Patient-Provider Language Concordance and Colorectal
Amy Linsky, MD, MSc1, Nathalie McIntosh, MSc2, Howard Cabral, PhD3, and Lewis E. Kazis, ScD4
1General Internal Medicine, Boston Medical Center, Boston, MA, USA;2Department of Health Policy and Management, Boston University
School of Public Health, Boston, MA, USA;3Biostatistics, Boston University, Boston, MA, USA;4Center for the Assessment of Pharmaceutical
Practices (CAPP)/Department of Health Policy and Management, Boston University School of Public Health, Boston, MA, USA.
BACKGROUND AND OBJECTIVE: Patient-provider
language barriers may play a role in health-care dispa-
rities,including obtaining colorectal cancer (CRC)screen-
ing. Professional interpreters and language-concordant
providers may mitigate these disparities.
DESIGN, SUBJECTS, AND MAIN MEASURES: We
performed a retrospective cohort study of individuals age
50 years and older who were categorized as English-
Concordant (spoke English at home, n=21,594); Other
Language-Concordant (did not speak English at home
but someone at their provider’s office spoke their
language, n=1,463); or Other Language-Discordant
(did not speak English at home and no one at their
provider’s spoke their language, n=240). Multivariate
logistic regression assessed the association of language
concordance with colorectal cancer screening.
KEY RESULTS: Compared to English speakers, non-
English speakers had lower use of colorectal cancer
screening (30.7% vs 50.8%; OR, 0.63; 95% CI, 0.51–0.76).
Compared to the English-Concordant group, the
Language-Discordant group had similar screening
(adjusted OR, 0.84; 95% CI, 0.58–1.21), while the
Language-Concordant group had lower screening
(adjusted OR, 0.57; 95% CI, 0.46–0.71).
CONCLUSIONS: Rates of CRC screening are lower in
individuals who do not speak English at home compared
to those who do. However, the Language-Discordant
cohort had similar rates to those with English concor-
dance, while the Language-Concordant cohort had lower
rates of CRC screening. This may be due to unmeasured
differences among the cohorts in patient, provider, and
health care system characteristics. These results suggest
that providers should especially promote the importance
of CRC screening to non-English speaking patients, but
that language barriers do not fully account for CRC
screening rate disparities in these populations.
KEY WORDS: language concordance; cancer screening; disparities.
J Gen Intern Med 26(2):142–7
© Society of General Internal Medicine 2010
The United States has tremendous ethnic and linguistic
diversity. According to the 2005–2007 American Community
Survey, minorities comprise 26% of the population, and nearly
20% of Americans speak a language other than English at
home. By 2050, it is projected that minorities will make up
about half of the US population, with a similar increase in
individuals speaking a language other than English at home.1
Compared to white non-Hispanics, minorities use fewer pre-
ventive services, including colorectal cancer (CRC) screening.2
Language plays a role in these health-care disparities.3, 4
Language barriers may undermine medical communication,
lead to inaccurate diagnosis, and contribute to poorer man-
agement or treatment adherence.5
Of individuals who do not speak English at home, roughly
44% speak English “less than well.”1Patient-provider commu-
nication problems may be common for individuals who have
limited English proficiency (LEP).1,2,6Compared to those with
English proficiency, LEP patients are more likely to have
difficulty understanding medical explanations,7getting infor-
mation,8and have worse management of care.9LEP patients
are less likely to have preventive10or primary care services,11
access to care,12or be satisfied with provider communica-
tion.13Access to, and the quality of, care for LEP patients can
be improved by using professional interpreters or language-
Colorectal cancer screening is recommended in the routine
care of older patients in the US and may be compromised
because of language barriers. CRC is the third most preva-
lent cancer in the US.2Although many minorities have lower
rates of CRC compared to white non-Hispanics, they tend to
be diagnosed at a later stage of disease and have higher
mortality rates.2The US Preventive Services Task Force
recommends colonoscopy every 10 years in adults aged 50–
75 years. Other recommendations include flexible sigmoid-
oscopy every 5 years or home-based fecal occult blood test
