Environment International 76 (2015) 32–40

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Arsenic exposure, hyperuricemia, and gout in US adults☆ Chin-Chi Kuo a,b,c,d,⁎, Virginia Weaver b,c,e, Jeffrey J. Fadrowski c,e,f, Yu-Sheng Lin g,1, Eliseo Guallar a,c,e, Ana Navas-Acien a,b,c a

Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA Department of Environmental Health Sciences, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins Medical Institutions, Baltimore, MD, USA d Kidney Institute and Division of Nephrology, Department of Internal Medicine, China Medical University Hospital and College of Medicine, China Medical University, Taichung, Taiwan e Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA f Division of Pediatric Nephrology, Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, MD, USA g Department of Environmental and Occupational Health, University of North Texas Health Science Center, Fort Worth, TX, USA b c

a r t i c l e

i n f o

Article history: Received 26 May 2014 Accepted 21 November 2014 Available online xxxx Keywords: Uric acid Hyperuricemia Arsenic Lead Gout

a b s t r a c t Background: There is very limited information on the association between arsenic and serum uric acid levels or gout. The aim of this study was to investigate the association of arsenic with hyperuricemia and gout in US adults. Methods: A cross-sectional study was conducted in 5632 adults aged 20 years or older from the National Health and Nutrition Examination Survey (NHANES) 2003–2010 with determinations of serum uric acid and urine total arsenic and dimethylarsinate (DMA). Hyperuricemia was defined as serum uric acid higher than 7.0 mg/dL for men and 6.0 mg/dL for women. Gout was defined based on self-reported physician diagnosis and medication use. Results: After adjustment for sociodemographic factors, comorbidities and arsenobetaine levels, the increase in the geometric means of serum uric acid associated with one interquartile range increase in total arsenic and DMA levels was 3% (95% CI 2–5) and 3% (2–5), respectively, in men and 1% (0–3) and 2% (0–4), respectively, in women. In men, the adjusted odds ratio for hyperuricemia comparing the highest to lowest quartiles of total arsenic was 1.84 (95% CI, 1.26–2.68) and for DMA it was 1.41 (95% CI, 1.01–1.96). The corresponding odds ratios in women were 1.26 (0.77, 2.07) and 1.49 (0.96, 2.31), respectively. The odds ratio for gout comparing the highest to lowest tertiles was 5.46 (95% CI, 1.70–17.6) for total arsenic and 1.98 (0.64–6.15) for DMA among women older than 40 years old. Urine arsenic was not associated with gout in men. Conclusion: Low level arsenic exposures may be associated with the risk of hyperuricemia in men and with the prevalence of gout in women. Prospective research focusing on establishing the direction of the relationship among arsenic, hyperuricemia, and gout is needed. © 2014 Elsevier Ltd. All rights reserved.

1. Introduction Hyperuricemia and gout have been linked to cardiovascular disease, diabetes, and chronic kidney disease and its progression (Feig et al., 2008; Dehghan et al., 2008; Nakagawa et al., 2006). While hyperuricemia is often related to excess adiposity and the metabolic syndrome, environmental factors can also induce hyperuricemia (Ryu et al., 2012). Among metals, elevated lead exposure is a well-defined risk factor for hyperuricemia and gout (Krishnan et al., 2012). Arsenic, a worldwide environmental pollutant, is an established risk factor for the development of cancer and cardiovascular disease, and possibly for the ☆ Financial disclosure for all authors: No specific funding was received for this study. ⁎ Corresponding author at: Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA and Kidney Institute and Division of Nephrology, Department of Internal Medicine, China Medical University Hospital and College of Medicine, China Medical University, Taichung, Taiwan. 1 Current address: National Center for Environmental Assessment, Office of Research and Development, U.S. Environmental Protection Agency, Washington, D.C., USA.

http://dx.doi.org/10.1016/j.envint.2014.11.015 0160-4120/© 2014 Elsevier Ltd. All rights reserved.

development of diabetes and chronic kidney disease (Zheng et al., 2012; Moon et al., 2013; Navas-Acien et al., 2008). Arsenic exposure could result in hyperuricemia secondary to kidney injury (Saxena et al., 2009), but animal studies have shown mixed results, including no association (Mahaffey and Fowler, 1977) and associations with low and high uric acid levels (Saxena et al., 2009; Jauge and Del-Razo, 1985). Indeed, arsenic may inhibit xanthine oxidase and thus lead to a reduction in uric acid level (Del-Razo et al., 2003). Evidence in humans is very limited. Two small human studies in areas with high arsenic concentrations in drinking water (mean N 50 μg/L) in Mexico and India reported that high exposure to inorganic arsenic was associated with hypouricemia (Del-Razo et al., 2003; Maiti et al., 2012). No studies, however, have examined the role of low–moderate arsenic exposure on serum uric acid levels and the risk of gout. Humans are exposed to different forms of arsenic, including inorganic (arsenite, arsenate) and organic (arsenobetaine, arsenosugars and arsenolipids) compounds (Navas-Acien et al., 2011). Organic arsenic compounds are present mainly in seafood and are considered non-toxic. In general

