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Mohamad B. Taha,
1
Javier Valero-Elizondo,
1,2
Tamer Yahya,
1
C
esar Caraballo,
3
Rohan Khera,
3,4
Kershaw V. Patel,
1
Hyeon Ju R. Ali,
1
Garima Sharma,
5
Elias Mossialos,
6
Miguel Cainzos-Achirica,
1,2
and
Khurram Nasir
1,2
Cost-Related Medication
Nonadherence in Adults With
Diabetes in the United States:
The National Health Interview
Survey 2013–2018
https://doi.org/10.2337/dc21-1757
OBJECTIVE
Health-related expenditures resulting from diabetes are rising in the U.S. Medica-
tion nonadherence is associated with worse health outcomes among adults with
diabetes. We sought to examine the extent of reported cost-related medication
nonadherence (CRN) in individuals with diabetes in the U.S.
RESEARCH DESIGN AND METHODS
We studied adults age ‡18 years with self-reported diabetes from the National
Health Interview Survey (NHIS) (2013–2018), a U.S. nationally representative sur-
vey. Adults reporting skipping doses, taking less medication, or delaying filling a
prescription to save money in the past year were considered to have experienced
CRN. The weighted prevalence of CRN was estimated overall and by age sub-
groups (<65 and ‡65 years). Logistic regression was used to identify sociodemo-
graphic characteristics independently associated with CRN.
RESULTS
Of the 20,326 NHIS participants with diabetes, 17.6% (weighted 2.3 million) of
those age <65 years reported CRN, compared with 6.9% (weighted 0.7 million)
among those age ‡65 years. Financial hardship from medical bills, lack of insur-
ance, low income, high comorbidity burden, and female sex were independently
associated with CRN across age groups. Lack of insurance, duration of diabetes,
current smoking, hypertension, and hypercholesterolemia were associated with
higher odds of reporting CRN among the nonelderly but not among the elderly.
Among the elderly, insulin use significantly increased the odds of reporting CRN
(odds ratio 1.51; 95% CI 1.18, 1.92).
CONCLUSIONS
In the U.S., one in six nonelderly and one in 14 elderly adults with diabetes
reported CRN. Removing financial barriers to accessing medications may improve
medication adherence among these patients, with the potential to improve their
outcomes.
In 2018, 13% of U.S. adults had diabetes, representing 34 million people (1).
The burden of diabetes has increased in recent years in the country, with a
1
Division of Cardiovascular Prevention and
Wellness, Department of Cardiology, Houston
Methodist DeBakey Heart & Vascular Center,
Houston, TX
2
Center for Outcomes Research, Houston
Methodist, Hou ston,TX
3
Center for Outcomes Research and Evaluation,
Yale-New Haven Hospital, New Haven, CT
4
Section of Cardiovascular Medicine, Department
of Internal Medicine, Yale School of Medicine,
New Haven, CT
5
Division of Cardiology, Johns Hopkins Ciccarone
Center for Prevention of Cardiovascular Disease,
Johns Hopkins University School of Medicine and
Hospital, Baltimore, MD
6
Department of Health Policy, London School of
Economics and Political Sciences, London, U.K.
Corresponding author: Khurram Nasir, knasir@
houstonmethodist.org
Received 20 August 2021 and accepted 9
December 2021
This article contains supplementary material online
at https://doi.org/10.2337/figshare.17157959.
M.B.T. and J.V.-E. contributed equally to this
work.
© 2022 by the American Diabetes Association.
Readers may use this article as long as the
work is properly cited, the use is educational
and not for profit, and the work is not altered.
More information is available at https://www.
diabetesjournals.org/journals/pages/license.
EPIDEMIOLOGY/HEALTH SERVICES RESEARCH
Diabetes Care 1
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reported 2.5% increase in absolute
age-adjusted prevalence over a 10-
year period (2008–2018), correspond-
ing to an increase from 26 million to
34 million in the same time period
(1,2). In the U.S., diabetes disproportion-
ately affects certain racial/ethnic groups,
including non-Hispanic Blacks, Native
Americans, South Asians, and Hispanics
(especially Mexicans) (1).
As one of the leading causes of mor-
bidity and mortality in the U.S. (3), diabe-
tes imposes a significant financial burden
on the health care system and individuals
alike (4). The estimated cost of diagnosed
diabetes in 2017 was $237 billion in
direct medical costs and $90 billion in
reduced productivity, a 26% increase
from 2012 to 2017. The average annual
cost for an individual with diabetes is
$16,750, two-thirds of which is attributed
directly to diabetes, with insulin alone
accounting for one-third of total cost. The
overall per capita health care–related
expenditure of individuals with diabetes
has been reported to be 2.3 times higher
when compared with that of those with-
out diabetes (4).
Oral and injectable medications are
cornerstones of diabetes management,
and medication adherence is essential
for adequate glycemic control and pre-
vention of microvascular and macrovas-
cular complications (5). Among U.S.
adults with diabetes in 2016, 67% were
prescribed at least one antihyperglyce-
mic medication, 11% were prescribed
three or more antihyperglycemic medi-
cations, and 60% were prescribed statin
(6,7). With rising medication costs and
the resulting financial hardship exacer-
bated by the introduction of novel,
more expensive medical therapies for
diabetes and other comorbid condi-
tions, the issue of affordability will likely
worsen in coming years. In the event of
financial limitations, patients with dia-
betes may forgo prescribed medica-
tions, leading to unfavorable health
outcomes (8,9).
