Prevalence of Obese Patients in a Primary Care Setting


  • Tracy Stecker,

    1. Division of Health Services Research, Department of Psychiatry, College of Medicine, University of Arkansas for Medical Sciences, Little Rock, Arkansas.
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  • Shane Sparks

    Corresponding author
    1. Division of Health Services Research, Department of Psychiatry, College of Medicine, University of Arkansas for Medical Sciences, Little Rock, Arkansas.
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VA HRS&D CeMHOR (152/NLR), 2200 Fort Roots Drive, North Little Rock, AR 72114. E-mail:


Objective: Previous research has addressed the relationship between BMI and chronic disease in primary care; however, little has been done with regard to the association between obesity and depression in primary care. The purpose of this paper is to assess the relationship between obesity and chronic conditions including depression.

Research Methods and Procedures: Data from primary care patients seen at a university-based family medicine clinic in the southeastern United States were extracted for the time between January 1, 1999 and January 1, 2002. Data extracted included most recent height and weight, age, ethnicity, pregnancy status, number of office visits, blood pressure, cholesterol, hemoglobin A1C, current diagnoses, and medications.

Results: A total of 8197 patients were included in the analysis. Sixty-nine percent of patients seen in a 3-year period were either overweight or obese. Comparing blood pressure, cholesterol, diagnoses, and medications between BMI groups found differences in virtually all categories. Diagnoses of high cholesterol, hypertension, diabetes, and depression significantly increased for obese patients.

Discussion: Obese patients are over-represented in primary care, and this over-representation of obesity correlates with several diagnoses, including depression. Depression is a chronic disease that may interfere with health-related behaviors and must be addressed within the health care system.


Obesity is a significant health problem in the United States and across the world. Obesity is defined as having a BMI ≥30 kg/m2 (1). The Centers for Disease Control have found a 21.0% incidence of obesity nationwide and a 22.4% incidence in Arkansas in 2001 (2). The National Health and Nutrition Examination Survey shows the rate of obesity among adults in the United States remained steady at 22.9% in 1988 to 1993 and increased thereafter to 30.5% in 2000 (3). This trend can also be seen in overweight Americans (BMI ≥ 25 kg/m2) as the percentage of overweight adults in the United States increased from 55.9% to 64.5% in the same time period (3). Overall, nearly two-thirds of the U.S. adult population is overweight at the current time (1,3). The health and economic benefits that can be gained from reducing the number of overweight and obese Americans are of substantial importance.

Obesity is an independent risk factor for many diseases, and a large number of adults are at an increased risk of morbidity and mortality because of being overweight or obese (4,5,6,7). Obesity has been associated with coronary heart disease, left ventricular hypertrophy, congestive heart failure, arrhythmia, and sudden death (4,5,6,7). It has also been linked to impaired glucose tolerance, which leads to type 2 diabetes, increased triglycerides, decreased high-density lipoprotein-cholesterol, gallstones, gastroesophageal reflux disease, and obstructive sleep apnea (4,8). Being overweight is associated with gallbladder disease, hypertension, and gradually increasing impairment of respiratory function (8). The American Cancer Society found that overweight men had increased rates of colorectal and prostate cancers, and overweight women had higher rates of endometrial, gallbladder, cervical, ovarian, and breast cancers.

There are also psychosocial problems associated with being overweight or obese, which are just as devastating as major medical comorbidities. Past research has shown a prejudice against obese persons independent of race, sex, age, or economic background. Children as young as 6 years old described silhouettes of an obese child in pejorative terms, using words such as “lazy,” “dirty,” “stupid,” “ugly,” “cheats,” and “lies.” When shown black and white line drawings of a child of normal weight, an obese child, and children with various handicaps (including missing hands and facial disfigurement), both children and adults rated drawings of the obese child as the least likable (9). Not surprisingly, many overweight people also have a negative self-image. One survey of overweight and obese patients receiving primary care treatment found a significantly lower health-related quality of life across physical, health perceptions, and vitality measures compared with non-overweight patients (10).

The economic impact of obesity has been drastically increasing. The Surgeon General estimated the cost of obesity in the United States to be about $117 billion in 2000, which was up from an estimated $70 billion in 1995 (11). Even though $117 billion or more is being spent each year on obesity, most cases are not even reported by primary care physicians. In 1996, physicians documented obesity in only 38% of their obese patients. Among visits by patients identified as obese, physicians frequently provided counseling for weight loss (35.5%), exercise (32.8%), and diet (41.5%). Patients with obesity-related comorbidities were treated more aggressively; weight loss counseling for these patients occurred in 52% of the total visits (12).

Overweight and obese patients have a higher rate of health care use than their normal-weight peers. A 1993 health care maintenance organization survey showed there was a clear association between BMI and annual rates of outpatient visits and inpatient days, annual cost of outpatient visits, and total cost of care (13). Despite the staggering health care costs of being overweight or obese, few studies have examined the prevalence of overweight and obesity in primary care clinics compared with the national incidence. A 1996 study in 19 Michigan primary care clinics found a much larger proportion of overweight and severely overweight patients visiting primary care practices. They suggested the prevalence of obesity in primary care practices may be much higher than rates estimated from population-based surveys (14). Since 1996, the prevalence of overweight and obesity has risen drastically, and new standard BMI designations have been implemented.

The purpose of this study is to assess the prevalence of overweight and obese individuals in one primary care setting. It is hypothesized that overweight and obese individuals are over-represented in primary care. It is further hypothesized that obesity is associated with a higher incidence of chronic conditions, specifically hyperlipidemia, hypertension, diabetes, and depression.

