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PRELIMINARY

COMMUNICATION

Arsenic Exposure and Prevalenceof Type 2 Diabetes in US Adults

Ana Navas-Acien, MD, PhD

Ellen K. Silbergeld, PhD

Roberto Pastor-Barriuso, PhD

Eliseo Guallar, MD, DrPH

INORGANIC ARSENIC IS HIGHLY TOXIC

and carcinogenic for humans.1,2

Millions of individuals worldwideareexposed to drinking water con-

taminated with inorganicarsenicmainlyfrom natural mineral deposits.3 In theUnited States, approximately 13 mil-lion individuals live in areas with a con-centration of inorganic arsenic in thepublic water supply that exceeds 10g/L, which is the US EnvironmentalProtection Agencys standard for ar-senic concentration in publicwater sys-tems.4

Inorganic arsenic at relatively high

concentrations increased glucose andinsulin levels in animal models,5 de-creased glucose uptake in insulin-sensitive cells,6-8 and interfered withtranscription factors involved in insu-lin signal transduction and insulin sen-sitivity in vitro.8-11 In epidemiologicstudies from Taiwan, Bangladesh, andMexico, high chronic exposure to in-organic arsenic in drinking water(100 g/L) was associated with dia-betes.12-18 High chronic exposure to in-organic arsenic in occupational set-

tings was also related to higher levelsof glycated hemoglobin, a marker ofblood glucose levels.19 However, theeffect of lower levels of exposure to in-organic arsenic on diabetes risk islargely unknown.20-23

In addition to inorganic arsenic,humans are exposed to organic arseniccompounds, such as arsenobetaine andarsenosugars,mainlyfromseafood.24 Thebiotransformation and toxicity of inor-

ganic and organic arsenic compoundsdiffer substantially.25 Inorganic arseniccompounds (arsenite and arsenate) aremetabolized to methylarsonate anddimethylarsinate and excreted in theurine together with unchanged inor-ganic arsenic.26 Arsenobetaine, anorganic arsenic compound, is excretedunchanged in the urine and is consid-For editorial comment see p 845.

Author Affiliations: Department of EnvironmentalHealth Sciences (DrsNavas-Acienand Silbergeld),andDepartment of Epidemiology, and Welch Center forPrevention, Epidemiology, and Clinical Research (DrsNavas-Acienand Guallar), JohnsHopkins BloombergSchool of Public Health, Baltimore, Maryland; Na-tional Center forEpidemiology, Institutode Salud Car-

los III, Madrid, Spain, and CIBER en Epidemiologa ySalud Publica, Madrid, Spain (Dr Pastor-Barriuso);De-partment of Cardiovascular Epidemiology and Popu-lation Genetics, Centro Nacional de InvestigacionesCardiovasculares, Madrid, Spain, and Department ofMedicine, Johns Hopkins Medical Institutions, Balti-more (Dr Guallar).Corresponding Author:Ana Navas-Acien, MD, PhD,Departmentof Environmental HealthSciences,JohnsHopkins Bloomberg School of Public Health, 615 NWolfe St, Room W7033B, Baltimore, MD 21205(anavas@jhsph.edu).

Context High chronic exposure to inorganic arsenic in drinking water has been re-lated to diabetes development, but the effect of exposure to low to moderate levelsof inorganic arsenic on diabetes risk is unknown. In contrast, arsenobetaine, an or-ganic arsenic compound derived from seafood intake, is considered nontoxic.

Objective To investigate the association of arsenic exposure, as measured in urine,with the prevalence of type 2 diabetes in a representative sample of US adults.

Design, Setting, and Participants Cross-sectional study in 788 adults aged

20 years or older who participated in the 2003-2004 National Health and NutritionExamination Survey (NHANES) and had urine arsenic determinations.

Main Outcome Measure Prevalence of type 2 diabetes across intake of arsenic.

Results The median urine levels of total arsenic, dimethylarsinate, and arsenobeta-ine were 7.1, 3.0, and 0.9 g/L, respectively. The prevalence of type 2 diabetes was7.7%. After adjustment for diabetes risk factors and markers of seafood intake, par-ticipants with type 2 diabetes had a 26% higher level of total arsenic (95% confi-dence interval [CI], 2.0%-56.0%) and a nonsignificant 10% higher level of dimeth-ylarsinate (95% CI, 8.0% to 33.0%) than participants without type 2 diabetes, andlevels of arsenobetaine were similar to those of participants without type 2 diabetes.After similar adjustment, the odds ratios for type 2 diabetes comparing participants atthe 80th vs the 20th percentiles were 3.58 for the level of totalarsenic (95% CI, 1.18-10.83), 1.57 for dimethylarsinate (95% CI, 0.89-2.76), and 0.69 for arsenobetaine(95% CI, 0.33-1.48).

Conclusions After adjustment for biomarkers of seafood intake, total urine arsenicwas associated with increased prevalence of type 2 diabetes. This finding supports thehypothesis that low levels of exposure to inorganic arsenic in drinking water, a wide-spread exposure worldwide, may play a role in diabetes prevalence. Prospective stud-ies in populations exposed to a range of inorganic arsenic levels are needed to estab-lish whether this association is causal.

JAMA. 2008;300(7):814-822 www.jama.com

814 JAMA,August 20, 2008Vol 300, No. 7(Reprinted) 2008 American Medical Association. All rights reserved.

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ered nontoxic.27 The relationship ofarsenobetaine withdiabeteshasnotbeenevaluated in human studies.

