Advances in Applied Sociology
2013. Vol.3, No.4, 193-198
Published Online August 2013 in SciRes (http://www.scirp.org/journal/aasoci) http://dx.doi.org/10.4236/aasoci.2013.34026
Copyright © 2013 SciRes. 193
Pathways to Health Services Utilization: Overcoming Economic
Barriers through Support Mechanisms
Priscila Diaz1, Jessica Stahl2, David Lovis-McMahon2, Summer H. Y. Kim2,
Virginia S. Y. Kwan2
1Psychology Department, Azusa Pacific University, Azusa, USA
2Psychology Department, Arizona State University, Tempe, USA
Received June 12th, 2013; revised July 12th, 2013; accepted July 19th, 2013
Copyright © 2013 Priscila Dia et al. This is an open access article distributed under the Creative Commons At-
tribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the
original work is properly cited.
Objective: By 2014, over 30 million Americans currently lacking health insurance will be able to access
health services. While enhancing accessibility to healthcare is a significant step towards reducing health
disparities, it is unclear whether access to health services will result in utilization of such services. Previ-
ous studies demonstrate that lower socioeconomic status (SES) is a key social determinant of poor health
outcomes. The present research examined the potential SES gradient in the utilization of medical services
considering healthcare accessibility, and how family support influences healthcare decision-making.
Methods: A sample of young Americans with universal access to healthcare services was surveyed to de-
termine whether decisions to visit the doctor for certain symptoms are differed by SES. In a follow-up
young adult sample, the bearing of various forms of family support was examined as potential mecha-
nisms that may explain SES differences in seeking healthcare. Results: Among informational, financial,
and emotional support, it was found that emotional (how emotionally supportive family is when one is ill)
and informational support (how often one consults family for health-related issues) mediated SES and the
frequency of health services utilization. Higher SES individuals received more emotional and informa-
tional health support from family, which was associated with more immediate healthcare utilization. Con-
clusion: The findings suggest an explanation for incrementally worse health outcomes for lower SES in-
dividuals because of their delay in seeking medical attention. While SES is not a controllable factor,
strengthening support networks for health consultation has valuable implications for healthcare promotion
Keywords: Health Services Utilization; Healthcare Coverage; Socioeconomic Status; Social Support
Health disparities are defined as differences in disease pre-
valence, health status or access to healthcare based on popula-
tion demographics US Department of Health and Human Ser-
vices, 2011. Currently, uninsured Americans have the poorest
health outcomes and many are from low socioeconomic back-
grounds (DeNavas-Walt, Proctor, & Smith, 2007). To address
long-standing health disparities in the US, President Obama
signed into law the Patient Protection and Affordable Care Act
(PPACA, March 23rd, 2010) that proposes access to healthcare
by 2014 for an estimated 30 million Americans who are cur-
rently uninsured (Consumer Health Reports, 2010). Specifically,
PPACA allocates government subsidies to increase accessibil-
ity of health services for individuals with low socioeconomic
Healthcare reform has generated a contentious political arena
beginning with early legal challenges from several states, de-
claring the law unconstitutional and leading to a recent repeal
of PPACA (Davis & Litvan, 2011). Despite the political mael-
strom surrounding healthcare reform, public opinion is clearly
divided, vacillating between support and opposition over time
(Brodie, Altman, Deane, Buscho, & Hamel, 2010). Vice Presi-
dent Biden expressed his optimism in 2010 as PPACA was
being signed into law at The White House: “Mr. President, you
are… literally about to make history… tens of millions of
Americans will be a whole lot healthier from this moment on.”
While enhancing accessibility to healthcare is a significant step
forward, little is known about whether merely having coverage
for health services will actually lead to timely, preventative
utilization of health services.
