O R I G I N A L P A P E R
Acculturation and Disability Rates Among Filipino-Americans
Leanne R. De Souza • Esme Fuller-Thomson
Published online: 11 October 2012
� Springer Science+Business Media, LLC 2012
Abstract Filipinos are the fastest growing Asian
subgroup in America. Among immigrants, higher accul-
turation (adaptation to host society) predicts disability
outcomes and may relate to disability prevalence among
older Filipinos. We conducted a secondary analysis of the
2006 American Community Survey using a representative
sample of older Filipinos (2,113 males; 3,078 females) to
measure functional limitations, limitations in activities of
daily living, blindness/deafness and memory/learning
problems. Filipino males who were Americans by birth/
naturalization had higher odds of blindness/deafness (OR
2.94; 95 % CI = 1.69, 5.12) than non-citizens. Males who
spoke English at home had higher odds of blindness/
deafness (OR 1.82; 95 % CI = 1.05, 3.17) and memory/
learning problems (OR 2.28; 95 % CI = 1.25, 4.15), while
females had higher odds of memory/learning problems (OR
1.75; 95 % CI = 1.13, 2.73). Acculturation is associated
with greater odds of disabilities for Filipino men. Males
may be more sensitive to acculturation-effects than females
due to culturally prescribed roles and gender-specific
experiences at the time of immigration.
Keywords Filipino � Disability � Activities of dailyliving � Immigration � Assimilation � Functional limitations
Introduction
The Asian American and Pacific Islander (AAPI) popula-
tion is the fastest growing minority group in the United
States, accounting for approximately 4 % of the total
population, with estimates projecting increases to 11 % or
41 million U.S. residents by the year 2050 [1]. To date,
studies about the health of Asian Americans have typically
aggregated ethnic groups into one category despite the fact
that there are considerable ethnic diversities in culture,
language, and immigration history among the different
Asian groups. However, recent research has highlighted the
importance of separating the study of each AAPI group
separately to focus on disparities among subpopulations
[2–5].
Among AAPIs in the United States, Filipinos form the
second largest subgroup after the Chinese, with one in five
Asians reporting Filipino ancestry [6]. The number of
Filipinos and other Asians immigrating to America
increased dramatically following amendments to immi-
gration laws in 1965 that removed Asian immigration
quotas. As such, by 2007 over 90 % of Filipinos in the U.S.
were foreign-born [7].
Older Filipino-Americans are comprised of three dis-
tinct groups based on their age at immigration: 35 %
immigrated before age 40, 30 % immigrated between 40
and 59 years of age and 35 % immigrated at 60 years or
older [7]. Growing evidence underscores the disparities in
health outcomes among individuals of Filipino ancestry
compared to their AAPI and Caucasian counterparts.
Studies range from child and adolescent health showing
higher prevalence of neonatal mortality, malnutrition, and
obesity [8], to studies demonstrating higher rates of cancer,
cardiovascular disease, diabetes, and mental illness among
adults [9–15]. Many of these chronic diseases show
L. R. De Souza (&)Institute of Medical Sciences, University of Toronto, Toronto,
ON, Canada
e-mail: [email protected]
E. Fuller-Thomson
Sandra Rotman Chair in Social Work, Factor Inwentash Faculty
of Social Work, University of Toronto, 246 Bloor Street West,
Toronto, ON M5S 1V4, Canada
e-mail: [email protected]
123
J Immigrant Minority Health (2013) 15:462–471
DOI 10.1007/s10903-012-9708-1
increasing prevalence with increasing age and accultura-
tion [14]. Though only a few studies have compared older
Filipinos to other AAPI subgroups, these consistently
report substantial vulnerabilities with respect to self-
reported mortality, depression, chronic diseases, physical
inactivity and disabilities [5, 16–18]. Moreover, higher
incidence and prevalence of blindness/deafness occurs
among immigrants, which may be related to socioeconomic
inequalities [19], type of employment and limited access to
job-related resources [20]. In the same way, blindness may
also be affected by similar socioeconomic variables and is
associated with many chronic diseases as a common
comorbidity [21].
In keeping with much of the recent gerontological
research [22, 23], we define ‘‘older’’ as age 55 and over.
Research indicates that functional health inequalities peak
in the 55–64 year old group, whether socioeconomic status
or differenes among visible minorities [24] are examined.
Indeed, studies have also demonstrated gender disparities
in disability outcomes that increase with age, where men
have worse outcomes of a serious medical nature than
women, while women have greater functional limitations
as they age [25]. The association between gender differ-
ences and health outcomes is complex and is affected by
variables such as reporting bias, acquired risk and biolog-
ical risk [26], and these in turn translate into different
mortality and morbidity outcomes [27].
A national survey study revealed that compared to their
U.S.-born counterparts, Chinese, Japanese and Filipino
immigrants had lower life expectancy and the risk of disability
and chronic disease increased according to length of residence
[28]. We recently showed that compared to Chinese respon-
dents, Filipinos had lower odds of cognitive problems, higher
odds of functional limitations and comparable odds of ADL
limitations [18]. Similarly, Kim and colleagues [17] found that
Filipinos exhibited marked differences in chronic diseases and
disability rates, and tended to have poor overall physical
health compared to Chinese, Japanese, and Koreans [17]. A
growing body of research underscores the apparent need to
disaggregate research of AAPIs to accurately portray the
varying disease burden of especially vulnerable subgroups
and to examine their respective life histories that lead to dis-
parities in disability rates.
Socioeconomic status (SES) and indicators of accultur-
ation are thought to influence health status [29]. A
comparison of older Asian-Americans with U.S.-born non-
Hispanic Whites showed that in later life, immigrant status
confers few disability advantages [30]. Moreover, disabil-
ity rates are influenced by the combined effects of age at
immigration and duration of residence in the U.S. [30].
