the essya should start with a theme , if not it lose points theme examples : health care providers can help reduce health disparities by implementing an inter sectional framework in theirinteractions with patients.Confronting discrimination at both the macro and micro-levels is a means to address health disparities.Promoting cultural humility among public health professionals is a useful measure toward achieving healthequity.teacher feedback I’ve had a chance to look at your paper again. It is still necessary that you begin with the theme. I see how you are addressing race and I think I can see how you are addressing medical encounters as well. It is important that you address immigrant health as well.Perhaps a theme for what you have already written could be something along the lines of:Examining research exploring racial/ethnic health disparities and immigrant health can improve medical encounters and strengthen health policy. Then your main ideas could be: Knowledge about racial/ethnic health disparities can help practitioners be more culturally competent Understanding immigrant health research can shed light on how health declines from one generation to the next. Being informed about racial/ethnic health disparities can help policymakers be aware of the needs of communities of coloryou already wrote it for me , please fix it, I will tip at the end895507
HPPXXX10.1177/1524839919895507Health Promotion PracticeAmuta-Jimenez et al. / Health Disparities And Heterogeneity Of Blacks/AAs
Resources, Frameworks, and Perspectives
Health Disparities and the Heterogeneity of Blacks/
African Americans in the United States: Why
Should We Care?
Ann Oyare Amuta-Jimenez, PhD1
Wura Jacobs, PhD2
Gabrielle Smith, PhD1
Each year, millions of dollars are spent on research and
public health interventions targeted toward reducing
health disparities primarily among the “Black/African
Americans” community, yet the progress made lags far
behind the amount of money and effort spent. We
hypothesize that part of the problem is that sociocultural
factors play a significant role in disease prevention.
Most studies and programs aggregate “Black immigrants” (BIs) and “African Americans” (AAs) as “Black/
African American.” This categorization assumes that
the sociocultural determinants that influence BIs are
the same as for AAs. BIs have health and mortality
profiles that vary from AAs. This commentary aims to
(1) introduce this idea in more depth and provide a
brief scope of the problem, (2) provide scientific evidence of noteworthy differences between AAs and BIs
in areas of sociodemographics, health behaviors, and
health outcomes, (3) discuss implications of considering the Black/AA group as homogeneous and provide
recommendations for disaggregation.
health promotion; health disparities;
Black/African American; minority health
ne of the overarching goals of Healthy People
2020 (2019) is to “achieve health equity, eliminate
disparities, and improve the health of all groups”
(p. 3). Despite the increased efforts to reduce and eliminate disparities, the literature shows that disparities in
health outcomes, determinants, and access to care persist especially between Black/African Americans (AAs)
and Whites. There remains discordance on effective
strategies or analytical approaches to address these
health disparities. Although the average health of all
U.S. populations has improved over the past century,
the gap between Blacks and Whites has widened. With
increased investments providing tailored health programs to reduce health disparities especially among
Blacks, this group continues to experience the worst
health outcomes (Xu, Murphy, Kochanek, Bastian, &
Arias, 2018). Studies examining the health and health
outcomes of U.S. Blacks suggest the need for specific
intragroup comparative research and analysis to gain
insight into the main causes shaping and contributing
to the racial disparities among U.S. Blacks (Jackson
et al., 2017).
As identified in the literature, principal factors of
health and health outcomes include “resources (e.g.,
individual and area-level measures of socioeconomic
status [SES]), environmental exposures (e.g., toxins and
sources of stress including discrimination), health behaviors (e.g., exercise and diet) and biology (e.g., genetics
and biomarkers)” (Jackson et al., 2017, p. 6). Particularly
among U.S. Blacks, we posit that these principal causes
do vary in impact among U.S. Black subgroups due their
heterogeneity. In this article, we highlight differences in
the sociodemographic, behavioral, and environmental
factors contributing to health disparities among AAs and
Texas Woman’s University, Denton, TX, USA
California State University Stanislaus, Turlock, CA, USA
Health Promotion Practice
Month XXXX Vol. XX, No. (X) 1­–4
DOI: 10.1177/1524839919895507
Article reuse guidelines:
© 2019 Society for Public Health Education
Authors’ Note: Address correspondence to Ann Oyare AmutaJimenez, Texas Woman’s University, CFO Building–1007, PO Box
425499, Denton, TX 76204, USA; e-mail:
Black immigrants (BIs) to further expatiate the need to
disaggregate the U.S. Black population.
With increasing migration and demographic transition, one out of every six U.S. Blacks will be an immigrant/foreign-born Black by 2060 (Anderson & Lopez,
2018). This variation in country of birth between a nativeborn U.S. Black/AA and a BI, for example, means that
sometimes the only similarity between individuals categorized as Blacks is the superficial characteristic of
being “Black” in skin color, which does not account for
other factors beyond their similar skin hue. The increasing diversity in the people that comprise the U.S. Black
population, means that U.S. Blacks typically have different social, environmental, and behavioral factors shaping
their risks for many diseases and/or conditions that are
tied to their country of birth. BIs, like other U.S. migrants,
tend to arrive in the United States healthy, possibly due
to selective migration or cultural buffering. However,
with time, this healthy immigrant advantage is eroded
possibly due to acculturation to the health risks and
health behaviors within the United States (AmutaJimenez, Cisse-Egbounye, Jacobs, & Smith, 2019). Failure
to identify and account for this diversity in the U.S. Black
population as it affects the principal factors influencing
health outcomes and illnesses among U.S. Black subgroups may hinder understanding of the drivers responsible for the persisting inter- and intraracial disparities
in health outcomes.
Sociodemographic factors such as age, cultural values, migration background and ethnicity, religious affiliation, marital status, household employment, and
income play an important role in health, health outcomes, and health disparities. Studies have demonstrated marked differences between AAs and BIs in
many of these sociodemographic factors. For instance,
compared to AAs, BIs tend to endorse different cultural
values that stem from their familial country. Most BIs
come from patriarchal cultures where deference to the
husband is upheld. BIs also espouse the idea that marriage is an important milestone that improves social
status (Ngazimbi, Daire, Carlson, & Munyon, 2017).
These cultural views influence attitudes and perceptions toward marriage that are reflected in the current
disparity in marital status among U.S. Blacks—48% of
BIs are married compared to 28% of AAs (Pew Research
Center, 2015). Additionally, due to historical antecedents, race relations affect the U.S. Blacks’ health outcomes. However, compared to AAs, BIs are found to be
much less conscious of skin color/race relations because
they do not generally see themselves through a racial
prism. Specifically, AAs are more likely to be negatively
affected by race-conscious experiences than BIs due to
socialization in a race-conscious society in which they
have minority status (Mouzon & McLean, 2017).
Furthermore, BIs are more likely to be religious, speak
more than one language, be older, have higher income
(BIs earn 30% more than AAs) and educational levels,
and have health insurance compared to AAs (Hamilton
& Hummer, 2011; Pinder, Nelson, Eckardt, & Goodman,
Along with genetics and medical care, health behaviors are a crucial determinant of health outcomes (Hood,
Gennuso, Swain, & Catlin, 2016). Health behaviors such
as physical activity, healthy diet, and routine screening
help early detection of and protect against illnesses and
diseases. While health behaviors such as excessive
drinking and substance use increase risk and susceptibility to diseases (Hood et al., 2016), both national and
regional studies on health behaviors by race/ethnicity
have found that there are within-group disparities in
protective and risk behaviors among all Blacks. For
example, compared to BIs, AAs were more likely to
smoke (currently or in the past), drink heavily, and misuse substances (Borrell, Crawford, Barrington, & Maglo,
2008; Lucas, Barr-Anderson, & Kington, 2003). Compared
to AA women, BI women reported lower screening rates
and lower general knowledge of breast and cervical cancer (Consedine, Tuck, Ragin, & Spencer, 2015; Grimm,
Alnaji, Watanabe-Galloway, & Leypoldt, 2017). Caribbean
men of African descent reported less frequent prostate
cancer screening than AA men (Consedine et al., 2015).