Lack of adequate healthcare coverage has often been noted
as a major cause of health disparities in the United States. Nev-
ertheless, health disparities persist even in countries with uni-
versal healthcare such as England (Townsend & Davidson,
1982) and Sweden (Lundberg, 1991). Socioeconomic status—
where an individual stands in society in terms of income, edu-
cation, and occupational prestige—is a consistent predictor of
health outcomes across samples of different demographics. The
pattern is a gradient such that, with every incremental decrease
in socioeconomic status, health status also worsens incremen-
tally with lower SES individuals reporting worse health status
(Adler, Boyce, Chesney, Folkman, & Kahn et al., 1993). This
gradient has been widely documented across ethnic groups, sex,
P. DIAZ ET AL.
occupational backgrounds, age groups, as well as in other rep-
resentative samples in the US (e.g., Ostrove, Feldman, & Adler,
1999; Goodman, Adler, Daniels, Morrison, Slap, & Dolan,
2003; Goodman, McEwen, Dolan, Schafer-Kalkhoff, & Adler,
2005; Operario, Adler, & Williams, 2004).
The bulk of literature regarding the SES-health gradient
clearly demonstrates that SES predicts health status regardless
of whether the individual has access to healthcare. Why do SES
differences in health status persist even when individuals have
equal access to medical services? Are there behavioral differ-
ences in medical attention seeking related with SES? Past lit-
erature has focused on actual health outcomes and has not ad-
dressed how SES relates to healthcare utilization. Understand-
ing SES differences in healthcare utilization may provide in-
sight into inclusive approaches towards reducing health dispari-
ties. Healthcare utilization refers to a variety of medical atten-
tion seeking behaviors including going to the doctor (Gorman
& Braverman, 2008). Different socioeconomic groups may ex-
hibit varying levels of healthcare utilization even when they all
have access to health services, which may provide insight into
the SES gradient regarding health outcomes.
A major aim of this research is to extend the work regarding
the SES-health status gradient to include the concept of health-
care utilization. SES is expected to be a significant determinant
of utilization when access to healthcare is not a limiting factor.
In two studies, we recruited an all-insured sample that suffi-
ciently varies in SES but equivalent in access to healthcare
service, of similar age, and comparable levels of education.
Rather than recruiting in the general community where health
insurance policies differ between individuals and healthcare
coverage varies by SES, the type of insurance coverage was
equivalent across all participants in this study (i.e. university
students), even of different SES backgrounds. This sample mir-
rors what PPACA aims to accomplish in the general population,
and therefore helps to simulate what might occur when most
Americans obtain reasonable access to health insurance.
In Study 1, we predicted individuals from lower socioeco-
nomic groups to utilize healthcare services for common symp-
toms less frequently than individuals from higher socioeco-
nomic groups. Another major aim of this research investigates
what factors may facilitate or hinder healthcare utilization ser-
vice among young adults from low SES. Study 2 examines
three forms of health related family support that account for
differences in healthcare utilization by SES, which is suggested
by the bodies of literature on socialization of health behaviors
and on forms of social support. By identifying these psychoso-
cial factors, intervention programs may be structured to pro-
mote timely utilization of health services and the effectiveness
of US healthcare.
Study 1: Healthcare Utilization and the SES
Participants. There were 194 individuals (mean age = 19)
who indicated having student healthcare coverage (female =
111). The insurance co-pay for a health visit was $10. Ethical
guidelines were followed and the study was approved by the
Institutional Review Board Committee. The participants at-
tended a southwestern state university and were compensated
with 1 credit hour to complete a research requirement. The
sample consisted of 153 White/Caucasian, 36 Latino/Hispanic,
4 indicated other. In validating the data, sixteen participants
were excluded. Eleven were excluded because they stated that
they did not have insurance. The remaining five were excluded
because they had missing values for either the SES or the
Healthcare Utilization questions.
Materials. To assess when individuals make the decision to
see a physician about an illness, participants were asked to
choose one of five answer choices that increased in severity or
duration for six common health symptoms (i.e., cough, stomach
pain, heartburn, dizziness, sore throat, and fever). Response
values depended on the symptom; for example, the symptom
Cough included: 1 = One week, 2 = Two weeks, 3 = One month,
4 = Two months, 5 = Three months, 6 = would not go to the
doctor until symptom lasted longer; whereas the symptom Fe-
ver included: 1 = 100˚, 2 = 101˚, 3 = 102˚, 4 = 103˚, 5 = 104˚, 6
= would not go to the doctor until symptom got worse. Partici-
pants were asked to recall their prior experience to answer the
questions or to make a best guess about what they would do if
they did have the symptom. The above were chosen based on a
pool of common symptoms listed on MayoClinic.com and their
generalizability for young adults, since it is likely that one has
experienced at least a few of the above symptoms by age 18.