(FOBT) every year.14It is estimated that 60% of CRC deaths
could be prevented if all persons age 50 years and older were
Current rates of CRC screening are less than 60%, with
lower rates in minorities.16Language appears to be a signifi-
cant factor.17Compared to white non-Hispanics, Spanish-
speaking Hispanics were 43% less likely to receive CRC
screening.18Communication problems when discussing
cancer screening are also documented with Vietnamese-
Americans.19Furthermore, there is evidence that fewer
Received March 19, 2010
Revised August 17, 2010
Accepted August 18, 2010
Published online September 21, 2010
providers discuss CRC screening with non-English speaking
patients20even when translators are available.21
Lack of physician recommendation is often the primary reason
patients are not current with guidelines.19Discussion of
screening for CRC is complicated and time consuming, and
may be omitted or abbreviated when there are language
barriers.22A recent study showed that patients who spoke
Spanish at home were less likely to receive CRC screening
compared to patients who spoke English at home, even after
controlling for English proficiency and patient characteris-
tics.23However, that study did not take into account whether
someone at the provider’s office spoke the patient’s preferred
language. The purpose of our study is to assess the association
of language concordance with CRC screening rates in patients
who do not speak English at home compared to rates in those
DESIGN AND SUBJECTS
We analyzed data from the Medical Expenditures Panel Survey
(MEPS), a nationally representative survey of non-institution-
alized US civilians with 2 years of longitudinal follow-up. We
used the Consolidated Household and Medical Conditions files
from the Household Component Survey and the Self-Adminis-
tered Questionnaire. We merged 2002, 2004 and 2006 data,
choosing alternate years to ensure distinct respondents, creating
a sample of 107,720 subjects. Individuals with a self-reported
history of colon or rectal cancer (International Classification of
Disease 9-CM codes 153, 154) and those less than 50 years were
excluded, as were individuals who did not have complete
responses for all variables of interest. Individuals greater than
75 years were included given lack of consensus on an upper age
limit for screening. Our final study sample was 23,297 subjects,
representing 222 million individuals.
To create cohorts of patient-provider language concordance,
we combined responses to the questions “What language is
spoken in your home most of the time?” and “Does someone at
your provider’s speak the language you prefer or provide
translator services?” If English was spoken at home, the
subject was categorized as English-Concordant. If English
was not spoken at home and someone at the provider’s spoke
the respondent’s preferred language or offered translation
services, the subject was categorized as Other Language-
Concordant. Subjects who reported not speaking English at
home and denied that someone at their provider’s spoke their
preferred language or offered translation services formed the
third cohort, Other Language-Discordant (Fig. 1).
We assessed CRC screening using self-reported rates of
FOBT and endoscopy. Given that patients may not have FOBT
exactly within 12 months, we considered tests performed
within 2 years prior to the date of MEPS survey completion to
be current with recommendations. In MEPS data, responses
for sigmoidoscopy and colonoscopy were combined into a
single variable with time frame choices either within or greater
than 5 years of the survey date. Therefore, if an individual had
FOBT within 2 years or endoscopy within 5 years, they were
classified as being current with CRC screening.
Covariates included: self-reported race/ethnicity, age, edu-
cation, marital status, family income, employment status, time
since last check-up, and health insurance status. Race and
ethnicity were combined into a variable with five categories:
white non-Hispanic, black, Hispanic, Asian, and other. Age
had three categories: age 50–<65 years, 65–<75 years, and age
75–85 years (this category may include subjects >85 years as
Figure 1. Sample cohorts.
Linsky et al.: Language Concordance and CRC Screening
MEPS top coded ages at 85). Education had four categories: no
degree, high school or equivalent, some college or greater, or
other. Marital status had two categories: married or not married.
