American Journal of Epidemiology
Copyright © 2003 by the Johns Hopkins Bloomberg School of Public Health
All rights reserved
Vol. 158, No. 9
Printed in U.S.A.
DOI: 10.1093/aje/kwg211
Association of a Woman’s Own Birth Weight with Her Subsequent Risk for
Pregnancy-induced Hypertension
Kim E. Innes1,2, Tim E. Byers1, Julie A. Marshall1, Anna Barón1, Miriam Orleans1, and Richard
F. Hamman1
1
2
Department of Preventive Medicine and Biometrics, University of Colorado Health Sciences Center, Denver, CO.
Southeastern Rural Mental Health Research Center, University of Virginia, Charlottesville, VA.
Received for publication March 10, 2003; accepted for publication April 22, 2003.
Studies have linked low birth weight to elevated risk for adult hypertension and insulin resistance. However, the
relation between birth weight and later risk for pregnancy-induced hypertension (PIH), a disorder associated with
insulin resistance and predictive of chronic hypertension, has not been well studied. This case-control study used
linked hospital discharge and vital record data from New York State. Subjects were healthy women born in New
York State who completed a first pregnancy there between 1994 and 1998. Records from each woman’s own
birth (1970–1985) were linked to those from her first pregnancy. Cases were 2,180 women diagnosed with PIH.
Controls were the 22,955 remaining women with no record of PIH. Birth weight showed a U-shaped relation to
risk for PIH, with the highest risks associated with very low and very high birth weights. Relative to women born
at 3.5–4.0 kg, odds ratios adjusted for gestational age were 2.1 (95% confidence interval (CI): 1.1, 3.9) and 1.6
(95% CI: 1.1, 2.4), respectively, for women with birth weights less than 1.5 kg and greater than 4.5 kg. Adjustment
for other perinatal factors reduced the association with high birth weight to 1.1 (95% CI: 0.7, 1.7) but strengthened
that with lower birth weights, leaving a strong, inverse relation between birth weight and PIH risk (p for trend <
0.0001). These findings support a possible role for early life factors, particularly fetal growth, in the etiology of PIH.
birth weight; hypertension; insulin resistance; pre-eclampsia; pregnancy
Abbreviations: CI, confidence interval; OR, odds ratio; PIH, pregnancy-induced hypertension.
Studies of older adults have repeatedly demonstrated
inverse associations between markers of fetal growth and
blood pressure (1) and hypertension (2), lending support to
the “fetal origins” hypothesis—that susceptibility to hypertension and related chronic adult conditions may be
programmed in utero. However, studies of younger populations continue to yield more conflicting findings (1, 3–11),
and observed effects have been small and of unclear clinical
significance (12). Several investigators have also argued that
the observed relation between hypertension and impaired
fetal growth could be confounded by later environmental
influences and/or by relative postnatal growth (12–14). In
addition, few studies in any age group have adjusted for the
potentially important confounding influence of maternal
hypertension (10, 15–18), which could lead to both impaired
fetal growth and chronic hypertension in the offspring (12,
16).
Pregnancy-induced hypertension (PIH) is a common
disorder of gestation that predicts future hypertension,
cardiovascular disease, and diabetes (19, 20). PIH shares
many features of the metabolic syndrome (19, 20) and is an
easily measurable condition that occurs relatively early in
life. PIH is therefore well suited for testing the fetal origins
hypothesis in young adult populations. To date, only two
published studies have examined the associations between
markers of a woman’s growth as a fetus and her subsequent
risk for hypertension as a pregnant adult (15, 21). Although
results from these studies suggest that impaired fetal growth
may increase risk for PIH, interpretation of findings is
limited by small sample sizes, which precluded detailed
evaluation of dose-response associations, of the relative
influence of high birth weight, and of potentially important
modifiers such as body mass index and race/ethnicity. In this
Correspondence to Dr. Kim E. Innes, Southeastern Rural Mental Health Research Center, McLeod Hall, University of Virginia, 202 15th Street
SW, Charlottesville, VA 22903-3306 (e-mail: [email protected]).
861
Am J Epidemiol 2003;158:861–870
862 Innes et al.
paper, we describe findings from a large, population-based
study designed to address these limitations.
MATERIALS AND METHODS
Data for this case-control study were drawn from two
large, computerized state databases maintained by the New
York State Department of Health: the livebirth registry and
the New York State hospital discharge records. Eligible
subjects included all women who completed a first pregnancy (and delivered a liveborn infant) in Upstate New York
between 1994 and 1998, and who were also born in New
York State in 1970 or later. The Bureau of Biometrics of the
New York State Department of Health performed all subject
selection and record linkages and produced the final anonymous data set of linked pregnancy and birth records.
Matching procedures are described elsewhere (22). The
study was approved by the Colorado Multiple Institutional
Review Board and the New York State Department of
Health Institutional Review Board.