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populations, the major sources of inorganic arsenic exposure are drinking water and food (especially rice and other grains) (Navas-Acien and Nachman, 2013). In the US, several million people are exposed to arsenic levels in drinking water above 10 μg/L, the US Environmental Protection Agency (EPA) standard for arsenic in drinking water systems (Ayotte et al., 2011). In this study, we analyzed a representative sample of US adults who participated in the 2003–2010 National Health and Nutritional Examination Survey (NHANES) to advance our understanding of the association of inorganic arsenic exposure with serum uric acid levels and gout. 2. Methods 2.1. Study population NHANES 2003–2010, conducted by the US National Center for Health Statistics, used a stratified multistage sampling design to obtain a nationally representative sample of the civilian non-institutionalized population of the United States. A total of 27,152 adults of 20 years of age and older completed the NHANES 2003–2010 in-home interview and the medical evaluation at the mobile examination center. The mean participation rate was 76.5% and 76.4% for NHANES cycle 2003–2010 and 2007–2010, respectively. For urine arsenic analyses, NHANES 2003–2010 selected a one-third random sample of study participants aged 6 years and older. Among 6932 participants who had total urine arsenic measured, we excluded 54 participants who were missing urine arsenobetaine or dimethylarsinate (DMA), 265 participants missing blood lead, 523 participants missing alcohol status and 452 participants missing other covariates, and 6 participants with serum uric acid less than 2 mg/dL, as very low serum uric acid is often related to genetic or acquired disorders (Maesaka and Fishbane, 1998). The final sample size for analyses based on serum uric acid levels was 5632 participants. For analyses of the association between arsenic levels and the prevalence of gout, we restricted the sample to 3171 participants with information available on self-reported gout history in NHANES 2007–2010. Gout was rare before 40 years of age (only 2 women and 13 men). For this reason, and consistent with previous epidemiologic studies of gout, we further restricted the sample to participants aged 40 and older (n = 2133) (Krishnan et al., 2012). These NHANES cycles were approved by the institutional review board of the National Center for Health Statistics. Oral and written informed consent was obtained from all participants. 2.2. Measurement of urine arsenic Spot urine samples for metal analysis were obtained at the time of the physical examination in metal-free containers, shipped on dry ice, stored frozen at −70 °C or lower, and analyzed within 3 weeks of sampling (Caldwell et al., 2009; Centers for Disease Control and Prevention (CDC)). Total arsenic and arsenic species were measured at the Environmental Health Sciences Laboratory of the National Center for Environmental Health following a standardized protocol (Centers for Disease Control and Prevention (CDC)). Total urine arsenic was analyzed using inductively coupled-plasma dynamic reaction cell-mass spectrometry (ICP-DRC-MS) on a ELAN® 6100 DRCPlus or ELAN® DRC II (PerkinElmer Instruments, Headquarters Office, 710 Bridgeport Ave., Shelton, CT 06484-4794) (Caldwell et al., 2009). The limit of detection (LOD) for total arsenic was 0.6 μg/L in 2003–2004 and 0.74 μg/L in 2005 to 2010. A total of 57 (0.83%) participants had total urine arsenic levels below the LOD and values were imputed as the LOD divided by the square root of 2. For external calibration verification, NHANES used the National Institute of Standards and Technology standard reference material 2670 (NIST SRM 2670) (Centers for Disease Control and Prevention (CDC)). For total urine arsenic, interassay coefficients of variation of quality control-pooled samples analyzed throughout 2003–2010 ranged between 2.9% and 10.5%.

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Urine arsenic species (arsenite, arsenate, methylarsonate, dimethylarsinate (DMA), and arsenobetaine) were measured using high performance liquid chromatography (HPLC) to separate the species coupled to ICP-DRC-MS. The LOD for arsenite (1.2 μg/L), arsenate (1.0 μg/L), and monomethylarsonate (0.9 μg/L) resulted in 96.9%, 96.4%, and 65.0% of the arsenite, arsenate, and monomethylarsonate levels, respectively bthe LOD. Therefore, these three metabolites were not used in this analysis. The LODs for urine DMA and arsenobetaine were 1.7 and 0.4 μg/L, respectively. The percent of study participants with levels below the LOD was 15.5% for DMA and 29.7% for arsenobetaine. Undetected DMA and arsenobetaine values were imputed as the LOD divided by the square root of 2. The interassay coefficients of variation for quality control-pooled samples ranged between 2.4% and 6.6% for DMA and between 3.9% and 17.8% for arsenobetaine. Urine creatinine, used to account for urine dilution in spot urine samples, was measured by the modified kinetic Jaffé method in 2003–2006 and by an enzymatic (creatinase) method in 2007–2010 (National Health and Nutrition Examination Survey (NHANES), 2009). To improve the comparison of urine creatinine data between different instrumentations, we performed a piecewise square root transformed adjustment for urine creatinine concentrations before 2007 following the analytic recommendations of NHANES (National Health and Nutrition Examination Survey (NHANES), 2009). 2.3. Serum uric acid and gout From 2003 to 2010, frozen serum samples were sent to the Collaborative Laboratory Services at Ottumwa, Iowa, for uric acid analyses (Centers for Disease Control and Prevention (CDC)). In 2003–2007, serum uric acid was measured using a Beckman Synchron LX20 while in 2008–2010, a Beckman Coulter UniCel® DxC800 Synchron was used. Both systems used a timed endpoint colorimetric method (Town et al., 1985). No difference was noted between the two instruments in the mean value or the reference ranges. For participants aged ≥ 18 years, the reference range was 3.6–8.4 mg/dL for men and 2.9–7.5 mg/dL for women (Centers for Disease Control and Prevention (CDC)). The interassay coefficients of variation for serum uric acid ranged between 0.6% and 2.7% for NHANES 2003–2010. We defined gout as self-reported physician diagnosis or medication use (McAdams et al., 2011; Choi et al., 2004). Self-reported medical history of gout was obtained using the question “has a doctor or other health professional ever told you that you had gout?” Medication use for gout was obtained by self-reported use of allopurinol, colchicine, probenecid, or sulfinpyrazone during the medical history. 2.4. Other variables Sociodemographic variables collected during the in-home interview included age, race/ethnicity, sex, education, cigarette smoking, and alcohol consumption. Smoking was categorized as current, former, or never. Alcohol consumption was categorized as never (b12 drinks in any 1 year in life), former (≥12 drinks in any 1 year in life and not drinking now), and current (≥12 drinks in any 1 year in life and drinking now). Body mass index was calculated as weight in kilograms divided by height in meters squared. Diabetes mellitus was defined as a selfreported physician diagnosis, medication use or glucose levels higher or equal than 126 mg/dL (fasting 8 h or more) or 200 mg/dL (fasting less than 8 h). Hypertension was defined as a self-reported physician diagnosis, use of antihypertensive medication or systolic blood pressure N140 mm Hg or diastolic blood pressure N 90 mm Hg. Serum C-reactive protein was analyzed by latex-enhanced nephelometry. Serum total cholesterol was measured enzymatically using reagents and analyzers by Roche Diagnostics. Serum cotinine was measured by an isotopedilution high-performance liquid chromatography/atmospheric pressure chemical ionization tandem mass spectrometric method. Urine albumin was determined using fluorescein immunoassay by a Sequoia-Turner

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digital fluorometer (model 450). Serum creatinine was measured at Collaborative Laboratory Services at Ottumwa, Iowa, using a Beckman Synchron LX20 in 2003–2007 and a Beckman Coulter UniCel® DxC800 Synchron in 2008–2010. Both instruments use the Jaffe rate method (kinetic alkaline picrate) to determine creatinine concentrations. Kidney function was assessed by the estimated glomerular filtration rate (eGFR) using the CKD-EPI equation. Whole blood lead was measured using a multi-element analytical technique based on quadrupole ICP-DRC-MS technology (ELAN series DRC, PerkinElmer Instruments, Shelton, CT) (NCHS (National Center for Health Statistics), 2012). The LOD for blood lead was 0.25 μg/dL. A total of 8 participants were below the LOD and those values were imputed as the LOD divided by the square root of two (Hornung and Reed, 1990; Centers for Disease Control and Prevention (CDC), 2005). Daily total protein, sugar, and vitamin C intake and recent shellfish and fish exposure were assessed based on a food frequency questionnaire during the first 24-hour dietary recall interview.

