no association between maternal pre-pregnancy obesity and risk of hypospadias or cryptorchidism in...

No Association between Maternal Pre-pregnancyObesity and Risk of Hypospadias or Cryptorchidism in

Male Newborns

Scott V. Adams,1,2* Theresa A. Hastert,1,2 Yi Huang,1 and Jacqueline R. Starr1–4

1Department of Epidemiology, University of Washington, Seattle, Washington2Fred Hutchinson Cancer Research Center, Seattle, Washington

3Department of Pediatrics, University of Washington, Seattle, Washington4Children’s Craniofacial Center, Seattle Children’s Hospital, Seattle, Washington

Received 29 October 2010; Revised 4 February 2011; Accepted 8 February 2011

BACKGROUND: Hypospadias and cryptorchidism, two relatively common male genital anomalies, may becaused by altered maternal hormone levels, blood glucose levels, or nutritional deficiencies. Maternal obe-sity, which increases risk of diabetes and could influence hormone levels, may, therefore, be associated withrisk of hypospadias and cryptorchidism. The purpose of this study was to assess the association betweenpre-pregnancy maternal obesity and hypospadias and cryptorchidism. METHODS: We conducted a case-con-trol study of hypospadias and cryptorchidism in male singleton newborns using Washington State birthrecords from 1992 to 2008 linked to birth-hospitalization discharge records. Maternal pre-pregnancy bodymass index (BMI) was calculated from pre-pregnancy weight and height. Adjusted odds ratios (aORs) and95% confidence intervals (95% CIs) for hypospadias or cryptorchidism were estimated by fitting multivari-able logistic regression models adjusted for year of birth, and maternal age, education, parity, race, and ciga-rette smoking during pregnancy. RESULTS: The complete-case analysis included 2219 hypospadias cases,2563 cryptorchidism cases, and 32,734 controls. Maternal obesity (BMI �30 kg/m2) was not associated withrisk of hypospadias or cryptorchidism in male offspring: hypospadias (aOR, 1.07; 95% CI, 0.95–1.21); cryp-torchidism (aOR, 0.99; 95% CI, 0.89–1.11), and no trend in risk with increasing maternal BMI was found.There was little indication of risk associated with BMI among any subgroup of mothers examined, includingwomen with pre-existing diabetes or hypertension, women who developed preeclampsia, non-Hispanicwhite women, first-time mothers, or mothers aged �30 years. CONCLUSIONS: The results of this study donot support the hypothesis that pre-pregnancy maternal obesity is a cause of hypospadias or cryptorchidismin male infants. Birth Defects Research (Part A) 91:241–248, 2011. � 2011 Wiley-Liss, Inc.

Key words: maternal obesity; genital birth defects; hypospadias; cryptorchidism; undescended testicles

INTRODUCTION

The genital defects hypospadias and cryptorchidismare relatively common among male infants, affectingapproximately 0.5% and 2 to 5%, respectively, of boysborn in the United States and Western Europe (Paulozziet al., 1997; Paulozzi, 1999; Carmichael et al., 2003; Thon-neau et al., 2003; Virtanen et al., 2007). Affected infantsoften require corrective medical procedures and are atincreased risk of long-term adverse health effects includ-ing poor semen quality and testicular cancer (Virtanenet al., 2007; Thorup et al., 2010; Toppari et al., 2010).

Hypospadias and cryptorchidism result from the dis-ruption of developmental processes that are predomi-

nantly regulated by androgens (Manson and Carr, 2003;Thonneau et al., 2003; Aschim et al., 2004). Furthermore,the Testicular Dysgenesis Syndrome hypothesis positsthat hypospadias, cryptorchidism, testicular cancer, andreduced fecundity share etiology, particularly endocrine dis-ruption (Skakkebaek et al., 2001; Sharpe, 2003; Skakkebaek,2003).