In most studies, results have shown that BIs consume a generally healthier diet than AAs. It is no secret
that AAs are at a disadvantage compared to other races
in terms of diet/nutrition. Their diets are typically
higher in saturated fats, sugar, and empty calories
(Chan, Stamler, & Elliott, 2015; Satia, Galanko, & SiegaRiz, 2004), while a traditional African diet is high in
fiber and low in fat, with higher amounts of fruits, vegetables, beans, rice, and cornmeal and very little meat.
A study in The Lancet Global Health found that subSaharan African staple diets ranked better and healthier than the typical American or European diets
(Imamura et al., 2015). Even following migration, several BIs continue to consume diets from their home
country; hence, they report consuming less fats, less
fast food, and overall lower energy intake compared to
AAs. BIs also consume a variety of necessary vitamins
including folate and Vitamin C, and potassium more
than AAs (Lancaster, Watts, & Dixon, 2006).
Blacks persistently experience poorer health than
Whites across the dimensions of health status. However,
when the data are disaggregated, BIs and AAs have evidently different health status concerns and disease occurrence between them. Overall, BIs have 7.4 years longer
life expectancy than AAs (Singh, Rodriguez-Lainz, &
Resources, Frameworks, and Perspectives
Kogan, 2013). Among U.S. Blacks the leading causes of
death are heart disease, cancer, hypertension/stroke, and
type 2 diabetes (Heron, 2018); however, when the data are
disaggregated, BIs report lower prevalence of these diseases compared to AAs. Although there are scant data on
mortality causes among BIs, the few available studies
identified infectious diseases as one of the leading causes
of death among this subgroup (Singh et al., 2013). Research
on cardiovascular and metabolic markers also demonstrates the validity of birthplace as a meaningful domain
for disaggregation. Levels of total serum cholesterol and
HDL (high-density lipoprotein) cholesterol were higher
among AAs compared to BIs (Lancaster et al., 2006). A
study of 214 Black men (138 BIs and 76 AAs) also showed
that compared with AAs, waist circumference was lower
among BIs; however, blood pressure and fasting glucose
levels were higher among BIs (O’Connor et al., 2014).
While health behaviors such as poor diet account for
some of the disparities between BIs and AAs, factors in
the environment such as family history, quality of neighborhoods, and exposure to stress may contribute to differences in health outcomes.
BIs and AAs both experience culturally bound stressors that contribute to adverse health outcomes; however,
the source of stressors often differ. Race-related stress is
linked to depression, hypertension, and heart disease,
with much stronger effects for AAs than BIs. While both
groups seek mental health treatment at lower rates than
Whites, BIs seek treatment less than AAs (Hastings &
Snowden, 2018). BIs experience stress related to navigating a new cultural environment with vastly different
social hierarchies and rules. While BIs initially have better mental health outcomes than AAs, prolonged stay in
the United States results in a decline in mental health
status (Sussner et al., 2009). BIs experience the “double
burden of acculturation,” which requires significant
psychological adjustment to acclimatize to both the
American and AA facets of U.S. culture (Mills, Fox,
Gholizadeh, Klonoff, & Malcarne, 2017).
Implications For Health
Aggregating all U.S. Blacks into one racial category
and comparing them to the White population provides
important information on racial disparities in health.
However, it prevents the understanding of how different psychosocial contexts within which the different
U.S. Black subgroups live influence their health status
and disease risk. More studies are needed to investigate
this phenomenon systematically. It is imperative that
researchers and health promotion program planners
increase efforts to understand the immigrant health
advantage and risks by disaggregating the U.S. Black
Public health researchers examine health disparities/
health equity from a purely racial lens by exploring
“Black/AA versus White non-Hispanic,” thus not
accounting for the presence of foreign-born Blacks
whose health risks and determinants also contribute to
the persisting health disparities. In fact, the most recent
U.S. Census asked respondents to self-identify as White,
Black/African American, Hispanic/Latino/Spanish origin, American Indian/Alaska Native, Asian Indian,
Chinese, Filipino, Japanese, Korean, Vietnamese, Native
Hawaiian, Guamanian or Chamorro, Samoan, Native
Hawaiian/other Pacific Islander, or “some other race.”
Black/African American was the only race put into one
category. Due to this perceived homogeneity of Blacks
in the United States, areas with large numbers of BIs are
erroneously collecting health data on this group.
Inclusion of BIs in studies intended to examine AAs,
given the previously described differences in behaviors,
experience, illness, and mortality, may lead to invalid
and erroneous implications.
Merging newly immigrated BIs and AAs may falsely
represent the health status of AAs who are the significantly larger aggregate of both populations. Collecting
data that do not distinguish BIs from AAs could lead to
a misrepresentation of the health needs of AAs and
“dilute” the current health status of AA’s (e.g., stroke,
heart disease). Disaggregation can also lead to a more
nuanced understanding of the health decline that occurs
in BIs over time and among subsequent generations who
are U.S.-born AAs. Studies that effectively disaggregate
by nativity find markedly different health outcomes and
mediating sociocultural factors for BIs and AAs concerning preventive care and cardiometabolic risks (AmutaJimenez et al., 2019; Consedine et al., 2015; Lancaster
et al., 2006; Sussner et al., 2009). Identifying essential
norms that produce positive results for BIs could aid in
the development of interventions to circumvent the
adverse health outcomes for AAs and BIs with extended
residency in the United States.
Consideration of differences in sociodemographic factors, health behaviors, and health status is necessary to
understand the within-group disparities among U.S.
Blacks. Engagement of patient cultural values and perspectives of health and wellness will enhance the quality
of assessments and allow health professionals to provide
culturally appropriate and effective care. Researchers
need to design interventions that recognize and address
the markedly different underlying mechanisms that drive
the poorer health-related outcomes for AAs compared
to BIs. Acknowledging intragroup diversity will facilitate the formulation of meaningful culturally relevant
and effective interventions that could be essential for
reducing health disparities among U.S. Blacks. Crafting
interventions tailored to the specific needs of these two
vastly different subgroups of U.S. Blacks will ensure
consideration of the specific needs of BIs (e.g., general
chronic disease awareness and increased cancer screening) and AAs (e.g., positive changes in health behaviors;
Amuta-Jimenez et al., 2019).
Ann Oyare Amuta-Jimenez
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HSBXXX10.1177/0022146519869027Journal of Health and Social BehaviorDiaz and Niño
Original Article
Familism and the Hispanic
Health Advantage: The Role
of Immigrant Status
Journal of Health and Social Behavior
2019, Vol. 60(3) 274­–290
© American Sociological Association 2019
DOI: 10.1177/0022146519869027
Christina J. Diaz1 and Michael Niño2
It is well known that Hispanic immigrants exhibit better physical and mental health than their U.S.-born
counterparts. Scholars theorize that stronger orientations toward the family, also known as familism,
could contribute to this immigrant advantage. Yet, little work directly tests whether familial attitudes may
be responsible for the favorable health of foreign-born Hispanics. We investigate this possibility using
biomarkers, anthropometrics, and mental health assessments from the Hispanic Community Health Study/
Study of Latinos (N = 4,078). Results demonstrate that the relationship between familial attitudes and
health vary depending on the outcome assessed. While Hispanics with strong attitudes toward familial
support have fewer symptoms of depression and anxiety, those who report high referent familism display
worse mental health outcomes. We find little evidence that familism is linked to physical health or that
immigrant generation moderates the relationship of interest. Our results challenge assumptions that
familism is responsible for the comparably better health of foreign-born Hispanics.
familism, Hispanic Community Health Study/Study of Latinos, Hispanic health advantage, immigration
Though Hispanics disproportionately reside in
underprivileged neighborhoods, lack adequate
health care, and accumulate limited financial
resources, they experience more favorable health
outcomes than non-Hispanics (Cunningham,
Ruben, and Narayan 2008; Heron 2013; Markides
and Eschbach 2005). Scholars argue that this advantage is driven by the comparably better health of
Hispanic immigrants who settle in the United States
(e.g., Hummer et al. 2000; Singh and Siahpush
2002). While some stress that data misreporting
(Elo et al. 2004; Palloni and Morenoff 2001; Smith
and Bradshaw 2006) and migrant selection (Palloni
and Arias 2004; Riosmena, Wong, and Palloni
2013) can explain the advantageous health of the
foreign-born, others posit that strong orientations
toward the family—also known as familism—­
protect against threats to physical and mental wellbeing (Almeida et al. 2009; Cook et al. 2009).
