Secondary Logo

Journal Logo

Pregnancy: Original Article

Prenatal and Perinatal Factors and Risk of Multiple Sclerosis

Gardener, Hannaha; Munger, Kassandra L.b; Chitnis, Tanujac; Michels, Karin B.a,d,e; Spiegelman, Donnaa,f; Ascherio, Albertoa,b,e

Author Information
doi: 10.1097/EDE.0b013e31819ed4b9

The etiology of multiple sclerosis (MS) is unknown, although the pathologic features are consistent with an autoimmune mechanism, and roles for both genetic and environmental factors have been suggested.1,2 The goal of this study was to examine whether prenatal and perinatal factors influence susceptibility to MS. A role of maternal factors is suggested by the higher recurrence risk for maternal half-siblings than paternal half-siblings.3 Prenatal stress is believed to increase the risk of pregnancy complications4–6 and modulate the hypothalamic-pituitary-adrenal axis, increasing adenocorticotropic hormone, corticotropic-releasing hormone, and cortisol, which may result in impaired immune function and thymic atrophy.4,7

Although a few studies have examined the relation between MS risk and month of birth8,9 and family structure,10 there are no previous reports directly assessing the effects of prenatal and perinatal exposures. Modest support for a role of pregnancy complications in autoimmunity and immune system development has been provided by studies on other autoimmune diseases. In 2 small case-control studies, high birthweight was associated with an increased risk of Sjögren syndrome11 and rheumatoid arthritis,12 but no significant associations were found for maternal disease during pregnancy, previous miscarriage, and gestational age.11,12 A role of prenatal and perinatal exposures in the causes of type-1 diabetes and atopic conditions has also been suggested, although results are inconsistent.13,14

We examined whether in utero and early-life factors relate to the risk of MS among participants in 2 large ongoing prospective cohorts, the Nurses' Health Study (NHS)15 and Nurses' Health Study II (NHS-II),16 together comprising more than 200,000 female nurses in the United States.



The Nurses' Health Studies

The NHS began in 1976 with 121,701 female nurses ages 30-55 years identified by US nursing boards. Following the initial questionnaire in 1976, these nurses receive a follow-up questionnaire every 2 years to collect information on demographic, lifestyle, and health-related factors, and newly diagnosed diseases. The NHS-II was established in 1989 with 116,680 female US registered nurses ages 25-42 years, followed with similar biennial questionnaires. A participation rate of about 90% has been achieved for both cohorts over time. This research was approved by the Institutional Review Board at Brigham and Women's Hospital in Boston, Massachusetts.

Nurses' Mothers' Cohort17

In 2001, permission was requested from NHS and NHS-II participants to send a questionnaire to their mothers regarding the nurses' early life exposures. This subcohort was restricted to living nurses who had not been diagnosed with cancer, with living biologic mothers who were free of dementia and other debilitating diseases prohibiting participation. Of these, 52,540 agreed to participate and 39,904 maternal questionnaires were returned. The questionnaire inquired about the mothers' experiences during the pregnancy and birth of their NHS-member daughter. For this study, the nurses' mothers' cohort was restricted to the NHS-II members (n = 35,815), as they comprised 90% of the mother's cohort.

Outcome Assessment

Cases were defined as physician-confirmed MS, as previously described.18,19 Briefly, cases were identified by self-report on the biennial questionnaires. Nurses were asked to report major illnesses throughout follow-up and were asked specifically about lifetime diagnosis of MS in 1991 and 1992. Subsequent questionnaires collected information on diagnosis within the past 2 years. Permission to review medical records was requested of everyone who reported an MS diagnosis. Diagnoses were confirmed by asking the treating neurologist to complete a questionnaire on diagnostic certainty, clinical history, clinical signs, and laboratory tests. If a neurologist was not involved in diagnosis or failed to respond, the woman's internist was contacted for diagnostic confirmation. A case was confirmed if the diagnosis was considered definite or probable by the treating neurologist or internist or by medical record review. In 90% of cases the treating physician was a neurologist.

