Rethinking Acculturation:
The influence of social contexts and gender on immigrant Asian mental health
Janxin Leu
Emily C. Walton
David Takeuchi
University of Washington
For submission to
Social Science & Medicine
Abstract
Acculturation is a popular but problematic variable in health research. An interactional,
ecological model of acculturation is used with data from the first nationally representative
survey of immigrant Asian mental health in the US (n=1583). Along with three
conventional measures of acculturation (e.g., English proficiency, proportion of life in the
US, and ethnic identification), the additive and moderating effects of gender and social
contexts (e.g., family, neighborhood, and community) on mental health were modeled.
Among immigrant males, family conflict, neighborhood ethnic density, and perceived
discrimination were associated with symptoms of depression and anxiety; perceived
discrimination moderated the relationship between English proficiency and symptoms of
depression and anxiety. Among immigrant females, ethnic identity was associated with
mental health outcomes; however, this relationship was moderated by family cultural
conflict. Results suggest that social contexts and gender may have important influences
on how acculturation is associated with immigrant mental health outcomes. Potential
influences on the mental health of immigrants may be overlooked if only conventional
acculturation models are considered.
Word Count 167
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Although the study of acculturation in health research is popular, it has been
widely criticized as lacking validity and reliability, as well as theoretical precision (Hunt,
Schneider, & Comer, 2004; Salant & Lauderdale, 2003; Zane & Mak, 2003; Phinney,
Horenczyk, Liebkind, & Vededr, 2001; Cuellar, Arnold, & Maldonado, 1995; Arcia,
Skinner, Bailiey, & Correa, 2001). The goal of this paper is to examine the relationship
between acculturation and mental health using an interactional, ecological model that
includes the influence of social contexts and gender. This model is demonstrated in the
first nationally representative sample of Asian immigrants in the US.
Acculturation, or an individual’s adaptation to culture contact and change, is
usually measured using multi-item scales or single-item measures by psychologists,
sociologists and epidemiologists. Multi-item scales assign an individual a single
summary score on dimensions such as language proficiency and ethnic identity. Scales
of acculturation often assume a unidimensional process anchored by ethnic culture and
mainstream “White American” culture at each end, ignoring dynamic macro-level
influences on mental health (Zane et al., 2003; Gutmann, 1999). Single-item measures
(i.e., time in the US) allow for separate dimensions of acculturation to vary in their
directionality. However, studies that include these measures also ignore social contexts
(Hunt et al., 2004). This paper investigate the influence of three frequently examined
dimensions of acculturation (i.e., English proficiency, time in the US, and ethnic identity),
and their influence on immigrant mental health. We apply a novel theoretical model to
examine how social contexts and gender interact with these dimensions of acculturation
to influence mental health among immigrants. to illustrate the interactional, ecological
model of studying acculturation.
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Acculturation influences on Asian immigrant mental health are complex
Acculturation measured by scales. The literature on scale-measured acculturation
and mental health among immigrants and ethnic minorities is inconclusive,
demonstrating the detrimental, protective, and null effects of adapting to the mainstream
host culture on mental health. For example, among Asian Americans, greater
acculturation has been associated with lower psychological distress and depression
among (Padilla, 1985; Mehta, 1998; Mumford et al., 1991; Shin, 1994) and higher life
satisfaction among South Asians (Mehta, 1998). However, it has also been associated
with greater depression among Vietnamese women and increased engagement in risky
behavior among Chinese and Vietnamese youth (Nguyen & Peterson, 1992; Shin, 1994;
Wong, 1999; Yi, 1998). Still other studies have found no relationship between
acculturation and mental health among South Asians (Songua-Barke & Mistry, 2000;
Ogden & Elder, 1998). These studies have no measurement consensus, and vary in both
the ethnicity (e.g., South Asian, Filipino, Chinese, Mexican, Turkish, Algerian) and
national context (e.g., US, UK, New Zealand, Australia, France, Israel, Canada) of their
samples.
Acculturation measured by single measures. The data are inconsistent even when
considering the three most commonly used single dimensions of acculturation. For
example, ethnic identity was not related to eating disorder prevalence in a sample of
South Asian women (Ogden et al., 1998). However, other research demonstrates that
ethnic minority identity may promote psychological well-being among immigrants and
ethnic minorities (Phinney & Devich-Navarro, 1997; Liebkind, 1996; Nesdale, Rooney &
Smith, 1997; Phinney et al., 2001; Gong, Takeuchi, Agbayani-Siewert, & Tacata, 2003).
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Research on time measures, such as nativity, generation, duration of residence in
the host country, and proportion of life in the host country, also present a complex set of
findings. For example, Leu (2008) has shown that the number of depression and anxiety
symptoms increases as the age of immigration decreases among Asian immigrant adults.