2.5. Statistical analysis Analyses were performed separately for men and women due to major differences in serum uric acid concentrations by sex. Statistical analyses were performed using the sample survey commands in STATA version 12.0 statistical software (StataCorp LP, College Station, Texas) to account for the complex sampling design and to incorporate appropriate weights, primary sampling units, and strata in NHANES 2003–2010 and obtain unbiased point estimates and robust linearized standard errors. We calculated new 8-year sample weights for NHANES 2003–2010 by dividing each of the 2-year appropriate subsample weights by 4 as recommended by the National Center for Health Statistics. For gout analyses, we calculated another 4-year sample weights for NHANES 2007–2010 by dividing each 2-year appropriate subsample weights by 2. The 2-sided statistical significance level was set at α = 0.05. To assess inorganic arsenic exposure we used total urine arsenic and urine DMA concentrations and removed the contribution of seafood arsenicals adjusting for arsenobetaine, a biomarker of seafood intake and considered non-toxic (Navas-Acien et al., 2011). As seafood exposure may associate with the development of hyperuricemia and gout, adjusting for arsenobetaine, an objective proxy of seafood exposure, was important to control this potential confounder. We used linear regression models to examine the association between urine arsenic (total arsenic and DMA) and serum uric acid concentrations. Serum uric acid concentrations were right skewed and were log-transformed to improve normality. We also used logistic regression to estimate the odds ratio of hyperuricemia and gout. Hyperuricemia was defined as serum uric acid level higher than 7.0 mg/dL for men and higher than 6.0 mg/dL for women, similar to criteria used in previous studies (Krishnan et al., 2006; Iseki et al., 2004). Both in linear regression and logistic regression models, we entered urine total arsenic and DMA as quartiles (tertiles for gout analysis due to low number of events) and as continuous log-transformed variables, in separate models. We conducted several sensitivity analyses. First, we reported associations for study outcomes comparing urine total arsenic levels above and below 10 μg/g creatinine as the current US-EPA standard for arsenic in drinking water system is 10 μg/L. This approach can also help inform risk assessment of arsenic at a policy level. Second, we repeated the analyses further adjusting for daily total protein, sugar, and vitamin C intake and recent shellfish and fish exposure, with consistent findings (Supplementary Table 5). Third, we repeated the analyses without adjusting for dietary factors in NHANES cycle 2003–2012, showing similar results (Supplementary Table 6). Fourth, we additionally adjusted for NHANES cycles to control for time trends in hyperuricemia, prevalence of gout, and arsenic metabolites at the population level, yielding consistent results (data not shown).

Linear and logistic regression models were initially adjusted for sociodemographic and lifestyle variables including age (restricted cubic splines to improve data fitting), education (less than high school/high school/higher than high school), race/ethnicity (Non-Hispanic white/ Non-Hispanic black/Mexican-American/Others), smoking status defined by serum cotinine level, alcohol consumption (never/former/current) and BMI (restricted cubic splines to improve data fitting) followed by adjustments for comorbidities including diabetes mellitus, hypertension, C-reactive protein, estimated glomerular filtration rate, blood lead and cadmium levels, and medications including diuretics, beta-blockers and anti-gout agents. All models were adjusted for urine creatinine to account for urine dilution (Barr et al., 2005). Because total arsenic and DMA concentrations were strongly correlated with arsenobetaine (Spearman correlation coefficients 0.82 and 0.48, respectively, after dividing by creatinine to remove correlation due to urine dilution), we ran additional analyses for total arsenic and DMA without adjustment for arsenobetaine concentrations but restricted to participants with very low arsenobetaine (b1 μg/L), to ensure that total arsenic and DMA reflected exposure to inorganic arsenic and not exposure to organic arsenicals in seafood. This approach avoided multicollinearity and restricted the study population to those in whom total urine arsenic most likely represents inorganic arsenic exposure. Exploratory subgroup analyses, separately for men and women, were conducted by including the product of log-transformed arsenic levels with the following covariates: age, race/ethnicity, smoking status (never/former/current), hypertension, diabetes mellitus, BMI, estimated glomerular filtration rate, blood lead levels and blood cadmium levels. Fully-adjusted regression models were checked for multicollinearity using variance inflation factor (VIF) as markers of arsenic exposure (total arsenic and DMA) and arsenobetaine were highly correlated. The maximum VIF of any of our explanatory variables when markers of arsenic exposure (total arsenic and DMA) were simultaneously in the model was less than 2, indicating that multicollinearity was not a serious problem in our models (Mukherjee et al., 1998). 3. Results Median serum uric acid was 6.0 mg/dL in men and 4.7 mg/dL in women. Median total urine arsenic and urine DMA concentrations were 7.5 and 3.3 μg/g creatinine, respectively, in men and 8.7 and 4.1 μg/g creatinine , respectively, in women. Both in men and women, total arsenic and DMA were higher in participants from other races/ethnicities, in former smokers, and in former alcohol drinkers and lowest in participants with high school education (Table 1). Among participants with no recent seafood intake (arsenobetaine ≤ 1 μg/L), the percentage of participants having urine arsenic levels higher than 10 μg/g creatinine among men and women with hyperuricemia was 12.2% and 9.6%, respectively. The Spearman correlation coefficient between creatinine-corrected total arsenic and DMA was 0.73 (95% CI, 0.72–0.74). The Spearman correlation coefficient between total urine arsenic and blood lead levels was 0.09 (0.06–0.12) and between DMA and blood lead levels it was 0.09 (0.07–0.12). 3.1. Urine arsenic, serum uric acid and hyperuricemia The increase in serum uric acid concentrations associated with an increase in one interquartile range of total arsenic and DMA concentrations were 3% (95% confidence interval [CI] 2, 5) and 3% (2,5), respectively, in men and 1% (0, 3) and 2% (0, 4), respectively, in women (Table 2, model 3). p-Values of interaction for serum uric acid concentrations by sex were 0.16 for total arsenic and 0.06 for DMA. In both sexes combined, the fully adjusted geometric mean ratios per interquartile range for total arsenic and DMA were 1.02 (1.01, 1.03) and 1.03 (1.01, 1.04), respectively (Supplementary Table 1). In analyses restricted to participants with very low arsenobetaine concentrations (≤1 μg/L) (N = 2569), the adjusted geometric mean ratios per interquartile range

C.-C. Kuo et al. / Environment International 76 (2015) 32–40

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Table 1 Median (IQR) of creatinine-adjusted urine arsenic and serum uric acid concentrations by participants' characteristics. Men (n = 2875) Characteristics