Despite such claims, demographers and health
scholars overlook the possibility that familism could
be responsible for the Hispanic health advantage.
Instead, family-oriented behaviors and attitudes are
invoked as residual explanations to account for foreign-born Hispanics’ relatively strong health profile.
Moreover, discussions surrounding how to appropriately measure familism are notably absent or
inconsistent in the health literature. This omission is
particularly striking given claims that sociocultural
practices likely play a nontrivial role in underlying
health disparities (Abraído-Lanza, Chao, and Florez
2005; Akresh 2007; Franzini and Fernandez-Esquer
2004; Hummer et al. 2007). The present study tests
University of Arizona, Tucson, AZ, USA
Willamette University, Salem, OR, USA
*Equal authorship
Corresponding Author:
Christina J. Diaz, School of Sociology, University of
Arizona, Social Sciences Building, Room 425, 1145 E.
South Campus Drive, Tucson, AZ 85721, USA.
Diaz and Niño
whether family orientation is associated with
Hispanic well-being and by doing so, seeks to
advance a widely used but weakly scrutinized theory.
We rely on biomarker and anthropometric data
collected by the Hispanic Community Health
Study/Study of Latinos (HCHS/SOL) to investigate
the relation between familism and physical health.
We also assess the association between family orientation and two measures of mental health:
depressive symptoms and anxiety. Following contemporary studies on familism (Esparza and
Sanchez 2008; Rodriguez et al. 2007; Villarreal,
Blozis, and Widaman 2005), we focus on familial
attitudes as opposed to reported behaviors. Although
attitudes are arguably more abstract, Hispanics
encounter numerous barriers to physically interacting with immediate and extended family members—many of whom live across borders that are
increasingly militarized (Dreby 2015; Slack et al.
2015). While it may be difficult for all individuals
to physically engage with family members who
reside in a foreign country, this is even more difficult for the nearly 12 million unauthorized immigrants living in the United States—the majority of
whom fall underneath the Hispanic pan-ethnic
umbrella (Baker 2018).
We then ask whether higher rates of familism
could explain the health advantage of foreign-born
Hispanics relative to their U.S.-born counterparts.
We distinguish between the first and 1.5 generations to better understand variation in health and
familistic attitudes. Our unique data source captures
multiple dimensions of familial attitudes and allows
us to control for cultural and socioeconomic attributes that likely confound the relationship of interest. Findings from this study thus inform ongoing
theoretical and empirical developments in the medical and social sciences that center on familism and
Hispanic well-being.
Hispanic Health and Well-Being
A large and growing body of work argues that
foreign-born Hispanics exhibit more favorable
health outcomes—including lower mortality rates
(Lariscy, Hummer, and Hayward 2015; Palloni and
Arias 2004), fewer chronic conditions (Bostean
2013; Rubalcava et al. 2008), and more positive
self-assessed health (Acevedo-Garcia et al. 2010;
Cunningham et al. 2008)—than their U.S.-born
counterparts. This advantage is documented among
infants (Acevedo-Garcia, Soobader, and Berkman
2005; Hummer et al. 2007), the elderly (Elo et al.
2004; Markides and Eschbach 2005), and across
multiple socioeconomic backgrounds (Braveman
et al. 2010; Kimbro et al. 2008). Given that Hispanic
immigrants earn lower wages and obtain fewer
years of schooling than non-Hispanic whites and
that the link between health and socioeconomic status is pervasive across industrialized nations (Adler
and Ostrove 1999; Buttenheim et al. 2010; Phelan,
Link, and Tehranifar 2010), their advantageous
health is largely deemed paradoxical (AbraidoLanza et al. 1999).
Though fewer studies assess the mental health
of Hispanics, the foreign-born may exhibit a lower
risk for certain psychiatric disorders than their U.S.born and white counterparts (Breslau et al. 2006;
Vega et al. 1998). Alegría and colleagues (2006)
argue that immigrants—Mexicans in particular—
are less likely to experience depression, social phobia, and anxiety than U.S.-born Hispanics. Others
posit that psychiatric differences are driven by confounders, such as English language ability and
socioeconomic background, as the correlation
between mental health and immigrant generation
disappears after the inclusion of such characteristics (Cook et al. 2009). However, a wide range of
mental health assessments have been employed
over time and across studies (Perreira et al. 2005;
Rogler, Cortes, and Malgady 1991), and estimates
can vary widely. Nevertheless, the balance of evidence demonstrates that Hispanics’ advantageous
health also extends to mental well-being.
The Paradox Explained?
In attempting to reconcile the Hispanic health
advantage, scholars generally emphasize three
explanations. The first possibility is that data
­inaccuracies—such as age and ethnic misclassifications (Palloni and Morenoff 2001) or the underreporting of chronic conditions—create an artificially
advantageous health profile. Though results are
mixed (Eschbach, Kuo, and Goodwin 2006; Smith
and Bradshaw 2006), classification errors are
unlikely to be solely responsible for the elevated
health of Hispanic immigrants (Arias et al. 2010;
Palloni and Arias 2004). And while limited access to
medical professionals and health insurance prohibit
Hispanic-origin immigrants from receiving diagnoses of underlying conditions, their attributes and
biomarkers are more likely to fall within a normal
range (e.g., blood pressure, body mass index [BMI])
than U.S.-born whites and nonwhites when surveyed by trained interviewers (Gordon-Larsen et al.
2003; Kaplan et al. 2004; Riosmena et al. 2013). Put
differently: The Hispanic advantage persists in settings where underreporting is unlikely to pose a
Another possibility is that health-related migration results in overly optimistic estimates of wellbeing. The healthy migrant hypothesis suggests that
individuals who engage in migration are in better
health than those who remain in their country of
origin. Health may directly influence the probability of migration (Chiswick, Lee, and Miller 2008),
or health may be associated with characteristics that
predict U.S. migration—such as education or ability. The salmon bias hypothesis argues that foreignborn persons are rendered “statistically immortal”
upon return migration (Pablos-Méndez 1994:1237);
individuals may return as a direct result of poor
health (Ceballos 2011), or return may be induced by
factors correlated with declining health—such as
limited employment opportunities (Diaz, Koning,
and Martinez-Donate 2016). Both hypotheses stress
that mortality and morbidity estimates are downwardly biased as individuals captured by surveys
do not accurately reflect the Hispanic population.
The extent to which selection affects estimates
depends on when health is assessed as well as the
measures examined (Rubalcava et al. 2008).
Nevertheless, there is some indication that both the
healthy migrant and salmon bias hypothesis contribute to the health advantage (Crimmins et al.
2005; Turra and Elo 2008).
A third possibility is that Hispanic-origin populations disproportionately engage in practices and
norms that are protective against deleterious health
conditions. Physical and mental health may be
­bolstered through the retention of cultural traditions
that promote well-being (Portes and Rumbaut
2006), the material and social support of the coethnic community (Bjornstrom and Kuhl 2014;
Kimbro 2009), and/or family ties (Fuller-Iglesias,
Webster, and Antonucci 2015; Keeler, Siegel,
Alvardo 2014; Mirowsky and Ross 2003; Pinquart
and Sörensen 2007). Referred to as familism, scholars suppose that Hispanics are more likely to exhibit
close relationships with extended family members
than other racial/ethnic groups do (Perez and Cruess
2014). Though familism receives less attention than
data misreporting or selection, scholars theorize that
such attitudes could potentially explain the Hispanic
immigrant health advantage (Valdivieso-Mora et al.
