Undiagnosed obesity: implications for undiagnosed hypertension, diabetes, and hypercholesterolemia.
ABSTRACT Since obesity is a risk factor for hypertension, diabetes, and hypercholesterolemia, health care providers should screen obese individuals for these common diseases. It is possible that obese adults are not receiving appropriate screening for these diseases. This study's objective was to describe the prevalence of undiagnosed obesity, diabetes, hypertension, and hypercholesterolemia, in a nationally representative sample of obese US adults, by patients' recollection of whether they had received such a diagnosis.
The prevalence of undiagnosed disease was obtained by identifying respondents in the 1999-2000 National Health and Nutrition Examination Survey (NHANES) who had findings consistent with a condition but who did not report being told they had that condition by a health care provider.
The prevalence of undiagnosed obesity, diabetes, hypertension, and hypercholesterolemia in currently obese US adults is 22.9%, 11.3%, 16.1%, and 37.7%, respectively. Significant predictors of undiagnosed obesity include black race and younger age. In addition, obese adults with excellent self-reported general health condition and lower body mass index are less likely to have diagnosed obesity.
Health care providers are missing valuable opportunities to address obesity and diagnose diabetes, hypercholesterolemia, and hypertension in obese adults. An emphasis on screening obese individuals for these diseases is needed to improve health promotion.
- SourceAvailable from: Jason C G Halford[Show abstract] [Hide abstract]
ABSTRACT: Several treatments for obesity have received regulatory approval, but health insurers and other payers typically refuse to support access to them. Thus, patients are left to bear significant out-of-pocket costs for obesity pharmacotherapy. This study aimed to assess preferences and willingness to pay (WTP) for obesity medications among people seeking weight loss in the United States and United Kingdom. An online survey was developed based on literature review, clinician interviews, and profiles of available therapies. Participants indicated their preference for hypothetical treatments which varied by seven attributes: percentage of weight loss, long-term health risk reduction, time to noticeable weight loss, delivery mode, side effects, lifestyle modification, and cost; 502 obese participants completed the survey (mean BMI 37.12 kg/m(2) (±4.63); 73.5% female; 47.7 (±12.9) years of age). The participants deemed weight loss of >21 kg (United Kingdom) and >28 kg (United State) as "acceptable". All treatment attributes were important (P < 0.001) except "time to noticeable weight loss." The survey found that percentage weight loss was the most important factor for patients and a reduction in long-term health risk was relatively less important. Patients were willing to pay £6.51/$10.49 per month per percentage point of weight loss that a pharmacotherapy could provide. Participants also highly valued therapies that did not require substantial lifestyle modifications and were willing to pay £17.78/$30.77 more per month for a one-pill-per-day treatment vs. a weekly injectable. Participants placed a high value on weight loss and avoiding changes to their lifestyle, and less value on reducing long-term risks to health.Obesity 02/2012; 20(10):2019-26. · 4.39 Impact Factor
Article: BUILDING BRIDGES IN HEALTHCARE[Show abstract] [Hide abstract]
ABSTRACT: or those who have not been in the Charleston area for several years, 2005 has marked the opening of a fabulous new span that links Charleston with Mount Pleasant. In mid July, the entire region turned out to stroll over the new bridges and celebrate their completion with a monumental fireworks display. The two dilapidated structures that had offered an aging and sometimes perilous connection between these Charleston and communities east of the Cooper River are now in the process of being torn apart, destined to be sunk somewhere off the South Carolina coast where they will serve as breeding grounds for fish. The new bridge is a beautiful structure that towers over the old rusty bridges and is visible from just about anywhere on the Charleston Peninsula. The eight-lane structure, with an additional 12 foot wide lane for walkers and bikers, makes the drive over the upper Charleston harbor a breeze. When accidents do occur (and there have been a few already), remaining drivers simply maneuver around the problem with little effect on the overall flow of traffic. What a pleasant change from the past when one disabled vehicle could easily bog down flow over the bridge for an hour or more. The new bridge to