A comprehensive examination of health conditions associated with obesity in older adults

A comprehensive examination of health conditions associated with obesity in older adults

A Comprehensive Examination of Health Conditions Associated with Obesity in Older Adults Ruth E. Patterson, PhD, RD, Laura L. Frank, PhD, RD, Alan R. ...

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A Comprehensive Examination of Health Conditions Associated with Obesity in Older Adults Ruth E. Patterson, PhD, RD, Laura L. Frank, PhD, RD, Alan R. Kristal, DrPH, Emily White, PhD Background: Over 70% of older adults in the United States are overweight or obese. To examine the overall health burden of obesity in older adults, the Vitamins and Lifestyle cohort study of western Washington State recruited 73,003 adults aged 50 to 76 who completed a self-administered questionnaire on current height and weight, medical history, and risk factors. Methods:

Cross-sectional analysis of body mass index (BMI) and health conditions was performed using data collected in 2000 to 2002. Participants were categorized as normal weight, overweight, obese I, or obese II/III using BMI cut-points. Health conditions included 7 serious diseases, 2 conditions associated with cardiovascular disease risk, 23 medical conditions, and 11 health complaints. Odds ratios (ORs) from logistic regression models were used to examine associations of the four BMI categories with each health condition. Analyses were gender stratified and adjusted for age, education, race/ethnicity, and smoking status.

Results:

Among women, 34% were overweight, 16% in the obese I category, and 10% in obese categories II/III. Among men, 49% were overweight, 18% in the obese I category, and 6% in obese categories II/III. Overall, 37 of 41 conditions examined for women and 29 of 41 conditions examined for men were associated with increased levels of BMI (trend p ⬍0.05 for all models). For women and men, respectively, the highest ORs comparing obese II/III to normal weight were diabetes (OR⫽12.5 and 8.3), knee replacement (OR⫽11.7 and 6.1), and hypertension (OR⫽5.4 and 5.6). Obesity also increased the odds of several rare diseases such as pancreatitis (OR⫽1.9 and 1.5) and health complaints such as chronic fatigue (OR⫽3.7 and 3.5) and insomnia (OR⫽3.5 and 3.1).

Conclusions: A broad range of diseases and health complaints are associated with obesity. Clinicians should be aware of the diverse ways in which being overweight or obese may affect the health of their patients when counseling them about weight loss. (Am J Prev Med 2004;27(5):385–390) © 2004 American Journal of Preventive Medicine

Introduction

T

he proportion of older adults in the United States who are obese has doubled over the past 30 years.1 Results from the 1999 –2000 National Health and Nutrition Examination Survey (NHANES), using measured heights and weights, indicate that over 70% of men and women aged 55 to 74 were overweight or obese.2 It is well documented that obesity is associated with increased risk of many common chronic diseases including coronary heart disease, stroke, some cancers, and diabetes mellitus, as well as disease risk

From the Cancer Prevention Research Program, Fred Hutchinson Cancer Research Center (Patterson, Frank, Kristal, White), and Department of Epidemiology, School of Public Health and Community Medicine, University of Washington (Patterson, Kristal, White), Seattle, Washington Address correspondence and reprint requests to: Ruth E. Patterson, PhD, RD, Cancer Prevention Research Program, Fred Hutchinson Cancer Research Center, P.O. Box 19024, M4-B402, Seattle WA 981091024. E-mail: [email protected].

factors such as hypertension and dyslipidemia.3 There is also evidence linking obesity with osteoarthritis,4,5 gallstones,6 asthma,7 depression8,9 and sleep disorders.10 Few studies have reported on the association of obesity with rare conditions (e.g., congestive heart failure,11 pancreatitis12) or with health complaints (e.g. bladder infections, headaches, fatigue). Finally, the literature is very limited when examining the association of extreme obesity with uncommon diseases and health complaints. This report provides cross-sectional associations of body mass index (BMI) with 43 conditions, including serious diseases, cardiovascular risk factors, other diagnosed medical conditions, and health complaints, using data from the Vitamins and Lifestyle (VITAL) cohort study. Previous studies of obesity have focused on incidence or mortality of a specific disease or a small number of diseases. This report focuses on disease prevalence (or history), that is, the health burden of overweight or obese individuals. No other published

Am J Prev Med 2004;27(5) © 2004 American Journal of Preventive Medicine • Published by Elsevier Inc.