Exposure Assessment

eTable 1 ( lists the prenatal and perinatal factors that have been assessed in the Nurses' Health Studies, including the nurses' mothers' cohort. Some factors were included in the NHS and NHS-II biennial questionnaires and were therefore self-reported by the nurses. However, the majority of factors were available only among the nurses' mothers' cohort, included in the questionnaire completed by the nurses' mothers in 2001. eTable 1 shows the sample available for each exposure (

For in utero diethylstilbestrol (DES) exposure, assessed in the NHS-II in 1993, a confirmation questionnaire was sent to all nurses who self-reported DES exposure to classify the level of certainty (very certain, somewhat certain, not certain, or not exposed). The current analysis uses a conservative approach and compares those who were very certain of DES exposure with those who self-reported as nonexposed.

For the maternal-reported exposures in the nurses' mothers' cohort, an obstetric suboptimality score was calculated by adding 1 point for each positive response to the factors listed in eTable 2 ( Due to the rarity of specific complications, optimality scales have been used to examine the relation between overall prenatal health and disease risk. A popular scale is the Gillberg Optimality Scale.20 The factors on the Gillberg scale are included in our score, in addition to factors included in the maternal questionnaire that were identified by the investigators as potentially representing a suboptimal prenatal environment (lack of prenatal health care, severe nausea, DES exposure, anemia, hospitalization, cigarette smoking, and infertility).

Three factors were hypothesized a priori to be related to maternal immune function during pregnancy: infections during pregnancy, preeclampsia or eclampsia, and proteinuria.21–23 Preeclampsia is a pregnancy condition of unknown etiology, characterized by hypertension and proteinuria.24 It may represent maternal immune rejection of the foreign fetus, resulting in a systemic inflammatory response.22,23 MS risk was examined in relation to exposure to any 1 or more of these factors by using a dichotomized variable (0 vs. 1+ “immune-related factors”).

Statistical Analysis

In the NHS, only MS cases with diagnosis after cohort recruitment (incident cases) were confirmed by requesting medical records. Therefore, women who reported MS with diagnosis before study enrollment were excluded from the NHS analyses. Each participant contributed person-time from the return date of the baseline questionnaire (1976) to the date of diagnosis, death, or end of follow-up (June 2002), whichever came first. In contrast, in the NHS-II, an attempt was made to confirm the MS diagnoses among women with diagnosis before enrollment in the study (prevalent cases) as well as the incident cases. For the NHS-II, person-time began at age 19 and extended to the date of diagnosis, death, or end of follow-up (June 2003), whichever came first. In addition to pooling the incident and prevalent cases, a sensitivity analysis was conducted that was restricted to person-time accrued after the baseline questionnaire, including only the incident cases. The nurses' mothers' cohort analyses were conducted identically to the full NHS-II analyses.

Cox proportional hazards models were used to estimate rate ratios (RRs) and 95% confidence intervals (CIs) for each factor stratified by age in months and calendar year. Multivariate-adjusted Cox models were used to estimate the RR for each factor simultaneously adjusting for the following MS risk factors assessed in the biennial questionnaires: age, calendar year, latitude at birth (north, middle, or south),25 sibship size (0, 1, 2+),26 paternal occupation (professional/managerial vs. other) as a proxy for early life socioeconomic status,27 pack-years of cigarette smoking (never, <10, 10-24, 25+ packs/y),18,28 and total energy-adjusted vitamin D intake during adulthood (quintiles).19,29,30

For factors examined in both the NHS and the NHS-II, a summary effect estimate was calculated using a random-effects model after pooling the results by using inverse-variance weighting.31 Tests of heterogeneity of the main exposures by cohort were performed using the Q statistic. Statistical analyses were performed using SAS9 (SAS institute, Cary, NC).

Linear tests of trend were conducted for the continuous variables (parental age at birth, maternal prepregnancy BMI, birth length, and obstetric suboptimality score), and ordinal categorical variables (birthweight, maternal weight gain, and activity level during pregnancy). We also examined the possibly nonlinear relation between these variables and the risk of MS nonparametrically with stepwise-restricted cubic splines.32 Tests for nonlinearity used the likelihood ratio test, comparing the model with only the linear term to the model with the linear and cubic spline terms.

Cases were accrued both before and after exposure assessment. The nurses' mothers' cohort analyses were primarily retrospective because the exposures were assessed in 2001, 2 years before the last year of case accrual. The analysis of self-reported prenatal smoke exposure was also primarily retrospective because exposure was assessed in 1999 and 2004. However, for the analyses of nurses' self-reported birthweight and preterm birth, 53% of the cases (n = 383) were accrued after exposure data collection (1991-1992), and for self-reported DES exposure 54% of the NHS-II cases (n = 262) were diagnosed after exposure assessment (1993). Due to the possibility of recall bias, for the latter 3 variables, sensitivity analyses were conducted restricted to person-time and case accrual following exposure assessment.


