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Abstract

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. REFERENCES
  9. Supporting Information

Objective

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

Methods

Among participants (age ≥20 years) 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. Body mass index (BMI) was examined in categories of <18.5 kg/m2, 18.5–24.9 kg/m2, 25–29.9 kg/m2, 30–34.9 kg/m2, 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.

Results

In the US, the crude prevalence of gout was 1–2% among participants with a normal BMI (18.5–24.9 kg/m2), 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% confidence interval [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 1.76 meters (5 feet 9 inches), a 1-unit higher BMI, corresponding to 3.1 kg (∼6.8 pounds) greater weight, was associated with a 5% greater prevalence of gout, even after adjusting for serum uric acid (P < 0.001).

Conclusion

Health care 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 whites, non-Hispanic African Americans, and Mexican Americans in the US.


INTRODUCTION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. REFERENCES
  9. Supporting Information

The prevalence of gout is increasing in the US, 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 whites, non-Hispanic African Americans, and Mexican Americans.

Significance & Innovations

  • 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 ≥30 kg/m2, is significantly associated with approximately twice the prevalence of gout as compared to nonobese persons, even after adjusting for serum uric acid.

  • For an American adult of average height standing 1.76 meters (5 feet 9 inches), a 1-unit higher BMI (corresponding to 3.1 kg [6.8 pounds] 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 US 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 comorbidities.

  • There is an elevated burden of gout among both overweight and obese adults, applicable to both women and men, and observed among non-Hispanic whites, non-Hispanic African Americans, and Mexican Americans in the US.

MATERIALS AND METHODS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. REFERENCES
  9. Supporting Information

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 2007–2008 and 2009–2010, using information gathered at mobile examination centers from participants age ≥20 years, 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 2007–2010) 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 World Health Organization 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) (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, sex, and race/ethnicity of all participants. Age was treated as both 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 African American, Mexican American, and other. Hyperuricemia was defined as a serum uric acid measurement >6.0 mg/dl (360 μmoles/liter) in women and >7.0 mg/dl (420 μmoles/liter) in men. Hypertension was defined by a systolic blood pressure ≥140 mm Hg or diastolic blood pressure ≥90 mm Hg or use of antihypertensive medications. Glomerular filtration rate (GFR) (6) was estimated using standardized serum creatinine measurements; low estimated GFR was defined as an estimated GFR <60 ml/minute per 1.73 m2. Low high-density lipoprotein (HDL) cholesterol was defined as <40 mg/dl for men and <50 mg/dl for women; high total cholesterol was defined as ≥240 mg/dl. Diabetes mellitus 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 nonexcessive, or current excessive, using accepted definitions (7). Importantly, data on medication use and alcohol consumption for the 2009–2010 NHANES survey were not available at the time of this 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). SEs for all estimates were calculated using the recommended Taylor series (linearization) method (3, 4). Weighted prevalence estimates, or means and their associated SEs, 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, sex, and race/ethnicity; adjusted for the preceding demographic characteristics plus obesity-related medical disorders (namely, hypertension, low estimated GFR, low HDL cholesterol, high total cholesterol, and self-reported diabetes mellitus); 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 software, version 11.1.

RESULTS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. REFERENCES
  9. Supporting Information

There were 16,521 adults age ≥20 years examined in NHANES 1988–1994 and 11,589 adults in NHANES 2007–2010 who responded to the query on gout status and underwent a BMI measurement. The demographic and clinical profiles for NHANES 2007–2010 adults and NHANES 1988–1994 adults are shown in Table 1 and in Supplementary Table 1 (available in the online version of this article at http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)2151-4658), 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 approximately 8.1 million adults. Regardless of the 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 1). Furthermore, across the full spectrum of BMI, the proportion of individuals with hyperuricemia exceeded the proportion with gout at any given BMI value.

Table 1. Weighted means and prevalence estimates by category of BMI in NHANES 2007–2010 (n = 299,539,907)*
 OverallBMI category (kg/m2)
<18.518.5–24.925–29.930–34.9≥35
  • *

    Values are the prevalence estimate (SE) unless indicated otherwise. N represents the weighted number for each survey period, representing the US population. BMI = body mass index; NHANES = National Health and Nutrition Examination Survey; GFR = glomerular filtration rate; HDL = high-density lipoprotein.

