ORIGINAL ARTICLE
Rural-Urban Differences in Access to Preventive Health Care
Among Publicly Insured Minnesotans
John Loftus, BS;
1
Elizabeth M. Allen, PhD;
2
Kathleen Thiede Call, PhD;
3
& Susan A. Everson-Rose, PhD
1,4
1 Program in Health Disparities Research, University of Minnesota Medical School, Minneapolis, Minnesota
2 Department of Public Health, St. Catherine University, St. Paul, Minnesota
3 School of Public Health, Division of Health Policy & Management, and SHADAC, University of Minnesota, Minneapolis, Minnesota
4 Department of Medicine, and Program in Health Disparities Research, University of Minnesota Medical School, Minneapolis, Minnesota
Disclosures: The authors report no conflicts of
interest.
Funding: The 2008 Disparities and Barriers to
Utilization among Minnesota Health Care
Program Data was funded under contract with
The Minnesota Department of Human Services
(PI: K. T. Call). E. M. Allen was supported by the
National Cancer Institute of the National
Institutes of Health under award number
R25CA163184. S. A. Everson-Rose was
supported by the Program in Health Disparities
Research and the Applied Clinical Research
Program at the University of Minnesota.
Acknowledgments: The authors extend our
sincere gratitude to Vicki Kunerth and James
McRae at Minnesota Department of Human
Services for supporting this work; Nicole
Martin-Rogers and her staff at the survey center
at Wilder Research; and the Cultural Wellness
Center (CWC) for partnering on the research,
hosting the Project Management Team and
creating a bridge to the community needed to
make this project a success. We are also
indebted to the State Health Access Data
Assistance Center for help with sampling,
weighting, and administrative support. We
thank the community members who came
together to learn about the survey results and
provided recommendations to improve the
delivery of health care. We also thank members
of health plans, health care and government
entities who joined the “Working Together”
forum on March 13, 2009, at the CWC. Finally,
we are very thankful to the thousands of public
program enrollees throughout Minnesota who
took the time to complete the survey and tell us
about their experiences with health care.
For further information, contact: Kathleen T.
Call, PhD, Division of Health Policy &
Management, University of Minnesota School of
Public Health, 15-223 PWB, SHADAC,
Minneapolis, MN 55455; e-mail:
Callx001@umn.edu.
doi: 10.1111/jrh.12235
Abstract
Purpose:
Reduced access to care and barriers have been shown in rural
populations and in publicly insured populations. Barriers limiting health care
access in publicly insured populations living in rural areas are not under-
stood. This study investigates rural-urban differences in system-, provider-,
and individual-level barriers and access to preventive care among adults and
children enrolled in a public insurance program in Minnesota.
Methods: This was a secondary analysis of a 2008 statewide, cross-sectional
survey of publicly insured adults and children (n = 4,388) investigating barri-
ers associated with low utilization of preventive care. Sampling was stratified
with oversampling of racial/ethnic minorities.
Results: Rural enrollees were more likely to report no past year preventive
care compared to urban enrollees. However, this difference was no longer
statistically significant after controlling for demographic and socioeconomic
factors (OR: 1.37, 95% CI: 1.00-1.88). Provider- and system-level barriers as-
sociated with low use of preventive care among rural enrollees included dis-
crimination based on public insurance status (OR: 2.26, 95% CI: 1.34-2.38),
cost of care concerns (OR: 1.72, 95% CI: 1.03-2.89) and uncertainty about
care being covered by insurance (OR: 1.70, 95% CI: 1.01-2.85). These and
additional provider-level barriers were also identified among urban enrollees.
Conclusions: Discrimination, cost of care, and uncertainty about insurance
coverage inhibit access in both the rural and urban samples. These barriers are
worthy targets of interventions for publicly insured populations regardless of
residence. Future studies should investigate additional factors associated with
access disparities based on rural-urban residence.
Key words access to health care, health disparities, preventive health care,
public health insurance, rural health.
The Journal of Rural Health 00 (2017) 1–8
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Rural-Urban Differences in Use of Preventive Care Loftus et al.
