Question:
You are given the full text of a scientific research paper.

    Your task is to generate a structured **policy brief** that includes the following components:

    - A concise, descriptive **title** that captures the central theme or policy issue addressed in the paper (do not label it with “Title:”).
    - **Policy Problem** - What societal or strategic challenge is the paper addressing?
    - **Scientific Research Findings** - What are the key results relevant to this issue?
    - **Scientific Research Study Methods** - What methodology or data supports these findings?
    - **Policy Implications** - How might the findings guide or influence policy?

    Write each section in a clear, accessible style suitable for policymakers. Avoid overly technical language, but use essential terms when necessary. Structure the output as a labeled five-part policy brief document.

    Scientific Research Paper:
    https://doi.org/10.1177/00221465231194043
Journal of Health and Social Behavior
2024, Vol. 65(1) 2–19
© American Sociological Association 2023
DOI: 10.1177/00221465231194043
journals.sagepub.com/home/hsb
Original Article
Preventive health care use can reduce the risk of dis-
ease, disability, and death (U.S. Department of
Health and Human Services [USDHHS] 2022). For
example, sigmoidoscopy and colonoscopy screen-
ings are important tools in reducing deaths from
colorectal cancer (Brenner, Stock, and Hoffmeister
2014), flu shots decrease the risk of serious illness if
infected (Ferdinands et al. 2021), and COVID-19
vaccinations prevented an estimated 14.4 to 19.8
million deaths worldwide during the first year of use
(Watson et al. 2022). “Preventive care” generally
includes spending on programs for public health
information, education, and counseling; immuniza-
tion, early disease detection, and healthy condition
monitoring programs (e.g., for monitoring preg-
nancy, child growth and development, general
health checkups); epidemiological surveillance; and
emergency preparedness and disaster response
(Kamal and Hudman 2020). Despite the clear health
benefits preventive care offers, the majority of U.S.
adults do not receive all recommended clinical
preventive services (Borsky et al. 2018). Thus,
understanding and addressing the determinants of
preventive care use is critical to reducing prevent-
able deaths, which are higher in the United States
than all other OECD countries, and vital for improv-
ing population health (Kamal and Hudman 2020).
A growing literature points to structural sexism as
an important upstream driver of population health in
the United States (Homan 2019, 2021a, 2021b;
Kavanagh and Graham 2019; Krieger 2020).
Structural sexism refers to systematic gender
inequality in power and resources in a given social
context (Homan 2019). Structural sexism directs
attention beyond individual sexist beliefs and
1194043 HSBXXX10.1177/00221465231194043Journal of Health and Social BehaviorDore et al.
research-article2023
1Emory University, Atlanta, GA, USA
2Florida State University, Tallahassee, FL, USA
Corresponding Author:
Emily C. Dore, Department of Sociology, Emory
University, 1555 Dickey Drive, Atlanta, GA 30322, USA.
Email: emily.catherine.dore@emory.edu
Structural Sexism and
Preventive Health Care Use
in the United States
Emily C. Dore1
, Surbhi Shrivastava1,
and Patricia Homan2
Abstract
Preventive health care use can reduce the risk of disease, disability, and death. Thus, it is critical to
understand factors that shape preventive care use. A growing body of research identifies structural sexism
as a driver of population health, but it remains unknown if structural sexism is linked to preventive care
use and, if so, whether the relationship differs for women and men. Gender performance and gendered
power and resource allocation perspectives lead to competing hypotheses regarding these questions.
This study explores the relationship between structural sexism and preventive care in gender-stratified,
multilevel models that combine data from the Behavioral Risk Factor Surveillance System with state-level
data (N = 425,454). We find that in states with more structural sexism, both men and women were less
likely to seek preventive care. These findings support the gender performance hypothesis for men and the
gendered power and resource allocation hypothesis for men and women.
Keywords
gender inequality, health disparities, preventive health care, state context, structural sexism

Dore et al.
3
behaviors to highlight the institutional arrangements
in a society that privilege men and subordinate
women (Homan 2019; Ridgeway and Correll 2004).
Studies have shown that structural sexism in U.S.
state-level institutions is linked to a variety of nega-
tive health outcomes among women, men, and chil-
dren, including worse self-rated health, more chronic
conditions, worse physical functioning, and higher
infant and adult mortality rates (Homan 2019;
Kavanagh, Shelley, and Stevenson 2017; Kawachi
et al. 1999; Koenen, Lincoln, and Appleton 2006).
One pathway through which structural sexism
may harm health is via its impact on health care.
There is very little research on the topic, but one
study by Rapp et al. (2022) found that higher state-
level structural sexism is associated with decreased
health care access and more barriers to affordability
among women. No studies to date have examined
the relationship between structural sexism and pre-
ventive care use and how it might differ among
women and men. This represents a major gap in
knowledge that can hinder efforts to improve health
and health equity in the United States.
To address this gap, the present study uses the
Behavioral Risk Factor Surveillance System
(BRFSS) combined with state-level data to explore
the relationship between structural sexism and nine
different types of preventive health care use in
gender-stratified, multilevel models. Gender perfor-
mance theories and gendered power and resource
allocation perspectives generate the study’s two
hypotheses about the relationship between structural
sexism and preventive care. In high-sexism environ-
ments, gender performance theory suggests that
men would be less likely and women more likely to
access needed preventive care, and gendered power
and resource allocation perspective posits that both
men and women would be less likely to access care.
Findings suggest that both theoretical perspectives
contribute to our understanding of health care use
among men, whereas only a gendered power and
resource allocation perspective is relevant for
women. Results demonstrate a pattern of universal
harm, suggesting that reducing structural sexism is a
promising approach to increasing preventive care
use for both women and men in the United States.
This study provides novel empirical evidence and
important theoretical insights with policy implica-
tions for preventive health care use.
Background
The overall picture of preventive health care use in
the United States is concerning. Preventive care
spending in the United States has declined as a share
of total health expenditure from 3.7% in 2000 to
2.9% in 2018 (Kamal and Hudman 2020). This
declining investment in preventing and controlling
risk exposure is problematic because more than a
quarter of all personal health care spending in the
United States in 2016 was due to modifiable risk
factors and preventable illnesses (Bolnick et al.
2020). Qualitative research finds that while provid-
ers know that preventive services can reduce the
burden of disease, most providers, including hospi-
tals and physicians, are paid to treat rather than to
prevent disease (Levine et al. 2019). Studies find
that most Americans do not access the benefits of
preventive health care. For example, only 8% of
U.S. adults age 35 or older received all recom-
mended, high-priority, appropriate clinical preven-
tive services in 2015, and nearly 5% received none
of the routine preventive screenings (Borsky et al.
2018). The present study focuses on preventive
health care use because of concerns around the pat-
terns of preventable deaths and illnesses in the
United States, low rates of preventive health care
use, and the promise of preventive health care for
improving population health.
There are a number of factors that can affect the
use of preventive health care services. Preventive
health care use among U.S. adults is consistently
and significantly associated with the level of health
insurance coverage and having a usual place and
provider (Blewett et al. 2008; DeVoe et al. 2003;
Faulkner and Schauffler 1997). Other studies have
found that a higher purpose in life (Kim, Strecher,
and Ryff 2014) and higher life satisfaction (Kim,
Kubzansky, and Smith 2015) are also associated
with a greater likelihood of preventive health care
use. Among adolescents, a greater proportion of
those aged 16 to 17 years compared to younger age
groups did not have a usual place for preventive
care and did not receive a well-child checkup or
visit a dentist in the past 12 months (Black, Nugent,
and Vahratian 2016). There are racial and ethnic
differences in preventive health care use as well,
such as low rates of breast cancer screening among
African American women and cancer screening
among Asian Americans (Hou, Sealy, and Kabiru
2011; Jones, Katapodi, and Lockhart 2015).
Furthermore, preventive care use is also highly
gendered. Research on U.S. adults shows that
women score higher than men on a composite mea-
sure of preventive care use (Asch et al. 2006), and
men are less likely to have their blood pressure and
cholesterol checked, less likely to visit the dentist,
and less likely to get flu shots compared to women