  • In order to account for a change in NHANES race/ethnicity definitions in 2007–2010, we placed Hispanic in the “other” category to be consistent with NHANES 1988–2004.

  • Defined as a systolic blood pressure ≥140 mm Hg or a diastolic blood pressure ≥90 mm Hg or blood pressure–lowering medication use.

  • §

    Defined as >7 mg/dl in men and >6 mg/dl in women.

  • Data were not available for 2009–2010 at the time of this analysis; as a result, these data represent the 2007–2008 survey only.

  • #

    Allopurinol, probenecid, colchicine, sulfinpyrazone, and alloxanthine. Data were not available for 2009–2010 at the time of this analysis; as a result, these data represent the 2007–2008 survey only.

Age, weighted mean ± SEM years46.79 ± 0.3343.14 ± 1.4344.05 ± 0.5248.18 ± 0.3948.49 ± 0.4347.21 ± 0.49
Male48.13 (0.39)27.96 (3.80)42.17 (1.12)55.94 (0.98)53.45 (1.22)37.42 (1.24)
Race/ethnicity      
 Non-Hispanic white68.61 (2.48)73.16 (3.37)70.59 (2.29)68.93 (2.56)67.17 (3.25)65.32 (3.22)
 Non-Hispanic African American11.33 (1.02)12.45 (1.75)8.88 (0.73)9.37 (0.88)13.03 (1.60)18.30 (2.07)
 Mexican American8.48 (1.32)2.17 (0.92)5.98 (0.80)9.82 (1.47)10.17 (1.97)8.88 (1.66)
 Other11.58 (1.28)12.21 (2.80)14.55 (1.62)11.88 (1.52)9.63 (1.41)7.50 (1.17)
BMI, weighted mean ± SEM kg/m228.64 ± 0.1017.57 ± 0.0622.39 ± 0.0427.41 ± 0.0432.18 ± 0.0340.51 ± 0.15
Estimated GFR <60 ml/minute/1.73 m26.49 (0.32)3.46 (1.31)5.43 (0.45)6.78 (0.42)7.01 (0.56)7.58 (0.70)
Low HDL cholesterol33.00 (0.82)12.88 (2.61)17.79 (1.26)30.80 (1.10)44.32 (1.25)55.71 (1.58)
Elevated total cholesterol14.04 (0.55)3.50 (1.82)11.35 (0.76)17.06 (1.05)15.94 (1.22)11.11 (0.93)
Hypertension31.63 (0.78)16.94 (3.17)19.83 (1.03)30.38 (1.15)39.58 (1.13)48.84 (1.49)
Self-reported diabetes mellitus8.37 (0.43)0.82 (0.43)3.59 (0.34)5.88 (0.46)12.19 (0.90)19.41 (1.47)
Serum uric acid, weighted mean ± SEM mg/dl5.46 ± 0.024.32 ± 0.104.92 ± 0.045.51 ± 0.035.88 ± 0.046.03 ± 0.04
Hyperuricemia§18.39 (0.56)1.70 (0.73)7.96 (0.58)16.07 (0.91)27.09 (1.52)34.95 (1.61)
Diuretic medications10.18 (0.77)4.14 (1.91)5.50 (0.55)9.22 (0.99)14.06 (0.96)17.89 (2.15)
Gout medications#1.32 (0.22)0.00.82 (0.27)0.89 (0.21)2.01 (0.41)2.66 (0.80)
Alcohol status      
 Never11.98 (0.88)20.24 (4.89)12.08 (1.27)12.04 (1.00)11.70 (1.17)11.25 (1.52)
 Former24.10 (1.71)30.57 (6.17)18.94 (1.44)21.53 (2.37)27.58 (2.39)35.84 (2.65)
 Nonexcessive current35.46 (1.30)33.46 (6.09)38.82 (1.44)33.22 (1.63)36.77 (1.85)32.14 (3.52)
 Excessive current28.46 (1.35)15.73 (5.82)30.16 (1.72)33.21 (2.60)23.94 (1.50)20.77 (2.13)
Table 2. Weighted prevalence (SE) and prevalence ratios (95% CI) of gout by BMI categories or as a continuous variable*
 NPrevalence (SE)UnadjustedModel 1Model 2Model 3
  • *

