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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
Arthritis Care Res (Hoboken). Author manuscript; available in PMC 2014 January 1.
Published in final edited form as:
PMCID: PMC3482278

Body Mass Index, Obesity, and Prevalent Gout in the United States in 1988–1994 and 2007–2010

Stephen P. Juraschek, BA,1,2 Edgar R. Miller, III, MD, PhD,1,2,3 and Allan C. Gelber, MD, MPH, PhD1,2,3



To determine the association and prevalence of gout among overweight, obese and morbidly obese segments of the US population.


Among participants (age 20 and older) of the National Health and Nutrition Examination Surveys, in 1988–1994 and 2007–2010, gout status was ascertained by self-report of a physician-diagnosis. BMI was examined in categories of <18.5, 18.5–24.9, 25–29.9, 30–34.9, and ≥35 kg/m2 and as a continuous variable. The cross-sectional association of BMI category with gout status was adjusted for demographic and obesity-related medical disorders.


In the US, the crude prevalence of gout was 1–2% among participants with a normal BMI (18.5–24.9 kg/2), 3% among overweight participants, 4–5% with class I obesity, and 5–7% with class II or class III obesity. The adjusted prevalence ratio comparing the highest to a normal BMI category was 2.46 (95% CI: 1.44, 4.21) in 1988–1994, and 2.21 (95% CI: 1.50, 3.26) in 2007–2010. Notably, there was a progressively greater prevalence ratio of gout associated with successively higher categories of BMI. In both survey periods, for an average American adult standing 1.76m (5 feet, 9 inches), a 1 unit higher BMI, corresponding to 3.1 kg (~6.8 lbs) greater weight, was associated with a 5% greater prevalence of gout, even after adjusting for serum uric acid (P < 0.001).


Healthcare providers should be aware of the elevated burden of gout among both overweight and obese adults, applicable to both women and men, and observed among non-Hispanic White, non-Hispanic Black and Mexican Americans in the US.

The prevalence of gout is increasing in the United States, a trend attributed in part to the obesity epidemic (1,2). Whether body weight contributes to gout risk via an obesity threshold effect, at a body mass index (BMI) value of 30 kg/m2, or rather in a graduated, progressive fashion across overweight, obese, and severely obese levels, has not been characterized in the general US population. Further, whether the association of BMI with gout persists after adjustment for serum uric acid and other obesity-related medical disorders is unclear.

The objectives of the present study are to determine the burden of gout across the full spectrum of BMI, using the National Health and Nutrition Examination Survey (NHANES) in 1988–1994 and 2007–2010. Furthermore, we examine whether the relationship between BMI and gout is applicable in both women and men, and among non-Hispanic White, non-Hispanic Black and Mexican Americans.


Study Population

The NHANES surveys, conducted by the National Center for Health Statistics (NCHS), utilize a complex, multistage sampling design. We examined NHANES III, conducted in 1988–1994, and the continuous NHANES in 2007–2010, using information gathered at mobile examination centers from participants over 20 years of age, including interviews, physical examinations, and laboratory measurements. Persons lacking a BMI measurement or those not answering the query regarding gout status were excluded. NCHS approved the NHANES protocols and obtained informed consent (3,4).

Outcome of Gout

Prevalent gout was defined by the affirmative response of NHANES participants to the questions, “Has a doctor or other health professional ever told you that you had gout?” (NHANES 2007–10) or “Has a doctor ever told you that you had gout?”(NHANES III).

BMI and Obesity as Exposure

BMI was calculated using weight and standing height measurements and treated as a continuous variable, then categorized using the WHO classification system, as follows: underweight (< 18.5 kg/m2), normal (18.5–24.9 kg/m2), overweight (25–29.9 kg/m2), obesity class I (30–34.9 kg/m2) and obesity classes II or III (35 kg/m2 and greater) (5). Furthermore, obesity was defined as a dichotomous variable for those participants with a BMI ≥30 kg/m2.