Indeed, Cho and Hummer [16] found marked differences in
disability status across AAPI subgroups with variations
attributable to nativity, age and SES status.
Chronic health conditions often culminate in some form
of disability with older age and in turn, disability can
reflect the severity of chronic diseases and their co-
morbidities [29, 30]. Accordingly, disability is considered a
reliable quality-of-life indicator capturing the diseased and
healthy conditions and has been proposed as a more
accurate assessment of well-being than traditional mor-
bidity and mortality data [31]. Careful monitoring of dis-
ability rates in vulnerable populations can facilitate
intervention strategies [32, 33] and health promotion.
Considering the disparities of chronic diseases among adult
Filipinos compared to other AAPIs, it is evident that dis-
ability prevalence is an important issue to examine in this
group.
Previously we described the variability in disability rates
across seven AAPI subgroups [18]. In the present study, we
conducted a secondary analysis of the Filipino subgroup to
develop a profile of older Filipino-Americans living with
disabilities. This may provide insight to help policy makers
drive decision-making, resource allocation and develop-
ment of social support programs targeting the needs of
older Filipino-Americans. In addition, such an analysis
may also improve health care professionals’ ability to tailor
services to the most vulnerable Filipino-Americans.
Methods
The American Community Health Survey (ACS) is a
nationally representative survey of community-dwelling
and institutionalized Americans, conducted annually by the
U.S. Census Bureau [34]. The ACS replaces the long-form
of the U.S. Census. Sampling is based on the US Census
Bureau’s Master Address File [35]. Data collection started
with multiple mailed surveys; non-respondents were then
contacted through computer-assisted telephone surveys. A
random sample of those who were non-responders to both
the mail and telephone survey were visited in person and
interviewed face to face. This strategy resulted in a
response rate of 97.5 %. Institutionalized community
members included those living in nursing homes, in-patient
hospice facilities, psychiatric hospitals, and adult correc-
tional facilities were included [34].
In the present study, we use the 2006 ACS (98 %
response rate) to examine disability outcomes of older
Filipino adults aged 55 and older (n = 5,192) to charac-
terize a disability profile in this cross-section of the pop-
ulation. Four self-reported disability outcomes were
examined: Respondents were asked if they had any of the
following long-lasting conditions: (a) ‘‘Blindness, deafness
or a severe vision or hearing impairment’’ (vision/hearing
limitations) (b) ‘‘A condition that substantially limits one
or more basic physical activities such as walking, climbing
J Immigrant Minority Health (2013) 15:462–471 463
123
stairs, reaching, lifting, or carrying’’ (functional limita-
tions); and whether ‘‘Because of a physical, mental, or
emotional condition lasting 6 months or more’’ they had
difficulty: (a) ‘‘Learning, remembering, or concentrating’’
(memory loss and learning difficulties) and/or (b) ‘‘Dress-
ing, bathing, or getting around inside the home’’ (ADL
limitations). Each item included a dichotomous yes/no
response option.
Demographic variables collected included age groups
(55–64, 65–74, 75–84, and 85 years or older) and marital
status (never married, separated, divorced or widowed
versus ‘‘now married’’). The socioeconomic variable
measured was level of education (only primary school or
less, some high school, high school graduate, bachelor
degree and graduate degree). Factors of acculturation
included age at immigration (U.S. born, immigrated prior
to age 20, aged 20–39, 40–59, 60 or older), citizenship
(American by birth or naturalization, non-citizen), and
speaking English at home (yes, no).
Because the only socioeconomic variable available for
the institutionalized respondents was level of education we
used it as a surrogate for SES in our analysis.
Marital status, education level, speaking English at
home, age at immigration and citizenship were included in
each analysis in a nationally representative sample of Fil-
ipino-Americans. Each of these variables was included in a
series of gender-specific multivariate logistic regression
analyses to characterize factors associated with each of the
four types of disability. The weighted prevalence, odds
ratios (OR), and 95 % confidence intervals (CIs) for each
disability type were calculated. All statistical analyses were
conducted using SPSS 17.0. Due to the dichotomous out-
come measure in logistic regression, a regular R-Square
could not be used. The Nagelkerke R-square is a pseudo-
R-Square measure for logistic regression analyses that
provides a measure of the explained variability in the
model.
Results
Results for demographic information and all four disability
types: ADLs, functional limitations, blindness/deafness,
and memory/learning disabilities are shown in Tables 1
through 5 respectively. We report the Odds Ratios (OR)
and 95 % Confidence Intervals (CI) in the tables.
Acculturation Factors
The odds of memory or learning disabilities (Table 5) were
significantly higher among women who spoke English at
home compared to those who did not (OR 1.75; 95 %
CI = 1.13, 2.73) and among women who immigrated at
age 60 years or older in comparison to those born in the
U.S. (OR 1.93; 95 % CI = 1.03, 3.62). Alternatively,
among Filipino males, those who immigrated at age
20 years or younger had significantly higher odds for all
four disability types, in comparison to those born in the
U.S. as follows: ADLs (Table 2: OR 4.19; 95 % CI =
1.73, 10.15), functional limitations (Table 3: OR 1.95;
95 % CI = 1.13, 3.36), blindness or deafness (Table 4: OR
1.91; 95 % CI = 1.00, 3.67), and memory or learning
problems (Table 5: OR 3.30; 95 % CI = 1.40, 7.78).