2016; Velasco-Mondragon et al. 2016). Before
detailing the linkages between familism and health,
it will be instructive to consider the multiple ways
familism is measured.
Journal of Health and Social Behavior 60(3)
Theories of Familism, Measurement
Broadly defined, familism is a multidimensional
construct that emphasizes the needs of the family
over the needs of the individual. One of the earliest
definitions argued that familism is made up of shared
goals, family-based socioeconomic resources, and
retention of the family unit (Burgess and Locke
1945). A multidimensional scale was later advanced
to reflect five aspects of the nuclear family: belongingness, unconditional support, economic and social
endowments, support during times of need, and
exchange networks (Heller 1970).
However, Arce (1978) argued that existing scales
were insufficient in reflecting the fundamental values and structure of the Hispanic family. He proposed three dimensions to more accurately capture
familism among Hispanics: behavioral, which
stresses active engagement with immediate and
extended family; structural, which highlights attitudes concerning family cohesion; and demographic,
which emphasizes family size and intactness. This
conception continues to serve as the foundation for
contemporary scholarship on familism as one of the
most widely used constructs—which includes perceived support for the family, familial obligations,
and referent familism (Sabogal et al. 1987)—draws
extensively on Arce’s assertions.
In recent years, scholars continue to refine definitions and scales, arguing for the incorporation of
family conflict (Rodriguez et al. 2007), family
interconnectedness (Lugo Steidel and Contreras
2003), and behavioral aspects of familism (Comeau
2012). Although debate persists, scholars uniformly
agree that familism is a multidimensional construct
that broadly represents a belief system; this system
emphasizes family ties, family structure, as well as
emotional, financial, and social support to the
immediate and extended family (Almeida et al.
Familism and Physical Health
Most studies that examine familism–health relationships do not examine physical health directly
and instead focus on health-related outcomes—
such as disease management, substance use, and
diet/exercise. Evidence suggests that perceived
familial obligations and support decreases the risk
for alcohol and drug use among youth (Castro,
Stein, and Bentler 2009; Gil, Wagner, and Vega
2000), improves exercise and dietary habits (Mellin
et al. 2004), and boosts the likelihood that Hispanic
Diaz and Niño
adults adhere to a diabetes treatment plan (Rustveld
et al. 2009).
However, the correlation between health behaviors and family orientation is sensitive to the type(s)
of familism that Hispanics engage in, and this is
especially true for women. On the one hand, perceived familial support decreases stress (Alferi
et al. 2001) and depressive symptoms (Pistrang and
Barker 1995) for women undergoing cancer treatment. On the other hand, familial ideals can inhibit
disease management and personal care. For
instance, Oomen, Owen, and Suggs (1999) argue
that familial responsibilities prevent diabetic
women from following recommended treatment
plans. Similar studies suggest Hispanic women
conceal cancer diagnoses or avoid medical care
because treatment would interfere with family
responsibilities (Ashing-Giwa et al. 2006). There is
also some indication that women will not use
household resources to meet their medical or
dietary needs due to fears of financially burdening
the family (Chesla et al., 2003; Horowitz,
Goodman, and Reinhardt 2004).
A nascent body of work does investigate the
relation between familism and physical health
among Hispanics. Some assert that familial support
is not associated with chronic health conditions,
activity limitations (Bostean 2010), or self-rated
health after the inclusion of important confounders
(Alegría, Sribney, and Mulvaney 2007). Yet, studies
exclusively rely on self-reported assessments that
are likely to misstate underlying health, and few
capture multidimensional familistic values that supposedly explain Hispanic well-being (Ruiz,
Campos, and Garcia 2016). It is also possible that
less positive aspects of family life—such as family
conflict—are associated with health outcomes.
Indeed, Hispanic respondents are more likely to
report chronic health conditions when exposed to
negative family interactions (Bostean 2010; Priest
and Woods 2015). For these reasons, it is imperative to account for both positive and negative
aspects of family dynamics.
Familism and Mental Health
Studies that assess the link between familism and
mental health often emphasize depressive symptoms and suicidality. Some demonstrate that familyoriented attitudes reduce the risk of depressive
symptoms for Hispanic immigrants (Ornelas and
Perreira 2011) and adolescents (Stein et al. 2015;
Zeiders et al. 2013). When families report high
cohesion and low conflict, for instance, the risk of
suicidality for Hispanic girls steeply declines
(Baumann, Kuhlberg, and Zayas 2010). Yet, others
find that familism has no effect on mental health
(Garza and Pettit 2010; Zayas et al. 2009). And in
some cases, high rates of family orientation may
increase the risk for depressive symptoms and suicidality (Baumann et al. 2010)—particularly among
those who provide medical care for a sick family
member (Losada et al. 2006). Although familism
could generate positive mental health outcomes,
individuals who report especially high levels of
family orientation may feel pressure to put the needs
of the family ahead of their own well-being.
Study Contribution
To reconcile the seemingly paradoxical relationship
between health and socioeconomic disadvantage,
scholars argue that exceptionally high levels of
­family-orientated beliefs and attitudes (e.g., familism)
may bolster the health of Hispanic populations.
Though the foreign-born exhibit relatively low rates
of mortality and morbidity, second- and third-generation Hispanics (Antecol and Bedard 2006; Finch
et al. 2009) report significantly worse health across a
myriad of outcomes—including BMI (GordonLarsen et al. 2003), smoking/alcohol use (AcevedoGarcia, Pan, et al. 2005), mental distress (Alderete
et al. 2000; Escobar, Nervi, and Gara 2000), consumption of saturated fats and refined sugar (Akresh
2007; Creighton et al. 2012), and birthweight
(Acevedo-Garcia, Soobader, and Berkman 2007).
There are two scenarios whereby familism
could remain a plausible explanation for the immigrant health advantage. First, we should observe
declines in family orientation across generations as
well as a positive relationship between familism
and health. Alternatively, the effect of familism on
health could grow weaker (less positive) across
generations. This scenario posits that familism has
interactive effects with resources and/or opportunities that vary across generations and results in dissimilar health outcomes—even in the absence of
generational declines in family orientation. We
investigate both scenarios by asking whether
familism is associated with a more positive health
profile and testing whether this correlation varies
across immigrant generation.
Data And Methods
Data were obtained from the HCHS/SOL parent
study and the Sociocultural Ancillary Study
(SCAS). The HCHS/SOL, which was conducted
during the 2008 to 2011 period, assessed chronic
conditions, disease, and associated risk factors
among Hispanics who lived in urban areas throughout the United States. Approximately 16,000
Hispanic/Latino origin persons—including Cuban,
Puerto Rican, Mexican, and South/Central
Americans—who resided in the Bronx (New York),
Chicago (Illinois), Miami (Florida), and San Diego
(California) were selected to participate.
The HCHS/SOL employed a two-stage sampling approach: First, a stratified-random sample of
block groups was selected within census tracts
across each location. Households nested within
each block group were then chosen at random, and
all individuals deemed eligible for participation
were selected for enumeration. Detailed information pertaining to migration history, generational
status, and sociodemographics was collected, making these data ideal for our purposes. Most importantly, the HCHS/SOL conducted on-site medical
assessments of health as well as key biomarkers
from blood and urine samples. Relying on measures
obtained from trained interviewers and medical
professionals allows us to rule out reporting errors
that may be especially common among Hispanics
(Sorlie et al. 2010).
The SCAS represents a target sample of 5,313
respondents from the HCHS/SOL study; approximately 88 percent of this subsample completed
questionnaires within nine months of the initial
baseline interview (Gallo et al. 2014). Respondents,
who were distributed evenly across the four field
sites, completed a battery of questions pertaining to
mental health, language acculturation, and orientation toward family life. Interviews were administered in English or Spanish depending on the
respondent’s stated preference.