Age (years) 20–50 50–65 ≥65 p-Value⁎

n

1493 663 719

Women (n = 2757)

Total arsenic

DMA

Serum uric acid

(μg/g)

(μg/g)

(mg/dL)

6.9 (4.1–13.7) 8.3 (4.6–17.0) 9.1 (5.0–18.3) b0.01

3.2 (2.1–5.1) 3.4 (2.2–5.8) 3.5 (2.5–5.5) b0.01

6 (5.2–6.9) 5.9 (5.2–6.9) 5.9 (5.1–6.9) 0.95

3.7 (2.4–6.3) 3.2 (2.0–5.1) 3.3 (2.2–5.4) b0.01

Education bHigh school 377 7.6 (4.7–14.8) =high school 1211 6.6 (4.0–13.0) Nhigh school 1287 8.1 (4.6–16.7) p-Value b0.01 Race/ethnicity Non-Hispanic white 1478 7.1 (4.2–13.9) Non-Hispanic black 568 6.6 (3.8–13.5) Mexican-American 544 7.4 (4.6–14.5) Others 285 11.9 (6.8–27.8) p-Value b0.01 Smoking Never 1220 7.5 (4.5–15.9) 945 8.2 (4.7–16.8) Former Current 710 6.5 (3.8–12.9) p-Value b0.01 Alcohol Never 556 7.9 (4.7–16.9) Former 808 8.3 (4.5–18.1) Current 1511 6.8 (4.1–12.9) p-Value b0.01 Body mass index 803 8.3 (4.5–16.0) b25 kg/m2 2072 7.3 (4.3–14.7) ≥25 kg/m2 p-Value 0.01 Hypertension Yes 1433 8.0 (4.5–16.1) No 1442 7.1 (4.2–14.4) p-Value 0.37 Diabetes mellitus Yes 414 7.4 (4.6–14.5) No 2461 7.5 (4.3–15.1) p-Value 0.72 Estimated glomerular filtration rate (mL/min/1.73 m2) ≥60 2614 7.4 (4.3–15.0) b60 261 8.8 (5.4–16.8) p-Value 0.16 Albuminuria b30 mg/g 2527 7.4 (4.3–15.0) 30–300 mg/g 288 8.1 (4.7–17.0) N300 mg/g 60 9.4 (4.8–16.8) p-Value 0.53 Total cholesterol level ≤200 mg/dL 1655 7.6 (4.4–15.0) N200 mg/dL 1220 7.4 (4.3–15.3) p-Value 0.52 a Serum uric acid (mg/dL) Hypouricemia 44 5.7 (4.6–10.8) Normouricemia 2694 7.5 (4.3–15.0) Hyperuricemia 137 8.3 (4.7–17.0) p-Value 0.25

n

Total arsenic

DMA

Serum uric acid

(μg/g)

(μg/g)

(mg/dL)