The mean response to the healthcare utilization questions was
calculated for each participant. This healthcare utilization index
had a minimum score of 1.17 and a maximum score of 5.33.
(Cronbach’s alpha = .64).
To examine the SES-health gradient, we measured both ob-
jective SES (e.g., education attainment, household income,
occupation type, and wealth), and subjective SES (e.g., Mac-
Arthur Scale of Subjective Social Status, which asks partici-
pants to indicate their position in a 9- or 10-rung ladder where
the top of the ladder indicated highest SES and bottom indi-
cated lowest SES). While both objective and subjective meas-
ures independently predict health outcomes, subjective SES
captures finer gradations of objective indicators, such that it
reflects the difference in quality (e.g., quality of education
based on the prestige of the school) that is not captured by the
objective indicators. To determine subjective SES, we asked
participants to choose their family’s socioeconomic status in
terms of income (working class = 1 to upper class = 5). The
majority of participants reported middle class (M = 3.40, SD
To examine how individuals of varying levels of SES utilize
healthcare for several symptoms, a bivariate correlation be-
tween SES and health utilization was conducted. SES and
healthcare utilization were significantly related, r (178) = −.17,
p < .05, indicating that individuals from a lower SES back-
ground delay utilizing healthcare for various symptoms (see
The results correspond to the gradient in health outcomes
based on SES as documented in past literature, but extend this
work to include the utilization of healthcare services. Findings
of Study 1 document an SES difference in health services utili-
zation; individuals from lower socioeconomic status utilize
health services less frequently than their higher SES counter-
parts. Every participant had access to an insurance policy, so
availability of access could not explain the pattern of utilization.
The link between SES and utilization of healthcare may con-
Copyright © 2013 SciRes.
P. DIAZ ET AL.
Socioeconomic status gradient in the delay of utilizing healthcare ser-
tribute to the SES-health gradient considering that individuals
of lower SES are not seeking medical attention in a timely
manner. Symptoms left untreated may lead to serious illness;
hence, a follow-up study examined the support mechanisms
involved in this process.
Study 2: Contextual Factors between SES and
Healthcare Utilization Link
Why did lower SES individuals with universal access to
healthcare delay seeking medical attention? SES is a key social
determinant of health that begins with delaying healthcare
utilization as shown in Study 1. However, the specific mecha-
nisms and processes of healthcare utilization remain unclear.
What factors may influence healthcare utilization among indi-
viduals of different socioeconomic backgrounds? It may be that
the action of utilizing healthcare is socialized within families
from an early age and sustained through a supportive network,
much like the formation of our attitudes, behaviors, and habits.
Thus, three forms of family support (emotional, informational,
financial) were investigated as intermediary links between SES
and healthcare utilization.
Families are the basic foundation for social connectedness
and supportive relationships. Social connectedness creates a
web of support that builds norms for adopting healthy habits,
diffuses information about health, and promotes access to ser-
vices (Kawachi, Kennedy, & Glass, 1999). Individuals who de-
cide to seek help from their social network are also more likely
to receive recommendations for assistance (Dew, Bromet, Schul-
berg, & Parkinson, 1991; Vogel, Wade, Wester, Larson, &
Prior research demonstrates the persistent influence of pa-
rental socialization on health beliefs, even after children be-
come young adults and leave home (e.g., to attend college; Lau,
Quadrel, & Hartman, 1990). The weight of socialization, atti-
tude internalization and belief formation from the family may
shape behaviors toward medical decisions, health-related per-
sonnel, and health services utilization patterns. More funda-
mentally, children learn from their parents to identify and de-
fine their bodily feelings as symptoms that may or may not
need medical attention (Cardol, Groenewegen, Spreeuwenberg,
Van Dijk, Van Den Bosch, & De Bakker, 2006). As a result of
this socialization process, family members utilize medical ser-
vices in similar ways.