The analysis included 593 incident MS cases (241 in the NHS and 352 in the NHS-II), and 130 prevalent cases diagnosed before baseline in the NHS-II. For all exposure variables other than DES, the conclusions based on the univariate age-adjusted Cox models were the same as those from the multivariate-adjusted analyses. Therefore, only multivariate-adjusted results are presented for all factors except DES.

The effect estimates for the multivariate-adjusted analyses of the relation between MS and the prenatal and perinatal exposures assessed by self-report in the NHS and NHS-II are shown in Table 1. There was no significant heterogeneity in the cohort-specific effect estimates for any factor. Overall, these self-reported factors were not associated with the risk of MS. For birthweight and preterm birth, there was no observed association in the full cohort analyses or in the prospective sensitivity analyses (not shown).

Prenatal/Perinatal Factors and Risk of MS in the NHS and NHS-II Cohorts

In the analysis of incident cases, there was a marginal 50% increased risk among women whose fathers smoked during the prenatal period, and a 24% increased risk among those passively exposed to parental smoking during childhood. When the sample was restricted to women who never smoked in adulthood, these associations were attenuated (for paternal smoking in prenatal period, RR = 1.2 [95% CI = 0.67–2.3]; for childhood passive smoke exposure, 1.2 [0.90–1.5]).

Table 2 shows the univariate age-adjusted and multivariate-adjusted RRs and 95% CIs for the association between self-reported prenatal DES exposure and risk of MS in the NHS-II. The univariate analysis restricted to all incident cases and that restricted to cases diagnosed after 1993 both showed an increased risk of MS associated with in utero exposure to DES, with effect estimates exceeding 2. However, this association was attenuated in the analysis that included the prevalent cases, and after multivariate adjustment.

Prenatal DES Exposure and Risk of MS in the NHS-II

The nurses' mothers' subcohort included 184 MS cases (132 incident and 52 prevalent cases). Table 3 shows the multivariate-adjusted RRs and 95% CIs for the factors assessed in the maternal questionnaire with an RR exceeding 1.50 or less than 0.67. In addition, the multivariate-adjusted RRs and 95% CIs for all factors assessed in the maternal questionnaire are listed in eTable 3 (

Prenatal/Perinatal Factors and Risk of MS in the Nurses' Mothers' Subcohort

As shown in Table 3, maternal adiposity was associated with risk of MS. In fact, the decreased risk associated with low maternal prepregnancy BMI persisted after controlling for the BMI of the nurses themselves at age 18 (0.39 [0.18–0.85]), although the increased risk observed in relation to maternal overweight and obesity was attenuated after controlling for the nurses' BMI at age 18 (1.5 [0.90–2.4]). After controlling for prepregnancy BMI, there was no substantial relation between weight gain and MS (not shown). Although there were no incident cases whose mothers reported diabetes during pregnancy, 2 prevalent cases were exposed, resulting in an observed 10-fold increase in risk associated with maternal diabetes. This association persisted after controlling for maternal prepregnancy BMI (9.6 [2.3–40]).

The obstetric suboptimality score was not associated with risk of MS. In the analysis that included both prevalent and incident cases, there was no association between the immune-related maternal complications and risk of MS. However, pregnancies with 1 or more of the factors hypothesized to be related to maternal immune function were associated with a 86% increased risk in the analysis restricted to the incident cases (CI = 1.1–3.3).

There was no significant nonlinearity with any continuous or ordinal variable except for maternal age. Because the observed trend for this variable was of an implausible bimodal form, we do not consider it further.


In this large prospective cohort study of women with more than 700 MS cases, no convincing association with risk of MS was observed for the majority of prenatal and perinatal factors, including parental age at birth, obstetric history, previous fetal loss, preterm birth, mode of delivery, and morning sickness. However, this exploratory analysis did suggest potential modest associations for some prenatal or perinatal factors including late initiation of prenatal care, lack of parental cohabitation at birth, elevated maternal prepregnancy BMI, and diabetes. In addition, a potential elevated risk of MS was suggested among women exposed prenatally to DES. Various potential early life risk factors warrant further examination in future studies, although their etiologic role, if present, may be modest.