1416 666 675

7.7 (4.6–15.6) 9.9 (5.5–23.9) 9.3 (5.6–19.4) b0.01

3.6 (2.4–5.9) 4.8 (3.2–8.0) 4.6 (3.1–7.2) b0.01

4.4 (3.8–5.1) 4.9 (4.2–5.8) 5.2 (4.4–6.1) b0.01

5.9 (5.1–6.9) 5.9 (5.1–6.8) 6.1 (5.3–6.9) 0.01

402 1277 1653

10.4 (5.5–18.9) 7.1 (4.6–13.8) 9.4 (5.3–20.0) b0.01

4.6 (2.7–7.8) 3.6 (2.4–5.8) 4.3 (2.9–7.1) b0.01

4.7 (3.9–5.6) 4.7 (4.0–5.7) 4.6 (3.9–5.4) 0.03

3.2 (2.1–5.0) 2.6 (1.8–4.4) 3.8 (2.5–5.8) 5.7 (3.5–10.2) b0.01

6.0 (5.2–6.9) 6.0 (5.2–7.0) 5.7 (5.1–6.5) 6.0 (5.2–7.0) b0.01

1386 535 510 326

8.3 (4.8–16.9) 8.1 (4.4–16.9) 8.7 (5.7–14.8) 15.6 (7.6–38.6) b0.01

4.0 (2.7–6.5) 3.2 (2.1–5.1) 4.4 (3.1–6.6) 6.7 (4.0–11.0) b0.01

4.7 (4.0–5.5) 4.9 (4.0–5.8) 4.4 (3.8–5.1) 4.5 (3.8–5.2) b0.01

3.3 (2.1–5.3) 3.4 (2.3–5.5) 3.0 (2.1–5.0) 0.06

6.0 (5.2–6.9) 6.1 (5.3–7.1) 5.8 (5.0–6.6) b0.01

1697 563 497

8.9 (5.0–18.7) 9.4 (5.4–19.2) 6.9 (4.4–13.8) b0.01

4.2 (2.7–6.9) 4.4 (2.9–6.5) 3.4 (2.3–5.8) b0.01

4.6 (4.0–5.5) 4.8 (4.0–5.8) 4.6 (3.9–5.4) 0.07

3.4 (2.2–5.6) 3.4 (2.3–5.6) 3.1 (2.1–5.1) 0.06

5.9 (5.2–6.8) 6.0 (5.2–6.9) 6.0 (5.2–6.9) 0.94

723 692 1342

9.2 (5.2–18.7) 9.3 (5.2–19.6) 7.9 (4.8–15.8) b0.01

4.3 (2.9–6.7) 4.2 (2.6–7.1) 3.8 (2.6–6.5) 0.02

4.6 (3.8–5.4) 4.6 (4.0.5.3) 4.8 (4.0–5.7) b0.01

3.6 (2.2–6.0) 3.2 (2.2–5.1) 0.01

5.5 (4.8–6.2) 6.2 (5.4–7.1) b0.01

845 1912

9.5 (5.3–20.0) 8.2 (4.8–16.9) b0.01

4.4 (2.8–7.5) 3.9 (2.7–6.2) b0.01

4.2 (3.6–4.8) 5.0 (4.2–5.8) b0.01

3.2 (2.1–5.2) 3.3 (2.2–5.6) 0.28

6.1 (5.2–7.1) 5.9 (5.2–6.6) b0.01

1465 1292

8.9 (5.0–18.3) 8.4 (4.9–17.7) 0.41

4.2 (2.8–6.8) 4.0 (2.6–6.4) 0.02

5.0 (4.1-5.9) 4.5 (3.8–5.1) b0.01

3.2 (2.1–5.4) 3.3 (2.2–5.3) 0.31

5.8 (4.9–7.0) 6.0 (5.2–6.9) 0.10

380 2377

8.6 (4.9–18.0) 8.7 (5.0–17.9) 0.77

4.1 (2.7–6.6) 4.0 (2.8–7.0) 0.36

5.3 (4.4–6.2) 4.6 (3.9–5.4) b0.01

3.2 (2.1–5.3) 3.7 (2.6–5.6) 0.14

5.9 (5.2–6.8) 6.7 (5.7–8.0) b0.01

2457 300

8.7 (5.0–17.9) 7.8 (4.7–17.8) 0.30

4.1 (2.7–6.7) 3.7 (2.6–6.1) 0.02

4.6 (3.9–5.4) 5.8 (5.0–6.9) b0.01

3.2 (2.1–5.3) 3.7 (2.4–5.7) 4.3 (2.9–6.2) 0.22

5.9 (5.2–6.8) 6.3 (5.4–7.2) 6.6 (5.6–8.5) b0.01

2451 269 37

8.7 (5.0–17.7) 9.1 (5.0–19.4) 9.4 (6.6–18.2) 0.42

4.0 (2.7–6.6) 3.9 (2.8–8.4) 5.8 (3.4–7.4) 0.10

4.7 (4.0–5.5) 4.8 (4.0–6.0) 5.5 (4.1–6.8) 0.05

3.2 (2.1–5.2) 3.3 (2.2–5.5) 0.16

5.8 (5.1–6.7) 6.2 (5.3–7.1) b0.01

1436 1321

8.2 (4.7–16.5) 9.1 (5.3–18.9) 0.03

3.8 (2.6–6.3) 4.3 (2.9–6.8) b0.01

4.5 (3.8–5.3) 4.9 (4.1–5.7) b0.01

2.7 (2.2–3.8) 3.3 (2.2–5.3) 3.8 (2.2–5.6) 0.35

3.3 (3.1–3.4) 5.9 (5.2–6.8) 8.9 (8.6–9.4) b0.01

67 2589 101

6.9 (5.0–18.0) 8.7 (5.0–17.9) 7.8 (4.2–16.5) 0.60

3.7 (2.8–4.8) 4.1 (2.7–6.7) 3.4 (2.7–5.3) 0.14

2.6 (2.3–2.8) 4.7 (4–5.4) 8.1 (7.9–8.7) b0.01

a The cut-off for hypouricemia and hyperuricemia is 3.6–8.4 mg/dL for men and 2.9–7.5 mg/dL for women according to the NHANES Laboratory Procedure Manual (2003–2010). ⁎ p-Value denoted the probability of observing the difference among each categorical variable containing two or more groups. The statistical significance was defined at p-value b 0.05.

for total arsenic and DMA were 1.02 (1.00, 1.04) and 1.03 (1.01, 1.05), respectively, for men and 1.01 (0.98, 1.03) and 0.99 (0.96, 1.02), respectively, for women. The results for hyperuricemia were very similar to those for uric acid levels in both men and women (Table 3; model 3 and Supplementary Table 2). The adjusted odds ratios for hyperuricemia in men with very low arsenobetaine concentrations were 1.54 (1.05, 2.26) for an interquartile range in total arsenic and 1.66 (1.04, 2.67) for an interquartile range in DMA. In women with very low arsenobetaine concentrations, the corresponding odds ratios were 0.98 (0.63, 1.51) for total arsenic

and 1.11 (0.70, 1.76) for DMA. Blood lead levels were significantly associated with serum uric acid after multivariable adjustment (the adjusted ratio of geometric means of serum uric acid was 3% (95% CI 1.02–1.04) higher per interquartile range (IQR) of blood lead level). Adjustment for blood lead, however, did not change the association between arsenic and uric acid levels or hyperuricemia. Finally, the adjusted odds ratio for hyperuricemia comparing urine total arsenic above vs. below 10 μg/g creatinine was 1.60 (95% CI 1.16–2.19) among men, 1.06 (95% CI 0.79–1.42) among women, and 1.33 (95% CI 1.06–1.69) for men and women combined.

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Table 2 Ratio (95% confidence intervals) of geometric means of serum uric acid by urine arsenic concentrations. Men (n = 2875)

Total arsenic (μg/L) Quartile 1 (≤4.2) Quartile 2 (N4.2 & ≤8.2) Quartile 3 (N8.2 & ≤17.3) Quartile 4 (N17.3) p-Trend Per IQRa Dimethylarsinate (μg/L) Quartile 1 (≤2.0) Quartile 2 (N2.0 & ≤3.6) Quartile 3 (N3.6 & ≤6.0) Quartile 4 (N6.0) p-Trend Per IQRa

Women (n = 2757)

Model 1

Model 2

Model 3

Model 1

Model 2

Model 3

1.00 (Ref) 1.01 (0.98–1.04) 1.03 (1.00–1.07) 1.04 (1.00–1.08) 0.02 1.03 (1.01–1.04)

1.00 (Ref) 1.01 (0.99–1.04) 1.04 (1.02–1.07) 1.06 (1.03–1.09) b0.01 1.03 (1.02–1.05)

1.00 (Ref) 1.01 (0.99–1.04) 1.04 (1.02–1.07) 1.05 (1.02–1.09) b0.01 1.03 (1.02–1.05)

1.00 (Ref) 1.00 (0.97–1.03) 0.98 (0.95–1.01) 0.98 (0.95–1.02) 0.39 1.00 (0.98–1.01)

1.00 (Ref) 1.02 (0.98–1.05) 1.01 (0.98–1.04) 1.02 (0.99–1.06) 0.21 1.01 (1.00–1.03)

1.00 (Ref) 1.01 (0.98–1.05) 1.01 (0.98–1.04) 1.03 (0.99–1.06) 0.18 1.01 (1.00–1.03)

1.00 (Ref) 1.00 (0.97–1.03) 1.00 (0.97–1.04) 1.03 (1.00–1.07) 0.02 1.02 (1.00–1.04)

1.00 (Ref) 1.00 (0.98–1.02) 1.01 (0.98–1.04) 1.05 (1.02–1.08) b0.01 1.03 (1.02–1.05)

1.00 (Ref) 1.00 (0.97–1.02) 1.01 (0.98–1.04) 1.04 (1.01–1.07) b0.01 1.03 (1.02–1.05)

1.00 (Ref) 1.00 (0.97–1.04) 0.99 (0.96–1.02) 1.00 (0.95–1.04) 0.82 1.00 (0.98–1.02)

1.00 (Ref) 1.02 (0.99–1.05) 1.01 (0.99–1.04) 1.03 (1.00–1.07) 0.08 1.02 (1.00–1.03)

1.00 (Ref) 1.02 (0.99–1.05) 1.01 (0.99–1.04) 1.03 (1.00–1.07) 0.07 1.02 (1.00–1.04)

Model 1: Adjusted for age, race, education, urine creatinine, and urine arsenobetaine. Model 2: Further adjusted for smoking, alcohol, body mass index, hypertension, diabetes, estimated glomerular filtration rate, albuminuria, C-reactive protein, blood cadmium and blood lead. Model 3: Further adjusted for diuretics, anti-gout medications, and beta-blockers. a Among log-transformed urine arsenic concentrations (N17.3 vs ≤4.20 for total arsenic and N6.0 vs ≤2.0 for DMA).

