- Email: [email protected]
Weight at birth and subsequent risk of preeclampsia as an adult
Weight at birth and subsequent risk of preeclampsia as an adult Jennifer C. Dempsey, MPH,a Michelle A. Williams, ScD,a,b David A. Luthy, MD,a,c Irvin Emanuel, MD, MS,b and Kirk Shy, MD, MPHd,e Seattle and Tacoma, Wash OBJECTIVE: We examined the influence of maternal birth weight on the risk of the development of preeclampsia, a likely precursor to adult chronic disease. STUDY DESIGN: This hospital-based case-control study included 181 preeclampsia cases and 349 control subjects. Participants provided information about their birth weight and other covariates that included medical and reproductive history, prepregnancy weight, and adult height. Odds ratios and 95% CIs were estimated by logistic regression. RESULTS: The risk of preeclampsia decreased as maternal birth weight increased (P = .01). After an adjustment was made for confounders, data showed that women with a low birth weight (<2500 g) had a 2.3fold increased risk of experiencing preeclampsia (95% CI, 1.0-5.3) as compared with women who weighed 2500 to 2999 g at birth. Conversely, women with a birth weight of $4000 g appeared to have a nonstatistically significant, but >50%, reduction in the risk of experiencing preeclampsia (95% CI, 0.2-1.2). This relationship differed for lean and overweight women (body mass index, <25 kg/m2 vs $25 kg/m2). Among lean women, those who were low birth weight had a near doubling in risk of the development of preeclampsia (odds ratio, 1.9; 95% CI, 0.8-4.6), although this association did not reach statistical significance. However, among overweight women, those women who weighed <2500 g at birth had an almost 4-fold increased risk of experiencing preeclampsia (odds ratio, 3.8; 95% CI, 1.1-13.8). CONCLUSION: These results confirm two earlier reports and expand the literature by showing that women who are small at birth and who become overweight as adults are at particularly high risk of the development of preeclampsia. (Am J Obstet Gynecol 2003;189:494-500.)
Key words: Maternal birth weight, preeclampsia, pregnancy, adiposity
The notion that factors that are encountered in utero may determine the development of disease later in life recently has sparked the interest of many investigators.1,2 The first such evidence dates back to the 1968 Oxford study that found that mother’s birth weight was directly related to the relative intrauterine growth of her infant (birth weight percentile for the week of gestation).3 This was followed by studies in the United States that documented that mother’s birth weight was directly From the Center for Perinatal Studies, Swedish Medical Center,a the Department of Epidemiology, University of Washington School of Public Health and Community Medicine,b Obstetrix Medical Group,c the Department of Obstetrics and Gynecology, University of Washington,d and the Department of Obstetrics and Gynecology, Harborview Medical Center.e Supported in part by awards from the National Institutes of Health (HD/HL R01-34888) and from the Maternal and Child Health Bureau, Health Resources and Services Administration, Department of Health and Human Services (MCJ-530837). Received for publication October 10, 2002; revised February 25, 2003; accepted March 28, 2003. Reprint requests: Jennifer Dempsey, MPH, Center for Perinatal Studies, 444N, Swedish Medical Center, 747 Broadway, Seattle, WA, 98122. E-mail: [email protected] Ó 2003, Mosby, Inc. All rights reserved. 0002-9378/2003 $30.00 + 0 doi:10.1067/S0002-9378(03)00491-5
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associated with the risk of preterm birth and low infant birth weight4,5 and with gestational duration and relative intrauterine growth.4 Since then, there have been repeated demonstrations of the importance of maternal, fetal, and postnatal growth on later reproductive success6 and on chronic diseases of older men and women, which include such problems as hypertension, coronary heart disease, stroke, and type 2 diabetes mellitus.7-9 Recently, investigators have begun to explore possible associations between maternal birth weight and the subsequent risk of the development of medical complications of pregnancy, such as gestational diabetes mellitus and preeclampsia. Williams et al10 demonstrated that maternal birth weight was inversely related to the risk of gestational diabetes mellitus, which was an observation that has been confirmed by several,11,12 but not all,13 other researchers. Two groups have published studies that examined preeclampsia or pregnancy-induced hypertension, and both groups have found an increase in risk in women who were small at birth.14,15 However, neither group specifically investigated the role of adiposity later in life in this association. We used data from a case-control study to determine the extent to which, if at all, maternal birth weight is associated with a subsequent risk of
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preeclampsia. We also examined how the birth weight– preeclampsia association may differ for lean versus overweight women.
Material and methods Study design and population. This case-control study was conducted at Swedish Medical Center in Seattle, Wash, and Tacoma General Hospital in Tacoma, Wash, from April 1998 through February 2001. During this study period, we identified 233 women with preeclampsia. We used the then-current American College of Obstetricians and Gynecologists guidelines to create an operational clinical research definition for preeclampsia.16 These guidelines defined preeclampsia as sustained pregnancyinduced hypertension with proteinuria. Hypertension was defined as sustained blood pressure readings of $140/90 mm Hg (with readings taking place $6 hours apart) and/ or a sustained 15-mm Hg diastolic rise or a 30-mm Hg rise in systolic blood pressure above the first-trimester blood pressure values. The American College of Obstetricians and Gynecologists defined proteinuria as urine protein concentrations of $30 mg/dL (or 1+ on a urine dipstick) on $2 random specimens collected $4 hours apart.16 Nulliparity was not a criterion for diagnosis. Eighty-five percent of eligible preeclampsia cases were enrolled. Normotensive women who were delivered on the same day as a case were potential control subjects. Control subjects were women with pregnancies that were uncomplicated by pregnancy-induced hypertension or proteinuria. We selected 386 control subjects by identifying women with no history of pregnancy-induced hypertension or proteinuria during the index pregnancy. Recruitment among eligible control subjects was 50%. Reasons for nonparticipation included (1) not having time to participate in the interview, (2) having no interest in the goals of the study, and (3) missed appointments. Given the low participation rate among control subjects in our study, we assessed data from Washington State computerized birth certificate files to evaluate the extent to which enrolled subjects were materially different from all women who were delivered at the 2 study hospitals. From this exercise, we noted that enrolled control subjects were largely similar for characteristics such as maternal race/ethnicity, marital status, gravidity, and smoking during pregnancy, to members of the general population of women who were delivered at the two study hospitals. We did, however, note that enrolled control subjects tended to be slightly older and better educated than women from the larger population. After the exclusion of women with chronic hypertension (32 cases, 3 control subjects), women who were the product of a twin pregnancy (8 cases, 10 control subjects), and women with a missing birth weight (12 cases, 24 control subjects), 181 cases and 349 control subjects remained for analysis.