The 2003-2004 National Healthand Nutrition Examination Survey(NHANES) measured for the first time

total urine arsenic and urine arsenicspecies in a representative sample of theUS population.28 Using these data, ourobjective was to investigate the asso-ciation of urine arsenic with the preva-lence of type 2 diabetes and with thelevels of glycated hemoglobin in adultNHANES 2003-2004 participants. Ourhypothesis was that exposure to inor-ganic arsenic is a risk factor for diabe-tes while exposure to organic arseniccompounds is not.

METHODS

Study PopulationNHANES 2003-2004, conductedby theUS National Center for Health Statis-tics, used a complex multistage sam-pling design to obtain a representativesample of the civilian noninstitutional-ized individuals within the US popula-tion.29 The 2003-2004 NHANES studyprotocolswere approved by the institu-tional review board of the National Cen-ter for Health Statistics. Oral and writ-teninformed consent wasobtained fromall participants. The participation ratein

NHANES 2003-2004 interviews andphysical examinations was 76%. For ar-senic measurements, NHANES 2003-2004 randomly selected a one-third ran-dom sample of study participants aged6 years and older (n=2673).28 Among1611 participants aged 20 years andolder (age threshold was set in accor-dance with NHANES 2003-2004 ques-tionnaires and questionnaire strategiesfor adults and to meet our goal of evalu-ating arsenic and type 2 diabetes inadults), we selected 1027 participants

who had fasted 8 to 24hours before ve-nipuncture. We then excluded 38 preg-nant women, 34 participants missingtotal urine arsenic or urine arsenic spe-cies, 24 participants without prior di-agnosis of diabetes missing serum glu-cose, 4 participants missing glycatedhemoglobin, 130 participants who re-ported seafood intake in the past 24

hours, and 9 participants missing othervariables ofinterest,leaving a total of788participants for this study.

Urine Arsenic

Spot urine samples (urine samples

obtained at the time of the physicalexaminations) for arsenic analysis werecollected in arsenic-free containers,shipped on dry ice, stored frozen at70C or lower, and analyzed within 3weeks of collection.30 Urine collectionandstorage materialswere screened forarseniccontaminationbeforeuse.28 Totalarsenic and arsenic species were mea-sured at the Environmental Health Sci-ences Laboratory of the National Cen-ter for Environmental Health followinga standardized protocol.31 Total urinearsenic levels (isotope mass 75) were

measured using inductively coupledplasma dynamic reaction cell massspectrometry on a PerkinElmer ELAN6100 DRCPLUS or ELAN DRC II ICP-MS(PerkinElmer SCIEX, Concord, ON,Canada).30 Thelimitofdetectionwas 0.6g/L, and 1.5% of study participantshad total urine arsenic levels below thelimit of detection. National Instituteof Standards and Technology standardreference material 2670 was used forexternal calibration.30 The interassaycoefficients of variationfor quality con-

trolpooledsamples analyzed through-out thedurationofthe survey were9.2%and 19.4% for total urine arsenic lotswith meanarsenic levelsof 8.15 g/L and4.07 g/L, respectively.31

Urine arsenic species (arsenite, arse-nate, methylarsonate, dimethylarsi-nate, and arsenobetaine) were mea-sured by inductively coupled plasmadynamic reaction cell mass spectro-metry using high-performance liquidchromatography.32 The limits of detec-tion for arsenite (1.2 g/L), arsenate (1.0

g/L), and methylarsonate (0.9 g/L)were too high for a population exposedto low or moderate arsenic levels, and96.1%, 93.5%, and 64.8% of sample par-ticipants had arsenite, arsenate, andmethylarsonate levels below the limit ofdetection, respectively. As a conse-quence, arsenite, arsenate, and methyl-arsonate levels were not used in our

analyses. The limits of detection for di-methylarsinate and for arsenobetainewere 1.7 and0.4g/L,respectively. Thepercent of study participants with lev-els below the limit of detection were14.5%fordimethylarsinateand32.2%for

arsenobetaine. The interassay coeffi-cients of variation for quality controlpooled samples with mean dimethylar-sinate levels of 6.66 g/L and meanarsenobetaine levelsof4.87 g/L were7%and 10%, respectively.32 For partici-pants with total arsenic, dimethylarsi-nate, or arsenobetaine levels below thelimit of detection, a level equal to thelimit of detection divided by the squareroot of 2 was imputed.

Diabetes End Points

Serum glucose concentration was mea-

sured using a Beckman Synchron LX20(Beckman Coulter Inc, Fullerton,California).29 Prevalent type 2 diabe-tes was defined as a fasting serum glu-cose level of 126 mg/dL or greater, aself-reported physician diagnosis of dia-betes, or self-reported use of insulin ororal hypoglycemic medication. Thenumber of participants with diabeteswas 93 (73 with a prior diagnosis). Gly-cated hemoglobin was measured by aboronate affinity high-performance liq-uid chromatography system and con-

verted to A1Clevels.29

Other Variables

Questionnaire information includedsex, age, race, and ethnicity; educa-tional, smoking, and alcohol consump-tion status; and dietary recall inter-views for the past 24 hours using anautomated multiple passmethod.29 Raceand ethnicity were based on self-report, which allowed for multiple op-tions and were subsequently catego-rizedby the NationalCenter for Health

Statistics as non-Hispanic white, non-Hispanic black, Mexican American,other Hispanic, and other. Seafood in-take in the 24 hours immediately pre-ceding the interview wasobtainedfromthe 24-hour dietary recall interview re-sults and assigned basedon US Depart-ment of Agriculture food codes con-taining fish or seafood asmain dishor