*Correspondence to: Scott V. Adams, Fred Hutchinson Cancer ResearchCenter, 1100 Fairview Ave N, M3-B232, Seattle, WA 98109. E-mail:[email protected] online 1 April 2011 in Wiley Online Library (wileyonlinelibrary.com).DOI: 10.1002/bdra.20805

Birth Defects Research (Part A): Clinical and Molecular Teratology 91:241�248 (2011)

� 2011 Wiley-Liss, Inc. Birth Defects Research (Part A) 91:241�248 (2011)

At least three potential mechanisms may relate mater-nal obesity to risk of hypospadias and cryptorchidism.Levels of circulating hormones, including androgens, dif-fer between obese and normal-weight women (Pasqualiand Gambineri, 2006; Pasquali et al., 2007; Blouin et al.,2008; Jansson et al., 2008; Morisset et al., 2008; Wei et al.,2009). Lower overall diet quality and blood concentra-tions of micronutrients have also been observed in obesewomen compared to non-obese women and may relateto risk of birth defects, including hypospadias, althoughdata are inconsistent (Goh et al., 2006; Carmichael et al.,2009; Ormond et al., 2009; Carmichael et al., 2010).Finally, impaired fasting glucose and impaired glucosetolerance before and during pregnancy are associatedwith obesity (Chu et al., 2007; American Dietetic Associa-tion, 2009), and uncontrolled glucose levels have beenassociated with birth defects (Carmichael et al., 2010).Based on the reported connections between obesity andthese mechanisms that could underlie development ofhypospadias and cryptorchidism, we hypothesized thatmale genital birth defects would be more common inbabies born to mothers who were obese before pregnancyrelative to babies born to normal-weight mothers.

METHODSStudy design

We conducted a population-based case control studyof risk of genital malformations in male newborns from1992 to 2008, by using Washington State birth recordslinked to Comprehensive Hospital Abstract ReportingSystem (CHARS) data. These data include diagnosis andprocedure codes from the birth hospitalization for bothmother and infant. Infants without hospitalization dataavailable for linkage to Washington State birth recordswere not included; this excludes approximately 7% ofbirths in Washington State that take place outside of hos-pitals and do not require hospitalization, and births in afederal facility such as a military hospital (WashingtonState Department of Health, 2010). Genital anomalieshave also been recorded on birth certificates: from 1992to 2002, check-boxes for ‘‘genital anomalies’’ and ‘‘otherurogenital malformation’’ appeared on the birth record;after 2002, both items were removed and a single check-box for hypospadias was added.

Cryptorchidism and hypospadias cases were identifiedon the basis of International Classification of Disease,Clinical Modification (ICD-9-CM) diagnostic codes andbirth certificate data. Live-born singleton males were eli-gible to be cases if birth hospitalization records includedICD-9-CM codes denoting cryptorchidism (752.5, 752.51,or 752.52) or hypospadias (752.6x), or if the birth certifi-cate record indicated ‘‘malformed genitalia,’’ ‘‘other uro-genital anomaly,’’ or hypospadias. The cryptorchidismand hypospadias case groups were not mutuallyexclusive.

For each eligible case, five singleton live-born maleswithout index ICD-9-CM codes in the birth hospitaliza-tion record and without indication of hypospadias, geni-tal anomaly, or other urogenital malformation on thebirth certificate were randomly selected as eligible con-trols. Controls were selected from the same year of birthas their corresponding case.

Exclusions. Because ICD-9-CM coding for hypospadiaschanged from 752.6 to 752.61 in October, 1996, infants

initially identified as eligible hypospadias cases but whowere diagnosed with ICD-9-CM codes 752.62 to 752.69and without 752.61 after 1996 were excluded as hypospa-dias cases (679 infants). Infants with malformed genitalia(n 5 182) or ‘‘other urogenital anomaly’’ (n 5 1839) indi-cated on the birth certificate records but without ICD-9-CM for either hypospadias or cryptorchidism indicatedin the hospitalization data were excluded. An additional51 infants born outside a hospital, birthing facility, orother medical clinic; 16 infants for whom the mother’sage was not recorded; and 6 infants with gestational ages<20 weeks recorded on birth records were excludedfrom all analyses. Infants with chromosomal defects,including Down Syndrome, indicated in the hospitaliza-tion record (ICD-9-CM code 758) or on the birth certifi-cate were also excluded from all analyses (93 controls; 18hypospadias cases; 30 cryptorchidism cases; and 4 withboth hypospadias and cryptorchidism). Thus, the controlgroup did not include infants with any urogenital defect,recorded on CHARS or on the birth certificate. However,case and control infants may have had other congenitalmalformations.Exposure. The primary exposure considered was