Of the 95,309 pregnancy records from 1994 to 1998 indicating birth of the mother in Upstate New York in 1970 or
later, 57,588 (60 percent) were successfully linked to the
women’s own birth records. From these linked records, all
but those pertaining to first pregnancies were then excluded,
leaving a total of 29,924 linked birth and first pregnancy
records. We then further excluded from the study any
woman whose pregnancy was complicated by multifetal
gestation (n = 270), by the use of illegal drugs (n = 678), or
by heart disease, essential hypertension, renal disease,
diabetes mellitus, acute or chronic lung disorders, or other
serious acute or preexisting chronic conditions requiring
medication or monitoring (n = 3,482) as indicated on her
hospital discharge or infant’s birth record. Women with
gestational diabetes (n = 608) were also excluded, leaving a
final sample of 25,135 eligible primigravida subjects.
Among eligible subjects, age at delivery ranged from 12 to
28 years and averaged 21.1 years (standard deviation, 3.5).
Cases were defined as eligible subjects with a record of
pregnancy-related hypertension, preeclampsia, or eclampsia
on their infant’s birth records and/or a diagnosis, according
to the International Classification of Diseases, Ninth Revision, of transient hypertension (codes 642.0–642.3), hypertension complicating pregnancy (code 642.9), mild
preeclampsia (code 642.4), severe preeclampsia (code
642.5), or eclampsia (code 642.6) on their hospital discharge
records. A total of 2,180 cases of PIH (8.7 percent of all
eligible first pregnancies) were identified on linked birth
registry and hospital discharge records. Cases included
1,044 pregnancies complicated by gestational hypertension,
1,095 by preeclampsia, and 41 by eclampsia. Because the
association of PIH with markers of fetal growth and other
perinatal factors did not differ appreciably by PIH category
(gestational hypertension vs. preeclampsia/eclampsia), diagnostic severity (mild vs. severe preeclampsia), or diagnostic
source (vital record vs. hospital discharge data), and the risk
profiles for these case groups were similar, all PIH cases
were combined for the analyses presented here. Controls
were defined as all remaining eligible subjects whose first
pregnancies were not complicated by PIH (n = 22,955).
Growth in utero was measured as the woman’s own birth
weight and gestational age (clinical estimate in weeks) as
indicated on her birth certificate. Birth weight was evaluated
both alone (as a measure of absolute birth size) and adjusted
for gestational age in weeks (as an indicator of relative fetal
growth). Implausibly extreme values (e.g., birth weights less
than 450 g and gestational ages less than 22 weeks or greater
than 46 weeks) were set to missing. Using New York State
vital record information, we assessed the relation of PIH risk
to other factors characterizing the subject’s own birth and
experience in utero, including multifetal gestation, subject
birth order (firstborn vs. later born), maternal age and
parental educational levels at the time of the subject’s birth,
and preeclampsia, chronic hypertension, diabetes, or other
serious conditions complicating the pregnancy of the
woman’s mother. In addition, we assessed the effects of
potential risk factors for PIH that characterized the woman’s
first pregnancy, including her race/ethnicity, age, marital
status, educational level, employment and insurance status,
participation in welfare, onset of prenatal care, tobacco use
during pregnancy, height, prepregnancy body mass index
(calculated as weight (kg)/height (m)2), and pregnancy
weight gain.
We used multiple logistic regression analysis to determine
the independent effects of a woman’s own birth size, relative
fetal growth gestational age, and other factors on the development of PIH, to evaluate the influence of potential
confounders and to assess linear trends. To assess the influence of birth weight adjusted for gestational age (a measure
of relative fetal growth) on PIH risk, we included gestational
age (in weeks) as a covariate in the multiple logistic regression model. We conducted additional analyses stratified by
factors known or suspected to modify the association
between fetal growth and PIH or chronic disease risk,
including prepregnancy body mass index, height, race/
ethnicity, and smoking status. Multiplicative interactions
were also assessed using logistic regression.
Primigravida women whose pregnancy records could not
be linked to those from their own birth were more likely than
matched women to be Black (20 percent vs. 12 percent) and
receiving Medicaid (46 percent vs. 38 percent), and they
averaged slightly younger ages at the time of delivery (20.7
vs. 21.1 years). However, unmatched women did not differ
from matched women in other demographic or anthropometric characteristics in the onset of prenatal care or in
tobacco use during pregnancy. Most importantly, linkage to
a birth record was not associated with the prevalence of PIH
either overall or within different categories of age and race/
ethnicity.
RESULTS
Relative to non-Hispanic White women, African-American women had a higher PIH risk (odds ratio (OR) = 1.2, 95
percent confidence interval (CI): 1.0, 1.3), and women of
Hispanic origin had a lower risk (OR = 0.75, 95 percent CI:
0.6, 1.0). PIH was weakly associated with marital status, age,
education, employment during pregnancy, and Medicaid
coverage (table 1).
Am J Epidemiol 2003;158:861–870
Birth Weight and Subsequent Risk for PIH 863
TABLE 1. Association of demographic factors characterizing a woman’s first pregnancy (1994–1998) and early life with her risk for
pregnancy-induced hypertension, among previously healthy, New York-born women†
PIH cases/total
with characteristic
No.