Demographic Characteristics and Obesity-Related Medical Conditions

The NHANES protocol recorded the age, gender, and race/ethnicity of all participants. Age was treated both as a continuous variable, and as a dichotomous variable using the median study population value of 44 years. Race/ethnicity was categorized as non-Hispanic white, non-Hispanic black, Mexican American, and other. Hyperuricemia was defined as a serum uric acid measurement >6.0 mg/dL (360 μmol/L) in women and >7.0 mg/dL (420 μmol/L) in men. Hypertension was defined by a systolic blood pressure ≥140 mmHg or diastolic blood pressure ≥90 mmHg or use of antihypertensive medications. Glomerular filtration rate (GFR) (6) was estimated using standardized serum creatinine measurements; low eGFR was defined as an eGFR <60 mL/min per 1.73 m2. Low high density lipoprotein cholesterol (HDLc) was defined as <40 mg/dL for men and <50 mg/dL for women; high total cholesterol was defined as ≥240 mg/dL. Diabetes was defined based on self-report. Medication use was dichotomized (yes or no) for any gout medications (allopurinol, probenecid, colchicine, sulfinpyrazone, and alloxanthine), and for any diuretic agents, including thiazides (loop diuretics, potassium-sparing diuretics, thiazide diuretics, carbonic anhydrase inhibitors, or miscellaneous diuretics). Alcohol consumption was categorized as never, former, current non-excessive, or current excessive, using accepted definitions (7). Importantly, data on medication use and alcohol consumption for the 2009–2010 NHANES survey were not available for study.

Statistical Analyses

All analyses were performed in concordance with the NHANES complex sampling design using the sample weights, primary sampling units, and strata accompanying each survey (3,4). Standard errors for all estimates were calculated using the recommended Taylor series (linearization) method (3,4). Weighted prevalence estimates, or means and their associated standard errors, were calculated for demographic characteristics, obesity-related medical disorders, use of gout and diuretic medications, and alcohol consumption for NHANES III and NHANES 2007–2010. In addition, we determined the prevalence of gout according to each BMI category. In order to visualize the association of BMI across the full range of BMI values, we plotted the proportion of NHANES participants with gout and hyperuricemia using linear spline models, with knots at each BMI category, to further evaluate the relationship between BMI, hyperuricemia, and gout.

Prevalence ratios comparing the various BMI categories to the reference category (the normal BMI range) and those derived using BMI as continuous variable were calculated using Poisson regression. Poisson models were nested in the following fashion: unadjusted; adjusted for age, gender, and race/ethnicity; adjusted for the preceding demographic characteristics plus obesity-related medical disorders, namely, hypertension, low eGFR, low HDLc, high total cholesterol, and self-reported diabetes; and finally further adjusted for serum uric acid concentration. We evaluated the prevalence of gout by obesity status according to demographic strata and obesity-related medical disorders. Further, we conducted a sensitivity analysis in which cases of gout were limited to individuals with a physician-diagnosis of gout and hyperuricemia. Finally, we evaluated whether the prevalence of gout was greater in 2007–2010 compared with the 1988–1994 survey period by strata of obesity. Analyses were performed in Stata 11.1 (StataCorp LP, College Station, TX).


There were 16,521 adults, age 20 and older, examined in NHANES 1988–1994 and 11,589 in NHANES 2007–2010, who responded to the query on gout status and underwent a BMI measurement. Their demographic and clinical profile is shown in Table 1 (& online supplement Table 1, respectively). In NHANES III there was an unweighted total of 469 participants with gout, representing a weighted prevalence of 2.64% or approximately 4.7 million adults with gout in the US. In NHANES 2007–2010, the unweighted number with gout was 541, corresponding to a higher weighted prevalence of 3.76% than in the earlier period, or about 8.1 million adults. Regardless of survey period, the prevalence of gout demonstrated a dose-response pattern in relation to BMI, being greater among higher BMI categories (Table 2). For example, while approximately 1–2% of the participants with a normal BMI value reported a diagnosis of gout, the proportion was 3% among the overweight participants, 4–5% among those with class I obesity, and 5–7% among individuals with class II or class III obesity. Graphically, at higher BMI values, the proportion with gout steadily increased (Figure 1A&B). Furthermore, across the full spectrum of BMI, the proportion of individuals with hyperuricemia exceeded the proportion with gout, at any given BMI value.