maternal pre-pregnancy obesity as indicated by bodymass index (BMI, weight divided by the square of height[kg/m2]; National Institutes of Health, 1998). Pre-preg-nancy weight has been recorded on birth certificates inWashington State since 1992. Weight is recorded to thenearest pound and is obtained from the mother’s physi-cian or medical records; whether this information wasassessed clinically or resulted from self-report was notindicated. If unavailable from these sources, the motheror another family member may provide pre-pregnancyweight (2003). For births before 2003, maternal heightwas obtained from state driver’s license records linked tomaternal information on birth records. Beginning in 2003,maternal height to the nearest inch was collected on birthrecords in the same manner as pre-pregnancy weight(Washington State Department of Health, 2003). BMI wascategorized as underweight (BMI <18.5 kg/m2), normalweight (18.5 � BMI <25 kg/m2), overweight (25 � BMI<30 kg/m2), or obese (BMI �30 kg/m2). An additionalcategory, morbidly obese (BMI >40 kg/m2), was addedin some analyses as noted. BMI as a continuous variable,included as either a single linear term or linear andquadratic terms, was also examined. For analysis with asingle linear BMI term, mothers with BMI <18.5 kg/m2

were excluded.Statistical analysis. Unconditional logistic regression

was used to estimate crude and adjusted odds ratios(aORs) and 95% confidence intervals (95% CIs) separatelyfor hypospadias and cryptorchidism.Based on a priori development of causal diagrams to

identify confounders, aOR estimates were adjusted foryear of birth (1992–1996, 1997–2002, 2003–2008) and thefollowing maternal characteristics: age (<20 years, 20–24years, 25–29 years, 30–34 years, or �35 years), race (non-Hispanic white, Hispanic, Asian or Pacific Islander,others), educational attainment (less than high school;completed high school; some college; completed college),number of previous live births (none, 1, 2, or more), andany smoking during pregnancy (yes or no). Maternalpre-pregnancy diabetes, pre-pregnancy hypertension, andpreeclampsia were not included as adjustment variablesbecause each is potentially in the causal path between

242 ADAMS ET AL.

Birth Defects Research (Part A) 91:241�248 (2011)

maternal BMI and birth defects. For the same reason,birth weight and gestational age were not considered aspotential confounders. The interaction of dichotomizedmaternal BMI (�26 kg/m2, >26 kg/m2), maternal age(<30, 30–34, �35 years), and previous births (none, any)was investigated following a previous report (Carmichaelet al., 2007). A single variable with 12 levels representingthe possible combinations of these variable parameteriza-tions was used as the exposure, with additional adjust-ment for other potential confounders as in the main anal-ysis. Linear combinations of coefficients from this modelwere examined for departures from a multiplicativemodel.

Sensitivity analyses. Pre-pregnancy BMI was unavail-able for approximately 30% of mothers. To explore somepossible biases due to missing BMI information, severaladditional analyses were performed. The completeness ofmaternal BMI information varied by birth year (1992–1996, 36.1% missing; 1997–2002, 32.1% missing; 2003–2008, 13.7% missing), likely as a result of the changes inrecording of height and weight noted above. We, there-fore, repeated the primary analysis separately by birthyear (1992–1996, 1997–2002, 2003–2008). In separate anal-yses, pre-pregnancy weight, categorized into quintiles oras a continuous variable, was used in place of BMI.Finally, we repeated analyses only for non-Hispanicwhites, among whom BMI information was more com-plete.

In addition, we applied multiple imputation separatelyto the hypospadias and cryptorchidism analyses. Twentysets of values of the natural logarithm of BMI were pre-dicted using multivariate normal imputation from thepotential confounders listed above and a dichotomousvariable indicating case status, including only mother-infant pairs with complete confounder information. Fromthese results, imputed BMI was calculated and used inmultivariable logistic regression models including thesame adjustment variables as the complete-case analysis,following standard multiple imputation analysis techni-ques to combine aOR point estimates and SEs (Rubin,1987; Schafer, 1997; Lee and Carlin, 2010).

To examine the sensitivity of our results to otherpotential sources of bias, several restricted analyses wereperformed. The complete-case analysis was repeated sep-arately after restriction to each of the following: birthweight 2500 to 4200 g; gestational age 37 to 42 weeks;mothers without pre-pregnancy hypertension; motherswithout pre-pregnancy diabetes; mothers who did notdevelop preeclampsia; and mothers without diabetes,hypertension, or preeclampsia.