Cost-related nonadherence (CRN) is
complex and multifactorial and repre-
sents a major issue in caring for patients
with diabetes. Studies have shown that
CRN is common among individuals with
diabetes, particularly in relation to social
determinants of health, including per-
ceived financial stress, financial insecu-
rity with health care, food insecurity
(10), and adverse socioeconomic and
health factors (11). Although informative,
these studies have not investigated the
variation of CRN across different age
groups or the effect of highly prevalent
diabetes comorbid conditions on CRN.
The current determinants of CRN among
individuals with diabetes in the U.S.
remain unclear as well.
In this study, we aimed to examine
the extent of reported CRN in individu-
als with diabetes in the U.S. using
updated, nationally representative data
and determine the relative contribution
of various potential upstream factors.
We were particularly interested in under-
standing patterns of CRN in adults with
diabetes age <65years,whodonot
have universal insurance protections
despite long-term health care needs for
diabetes, compared with those age $65
years, who have access to Medicare.
RESEARCH DESIGN AND METHODS
Setting and Study Design
We used 2013–2018 data from the
National Health Interview Survey (NHIS)
for our analyses. The NHIS, a U.S. nation-
ally representative survey administered
by the National Center for Health Statis-
tics/Centers for Disease Control and Pre-
vention, is administered on a yearly basis
and uses complex, multistage sampling to
provide estimates of prevalence data on
the noninstitutionalized U.S. population
(12). The NHIS questionnaire is divided
into four core components, and question-
naires for each component are adminis-
tered: Households Composition, Family
Core, Sample Child Core, and Sample
Adult Core (13). The Household Composi-
tion questionnaire collects basic informa-
tion and relationship information about
all individuals in a household. The Family
Core questionnaire collects information
about sociodemographic characteristics,
basic indicators of health status, activity
limitations, injuries, health insurance cov-
erage, and access to and use of health
care services. From each family, one sam-
ple child and one sample adult are ran-
domly selected in order to gather more
in-depth information. This study was
basedontheSampleAdultCorefiles
(with relevant variables added from
the Family Core files), which are sup-
plemented with demographic and socio-
economic characteristics, health status,
health care services, and health-related
behaviors of the U.S. adult population
(13). Because NHIS data are publicly
available, deidentified data, this study
was exempt from the purview of the
Houston Methodist Hospital Institutional
Review Board Committee (14).
Study Population
We used self-reported data to ascertain
diabetes status. Specifically, individuals
were considered to have diabetes and
therefore were included in the analysis
if they answered positively to the fol-
lowing question: “Have you ever been
told by a doctor or health professional
that you have diabetes or sugar dia-
betes?”We carried all analyses on two
distinct adult age groups separately
(nonelderly age 18–64 years; elderly age
$65 years) to capture the nuances of
those with and without universal finan-
cial protections from public insurance.
Study Outcomes
CRN, our main study outcome, was
considered present in individuals who
reported doing/having done any of
the following to save money in the
previous 12 months: skipping medica-
tion doses, taking less medicine, or
delaying filling a prescription. As sec-
ondary outcomes, we also analyzed the
following additional self-reported cost-
reducing behaviors (to save money):
asked doctor for lower-cost medication,
bought prescription drugs from another
country, and used alternative therapies.
Both our main and secondary outcomes
have been used as standards in prior lit-
erature (10,15–18).
Candidate Factors Associated With
CRN
Candidate factors associated with CRN
were identified based on prior work in
this space (19–21). Covariates in this
study were self-reported and included
sex, race/ethnicity, education, insurance
status, family income, financial hardship
from medical bills, U.S. region, years
since diabetes diagnosis, insulin use,
cardiovascular risk factors, atheroscle-
rotic cardiovascular disease (ASCVD),
and number of chronic comorbidities.
Categorical variables were classified as
follows: two categories for sex, four cat-
egories for race/ethnicity (non-Hispanic
White, non-Hispanic Black, non-Hispanic
Asian, or Hispanic), two categories for
education (some college or higher or
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high school or lower), three categories
for insurance type (public, private, or
uninsured), two categories for family
income (based on percentage of family
income to the federal poverty limit from
the Census Bureau) (middle/high income
[$200%] or low income [<200%]), and
four categories for geographic region
(Northeast,Midwest,South,orWest).
The following questions were used in
the NHIS to assess financial hardship
from medical bills: “In the past 12
months did you/anyone in your family
have problems paying or were unable
to pay any medical bills? Include bills
for doctors, dentists, hospitals, thera-
pists, medication, equipment, nursing
home or home care.”“Do you/anyone
in your family currently have any medi-
cal bills that are being paid off over
time? This could include medical bills
being paid off with a credit card, through
personal loans, or bill paying arrange-
ments with hospitals or other providers.
The bills can be from earlier years as
well as this year.”
The cardiovascular risk factors assessed
were self-reported and included diagnosis
of hypertension, high cholesterol, obesity
(calculated as BMI $30 kg/m
2
), current
smoker, or insufficient physical activity
(defined as not participating in $150 min
per week of moderate-intensity aerobic
physical activity, $75 min per week of
vigorous-intensity aerobic physical activity,
or a total combination of $150 min per
week of moderate/vigorous-intensity aer-
obic physical activity).