Figure 1
Linear spline graph of the proportion of the US population with gout (solid line) or hyperuricemia (dashed line) in NHANES III (A) or NHANES 2007–2010 (B) according the body mass index (kg/m2). Knots are located at 18.5, 25, 30, and 35 kg/m2. ...
Table 1
Weighted means and prevalence estimates by category of body mass index in NHANES III (1988–1994)
Table 2
Weighted prevalence (SE) and prevalence ratios (95% CI) of gout by body mass index (kg/m2) categories or as a continuous variable

Moreover, the apparent dose-response relationship between BMI and prevalent gout persisted after adjustment for demographic factors (Table 2, Model 1). After further adjustment for obesity-related medical disorders (Model 2), being overweight was associated with a 76% (prevalence ratio: 1.76; 95% CI: 1.18, 2.61) or 48% (prevalence ratio: 1.48; 95% CI: 1.05, 2.08) higher prevalence of gout than the normal BMI category in 1988–1994 and 2007–2010, respectively. Although adjustment for serum uric acid (Model 3) further attenuated this association, the prevalence of gout remained about 1.8 times greater among class I obese individuals, and over 2.2 times greater among class II or III obesity, compared to individuals with a BMI in the normal range. Notably, when the association of BMI category with prevalent gout was further adjusted, among the NHANES III participants, for use of diuretic agents and alcohol consumption, the results were fundamentally unchanged (data not shown). Interestingly, these associations were similarly observed when BMI was examined as a continuous variable. After adjusting for serum uric acid, a 1 unit higher BMI - corresponding to 3.1 kg (~6.8 lb) greater weight in an average US adult standing 1.76m (5 feet 9 inches) (8) - was associated with a 5% (NHANES III prevalence ratio: 1.05; 95% CI: 1.03, 1.08) or 4% (NHANES 2007–2010 prevalence ratio: 1.04; 95% CI: 1.02, 1.05) greater prevalence of gout. Notably, in a sensitivity analysis restricted to those with a reported physician-diagnosis of gout and hyperuricemia, a similar pattern of association was observed (Online Supplemental Table 2).

The overall adjusted prevalence of gout was 1.54 (95% CI: 1.21, 1.95) to 1.72 (95% CI: 1.32, 2.25) times greater in obese participants in NHANES III and in NHANES 2007–2010, respectively (Tables 3). Stratification by age, gender and race did not significantly modify this association. Notably, despite being inconsistent by survey period, obesity was related to a greater prevalence of gout among non-Hispanic white, non-Hispanic black and Mexican Americans. For example, among Mexican Americans in NHANES III, obesity was related to a two-fold greater prevalence of gout (prevalence ratio 2.49; 95% CI 1.20, 5.15), and in the stratum of non-Hispanic blacks in NHANES 2007–2010 was 2.17 (95% CI 1.38, 3.42). Further, for each stratum defined by the various obesity-related medical disorders, obesity was associated with a higher prevalence of gout, other than among those NHANES 2007–2010 participants with diabetes mellitus (Table 3).

Table 3
Weighted prevalence of gout by obesity status, stratified by demographic characteristics and obesity-related medical disorders in NHANES 2007–2010

Further, much of the temporal increase in gout prevalence occurred among obese participants (prevalence ratio: 1.37; 95% CI: 1.04, 1.80) (Online Supplemental Material Table 3). However, after demographic adjustment, the prevalence ratio for gout, comparing 2007–2010 with 1988–1994, was no longer significant (prevalence ratio: 1.28; 95% CI: 0.98, 1.67).


The prevalence of both gout and obesity is rising. This study represents a comprehensive examination of the burden of gout in relation to the full range of BMI values in the US. We found a significant, graded association between successive BMI categories and higher gout prevalence ratios, even after adjustment for obesity-related medical disorders. Notably, after further adjustment for serum uric acid, compared to participants in the normal BMI range, the prevalence of gout was 1.3–1.5 times greater among the overweight NHANES participants, while the prevalence ratio was higher at 1.8 for class I obesity, and to 2.2–2.4 for participants with class II or III obesity.