Compared to non-citizens, Filipino males with Ameri-
can citizenship had significantly higher odds of blindness
or deafness (Table 4: OR 2.94; CI 1.69, 5.12). Compared to
those who did not speak English at home, males who spoke
English at home had significantly higher odds of blindness
or deafness (Table 4: OR 2.09; 95 % CI = 1.29, 3.39) and
memory or learning problems (Table 5: OR 2.28; 95 %
CI = 1.25, 4.15). Women who spoke English at home in
comparison to those who did not had increased odds of
memory or learning problems (Table 5: OR 1.75;
CI = 1.13, 2.73).
Demographic Factors
In comparison to females in the 55–64 year old age
bracket, each older age cohort had higher odds of disabil-
ity. For example as shown in Table 2, the odds of limita-
tions in ADLs were 2.05 (95 % CI 1.28, 3.28) times higher
for 65-74 year old women, 6.20 times higher (95 % CI
3.79, 10.16) for 75–84 year olds and 20.26 (95 %
CI = 11.18, 36.69) times higher for women aged 85 or
older. Similarly, for females, odds of functional limitations
were 2.6, 4.9 and 10.9 times higher, in the 65–74, 75–84
and 85? cohorts, respectively (Table 3). The patterns were
also similar for the other disability types: for those aged 85
and older in comparison to those aged 55–64, females odds
of blindness/deafness reached 13.20 (Table 4: 95 %
CI = 7.41, 23.53) and the odds of memory/learning prob-
lems was 11.05 (Table 5: 95 % CI = 6.47, 18.86). Similar
outcomes were found for males (Tables 2, 3, 4, 5).
Unmarried females had significantly higher odds of
functional limitations (Table 1: OR 1.28; 95 % CI = 1.05,
1.56), memory or learning problems (Table 5: OR 1.50;
95 % CI = 1.13, 2.00) and blindness or deafness (Table 4:
OR 1.63; 95 % CI = 1.19, 2.22), in comparison to married
females. Among males, unmarried status was associated
with higher odds of functional limitations in comparison to
married males (Table 3: OR 1.48; 95 % CI = 1.10, 2.01).
Socioeconomic Factors
Lower levels of education were associated with higher
odds of disability. In comparison to those with a graduate
464 J Immigrant Minority Health (2013) 15:462–471
123
degree, higher odds of functional limitations were apparent
for both males (OR 2.12; 95 % CI = 1.19, 3.77) and
females (OR 2.01; 95 % CI = 1.28, 3.16) who had only
completed primary school (Table 3). Similarly, the odds of
blindness or deafness were higher among males (OR 2.32;
95 % CI = 1.09, 4.91) and females (Table 4: OR 3.26;
95 % CI = 1.19, 7.82) with only primary school education
and the same was true for memory or learning problems
among males (OR 6.98; 95 % CI = 2.07, 23.54) and
females (OR 4.94; 95 % CI = 2.24, 10.90). The odds of
Table 1 Demographicdescription of Filipino male and
female respondents to the 2006
ACS survey
Variables Males
(n = 2,113)Females
(n = 3,079)Total
(n = 5,192)p value
ADL
No 2,000 (94.7 %) 2,883 (93.0 %) 4,883 (93.7 %) 0.014
Yes 113 (5.3 %) 196 (7.0 %) 309 (6.3 %)
Functional limitations
No 1,742 (83.2 %) 2,452 (79.4 %) 4,194 (80.9 %) 0.001
Yes 371 (16.8 %) 627 (20.6 %) 998 (19.1 %)
Blindness/deafness
No 1,899 (89.5 %) 2,844 (92.1 %) 4,743 (91.1 %) 0.001
Yes 214 (10.5 %) 235 (7.9 %) 449 (8.9 %)
Memory/learning
No 1,970 (93.4 %) 2,808 (90.5 %) 4,778 (91.6 %) 0.000
Yes 143 (6.6 %) 271 (9.5 %) 414 (8.4 %)
Demographics
Age
55–64 1,134 (53.7 %) 1,636 (50.9 %) 2,770 (52.0 %) 0.013
65–74 604 (27.9 %) 864 (28.5 %) 1,468 (28.3 %)
75–84 296 (14.9 %) 457 (16.0 %) 753 (15.6 %)
85? 79 (3.4 %) 122 (4.6 %) 201 (4.1 %)
Marital status
Never married/divorced/
separated/widowed
322 (16.1 %) 1,237 (44.2 %) 1,559 (33.1 %) 0.000
Yes 1,791 (83.9 %) 1,842 (55.8 %) 3,633 (66.9 %)
Education in levels
Primary 166 (7.8 %) 429 (14.8 %) 595 (12.0 %) 0.000
High school (no diploma) 110 (4.9 %) 210 (6.3 %) 320 (5.8 %)
High school (diploma ? other
education/not bachelors)
913 (42.5 %) 1,047 (35.6 %) 1,960 (38.3 %)
Bachelors degree 717 (34.5 %) 1,149 (35.5 %) 1,866 (35.1 %)
Graduate degree 207 (10.4 %) 244 (7.7 %) 451 (8.8 %)
Age at immigration
Born in the US 245 (11.4 %) 240 (7.4 %) 485 (9.0 %) 0.000
20 146 (6.4 %) 84 (2.3 %) 230 (3.9 %)20–39 954 (43.1 %) 1,429 (43.0 %) 2,383 (43.0 %)
40–59 553 (27.4 %) 984 (33.8 %) 1,537 (31.2 %)
60–100 215 (11.8 %) 342 (13.6 %) 557 (12.9 %)
Citizenship
Not a citizen 370 (19.6 %) 637 (23.3 %) 1,007 (21.8 %) 0.002
Citizen by birth or
naturalization
1,743 (80.4 %) 2,442 (76.7 %) 4,185 (78.2 %)
English-speaking
Does not speak English at home 1,829 (87.2 %) 2,697 (87.8 %) 4,526 (87.5 %) 0.52
Speaks english at home 284 (12.8 %) 382 (12.2 %) 666 (12.5 %)
J Immigrant Minority Health (2013) 15:462–471 465
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ADL disabilities were increased among females with only
primary school education (OR 2.48; 95 % CI = 1.06, 5.83)
compared to those with a graduate degree (Table 2). Fur-
thermore, women with only some high school had higher
odds of blindness or deafness (Table 4: OR 4.08; 95 %
CI = 1.60, 10.40) and memory or learning problems
(Table 5: OR 3.10; 95 % CI = 1.30, 7.41) than women
with a graduate degree. Women with a high school diploma
reported greater odds of memory or learning problems than
their peers with a graduate degree (Table 5: OR 2.54; 95 %
CI = 1.16, 5.55).