    Model 1: adjusted for age, sex, race/ethnicity. Model 2: model 1 plus hypertension, reduced estimated glomerular filtration rate, low high-density lipoprotein cholesterol, elevated total cholesterol, and diabetes mellitus. Model 3: model 2 plus serum uric acid. 95% CI = 95% confidence interval; BMI = body mass index; NHANES = National Health and Nutrition Examination Survey; ref. = reference.

  • N represents the unweighted number of participants in each model.

  • In NHANES III, the unweighted number of gout cases in each BMI category was 6, 102, 182, 109, and 70, respectively.

  • §

    In NHANES 2007–2010, the unweighted number of gout cases in each BMI category was 4, 70, 164, 151, and 152, respectively.

  • For an average US height of 1.7645 meters (8), a 1-unit greater BMI is equal to 3.113 kg (6.863 pounds). The total unweighted number of gout cases was 469 in NHANES III and 541 in NHANES 2007–2010.

NHANES III, no.  16,52116,52115,28815,288
 BMI <18.5 kg/m23560.93 (0.52)0.74 (0.22–2.47)0.82 (0.25–2.72)1.11 (0.34–3.61)1.30 (0.40–4.21)
 BMI 18.5–24.9 kg/m26,1881.26 (0.21)1.0 (ref.)1.0 (ref.)1.0 (ref.)1.0 (ref.)
 BMI 25–29.9 kg/m25,7533.32 (0.34)2.63 (1.79–3.87)1.90 (1.27–2.82)1.76 (1.18–2.61)1.57 (1.08–2.28)
 BMI 30–34.9 kg/m22,7014.06 (0.39)3.21 (2.18–4.74)2.56 (1.75–3.76)2.12 (1.49–3.02)1.77 (1.23–2.55)
 BMI ≥35 kg/m21,5235.25 (0.98)4.16 (2.52–6.85)4.53 (2.70–7.61)3.15 (1.88–5.29)2.46 (1.44–4.21)
NHANES 2007–2010, no.§  11,58911,58910,53510,532
 BMI <18.5 kg/m21861.29 (0.68)0.81 (0.25–2.62)0.91 (0.29–2.81)1.15 (0.37–3.55)1.21 (0.39–3.74)
 BMI 18.5–24.9 kg/m23,1191.61 (0.22)1.0 (ref.)1.0 (ref.)1.0 (ref.)1.0 (ref.)
 BMI 25–29.9 kg/m23,9563.36 (0.28)2.09 (1.47–2.98)1.58 (1.14–2.18)1.48 (1.05–2.08)1.31 (0.94–1.84)
 BMI 30–34.9 kg/m22,4605.42 (0.60)3.38 (2.50–4.56)2.64 (1.98–3.51)2.15 (1.51–3.05)1.79 (1.27–2.52)
 BMI ≥35 kg/m21,8687.05 (0.73)4.39 (3.24–5.95)4.32 (3.20–5.82)2.92 (1.98–4.31)2.21 (1.50–3.26)
BMI as continuous variable      
 NHANES III16,5212.64 (0.19)1.07 (1.06–1.09)1.08 (1.07–1.10)1.07 (1.05–1.08)1.05 (1.03–1.08)
 NHANES 2007–201011,5893.76 (0.24)1.06 (1.05–1.07)1.07 (1.06–1.08)1.05 (1.03–1.06)1.04 (1.02–1.05)
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Figure 1. Linear spline graph of the proportion of the US population with gout (solid line) or hyperuricemia (broken line) in NHANES III (A) or NHANES 2007–2010 (B) according to the body mass index. Knots are located at 18.5, 25, 30, and 35 kg/m2. Hyperuricemia is defined by a serum uric acid measurement >6.0 mg/dl in women and >7.0 mg/dl in men. NHANES = National Health and Nutrition Examination Survey.