Crude
OR‡
95%
CI‡
Adjusted
OR§
95%
CI
%
Subject’s demographic characteristics at first pregnancy
Race
Non-Hispanic White
1,749/20,345
8.59
1.00
Referent
1.00
Referent
Black
295/2,969
9.94
1.15*
1.01, 1.31
1.14
0.99, 1.30
Hispanic
92/1,362
6.75
0.75**
0.59, 0.96
0.72*
0.56, 0.93
Other non-White
33/356
9.27
0.99
0.68, 1.44
0.99
0.68, 1.44
<17
183/2,018
9.07
1.00
Referent
1.00
Referent
17–20
782/9,747
8.02
0.88
0.74, 1.04
0.99
0.82, 1.20
21–24
811/8,042
10.08
1.07
0.91, 1.27
1.35***
1.09, 1.67
25–28
474/5,395
8.79
0.91
0.76, 1.09
1.23
0.96, 1.57
Age at delivery (years)
p for trend
NS‡
NS
Marital status
Married
1,632/18,715
8.72
1.00
Referent
1.00
Referent
Single
548/6,420
8.54
0.96
0.87, 1.06
0.88*
0.78, 0.99
36/522
6.90
0.71
0.50, 1.00
0.77
0.54, 1.12
Years of education
<9
9–11
488/5,558
8.78
0.95
0.85, 1.07
1.00
0.88, 1.14
12
842/9,277
9.08
1.00
Referent
1.00
Referent
13–15
520/6,187
8.40
0.92
0.82, 1.03
0.89
0.79, 1.00
≥16
236/3,119
7.57
0.83**
0.72, 0.97
0.77**
0.65, 0.91
p for trend
NS
NS
Employed during pregnancy
Yes
1,224/14,391
8.51
0.95
0.87, 1.03
0.94
0.84, 1.04
No
921/10,327
8.92
1.00
Referent
1.00
Referent
Private insurance/HMO‡
1,229/14,669
8.38
1.00
Referent
1.00
Referent
Medicaid
885/9,670
9.15
1.10*
1.01, 1.20
1.10
0.98, 1.24
Uninsured
26/354
7.34
0.83
0.55, 1.24
0.83
0.54, 1.26
<9
131/1,404
9.33
1.18
0.96, 1.46
1.21
0.96, 1.53
9–11
374/4,269
8.76
1.11
0.96, 1.28
1.09
0.92, 1.28
Primary insurance payer
Parental level of education at time of subject’s own birth
Father’s education (years)
12
1,011/11,553
8.75
1.10
0.98, 1.24
1.08
0.95, 1.23
>12
414/5,178
8.00
1.00
Referent
1.00
Referent
p for trend
0.08
NS
Mother’s education (years)
<9
93/1,182
7.87
0.93
0.73, 1.18
0.84
0.63, 1.12
9–11
495/5,821
8.50
1.01
0.87, 1.17
0.95
0.80, 1.13
12
1,206/13,469
8.95
1.07
0.94, 1.21
1.03
0.90, 1.18
>12
335/3,968
8.44
1.00
Referent
1.00
Referent
p for trend
NS
* p < 0.05; ** p < 0.025; *** p < 0.01.
† A total of 2,180 pregnancy-induced hypertension (PIH) cases among 25,135 first pregnancies.
‡ OR, odds ratio; CI, confidence interval; NS, nonsignificant (p > 0.1); HMO, health maintenance organization.
§ Adjusted for other variables in the table.
Am J Epidemiol 2003;158:861–870
NS
864 Innes et al.
TABLE 2. Relation of factors characterizing a woman’s first pregnancy to her risk for pregnancy-induced hypertension,
New York State, 1994–1998†
PIH cases/total with
characteristic
Crude
OR‡
No.
%
<20.55
311/6,067
5.40
1.00
20.55–22.89
375/5,882
6.81
22.90–26.66
542/6,110
9.73
>26.66
829/5,617
17.31
95%
CI‡
Adjusted for birth weight
and gestational age
Adjusted also for other
perinatal factors§
OR
95% CI
OR
95% CI
Referent
1.00
Referent
1.00
Referent
1.23*
1.06, 1.43
1.25*
1.07, 1.46
1.34*
1.14, 1.59
1.77*
1.53, 2.04
1.78*
1.54, 2.05
1.82*
1.56, 2.13
3.26*
2.86, 3.73
3.30*
2.89, 3.78
3.65*
3.15, 4.24
Prepregnancy BMI‡
(quartiles)
p for trend
0.0001
0.0001
0.0001
Height in inches¶
(quartiles)
<63
532/5,931
9.85
1.00
Referent
1.00
Referent
1.00
Referent
63–64.99
584/7,002
9.10
0.92
0.82, 1.04
0.93
0.82, 1.05
0.97
0.85, 1.12
65–66
525/6,044
9.51
0.97
0.86, 1.10
0.99
0.87, 1.12
0.99
0.86, 1.14
>66
469/5,268
9.77
0.98
0.86, 1.12
0.99
0.87, 1.14
0.96
0.82, 1.11
p for trend
NS‡
NS
NS
Pregnancy weight gain
(pounds#)
<25
323/5,009
6.89
1.00
Referent
1.00
Referent
1.00
Referent
25–34.9
453/6,977
6.94
0.99
0.86, 1.15
1.01
0.87, 1.17
1.32*
1.13, 1.54
35–44.9
511/6,114
9.12
1.28*
1.11, 1.47
1.32*
1.14, 1.53
1.82*
1.57, 2.12
≥45
763/5,408
16.43
2.34*
2.05, 2.67
2.41*
2.11, 2.77
3.29*
2.85, 3.79
p for trend
0.0001
0.0001
0.0001
Smoking in pregnancy
Yes
305/4,479
7.31
0.74*
0.65, 0.83
0.73*
0.65, 0.83
0.68*
0.59, 0.78
No
1,830/20,256
9.93
1.00
Referent
1.00
Referent
1.00
Referent
* p < 0.01.