Males with only a high school diploma had higher odds
of blindness or deafness (Table 4: OR 2.53; 95 %
CI = 1.33, 4.80) compared to those with a graduate
degree. There was also a graded increase in the odds of
functional limitations among males who graduated from
high school (OR 1.64; CI 1.02, 2.63), to completion of only
some high school (OR 2.06; CI 1.09, 3.89), to only primary
school education (reported above) compared to those with
a graduate degree (Table 3). This increasing risk compared
to those with a graduate degree, was also observed for
memory or learning problems among Filipino males
(Table 5), from high school graduate (OR 5.42; CI 1.71,
17.18), to only some high school completed (OR 6.62; CI
1.83, 23.97), to only primary school (reported above).
Discussion
Few studies have investigated health outcomes of older
adults from distinct AAPI subpopulations [5, 16–18].
Disaggregating the study of AAPIs to evaluate the impact
Table 2 Logistic regression oflimitations in activities of daily
living (ADL) according to
demographic, socioeconomic
and immigration-related
variables in older Filipino males
(n = 2,113) and Females
(n = 3,079)
Per cent change in Nagelkerke
R Square associated with the
addition of education
level = 0.8 % male, 0.6 %
female
Per cent change in Nagelkerke
R Square associated with
addition of age at
immigration = 2.6 % male,
0.2 % female
Per cent change in Nagelkerke
R Square associated with
addition of citizenship status
and language spoken at
home = 0.01 % male, 0.1 %
female
Total Nagelkerke R-Square
value for full model = 0.179
male, 0.207 female
Nagelkerke R Square associated
with age and marital
status = 0.144 male, 0.198
female
Male Female
OR 95 % CI OR 95 % CI
Demographic variables
Age
55–64 1.00 Referent 1.00 Referent
65–74 1.05 (0.56, 1.93) 2.05 (1.28, 3.28)
75–84 4.23 (2.36, 7.58) 6.20 (3.79, 10.16)
85? 12.04 (5.85, 24.77) 20.26 (11.18, 36.69)
Marital status
Marital status
Not married 1.19 (0.72, 1.96) 1.21 (0.87, 1.69)
Married 1.00 Referent 1.00 Referent
Adult socioeconomic status
Education
Primary 1.59 (0.60, 4.25) 2.48 (1.06, 5.83)
Some high school 2.66 (0.96, 7.36) 2.00 (0.77, 5.20)
High school graduate 1.51 (0.64, 3.55) 2.15 (0.93, 4.94)
Bachelor degree 1.36 (0.55, 3.34) 1.46 (0.62, 3.42)
Graduate degree 1.00 Referent 1.00 Referent
Immigration and citizenship
Age at immigration
U.S. born 1.00 Referent 1.00 Referent
20 4.19 (1.73, 10.15) 0.97 (0.27, 3.44)20–39 0.90 (0.37, 2.23) 1.42 (0.69, 2.90)
40–59 1.33 (0.53, 3.31) 1.48 (0.74, 2.97)
60–100 1.58 (0.61, 4.09) 1.74 (0.84, 3.61)
Citizenship
American by birth or naturalization 1.44 (0.76, 2.72) 1.05 (0.71, 1.56)
Not a citizen 1.00 Referent 1.00 Referent
Speaks english at home
Yes 0.98 (0.48, 1.99) 1.25 (0.73, 2.15)
No 1.00 Referent 1.00 Referent
466 J Immigrant Minority Health (2013) 15:462–471
123
of migration histories, indicators of acculturation and
socio-demographic variables on health outcomes reveals
important insights into the health of vulnerable subgroups
[5] such as older Filipino-Americans.
Among the adult Filipino population we found that older
age, marriage, education and common indicators of
acculturation: speaking English at home, age at immigra-
tion and citizenship, were associated with higher odds of
functional disability, limitations in ADLs, memory or
learning problems and blindness or deafness. These asso-
ciations were different between men and women, indicat-
ing unique sex-specific factors associated with disability
outcomes.
Older age often involves some deterioration in physical
(functional limitations, ADLs, blindness or deafness) and
cognitive function (memory or learning problems) that
varies between genders regardless of ethnicity [36–38].
Research indicates that older women have a higher prev-
alence of disability and functional limitations than their
male peers [39]. The incidence of new disability among
older adults is generally higher in women, than in men
[40]. However, a systematic review of the literature indi-
cates that when studies control for socioeconomic factors
and health conditions, the gender differences in incidence
of functional disability are often reduced to non-signifi-
cance [40].