0749-3797/04/$–see front matter doi:10.1016/j.amepre.2004.08.001

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Table 1. Characteristics of women (n⫽37,005) and men (n⫽35,998) participating in the Vitamins and Lifestyle cohort study of western Washington State Characteristic Age (years) 50–59 60–69 ⱖ70 Race/ethnicity White Asian/Pacific Islander American Indian/Alaskan Black Hispanic Other Education (years) ⱕ12 13–15 ⱖ16 Current smokers BMI (kg/m2) Normal (18.5 to ⬍25.0) Overweight (25.0 to ⬍30.0) Obese I (30 to ⬍35) Obese II (35 to ⬍40) Obese III (ⱖ40)

Women % (nⴝ37,005)

Men % (nⴝ35,999)

47.6 33.4 19.0

45.2 35.9 18.9

93.3 2.6 1.5 1.2 0.9 0.5

93.4 2.3 1.5 1.3 0.8 0.7

23.3 41.6 35.2 7.7

15.8 34.9 49.3 8.6

40.3 34.0 15.7 6.2 3.9

27.3 49.0 17.8 4.5 1.5

Health Conditions

BMI, body mass index.

report has examined the association of overweight and obesity with such a wide range of health conditions.

Methods Recruitment and Baseline Data Collection Cohort recruitment and response rates. The VITAL study recruited men and women aged 50 to 76, who lived in a 13-county area in western Washington State. Using names purchased from a commercial mailing list, 364,418 baseline questionnaires were mailed, followed by a postcard reminder after 2 weeks. The cover letter described the study as being on supplement use and cancer risk, but not restricted to supplement users. Recruitment was conducted from October 2000 to December 2002, during which time 79,168 (21.7%) questionnaires were returned. Of these, 77,746 passed eligibility and questionnaire quality control checks. Data collection was accomplished using a 24-page, self-administered, genderspecific, optically scanned questionnaire that covered supplement use, diet, medical history, and risk factors. Data were also collected on demographic and health-related characteristics, including age, gender, education, race/ethnicity, and smoking. Details regarding the survey design and questionnaire have been published.13

Body Mass Index Height and weight were self-reported. BMI is defined as weight (in kilograms) divided by the square of height (in meters). BMI was categorized using cut-offs recommended by the National Heart, Lung, and Blood Institute Expert Panel14 and the World Health Organization Consultation on Obesity,15 which are given in Table 1. Because of small numbers, the upper

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categories of BMI (obese II/III) were combined for these analyses. The following people were excluded: 679 participants who were underweight (BMI⬍18.5) and 3864 participants with missing or implausible height, weight, or BMI.

Forty-three health conditions based on self-report (see Tables 2 and 3 for complete list) were examined in these analyses. These conditions were grouped into four categories: 7 serious diseases such as stroke and cancer, 2 asymptomatic health conditions associated with cardiovascular disease risk, 23 physician-diagnosed medical conditions such as ulcers and osteoarthritis, and 11 health complaints such as chronic headaches and fatigue. In most cases, participants simply marked whether they had the condition. Additional details regarding data collection are given below. Coronary artery disease was defined as self-report of any of the following: heart attack, coronary bypass surgery, angioplasty, or physician-diagnosed angina. History of cancer did not include nonmelanoma skin cancer. The cardiovascular disease risk factors were hypercholesterolemia, based on current use of cholesterol-lowering medications, and hypertension, based on use of blood pressure–lowering medications. Physician-diagnosed medical conditions included selfreport of conditions diagnosed by a physician (e.g., ulcers); currently being treated with prescription medications (e.g., diabetes); or conditions for which there has been a medical procedure (e.g., gallbladder removal). Only women were asked whether they had multiple (five or more) bladder infections or multiple (three or more) yeast infections. Only men were asked whether they had enlarged prostate (not including cancer) or impotence. Health complaints were defined as symptoms or conditions that participants experienced for at least half the days of the past year or were treating, including chronic neck, back, or joint pain (excluding arthritis); indigestion or heartburn (excluding gastroesophageal reflux disease); feeling depressed or anxious (excluding taking medication for depression); and fatigue or lack of energy. Frequent headaches (excluding migraines) were defined as two or more per week in the last year. Constipation was defined as use of laxatives once per week or more. Stress was classified as reporting high levels of stress in life combined with poor ability to handle stress (both scoring five or higher on a six-point scale). Insomnia was considered any sleeping problems (trouble falling asleep, waking at night, or waking too early), and not rested or excessively sleepy during the day for more than half of the days in the past year.16 After excluding 200 participants with missing medical conditions information, a total of 73,003 participants remained in the sample.

