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McTigue K, Harris R, Hemphill MB, et al. Screening and Interventions for Overweight and Obesity in Adults [Internet]. Rockville (MD): Agency for Healthcare Research and Quality (US); 2003 Dec. (Systematic Evidence Reviews, No. 21.)

  • This publication is provided for historical reference only and the information may be out of date.

This publication is provided for historical reference only and the information may be out of date.

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Screening and Interventions for Overweight and Obesity in Adults [Internet].

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Obesity, a condition characterized by excess body fat, carries significant health implications for both chronic disease and mortality. In the setting of escalating prevalence, the importance of obesity as a health problem in the United States is increasingly evident - as emphasized by the recent Surgeon General's “Call to Action to Prevent and Decrease Overweight and Obesity.”1

Obesity is usually defined in terms of the body mass index (BMI, calculated by dividing kilograms of weight by meters of height squared), which is a measure of weight adjusted for height. Although numerous techniques are available for evaluating body fat, the variables for BMI are easy to measure. BMI has been shown to correlate closely with body fat content in adults and children.2

Adults with a BMI of 25 to 29.9 are identified as overweight and those with a BMI ≥ 30 as obese. These cutoffs are based on epidemiologic evidence of discernible, then substantial, increases in mortality.3 For example, if a 5'6" women weighs 155 pounds, her BMI is 25 (overweight); if she weighs 186 pounds, her BMI is 30 (obese). BMI calculations can be tedious, so electronic BMI calculators (eg, from the National Institutes of Health [NIH], or tables of BMI by height and weight (eg, from NIH, may be useful tools for clinicians and patients. Waist circumference and the waist-to-hip ratio are common adjuvant measures used to classify the distribution of body fat in people who are overweight, as obesity-related complications are most closely correlated with abdominal fat distribution.4–6

The prevalence of obesity is increasing. Data from the National Center for Health Statistics show that, over the past 40 years, obesity prevalence increased from 13% to 27% of the U.S. adult population; the prevalence of the less severe overweight category increased from 31% to 34%.7, 8 Concurrently, a rise in prevalence of obesity has been noted in adolescent and pediatric populations.9, 10 Self-report data from the Behavioral Risk Factor Surveillance Survey (BRFSS) show the increase in prevalence continuing into the year 2000.11

Obesity prevalence is higher in women; overweight is more common in men.7 Obesity is especially common in certain minority ethnic groups, including African Americans, some Hispanic populations, Native Americans, and Native Hawaiians.

All classes of excess body weight have substantial prevalence among U.S. adults. In the National Health and Nutrition Examination Survey III (NHANES III, 1988-1994), the prevalence of BMI 25 to 29.9 was 44% for people ages 55 years and older and 41% for people ages 25 to 54.9 years.12, 13 For these older (55 years of age and older) and younger (25–54.9 years) groups, the prevalence of BMI 30 to 34.9 was 18% and 14%, respectively. The prevalence of BMI 35 to 39.9 was 4% and 3%, respectively, and for BMI 40 or above, 1% and 2%.

Obesity is a risk factor for major causes of death, including cardiovascular disease, some cancers, and diabetes. Obesity has also been linked with many sources of morbidity, including osteoarthritis, gall bladder disease, sleep apnea, and respiratory impairment. Excess weight is a risk factor for cancers of the colon, rectum, prostate, gall bladder, biliary tract, breast, cervix, endometrium, and ovary.2 It is associated with concerns of quality of life, including diminished mobility and social stigmatization.14

Most studies have found that mortality assumes a J-shaped or U-shaped relationship with BMI, with elevated risk at low BMI being attributable, at least in part, to the effect of smoking or concurrent disease. The BMI associated with the lowest risk varies among studies and populations. For example, in our review of cohort studies with at least 10 years of follow-up data,15–26 the BMI range associated with the lowest overall mortality risk was generally within the “normal” BMI range for men, but in the normal-to-overweight range for women (Table 1).

Table 1. Ranges of Body Mass Index with Minimal Absolute Risk for Mortality in Men and Women.


Table 1. Ranges of Body Mass Index with Minimal Absolute Risk for Mortality in Men and Women.

Risk associated with specific morbidity tends to increase more linearly with BMI than the risk associated with total mortality. This trend has been demonstrated most frequently for cardiovascular disorders, so we focus on those health outcomes in this systematic evidence review (SER). In a study of a British cohort of men, the incidence of major coronary events was 9.1 per 1,000 person-years for those with a baseline BMI of 24 to 25.9.18 By contrast, coronary heart disease incidence in Framingham heart participants was 18 per 1,000 person-years for men with a baseline BMI of 23.8 to 25.9.27 In both these cohorts, and in a third from Sweden,24 cardiovascular risk generally increased with increasing baseline BMI for men (Figure 1). A similar rise in cardiovascular health risk is seen with increasing baseline BMI in cohort studies of women (Figure 2).

Figure 1. Cardiovascular Morbidity in Men.


Figure 1. Cardiovascular Morbidity in Men.

Figure 2. Cardiovascular Morbidity in Women.


Figure 2. Cardiovascular Morbidity in Women.