Outcome Variables
To reduce concerns related to health misreporting
and inaccuracies, we relied on biomarkers and
anthropometrics gathered by trained interviewers.
Elevated levels of C-reactive protein, defined as a
concentration greater than 3.0 mg/L by the American
Heart Association, were used to identify respondents suffering from inflammation and heightened
cardiovascular risk (Heffner et al. 2011). To further
assess the likelihood of heart disease, we created
a cardiac risk ratio by dividing total cholesterol
by high-density lipoprotein cholesterol. We also
assessed BMI (kg/m2) as recorded at the time of survey. A dichotomous measure was then created to
signal individuals had diabetes; respondents were
Journal of Health and Social Behavior 60(3)
considered diabetic if: (a) fasting glucose was
greater than 126 mg/dL, (b) the oral glucose tolerance test was greater than 200 mg/dL, or (3) A1C
levels were greater than 6.5 percent.
For mental health, we included two indicators
that capture depressive symptoms and anxiety.
Depressive symptoms were measured using the
Center for Epidemiologic Studies Depression Scale
(CES-D 10), which is based on 10 items that ask
respondents about depressive symptoms experienced in the past week (e.g., “I was bothered by
things that usually don’t bother me,” “I felt lonely”).
Response categories ranged from 0 (rarely or none
of the time) to 3 (all of the time); items were then
summed to obtain a total depression score. Our anxiety measure was derived from the 10-item
Spielberger Trait Anxiety Inventory (STAI). This
scale consists of such questions as “I feel nervous
and restless,” “I feel like a failure,” and “I worry
too much over something that really doesn’t matter.” Participants were asked to report their general
feeling/sentiment and choose from answer categories that ranged from 1 (almost never) to 4 (always);
values were summed so that higher scores represent
a greater risk for anxiety disorders. Internal reliability was calculated as .83 for the CES-D and .81 for
the STAI.
Constructing Familism
Because conflating attitudinal and behavioral
dimensions of familism can misrepresent family
dynamics, we relied on a 14-item multidimensional
scale to capture attitudes surrounding family obligations, family support, and referent familism
(Sabogal et al. 1987). The family obligations (α =
.71) subscale included six items that assessed the
extent to which respondents agreed with the following: one should make sacrifices to guarantee a good
education for their children, help economically support younger siblings, help relatives if they have
financial difficulties, hope to live long enough to
watch grandchildren grow up, believe aging parents
should live with relatives, and believe family should
share their home. We also used three items to capture attitudes toward family support (α = .65), which
included providing help in difficult times (e.g.,
“when one has problems, one can count on the help
of relatives”). Referent familism (α = .68) consisted of five items that asked respondents the
extent to which they agreed with the following:
having children should be a major life goal, children should please their parents, family should be
consulted in important decisions, children should
Diaz and Niño
live with parents until marriage, and one should be
embarrassed by sibling’s poor choices; response values ranged from 1 (disagree a lot) to 5 (agree a lot).
Results from a confirmatory factor analysis
(CFA) signaled that a one-factor model was a mediocre fit (root mean square error of approximation
[RMSEA] > .10); a subsequent CFA found the
three-factor model fit the data reasonably well
(RMSEA = .05). Our findings thus align with assertions that familism consists of multiple and distinctive beliefs about family life (Lugo Steidel and
Contreras 2003; Sabogal et al. 1987). We calculated
averages for each subscale, with larger values corresponding to a higher degree of familism. Factor
correlations ranged between .30 and .51, suggesting
collinearity between subscales was unlikely to pose
an issue.1
Generational Status
We defined generational status using respondent’s
country of birth and their age of arrival in the United
States. For the purposes of this study, we classified
respondents as first generation if they were foreignborn and arrived to the United States at age 13 years
or older. The 1.5 generation consisted of those who
were foreign-born but entered when they were
younger than 13 years of age (Rumbaut 2004). Both
the first and 1.5 generations must have had parents
who were born outside of the United States, whereas
the “U.S.-born” consisted of second-, third-, and
later-generation respondents. Unfortunately, sample
size constraints precluded a more thorough examination of those born in the United States.
It is essential to adjust for measures that confound
the relation between health and familism. We thus
controlled for age, gender, marital status (married/
cohabiting, single, other), and number of children
(zero, one or two, three or more). We included a
quadradic term for age to capture potential nonlinearities in the association of interest (Zeiders et al.
2013). We adjusted for socioeconomic attributes,
such as educational attainment (less than high
school, high school completion/equivalent, some
college or more), household income (less than $10k,
$10k–$20k, $20k–$30k, $30k–$50k, more than
$50k), and employment status (full-time employment, part-time employment, retired, unemployed).
Both ethnic background (Central/South American,
Cuban, Mexican, Puerto Rican, other) and English
language fluency (higher values indicate greater
fluency) were also included as controls.2 We then
created a dichotomous indicator to signal whether
respondents had health insurance at the time of survey. Finally, we included a dummy measure to capture whether the respondent was aware of any family
conflicts occurring within the past three months.
Analytic Approach
We began by simply asking if familism declines
across generations. We then assessed whether
familism is correlated with physical and mental
health. While logistic regression was used to evaluate the likelihood of elevated C-reactive protein and
diabetes, linear regression predicted cardiac risk and
BMI. Diagnostic tests indicated that our measures
of depression and anxiety exhibited overdispersion
and violated key assumptions of linear regression.
To avoid model misspecification and artificially
small standard errors, we used negative binominal
regression. Next, we interacted generational status
with each familism subcategory to test whether the
influence of familism on health became weaker
across immigrant generation. In combination, these
efforts allowed us to evaluate two possible scenarios
that would support the notion that familism contributes to the Hispanic health advantage.
Given that approximately 9 percent of all cases
were missing, we employed listwise deletion to
obtain our final sample size (N = 4,078). As a sensitivity check, multiple imputation with chained
equations was used to impute missing items (m =
25); interactions and higher order terms were
included in the imputation model, and models were
separately estimated across immigrant generation.
Results, which are available on request, are similar
in direction, magnitude, and statistical significance.
We applied appropriate sampling weights and also
accounted for the complex design of the HCHS/
SOL. When weighted, data were representative of
Hispanics residing in urban cities across the United
Descriptive Statistics
Table 1 contains weighted descriptives with agestandardized health outcomes to account for dissimilar age distributions across immigrant generations.
First-generation Hispanics report significantly fewer
symptoms of depression and anxiety than the 1.5
generation and the U.S.-born, and they also exhibit
lower BMI. Fewer first-generation Hispanics also
Journal of Health and Social Behavior 60(3)
Table 1. Weighted Descriptive Statistics by Generation.
Age standardized health outcomes
Depression (range: 0–30)
Anxiety (range: 10–40)
Cardiac risk ratio
Elevated C-reactive protein
Body mass index
Family obligations (range: 1–5)
Family support (range: 1–5)
Family as referents (range: 1–5)
Family conflict
Currently has health insurance
Marital status
Country of origin
Puerto Rican
South/Central American
Number of children
3 or more
English acculturation
Less than high school
High school
Some college or more
Household income
< $10k $10k–$20k $20k–$30k $30k–$50k > $50k
First Generation
1.5 Generation
N = 2,983
N = 361
N = 734
Mean or % (SD)
Mean or % (SD)
Mean or % (SD)
7.02 (9.13)a,b
16.77 (8.21)a,b
4.41 (2.01)a
29.40 (7.44)a,b
4.26 (.68)b
3.96 (.96)
3.40 (1.45)a,b
9.17 (19.19)
18.57 (16.49)
4.10 (1.71)
31.54 (13.55)
4.25 (.62)c
3.95 (.88)
3.07 (1.09)c
8.33 (12.41)
18.28 (10.85)
4.62 (7.59)
30.55 (9.39)
4.18 (.61)
3.95 (.88)
2.89 (.93)
46.86 (22.84)a,b
38.09 (33.48)c
32.42 (17.71)
1.36 (.91)a,b
3.02 (1.08)c
3.49 (1.32)
Source: Hispanic Community Health Study/Study of Latinos Parent and Sociocultural Ancillary Study, 2008–2011.