Nativity also seems related to mental health outcomes; despite better material affordances
and greater access to health care, the descendants of Asian immigrants in the US are less
mentally healthy than their parents’ generation (Takeuchi, Zane, Hong, Chae, Gong, Gee,
Walton et al., 2007; Takeuchi, Alegria, Jackson & Williams, 2007; Breslau & Chang,
2006). Similarly, studies that directly measure the influence of years in the host country
on mental health have found increased risk for depression and anxiety among Cambodian
refugees (Carlson & Rosser-Hogan, 1993; greater alcohol and cigarette usage among
Korean women (Hong & Faedda, 1996). However, in other studies, there is no
demonstrated relationship between time measures and mental health outcomes among
Hmong refugees (Mouanoutoua et al., 1991) Asian college students (Meston, Trapnell, &
Gorzalka 1996), and Chinese (Takeuchi, Chung, Lin, Shen, Kurasaki, Chun, & Sue,
1998). Moreover, there is also evidence that time in the host country is associated with
improvements in mental health (Westermeyer, Neider, & Vang, 1984) and health services
use (Juon, Choi, & Kim, 2000; Leclere, Jensen, & Biddlecome, 1994).
Research on the relevance of English proficiency to mental health among
immigrant Asians is similarly inconsistent. English proficiency has been associated with
risk for depression among Laotian refugees (Nicassio et al., 1986) and Vietnamese
refugees (Nwadiora & McAdoo, 1996). However, English proficiency was also
associated with decreased morbidity among Chinese (Takeuchi et al., 1998) and
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improvements in depression among Hmong refugees (Westermeyer et al., 1984). Still, in
at least one study, using data from the Filipino American Epidemiological Study, English
proficiency was not associated with distress (Gong et al., 2003).
Social contexts influence Asian immigrant mental health
Research has already demonstrated that social contexts are relevant to mental
health outcomes in ethnic minority and immigrant communities. For example, greater
cultural conflict in Asian families is associated with higher rates of depression and lower
psychological well-being among individuals (Chun & Akutsu, 2003; Tseng, 2004;
Greenberger & Chen, 1996; Tsai-Chae & Nagata, 2008; Farver, Narang, & Bhadha,
2002; Ying & Han, 2007, Phinney, Ong, & Madden, 2000). Similarly, among Asian
Americans, the ethnic density of a neighborhood may protect against poor mental health,
such that the greater the ethnic density, the lower the prevalence of poor health (Walton
& Takeuchi, in press). Additionally, commonplace discrimination experienced in
everyday interactions in society may cause emotional distress (Wang, Leu, & Shoda,
under review). Among Asian Americans, discrimination has been associated with poor
mental health outcomes (Liang, Li, & Kim, 2004; Wong & Halgin, 2006), as well as poor
physical health and well-being outcomes (Gee, Spencer, Chen & Takeuchi, 2007, Chan &
Mendoza-Denton, 2008; Alvarez & Helms, 2001).
An interactional, ecological model of acculturation is needed
The present study tests the influence of acculturation on mental health using an
interactional, ecological model of cultural development. An interactional model of
acculturation assumes a dynamic, complex process that takes into consideration
individual characteristics of the immigrant, the context of their settlement, and the
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interaction among these factors (Phinney et al., 2001; Berry, 1997; Horenczyk, 1997;
Jasinskaja-Lahti et al., 2003). An ecological model of human development can be used
to study acculturation, as well. It argues for the examination of individual behavior
within multiple environments that shape and constrain adaptation to change across time
(Lerner, 2002; Bronfenbrenner & Morris, 1998; Elder, 1974; 1998; Gabarino, 1992).
Therefore, an interactional, ecological model may be a promising step in research on
acculturation and health because it allows for individual variables to interact with varying
levels of social contexts.
There are two ways in which social context may change the influence of
acculturation on mental health. On the one hand, social contexts of family, neighborhood,
and community reception can increase or diminish the effect of acculturation variables
when directly added to a model of mental health. For example, in a study of tobacco use
among Vietnamese youth, the relationship between acculturation and smoking risk
disappeared after social context factors were added to the model (Rissel, McLellan, &
Bauman, 2000).
On the other hand, social contexts can moderate or interact with acculturation to
influence mental health outcomes. In particular, an immigrant’s acculturation status may
interact with her family context to influence her mental health (Chun et al., 2003). For
example, if she is highly identified with her ethnic background and experiences
intergenerational cultural conflicts in her family context, she may be likely to experience
worse mental health than if she were not highly identified with her ethnic background
(e.g., if family were not an important cultural value). Similarly, an immigrant’s
acculturation status may interact with the community reception to influence health
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outcomes (for tobacco use, Unger et al., 2000; for psychological distress, Lay & Nguyen,
1998; for tobacco use, Rissel et al., 2000). For example, if he speaks English poorly and
commonly experiences discrimination, he may suffer from poorer mental health than if
he spoke English fluently.
Gender may pattern the influence of acculturation on mental health
A recent review of the literature on acculturation and health in Asian immigrant
populations suggests that there is debate about whether gender modifies this relationship
(cf. Salant et al., 2003). There is theoretical reason to suspect that gender may interact
with individual acculturation dimensions and/or social contexts to influence mental health
outcomes, and/or that it may interact with social contexts to influence mental health
outcomes (Mahalingam, 2006). However, there is empirical evidence to suggest both the
relevance and irrelevance of gender. A greater maintenance of gender roles among
women than men may suggest that acculturation may be less relevant to the mental health
of immigrant women, relative to men (Ghuman, 2000; Palinkas & Pickwell, 1995;
Nguyen & Peterson, 1992; Romero, Carvajal, Valie, & Orduna, 2007; Ogden et al., 1998).