Years since diabetes diagnosis was
ascertained via self-report and catego-
rized as <10 years or $10 years. ASCVD
was defined as having coronary artery
disease (yes to any of the following
three questions: “Have you ever been
told by a doctor or other health profes-
sional that you had coronary heart dis-
ease?”,“…angina, also called angina
pectoris?”,or“…a heart attack [also
called myocardial infarction]?”)and/or
stroke disease (yes to the following
question: “Have you ever been told by
a doctor or other health professional
that you had a stroke?”). Self-reported
chronic comorbidities, including emphy-
sema, chronic obstructive pulmonary
disease, asthma, gastrointestinal ulcer,
cancer (any), arthritis (including arthri-
tis, gout, fibromyalgia, rheumatoid arth-
ritis, and systemic lupus erythemato-
sus), any kind of liver condition, and
weak/failing kidneys, were aggregated
for this analysis, and participants were
categorized as having zero, one, or two
or more.
Statistical Analyses
All analyses were carried out using Stata
version 16 (StataCorp, LP, College Sta-
tion, TX). All covariates in the study are
displayed for individuals with diabetes,
with or without CRN, and stratified by
age group. Categorical variables are pre-
sented as a number of observations and
weighted proportions, and the Rao-
Scott x
2
test was used to test for differ-
ences. In addition, the weighted prev-
alence of CRN was plotted for certain
sociodemographic and disease-spe-
cific subgroups at higher risk for CRN
to see where CRN had the highest
impact within each age group (elderly
and nonelderly).
Because CRN was a combination of
different individual variables, we pre-
sented the weighted prevalence of each
individual CRN component (including
the final composite for CRN) within soci-
odemographic and clinical factors by
age group.
Univariable and multivariable logistic
regression models were used to study
the association between CRN and the
candidate explanatory variables. The
explanatory variables were informed by
previous literature, and we used the
Hosmer-Lemeshow test for the good-
ness of fit of our multivariable model.
Thevariableforincomeincluded10%
missing values, for which we used the
multiple imputation files provided by the
NHIS. Results from all regression analy-
ses include imputed values for missing
income. Excluding income, <5% of NHIS
participants from years 2013 to 2018
had missing responses in any of the rele-
vant questions used for this analysis.
Those participants were excluded from
the present analysis to ensure that the
same study population was included in
the descriptive analyses and in the
regression analyses, which used a com-
plete case approach.
Variance estimation for the entire
pooled cohort was obtained from the
Integrated Public Use Microdata Series
(https://www.ipums.org) (22). For all
statistical analyses, P<0.05 was con-
sidered statistically significant. All analy-
ses incorporated the survey weights
and strata to account for the NHIS com-
plex survey design and reliably produce
nationally representative estimates.
RESULTS
Study Population
From 2013 to 2018, 20,326 participants
with self-reported diabetes were sur-
veyed in the NHIS (weighted prevalence
9.7%, representing 23.1 million people).
Of them, 10,368 (weighted 13.3 million)
were nonelderly and 9,958 (weighted
9.79 million) were elderly.
Prevalence of CRN and Its
Components
Among nonelderly participants, 1,898
(weighted prevalence 17.6%, represent-
ing 2.3 million) reported CRN, whereas
among elderly participants, 715 (wei-
ghted prevalence 6.9%, representing 0.7
million) reported CRN. Among noneld-
erly individuals who reported CRN,
there were more women (57%) than
men (43%), and more than half came
from low-income households (55%)
(Table 1). Although a majority of non-
elderly adults had insurance, 21% did
not. Most reported a high burden of
comorbidities and cardiovascular risk
factors. The frequency of female sex,
non-Hispanic White race/ethnicity, low
income, lack of insurance, and burden
of cardiovascular risk factors and com-
orbidities was significantly higher in
these individuals than in those without
CRN (all P<0.05). With regard to diabe-
tes, nonelderly individuals who reported
CRN had on average a longer duration of
diabetes and were using insulin more
frequently than their non-CRN counter-
parts (35% vs. 30%) (P<0.05).
A higher proportion of women and
a higher burden of cardiovascular risk
factors and comorbidities were also
observed among elderly participants
withCRNcomparedwiththosewith-
out.TheprevalenceofASCVDwas
markedly higher in elderly partici-
pants with CRN (41%) than in younger
participants with CRN (24%) (P<
0.05). With regard to diabetes, there
were no statistically significant differ-
ences in diabetes duration between
elderly individuals with and without
CRN (P50.18), whereas those with
CRN were using insulin more fre-
quently (39% vs. 28%) (P<0.05).
