated with moving to a new country, immigrants tend to arrive
in the U.S. with better physical and mental health than their native-born counterparts (Alegría, 2004;
2007; Gong, 2006; Kimbro, 2012; Markides, 1986; Mossakowski, 2003, 2007; Rumbaut, 1996;
Takeuchi, 2002; Vega, 1991). This phenomenon is referred to as the “immigrant paradox,”
“epidemiological paradox,” and “healthy immigrant effect” and has been documented among a host of
populations from a variety of countries of origin (Alegría, 2004; 2007; Caplan, 2007; Chen, 2006;
Gong, 2006; Lincoln, 2007; Kimbro, 2012; Markides, 1986; Mossakowski, 2003, 2007; Rumbaut,
1996; Suárez-Orozco, 2008; Takeuchi, 2002; Vega, 1991). Over time the health advantage of
immigrants erodes, such that the health of long-term residents becomes comparable to that of their
U.S.-born counterparts (Alegría, 2007; Finch, 2003; Frisbie, 2001; Zhang, 2009). A number of reasons
have been proposed to explain this health decline, including social stresses and difficulties with
adjustment. However, results from empirical studies have been equivocal; thus, it remains unclear
whether there are protective factors that might inhibit this health decline (Takeuchi, Gong & Gee,
2012). The goal of this chapter is to examine the extent to which the relationship between length of
residence in the U.S. and mental and physical health is moderated by cultural resources among Asian
Americans.
The Effects of Longer Duration in U.S. on Immigrant Health
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A number of researchers have sought to explain why immigrants, who arrive in the U.S. with
superior health status, suffer health declines with longer residence in the U.S. Research conducted on
earlier cohorts of immigrants (i.e., those that entered during the late 19
th
and early 20
th
centuries)
yielded a body of literature referred to as “classic assimilation theory,” which described a process of
immigrant accommodation and incorporation into new environments (Gordon, 1964; Park, 1921). The
classic assimilation framework was based on observations of immigrants who shed their traditional
cultures, behaviors, and attitudes, and replaced them with those of the new host society in order to
attain economic success and well-being (Gong, 2006; Portes, 2006). However, the improvements
documented among prior groups of immigrants in terms of their financial and health outcomes are not
always the case among more recent cohorts of immigrants (Portes & Rumbaut, 2006). Late-20th and
early-21st century immigrants display wider variation than their predecessors in terms of health and
socioeconomic outcomes. While some immigrants maintain good health, many more are at increased
risk of health problems with longer residence in the U.S. (Alegría, 2007; Finch, 2003; Frisbie, 2001;
Zhang, 2009).
Many scholars have offered hypotheses to explain immigrant health declines. First, some
researchers suggest that immigrants change their beliefs, values, and lifestyles to adapt to the new host
culture, and that these changes negatively impact health status (Cook, 2009; Ma, 2004). Others suggest
that increasing exposure to societal stressors such as discrimination has deleterious effects on health
(Caplan, 2007; Gee, 2002; Gong, 2006; Landale, 1999; Mossakowski, 2007; Noh, 2003; Portes, 1984).
Specifically, over time immigrants often gain heightened awareness of differential treatment, have
more exposure to mainstream society, and are more likely to interpret interactions as discriminatory, all
of which increase their risk for health problems (Cook, Alegría, Lin, & Guo, 2009). Growing up in a
social context in which one was part of the racial majority, then migrating into a “minority” status can
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be psychologically jarring, especially when entering a racially stratified society such as the U.S.
(Mossakowski, 2007). Finally, mental health problems often emerge when family conflict is sparked by
increasing cultural discongruence between generations (Cook, Alegría, Lin, & Guo, 2009).
In addition to identifying the reasons for the decline in immigrant health, it is also important to
determine whether protective factors exist that might prevent or curtail the downward trajectory. The
cultural resource hypothesis shows promise for explaining why some members of disadvantaged
populations remain healthy compared to others facing similar circumstances (Abdou, 2010; 2012). It is
possible that cultural resources operate by buffering the cumulative negative effects on health by the
social and behavioral risk factors described above, such as discrimination and family conflict.
Alternatively, the presence or salience of protective cultural values might recede with longer residence
in the U.S.; the psychological distance from one's country of origin may feel greater over time.
However, certain aspects of culture might prove to be less vulnerable to “erosion” than others (Sue,
Mak, & Sue, 1998, p. 294). Ethnic identity can become weaker over time in a new country (Rosenthal
& Feldman, 1992), as can native language proficiency (García, 2003; Tse, 2001; Wong Fillmore, 1991).
Similarly, religious participation decreases substantially after international migration (Connor, 2008).
However, it remains unclear whether these decreases differentially affect Asian American health status.
The aim of this study is to examine the interactive effects of three cultural resources with duration of
time in the U.S. health in order to better understand which cultural resources are the most likely to
protect health over time. Specifically, this study examines whether ethnic identity, native language
proficiency, and religious attendance moderate the effects of time in the U.S. on mental and physical
health among a representative sample of Asian American adults.
Methods
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Data
Data for this analysis come from the National Latino and Asian American Study (NLAAS),
which employed a multiframe, stratified area probability sampling design and was collected during
2002-2003 (Alegría, 2004a, 2004b; Heeringa, 2004; Pennell, 2004). The NLAAS included a nationally
representative sample of Asian Americans aged 18 and over and used trained, multilingual interviewers
to implement the survey in the respondent's preferred language. The full data set contains 2,095 Asian
American adults and the present analytic sample is comprised of the 2,038 respondents who had
complete data on included variables.
Measures
Dependent variables. Mental health disorder (MHD) was a composite of 11 International
Classification of Diseases (ICD) disorders including depressive, anxiety, and substance use disorders.
Respondents were classified as having a disorder if they met criteria for any of the following diagnoses:
major depressive disorder or dysthymia; panic disorder, generalized anxiety disorder or post-traumatic
stress disorder; alcohol abuse or dependence and drug abuse or dependence. Responses were
dichotomized so that 0 = no disorder and 1 = 1 or more disorder. Physical health problems (PHP) were
assessed using a composite of chronic health conditions from the World Health Composite International
Diagnostic Interview (CIDI). The measure included cardiovascular and respiratory conditions, pain,
diabetes, cancer, and epilepsy, among others. The number of health problems in the NLAAS Asian
American sample ranged from 0 to 10 (Kim, Chen, & Spencer, 2012). Responses were dichotomized so
that 0 = no health problem and 1 = 1 or more problems.
Independent variables. Cultural resources included in this study were ethnic identity, native
language proficiency, and religious attendance. Each measure consisted of a single item with Leikert-
style response options, with higher scores reflecting a higher level of each construct. Ethnic identity
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was measured by the question “How close do you feel, in your ideas and feelings about things, to other
people of the same racial and ethnic descent?” (Félix-Ortiz, Newcomb, & Myers, 1994). Responses
ranged from 1 = “not at all” through 4 = “very close.” Native language proficiency was measured by
the question “How well do you speak Mandarin/Cantonese/Tagalog/Vietnamese/Other Asian
language?” Responses ranged from 1 = “poor” through 4 = “excellent.” Religious attendance was
measured by the question “How often do you usually attend religious services?” Response options were
1 = “never” through 5 = “more than once a week.”
Duration of residence in the U.S. was measured by a single item (1 = less than 5 years, 2 = 5-10
years, 3 = 11-20 years, 4 = 20+ years, 5 = entire life). Sociodemographic characteristics included
gender (self-identified, 0 = male; 1 = female); age (measured continuously); ethnicity (categorized into
four groups: Chinese, Filipino, Vietnamese, and Other Asian; Chinese is referent); educational
attainment (measured continuously); income (income-to-needs ratio, calculated by dividing 12-month
household income by the federal poverty threshold for the corresponding household size and
composition, based on the 2000 U.S. Census [Chen & Takeuchi, 2011]).
Data Analytic Strategy
Hierarchical multivariate logistic regression analyses were conducted to test the hypothesis that
cultural resources moderate the effects of duration of residence in U.S. on mental and physical health.
The first step of the analysis estimated the relationship between sociodemographic factors, cultural
resources and mental and physical health. The second step included interaction terms for each cultural
resource variable with Years in U.S. An indicator of model fit (Wald chi-square) was used to examine
model improvement between the first and second steps of the analysis. All models were estimated using
the full sample (n = 2,038) first and then stratified by ethnic group (Chinese, Filipino, and Vietnamese).
Since two outcomes (MHD and PHP) were analyzed, a total of eight analyses were conducted. All
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analyses were performed using the “surveyreg” procedure in SAS software, version 9.2 (SAS Institute
Inc., 2008). The reported standard errors take into account the complex multistage survey design of the
NLAAS sample, including unequal probabilities of selection, nonresponse, and poststratification.
Results
Characteristics of the sample are presented in Table 3.1. Among the full sample of Asian
Americans, more than half (53%) were female, over three-fourths (81%) were 54 years old or less, and
nearly one-quarter (23%) were born in the U.S. About one-quarter (26%) of respondents were born
outside of the U.S. and arrived within the past 10 years, while about half (51%) arrived over 10 years
prior. Over two-thirds (67%) had more than a high school education and a similar proportion (68%) had
an income level at least three times above the national poverty line. In terms of ethnic identity, 84%
reported feeling “close” or “very close” with others of their ethnic background. Nearly one-third (32%)
reported attending religious services at least weekly, and 64% reported a “good” or “excellent” level of
native language proficiency. Eleven percent of respondents endorsed at least one mental health disorder
and 58% endorsed at least one physical health problem. Significant ethnic group differences were
found for a number of variables: age, years in U.S., education, income, and physical health problems.
The distributions of the three cultural resources also varied by ethnic group; with the highest level of
ethnic identity and native language proficiency reported by Vietnamese adults, and the highest level of
weekly religious attendance reported by Filipino adults.
Results from the logistic regressions predicting mental health and physical health are presented
in Tables 3.2 and 3.3, respectively (non-significant interaction models and terms not shown).
Predicting Mental Health Disorder
Table 3.2 displays the association between sociodemographic variables, cultural resources and
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mental health disorder (MHD) using the full sample of Asian Americans. Findings revealed that older
age was associated with lower odds of MHD (OR = 0.98, 95% CI = 0.97, 0.99). The cross-product
between ethnic identity and time in U.S. was added to test the extent to which the relationship between
ethnic identity and MHD is moderated by time in the U.S. Findings revealed a significant interaction
effect (OR = 0.88, 95% CI = 0.72, 1.00, p < .05). Specifically, higher levels of ethnic identity increased
the risk for MHD for those with fewer years in the U.S. and decreased the risk for MHD for those
Asian residing in the U.S. for a longer period of time (Figure 3.1).