† A total of 2,180 pregnancy-induced hypertension (PIH) cases among 25,135 first pregnancies.
‡ OR, odds ratio; CI, confidence interval; BMI, body mass index; NS, nonsignificant (p > 0.1).
§ Including all variables in table and subject’s age, race, education, employment status, and exposure to maternal
preeclampsia.
¶ One inch = 2.54 cm.
# One pound = 0.45 kg.
The risk for PIH rose strongly with increasing prepregnancy body mass index and pregnancy weight gain (table 2).
Relative to women in the lowest body mass index quartile,
those in the highest quartile were over three times as likely to
develop PIH (unadjusted OR = 3.3, 95 percent CI: 2.9, 3.7).
Likewise, the risk for PIH was over twofold higher among
women who gained 45 pounds (20.412 kg) or more during
pregnancy than among those who gained less than 25 pounds
(11.340 kg) (OR = 2.3, 95 percent CI: 2.1, 2.7). Women who
smoked during pregnancy were less likely to develop PIH
(OR = 0.7, 95 percent CI: 0.6, 0.8) (table 2). Adjustment for
other perinatal factors did not alter the protective effect of
smoking on risk for PIH and slightly strengthened the relation of prepregnancy body mass index and pregnancy weight
gain to PIH risk.
Birth weight, both alone and adjusted for gestational age,
showed a U-shaped relation to risk for PIH, with very low
and very high birth weights demonstrating the most
pronounced increase in risk (adjusted ORs for <1.5 kg and
≥4.5 kg = 2.10 (95 percent CI: 1.1, 3.9) and 1.6 (95 percent
CI: 1.1, 2.4), respectively) (table 3). With birth weight up to
4,000 g, the risk for PIH decreased progressively with rising
birth weight (p for trend = 0.007). Adjustment for other perinatal factors strengthened this inverse, dose-response relation. In contrast, controlling for other risk factors and,
specifically, prepregnancy body mass index and pregnancy
weight gain largely eliminated the relation between high
birth weight and risk for PIH (OR for birth weight of ≥4.5 kg
after adjustment for these two factors alone = 1.1, 95 percent
CI: 0.7, 1.7) (p for trend < 0.0001). These associations did
not differ appreciably by PIH category (adjusted ORs for
birth weight of <2,000 g = 1.7 (95 percent CI: 1.0, 2.9) (p for
trend = 0.02) for gestational hypertension vs. 2.0 (95 percent
CI: 1.2, 3.3) (p for trend = 0.002) for preeclampsia) (table 4).
Likewise, these associations were similar by source of diagnosis (adjusted ORs for birth weight of <2,000 g = 1.7 (95
Am J Epidemiol 2003;158:861–870
Birth Weight and Subsequent Risk for PIH 865
TABLE 3. Relation of factors characterizing a woman’s own birth (1970–1986) to her later risk for pregnancy-induced
hypertension in her first pregnancy (1994–1998), New York State†
PIH cases/total with
characteristic
No.
Crude
OR‡
95%
CI‡
%
Adjusted for birth weight
and/or gestational age§
OR
Adjusted also for other
perinatal factors¶
95% CI
OR
95% CI
Birth weight (g)
<1,500
13/95
13.68
1.78
0.99, 3.23
2.08**
1.11, 3.91
2.08*
1.01, 4.28
1,500–1,999
29/275
10.55
1.33
0.90, 1.97
1.35
0.88- 2.08
1.56
0.96, 2.53
2,000–2,499
132/1,423
9.28
1.15
0.94, 1.41
1.16
0.94, 1.43
1.45***
1.16, 1.81
2,500–2,999
479/5,503
8.70
1.07
0.94, 1.22
1.08
0.94, 1.23
1.27***
1.10, 1.46
3,000–3,499
864/10,090
8.56
1.05
0.95, 1.18
1.06
0.95, 1.20
1.13
1.00, 1.28
3,500–3,999
493/6,041
8.16
1.00
Referent
1.00
Referent
1.00
Referent
4,000–4,499
136/1,389
9.79
1.22*
1.00, 1.49
1.20
0.98, 1.47
1.10
0.88, 1.36
≥4,500
28/235
11.91
1.52*
1.02, 2.28
1.58**
1.05, 2.37
1.12
0.72, 1.75
p for trend
0.01#
0.007#
0.0001
Gestational age (weeks)
<33
39/353
11.05
1.31
0.93, 1.83
1.28
0.91, 1.81
1.03
0.68, 1.57
33–34
39/441
8.84
1.02
0.73, 1.42
1.00
0.72, 1.41
1.06
0.74, 1.53
35–36
89/1,115
7.98
0.91
0.73, 1.14
0.91
0.72, 1.13
0.89
0.69, 1.15
37–42
1,764/20,319
8.68
1.00
Referent