Total family income had four categories defined by the federal
poverty line (FPL): poor/near-poor (<125% FPL), low income
(125–<200% FPL), middle income (200–<400% FPL), and high
income (≥400% FPL). Employment status had two categories:
employed or unemployed. Time since the last checkup had three
insurance status had three categories: any private insurance,
public insurance only, and no insurance.
Co-morbidities are often considered when recommending
CRC screening; however, these indices are not included in
MEPS. As a proxy, the Physical Component Score (PCS) and
Mental Component Score (MCS) of the 12 Item Short Form
Health Survey (SF-12) were used. These scores have been well
validated and are standardized with a mean of 50 for the
general population.24Scores were converted into two catego-
ries: scores less than the sample median (“low” PCS/MCS) and
those greater than or equal to the median (“high” PCS/MCS).
Sample PCS and MCS medians were 47 and 54, respectively.
Of note, Medicare coverage of endoscopy for average-risk
adults began in 2001, so year of survey was also included.
We included US region to account for regional variations. The
following provider-level variables were also included: provider
race, ethnicity, and sex; and provider type and specialty.
To account for the complex sample design, survey statistical
procedures were used. Weighted prevalence and standard
error (SE) estimates were calculated for independent variables
using MEPS survey weights, and χ2tests assessed for
differences between cohorts. Variables with proportion of
missing responses greater than 65% (provider characteristics)
were eliminated. For the remaining variables, individuals with
complete data were compared to those with missing data to
assess generalizability. All subsequent analyses were done on
samples with complete data for all variables retained (n=
Bivariate odds ratios (ORs) and 95% confidence intervals
(CIs) were used to evaluate the associations between each
independent variable and receipt of CRC screening. Variables
were independently assessed for confounding or effect modifi-
cation of language concordance. Those yielding a ≥10%
change in the magnitude of effect were considered as potential
We used multivariate logistic regression to determine the
association of language concordance with CRC screening. We
included in the model those variables determined a priori to be
potentially associated with screening (sex, age, time since last
checkup, marital status, employment status, year, region), as
well as variables found to be confounders (race/ethnicity,
education, family income, and health insurance status) or
effect modifiers (PCS).
We evaluated our definitions of both the primary explanatory
variable and outcome variables. Patient language was re-defined
by comfort level speaking English using the question “Are you
comfortable conversing in English?” Individuals with LEP (those
who responded “No”) were then grouped by whether someone at
their provider’s spoke their preferred language or offered trans-
lation services. In this way, three cohorts based on English
proficiency were created: English-proficient, LEP-Concordant
and LEP-Discordant. A simple logistic regression using these re-
defined cohorts was compared to that using the original cohorts
based on language spoken at home. In addition, receipt of CRC
screening was re-defined in several ways. We assessed receipt of
FOBT alone, endoscopy alone, endoscopy ever, and any screen
All prevalence, odds ratio, and variance estimates are
presented from weighted analyses unless otherwise specified.
Statistical significance was set at α=0.05. All analyses were
conducted with SAS (version 9.2, SAS Institute Inc., Cary, NC).
This study was granted exempt status by the Boston Univer-
sity Institutional Review Board.
The final study sample of 23,297 represents 222 million
individuals age 50 years or older with no history of CRC. The
vast majority of respondents spoke English at home (96%).
Overall, most were white non-Hispanic (81.1%), had at least a
high school education (75.5%), were married (61.8%), were
aged 50–64 years (57.8%), were female (54.7%), and were
employed (51.3%). Few were uninsured (6.1%).
The English-Concordant cohort was predominantly white
non-Hispanic (83.7%), more likely to have a high school
education, and to have high income and private insurance
(Table 1). The Other Language-Concordant cohort had the
highest prevalence of Hispanics (60.9%), was the least educat-
ed, and most likely to be poor, have public health insurance,
and be from the west. The Other Language-Discordant cohort
had the highest percentage of Asians (29.4%) and those 75-
85 years (29.6%), and was most likely to be unemployed or
uninsured. The three cohorts were similar regarding sex,
marital status, and time since last checkup. Given the large
sample size, the cohorts were statistically different for all
covariates except marital status (p=0.13).