Data Analysis Odds ratios from separate logistic regression models were used to examine associations of the four BMI categories with health conditions treated as dichotomous variables. All analyses were gender-stratified and adjusted for age (50 to 59, 60 to 69, ⱖ70); education (ⱕ12, 13 to 15, ⱖ16 years); race/ethnicity (white,

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Table 2. Associations of BMI with health conditions among 37,005 women participants in Vitamins and Lifestyle cohort study of western Washington State (odds ratios adjusted for age, race/ethnicity, education, and smoking status) Odds ratio of BMI (kg/m2) categoriesa with health conditions Health condition History of serious diseases Coronary artery diseasec Congestive heart failure Stroke Emphysema, chronic bronchitis, or obstructive pulmonary disease Pulmonary embolism Deep vein thrombosis History of cancer (excluding nonmelanoma skin cancer) Cardiovascular disease risk factorsd Hypercholesterolemia Hypertension Physician-diagnosed medical conditions Depressiond Migraine headaches Macular degeneration Cataract removal Glaucoma Asthma Gingivitis Gastroesophageal reflux disease Ulcers Ulcerative colitis Diabetes Gallbladder removal Multiple bladder infections Multiple yeast infections Pancreatitis Kidney stones Kidney disease Viral hepatitis Osteoarthritis Knee replacement Health complaints Hip replacement Osteoporotic fracture (broken hip, wrist, or forearm after age 50) Neck, back, or joint paine,f Frequent headachesg Stress Fatigue/lack of energye Chronic insomnia Feeling depressed/anxiouse,h Indigestion or heartburne,i Frequent constipation Skin problems Allergies to plants, molds, trees, dust, or animals

Normal

Overweight

Obese I

Obese II/III

p for trend

5.1 1.4 2.1 3.9

1.0 1.0 1.0 1.0

1.4 1.5 1.3 1.0

2.1 2.5 1.4 1.5

2.7 5.6 1.8 2.0

<0.001 <0.001 <0.001 <0.001

0.9 3.5 16.1

1.0 1.0 1.0

1.6 1.4 1.0

2.2 1.9 1.1

4.3 2.7 1.1

<0.001 <0.001 <0.01

14.8 32.1

1.0 1.0

1.9 1.9

2.6 3.3

2.5 5.4

<0.001 <0.001

14.5 16.0 1.8 7.0 3.0 11.4 6.2 14.7 8.5 1.5 5.8 15.1 10.9 13.3 1.0 4.4 1.1 2.8 38.9 2.2

1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0

1.4 1.1 1.4 1.0 1.0 1.5 1.2 1.7 1.1 1.1 2.3 1.8 1.1 1.1 1.3 1.2 1.1 0.9 1.3 2.3

1.7 1.2 1.3 1.1 1.1 1.9 1.4 2.4 1.4 1.0 5.2 3.1 1.1 1.2 1.2 1.6 1.2 0.9 1.7 5.4

2.3 1.1 1.8 1.3 1.5 2.7 1.3 2.6 1.5 1.0 12.5 4.9 1.3 1.4 1.9 1.8 1.9 1.2 2.4 11.7

<0.001 <0.01 <0.001 <0.05 <0.001 <0.001 <0.001 <0.001 <0.001 NS <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 NS <0.001 <0.001