Note: Data weighted to account for complex sampling design. Mean/percentages listed for each generation, standard
deviations in parentheses. Tests for differences are explained in the following notes.
First generation significantly different from 1.5 generation.
First generation significantly different from U.S.-born.
The 1.5 generation significantly different from U.S.-born.
Diaz and Niño
have elevated levels of C-reactive protein (37 percent) than those who arrived to the United States at
younger ages (43 percent). Yet, the first generation
exhibits a higher cardiac risk ratio than their
1.5-generation counterparts, and there is no indication that diabetes varies across immigrant generation. Though the health advantage appears to persist
for some but not all of these indicators, patterns are
consistent with prior work that uses biomarkers to
assess Hispanic health (Barcellos, Goldman, and
Smith 2012; Peek et al. 2010).
First-generation respondents are also significantly older and are more likely to be employed
full-time, have three or more children, and be
involved in a romantic union than the 1.5-­generation
or U.S.-born respondents. English language fluency
steeply increases across generations, with the highest levels reported by those born in the United
States. Over 46 percent of 1.5-generation and U.Sborn Hispanics attend college or earn a higher level
of attainment; these adults are also more likely to
have health insurance and reside in households that
earn more than $50,000 (our specified top income
category). It is worth noting that reports of family
conflict increase across generations; these individuals may have more complete information regarding
family dynamics, or conflict could be especially
common in intergenerational families (Kwak
Familism Patterns
Evidence also suggests that attitudes toward family
obligations are stronger among foreign-born
Hispanics than the U.S.-born. And while referent
familism significantly declines across generations,
attitudes toward familial support remain relatively
stable (Table 1). To test whether such descriptive
patterns persist with the inclusion of confounders,
we estimate a series of linear regressions; immigrant generation is used to predict each familism
subscale (see Table A1 in the online version of the
article). After the inclusion of demographic, socioeconomic, and cultural characteristics, however,
generational status does not exhibit an independent
association with familial attitudes. We thus find little evidence that familism systematically declines
across immigrant generation.
Is There a Link between Familism
and Health?
Table 2, Panel A contains estimates that assess generational differences in health as well as the relation
between familial attitudes and health. We focus on
four measures of physical health (cardiac risk ratio,
BMI, diabetes, C-reactive protein) and two indicators of mental health (depressive symptoms and
anxiety). Coefficients are obtained from separate
regressions that control for sociodemographic characteristics, family conflict, English fluency, health
insurance coverage, and country of origin. Table
A2, which can be found in the online version of the
article, contains a complete list of covariates from
all specifications.
After adjusting for key confounders, results provide modest evidence of generational declines in
health. Compared to first-generation Hispanics, the
U.S.-born have significantly higher BMI (β = 1.73)
and are more likely to suffer from elevated levels of
C-reactive protein (odds ratio [OR] = 1.55). And
while the 1.5 generation also exhibits greater BMI
(β = 1.62) than their first-generation counterparts,
they have significantly lower odds of diabetes
(OR = .51). Wald tests allow us to generate further
comparisons across generations, though there is little indication that native-born Hispanics are in
worse health than those who arrived to the United
States at younger ages. The one exception is that the
U.S.-born have nearly twice the probability of suffering from diabetes than the 1.5 generation (10
percent vs. 5 percent, predicted probabilities
obtained via logistic regression). That we observe
such patterns when relying on data collected by
medical professionals suggests that these health differences are unlikely driven by data inaccuracies or
underreported chronic conditions.
With respect to the link between familism and
health, findings are more complex. We find no evidence of a substantively large or statistically significant correlation between family obligations and
physical or mental health. However, Hispanics who
report stronger orientations toward familial support
have significantly fewer depressive (incidence rate
ratio [IRR] = .94) and anxiety symptoms (IRR =
.97) than those less inclined to agree with such sentiments. And with the exception of cardiac risk and
diabetes, familial support is associated with worse
physical health; however, it must be stressed that
the only significant outcome observed is BMI (β =
.48). Estimates also suggest that respondents who
report stronger referent familism exhibit a significantly elevated risk for depression (IRR = 1.13) and
anxiety (IRR = 1.04).
It is worth highlighting a few key patterns that
emerge from covariates (see Table A2 in the online
version of the article). Hispanic men report lower
BMI (β = −1.27), fewer depressive symptoms
1.62** (.58)
1.73*** (.50)
–.10 (.36)
.48* (.23)
–.35 (.23)
20.80** (1.85)
1.21 (4.15)
–.95 (3.37)
–.25 (.38)
.31 (.25)
–.19 (.23)
–.55 (1.15)
.75 (1.13)
1.53 (.80)
.03 (.82)
–1.08 (.75)
–.19 (.58)
21.40*** (1.86)
.06 (.15)
.28 (.17)
.13 (.08)
–.03 (.07)
–.07 (.05)
1.58** (.51)
–.16 (.81)
1.73 (1.19)
.13 (.08)
–.02 (.06)
–.01 (.05)
–.19 (.26)
.05 (.20)
.25 (.24)
–.15 (.22)
.01 (.15)
–.36* (.14)
1.27*** (.49)
β (SE)
1.04 [.27, 4.04]
1.25 [.51, 3.04]
1.82 [.75, 4.42]
1.24 [.71, 2.18]
1.33 [.69, 2.59]
.77 [.45, 1.34]
.00*** [.00, .02]
.86 [.61, 1.21]
.90 [.70, 1.16]
1.26* [1.02, 1.57]
.02 [.00, 1.41]
.38 [.01, 13.43]
.90 [.66, 1.23]
.99 [.80, 1.23]
1.22* [1.01, 1.47]
.00*** [.00, .01]
.51* [.29, .93]
1.03 [.66, 1.61]
OR [95% CI]
.63 [.23, 1.74]
.93 [.47, 1.82]
2.00 [.96, 4.19]
1.15 [.71, 1.86]
.70 [.44, 1.11]
1.24 [.84, 1.82]
.15** [.04, .60]
.96 [.72, 1.28]
1.07 [.85, 1.34]
1.02 [.86, 1.22]
1.91 [.06, 58.02]
.64 [.07, 6.17]
.89 [.71, 1.12]
1.19 [.99, 1.43]
1.03 [.89, 1.19]
.13** [.03, .47]
1.41 [.89, 2.22]
1.55* [1.03, 2.33]
C-Reactive Protein
OR [95% CI]
1.19 [.83, 1.69]
1.20 [.99, 1.45]
.87 [.71, 1.07]
.89 [.77, 1.02]
.98 [.81, 1.18]
.92 [.82, 1.04]
3.74*** [2.11, 6.64]
.90* [.82, 1.00]
.98 [.91, 1.05]
1.15*** [1.08, 1.23]
.91 [.33, 2.53]
1.04 [.51, 2.13]
.96 [.89, 1.05]
.94* [.88, .99]
1.13*** [1.07,1.19]
3.61*** [2.14, 6.08]
1.00 [.85, 1.18]
1.09 [.94, 1.26]
IRR [95% CI]
Source: Hispanic Community Health Study/Study of Latinos Parent and Sociocultural Ancillary Study, 2008–2011.
Note: β = unstandardized coefficient; BMI = body mass index; CI = confidence interval; IRR = incidence rate ratio; OR = odds ratio; SE = standard error.