Predicting Physical Health Problems
Table 3.3 displays estimates of the association between sociodemographic variables, cultural
resources and physical health problems using the full sample of Asian Americans. Results from the
logistic regression revealed that female gender (OR = 1.26, 95% CI = 1.01, 1.57), older age (OR =
1.05, 95% CI = 1.04, 1.06), more years of residence in the U.S. (OR = 1.15, 95% CI = 1.04, 1.26), and
religious attendance (OR = 1.09, 95% CI = 1.00, 1.19) were associated with higher odds of physical
health problems among all Asian Americans. Native language proficiency was associated with lower
odds of physical health problems (OR = 0.83, 95% CI = 0.76, 0.91). To test whether time in the U.S.
moderates the relationship between cultural resources and physical health problems, the cross product
between native language proficiency and years in U.S. was added to the model. Findings indicated that
the interaction was significant (OR = 0.93, 95% CI = 0.86, 1.00, p < .05), with the negative association
between proficiency and physical health problems being more pronounced for those with longer
residence in the U.S. compared to those with fewer years (Figure 3.2).
Table 3.3 also displays the results of the single interaction model that was significant when the
sample was stratified by ethnic group. Among Vietnamese adults, older age (OR = 1.05, 95% CI =
1.03, 1.07), higher levels of education (OR = 1.07, 95% CI = 1.01, 1.12), and religious attendance (OR
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CULTURAL RESOURCES AND HEALTH Ray-Letourneau
= 1.22, 95% CI = 1.08, 1.38) predicted greater risk for physical health problems. Native language
proficiency decreased one's odds of having a physical health problem (OR = 0.65, 95% CI = 0.50,
0.87). An interaction term was added to the model to test the extent to which time in the U.S. moderates
the relationship between cultural resources and physical health. The interaction between ethnic identity
and years in U.S. was significant (OR = 1.37, 95% CI = 1.13, 1.67); ethnic identity was associated with
lower risk of health problems only among Vietnamese adults who have fewer years of residence in the
U.S. (Figure 3.3).
Discussion
This is the first study to examine the moderating role of cultural resources (e.g., ethnic identity,
native language proficiency, and religious attendance) in the relationship between duration of residence
in the U.S. and mental and physical health among Asian Americans. Overall, results provide some
support for the cultural resource hypothesis, and suggest that the effects of cultural resources on health
are not uniform. Rather, they vary based on one's ethnic sub-group, duration of time spent in the new
host country, and health outcome under investigation. The results indicate that longer residence in the
U.S. does not necessarily lead to an increase in health problems, contrary to prior research findings
supporting the “immigrant paradox” and subsequent health declines (Alegría, 2007; Finch, 2003;
Frisbie, 2001; Rumbaut 1997a, 1997b; Zhang, 2009). Longer duration of residence in the U.S. is often
detrimental to health; however, findings from this study suggest that health declines can be offset by
the presence of certain cultural resources, particularly ethnic identity and native language proficiency.
The pattern of results presents a more nuanced picture of Asian American health than has been
previously available, and contributes to the literature documenting Asian American heterogeneity.
The finding that ethnic identity is protective for the mental health of long-term residents but
74
CULTURAL RESOURCES AND HEALTH Ray-Letourneau
detrimental for more recent arrivals is consistent with previous studies reporting countervailing effects
of ethnic identity on health (Chae, 2008a; 2008b; Yip, 2008). The relationship between ethnic identity,
time in U.S., and health may be explained through ethnic identity's effects on an individual's
experience or perception of discrimination (Gee, 2009; Lee, 2005; Yip, 2008). Discrimination tends to
“weather” away the immigrant health advantage (Geronimus, 2006; Gee, 2009), as it exerts stronger
effects over time (Gee, 2008; Gee, 2009). However, the harmful effects of discrimination on health can
be mitigated by having higher levels of ethnic identity (Chae, 2008a; 2008b; Mossakowski, 2003; Noh,
1999; Sellers, 2003a). Therefore, as immigrants reside in the U.S. for longer duration and have
increasing exposure to discrimination, the protective effects of ethnic identity may become more
pronounced.
Among Vietnamese adults, the protective effects of ethnic identity on physical health were
strongest among recent arrivals. This finding is consistent with previous studies reporting that cultural
resources exert strongest effects among members of highly disadvantaged populations (Abdou, 2010,
2012; Campos, 2008) as well as empirical findings indicating that the association between ethnic
identity and health is strongest among those occupying the most disadvantaged statuses in society
(Phinney, 1990; Ong, 2006; Operario, 2001; Rumbaut, 1994; Simons, 2002; Walker, 2008). Vietnamese
Americans constitute the most disadvantaged group of the major Asian ethnic groups, according to
various socioeconomic indicators. Not only do they have lower levels of educational attainment and
higher poverty rates than other Asian American groups (Terrazas & Batog, 2010), they also report the
poorest English proficiency and highest levels of financial strain and acculturative stress (Franks, 1990;
Mui, 2006; Terrazas , 2010). Furthermore, Vietnamese adults who most recently arrived in the U.S.
present the most extreme cases of these vulnerabilities: they have poorer socioeconomic status, lower
English proficiency, and worse financial strain and acculturative stress than long-duration Vietnamese
75
CULTURAL RESOURCES AND HEALTH Ray-Letourneau
adults (analyses not shown).
Ethnic identity may be more protective for recent arrivals than those with longer residence
because recent arrivals tend to have higher levels of ethnic identity (Arcia, 2001; Mossakowski, 2007)
and have less time or potentially less interest in integrating into mainstream U.S. culture. In addition,
many recent arrivals are more comfortable living in an ethnic community with those who share their
language, culture and worldview (Mazumdar, Mazumdar, Docuyanan & McLaughlin, 2000); which, to
some extent, limits the opportunity for integration and acculturation. However over time, these
individuals may interact with the broader society (i.e., housing, employment, school), increasing
opportunities for integration and acculturation, and potentially, lower levels of ethnic identity, which is
an important protective factor against the negative health effects of living in what may be perceived as
an antagonistic and discriminatory environment (Mereish, 2011; Mossakowski, 2003; Yip, 2008).
The finding that the protective effects of native language proficiency for physical health are
more pronounced for those with longer residence in the U.S. is consistent with findings from studies
examining immigrant health (Portes, 2002, 2006; Yee, 2009). Health advantages related to native
language proficiency may be due, in part, to the benefits to family communication patterns and family
cohesion (Portes, 2002, 2006; Yee, 2009). But, the reason for the stronger language-health relationship
for those with longer residence in the U.S. compared to recent arrivals warrants additional explanation.
Patterns of residential mobility and linguistic isolation may help to elucidate this finding.
The act of migration itself has been characterized as an “ecological transition” (Bronfenbrenner,
1977). Often, immigrants to the U.S. initially settle in urban ethnic enclaves or “gateway”
communities, with many people of the same ethnic background who share similar cultural practices,
tastes, and values (Miller, 2009; Mazumdar, 2000; Pastor, 2010; Singer, 2004). These ethnic
communities can provide social support, connection to employment networks and other economic
76
CULTURAL RESOURCES AND HEALTH Ray-Letourneau
opportunities. They also provide other health-promoting community assets, including grocery stores,
pharmacies, places of worship, and medical services that serve their communities in a culturally and
linguistically appropriate manner (Finch & Vega, 2003; Kandula, 2009; Kang, 2009; Mazumdar, 2000;
Sam, 2005; Viruell-Fuentes, 2007). Over time, many residents of enclave neighborhoods choose to
move to communities with better housing and schools (Alba, 1999; Funkhouser, 2000; Singer, 2004)
and denser service sector employment opportunities (Marcelli, 2004). While for many, such residential
movement is reflective of “upward mobility,” “spatial assimilation,” and attainment of the “American
Dream” (Alba, 1999; Clark, 2003; Myers, 2007), the move from fairly homogenous enclaves into more
diverse or majority-white communities can also result in feelings of interpersonal distance, cultural
discontinuity, and anomie (Katz, 2001; Sampson, 2008; Vega & Rumbaut, 1991). Immigrants may also
face increased exposure to xenophobia, racial bias, and discrimination in their new neighborhoods
(Caplan, 2007; Gee, 2009; Ramirez, 2009; Syed, 2011; Vega, 1991). Immigrants who lose access to
familiar cultural touchstones and social networks are at greater risk of acculturative stress and social
isolation (Arcia, 2001; Domínguez, 2008; Litwin, 1997; Weine, 1998; Miller, 2009; Spoonley, 2005).
All of these factors have been linked to declines in health (Gee, 2009; Hovey, 2000; John, 2012; Kang,
2009; Kessler, 1999; Leu, 2011; McBride, 1996; Spoonley, 2005; Syed, 2011). For instance, compared
to Korean immigrant elders living in an ethnic enclave in New York City, those living in “mainstream
communities” in Arizona had more medical conditions and nearly 40 percent higher incidence rates of
depression, a finding that was largely explained by communication issues (Kang, Domanski, & Moon,
2009). However, immigrants who maintain proficiency in their native language preserve a link to their
cultural identity and remain able to communicate with others with a shared ethnic heritage and
worldview (Kang, 2012; Lee, 2002). This preservation of cultural connection may offset the health
declines typically associated with acclimating to a new host society, and it makes sense that this effect
77
CULTURAL RESOURCES AND HEALTH Ray-Letourneau
would gain strength with longer duration of residence in the U.S., as demonstrated in this study.
Limitations
These findings should be considered in light of several limitations. First, it is important to
interpret the results with caution because the NLAAS data were cross-sectional and therefore do not
permit the examination of causal relationships. Given that there are no longitudinal studies of large
samples of Asian Americans that include cultural resource variables, this study represents an important
first step in examining the interactions between cultural resources and duration of residence in the U.S.
among Asian Americans. However, since time (operationalized as duration of residence in the U.S.) is a
central component of the main research question in this study, examination of longitudinal data will be
an important next step. This would facilitate improved understanding of how changes in levels of
cultural resources precipitate changes in health status. Also, each of the cultural resources was
measured by a single-item indicator. While prior literature supports the inclusion of these constructs as
individual items (Alegria, 2004b; Leu, 2011; Schachter, 2012; Yip, 2008;), it is possible that multiple-
item scales would account for the fuller complexity of each construct and produce more reliable
estimates. Moreover, the cultural resource variables included in this study only constitute a small subset
of constructs that could be viewed as important cultural contributors to health. Further research is
needed to determine what aspects of cultural life are most related to health outcomes among Asian
Americans, and how they might best be operationalized in scientific study. Lastly, respondents' age at
migration was not accounted for in these analyses. Although it was excluded for reasons of
multicollinearity, age at migration might warrant inclusion in future research, since the timing of
migration in the life course (i.e., during childhood, adolescence, or adulthood) is an important factor in
how contributors to health operate (see Gong, Xu, Fujishiro, & Takeuchi, 2011).