On the other hand, greater social isolation among immigrant women, compared with men,
suggests the greater relevance of acculturation to mental health (Mahalingam & Leu,
2005; Williams, Alvarez, & Hauck, 2002; Viruell-Fuentes, 2008; Pedraza, 1991;
Valenzuela, 1999; Hirsch, 1999; Nguyen & Peterson, 1992). Examining the role of
gender in the association between acculturation and mental health among Asian
immigrants is therefore important to contribute to both the empirical and theoretical
understanding.
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In summary, this paper tests three hypotheses. The first hypothesis suggests that
conventional individual-level acculturation variables, such as English proficiency, a
measure of time in the host country, and ethnic identification, may influence the mental
health of Asian immigrants. The second hypothesis is that social contexts may directly
influence mental health. The third hypothesis is that social contexts may moderate the
relationship between conventional acculturation variables and mental health. The
potential moderating role of gender in all these relationships is also examined.
Methods
Data were selected from the first-ever nationally representative sample of Asian
American immigrants (N=1583), the National Latino and Asian American Survey
(NLAAS). The NLAAS used a multi-frame, stratified probability sampling scheme,
described in detail elsewhere (Heeringa, Wagner, Torres, Duan, Adams, & Berglund,
2004). In summary, samples were drawn using three methods. In the first, participants
were recruited with a multistage stratified area probability sampling design: (a) city or
contiguous census blocks were sampled based on population density in each
neighborhood; (b) dwelling units were sampled within each block; (c) one adult was
sampled within each selected dwelling unit. In the second method, census blocks with at
least five percent of Asian households were over-sampled. In the third method, to
increase the sample size, a second respondent from a previously sampled household was
recruited. Weighting corrections were constructed to control for differences in selection
probability.
Among the surveyed Asian Americans (N=2095), 454 were US-born, 1639 were
foreign-born, and 2 did not identify a place of birth. Interviews were offered in English,
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Mandarin, Cantonese, Tagalog, and Vietnamese. The three largest ethnic groups
represented were Chinese (32%), Filipino (20%), and Vietnamese (16%). Participants
self-identified with national origins in the regions of East Asia, Southeast Asia, South
Asia, and Central Asia. This analysis only included data from foreign-born Asian
American participants aged 18 and over (N=1583).
Measures
Mood Dysfunction. Our dependent variable was the presence of mood
dysfunction in the 12 months prior to the interview (12 month period prevalence). Mood
dysfunction was a composite formed by the presence of at least one clinical or subclinical symptom of anxiety or affective disorder, as measured by the Composite
International Diagnostic Interview (CIDI; World Health Organization). The CIDI is the
most widely used structured diagnostic interview and was designed to be used across
cultures. This composite variable has been used in other published studies using this
dataset (Leu et al., 2008).
Individual acculturation measures. Three measures of individual acculturation
were used. These measures reflect the most common items in acculturation scales (e.g.,
Zane & Mak, 2002). English language proficiency was measured using a scale that asked
the respondent to rank his or her ability to speak, read and write in English. Participant’s
scores were the sum of three questions. Response categories ranged from (1) poor to (4)
excellent, yielding minimum and maximum scores from 3 to 12. Higher values reflected
greater English proficiency.
The amount of time spent in the US was calculated in relation to a participant’s
age and age at immigration. While many acculturation scales only include years in the
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host country as a measure of exposure to a new culture, recent evidence suggests that the
age at immigration is also relevant to understanding cultural exposure in relation to mood
dysfunction (Takuechi cite; Leu Cite). Therefore, we created a variable to measure the
proportion of an immigrant’s life spent in the US (e.g., (current age – age at
immigration)/current age)), which has been used in other studies (Juon et al., 2000;
Maxwell, Bastani, & Warda, 2000). Responses ranged from (0%) to (100%).
Ethnic identification consisted of one measure, using a 4-point scale (Felix-Ortiz,
Newcomb, & Myers, 1994). Participants responded to the questions, “How close do you
feel, in your ideas and feelings about things, to other people of the same racial and ethnic
descent?” This question has been used as a measure of ethnic identity in other studies
(Tseng, Takeuchi, X); it is similar to items in other scales of ethnic identification,
including the Suinn-Lew Asian Self-Identity Acculturation Scale which is the most
commonly used acculturation scale among Asian Americans (Suinn, Rickard-Figueroa,
Lew & Virigil, 1987; Zane et al., 2002).
Family context measure. To measure family context, participants were asked to
respond to five questions about family cultural conflict (a subscale from Cervantes cite).
The scale included items such as, “You have felt that being too close to your family
interfered with your own goals,” and “Because you have different customs, you have had
arguments with other members of your family.” Response categories ranged from (1)
hardly ever to (3) often, yielding minimum and maximum sum scores from 5 to 15.
Higher values indicated greater cultural conflicts in the family context.
Neighborhood context measure. To measure the influence of ethnic density in an
immigrant’s neighborhood on mood dysfunction, we operationalized ethnic density of
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their neighborhoods by dividing the number of Asians by the total population of the
census tract. Minimum and maximum scores ranged from 0% to 69.6%. Higher values
reflected greater ethnic density in the participant’s neighborhood.