1.00
Referent
1.00
Referent
>42
184/2,033
9.05
1.05
0.89, 1.23
1.05
0.90, 1.24
1.01
0.84, 1.21
p for trend
NS‡
NS
NS
Maternal preeclampsia/
eclampsia
Yes
44/357
No
1,907/22,073
12.32
8.64
1.49**
1.08, 2.05
1.48**
1.07, 2.06
1.25
0.87, 1.79
1.00
Referent
1.00
Referent
1.00
Referent
Any form of maternal
hypertension
Yes
59/495
No
1,892/21,935
11.92
1.47**
1.07, 1.86
1.41**
1.06, 1.88
1.20
0.87, 1.65
8.63
1.00
Referent
1.00
Referent
1.00
Referent
11.86
1.42
0.64, 3.12
1.48
0.67, 3.28
1.26
0.51, 3.08
8.69
1.00
Referent
1.00
Referent
1.00
Referent
Maternal diabetes
mellitus
Yes
7/59
No
1,944/22,371
Any complication of
pregnancy
Yes
123/1,132
No
1,828/21,298
10.87
1.30***
1.07, 1.58
1.29**
1.06, 1.57
1.17
0.94, 1.45
8.58
1.00
Referent
1.00
Referent
1.00
Referent
Twin or triplet
Yes
24/236
10.17
1.20
0.78, 1.83
1.23
0.80, 1.90
1.10
0.67, 1.81
No
2,154/24,886
8.66
1.00
Referent
1.00
Referent
1.00
Referent
Yes
743/8,205
9.06
1.07
0.99, 1.18
1.06
0.96, 1.17
1.03
0.93, 1.15
No
1,437/16,970
8.49
1.00
Referent
1.00
Referent
1.00
Referent
<17
41/558
7.35
0.83
0.61, 1.14
0.87
0.63, 1.20
0.78
0.54, 1.13
17–19
285/3,290
8.66
0.99
0.87, 1.13
0.97
0.85, 1.11
0.95
0.82, 1.10
20–34
1,743/20,003
8.71
1.00
Referent
1.00
Referent
1.00
Referent
≥35
111/1,279
8.68
1.00
0.82, 1.21
1.00
0.82, 1.23
1.05
0.83, 1.32
Firstborn
Maternal age (years) at
subject’s birth
p for trend
NS
NS
NS
* p < 0.05; ** p < 0.025; *** p < 0.01.
† A total of 2,180 pregnancy-induced hypertension (PIH) cases among 25,135 first pregnancies.
‡ OR, odds ratio; CI, confidence interval; NS, nonsignificant (p > 0.1).
§ Birth weight adjusted for gestational age only; gestational age adjusted for other perinatal factors only. All other variables adjusted for both birth
weight and gestational age.
¶ Including other variables in table and age, race, education, employment status, prepregnancy body mass index, and pregnancy weight gain.
# Test for trend (birth weight) including only birth weights under 4,000 g.
Am J Epidemiol 2003;158:861–870
866 Innes et al.
increasing birth weight among women with low and average
prepregancy body mass index (p for trend = 0.0006 and
0.001, respectively), no directional trend was apparent
among heavier women (p for trend = 0.53). The association
of birth weight with PIH risk was also weaker among Black
women than among other racial/ethnic groups (table 6: p for
interaction = 0.006; χ21 df = 7.72). Although Black women in
this study weighed significantly less at birth than did nonBlack subjects (3,022 g (standard deviation, 545) vs. 3,226
g (standard deviation, 514) and were more than twice as
likely to have been low birth weight as newborns (OR = 2.2,
95 percent CI: 2.0, 2.5), reduced birth weight was not related
to PIH risk in this group and did not explain the increased
risk for PIH observed among Black women. Stratifying
Black women by body mass index or gestational age at birth
did not alter these results.
Women born to mothers whose pregnancies were complicated by hypertension were themselves at approximately 50
percent increased risk of developing PIH in their first pregnancies (ORs = 1.6 (95 percent CI: 1.1, 2.1) for maternal
preeclampsia and 1.5 (95 percent CI: 1.1, 1.9) for any form
of maternal hypertension). Although adjustment for a
woman’s own birth weight and gestational age did not appreciably alter these risk estimates, further adjustment for body
mass index, smoking, and other factors attenuated the
strength of these associations (table 3). Excluding women
born to mothers whose pregnancies were complicated by
hypertension did not appreciably change either the strength
or the magnitude of the relation between birth weight and
risk for PIH (OR adjusted for body mass index and other
factors = 2.1, 95 percent CI: 1.0, 4.6) (p for trend = 0.007).