The primary strengths of this study are the use of a large cohort with thorough case ascertainment, confirmation of self-reported diagnosis, and comprehensive data on other risk factors for MS. Despite these important strengths, there are also limitations. First, some exposure misclassification is inevitable as the mothers were asked to recall pregnancies that occurred more than 30 years ago, and the nurses were asked to report events from their own prenatal period and infancy. Because exposures were assessed in many women after the onset of MS, differential recall of prenatal factors cannot be excluded.

For the NHS-II individuals whose mothers participated in the maternal subcohort, we compared the nurses' reports with their mothers' reports for birthweight, preterm birth, prenatal DES use, and prenatal smoke exposure. The use of nurses' self-reported exposures in the primary analyses is supported by the high level of agreement with their maternal reports. We observed more than 89% agreement for the birthweight categories, preterm birth, DES exposure, and maternal smoking during pregnancy. Troy et al33 conducted a similar validation study with 538 NHS-II participants, and also reported a high degree of validity for birthweight and breast-feeding.

A study that assessed the reproducibility and validity of a similar maternal questionnaire provides evidence to support the use of retrospective maternal report of pregnancy-related events from more than 30 years ago.34 Reliability was examined by comparing questionnaires administered 2 years apart to 146 NHS mothers. A correlation of over 0.7 was achieved for prepregnancy weight, previous fetal loss, pregnancy complications, smoking, alcohol use, caffeine intake, preterm delivery, birthweight, and breast-feeding.34 This study also compared maternal recall of pregnancy-related factors with data collected during the pregnancies for 154 participants of the National Collaborative Perinatal Project. Validity of maternal recall was suggested by correlations of greater than 0.85 for birthweight and prepregnancy weight, in addition to specificity of over 0.85 for late initiation of prenatal care, smoking, pregnancy complications, preterm delivery, breech birth, and cesarean section. However, sensitivity was weak (<0.60) for late initiation of prenatal care, pregnancy complications, and forceps or vacuum extraction.34

This is the first study to assess directly the relation between prenatal DES exposure and risk of MS. DES is a synthetic nonsteroidal estrogen administered to pregnant women between 1940 and 1972 to treat and prevent pregnancy problems. Small preliminary studies have suggested an increased risk of any autoimmune disease35 or, more broadly, of diseases involving impaired immune function,36,37 among individuals with prenatal DES exposure. Experimental studies in laboratory animals as well as human case series have also indicated altered immune cell function associated with DES exposure, such as abnormal natural killer cell activity, T cell-mediated immunity, and thymic development.37–39 Despite the limited statistical power with this very rare exposure, there was modest support for a positive association. Further examination is warranted, especially because the potential association may be generalized to other prenatal hormone exposures.

Both maternal diabetes during pregnancy and increased prepregnancy BMI were suggested risk factors for MS in the maternal subcohort. Interpretation of the association with maternal diabetes must be made cautiously due to the limited data, the fact that only 2 cases were exposed, lack of screening during that time period resulting in likely exposure misclassification, and unknown time of onset (ie, whether it was gestational or preexisting diabetes).

Maternal prepregnancy weight has been shown to affect fetal growth and development, possibly due to the metabolic abnormalities and inflammatory markers associated with obesity.40,41 It is possible that the hormonal and metabolic disturbances and oxidative stress due to maternal obesity and diabetes can have lasting consequences for offspring health and development.42,43 A potential positive association between maternal BMI and risk of MS may be due to insufficient prenatal exposure to vitamin D because as high BMI is associated with decreased levels of vitamin D,44 and vitamin D exposure is suggested to be a protective factor for MS.19,45 It is also of note that maternal vitamin D deficiency has been associated with an increased risk of preeclampsia.46

Cigarette smoking is an established risk factor for MS.18 This is the first study to examine the relation between prenatal and childhood passive smoke exposure and MS risk, and no association was observed among never-smokers. The current results do not exclude a moderate effect of early-life passive smoke exposure. They do provide further indirect support for the causal nature of the relation between adult cigarette smoking and MS.