Conclusions
78
CULTURAL RESOURCES AND HEALTH Ray-Letourneau
This study demonstrates that the health declines often observed among immigrant populations
are not a foregone conclusion. Asian Americans' connection to cultural resources can increase their
likelihood of maintaining good health, even after many years of living in the United States. A major
finding is that maintenance of identification with one's ethnic group and proficiency in one's native
language seem to have protective effects on mental and physical health, respectively, especially for
Asian Americans who have lived in the U.S. for longer periods of time. These findings are suggestive
not only of the health-benefiting nature of cultural resources, but also as predicted by the cultural
resource hypothesis, that the most pronounced effects may be found among those for whom poorest
health is expected. Strengthening and supporting cultural identities and communities can increase the
ease with which ethnic minority groups acclimate to the U.S. and maintain their health and well-being
over time. Health and social service providers should craft interventions and policies that are attuned to
and incorporate such cultural resources as a practical way to improve acceptability of services and
improve long-term health outcomes among this large and growing population.
79
CULTURAL RESOURCES AND HEALTH Ray-Letourneau
80
Table 3.1.
Descriptive characteristics of Asian Americans in the National Latino and Asian American Study
Gender (Female)
1097 52.6 316 53.6 273 55.5 277 54.6
Age*
18-34 799 39.5 210 31.7 191 35.9 162 30.0
35-54 920 41.3 294 48.8 203 38.7 253 47.4
55-74 321 16.0 78 15.5 95 20.1 92 19.6
75+ 55 3.3 18 4.0 19 5.3 13 2.9
Years in U.S.*
10 or less 602 26.2 152 27.8 91 18.5 210 41.0
11 or more 1036 50.7 321 54.1 257 51.6 292 56.0
Native born 454 23.1 125 18.0 159 29.8 18 3.0
Education*
0-11 years 316 15.1 85 18.7 53 11.6 152 34.2
12 years 371 17.6 96 16.8 97 19.8 115 21.2
13-15 years 529 25.3 117 20.5 168 33.0 129 22.2
16+ years 878 42.0 302 44.0 190 35.6 123 22.4
Income*
Below poverty level 239 12.1 74 14.5 45 10.2 81 17.4
At poverty level 228 9.9 56 10.8 31 5.9 108 20.4
200% of poverty level 226 10.3 54 7.7 52 11.6 79 14.9
300%+ of poverty level 1402 67.7 416 67.0 380 72.3 252 47.3
Ethnic Identity*
Low 277 15.8 94 18.4 80 18.0 39 8.0
High 1806 84.2 502 81.6 425 82.0 477 92.0
Religious Attendance*
Less than weekly 1374 68.1 482 85.7 253 49.1 335 68.3
Weekly or more 682 31.9 100 14.3 249 50.9 181 31.7
Native Language Proficiency*
None to fair 703 35.9 197 32.6 234 46.0 94 16.4
Good or better 1386 64.1 402 67.4 271 54.0 425 83.6
Self-rated Mental Health*
Poor/fair 204 8.9 78 14.5 35 7.2 67 13.0
Good/excellent 1890 91.1 521 85.5 473 92.8 453 87.0
Self-rated Physical Health*
Poor/fair 354 15.8 133 22.6 58 11.8 119 23.7
Good/excellent 1741 84.2 467 77.4 450 88.2 401 76.3
210 10.5 68 11.2 54 10.7 37 7.1
1237 58.2 361 60.6 341 65.8 297 59.7
a = unweighted; b = weighted; c = presence of one or more
*Rao-Scott Chi-Square test of difference between groups is significant
Total sample
(n=2095)
Chinese
(n=600)
Filipino
(n=508)
Vietnamese
(n=520)
Freq
a
%
b
Freq
a
%
b
Freq
a
%
b
Freq
a
%
b
Mental Health Disorder
c
Physical Health Problem
c
*
CULTURAL RESOURCES AND HEALTH Ray-Letourneau
81
Table 3.2.
OR 95% CI
Step 1
1.20 ( 0.76 , 1.90 )
Age 0.98 ( 0.97 , 0.99 )
Vietnamese 0.68 ( 0.38 , 1.16 )
Filipino 0.79 ( 0.46 , 1.46 )
Other 0.80 ( 0.49 , 1.37 )
Years in U.S. 1.12 ( 0.75 , 1.95 )
Education 0.98 ( 0.93 , 1.05 )
Income 0.98 ( 0.94 , 1.03 )
Ethnic Identity 0.87 ( 0.82 , 2.37 )
Religious Attendance 1.05 ( 0.60 , 1.31 )
Native Language Proficiency 0.84 ( 0.44 , 1.05 )
50.37
Step 2
0.88 ( 0.72 , 1.00 )
-- --
-- --
64.07
Logistic regression analysis predicting mental
health disorder.
Total sample
(n=2038)
Gender
a
Ethnic Group
b
Wald X
2
Years in U.S. x
Ethnic Identity
Years in U.S. x
Religious Attendance
Years in U.S. x
Native Language Proficiency
Wald X
2
Note: a=male is referent. b=Chinese is referent.
CULTURAL RESOURCES AND HEALTH Ray-Letourneau
82
Table 3.3
Logistic regression analyses predicting physical health problem.
Vietnamese (n=511)
OR 95% CI OR 95% CI
Step 1
1.26 ( 1.01 , 1.57 ) 1.35 ( 0.83 , 2.18 )
Age 1.05 ( 1.04 , 1.06 ) 1.05 ( 1.03 , 1.07 )
Vietnamese 1.01 ( 0.75 , 1.37 ) --
Filipino 0.99 ( 0.71 , 1.38 ) --
Other 0.69 ( 0.51 , 0.93 ) --
Years in U.S. 1.15 ( 1.04 , 1.26 ) 0.95 ( 0.76 , 1.18 )
Education 1.02 ( 0.98 , 1.05 ) 1.07 ( 1.01 , 1.12 )
Income 1.00 ( 0.97 , 1.03 ) 0.98 ( 0.91 , 1.05 )
Ethnic Identity 0.95 ( 0.81 , 1.12 ) 0.76 ( 0.55 , 1.05 )
Religious Attendance 1.09 ( 1.00 , 1.19 ) 1.22 ( 1.08 , 1.38 )
Native Language Proficiency 0.83 ( 0.76 , 0.91 ) 0.65 ( 0.50 , 0.87 )
269.53 79.26
Step 2
-- -- 1.37 ( 1.13 , 1.67 )
-- -- -- --
0.93 ( 0.86 , 1.00 ) -- --
305.26 151.82
Total sample
(n=2038)
Gender
a
Ethnic Group
b
Wald X
2
Years in U.S. x
Ethnic Identity
Years in U.S. x
Religious Attendance
Years in U.S. x
Native Language Proficiency
Wald X
2
Note: a=male is referent. b=Chinese is referent.
CULTURAL RESOURCES AND HEALTH Ray-Letourneau
Figure 3.1.
Mental health disorder predicted by the interaction of ethnic identity and duration of residence in the
U.S. among Asian Americans.
Figure 3.2.
Physical health problem predicted by the interaction of native language proficiency and duration of
residence in the U.S. among Asian Americans.
83
CULTURAL RESOURCES AND HEALTH Ray-Letourneau
Figure 3.3.
Physical health problem predicted by the interaction of ethnic identity and duration of residence in the
U.S. among Vietnamese Americans.
84
CULTURAL RESOURCES AND HEALTH Ray-Letourneau
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Chapter 4 (Study 3):
A Latent Class Analysis of Asian Americans, Health and Ethnic Identity
In recent years, the availability of nationally representative data on Asian Americans paved the
way for a proliferation of empirical research documenting a wider range of health statuses among this
diverse group than was previously known. For decades, popular culture portrayed Asian Americans as a
“model minority” – a stereotype indicating that along with a superior work ethic and socioeconomic
status (SES), Asian Americans presumably had above-average health status (Masood, 2009; McBride,
1996; Sue, 1995; Yee, 2009). However, recent studies have revealed this generalization to be a “myth,”
as many Asian Americans struggle with health problems as well as poor socioeconomic conditions and
limited opportunities for success (Lee, 2009; Yee, 2009). This myth or “positive stereotype,” which
persists to this day, is damaging because it obscures reality and overshadows discussion of
psychosocial challenges that can impact health (Masood, 2009; McBride, 1996). Asian Americans are
as heterogeneous as any other ethnic or racial group in the U.S., and their health outcomes are similarly
wide-ranging (Gee, 2009; Mereish, 2011; Sue, 1995; Takeuchi, 1998, 2012; Uehara, 1994). So while
the health of some Asian American groups and individuals lies above national averages, that of others
falls far below; potentially resulting in individuals frequently not receiving the resources and services
they might need, simply because they are seen as members of a relatively “well-off” group (McBride,
1996; Yee, 2009).
A wealth of research demonstrates that although immigrant groups, including Asian Americans,
arrive in the U.S. with a health advantage (a phenomena often called the “healthy immigrant effect” or
“immigrant health paradox”), the advantage tends to diminish over time, resulting in health outcomes
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for long-term and second-generation Asian Americans that are similar to their U.S.-born counterparts
(Dolly, 2012; Frisbie, 2001; Kimbro, 2012; Schachter, 2012; Zhang, 2009). Little attention has been
paid to those that defy these general trends. While diversity has been well-documented among Asian
Americans, with those from Southeast Asia, for example, having poorer health statuses than those from
other parts of Asia (Chu, 2011; McCracken, 2007; Takada, 1998), the underlying factors that account
for differential health status among Asian Americans are largely unknown. The results of studies
exploring risk and protective factors for health are sometimes contradictory; variables that are
protective in some studies, such as ethnic identity (Mossakowski, 2003), have no discernible effect in
other studies (Nesdale & Mak, 2003), or have been shown to exacerbate health problems in others (Yip,
Gee, Takeuchi, 2008).
One major limitation of prior research on Asian American health is that the methods used for
understanding heterogeneity have been limited to variable-centered models that tend to obscure within-
group differences. Since variable-centered analyses use predictive models that allow only some
variables to be associated with the outcome, they preclude the idea that they all might be associated
with the outcome. In contrast to variable-centered models, “person-centered” methodological
approaches, including latent class analysis (LCA) and latent profile analysis, are “designed to divide
the population under study into a set of latent subpopulations that share a distinct interpretable pattern
of relationships among the indicators” (Lincoln, Chatters, Taylor, Jackson, 2007, p. 5; see also Meiser
& Ohrt, 1996). The resulting “classes” represent subgroups of individuals who are similar to each other
on the variables entered into the analysis and are different from the individuals in the other classes
(Lincoln et al., 2007). LCA provides a novel approach to understand and visualize sociodemographic
characteristics and health among Asian Americans. This study is an effort to overcome some of the
methodological limitations of prior empirical research. Specifically, a person-centered, probabilistic
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technique will be used to identify mutually exclusive and exhaustive “classes” or groups of individuals
based on their reported sociodemographic characteristics and health status, capturing the heterogeneity
of Asian Americans in ways that have not been done before.
