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OBSTETRICS

Gestational weight gain as a risk factor for hypertensive

disorders of pregnancy

Corrie Macdonald-Wallis, PhD; Kate Tilling, PhD; Abigail Fraser, PhD; Scott M. Nelson, PhD, MRCOG; Debbie A. Lawlor, PhD, FFPH

OBJECTIVE:Pregnancy interventions to limit gestational weight gain (GWG) have been proposed as a means of preventing hypertensive disorders of pregnancy (HDP); however, it is currently unclear whether GWG has a causal influence on the development of HDP. Thus, we aimed to determine whether GWG in early pregnancy is a risk factor for preeclampsia and gestational hypertension and whether GWG pre-cedes the increases in blood pressure in normotensive women across pregnancy.

STUDY DESIGN:We examined repeat antenatal clinic measurements

of weight and blood pressure (median of 12 and 14 per woman, respectively) of 12,522 women in the Avon Longitudinal Study of Parents and Children.

RESULTS: Greater prepregnancy weight was associated with an

increased risk of gestational hypertension and preeclampsia per 10 kg of prepregnancy weight: odds ratio (OR), 1.80; 95% confidence interval (CI), 1.70e1.91 and OR, 1.71; 95% CI, 1.49e1.95, respectively, for

women weighing 90 kg or less before pregnancy; OR, 1.24; 95% CI, 1.03e1.49 and OR, 1.61; 95% CI, 1.18e2.19 for women weighing more than 90 kg. Fully adjusted odds ratios for gestational hypertension and preeclampsia per 200 g per week GWG up to 18 weeks were OR, 1.26; 95% CI, 1.16e1.38 and OR, 1.31; 95% CI, 1.07e1.62. In normotensive women, GWG in early pregnancy was associated posi-tively with blood pressure change in midpregnancy and negaposi-tively with blood pressure change in late pregnancy. In all gestational periods, GWG was positively associated with concurrent blood pressure change. However, there was no evidence that blood pressure changes in any period were associated with subsequent GWG.

CONCLUSION:These findings suggest that GWG in early pregnancy may be a potential target for interventions aimed at reducing the risk of HDP. Key words:Avon Longitudinal Study of Parents and Children, blood pressure, gestational weight gain, hypertensive disorder of pregnancy, preeclampsia

Cite this article as: Macdonald-Wallis C, Tilling K, Fraser A, et al. Gestational weight gain as a risk factor for hypertensive disorders of pregnancy. Am J Obstet Gynecol 2013;209:327.e1-17.

T

he hypertensive disorders of

preg-nancy (HDP), including gestational hypertension and preeclampsia, remain a leading cause of maternal and perinatal mortality and morbidity worldwide1-5and can affect up to 10% of pregnancies.6At

present, effective treatments are limited, and consequently, there is considerable interest in their prevention. Prepregnancy maternal adiposity is the strongest

modi-fiable risk factor for HDP7-10 and thus provides a potential means of prevention;

however, it is increasingly recognized that reducing overweight/obesity in all women of reproductive age is extremely difficult. As a result there has been increased interest in the extent to which gestational weight gain (GWG) may

in-fluence HDP and hence provide a

po-tential target for interventions aimed at reducing its risk.11

Several studies have shown that HDP are more likely to develop in women who have greater GWG12-15; however, most of these studies have important methodological limitations.15 The pri-mary concern is that previous studies have related total GWG across pregnancy to the risk of HDP. This is problematic because women who develop HDP are more likely to experience edema during pregnancy than women who remain normotensive,16 and this in turn may result in greater GWG. Therefore, a pos-itive association of total GWG with HDP could represent increased edema in women with HDP, causing greater weight From the Medical Research Council Centre for Causal Analyses in Translational Epidemiology

(Drs Macdonald-Wallis, Fraser, and Lawlor) and the School of Social and Community Medicine (Drs Macdonald-Wallis, Fraser, Tilling, and Lawlor), University of Bristol, Bristol, England, and the School of Medicine, University of Glasgow, Glasgow, Scotland (Dr Nelson), UK.

Received Dec. 18, 2012; revised March 20, 2013; accepted May 21, 2013.

This work was supported by the UK Wellcome Trust (grant WT087997MA), which provided the salary of C.M.-W.; the National Institutes of Health (grant R01 DK077659); and the UK Medical Research Council (grant G1000726). Core support for Avon Longitudinal Study of Parents and Children is provided by the UK Medical Research Council, the Wellcome Trust, and the University of Bristol. The UK Medical Research Council provides funding for the Medical Research Council Centre for Causal Analyses in Translational Epidemiology (grant G0600705). C.M.-W. and A.F. are supported by UK Medical Research Council research fellowships. The funders had no role in the study design, the data collection and analysis, the decision to publish, or the preparation of the manuscript.