4
Journal of Health and Social Behavior 65(1)
(Vaidya, Partha, and Karmakar 2012). Yet at the
same time, research shows that when accessing
health care, women are less likely than men to
receive the most advanced or effective treatments
and more likely to experience physician bias and
discrimination that can undermine their health
(Borkhoff et al. 2008; Chapman, Kaatz, and Carnes
2013; Greenwood, Carnahan, and Huang 2018).
Examining these patterns of gender differences is
crucial, but this approach alone provides an incom-
plete picture because it does not capture the impact
of structural factors on these outcomes. More spe-
cifically, this approach does not consider how gen-
der inequality varies across social contexts in ways
that may influence the uptake and receipt of health
care services and the effect on health of both men
and women (Homan 2019; Schofield 2015). A
structural sexism approach shifts the focus from
comparisons between men and women to within-
gender comparisons across social contexts charac-
terized by varying levels of systematic gender
inequality (i.e., structural sexism). This approach
illuminates how the unequal gendered distribution
of valued resources and opportunities in a society
may shape the health of all its members.
Structural Sexism, Health, and Health Care
A nascent body of research has linked structural
sexism in U.S. state-level institutions to a variety of
negative health outcomes, including worse self-
rated health, more chronic conditions, and worse
physical functioning among both men and women;
higher mortality risk among men; more depressive
symptoms, higher risk of disordered eating, and
more unnecessary c-sections among women; and
higher infant mortality rates (Beccia et al. 2022;
Chen et al. 2005; Homan 2019; Kavanagh et al.
2017, 2018; Kawachi et al. 1999; Nagle and Samari
2021). While this growing evidence sheds light on
the associations between structural sexism and pop-
ulation health outcomes, the role of health care
remains poorly understood. Only one study has
examined U.S. state-level structural sexism and
health care access among men and women, and it
found that higher structural sexism is associated
with more barriers to health care access for women
but not men (Rapp et al. 2022). To our knowledge,
no study has focused on understanding structural
sexism as a determinant of preventive health care
use in the United States.
Nevertheless, Rapp et al.’s (2022) study and
prominent theories of gender and health point to a
number of ways for structural sexism to impact
preventive health care use, perhaps differentially for
women and men. Particularly relevant are gender
performance and gendered power and resource allo-
cation perspectives (Courtenay 2000; Kavanagh and
Graham 2019), which generate hypotheses regard-
ing the patterns of association between structural
sexism and preventive health care use among
women and men. A gender performance perspective
suggests that structural sexism fosters hegemonic
gender norms that men and women enact through
the performance of health-related behaviors, includ-
ing preventive health care use. A gendered power
and resource allocation perspective argues that
structural sexism disempowers women, which sets
in motion social, political, and economic processes
that limit the health-promoting resources available
to everyone (e.g., health care and social program
spending). Figure 1 illustrates the patterns of associ-
ation predicted by the two theoretical perspectives,
which we discuss in detail in the following.
Structural sexism and gender performance.  A gen-
der performance perspective links structural sexism
to preventive health care use through its connection
to gender relations and norms that shape men’s and
women’s behavior. From this perspective, gender is
an interactive accomplishment, something people do
in everyday life rather than who or what people are
(West and Zimmerman 1987). Individuals “do gen-
der” when they orient their behavior toward widely
accepted norms of masculinity and femininity (West
and Zimmerman 1987). Moreover, gender relations
manifest at macro levels such as in the economy and
the state (Connell 2012). For instance, institutions
such as transnational corporations can maintain gen-
dered division of labor in the workplace. Therefore,
a sexist environment at macro levels can shape pro-
cesses, even if indirectly, that reinforce doing gender
at meso and micro levels. Additionally, research and
theory suggest that the subordination of women in
patriarchal societies is linked to stronger dominance
hierarchies among men, resulting in increased com-
petition and amplifying the importance of conform-
ing to hegemonic masculine norms (Connell 1987,
2012; Wilkinson 2005).
Masculinities and health theory argues that men
demonstrate their conformity to hegemonic mascu-
line ideals of strength, bravery, stoicism, self-
reliance, control, dominance, and sexual prowess/
virility through risk-taking and unhealthy behaviors
in order to preserve their status and patriarchal priv-
ilege (Cheng 1999; Connell 1987, 2005, 2012;
Connell and Messerschmidt 2005; Gray et al. 2002;
Kavanagh and Graham 2019; Mahalik, Burns, and

Dore et al.
5
Syzdek 2007). Indeed, studies have shown that
adherence to these masculine norms is linked to
greater substance use, violence, sexual risk behav-
iors, health care avoidance, and a variety of other
negative health-related beliefs and behaviors
(Courtenay 2000; Fleming and Agnew-Brune 2015;
Mahalik et al. 2007; Seidler et al. 2016). In terms of
preventive care, there is evidence that masculinity
norms (particularly avoidance of femininity, risk-
taking, and self-reliance) are inversely associated
with colorectal cancer screening (Christy, Mosher,
and Rawl 2014).
Norms of femininity are largely framed in oppo-
sition to masculinity. Emphasized femininity is the
complement to hegemonic masculinity and involves
orienting one’s behavior toward the interests and
desires of men (Connell 1987). Such femininity typ-
ically entails gentleness, nurturing, passivity, beauty,
youth, fragility, and a domestic/family orientation.
While there is much less research on femininity and
health, positive health beliefs and behaviors, includ-
ing health care use, are typically considered
feminine-typed behavior (Courtenay 2000; Fleming
and Agnew-Brune 2015). Additionally, the feminine
ideals of youth, beauty, and nurturing may lead to
increased contact with health care providers to
obtain services for women themselves and their
children (Daly and Groes 2017). In sum, to the
extent that structural sexism increases pressure to
conform to the hegemonic ideals of masculinity and
emphasized femininity (Connell 1987, 2012), we
would expect greater structural sexism to be associ-
ated with higher levels of preventive health care use
among women and lower levels among men (see
Figure 1a).
Structural sexism and gendered power and resource
allocation.  A gendered power perspective links struc-
tural sexism to preventive health care use through the
impact of women’s (dis)empowerment on social,
political, and economic processes that allocate
resources relevant for population health. At the state
level, more liberal policies expand economic regula-
tions, protect marginalized groups, and are associated
with longer life expectancies (Montez et al. 2020).
Such policies are more likely to support women and
be supported by women in power (Kavanagh and
Graham 2019). Evidence from around the world also
show that when women are empowered socially and
politically, there are greater investments in education,
health care, public health, and other social programs
that tend to improve health for the entire population
(Boehmer and Williamson 1996; Bolzendahl and
Brooks 2007; Little, Dunn, and Deen 2001; Miller
2008; Young 2001). Differences in state-level poli-
cies can also affect health care use through barriers to
accessing services, such as lack of insurance options
like expansion of Medicaid, unavailability of flexible
appointments, inadequate transportation, and poor
social support for childcare, among other factors
(National Academies of Sciences, Engineering, and
Medicine 2018). This leads to the hypothesis that
states with higher levels of structural sexism may
offer less generous safety-net policies and allocate
fewer resources to health care, leading to lower levels
of preventive health care use among both men and
women, as illustrated in Figure 1b. This pattern
would be consistent with the findings of Homan
(2019) that state-level structural sexism exposure
was universally harmful for health, negatively
impacting outcomes for both men and women.
Figure 1.  Potential Relationships between Structural Sexism and Preventive Care Use Based on
Gender Theories.

6
Journal of Health and Social Behavior 65(1)
Because structural sexism involves material and
social advantages for men, it is also theoretically
possible that men could leverage their greater per-
sonal resources to achieve good health even in the
absence of health-promoting collective conditions,
and we might thereby observe a positive associa-
tion between greater sexism and preventive care
among men. However, this is unlikely based on
masculinity and health research and previous find-
ings on structural sexism and men’s health that
have found harmful effects of state-level structural
sexism on men’s health (Homan 2019; Kavanagh
et al. 2018). Thus far, no empirical studies have
identified a health benefit of state-level sexism
exposure for men. For this reason, we do not picture
or further explicate this additional possible but
unlikely scenario.
The Present Study
In this study, we examine the association between
state-level structural sexism and preventive health
care use among men and women in the United States.
We construct a measure of structural sexism based on
Homan (2019) and estimate gender-stratified multi-
level models that capture state-level context and
individual-level demographics. We ask: (1) Is struc-
tural sexism associated with preventive health care
use among women and men? and (2) If so, are the
patterns more consistent with theories of gender
norms and health behaviors or gendered power and
resource allocation? It is important to note that both
theoretical perspectives predict a negative relation-
ship between structural sexism and preventive care
use for men. Therefore, we can only confirm/deny
that one or both of these theories applies to this case.
But the theoretical perspectives generate conflicting
hypotheses regarding the direction of the relationship
among women, and we can therefore determine
which is most supported by the evidence.
Data And Methods
We build on previous work on structural sexism
(Homan 2019; Homan and Burdette 2021) and
examine the relationship between individual-level
health data with a measure of structural sexism at
the state level and other relevant state-level and
individual-level covariates. For individual-level
data, we used the BRFSS from 2018 (Centers for
Disease Control and Prevention, 2018). For state-
level environments, we included controls from the
U.S. Census Bureau and a measure of structural sex-
ism constructed from various administrative
sources, including the U.S. Census Bureau, the
Bureau of Labor Statistics, the Center for American
Women and Politics, and Guttmacher Institute. We
linked these state-level measures and individual-
level data from BRFSS to examine the association
between structural sexism and gendered use of pre-
ventive health care.
Sample
The sample was composed of men and women from
the BRFSS national survey in 2018. BRFSS is the
largest continuously conducted health survey in the
world and collects annual, cross-sectional data from
respondents in all 50 states about health behaviors
and conditions and demographics. Some questions
vary each year, thus we used 2018 data because it
was the most recent year that had the most applica-
ble and complete data on preventive health care use.
It was also important to avoid 2020 data due to the
impact of COVID-19 on health care use. Our ana-
lytic sample consisted of 425,454 individuals, of
which 192,854 were men and 232,600 were women.
The sample sizes varied for each preventive health
care service outcome, depending on how many indi-
viduals responded to each of the questions.
Dependent Variables
Our analysis involved several dependent variables
that measured the use of preventive health care from
BRFSS. Several of these BRFSS variables have dif-
ferent versions that factor age of respondent and fre-
quency of use of the service. For these measures, we
analyzed the versions that included the largest sample
sizes to provide the most complete picture of gen-
dered patterns of health care use. For example, there
were two versions of the question about mammo-
grams: (1) women who have ever had a mammogram
and (2) women age 40+ who have had a mammo-
gram in the past 2 years. We used the former measure
because the 2018 mammogram recommendations
vary for women 40 years and older, and therefore, the
latter measure may miss important variation by limit-
ing the time period. Most health care services apply
to both men and women; however, there were three
that were asked only of women and one that was
asked only of men (described in the following).
All respondents were asked about a variety of
health care services. These included dichotomous
measures of whether respondents had a person they
thought of as their personal doctor, if they had ever
had a colonoscopy/sigmoidoscopy or been tested
for human immunodeficiency virus (HIV), and