ARSENIC EXPOSURE AND DIABETES

2008 American Medical Association. All rights reserved. (Reprinted) JAMA,August 20, 2008Vol 300, No. 7 815



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in combination with other food items.33

Body mass index was calculated by di-viding measured weight in kilogramsby measured height in meters squared.Serumcotinine was measuredby an iso-tope-dilutionhigh-performance liq-

uid chromatography/atmospheric pres-sure chemical ionization tandem massspectrometric method. Blood mercurylevels were measured using multiele-ment quadrupole inductively coupledplasma mass spectrometry technology(PerkinElmer Instruments, Shelton,Connecticut). A level equal to the limitof detection divided by the square rootof 2 was imputed to those participantswith levels below the limit of detec-tion for serum cotinine (18.3% below0.015 ng/mL [SI conversion: multiplyby 5.675 for nmol/L]) or blood mer-

cury (8.0% below 0.2 g/L [SI conver-sion: multiply by 4.985 for nmol/L]).Urine creatinine, used to account forurine dilution in spot urine samples,was determined using a Jaffe rate reac-tion measured with a CX3 analyzer(Beckman Coulter Inc).

Statistical Analysis

All statistical analyses were per-formed using the survey package in Rversion 2.4.1 (R Foundation for Statis-tical Computing, Vienna,Austria)to ac-

count for the complex sampling de-sign. Strata,primary sampling units,andspecial sample weights for arsenicanalyses were used to obtain unbiasedpoint estimates and robust linearizedstandard errors.28 The statistical sig-nificance level wasset at=.05. All sta-tistical analyses were 2-sided.

Total arsenic, dimethylarsinate, andarsenobetaine levels were right-skewedandlog-transformedfor theanalyses. Foreach arsenical, the ratio of geometricmean arsenic concentrations andits 95%

confidence interval (CI) in participantswith diabetes compared with partici-pants without diabetes were estimatedusing linear regression models on log-transformed arsenic levels. Forrisk analy-ses, logistic regression was used to esti-mate the odds ratio (OR) of diabetescomparing the 80th vs the 20th percen-tileof each arsenical distribution and as-

suming a log-linear dose-response rela-tionship with diabetes. To assessnonlinear relationships, we estimatedORs comparing tertiles 2 and 3 to thelowest tertile of the arsenical distribu-tion, as well as ORs based on restricted

quadratic splines with knots at the 5th,50th, and 95th percentiles.Although we restricted the analyses

to participants who did not report sea-food intake in the past 24 hours, wecould notremove all thecontribution oforganic arsenic exposure to total urinearsenicpossibly due to complex me-tabolism and excretion of organic ar-senic compounds, incomplete dietary re-call of all seafood sources, andpotentialpresence of arsenobetaine and arseno-sugars in unknown sources. We wereprimarilyinterested in evaluatingthere-

lationship of diabetes with exposure toinorganic arsenic; therefore, our pri-mary assessment of exposure was totalurine arsenic concentration adjusted forobjective biomarkers of seafood con-sumption (arsenobetaine andblood mer-cury). Measures of other organic ar-senic compounds derivedfromseafood,such as arsenosugars, arsenolipids, andtheir metabolites, are technically chal-lenging and were not available.

Our linear and logistic regressionmodels for total urine arsenic concen-

trations anddiabetes endpointswere fit-ted with increasing degrees of adjust-ment.First, weadjusted forsex, age, raceand ethnicity (known determinants ofdiabetes that may be related to arsenicexposure), and urine creatinine. Sec-ond, each modelwas further adjustedforeducation, body mass index, serum co-tinine, and useof antihypertensive medi-cation. This model represents the asso-ciation of total arsenic exposure withdiabetes independent of the source butadjusted for traditional diabetes riskfac-

tors. Third, each model was further ad-justedfor urine arsenobetaine andbloodmercury levels. Thismodel provideses-timates for the association of inorganicarsenic not derived from seafood andforarsenobetaine. Further adjustment forsmoking status and alcohol intake, aswell as exclusion of participants show-ing levels below the limit of detection,

did not modify the observed associa-tions (results not shown). We followedsimilar analytical strategies to evaluatethe relationshipsof dimethylarsinateandarsenobetaine with type 2 diabetes.

To evaluate the consistency of the

findings by participant characteris-tics, we estimated the ratio of geomet-ric meantotal arsenic concentrations bycomparing participants with type 2 dia-betes with participants without type 2diabetes for subgroups defined by sex,age, race andethnicity, education, bodymass index, and smoking status.

RESULTS

The median urine levels in the studypopulation were 7.1 g/L for total ar-senic, 3.0 g/L for dimethylarsinate, and0.9 g/L for arsenobetaine (for SI con-

version from g/L to mol/L, multiplyby 0.0133;TABLE1). After adjusting forsex, age, race, andurine creatinine, urinelevels of total arsenic, dimethylarsinate,and arsenobetaine were substantiallyhigher among participants categorizedasblack, MexicanAmerican, andother raceor ethnicityand in participantswith highblood mercury levels. Total arsenic washighly correlated with dimethylarsi-nate (Pearsoncorrelation coefficient forlog-transformed variablesr=0.81) andarsenobetaine (r=0.76), and moder-

ately correlated with blood mercury(r=0.39). Dimethylarsinate wasmoder-ately correlated with arsenobetaine(r=0.46) and blood mercury (r=0.28).Arsenobetaine and blood mercury werealso moderately correlated with onean-other (r=0.48).