In addition, previous research shows that when we experi-
ence the symptoms of an illness, we first seek help from our
social network (e.g., family) before seeking professional help
(Horwitz, 1977). The types of help that we seek from our social
network can be categorized into different types of social sup-
port: emotional support and instrumental support (Seeman,
1996; House, Umberson, & Landis, 1988). Emotional support
includes providing encouragement and a sense of comfort. In-
strumental support may be organized into further subcategories,
such as financial support (providing monetary help) and infor-
mational support (providing advice). Given that social suppor-
tive connections play a vital role in an individual’s decisions
(including health behaviors), we posited that one’s family
members would be a source of support and that such support
would positively relate to health outcomes. Consequently,
Study 2 investigated the pattern of three distinct means of fam-
ily social support (i.e., emotional, informational and financial
support) on healthcare utilization in consideration of SES. In-
creased levels of these three support mechanisms were pre-
dicted to mediate the relationship between SES and the decision
of when to see the doctor.
Participants. There were 557 students (female = 308) with
health insurance attending a southwestern state university
(mean age = 19.6). The insurance co-pay for a health visit was
$10. The study was approved by the Institutional Review Board
Committee and ethical guidelines with participants were fol-
lowed. The sample consisted of 356 White/Caucasian, 87 La-
tino/Hispanic, 30 Black/African American, 8 Native American,
41 Asian/Asian-American, 14 Arab/Middle Eastern and 20 in-
dicated Other. Of the initial 557 participants, forty-eight were
excluded for stating that they did not have health insurance. A
further thirteen participants were excluded for having some
combination of missing values on the SES, three family support
items, or the healthcare utilization index.
Materials. Healthcare utilization and SES measures from
Study 1 were used in Study 2. As with the Study 1, each par-
ticipant received a healthcare utilization index score. This
healthcare utilization index had a minimum score of 1.17 and a
maximum score of 5.83. Cronbach’s alpha for the index was .69.
The majority of participants reported middle class (M = 3.30,
SD = .86).
Three items assessed the type and level of family support
with an illness. One item asked participants to report how emo-
tionally supportive their family would be if they were sick and
the second item asked about financial support (1 = Not suppor-
tive to 5 = Very supportive). The third item assessed the level
of communication about health within one’s family by asking
participants if they consulted with their family about medical
decisions (1 = Very often to 5 = Never).
Bivariate correlations were conducted to examine the rela-
tionships between SES, family support factors and health utili-
zation (see Table 1). Similar to Study 1 results, SES was sig-
nificantly related to healthcare utilization (r = −.10, p < .05).
Copyright © 2013 SciRes. 195
P. DIAZ ET AL.
Study 2 correlations between socioeconomic status, support and health-
care utilization behaviors.
1 2 3 4 5
1. SES 1 .214** .109* .323** −.095*
2. Information 1 .243** .301** −.257**
3. Emotional 1 .430** −.156**
4. Financial 1 −.081
Individuals who reported a lower SES tended to wait longer
to visit the doctor. SES also correlated with emotional support,
(r = .11, p < .05), financial support, (r = .32, p < .05), and in-
formational support, (r = .22, p < .05). Individuals who reported
a higher SES generally communicated with their family about
healthcare to a greater extent and reported greater emotional
and financial support. However, healthcare utilization was sig-
nificantly related to emotional support (r = −.26, p < .05) and
informational support (r = −.16, p < .05) but not financial sup-
port (r = −.08, p > .05). With greater emotional and informa-
tional support, individuals with health insurance were more
likely to visit the doctor sooner.
Based on the results of the correlation analyses, we next
tested whether informational support and emotional support are
significant mediators underlying the effects of SES on health-
care utilization. Following Baron and Kenny’s (1986) four-step
procedure, we conducted a series of regression analyses to es-
tablish the mediating role of information support. On step 1,
SES was significantly associated with informational support (β
= .21; R2 = .05, p < .01). On step 2, SES was significantly asso-
ciated with healthcare utilization (β = −.10; R2 = .01, p < .05).