Regular utilization of preventive health care is critical for
avoiding exposure to disease, timely diagnosis and effec-
tive management of disease, reducing the need for ag-
gressive interventions, lowering health care costs, and
improving health overall. Although nationwide rates of
cancer screening, immunizations, blood pressure checks,
and diabetes checks have increased, they still remain be-
low Healthy People 2020 goals.
1-4
Rural patients use pre-
ventive care less often than urban populations, and they
also experience problems accessing health care.
5-7
Sim-
ilarly, compared to privately insured populations, those
enrolled in public health insurance programs use pre-
ventive care at lower rates,
3,4
and they are more likely
to use emergency departments to access primary care
services.
4
Barriers to care reported among rural populations,
both privately and publicly insured, exist at the sys-
tem, provider, and individual levels. System-level
barriers for rural populations have included financial
barriers; distance to clinics; lack of available clinics,
hospitals or assisted living facilities; and concerns about
confidentiality.
8,9
Provider-level barriers have included
provider-patient relationship problems, low satisfaction
with and lack of confidence or trust in providers or
the health care system, language barriers, and concerns
about confidentiality.
9-13
Discrimination and unfair
treatment based on race or health status have also been
reported as provider-level barriers.
9
Individual-level
barriers, including concerns about stigma and resistance
to medical interventions, have been reported.
9
Those with public insurance also report significant bar-
riers to health care access. Specifically, system-level bar-
riers such as transportation barriers, concerns about cost
of care, difficulty making appointments, not knowing
where to go for care, and confusion about insurance cov-
erage have all been identified as significant barriers to
care among publicly insured populations.
14-20
Barriers re-
lated to one’s relationship with providers, wait times in
health care facilities, language barriers, cultural misun-
derstanding, along with discrimination based on race or
public insurance status can all inhibit access to health
care services.
21-23
Individual-level barriers such as con-
flicts with childcare needs and other work or family obli-
gations have also been identified.
24-31
Moreover, many of
these barriers are associated with a greater likelihood of
delaying or going without needed health care.
19,21-23
There is some evidence of rural-urban differences in
access to prenatal care for low-income women and par-
ticularly women of color,
32
and higher prevalence of re-
ports of unmet health care needs among publicly insured
women in Minnesota.
33
However, there is very little re-
search into rural-urban differences or disparities in access
to preventive care within publicly insured populations.
This study fills the gap in knowledge of access barriers
to preventive health care services among populations that
are both rural and enrolled in public health insurance
programs. Specifically, the purpose of this analysis was
to identify barriers associated with use of preventive care
in a population of Minnesota Health Care Program en-
rollees. Minnesota Health Care Programs (MHCP) are the
publicly funded health insurance programs in Minnesota,
including Medicaid (known as Medical Assistance),
Minnesota Care, which targets populations with incomes
too high to qualify for Medical Assistance, and additional
state programs. Individuals and families qualify for MHCP
based on a combination of factors including income
and assets, family size, and disability status. Minnesota
is an ideal location for a study such as this, consider-
ing the significant health outcome and socioeconomic
disparities between rural and urban Minnesotans.
34
We
hypothesized that rural MHCP enrollees experience re-
duced access to preventive care services and more barriers
compared to their urban counterparts. Understanding the
differences between barriers to preventive care in urban
and r ural publicly insured populations may inform tar-
geted interventions toward the unique challenges faced
in these communities.
Methods
Survey Design and Study Population
This study is a secondary data analysis of a statewide sur-
vey of MHCP enrollees carried out in 2008.
35
Random
sampling was stratified with oversampling of American
Indian, Latina/o, Somali, Hmong, and African American
enrollees, then weighted to represent the MHCP pop-
ulation. Survey administration was mixed-mode, using
mailed surveys and follow-up by telephone for enrollees
who did not return the survey. Mailed surveys were in
English only and telephone interviews were available in
English, Spanish, Hmong, or Somali. Both child and adult
enrollees were sampled (n = 2,432 and n = 2,194, re-
spectively) for a total sample size of 4,626. However, only
enrollees for whom complete demographic and socioeco-
nomic information was available were included in this
analysis, for a final sample size of n = 4,388. For child
enrollees, one parent in the household completed the
survey regarding their experiences seeking health care
for their child. The overall response rate was 44.3%,
which is consistent with similar surveys of publicly in-
sured populations.