The prevalence of CRC screening was greatest in the
English-Concordant group, followed by the Other Language-
Discordant group, and then the Other Language-Concordant
group (50.8% vs 37.9% vs 28.9%, respectively). Compared to
the English-Concordant cohort, the unadjusted odds of
being current with CRC screening for Other Language-
Concordant patients was 0.40 (95% CI, 0.33–0.47) and for Other
Language-Discordant patients was 0.59 (95% CI, 0.42–0.84)
After adjusting for confounding, demographic and socioeco-
nomic variables, the odds of being current with CRC screening
for those who did not speak English at home was lower
compared to those who did (30.7% vs 50.8%, respectively;
OR, 0.63; 95% CI, 0.51–0.76).
When looking at patient-provider language concordance
determined by language spoken at home and if someone at
the provider’s spoke the patient’s preferred language, the
adjusted odds of being current with CRC screening was lower
for those in the Other Language-Concordant cohort compared
to those in the English-Concordant cohort (OR, 0.57; 95% CI,
Linsky et al.: Language Concordance and CRC Screening
0.46–0.71). The Other Language-Discordant cohort did not
statistically differ from the English-Concordant cohort (OR,
0.84; 95% CI, 0.58–1.21) (Table 2).
Defining language concordance using English proficiency
rather than language spoken at home did not change the
patterns of association with CRC screening (LEP-Discordant:
OR, 0.41; 95% CI, 0.20–0.83; LEP-Concordant: OR, 0.27; 95%
CI, 0.19–0.37, referent to English-proficient). Furthermore,
using different definitions of CRC screening (e.g., FOBT only,
endoscopy only, endoscopy ever, and any screen ever) also
yielded similar patterns of association, with lower rates of CRC
screening in individuals who did not speak English at home
compared to those who did, and higher rates of CRC screening
in the Other Language-Discordant cohort compared to the
Other Language-Concordant cohort (data not shown).
We found that individuals who do not speak English at home
are less likely to be adherent with CRC screening compared to
those who do. This is consistent with other reports.3,10,23
However, in our adjusted model, we found that the Other
Language-Discordant cohort is as likely as the English-
Concordant cohort to be adherent to CRC screening guidelines,
while the Other Language-Concordant cohort is less likely to
be adherent. This was unexpected. We hypothesized that the
Other Language-Concordant cohort would experience better
Table 1. Baseline Characteristics of Study Population by Language Concordance
Other language concordance
Other language discordance
n Weighted % (SE)n Weighted % (SE)n Weighted % (SE)
High school Or GED
College or greater
Time since last checkup
Physical component score†
Mental component score†
9,40245 (0.25) 55943 (1.32)86 39 (3.10)
SE = standard error;
*Poor/near-poor (<125% Federal Poverty Level), low (125–<200 % FPL), middle (200–<400% FPL), high (Q400% FPL),†low = scores < median of the study
population; high = scores ≥ median of the study population
Linsky et al.: Language Concordance and CRC Screening
communication with their providers compared to the Other
Language-Discordant cohort, thereby leading to higher CRC
These findings might be due to differences between the
Other Language-Concordant and Other Language-Discordant
cohorts. Compared to the Other Language-Concordant group,
the Other Language-Discordant respondents were less likely to
be Hispanic (42% vs 61%) and more likely to be white non-
Hispanic (23% vs 14%). They were also more likely to have
attended college (19% vs 12%) and have a high income (27% vs
17%). Income and education are predictors of preventive
health-care use;25however, these variables were controlled
for in our model.
The discrepancy in CRC screening between the Other
Language-Concordant and Other Language-Discordant
groups may also be related to other unmeasured differences
between the two groups. For example, provider cultural
competence7,13,26,27and better quality of communication
between patients and providers4,22are associated with higher
CRC screening rates. Similarly, rates are higher with greater
patient acculturation28and health literacy.9,27,29While these
variables have been shown to be associated with CRC screen-
ing rates, we were unable to measure and include them in our
There are additional limitations to this study. It is possible
that individuals who do not speak English at home speak
English well enough to communicate adequately but answered
that someone at their provider’s office did not speak their
language. These individuals would be misclassified as Other
Language-Discordant. As a result, our cohorts may not have
appropriately captured patient-provider language barriers.