In our analysis we were able to utilize the NHANES 2009–2010 survey data to provide a more precise estimate of the current prevalence of gout. Previous research suggests that the prevalence of gout increased between 1988–1994 and 2007–2008 (1). We found that the crude prevalence of gout was higher in both non-obese and obese participants in NHANES 2007–2010; however, this increase in unadjusted prevalence was only significant among obese participants. Furthermore, adjustment for demographic characteristics rendered the prevalence ratio among obese participants, non-significant. This suggests that while the obesity epidemic is a major contributor to the rising burden of gout in the United States, temporal trends in demographic characteristics and comorbidity profiles largely explain the higher prevalence of gout reported in the later NHANES survey period.

Obesity is often thought to impact gout risk via elevated levels of serum uric acid (9). Interestingly, obesity has been shown to increase proinflammatory molecules, including tumor necrosis factor-α and interleukin-6 (10,11). Further, in the present analyses, the comorbidity profile associated with overweight and obesity further impacts upon gout prevalence. Each of these considerations appears to contribute to the higher prevalence of gout in those with successively higher levels of weight in the general US population.

A number of important limitations warrant discussion. First, NHANES is a cross-sectional study, susceptible to unmeasured confounders and reverse causation. Whereas a clinical diagnosis of gout may include aspiration of synovial fluid (arthrocentesis) for the identification of urate crystals (12), the survey methodology used here requires self-report of a physician diagnosis of gout, a reliable and sensitive approach, as assessed in a different, population-based survey (13). A crystal-proven diagnosis is the gold standard diagnostic approach in clinical practice, yet impractical to implement in the context of epidemiologic research. Moreover, recent NHANES reports have underscored this approach (1,14). Importantly, when in sensitivity analyses, the definition of gout was restricted to those with concomitant evidence of hyperuricemia, a more restrictive case-definition, the observation association with body mass index and gout was unchanged.

Our study demonstrated that BMI is strongly associated with prevalent gout, which has important public health ramifications given that about 34% of Americans are overweight, about 20% are obese, and about 14% are obese stages II or greater (2). We found that the proportion with gout was greater among participants possessing higher BMI values, with overweight persons having 1.48–1.76 times the prevalence of gout than their counterparts with BMI values in the normal range. In conclusion, successive categories of BMI are associated in a dose-response fashion with a higher prevalence of gout. These associations are observed among women and men, as well as among non-Hispanic White, non-Hispanic Black and Mexican Americans. The relationship between obesity and gout persisted even after adjustment for serum uric acid, suggesting that hyperuricemia may not be the sole mediator underlying this relationship. Health care providers treating obese, or even overweight, patients should be cognizant of the elevated burden of gout among these segments of the US population.

Significance and Innovation

  • There is a dose-response relationship between body mass index (BMI) and prevalent gout with successively higher prevalence ratios of gout in overweight, obese, and severely obese participants.
  • Obesity, defined as a BMI category over 30 kg/m2, is significantly associated with approximately twice the prevalence of gout as compared to non-obese persons, even after adjusting for serum uric acid.
  • For an American adult of average height, standing 1.76 m (5 feet 9 inches), a 1 unit higher BMI - corresponding to 3.1 kg (6.8 lb) greater weight, was associated with a 5% greater prevalence of gout (P < 0.001).
  • Much of the increase in the prevalence of gout in the United States is attributable to the higher levels of obesity over time; however, this increase is explained by secular trends in age, sex, and race/ethnicity composition of the population and in gout-related co-morbidites.
  • There is an elevated burden of gout among both overweight and obese adults, applicable to both women and men, and observed among non-Hispanic White, non-Hispanic Black and Mexican Americans in the US.

Supplementary Material

Supp Table 01-03


Supported in part by a NIH/NHLBI T32HL007024 Cardiovascular Epidemiology Training Grant, the Donald B. and Dorothy Stabler Foundation.



All authors were involved in drafting the article or revising it critically for important intellectual content, and all authors approved the final version to be published. Stephen Juraschek had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Study conception and design. Juraschek, Gelber.

Acquisition of data. Juraschek.

Analysis and interpretation of data. Juraschek, Miller, Gelber.


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