Community reception context measure. As a broad measure of reception by other
racial/ethnic groups in the US, participants responded to an 9-item scale measuring
everyday discrimination (James cite). This scale is obtained by adding up the answers to
the following questions: “You are treated with less courtesy than other people;” “You are
treated with less respect than other people;” “You receive poorer service than other
people at restaurants or stores;” “People act as if they think you are not smart;” “People
act as if they are afraid of you;” “People act as if they think you are dishonest;” “People
act as if you are not as good as they are;” “You are called names or insulted;” and “You
are threatened or harassed.” Response categories ranged from (1) almost every day to (6)
never; scores were reverse coded so that higher value indicates more often discriminated,
yielding minimum and maximum scores from 9 to 54. Higher values reflected more
frequent perceived discrimination.
Demographics. Five groups of demographic variables were used as control
variables. Each of these variables, socioeconomic status, marital status, age, gender,
ethnicity, and citizenship, is associated with mental health outcomes. Socioeconomic
status was measured using five items, including educational attainment, household
income, family size, employment status, and subjective social status. Marital status, age,
ethnicity, and citizenship were measured using single-item measures.
Socioeconomic status was considered measured in five ways. Educational
attainment was measured by having respondents indicate the number of years of
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schooling they had completed. Household income was the sum of the midpoints of the
following income measures: personal, spouse, other family members, social security,
government assistance, and other sources. Because of a large number of missing values
(270 missing), this variable was imputed using hot deck methods based on the variables
of ethnicity, sex, age, education, household composition, and employment status. We
divided household income by 1000 and collapsed it into four categories that we represent
as a series of meaningful dichotomies, using $80,000 or more as the reference group. We
controlled for the family size in order to make household income interpretable at the
individual level among immigrants. Many participants did not report their occupation
(95 missing values). Instead, employment status was calculated by categorizing
participants as employed, unemployed, out of the labor force, or missing.
Lastly, we used a new measure of socioeconomic status which has been
demonstrated to be associated with mental health outcomes in immigrant and nonimmigrant national studies (Adler et al., 1994; other cites). Our independent variable was
subjective social status, as measured by a symbolic ladder with ten rungs, where the first
and tenth rung represent the lowest and highest social status in the US, respectively
(Cantril, 1965; Adler et al., 2000). Respondents were asked to, “Think of this ladder as
representing where people stand in the US. At the top of the ladder are the people who
are the best off, those who have the most money, most education, and best jobs. At the
bottom are the people who are the worst off, those who have the least money, least
education, and worst jobs or no job. What is the number to the right of the rung where
you think you stand at this time in your life, relative to other people in the United
States?”
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Demographic variables. Gender, ethnicity, US citizenship, and marital status
were included in our analysis. Gender was coded as either male or female depending on
participants’ self-identification. Ethnicity was categorized into one of four groups
(Vietnamese, Filipino, Chinese, and Other Asian), where Chinese was the reference
group as the largest ethnicity represented. US citizenship was dichotomized non-citizen
versus citizen (reference group). Marital status was dichotomized married versus nonmarried (reference group).
Results
Statistical Analysis
Our main analysis consists of a series of nested multivariate survey logistic
regression models, split by gender, which assess the net effect of acculturation variables
on the presence of mood dysfunction. The analyses were split by gender to allow for an
easier interpretation of potential three-way interaction effects across gender, individual
acculturation variables, and social context variables. All of the analyses adjust for the
hierarchical nature of the multistage survey data using SAS-callable SUDAAN
procedures. The SUDAAN procedures allow for the incorporation of complex survey
sampling methods, including designs with stratification, clustering, and unequal sampling
weights, in the point and standard error (SE) estimation.
Since we have different sets of analyses to describe, we will move back and forth
through different tables depending on the variables under consideration. The analyses
consist of four tables. Table 1 provides descriptive statistics for the total sample, and
stratifies the sample by gender. T-tests were used to compare the weighted means for all
variables by gender. Table 2 reports the results from a series of survey logistic
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regressions that focus on the relationship between conventional acculturation measures
and social contexts and their relationship to mood dysfunction among immigrant males.
Table 3 reports the results among immigrant females. We report unstandardized
maximum likelihood coefficients and their significance levels. We perform this analysis
in five steps. Model 1 tests the unadjusted bivariate relationship of conventional
acculturation variables with mood dysfunction, controlling for relevant demographic
variables. Models 2, 3, and 4 sequentially add social context variables (e.g., family,
neighborhood, and community reception) to determine if the effects of conventional
acculturation measures on mood dysfunction remain after their inclusion in the analyses.
In Model 4, we test the combined effect of social contexts and conventional acculturation
variables on mood dysfunction.
Table 4 tests whether mood dysfunction depends on interactions between
conventional acculturation measures and social contexts, separately for immigrant males
and females. For example, the social context of the community reception is determined
to moderate the relationship between a conventional acculturation variable and mood
dysfunction if there is a significant interaction between English proficiency and perceived
discrimination (Baron & Kenny, 1986). Similarly, the social context of family is tested
as a moderator of the association between ethnic identification and mood dysfunction.
All possible interactions between conventional measures of acculturation and social
context were tested; however, only significant results are reported in Table 4.