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Data collection. During a participant’s hospital stay, we administered a structured in-person interview questionnaire to collect information on maternal sociodemographic, medical, reproductive, and lifestyle characteristics. All interviews were performed in English. We reviewed maternal and infant medical records to collect detailed information concerning antepartum, labor and delivery characteristics, and conditions of the newborn infant. Gestational age was based on the date of the last menstrual period and was confirmed by ultrasound examination (performed before 20 weeks of gestation). We used body mass index (BMI; weight in kilograms divided by height in square meters) as a measure of adiposity. BMI was computed for each woman from measurements of her height and weight 3 months before the index pregnancy and at age 18 years. Statistical analyses. We examined frequency distributions of maternal sociodemographic characteristics and medical and reproductive histories according to casecontrol status. We also examined the distribution of continuous variables and found them to be approximately normal. When making comparisons between cases and control subjects for categoric variables, we used the v2 test or Fisher exact test, where appropriate. Maternal birth weight was categorized a priori into the following four groups: <2500 g, 2500 to 2999 g, 3000 to 3999 g, and $4000 g. Women with a birth weight of 2500 to 2999 g were selected a priori as the reference group. Prepregnancy BMI and BMI at age 18 years were categorized as follows: <20 kg/m2, 20 to 24.9 kg/m2, 25 to 29.9 kg/ m2, and $30 kg/m2. Several variables (eg, number of pregnancies and miscarriages) were dichotomized into 0 and $1 categories because of low frequency. Multivariate models were estimated with the use of logistic regression, with preeclampsia status as the dependent variable; odds ratios and 95% CIs were calculated. To assess confounding, covariates were entered into logistic regression models one at a time, and the adjusted and unadjusted odds ratios were compared. Final logistic regression models included covariates that altered unadjusted odds ratios by at least 10% and those covariates of a priori interest, such as maternal age and parity. Covariates that were considered included gravidity, years of education, physical activity during pregnancy, employment status, marital status, household income, race/ ethnicity, smoking during pregnancy, family history of hypertension and diabetes mellitus, maternal BMI, and characteristics of the participants’ mothers. Collinearity diagnostics were examined for the final models. A post hoc analysis was conducted to examine the relation between maternal birth weight and preeclampsia as defined by the criteria advocated by the National High Blood Pressure Education Program Working Group on High Blood Pressure in Pregnancy.17 After the exclusion of women with proteinuria and with elevations in blood
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pressure of $30 mm Hg systolic or $15 mm Hg diastolic above baseline and who did not meet a minimum threshold of $140 mm Hg systolic or $90 mm Hg diastolic after 20 weeks of gestation, 86 cases and 349 control subjects remained for the post hoc analysis. The procedures that were used in this study were in agreement with the protocols that had been approved by the Institutional Review Boards of Swedish Medical Center and Tacoma General Hospital, respectively. All participants provided written informed consent.
Results The sociodemographic, medical, and reproductive characteristics of cases and control subjects are presented in Table I. Cases tended to be younger, nulliparous, heavier, and more likely to have a family history of hypertension. Unadjusted and adjusted odds ratios of preeclampsia risk according to maternal birth weight category are shown in Table II. Those women who were in the lowest birth weight category had the greatest risk of preeclampsia; those women who had weighed the most at birth had the lowest risk. When compared with a birth weight of 2500 to 2999 g, the unadjusted odds ratios for birth weights of <2500 g, 3000 to 3999 g, and $4000 g were 2.05 (95% CI, 0.99-4.21), 0.77 (95% CI, 0.50-1.19), and 0.56 (95% CI, 0.25-1.25), respectively. After adjustment for maternal age, race/ethnicity, parity, education, hypertension in a first-degree relative, BMI at age 18 years, and prepregnancy BMI, the women in the highest birth weight category still experienced the lowest risk (odds ratio, 0.46; 95% CI, 0.17-1.21), although this association did not approach statistical significance. There was a negative trend in the risk of preeclampsia with increasing birth weight (probability for linear trend, .01). Maternal birth weight was also examined as a continuous variable. After adjusting for confounders, we noted that a 100-g increase in maternal birth weight was associated with an 8% reduction in the risk of preeclampsia (odds ratio, 0.92; 95% CI, 0.88-0.96). We next evaluated the extent to which maternal prepregnancy adiposity had an impact on the association between maternal birth weight and preeclampsia risk. First, we assessed the association separately in lean (BMI, <25 kg/m2) and overweight (BMI, $25 kg/m2) women. In the former group, those women who weighed <2500 g at birth had an almost 2-fold increase in the risk of preeclampsia when compared with those women who weighed $2500 g at birth (odds ratio, 1.90; 95% CI, 0.784.60), although this association did not reach statistical significance. Overweight women who were born small had 3.8 times the risk of those women who weighed $2500 g at birth (95% CI, 1.05-13.75). We then assessed the independent and joint contributions of maternal birth
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weight and prepregnancy BMI to the risk of preeclampsia. For these analyses, we created a series of indicator variables for the 4 combinations of maternal birth weight (<2500 g: yes/no) and prepregnancy overweight status (BMI, $25 kg/m2: yes/no) (Table III). Women who weighed $2500 g at birth and who were lean (BMI, <25 kg/m2) before the index pregnancy served as the reference group. Compared with this reference group, low-birth-weight women who remained lean had an elevated risk for the development of preeclampsia (odds ratio, 2.0; 95% CI, 0.78-5.36), although this observation was based on a small number of cases and control subjects and did not reach statistical significance. However, lowbirth-weight women who subsequently became overweight had an almost 24-fold increase in risk for the development of this disease (odds ratio, 23.9; 95% CI, 5.91-96.27), but again the confidence interval was wide, and the number of cases and control subjects was small. Women with a birth weight of $2500 g who later became overweight were also at an increased risk compared with the reference group (odds ratio, 5.9; 95% CI, 3.44-10.03). These data suggest that the joint effect of maternal low birth weight and subsequent increased adiposity is more than additive. Inferences regarding the relation between maternal birth weight and preeclampsia were largely similar in direction and magnitude when analyses were restricted to those preeclampsia cases that met the new diagnostic criteria17 (Table IV). Compared with women who weighed 2500 to 2999 g at birth, those women who weighed <2500 g had a 3.2-fold increased risk of preeclampsia (95% CI, 1.12-9.31), after adjustment for confounders. When we reexamined the independent and joint contributions of maternal birth weight and prepregnancy BMI to the risk of preeclampsia, the data again suggested that the joint effect was more than additive (data not shown).
Comment Women who reported a birth weight of <2500 g were found to be at an increased risk of the development of preeclampsia in this case-control study. After an adjustment for confounders was made, women who were in this lowest birth weight group had a 2.3-fold increased risk compared with women who weighed between 2500 and 2999 g at birth. Women who weighed 3000 to 3999 g or $4000 g at birth had a 44% and 54% reduced risk of preeclampsia, respectively, although these associations were not statistically significant. The increased risk of preeclampsia that is associated with maternal low birth weight appears to be restricted to those women who became overweight as adults. The relative risk for women of low birth weight who remained lean was 1.1. However, women who were born small who became overweight had a 16-fold increase in risk.