In summary, the results of this study suggest a potential association between select prenatal and perinatal exposures and risk of MS, including in utero DES exposure, late maternal initiation of prenatal care, lack of parental cohabitation at birth, maternal prepregnancy overweight/obesity, diabetes during pregnancy, and exposure to maternal immune-related medical conditions during pregnancy. However, no association was observed for the majority of prenatal and perinatal factors examined. The possibility of associations due to chance must be underscored because 46 factors were studied. The results should also be interpreted cautiously due to the limited statistical power for rare exposures, the exploratory nature of the maternal subcohort analysis, and potential exposure misclassification.


We thank Steve Buka and Janet Rich-Edwards for their help and guidance in reviewing the results and manuscript. We also thank Alvin Wing and Eilis O'Reilly for reviewing the statistical programs.


1. Kenealy SJ, Pericak-Vance MA, Haines JL. The genetic epidemiology of multiple sclerosis. J Neuroimmunol. 2003;143:7–12.
2. Ascherio A, Munger KL. Environmental risk factors for multiple sclerosis, part 1: the role of Infection. Ann Neurol. 2007;61:288–299.
3. Ebers GC, Sadovnick AD, Dyment DA, et al. Parent-of-origin effect in multiple sclerosis: observations in half–siblings. Lancet. 2004;363:1773–1774.
4. Sandman CA, Wadhwa PD, Chicz-DeMet A, Dunkel-Schetter C, Porto M. Maternal stress, HPA activity, and fetal/infant outcome. Ann N Y Acad Sci. 1997;814:266–275.
5. Rondo PH, Ferreira RF, Nogueira F, et al. Maternal psychological stress and distress as predictors of low birth weight, prematurity and intrauterine growth retardation. Eur J Clin Nutr. 2003;57:266–272.
6. Wadhwa PD, Sandman CA, Garite TJ. The neurobiology of stress in human pregnancy: implications for prematurity and development of the fetal central nervous system. Prog Brain Res. 2001;133:131–142.
7. Ruiz RJ, Avant KC. Effects of maternal prenatal stress on infant outcomes: a synthesis of the literature. Adv Nurs Sci. 2005;28:345–355.
8. Torrey EF, Miller J, Rawlings R, Yolken RH. Seasonal birth patterns of neurological disorders. Neuroepidemiology. 2000;19:177–185.
9. Willer CJ, Dyment DA, Sadovnick AD, et al. Timing of birth and risk of multiple sclerosis: population based study. Br Med J. 2005;63:1–5.
10. Montgomery SM, Lambe M, Olsson T, Ekbom A. Parental age, family size, and risk of multiple sclerosis. Epidemiology. 2004;15:717–723.
11. Mostafavi B, Akyuz S, Jacobsson ME, et al. Perinatal characteristics and risk of developing primary Sjögren's syndrome: a case–control study. J Rheumatol. 2005;32:665–668.
12. Jacobsson LT, Jacobsson ME, Askling J, Knowler WC. Perinatal characteristics and risk of rheumatoid arthritis. Br Med J. 2003;326:1068–1069.
13. Peng H, Hagopian W. Environmental factors in the development of type 1 diabetes. Rev Endocr Metab Disord. 2006;7:1491–62.
14. Bernsen RM, van der Wouden JC, Nagelkerke NJ, de Jonste JC. Early life circumstances and atopic disorders in childhood. Clin Exp Allergy. 2006;36:858–865.
15. Colditz GA, Manson JE, Hankinson SE. The Nurses' Health Study: 20–year contribute to the understanding of health among women. J Womens Health. 1997;6:49–62.
16. Chasen-Taber L, Willett WC, Manson JE, et al. Prospective study of oral contraceptives and hypertension among women in the United States. Circulation. 1996;94:483–489.
17. Michels KB, Willett WC, Graubard BI, et al. A longitudinal study of infant feeding and obesity throughout life course. In J Obes. 2007;31:1078–1085.
18. Hernan MA, Olek MJ, Ascherio A. Cigarette smoking and incidence of multiple sclerosis. Am J Epidemiol. 2001;154:69–74.
19. Munger KL, Zhang SM, O'Reilly E, et al. Vitamin D intake and incidence of multiple sclerosis. Neurology. 2004;62:60–65.