Descriptive statistics and associations
Descriptive statistics. We limited data to foreign-born participants aged 18 and
older (N=1583). Almost twelve percent of the sample reported mood dysfunction in the
15
past 12 months (see Table 1). Weighted 12-month period prevalence was based on the
presence of at least one clinical or sub-threshold report of an affective or anxiety disorder
in the past 12 months (including symptoms of panic disorder, agoraphobia, social phobia,
post-traumatic stress disorder, generalized anxiety disorder, major depressive episode and
dysthymia). Participants could have reported multiple dysfunctions.
Respondents reported above-average proficiency in English (M = 8.1mean on a
scale of 3 to 12), spent roughly 40% of their lives in the US (SE = 1.38), and were
relatively high in their ethnic identification (M = 3.24 on a scale of 1 to 4). Relatively
low levels of family cultural conflict (M = 6.6 on a scale of 5 to 15) and perceived
discrimination (M = 15.7 on a scale of 9 to 54). The mean ethnic density of Asians in the
neighborhood of residence was 24% (SE = 1.43).
The average age was 42 years old (SE = 0.82), and 72% (SE = 2.96) of the sample
was married. The sample was 53% female. The mean number of years of formal
education was 13 (SE = 0.19), the mean household income was $80,000
(median=$64,500). Roughly 64% (SE = 1.74) of the total sample was employed, and
participants ranked themselves as having above-average social status relative to other
Americans (M = 5.8 on a subjective social status scale of 1 to 10).
Descriptive associations. Among immigrant males, English proficiency levels
were significantly correlated with proportion of life in the US (r = 0.32; p<.001) but was
not associated with ethnic identification (r = -0.06; n.s.). Ethnic identification and
proportion of life in the US were negatively associated (r = -0.19; p<001). Among
immigrant females, English proficiency levels were significantly correlated with
proportion of life in the US (r = 0.40; p<.001). English proficiency was negatively
16
associated with ethnic identification (r = -0.16; p<001). Similarly, ethnic identification
and proportion of life in the US were also negatively associated (r = -0.23; p<001).
Comparisons by gender. As see in Table 1, Asian immigrant males were more
proficient in English than females, reported more perceived discrimination, achieved
greater educational attainment, and were significantly more likely to be employed (73%
versus 56%). Consistent with the last finding, women were more likely to be out of the
labor force or to have missing employment data, compared with men.
Hypothesis 1: Conventional acculturation variables as predictors of mental health
Males. Table 2 presents the results of Model 1 that examined the relationship
between conventional acculturation measures, controlling for demographics, and mood
dysfunction. English language proficiency was a significant predictor of mood
dysfunction (B=-0.29 (0.09), p<0.01) after adjusting for relevant demographic measures.
Greater proficiency in English was associated with a lower chance of mood dysfunction.
Ethnic identity was also a significant predictor of mood dysfunction (B=-0.45 (0.16),
p<0.01) after adjusting for relevant demographic measures. Stronger ethnic identity was
associated with a lower chance of mood dysfunction. Proportion of life in the US was
not related to mood dysfunction.
Females. Table 3 presents the results of Model 1 that examined the relationship
between conventional acculturation measures, controlling for demographics, and mood
dysfunction among immigrant females. None of the conventional acculturation measures
was associated with mood dysfunction after controlling for relevant demographic
measures.
Hypothesis 2: Social contexts as predictors of mental health
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Males. Table 2 presents four models that examined the relationship between
social contexts and mood dysfunction. Models 2, 3, and 4 test the effect of a single social
context on mood dysfunction; Model 5 tests the independent effects for each social
context when they are entered into the model simultaneously. Family cultural conflict
was a significant predictor of mood dysfunction (B= 0.34 (0.06), p<0.001) after adjusting
for conventional acculturation variables and relevant demographics (Model 2). Higher
ratings of family cultural conflict were associated with higher chances of mood
dysfunction. Neighborhood ethnic density was also a significant predictor of mood
dysfunction (B= -2.56 (0.79), p<0.01) after adjusting for conventional acculturation
variables and relevant demographics (Model 4). Greater ethnic density in the
neighborhood was associated with lower chances of mood dysfunction. Everyday
discrimination was also a significant predictor of mood dysfunction (B= 0.07 (0.02),
p<0.01) after adjusting for conventional acculturation variables and relevant
demographics (Model 3). Higher ratings of perceived discrimination were associated
with higher chances of mood dysfunction.
In Model 5, when the social context variables were entered simultaneously, only
family cultural conflict and neighborhood ethnic density remained significantly
associated with mood dysfunction, controlling for conventional acculturation variables
and relevant demographic measures. Greater family cultural conflict was associated with
increased chances of mood dysfunction (B= 0.92 (0.80), p<0.001), whereas greater ethnic
density was associated with decreased chances of mood dysfunction (B= -2.30 (0.86),
p<0.05).
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Females. Among immigrant females, family cultural conflict was a significant
predictor of mood dysfunction (B= 0.36 (0.07), p<0.001) after adjusting for conventional
acculturation variables and relevant demographics (Model 2 in Table 3). Higher ratings
of family cultural conflict were associated with higher chances of mood dysfunction.