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Table I. Distribution of preeclampsia cases and control subjects by selected demographic characteristics (Seattle and Tacoma, Wash, 1998-2001)
Characteristic Maternal birth weight (g) <2500 2500-2999 3000-3999 $4000 Primiparous Primigravid $1 miscarriage $1 abortion Maternal age (y) #19 20-34 $35 Ethnicity White, non-Hispanic African American Other Missing data <12 y of education Employed during pregnancy Unmarried Household income ($) #29,999 30,000-69,999 $70,000 Missing data Prepregnancy BMI (kg/m2) <20 20-24.9 25-29.9 $30 Missing data BMI at age 18 y (kg/m2) <20 20-24.9 25-29.9 $30 Missing data History of hypertension in first-degree relative Smoked at beginning of pregnancy Participant’s mother smoked during pregnancy with participant
Preeclampsia cases (n = 181)
Control subjects (n = 349)
No.
%
No.
%
22 46 103 10 86 135 35 41
12.15 25.41 56.91 5.52 47.51 74.59 19.34 22.65
18 77 224 30 129 188 73 73
5.16 22.06 64.18 8.60 36.96 53.87 20.92 20.92
7 134 40
3.87 74.03 22.10
22 223 104
6.30 63.90 29.80
126 19 36 0 13 155 56
69.61 10.50 19.89 — 7.18 85.64 30.94
252 26 70 1 24 300 79
72.21 7.45 20.06 0.28 6.88 85.96 22.64
45 71 56 9
24.86 39.23 30.94 4.97
65 110 158 16
18.62 31.52 45.27 4.58
10 71 46 54 0
5.52 39.23 25.41 29.83 —
80 195 47 26 1
22.92 55.87 13.47 7.45 0.29
67 74 24 12 4 104 31 35
37.02 40.88 13.26 6.63 2.21 57.46 17.13 19.34
144 165 23 6 11 157 45 89
41.26 47.28 6.59 1.72 3.15 44.99 12.89 25.50
Several important limitations must be considered in the interpretation of the results from our study. First, we cannot exclude the possibility of selection bias. In this study, the control participation rate was 50%, and the case participation rate was 85%. Although demographic and reproductive characteristics were largely similar for enrolled control subjects and members of the source population from which they were drawn, we cannot exclude the possibility that the observed associations are biased. However, our observation of an association between maternal low birth weight and preeclampsia is consistent with the two other published studies14,15 and suggests the face validity of our data. Second, maternal birth weight was self-reported and thus subject to potential recall bias. However, errors in the reporting of
birth weight would be expected to be random, and this possible misclassification would tend to underestimate the association between birth weight and preeclampsia risk. Third, we did not know the gestational age of these women at birth, so we were unable to separate the effects of low birth weight due to being preterm and those produced by intrauterine growth restriction. Exclusion of women with essential hypertension and women who were born a twin and the adjustment for confounders (such as maternal age, parity, race/ethnicity, family history of hypertension, and body mass index) reduced the likelihood of confounding. Fourth, small numbers limit the inferences we can make from our analyses, particularly those analyses designed to assess the possible interaction between low birth weight and subsequent adiposity.
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Table II. Risk of preeclampsia according to maternal birth weight categories (Seattle and Tacoma, Wash, 1998-2001) Preeclampsia cases (n = 181)
Control subjects (n = 349)
Maternal birth weight (g)
No.
%
No.
%
<2500 2500-2999 3000-3999 $4000
22 46 103 10
11.40 23.83 53.37 5.18
18 77 224 30
4.83 20.64 60.05 8.04
Odds ratio (95% CI)* 2.05 1.0 0.77 0.56
(0.99–4.21) (reference) (0.50–1.19) (0.25–1.25)
Odds ratio (95% CI)y 2.27 (0.97–5.32) 1.0 (reference) 0.56 (0.34–0.94) 0.46 (0.17–1.21)
*Unadjusted, probability value for trend = .01. for age, race/ethnicity, parity, hypertension in first-degree relative, education, BMI at age 18 years, and prepregnancy BMI.
yAdjusted
Table III. Risk of preeclampsia according to maternal birth weight and prepregnancy BMI (Seattle and Tacoma, Wash, 1998-2001) Preeclampsia cases (n = 181)
Control subjects (n = 348)*
Maternal birth weight/ prepregnancy BMI
No.
%
No.
%
<2500 g, $25 kg/m2 <2500 g, <25 kg/m2 $2500 g, $25 kg/m2 $2500 g, <25 kg/m2
14 8 86 73
7.73 4.42 47.51 40.33
3 15 70 260
0.86 4.31 20.11 74.71
Odds ratio (95% CI)y 16.69 1.91 4.39 1.0
(4.67-59.63) (0.78-4.67) (2.92-6.61) (Reference)
Odds ratio (95% CI)à 23.85 2.04 5.88 1.0
(5.91-96.27) (0.78-5.36) (3.44-10.03) (Reference)
*One control is missing from this analysis. yUnadjusted. àAdjusted for age, race/ethnicity, parity, hypertension in first-degree relative, education, and BMI at age 18 years.
We are aware of only two published reports that specifically examined the association between maternal birth characteristics and the subsequent risk of preeclampsia or pregnancy-induced hypertension, and our results confirm the relationships seen previously. Klebanoff et al15 examined, through a birth registry, 1261 Danish women who had 2008 singleton pregnancies between 1974 and 1989. They found that women who were small for gestational age at birth were 70% more likely to have hypertension during pregnancy than those women who were appropriate for gestational age (95% CI, 1.1-2.6). Women who were born preterm were also more likely to have this condition than women who were born at term, although this result was not statistically significant (odds ratio, 1.3; 95% CI, 0.8-2.0). Innes et al14 conducted a case-control study using linked birth registry data in Colorado and found a strong inverse relationship between a woman’s gestational age as a newborn infant and her subsequent risk of preeclampsia. Women who were born at 34 to 37 weeks of gestation had a slight increase in risk (odds ratio, 1.38; 95% CI, 0.85-2.45), but those women who were born at <34 weeks had three times the risk when compared with those women who were born at term (odds ratio, 3.33; 95% CI, 1.25-7.49). In addition, women who were born weighing <4.5 pounds were at the greatest risk of preeclampsia compared with those women who weighed $8.5 pounds (odds ratio, 5.16; 95% CI, 1.24-21.51).
The literature is rife with studies that have examined the association between birth weight and/or length and adult blood pressure in men and nonpregnant women. For example, Huxley et al18 reviewed 80 studies that described the relationship between adult blood pressure and birth weight and found that most demonstrated an inverse relationship. However, other authors have shown no such association.19 In the Nurses Health Study parts I and II, Curhan et al8 showed increases of 39% and 43%, respectively, in risk of adult hypertension when comparing women who had weighed <5 pounds at birth to those who had weighed between 7 and 8.5 pounds. In a prospective study of 438 Swedish women, weight and length at birth were significant predictors of hypertension at age 60 years.20 A cross-sectional study of 297 British women revealed that low birth weight was associated with increased systolic blood pressure at age 60 to 71 years. Notably, lower birth weights were also correlated with cardiovascular disease risk factors that include higher plasma concentrations of glucose and insulin, higher serum triglyceride concentrations, lower serum highdensity lipoprotein cholesterol concentrations, and higher waist/hip ratios.9 Adult BMI has been shown to modify these associations, as women who were small at birth and currently obese had the least favorable risk factor profiles.9,21 This profile is characteristic of insulin resistance syndrome, a metabolic disorder that usually appears later in life but may also be unmasked during
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Table IV. Risk of preeclampsia according to maternal birth weight categories (post hoc analysis; Seattle and Tacoma, Wash, 1998-2001) Preeclampsia cases (n = 86)
Control subjects (n = 349)
Maternal birth weight (g)
No.