The authors report no conict of interest. Reprints not available from the authors.

0002-9378/$36.00ª2013 Mosby, Inc. All rights reserved.http://dx.doi.org/10.1016/j.ajog.2013.05.042

See Journal Club, page 391

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gain, rather than greater GWG infl u-encing increases in blood pressure.17 Furthermore, although a recent meta-analysis of interventions designed to limit GWG did show a reduction in HDP,18this could be explained by the treatment of gestational diabetes mellitus that oc-curred in the 2 largest studies contrib-uting to the metaanalysis.19,20

Therefore, clarification of whether greater GWG precedes HDP and there-fore could be a potential causal risk factor is urgently needed. The primary aim of this study was to examine whether GWG up to 18 weeks’ gestation is associated with the subsequent development of HDP. GWG prior to 18 weeks’gestation, the time of the nadir in blood pressure,21 is unlikely to be affected by edema caused by HDP because it occurs before blood pressure begins to increase, and generally clinical edema does not occur until the second half of pregnancy.22

To further examine whether GWG influences blood pressure in pregnancy, we also investigated whether greater GWG in different periods of pregnancy precedes greater increases in blood pres-sure. In this second analysis, we excluded women with HDP to exclude the possi-bility that the relationships are explained by changes in weight caused by HDP.

M

ATERIALS AND

M

ETHODS

The Avon Longitudinal Study of Parents and Children (ALSPAC) is a prospective birth cohort study investigating the health and development of children. The study has been described in full elsewhere23and on the website (Available at:www.bris.ac. uk/alspac. Accessed March 20, 2013). Women with expected delivery dates be-tween April 1, 1991, and Dec. 31, 1992, who were living in a defined area of Avon during their pregnancy were eligible for recruitment. Ethical approval was ob-tained from the ALSPAC Law and Ethics Committee and from the National Health Service local ethics committee.

A total of 14,541 women were enrolled, 13,678 women had a singleton live birth, and 13,461 of these had data abstracted from obstetric records. We excluded women who reported having a previous diagnosis of hypertension

outside pregnancy (n ¼ 445), leaving

13,016 women of whom 12,522 had at least 1 measurement of blood pressure and weight during pregnancy.

Antenatal blood pressure and weight measurements

All weight and blood pressure measure-ments (median [interquartile range] per woman: 12 [10e14] and 14 [11e16], respectively) taken routinely as part of antenatal care by midwives or obstetri-cians were abstracted from obstetric re-cords by 6 trained research midwives. There was no between-midwife varia-tion in the mean values of the data abstracted, and error rates were consis-tently less than 1% in repeated data entry checks.

Gestational age at delivery was calcu-lated as the difference between the de-livery date and the mother’s reported last menstrual period date or updated if ul-trasound information was available, which led to a reassessment of gestation. At the time of recruitment,first-trimester ultrasound gestational age dating was not routine clinical practice, and the infor-mation abstracted from clinical records did not indicate which few women had their gestational age adjusted.

HDP was defined according to

International Society for the Study of Hypertension in Pregnancy criteria of systolic blood pressure (SBP) of 140 mm Hg or greater or diastolic blood pressure (DBP) of 90 mmHg or greater, measured on 2 occasions after 20 weeks’ gestation for gestational hypertension and the same criteria in conjunction

with proteinuria of at least 1þ on

dipstick testing for preeclampsia.24 Prepregnancy weight was obtained from the predicted weight at 0 weeks’ gestation from multilevel models based on the antenatal weight measurements (see the following text). This correlated highly with self-reported prepregnancy weight from a questionnaire adminis-tered during pregnancy (r ¼0.94). Ab-solute weight gain was calculated by subtracting the predicted weight at 8 weeks (because there were few measure-ments prior to this time) from the pre-dicted weight at 40 weeks’gestation, using a multilevel model for weight change across pregnancy including women with

term pregnancies (see the following text) and was then categorized according to Institute of Medicine (IOM) recom-mendations (Appendix; Supplementary Table 1).17 Consistent results to those presented here for associations of IOM categories with HDP were found if self-reported prepregnancy weight and the last antenatal weight measurement (in which this was after 37 weeks) were used to define absolute weight gain.