On step 3, informational support was significantly associated
with healthcare utilization (β = −.26; R2 = .07, p < .01). On step
4, the regression of healthcare utilization on informational sup-
port (β = −.25, p < .05) was significant but not SES (β = −.04, p
> .05) with the overall model R2 = .07, p < .01. The relationship
between SES and healthcare utilization did not remain signifi-
cant when family informational support is accounted for, sug-
gesting that the relationship between SES and healthcare utili-
zation is mediated by informational support (Sobel test, z =
−3.76, p < .01). Thus, individuals with higher SES received
more health consultation from family, which, in turn, associated
with more immediate healthcare utilization (Figure 2).
Likewise, we conducted a series of regression analyses to
establish the mediating role of emotional support. On step 1,
SES was significantly associated with emotional support (β
= .11; R2 = .01, p < .05). On step 2, SES was significantly asso-
ciated with healthcare utilization (β = −.10; R2 = .01, p < .05).
On step 3, emotional support was significantly associated with
healthcare utilization (β = −.15; R2 = .02, p < .05). On step 4,
the regression of healthcare utilization on emotional support (β
= −.15, p < .05) was significant but not for SES (β = −.08, p
> .05) with the overall model R2 = .04, p < .05. The relationship
between SES and healthcare utilization did not remain signifi-
cant with family emotional support, suggesting that the rela-
tionship between SES and healthcare utilization is mediated by
emotional support (Sobel test, z = −1.99, p < .05). Thus, indi-
viduals with higher SES tended to receive more emotional
health support from family, which, in turn, was associated with
more immediate healthcare utilization (Figure 3). Together,
these findings provide mechanisms of the contextual factors
that may contribute to the effect of SES on healthcare utiliza-
tion. In particular, health information and emotional support
provided by family are strong determinants in explaining how
individuals from varying levels of SES differ in their healthcare
The current findings demonstrate that in a sample with uni-
versal access to healthcare, low SES individuals tend to delay
utilization of healthcare when presented with concerning
symptoms (i.e., fever of 104˚). Family emotional and informa-
tional support accounts for these differences in SES and
healthcare utilization behaviors. The landmark Whitehall stud-
ies (Marmot, Stansfield, Patel, North, Head, White et al., 1991)
identified an SES gradient in health outcomes among workers
with universal access to health services, in which lower SES
individuals had incrementally worse health outcomes at every
level of the gradient. Study 1 revealed a SES-utilization gradi-
ent with individuals from lower SES backgrounds delaying
utilization of health services for various symptoms. Despite
concerns about newly insured patients overwhelming the
healthcare system (Heflin, 2010), access does not necessarily
lead to greater utilization as Study 1 and 2 findings show low
SES individuals delay medical attention. These findings sug-
gest a potential explanation for incrementally worse health
outcomes for lower SES individuals because of their delay in
The mediation of socioeconomic status on the delay of utilizing health-
care services by Family Informational Support.
The partial mediation of socioeconomic status on the delay of utilizing
healthcare services by Family Emotional Support.
Copyright © 2013 SciRes.
P. DIAZ ET AL.
seeking medical attention. Identifying the key factors concomi-
tant with timely, appropriate health services utilization could
significantly increase the effectiveness of health promotion
Prior research has established that family does play a part in
how individuals seek professional help. Similarly, Study 2
found that higher SES individuals report greater emotional and
financial support and communicated with their family about
healthcare to a greater extent. The SES-utilization gradient
from Study 1 was replicated as lower SES individuals waited
longer to visit the doctor for symptoms. The key to under-
standing the SES-utilization gradient may lie in the fact that
individuals with higher SES engaged in more health consulta-
tion with their family and received greater emotional support.
These two factors associated with timely healthcare utilization,
whereas financial support was not significantly related to health
services utilization among individuals with health insurance.
Thus, the relationship between SES, emotional support and
health consultation with close others may be a key factor in
medical attention seeking behavior. In that case, health promo-
tion efforts focused on increasing communication about health
matters with family, friends, and significant others may be
highly effective, which would be congruent with the success of
peer mentor programs, and community health advocates.