We repeated the complete-case primary analysis afterrestriction of controls to infants with no congenitaldefects of any kind and restriction of cases to thoseinfants with only the index defect and no others(‘‘isolated cases’’). In addition, the complete-case analysiswas repeated restricting hypospadias cases to those bornafter 1996 with additional diagnosis of congenital chor-dee indicated in the birth hospitalization record (ICD-9-CM 752.63; n 5 137); and, separately, to hypospadiascases indicated on both the specific birth certificate check-box and the birth hospitalization record (2003–2008 only;n 5 258).

The sensitivity of the results to non-differential mis-classification was examined using a published statisticalsimulation tool implemented in Microsoft Excel (Red-

mond, WA) 2003 (Fox et al., 2005; Lash, 2009). In sum-mary, this tool back-calculates the ‘‘true’’ odds ratio (OR)after randomly selecting values of sensitivity and speci-ficity for both exposure and disease, from ranges pro-vided by the user. The software repeated this calculation5000 times to generate a ‘‘simulation interval’’ thatincludes 95% of all back-calculated ‘‘true’’ ORs, account-ing for misclassification and random error. To preventcomputer memory overrun, the number of controls wasreduced to 1000 with obese mothers and 3068 with nor-mal-BMI mothers. Only normal-BMI and obese motherswere included in a dichotomized exposure classification,ignoring other women for the purposes of sensitivityanalysis, and we did not include stratification on anypotential confounders in the simulations. For bothdisease and exposure, the sensitivity and specificity ofclassification varied from 60 to 80% and 85 to 100%,respectively.Data cleaning, logistic regression, and multiple imputa-

tion were completed with Stata/SE versions 10 and 11(StatCorp LP, College Station, TX).Ethical conduct of research. The Internal Review

Board for Protection of Human Subjects at the Universityof Washington, Seattle, and the Washington State Depart-ment of Health approved this research.

RESULTS

The study included for analysis 3268 male singletoninfants diagnosed with hypospadias, 3946 diagnosedwith cryptorchidism, and 48,874 controls randomlyselected from all singleton male infants without any geni-tal defect. Of these, maternal pre-pregnancy BMI datawere missing for 909 hypospadias cases (27.8%), 1187cryptorchidism cases (30.1%), and 13,606 controls (27.8%).Therefore, analyses included 2359 hypospadias cases and2759 cryptorchidism cases, including 36 infants with bothconditions, in addition to 35,268 controls with completematernal BMI information (Table 1).Compared to mothers of controls, a larger proportion

of mothers of boys with hypospadias were over 35 yearsof age, non-Hispanic white, and college-educated (Table1). In contrast, mothers of infants with cryptorchidismwere very similar to mothers of controls. Infants with ei-ther anomaly were more often the mother’s first childthan were control infants.Infants born to underweight, overweight, or obese

mothers were not at higher risk of hypospadias or cryp-torchidism relative to infants born to normal BMI moth-ers (Table 2). No association was observed when mater-nal BMI was included as a linear continuous variable inthe statistical model (Table 2); and addition of a quad-ratic BMI term did not change results (not shown). CrudeOR estimates and estimates adjusted for year of birthand maternal age, race, parity, education, and smokingduring pregnancy differed only slightly, suggesting mini-mal confounding by these maternal characteristics (Table2). When obese mothers were divided into obese (30 <BMI <40 kg/m2) and morbidly obese (BMI �40 kg/m2)categories, risk estimates did not differ substantiallybetween the two categories and were similar to estimateswith a single obese category comparing morbidly obeseto normal BMI, hypospadias (aOR, 1.15; 95% CI, 0.89–1.48), cryptorchidism (aOR, 1.04; 95% CI, 0.82–1.33).Results of analysis substituting quintiles of maternal pre-

243OBESITY AND HYPOSPADIAS OR CRYPTORCHIDISM


Table 1Characteristics of mothers with complete body mass index (BMI) information and their infants selected for study

from Washington State registered births, 1992–2008

Controls Hypospadias Cryptorchidism

N % N % N %

35,268 2359 2759Birth year

1992–1996 8893 25.2 649 27.5 711 25.81997–2002 14,128 40.1 676 28.7 901 32.72003–2008 12,247 34.7 1034 43.8 1147 41.6

Mother’s ageLess than 20 3450 9.8 184 7.8 293 10.620–24 8589 24.4 542 23.0 680 24.625–29 10,057 28.5 660 28.0 732 26.530–34 8462 24.0 580 24.6 673 24.4351 4710 13.4 393 16.7 381 13.8