Dore et al.
7
whether within the past year they had visited a doc-
tor for a routine checkup, gotten a flu shot, or vis-
ited a dentist, dental hygienist, or dental clinic. For
women, they were also asked if they had ever had a
mammogram, pap test, or human papillomavirus
(HPV) test. For men, they asked if they had ever
had a prostate-specific antigen (PSA) test. All vari-
ables were coded 0/1 so that 1 indicated the partici-
pant had used the health care service within the
specified timeframe.
Independent Variables
We constructed a state-level measure of structural
sexism based on Homan (2019) from a variety of data
sources. The sexism measure is a composite score of
political, economic, cultural, and physical/reproduc-
tive factors. We used data that were as chronically
close to 2018 to be relevant to the individual BRFSS
data, depending on data availability for each source.
For the political measure, we calculated percentage
of state legislature seats occupied by men in 2018
using data from the Center for American Women and
Politics (2023). For the cultural measure, we included
the percentage of state population composed of reli-
gious conservatives (evangelical Protestant or Latter-
Day Saints) from Pew Research in 2014 (Pew
Research Center 2014). This is an important indicator
of structural sexism because conservative religious
institutions endorse gender essentialist beliefs and
restrict women to subordinate roles in the church, the
family, and society at large (Barr 2021; Chaves and
Eagle 2015; Council on Biblical Manhood and
Womanhood [CBMW] 2023; Homan 2019). The
prevalence of religious conservatives in a state is
associated with traditional/patriarchal gender norms
net of individual attitudes (Moore and Vanneman
2003). For economic measures, we calculated a ratio
of men’s to women’s labor force participation rates,
ages 16+, a ratio of men’s to women’s poverty rate
from IPUMS USA (Ruggles et al. 2022), and a ratio
of men’s to women’s median usual weekly earnings
of full-time wage and salary workers in 2018 (U.S.
Bureau of Labor Statistics 2019). We then standard-
ized and summed all variables to create a structural
sexism index (α = .79) and standardized the final
structural sexism index for an easier interpretation of
results. A higher value on the structural sexism index
indicates more structural sexism.
Additional Covariates
At the individual level, we controlled for a range of
characteristics known to be associated with health
care use. These included continuous measures of
age and income, parental status (has at least one
child under 18 in the house or no children under 18
in the house), marital status (married or a member of
an unmarried couple or not married/in a couple),
and categorical measures of education (less than
high school, high school graduate, some college,
and bachelor degree), and race (White, Black,
American Indian or Alaskan Native, Asian, Native
Hawaiian or Pacific Islander, other race, multiracial,
and Hispanic). We also controlled for a categorical
variable of self-rated health (poor, fair, good, very
good, and excellent) given that individuals in worse
health may be more likely to seek health care ser-
vices. Finally, we controlled for insurance status to
isolate the effect of structural sexism on preventive
health care use given that Rapp et al. (2022) showed
that higher state-level sexism is associated with
being uninsured for both men and women.
Because we are examining the associations
between individual health care behaviors with
state-level sexism contexts, we also controlled for
other relevant state-level measures. These included
racial composition (% non-White) and poverty rate
in 2018 from IPUMS USA (Ruggles et al. 2022),
the state Gini coefficient (Frank 2021), and if the
state is in the South based on U.S. census defini-
tions (U.S. Census Bureau 2017).
Analytic Strategy
First, we calculated descriptive statistics for the state-
level measures and individual-level measures. For the
individual-level descriptive statistics, we stratified by
gender and estimated t tests for continuous variables,
test of proportion for dichotomous variables, and chi-
square tests for categorical variables to understand
statistical differences between men and women. Then,
we stratified the sample by gender and ran several
multilevel logit models, with individuals nested
within states, for each health care service. These mod-
els predicted the use of each preventive health care
service as a function of state-level structural sexism
exposure. Each model included all previously men-
tioned state-level and individual-level covariates. We
retained the largest sample size for each outcome,
which means that the sample size varies depending on
how many individuals responded to each question.
The sample sizes range from 115,012 to 182,582 for
women and 95,317 to 159,469 for men.
Supplemental analyses.  We ran several supple-
mental analyses to check the robustness of our find-
ings to different specifications. First, we replicated

8
Journal of Health and Social Behavior 65(1)
the main analyses but included a control for if the
state had expanded Medicaid by 2018 (Kaiser Fam-
ily Foundation 2023). Medicaid expansion increased
access to health insurance, and health insurance
facilitates access to care, thus it is possible this state-
level policy would affect use of preventive care.
However, a gendered power and resource allocation
perspective suggests that Medicaid expansion deci-
sions are a consequence of structural sexism (i.e.,
lower structural sexism leads to greater investment
in social and health policy that improves population
health), and indeed, some studies have used Medic-
aid expansion as an indicator of structural sexism
(Rapp et al. 2022). Therefore, controlling for Med-
icaid expansion risks underestimating the impact of
structural sexism on preventive care to the extent
that it functions as a mechanism. Thus, we chose to
include this measure in supplemental models (see
Appendix Tables 1 and 2 in the online version of the
article) rather than the main analyses. For the sec-
ond supplemental analysis (see Appendix Tables 3
and 4 in the online version of the article), we
removed self-rated health as a covariate from the
main model. We used self-rated health as a measure
of general health, which is likely to be associated
with health care use in general because individuals
who are sick are more likely to receive care than
individuals who are not sick. We chose to include
this control in our main analyses to remove the
impact of health status on preventive care use, but
we did not include it for a supplemental analysis to
understand if it affects the relationship between
structural sexism and preventive health care use.
The third supplemental analysis was a modifica-
tion to the measure of structural sexism. One recent
study suggested the removal of religious conserva-
tism as an indicator of structural sexism (McKetta
et al. 2022); therefore, we estimated models with this
item left out of the sexism index (see Appendix
Tables 5 and 6 in the online version of the article).
Results were substantively similar, and we chose to
retain the religious conservatism item in our main
analysis because theory and previous research high-
light the important role of conservative religious insti-
tutions as a foundational element of sexist oppression
in the United States (Barr 2021; CBMW 2023;
Chaves and Eagle 2015; Homan 2019; Homan and
Burdette 2021; Moore and Vanneman 2003). Fourth,
we replicated our analyses with samples limited to
only ages recommended by the U.S. Preventive
Services Task Force for the applicable preventive
care services (see Appendix Tables 7 and 8 in the
online version of the article). Because the screening
and testing services, such as mammography and HPV
tests, are generally recommended only for specific
ages, individuals within these age ranges may be
more likely to get the services regardless of structural
sexism. However, we included all ages in the main
analyses because recommendations may vary by
characteristics other than age, such as family history.
Finally, we tested an interaction between gender and
structural sexism for the full sample to understand
whether the effect of structural sexism differs by gen-
der (see Appendix Table 9 in the online version of the
article). Results remained largely consistent across all
these supplemental models, indicating that our key
findings and conclusions are robust to a variety of
alternative specifications. See the Appendix in the
online version of the article for further details.
Results
Descriptive statistics are shown in Table 1 for state-
level measures and Table 2 for individual-level
measures. Earnings ratio, labor force ratio, and pov-
erty ratio all have means that are above 1, indicating
gender inequality that favors men. Proportion of
men in state legislature is 74%, signaling that men
consistently outnumber women in local govern-
ment, and proportion of women without abortion
access is almost 50%, again showing women in a
disadvantaged position, this time regarding repro-
ductive health care access.
Individual-level descriptive statistics show that
women are more likely to receive preventive health
care services compared to men and that the differ-
ences are statistically significant. For example,
83.8% of women had seen a doctor in the past year
compared to 76.3% of men. Similarly, 87.6% of
women have a person they consider a personal doc-
tor compared to 78.0% of men. These were the two
most highly endorsed measures, while the health
care services least likely to be used were getting a
flu shot in the past year (36.7% of men and 41.8%
of women) and ever having tested for HIV (33.0%
of men and 33.5% of women). Women were
slightly older on average (56.2 years compared to
53.5 years), were less likely to be married (52.0%
compared to 59.0%), were more likely to be parents
(36.9% compared to 25.3%), and had lower
incomes ($50,382 on average compared to
$56,439). The remainder of individual descriptive
statistics were statistically different although per-
haps not meaningfully different, including the
racial breakdown, self-rated health, and education.
The results for the gender-stratified multilevel
models that predict use of preventive health care
services conditional on exposure to structural