Research Methods and Procedures

Participants and Procedures

Data from January 1, 1999 to January 1, 2002 were extracted from an electronic medical record used by a university-based family medicine clinic. Data extracted included most recent height and weight, age, ethnicity, sex, pregnancy status, number of office visits, blood pressure, cholesterol, hemoglobin A1C, and current diagnoses and medications. The diagnoses were made by the clinician in routine practice, based on patient complaints and presentation rather than systematic screening. To be included in the analysis, the patient had to be over the age of 18, not pregnant, and have current height and weight information documented in the chart.

Data Analysis

Obesity prevalence was calculated and compared with national and state rates. Frequency data were calculated for BMI, chronic conditions, number of visits, and medications. BMI groups were computed based on BMI data. Individuals were classified as normal weight if they had a BMI <25 kg/m2. BMI was classified as overweight if BMI was between 25 and 29.9 kg/m2. BMI was classified as obese if BMI was >30 kg/m2. ANOVAs were run to compare BMI and diagnoses and to look at BMI and important diagnostic tests and clinical assessments.


A total of 8197 patients were included in the analysis. Sixty-five percent were women, ranging in age from 21 to 97 years, with a mean age of 45 years. Demographic information is included in Table 1.

Table 1. . Demographic information (N = 8197)
  • *

    Some patients’ ethnicity was listed as “unknown” or “other” in the electronic medical record.

SexSystolic blood pressure (mm Hg)
 Male 35% Range 77–240
 Female 65% Mean 128.92
Ethnicity*Diastolic blood pressure (mm Hg)
 White 53% Range 46–156
 Black 38% Mean 79.07
 Latino/a 1.7%Serum cholesterol (mg/dL)
 Asian 1.8% Range 53–750
Weight (kg) Mean 198.34
 Range 68–550High-density lipoprotein-cholesterol (mg/dL)
 Mean 182.69 
BMI (kg/m2) Range 15–507
 Range 14–77.8 Mean 52.07
 Mean 29.49Low-density lipoprotein-cholesterol (mg/dL)
Number of office visits 
 Range 1–155 Range 3–420
 Mean 9.37 Mean 118.07

As seen in Table 1, the mean BMI was 29.49 kg/m2. BMIs ranged from 14 to 77.8 kg/m2. Table 2 shows that 40% of patients were obese, with an additional 29% that were overweight. Overall, 69% of patients seen in this clinic in the 3-year time period met the BMI criteria for overweight (BMI 25 to 29.9 kg/m2) or obesity (BMI ≥30 kg/m2). Women had higher rates of obesity (p < 0.000), particularly African-American women, although men were more likely to be overweight.

Table 2. . BMI and sex
 WhiteAfrican AmericanWhiteAfrican AmericanTotal
  1. Some columns do not total 100% due to rounding.

Normal weight (BMI < 25 kg/m2)38%24%30%33%31%
Overweight (BMI 25 to 29.9 kg/m2)26%24%37%35%29%
Obese (BMI > 30 kg/m2)36%51%32%33%40%

Clinical differences in blood pressure, cholesterol, diagnoses, and medications between BMI groups (normal weight, overweight, obese) were assessed. Differences were found between obese patients and those of normal weight across virtually all categories (Table 3). Specifically, systolic and diastolic blood pressure, as well as total and low-density lipoprotein-cholesterol increased significantly as weight increased. The average number of visits for patients of normal weight was 8 vs. 12 for the obese patient. Diagnoses of high cholesterol, hypertension, diabetes, and depression were also significantly higher in obese patients, as was the use of medications. This was particularly true with cholesterol and hypertension medication, which increased from 5% for normal to 14% for obese patients and 9% for normal to 22% for obese patients, respectively.

Table 3. . Clinical mean differences seen between BMI groups
  1. Bold signifies significance at p < 0.01.

Systolic blood pressure123.33129.76133.51
Diastolic blood pressure75.8579.8081.78
Serum cholesterol193.61199.21200.07
High-density lipoprotein-cholesterol57.6051.2649.68
Low-density lipoprotein-cholesterol112.22119.24120.24
Number of visits8.449.4311.50
On cholesterol medication5%9%14%
On hypertension medication9%13%22%
On diabetic medication0%1%1%
On insulin medication0%0%1%


Obese patients were over-represented in this clinic. National prevalence rates of obesity indicate that ∼25% of the population in Arkansas is obese, yet 40% of our clinic population was found to meet diagnostic criteria for obesity. This over-representation of obesity correlates with diagnoses of hypertension, high cholesterol, diabetes, and depression, all of which were statistically and clinically significantly higher for obese patients (15,16). Future studies need to determine what these findings mean for the cost of care, the health care system, and provider time.

It is important to recognize depression and the relationship depression has with obesity and chronic medical conditions. Depression associated with medical conditions can have a substantial impact on symptoms and the severity of symptoms (17) and is associated with worse outcomes in individuals with comorbid medical conditions (18). This study describes how depression increases with BMI. Further work should occur to assess the relationship among depression, comorbid medical disease, and obesity.

This retrospective study was limited in that sampling occurred over a 3-year period in one primary care center. Results may not be generalizable to other primary care centers in the southeastern United States. It is important to recognize that this center treats a patient population that tends to have a lower socioeconomic status. Also, data on cost of care were not calculated. It can be assumed to be higher for obese individuals based on study data; however, more specific information is needed. It is also possible that obesity rates are higher than were indicated in this report because of difficulty in obtaining accurate weight information for the severely obese. Some of these patients are wheelchair-bound and are unable to be weighed, whereas others may refuse to have weight information assessed and recorded.


There was no funding/outside support for this study.