%
No.
%
<2500 2500-2999 3000-3999 $4000
13 24 44 5
15.12 27.91 51.16 5.81
18 77 224 30
5.16 22.06 64.18 8.60
Odds ratio (95% CI)* 2.32 1.0 0.63 0.54
(0.99-5.41) (Reference) (0.36-1.10) (0.19-1.53)
Odds ratio (95% CI)y 3.23 1.0 0.47 0.42
(1.12-9.31) (Reference) (0.24-0.92) (0.11-1.57)
*Unadjusted. yAdjusted for age, race/ethnicity, parity, hypertension in first-degree relative, education, BMI at age 18 years, and prepregnancy BMI.
pregnancy in the form of preeclampsia.22 Exploration of the relationship between birth weight and preeclampsia may help to elucidate the pathophysiology and identify subpopulations of women who are at particularly high risk of the development of chronic hypertension, insulin resistance syndrome, and related disorders including non-insulin-dependent diabetes mellitus. The causal pathways that are involved in the relationship between birth characteristics and future risk of preeclampsia or chronic hypertension have yet to be elucidated. However, there are compelling and biologically plausible hypothesized mechanisms that merit discussion. One such mechanism involves the kidney, which undergoes critical development in late gestation and can be compromised as the result of restricted fetal growth.23 Individuals with such a prenatal history are thought to have an excessive hemodynamic burden, which makes them more likely to experience hypertension when exposed to fluctuations in body mass index and other stresses,24 of which pregnancy may qualify. A second possible mechanism involves insulin resistance. Individuals with a history of inadequate fetal growth are hypothesized to be at an increased risk of having insulin resistance and associated complications in adulthood. Investigators have postulated that growth-restricted infants may have a reduced number of pancreatic b cells and a subsequent diminished capacity to produce insulin.1 In addition, those women who become obese later in life are likely to be at particularly high risk of having insulin resistance.25,26 The association between birth characteristics and preeclampsia needs further validation, especially in large, prospective studies. However, our results support the hypothesis that low birth weight is predictive of preeclampsia risk later in life. Continued investigation into the biologic mechanisms that are likely to underlie these observed associations is necessary to establish the public health significance and clinical implications of these findings. We thank the participants of the Alpha Study for their cooperation and Malou Andresen, Penny Anders-
Bartolo, Ihunnaya Frederick, Raymond Miller, Trudi Witt, and Kathy Ramsey for their technical expertise. REFERENCES 1. Godfrey KM, Barker DJP. Fetal nutrition and adult disease. Am J Clin Nutr 2000;71:1344-1352S. 2. Byrne CD, Phillips DI. Fetal origins of adult disease: epidemiology and mechanisms. J Clin Pathol 2000;53:822-8. 3. Ounsted M, Ounsted C. Rate of intra-uterine growth. Nature 1968; 220:599-660. 4. Hackman E, Emanuel I, van Belle G, Daling J. Maternal birth weight and subsequent pregnancy outcome. JAMA 1983;250:2016-9. 5. Klebanoff MA, Graubard BI, Kessel SS, Berendes HW. Low birth weight across generations. JAMA 1984;252:2423-7. 6. Emanuel I, Leisenring W, Williams MA, Kimpo C, Estee S, O’Brien W, et al. The Washington State Intergenerational Study of Birth Outcomes: methodology and some comparisons of maternal birthweight and infant birth weight and gestation in four ethnic groups. Paediatr Perinat Epidemiol 1999;13:352-71. 7. Barker DJP, Sultan HY. Fetal programming of human disease. In: Hanson MA, Spencer JA, Rodeck CH, editors. Fetus and neonate: physiology and clinical applications. Cambridge (UK): Cambridge University Press; 1995. p. 255-74. 8. Curhan GC, Chertow GM, Willett WC, Spiegelman D, Colditz GA, Manson JE, et al. Birth weight and adult hypertension and obesity in women. Circulation 1996;94:1310-5. 9. Fall CHD, Osmond C, Barker DJP, Clark PMS, Hales CN, Stirling Y, et al. Fetal and infant growth and cardiovascular risk factors in women. BMJ 1995;310:428-32. 10. Williams MA, Emanuel I, Kimpo C, Leisenring WM, Hale CB. A population-based cohort study of the relation between maternal birth weight and risk of gestational diabetes mellitus in four race/ ethnic groups. Paediatr Perinat Epidemiol 1999;13:452-65. 11. Innes KE, Byers TE, Marshall JA, Baron A, Orleans M, Hamman RF. Association of a woman’s own birth weight with subsequent risk for gestational diabetes. JAMA 2002;287:2534-41. 12. Egeland GM, Skjaerven R, Irgens LM. Birth characteristics of women who develop gestational diabetes: population based study. BMJ 2000;321:546-7. 13. Moses RG, Moses J, Knights S. Birth weight of women with gestational diabetes. Diabetes Care 1999;22:1059-62. 14. Innes KE, Marshall JA, Byers TE, Calonge N. A woman’s own birth weight and gestational age predict her later risk of developing preeclampsia, a precursor of chronic disease. Epidemiology 1999; 10:153-60. 15. Klebanoff MA, Secher NJ, Mednick BR, Schulsinger C. Maternal size at birth and the development of hypertension during pregnancy: a test of the Barker hypothesis. Arch Intern Med 1999;159:1607-12. 16. American College of Obstetricians and Gynecologists. Hypertension in pregnancy. Washington (DC): The College; 1996. Technical Bulletin No.: 219. p. 1-8. 17. National High Blood Pressure Education Program Working Group on High Blood Pressure in Pregnancy. Report of the national high blood pressure education program working group on high blood pressure in pregnancy. Am J Obstet Gynecol 2000;183:S1-22.
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18. Huxley RR, Shiell AW, Law CM. The role of size at birth and postnatal catch-up growth in determining systolic blood pressure: a systematic review of the literature. J Hypertens 2000;18:815-31. 19. Falkner B, Hulman S, Kushner H. Birth weight versus childhood growth as determinants of adult blood pressure. Hypertension 1998;31:145-50. 20. Andersson SW, Lapidus L, Niklasson A, Hallberg L, Bengtsson C, Hulthen L. Blood pressure and hypertension in middle-aged women in relation to weight and length at birth: a follow-up study. J Hypertens 2000;18:1753-61. 21. Law CM, de Swiet M, Osmond C, Fayers PM, Barker DJP, Cruddas AM, Fall CHD. Initiation of hypertension in utero and its amplification throughout life. BMJ 1993;306:24-7.