“Person-centered” techniques such as LCA have shown promise for improving our knowledge
of several complex phenomena. For example, LCA has been used in social science literature to help
elucidate depression (Lincoln et al., 2007), psychopathology (Bergman & Magnusson, 1997), risky
substance and sexual behaviors (Auerbach, 2006; Connell, 2009), conflict (Nylund, Bellmore, Nishina
& Graham, 2007) and victimization (Van Gaalen & Dykstra, 2006). It has also been used to create
typologies of individuals according to their socioeconomic status and examine associations between
their class assignments and health outcomes (Scharoun-Lee et al., 2011). Among Asian Americans,
LCA has been used to identify profiles of adherence to cultural values (Wong et al., 2012) and to
categorize immigrants by their reasons for migration (Gong, Xu, Fujishiro, & Takeuchi, 2011). But
there is no evidence that LCA has been used to create classes of individuals (or profiles) based on their
health status and sociodemographic characteristics.
Therefore, the primary research question for this study is: Can risk profiles of health be
empirically identified among a heterogeneous sample of Asian Americans? If so, what is the
composition of these profiles in terms of sociodemographic characteristics? A secondary question that
will be addressed is whether an individual's level of ethnic identity – operationalized as feelings of
closeness with others of the same racial and ethnic descent – is associated with their class membership.
In other words, is ethnic identity associated with a particular health profile and if so, for whom?
Ethnic identity is “that part of an individual's self-concept which derives from his knowledge of
his membership of a social group (or groups) together with the value and emotional significance
attached to that membership” (Tajfel, 1981, p. 255). It is considered a construct of particular relevance
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to people of Asian descent due to a cultural orientation toward interdependence and collectivism, which
emphasize the group over the individual (Kitayama, 2010; Mossakowski, 2007; Triandis, 1988). Due to
Asian Americans' more interdependent self-construals, they “are more likely to be influenced by the
situational context and their in-group members in defining their identities” than their non-Asian
counterparts (Sue, Mak, & Sue 1998; p. 315). In general, having stronger ethnic identity is linked to
improved health outcomes (Mossakowski, 2003; Siegel, 2000; Yip, 2008). For example, among
Filipino Americans, ethnic identity is associated with fewer depressive symptoms (Mossakowski,
2007). However, ethnic identity has mostly been examined in the context of mental health among Asian
Americans; few, if any, studies examine the role of ethnic identity in physical health outcomes among
Asian Americans. The potential effects of ethnic identity and its malleability through practices and
policies that can encourage or discourage people from maintaining it, make the second research
question an important one; that is, Is ethnic identity associated with a particular health profile and if so,
for whom? Therefore, once health profiles among Asian Americans are identified, the extent to which
ethnic identity predicts class membership will be examined.
Methods
Sample Data
Data for this study come from the National Latino and Asian American Study (NLAAS), which
surveyed a nationally representative sample of non-institutionalized Asian and Latino Americans aged
18 or older. The NLAAS study was conducted during 2002 to 2003 and employed a multiframe,
stratified area probability design. Detailed descriptions of the sampling methods and study procedures
are published elsewhere (see Alegría, 2004a, 2004b; Heeringa, 2004; Pennell, 2004). Sample design
and weights correct for disproportionate sampling, nonresponse, and population representation across
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multiple sociodemographic characteristics.
The present analysis used the Asian subsample of the NLAAS, which included 2,095
respondents (N = 2,083). The final weighted sample was 53% female, approximately 29% of
respondents were 30 years or younger, 45% were 31 to 50 years old, and 26% were 51 years or older.
The ethnic breakdown of the sample was 13% Vietnamese, 22% Filipino, 29% Chinese, and 37% from
other Asian ethnic backgrounds. A majority (63%) resided in the U.S. for 20 years or less, 24% had
over 20 years of residence, and 23% were born in the U.S. Sixty-seven percent had obtained more than
12 years of education and approximately 78% lived above the poverty line.
Measures
Physical health problem was measured by a composite of ten conditions indicated in the World
Mental Health Composite International Diagnostic Interview (CIDI), including cardiovascular,
respiratory, pain, diabetes, cancer, and epilepsy, among others (Kim, Chen, & Spencer, 2012). For the
present analysis, the score was dichotomized (0 = no physical health problems and 1 = 1 or more
problems).
Ethnic identity was measured by responses to the question “How close do you feel, in your
ideas and feelings about things, to other people of the same racial and ethnic descent?” (Félix-Ortiz,
Newcomb, & Myers, 1994). The four response categories were dichotomized (0 = not at all/not very
close, 1 = somewhat/very close). Sociodemographic factors included in the analysis were gender (self-
identified: 0 = male, 1 = female); age (at time of interview, 18-30, 31-50 and Over 50 years); ethnic
group (Chinese, Filipino, Vietnamese, and Other Asian); duration of residence in the U.S. (number of
years lived in the United States: 1 = less than 5 years, 2 = 5-10 years, 3 = 11-20 years, 4 = 20 or more
years, 5 = entire life); education (measured in years, 0-11, 12, 13-15, and 16 or more); and household
income [calculated by dividing 12-month household income by the federal poverty threshold for the
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corresponding household size and composition, based on the 2000 U.S. Census; (Chen & Takeuchi,
2011), 0= at or below poverty level, 1= above poverty level].
Data analysis
Latent class analysis (LCA) was used to identify distinct classes of Asian Americans according
to their health status and sociodemographic characteristics. This “person-centered” approach was
employed to address the debate concerning the two issues discussed above, namely, over-generalization
of Asians as “model minorities” and the question of how heterogeneity should be explored among this
diverse group. LCA addresses these issues by enabling the identification of relatively homogeneous
subgroups within a heterogeneous population based on similarity of characteristics, and helping to
identify covariates that differentiate class membership (Auerbach, 2006; Connel, 2009; Lanza, 2007;
Nylund, 2007). Instead of relying on predetermined groupings or categories, this multivariate approach
assumes an underlying categorical latent variable that determines individuals' class membership
(Nylund et al., 2007). Other benefits of the LCA approach are that it allows for the inclusion of
predictor and outcome variables simultaneously in the model and provides statistical fit indices, which
can be used to assess model fit as well as help decide the number of classes (Nylund et al., 2007).
LCA provides estimates of class membership probabilities (e.g., health status classes or health
profiles) and probability of sociodemographic characteristics within each class. The relationship of a
covariate (in this case, ethnic identity) to class membership was determined through simultaneously
estimated multinomial logistic regression models with corresponding odds ratios estimated to indicate
the effect of a given level of the covariate on probability of class membership relative to a reference
class.
All analyses for this study were conducted using Mplus Version 6.12 (Muthén & Muthén, 1998-
2011). A series of models were run sequentially to determine the appropriate number of classes, based
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on health and sociodemographic characteristics (gender, age, ethnic group, years in U.S., education,
and income). A one-class model was estimated first, followed by a series of models specifying an
increased number of classes (two-class, three-class, etc.). Fit indices among models were compared,
with optimal model selection guided by recommended indices including Adjusted Bayesian
Information Criterion (BIC) compared to other models, the Lo-Mendal-Rubin likelihood ratio test, and
entropy values (Connell, 2009; Nylund, 2007). To examine the overall differences in health status
among the resulting classes, a chi-square test was employed. Following the successive analyses, the
classes resulting from the final model were regressed on ethnic identity to examine whether this
variable accounted for the differentiation in membership between classes. All analyses were weighted
by specifying the data as “complex” and including the appropriate cluster, weight, and stratification
variables to adjust for sample selection probabilities.
Results
Results of the successive LCA models are presented in Table 4.1. Adjusted Bayesian
Information Criterion (BIC) scores were consulted to determine the best-fitting model, with lower
scores indicating better fit. The Lo-Mendell-Rubin likelihood ratio test (LMR LRT) was also consulted
to determine the number of classes that best fit the data. The LMR LRT compares the estimated model
to a model with one less class (Lo, Mendell, & Rubin, 2001). The LMR LRT gives a p-value that
represents the probability that a model with one less class generated the data. A p-value greater than
0.05 indicates that a model with one less class is preferable to the present estimated model. Lastly, the
measure of entropy was consulted, which is a standardized summary of the classification accuracy of
placing participants in classes based on their model-based probabilities; a lower value is considered
superior to a higher value.
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There was some discrepancy among the fit statistics regarding which model best represents the
data. According to the Adjusted BIC, a six-class model provided the best fit to the data. However, the
lower entropy value and significant p-value for the LMR LRT (p = 0.76) indicated that the five-class
model was superior. Moreover, two of the classes in the five-class model were virtually
indistinguishable from each other; a problem that was remedied in the four-class model, in which all
four classes were easily interpretable. Accordingly, the four-class model, which retains acceptably
strong fit statistics (Adjusted BIC = 28907.37; LMR LRT p < 0.05, Entropy = 0.669), was accepted.
Estimated average probabilities of class membership for each of the four classes were derived
from the model-based probabilities for all respondents to be in each class. All four classes had
probabilities between 0.804 and 0.836, suggesting acceptable definition of class membership. Thus,
individuals in this sample had, on average, a relatively high probability of being a member of the class
to which they were assigned.
Results of the four-class model were used to summarize conditional probabilities for the health
and sociodemographic characteristics included in the analysis, based on class membership (Table 4.2,
Figure 4.1). The classes were well differentiated by physical health status, and were named based on
the proportion of individuals in each class reporting one or more physical health problem. Among the
“excellent health” class, 30% of individuals reported a physical health problem. Members of the “good
health” class had a 48% probability of having a health problem, while those in the “fair health” and
“poor health” classes had 67% and 77% probability of having a problem, respectively. The result of a
Wald test of difference indicated that the proportion of respondents with a physical health problem
varied significantly between the class with the best health and the two classes with the worst health. In
other words, the proportion of respondents reporting a physical health problem in the “excellent health”
class was significantly higher than the proportion found among the “fair” and “poor” health classes.
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Notable distinguishing features of each of the classes are described here, and the full class
profiles can be found in Table 4.2 and Figure 4.1. The “excellent health” class accounted for 25% of the
sample. This class was comprised of a relatively young (100% aged 18-50), well-educated (85% had 13
years or more of schooling), higher-income (84% were above poverty line) group of respondents, who
were almost exclusively foreign-born (94%). The “good health” class accounted for 17% of the sample.
This class was primarily comprised of 18-30 year-olds (93%). The majority (58%) of this group was
native-born. Nearly one-third (30%) of this class had 12 years or less of schooling and 33% lived at or
below the poverty line. The “fair health” class accounted for 20% of the sample and was the only group
to have a fairly unequal gender distribution, with over 65% being female. The composition of this
group was relatively older (45% were 31-50 and 47% were over 50), foreign-born (100%) and were
mostly long-term residents (62% lived in the U.S. for 11 years or more). Lower socioeconomic status
characterized this group, with 73% of members having 12 years or less of schooling and 48% living at
or below the poverty line. Finally, the “poor health” class accounted for 38% of the sample. It was the
oldest group, with 98% being over 30 (54% were 31-50 and 44% over 50). The majority (75%) were
either born in the U.S. or had resided in the U.S for at least 20 years. With respect to socioeconomic
status, 23% of the members in the “poor health” class had 12 years or less of education and 7%
reported living at or below the poverty level.