Mount Pleasant reminds me that connectivity have as much to do with efficient and safe health care as it does vehicular traffic. The cornerstone of effective patient care is the exchange of information between the patient and her or his physician. Likewise, communicating information about the patient to others on the health care team such as nurses, consulting physicians, and hospitals, is just as valuable to assuring that patients get the best and safest care possible. Yet, for much of the past eighty years our communication in health care has been on par with the old Cooper River bridges. Communication systems usually worked, but in places they were rusty, in other places a break-down could jam up the entire system, and in other places communication could be so faulty that it created dangerous conditions. Just like a new Cooper River bridge to bring commuters to Charleston more efficiently and safely, we need to figure out how we can do the same thing to improve patient communication with the health care system. In our own offices, we have been pioneers with electronic medical record systems. Family Medicine has had a computerized medical record since the early 1970's. The Department started out on a home-grown system housed on a massive mainframe computer located in two large offices in our Calhoun Street building. Faculty and residents in our office connected to this mainframe via dummy terminals situated throughout the building. Over time as computer systems shrunk in size, we were able to retire the mainframe and run our system off computers that are now linked throughout Charleston so that the same record serves our office downtown, our North Charleston office, and our East Cooper office. In addition, faculty members have tapped into the record from the nursing home or remote clinic sites on Johns Island. This connectivity assures that the latest information about patients is available to all our doctors all the time. In addition, we have been working
- [Show abstract] [Hide abstract]
ABSTRACT: Physician counseling is effective in promoting healthy behavior. We evaluated whether patient reports of physician acknowledgment of overweight patients' weight status are associated with the patients' perceptions of their own weight and desire to lose weight. We analyzed the 2005-2008 National Health and Nutrition Examination Survey data on adults aged 20 to 64 years with a body mass index (BMI) of at least 25.0 (calculated as weight in kilograms divided by height in meters squared). Logistic regressions were computed to evaluate the impact of reports of physician acknowledgment of patients' weight status on patients' perceptions of their weight, desire to weigh less, and attempts to lose weight. In logistic regressions controlling for relevant confounding variables, participants with a BMI of 25 or greater (odds ratio [OR], 6.11; 95% confidence interval [CI], 4.38-8.53) and those with a BMI of 30 or greater (OR, 7.58; 95% CI, 5.83-9.84) both had an increased likelihood to perceive themselves as overweight if they were told by their physician that they were overweight. Similarly, participants with a BMI of 25 or greater (OR, 2.51; 95% CI, 2.15-2.94) and those with a BMI of 30 or greater (OR, 2.24; 95% CI, 1.74-2.88) had an increased likelihood to have attempted to lose weight in the previous 12 months if they had reported being told they were overweight. However, only 45.2% of individuals with a BMI of 25 or greater and 66.4% of those with a BMI of 30 or greater reported being told by a physician that they were overweight. Among patients who were overweight or obese, patient reports of being told by a physician that they were overweight were associated with more realistic perceptions of the patients' own weight, desire to lose weight, and recent attempts to lose weight.Archives of internal medicine 02/2011; 171(4):316-21. · 11.46 Impact Factor
639Vol. 36, No. 9
The deleterious effects of obesity on health have been
well documented. Obesity has been shown to increase
mortality,1-3 aggravate common medical conditions such
as cardiovascular disease4,5 and diabetes,6 and increase
health care costs.7 Obesity is also common, with its
prevalence in the US population continuing to rise de-
spite the growing evidence that it is unhealthy and
costly. A recent study showed increased prevalence of
obesity to 30.5% of the US population in 1999–2000
from 22.9% in 1994–1998, with a concomitant increase
in overweight individuals and extreme obesity.8 This
demonstrates the continuation of a trend that began in
the 1980s, given that the prevalence of obesity had been
relatively stable from 1960 to 1980.9,10
Diabetes mellitus, hypertension, and dyslipidemia are