We found little evidence for an association between risk
for PIH and other factors characterizing the subject’s own
birth, including maternal age, parental educational level,
birth order, prematurity, and multifetal gestation. Similarly,
a woman’s height, timing of first prenatal care visit, or
TABLE 4. Association of a woman’s own weight at birth (1970–
1986) with her later risk for pregnancy-induced hypertension in
her first pregnancy (1994–1998), stratified by diagnostic
category, New York State*
Birth weight (g)
Gestational hypertension
(n = 1,044 cases)
Preeclampsia
(n = 1,136 cases)
OR†
95% CI†
OR
95% CI
<2,000
1.96
1.15, 3.33
1.66
0.95, 2.91
2,000–2,499
1.51
1.12, 2.04
1.47
1.08, 2.00
2,500–2,999
1.33
1.10, 1.62
1.23
1.01, 1.50
3,000–3,499
1.19
1.00, 1.40
1.12
0.94, 1.33
3,500–3,999
1.00
4,000–4,499
0.93
0.68, 1.27
1.28
0.97, 1.70
≥4,500
1.17
0.66, 2.07
0.98
0.52, 1.86
p for trend
1.00
0.002
0.02
* Odds ratios adjusted for gestational age, prepregnancy body
mass index, race, age, smoking status, and maternal hypertension;
additional adjustment for pregnancy weight gain did not appreciably
alter these results.
† OR, odds ratio; CI, 95% confidence interval.
percent CI: 0.9, 3.5) (p for trend = 0.009) for cases identified
on vital records vs. 1.9 (95 percent CI: 1.1, 3.4) (p for trend =
0.025) for cases identified on hospital discharge records).
Including women with a record of both gestational diabetes
mellitus and PIH (n = 98) in the analysis slightly strengthened the inverse relation between birth weight and PIH
(adjusted OR for <1.5 kg = 2.3 (95 percent CI: 1.1, 4.5) (p for
trend < 0.0001)).
The inverse association of birth weight with risk for PIH
was more pronounced among thinner than among heavier
women (table 5: p for interaction < 0.0001; χ21 df = 45.59).
Although risk for PIH decreased progressively with
TABLE 5. Association between a woman’s own weight at birth (1970–1986) and her later risk for
pregnancy-induced hypertension in her first pregnancy (1994–1998), stratified by the subject’s
prepregnancy body mass index, New York State*,†
Prepregnancy BMI‡
Birth weight (g)
Thin (BMI, <21)
(n = 7,115)
OR‡
Average (BMI, 21–<25)
(n = 8,805)
Heavy (BMI, ≥25)
(n = 7,756)
95% CI‡
OR
95% CI
OR
95% CI
<2,000
2.98
1.40, 6.36
2.64
1.22, 5.68
2.10
0.93, 4.75
2,000–2,499
1.84
1.14, 2.96
2.54
1.58, 4.09
2.05
1.28, 3.27
2,500–2,999
1.54
1.10, 2.17
1.69
1.14, 2.51
2.33
1.64, 3.31
3,000–3,499
1.42
1.04, 1.94
1.52
1.04, 2.23
2.23
1.64, 3.11
3,500–3,999
1.00
Referent
1.30
0.88, 1.94
2.08
1.47, 2.94
≥4,000
0.84
0.45, 1.56
1.36
0.84, 2.20
2.44
1.64, 3.62
p for trend
0.0006
0.001
0.46
χ21 df
11.89
10.86
0.53
* Odds ratios adjusted for gestational age and pregnancy weight gain.
† Test for interaction of birth weight and body mass index category: p < 0.0001; χ21 df = 45.59.
‡ BMI, body mass index; OR, odds ratio; CI, confidence interval.
Am J Epidemiol 2003;158:861–870
Birth Weight and Subsequent Risk for PIH 867
TABLE 6. Association between a woman’s own weight at birth (1970–1986) and her later
risk for pregnancy-induced hypertension in her first pregnancy (1994–1998), stratified by
the subject’s race/ethnicity, New York State*,†
Black
Non-Hispanic White
Other racial/ethnic groups
Birth weight (g)
OR‡
95% CI‡
OR
95% CI
OR
<2,000
0.62
0.22, 1.69
2.31
1.48, 3.61
3.06
0.33, 28.31
2,000–2,499
1.61
0.97, 2.66
1.32
1.02, 1.72
3.13
1.20, 8.17
2,500–2,999
1.09
0.74, 1.60
1.28
1.09, 1.50
1.65
0.81, 3.35
3,000–3,499
0.83
0.57, 1.21
1.20
1.05, 1.37
1.25
0.66, 2.37
3,500–3,999
1.00
Referent
1.00
Referent
1.00
Referent
≥4,000
1.17
0.56, 2.46
1.10
0.89, 1.36
1.34
0.53, 3.44
p for trend
0.25
0.001
95% CI
0.048
* Odds ratios adjusted for gestational age, prepregnancy body mass index, and pregnancy
weight gain.
† Test for interaction of birth weight and Black race: p = 0.006; χ21 df = 7.72.
‡ OR, odds ratio; CI, confidence interval.
participation in low income programs was not related to her
risk of developing PIH.
DISCUSSION
In this population-based study of young, primigravida
New York women, we found a marked U-shaped association
between a woman’s risk for PIH in her first pregnancy and
her own birth weight as a newborn, both alone and adjusted
for gestational age. Adjustment for other perinatal factors, in
particular prepregnancy body mass index and pregnancy
weight gain, considerably attenuated the association with
high birth weight but strengthened that with low birth
weights, leaving a strong, inverse dose-response relation
between birth weight and risk for PIH. This inverse association was less apparent among Black women and among
women with a prepregnancy body mass index of 25 or
greater.