3.2. Urine arsenic concentrations and gout

3.3. Exploratory subgroup analyses

The weighted prevalence of gout in the population 40 years and older was 8.3% in men and 2.2% in women (with a weighted prevalence of anti-gout medication 2.4% in men and 0.4% in women). The adjusted odds ratio (95% CI) of gout comparing the interquartile range in total urine arsenic concentrations was 1.15 (0.71, 1.89) in men and 3.44 (1.26, 9.38) in women (Table 4, model 3). The corresponding odds ratios for DMA were 0.93 (0.59, 1.46) in men and 1.62 (0.69, 3.81) in women. Further adjustment for estrogen use showed similar results (Supplementary Table 3). p-Values of interaction for gout by sex were 0.53 for total arsenic and 0.82 for DMA. In sex-pooled analysis, the adjusted odds ratios comparing the highest tertile to lowest tertile were 1.86 (0.99, 3.49) for total arsenic and 1.27 (0.61, 2.66) for DMA (Supplementary Table 4). The adjusted odds ratio for gout comparing urine total arsenic above vs. below 10 μg/g creatinine was 1.50 (95% CI 0.94–2.40) among men and women combined.

Among men, the association between arsenic and hyperuricemia was consistent for most subgroups evaluated except for stronger associations between DMA and hyperuricemia among participants without diabetes and between total arsenic and hyperuricemia among participants with BMI over 25 kg/m2 (Fig. 1). In women, the lack of association between urine arsenic and hyperuricemia was also consistent across subgroups, except among former smokers and hypertension (Fig. 2). 4. Discussion In this large cross-sectional study in NHANES 2003–2010, arsenic exposure, as measured in urine, was associated with higher serum uric acid levels and increased prevalence of hyperuricemia in men but not with self-reported gout. In women, urine arsenic was associated with selfreported gout, but not with serum uric acid level and hyperuricemia.

Table 3 Odds ratios (95% confidence interval) of hyperuricemia (defined as serum uric acid level ≥ 7 for men and ≥6 for women) by urine arsenic concentrations. Men (n = 2875)

Total arsenic (μg/L) Quartile 1 (≤4.2) Quartile 2 (N4.2 & ≤8.2) Quartile 3 (N8.2 & ≤17.3) Quartile 4 (N17.3) p-Trend Per IQRa Dimethylarsinate (μg/L) Quartile 1 (≤2.0) Quartile 2 (N2.0 & ≤3.6) Quartile 3 (N3.6 & ≤6.0) Quartile 4 (N6.0) p-Trend Per IQRa

Women (n = 2757)

C/NC

Model 1

Model 2

Model 3

n (C/NC)

Model 1

Model 2

Model 3

97/442 157/557 191/609 205/617

1.00 (Ref) 1.20 (0.83–1.74) 1.36 (0.89–2.08) 1.55 (1.04–2.30) 0.06 1.31 (1.08–1.58)

1.00 (Ref) 1.26 (0.89–1.79) 1.53 (1.03–2.29) 1.87 (1.27–2.76) b0.01 1.47 (1.21–1.79)

1.00 (Ref) 1.24 (0.87–1.76) 1.54 (1.03–2.30) 1.84 (1.26–2.68) b0.01 1.46 (1.20–1.77)

121/634 138/571 128/536 119/510

1.00 (Ref) 1.24 (0.84–1.83) 1.05 (0.74–1.48) 0.88 (0.56–1.36) 0.22 0.90 (0.75–1.08)

1.00 (Ref) 1.45 (0.95–2.22) 1.39 (0.94–2.07) 1.21 (0.75–1.95) 0.98 1.05 (0.85–1.30)

1.00 (Ref) 1.44 (0.95–2.20) 1.43 (0.95–2.16) 1.26 (0.77–2.07) 0.89 1.07 (0.86–1.35)

1.00 (Ref) 0.98 (0.72–1.31) 0.94 (0.67–1.32) 1.25 (0.87–1.78) 0.08 1.16 (0.98–1.36)

1.00 (Ref) 0.94 (0.69–1.27) 1.04 (0.75–1.45) 1.46 (1.04–2.04) b0.01 1.34 (1.13–1.59)

1.00 (Ref) 0.91 (0.67–1.25) 1.05 (0.75–1.46) 1.41 (1.01–1.96) 0.01 1.30 (1.09–1.55)

122/650 135/558 115/499 134/544

1.00 (Ref) 1.27 (0.90–1.80) 0.88 (0.61–1.28) 1.01 (0.69–1.46) 0.69 0.97 (0.79–1.18)

1.00 (Ref) 1.60 (1.14–2.25) 1.14 (0.77–1.67) 1.48 (0.95–2.29) 0.26 1.19 (0.94–1.49)

1.00 (Ref) 1.61 (1.16–2.25) 1.19 (0.82–1.73) 1.49 (0.96–2.31) 0.25 1.22 (0.97–1.54)

650/2225 97/423 162/555 159/608 232/639 650/2225

506/2251

506/2251

C: cases; NC: non-cases. Model 1: Adjusted for age, race, education, urine creatinine, and urine arsenobetaine. Model 2: Further adjusted for smoking, alcohol, body mass index, hypertension, diabetes, estimated glomerular filtration rate, albuminuria, C-reactive protein, blood cadmium, and blood lead. Model 3: Further adjusted for diuretics, anti-gout medications, and beta-blockers. a Among log-transformed urine arsenic concentrations (N17.3 vs. ≤ 4.20 for total arsenic and N6.0 vs. ≤2.0 for dimethylarsinate).