We found that unmarried females demonstrated signif-
icantly higher odds of functional limitations, blindness or
deafness and memory or learning problems in comparison
to married women. Conversely, marital status of males
showed no significant association with any of the four
types of disability and only approached significance with
functional limitations. Approximately half of Filipinos in
America are married, according to the 2000 U.S. census
Table 3 Logistic regression offunctional limitations according
to demographic, socioeconomic
and immigration-related
variables in older Filipino males
(n = 2,113) and females
(n = 3,079)
Per cent change in Nagelkerke
R Square associated with the
addition of education
level = 1.3 % male, 0.7 %
female
Per cent change in Nagelkerke
R Square associated with
addition of age at
immigration = 1.1 % male,
0.0 % female
Per cent change in Nagelkerke
R Square associated with
addition of citizenship status
and language spoken at
home = 0.3 % male, 0.1 %
female
Total Nagelkerke R-Square
value for full model = 0.168
male, 0.182 female
Nagelkerke R Square associated
with age and marital
status = 0.141 male, 0.174
female
Male Female
OR 95 % CI OR 95 % CI
Demographic variables
Age
55–64 1.00 Referent 1.00 Referent
65–74 1.37 (1.00, 1.88) 2.62 (2.05, 3.34)
75–84 4.49 (3.15, 6.41) 4.90 (3.64, 6.60)
85? 7.82 (4.45, 13.72) 10.88 (6.98, 16.94)
Marital status
Marital status
Not married 1.48 (1.10, 2.01) 1.28 (1.05, 1.56)
Married 1.00 Referent 1.00 Referent
Adult socioeconomic status
Education
Primary 2.12 (1.19, 3.77) 2.01 (1.28, 3.16)
Some high school 2.06 (1.09, 3.89) 1.58 (0.93, 2.67)
High school graduate 1.64 (1.02, 2.63) 1.45 (0.95, 2.22)
Bachelor degree 1.16 (0.70, 1.89) 1.21 (0.79, 1.85)
Graduate degree 1.00 Referent 1.00 Referent
Immigration and citizenship
Age at immigration
U.S. born 1.00 Referent 1.00 Referent
20 1.95 (1.13, 3.36) 0.90 (0.43, 1.90)20–39 0.94 (0.58, 1.52) 0.91 (0.60, 1.40)
40–59 0.88 (0.53, 1.48) 0.90 (0.59, 1.39)
60–100 1.16 (0.65, 2.05) 0.96 (0.60, 1.55)
Citizenship
American by birth or naturalization 1.42 (0.98, 2.08) 1.03 (0.80, 1.33)
Not a citizen 1.00 Referent 1.00 Referent
Speaks english at home
Yes 1.25 (0.83, 1.90) 0.84 (0.59, 1.19)
No 1.00 Referent 1.00 Referent
J Immigrant Minority Health (2013) 15:462–471 467
123
[6]. Research studies have described marriage as a pro-
tective factor for disability outcomes [7]. Moreover, evi-
dence shows that cognitive decline is more apparent in
women without a stable partnership [7].
Higher levels of education are considered protective
against cognitive problems and other disabilities [16]. In
the present study, for both genders, lower education levels
were associated with higher odds of functional limitations,
blindness or deafness and memory or learning problems.
A particularly strong association was apparent between
lower education level and memory or learning disabilities.
Education is a surrogate indicator of SES as it usually
indicates the propensity for job acquisition and career
development [7, 38, 41, 42]. Those individuals with higher
education are more likely to be employed and may receive
benefits that support resources for medical care and
improved quality of life, important factors to delaying
disability. Even with lower education, men in this cohort
may have been able to access job opportunities for financial
security. Moreover, men in our cohort may have belonged
to a population of early immigrant Filipino men who were
active members of the U.S. military and as such, acquired
citizenship through the U.S. Immigration and Naturaliza-
tion Act, which in 1990 permitted special provision of U.S.
citizenship to Filipino male veterans. Many of the older
Filipino males in our sample may have belonged to this
unique group, which could in turn contribute to some
specific cohort effects in our study [43].
Our findings are consistent with other research demon-
strating that higher SES as indicated by education corre-
sponds to lower mortality and morbidity rates [5, 44]. The
major exception in this study was the lack of a significant
Table 4 Logistic regression ofblindness/deafness/severe
sensory impairment according
to demographic, socioeconomic
and immigration-related
variables in older Filipino males
(n = 2,113) and females
(n = 3,079)
Per cent change in Nagelkerke
R Square associated with the
addition of education
level = 1.9 % male, 1.4 %
female
Per cent change in Nagelkerke
R Square associated with
addition of age at
immigration = 1.0 % male,
0.8 % female
Per cent change in Nagelkerke
R Square associated with
addition of citizenship status
and language spoken at
home = 2.1 % male, 0.0 %
female
Total Nagelkerke R-Square
value for full model = 0.220
male, 0.211 female
Nagelkerke R Square associated
with age and marital
status = 0.170 male, 0.189
female
Male Female
OR 95 % CI OR 95 % CI
Demographic variables
Age
55–64 1.00 Referent 1.00 Referent
65–74 2.76 (1.83, 4.17) 2.49 (1.61, 3.87)
75–84 6.66 (4.23, 10.50) 6.17 (3.87, 9.84)
85? 15.66 (8.39, 29.22) 13.20 (7.41, 23.53)
Marital status
Marital status
Not married 0.92 (0.62, 1.36) 1.63 (1.19, 2.22)
Married 1.00 Referent 1.00 Referent
Adult socioeconomic status
Education
Primary 2.32 (1.09, 4.91) 3.26 (1.36, 7.82)
Some high school 2.02 (0.88, 4.63) 4.08 (1.60, 10.40)
High school graduate 2.53 (1.33, 4.80) 2.31 (0.98, 5.47)
Bachelor degree 1.32 (0.66, 2.63) 1.90 (0.79, 4.57)
Graduate degree 1.00 Referent 1.00 Referent
Immigration and citizenship
Age at immigration
U.S. born 1.00 Referent 1.00 Referent
20 1.91 (1.00, 3.67) 0.37 (0.08, 1.62)20–39 1.06 (0.59, 1.91) 0.78 (0.41, 1.50)
40–59 1.30 (0.70, 2.41) 1.35 (0.73, 2.48)
60–100 1.75 (0.90, 3.40) 0.97 (0.50, 1.88)
Citizenship
American by birth or naturalization 2.94 (1.69, 5.12) 1.19 (0.82, 1.72)
Not a citizen 1.00 Referent 1.00 Referent
Speaks English at home
Yes 2.09 (1.29, 3.39) 0.97 (0.56, 1.67)
No 1.00 Referent 1.00 Referent
468 J Immigrant Minority Health (2013) 15:462–471
123
link between education and ADL limitations for males.