1.8 4.4

1.0 1.0

1.2 0.9

1.4 0.8

1.7 0.7

<0.001 <0.001

27.4 6.8 6.9 22.7 23.4 7.7 9.5 4.3 9.8 37.3

1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0

1.3 1.1 1.1 1.5 1.5 1.1 1.7 0.8 1.2 1.1

1.4 1.2 1.3 2.3 2.2 1.4 2.3 0.7 1.4 1.2

1.8 1.2 1.6 3.7 3.5 1.7 2.4 0.6 2.0 1.2

<0.001 <0.01 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001

%

BMI, body mass index; NS, not significant. a Percent sample in BMI categories: 40.3 normal (BMI 18.5⬍25), 34.0 overweight (BMI 25⬍30), 15.7 obese I (BMI 30⬍35), and 10.1 obese II/III (BMIⱖ35). b Significant p trend bolded. c Heart attack, coronary bypass surgery, angioplasty, or angina. d Defined as taking medication for the condition. e At least half the days of the past year. f Excluding women with osteoarthritis. g Excluding women with migraines. h Excluding women taking medication for depression. i Excluding women with gastroesophageal reflux disease.

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Table 3. Associations of BMI and health conditions among 35,998 men participants in Vitamins and Lifestyle cohort study of western Washington State (odds ratios adjusted for age, race/ethnicity, education, and smoking status) Odds ratio of BMI (kg/m2) categoriesa with health conditions Health condition History of serious diseases Coronary artery diseasec Congestive heart failure Stroke Emphysema, chronic bronchitis, or obstructive pulmonary disease Pulmonary embolism Deep vein thrombosis History of cancer (not including nonmelanoma skin cancer) Cardiovascular disease risk factorsd Hypercholesterolemia Hypertension Physician-diagnosed medical conditions Depressiond Migraine headaches Macular degeneration Cataract removal Glaucoma Asthma Gingivitis Gastroesophageal reflux disease Ulcers Ulcerative colitis Diabetes Gallbladder removal Enlarged prostate (not including prostate cancer) Pancreatitis Kidney stones Kidney disease Viral hepatitis Osteoarthritis Health complaints Knee replacement Hip replacement Osteoporotic fracture (broken hip, wrist, or forearm after age 50) Neck, back or joint paine,f Frequent headachesg Stress Fatigue/lack of energye Feeling depressed/anxiouse,h Chronic insomnia Indigestion or heartburne,i Frequent constipation Impotence Skin problems Allergies to plants, molds, trees, dust, or animals