Previous live births0 14,668 41.6 1097 46.5 1324 48.01 11,548 32.7 738 31.3 789 28.621 8857 25.1 514 21.8 624 22.6Missing 195 0.6 10 0.4 22 0.8

Mother’s educationLess than high school 5784 16.4 274 11.6 498 18.1High school graduate 9743 27.6 633 26.8 751 27.2Some college 9334 26.5 683 29.0 700 25.4College graduate 8788 24.9 682 28.9 686 24.9Missing 1619 4.6 87 3.7 124 4.5

Mother’s race/ethnicityWhite 26,594 75.4 1984 84.1 2013 73.0Hispanic 3399 9.6 100 4.2 271 9.8Asian/Pacific Islander 2645 7.5 113 4.8 228 8.3Other 1890 5.4 109 4.6 192 7.0Missing 740 2.1 53 2.2 55 2.0Mother smoked during pregnancyNo 30,181 85.6 2015 85.4 2300 83.4Yes 4723 13.4 324 13.7 423 15.3Missing 364 1.0 20 0.8 36 1.3

Gestational age (weeks)Less than 37 weeks 2055 5.8 269 11.4 271 9.837–42 weeks 32,762 92.9 2068 87.7 2450 88.8421 weeks 37 0.1 1 0.0 1 0.0Missing 414 1.2 21 0.9 37 1.3

Birth weight (g)Less than 2500 1140 3.2 215 9.1 219 7.92500–3999 28,526 80.9 1845 78.2 2212 80.2�4000 5538 15.7 288 12.2 319 11.6Missing 64 0.2 11 0.5 9 0.3

Maternal diabetesNo diabetes 33,287 94.4 2206 93.5 2554 93Pre-existing diabetes 138 0.4 14 0.6 17 1Gestational diabetes 1397 4.0 95 4.0 126 5Missing 446 1.3 44 1.9 62 2

Chronic hypertensionNo 34,472 97.7 2281 96.7 2660 96.4Yes 350 1.0 34 1.4 37 1.3Missing 446 1.3 44 1.9 62 2.2

PreeclampsiaNo 32,970 93.5 2127 90.2 2509 90.9Yes 1852 5.3 188 8.0 188 6.8Missing 446 1.3 44 1.9 62 2.2

BMI category (kg/m2)Underweight (<18.5) 1421 4.0 97 4.1 130 4.7Normal (18.5–24.9) 19,367 54.9 1266 53.7 1484 53.8Overweight (25–29.9) 8168 23.2 545 23.1 651 23.6Obese (301) 6312 17.9 451 19.1 494 17.9

244 ADAMS ET AL.


pregnancy weight, in the place of BMI, yielded similarresults; aOR (95% CI) comparing the uppermost quintileof pre-pregnancy weight (>79.1 kg) to the second-lowestquintile (54.5–61.0 kg) were 1.13 (1.00–1.28) for hypospa-dias and 1.02 (0.91–1.15) for cryptorchidism. Pre-preg-nancy weight as a continuous variable was also not asso-ciated with risk of either malformation.

No important differences in the association of BMI,dichotomized at 26 kg/m2, with either malformationwere observed between strata formed by maternal ageand parity. For hypospadias, the strongest associationwith maternal BMI over 26 kg/m2 compared to thosebelow 26 kg/m2 was observed among nulliparous moth-ers over age 35 (125 cases total; aOR, 1.37; 95% CI, 0.93–2.02). Similar analysis of cryptorchidism consistentlyshowed very weak associations among all strata combin-ing maternal age and parity (not shown).

Pre-existing maternal diabetes, chronic hypertension,or preeclampsia were more common among mothers ofinfants with hypospadias or cryptorchidism (Table 1).Analysis of the association between maternal BMI andhypospadias and cryptorchidism restricted to womenwithout each of these conditions, or without any of them,yielded results similar to the primary analysis among allparticipants (not shown). Results of restricted analysisincluding only infants born after 37 to 42 weeks gesta-tion, or weighing 2.5 to 4.0 kg at birth, also did not differsubstantially (not shown).

Restriction of the control group to infants without a di-agnosis of any congenital defects (ICD-9-CM 740.0–759.9)excluded 1271 infants. Restriction of case groups toinfants without defects other than hypospadias or cryp-torchidism excluded 350 and 288 infants, respectively.Among this restricted set of infants, the aORs comparingobese to normal-weight mothers for hypospadias (aOR,1.02; 95% CI, 0.89–1.16) or cryptorchidism (aOR, 0.97;95% CI, 0.86–1.09) were not substantially different com-pared to the results in Table 2.