Speaking English at home and citizenship status were each
measured as common indicators of acculturation. The 2000
U.S. census reports that 29 % of Filipinos have less than a
9th
grade education and that 17 % are linguistically iso-
lated, with 56 % reporting that they do not speak English
very well [6]. Males who speak English at home had higher
odds of blindness or deafness. Speaking English at home
was also associated with higher odds of memory or
learning problems for both males and females. These sur-
prising findings should be replicated in other, large,
nationally representative surveys. Future research is also
needed to examine possible pathways and/or confounding
factors that may shed light on this association.
We also found that Filipino males who were U.S. citi-
zens had increased odds of blindness or deafness compared
to non-citizens. Foreign-born persons are thought to be
healthier than their U.S.-born counterparts because of the
self-selectivity of immigration and prerequisite health
requirements to migrate to the U.S. [45], their strong
family support systems [46] and resilience [7]. These
characteristics that describe the ‘healthy migrant effect’ are
thought to diminish over time with longer residence in the
U.S. due to deterioration of healthy behaviours [7, 28] and
adoption of American lifestyle and practices. In addition,
reasons for migration such as family reunification and
pursuit of job opportunities, alongside acculturation factors
can also have a positive influence toward improved
opportunities, access to healthy behaviours in the host
nation, knowledge and attitudes about health, stress man-
agement and accumulation of health resources [5].
In comparison to the US-born, only Filipino males who
immigrated before 20 years old had significantly higher
odds of all four disability types. This may be due to the
Table 5 Logistic regression ofmemory/learning problems
according to demographic,
socioeconomic and
immigration-related variables
for older Filipino males
(n = 2,113) and females
(n = 3,079)
Per cent change in Nagelkerke
R Square associated with the
addition of education
level = 2.6 % male, 2.6 %
female
Per cent change in Nagelkerke
R Square associated with
addition of age at
immigration = 1.7 % male,
0.4 % female
Per cent change in Nagelkerke
R Square associated with
addition of citizenship status
and language spoken at
home = 0.8 % male, 0.3 %
female
Total Nagelkerke R-Square
value for full model = 0.189
male, 0.212 female
Nagelkerke R Square associated
with age and marital
status = 0.138 male, 0.179
female
Male Female
OR 95 % CI OR 95 % CI
Demographic variables
Age
55–64 1.00 Referent 1.00 Referent
65–74 1.19 (0.70, 2.02) 2.36 (1.61, 3.47)
75–84 3.63 (2.13, 6.19) 4.82 (3.16, 7.37)
85? 8.89 (4.48, 17.62) 11.05 (6.47, 18.86)
Marital status
Marital status
Not married 0.94 (0.59, 1.50) 1.50 (1.13, 2.00)
Married 1.00 Referent 1.00 Referent
Adult socioeconomic status
Education
Primary 6.98 (2.07, 23.54) 4.94 (2.24, 10.90)
Some high school 6.62 (1.83, 23.97) 3.10 (1.30, 7.41)
High school graduate 5.42 (1.71, 17.18) 2.54 (1.16, 5.55)
Bachelor degree 3.17 (0.97, 10.42) 1.70 (0.77, 3.78)
Graduate degree 1.00 Referent 1.00 Referent
Immigration and citizenship
Age at immigration
U.S. born 1.00 Referent 1.00 Referent
20 3.30 (1.40, 7.78) 0.56 (0.15, 2.19)20–39 1.84 (0.80, 4.21) 1.48 (0.81, 2.71)
40–59 2.26 (0.96, 5.30) 1.69 (0.93, 3.04)
60–100 4.71 (1.95, 11.41) 1.93 (1.03, 3.62)
Citizenship
American by birth or naturalization 1.24 (0.74, 2.09) 1.04 (0.74, 1.45)
Not a citizen 1.00 Referent 1.00 Referent
Speaks english at home
Yes 2.28 (1.25, 4.15) 1.75 (1.13, 2.73)
No 1.00 Referent 1.00 Referent
J Immigrant Minority Health (2013) 15:462–471 469
123
early age at immigration, or potential cohort effects of this
particular age group. On the other hand, both men and
women who immigrated over the age of 60 years had
higher odds of memory or learning disabilities than US
born Filipino-Americans, which may reflect the reason for
immigration. The reasons for immigrating and timing of
migration among Filipinos are diverse and their experience
in the U.S. varies accordingly [7, 32]. Perhaps adult chil-
dren established in the U.S. sponsor their parents to
immigrate through family reunification policies when their
parents are in need of care, as would be the case for those
with Alzheimers disease or other chronic disease. [47].
There are a several limitations of this study that should be
considered when interpreting the results. Income and wealth
vary greatly among AAPI subpopulations [4, 42, 43,48] and
are highly correlated with level of disability in older adults.
However, information about wealth was not available in the
dataset, which precluded our analysis of this relationship.
Additionally, this data is based on a cross-sectional sample
that did not provide information about the onset and pro-
gression of disability; therefore we cannot determine causal
relationships in our findings [7]. Also, as described earlier,
another limitation inherent to the cross-sectional design of
this study is the potential cohort effects of particular waves of
immigrants that may render some of our findings specific to
this population.