%

Normal

Overweight

Obese I

Obese II/III

p for trendb

13.4 2.1 2.8 3.3

1.0 1.0 1.0 1.0

1.1 1.1 0.9 0.7

1.6 1.8 1.1 0.9

1.7 3.9 1.2 1.6

<0.001 <0.001 NS <0.05

0.7 2.1 12.4

1.0 1.0 1.0

1.6 1.3 1.0

2.7 1.7 1.0

3.1 2.6 1.0

<0.001 <0.001 NS

25.7 33.5

1.0 1.0

1.5 1.8

1.9 3.4

2.0 5.6

<0.001 <0.001

6.6 4.6 1.4 6.0 3.1 8.1 5.6 12.5 9.7 1.1 8.0 4.8 16.0

1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0

1.0 0.9 1.0 1.0 1.1 0.9 1.0 1.3 1.0 1.0 1.6 1.3 0.9

1.2 0.9 1.2 1.2 1.2 1.0 1.2 1.5 1.0 1.0 3.8 2.1 0.8

2.0 0.9 1.3 1.2 1.5 1.4 1.2 1.6 1.2 1.4 8.3 2.9 0.8

<0.001 NS NS <0.05 <0.01 <0.05 <0.01 <0.001 NS NS <0.001 <0.001 <0.001

0.7 10.2 1.0 3.4 25.7

1.0 1.0 1.0 1.0 1.0

1.1 1.1 1.0 0.9 1.2

1.6 1.3 1.0 0.9 1.6

1.5 1.3 1.2 1.1 1.9

<0.05 <0.001 NS NS <0.001

1.8 1.7 2.5

1.0 1.0 1.0

2.1 1.1 0.9

3.7 1.8 1.0

6.1 2.8 1.0

<0.001 <0.001 NS

23.7 4.5 4.0 14.2 5.8 17.4 8.5 1.6 28.1 10.4 29.9

1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0

1.1 1.0 1.0 1.1 1.1 1.2 1.3 0.9 1.3 1.0 0.9

1.3 1.1 1.2 1.8 1.2 1.8 1.6 0.9 1.8 1.3 1.0

1.5 1.6 1.9 3.5 1.6 3.1 1.5 1.1 2.3 1.6 1.0

<0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 NS <0.001 <0.001 NS

BMI, body mass index; NS, not significant. a Percent sample in BMI categories: 27.3 normal (BMI 16.5⬍25), 49.0 overweight (BMI 25⬍30), 17.8 obese I (BMI 30⬍35), and 6.0 obese II/III (BMIⱖ35). b Significant p trend bolded. c Heart attack, coronary bypass surgery, angioplasty, or angina. d Defined as taking medication for the condition. e At least half the days of the past year. f Excluding men with osteoarthritis. g Excluding men with migraines. h Excluding men taking medication for depression. i Excluding men with gastroesophageal reflux disease.

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Asian/Pacific Islander, American Indian/Alaskan, black, Hispanic, or other); and smoking status (current or nonsmoker). The association of BMI with health conditions was assessed by a test for trend, using the logistic regression analogue to the Mantel extension test (i.e., a test based on the significance of a single trend variable coded as the category of exposure). All analyses were performed using SAS 8.0 (SAS Institute Inc., Cary NC, 2001).

Results Characteristics of the participants (n ⫽73,003) are shown in Table 1. Mean age was 61.8 years for women and 62.0 years for men. The sample was 93% white and education levels were high, with 42% of the sample completing ⱖ16 years of education. Smoking rates were very low (less than 10%). Among women, 59.7% were overweight or obese, and among men, 72.7 % were overweight or obese. Tables 2 and 3 give results of logistic regression models assessing the associations of BMI categories (normal, overweight, obese I and obese II/III) with each health condition for women and men. For women, there were statistically significant (p ⬍0.05) trends of increased prevalence of the health condition associated with higher BMI for 37 of the 41 health conditions examined. The strongest associations (odds ratio [OR]⬎3 for obese category II/III compared to normal weight) were for diabetes (OR⫽12.5), knee replacement (OR⫽11.7), history of congestive heart failure (OR⫽5.6), hypertension (OR⫽5.4), gallbladder removal (OR⫽4.9), pulmonary embolism (OR⫽4.3), chronic fatigue/lack of energy (OR⫽3.7), and insomnia (OR⫽3.5). There were significant, although modest, inverse associations for osteoporotic fractures and constipation. For men, of the 41 health conditions examined, 29 were associated with increasing levels of obesity (p ⬍ for trend, ⬍0.05). The strongest associations (for obese category II/III) were for diabetes (OR⫽8.3), knee replacement (OR⫽6.1), hypertension (OR⫽5.6), congestive heart failure (OR⫽3.9), fatigue/ lack of energy (OR⫽3.5), pulmonary embolism (OR⫽3.1), and insomnia (OR⫽3.1). There was a modest significant inverse association with enlarged prostate.

Comment Of the conditions examined, 90% were associated with increased BMI in women and 71% in men. The high proportion of positive associations is especially interesting in that the health conditions were selected to characterize the health status of the cohort and predict future morbidity and mortality, and not because of hypothesized associations with obesity.