The ethnic group breakdown of each of the classes is presented in Figure 4.2. Vietnamese
respondents were more likely to be in the “fair health” class (43%) than in the other classes, while
Filipinos had approximately equal chances of being in the “good health” (30%) or “poor health” (32%)
classes. Chinese respondents were most likely to be in the “fair health” class (42%), followed by
“excellent” (31%) and “poor” (25%). Respondents comprising the “Other” Asian ethnic group were
most heavily represented in the “excellent health” class (53%), followed by the “good” (49%) and
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“poor” (39%) classes.
Table 4.3 presents the results of a multinomial logistic regression analysis examining the
association of ethnic identity with each class. The “excellent health” class was used as the normative
comparison group (e.g., referent). Three covariate comparisons were made: (a) the likelihood of being
in the “good health” class compared to the “excellent health” class; (b) the likelihood of being in the
“fair health” class compared to the “excellent health” class; and (c) the likelihood of being in the “poor
health” class compared to the “excellent health” class. In response to the second research question,
findings indicated that ethnic identity was a significant predictor of class membership. Specifically,
results of the multinomial logistic regression analysis indicated that those with high ethnic identity
were less likely to be in the “good health” class compared to the “excellent health” class (OR = 0.29;
95% CI = 0.10-0.89; p < .05). Put another way, Asian Americans with high levels of ethnic identity are
more likely to be in the “excellent health” class than the “good health” class. This finding illustrates
that having higher levels of ethnic identity can promote health among Asian Americans; it is part of
what differentiates those with “good health” from those with “excellent health.” This difference was
not observed when comparing the fair and poor health classes with the excellent health class. It is worth
noting again that the “excellent health” class was comprised of a relatively young, high SES group of
respondents, who were almost exclusively foreign-born.
Discussion
The purpose of this study was to empirically identify profiles of health among a representative
sample of Asian American adults. Results demonstrated the utility of a “person-centered” approach,
and indicated that Latent Class Analysis is useful for empirically identifying health profiles. The
findings were aligned with prior literature documenting heterogeneity among Asian Americans (Gee,
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2009; Mereish, 2011; Sue, 1995; Takeuchi, 1998, 2012; Uehara, 1994), but go beyond what prior
“variable-centered” models have been able to demonstrate. Examining the sociodemographic
composition of each class provides a more nuanced picture of health risk than was previously available.
For example, whereas much research points to older age as a risk factor for poor health (Kim, 2012;
McBride, 1996; Rohrer, 2004), this study demonstrates that those in the “excellent” health class are not
necessarily the youngest; in fact, the proportion of older people in the “excellent health” class was
larger than that in the “good health” class, meaning that age is not the consistent predictor of health that
previous studies have reported. Similarly, while longer duration of residence in the U.S. generally
predicts poorer health (Frisbie, 2001; Goel, 2004; Gong, 2006; Zhang, 2009), among this sample, a
sizable majority (63%) of the “good health” class was comprised of those living in the U.S. for over 20
years. Therefore, the LCA results provide a more nuanced and sophisticated picture of Asian American
health than was available in prior literature.
The four classes were well-differentiated in terms of their sociodemographic composition, yet
each class was heterogeneous with respect to demographic composition; that is, men and women were
represented in each class, as were low SES, high SES, ethnic group, etc. with the exception of the
oldest age group, which was not represented in the “excellent” and “good” health classes and U.S.-
born, which were not represented in the “fair” health class. These findings establish the presence of
discrete “poor,” “fair,” “good,” and “excellent” health groups and demonstrate the importance of
examining heterogeneity that exists within racial and ethnic groups.
Consistent with previous literature, the youngest age group was heavily represented in the
“excellent” and “good” health classes while the oldest age group was exclusively found in the “fair”
and “poor” health classes. However, the middle age group had a more bipolar distribution, with heavy
representation in the “excellent health” and “poor health” classes and a lower probability of
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membership in the middle two classes (e.g., “good” and “fair”). This finding would be difficult to
detect in a variable-centered analysis. These novel findings support the use of LCA as an appropriate
method for investigating heterogeneity among Asian Americans, as a closer examination of each class
will further illustrate.
The finding that the “excellent health” class was comprised largely of young adults, immigrants,
and individuals with high socioeconomic status was not surprising in light of findings from previous
literature. Foreign-born status, higher income and educational attainment, and younger age are well-
established protective factors for health (Finch, 2003; Gee, 2007; Kim, 2012; Mulvaney-Day, 2007;
Takeuchi, 2007). The interesting finding regarding this class pertains to its ethnic group composition; it
is the only class that is comprised mostly (53%) of members of the “Other” Asian category. Although
Chinese, Filipinos, and Vietnamese together account for over 63% of the total U.S. Asian population
(Takeuchi et al., 2007), they comprised less than half of the “excellent health” class. Meanwhile, the
“Other” category is comprised largely of East Indian, Korean, and Japanese adults, who make up
approximately 18%, 10%, and 8% of the Asian American population, respectively (Hoeffel, Rastogi,
Kim, & Shahid, 2012). The over-representation of “Other” ethnic group adults in the “excellent health”
class might be partly explained by the fact that this class also has an over-representation of recently
arrived immigrants, as predicted by the “healthy immigrant effect” literature (Dolly, 2012; Frisbie,
2001; Kimbro, 2012; Schachter, 2012; Zhang, 2009). Many in this class may have arrived after the
Immigration Act of 1990 was passed (U.S. Congress, 1990). This Act reorganized the system of
immigration preferences to favor certain professional groups, resulting in an increase in arrivals with
scientific and technical training from countries like South Korea and India (U.S. Census Bureau, 2007).
Supporting this explanation is the fact that the “excellent health” class had the highest percentage of
highly educated respondents, with 73% reporting 16 years or more of education. This constellation of
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factors results in a clustering of younger individuals, highly educated individuals and recent arrivals
who report superior health status, which the “excellent health” class reflects.
The defining characteristic of the “good health” class was youth; 93% of respondents in this
class were 30 years old or younger. The majority of the class (58%) was born in the U.S. As such,
members of this class possessed mixed levels of educational attainment (fairly evenly distributed
between high school graduates, college graduates, and those with post-graduate education) and a wide
range of income levels, commensurate with the diversity found among U.S.-born Asian Americans
(Lee, 2009; Portes, 2006; Zhou, 2008). Despite their relative youth, 48% of members of the “good
health” class reported at least one physical health problem. This finding provides further evidence
supporting the “immigrant health paradox,” indicating that U.S.-born individuals tend to have poorer
health status than their foreign-born counterparts. In terms of ethnic composition, the “good health”
class was largely comprised of “Other” ethnic group adults (49%), followed by Filipino (30%), and
Chinese (17%) adults. The over-representation of respondents in the “Other” Asian category was
similar to that found in the “excellent health” class and points to the need for future research to tease
out the reasons that respondents from countries such as India, South Korea, and Japan are healthier than
their counterparts.
The only class that had a noteworthy gender difference was the “fair health” class, with 65%
female composition. This class also contained a far greater proportion of older, poor, and low-educated
respondents than the other classes. This constellation of characteristics is in line with previous research
documenting risk factors for health problems among Asian Americans (Barnes, 2008; Kim, 2012;
Ward, 2004). The “fair health” class also contained a higher proportion of Vietnamese adults than any
other class. Prior literature indicates that Vietnamese adults, especially women, are less likely to hold a
bachelor's degree, more likely to be poor, and have greater risk of being in poor health than other Asian
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subgroups (Barnes, 2008; McCracken, 2007; Terrazas, 2010; Ward, 2004). Additionally, a majority
(62%) of the respondents in the “fair health” class were immigrants who also reported living in the U.S.
for over ten years. Given that the NLAAS data were collected in 2002-2003, one can assume that many
of these respondents arrived in the U.S. during the aftermath of the Vietnam War and communist
takeover, during the late 1970s, 80s, and early 90s. At that time, ongoing political and social turbulence
caused a mass exodus of hundreds of thousands of Southeast Asians (United Nations High
Commissioner for Refugees, 2000). Emigrants of the region often applied for political asylum and
refugee status in other countries, especially the United States (Development Research Centre on
Migration, Globalisation and Poverty, 2007; Monger, 2009; Terrazas, 2010). Refugees and asylees are
at increased risk of health problems due to exposure to various forms of trauma and disadvantaged
circumstances prior to and during migration (Fortuna, 2008; Kandula, 2004; Steel, 2006). In light of the
confluence of health risk factors found among the “fair health” class, the relatively high odds of having
a physical health disorder (67%) for members of this class are not surprising.
The distinctive characteristic of the “poor health” class is the high rate of physical health
problems, itself, at 77%. Since this class comprised over one-third (38%) of the sample, it is clear that
the “model minority myth” (Lee, 2009; Masood, 2009; McBride, 1996; Yee, 2009) is not applicable to
a large segment of the Asian American population. The vast majority of the “poor health” class were in
their middle (31-50; 54%) or late (over 50; 44%) adult years, with just 2% in the 18-30 age group, as
predicted by extensive literature indicating that health declines over the life span (Fries, 1980; Kim,
2012; McBride, 1996; Rohrer, 2004). Most of the class was comprised of respondents born in the U.S.
(31%) and long-term immigrants who had lived in the U.S. for at least 20 years (44%). The under-
representation of foreign-born, recently arrived respondents in the “poor health” class supports research
documenting the “healthy immigrant effect” and the health decline over time (Frisbie, 2001; Kimbro,
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2012; Zhang, 2009). However, the relatively high socioeconomic status of this class runs counter to
established theory that poor health status is strongly predicted by low levels of income and education
(Abdou, 2010; Adler, 2002; Chen, 2006; Finch, 2003). The finding that 77% of the “poor health” group
reported 13 years or more of schooling and just 7% lived in poverty gives support to the phenomenon
documented by Gong and colleagues (2012), whereby among Asian Americans, conventional measures
of SES fail to capture important dimensions of status, and therefore lack the associations with health
that are typically found among Americans. This finding echoes that of Williams and Collins (1995),
who found that whites receive higher “returns” from education and other markers of SES than do
blacks and Hispanics. As they point out, “SES measures are crude indicators of location in social
structure” (p. 377) and are often inadequate in explaining health differences. The health benefits that
typically arise from higher education and income among white Americans are reduced or nonexistent
among ethnic minority groups. Instead of relying on conventional, objective measures of SES such as
income and educational attainment, Gong and colleagues (2012) propose including measures of
subjective socioeconomic status (i.e., class standing relative to others) in studies of Asian American
health. The present study therefore extends the idea of diminishing “returns” of SES beyond African
American and Latino populations to include Asian Americans, and supports the contention that
subjective measures of socioeconomic status should be incorporated into studies of Asian American
health.