Dore et al.
9
sexism are in Table 3 for women and Table 4 for
men. Figure 2 visualizes the results for both men
and women in a forest plot with a darker color rep-
resenting significant results. Overall, we found that
both women and men were less likely to use pre-
ventive services in states with more structural sex-
ism. Women were less likely to have had a
colonoscopy or sigmoidoscopy (OR = .94, p =
.018), to have tested for HIV (OR = .82, p < .001),
and to have had a mammogram (OR = .95, p =
.009), a pap test (OR = .94, p = .011), and an HPV
test (OR = .87, p < .001) in states with more struc-
tural sexism compared to women in states with less
structural sexism. Men were similar in that they
were less likely to have a personal doctor (OR =
.91, p = .031), to have had a colonoscopy or sig-
moidoscopy (OR = .93, p = .006), and to have
tested for HIV (OR = .85, p < .001) in states with
more structural sexism compared to men in states
with less structural sexism. However, men also
were more likely to have had a PSA test in states
with more structural sexism (OR = 1.06, p = .003),
which was the only service positively associated
with structural sexism.
The coefficients can be interpreted as the ORs
for using a particular service associated with a 1
standard deviation increase in the structural sexism
index. For example, a 1 standard deviation increase
in the structural sexism index is associated with a
.87 OR of women getting tested for HPV, which
translates to 13% lower odds. To further aid in the
interpretation of these results, we used our model to
calculate the predicted probabilities of HPV testing
among women across the range of sexism
exposures observed in our sample: A woman
exposed to the lowest observed level of sexism has
a .51 predicted probability of testing for HPV, while
a woman exposed to the highest level of sexism has
only a .38 predicted probability of testing for HPV.
Discussion
This study measures the association between state-
level exposure to structural sexism on gendered use
of preventive health care. We build on the growing
literature examining the relationship between struc-
tural sexism and health (Homan 2019; McKetta
et al. 2022; Rapp et al. 2022; Rapp, Volpe, and
Neukrug 2021). Preventive health care use is an
important outcome to study in this context due to its
relevance to population health outcomes and the
gendered patterns of use (USDHHS 2022). Most
studies focus on individual-level factors in deter-
mining health care use despite the growing empha-
sis on upstream structural determinants in the health
disparities literature (Braveman and Gottlieb 2014;
Homan and Brown 2022; Montez 2017; Montez,
Hayward, and Zajacova 2021). Our research ques-
tions were: (1) Is structural sexism associated with
preventive health care use among women and men?
and (2) If so, are the patterns more consistent with
theories of gender norms and health behaviors or
gendered power and resource allocation? We had
two hypotheses based on two different perspectives.
First, based on the gender performance perspective,
we hypothesized that in states with more structural
sexism, men would be less likely to use preventive
health care and women would be more likely to use
Table 1.  State-Level Data and Descriptive Statistics (N = 50).
Measure
Data Source
Mean (SD)
Range
Structural Sexism Index
.00 (1)
[−1.71, 2.84]
  Earnings ratio (M:W)
Bureau of Labor Statistics
1.25 (.07)
[1.13, 1.47]
  Labor force ratio (M:W)
IPUMS American Community Survey
1.15 (.03)
[1.08, 1.26]
  Poverty ratio (W:M)
IPUMS American Community Survey
1.05 (.06)
[.89, 1.22]
  Proportion men in state
legislature
Center for American Women in
Politics
.74 (.08)
[.60, .89]
  Proportion women without
abortion access
Guttmacher Institute
.47 (.26)
[.03, .96]
Percentage religious conservatives
PEW Research Center
.29 (.12)
[.10, .62]
Racial composition
U.S. Census Bureau
.21 (.12)
[.05, .74]
Poverty rate
U.S. Census Bureau
.12 (.03)
[.07, .20]
Gini coefficient
Frank (2021)
.61 (.03)
[.55, .70]
Southern region
U.S. Census Bureau
16 states
Note: W:M = women-to-men; M:W = men-to-women.

10
Journal of Health and Social Behavior 65(1)
preventive health care compared to their same-
gender counterparts in states with less sexism.
Second, based on the gendered power and resource
allocation perspective, we argued that in states with
more structural sexism, there would be less funding,
education, and infrastructure for health care such
that both men and women would be less likely to
use preventive health care compared to their coun-
terparts in states with less sexism.
Overall, our results indicate a strong negative
relationship between exposure to structural sexism
at the state level and the use of preventive health
Table 2.  Descriptive Statistics, Behavioral Risk Factor Surveillance System, 2018, N = 425,454.
Men
Women
Gender Difference

(n = 192,854)
(n = 232,600)
p Value
Preventive care use
  Visited a doctor in past year
76.3%
83.8%
.001
  Have a personal doctor
78.0%
87.6%
.001
  Flu shot within past year
36.7%
41.8%
.001
  Sigmoidoscopy or colonoscopy within
past year
73.0%
75.6%
.001
  Ever tested for HIV
33.0%
33.5%
.006
  Visited dentist in past year
65.5%
70.6%
.001
  Ever had a mammogram
—
79.2%
—
  Ever had a pap test
—
94.1%
—
  Women who ever had HPV test
—
43.2%
—
  Ever had a PSA test
51.7%
—
—
Individual-level controls
  Age
53.5 (17.6)
56.2 (17.2)
.001
  Race
.001
    White
77.1%
77.3%

    Black
7.1%
9.0%

    American Indian or Alaskan Native
1.8%
1.8%

    Asian
2.6%
1.9%

    Native Hawaiian or Pacific Islander
.4%
.3%

    Other race
.9%
.6%

    Multiracial
2.1%
1.9%

    Hispanic
8.0%
7.2%

  Married/in a couple
59.0%
52.0%
.001
  Income
56,439 (28,658)
50,382 (29,123)
.001
  Insurance
90.3%
93.1%
.001
  Parent
25.3%
36.9%
.001
  Education
.001
    Less than high school
7.8%
7.0%

    High school degree
28.2%
26.8%

    Some college
26.1%
29.0%

    Bachelor degree
37.9%
37.2%

  Self-rated health
.001
    Excellent
16.8%
16.1%

    Very good
32.5%
33.1%

    Good
32.2%
31.3%

    Fair
13.4%
14.0%

    Poor
5.1%
5.5%

Note: Descriptive statistics use data from the Behavioral Risk Factor Surveillance System and other sources listed in
Table 1. HIV = human immunodeficiency virus; HPV = human papillomavirus; PSA = prostate-specific antigen.

11
Table 3.  Associations between Structural Sexism and Preventive Health Care Use among Women, Odds Ratios.
Visited a
Doctor in Past
Year
Has a
Personal
Doctor
Flu Shot
in Past Year
Ever Had a
Sigmoidoscopy
or
Colonoscopy
Ever
Tested
for HIV
Visited
Dentist in
Past Year
Ever Had a
Mammogram
Ever Had
a Pap Test
Ever Had
HPV Test
Structural sexism
.99
.92
1.03
.94*
.82***
1.02
.95**
.94*
.87***
Age
1.03***
1.04***
1.03***
1.05***
.96***
1.01***
1.14***
1.05***
.96***
Race (reference: White)
  Black
2.06***
1.15***
.81***
1.27***
2.49***
.97
1.52***
.96
1.38***
  AIAN
1.31***
.54***
.99
.76***
1.75***
1.08
1.22**
.72***
1.45***
  Asian
1.14**
.78***
1.37***
.66***
.43***
.98
.79***
.17***
.38***
  NHPI
1.17
.76*
.94
.60***
.73**
.80*
1.30*
.47***
.78*
  Other race
.93
.77**
.85*
.85
1.46***
.97
1.07
.51***
1.19*
  Multiracial
1.05
.89*
.89**
.97
1.65***
.79***
1.04
1.01
1.30***
  Hispanic
1.40***
.80***
1.13***
.93
1.07**
1.32***
1.33***
.73***
1.00
Education (reference: < HS)
  HS degree
1.03
1.28***
.87***
1.27***
.92**
1.37***
1.18***
1.28***
1.03
  Some college
1.01
1.38***
.96
1.56***
1.37***
1.63***
1.25***
1.94***
1.35***
  College degree
.99
1.36***
1.28***
1.84***
1.57***
2.34***
1.23***
3.47***
1.62***
Married/in a couple
.98
1.11***
.95***
1.20***
.81***
1.02
1.10***
2.43***
1.06***
Income
1.00***
1.00***
1.00***
1.00***
1.00
1.00***
1.00***
1.00***
1.00***
Insurance
3.67***
4.39***
2.21***
2.42***
.98
1.94***
1.36***
1.11**
1.16***
Parent
.90***
1.12***
1.01
.67***
1.73***
.93***
.85***
2.42***
1.69***
Self-rated health
.84***
.85***
.95***
.89***
.82***
1.28***
.92***
.94***
.97***
Intercept
.67
1.02
.24**
.10***
1.08
.16***
.004***
1.07
4.83***
Level 2 variance (SE)
.04***
(.01)
.08***
(.02)
.03***
(.01)
.02***
(.01)
.04***
(.01)
.01***
(.002)
.01***
(.003)
.02***
(.01)
.02***
(.01)
n
181,713
182,582
178,178
115,012
168,197
182,082
176,741
176,040
131,406
Note: All models control for state-level measures of poverty rate, Gini coefficient, racial composition, and southern region. Models use data from the Behavioral Risk Factor
Surveillance System and other sources listed in Table 1. The sample sizes range from 115,012 to 182,582 observations depending on the outcome. HIV = human immunodeficiency
virus; HPV = human papillomavirus; AIAN = American Indians and Alaska Natives; NHPI = Native Hawaiian and Pacific Islander; HS = high school.
*p < .05. **p < .01. ***p < .001.