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22. Kaaja R, Tikkanen MJ, Viinikka L, Ylikorkala O. Serum lipoproteins, insulin, and urinary prostanoid metabolites in normal and hypertensive pregnant women. Obstet Gynecol 1995;85:353-6. 23. Marchand MC, Langley-Evans SC. Intrauterine programming of nephron number: the fetal flaw revisited. J Nephrol 2001;14: 327-31. 24. Mackenzie HS, Brenner BM. Fewer nephrons at birth: a missing link in the etiology of essential hypertension? Am J Kidney Dis 1995; 26:91-8. 25. Phillips DIW, Hirst S, Clark PMS, Hales CN, Osmond C. Fetal growth and insulin secretion in adult life. Diabetologia 1994;37:592-6. 26. Phillips DIW. Insulin resistance as a programmed response to fetal undernutrition. Diabetologia 1996;39:1119-22.
Key words: Maternal birth weight, preeclampsia, pregnancy, adiposity
The notion that factors that are encountered in utero may determine the development of disease later in life recently has sparked the interest of many investigators.1,2 The first such evidence dates back to the 1968 Oxford study that found that mother’s birth weight was directly related to the relative intrauterine growth of her infant (birth weight percentile for the week of gestation).3 This was followed by studies in the United States that documented that mother’s birth weight was directly From the Center for Perinatal Studies, Swedish Medical Center,a the Department of Epidemiology, University of Washington School of Public Health and Community Medicine,b Obstetrix Medical Group,c the Department of Obstetrics and Gynecology, University of Washington,d and the Department of Obstetrics and Gynecology, Harborview Medical Center.e Supported in part by awards from the National Institutes of Health (HD/HL R01-34888) and from the Maternal and Child Health Bureau, Health Resources and Services Administration, Department of Health and Human Services (MCJ-530837). Received for publication October 10, 2002; revised February 25, 2003; accepted March 28, 2003. Reprint requests: Jennifer Dempsey, MPH, Center for Perinatal Studies, 444N, Swedish Medical Center, 747 Broadway, Seattle, WA, 98122. E-mail: [email protected] Ó 2003, Mosby, Inc. All rights reserved. 0002-9378/2003 $30.00 + 0 doi:10.1067/S0002-9378(03)00491-5
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associated with the risk of preterm birth and low infant birth weight4,5 and with gestational duration and relative intrauterine growth.4 Since then, there have been repeated demonstrations of the importance of maternal, fetal, and postnatal growth on later reproductive success6 and on chronic diseases of older men and women, which include such problems as hypertension, coronary heart disease, stroke, and type 2 diabetes mellitus.7-9 Recently, investigators have begun to explore possible associations between maternal birth weight and the subsequent risk of the development of medical complications of pregnancy, such as gestational diabetes mellitus and preeclampsia. Williams et al10 demonstrated that maternal birth weight was inversely related to the risk of gestational diabetes mellitus, which was an observation that has been confirmed by several,11,12 but not all,13 other researchers. Two groups have published studies that examined preeclampsia or pregnancy-induced hypertension, and both groups have found an increase in risk in women who were small at birth.14,15 However, neither group specifically investigated the role of adiposity later in life in this association. We used data from a case-control study to determine the extent to which, if at all, maternal birth weight is associated with a subsequent risk of
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preeclampsia. We also examined how the birth weight– preeclampsia association may differ for lean versus overweight women.
Material and methods Study design and population. This case-control study was conducted at Swedish Medical Center in Seattle, Wash, and Tacoma General Hospital in Tacoma, Wash, from April 1998 through February 2001. During this study period, we identified 233 women with preeclampsia. We used the then-current American College of Obstetricians and Gynecologists guidelines to create an operational clinical research definition for preeclampsia.16 These guidelines defined preeclampsia as sustained pregnancyinduced hypertension with proteinuria. Hypertension was defined as sustained blood pressure readings of $140/90 mm Hg (with readings taking place $6 hours apart) and/ or a sustained 15-mm Hg diastolic rise or a 30-mm Hg rise in systolic blood pressure above the first-trimester blood pressure values. The American College of Obstetricians and Gynecologists defined proteinuria as urine protein concentrations of $30 mg/dL (or 1+ on a urine dipstick) on $2 random specimens collected $4 hours apart.16 Nulliparity was not a criterion for diagnosis. Eighty-five percent of eligible preeclampsia cases were enrolled. Normotensive women who were delivered on the same day as a case were potential control subjects. Control subjects were women with pregnancies that were uncomplicated by pregnancy-induced hypertension or proteinuria. We selected 386 control subjects by identifying women with no history of pregnancy-induced hypertension or proteinuria during the index pregnancy. Recruitment among eligible control subjects was 50%. Reasons for nonparticipation included (1) not having time to participate in the interview, (2) having no interest in the goals of the study, and (3) missed appointments. Given the low participation rate among control subjects in our study, we assessed data from Washington State computerized birth certificate files to evaluate the extent to which enrolled subjects were materially different from all women who were delivered at the 2 study hospitals. From this exercise, we noted that enrolled control subjects were largely similar for characteristics such as maternal race/ethnicity, marital status, gravidity, and smoking during pregnancy, to members of the general population of women who were delivered at the two study hospitals. We did, however, note that enrolled control subjects tended to be slightly older and better educated than women from the larger population. After the exclusion of women with chronic hypertension (32 cases, 3 control subjects), women who were the product of a twin pregnancy (8 cases, 10 control subjects), and women with a missing birth weight (12 cases, 24 control subjects), 181 cases and 349 control subjects remained for analysis.