The finding that ethnic identity contributed to improved health status among those with above-
average health was consistent with other studies noting the protective effects of ethnic identity
(Mossakowski, 2003; Siegel, 2000; Yip, 2008). The reason ethnic identity differentiates “excellent”
from “good” health status may have to do with the sociodemographic composition of those two classes.
Specifically, the “excellent health” class has higher proportions of immigrants and of adults in the 31-
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50 age range, while the “good health” class has higher proportions of U.S.-born members and adults in
the 18-30 age range. Age and nativity both affect levels of ethnic identity (Rumbaut, 1994; Yip, 2008).
Among Asian Americans, immigrants have higher levels of ethnic identity than those born in the U.S.
(Yip, Gee, & Takeuchi, 2008). Immigrants may feel a stronger connection to their country of origin
than their U.S.-born counterparts, as evidenced by their greater likelihood of using self-identifying
labels that reflect their country of origin (Rumbaut, 1994, Yip, 2008). Older age has also been linked to
higher levels of ethnic identity among Asian Americans (Yip, Gee, & Takeuchi, 2008). Processes of
identity development across the life span tend to generate an increasingly clear and complex sense of
self, including ethnic aspects of self (Yip, Gee, & Takeuchi, 2008). Therefore, ethnic identity's role in
differentiating “good health” from “excellent health” classes may simply be a reflection of differences
in age and nativity between the groups, but further research is warranted to examine alternative
possible mechanisms by which ethnic identity influences health among Asian Americans.
Findings from this study should be considered within the context of its strengths and limitations.
First, since it relies on cross-sectional data, it is limited in its ability to establish the causal direction for
observed effects. As with any cross-sectional analyses, causal inferences are problematic and
longitudinal data are preferred. In the absence of prospective data, we are limited in the ability to
understand the causal processes by which specific demographic factors influence physical health status.
For example, without prospective data, it is difficult to ascertain whether low socioeconomic status
predispose or facilitate the onset of physical health problems or whether the impairment and disability
resulting from chronic health conditions negatively impacts the ability to attain or maintain desirable
socioeconomic positions and resources for Asian Americans. In addition, because certain segments of
the population such as homeless and institutionalized individuals were not represented in the data, our
findings are not generalizable to these subgroups. While the LCA results are contingent upon the
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variables entered into the model, the included variables covered a breadth of domains consistent with
established theory on the nature of health. Since a single variable was used to measure physical health,
it cannot capture the full range of health issues that are present in the population. Even though the
measure was a composite of ten chronic conditions, this study is limited in the extent to which it can
discuss contributors to “overall” health among Asian Americans. Future studies should consider
including mental health measures as well as alternative indicators of physical health status in latent
class analyses of Asian American health. Also, since conventional measures of socioeconomic status
like income and educational attainment have limited effects on health among Asian Americans (Gong
et al., 2012), other measures such as home ownership, wealth (net worth), and subjective social status
should be considered in future analyses of the relationships between sociodemographic factors and
health. Finally, the fact that all other Asian groups (including Korean, Indian, Japanese, and many
others) were aggregated into the “Other Asian” group is somewhat problematic; combining such
disparate groups may lead to erroneous conclusions. The distinct histories and life experiences of Asian
Americans originating from different regions and countries have likely had an important influence on
shaping their patterns of health and illness in ways that are different from one another. Future research
should include more disaggregated analyses to provide scholars and decision-makers with more
detailed information to aid in reducing health differences between groups.
Despite these limitations, the present study contributes to the literature documenting Asian
American heterogeneity by treating Chinese, Filipino, and Vietnamese groups as separate ethnic
groups, rather than treating them as monolithic groups, as is fairly common in the literature (Uehara,
Takeuchi, & Smuckler, 1994). The significant advantages of the sample, methods, and analysis used in
this study provided a unique opportunity to examine differences in sociodemographic profiles and
health within a heterogeneous sample of Asian American adults. This “person-centered” latent class
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analysis resulted in a more nuanced understanding of the associations among sociodemographics,
ethnic identity, and health than prior “variable-centered” analyses of Asian Americans could provide.
The final model identified four classes with distinct profiles and levels of physical health problems,
thus providing insight regarding the risk and protective factors associated with health status among this
diverse population. The results can be used to inform health promotion efforts. For example, targeting
culturally appropriate intervention activities toward members of the “fair health” class – heavily
comprised of females, immigrants, individuals from Vietnam and members with low income and
education – might boost health and prevent them from falling into the “poor health” group.
Additionally, services and policies that serve to increase feelings of ethnic identity among the “good
health” group might help its members become resistant to the health declines that tend to occur with
longer duration of residence in the U.S. This elucidation of risk and protective profiles of health
facilitates our understanding of heterogeneous health outcomes among Asian American adults.
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112
Table 4.1.
Model Description Adjusted BIC LMR LRT Entropy
p
1 One class (no covariates) 31785.46 -- --
2 Two class 29394.13 <0.0001 0.644
3 Three class 29070.06 <0.0001 0.659
4 Four class 28907.37 0.0005 0.669
5 Five class 28834.68 0.0002 0.684
6 Six class 28806.16 0.7600 0.682
Fit statistic comparisons of latent class analysis models based on health and sociodemographic
characteristics
Notes: BIC=Bayesian Information Criterion; LMR LRT=Lo-Mendell-Rubin likelihood ratio test p value
for (K-1) classes; a significant p value indicates that the (K-1) class model should be rejected in favor
of a model with at least K classes.
CULTURAL RESOURCES AND HEALTH Ray-Letourneau
113
Table 4.2.
Four-class latent class analysis model of conditional probabilities of all variables, by class
Excellent health Good health Fair health Poor health
Class prevalence (25%) (17%) (20%) (38%)
Gender
Male 0.54 0.49 0.35 0.49
Female 0.46 0.51 0.65 0.51
Age
18-30 0.44 0.93 0.08 0.02
31-50 0.56 0.07 0.45 0.54
51 and older 0.00 0.00 0.47 0.44
Ethnic Group
Vietnamese 0.08 0.04 0.43 0.05
Filipino 0.08 0.30 0.14 0.32
Chinese 0.31 0.17 0.42 0.25
All other Asian 0.53 0.49 0.02 0.39
Years in U.S.
Less than 5 years 0.37 0.08 0.14 0.02
5-10 years 0.20 0.04 0.24 0.04
11-20 years 0.29 0.26 0.40 0.18
20 or more years 0.09 0.05 0.22 0.44
U.S.-born 0.06 0.58 0.00 0.31
Education
11 years or less 0.09 0.02 0.48 0.08
12 years 0.07 0.31 0.25 0.15
13-15 years 0.12 0.43 0.17 0.31
16 or more years 0.73 0.25 0.10 0.46
Income
At or below poverty line 0.16 0.33 0.48 0.07
Above poverty line 0.84 0.67 0.52 0.93
Physical Health Disorder
No disorder 0.70 0.53 0.33 0.23
One or more disorder 0.30 0.48 0.674* 0.767*
* Wald test indictates significant difference from the referent (Excellent health class)
CULTURAL RESOURCES AND HEALTH Ray-Letourneau
114
Table 4.3.
Odds ratio results of latent class logistic regression model
Covariate OR (95% CI) OR (95% CI) OR (95% CI)
Ethnic Identity
.29* 1.18 0.61
(0.10-0.89) (0.35-3.96) (0.19-2.01)
Good health vs
Excellent
Fair health vs.
Excellent
Poor health vs.
Excellent
Notes: OR = odds ratio; CI = confidence interval.
*p < .05.
CULTURAL RESOURCES AND HEALTH Ray-Letourneau
Figure 4.1.
Class composition
Figure 4.2.
Ethnic group composition, by class
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CHAPTER 5:
Conclusions and Future Directions
The aim of this dissertation study was to clarify the relationships between social position,
culture, and health status, drawing on the cultural resource hypothesis as a possible explanation.
Numerous studies of immigrant populations have documented health declines with length of residence
in the U.S. (Alegría, 2007; Finch, 2003; Portes, 2006; Rumbaut 1997a, 1997b), including among Asian
Americans, specifically (Frisbie, 2001; Gong, 2006; Zhang, 2009). However, relatively little is known
about how the cultural factors that shape a person’s life in a new country also influence their health.
The high degree of variability among Asian Americans in terms of their social standing and health
status implies that there will also be heterogeneity in health trajectories over time. The downward
trajectory in health status is really an average description of health status for immigrants, which implies
that there will be some individuals who are both above and below the mean.
Accordingly, this study examined three possible protective factors – ethnic identity, religious
service attendance, and native language proficiency – to begin to understand whether these cultural
resources have the potential to improve long-term health outcomes among Asian Americans. Cultural
resources have helped to explain the unexpected positive health outcomes among other disadvantaged
populations (Abdou, 2010, 2012; Campos, 2008); however, the cultural resource hypothesis has not
been applied to Asian Americans until now. The present dissertation study sought to fill this gap by
testing the cultural resource hypothesis as an explanation for variation in health outcomes among Asian
Americans. This chapter will present some of the central findings from the three empirical chapters as
well as describe the limitations of the study. This chapter will conclude by providing potential
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implications for theory, practice, and future research.
Major Findings
Findings from this study have made significant contributions to understanding the sociocultural
processes that lead to divergent health outcomes among Asian Americans. Findings indicate that at
least some of the heterogeneity in health outcomes among Asian Americans can be attributed to the
influence of cultural resources. The two cultural resources that demonstrated consistent protective
effects for objective health status among all Asian Americans and across all three studies were ethnic
identity and native language proficiency. In Study 1, native language proficiency was associated with
an improvement in mental health disorder (MHD) and physical health problems (PHP) among all Asian
Americans. Findings from Study 2 specified that native language proficiency had a particularly
beneficial impact on physical health for longer-term residents. Study 2 also demonstrated that ethnic
identity was protective for MHD, but only for those who had resided in the U.S. for a long duration of
time. Results from Study 3 indicated that higher levels of ethnic identity are part of what differentiates
an “excellent health” profile from a “good health” profile among Asian Americans. This set of findings
is consistent with previous research documenting the protective health effects of ethnic identity and the
maintenance of native language. However, findings from the current study provide a more nuanced
understanding of who, in particular, benefits the most.
A main contribution of this study is that it estimated models of contributors to health while
taking into account heterogeneity among Asian Americans. Many previous studies of Asian American
health treat this diverse population as a monolith, and aggregate all ethnic groups. One improvement
among studies is to add ethnic group as a covariate in the model. However, even this approach does not
produce the more nuanced findings that come from specifying separate models for each subgroup or
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using a latent class approach. By running separate models for Chinese, Filipino, and Vietnamese adults,
this study was able to explore specific contributors to health for each group. Doing so revealed that the
effects of cultural resources vary by ethnic group. For example, ethnic identity was not associated with
any health outcome among the full Asian American sample in the first-order models (Study 1).