*p < .05, **p < .01, *** p < .001. Panel A Immigrant generation (First generation) 1.5 generation U.S.-born Familism Obligations Support Referents Constant Panel B Immigrant generation (First generation) 1.5 generation U.S.-born Familism Obligations Support Referents Interactions 1.5 generation × Obligations U.S.-born × Obligations 1.5 generation × Support U.S.-born × Support 1.5 generation × Referents U.S.-born × Referents Constant N Cardiac Risk β (SE) Table 2. Predicting Health Using Familism, Immigrant Generation, and Interactions. 1.13 [.96, 1.33] 1.02 [.92, 1.14] .91 [.82, 1.01] .93 [.86, 1.00] .97 [.91, 1.04] 1.00 [.95, 1.06] 11.72*** [9.50, 14.45] 4,078 .99 [.94, 1.03] 1.00 [.97, 1.03] 1.05*** [1.02, 1.07] .97 [.64, 1.46] 1.26 [.90, 1.76] 1.01 [.97, 1.04] .97* [.94, .99] 1.04*** [1.02, 1.07] 11.97*** [9.86, 14.54] 1.02 [.95, 1.09] 1.03 [.97, 1.10] Anxiety IRR [95% CI] 283 Diaz and Niño (IRR = .77), and less anxiety (IRR = .93) but exhibit a greater cardiac risk (β = .70) than women. Employed individuals as well as those with higher levels of income and educational attainment exhibit a lower risk of poor mental health than their less advantaged counterparts, and we find striking health differences by country of origin. Relative to Mexican-origin respondents, Cubans, Central/ South Americans, and Hispanics from other origin countries are less likely to have diabetes (β = .55, β = .67, β = .61) but more likely to suffer from elevated levels of C-reactive protein (OR = 1.60, OR = 1.33, OR = 1.60). And Central/South Americans report less anxiety than their Mexican counterparts (IRR = .96), perhaps because many emigrated from particularly stressful and violent contexts (Menjivar and Abrego 2012). Supplemental analyses support this assertation as over half of Central/South Americans arrived to the United States during periods characterized by internal conflict and increased drug cartel violence (United Nations Office on Drugs and Crime 2017). Finally, knowledge of a recent family conflict appears to significantly heighten the risk for depressive symptoms and anxiety (IRR = 1.35, IRR = 1.11). Do Familial Attitudes and Health Differ across Generations? It would appear that familism does not decline across immigrant generation, nor is familism associated with physical health. The few consistent patterns we observe are for mental health as results for physical well-being are null or inconsistent. However, it could still be the case that the relationship between familism and health systematically differs across generation. Table 2, Panel B provides estimates evaluating the potential moderating influence of immigrant generation on the associations of interest; see Table A3 (available in the online version of the article) for further details. We rely on figures that illustrate results in the form of predicted values and probabilities by generational status and familism (Figure 1). Each row contains a specific health outcome, and each column represents a given dimension of familism. All y-axes correspond to predicted values or probabilities, x-axes represent specified levels of familial attitudes, and shaded prediction lines represent three categories of immigrant generation. Overall, results indicate that immigrant generation plays a relatively minor role in the familismhealth relationship. Immigrant generation does not moderate the association between cardiac risk and attitudes toward familial obligations or support (row 1); despite apparent differences in magnitude, estimated slopes do not statistically differ from each other. There is some indication, however, that cardiac risk declines more steeply with increasing referential familism among U.S.-born respondents than among the first generation. Yet, we remain hesitant to emphasize this sole significant finding. We do not observe statistically significant or substantive differences between familism and BMI across generational status (Figure 1, row 2). Moreover, we observe little variation across immigrant generation and familism when estimating the likelihood of diabetes, and many of these estimated slopes are close to zero. Higher levels of referent familism do appear to be associated with increased diabetes risk among foreign-born Hispanics, but the magnitude of this association is quite trivial. And while stronger attitudes toward family obligations appear negatively correlated with elevated C-reactive protein, the reverse is true for those reporting higher levels of familial support. However, slopes are not statistically distinguishable from each other, and correlations are quite small. With respect to referent familism and elevated C-reactive protein, we observe significantly different patterning among the 1.5 generation (negative slope) and the U.S.-born (positive slope). An assessment of depressive symptoms continues to suggest that immigrant generation is unlikely to moderate the relationship of interest (row 5). Though we observe a significant and positive relationship between depression and referent familism, there is no indication that this differs across generations. A negative correlation emerges for attitudes surrounding family support and depressive symptoms, but large confidence intervals suggest slopes are unlikely to differ from zero. There is also no evidence that generational differences exist between family obligations and depression. Moreover, we find remarkably similar patterns for anxiety across each dimension of familism: little evidence that slopes differ from each other (or zero) with respect to familial support and obligations, whereas those who report stronger levels of referent familism exhibit higher anxiety (row 4). Again, this relationship does not appear to vary by immigrant generation. Discussion Although numerous studies employ the logic of cultural familism to reconcile patterns of health and well-being among Hispanics, it is generally invoked 284 Journal of Health and Social Behavior 60(3) () Figure 1. Predicted Values of Health Outcomes by Immigrant Generation and Familism. Note: Confidence intervals not shown. First generation significantly different from 1.5 generation. First generation significantly different from U.S.-born. The 1.5 generation significantly different from U.S.-born. 285 Diaz and Niño as a residual explanation with little consideration for key measurement issues. Moreover, attempts to empirically test the linkages between familism and physical health remain exceedingly sparse. This article makes significant contributions to the literature by drawing on a unique data source with information on familial attitudes, mental health, and biomarkers. We assessed the link between familism and health and asked whether this correlation is moderated by immigrant generation. If familism is associated with Hispanic well-being and also declines across generations—or if the effects of familism are weaker among the U.S.-born— familism could be a nontrivial contributor to the health advantage. While there is some indication that physical and mental health declines across immigrant generation, this association weakens with the inclusion of relevant confounders—namely, socioeconomic and cultural characteristics. That we observe such patterns when relying on biomarkers and anthropometrics suggests that the advantageous health observed in the first generation is unlikely to be solely due to data misreporting or undiagnosed conditions. Recent work in medical sociology and public health identify similar patterns in both selected and nationally representative samples of Hispanic populations (e.g., Crimmins et al. 2007). Results also suggest that familism is not associated with the physical health measures used in this study. We do, however, observe a moderately robust relationship between familism and mental health. On the one hand, respondents who report stronger attitudes toward referent familism exhibit heightened symptoms of depression and anxiety. On the other hand, those who hold stronger beliefs toward familial support appear to report better mental health outcomes. Given that perceptions of social support are linked to lower levels of depression among Hispanics and the overall population (Lin, Ye, and Ensel 1999; Russell and Taylor 2009), this pattern is not entirely surprising. And because reports of strong referent familism are associated with elevated anxiety and depression, familism may not consistently operate in a way that is favorable to individuals; numerous obligations and/or mounting pressure may be common among those who form especially strong attachments to relatives. We also emphasize that each familism subscale exhibits a unique relation to health. In fact, referent familism and support operate in competing directions with respect to depression and anxiety. Future work must consider the implications of including a single item or a single dimension of familism in analyses—as opposed to including the entire construct. Although familial support receives substantial attention in the literature and is undoubtedly a key component of a family-oriented belief system, it is one piece of a larger construct that includes multiple dimensions of family life. To ensure appropriate conclusions are drawn, we urge scholars to engage in careful and nuanced consideration to the meaning and measurement of familism (e.g., not conflating social support with familism). Finally, analyses suggest that the correlation between familism and health does not systematically differ across generations. If anything, associations are quite similar for the vast majority of outcomes. To sum: Results illustrate that familism boasts a weak relationship to health, familism does not systematically decline across generations, and the effects of familism on health do not weaken across immigrant generation. We thus believe