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Data collection. During a participant’s hospital stay, we administered a structured in-person interview questionnaire to collect information on maternal sociodemographic, medical, reproductive, and lifestyle characteristics. All interviews were performed in English. We reviewed maternal and infant medical records to collect detailed information concerning antepartum, labor and delivery characteristics, and conditions of the newborn infant. Gestational age was based on the date of the last menstrual period and was confirmed by ultrasound examination (performed before 20 weeks of gestation). We used body mass index (BMI; weight in kilograms divided by height in square meters) as a measure of adiposity. BMI was computed for each woman from measurements of her height and weight 3 months before the index pregnancy and at age 18 years. Statistical analyses. We examined frequency distributions of maternal sociodemographic characteristics and medical and reproductive histories according to casecontrol status. We also examined the distribution of continuous variables and found them to be approximately normal. When making comparisons between cases and control subjects for categoric variables, we used the v2 test or Fisher exact test, where appropriate. Maternal birth weight was categorized a priori into the following four groups: <2500 g, 2500 to 2999 g, 3000 to 3999 g, and $4000 g. Women with a birth weight of 2500 to 2999 g were selected a priori as the reference group. Prepregnancy BMI and BMI at age 18 years were categorized as follows: <20 kg/m2, 20 to 24.9 kg/m2, 25 to 29.9 kg/ m2, and $30 kg/m2. Several variables (eg, number of pregnancies and miscarriages) were dichotomized into 0 and $1 categories because of low frequency. Multivariate models were estimated with the use of logistic regression, with preeclampsia status as the dependent variable; odds ratios and 95% CIs were calculated. To assess confounding, covariates were entered into logistic regression models one at a time, and the adjusted and unadjusted odds ratios were compared. Final logistic regression models included covariates that altered unadjusted odds ratios by at least 10% and those covariates of a priori interest, such as maternal age and parity. Covariates that were considered included gravidity, years of education, physical activity during pregnancy, employment status, marital status, household income, race/ ethnicity, smoking during pregnancy, family history of hypertension and diabetes mellitus, maternal BMI, and characteristics of the participants’ mothers. Collinearity diagnostics were examined for the final models. A post hoc analysis was conducted to examine the relation between maternal birth weight and preeclampsia as defined by the criteria advocated by the National High Blood Pressure Education Program Working Group on High Blood Pressure in Pregnancy.17 After the exclusion of women with proteinuria and with elevations in blood
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pressure of $30 mm Hg systolic or $15 mm Hg diastolic above baseline and who did not meet a minimum threshold of $140 mm Hg systolic or $90 mm Hg diastolic after 20 weeks of gestation, 86 cases and 349 control subjects remained for the post hoc analysis. The procedures that were used in this study were in agreement with the protocols that had been approved by the Institutional Review Boards of Swedish Medical Center and Tacoma General Hospital, respectively. All participants provided written informed consent.
Results The sociodemographic, medical, and reproductive characteristics of cases and control subjects are presented in Table I. Cases tended to be younger, nulliparous, heavier, and more likely to have a family history of hypertension. Unadjusted and adjusted odds ratios of preeclampsia risk according to maternal birth weight category are shown in Table II. Those women who were in the lowest birth weight category had the greatest risk of preeclampsia; those women who had weighed the most at birth had the lowest risk. When compared with a birth weight of 2500 to 2999 g, the unadjusted odds ratios for birth weights of <2500 g, 3000 to 3999 g, and $4000 g were 2.05 (95% CI, 0.99-4.21), 0.77 (95% CI, 0.50-1.19), and 0.56 (95% CI, 0.25-1.25), respectively. After adjustment for maternal age, race/ethnicity, parity, education, hypertension in a first-degree relative, BMI at age 18 years, and prepregnancy BMI, the women in the highest birth weight category still experienced the lowest risk (odds ratio, 0.46; 95% CI, 0.17-1.21), although this association did not approach statistical significance. There was a negative trend in the risk of preeclampsia with increasing birth weight (probability for linear trend, .01). Maternal birth weight was also examined as a continuous variable. After adjusting for confounders, we noted that a 100-g increase in maternal birth weight was associated with an 8% reduction in the risk of preeclampsia (odds ratio, 0.92; 95% CI, 0.88-0.96). We next evaluated the extent to which maternal prepregnancy adiposity had an impact on the association between maternal birth weight and preeclampsia risk. First, we assessed the association separately in lean (BMI, <25 kg/m2) and overweight (BMI, $25 kg/m2) women. In the former group, those women who weighed <2500 g at birth had an almost 2-fold increase in the risk of preeclampsia when compared with those women who weighed $2500 g at birth (odds ratio, 1.90; 95% CI, 0.784.60), although this association did not reach statistical significance. Overweight women who were born small had 3.8 times the risk of those women who weighed $2500 g at birth (95% CI, 1.05-13.75). We then assessed the independent and joint contributions of maternal birth
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weight and prepregnancy BMI to the risk of preeclampsia. For these analyses, we created a series of indicator variables for the 4 combinations of maternal birth weight (<2500 g: yes/no) and prepregnancy overweight status (BMI, $25 kg/m2: yes/no) (Table III). Women who weighed $2500 g at birth and who were lean (BMI, <25 kg/m2) before the index pregnancy served as the reference group. Compared with this reference group, low-birth-weight women who remained lean had an elevated risk for the development of preeclampsia (odds ratio, 2.0; 95% CI, 0.78-5.36), although this observation was based on a small number of cases and control subjects and did not reach statistical significance. However, lowbirth-weight women who subsequently became overweight had an almost 24-fold increase in risk for the development of this disease (odds ratio, 23.9; 95% CI, 5.91-96.27), but again the confidence interval was wide, and the number of cases and control subjects was small. Women with a birth weight of $2500 g who later became overweight were also at an increased risk compared with the reference group (odds ratio, 5.9; 95% CI, 3.44-10.03). These data suggest that the joint effect of maternal low birth weight and subsequent increased adiposity is more than additive. Inferences regarding the relation between maternal birth weight and preeclampsia were largely similar in direction and magnitude when analyses were restricted to those preeclampsia cases that met the new diagnostic criteria17 (Table IV). Compared with women who weighed 2500 to 2999 g at birth, those women who weighed <2500 g had a 3.2-fold increased risk of preeclampsia (95% CI, 1.12-9.31), after adjustment for confounders. When we reexamined the independent and joint contributions of maternal birth weight and prepregnancy BMI to the risk of preeclampsia, the data again suggested that the joint effect was more than additive (data not shown).
Comment Women who reported a birth weight of <2500 g were found to be at an increased risk of the development of preeclampsia in this case-control study. After an adjustment for confounders was made, women who were in this lowest birth weight group had a 2.3-fold increased risk compared with women who weighed between 2500 and 2999 g at birth. Women who weighed 3000 to 3999 g or $4000 g at birth had a 44% and 54% reduced risk of preeclampsia, respectively, although these associations were not statistically significant. The increased risk of preeclampsia that is associated with maternal low birth weight appears to be restricted to those women who became overweight as adults. The relative risk for women of low birth weight who remained lean was 1.1. However, women who were born small who became overweight had a 16-fold increase in risk.
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Table I. Distribution of preeclampsia cases and control subjects by selected demographic characteristics (Seattle and Tacoma, Wash, 1998-2001)
Characteristic Maternal birth weight (g) <2500 2500-2999 3000-3999 $4000 Primiparous Primigravid $1 miscarriage $1 abortion Maternal age (y) #19 20-34 $35 Ethnicity White, non-Hispanic African American Other Missing data <12 y of education Employed during pregnancy Unmarried Household income ($) #29,999 30,000-69,999 $70,000 Missing data Prepregnancy BMI (kg/m2) <20 20-24.9 25-29.9 $30 Missing data BMI at age 18 y (kg/m2) <20 20-24.9 25-29.9 $30 Missing data History of hypertension in first-degree relative Smoked at beginning of pregnancy Participant’s mother smoked during pregnancy with participant
Preeclampsia cases (n = 181)
Control subjects (n = 349)
No.
%
No.