prevalent diseases that are linked to obesity. The Ex-
pert Committee on the Diagnosis and Classification of
Diabetes Mellitus identified being overweight or obese,
defined as a body mass index (BMI) ≥ 27 in 1997, as a
major risk factor for type 2 diabetes.11 Obesity and
weight gain have been associated with an increased risk
of hypertension and dyslipidemia in a number of stud-
ies.12-16 Currently, the US Preventive Services Task Force
states that obesity is a risk factor for diabetes, hyper-
tension, and hypercholesterolemia. However, the time
interval between screenings and the age to begin screen-
ing for obese patients has not been well-defined.17 This
is an important issue, considering that hypertension,
diabetes, and hypercholesterolemia lead to consider-
able morbidity and mortality, which can be mitigated
through early recognition and treatment, with weight
loss being a key management goal.18-22
The recognition of obesity by physicians is a crucial
initial step to health promotion. However, the preva-
lence of physician-diagnosed obesity is less than opti-
mal, even for patients with comorbid diseases that are
linked to weight. For instance, a study using the 1999
Behavioral Risk Factor Surveillance System reported
that health providers had given weight loss counseling
Clinical Research and Methods
Undiagnosed Obesity: Implications for Undiagnosed
Hypertension, Diabetes, and Hypercholesterolemia
Vanessa A. Diaz, MD; Arch G. Mainous, III, PhD;
Richelle J. Koopman, MD, MS; Mark E. Geesey, MS
From the Department of Family Medicine, Medical University of South
Background and Objectives: Since obesity is a risk factor for hypertension, diabetes, and hypercholester-
olemia, health care providers should screen obese individuals for these common diseases. It is possible
that obese adults are not receiving appropriate screening for these diseases. This study’s objective was to
describe the prevalence of undiagnosed obesity, diabetes, hypertension, and hypercholesterolemia, in a
nationally representative sample of obese US adults, by patients’ recollection of whether they had re-
ceived such a diagnosis. Methods: The prevalence of undiagnosed disease was obtained by identifying
respondents in the 1999–2000 National Health and Nutrition Examination Survey (NHANES) who had
findings consistent with a condition but who did not report being told they had that condition by a health
care provider. Results: The prevalence of undiagnosed obesity, diabetes, hypertension, and hypercholes-
terolemia in currently obese US adults is 22.9%, 11.3%, 16.1%, and 37.7%, respectively. Significant
predictors of undiagnosed obesity include black race and younger age. In addition, obese adults with
excellent self-reported general health condition and lower body mass index are less likely to have diag-
nosed obesity. Conclusions: Health care providers are missing valuable opportunities to address obesity
and diagnose diabetes, hypercholesterolemia, and hypertension in obese adults. An emphasis on screen-
ing obese individuals for these diseases is needed to improve health promotion.
(Fam Med 2004;36(9):639-44.)
to only 50% of overweight and obese people with dia-
betes and to 21% of overweight and obese nondiabet-
ics.23 This failure to deal with obesity in those with
weight-related conditions suggests that the obese may
also receive inadequate screening for weight-related
This study describes the patient-reported prevalence
of physician-diagnosed obesity using a recent nation-
ally representative sample, emphasizing groups at risk
for undiagnosed obesity. Because of the acknowledged
association between obesity and hypertension, hyper-
cholesterolemia, and diabetes, we also describe the
prevalence of undiagnosed hypertension, hypercholes-
terolemia, and diabetes in obese adults.
We analyzed data from the 1999–2000 National
Health and Nutrition Examination Survey (NHANES
1999–2000).24 The NHANES 1999–2000 is a product
of the National Center for Health Statistics. It is a con-
tinuous, annual survey involving participants from a
nationally representative sample of noninstitutionalized
residents of the United States. Minority groups were
oversampled to ensure adequate numbers for analysis,
and samples are weighted so they are representative of
the US population. Sampling weights were calculated
taking into account unequal probabilities of selection
due to sample design and planned oversampling, then
matched to known population control totals to be rep-
resentative of the US population. The number of
unweighted adult respondents, defined as those ≥ 20
years old, is 4,880, with 1,247 of these being obese,
defined as a BMI ≥ 30. This results in a weighted sample
size of 49,915,375 obese adults.