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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% confidence interval [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 approximately 1.8 times greater among individuals with class I obesity, and more than 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 pounds) greater weight in an average US adult standing 1.76 meters (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 self-reported physician diagnosis of gout and hyperuricemia, a similar pattern of association was observed (Supplementary Table 2, available in the online version of this article at http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)2151-4658).

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 (Table 3 and Supplementary Table 3, available in the online version of this article at http://onlinelibrary.wiley.com/journal/10.1002(ISSN)2151-4658). Stratification by age, sex, 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 whites, non-Hispanic African Americans, and Mexican Americans. For example, among Mexican Americans in NHANES III, obesity was related to a 2-fold greater prevalence of gout (prevalence ratio 2.49, 95% CI 1.20–5.15), and in the stratum of non-Hispanic African Americans 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*
 NGout prevalence, % (SE)Obese vs. nonobese PR (95% CI)
Nonobese (n = 7,261)Obese (n = 4,328)Partially adjustedFully adjusted§
  • *

    NHANES = National Health and Nutrition Examination Surveys; PR = prevalence ratio; 95% CI = 95% confidence interval; GFR = glomerular filtration rate; HDL = high-density lipoprotein.

  • Represents the unweighted denominator in each stratum.

  • Adjusted for dichotomous age, sex, and race/ethnicity

  • §

    Adjusted for dichotomous age, sex, and race/ethnicity, hypertension, low estimated GFR, total cholesterol, low HDL, and diabetes mellitus.

Overall11,5892.51 (0.16)6.12 (0.54)2.34 (1.88–2.90)1.72 (1.32–2.25)
Age, years     
 <444,6360.34 (0.10)2.61 (0.61)8.01 (3.61–17.75)5.08 (1.60–16.17)
 ≥446,9534.41 (0.26)8.67 (0.76)1.99 (1.58–2.49)1.49 (1.15–1.94)
Sex     
 Female5,9621.31 (0.21)3.53 (0.31)2.53 (1.75–3.66)1.85 (1.11–3.09)
 Male5,6273.76 (0.36)9.09 (1.05)2.27 (1.76–2.91)1.69 (1.26–2.26)
Race/ethnicity     
 Non-Hispanic white5,4852.91 (0.24)6.61 (0.65)2.13 (1.70–2.67)1.59 (1.19–2.12)
 Non-Hispanic African American2,2412.61 (0.50)6.58 (0.87)2.76 (1.79–4.26)2.17 (1.38–3.42)
 Mexican American2,0590.76 (0.19)2.11 (0.49)2.91 (1.19–7.11)1.68 (0.76–3.72)
 Other1,8041.36 (0.32)5.98 (1.77)4.16 (2.10–8.25)2.82 (1.36–5.82)
Hypertension     
 No6,9441.22 (0.16)3.12 (0.61)2.72 (1.77–4.20)2.46 (1.52–4.00)
 Yes4,2656.65 (0.48)10.24 (0.94)1.64 (1.31–2.04)1.43 (1.09–1.87)
Estimated GFR, ml/minute/1.73 m2     
 ≥609,8811.92 (0.16)5.08 (0.54)2.52 (1.90–3.33)1.83 (1.35–2.47)
 <6097012.01 (1.32)17.42 (2.25)1.53 (1.06–2.21)1.42 (1.00–2.04)
Total cholesterol, mg/dl     
 <2409,3402.51 (0.18)5.96 (0.61)2.22 (1.71–2.88)1.66 (1.25–2.21)
 ≥2401,5422.62 (0.61)5.91 (1.73)2.34 (1.03–5.32)2.13 (0.92–4.92)
Low HDL cholesterol     
 No7,2452.39 (0.19)5.29 (0.58)1.97 (1.49–2.61)1.66 (1.25–2.20)
 Yes3,6372.96 (0.44)6.64 (0.89)2.12 (1.45–3.11)1.80 (1.16–2.79)
Diabetes mellitus     
 No10,1942.18 (0.17)5.06 (0.61)2.33 (1.73–3.16)1.96 (1.48–2.60)
 Yes1,3869.13 (1.69)12.01 (1.06)1.33 (0.87–2.03)1.06 (0.63–1.78)

Further, much of the temporal increase in gout prevalence occurred among obese participants (prevalence ratio 1.37, 95% CI 1.04–1.80) (Supplementary Table 4, available in the online version of this article at http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)2151-4658). 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).