Future cohorts of AAPI elders will differ with respect to
their early life experiences, education and economic status
that may correspond to improvements to functional status
[49].
Finally, the behavioural risk factors of Asian subpopu-
lations may change with time and could affect future
cohorts of aging Filipinos. For example, current neonatal
and childhood diabetes and obesity trends [8], and a shift
in employment opportunities away from agricultural jobs
[3–5], may change future disability trends. The rapid
growth of the AAPI population necessitates accurate and
representative data to make informed health policy and
planning decisions. Each AAPI ethnic group deserves
distinct attention in order to offer culturally-sensitive rec-
ommendations for vulnerable populations. The data
reported here were obtained from a nationally-representa-
tive sample including community-based and institutional-
ized elders. This study identified factors associated with
each of the four types of disabilities among older male and
female Filipino-Americans. Older adults, those who speak
English at home, the unmarried and those with only a
primary school education had higher odds of disability and
therefore Filipino-Americans with these characteristics
should be targeted for improved prevention and treatment
interventions.
Continued surveillance of national surveys and pro-
spective studies will permit further understanding of the
trends in disability outcomes among older Filipinos and
other under investigated AAPI subgroups. There is likely a
complex interplay between migrant selection effects,
positive versus negative acculturation effects, and SES
factors that relate to both timing of immigration and
country of origin [50]. This area of public health research is
especially important given the high prevalence and inci-
dence rates of chronic diseases and disability. Both chronic
diseases and disabilities result in a substantial economic
burden for the country as well as decreased quality of life
for the individual.
Acknowledgments The authors would like to thank Rachel Zhoufor her assistance with preparation of the tables.
References
1. Ghosh C. Healthy people 2010 and Asian Americans or Pacific
Islanders: defining a baseline of information. Am J Public Health.
2003;93:2093–8.
2. Yu ESH, Liu WT. U.S. national health data on Asian Americans
and Pacific Islanders: a research agenda for the 1990s. Am J
Public Health. 1992;82:1645–52.
3. Chen MS, Hawks BL. A debunking of the myth of healthy Asian
Americans and Pacific Islanders. Am J Health Promot.
1995;9:261–8.
4. Douglas KC, Fujimoto D. Asian Pacific elders: implications for
health care providers. Clin Geriatr Med. 1995;11:69–82.
5. Kuo J, Porter K. Health status of Asian Americans: United States,
1992–94. Adv Data. 1998;298:1–16.
6. U.S. Census Bureau. We the people: Asians in the United States,
Census 2000 special reports. Available at http://www.census.gov/
prod/2004pubs/censr-17.pdf. Updated 2004. Accessed 20 Oct
2010.
7. Mui AC, Shibusawa T. Asian American elders in the twenty-first
century: key indicators of well-being. 2008. p. 208.
8. Javier J, Huffman L, Mendoza F. Filipino child health in the
United States: do health and health care disparities exist? Prev
Chronic Dis. 2007;4:A36.
9. DeLaCruz F, McBride M, Compas L, Calixto PR, Van Derveer
C. White paper on the health status of Filipino Americans and
recommendations for research. Nurs Outlook. 2002;50:7–15.
10. Halfon N, Hochstein M. Life course health development: an
integrated framework for developing health, policy, and research.
Milbank Q. 2002; 80:433–79, iii.
11. Gomez S, Kelsey J, Glaser S, Lee M, Sidney S. Immigration and
acculturation in relation to health and health-related risk factors
among specific Asian subgroups in a health maintenance orga-
nization. Am J Public Health. 2004;94:1977–84.
12. Wise P. The transformation of child health in the United States.
Health affairs (Project Hope). 2004;23:9–25.
13. Fuller-Thomson E, Rotermann M, Ray JG. Elevated risk factors
for adverse pregnancy outcomes among Filipina-Canadian
women. J Obstet Gynaecol Can. 2010;32:113–9.
14. Cuasay LC, Sue Lee E, Orlander PP, Steffen-Batey L, Hans CL.
Prevalence and determinants of Type 2 Diabetes among Filipino-
Americans in the Houston, Texas metropolitan statistics area.
Diabetes Care. 2001;24:2054–8.
15. Chu KC, Chu KT. 1999–2001 cancer mortality rates for Asian
and Pacific Islander ethnic groups with comparisons to their
1988–1992 rates. Cancer. 2005;104(12 Suppl):2989–98.
470 J Immigrant Minority Health (2013) 15:462–471
123
16. Cho Y, Hummer R. Disability status differentials across fifteen
Asian and Pacific Islander groups and the effect of nativity and
duration of residence in the U.S. Soc Biol. 2001;48:171–95.
17. Kim G, Chiriboga DA, Jang Y, Lee S, Huang C, Parmelee P.
Heatlh status of older Asian Americans in California. J Am
Geriatr Soc. 2010;58:2003–8.
18. Fuller-Thomson E, Brennenstuhl S, Hurd M. Comparison of
disability rates among older adults in aggregated and separate
Asian American or Pacific Islander subpopulations. Am J Public
Health. 2010;101:94–100.
19. Helvik AS, Krokstad S, Tambs K. Socioeconomic inequalities in
hearing loss in a healthy population sample: The HUNT Study.
Am J Public Health. 2009;99(8):1376–8.
20. Rabinowitz PM, Kanta D, Sircar KD, Tarabar S, Galusha D,
Slade MD. Hearing loss among migrant agricultural workers.
J Agromedicine. 2005;10(4):9–17.
21. Roodhooft JM. Leading causes of blindness worldwide. Bull Soc
Belge Ophtalmol. 2002;283:19–25.
22. Anton SD, Manini TM, Milsom VA, et al. Effects of a weight loss
plus exercise program on physical function in overweight, older
women: a randomized controlled trial. Clin Interv Aging.