In models adjusted for sociodemo-graphic and diabetes risk factors(TABLE 2; models 1 and 2), partici-pants with type 2 diabetes had similarlevels of total arsenic and dimethylar-sinate, and lower levels of arsenobeta-

ine compared with participants with-out type 2 diabetes. After adjustmentfor urine arsenobetaine and blood mer-cury, biomarkers of seafood intake, par-ticipants with type 2 diabetes had 26%higher total arsenic levels (95% CI,2.0%-56.0%), nonsignificant 10%higher dimethylarsinate levels (95%CI,8.0% to 33.0%), and similar arseno-





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betaine levels than participants with-out type 2 diabetes (Table 2; model 3).

The ORs for diabetes comparing par-ticipants in the 80th vs the 20th per-centiles of totalurine arsenic were 1.05(95% CI, 0.57-1.94) before adjust-

ment for biomarkers of seafood intakeand 3.58 (95% CI,1.18-10.83) after ad-

justment (TABLE 3; models 2 and 3).For urine dimethylarsinate, the corre-sponding ORswere 1.19 (95% CI, 0.72-1.98) and1.57 (95% CI, 0.89-2.76), andfor urine arsenobetaine they were 0.53(95% CI, 0.22-1.26) and 0.69 (95% CI,

0.33-1.48). After adjustment for bio-markers of seafood intake, positive as-

sociations with increasing total ar-senic were also evident in models basedon tertiles (Table 3) or on restrictedquadratic splines (FIGURE1).

Insensitivityanalysesrestrictedto385participants(50withtype2diabetes,335

withouttype2diabetes)witharsenobeta-inelevelsbelowthemedian(0.9g/L),

Table 1.Urine Arsenic Concentrations by Participant Characteristics

Characteristics No. (%)a

Urine Arsenic Concentration, Median (IQR), g/L PValue b

Total Arsenic Dimethylarsinate ArsenobetaineTotal

Arsenic Dimethylarsinate Arsenobetaine

Overall 788 7.1 (3.6-13.9) 3.0 (2.0-5.6) 0.9 (0.3-3.5)

SexMen 417 (49.4) 8.6 (4.6-14.3) 4.0 (2.3-6.0) 1.1 (0.3-3.8)

.07 .26 .37Women 371 (50.6) 6.0 (2.9-13.1) 3.0 (2.0-5.0) 0.7 (0.3-3.4)

Age, y20-39 262 (39.3) 7.4 (4.2-15.5) 4.0 (2.0-6.0) 0.8 (0.3-2.9)

40-59 237 (40.3) 6.6 (3.1-11.6) 3.0 (2.0-5.0) 0.9 (0.3-3.5) .004 .16 .1260 289 (20.4) 6.8 (3.4-14.5) 3.0 (2.0-5.2) 1.0 (0.3-5.3)

Race/ethnicityWhite 417 (74.8) 6.2 (3.1-11.6) 3.0 (2.0-5.0) 0.7 (0.3-2.7)

Black 172 (11.0) 9.2 (5.4-16.5) 4.0 (2.7-6.3) 1.7 (0.5-5.9).001 .001 .21

Mex ican American 160 (8.2) 10.3 (5.9- 16.2) 5.1 (3.0-7.0) 1.1 (0.3- 3.0)

Otherc 39 (6.0) 17.2 (7.2- 33.4) 8.0 (4.0-15.3) 2.2 (0.3- 12.3)

EducationHigh school 237 (18.2) 7.4 ( 3. 5-14.8) 3.4 (2.0-6.5) 0.7 ( 0. 3-2. 9)

High school 214 (30.2) 7.4 (3.9-15.5) 3.9 (2.0-5.6) 1.1 (0.3-3.7) .16 .48 .17

High school 337 (51.6) 6.9 ( 3. 5-12.7) 3.0 (2.0-5.0) 0.9 ( 0. 3-3. 6)

Body mass index d

25 245 (32.0) 6.9 (3.3-14.4) 3.0 (2.0-5.9) 0.8 (0.3-3.9)

25-30 291 (37.9) 7.4 (3.7-13.8) 3.8 (2.0-5.3) 1.1 (0.3-4.3) .05 .07 .23

30 252 (30.1) 6.4 (4.0-13.9) 3.0 (2.0-5.9) 0.8 (0.3-2.6)

SmokingNever 387 (48.6) 7.0 (3.7-14.4) 3.0 (2.0-5.7) 0.9 (0.3-3.9)

Former 226 (25.7) 7.6 (3.8-14.6) 3.8 (2.0-5.2) 1.4 (0.3-4.5) .10 .18 .15

Current 175 (25.8) 6.5 (3.5-11.3) 3.0 (2.0-5.1) 0.7 (0.3-1.7)

Serum cotinine, ng/mL0.015 144 (14.6) 6.9 (3.2-13.9) 3.1 (2.0-6.0) 0.7 (0.3-3.5)

0.015-10.0 429 (54.4) 7.3 (4.0-14.8) 3.5 (2.0-5.7) 1.1 (0.3-4.2) .22 .14 .60

10.0 215 (31.0) 6.7 (3.4-11.6) 3.0 (2.0-5.0) 0.7 (0.3-2.8)

Arsenobetaine, g/LTertile 1 (0.4) 274 (35.9) 3.4 (1.7-6.5) 2.0 (1.2-4.0) 0.3 (0.3-0.3)