The NHANES 1999–2000 consists of detailed house-
hold interviews and physical examinations that include
lab work in mobile examination centers. If respondents
are unwilling or unable to receive the full examination,
home examinations consisting of a subset of exam com-
ponents are offered. Nonresponse/refusal rates undergo
statistical adjustment by using appropriate sampling
The respondents were divided into groups based on
race, age, gender, and BMI. Race was self-reported.
Age groups were formed based on screening recom-
mendations from the National Cholesterol Education
Program (NCEP), which advocates cholesterol testing
starting at age 20, and American Diabetes Association
(ADA) guidelines, which recommend screening for
diabetes starting at age 45.11,25 BMI was based on mea-
sured weight and height. BMI categories are consistent
with 1998 National Heart, Lung, and Blood Institute
guidelines, which classify obesity as a BMI ≥ 30.0.26
Definition of Disease
Because physician-diagnosed disease is dependent
on seeing a physician, only individuals with at least
one visit to a health care provider over the past year
were included in the analysis. Individuals who reported
never having been told by a health care provider that
they have a condition, but who have a laboratory or
examination result that is consistent with the condition,
are classified as having undiagnosed disease. We would
only expect physicians to diagnose disease based on
guidelines already in place prior to the survey, which
began in 1999. Thus, to remain consistent with the sam-
pling time frame, diagnostic criteria established after
1998 were not used. Undiagnosed obesity was identi-
fied in respondents having a BMI ≥ 30.026 who did not
report ever being told they were “overweight” or that
they should “lose weight.” A fasting plasma glucose
level >126 mg/dL was used to establish a diagnosis of
diabetes, which is consistent with the level proposed in
the 1997 ADA guidelines for use in epidemiologic stud-
ies.11 This approach, using one fasting plasma glucose
level, may actually lead to slightly lower estimates of
prevalence than would be obtained from the combined
use of fasting plasma glucose and an oral glucose tol-
erance test.27 Respondents who met the criteria were
defined as having undiagnosed diabetes if they did not
report ever being told by a health care provider they
had diabetes or sugar diabetes.
Undiagnosed hypercholesterolemia was defined as
those with total serum cholesterol >200 mg/dL who
did not report ever being told they had elevated choles-
terol. This classification is consistent with 1993 NCEP
guidelines.25 Undiagnosed hypertension was defined
based on an average of three blood pressure measure-
ments performed on the same day. Respondents with a
mean systolic blood pressure >140 mmHg or diastolic
blood pressure >90 mmHg who did not report ever be-
ing told they had hypertension or high blood pressure
were classified as having undiagnosed hypertension.
This classification standard is consistent with guide-
lines from the Sixth Report of the Joint National Com-
mittee on Prevention, Detection, Evaluation, and Treat-
ment of High Blood Pressure.18
Health care utilization was defined using the self-
reported number of outpatient visits over the prior year
to a health care provider. Education level was based on
the highest education level completed. General health
condition was self-reported, with respondents asked to
characterize their health as excellent, very good, good,
fair, or poor. We were not able to include income in our
analysis due to its withdrawal from the NHANES 1999–
2000 data set in March 2003 as a result of inconsisten-
cies in the data.
641 Vol. 36, No. 9
Because of the complex survey design used in the
NHANES 1999–2000, we accounted for the sampling
design and appropriate weights in the analysis using
SUDAAN (Research Triangle Institute, Research Tri-
angle Park, NC). This strategy allows for the computa-
tion of nationally representative estimates. Population
characteristics of obese adults were calculated. Sub-
group analysis on the prevalence of unrecognized obe-
sity was performed using a chi-square test for indepen-
dence. A logistic regression with undiagnosed obesity
as the dependent variable was performed. Forced in-
clusion of the predictor variables was used for this lo-
gistic regression model.