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Table 4 Odds ratios (95% confidence intervals) of gout by urine arsenic concentrationsa. Men (N = 1048) C/NC Total arsenic (μg/L) Tertile 1 (≤5.2) Tertile 2 (N5.2 & ≤12.5) Tertile 3 (N12.5) p-Trend Per IQRb Dimethylarsinate (μg/L) Tertile 1 (≤2.5) Tertile 2 (N2.5 & ≤ 4.8) Tertile 3 (N4.8) p-Trend Per IQRb

25/238 40/315 48/382 113/935 29/235 41/311 43/389 113/935

Women (N = 1085)

Model 1

Model 2

Model 3

C/NC

Model 1

Model 2

Model 3

1.00 (Ref) 1.41 (0.81–2.47) 1.53 (0.77–3.05) 0.40 1.24 (0.80–1.92)

1.00 (Ref) 1.64 (0.89–3.03) 1.46 (0.67–3.20) 0.70 1.19 (0.72–1.96)

1.00 (Ref) 1.57 (0.84–2.94) 1.40 (0.64–3.08) 0.75 1.15 (0.71–1.89)

7/396 12/340 11/319

1.00 (Ref) 2.17 (0.98–4.82) 3.65 (1.31–10.14) 0.03 2.53 (1.09–5.90)

1.00 (Ref) 2.82 (1.12–7.10) 4.79 (1.63–14.1) 0.02 3.07 (1.27–7.41)

1.00 (Ref) 3.07 (1.17–8.08) 5.46 (1.70–17.6) 0.01 3.44 (1.26–9.38)

1.00 (Ref) 1.34 (0.69–2.63) 1.37 (0.58–3.26) 0.57 1.10 (0.75–1.61)

1.00 (Ref) 1.52 (0.68–3.37) 1.24 (0.44–3.51) 0.90 0.96 (0.62–1.50)

1.00 (Ref) 1.43 (0.66–3.13) 1.19 (0.42–3.37) 0.94 0.93 (0.59–1.46)

11/396 12/323 7/336

1.00 (Ref) 1.33 (0.65–2.73) 1.34 (0.48–3.75) 0.59 1.30 (0.60–2.84)

1.00 (Ref) 1.64 (0.81–3.32) 1.89 (0.65–5.46) 0.24 1.58 (0.71–3.54)

1.00 (Ref) 1.83 (0.85–3.90) 1.98 (0.64–6.15) 0.24 1.62 (0.69–3.81)

30/1055

30/1055

C: cases; NC: non-cases. Model 1: Adjusted for age, race, education, urine creatinine, and urine arsenobetaine. Model 2: Further adjusted for smoking, alcohol, body mass index, hypertension, diabetes, estimated glomerular filtration rate, albuminuria, C-reactive protein, blood cadmium, and blood lead. Model 3: Further adjusted for diuretics and beta-blockers. a The analysis was restricted to men and women ≥40 years in NHANES 2007–2010 (N = 2133). b Log-transformed urine arsenic concentrations (percentiles 25th and 75th were 4.1 and 17.3 for total arsenic and 2.0 and 5.9 for DMA, respectively).

While our study indicates that arsenic may play a role in the development of hyperuricemia and gout, the study needs to be interpreted with caution due to possible sex-differences in hyperuricemia and gout, the crosssectional design, and the small number of cases of self-reported gout in women (Weaver, 2008; Doherty, 2009).

Little is known about the association of arsenic exposure with uric acid and gout. In a small study conducted in Northern Mexico enrolling mostly women (85 women vs. 12 men), high arsenic exposure in drinking water (mean 130 μg/L) was associated with hypouricemia and hypouricosuria (Del-Razo et al., 2003). Another study from India also

Fig. 1. Odds ratio (ORs) for hyperuricemia comparing the 75th with 25th percentile of the total arsenic and dimethylarsinate (DMA) in men (N = 2875), by participant characteristics, National Health and Nutrition Examination Survey, 2003–2010. The 75th and 25th percentiles were 17.3 and 4.2 μg/L for total arsenic and 6.0 and 2.0 μg/L for dimethylarsinate. Odds ratios were adjusted by age, education (bhigh school, =high school, Nhigh school), race/ethnicity, smoking (never, former, current), alcohol (never, former, current), body mass index (kg/m2), hypertension (yes, no), diabetes (yes, no), estimated glomerular filtration rate (mg/min/1.73 m2), albuminuria (mg/g), C-reactive protein (mg/dL), blood cadmium (μg/L), and blood lead (μg/L). For all arsenic measures, urine creatinine was adjusted to account for urine dilution and urine arsenobetaine was adjusted for total arsenic and DMA. Estimated 2-sided p values for the interaction between all urine species with participants' characteristics were computed by using the Wald test adjusting for complex design.

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Fig. 2. Odds ratio (ORs) for hyperuricemia comparing the 75th with 25th percentile of the total arsenic and dimethylarsinate (DMA) in women (N = 2757), by participant characteristics, National Health and Nutrition Examination Survey, 2003–2010. The 75th and 25th percentiles were 17.3 and 4.2 μg/L for total arsenic and 6.0 and 2.0 μg/L for dimethylarsinate. Odds ratios were adjusted by age, education (bhigh school, =high school, Nhigh school), race/ethnicity, smoking (never, former, current), alcohol (never, former, current), body mass index (kg/m2), hypertension (yes, no), diabetes (yes, no), estimated glomerular filtration rate (mg/min/1.73 m2), albuminuria (mg/g), C-reactive protein (mg/dL), blood cadmium (μg/L), and blood lead (μg/L). For all arsenic measures, urine creatinine was adjusted to account for urine dilution and urine arsenobetaine was adjusted for total arsenic and DMA. Estimated 2-sided p values for the interaction between all urine species with participants' characteristics were computed by using the Wald test adjusting for complex design.

found that high arsenic levels in drinking water (N100 μg/L) were associated with hypouricemia in both men and women and speculated that this could be related to the consumption of serum uric acid as an antioxidant against arsenic induced oxidative stress (Maiti et al., 2012; Ames et al., 1981; Lu et al., 2010). Animal studies have found both hyper and hypouricemia induced by arsenic, although arsenic exposure levels were relatively high (Saxena et al., 2009; Jauge and Del-Razo, 1985). The generalizability of these human and animal studies to populations exposed to low–moderate inorganic arsenic levels in drinking water, such as the US, is unclear. In our study, indeed, the associations were in the opposite direction. The sex differences in the association between arsenic on uric acid and gout are less conclusive. In our study, the association in men was clear with hyperuricemia but not with gout, although the p-value for interaction by sex was not significant. In women, we found the opposite, a possible association with gout but not with hyperuricemia. However, among female participants with hyperuricemia (serum uric acid ≥ 6 mg/dL), the odds ratio of gout for an interquartile range increase in urine total arsenic was strengthened to 7.59 (95% CI 1.17–49.4). As the positive relationship between hyperuricemia and gout has long been established in men (Campion et al., 1987; Choi et al., 2005), large prospective evidence supporting the role of hyperuricemia in gout among women has been available only recently (Bhole et al., 2010). Female gout has different clinical features relative to men including more inflammation in the upper limb joints, multiple joints involved, and less recurrence. The risk profile is also different. Female gout is related to diuretic use and comorbidities such as hypertension and impaired renal function (Bhole et al., 2010; De Souza et al., 2005; Harrold et al., 2006) and less to genetic variants (Zhang et al., 2013). The influence of sex on arsenic metabolism, as measured in urine, has been recognized for