Among Medicare beneficiaries, 8.4% of
diabetesjournals.org/care Taha and Associates 3
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Table 1—General characteristics among adults with diabetes, with or without CRN, from the NHIS, 2013–2018
Adults with diabetes
Nonelderly (age 18–64 years) Elderly (age $65 years)
No CRN CRN PNo CRN CRN P
Sample, n8,470 1,898 9,243 715
Weighted sample (weighted %) 10,950,851 (82.4) 2,338,902 (17.6) 9,122,442 (93.1) 673,568 (6.9)
Sex <0.001 <0.001
Male 52.3 (50.9, 53.8) 43.0 (40.1, 46.0) 51.2 (49.8, 52.5) 40.8 (35.8, 45.7)
Female 47.7 (46.2, 49.1) 57.0 (54.0, 59.9) 48.8 (47.5, 50.2) 59.2 (54.3, 64.2)
Race/ethnicity <0.001 0.010
Non-Hispanic White 57.6 (55.9, 59.2) 59.6 (56.6, 62.7) 69.1 (67.6, 70.6) 63.8 (58.9, 68.7)
Non-Hispanic Black 17.0 (15.8, 18.2) 19.6 (17.3, 21.9) 13.1 (12.2, 14.1) 18.4 (14.7, 22.2)
Non-Hispanic Asian 5.9 (5.1, 6.6) 2.1 (1.2, 3.0) 5.0 (4.2, 5.7) 3.7 (2.0, 5.4)*
Hispanic 19.6 (18.1, 21.1) 18.7 (16.2, 21.2) 12.8 (11.6, 14.0) 14.1 (10.4, 17.8)
Education 0.02 0.40
Some college or higher 53.7 (52.2, 55.2) 49.9 (46.8, 52.9) 47.2 (45.8, 48.6) 49.3 (44.6, 53.9)
HS/GED or less than HS 46.3 (44.8, 47.8) 50.1 (47.1, 53.2) 52.8 (51.4, 54.2) 50.7 (46.1, 55.4)
Insurance status <0.001 <0.001
Private 54.6 (53.0, 56.1) 40.7 (37.7, 43.6) 2.7 (2.2, 3.1) 2.0 (0.7, 3.2)*
Public 36.1 (34.7, 37.5) 38.6 (35.8, 41.5) 96.9 (96.4, 97.4) 95.6 (93.7, 97.6)
Uninsured 9.3 (8.4, 10.2) 20.7 (18.3, 23.1) 0.4 (0.3, 0.6)* 2.4 (0.8, 4.0)*
Family income <0.001 <0.001
Middle/high 62.0 (60.4, 63.6) 44.9 (41.9, 47.8) 64.1 (62.6, 65.6) 44.9 (39.9, 49.8)
Low 38.0 (36.4, 39.6) 55.1 (52.2, 58.1) 35.9 (34.4, 37.4) 55.1 (50.2, 60.1)
Financial hardship from medical bills, n
(weighted %)
<0.001 <0.001
No 65.6 (64.2, 67.1) 26.1 (23.5, 28.7) 81.1 (80.0, 82.2) 41.9 (37.5, 46.4)
Yes 34.4 (32.9, 35.8) 73.9 (71.3, 76.5) 18.9 (17.8, 20.0) 58.1 (53.6, 62.5)
Region <0.001 0.38
Northeast 16.2 (15.0, 17.5) 12.2 (10.2, 14.2) 18.1 (16.9, 19.4) 15.7 (12.2, 19.2)
Midwest 22.2 (20.8, 23.5) 25.9 (23.5, 28.4) 22.4 (21.1, 23.7) 24.1 (19.6, 28.7)
South 39.8 (38.0, 41.5) 44.9 (41.9, 47.9) 38.9 (37.2, 40.6) 41.7 (36.6, 46.8)
West 21.8 (20.3, 23.4) 17.0 (14.6, 19.4) 20.6 (19.1, 22.0) 18.5 (14.5, 22.5)
Years since diabetes diagnosis <0.001 0.18
<10 56.2 (54.8, 57.6) 50.4 (47.6, 53.3) 31.8 (30.6, 33.0) 35.2 (30.3, 40.2)
$10 43.8 (42.4, 45.2) 49.6 (46.7, 52.4) 68.2 (67.0, 69.4) 64.8 (59.8, 69.7)
Now taking insulin 0.003 <0.001
No 69.6 (68.4, 70.9) 65.0 (62.2, 67.8) 71.8 (70.6, 73.0) 61.4 (56.8, 66.1)
Yes 30.4 (29.1, 31.6) 35.0 (32.2, 37.8) 28.2 (27.0, 29.4) 38.6 (33.9, 43.2)
Comorbidities, n<0.001 <0.001
0 44.4 (43.0, 45.8) 26.9 (24.3, 29.4) 24.0 (22.9, 25.1) 12.9 (9.9, 15.9)
1 32.5 (31.2, 33.7) 33.0 (30.1, 35.8) 37.4 (36.2, 38.7) 34.5 (29.9, 39.0)
$2 23.1 (22.0, 24.3) 40.2 (37.3, 43.0) 38.6 (37.3, 39.9) 52.6 (47.8, 57.5)
ASCVD status <0.001 0.01
No 83.1 (82.1, 84.1) 76.0 (73.5, 78.5) 64.6 (63.4, 65.9) 58.6 (53.9, 63.3)
Yes 16.9 (15.9, 17.9) 24.0 (21.5, 26.5) 35.4 (34.1, 36.6) 41.4 (36.7, 46.1)
Smoking status <0.001 0.006
Never 57.4 (55.9, 58.8) 46.6 (43.6, 49.6) 50.2 (48.9, 51.5) 46.4 (41.7, 51.2)
Former 24.1 (22.9, 25.3) 25.9 (23.2, 28.6) 42.3 (41.0, 43.6) 41.6 (36.9, 46.3)
Current 18.5 (17.4, 19.6) 27.5 (24.7, 30.2) 7.5 (6.8, 8.2) 12.0 (8.7, 15.2)
Obesity 0.002 <0.001
No 39.0 (37.7, 40.4) 33.8 (31.0, 36.6) 53.8 (52.5, 55.1) 41.3 (36.8, 45.9)
Yes 61.0 (59.6, 62.3) 66.2 (63.4, 69.0) 46.2 (44.9, 47.5) 58.7 (54.1, 63.2)
Physical activity 0.007 0.17
Sufficiently active 37.2 (35.8, 38.7) 32.7 (29.8, 35.6) 28.3 (27.1, 29.5) 25.0 (20.8, 29.3)
Insufficiently active 62.8 (61.3, 64.2) 67.3 (64.4, 70.2) 71.7 (70.5, 72.9) 75.0 (70.7, 79.2)
Continued on p. 5
4 Cost-Related Nonadherence in Diabetes Diabetes Care
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those with supplemental coverage (Part
D and/or private) reported CRN com-
pared with 6.2% of individuals without
such supplemental coverage (Part A or B
only). However, these differences were
not statistically significant (P50.08).