Neighborhood ethnic density was not a significant predictor of mood dysfunction, after
adjusting for conventional acculturation variables and relevant demographics (Model 4).
Everyday discrimination was a significant predictor of mood dysfunction (B= 0.09 (0.03),
p<0.01) after adjusting for conventional acculturation variables and relevant
demographics (Model 3). Higher ratings of perceived discrimination were associated
with higher chances of mood dysfunction.
In Model 5, when the social context variables were entered simultaneously, only
family cultural conflict remained significantly associated with mood dysfunction,
controlling for conventional acculturation variables and relevant demographic measures.
Greater family cultural conflict was associated with increased chances of mood
dysfunction (B= 0.31 (0.07), p<0.001).
Hypothesis 3: Social contexts as moderators in the relationship between conventional
acculturation measures and mental health
Males. We explored the possibility that social contexts may moderate the
relationship between conventional acculturation variables and mood dysfunction. As
seen in Model 1 of Table 4, perceived discrimination moderated the relationship between
language proficiency and mood dysfunction (B= -0.01 (0.01), p<0.05). Figure 1
demonstrates that perceived discrimination and mental health outcomes was significantly
more strongly associated among immigrant males with poor or fair English proficiency
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(B= 0.11 (0.05), p<0.05) than among those with good or excellent English skills
(reference group). No other interactions between acculturation variables and social
contexts were statistically significant.
This interaction changed the results presented in Model 5 of Table 2. With the
interaction, English language proficiency was no longer directly associated with mood
dysfunction. Instead, perceived discrimination was significantly associated (B= 0.15
(0.05), p<0.01). Family cultural conflict (B= 0.28 (0.08), p<0.001) and ethnic density
(B= -2.28 (0.93), p<0.05) remained significantly associated. Therefore, in the presence
of an interaction between English language proficiency and perceived discrimination, no
conventional acculturation measures were directly associated with mood dysfunction
among immigrant males.
Females. As seen in Model 2 of Table 4, the family social context moderated the
relationship between ethnic identity and mood dysfunction (B= -0.19 (0.09), p<0.05).
Figure 2 demonstrates that family cultural conflict and mental health outcomes were
more strongly associated among immigrant females who were strongly identified with
their ethnicity than among those who were less identified. No other interactions between
acculturation variables and social contexts were statistically significant.
This interaction changed the results presented in Model 5 of Table 3. With the
interaction, ethnic identity became significantly associated (B= 1.85 (0.81), p<0.05) with
mood dysfunction among immigrant females. Family cultural conflict was no longer a
significant predictor. Therefore, in the presence of an interaction between ethnic identity
and family cultural conflict, one conventional acculturation measure (e.g., ethnic identity)
20
and no social context measures became directly associated with mood dysfunction among
immigrant females.
Discussion
Three hypotheses were tested using the first nationally representative sample of
Asian American mental health. Conventional acculturation variables were predicted to
be associated with symptoms of anxiety and affective disorders among immigrant males
and females. Social contexts were also predicted to be directly associated with the
mental health outcome. Additionally, social contexts were expected to moderate the
relationship between conventional acculturation variables and mood dysfunction.
Individual acculturation traits influence immigrant mental health
Even after considering the influences of relevant social contexts, ethnic identity
seems potentially important to mental health among Asian immigrant women. Among
immigrant females, frequent family cultural conflict seems a particularly high risk among
those who are highly identified with their ethnic identity. English language proficiency
was also relevant to the mental health of immigrant males in the context of community
reception. For example, perceived discrimination among immigrant males with poor
English proficiency seems especially powerful in predicting poor mental health. We
found no evidenced that time in the host country was relevant to immigrant mental health.
Social contexts influence immigrant mental health
The inclusion of social contexts in models of immigrant mental health suggests
that family, neighborhood, and community reception social contexts are all relevant.
Among immigrant males, increasing family cultural conflict is a risk factor, whereas
living in a neighborhood with increasing representation of other Asians seems to protect
21
against poor mental health. Discrimination is associated with increases in the likelihood
of poor mental health. Furthermore, discrimination seems especially harmful for
immigrant males who have poor or fair English language proficiency, perhaps because
immigrant males may attribute unfair treatment to a personal failure more easily if they
speak English poorly than if they spoke English well. Fluent English speakers who
experience discrimination may be more likely than poor English speakers to interpret the
unfair treatment as racial discrimination. Literature in social psychology suggests that
attributing unfair treatment to racial bias may protect self-esteem (Crocker & Major,
1989).
Among immigrant females, family cultural conflict seems especially harmful
among those who are highly identified with their ethnicity. This may be because family
harmony is a central Asian cultural value, especially for women. Women who are not
identified with their Asian ethnicity may find conflict over cultural values in the family
less disruptive compared with those who feel closely aligned with the value of family
harmony.
Social contexts moderate the association between acculturation and mental health
The analyses also demonstrated the sensitivity of the relationship between
conventional acculturation measures with mental health outcomes to social context.
For example, when examining only the influence of conventional single-measure
acculturation variables among males, English proficiency and ethnic identification were
protective of mood dysfunction. However, once three social contexts representing
increasingly macro-environments were added to the model, only English proficiency was
still significant. Instead, we observed that family conflict was a risk factor, and that
22
neighborhood ethnic density was a protective factor, relative to immigrant male mental
health. Finally, when an interaction between English language proficiency and
discrimination was modeled, no conventional acculturation measures were significantly
related with mood dysfunction.