Excess body weight has been linked to increased mortality for patients up to 74 years in age. The risk lessens with age:28 however, the relationship between weight and health risk is unclear beyond that point.3, 29

The association between obesity and health outcomes may vary by ethnic group. Figures 3 and 4 present data from 2 long (>10 year) cohort studies that reported data on more than 1 racial group.22, 23 These studies suggested that the association between excess body weight and mortality may be weaker for black populations than for white. One review of these and other studies found that only tentative conclusions could be reached about mortality at elevated levels of BMI in black men, with the best evidence showing only modest increases in risk.30 Likewise, the BMI-mortality association appears weaker in black women than in white women. These ethnic-specific studies assessed only all-cause mortality, not disease-specific mortality or morbidity. Evidence about obesity and other outcomes for black populations and about the association of obesity and health outcomes in general in other ethnic groups is insufficient to draw conclusions.

Figure 3. All-cause Mortality in Men: Studies with Race Differentials.


Figure 3. All-cause Mortality in Men: Studies with Race Differentials.

Figure 4. All-cause Mortality in Women: Studies with Race Differentials.


Figure 4. All-cause Mortality in Women: Studies with Race Differentials.

Weight cycling - cycles of weight loss followed by weight regain - potentially carries health risk, but the relationship has not been clearly established. Weight cycling has been linked with increases of mortality;31–34 this association is not, however, found consistently,35 and these studies do not distinguish between intentional and unintentional weight loss. The evidence is mixed about the relationship between weight cycling associated with intentional weight loss (on the one hand) and coronary artery disease risk factors (on the other). One observational study showed 7% lower high-density lipoprotein (HDL) cholesterol levels among women with coronary risk factors,36 and another showed a 4-fold increased risk of hypertension (odds ratio [OR], 4.1; confidence interval [CI], 2.4–6.9) in Italian women.37 However, in 46,224 women of the Nurses Health Study II, adjusting for BMI and weight gain, mild or severe weight cycling was not associated with increased risk of hypertension incidence.38 Likewise, in a large cohort of men, those who weight cycled did not have smaller improvements in total cholesterol, HDL, or blood pressure compared with noncyclers.39 The psychological impact of weight cycling is also unclear: weight fluctuation has been linked with covert hostility40 in one study and not associated with measures of depression, stress, anxiety, and anger in another.41

Cost of Obesity and Overweight

Financially, obesity incurs substantial cost. Recent analyses estimate that direct costs of obesity are 5.7% of total U.S. health expenditures42 and 2.4% of the total health care budget of Canada.43 A U.S.-based study looking at the impact of obesity on the cost of expected lifetime medical care on 5 diseases (hypertension, hypercholesterolemia, diabetes mellitus, coronary heart disease, and stroke) found that costs increased by 20% with mild obesity, by 50% with moderate obesity, and nearly 200% with severe obesity.44

At least 2 types of interventions might be considered for reducing the burden of suffering from obesity: public health measures for the population at large or screening and intervention in the individual patient's clinical encounter. This systematic evidence review considers the question of efficacy and effectiveness of screening and intervention in the clinical setting.

Some might ask why the issue of screening for obesity arises at all, as the diagnosis of obesity may seem obvious. Clinicians, however, frequently do not address the issue of obesity with obese patients. In a large national study of adults with a BMI of 30 or greater, for example, only 42% reported that their health care professional advised them to lose weight.45 Thus, by screening we refer here to the conscious measurement of BMI by the clinician, with the purpose of addressing body weight in the clinical setting.

Obesity is a difficult problem to treat. This difficulty is the main concern that led prior systematic reviews to have reservations about screening for obesity. Our SER focuses primarily on the efficacy of potential interventions that might be initiated within the clinical setting. These interventions include counseling and behavioral therapy for calorie reduction and increasing physical activity, pharmacotherapy, and surgical approaches.

Prior Recommendations about Obesity Screening

In 1996, the U.S. Preventive Services Task Force (USPSTF) recommended periodic measurement of height and weight for all patients.2 Since then, 3 large systematic reviews have examined screening for obesity; they are evidence reports from National Institutes of Health (NIH),3 the Canadian Task Force on Preventive Health Care,46and the University of York for the UK National Health Service (NHS).47

Although all 3 reviews promoted clinical attention to obesity, their specific recommendations varied. Since their completion, the prevalence of obesity has continued to climb precipitously, new medications have become available, and more studies have addressed the role of weight loss on health outcomes. To assist the USPSTF in updating its recommendation, the RTI-UNC Evidence-based Practice Center undertook a systematic review of the evidence concerning screening for obesity. In our analysis, we combined the findings of the prior reviews with an assessment of more recent or not previously covered studies of fair to good quality.

In our SER, we address screening for adult populations. Obesity in childhood and adolescence is a significant and compelling issue that requires an evidence review dedicated to that age group.9, 10 The USPSTF regards the issue as sufficiently important that it expects to review screening for obesity in children and adolescents separately in the future.

Organization of This Review

Chapter 2 of the SER documents our methods. Results appear in Chapter 3; Chapter 4 discusses the implications of our findings and offers suggestions about future research. Figures and tables are found at the end of chapters where they are first called out.Appendix A acknowledges the assistance of USPSTF liaisons to this project, the work of EPC staff, and the helpful comments from external peer reviewers. Evidence tables are presented in Appendix B.


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