The generalization of the results is limited to college students,
which may suitable in this initial investigation. Given that the
U.S. currently does not have universal healthcare and that all
provisions of the PPACA will not be fully implemented until
2018, it is challenging to select a sample with sufficient diver-
sity and universal access to health services. In that sense, the
sample was both demographically representative and uniquely
homogenous with regard to access to health services since all
students had access to the same student health insurance and the
student health center, which was conveniently located on the
campus. Thus, universal access to care was removed as an ob-
stacle for this study whereas it remains a challenge in the US
population. Future research should include a larger sample with
more diversity in terms of age, level of education, occupations,
health status, and life experience. It would likely be informative
to explore the specific content and characteristics of emotional
support and health consultation with significant others that lead
to health service utilization, particularly for groups where fam-
ily dependence varies. Certain trusted figures may have more
influence than others (e.g., mother vs. best friend) and possibly
more frequent discussions with multiple people have a more
powerful influence on health decision-making. Beyond the
scope of the current research is to evaluate the appropriate time
to utilize health services. Future studies should incorporate
doctor’s recommendations on when to seek medical attention
for these symptoms (a fever of 100˚ vs. a fever of 104˚), in
order to accurately utilize healthcare services when given ac-
cess and survey individuals’ real experiences with these ill-
nesses rather than hypothetical accounts.
Public health campaigns, health directives from medical pro-
fessionals, and community health efforts all seek to increase
positive health outcomes. Yet, it has been challenging to iden-
tify the major characteristics of successful health promotion.
Society has generally relied upon retrospective analyses to de-
termine the effectiveness of health promotion efforts rather than
being able to confidently predict whether they will be effective.
Much of the recent debate regarding healthcare reform has
focused on the need to reduce utilization of health services
because of the perceived costs and the anticipated strain on the
current medical system when 32 million Americans begin to
utilize health services (Cutler, 2010). However, the preponder-
ance of research elucidates the high financial and social costs of
ineffective health promotion efforts and the negative, long-term
health effects of delayed healthcare, emphasizing the benefits
of timely health services utilization. This research demonstrates
that supportive emotional relationships and health consultation
with significant others is an important aspect of individuals not
delaying medical attention. This provides an operative frame-
work for appropriate public health messages, programs, and
campaigns. It could also provide health professionals with a
constructive avenue to conversations with patients regarding
health issues as they encourage the patient to share information
with their significant others rather than focusing solely on con-
veying health information to the patient in the medical setting.
Effective health promotion efforts may also be the soundest
way to reduce the prevalence of diseases (e.g., obesity, diabetes)
that are rooted in lifestyle choices wherein the patient does not
perceive the necessity for behavior change. This research sug-
gests that individuals who share, trust and seek advice on health
issues with significant others are more likely to utilize health
services, which also suggests that they take a more proactive
approach towards their own health. Successful health promo-
tion efforts are essential as society faces an unprecedented ur-
gency for effective health promotion methods with millions of
new patients entering into the healthcare system.
We would like to thank the following individuals for their
comments on an earlier version of this manuscript and help
with data collection: Andrea Fessler, Aresh Vasefi, Benjamin
Lozada, Jason Baxter, Jose Alba and Megan Leonhardt. The
first author has been partially supported by National Institute of
Mental Health Grant T32MH018387-24.
Adler, N. E., Boyce, T., Chesney, M. A., Cohen, S., Folkman, S., Kahn,
R. L., & Syme, S. L. (1994). Socioeconomic status and health: The
challenge of the gradient. American Psychologist, 49, 15-24.
Baron, R. M., & Kenny, D. A. (1986). The moderator-mediator variable
distinction in social psychological research: Conceptual, strategic,
and statistical considerations. Journal of Personality and Social Psy-
chology, 51, 1173-1182. doi:10.1037/0022-35126.96.36.1993
Brodie, M., Altman, D., Deane, C., Buscho S., & Hamel, E. (2010).
Liking the pieces, not the package: Contradictions in public opinion
during health reform. Health Affairs, 29, 2323-2334.
Cardol, M., Groenewegen, P. P., Spreeuwenberg, P., Van Dijk, L., Van
Den Bosch, W. J. H. M., & De Bakker, D. H. (2006). Why does it
run in families? Explaining family similarity in help-seeking behav-
iour by shared circumstances, socialization, and selection. Social Sci-
ence & Medicine, 63, 920-932. doi:10.1016/j.socscimed.2006.01.025
Consumer Health Reports (2010).