The results also suggest some sensitivity to social context when examining the
influence of acculturation on the mental health of immigrant females. Whereas no
conventional acculturation measures were observed to be related to symptoms of
depression and anxiety when social contexts were considered, family cultural conflict
was observed as a significant predictor. However, when an interaction between ethnic
identity and family cultural conflict was added, this effect disappeared. Instead, the
conventional acculturation measure of ethnic identity was observed as a risk factor
among immigrant females, whereas in early models of immigrant males, ethnic identity
was observed as a protective factor.
Gender is an important social context
One of the most striking findings was that the results differed greatly by gender.
Family cultural conflict was the only predictor that influenced the mental health of both
immigrant males and females. Ethnic identity only influenced mental health among
immigrant females when all significant interactions between acculturation and social
contexts were considered. Among immigrant males, however, discrimination,
neighborhood ethnic density, and English language proficiency were associated with
mental health when all interactions were modeled. It is not clear why ethnic identity
seems only relevant Asian immigrant women…
Family context is important to immigrant mental health
23
These results suggest the potential significance of the family context, as measured
by the frequency of cultural conflict, on the mental health of Asian immigrant males and
females. Of the three most commonly used conventional individual-level acculturation
measures and three ecological-level social context measures, only family cultural conflict
was significantly related to symptoms of depression and anxiety among both genders.
Among immigrant males and immigrant females who are highly identified with their
ethnicity, family conflict acts as a risk factor for poor mental health.
Limitations
A panel study is needed to adequately justify a causal interpretation of the
observed associations in this cross-sectional study. These findings remain important
because this is the only study that examines acculturation within social contexts using a
nationally representative sample of Asian immigrants in the U.S, including multiple
ethnic groups. Therefore, it is more generalizable to the population of Asian immigrants
than convenience samples. While Asians comprised only 4% of the US population in
2005, they are expected to be 13% of the population by 2050 (Pew Research Center,
2008). As a result of migration, roughly one in ten American adults is foreign-born
(Urban Institute, 2004; US Census, 2000). Therefore, it is important to test an
interactional, ecological model of acculturation in other immigrant groups.
There may have been significant predictors of mood dysfunction relevant to
immigrant mental health that we missed. However, in trying to build a model that could
explain more variability in the rates of mental health problems, neither family cohesion
nor social cohesion was a significant buffer against mental health distress.
Significance of findings
24
Since the analytical model includes both individual-level conventional variables
and macro-level social contexts, these results make a significant theoretical and empirical
demonstration that individual acculturation traits, social contexts, and gender matter in
the health of immigrants. More importantly, these results suggest that individual-level
acculturation traits interact with social contexts and gender to impact mental health.
Family cultural conflict seems to be a particularly important predictor of mental
health among both immigrant males and females. Given this, exactly what domains of
family cultural conflict and the mechanisms by which conflict impacts health deserve
more research attention. Individual-level acculturation traits, on the other hand, seem
potentially predictive of mental health among immigrants when considered in their social
context. The interactions between individual acculturation traits (i.e., English language
proficiency, ethnic identity) and social contexts (i.e., community reception context and
family context) suggest that mental health needs to be understood at the intersection of
the individual, gender, and society, perhaps particularly for immigrants.
25
Table 1. Descriptive Statistics for Total Sample and Stratified by Gender (N=1583)
Total Sample (N=1583)