Our finding of increased risk for PIH among women born
at lower birth weights is consistent with those of two recent
investigations (15, 21). In our previous study of young Colorado-born women, we observed an elevated risk for PIH with
low birth weight but no significant directional trend (21).
However, the power of this study was limited by its small
size (345 cases). Similarly, in a recent prospective study of
Danish women, Klebanoff et al. (15) found that women born
small for gestational age were at elevated risk for hypertension in pregnancy (adjusted OR = 1.8, 95 percent CI: 1.1,
2.8). However, again case numbers were small (157 hypertensive pregnancies), and the dose-response relation was not
evaluated in detail.
The inverse association between birth weight and PIH risk
observed in the present study also parallels recently
published findings regarding fetal growth and subsequent
risk for gestational diabetes mellitus (22–25), suggesting a
possible etiologic link between these disorders. In particular,
our recent study in the same population of primiparous New
York-born women demonstrated a similar U-shaped relation
Am J Epidemiol 2003;158:861–870
between a woman’s own birth weight and gestational
diabetes mellitus (22). Consistent with findings of the
current study, adjustment for prepregnancy body mass index
largely eliminated the effect of high birth weight but
strengthened the inverse association between birth weight
and subsequent risk for gestational diabetes mellitus (22).
To our knowledge, this is the first study to demonstrate a
clear dose-response association between birth weight and
risk for PIH. Our results meet the criteria recently outlined
by Lucas et al. (14), who have argued that, in order for data
to support the fetal origins hypothesis, birth weight should
have a significant inverse effect in models unadjusted for
current weight or body mass index. Some previous investigations have reported an inverse relation between birth
weight and blood pressure that is apparent only after adjustment for current body size (14) or that is stronger among
heavy (9, 26) individuals, suggesting that greater postnatal
change in size may explain or amplify the influence of birth
weight. In contrast, our finding of a stronger relation
between low birth weight and subsequent PIH risk among
leaner than among heavier women suggests that the influence of reduced fetal growth on risk for PIH is neither
explained by relative postnatal weight gain nor amplified by
adult obesity. These results also suggest that the effects of
low birth size and obesity are independent and may influence
PIH risk in part via different pathways.
Black women have a higher prevalence of both low birth
weight and hypertension (5). However, reduced birth size
was not strongly related to risk for PIH among Black women
in our study and did not explain their elevated incidence of
PIH. In contrast, we observed a strong inverse relation
between birth size and PIH risk among non-Black subjects.
Although the reasons for this racial difference are unclear,
our findings are consistent with recent studies of Black
Americans showing no relation between birth weight and
adult blood pressure (5, 27).
PIH is characterized by relative insulin resistance, glucose
intolerance, and hyperlipidemia and by endothelial dysfunc-
868 Innes et al.
tion and elevated levels of specific coagulation and fibrinolytic factors known to predict cardiovascular disease (19,
20). Biologic mechanisms underlying the link between birth
size and the later development of PIH may include early
alterations in lipid metabolism, endothelial function, and
carbohydrate metabolism. Low birth weight has been linked
to impaired endothelial function (28), dyslipidemia (29, 30),
insulin resistance (30–32), and reduced glucose tolerance
(31, 32) later in life, and a growing body of experimental
work in animals suggests that these changes can be
programmed in utero (31, 33, 34). The hyperlipidemia and
insulin resistance that normally accompany pregnancy are
exacerbated in women who develop PIH (20). Such metabolic alterations may compromise a woman’s ability to meet
the diabetogenic and lipogenic challenges of pregnancy and
thus render her more likely to develop PIH.
Exposure to maternal hypertension, which has been associated with both impaired fetal growth (12) and PIH in the
female offspring (35), could also help explain the association
between low birth weight and the subsequent development
of high blood pressure in pregnancy. However, although our
results indicated that maternal hypertension was indeed a
risk factor for PIH in the daughter, neither adjustment for
maternal hypertension nor exclusion of subjects exposed to
this or other maternal pregnancy complications altered the
observed inverse relation between birth size and PIH.
Consistent with our findings, adjustment for maternal hypertension did not alter the association of a woman’s own
impaired fetal growth with her subsequent risk for PIH in a
prospective study of Danish women (15). Likewise, in
studies of European children and adolescents, investigators
did not find maternal blood pressure during pregnancy to
alter the observed association between birth weight and
blood pressure in the offspring (17, 26).
In the present study, the risk for PIH rose with increasing
prepregnancy body mass index and pregnancy weight gain.
In agreement with our findings, several previous studies
have demonstrated an elevated risk for both preeclampsia
and gestational hypertension among heavier women (36,
37). Increased pregnancy weight gain has been prospectively
linked to elevated risk for PIH in several previous investigations (38, 39). Obesity and weight gain are associated with
insulin resistance and dyslipidemia (40–42), and weight loss
improves both insulin sensitivity and lipid profiles (40).