36
The survey design and administra-
tion were performed using a community-based participa-
tory research (CBPR) approach, with the partnership of
local community organizations in the study design, data
collection, interpretation, and communication of results
2 The Journal of Rural Health 00 (2017) 1–8
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Loftus et al. Rural-Urban Differences in Use of Preventive Care
for this research.
37
Survey items included measures of de-
mographics, socioeconomic status, health and disability
status, access to medical and dental care, and barriers to
care. Complete information on survey design is available
elsewhere.
35
Dependent Variables
The primary outcome of interest was use of preventive
care, which was measured by one survey item. Partici-
pants were asked how long it had been since they used
preventive care: “About how long has it been since you
(your child) went to a doctor or clinic for regular or rou-
tine care?” Responses were binary and coded as “within
the past year” or “more than one year.”
Independent Variables
Rural or urban residence was determined using admin-
istrative data for enrollees based on county of residence.
Due to sample size limitations, enrollees residing in coun-
ties that were part of any of the 8 Metropolitan Statistical
Areas (MSAs) in Minnesota were considered urban, and
those outside of MSAs were considered rural. Instead of
grouping enrollees by sample strata, they were grouped
based on self-reported race/ethnicity as American Indian,
Latina/o, Asian American or Pacific Islander, black, and
white. This was done to maximize the sample size of mi-
nority race/ethnicity groups in the rural sample to allow
sufficient power in our analyses. Other demographic vari-
ables were sex, age group (child under 18; adults 18-39;
adults 40-64; adults 65+), US born, survey language
(English or not), marital status (married or unmarried),
employment status (employed or not), educational at-
tainment (high school graduate or not), disability sta-
tus, and self-reported health status (excellent, very good,
good or fair, poor). Given that preventive care guidelines
vary by age, we tested the sensitivity of the results to dif-
ferent age specifications; the results remained largely un-
changed.
Enrollees were questioned about 24 barriers to care,
all of which were included in this analysis. Barriers
were grouped conceptually as system-, provider-, or
individual-level barriers according to the Institute of
Medicine’s framework for understanding access to per-
sonal health services.
38
Enrollees were asked to identify if
each barrier was a problem for them in accessing health
care services. Barriers related to transportation, difficulty
navigating the health care system, clinic hours, cost of
care, and uncertainty with MHCP insurance were consid-
ered system-level. Provider-level barriers were those re-
lated to one’s relationship with his/her provider, includ-
ing trust, understanding of culture and religion, language
differences, and discrimination; the latter was measured
by 4 variables, including perceived unfair treatment based
on MHCP enrollment, based on ability to pay for care,
based on race, and based on sex or gender. Finally, com-
peting work or family obligations or childcare needs that
restrict access to care were considered individual-level
barriers.
Analysis
Chi-square tests were used to compare demographic and
socioeconomic factors between the rural and urban par-
ticipants. Subsequent bivariate logistic regression models
were estimated, adjusting for demographic and socioe-
conomic covariates. Next, to investigate associations be-
tween reported barriers and reports of no past year use
of preventive care, we constructed multivariate logistic
regressions stratified by rural/urban status and control-
ling for demographic and socioeconomic variables. That
is, analyses for these associations were replicated in the
rural and urban groups separately. All analyses were per-
formed using Statistical Analysis Software 9.21.
39
Results
Demographic information for urban (n = 3,355, 68%)
and rural (n = 983, 32%) participants is shown in Table 1.
The rural sample included greater proportions of white
and American Indian populations, while Asian American
and African American participants were more repre-
sented in the urban group. The urban group also included
a greater proportion of participants who took the sur-
vey in Hmong, Spanish, or Somali. Greater proportions of
the rural group were employed, married, and high school
graduates. Enrollees’ ages ranged from 1 to 89. There
were no differences in health status or disability status
between the urban and rural participants.