Approximately 30% of birth records for infants eligiblefor inclusion in this study were missing maternal BMI in-formation. From 2003 to 2008, maternal height wasrecorded directly on the birth certificate, and the propor-tion of birth records missing maternal BMI dropped to14%, but results of analyses restricted to this range of

birth years did not differ substantially from the mainanalysis results comparing obese to normal-weightwomen, restricted to 2003 to 2008, hypospadias (aOR,1.02; 95% CI, 0.86–1.21), cryptorchidism (aOR, 0.88; 95%CI, 0.75–1.04).The estimated ORs for hypospadias or cryptorchidism

in each of the multiple imputation analyses also showedlittle difference from the complete-case analysis. Multipleimputation resulted in the inclusion of an additional 714hypospadias cases, 934 cryptorchidism cases, and 10,906controls. Including imputed data, the estimated compar-ing obese to normal-weight women were (aOR, 1.09; 95%CI, 0.98–1.22) and (aOR, 0.97; 95% CI, 0.87–1.09) forhypospadias and cryptorchidism, respectively, similar tothe result of the complete-case analysis.

DISCUSSION

Overall, we observed little or no evidence of associa-tion between pre-pregnancy maternal BMI and risk ofhypospadias or cryptorchidism, two of the most commongenital defects in male infants.Our study has important strengths. It is population-

based, with the vast majority of births in WashingtonState over 17 years eligible to be included. To our knowl-edge, our study includes the largest number of cases ofstudies to date of the relationship between maternal BMIand these defects in the United States. One previousstudy, conducted in Sweden (Blomberg and Kallen,2010), included nearly 3000 hypospadias cases but didnot examine cryptorchidism.We relied on height and weight information routinely

collected as part of the Washington State birth registra-tion system. According to the protocol for completingbirth records, maternal pre-pregnancy weight and, after2002, height, were obtained from medical records. It isnot known whether the information in the medical recordis self-reported or clinically assessed, but in either case,weight information in the medical record was obtainedprior to birth and, therefore, was not influenced by mal-formations in the infant. We also used simulations toexamine the impact of misclassification of maternal BMIand found that this is an unlikely explanation for ourresults. For maternal height before 2003, information

Table 2Crude OR and aORs and 95% CIs of association between maternal pre-pregnancy BMI category and hypospadias

or cryptorchidism among Washington State male singleton infants, 1992–2008

Controls Hypospadias Cryptorchidism

N* N** N* OR* (95% CI) N** aOR** (95% CI) N* OR* (95% CI) N** aOR** (95% CI)

BMI Categoryy

Underweight 1421 1283 97 1.04 (0.84–1.29) 83 1.06 (0.84–1.33) 130 1.20 (0.99–1.44) 116 1.14 (0.93–1.39)Normal 19,367 17,895 1266 Ref. 1193 Ref. 1484 Ref. 1382 Ref.Overweight 8168 7600 545 1.02 (0.92–1.13) 518 1.04 (0.93–1.16) 651 1.04 (0.95–1.15) 606 1.03 (0.93–1.14)Obese 6312 5956 451 1.09 (0.98–1.22) 425 1.07 (0.95–1.21) 494 1.02 (0.92–1.14) 459 0.99 (0.89–1.11)Per 5 kg/m2yy 1.03 (0.99–1.07) 1.03 (0.99–1.07) 1.01 (0.98–1.05) 1.01 (0.97–1.05)

*Includes infants with complete maternal body mass index data but incomplete maternal education, previous births, race, or smokinginformation; unadjusted (crude) OR and 95% CI.

**Includes infants with complete information on maternal BMI and adjustment variables; OR and 95% CI adjusted for mother’s age,mother’s education, previous number of live births, mother’s race, year of birth, and maternal smoking during pregnancy.

yBMI categories: underweight (<18.5 kg/m2); normal (18.5–24.9 kg/m2); overweight (25.0–29.9 kg/m2), obese (�30 kg/m2).yyBMI modeled as a single linear continuous variable, excluding mothers with BMI <18.5 kg/m2. OR, odds ratio; aORs, adjusted

odds ratios; CI, confidence interval; BMI, body mass index.



from Washington State driver’s license records waslinked to birth records. Women may have misrepresentedtheir heights, provided by self-report at the time of driv-er’s license issue, but misclassification of height informa-tion is unlikely to be differential with respect to the casestatus of a woman’s child. The minimization of potentialdifferential misclassification of pre-pregnancy maternalBMI is a strength of our methodological approach.