Tertile 2 (0.4-2.0) 236 (31.1) 6.4 (4.2- 9.5) 4.0 (2.0-5.0) 1.0 (0.7- 1.4) .001 .001

Tertile 3 (2.0) 278 (33.0) 16.2 (10.5-32.7) 5.0 (3.0-8.0) 7.1 (3.6- 15.8)

Blood mercury, g/LTertile 1 (0.6) 271 (33.0) 5.1 (2.9-9.4) 3.0 (2.0-4.3) 0.3 (0.3-0.8)

Tertile 2 (0.6-1.3) 267 (32.3) 7.0 (3.4- 12.4) 3.0 (2.0-5.3) 1.0 (0.3- 2.6) .001 .001 .001

Tertile 3 (1.3) 250 (34.7) 10.6 ( 5. 6-21.6) 4.0 (3.0-7.0) 2.5 ( 0. 7-10.4)

DiabetesYes 93 (7.7) 6.9 ( 3.0-10.9) 3.0 (2.0-4.3) 0.5 ( 0.3-2.2)

.60 .73 .03No 695 (92.3) 7.1 (3.6-14.3) 3.3 (2.0-5.7) 0.9 (0.3-3.6)

Abbreviation: IQR, interquartile range.SI conversion factors: Toconvert total arsenic, dimethylarsinate, or arsenobetaine from g/L tomol/L, multiply by0.0133; forblood mercury from g/L to nmol/L, multiply by 4.985.a Percentage values are weighted.b Pvalues are adjusted for sex, age, race and ethnicity, and urine creatinine level (log-transformed).c Combinesother race and other Hispanic categories due to limited sample size.d Calculated as weight in kilograms divided by height in meters squared.





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theratioof geometric mean total arsenicconcentrations in individualswithdia-betesvsthosewithoutwas1.22(95%CI,0.97-1.55) afteradjustmentfor sex,age,race,urinecreatinine, education, bodymass index,serum cotinine, andhyper-

tensionmedication.Aftersimilaradjust-ment,theORoftype2diabeteswas2.41(95%CI, 0.69-8.44)comparing partici-pants in the 80th vs 20th percentile oftotal urine arsenic distribution.

Total urine arsenic and dimethylar-sinate levels, but notarsenobetaine,werealso positively associated with increas-ing levels of glycated hemoglobin afteradjustment for markers of seafood in-

take, althoughthe associations werenotstatistically significant (TABLE 4).

The positive association betweentotal urine arsenic anddiabetes after ad-justment for markers of seafood in-take was consistent for most sub-

groups examined, with somewhatgreater associations in participants whowere younger, overweight, and neversmokers (FIGURE2).

COMMENT

In a representative sample of US adults,increasing levels of total urine arsenicwere positively associated with type 2

diabetes prevalence and with levels ofglycated hemoglobin after adjustmentfor diabetes risk factors and markersof seafood intake. A nonsignificantassociation was observed for urine di-methylarsinate and no association was

observed for urine arsenobetaine. Afteradjustment for objective biomarkers ofseafood intake, the main source of or-ganic arsenicals, the association of totalurine arsenicwithdiabetes wasprogres-sive with no obvious threshold,andcon-sistent for most population subgroups.

Theseresults support our hypothesisthatexposureto inorganic arsenic, whichin this population was most likely de-rived from drinking water, is associatedwith an increased risk of diabetes whileexposure to organicarsenicals isnot.Ourfindings extend previous studies con-ducted in populations exposed to highinorganic arsenic concentrations indrinking water to a population with low-or moderate-arsenic exposure,and sug-gest that inorganic arsenic may have arole in diabetes development.

Arsenic Exposure

Humans may be exposed to inorganic(arsenite andarsenate) and organic (eg,arsenobetaine, arsenosugars, arsenolip-

Table 2.Ratio of Arsenic Concentrations Comparing Participants With Type 2 Diabetes(n = 93) vs Without (n = 695)

Total Arsenic Dimethylarsinate ArsenobetaineWith diabetes/without diabetes,

geometric mean, g/L6.2/7.3 3.2/3.5 0.9/1.4

Model 1a 0.94 (0.73-1.20) 0.98 (0.84-1.13) 0.62 (0.41-0.96)

Model 2b 1.01 (0.80-1.28) 1.02 (0.87-1.20) 0.66 (0.43-1.00)

Model 3c 1.26 (1.02-1.56) 1.10 (0.92-1.33) 0.88 (0.63-1.22)

SI conversion factor: To converttotal arsenic,dimethylarsinate, or arsenobetaine fromg/L to mol/L, multiplyby 0.0133.a Model 1 is shown as adjusted ratio of geometric mean (95% confidence interval); adjusted for sex, age, race and

ethnicity, and urine creatinine level (log-transformed).b Model 2 is shownas adjustedratioof geometricmean(95%confidence interval); further adjusted foreducation,body

mass index (calculated as weight in kilograms divided by height in meters squared), serum cotinine level (log-transformed), and hypertension medication.

c Model 3 is shown as adjusted ratio of geometric mean (95% confidence interval); further adjusted for arsenobetaine(log-transformed) and blood mercury levels (log-transformed), except for arsenobetaine model that was further ad-

justed for blood mercury only.