Some suggest that LEP is a better measure of language
barriers.4To address this, alternatively defined cohorts based
on comfort speaking English were used. Results in an
unadjusted model were similar to those based on language
spoken at home. Therefore, regardless of how we defined
language concordance, our results suggest that individuals
who are ‘other language-concordant’ with their providers have
lower adherence to CRC screening.
In addition, our definition of being adherent to CRC
screening guidelines is conservative and may misclassify some
as non-adherent. To address this, multivariate models substi-
tuting adherence to current CRC guidelines with other CRC
screening outcomes were analyzed. Results showed similar
findings; individuals in the Other Language-Discordant groups
had higher rates for each of the CRC testing outcomes
compared to individuals in the Other-Language Concordant
group. Furthermore, we could not identify if FOBT or endos-
copy was done for diagnostic purposes due to symptoms or in
individuals with higher risk, such as those with family history
of CRC, which could overestimate CRC screening rates. We did
not control for patient co-morbidities, which may influence the
appropriateness of screening. As a proxy for co-morbidities,
however, we included physical summary health status scores
(PCS) in our multivariate model.30
Similar to prior studies, our results suggest that speaking a
language other than English at home is associated with lower
CRC screening. In addition, in our adjusted model we found
that individuals who do not speak English at home and do not
have anyone at their provider’s who speaks their preferred
language had CRC screening rates comparable to English
speakers, while those who do not speak English at home and
Table 2. Association of Independent Variables with Colorectal
(n in thousands)
English (ref) (21.6)
Other concordance (1.4)
Other discordance (0.2)
50–64 (ref) (13.3)
Male (ref) (10)
High income (ref) (9.1)
Middle income (6.4)
Low income (3.3)
Poor/near poor (4.5)
College (ref) (4.9)
High school or GED (11.2)
No degree (5.6)
Any private (ref) (15.3)
Public only (6.2)
2002 (ref) (8.7)
Northeast (ref) (3.9)
Physical component score§
High (ref) (11.7)
Mental component score§
High (ref) (11.6)
Employed (ref) (11.1)
Not employed (12.2)
Married (ref) (13.8)
Not married (9.5)
Time since last checkup
Never (ref) (0.8)
>2 years (2.6)
≤2 years (19.9)
*Odds ratios determined from weighted sample
†Adjusted for all variables in table except MCS
‡Poor/near-poor (<125% Federal Poverty Level), low (125–<200 % FPL),
middle (200–<400% FPL), high (Q400% FPL)
§Low = scores less than the median of the study population; high = scores
greater than or equal to the median of the study population
Linsky et al.: Language Concordance and CRC Screening
have someone at their provider’s who speaks their preferred Download full-text
language, had lower rates. These findings may be related to
unmeasured differences between the two cohorts, including
patient characteristics, provider cultural competence, patient
acculturation, the quality of patient-provider communication,
and the level of patient health literacy. Our results suggest that
providers should especially promote the importance of CRC
screening to non-English speaking patients, but that patient-
provider language barriers do not fully account for lower CRC
screening in patients who do not speak English at home.
Acknowledgements: This research was unfunded. Results were
presented in poster format at the national meetings of the American
College of Preventive Medicine, February 2010, Washington DC and
AcademyHealth, June 2010, Boston MA.
Conflict of Interest: None disclosed.
Corresponding Author: Amy Linsky, MD, MSc; Section of General
Internal Medicine, Boston Medical Center, 801 Massachusetts Avenue,
2nd Floor, GIM, Boston, MA, USA (e-mail: Amy.Linsky@bmc.org).
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Linsky et al.: Language Concordance and CRC Screening