2011;6:141–9.
23. Paterson K, Hill K, Lythgo N. Stride dynamics, gait variability
and prospective falls risk in active community dwelling older
women. Gait Posture. 2011;33(2):251–5.
24. Nuru-Jeter AM, Thorpe RJ Jr, Fuller-Thomson E. Black-white
differences in self-reported disability outcomes in the U.S.: early
childhood to older adulthood. Public Health Rep. 2011;126(6):
834–43.
25. Gorman BK, Read JG. Gender disparities in adult health: an
examination of three measures of morbidity. J Health Social
Behav. 2006;47(2):95–110.
26. Macintyre S, Hunt K, Sweeting H. Gender differences in health:
are things really as simple as they seem? Soc Sci Med.
1996;42(4):617–24.
27. Murray JLC, Lopez AD. Alternative projections of mortality and
disability by cause 1990–2020: global burden of disease study.
Lancet. 1997;349(9064):1498–504.
28. Singh G, Miller B. Health, life expectancy, and mortality patterns
among immigrant populations in the United States. Can Journal
Public Health. 2004;95:I14–21.
29. Minkler M, Fuller-Thomson E, Guralnik J. Gradient of disability
across the socioeconomic spectrum in the United States. N Engl J
Med. 2006;355:695–703.
30. Mutchler JE, Pracash A, Burr JA. The demography of disability
and the effects of immigrant history: older Asians in the United
States. Demography. 2007;44:251–63.
31. Fuller-Thomson E, Yu B, Nuru-Jeter A, Guralnik J, Minkler M.
Basic ADL disability and functional limitation rates among older
Americans from 2000–2005: the end of the decline? J Gerontol
Ser A Biol Sci Medical Sci. 2009;64:1333–6.
32. Mui A, Kang SY. Acculturation stress and depression among
Asian immigrant elders. Soc Work. 2006;51:243–55.
33. Jane Field M, Jette MA, & of Medicine (U.S.). Committee on
disability in America: a new look, I. The future of disability in
America. 2007. p. 592.
34. U.S. Census Bureau. American Community Survey (ACS).
Available at: http://www.census.gov/acs/www/acs-php/quality_
measures_response_ 2006.php. Updated 2007. Accessed Jan
2011.
35. Use A—US Bureau of the Census. Design and methodology,
American Community Survey. Washington, US Government
Printing Office, 2009.
36. McBride M. Health and health care of Filipino American elders
[online]. Available at http:ororwww.standford.eduorgrouporethn
ogerorfilipino.html. Accessed Jan 2011.
37. Dey A, Lucas J. Physical and mental health characteristics of
U.S.- and foreign-born adults: United States, 1998–2003.
Advance data. 2006;369:1–19.
38. Frisbie W, Cho Y, Hummer R. Immigration and the health of
Asian and Pacific Islander adults in the United States. Am J
Epidemiol. 2001;153:372–80.
39. Merrill SS, Seeman TE, Kasl SV, Berkman LF. Gender differ-
ences in the comparison of self-reported disability and perfor-
mance measures. J Gerontol A Biol Sci Med Sci. 1997;52(1):
M19–26.
40. Rodrigues MA, Facchini LA, Thumé E, Maia F. Gender and inci-
dence of functional disability in the elderly: a systematic review.
Cad Saúde Pública Rio de Janeiro. 2009;25(Sup 3):S464–76.
41. Braveman PA, Cubbin C, Egerter S, Chideya S, Marchi KS,
Metzler M, et al. Socioeconomic status in health research: one
size does not fit all. J Am Med Assoc. 2005;294:2879–88.
42. Schoeni RF, Martin LG, Andreski PM, Freedman VA. Persistent
and growing socioeconomic disparities in disability among the
elderly: 1982–2002. Am J Public Health. 2005;95:2065–70.
43. American Coalition for Filipino Veterans Inc. History. Available
at: http://usfilvets.tripod.com/id10.html. Accessed May 2012.
44. Williams DR. Socioeconomic differences in health: A review and
redirection. Soc Phsychol Q. 53: 81–99. 1990. In Williams DR,
Lavizzo-Mourey R, Warren RC. The concept of race and health
status in America. Public Health Rep 1994: 26–41.
45. Marmot MG, Adelstein AM, Bulusu L. Lessons from the study of
immigrant mortality. Lancet. 1984;112:1455–7.
46. Landale NS, Oropesa RS, Lanes DL, Gorman BK. Does Amer-
icanization have adverse effects on health?: stress, health habits,
and infant health outcomes among Puerto Ricans. Soc Forces.
1999;78:613–42.
47. Lee RD, Enmsminger ME, LaVeist TA. The responsibility con-
tinuum: never primary, coresident and caregiver heterogeneity in
the African American grandmother experience. Int J Aging
Human Dev. 2005;60:295–304.
48. Kington RS, Smith JP. Socioeconomic status and racial and
ethnic differences in functional status associated with chronic
diseases. Am J Public Health. 1997;87:805–10.
49. Ofstedal MB, Zimmer Z, Hermalin AI, Chan A, Chuang Y,
Natividad J, Tang Z. Short-term trends in functional limitation
and disability among older Asians: a comparison of five Asian
settings. J Cross Cult Gerontol. 2007;22:243–61.
50. Oza-Frank R, Stephenson R, Venkat Narayan KM. Diabetes
prevalence by length of residence among US immigrants.
J Immigrant Minority Health. 2011;13:1–8.
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- Acculturation and Disability Rates Among Filipino-Americans
- Abstract
- Introduction
- Methods
- Results
- Acculturation Factors
- Demographic Factors
- Socioeconomic Factors
- Discussion
- Acknowledgments
- References