Table 3.Odds Ratio of Diabetes by Urine Arsenic Concentrations

80th vs 20thPercentile Tertile 1 Tertile 2 Tertile 3

P Valuefor Trenda

Total arsenic, g/L 16.5 vs 3.0 4.8 4.8 to 10.8 10.8

With diabetes/without diabetes, No. 93/695 29/202 30/230 34/263

Model 1b 0.82 (0.46-1.46) 1 [Reference] 0.89 (0.29-2.79) 0.64 (0.24-1.72) .48

Model 2c 1.05 (0.57-1.94) 1 [Reference] 0.94 (0.25-3.48) 0.74 (0.25-2.20) .86

Model 3d 3.58 (1.18-10.83) 1 [Reference] 1.27 (0.36-4.48) 1.60 (0.46-5.54) .03

Dimethylarsinate, g/L 6.0 vs 2.0 2.4 2.4-5.0 5.0





Arsenobetaine, g/L 5.5 vs 0.3 0.5 0.5-2.0 2.0





SI conversion factor: To convert total arsenic, dimethylarsinate, or arsenobetaine from g/L to mol/L, multiply by 0.0133.a Pvalue for trend based on log-transformed arsenic concentrations.b Model 1 is shown as odds ratio (95% confidence interval); adjusted for sex, age, race and ethnicity, and urine creatinine level (log-transformed).c Model 2 is shown as odds ratio (95% confidence interval); further adjusted for education, body mass index (calculated as weight in kilograms divided by height in meters squared),

serum cotinine level (log-transformed), and hypertension medication.d Model 3 is shown as odds ratio (95% confidence interval); further adjusted for arsenobetaine (log-transformed) and blood mercury levels (log-transformed), except for arseno-

betaine models that were further adjusted for blood mercury only.





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ids) arsenic compounds.24,25 The mainsources of inorganicarsenic are contami-nated drinking water and food.3,34-36 Inthe United States, contaminated waterfrom naturally occurring inorganic ar-senicinrocksandsoils iscommonincer-

tain areas of the West, Midwest, andNortheastregions.It isestimated that 8%of public water supply systems in theUnited States may exceed arsenic levels

of 10 g/L, 14% may exceed levels of5 g/L, and 25% may exceed levels of2 g/L.35 The US Environmental Protec-tion Agencys standard for arsenic con-centrations in drinking water (10 g/L)was based on quantitative estimates of

the effect of arsenic on cancer inci-dence.2 Foods such as flour and rice canalso provide small quantities of inor-ganic arsenic, particularly if grown or

cooked in areas with arsenic contami-nation insoilandwater.37 Estimated dailydietaryintake of inorganic arsenicin theUnitedStates ranges from 8.4to 14 g/dfor various age groups.36

Seafood is the main source of organic

arsenic compounds in the human diet.

24

Most fish and shellfish are rich in ar-senobetaine that is rapidly excreted un-changed in urine. Based on toxicity ex-

Table 4.Mean Difference in Percent Levels of Glycated Hemoglobin by Urine Arsenic Concentrations

80th vs 20thPercentile Tertile 1 Tertile 2 Tertile 3

P Valuefor Trenda

Total arsenic, g/L 16.5 vs 3.0 4.8 4.8 to 10.8 10.8

Model 1b 0.04 (0.16 to 0.08) 0 [Reference] 0.03 (0.16 to 0.09) 0.00 (0.20 to 0.19) .52

Model 2c 0.00 (0.13 to 0.13) 0 [Reference] 0.01 (0.12 to 0.13) 0.05 (0.16 to 0.26) .95

Model 3d 0.18 (0.20 to 0.56) 0 [Reference] 0.08 (0.07 to 0.23) 0.23 (0.18 to 0.63) .32

Dimethylarsinate, g/L 6.0 vs 2.0 2.4 2.4 to 5.0 5.0




Arsenobetaine, g/L 5.5 vs 0.3 0.5 0.5 to 2.0 2.0




SI conversion factor: To convert total arsenic, dimethylarsinate, or arsenobetaine from g/L to mol/L, multiply by 0.0133.a Pvalue for trend based on log-transformed arsenic concentrations.b Model 1 is shown as mean difference (95% confidence interval); adjusted for sex, age, race and ethnicity, and urine creatinine level (log-transformed).c Model 2 is shown as mean difference (95% confidence interval); further adjusted for education, body mass index (calculated as weight in kilograms divided by height in meters

squared), serum cotinine level (log-transformed), and hypertension medication.d Model 3 is shown as mean difference (95% confidence interval); further adjusted for arsenobetaine (log-transformed) and blood mercury levels (log-transformed), except for ar-

senobetaine models that were further adjusted for blood mercury only.

Figure 1.Odds Ratio of Diabetes by Urine Arsenic Concentrations

8

2

4

1

0.5

0.25 0

50

40

30

20

10

0.4 1 5 20 150

Urine Concentration, g/L

Total Arsenic

AdjustedOddsRatio

WeightedPercentage

8

2

4

1

0.5

0.25 0

50

40

30

20

10

1.2 2 5 10 25


Dimethylarsinate

AdjustedOddsRatio

WeightedPercentage

8

2

4

1

0.5

0.25 0

50

40

30

20

10

0.3 1 5 20 100


Arsenobetaine

AdjustedOddsRatio

WeightedPercentage

Adjusted odds ratio

Model 2

Model 3

Distribution of urinary

arsenical concentration

Lines represent adjusted odds ratios based on restricted quadratic splines for log-transformed arsenic concentrations with knots at 5th, 50th, and 95th percentiles. Thereference value was set at the 10th percentile of each arsenical distribution. Odds ratios were adjusted for sex, age, race and ethnicity, urine creatinine level, education,body mass index (calculated as weightin kilograms divided by heightin meterssquared), serum cotinine andhypertension medication formodel2, andfurther adjustedfor arsenobetaine (except arsenobetaine model) and blood mercury for model 3. Bars represent the weighted histogram of each arsenical distribution. For urinaryarsenical distributions, 10 equally sized bins were selected from the 1st to the 99th percentiles of each log-transformed arsenical distribution except for dimethylarsi-

nate. For dimethylarsinate, 9 equally sized bins were selected to improve the shape of the histogram (many dimethylarsinate measurements were whole numbers).