(Supplementary Fig. 1).
Theprevalenceofeachcomponentof
CRN is presented in Fig. 1. In the noneld-
erly population, 13.5% reported skipping
doses, 13.9% took less medicine, and
16.4% delayed filling a prescription
(all to save money). In the elderly
population, these prevalences were
lower (4.2%, 4.7%, and 5.8%, res-
pectively).
Factors Associated With CRN
TheprevalenceofCRNwashigherwithin
certain subgroups. In unadjusted analy-
ses, nonelderly individuals with ASCVD,
hypertension, high cholesterol, diabetes,
or obesity; those currently using insulin;
those from low-income households; and
those with financial hardship from medi-
cal bills reported a higher prevalence of
CRN. The same unadjusted trends were
seen in the elderly population, although
at lower magnitudes. Figure 2 shows
prevalence ratios of CRN in nonelderly
compared with elderly adults with diabe-
tes.Theweightedprevalenceofeach
individual component of CRN, by socio-
demographic and clinical characteristics,
is presented in Supplementary Table 1
(nonelderly) and Supplementary Table 2
(elderly).
The results of univariable and multi-
variable logistic regression analyses eval-
uating independent factors associated
withCRNarepresentedinTable2.
Within the nonelderly population, the
factors most strongly associated with
reporting CRN included financial hard-
ship from medical bills (odds ratio [OR]
4.49; 95% CI 3.82, 5.29), lack of insur-
ance (OR 2.11; 95% CI 1.66, 2.68), higher
comorbidity count (one comorbidity: OR
1.60; 95% CI 1.32, 1.93; two or more
comorbidities: OR 2.33; 95% CI 1.90,
2.86), low income (OR 1.53; 95% CI 1.29,
1.82), female sex (OR 1.32; 95% CI 1.12,
1.55), and $10 years since diabetes
diagnosis (OR 1.25; 95% CI 1.06, 1.48).
Several cardiovascular risk factors were
also associated with higher odds of
reporting CRN, including presence of
high cholesterol (OR 1.45; 95% CI 1.23,
1.73) and hypertension (OR 1.24; 95% CI
1.03, 1.48) and being a current smoker
(OR 1.38; 95% CI 1.15, 1.67). Compared
with the other racial/ethnic groups, non-
Hispanic Asians had statistically signifi-
cantly lower odds of reporting CRN in
multivariable analyses (OR compared
with non-Hispanic Whites 0.58; 95% CI
0.35, 0.95).
Within the elderly population, female
sex, low income, financial hardship, and
burden of comorbidities remained strongly
associated with CRN. In contrast, years
since diabetes diagnosis, current smoking,
hypertension, and hypercholesterolemia
were not statistically associated with CRN
in the elderly. On the other hand, current
use of insulin had a strong association
Table 1—Continued
Adults with diabetes
Nonelderly (age 18–64 years) Elderly (age $65 years)
No CRN CRN PNo CRN CRN P
Hypertension <0.001 0.03
No 36.1 (34.7, 37.4) 29.2 (26.4, 32.0) 20.1 (19.1, 21.2) 15.9 (12.5, 19.3)
Yes 63.9 (62.6, 65.3) 70.8 (68.0, 73.6) 79.9 (78.8, 80.9) 84.1 (80.7, 87.5)
High cholesterol <0.001 0.002
No 42.5 (41.1, 43.9) 33.0 (30.2, 35.7) 32.4 (31.1, 33.7) 25.3 (21.3, 29.2)
Yes 57.5 (56.1, 58.9) 67.0 (64.3, 69.8) 67.6 (66.3, 68.9) 74.7 (70.8, 78.7)
Data given as weighted % (95% CI) unless otherwise indicated. HS, high school; GED, General Equivalency Diploma. *These observations are
included for descriptive purposes but are insufficient to contribute to national estimates.
Figure 1—Prevalence of individual components for CRN by age subgroup among adults with
diabetes from the NHIS, 2013–2018.
diabetesjournals.org/care Taha and Associates 5
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with CRN in this group (OR 1.51; 95% CI
1.18, 1.92).