The demographic composition of the population of
obese adults is shown in Table 1. No analysis was per-
formed on the “other” racial category due to heteroge-
neity of the group and the small sample size, which
may not yield a reliable estimate.
The prevalence of undiagnosed disease in obese
adults is shown in Table 2. These prevalences repre-
sent undiagnosed disease in patients with an easily iden-
tifiable risk factor—obesity—that should lead to screen-
ing for these conditions. Further analysis shows a large
proportion of individuals with unrecognized hyperten-
sion, hypercholesterolemia, and diabetes have the ac-
knowledged risk factor of obesity. Among individuals
with unrecognized hypercholesterolemia, 28.4% were
obese. Similarly, among individuals with undiagnosed
hypertension and undiagnosed diabetes, 28.2% and
53.7%, respectively, were obese.
The prevalence of undiagnosed obesity stratified by
race/ethnicity is presented in Table 3. To account for
the possibility of differential health care utilization
based on race/ethnicity, the prevalences in Table 3 are
based on respondents who had at least one visit to a
health care provider over the last year, although diag-
nosis could have occurred at any time, not just over the
last year. Unadjusted relationships between race/
ethnicity and obesity that are initially significant drop
out when stratified by age and gender. There also ap-
pears to be an effect modification by gender, with
women being more likely to have significant differences
based on race/ethnicity, especially in the younger age
Results from a logistic regres-
sion using predictors for the diag-
nosis of obesity are shown in Table
4. As expected, BMI is an impor-
tant predictor, with respondents
with higher BMIs being more
likely to have diagnosed obesity.
Race and age were also important
predictors, with younger subjects
and blacks exhibiting a higher like-
lihood of having undiagnosed obe-
sity, even after controlling for other
variables. Respondents with worse
general health condition have a
lower prevalence of undiagnosed
obesity. There appeared to be no
effect based on health care utiliza-
tion, since there was no significant
difference in the diagnosis of dis-
ease for respondents with only one
visit when compared to those with
more than one visit over the last
Diagnosis of obesity in this study
was based on patient recollection.
It was defined as patients report-
ing that their health care provider
told them they were overweight or
advised them to lose weight. Many
factors, such as the perceived inef-
fectiveness of interventions, lack of
Clinical Research and Methods
Population Characteristics for Obese Adults
(Age ≥ 20, BMI ≥ 30) in the US Population*
Mean age (SD)
Mean BMI (SD)
BMI—body mass index
Prevalence of Unrecognized Disease in Obese Adults in the US Population
Female (%) 6,574,501
Total (%) 11,162,133
time, lack of reimbursement, and patient indifference,
may be associated with no or ineffective counseling,
leading to patients reporting that they were not identi-
fied as overweight by a physician. Either scenario can
emphasize groups at high risk for undiagnosed obesity
that need to be targeted for more aggressive counsel-
ing by physicians. Obtaining a current estimate is sig-
nificant since we expect there might be a change in the
prevalence of diagnosed obesity in comparison to pre-
vious studies due to the ongoing emphasis on weight
issues by the medical literature and media.
The diagnosis of obesity by health care providers is
also important due to the association of obesity with
diabetes, hypertension, and hypercholesterolemia. By
including only those respondents with a BMI ≥ 30, we
expected respondents would be easily identifiable as
obese by health care providers based on visual inspec-
tion and that this would lead to screening even if it did
not lead to extensive weight loss counseling. Instead
we found there was a significant prevalence of unrec-
ognized diabetes, hypertension, and hypercholester-
olemia in obese adults, ranging from 11.3% to 37.7%.
This is a large proportion considering that the presence
of an obvious risk factor
that should lead to screen-
ing and that these diseases
have considerable mor-
bidity and mortality pre-
ventable with early diag-
nosis and treatment. This
shows providers are miss-
ing opportunities to diag-
nose these treatable dis-
eases in obese patients.
This suggests it might be
warranted to decrease the
time interval between
screenings and start
screening at a younger age
in the obese population.
However, further evi-
dence is necessary before
can be made.