12
Table 4.  Associations between Structural Sexism and Preventive Health Care Use among Men, Odds Ratios.
Visited a Doctor
in Past Year
Has a Personal
Doctor
Flu Shot in Past
Year
Ever had a
Sigmoidoscopy
or Colonoscopy
Ever Tested for
HIV
Visited Dentist in
Past Year
Ever Had a PSA
Test
Structural sexism
.98
.91*
1.02
.93**
.85***
1.00
1.06**
Age
1.04***
1.05***
1.03***
1.06***
.98***
1.01***
1.09***
Race (reference: White)
  Black
1.79***
1.07*
.90***
1.15***
3.02***
.94**
1.45***
  AIAN
1.26***
.79***
1.00
.71***
1.75***
.99
.76***
  Asian
1.32***
1.05
1.40***
.58***
.51***
.82***
.51***
  NHPI
1.33**
1.21
1.08
.71*
.84
.80*
.59***
  Other race
.93
.72***
.80**
.76**
1.67***
.89
.82*
  Multiracial
1.06
.93
1.02
.94
1.58***
.79***
.83**
  Hispanic
1.25***
.79***
1.12***
.86***
1.23***
1.28***
.99
Education (reference: < HS)
  HS degree
1.15***
1.29***
.99
1.36***
1.07*
1.39***
1.46***
  Some college
1.22***
1.46***
1.16***
1.78***
1.38***
1.67***
1.92***
  College degree
1.20***
1.58***
1.69***
2.22***
1.49***
2.43***
2.43***
Married/in a couple
1.07***
1.20***
1.12***
1.40***
.75***
1.19***
1.27***
Income
1.00***
1.00***
1.00***
1.00***
1.00
1.00***
1.00***
Insurance
3.66***
4.27***
2.58***
2.75***
1.07**
2.03***
1.82***
Parent
.87***
.97*
.94***
.67***
1.29***
.90***
.61***
Self-rated health
.83***
.88***
.92***
.91***
.89***
1.21***
1.01
Intercept
.18***
.16*
.09***
.02***
.44
.13***
.0005***
Level 2 variance (SE)
.03***
(.01)
.08***
(.02)
.03***
(.01)
.03***
(.01)
.03***
(.01)
.01***
(.003)
.01***
(.003)
n
158,644
159,469
155,392
95,317
146,983
159,048
110,839
Note: All models control for state-level measures of poverty rate, Gini coefficient, racial composition, and southern region. Models use data from the Behavioral Risk Factor
Surveillance System and other sources listed in Table 1. The sample sizes range from 95,317 to 159,469 observations depending on the outcome. HIV = human immunodeficiency
virus; PSA = prostate-specific antigen; AIAN = American Indians and Alaska Natives; NHPI = Native Hawaiian and Pacific Islander; HS = high school.
*p < .05. **p < .01. ***p < .001.

Dore et al.
13
care services among both men and women. These
results partially supported our hypothesis based on
a gender performance perspective because men
were less likely to use preventive health care in
states with more structural sexism, consistent with
the idea that performing masculinity entails health
care avoidance and negative health beliefs and
behaviors (Courtenay 2000). However, a gender
performance perspective was not generally sup-
ported for women, who were also less likely to use
preventive health care in states with more structural
sexism but who were hypothesized to increase
health care utilization in conjunction with perform-
ing femininity. Our results fully supported a gen-
dered power and resource allocation perspective
because both men and women were overall less
likely to use preventive health care services in
states with more sexism. This pattern would be
expected if the disempowerment of women in sex-
ist environments leads to the contraction of health-
promoting resources for everyone to access.
These findings align with much of the literature
on structural sexism and health but contribute a key
piece by examining the gendered use of preventive
health care. Most relevant to the current study,
Rapp et al. (2022) found that women in states with
more sexism face more barriers to accessing and
affording health care, while men’s access is unaf-
fected by structural sexism. Although they did not
examine preventive health care explicitly, it is pos-
sible these findings apply to preventive health care
and can help to explain our findings that women in
states with more sexism were less likely to access
preventive health care. However, they do not help
to explain our finding that men were generally also
less likely to access preventive health care in states
with more sexism. Nagle and Samari (2021) found
that birthing people living in states with more sex-
ism were more likely to have had a cesarean sec-
tion. These findings align with the results of this
study because women in states with more sexism
were not receiving care in the recommended way or
frequency. Finally, Homan (2019) found that struc-
tural sexism was associated with more chronic con-
ditions, worse self-rated health, and worse physical
functioning for women and worse physical func-
tioning for men. Our study in conjunction with
Rapp et al. (2022) and Nagle and Samari (2021)
provide evidence on negative interactions with the
health care system in sexist states, suggesting pos-
sible explanations for Homan’s (2019) findings that
women and men in sexist states have worse health.
There was one particularly interesting finding in
our study that did not fit the same pattern as the
other results. In states with more sexism, men were
more likely to get PSA tests compared to men in
states with less sexism, which was the opposite
relationship for all other forms of preventive care
among men in this study. While initially somewhat
surprising, this can also be understood from a modi-
fied gender performance perspective. From a hege-
monic masculinity viewpoint, prostate cancer
(which can be detected by PSA tests, allowing for
timely treatment) presents a unique threat to mascu-
linity because it often causes incontinence and erec-
tile dysfunction, which can be perceived as
weakness, lack of control over bodily function, and
failure to fulfill masculine ideals of sexual prowess
Figure 2.  Associations between Structural Sexism and Odds of Using Preventive Health Care Services
among Women and Men.
Note: Models use data from the Behavioral Risk Factor Surveillance System and other sources listed in Table 1. The
sample sizes range from 115,012 to 182,582 for women and 95,317 to 159,469 for men.

14
Journal of Health and Social Behavior 65(1)
(Gray et al. 2002). Thus, while it may be generally
considered unmasculine to seek out health care
(especially preventive care that is not an urgent
necessity), men may make exceptions for care that
sustains sexual function. Indeed, a qualitative study
of men’s constructions of masculinity and their
help-seeking behavior in Scotland found that while
there was widespread agreement with the hege-
monic view that real men should not need help or
consult with physicians for “minor” symptoms or
pain, men were much more in favor of help-seeking
when it was used as a means to preserve other
enactments of masculinity that they valued, espe-
cially their physical strength and sexual perfor-
mance (O’Brien, Hunt, and Hart 2005). Thus, to the
extent that exposure to high levels of structural sex-
ism exerts increased pressure to conform to hege-
monic norms of masculinity, men in these
environments must navigate competing demands of
masculine invincibility and self-reliance that
encourage health care avoidance versus the mascu-
line imperative to preserve the functioning of the
penis—itself the very symbol of manhood, power,
and sexuality (Cheng 1999; Gray et al. 2002; Potts
2000). In sum, our findings suggest that while
higher structural sexism exposure decreases men’s
use of preventive care services in general (either
through performing masculinity, decreased health
care resources and accessibility, or both), it may
increase the demand for preventive health care
directly affecting men’s sexual performance, which
functions as a central element of their identity as
men. Future research should investigate the associ-
ations between structural sexism and other sexual
and urological services and outcomes to further
explore this issue.
Limitations and Future Research
This research makes an important contribution to
the literature on structural factors that shape health
care use and, therefore, health outcomes. However,
there are limitations to this research worth noting.
First, we use cross-sectional data from a single year
and can therefore not claim a causal relationship.
Second, we do not explicitly test mechanisms, so
the pathways through which structural sexism may
shape preventive care remain unclear. Rapp et al.
(2022) provides evidence that states with more sex-
ism bar women from accessing health care gener-
ally, but determining the specific factors and barriers
affecting women’s and men’s preventive health care
use in particular requires further research. We sug-
gest that future researchers further investigate gen-
der performance perspectives by combining
structural sexism measures with individual-level
data on gender norms/beliefs and health care use
and examining the role of cultural sexism (i.e.,
contextual-level gender norms/ideology; see Price
et al. 2021). Additionally, researchers can further
investigate gendered power and resources alloca-
tion perspective by examining the relationships
between structural sexism and specific social poli-
cies (e.g., welfare spending, unemployment insur-
ance, Medicaid expansion, education spending,
health care spending, parental leave, etc.) that redis-
tribute resources in ways that improve population
health and may therefore act as mechanisms
between structural sexism and preventive health
care use. Third, our measures of preventive health
care are self-reported and may be subject to recall
bias, and we also only include the available mea-
sures of preventive health care in BRFSS. The mea-
sures are also dichotomous, which may miss more
nuanced responses. Thus, investigating the associa-
tions between structural sexism and a variety of
other measures of health care service use and health
behaviors is an important area for future research.
Fourth, we captured several important aspects
of structural sexism and other state-level and
individual-level covariates that may impact preven-
tive health care use, but our measure of structural
sexism is not exhaustive. Future research should
develop additional measures of structural sexism
and examine the strengths and limitations of differ-
ent measurement approaches. Fifth, there are a vari-
ety of other state-level social, economic, and
political characteristics not included in our models
that may be relevant for preventive care and may or
may not be related to structural sexism. While these
factors could potentially confound the relationship
between sexism and health or health care, it is also
possible that they serve as important mechanisms.
Thus, careful examination of the complex relation-
ships between structural sexism and various fea-
tures of state contexts is an important area for future
research.
Sixth, we have focused specifically on the role
of structural sexism in shaping preventive care
given recent evidence of its associations with
health, but it does not operate in isolation. Homan,
Brown, and King (2021) provide a theoretical
framework to examine health and health care out-
comes through a structural intersectional lens.
Because gendered expectations can be both classed
and racialized, future research should investigate
use of preventive health care at the intersection of
multiple oppressive systems. This will involve
measuring multiple forms of structural oppression
(e.g., structural sexism and structural racism) and