Other Cost-Reducing Behaviors
IndividualswithCRNengagedmuch
more frequently in cost-reducing behav-
iors aimed at saving money compared
with those without CRN. In nonelderly
adults with CRN, 71.4% reported asking
their health care provider for a lower-
cost medication (vs. 19.7% of those with-
out CRN), 4.3% reported buying prescrip-
tion medications from another country
(vs. 1.5% of those without CRN), and
16.6% reported using alternative thera-
pies (vs. 2.7% of those without CRN). In
elderly adults with CRN, the prevalence
of cost-reducing behaviors was similar to
that in nonelderly adults (Table 3) (P<
0.05 for all comparisons).
CONCLUSIONS
In a U.S. nationally representative study
using the most updated data (2013–2018)
fromtheNHIS,wefoundthatoneinsix
nonelderly and one in 14 elderly adults
with diabetes reported nonadherence to
medications because of costs. Financial
hardship from medical bills, low household
income, female sex, and greater comorbid-
ity burden were strongly associated with
CRN across age groups. The most notable
differences in the odds of reporting CRN
between nonelderly and elderly adults
were lack of insurance and cardiovascular
risk factors among nonelderly adults (age
<65 years) vs. insulin use among elderly
adults (age $65 years). Furthermore, indi-
viduals who reported CRN engaged much
more frequently in cost-reducing behaviors
aimed at saving money compared with
those without CRN, such as asking for a
lower-cost medication, buying prescription
medications from another country, and
using alternative therapies.
Our findings build on the prior pub-
lished literature in this space. A previous
NHIS analysis from 2013 estimated the
overall prevalence of CRN among adults
with diabetes in the U.S. to be 14% (10).
Our analysis, using more updated NHIS
data and generating age-stratified esti-
mates, revealed a big gap in the preva-
lence of CRN between nonelderly (17.6%)
and elderly (6.9%) individuals with diabe-
tes. This suggests that lack of health
insurance, which was remarkably higher
among nonelderly than among elderly
participants, may be strongly associated
with poor medication adherence in pat-
ients with diabetes (11,23). Specifically, as
opposed to elderly adults, nearly all of
whom have Medicare coverage, noneld-
erly adults had twofold increased odds of
reporting CRN when uninsured. For Medi-
care beneficiaries, elderly individuals with
or without supplemental insurance (Part
D or private) had similar rates of CRN.
This raises the possibility of underinsur-
ance in the elderly population. To further
support this, a study by Yala et al. (24)
showed that patients with diabetes rec-
eiving a low-income subsidy for Medicare
Part D were found to have lower out-of-
pocket (OOP) costs and better medication
adherence, and those with private insur-
ance with a deductible in the nonelderly
population with diabetes are more likely
to report forgoing needed medical serv-
ices (25).
In this study, financial hardship
from medical bills was the strongest
variable associated with CRN, regard-
less of family income or insurance
status. It was reported in 74% and
58% of nonelderly and elderly adults
Figure 2—Prevalence ratios of CRN in nonelderly compared with elderly adults with diabetes by high-risk subgroup from the NHIS, 2013–2018.
6 Cost-Related Nonadherence in Diabetes Diabetes Care
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Table 2—Factors associated with CRN among adults with diabetes from the NHIS, 2013–2018
Adults with diabetes
Age 18–64 years Age $65 years
Model 1* Model 2†Model 1* Model 2†
Sex
Male Reference Reference Reference Reference
Female 1.45 (1.27, 1.67) 1.32 (1.12, 1.55) 1.52 (1.23, 1.88) 1.41 (1.09, 1.81)
Race/ethnicity
Non-Hispanic White Reference Reference Reference Reference
Non-Hispanic Black 1.11 (0.94, 1.31) 1.02 (0.83, 1.25) 1.52 (1.18, 1.96) 1.05 (0.78, 1.42)
Non-Hispanic Asian 0.35 (0.22, 0.54) 0.58 (0.35, 0.95) 0.81 (0.49, 1.33) 0.90 (0.46, 1.74)
Hispanic 0.92 (0.77, 1.10) 0.97 (0.78, 1.20) 1.19 (0.87, 1.63) 0.88 (0.60, 1.28)
Education
Some college or higher Reference Reference Reference Reference
HS/GED or less than HS 1.17 (1.02, 1.33) 0.90 (0.77, 1.05) 0.92 (0.76, 1.12) 0.83 (0.65, 1.05)
Insurance status
Private Reference Reference ——
Public 1.44 (1.24, 1.66) 0.91 (0.75, 1.11) ——
Uninsured 2.98 (2.48, 3.59) 2.11 (1.66, 2.68) ——
Family income
Middle/high Reference Reference Reference Reference
Low 2.01 (1.76, 2.29) 1.53 (1.29, 1.82) 2.20 (1.78, 2.71) 1.91 (1.51, 2.42)
Financial hardship from medical bills
No Reference Reference Reference Reference
Yes 5.41 (4.64, 6.29) 4.49 (3.82, 5.29) 5.94 (4.88, 7.23) 4.45 (3.55, 5.57)
Region
Northeast Reference Reference Reference Reference
Midwest 1.56 (1.24, 1.96) 1.18 (0.91, 1.52) 1.25 (0.89, 1.74) 0.96 (0.66, 1.42)
South 1.50 (1.21, 1.87) 1.08 (0.85, 1.37) 1.24 (0.93, 1.65) 0.92 (0.66, 1.27)
West 1.03 (0.81, 1.33) 1.09 (0.83, 1.44) 1.04 (0.73, 1.47) 1.02 (0.69, 1.52)
Years since diabetes diagnosis
<10 Reference Reference Reference Reference