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periments, arsenobetaine is considerednontoxic.27 In our study, urine arseno-betaine wasnot related to diabetesor gly-cated hemoglobin after adjustment forblood mercury. Seaweed and some sea-foodsuchasscallops and mussels are also

rich in arsenosugars that are metabo-lized to several compounds (includingdimethylarsinate)thatcontribute to totalurine arsenic levels.38,39 In our study, weadjusted the relationship of total ar-senic and dimethylarsinate with diabe-tes for objective markers of seafood in-take and thus, we indirectly controlledfor arsenosugars. Although we wereun-able to evaluate the relationship of ex-posure to arsenosugars with diabetes,toxicity experimentsseemto indicatethatarsenosugars and their metabolites areeither nontoxic or have very low toxic-

ity compared with inorganic arsenic.38

Inorganic Arsenic and Diabetes

High levelsof inorganicarsenic in drink-ing water have been associated with in-creased risk of type 2 diabetes in Tai-wan, Bangladesh, and Mexico.12-14,18 In

a meta-analysis comparing extreme ar-senicexposure categories (village drink-ing water levels or living in a high- vslow-arsenic area) in studies from Tai-wan and Bangladesh, the pooled rela-tive risk for diabetes was 2.52 (95% CI,

1.69-3.75).

16

In these studies, arsenic ex-posure was determined based on eco-logicmeasuresofarsenic in drinking wa-ter, but no information on arsenicexposure was available at the indi-vidual level. In a case-control study inMexico, the OR for diabetes comparingthe highest tertile (104 g/g creati-nine) to the lowest tertile (64 g/g cre-atinine) of total urine arsenic concen-trations was 2.84(95%CI, 1.64-4.92).15

Since these studies were conducted inpopulations exposed to high arseniclev-els and arsenic exposure was mostly as-

sessed ecologically, the implications fordiabetesin populationsexposedto lowerlevels have been debated.16,40,41

Few studies have addressed the asso-ciation of low or moderate exposure toinorganic arsenic with diabetes risk.20-22

In 660 participants exposed to rela-

tively lowarsenic levelsin drinking wa-ter in Central Taiwan, hair arsenic lev-elswere associated with elevated plasmaglucose levels and with the prevalenceof the metabolic syndrome.23 In Utah,an ecologic study found no association

between arsenic levels in drinking wa-ter and diabetes mortality after control-ling only for age and sex.21 In a cross-sectional study in Wisconsin, the age,sex, body mass index,and smoking sta-tus adjusted OR for self-reported diabe-tes comparing participants with ar-senic levels in drinking water between2 and 10g/Land levels greater than 10g/L to participants with arsenic levelsin drinking water of less than 2 g/Lwere 1.35 (95% CI,0.78-2.33) and1.02(95% CI, 0.49-2.15), respectively.20 Bio-markers of arsenic exposure were not

measured in this study. In a small case-control study in southern Spain, 38 par-ticipants with diabetes had similar totalurinearsenic concentrations(mean level3.44 g/L) compared with 49 controlparticipants (mean level 3.68 g/L), butthe study was not adjusted for diabetes

Figure 2.Urine Arsenic Concentrations Comparing Participants With Type 2 Diabetes vs Participants Without

Total Urine Arsenic Concentration,

Geometric Mean, g/L

Favors No

Association

Favors

Association

1.5 2.51.00.75

Adjusted Ratio (95% Confidence Interval)

Participants With

Type 2 Diabetes

Participants Without

Type 2 DiabetesParticipant Subgroup

Adjusted Ratio

(95% Confidence Interval)

aPfor

Interaction

.86

Sex8.2 8.4Men 1.28 (1.00-1.63)4.3 6.5Women 1.24 (0.97-1.59)

Race/ethnicity5.1 6.3White 1.30 (1.00-1.69)

11.6 11.4Other 1.22 (0.98-1.52)

Smoking

5.6 7.4Never 1.54 (1.16-2.04)6.7 7.3Ever 1.12 (0.89-1.39)

6.2 7.3Overall 1.26 (1.02-1.56)

Education6.1 8.1High school 1.18 (0.92-1.50)6.4 6.7>High school 1.35 (1.09-1.68)

Age, y10.8 8.220-39 1.71 (1.23-2.37)

4.3 6.740-59 1.38 (0.99-1.93)8.1 6.960 1.14 (0.94-1.38)

Body mass indexb

5.9 7.3


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risk factors or for markers of seafoodintake.22