Dore et al.
15
examining their individual and joint effects on
health care use among individuals with varied inter-
sectional identity categories (e.g., Black women
with a college degree vs. White men without a high
school diploma). Research on structural sexism has
thus far used data with predominantly White sam-
ples, suggesting an intersectional approach is cru-
cial for providing further theoretical insight.
It is also important to consider the role of sexu-
ality in affecting men’s health-seeking behavior.
Studies find that gay men are likelier to get PSA
testing than their heterosexual counterparts (Ma
et al. 2021; Wilcox Vanden Berg et al. 2022).
However, whether exposure to higher structural
sexism may or may not affect greater PSA testing
among gay men warrants further study. Finally, our
sample is limited by data constraints in the BRFSS
such that we can only study the associations
between structural sexism and preventive health
care among cisgender men and women. It is essen-
tial that future research investigate the impact of
structural sexism among transgender and nonbinary
people and develop new measures of structural sex-
gender-sexuality-based oppression such as cishet-
eropartiarchy and gender binarism (Everett et al.
2022; Krieger 2020).
Conclusion
Structural sexism is an important determinant of
preventive health care use for both men and women.
These findings suggest a few possible explanations
related to the gender performance and gendered
power and resource allocation perspectives. Specific
to men, structural sexism may exacerbate gender
norms that disincentivize them from using care to
avoid appearing vulnerable. For both men and
women, a lack of resources and state-level supports
may prevent them from receiving preventive health
care services. This work contributes to a growing
body of research on the universal harm of structural
sexism and the urgency of dismantling oppressive
gender systems to improve population health.
Funding
The authors disclosed receipt of the following financial
support for the research, authorship, and/or publication of
this article: Research reported in this publication was sup-
ported by the National Institute on Minority Health and
Health Disparities of the National Institutes of Health
under Award No. F31MD017935, and the Network on
Life Course Health Dynamics and Disparities in 21st
Century America (Award No. 2 R24 AG 045061-06) from
the National Institutes on Aging. The content is solely the
responsibility of the authors and does not necessarily
represent the official views of the National Institutes of
Health.
ORCID iDs
Emily C. Dore
 https://orcid.org/0000-0002-0899-0200
Patricia Homan
 https://orcid.org/0000-0003-3609-8188
SUPPLEMENTAL MATERIAL
Appendices Table 1 through 9 and Figures 1 through 5 are
available in the online version of the article.
References
Asch, Steven M., Eve A. Kerr, Joan Keesey, John L.
Adams, Claude M. Setodji, Shaista Malik, and
Elizabeth A. McGlynn. 2006. “Who Is at Greatest
Risk for Receiving Poor-Quality Health Care?” New
England Journal of Medicine 354(11):1147–56.
doi:10.1056/nejmsa044464.
Barr, Beth Allison. 2021. The Making of Biblical
Womanhood: How the Subjugation of Women Became
Gospel Truth. Grand Rapids, MI: Brazos Press.
Beccia, Ariel L., S. Bryn Austin, Jonggyu Baek,
Madina Agénor, Sarah Forrester, Eric Y. Ding,
William M. Jesdale, and Kate L. Lapane. 2022.
“Cumulative Exposure to State-Level Structural
Sexism and Risk of Disordered Eating: Results
from a 20-Year Prospective Cohort Study.” Social
Science & Medicine 301:114956. doi:10.1016/j.socs-
cimed.2022.114956.
Black, Lindsey I., Colleen N. Nugent, and Anjel
Vahratian. 2016. “Access and Utilization of Selected
Preventive Health Services among Adolescents Aged
10–17.” NCHS Data Brief No. 246. Hyattsville, MD:
National Center for Health Statistics.
Blewett, Lynn A., Pamela Jo Johnson, Brian Lee, and Peter
B. Scal. 2008. “When a Usual Source of Care and
Usual Provider Matter: Adult Prevention and Screening
Services.” Journal of General Internal Medicine
23(9):1354–60. doi:10.1007/S11606-008-0659-0.
Boehmer, Ulrike, and John B. Williamson. 1996. “The
Impact of Women’s Status on Infant Mortality
Rate: A Cross-National Analysis.” Social Indicators
Research 37(3):333–60.
Bolnick, Howard J., Anthony L. Bui, Anne Bulchis,
Carina Chen, Abigail Chapin, Liya Lomsadze, Ali H.
Mokdad, Francois Millard, and Joseph L. Dieleman.
2020.
“Health-Care
Spending
Attributable
to
Modifiable Risk Factors in the U.S.A.: An Economic
Attribution Analysis.” The Lancet Public Health
5(10):e525–35. doi:10.1016/S2468-2667(20)30203-6.
Bolzendahl, Catherine, and Clem Brooks. 2007.
“Women’s Political Representation and Welfare
State Spending in 12 Capitalist Democracies.” Social
Forces 85(4):1509–34. doi:10.1353/sof.2007.0061.
Borkhoff, Cornelia M., Gillian A. Hawker, Hans J.
Kreder, Richard H. Glazier, Nizar N. Mahomed,
and James G. Wright. 2008. “The Effect of Patients’

16
Journal of Health and Social Behavior 65(1)
Sex on Physicians’ Recommendations for Total
Knee Arthroplasty.” CMAJ: Canadian Medical
Association Journal 178(6):681–87. doi:10.1503/
cmaj.071168.
Borsky, Amanda, Chunliu Zhan, Therese Miller, Quyen
Ngo-Metzger, Arlene S. Bierman, and David Meyers.
2018. “Few Americans Receive All High-Priority,
Appropriate Clinical Preventive Services.” Health
Affairs
(Milwood)
37(6):925–28.
doi:10.1377/
HLTHAFF.2017.1248.
Braveman, Paula, and Laura Gottlieb. 2014. “The Social
Determinants of Health: It’s Time to Consider
the Causes of the Causes.” Public Health Reports
129(Suppl. 2):19–31.
Brenner, Hermann, Christian Stock, and Michael
Hoffmeister.
2014.
“Effect
of
Screening
Sigmoidoscopy and Screening Colonoscopy on
Colorectal Cancer Incidence and Mortality: Systematic
Review and Meta-analysis of Randomised Controlled
Trials and Observational Studies.” BMJ (Clinical
Research Ed.) 348:g2467. doi:10.1136/bmj.g2467.
Center for American Women and Politics. 2023. “Women
in State Legislatures 2018.” https://cawp.rutgers.edu/
facts/levels-office/state-legislature/women-state-
legislatures-2018.
Centers for Disease Control and Prevention. 2018.
Behavioral Risk Factor Surveillance System Survey
Data. Atlanta, GA: U.S. Department of Health and
Human Services, Centers for Disease Control and
Prevention.
Chapman, Elizabeth N., Anna Kaatz, and Molly
Carnes. 2013. “Physicians and Implicit Bias: How
Doctors May Unwittingly Perpetuate Health Care
Disparities.” Journal of General Internal Medicine
28(11):1504–10. doi:10.1007/s11606-013-2441-1.
Chaves, Mark, and Allison Eagle. 2015. “Religious
Congregations in 21st Century America: A Report
from the National Congregations Study.” Department
of Sociology, Duke University. https://sites.duke.
edu/ncsweb/files/2019/02/NCSIII_report_final.pdf
Chen, Ying-Yeh, S. V. Subramanian, Doloros Acevedo-
Garcia, and Ichiro Kawachi. 2005. “Women’s
Status and Depressive Symptoms: A Multilevel
Analysis.” Social Science & Medicine 60(1):49–60.
doi:10.1016/j.socscimed.2004.04.030.
Cheng, Cliff. 1999. “Marginalized Masculinities and
Hegemonic Masculinity: An Introduction.” The
Journal of Men’s Studies 7(3):295–315. doi:10.3149/
jms.0703.295.
Christy, Shannon M., Catherine E. Mosher, and Susan
M. Rawl. 2014. “Integrating Men’s Health and
Masculinity Theories to Explain Colorectal Cancer
Screening Behavior.” American Journal of Men’s
Health 8(1):54–65. doi:10.1177/1557988313492171.
Connell, R. W. 1987. Gender and Power: Society, the
Person, and Sexual Politics. Stanford, CA: Stanford
University Press.
Connell, Raewyn W. 2005. Masculinities. Rev. ed.
Cambridge, UK: Polity Press.
Connell,
Raewyn.
2012.
“Gender,
Health,
and
Theory: Conceptualizing the Issue, in Local and
World Perspective.” Social Science & Medicine
74(11):1675–83.
doi:10.1016/j.socscimed.2011.06
.006.
Connell, R. W., and James W. Messerschmidt. 2005.
“Hegemonic Masculinity: Rethinking the Concept.”
Gender & Society 19(6):829–59. doi:10.1177/
0891243205278639.
Council on Biblical Manhood and Womanhood.
2023. “The Council on Biblical Manhood and
Womanhood.” http://cbmw.org/.
Courtenay, Will H. 2000. “Constructions of Masculinity
and Their Influence on Men’s Well-Being: A
Theory of Gender and Health.” Social Science and
Medicine
50(10):1385–401.
doi:10.1016/S0277-
9536(99)00390-1.
Daly, Moira, and Fane Groes. 2017. “Who Takes the
Child to the Doctor? Mom, Pretty Much All of the
Time.” Applied Economics Letters 24(17):1267–76.
doi:10.1080/13504851.2016.1270410.
DeVoe, Jennifer E., George E. Fryer, Robert Phillips,
and Larry Green. 2003. “Receipt of Preventive
Care among Adults: Insurance Status and Usual
Source of Care.” American Journal of Public Health
93(5):786–91. doi:10.2105/AJPH.93.5.786.
Everett,
Bethany
G.,
Aubrey
Limburg,
Patricia
Homan, and Morgan M. Philbin. 2022. “Structural
Heteropatriarchy and Birth Outcomes in the
United
States.”
Demography
59(1):89–110.
doi:10.1215/00703370-9606030.
Faulkner, Lisa A., and Helen Haplin Schauffler. 1997.
“The Effect of Health Insurance Coverage on
the Appropriate Use of Recommended Clinical
Preventive
Services.”
American
Journal
of
Preventive Medicine 13(6):453–58.
Ferdinands, Jill M., Manjusha Gaglani, Emily T. Martin,
Arnold S. Monto, Donald Middleton, Fernanda
Silveira, H.Keipp Talbot, Richard Zimmerman, and
Manish Patel. 2021. “Waning Vaccine Effectiveness
against Influenza-Associated Hospitalizations among
Adults, 2015–2016 to 2018–2019, United States
Hospitalized Adult Influenza Vaccine Effectiveness
Network.” Clinical Infectious Diseases 73(4):726–29.
Fleming, Paul J., and Christine Agnew-Brune. 2015.
“Current Trends in the Study of Gender Norms and
Health Behaviors.” Current Opinion in Psychology
5:72–77. doi:10.1016/j.copsyc.2015.05.001.
Frank, Mark W. 2021. “The U.S. State-Level Income
Inequality Data.” https://www.shsu.edu/eco_mwf/
inequality.html.
Gray, Ross E., Margaret I. Fitch, Karen D. Fergus,
Eric Mykhalovskiy, and Kathryn Church. 2002.
“Hegemonic Masculinity and the Experience of
Prostate Cancer: A Narrative Approach.” Journal of
Aging and Identity 7(1):43–62.
Greenwood, Brad N., Seth Carnahan, and Laura Huang.
2018. “Patient–Physician Gender Concordance and
Increased Mortality among Female Heart Attack