$10 1.26 (1.11, 1.44) 1.25 (1.06, 1.48) 0.86 (0.68, 1.08) 0.81 (0.63, 1.04)
Now taking insulin
No Reference Reference Reference Reference
Yes 1.23 (1.07, 1.41) 1.09 (0.92, 1.29) 1.60 (1.30, 1.96) 1.51 (1.18, 1.92)
Comorbidities, n
0 Reference Reference Reference Reference
1 1.68 (1.43, 1.97) 1.60 (1.32, 1.93) 1.71 (1.27, 2.31) 1.58 (1.11, 2.27)
$2 2.87 (2.45, 3.36) 2.33 (1.90, 2.86) 2.54 (1.90, 3.38) 2.04 (1.43, 2.91)
ASCVD status
No Reference Reference Reference Reference
Yes 1.55 (1.34, 1.81) 1.18 (0.98, 1.41) 1.29 (1.06, 1.58) 1.15 (0.91, 1.46)
Smoking status
Never Reference Reference Reference Reference
Former 1.32 (1.12, 1.56) 1.17 (0.96, 1.42) 1.06 (0.86, 1.32) 1.10 (0.86, 1.42)
Current 1.83 (1.56, 2.14) 1.38 (1.15, 1.67) 1.72 (1.22, 2.43) 1.23 (0.84, 1.79)
Obesity
No Reference Reference Reference Reference
Yes 1.26 (1.09, 1.44) 0.98 (0.83, 1.16) 1.65 (1.36, 2.01) 1.20 (0.95, 1.53)
Physical activity
Sufficiently active Reference Reference Reference Reference
Insufficiently active 1.22 (1.06, 1.41) 1.00 (0.83, 1.19) 1.18 (0.93, 1.49) 0.99 (0.74, 1.32)
Hypertension
No Reference Reference Reference Reference
Yes 1.37 (1.18, 1.58) 1.24 (1.03, 1.48) 1.34 (1.03, 1.74) 0.98 (0.72, 1.34)
Continued on p. 8
diabetesjournals.org/care Taha and Associates 7
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describing CRN, respectively. Further-
more, individuals with CRN engaged
much more frequently in cost-reduc-
ing behaviors aimed at saving money
compared with those without CRN,
such as asking their health care pro-
vider for a lower-cost medication,
buying prescription medications from
another country, and using alterna-
tive therapies. Our findings suggest
that CRN is the natural consequence
of financial hardship from medical
bills and also suggest that financial
hardship from medical bills, CRN, and
cost-reducing behaviors cluster in the
same individuals, consistent with pre-
vious studies (26). Future public health
interventions addressing cost-related bar-
riers are needed to improve medication
adherence.
Insulin use has been linked to an
increased risk of nonadherence to medi-
cal therapy resulting from costs (4,27,28).
Our results indicate that insulin is inde-
pendently associated with CRN in the
elderly population. Participants in the
standard Part D plan have OOP insulin
costs surpassing $1,000. Despite closing
the coverage gap and the expected
reduction in OOP costs, insulin prices
increased by 55% from 2014 to 2019
(29,30). Another important trend affecting
overall costs for insulin is the shift in
insulin use from the less expensive
human insulins to more expensive human
insulin analogs (31). Furthermore, newer
and more expensive noninsulin diabetic
treatment options, including sodium-glu-
cose cotransporter 2 (SGLT2) inhibitors
and glucagon-like peptide 1 (GLP-1)
receptor agonists, with their favorable
cardiovascular and diabetic kidney disease
outcomes (32–34), are being used more
frequently (35). However, these more
novel drugs usually come at higher costs
to patients and could have also contrib-
uted to higher reported CRN among
adults with diabetes between 2005–2007
and 2015–2017, with greater impact on
the most vulnerable patients (30,36).
We found important racial/ethnic and
economic differences in the prevalence
of CRN. The non-Hispanic Asian popula-
tion was the only racial/ethnic group
with significantly lower odds of reporting
CRN in the nonelderly group, even after
adjusting for income and insurance status,
as noted in past literature (37). Between
2010 and 2016, there were large gains in
insurance coverage among the nonelderly
population across racial/ethnic groups;
however, racial/ethnic minorities rem-
ained more likely to be uninsured, most
notably Native Americans, Hispanics, and
non-Hispanic Blacks. Non-Hispanic Asians
had lower insurance rates by 2018 (38).
Similarly, racial disparities in income and
poverty were more prominent among
Hispanic and non-Hispanic Black house-
holds, while non-Hispanic Asians had the
highest median household incomes and
poverty rates similar to those of non-His-
panic Whites (39). Furthermore, women
were more likely to report CRN regardless
of age. Sex disparity in CRN is well docu-
mented among patients with ASCVD (18),
diabetes (11,40,41), and cancer (42).
Among adult individuals with diabetes
reporting CRN in this study, 60% were
women, and female sex was significantly
associated with CRN. Although women
are less likely than men to be uninsured,
more women are enrolled in Medicaid
than men, and insurance plans differ sig-
nificantly by sex (43). In addition, women
are less likely than men to have coverage
through their own employer and more
likely to obtain coverage through their
spouse and more likely to have higher
OOP expenses, and low-income women,
women of color, and noncitizen women
are at greater risk of being uninsured
(43,44). These findings add to the growing
literature indicating the role of existing
social determinants of health in widening
socioeconomical disparities in the medical
care of diabetes (45,46).