Approximately 24% of the rural population reported
no past year use of preventive care compared to just un-
der 19% of the urban population (P = .03). Of the 24
barriers, 7 were more prevalent in the urban group com-
pared to the rural group. Urban participants were more
likely to report not knowing where to go for care, pre-
scription drug cost concerns, provider not understanding
culture, language barriers, unwelcoming health care facil-
ities, and unfair treatment based on race (Table 2). How-
ever, after adjusting for demographic and socioeconomic
differences between urban and rural populations, there
were no differences in reported barriers in each group
with the exception of prescription drug cost concerns
(data not shown). After controlling for demographics, so-
cioeconomics, and health and disability status, the odds
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Table 1 Demographic Differences Between Rural and Urban MHCP En-
rollees
Total N Rural Urban
Sample Size 4,338 32% 68% P Value
Sex .074
Female 2,459 60.0% 54.6%
Male 1,879 40.0% 45.4%
Age (Mean = 24.6) .847
Child (0 to <18) 2,253 43.4% 45.9%
Adult (18-39) 1,027 26.5% 25.9%
Adult (40-64) 792 23.8% 22.0%
Adult (65+) 266 6.2% 6.2%
Race/ethnicity < .001
American Indian 611 9.5% 6.2%
Asian and Pacific Islander 1,011 1.9% 9.0%
Black 1,209 3.5% 26.3%
Latina/o 776 8.6% 9.9%
White 731 76.5% 48.7%
Born in the United States < .001
Yes 2,107 93.0% 74.5%
No 2,231 7.0% 25.5%
Survey language < .001
English 3,215 97.0% 90.3%
Hmong, Somali, or Spanish 1,373 3.0% 9.7%
Marital status < .001
Married 2,358 56.6% 45.7%
Unmarried 1,980 43.4% 54.3%
Employment status < .001
Employed 1,820 54.9% 43.9%
Not Employed 2,518 45.1% 56.1%
Educational attainment .048
Less than High School grad 2,007 19.5% 24.0%
High School grad or Greater 2,331 80.5% 76.0%
Health status .843
Fair or Poor 657 15.7% 16.0%
Excellent, Very good, or Good 3,681 84.4% 84.0%
Disability status .107
Yes 565 13.8% 17.4%
No 3,773 86.2% 82.6%
Unweighted sample sizes and weighted percentages are presented. Sig-
nificant differences were assessed using chi-square and are indicated by
P values shown in bold.
of reporting no past year use of preventive care was not
significantly different among rural participants compared
to urban (OR: 1.37, 95% CI:1.00-1.88; top of Table 3).
Table 3 also shows the results of multivariate logistic
regressions with each individual barrier predicting the
odds of no past year preventive care for the urban and
rural participants after adjusting for demographic, so-
cioeconomic, and health and disability status differences
between urban and rural populations. For both the
urban and rural participants, untrustworthy providers,
unfair treatment based on ability to pay for care, unfair
treatment based on MHCP enrollment, concern about
care costing more than expected and concern that care
won’t be covered by insurance were associated with
no past year preventive care. In addition, for urban
participants, not knowing where to go for care (OR:
1.75, 95% CI: 1.16-2.64), provider not understanding
culture (OR: 2.04, 95% CI: 1.33-3.14), provider not
understanding religion (OR: 2.08, 95% CI: 1.18-3.69),
and language barriers (OR: 1.77, 95% CI: 1.11-2.81)
were also associated with no past year preventive care.
Discussion
This study identified barriers to health care utilization
common to both rural and urban populations as well as
some barriers unique to urban residents. Rural residents
were more likely to report not using preventive care
in the past year compared to their urban counterparts,
with 24% of the rural sample reporting no past year
use of preventive care compared to just under 19%
of the urban sample. However, when controlling for
demographics, socioeconomics, health and disability
status, this difference was not statistically significant.
There were some differences between rural and urban
participants in terms of barriers, or barriers associated
with no past year use of preventive care. A few barriers
were significantly associated with no past year use of
preventive care in the urban group but not the rural
group. These include not knowing where to go for care,
and provider-level barriers including providers who are
unfamiliar with patients’ culture or religion. Notably,
these barriers were significantly associated with no past
year use of preventive care in the urban group, but not
in the rural group, despite controlling for demographic
and socioeconomic differences. These findings are largely
in agreement with the literature on barriers to care
in publicly insured populations. System-level barriers
including cost of care concerns,
16,18,19,32
provider-level
barriers such as provider-patient relationship factors, and
individual-level barriers such as competing work or fam-
ily obligations have been previously reported in publicly
insured populations.