Results from the logis-
tic regression highlight
subgroups at higher risk of
having undiagnosed obe-
sity. Younger people will
obtain the most benefit
from weight reduction,
based on years of life re-
maining.3 Further, young
adults have had the great-
est increase in the preva-
lence of obesity in recent
Prevalence of Unrecognized Obesity
in US Adults with BMI ≥ 30
.006 Race total
Logistic Regression for Probability of Undiagnosed Obesity in Obese US Adults
OR95% CI Beta
Body mass index (kg/m2)0.819 (0.770–0.872)-0.200
Age Group (years)
Utilization (# of outpatient visits in previous year
General health condition
< high school
High school graduate
643Vol. 36, No. 9
years.28 Blacks, on the other hand, are also less likely
to be diagnosed as obese. Although many factors are
probably involved, this may be in part due to cultural
differences that lead to greater acceptance of obesity
by black patients as well as by their providers.29 As a
result, health care providers should emphasize cultur-
ally appropriate weight counseling for this subgroup to
overcome barriers to achieving a healthy weight. Fi-
nally, we see that obese patients with lower BMIs are
more likely to have undiagnosed obesity. It is in this
early stage of obesity where weight loss sufficient to
reach normal weight may seem more attainable, and
patients may thus be more receptive to weight loss
methods than if counseled once they are already far
above normal weight and suffering from weight-
associated conditions, such as osteoarthritis, that inter-
fere with exercise. Therefore, it is important to diag-
nose obesity early to institute appropriate interventions
sooner in an attempt to control the condition.
Several limitations must be considered when inter-
preting these results. First, due to the NHANES 1999–
2000 survey design based on one examination, our cri-
teria for the diagnosis of diabetes and hypercholester-
olemia are based on one blood measurement rather than
the more stringent definitions requiring follow-up mea-
Also due to the NHANES 1999–2000 design, our
criteria for hypertension diagnosis, although an aver-
age of three measurements, is based on measurements
taken on 1 day. This is the strategy the National Center
for Health Statistics uses to make population estimates,
which are reasonably valid and reliable.27,30,31 Results
based on this strategy are accepted throughout the re-
search community.32-35 While the use of this strategy is
unlikely to add a systematic bias to our results, it may
lead to some lack of precision.
Further, elevated cholesterol is a screening test that
should lead to further evaluation of LDL levels. We
did not use LDL to make population estimates in this
study since only one third of our sample had this test
done, and such a small sample size would lead to un-
stable population estimates.
We were not able to use income in this study due to
its withdrawal from the NHANES 1999–2000 at the
time of this analysis. We doubt this will affect our analy-
sis substantially, since a recent study shows that asso-
ciations with the prevalence of weight loss counseling
are not affected by adjustment for income.23 In addi-
tion, much of the effects of income may be due to dif-
ferences in access to care, which are controlled in our
study by a measure of health care utilization. Our re-
sults are based on self-reported data, which are prone
to recall bias. However, in this instance, using self-re-
port is valid since we are interested in the patients’
awareness of their condition, based on their interpreta-
tion of dialogue with their health care provider. Even if
the issue was discussed, if the patient has no recollec-
tion of it, it still signifies a need for further recognition
and counseling. Finally, a major strength of this study
is its use of a nationally representative sample from a
large database, which enables us to make estimates for
the US population.
Health care providers are missing valuable opportu-
nities to identify obesity and diagnose diabetes, hyper-
cholesterolemia, and hypertension in obese adults.
Emphasizing obesity as a risk factor for these condi-
tions, with further emphasis on screening the obese
population, is needed to improve health promotion.
Acknowledgments: This study was funded in part through grants
1D12HP00023-03 and 1D14HP00161-02 from the Health Resources and
Corresponding Author: Address correspondence to Dr Diaz, Medical Uni-
versity of South Carolina, Department of Family Medicine, 295 Calhoun
Street, PO Box 250192, Charleston, SC 29425. 843-792-3678. Fax: 843-
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