Approximately 30% of cases and controls eligible forour study were missing either height or weight informa-tion, precluding calculation of BMI for these individuals.We observed that BMI information was more likely to bemissing for Hispanic and African-American mothers, andamong mothers with lower educational attainment.Because these groups could have differing risk of con-genital defects, the direction of bias introduced by miss-ing BMI cannot easily be predicted. However, the pro-portions of infants with missing maternal BMI informa-tion in each case group and among controls were nearlyidentical (29%, 31%, and 30% for hypospadias, cryptorch-idism, and controls, respectively). Furthermore, we inves-tigated the impact of missing BMI by using restrictedanalyses and multiple imputation. Neither approach sug-gested that the complete-case analysis we undertook issubstantially biased due to incomplete BMI data on somemothers.

These results regarding hypospadias are consistentwith one early study (Polednak and Janerich, 1983), butstand in contrast to those reported from several morerecent studies in which there was increased risk of hypo-spadias among infants born to obese mothers comparedto normal-weight mothers (Carmichael et al., 2007; Walleret al., 2007; Akre et al., 2008; Blomberg and Kallen, 2010).Two of these reports arose from the same study samplethat ascertained cases from birth defects registries ineight different U.S. states and controls from separate hos-pital records, and relied on maternal self-report of pre-pregnancy weight up to 24 months after delivery (Yoonet al., 2001; Carmichael et al., 2007; Waller et al., 2007).Carmichael et al. (2007) also suggested that the associa-tion between maternal BMI and risk of hypospadias var-ied depending on maternal age and the number of previ-ous births, and was strongest among older, first-timemothers. In our study, we observed at most a small dif-ference in risk of hypospadias and cryptorchidism amongthese groups, and our aOR estimates were accompaniedby wide CIs, suggesting that any difference may reflect achance finding. A larger study based upon Swedish birthrecords, hospital data, and birth defects registry data pro-duced results similar to those of Carmichael et al. (2007)in which boys born to obese mothers had a statisticallysignificant �30% higher odds of hypospadias (Carmi-chael et al., 2007; Waller et al., 2007; Blomberg andKallen, 2010). A smaller study, combining Swedish andDanish cases recruited from clinical and administrativesources and which also relied on self-reported pre-preg-nancy weight, estimated an OR of 2.6 for hypospadias,comparing obese to normal-BMI mothers (Akre et al.,2008). All of these studies excluded infants with congeni-tal defects from the control group, in contrast to ourapproach. However, when we did exclude infants withother defects from our control group and restricted anal-ysis to isolated cases, our results were not changed.

Risk of cryptorchidism persisting for 1 year after birthhas also been associated with high maternal BMI in a

case-control study (Depue, 1984) and prospective cohortstudy (Berkowitz et al., 1995). However, these reportscontrast with the results of a recent prospective study inDenmark and Finland in which cryptorchidism wasassessed at 3 months of age (Damgaard et al., 2008), andwith the results of an earlier clinic-based case-controlstudy that included only infants with cryptorchidism atage 1 year or later (McBride et al., 1991), which bothreported no association. Our results indicate no relation-ship between maternal BMI and cryptorchidism assessedat birth or shortly thereafter. Thus, considerable uncer-tainty remains about whether maternal obesity is associ-ated with risk of cryptorchidism, and may result in partfrom differences in case definition and ascertainment.Non-differential misclassification of maternal BMI or

diagnosis of genital defects in our study could have atte-nuated our estimates of association. To assess this possi-bility, we simulated the combination of non-differentialmisclassification of exposure and disease (Fox et al., 2005;Lash, 2009). A study in California found that <10% ofhypospadias cases reported in hospital discharge recordsare false-positives, but did not quantify false-positivecryptorchidism cases (Hexter et al., 1990). The sensitivityof hospital discharge records in detecting hypospadiasand cryptorchidism may be as low as �70% and 65%,respectively (Calle and Khoury, 1991). Using these valuesas a plausible range, and the values for the sensitivityand specificity of maternal BMI, the results of our simu-lations estimated a corrected aOR for hypospadias and95% simulation interval of (aOR, 1.15; 95% CI, 0.97–1.36),comparing obese mothers to normal-BMI mothers. Thusthe results of our study are not likely to be fullyaccounted for by non-differential misclassification ofmaternal BMI, infant case status, or both.A reliance on hospital-discharge diagnosis codes to