DISCUSSION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. REFERENCES
  9. Supporting Information

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 to 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 data, through the most recent 2009–2010 survey period, 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 nonobese 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 as nonsignificant. This suggests that while the obesity epidemic is a major contributor to the rising burden of gout in the US, 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 BMI and gout was unchanged.

Our study demonstrated that BMI is strongly associated with prevalent gout, which has important public health ramifications given that approximately 34% of Americans are overweight, approximately 20% are obese, and approximately 14% are obese at 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 whites, non-Hispanic African Americans, 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.

AUTHOR CONTRIBUTIONS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. REFERENCES
  9. Supporting Information

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 submitted for publication. Dr. Gelber 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.

REFERENCES

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. REFERENCES
  9. Supporting Information
  • 1
    Zhu Y, Pandya BJ, Choi HK. Prevalence of gout and hyperuricemia in the US general population: the National Health and Nutrition Examination Survey 2007–2008. Arthritis Rheum 2011; 63: 313641.
  • 2
    Flegal KM, Carroll MD, Ogden CL, Curtin LR. Prevalence and trends in obesity among US adults, 1999-2008. JAMA 2010; 303: 23541.
  • 3
    Centers for Disease Control. NHANES-NHANES III: reports and reference manuals. 1988. URL: http://www.cdc.gov/nchs/nhanes/nh3rrm.htm.
  • 4
    Centers for Disease Control. NHANES-NHANES 1999-2010: manuals, brochures, and consent documents. 1999. URL: http://www.cdc.gov/nchs/nhanes/.
  • 5
    World Health Organization Expert Committee on Physical Status. Physical status: the use and interpretation of anthropometry. Geneva: World Health Organization; 1995.
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    Levey AS, Stevens LA, Schmid CH, Zhang YL, Castro AF III, Feldman HI, et al. A new equation to estimate glomerular filtration rate. Ann Intern Med 2009; 150: 60412.
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    Tsai J, Ford ES, Li C, Zhao G. Past and current alcohol consumption patterns and elevations in serum hepatic enzymes among US adults. Addict Behav 2012; 37: 7884.
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    Merrill RM, Richardson JS. Validity of self-reported height, weight, and body mass index: findings from the National Health and Nutrition Examination Survey, 2001-2006. Prev Chronic Dis 2009; 6: A121.
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    Zhu Y, Zhang Y, Choi HK. The serum urate-lowering impact of weight loss among men with a high cardiovascular risk profile: the Multiple Risk Factor Intervention Trial. Rheumatology (Oxford) 2010; 49: 23919.
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    Sell H, Eckel J. Adipose tissue inflammation: novel insight into the role of macrophages and lymphocytes. Curr Opin Clin Nutr Metab Care 2010; 13: 36670.
  • 11
    Weisberg SP, McCann D, Desai M, Rosenbaum M, Leibel RL, Ferrante AW Jr. Obesity is associated with macrophage accumulation in adipose tissue. J Clin Invest 2003; 112: 1796808.
  • 12
    Wallace SL, Robinson H, Masi AT, Decker JL, McCarty DJ, Yu TF. Preliminary criteria for the classification of the acute arthritis of primary gout. Arthritis Rheum 1977; 20: 895900.
  • 13
    McAdams MA, Maynard JW, Baer AN, Kottgen A, Clipp S, Coresh J, et al. Reliability and sensitivity of the self-report of physician-diagnosed gout in the campaign against cancer and heart disease and the atherosclerosis risk in the community cohorts. J Rheumatol 2011; 38: 13541.
  • 14
    Choi HK, Ford ES, Li C, Curhan G. Prevalence of the metabolic syndrome in patients with gout: the Third National Health and Nutrition Examination Survey. Arthritis Rheum 2007; 57: 10915.

Supporting Information

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. REFERENCES
  9. Supporting Information

Additional Supporting Information may be found in the online version of this article.

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ACR_21791_sm_SupplTable1.doc126KSupplementary Tables 1, 2, 3 and 4

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