Males (n=749)
Variable
Mean
SE
Mean
SE
Mood Dysfunction
11.9%
(0.87)
10.3%
(1.46)
English Language Proficiency (scale 3 to 12)
8.06
(0.19)
8.27
(0.21)
Proportion of Life in US
39.1%
(1.38)
39.9%
(1.79)
Ethnic Identification (scale 1 to 4)
3.24
(0.03)
3.24
(0.04)
Family Cultural Conflict (scale 5 to 15)
6.57
(0.06)
6.56
(0.08)
Everyday Discrimination (scale 9 to 54)
15.73
(0.21)
16.60
(0.42)
Ethnic Density
23.9%
(1.43)
24.0%
(1.69)
Education (years)
13.48
(0.19)
13.87
(0.22)
Household Income (thousands of dollars)
79.92
(2.96)
85.27
(4.12)
Subjective Social Status (scale 1 to 10)
5.76
(0.09)
5.69
(0.14)
Employment Status
Employed
63.7%
(1.74)
72.7%
(1.98)
Unemployed
6.5%
(0.73)
5.7%
(0.79)
Out of Labor Force
16.9%
(1.62)
12.6%
(1.73)
Missing
13.0%
(1.44)
9.0%
(1.54)
Family Size (persons)
2.95
(0.07)
2.93
(0.10)
Married
72.4%
(1.64)
71.6%
(2.76)
Age (years)
42.27
(0.82)
41.59
(0.95)
Ethnicity
Vietnamese
15.4%
(2.26)
15.4%
(2.29)
Filipino
19.9%
(2.28)
18.2%
(2.41)
Chinese
30.5%
(3.22)
30.2%
(3.58)
Other Asian
34.2%
(2.66)
36.3%
(3.51)
Non-citizen
40.6%
(2.49)
42.7%
(2.91)
*p<.05, **p<.01, ***p<.001
Females (n=834)
Mean
SE
13.3%
(1.51)
7.88
(0.19)
38.5%
(1.61)
3.24
(0.03)
6.57
(0.08)
14.98
(0.26)
23.8%
(1.35)
13.15
(0.21)
75.22
(3.64)
5.82
(0.09)
55.8%
7.2%
20.6%
16.4%
2.97
73.1%
42.87
(2.47)
(1.22)
(2.56)
(1.94)
(0.09)
(1.87)
(0.87)
15.5%
21.3%
30.9%
32.3%
38.7%
(2.38)
(2.55)
(3.23)
(2.54)
(2.72)
Gender
Difference
*
**
***
***
**
**
Table 2. Logistic Regressions of Conventional Acculturation Measures and Social Contexts on Mood Dysfunction among Males (n=749)
Model 1
Model 2
Model 3
Model 4
Model 5
Variables
B
(SE)
B
(SE)
B
(SE)
B
(SE)
B
(SE)
Intercept
-1.03
(1.27) -3.69
(1.33)
-1.90
(1.18)
-0.51
(1.28) -3.42*
(1.45)
English Language Proficiency
-0.29** (0.09) -0.23*
(0.09)
-0.28**
(0.08)
-0.30** (0.09) -0.24*
(0.09)
Proportion of Life in US
1.89
(1.13)
1.52
(1.08)
1.53
(1.11)
1.80
(1.15)
1.30
(1.07)
Ethnic Identification
-0.45** (0.16) -0.42*
(0.20)
-0.41*
(0.17)
-0.40*
(0.18) -0.37
(0.23)
Family Cultural Conflict
0.34***
(0.06)
0.29*** (0.08)
Everyday Discrimination
0.07**
(0.02)
0.04
(0.02)
Ethnic Density
-2.56** (0.79) -2.30*
(0.86)
*p<.05, **p<.01, ***p<.001
Note: Models control for Education, Household Income, Subjective Social Status, Employment Status, Family Size, Marital Status, Age, Ethnicity, and Citizenship
Table 3. Logistic Regressions of Conventional Acculturation Measures and Social Contexts on Mood Dysfunction among Females
(n=834)
Model 1
Model 2
Model 3
Model 4
Model 5
Variables
B
(SE)
B
(SE)
B
(SE)
B
(SE)
B
(SE)
Intercept
-0.58
(1.36) -3.86*
(1.58)
-1.82
(1.40)
-0.63
(1.34) -4.09*
(1.53)
English Language Proficiency
-0.02
(0.07) -0.01
(0.09)
-0.05
(0.07)
-0.02
(0.07) -0.03
(0.08)
Proportion of Life in US
1.00
(0.84)
1.03
(1.01)
0.97
(0.86)
1.00
(0.84)
0.98
(1.00)
Ethnic Identification
0.36
(0.23)
0.49
(0.25)
0.30
(0.23)
0.36
(0.23)
0.43
(0.27)
Family Cultural Conflict
0.36***
(0.07)
0.31*** (0.07)
Everyday Discrimination
0.09**
(0.03)
0.05
(0.03)
Ethnic Density
0.23
(0.62) -0.07
(0.66)
*p<.05, **p<.01, ***p<.001
Note: Models control for Education, Household Income, Subjective Social Status, Employment Status, Family Size, Marital Status, Age, Ethnicity, and Citizenship
27
Table 4. Logistic Regressions of Conventional Acculturation Measures, Social Contexts , and Interactions on
Mood Dysfunction
Model 1
Males
Variables
Intercept
English Language Proficiency
Proportion of Life in US
Ethnic Identification
Family Cultural Conflict
Everyday Discrimination
Ethnic Density
English Language Proficiency * Everyday Discrimination
Ethnic Identification * Family Cultural Conflict
B
-5.59**
0.03
1.45
-0.37
0.28***
0.15**
-2.28*
-0.01*
(SE)
(1.65)
(0.15)
(1.01)
(0.21)
(0.08)
(0.05)
(0.93)
(0.01)
Model 2
Females
B
(SE)
-8.81**
-0.04
0.91
1.85*
0.92
0.06
-0.11
(3.16)
(0.09)
(1.01)
(0.81)
(0.33)
(0.03)
(0.67)
-0.19*
(0.09)
*p<.05, **p<.01, ***p<.001
Note: Models control for Education, Household Income, Subjective Social Status, Employment Status, Family Size, Marital Status,
Age, Ethnicity, and Citizenship
28
Figure 1.
Predicted Probability of Mood Dysfunction
1.00
0.90
0.80
 Low English Proficiency
 High English Proficiency
0.70
0.60
0.50
0.40
0.30
0.20
0.10
0.00
9
18
27
36
45
54
Everyday Discrimination
29
Figure 2.
Predicted Probability of Mood Dysfunction
1.00
0.90
0.80
 High Ethnic Identification
0.70
 Low Ethnic Identification
0.60
0.50
0.40
0.30
0.20
0.10
0.00
5
6
7
8
9
10
11
12
13
14
15
Family Cultural Conflict
30