20. Gillberg C, Gillberg IC. Infantile autism: a total-population study of the reduced optimality in the pre-, peri-, and neonatal period. J Autism Dev Disord. 1983;13:152–166.
21. Harry GJ, Lawler C, Brunssen SH. Maternal infection and white matter toxicity. Neurotoxicology. 2006;27:658–670.
22. Sibai B, Dekker G, Kupferminc M. Pre-eclampsia. Lancet. 2005;365:785–799.
23. Schiessl B. Inflammatory response in preeclampsia. Mol Aspects Med. 2007;39:474–477.
24. Gleicher N. Why much of the pathophysiology of preeclampsia-eclampsia must be of an autoimmune nature. Am J Obstet Gynecol. 2007;196:5.e1–e5, e7.
25. Hernan MA, Olek MJ, Ascherio A. Geographic variation of MS incidence in two prospective studies of US women. Neurology. 1999;53:1711–1718.
26. Ponsonby AL, van der Mei I, Dwyer T, et al. Exposure to infant siblings during early life and risk of multiple sclerosis. J Am Med Assoc. 2005;293:463–469.
27. Kurtzke JF, Page WF. Epidemiology of multiple sclerosis in US veterans: VII. Risk factors for MS. Neurology. 1997;48:204–213.
28. Al-Delaimy WK, Mahoney GN, Speizer FE, et al. Toenail nicotine levels as a biomarker of tobacco smoke exposure. Cancer Epidemiol Biomarkers Prev. 2002;11:1400–1404.
29. Willett W, Sampson L, Browne ML, et al. The use of a self-administered questionnaire to assess diet four years in the past. Am J Epidemiol. 1988;127:188–199.
30. Salvini S, Hunter DJ, Sampson L, et al. Food-based validation of a dietary questionnaire: the effects of week–to-week variation in food consumption. Int J Epidemiol. 1989;18:858–867.
31. DerSimonian R, Laird N. Meta-analysis in clinical trials. Control Clin Trials. 1986;7:177–188.
32. Durrelman S, Simon R. Flexible regression models with cublic splines. Stat Med. 1989;8:551–561.
33. Troy LM, Michels KB, Hunter DJ, et al. Self-reported birthweight and history of having been breastfed among younger women: an assessment of validity. In J Epidemiol. 1996;25:122–126.
34. Tomeo CA, Rich-Edwards JW, Michels KB, et al. Reproducibility and validity of maternal recall of pregnancy-related events. Epidemiology. 1999;10:774–777.
35. Noller KL, Blair PB, O'Brien PC, et al. Increased occurrence of autoimmune disease among women exposed in utero to diethylstilbestrol. Fertil Steril. 1988;49:1080–1082.
36. Wingard DL, Turiel J. Long-term effects of exposure to diethylstilbestrol. West J Med. 1988;149:551–554.
37. Giusti RM, Iwamoto K, Hatch EE. Diethylstilbestrol revisited: a review of the long–term health effects. Ann Intern Med. 1995;122:778–788.
38. Burke L, Segall-Blank M, Lorenzo C, et al. Altered immune response in adult women exposed to diethylstilbestrol in utero. Am J Obstet Gynecol. 2001;185:78–81.
39. Holladay SD. Prenatal immunotoxicant exposure and postnatal autoimmune disease. Environ Health Perspect. 1999;107:687–691.
40. Deitl J. Maternal obesity and complications during pregnancy. J Perinat Med. 2005;33:100–105.
41. King JC. Maternal obesity, metabolism, and pregnancy outcomes. Annu Rev Nutr. 2006;26:271–291.
42. Ben-Haroush A, Yogev Y, Hod M. Epidemiology of gestational diabetes mellitus and its association with type 2 diabetes. Diabet Med. 2004;21:103–113.
43. Biri A, Onan A, Devrim E, et al. Oxidant status in maternal and cord plasma and placental tissue in gestational diabetes. Placenta. 2006;27:327–332.
44. Hypponen E, Power C. Hypovitaminosis D in British adults age 45 yr: nationwide cohort study of dietary and lifestyle predictors. Am J Clin Nutr. 2007;85:860–868.
45. Ascherio A, Munger KL. Environmental risk factors for multiple sclerosis, part II: noninfectious factors. Ann Neurol. 2007;61:504–513.
46. Bodnar LM, Catov JM, Simhan HN, et al. Maternal vitamin D deficiency increases risk of preeclampsia. J Clin Endocrinol Metab. 2007;92:3517–3522.

Supplemental Digital Content

© 2009 Lippincott Williams & Wilkins, Inc.