It is interesting that more associations of obesity with health conditions were found among women than men. There are two potential explanations for this finding. It is possible that this represents a real gender difference. That is, obesity may actually present a greater health burden in women than men. However, it is also conceivable that women are more likely to report obesity and health conditions than men, either because they are more accurate reporters, or because of other psychosocial factors, such as low self-esteem. Additional studies on gender differences of the health impacts of obesity are needed to address this question. Few studies have assessed the health burden of obesity across multiple conditions. In the 1994 Canadian National Population Health Survey, Cairney et al.17 examined the relationship of BMI to nine conditions and found positive associations for heart disease, respiratory problems, stroke, hypertension, diabetes, stomach problems, and arthritis (but not cancer or migraines). In the United States, similar findings were reported using NHANES data (for six conditions)18 and Behavioral Risk Factor Surveillance System data (for five conditions).19 At the 10-year follow-up of the Nurses Health Study and the Health Professional Study, researchers found statistically significant associations of BMI with risk of developing diabetes, gallstones, hypertension, heart disease, colon cancer and stroke in men (but not high cholesterol levels).20 The latter study was of disease incidence, so certain results might differ (e.g., stroke in men) from studies on disease burden (prevalence), if obesity both increases incidence and decreases survival. There are several considerations regarding interpretation of the data presented here. Principally, this is a cross-sectional analysis, so the direction of effect cannot be discerned. For conditions without symptoms (e.g., high blood pressure), it is probable that BMI is causally related to the health condition. However other associations are likely circular in nature. For example, depression may result in weight gain, which can lead to depression.21 Either direction of effect illustrates the burden of obesity. It is also important to note that physical activity levels were not controlled for in these analyses. Obesity may result in reduced physical activity, which would exert independent effects on many of these health conditions. However, the objective of this manuscript was to characterize the health burden of obesity regardless of the mechanism of effect. Another consideration is that VITAL participants were selected by their willingness to join a cohort study and are primarily Caucasian and well educated. Smoking was less common in the study cohort (8.1%) than in Washington State (15.7% for people aged 55 to 64 in 2001), although the proportions of the cohort who were overweight and obese were fairly similar to the state (41.5% overweight and 24.8% obese in the cohort vs 34.5% and 27.1% for people aged 55 to 64 in Washington State in 2001).22 Nonetheless, the volunteer nature of this sample should not bias the magnitude of the associations between BMI Am J Prev Med 2004;27(5)

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What This Study Adds . . . Obesity increases the risk of many common chronic diseases and risk factors. This report assesses the overall health burden of obesity by examining its association with a wide range of health conditions. Thirty-seven of 41 conditions for women and 29 of 41 conditions for men were significantly associated with increased levels of BMI. These data add support that obesity has the potential to be the most serious public health threat faced by the United States.

and health conditions except if study participation was jointly related to BMI and certain health conditions. All the data in the study are based on self-reporting. In particular, self-reported height is likely to be somewhat over-estimated while weight is under-estimated.23 However, correlations of self-report with measured height and weight are high.24 In addition, information on medical conditions was from self-report and not verified by medical records. Therefore for certain conditions that have variable definitions (e.g., diabetes), use of prescription drugs or medical procedures rather than simple self-report of a diagnosis was relied upon. Nonetheless, participants with some conditions were misclassified because they were not aware that they had the condition or were not taking medication. No other study has provided data on the association of BMI with such a compendium of health conditions. As documented here, obesity is associated with many serious diseases that may be life threatening (e.g., congestive heart failure); common conditions that increase risk of more serious diseases (e.g., hypertension); rare conditions (e.g., pancreatitis); and health complaints that can reduce quality of life (e.g., chronic fatigue). Clinicians should be aware of the diverse ways in which being overweight or obese may impact their patients when counseling them about weight loss. From a population-based perspective, the epidemic levels of overweight and obesity seen in the United States, combined with the associated health burden, suggest that obesity has the potential to be the most serious public health threat faced by this nation. Identification of effective and practical public health approaches to preventing weight gain and treating obesity are urgently needed. This study was supported by the National Cancer Institute (grant R01 CA74846).