%
22 46 103 10 86 135 35 41
12.15 25.41 56.91 5.52 47.51 74.59 19.34 22.65
18 77 224 30 129 188 73 73
5.16 22.06 64.18 8.60 36.96 53.87 20.92 20.92
7 134 40
3.87 74.03 22.10
22 223 104
6.30 63.90 29.80
126 19 36 0 13 155 56
69.61 10.50 19.89 — 7.18 85.64 30.94
252 26 70 1 24 300 79
72.21 7.45 20.06 0.28 6.88 85.96 22.64
45 71 56 9
24.86 39.23 30.94 4.97
65 110 158 16
18.62 31.52 45.27 4.58
10 71 46 54 0
5.52 39.23 25.41 29.83 —
80 195 47 26 1
22.92 55.87 13.47 7.45 0.29
67 74 24 12 4 104 31 35
37.02 40.88 13.26 6.63 2.21 57.46 17.13 19.34
144 165 23 6 11 157 45 89
41.26 47.28 6.59 1.72 3.15 44.99 12.89 25.50
Several important limitations must be considered in the interpretation of the results from our study. First, we cannot exclude the possibility of selection bias. In this study, the control participation rate was 50%, and the case participation rate was 85%. Although demographic and reproductive characteristics were largely similar for enrolled control subjects and members of the source population from which they were drawn, we cannot exclude the possibility that the observed associations are biased. However, our observation of an association between maternal low birth weight and preeclampsia is consistent with the two other published studies14,15 and suggests the face validity of our data. Second, maternal birth weight was self-reported and thus subject to potential recall bias. However, errors in the reporting of
birth weight would be expected to be random, and this possible misclassification would tend to underestimate the association between birth weight and preeclampsia risk. Third, we did not know the gestational age of these women at birth, so we were unable to separate the effects of low birth weight due to being preterm and those produced by intrauterine growth restriction. Exclusion of women with essential hypertension and women who were born a twin and the adjustment for confounders (such as maternal age, parity, race/ethnicity, family history of hypertension, and body mass index) reduced the likelihood of confounding. Fourth, small numbers limit the inferences we can make from our analyses, particularly those analyses designed to assess the possible interaction between low birth weight and subsequent adiposity.
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Table II. Risk of preeclampsia according to maternal birth weight categories (Seattle and Tacoma, Wash, 1998-2001) Preeclampsia cases (n = 181)
Control subjects (n = 349)
Maternal birth weight (g)
No.
%
No.
%
<2500 2500-2999 3000-3999 $4000
22 46 103 10
11.40 23.83 53.37 5.18
18 77 224 30
4.83 20.64 60.05 8.04
Odds ratio (95% CI)* 2.05 1.0 0.77 0.56
(0.99–4.21) (reference) (0.50–1.19) (0.25–1.25)
Odds ratio (95% CI)y 2.27 (0.97–5.32) 1.0 (reference) 0.56 (0.34–0.94) 0.46 (0.17–1.21)
*Unadjusted, probability value for trend = .01. for age, race/ethnicity, parity, hypertension in first-degree relative, education, BMI at age 18 years, and prepregnancy BMI.
yAdjusted
Table III. Risk of preeclampsia according to maternal birth weight and prepregnancy BMI (Seattle and Tacoma, Wash, 1998-2001) Preeclampsia cases (n = 181)
Control subjects (n = 348)*
Maternal birth weight/ prepregnancy BMI
No.
%
No.
%
<2500 g, $25 kg/m2 <2500 g, <25 kg/m2 $2500 g, $25 kg/m2 $2500 g, <25 kg/m2
14 8 86 73
7.73 4.42 47.51 40.33
3 15 70 260
0.86 4.31 20.11 74.71
Odds ratio (95% CI)y 16.69 1.91 4.39 1.0
(4.67-59.63) (0.78-4.67) (2.92-6.61) (Reference)
Odds ratio (95% CI)à 23.85 2.04 5.88 1.0
(5.91-96.27) (0.78-5.36) (3.44-10.03) (Reference)
*One control is missing from this analysis. yUnadjusted. àAdjusted for age, race/ethnicity, parity, hypertension in first-degree relative, education, and BMI at age 18 years.
We are aware of only two published reports that specifically examined the association between maternal birth characteristics and the subsequent risk of preeclampsia or pregnancy-induced hypertension, and our results confirm the relationships seen previously. Klebanoff et al15 examined, through a birth registry, 1261 Danish women who had 2008 singleton pregnancies between 1974 and 1989. They found that women who were small for gestational age at birth were 70% more likely to have hypertension during pregnancy than those women who were appropriate for gestational age (95% CI, 1.1-2.6). Women who were born preterm were also more likely to have this condition than women who were born at term, although this result was not statistically significant (odds ratio, 1.3; 95% CI, 0.8-2.0). Innes et al14 conducted a case-control study using linked birth registry data in Colorado and found a strong inverse relationship between a woman’s gestational age as a newborn infant and her subsequent risk of preeclampsia. Women who were born at 34 to 37 weeks of gestation had a slight increase in risk (odds ratio, 1.38; 95% CI, 0.85-2.45), but those women who were born at <34 weeks had three times the risk when compared with those women who were born at term (odds ratio, 3.33; 95% CI, 1.25-7.49). In addition, women who were born weighing <4.5 pounds were at the greatest risk of preeclampsia compared with those women who weighed $8.5 pounds (odds ratio, 5.16; 95% CI, 1.24-21.51).
The literature is rife with studies that have examined the association between birth weight and/or length and adult blood pressure in men and nonpregnant women. For example, Huxley et al18 reviewed 80 studies that described the relationship between adult blood pressure and birth weight and found that most demonstrated an inverse relationship. However, other authors have shown no such association.19 In the Nurses Health Study parts I and II, Curhan et al8 showed increases of 39% and 43%, respectively, in risk of adult hypertension when comparing women who had weighed <5 pounds at birth to those who had weighed between 7 and 8.5 pounds. In a prospective study of 438 Swedish women, weight and length at birth were significant predictors of hypertension at age 60 years.20 A cross-sectional study of 297 British women revealed that low birth weight was associated with increased systolic blood pressure at age 60 to 71 years. Notably, lower birth weights were also correlated with cardiovascular disease risk factors that include higher plasma concentrations of glucose and insulin, higher serum triglyceride concentrations, lower serum highdensity lipoprotein cholesterol concentrations, and higher waist/hip ratios.9 Adult BMI has been shown to modify these associations, as women who were small at birth and currently obese had the least favorable risk factor profiles.9,21 This profile is characteristic of insulin resistance syndrome, a metabolic disorder that usually appears later in life but may also be unmasked during
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Table IV. Risk of preeclampsia according to maternal birth weight categories (post hoc analysis; Seattle and Tacoma, Wash, 1998-2001) Preeclampsia cases (n = 86)
Control subjects (n = 349)
Maternal birth weight (g)
No.
%
No.