The potential role of arsenic in dia-betes development is supported byexperimental and mechanistic evi-dence. Rats administered 1.7 mg/kg of

sodium arsenite by gavage for 90 dayshad higher glucose and insulin levels,lower glucose-to-insulin ratio, andhigherhomeostasis model assessmentofinsulin resistance compared with con-trol participants.5 Insulin synthesis andsecretion was impaired in pancreatic cells treated with arsenite 0.5 to 10 molfor 72 to 144 hours.42 In insulin-sensitive cells exposed both to insulinand arsenite, glucose uptake decreasedcompared with insulin alone.6-8 Glu-cose uptake was also inhibited in cellsexposed to methylarsonite for 4-hour

or 24-hour periods.6,8 Other potentialmechanisms include arsenic influenceon the expression of gene transcriptionfactors related to insulin signal trans-duction,9,43,44 adipocyte differentiation,and insulin sensitivity.8,10,11 Finally, ar-senic could induce diabetes by nonspe-cific mechanisms such as oxidativestress, inflammation, or apoptosis,mechanismsthathave been relatedbothto arsenic exposure and diabetes devel-opment. However,mostmechanisticex-periments havebeen conducted at high-

arsenic concentrations and furtherresearch is neededto establishthe path-ways potentially affected by arsenic atlowand moderatelevels ofexposure.Ex-perimental evidence will also be essen-tial to investigate important biologicalquestions on the role of arsenic in dia-betes, such as the arsenic effect and me-tabolism at the cellular level.6,8,45

Strengths and Limitations

Important strengths of this study in-clude the useof a representative sample

of the general US population; the useof urine arsenic, the biomarker recom-mended by the US National ResearchCouncil Subcommittee on Arsenic inDrinking Water,2 to assessexposure; theadjustment for relevant diabetes riskfactors and for biomarkers of seafoodintake; and the rigorous quality con-trol of study procedures in NHANES.

Whilethe publichealthand researchimplications of this study are impor-tant, some limitations must also be con-sidered. First, our analysis was limitedby a relatively small sample sizebecauseNHANES 2003-2004measured arsenic

in just a random third of survey par-ticipants. Second, the study is cross-sectional andtemporalitybetween urinearsenic levels and diabetes develop-ment cannot be completely ensured. Itis unknown if diabetesalters theexcre-tion and metabolism of arsenic. Pro-spectiveepidemiologic studies in popu-lations exposed to a wide range ofinorganic arsenic are needed to con-firm this association. Third, because ofitsrelatively short half-life, urinearsenicmay not reflect long-term exposure. Inthe absence of public health interven-

tions, however, arsenic concentra-tions in drinking water are relativelystable over time,46-48 resulting in steadyurine arsenic levels. Indeed, repeatedurine samples in populations withlow-seafood intake have shown relativelyconstant urine arsenic levels over timereflecting ongoing chronic exposure toinorganic arsenicfromdrinking water.49

Fourth, the high limits of detection forarsenite, arsenate, and methylarsonate(speciesthat morereadily reflect expo-sureto inorganicarsenic), precluded the

use of those species in theanalyses. Fortotal arsenic, dimethylarsinate, andarsenobetaine, the relatively highcoef-ficients of variation, limits of detec-tion, or both couldhave resulted in sub-stantial misclassification and potentialunderestimation of the associations.Other limitationsincludethe useofspoturine samples and the need to adjustfor urine creatinine levelsto account forurine dilution and the possibility ofresidual confounding by geographicallocation or by urbanization.

CONCLUSIONS

We found a positive association be-tween total urine arsenic, likely reflect-ing inorganic arsenic exposure fromdrinking water andfood, with thepreva-lence of type 2 diabetes in a populationwith low to moderate arsenic expo-sure. Together with the experimental

and epidemiologic evidence support-ing a diabetes effect for high levels of ar-senic exposure, these findings rein-force the need to evaluate the role ofinorganic arsenic in diabetes develop-ment in high-quality prospective stud-

iesconductedin populations exposed toa wide range of arsenic levels.From a public health perspective,

confirmation of a role for arsenic in dia-betes development would add to theconcerns posed by the carcinogenic,cardiovascular, developmental, and re-productive effects of inorganic arsenicin drinking water,1,2,50,51 and could sub-stantially modify risk assessment andrisk-benefit analyses estimating the con-sequences of arsenic exposure. Givenwidespread exposure to inorganic ar-senic from drinking water worldwide,

elucidating the contribution of ar-senic to the diabetes epidemic is a pub-lic health research priority with poten-tial implications for the prevention andcontrol of diabetes.

Author Contributions: Dr Navas-Acien had full ac-cess to all of the data in the study and takes respon-sibility for the integrity of the data and the accuracyof the data analysis.Study concept and design:Navas-Acien, Silbergeld,Guallar.Acquisition of data:Navas-Acien.Analysis and interpretation of data: Navas-Acien,Silbergeld, Pastor-Barriuso, Guallar.Drafting of the manuscript:Navas-Acien, Silbergeld,Pastor-Barriuso, Guallar.

Critical revision of the manuscript for importantintellectual content: Navas-Acien, Silbergeld,Pastor-Barriuso, Guallar.Statis tical analysi s: Navas-Acien, Pastor-Barriuso,Guallar.Administrative, technical, or material support:Navas-Acien.Financial Disclosures:None reported.Funding/Support:This work was supported by grantP30 ES 03819 from the National Institute of Environ-mental HealthSciencesCenter in UrbanEnvironmen-tal Health.Role of the Sponsor:The National Institute of Envi-ronmental Health Sciences Center in Urban Environ-mental Health at theJohns HopkinsBloomberg Schoolof PublicHealth playedno role in thedesign andcon-duct of the study; collection, management, analysis,and interpretation of the data; and preparation, re-view, or approval of the manuscript.

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