Because sudden weight gain is considered a symptom of
severe preeclampsia, it could be argued that pregnancy
weight gain should not be considered as a covariate in the
model. However, removing pregnancy weight gain from the
model did not appreciably alter the inverse association
between birth weight and risk for PIH (adjusted for body
mass index only, OR = 1.9 (95 percent CI: 1.0, 3.8) for birth
weight of <1,500 g (p for trend = 0.025)), and milder forms
of PIH, which are not generally characterized by precipitous
weight gain, were as strongly related to pregnancy weight
gain as was preeclampsia. In addition, prior studies suggest
that excessive weight gain may itself predispose to the development of PIH (38, 39).
This study has several strengths, including the populationbased design, the racial and ethnic diversity of the study
population, and the large sample sizes, which allowed us to
evaluate in detail the relation between birth weight and PIH
risk and to assess potentially important modifying or
confounding factors. Because the data on birth characteristics were derived from vital records, and thus gathered well
in advance of the pregnancy outcomes, biases in measurement or diagnosis are unlikely. Using linked vital record and
hospital discharge data also enabled us to increase the sensitivity in detecting PIH and other conditions complicating
pregnancy. Studies in New York (M. Zdeb, New York State
Department of Health, unpublished data) and other states
(43) have shown that linking birth registry to hospital
discharge data considerably increases the sensitivity in
detecting obstetric and birth outcomes. Moreover, although
sensitivities for conditions complicating pregnancy are often
low for vital records, accuracy, as indicated by positive and
negative predictive values, can be high. For example, a large
Tennessee validation study of birth certificate information
demonstrated low-to-moderate sensitivities but good-toexcellent predictive values for reporting of diabetes, chronic
hypertension, and pregnancy-induced hypertension (44).
The use of vital record and hospital discharge data also
presents limitations. We were unable to adjust for certain
known and potential risk factors for PIH, including family
history of hypertension or diabetes, dietary intake, exercise
habits, and maternal smoking. However, it is improbable that
confounding by unmeasured variables could explain our
findings. In several previous investigations, adjustment for
maternal smoking (10, 45), socioeconomic status (6, 15, 45–
47), and other potential confounders (6, 48, 49) did not
appreciably alter observed associations between blood pressure or hypertension and birth weight. Another limitation is
the probable underreporting of certain pregnancy complications in the New York State vital records during the period
between 1970 and 1985. In particular, our ascertainment of
maternal hypertension (hypertension complicating the pregnancy of the subject’s mother) is likely incomplete, based on
prevalence reported in previous studies (15, 36). Nonetheless, in a recent study (15) in which the authors obtained
comprehensive information on hypertension complicating
the mother’s pregnancy, the risk estimates for PIH associated with maternal hypertension (ORs = 1.3–1.8) were
similar to those observed in our investigation. Because
gestational age estimates were based on the last menstrual
period, a method that tends to overestimate true gestational
age (50), preterm birth is also likely to have been underreported. Certain lifestyle factors characterizing a woman’s
first pregnancy are also likely to be underreported, including
smoking. However, the observed negative association
between tobacco use and PIH risk is consistent with that of
previous studies (51).
PIH in the woman’s own pregnancy is also likely to have
been underascertained, leading to misclassification of
controls. Preeclampsia is estimated to complicate 7–10
percent of all first pregnancies (36, 52), in contrast to our
observed incidence of 4.5 percent. Similarly, recent studies
have reported gestational hypertension to complicate 5–17
percent of first pregnancies without chronic hypertension or
diabetes (36, 53), whereas we observed a rate of 4.2 percent.
However, since any resulting misclassification of controls is
unlikely to be differentially related to a woman’s birth
Am J Epidemiol 2003;158:861–870
Birth Weight and Subsequent Risk for PIH 869
weight, incomplete ascertainment of PIH would likely lead
to an underestimation of the association between PIH and
birth weight.
This study did not include any women over the age of 28
years, precluding generalization of our results to older primiparas. We were also unable to link approximately 40 percent
of the pregnancy and birth records, raising the possibility of
selection bias. However, primigravida women whose
records could not be linked were similar to matched women
in most demographic factors, in anthropometric characteristics, in lifestyle choices during pregnancy, and in the timing
of prenatal care initiation. Most importantly, the prevalence
rates of PIH, both overall and within specific age and racial/
ethnic groups, were similar in the matched and unmatched
samples, as were the associations of demographic and
anthropometric factors with PIH risk.
In summary, this large study of young, primiparous, New
York-born women showed a significant, inverse relation
between a woman’s own birth weight and her later risk for
PIH, an important complication of pregnancy and marker for
chronic disease risk. These findings are consistent with the
hypothesis that susceptibility to hypertension and related
insulin resistance conditions may be programmed in utero,
and they suggest that early life factors and, in particular, fetal
growth may be important in the etiology of PIH.
ACKNOWLEDGMENTS
This study was supported by grant 1RO3HL59467-d from
the National Institute of Diabetes and Digestive and Kidney
Diseases.
The authors thank Gene Therriault, Director, and Robert
Draiss, Senior Computer Analyst, of the New York State
Health Department Bureau of Biometrics for their assistance
in creating the anonymous linked data set for us and for
offering numerous helpful suggestions and comments during
various stages of this project.
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
20.
21.
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