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References 1. Flegal KM, Carroll MD, Kuczmarski RJ, Johnson CL. Overweight and obesity in the United States: prevalence and trends, 1960 –1994. Int J Obes Relat Metab Disord 1998;22:39 – 47. 2. National Center of Health Statistics. Prevalence of overweight and obesity among adults: United States, 1999 –2000. Centers for Disease Control and Prevention, May 4, 2004. Available at: www.cdc.gov/nchs/products/pubs/ pubd/hestats/obese/obse99.htm#Table%201. Accessed April, 2004. 3. National Task Force on the Prevention and Treatment of Obesity. Overweight, obesity, and health risk. Arch Intern Med 2000;160:898 –904. 4. Anderson JJ, Felson DT. Factors associated with osteoarthritis of the knee in the first national Health and Nutrition Examination Survey (HANES I). Evidence for an association with overweight, race, and physical demands of work. Am J Epidemiol 1988;128:179 – 89. 5. Felson DT, Lawrence RC, Dieppe PA, et al. Osteoarthritis: new insights. Part 1: the disease and its risk factors. Ann Intern Med 2000;133:635– 46. 6. Stampfer MJ, Maclure KM, Colditz GA, Manson JE, Willett WC. Risk of symptomatic gallstones in women with severe obesity. Am J Clin Nutr 1992;55:652– 8. 7. Redd SC, Mokdad AH. Invited commentary: obesity and asthma—new perspectives, research needs, and implications for control programs. Am J Epidemiol 2002;155:198 –202 (comment). 8. Blazer DG, Moody-Ayers S, Craft-Morgan J, Burchett B. Depression in diabetes and obesity: racial/ethnic/gender issues in older adults. J Psychosom Res 2002;53:913– 6. 9. Faith MS, Matz PE, Jorge MA. Obesity-depression associations in the population. J Psychosom Res 2002;53:935– 42. 10. Peppard PE, Young T, Palta M, Dempsey J, Skatrud J. Longitudinal study of moderate weight change and sleep-disordered breathing. JAMA 2000;284:3015–21. 11. Kaltman AJ, Goldring RM. Role of circulatory congestion in the cardiorespiratory failure of obesity. Am J Med 1976;60:645–53. 12. Torgerson JS, Lindroos AK, Naslund I, Peltonen M. Gallstones, gallbladder disease, and pancreatitis: cross-sectional and 2-year data from the Swedish Obese Subjects (SOS) and SOS reference studies. Am J Gastroenterol 2003;98:1032– 41. 13. White E, Patterson RE, Kristal AR, et al. The Vitamins and Lifestyle (VITAL) Cohort Study: study design and characteristics of supplement users. Am J Epidemiol 2004;159:83–93. 14. Expert Panel on the Identification Evaluation and Treatment of Overweight in Adults. Clinical guidelines on the identification, evaluation, and treatment of overweight and obesity in adults: executive summary. Am J Clin Nutr 1998;68:899 –917. 15. World Health Organization. Report of a WHO consultation on obesity. Obesity: Preventing and managing the global epidemic. Geneva: World Health Organization, 1998. 16. National Center on Sleep Disorders Research. Insomnia: assessment and management in primary care. Bethesda MD: U.S. Department of Health and Human Services, National Institutes of Health, National Heart, Lung, and Blood Institute, 1998 (NIH Pub 98-4088). 17. Cairney J, Wade TJ. Correlates of body weight in the 1994 National Population Health Survey. Int J Obes Relat Metab Disord 1998;22:584 –91. 18. Must A, Spadano J, Coakley EH, Field AE, Colditz G, Dietz WH. The disease burden associated with overweight and obesity. JAMA 1999;282:1523–9. 19. Mokdad AH, Ford ES, Bowman BA, et al. Prevalence of obesity, diabetes, and obesity-related health risk factors, 2001. JAMA 2003;289:76 –9. 20. Field AE, Coakley EH, Must A, et al. Impact of overweight on the risk of developing common chronic diseases during a 10-year period. Arch Intern Med 2001;161:1581– 6. 21. Cohen JH, Kristal AR, Neumark-Sztainaer D, Rock CL, Neuhouser ML. Psychological distress is associated with unhealthful dietary practices. J Am Diet Assoc 2002;102:699 –703. 22. Ahluwalia IB, Mack KA, Murphy W, Mokdad AH, Bales VS. State-specific prevalence of selected chronic disease-related characteristics—Behavioral Risk Factor Surveillance System, 2001. Centers for Disease Control and Prevention, August 13, 2003. Available at: www.cdd.gov/mmwr/preview/ mmwrhtml/ss5208al.htm. Accessed April, 2004. 23. Stewart AW, Jackson RT, Ford MA, Beaglehole R. Underestimation of relative weight by use of self-reported height and weight. Am J Epidemiol 1987;125:122– 6. 24. Kuczmarski MF, Kuczmarski RJ, Najjar M. Effects of age on validity of self-reported height, weight, and body mass index: findings from the Third National Health and Nutrition Examination Survey, 1988 –1994. J Am Diet Assoc 2001;101:28 –34, 35– 6.

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