%
<2500 2500-2999 3000-3999 $4000
13 24 44 5
15.12 27.91 51.16 5.81
18 77 224 30
5.16 22.06 64.18 8.60
Odds ratio (95% CI)* 2.32 1.0 0.63 0.54
(0.99-5.41) (Reference) (0.36-1.10) (0.19-1.53)
Odds ratio (95% CI)y 3.23 1.0 0.47 0.42
(1.12-9.31) (Reference) (0.24-0.92) (0.11-1.57)
*Unadjusted. yAdjusted for age, race/ethnicity, parity, hypertension in first-degree relative, education, BMI at age 18 years, and prepregnancy BMI.
pregnancy in the form of preeclampsia.22 Exploration of the relationship between birth weight and preeclampsia may help to elucidate the pathophysiology and identify subpopulations of women who are at particularly high risk of the development of chronic hypertension, insulin resistance syndrome, and related disorders including non-insulin-dependent diabetes mellitus. The causal pathways that are involved in the relationship between birth characteristics and future risk of preeclampsia or chronic hypertension have yet to be elucidated. However, there are compelling and biologically plausible hypothesized mechanisms that merit discussion. One such mechanism involves the kidney, which undergoes critical development in late gestation and can be compromised as the result of restricted fetal growth.23 Individuals with such a prenatal history are thought to have an excessive hemodynamic burden, which makes them more likely to experience hypertension when exposed to fluctuations in body mass index and other stresses,24 of which pregnancy may qualify. A second possible mechanism involves insulin resistance. Individuals with a history of inadequate fetal growth are hypothesized to be at an increased risk of having insulin resistance and associated complications in adulthood. Investigators have postulated that growth-restricted infants may have a reduced number of pancreatic b cells and a subsequent diminished capacity to produce insulin.1 In addition, those women who become obese later in life are likely to be at particularly high risk of having insulin resistance.25,26 The association between birth characteristics and preeclampsia needs further validation, especially in large, prospective studies. However, our results support the hypothesis that low birth weight is predictive of preeclampsia risk later in life. Continued investigation into the biologic mechanisms that are likely to underlie these observed associations is necessary to establish the public health significance and clinical implications of these findings. We thank the participants of the Alpha Study for their cooperation and Malou Andresen, Penny Anders-
Bartolo, Ihunnaya Frederick, Raymond Miller, Trudi Witt, and Kathy Ramsey for their technical expertise. REFERENCES 1. Godfrey KM, Barker DJP. Fetal nutrition and adult disease. Am J Clin Nutr 2000;71:1344-1352S. 2. Byrne CD, Phillips DI. Fetal origins of adult disease: epidemiology and mechanisms. J Clin Pathol 2000;53:822-8. 3. Ounsted M, Ounsted C. Rate of intra-uterine growth. Nature 1968; 220:599-660. 4. Hackman E, Emanuel I, van Belle G, Daling J. Maternal birth weight and subsequent pregnancy outcome. JAMA 1983;250:2016-9. 5. Klebanoff MA, Graubard BI, Kessel SS, Berendes HW. Low birth weight across generations. JAMA 1984;252:2423-7. 6. Emanuel I, Leisenring W, Williams MA, Kimpo C, Estee S, O’Brien W, et al. The Washington State Intergenerational Study of Birth Outcomes: methodology and some comparisons of maternal birthweight and infant birth weight and gestation in four ethnic groups. Paediatr Perinat Epidemiol 1999;13:352-71. 7. Barker DJP, Sultan HY. Fetal programming of human disease. In: Hanson MA, Spencer JA, Rodeck CH, editors. Fetus and neonate: physiology and clinical applications. Cambridge (UK): Cambridge University Press; 1995. p. 255-74. 8. Curhan GC, Chertow GM, Willett WC, Spiegelman D, Colditz GA, Manson JE, et al. Birth weight and adult hypertension and obesity in women. Circulation 1996;94:1310-5. 9. Fall CHD, Osmond C, Barker DJP, Clark PMS, Hales CN, Stirling Y, et al. Fetal and infant growth and cardiovascular risk factors in women. BMJ 1995;310:428-32. 10. Williams MA, Emanuel I, Kimpo C, Leisenring WM, Hale CB. A population-based cohort study of the relation between maternal birth weight and risk of gestational diabetes mellitus in four race/ ethnic groups. Paediatr Perinat Epidemiol 1999;13:452-65. 11. Innes KE, Byers TE, Marshall JA, Baron A, Orleans M, Hamman RF. Association of a woman’s own birth weight with subsequent risk for gestational diabetes. JAMA 2002;287:2534-41. 12. Egeland GM, Skjaerven R, Irgens LM. Birth characteristics of women who develop gestational diabetes: population based study. BMJ 2000;321:546-7. 13. Moses RG, Moses J, Knights S. Birth weight of women with gestational diabetes. Diabetes Care 1999;22:1059-62. 14. Innes KE, Marshall JA, Byers TE, Calonge N. A woman’s own birth weight and gestational age predict her later risk of developing preeclampsia, a precursor of chronic disease. Epidemiology 1999; 10:153-60. 15. Klebanoff MA, Secher NJ, Mednick BR, Schulsinger C. Maternal size at birth and the development of hypertension during pregnancy: a test of the Barker hypothesis. Arch Intern Med 1999;159:1607-12. 16. American College of Obstetricians and Gynecologists. Hypertension in pregnancy. Washington (DC): The College; 1996. Technical Bulletin No.: 219. p. 1-8. 17. National High Blood Pressure Education Program Working Group on High Blood Pressure in Pregnancy. Report of the national high blood pressure education program working group on high blood pressure in pregnancy. Am J Obstet Gynecol 2000;183:S1-22.
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18. Huxley RR, Shiell AW, Law CM. The role of size at birth and postnatal catch-up growth in determining systolic blood pressure: a systematic review of the literature. J Hypertens 2000;18:815-31. 19. Falkner B, Hulman S, Kushner H. Birth weight versus childhood growth as determinants of adult blood pressure. Hypertension 1998;31:145-50. 20. Andersson SW, Lapidus L, Niklasson A, Hallberg L, Bengtsson C, Hulthen L. Blood pressure and hypertension in middle-aged women in relation to weight and length at birth: a follow-up study. J Hypertens 2000;18:1753-61. 21. Law CM, de Swiet M, Osmond C, Fayers PM, Barker DJP, Cruddas AM, Fall CHD. Initiation of hypertension in utero and its amplification throughout life. BMJ 1993;306:24-7.
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22. Kaaja R, Tikkanen MJ, Viinikka L, Ylikorkala O. Serum lipoproteins, insulin, and urinary prostanoid metabolites in normal and hypertensive pregnant women. Obstet Gynecol 1995;85:353-6. 23. Marchand MC, Langley-Evans SC. Intrauterine programming of nephron number: the fetal flaw revisited. J Nephrol 2001;14: 327-31. 24. Mackenzie HS, Brenner BM. Fewer nephrons at birth: a missing link in the etiology of essential hypertension? Am J Kidney Dis 1995; 26:91-8. 25. Phillips DIW, Hirst S, Clark PMS, Hales CN, Osmond C. Fetal growth and insulin secretion in adult life. Diabetologia 1994;37:592-6. 26. Phillips DIW. Insulin resistance as a programmed response to fetal undernutrition. Diabetologia 1996;39:1119-22.