Dore et al.
17
Patients.” Proceedings of the National Academy
of
Sciences
115(34):8569–74.
doi:10.1073/
pnas.1800097115.
Homan,
Patricia.
2019.
“Structural
Sexism
and
Health in the United States: A New Perspective
on Health Inequality and the Gender System.”
American
Sociological
Review
84(3):486–516.
doi:10.1177/0003122419848723.
Homan, Patricia. 2021a. “Sexism and Health: Advancing
Knowledge through Structural and Intersectional
Approaches.” American Journal of Public Health
111(10):1725–27. doi:10.2105/AJPH.2021.306480.
Homan, Patricia A. 2021b. “Structural Sexism and Life-
Course Health: Implications for Public Policy.”
Pp. 31–40 in Life Course Implications of US Public
Policy, edited by J. M. Wilmoth and A. S. London:
Routledge.
Homan, Patricia A., and Tyson H. Brown. 2022. “Sick
and Tired of Being Excluded: Structural Racism in
Disenfranchisement as a Threat to Population Health
Equity.” Health Affairs 41(2):219–27. doi:10.1377/
hlthaff.2021.01414.
Homan, Patricia, Tyson H. Brown, and Brittany King.
2021. “Structural Intersectionality as a New
Direction for Health Disparities Research.” Journal
of Health and Social Behavior 62(3):350–70.
doi:10.1177/00221465211032947.
Homan, Patricia, and Amy Burdette. 2021. “When
Religion Hurts: Structural Sexism and Health in
Religious Congregations.” American Sociological
Review 86(2):234–55.
Hou, Su-I., Diadrey-Anne Sealy, and Caroline W. Kabiru.
2011. “Closing the Disparity Gap: Cancer Screening
Interventions
among
Asians—A
Systematic
Literature Review.” Asian Pacific Journal of Cancer
Prevention 12(11):3133–39.
Jones, Tarsha P., Maria C. Katapodi, and Joan S.
Lockhart.
2015.
“Factors
Influencing
Breast
Cancer Screening and Risk Assessment among
Young African American Women: An Integrative
Review of the Literature.” Journal of the American
Association of Nurse Practitioners 27(9):521–29.
doi:10.1002/2327-6924.12223.
Kaiser Family Foundation. 2023. “Status of State
Medicaid Expansion Decisions: Interactive Map.”
https://www.kff.org/medicaid/issue-brief/status-
of-state-medicaid-expansion-decisions-interactive-
map/.
Kamal, Rabah, and Julie Hudman. 2020. “What Do
We Know about Spending Related to Public
Health in the U.S. and Comparable Countries?”
Peterson-KFF Health System Tracker. https://www
.healthsystemtracker.org/chart-collection/what-do-
we-know-about-spending-related-to-public-health-
in-the-u-s-and-comparable-countries/.
Kavanagh, Shane A., and Melissa Graham. 2019. “How
Gender Inequity Impacts on Men’s Health. An
Exploration of Theoretical Pathways.” International
Journal of Men’s Social and Community Health
2(1):e11–21. doi:10.22374/ijmsch.v2i1.5.
Kavanagh, Shane A., Julia M. Shelley, and Christopher
Stevenson. 2017. “Does Gender Inequity Increase
Men’s Mortality Risk in the United States? A
Multilevel Analysis of Data from the National
Longitudinal Mortality Study.” SSM - Population
Health 3:358–65. doi:10.1016/j.ssmph.2017.03.003.
Kavanagh, Shane A., Julia M. Shelley, and Christopher
Stevenson. 2018. “Is Gender Inequity a Risk Factor
for Men Reporting Poorer Self-Rated Health in
the United States?” PLoS One 13(7):e0200332.
doi:10.1371/journal.pone.0200332.
Kawachi, Ichiro, Bruce P. Kennedy, Vanita Gupta, and
Deborah Prothrow-Stith. 1999. “Women’s Status
and the Health of Women and Men: A View from
the States.” Social Science & Medicine 48(1):21–32.
doi:10.1016/S0277-9536(98)00286-X.
Kim, Eric S., Laura D. Kubzansky, and Jacqui Smith.
2015. “Life Satisfaction and Use of Preventive Health
Care Services.” Health Psychology 34(7):779–82.
doi:10.1037/HEA0000174.
Kim, Eric S., Victor J. Strecher, and Carol D. Ryff. 2014.
“Purpose in Life and Use of Preventive Health Care
Services.” Proceedings of the National Academy
of
Sciences
111(46):16331–36.
doi:10.1073/
PNAS.1414826111.
Koenen, Karestan C., Alisa Lincoln, and Allison
Appleton. 2006. “Women’s Status and Child Well-
Being: A State-Level Analysis.” Social Science &
Medicine 63(12):2999–3012. doi:10.1016/j.socs-
cimed.2006.07.013.
Krieger, Nancy. 2020. “Measures of Racism, Sexism,
Heterosexism, and Gender Binarism for Health
Equity Research: From Structural Injustice to
Embodied Harm—An Ecosocial Analysis.” Annual
Review of Public Health 41:37–62.
Levine, Susan, Erin Malone, Akaki Lekiachvili, and Peter
Briss. 2019. “Health Care Industry Insights: Why the Use
of Preventive Services Is Still Low.” Preventing Chronic
Disease 16:180625. doi:10.5888/PCD16.180625.
Little, Thomas H., Dana Dunn, and Rebecca E. Deen.
2001. “A View from the Top: Gender Differences
in Legislative Priorities among State Legislative
Leaders.”
Women
&
Politics
22(4):29–50.
doi:10.1300/J014v22n04_02.
Ma, Sung Jun, Oluwadamilola T. Oladeru, Katy Wang,
Kristopher Attwood, Anurag K. Singh, Daphne A.
Haas-Kogan, and Paula M. Neira. 2021. “Prostate
Cancer Screening Patterns among Sexual and
Gender Minority Individuals.” European Urology
79(5):588–92. doi:10.1016/j.eururo.2020.11.009.
Mahalik, James R., Shaun M. Burns, and Matthew Syzdek.
2007. “Masculinity and Perceived Normative Health
Behaviors as Predictors of Men’s Health Behaviors.”
Social Science & Medicine 64(11):2201–209.
doi:10.1016/j.socscimed.2007.02.035.
McKetta, Sarah, Seth J. Prins, Deborah Hasin, Megan E.
Patrick, and Katherine M. Keyes. 2022. “Structural
Sexism and Women’s Alcohol Use in the United
States, 1988–2016.” Social Science & Medicine
301:114976. doi:10.1016/j.socscimed.2022.114976.