that the logic of cultural familism is an unsatisfactory explanation for the relatively good health of foreign-born Hispanics. Although future work should continue to explore behaviors related to familism, it is also essential to focus on discrimination and other structural barriers that impede health and well-being. Other Considerations Given that patterns of health and family orientation may differ among men and women (Horowitz et al. 2004; Pistrang and Barker 1995), we investigate this possibility using the HCHS/SOL. Results, which are available on request, provide little indication that gender moderates the association between familism and health. Put differently: The direction and magnitude of estimates are similar for Hispanic men and women, and they are nearly identical to results presented here. Although findings seem to contradict past work, one explanation for this discrepancy could be our focus on familial attitudes as opposed to behaviors. In addition, family conflict may alter the impact of familism on Hispanic well-being (Bostean 2010; Priest and Woods 2015). We thus consider whether recent family conflict moderates the association of interest. There is no evidence that familism and physical well-being systematically differ by the presence of conflict (see Table A4 in the online version of the article). However, conflict appears to moderate the relationship between mental health and certain dimensions of familism—namely, family obligations and referent familism. While a positive correlation emerges between poor mental health and family obligations among those 286 reporting a conflict, the correlation is negative when such conflicts are absent; these estimates, however, are accompanied by large confidence intervals. And while the estimated relation between depression and referent familism is minimal among those reporting conflict, a positive association emerges for those unaware of family conflict. Conflict thus appears to increase depressive symptoms among Hispanics who express particularly low levels of referent familism. This study is not without limitations. First, we rely on cross-sectional data that make it difficult to ascertain the causal direction of interest. While we are unable to address such concerns with these data, the release of subsequent HCHS/SOL data will allow researchers to better evaluate issues surrounding causality and temporal ordering. Second, these data are representative of urban locations that have long histories of hosting immigrant and U.S.born Hispanics. It is thus unlikely that findings generalize to Hispanics residing in rural/suburban areas, who may exhibit a different health profile as a result of unequal access to material and social resources (Derose, Escarce, and Lurie 2007). Despite these limitations, our study provides new insight on familism, immigrant generation, and Hispanic health. We provide a more nuanced understanding of familism and call into question assumptions that family-oriented beliefs and attitudes explain the immigrant health advantage. Supplemental Material Tables A1 through A4 are available in the online version of the article. Acknowledgments The authors are grateful for comments provided by three anonymous reviewers as well as advice from Jenna Nobles. An early version of this manuscript was presented at the annual meetings of the 2019 Population Association of America. Authors’ Note Authors share equal authorship. Funding The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was partially supported by Career Enhancement Fellowships from the Woodrow Wilson Foundation. Opinions reflect those of the authors and not necessarily those of the Foundation. Journal of Health and Social Behavior 60(3) Notes 1. 2. Correlations between factors, which are obtained after rotation, are as follows: rsupport_obligations = .51; rsupport_referent = .42; robligations_referent = .30. 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Supple. 2015. “The Protective Role of Familism in the Lives of Latino Adolescents.” Journal of Family Issues 36(10):1255–73. Turra, Cassio M., and Irma T. Elo. 2008. “The Impact of Salmon Bias on the Hispanic Mortality Advantage: Journal of Health and Social Behavior 60(3) New Evidence from Social Security Data.” Population Research and Policy Review 27(5):515–30. United Nations Office on Drugs and Crime. 2017. World Drug Report 2017. Vienna: United Nations. Valdivieso-Mora, Esmeralda, Casie L. Peet, Mauricio Garnier-Villarreal, Monica Salazar-Villanea, and David K. Johnson. 2016. “A Systematic Review of the Relationship between Familism and Mental Health Outcomes in Latino Population.” Frontiers in Psychology 7(1):16–32. Vega, William A., Bohdan Kolody, Sergio AguilarGaxiola, Ethel Alderete, Ralph Catalano, and Jorge Caraveo-Anduaga. 1998. “Lifetime Prevalence of DSM-III-R Psychiatric Disorders among Urban and Rural Mexican Americans in California.” Archives of General Psychiatry 55(9):771–78. Velasco-Mondragon, Eduardo, Angela Jimenez, Anna G. Palladino-Davis, Dawn Davis, and John EscamillaCejudo. 2016. “Hispanic Health in the USA: A Scoping Review of the Literature.” Public Health Review 7(1):1–27. Villarreal, Ricardo, Shelley A. Blozis, and Keith F. Widaman. 2005. “Factorial Invariance of a PanHispanic Familism Scale.” Hispanic Journal of Behavioral Sciences 27(4):409–25. Zayas, Luis H., Charlotte L. Bright, Thyria Álvarez-Sánchez, and Leopoldo J. Cabassa. 2009. “Acculturation, Familism and Mother–Daughter Relations among Suicidal and Non-suicidal Adolescent Latinas.” The Journal of Primary Prevention 30(3):351–69. Zeiders, Katharine H., Mark W. Roosa, George P. Knight, and Nancy A. Gonzales. 2013. “Mexican American Adolescents’ Profiles of Risk and Mental Health: A Person-Centered Longitudinal Approach.” Journal of Adolescence 36(3):603–12. Author Biography Christina J. Diaz is an assistant professor in the School of Sociology and an affiliate of the Department of Latin American Studies at the University of Arizona. Her research focuses on Hispanic well-being, with attention to migration patterns along the Mexico–U.S. border. She is currently studying the contribution of immigrants to American culture and the implications of this process for U.S. race-ethnic relations. Diaz received a 2018 Career Enhancement Fellowship from the Woodrow Wilson Foundation. Michael D. Niño is an assistant professor of sociology at Willamette University. His current research agenda focuses on integrating theory and methods from the biological and social sciences to advance our understanding of how immigration, race, and incarceration shape population health disparities and health behaviors in the United States. He also received a 2018 Career Enhancement Fellowship from the Woodrow Wilson Foundation. RESEARCH AND PRACTICE Black–White Health Disparities in the United States and Chicago: A 15-Year Progress Analysis Jennifer M. Orsi, MPH, Helen Margellos-Anast, MPH, and Steven Whitman, PhD Racial disparities in health in the United States have been well documented, and federal initiatives have been undertaken to reduce these disparities. One of the first federal initiatives to bring awareness to racial disparities in health was the 1985 Report of the Secretary’s Task Force on Black and Minority Health, which highlighted the need for programs and policies to address disparities in health within the United States.1 Many initiatives have followed. The most recent federal initiative is Healthy People 2010, which consists of 2 main goals, 28 focus areas, and 467 objectives. One of the main goals is the elimination of health disparities within the United States.2 This builds upon one of the goals from Healthy People 2000, which aimed at the reduction of health disparities.3 Interestingly, although the reduction and elimination of health disparities are declared priorities, there are few reports that comprehensively examine progress in this area by analyzing changes in multiple indicators. In 2001, Silva et al. published a study of 22 health status indicators in Chicago, Illinois, and compared outcomes for Black and White people between 1980 and 1998.4 An important contribution in this area came from Keppel et al. in 2002 when they evaluated the Healthy People 2000 goal of reducing health disparities at the national level by examining progress in reducing disparities among the 5 largest racial/ethnic groups in the United States for 17 health status indicators between 1990 and 1998.5 The analysis revealed that for the majority of indicators, racial/ethnic disparities had declined over the period on the national level. However, a comparable Chicago-specific analysis by Margellos et al. focusing on non-Hispanic Black–non-Hispanic White disparities found that although the majority of Black–White disparities narrowed nationally between 1990 and 1998, the opposite was true in Chicago with the majority widening over the same interval.6 First, we wanted to determine whether the Black–White disparity within each of 15 health Objectives. In an effort to examine national and Chicago, Illinois, progress in meeting the Healthy People 2010 goal of eliminating health disparities, we examined whether disparities between non-Hispanic Black and non-Hispanic White persons widened, narrowed, or stayed the same between 1990 and 2005. Methods. We examined 15 health status indicators. We determined whether a disparity widened, narrowed, or remained unchanged between 1990 and 2005 by examining the percentage difference in rates between non-Hispanic Black and non-Hispanic White populations at both time points and at each location. We calculated P values to determine whether changes in percentage difference over time were statistically significant. Resul... Purchase answer to see full attachment

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