15,18,25-27,40
These barriers have also
been identified in rural populations.
8,11,13,41
Still, there
is little research investigating the intersection between
rural-urban residence and public insurance status or the
specific experiences of rural public insurance enrollees.
MHCP enrollees, regardless of residence, experience
barriers to health care at the system, provider, and in-
dividual levels, and these barriers explain, at least in part,
reduced access to care. These barriers represent worth-
while targets for interventions. System-level barriers such
as concerns about cost of care and confusion about insur-
ance coverage, along with provider-level barriers such as
4 The Journal of Rural Health 00 (2017) 1–8
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Loftus et al. Rural-Urban Differences in Use of Preventive Care
Table 2 Prevalence of Reporting No Preventive Care in the Past Year and Barriers Among Rural and Urban MHCP Enrollees
Rural Percentage Urban Percentage P Values
Dependent variable
No past year use of preventive care 24.0 18.9 .034
System-level Barriers
Difficulty making appointments 33.5 32.6 .747
Transportation barriers 22.6 24.8 .336
Not knowing where to go for care 11.1 14.9 .056
Do not know where to go with questions 24.9 29.8 .062
Unable to see preferred provider 24.1 23.2 .691
Concerns about care being unaffordable 43.2 47.4 .145
Do not know what care is covered by insurance 36.4 40.0 .203
Concern about being dropped from MHCP 35.9 44.4 .003
Concern that care won’t be covered by insurance 33.8 37.8 .155
Concerns about care costing more than expected 33.6 37.8 .135
Prescription drug cost concerns 24.8 34.4 <.001
Provider-level barriers
Lack of confidence in provider 42.3 43.2 .751
Provider is not trustworthy 15.6 16.8 .584
Inconvenient clinic hours 15.4 16.9 .493
Language barriers 9.9 14.7 .008
Health care facility is unwelcoming 6.4 11.8 <.001
Provider does not understand culture 4.3 9.6 <.001
Provider does not understand religion 2.3 3.9 .019
Unfair treatment based on MHCP enrollment 33.1 33.8 .777
Unfair treatment based on ability to pay for care 32.6 32.3 .829
Unfair treatment based on race 7.9 13.9 <.001
Unfair treatment based on sex or gender 6.2 9.1 .088
Individual-level barriers
Competing work or family obligations 26.7 29.8 .238
Childcare needs 18.9 21.7 .238
Weighted percentages are presented. Significant differences were assessed using chi-square and are indicated by P values shown in bold.
unfair treatment based on public insurance status were
associated with no past-year use of preventive care and
were widely reported in this sample. Beyond these, addi-
tional system- and provider-level barriers were reported
at high rates across the sample. In particular, concerns
about care being unaffordable and lack of confidence in
providers were reported by over 40% of both the rural
and urban enrollees. Unfair treatment based on MHCP
enrollment and ability to pay for care, along with addi-
tional system-level barriers, was reported by over 30% of
both groups.
Unfair treatment based on insurance status, as well as
unfair treatment based on race or sex or gender have
been reported in publicly insured populations and identi-
fied as a barrier to care.
9,17,19,22,41
In Minnesota, a recent
statewide survey documented experiences of insurance-
based discrimination and showed that publicly insured
patients experience discrimination at much higher rates
compared to privately insured patients, controlling for
socioeconomic status differences, and that discrimina-
tion was associated with lower odds of having a usual
source of care and greater barriers to care.
42,43
Insurance-
based discrimination may be explained by disparities in
provider reimbursement rates between public and private
insurance.
43-45
This creates a financial incentive to limit
patient contact time and costly services for patients with
public insurance, leading to experiences of discrimina-
tion. In addition, unconscious biases of providers against
poor people, or racial/ethnic minorities, who are dispro-
portionately represented in public insurance, may be an-
other explanation.
42
Limitations
Some limitations should be considered when interpret-
ing the results of this analysis. First, there are inherent
limitations with cross-sectional survey data in establish-
ing cause and effect relationships. Second, there is also
susceptibility to nonresponse or sampling bias. Previous
analyses of these data have demonstrated that respon-
dents were more likely to be female, white, Asian, and
younger, and less likely to be black or American Indian.
36
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