18
Journal of Health and Social Behavior 65(1)
Miller, Grant. 2008. “Women’s Suffrage, Political
Responsiveness, and Child Survival in American
History.” The Quarterly Journal of Economics
123(3):1287–327.
Montez,
Jennifer
Karas.
2017.
“Deregulation,
Devolution, and State Pre-emption Laws’ Impact
on U.S. Mortality Trends.” American Journal of
Public
Health
107(11):1749–50.
doi:10.2105/
AJPH.2017.304080.
Montez, Jennifer Karas, Jason Beckfield, Julene Kemp
Cooney, Jacob M. Grumbach, Mark D. Hayward,
Huseyin Zeyd Koytak, Steven H. Woolf, and Anna
Zajacova. 2020. “U.S. State Policies, Politics, and
Life Expectancy.” Milbank Quarterly 98(3):1–32.
doi:10.1111/1468-0009.12469.
Montez, Jennifer Karas, Mark D. Hayward, and Anna
Zajacova. 2021. “Trends in U.S. Population Health:
The Central Role of Policies, Politics, and Profits.”
Journal of Health and Social Behavior 62(3):286–
301. doi:10.1177/00221465211015411.
Moore, Laura M., and Reeve Vanneman. 2003. “Context
Matters: Effects of the Proportion of Fundamentalists
on Gender Attitudes.” Social Forces 82(1):115–39.
doi:10.1353/sof.2003.0099.
Nagle, Amanda, and Goleen Samari. 2021. “State-
Level Structural Sexism and Cesarean Sections
in the United States.” Social Science & Medicine
289:114406. doi:10.1016/j.socscimed.2021.114406.
National Academies of Sciences, Engineering, and
Medicine. 2018. Health-Care Utilization as a Proxy
in Disability Determination. Washington, DC: The
National Academies Press.
O’Brien, Rosaleen, Kate Hunt, and Graham Hart. 2005.
“‘It’s Caveman Stuff, but That Is to a Certain
Extent How Guys Still Operate’: Men’s Accounts
of Masculinity and Help Seeking.” Social Science
& Medicine 61(3):503–16. doi:10.1016/j.socscimed
.2004.12.008.
Pew Research Center. 2014. “Evangelical Protestants.”
https://www.pewresearch.org/religion/religious-
landscape-study/religious-tradition/evangelical-prot
estant/.
Potts, Annie. 2000. “‘The Essence of the Hard
on’: Hegemonic Masculinity and the Cultural
Construction of ‘Erectile Dysfunction.’” Men and
Masculinities
3(1):85–103.
doi:10.1177/10971
84X00003001004.
Price, Maggi A., Sarah McKetta, John R. Weisz, Jessie
V. Ford, Micah R. Lattanner, Hilary Skov, Elizabeth
Wolock, and Mark L. Hatzenbuehler. 2021. “Cultural
Sexism Moderates Efficacy of Psychotherapy:
Results from a Spatial Meta-analysis.” Clinical
Psychology: Science and Practice 28(3):299–312.
doi:10.1037/cps0000031.
Rapp, Kristen Schorpp, Vanessa V. Volpe, Tabitha L.
Hale, and Dominique F. Quartararo. 2022. “State-
Level Sexism and Gender Disparities in Health
Care Access and Quality in the United States.”
Journal of Health and Social Behavior 63(1):2–18.
doi:10.1177/00221465211058153.
Rapp, Kristen Schorpp, Vanessa V. Volpe, and Hannah
Neukrug. 2021. “State-Level Sexism and Women’s
Health Care Access in the United States: Differences
by Race-Ethnicity, 2014–2019.” American Journal
of Public Health 111(10):1796–805. doi:10.2105/
AJPH.2021.306455.
Ridgeway, Cecilia L., and Shelley J. Correll. 2004.
“Unpacking the Gender System: A Theoretical
Perspective
on
Gender
Beliefs
and
Social
Relations.” Gender and Society 18(4):510–31.
doi:10.1177/0891243204265269.
Ruggles, Steven, Sarah Flood, Ronald Goeken, Megan
Schouweiler, and Matthew Sobek. 2022. IPUMS
USA: Version 12.0 [Dataset]. Minneapolis, MN:
IPUMS.
Schofield, Toni. 2015. A Sociological Approach to
Health Determinants. Port Melbourne, Australia:
Cambridge University Press.
Seidler, Zac E., Alexei J. Dawes, Simon M. Rice, John L.
Oliffe, and Haryana M. Dhillon. 2016. “The Role of
Masculinity in Men’s Help-Seeking for Depression:
A Systematic Review.” Clinical Psychology Review
49:106–18. doi:10.1016/j.cpr.2016.09.002.
U.S. Bureau of Labor Statistics. 2019. “Highlights of
Women’s Earnings in 2018.” https://www.bls.gov/
opub/reports/womens-earnings/2018/home.htm.
U.S. Census Bureau. 2017. “Census Bureau Region and
Division Codes and Federal Information Processing
System (FIPS) Codes for States.” https://www2.cen
sus.gov/programs-surveys/popest/geographies/2016/
state-geocodes-v2016.xls.
U.S. Department of Health and Human Services. 2022.
“Preventive Care.” Healthy People 2030. https://
health.gov/healthypeople/objectives-and-data/
browse-objectives/preventive-care.
Vaidya, Varun, Gautam Partha, and Monita Karmakar.
2012. “Gender Differences in Utilization of
Preventive Care Services in the United States.”
Journal of Women’s Health 21(2):140–45.
Watson, Oliver J., Gregory Barnsley, Jaspreet Toor,
Alexandra B. Hogan, Peter Winskill, and Azra C.
Ghani. 2022. “Global Impact of the First Year of
COVID-19 Vaccination: A Mathematical Modelling
Study.” The Lancet Infectious Diseases 22(9):1293–
302. doi:10.1016/S1473-3099(22)00320-6.
West, Candace, and Don H. Zimmerman. 1987. “Doing
Gender.” Gender & Society 1(2):125–51. doi:10.117
7/0891243287001002002.
Wilcox Vanden Berg, Rand N., Spyridon P. Basourakos,
Jonathan Shoag, Douglas Scherr, and Bashir Al
Hussein Al Awamlh. 2022. “Prostate Cancer
Screening for Gay Men in the United States.” Urology
163:119–25. doi:10.1016/j.urology.2021.07.027.
Wilkinson, Richard G. 2005. The Impact of Inequality:
How to Make Sick Societies Healthier. London:
Routledge.

Dore et al.
19
Young, Frank W. 2001. “Structural Pluralism and Life
Expectancy in Less-Developed Countries: The Role
of Women’s Status.” Social Indicators Research
55(2):223–40. doi:10.1023/A:1010982822560.
Author Biographies
Emily C. Dore is a PhD student in the Department of
Sociology at Emory University. She previously earned her
master’s of public health and master’s of social work
degrees at Boston University. She studies the impact of
state contexts and social policies on health disparities
throughout the life course. Ms. Dore’s recent work has
been published in Health Affairs, BMC Research Notes,
and Psychology of Violence. Her research is currently sup-
ported by the National Institute of Minority Health and
Health Disparities.
Surbhi Shrivastava is a PhD student in the Department of
Sociology at Emory University. She has a master’s of pub-
lic health from Tata Institute of Social Sciences and a
bachelor’s of dental surgery from Manipal University,
India. Her current research focuses on obstetric violence,
maternal health, and social inequality in India and Brazil.
Her previous work has been published in Journal of
Biosocial Science, Indian Journal of Medical Ethics, and
BMJ Tobacco Control.
Patricia (Trish) Homan is an associate professor of soci-
ology and the associate director of the Public Health
Program at Florida State University. She is also an associ-
ate of Florida State University’s Pepper Institute on Aging
and Public Policy and the Center for Demography and
Population Health. Her research focuses on developing
theory and measurement for structural sexism, structural
racism, and other forms of structural oppression and exam-
ining how these forces shape health. Her work has been
published in American Sociological Review, Demography,
American Journal of Public Health, The Milbank
Quarterly, Health Affairs, Social Forces, Social Science &
Medicine, Journal of Health and Social Behavior, The
Gerontologist, and The Journals of Gerontology: Series B,
among other outlets. Her research has won multiple
national awards, including the 2022 NIH Matilda White
Riley Early Stage Investigator Award, the 2022 Early
Career Gender Scholar Award from SWS South, the 2021
ASA Sex & Gender Section Distinguished Article Award,
and the 2019 Roberta G. Simmons Outstanding Dissertation
Award from the ASA Medical Sociology Section. Dr.
Homan earned her PhD in sociology from Duke University
before joining Florida State University in 2018.

    Policy Brief:

Answer:
**Structural sexism and preventive health care use in the United States**

**Policy Problem**Despite decades of evidence that timely preventive services avert disease, disability, and premature death, most U.S. adults still fail to obtain recommended screenings and vaccinations. New multilevel research shows that the shortfall is not simply a matter of personal choice or insurance coverage: states with higher structural sexism—systematic gender inequality embedded in economic, political, cultural-religious, and reproductive domains—have significantly lower uptake of nine core preventive services for both women and men, after adjusting for income, education, insurance, and other factors. Structural sexism suppresses women’s political voice and economic security, constrains reproductive autonomy, and amplifies masculinist norms that discourage care-seeking; together these forces shrink public investment in health infrastructure, raise practical and psychosocial barriers to care, and ultimately depress preventive utilization across the population. The resulting burden is substantial: a one–standard-deviation increase in state structural sexism translates into 13 % lower odds of women receiving an HPV test, 7 % lower odds of men undergoing life-saving colonoscopy, and similar declines in flu vaccination, HIV testing, and access to a regular doctor—patterns that help explain enduring state-level gaps in morbidity, mortality, and health spending. In short, entrenched gender inequities are undermining the nation’s disease-prevention strategy, making the reduction of structural sexism a pressing public-health imperative.

**Scientific Research Findings**• We find that overall, both men and women use less preventive health care in states with higher levels of structural sexism.
• In general, these findings support the gender performance theory for men, because men are less likely to seek care in a context encouraging traditional masculine traits, and the gendered power and resource allocation theory for both men and women, because states in which women are less empowered are less likely to have health-promoting policies for all.
• One finding does not follow this pattern: Men are more likely to test for prostate cancer in states with more structural sexism.

**Scientific Research Study Methods**We merged the 2018 Behavioral Risk Factor Surveillance System microdata for 425 454 adults with a state‑level structural‑sexism index that we created by standardizing and summing six indicators of gender inequality in political representation, economic status, cultural conservatism, and reproductive autonomy, then standardized the composite. We classified nine recommended preventive‑care services (personal doctor, routine check‑up, flu shot, dentist visit, colonoscopy/sigmoidoscopy, HIV test, mammogram, Pap test, HPV test; plus PSA test for men) as dichotomous outcomes and estimated gender‑stratified multilevel logistic models with random state intercepts. Models controlled for individual age, race/ethnicity, education, income, marital and parental status, insurance, self‑rated health, and state‑level poverty, racial composition, income inequality, and southern region. We further tested robustness to Medicaid expansion status, self‑rated health omission, alternative sexism index specifications, USPSTF age‑restricted subsamples, and a gender×sexism interaction, confirming that higher structural sexism predicts lower uptake of most preventive services for both women and men.

**Policy Implications**This study identifies an important relationship between state-level structural sexism and preventive health care. Our findings suggest that policymakers can strive to increase preventive care use by targeting harmful gender norms and increasing access to health-promoting resources. For example, policies that encourage men to embrace the traditionally feminine task of care taking, such as paid parental leave, may reshape gendered expectations, thereby altering masculine behaviors like avoiding care. In addition, policymakers should embrace policies that decrease barriers to preventive care. Expanding Medicaid in all states would increase access to health insurance and health care. Policies can also tackle logistical challenges of receiving care by providing affordable childcare and accessible public transportation. By addressing underlying reasons for insufficient use of care, the United States can decrease preventable illness and death.