Cutler, D. (2010). How health care reform must bend the cost curve.
Health Affairs, 29, 1131-1135. doi:10.1377/hlthaff.2010.0416
Davis, J. H., & Litvan, L. (2011). Senate republicans introduce health-
overhaul repeal. Bloomber Business Week.
Copyright © 2013 SciRes. 197
P. DIAZ ET AL.
Copyright © 2013 SciRes.
DeNavas-Walt, C., Proctor, B. D., & Smith, J. (2007). Income, poverty,
and health insurance coverage in the United States: 2006. Washing-
ton DC: US Government Printing Office.
Dew, M. A., Bromet, E. J., Schulberg, H. C., & Parkinson, D. K. (1991).
Factors affecting service utilization for depression in a white collar
population. Social Psychiatry and Psychiatric Epidemiology, 26, 230-
Goodman, E., Adler, N. E., Daniels, S. R., Morrison, J. A., Slap, G. B.,
& Dolan, L. M. (2003). Impact of objective and subjective social sta-
tus on obesity in a biracial cohort of adolescents. Obesity Research,
11, 1018-1026. doi:10.1038/oby.2003.140
Goodman, E., McEwen, B. S., Dolan, L. M., Schafer-Kalkhoff, T., &
Adler, N. E. (2005). Social disadvantage and adolescent stress. Jour-
nal of Adolescent Health, 37, 484-492.
Gorman, B., & Braverman, J. (2008). Family structure differences in
healthcare utilization among U.S. children. Social Science & Medi-
cine, 67, 1766-1775. doi:10.1016/j.socscimed.2008.09.034
Heflin, J. (2010). Health reform threatens to cram already overwhelmed
emergency rooms. The Hill.
Horwitz, A. (1977). Pathways into psychiatric treatment: Some differ-
ences between men and women. Journal of Health and Social Be-
havior, 18, 169-178. doi:10.2307/2955380
House, J., Landis, K., & Unberson, D. (1988). Social relationships and
health. Science, 241, 540-545. doi:10.1126/science.3399889
Kawachi, I., Kennedy, B. P., & Glass, R. (1999). Social capital and
self-rated health: A contextual analysis. American Journal of Public
Health, 89, 1187-1193. doi:10.2105/AJPH.89.8.1187
Lau, R., Quadrel, M., & Hartman, K. (1990). Development and change
of young adults’ preventive health beliefs and behavior: Influence
from parents and peers. Journal of Health and Social Behavior, 31,
Lundberg, O. (1991). Causal explanations to class inequalities in health:
An empirical analysis. Social Science & Medicine, 32, 385-394.
Marmot, M. G., Stansfield, S., Patel, C., North, F., Head, J., White, I.,
Brunner, E., Feeney, A., Marmot, M. G., & Davey-Smith, G. (1991).
Health inequalities among British civil servants: The whitehall II
study. Lancet, 337, 1387-1393. doi:10.1016/0140-6736(91)93068-K
Operario, D., Adler, N. E., & Williams, D. R. (2004). Subjective social
status: Reliability and predictive utility for global health. Psychology
& Health, 19, 237-246. doi:10.1080/08870440310001638098
Ostrove, J. M., Feldman, P., & Adler, N. E. (1999). Relations among
socioeconomic status indicators and health for African-Americans
and Whites. Journal of Health Psychology, 4, 451-463.
Patient Protection and Affordable Care Act (2010). PPACA, P.L., 23
March 2010, 111-148.
Seeman, T. E. (1996). Social ties and health. Annals of Epidemiology, 6,
Townsend, P., & Davidson, N. (1982). Inequalities in health: The black
report. Penguin: Harmondsworth.
US Department of Health and Human Services (2011).
Vogel, D. L., Wade, N. G., Wester, S. R., Larson, L., & Hackler, A. H.
(2007). Seeking help from a mental health professional: The influ-
ence of one’s social network. Journal of Clinical Psychology, 63,