many years (Kristiansen et al., 1997). Men have lower relative proportions of DMA in urine compared to women. Unfortunately we could not evaluate the association between arsenic metabolism and uric acid as inorganic arsenic and MMA, species that are essential to understand arsenic metabolism, had high LODs in NHANES. Future research is warranted to elucidate underlying mechanisms of sex differences in the epidemiological profile between arsenic, hyperuricemia and gout. We also found that diabetes status modified the association between arsenic and hyperuricemia in men. In men, the association between arsenic and serum uric acid levels was observed mostly in those without diabetes. While some reports support the inverse relationship between serum uric acid level and diabetes (Bandaru and Shankar, 2011; Nan et al., 2007), this issue remains controversial as other reports have opposite findings (Dehghan et al., 2008; Kramer et al., 2009). Overweight and obesity (BMI ≥ 25 kg/m2) and hypertension also modified the association between arsenic and hyperuricemia in men and women, respectively. In the absence of a strong biologic hypothesis for the association between arsenic and serum uric acid levels, the subgroup analyses need to be interpreted with caution. The cross-sectional design is a major limitation of this study. Exposure and outcome were measured at the same time and we cannot evaluate temporality of the association. The diagnosis of gout was based on self-report. However, the case definition used has been validated in previous epidemiological studies (Gelber et al., 1997). The small number of cases of gout in women was an additional limitation. In this study we were able to adjust for many factors that affect serum uric acid level. Our study, moreover, was conducted in a population with mostly normal kidney function and the findings persisted after adjustment for eGFR. Although dietary factors such as fructose, meat, coffee, vegetables and fiber intake (Choi et al., 2005, 2007, 2010) have been related to

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hyperuricemia/gout, the relevance of these factors remains under debate (Sun et al., 2010; Wang et al., 2012). Regarding confounding by seafood, for total arsenic and DMA, we adjusted for arsenobetaine as an objective biomarker of seafood intake in order to evaluate the association for arsenic that is not derived from seafood. Finally, our sensitivity analyses among participants with very low arsenobetaine levels, adjusting for seafood and daily total protein, sugar, and vitamin C intake, and joint analyses with the latest NHANES cycle 2011–2012 all showed consistent results. Our findings may motivate experimental and mechanistic research to investigate the biological mechanisms linking environmentally relevant arsenic exposure levels to hyperuricemia. 5. Conclusion Low-level arsenic exposure was associated with increasing serum uric acid level and the prevalence of hyperuricemia among a representative sample of US men and with serum uric acid and increased prevalence of gout in women. Experimental and mechanistic studies at relevant exposure levels and prospective studies in humans are needed to confirm the associations among environmental arsenic exposures, serum uric acid, and gout. Potential conflicts of interest All authors report no conflicts of interest. Appendix A. Supplementary data Supplementary data to this article can be found online at http://dx. doi.org/10.1016/j.envint.2014.11.015. References Ames, B.N., Cathcart, R., Schwiers, E., Hochstein, P., 1981. Uric acid provides an antioxidant defense in humans against oxidant- and radical-caused aging and cancer: a hypothesis. Proc. Natl. Acad. Sci. U. S. A. 78, 6858–6862. Ayotte, J.D., Gronberg, J.M., Apodaca, L.E., 2011. Trace elements and radon in groundwater across the United States, 1992–2003. Scientific Investigations Report 2011–5059. Bandaru, P., Shankar, A., 2011. Association between serum uric acid levels and diabetes mellitus. Int. J. Endocrinol. 2011, 604715. Barr, D.B., Wilder, L.C., Caudill, S.P., Gonzalez, A.J., Needham, L.L., Pirkle, J.L., 2005. Urinary creatinine concentrations in the U.S. population: implications for urinary biologic monitoring measurements. Environ. Health Perspect. 113, 192–200. Bhole, V., de Vera, M., Rahman, M.M., Krishnan, E., Choi, H., 2010. Epidemiology of gout in women: fifty-two-year followup of a prospective cohort. Arthritis Rheum. 62, 1069–1076. Caldwell, K.L., Jones, R.L., Verdon, C.P., Jarrett, J.M., Caudill, S.P., Osterloh, J.D., 2009. Levels of urinary total and speciated arsenic in the us population: National Health and Nutrition Examination Survey 2003–2004. J. Expo. Sci. Environ. Epidemiol. 19, 59–68. Campion, E.W., Glynn, R.J., DeLabry, L.O., 1987. Asymptomatic hyperuricemia. Risks and consequences in the normative aging study. Am. J. Med. 82, 421–426. Centers for Disease Control and Prevention (CDC), 2005. Us Department of Health and Human Services. Third National Report on Human Exposure to Environmental Chemicals. Centers for Disease Control and Prevention, Atlanta, GA. Centers for Disease Control and Prevention (CDC). National Center for Health Statistics. Centers for Disease Control and Prevention Website. Documentation, codebook, & frequencies: laboratory component: total and speciated arsenic NHANES 2003–2004, 2005–2006, 2007–2008, 2009–2010. Centers for Disease Control and Prevention (CDC). National Health and Nutrition Examination Survey (NHANES). Laboratory procedure manual. 2003–4, 2005–6, 2007–8, 2009–10. Choi, H.K., Atkinson, K., Karlson, E.W., Willett, W., Curhan, G., 2004. Purine-rich foods, dairy and protein intake, and the risk of gout in men. N. Engl. J. Med. 350, 1093–1103. Choi, H.K., Mount, D.B., Reginato, A.M., 2005. Pathogenesis of gout. Ann. Intern. Med. 143, 499–516. Choi, H.K., Willett, W., Curhan, G., 2007. Coffee consumption and risk of incident gout in men: a prospective study. Arthritis Rheum. 56, 2049–2055. Choi, H.K., Willett, W., Curhan, G., 2010. Fructose-rich beverages and risk of gout in women. JAMA 304, 2270–2278. De Souza, A., Fernandes, V., Ferrari, A.J., 2005. Female gout: clinical and laboratory features. J. Rheumatol. 32, 2186–2188. Dehghan, A., van Hoek, M., Sijbrands, E.J., Hofman, A., Witteman, J.C., 2008. High serum uric acid as a novel risk factor for type 2 diabetes. Diabetes Care 31, 361–362.

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