However, after stratifying the sample by ethnicity, findings revealed that ethnic identity was associated
with a reduction in MHD among Filipino adults. This unique finding would have been obscured if the
models were estimated using data from the full Asian American sample only. Heterogeneity was further
revealed in Study 3 by utilizing an innovative statistical approach, latent class analysis, to estimate
“person-centered” rather than “variable-centered” models. In doing so, distinct classes or profiles of
individuals were identified that provide information that will be useful for designing targeted
interventions and also contribute to knowledge about factors that increase or decrease the health risk
for Asian Americans.
Findings from the present study are generally consistent with existing theoretical and empirical
research regarding immigrant health (Frisbie, 2001; Gong, 2006; Zhang, 2009), as duration of
residence in the U.S. was the most consistent risk factor for MHD and PHP (Tables 2.2, 2.4, 2.6). Not
only was this true for Asian Americans as a whole, but it was also the case for each major subgroup
(Chinese, Filipino, and Vietnamese) individually. However, one result from Study 3 ran counter to
predictions based on immigrant health literature, in which longer duration in the U.S. is a risk factor for
poor health (Alegría, 2007; Finch, 2003; Portes, 2006; Rumbaut 1997a, 1997b). The “good health”
class identified by using a latent class approach in Study 3 was comprised of individuals who had
relatively low rates of physical health problems despite the relatively high proportion of individuals in
the class with longer-term residence in the U.S. (Table 4.2, Figure 4.1). However, this finding can be
explained, in part, by the overrepresentation of young adults in the “good health” class relative to the
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“fair health” and “poor health” classes. This corresponds with overwhelming evidence that younger age
is protective for physical health (Gee, 2002; Mulvaney-Day, 2007; Robert, 2001; Schachter, 2012;
Sellers, 2009; Zhang, 2009 and Tables 2.2, 2.5, and 2.6).
Another result that ran counter to existing theoretical and empirical research was the lack of
association between indicators of socioeconomic status (SES) and health in both the bivariate (Table
2.2) and multivariate (Tables 2.4 and 2.6) contexts. In almost all models predicting MHD and PHP,
educational attainment and income were not associated with health for any group. The two exceptions
were the negative association between income and MHD among Chinese adults and the positive
association between education and PHP among Filipino and Vietnamese adults. While this general lack
of association was surprising, it was consistent with findings from previous studies demonstrating the
insignificance of conventional measures of SES (e.g., education and income) for Asian Americans
(Gong, 2006; Gong, 2012). Alternative measures reflecting SES, such as self-perceived community
standing (de Castro, 2010; Gong, 2012) and subjective social status (Leu, Schroth, Obradovic, & Cruz,
2012), may be more appropriate in studies of Asian American health because unlike objective measures
of SES, that may bear different meanings for Asian Americans. The more subjective measures may
better reflect the material and psychosocial resources that typically correspond with financial resources
among Americans. Conventional SES measures do not fully capture important dimensions of status for
immigrant groups, thus potentially explaining the lack of association of SES with health in the current
study. Measures of subjective SES have relatively strong associations with various measures of health
among Asian Americans (de Castro, 2010; Gong, 2012). Since subjective SES might capture variations
in status that are usually unaccounted for by conventional (objective) measures of SES, these subjective
measures can serve as a more global measure of SES and should be included in future studies of Asian
American health.
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Another intriguing finding was that half (four out of eight) of the protective effects found in
models predicting health stratified by ethnic group (Tables 2.3-2.6) were found among the group
reporting the lowest level of a particular cultural resource (Table 2.1). Specifically, religious attendance
was protective for self-rated mental health (SRMH) among Chinese adults, who reported the lowest
average levels of religious attendance. The lowest levels of native language proficiency were reported
among Filipino adults, and that was the only cultural resource to have an association with their SRMH
and SRPH. Lastly, Filipino adults had among the lowest rates of ethnic identity, but that is the cultural
resource that reduced their likelihood of MHD. Perhaps there is something unique about individuals
who seek out cultural connection in ways that are atypical of their ethnic group. It is beyond the scope
of the present study to explain this peculiar finding, but it is suggestive of the need to further explore
the mechanisms by which cultural resources operate on health.
Limitations
In addition to the contributions to the literature on Asian American health, findings from this
dissertation study should be considered in light of several limitations. First, only a small subset of
social and cultural factors that could impact health were examined. The use of secondary data limits the
extent to which other potentially relevant cultural resources could be utilized. Previous literature
regarding cultural resources, ethnic minorities, and disadvantaged populations indicates that there are
other cultural values, beliefs, and practices that are important components of the cultural milieu of
many groups and individuals. Since the present study included three of the main internal and external
cultural resources contained in the NLAAS data set – ethnic identity, native language proficiency and
religious service attendance – additional data would need to be collected or a different data set used in
order to include other cultural variables in future analyses. Additional cautionary notes regarding the
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operationalization and measurement of the three included cultural resource constructs can be found in
Chapter 2.
Second, this study was limited to including just a few sociodemographic predictors and health
outcomes in the analyses. The study did not account for immigration-related factors such as reasons for
migration, pre-migration context, context of reception, and post-migration stressors; factors that can
affect how immigrants and their descendants experience the transition to a new host society (Angel,
1992; Frey, 2005; Funkhouser, 2000; Gong, 2006, 2011; Portes, 2006; Rumbaut, 1997a, 1997b;
Schweitzer, 2006; Zhang, 2009), along with subsequent health effects (Angel, 1992; Carswell, 2009;
Gong, 2006, 2011; Silove, 1997; Takeuchi, 2007; Zhang, 2009). Due to issues of multicollinearity with
age, duration in U.S. and limitations of the dataset, generational status and age at immigration were not
included in the present analysis, but would be important to consider in future studies of Asian American
health.
Third, the objective health measures utilized in this study, mental health disorder and physical
health problems, were composites of a diverse set of health problems. Examining contributors to health
conditions such as major depressive disorder or cancer individually would provide a more diverse
picture of Asian American health. However, the present study was an initial “first step” to explore the
effects of cultural resources on health. Considering the individual physical health conditions separately
would have resulted in inadequate cell sizes in many cases. Thus, it was necessary to use composite
measures. Although these measures have demonstrated their adequacy in previous studies of Asian
American health (Kim, 2012; Takeuchi, 2007), more specific health measures (rather than global
measures) are important to include in future studies of cultural resources and health.
Fourth, regarding the mental health measures, it is important to note that some Asian Americans
reportedly are hesitant to discuss or endorse psychological symptoms (Chen, 2005; Morris, 1992;
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Singh, 2011; Zhang, 1998). Many Asian Americans take a traditional view of health that does not
separate body and mind (Chen, Kramer, Chen & Chen, 2005). Others prioritize emotional restraint or
feel that mental health diagnosis is shameful or stigmatizing (Morris, 1992; Singh, 2011; Yang, 2007).
Therefore, many Asian Americans prefer to express their psychological state in terms of somatic
metaphors (Singh, 2011). The NLAAS data set does include a somatic symptom scale, but results of
similar analyses to those in this study did not differ substantially whether the somatic scale or MHD
composite were examined. Therefore, for purposes of cross-ethnicity comparison and potential
replicability, the more frequently used MHD measure was employed in the present study.
Lastly, the findings and interpretations from this dissertation should be considered with caution
because the data represent a single point in time. Cross-sectional studies provide a helpful snapshot of
health status, but they do not allow for a determination of causality. It is possible that findings as a
result of using the NLAAS data may be reflective of cohort or period effects. Furthermore, since it has
been over a decade since the data were collected, it will be helpful for future studies to gather more
recent data on Asian American health, as it would be important to support the associations found in this
study with more recent data that might also include more recently arrived immigrants or reflect the
changing demographics of an aging population. Collection and analysis of longitudinal data would be a
critical next step for examining health over time among Asian Americans. Since the effects of
migration and acculturation are very much tied to the timing of such an event in the life course, it is
important to have multiple time points of data.
Implications
Implications for Theory
The results from this dissertation study provide additional support for the cultural resource
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hypothesis proposed and substantiated by Abdou and others (Abdou, 2010, 2012; Campos, 2008).
Findings demonstrate the applicability of this framework for Asian Americans, thus contributing to
previous research findings that have demonstrated the importance of cultural resources for the health
and well-being of mothers and infants from African American, Latino, and low-income White
backgrounds (Abdou, 2010, 2012). Ultimately, the current study contributes to the body of evidence in
support of the cultural resource hypothesis as a promising framework for understanding minority health
and reducing health disparities.
The present study also contributes to our understanding of the immigrant health paradox, which
posits that immigrants arrive in the U.S. in better health than their U.S. born counterparts, but that this
health advantage diminishes over time (Frisbie, 2001; Dolly, 2012; Zhang, 2009). While findings from
this study are consistent with this perspective, they also expand on it by indicating that maintenance of
certain cultural resources may serve to buffer the detrimental effects that time has on health among
immigrants. Specifically, retaining higher levels of ethnic identity and native language proficiency can
protect the mental health and physical health, respectively, of Asian Americans who have resided in the
U.S. for a long duration of time.
Lastly, this study provides support for the conceptual distinction proposed by Chia and Costigan
(2006) regarding cultural domains. By examining both the “internal domain” of culture, represented by
ethnic identity, and the “external domain,” represented by native language proficiency and religious
service attendance, this study was able to provide a more comprehensive understanding of the role of
cultural resources in health than if they had been represented by a single, monolithic construct. Future
research would do well to incorporate both internal and external components of cultural resources, as
they differentially impact health and tell different stories about how cultural backgrounds, values,
beliefs, and behaviors coalesce to influence individuals' experiences and well-being.
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Implications for Policy and Practice
Based on findings from this study, medical and social service providers should be made aware
of the health-supportive functions of cultural resources among Asian American adults. Ethnic identity
and native language use, in particular, should be incorporated into the repertoire of interventions
employed by service providers working in communities serving Asian American clients. This can be
accomplished through multiple routes. First, agencies serving Asian American communities can
increase recruitment, employment, and retention of bilingual/bicultural service providers, reflecting the
specific ethnic group composition of their communities. Federal, state, and local governments should
enact policies facilitating the transition to a helping profession workforce that is culturally competent,
relevant and congruent to the service population. Policies that increase tuition assistance, provide low-
interest student loans, and increase accessibility of loan repayment programs for Asian American
students in helping professions should be considered.
Second, health and social service agencies should respond to the growing need for culturally
and linguistically appropriate services by ensuring that all front-line staff, regardless of ethnic
background and language capacities, are adequately prepared to interact with clients of all ethnic and
cultural backgrounds. This may require training and on-going support regarding the cultural traditions,
values, and health practices of the specific client populations served by a particular agency. Since the
federal immigration policy changes of the 1960s have led to an increasingly large and diverse
population of Asian Americans, this kind of preparation will be especially critical in the coming years.