determine case and control status among infants limitedour ability to determine the severity of hypospadias orcryptorchidism. Because surgical correction of thesedefects is typically an outpatient procedure and, there-fore, is not reflected in the hospitalization data, we couldnot use evidence of such treatment to refine or confirmthe diagnoses. Three degrees of severity are usually rec-ognized for hypospadias depending on the location ofthe urethral meatus; with a more proximal location con-sidered more severe (Baskin et al., 2001; Madhok et al.,2009; Brouwers et al., 2010). According to previousreports, 60 to 80% of hypospadias cases are distal, with aglanular or coronal meatus, and <10% are the mostsevere, characterized by the meatus on or below the scro-tum (Baskin et al., 2001; Baskin and Ebbers, 2006; Carlsonet al., 2009; Madhok et al., 2009). Thus, we expect thatthe majority of the cases included in our analysis wereglanular or coronal and relatively mild, in contrast tosome earlier studies that focused on more severe hypo-spadias (Carmichael et al., 2007; Waller et al., 2007).Nonetheless, we identified 101 hypospadias cases also

diagnosed with congenital chordee, a second defect asso-ciated with more severe hypospadias (Baskin et al., 2001;Baskin and Ebbers, 2006), and repeated our primary com-plete-case analysis. Results were largely unchanged,although the precision of the aOR estimates was greatlyreduced. We also conducted a separate analysis restrictedto hypospadias cases identified on both the birth certifi-cate and hospital records, on the assumption that defectsrecorded in both places may be more readily apparent

246 ADAMS ET AL.


and hence, more severe. No noteworthy change in theaOR estimates resulted given the small size of these sub-groups. Nonetheless, to the extent that disease of differ-ing severity has different etiology, misclassification ofcase status by severity could bias our results.

For cryptorchidism, there is an accepted distinctionbetween cases that resolve spontaneously in the monthsfollowing birth, and more serious cases that ultimatelyrequire surgical correction. Overall, 2 to 5% of maleinfants are born with cryptorchidism, but the prevalenceat birth is as high as 20 to 30% among infants <2500 g atbirth (Berkowitz et al., 1993; Boisen et al., 2004; Corteset al., 2008). About 50% of cryptorchidism cases resolvewithin 3 months of birth, irrespective of birth weight(Berkowitz et al., 1993; Boisen et al., 2004; Cortes et al.,2008). We performed two additional analyses, restrictedto full-term (37–42 weeks) and to full-term normal-weightinfants (37–42 weeks and 2.5–4.0 kg), and the results didnot change. However, because we lacked follow-up infor-mation on the severity of cryptorchidism or follow-updata on infants in our study sample, we were unable toidentify cryptorchidism cases that later resolved throughspontaneous descent. Thus, although we observed noassociation between high maternal BMI and cryptorchid-ism, such an association may be limited to the 25 to 50%of cases whose cryptorchidism does not spontaneouslyresolve. Given the many cases included in our study,however, such an association could not be strong or wewould likely have observed some evidence of it in ouranalyses.

In summary, we observed no relation between mater-nal BMI and the male genital anomalies hypospadias andcryptorchidism. Although non-differential misclassifica-tion may be present in our study sample, simulationsindicate that it would need to be extreme to account forour results if the true association between maternal obe-sity and hypospadias and cryptorchidism is consistentwith previous studies (Berkowitz et al., 1995; Carmichaelet al., 2007; Akre et al., 2008; Blomberg and Kallen, 2010).Missing BMI information is also unlikely to explain ourobservations, based on the results of analysis restricted toyears with the most complete data, and the results ofanalysis employing multiple imputation to predict miss-ing maternal BMI values. Therefore, the results of thisstudy are most consistent with the conclusion that pre-pregnancy maternal obesity is not associated with risk ofeither hypospadias or cryptorchidism in male offspring.

ACKNOWLEDGEMENTSThe authors thank Mr. Bill O’Brien for data manage-

ment and programming, the Washington State Depart-ment of Health for access to birth records, and Drs. BethMueller and Stephen Hawes for comments.

Supported in part by a grant from the National Insti-tutes of Health, National Cancer Institute Cancer Preven-tion Training Grant R25 CA094880 to SVA.

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