Despite its cross-sectional design, this
study together with the previous body
Table 2—Continued
Adults with diabetes
Age 18–64 years Age $65 years
Model 1* Model 2†Model 1* Model 2†
High cholesterol
No Reference Reference Reference Reference
Yes 1.50 (1.31, 1.73) 1.45 (1.23, 1.72) 1.42 (1.14, 1.76) 1.18 (0.91, 1.54)
Data given as OR (95% CI). HS, high school; GED, General Equivalency Diploma. *Model 1: unadjusted. †Model 2: adjusted for all variables in
table (with exception of insurance in elderly group, given that most are insured and observations for uninsured were too small for nationally
representative estimates).
Table 3—Prevalence of cost-reducing behaviors among adults with diabetes, with or without CRN, from the NHIS, 2013–2018
Adults with diabetes
Nonelderly (age 18–64 years) Elderly (age $65 years)
No CRN CRN No CRN CRN
Asked doctor for lower-cost medication 19.7 (18.5, 21.0) 71.4 (68.6, 74.1) 18.3 (17.2, 19.3) 71.3 (66.8, 75.8)
Bought prescription drugs from another country 1.5 (1.1, 1.9) 4.3 (3.1, 5.4) 1.4 (1.1, 1.7) 5.8 (3.5, 8.0)
Used alternative therapies 2.7 (2.3, 3.2) 16.6 (14.6, 18.6) 1.4 (1.1, 1.7) 11.8 (8.5, 15.0)
Data given as weighted % (95% CI). P<0.05 for all comparisons.
8 Cost-Related Nonadherence in Diabetes Diabetes Care
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of literature in this space has important
implications for potential interventions
at the individual, provider, and policy
levels. First, our findings further reinforce
the importance of screening of social
determinants of health, with special att-
ention to characteristics associated with
CRN, because some groups are affected
disproportionately as a result of inequita-
ble resource allocation. Health disparities
in diabetes, in general, are prominent
among racial, ethnic, geographic, and
socioeconomic groups, particularly fami-
lies and individuals with the lowest
incomes and most limited resources (47).
Providers should discuss costs with pat-
ients when choosing a medical treatment.
Ideally, cost minimization approaches
should be explored in all patients with
diabetes, particularly among those most
vulnerable to financial hardship and CRN,
while still providing them with the high-
est-quality, equitable care. Second, policy
interventions should aim at attenuating
the continuous rise in price of diabetes
drugs and ensure equitable pricing; these
strategies could help reduce OOP costs
and influence patients’decisions regard-
ing cost-reducing behaviors, such as pur-
chasing prescription medications from
another country. In addition, enhancing
current health care coverage could be a
venue for improved adherence to medi-
cations in nonelderly adults, leading to
enhanced health outcomes in the ever-
increasing population of patients with dia-
betes in the U.S.
Lastly, it is important to note that
perhaps the most effective intervention
to prevent CRN in patients with diabe-
tes is the primordial prevention of dia-
betes itself. This can result in dramatic
cost savings for patients and health care
systems, and efforts should be made to
curb the concerning trends in the preva-
lence of diabetes recently observed in
our country.
The current study has a few limita-
tions. First, our results are based on sur-
vey data in which information biases,
such as recall bias or social desirability
bias, may have affected the results. Sec-
ond, diabetes was based on self-report.
Although self-report of conditions can
be potentially inaccurate, the preva-
lence of self-reported diabetes in the
NHIS is consistent with the national
rates of diagnosed diabetes reported by
the National Diabetes Statistic Report
(1). Third, the survey did not include a
nonadherence question specifictousing
diabetes medications, and CRN includes
both diabetes and other medications.
Finally, we were unable to establish cau-
sality because of the cross-sectional
nature of this study.
Medication nonadherence resulting
from cost is frequently reported among
individuals with diabetes living in the U.S.,
particularly in nonelderly adults. Greater
attention to CRN vulnerability and policy
interventions aimed at reducing medica-
tion costs and enhancing health care cov-
erage may help improve adherence to
medications, and potentially health out-
comes, in the ever-increasing population
of individuals with diabetes in the U.S.
Funding. K.N. is supported in part by the Jer-
old B. Katz Academy of Translational Research.
Duality of Interest. K.N. is on the advisory
boards of Amgen, Novartis, and Medicine Com-
pany. No other potential conflicts of interest
relevant to this article were reported.
Author Contributions. M.B.T., J.V.-E., T.Y.,
M.C.-A., and K.N. designed the study. M.B.T.,
J.V.-E., T.Y., and C.C. wrote the manuscript. J.V.-E.
prepared the statistical analysis. M.B.T. prepared
the figures. R.K., K.V.P., H.J.R.A., G.S., E.M.,
M.C.-A., and K.N. reviewed and edited the
manuscript. All authors reviewed and revised
the manuscript and agreed to the submission
of the final manuscript J.V.-E. and K.N. are
the guarantor of this work and, as such, had
full access to all the data in the study and
takes responsibility for integrity of the da ta
and the accuracy of the data analysis.
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