The U.S. population, including Asian Americans, will undergo major demographic shifts with older
adults comprising a rapidly growing segment of the population. As an increasing number of Asian
Americans will be experiencing the health-deteriorating processes of aging and post-migration
exposure to the U.S. context, demand for culturally and linguistically appropriate health and social
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services will be crucial and service delivery systems will need to be prepared to accommodate these
needs.
Both of the protective cultural resources found in the present study, ethnic identity and native
language proficiency, tend to decline as individuals reside in the U.S. for longer durations (Table 2.2).
Facilitating preservation of these cultural resources may help to prolong the health advantages that
many Asian Americans possess upon arrival in the U.S. Longer duration of residence could come to be
seen less as a risk factor for health problems, and more as an opportunity for targeted interventions
designed to promote feelings of identification with one's ethnic group. This perspective, supported by
the findings of this study, are closely aligned with the strengths-based orientation of social work. Social
work practitioners working in both clinical and community settings should be attuned to the
opportunity for health improvements among Asian Americans, drawing on cultural resources to protect
health and well-being among this growing population.
In clinical contexts, existing services and evidence-based practices should be modified and
tested to more appropriately serve the specific needs of ethnic groups, making sure to promote feelings
of ethnic identity and use of native languages. In community settings, ethnic group-specific
neighborhood action committees, advocacy groups, and community development teams can be
facilitated and supported by existing social service agencies. Community health promotion activities
based on the promatoras model developed in Latino communities may have relevance for Asian
American populations as well. When linguistically and culturally matched lay community health
workers educate their peers about important health issues, residents may be more receptive than if the
messages were delivered by professionals from outside their cultural community. In this way,
components of ethnic identity and native language use may be combined with health-promotion
interventions to improve community health outcomes among Asian Americans. Lastly, there are many
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CULTURAL RESOURCES AND HEALTH Ray-Letourneau
existing community agencies that are dedicated to the social, legal, and/or educational needs of
particular ethnic groups. These agencies might be prime points of entry for health promotion
programming, as they have the potential to synthesize an ethnic group focus with health-related
messaging, delivered in a context that is already accessible and credible among the target population.
Therefore, institutions aimed at improving health would do well to partner with Asian American
community-based agencies to deliver culturally specific health promotion programs.
Findings regarding the heterogeneity of the Asian American population suggest the importance
of implementing health promotion policies and programs specifically targeted for different risk groups.
In Study 3, two classes demonstrated high rates of physical health problems. Though they had similar
age profiles, they were quite distinct in terms of other aspects of their sociodemographic composition.
Policy and intervention development should account for these differences, tailoring programs and
services to best meet the specific needs of each group. For example, since the “fair health” class was
characterized by low socioeconomic status (SES) and a high proportion of immigrants, interventions
aimed at improving health access and utilization might require addressing economic barriers, such as
lack of financial resources to pay for health insurance or availability of transportation to medical
appointments, as well as educational and communication barriers, such as low levels of literacy and
English proficiency. Provision of culturally appropriate services and written materials in languages that
reflect the needs of the community would be critical for improving health access and outcomes for
Asian Americans in the “fair health” class. Meanwhile, since the “poor health” class was comprised
largely of high-SES and U.S.-born respondents, their needs may pertain more to the very high
proportion of members reporting health problems. Accordingly, intervention development to improve
health service access and utilization may focus more on addressing physical frailty and reduced
mobility. In these ways, health and social service practitioners can use the findings regarding
132
CULTURAL RESOURCES AND HEALTH Ray-Letourneau
heterogeneity found in this study to refine and target interventions to improve health service access and
medical outcomes of the groups that need them most.
Implications for Research
Findings from this dissertation study provide initial support for the cultural resource hypothesis
among Asian Americans. Cultural resources have promise for explaining divergent health outcomes
among this diverse population, but further research is needed to support the results of the present study.
First, additional research regarding the measurement of cultural resources is needed. Future studies
could examine multi-dimensional constructs reflecting both internal and external domains of culture.
Other cultural measures more specifically related to Asian American culture include collectivism
(Mossakowski, 2007; Triandis, 1988), interdependence (Kitayama, Karasawa, Curhan, Ryff, & Markus,
2010), filial piety (Juang & Cookston, 2009), and traditional beliefs about health and wellness (Tabora,
1997; Zhao, 2010), among others. These constructs were not available in the NLAAS data set, but
would be important to include in future studies of Asian American health. As future studies include
expanded measures of cultural resources, more definitive conclusions can be drawn.
Second, it will be important to examine how each cultural resource is differentially associated
with health along major sociodemographic lines. For example, are the effects of cultural resources
different for men and women, or for younger and older adults? Regression models disaggregated by
gender and age group would provide increased specificity regarding the role of cultural resources in
health among Asian Americans. Finally, further research should compare the differential processes of
the effects of cultural resources on health between Asian Americans and other groups. For example,
these relationships could be examined among other racial/ethnic groups living in the U.S., such as
Latinos, African Americans and Whites, as well as Asian populations remaining in Asian countries.
This work would augment both the theoretical and empirical literature regarding the effects of cultural
133
CULTURAL RESOURCES AND HEALTH Ray-Letourneau
resources on health among immigrants, the general U.S. population, and international populations.
The present study was based on cross-sectional data of a representative sample of Asian
Americans, collected during the early 2000s. Use of the NLAAS data set provided the ability to
generalize results to the U.S. Asian American population. However, these data were not collected with
the explicit aim of deeply understanding how cultural resources relate to health. Since findings revealed
some support for the hypothesis that cultural resources are beneficial for health, an important next step
would be to attempt to unravel the “how” and “why” cultural resources contribute to health. Multiple
methods should be considered for developing the literature in this direction. Qualitative research among
specific Asian American ethnic groups would be important for obtaining rich, detailed information that
is not available in the quantitative results presented here. For instance, ethnographic research could
help to explore cultural resources and health at a community level, while in-depth qualitative
interviews and focus groups could shed light on the individual and family processes that may link
cultural resources to health. Also, studies with a longitudinal design would facilitate an examination of
how differing levels of cultural resources at different points in the life course have divergent effects on
health. For example, ethnic identity may have a curvilinear or bimodal relationship with health over
time (i.e., it may play a stronger role in young adulthood and/or during the transition into retirement).
Results such as these were impossible to detect in the present study due to its reliance on a single time
point.
Even without the collection of qualitative or longitudinal data, existing quantitative data (i.e.,
the NLAAS data set) could be examined using advanced statistical methods to expand on the present
study findings. Structural equation modeling (SEM), for example, could be used to test alternative
mediation models simultaneously in order to better understand the specific pathways whereby
sociodemographic factors, immigration-related factors, and cultural resources influence health
134
CULTURAL RESOURCES AND HEALTH Ray-Letourneau
outcomes. Also, while Study 3 of this dissertation utilized latent class analysis to generate profiles of
physical health among Asian Americans, a similar method could be used to generate profiles of cultural
resources. In this way, it would be possible to explore how certain cultural resources cluster together
among Asian Americans, and to examine the association of such profiles with health outcomes. These
findings have the potential to enhance our understanding of how cultural resources operate together or
separately to influence health among different ethnic groups.
Conclusions
This dissertation study provided a counterbalance to the lifestyle and behavior frameworks that
have dominated the extant literature on immigrant health. Findings have contributed to the literature on
Asian American health by testing the effects of three distinct cultural resources, ethnic identity, native
language proficiency, and attendance at religious services, on mental and physical health. Results are
suggestive of the health-promoting benefits of ethnic identity and native language proficiency,
providing initial support for the cultural resource hypothesis among a representative sample of Asian
Americans. This study contributes to the literature regarding the “immigrant health paradox” by
demonstrating that cultural resources can buffer the detrimental effects of length of residency in the
U.S. on health. Health and social service interventions should therefore facilitate the maintenance of
cultural resources to counteract the downward trajectory in health that occurs among some immigrant
populations. Programs and policies that support and extend cultural resources will be especially
beneficial for Asian Americans who have resided in the U.S. for many years. Lastly, findings from this
study enhance our understanding of Asian American diversity, as ethnic subgroups were analyzed
separately and advanced statistical methods used to reveal heterogeneity in Asian American health
profiles. This contribution is especially important given that overgeneralizations and stereotypes of
135
CULTURAL RESOURCES AND HEALTH Ray-Letourneau
Asians as a “model minority” persist, obscuring the real and growing needs for culturally appropriate
services among this increasingly large and diverse segment of the U.S. population.
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CULTURAL RESOURCES AND HEALTH Ray-Letourneau
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139

Abstract (if available)

Abstract The primary aim of this study is to improve our understanding of Asian American health. Stereotypes such as the “model minority myth” continue to obscure diversity and give the impression that Asian Americans are uniformly successful and healthy. However, some sub‐groups of Asian Americans are at higher risk of health problems than others. It is important to better understand the risk and protective factors that contribute to health among this large and growing segment of the U.S. population. ❧ The “immigrant paradox” is often used to explain heterogeneity in health outcomes among Asian Americans. This perspective posits that immigrants have superior health status compared to those who are U.S.‐born. However, over time this health advantage deteriorates, such that the health status of long‐term immigrants and subsequent generations tends to converge to that of their U.S.‐born counterparts. Using data from the National Latino and Asian American Survey (NLAAS) and the cultural resource hypothesis as a conceptual framework, this dissertation examines the effects of three cultural resources—ethnic identity, native language proficiency, and religious service attendance—on mental and physical health outcomes. ❧ Study 1 of this multiple‐manuscript dissertation explores the impact of each cultural resource on mental and physical health, stratified by ethnic group. Findings indicate that native language proficiency and ethnic identity are associated with better health for at least one ethnic group. Study 2 examines the moderating role of cultural resources in the relationship between longer duration of residence and health, finding moderating effects of ethnic identity and native language proficiency. Study 3 uses latent class analysis to empirically identify risk profiles of health among Asian Americans, revealing four sociodemographically distinct profiles. ❧ Findings from this dissertation illustrate the potential of cultural resources as protective factors for health and extend the cultural resource hypothesis to include Asian Americans. Instead of accepting health declines among immigrant populations as inevitable, it is important to consider heterogeneity and understand that longer duration of residence in the U.S. does not always result in poor health. Helping professionals can facilitate maintenance of cultural resources as part of a larger effort to improve health among Asian Americans.

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Asset Metadata

Creator Letourneau, Diana Ray (author)

Core Title Cultural resources and health among Asian Americans: results from the National Latino and Asian American Study

School School of Social Work

Degree Doctor of Philosophy

Degree Program Social Work

Publication Date 04/18/2014

Defense Date 03/18/2014

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag Asian Americans,cultural resources,ethnic identification,latent class analysis,Mental Health,OAI-PMH Harvest,physical health,protective factors

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Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Lincoln, Karen D. (committee chair), Abdou, Cleopatra (committee member), Vega, William A. (committee member)

Creator Email dianaray07@gmail.com,dray@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c3-380675

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