Maternal characteristics

Maternal age at delivery and offspring sex were abstracted from obstetric re-cords. Maternal height, parity, highest educational qualification, and smoking status were obtained from question-naires administered during early preg-nancy. Prepregnancy body mass index (BMI) was calculated as predicted prepregnancy weight (kilograms)/self-reported height (meters) squared and classified according to the World Health Organization categories (Supplementary Table 1). Smoking status was classed as never for women who did not smoke immediately prior to or during preg-nancy, before pregnancy/first trimester for women who smoked only immedi-ately prior to pregnancy or in the first 3 months of gestation, or throughout for women who continued to smoke after thefirst trimester.

Statistical analysis

IOM categories of GWG and risk of HDP

For women with complete data on IOM categories of GWG and covariates (n¼ 9596), we used a multinomial regression model to assess the risk of develop-ing gestational hypertension and pre-eclampsia (with normotensive women as the comparison group) by the IOM category of GWG, adjusting for pre-pregnancy BMI, maternal age, parity, smoking, education, and sex of offspring.

Early pregnancy GWG and risk of HDP

Using all weight measurements up to 18 weeks’ gestation for women with at least 1 weight measurement prior to

this time (n ¼ 11,760), we developed

a multilevel model for the change in weight with gestational age, using a

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Characteristics of the cohort and subsamples by HDP

Maternal characteristic

Full dataset (total n[12,522) mean (SD) or %

Complete data for GWG at£18 weeks and HDP analysis (n[9536), mean (SD) or %

Complete data for GWG and BP change analysis (n[7975) mean (SD) or % Normotensive (n[10,346) Gestational hypertension (n[1892) Preeclampsia (n[284) Normotensive (n[7869) Gestational hypertension (n[1466) Preeclampsia (n[201) Normotensive (n[7975) Height, cm (n¼9085) (n¼1674) (n¼243) 163.81 (6.66) 164.70 (6.95) 162.97 (6.69) 163.88 (6.61) 164.71 (6.96) 162.99 (6.71) 163.94 (6.59) Age, y (n¼10,346) (n¼1892) (n¼284) 15-19 5.08 3.96 8.10 3.24 2.52 3.48 3.60 20-24 19.04 21.93 26.41 16.02 19.37 28.36 16.20 25-29 38.49 39.11 34.86 39.69 40.72 35.32 39.44 30-34 27.94 24.68 17.96 30.73 27.08 20.40 30.39 35 9.44 10.31 12.68 10.32 10.30 12.44 10.37 Parity (n¼9610) (n¼1758) (n¼255) Nulliparous 42.58 57.05 70.98 42.66 57.71 71.64 42.39 Multiparous 57.42 42.95 29.02 57.34 42.29 28.36 57.61 Smoking in pregnancy (n¼9713) (n¼1771) (n¼256) Never 65.42 69.85 74.22 68.31 72.24 75.12 68.13 Before pregnancy/first trimester 13.60 14.85 16.41 12.99 14.05 17.91 13.25 Throughout 20.98 15.30 9.38 18.71 13.71 6.97 18.62 Highest qualification (n¼9253) (n¼1707) (n¼242) CSE/vocational 30.41 29.23 28.10 28.20 27.49 27.36 28.30 O level 33.99 36.44 36.78 34.63 37.18 36.82 34.51 A level 22.72 21.32 23.55 23.79 22.17 24.38 23.59 Degree 12.88 13.01 11.57 13.38 13.17 11.44 13.61

Macdonald-Wallis. Weight gain and blood pressure in pregnancy. Am J Obstet Gynecol 2013. (continued)

Obstetrics

Research

OCTOBER 2013 American Journal of Obstetric s & Gynecology 327. e3
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linear slope. The model had 2 levels: measurement occasion (occasion level) within woman (individual level); and 2 individual-level random effects repre-senting weight at 0 weeks (the intercept; referred to as prepregnancy weight) and average GWG per week up to 18 weeks. The individual-level random effects were then used as exposure variables in multinomial logistic regression models.

The outcome variable had 3 categories: normotensive (comparison group), ges-tational hypertension, and preeclampsia. We adjusted for maternal height, age, parity, smoking, education, and offspring sex, and to examine the exposure of GWG up to 18 weeks, we additionally adjusted for prepregnancy weight. We tested for nonlinearity in these associa-tions using fractional polynomials, and any nonlinear relationships were ap-proximated using linear splines. We also tested for an interaction between pre-pregnancy BMI category and GWG up to 18 weeks.

GWG and changes in blood pressure in normotensive women

We have previouslyfitted multilevel linear spline models for changes in SBP, DBP,21 and weight25 with gestational age sepa-rately. We combined these models to develop 2 bivariate multilevel linear spline models,26the first including changes in SBP and weight in parallel and the second including changes in DBP and weight in parallel (Supplementary material).

This analysis was restricted to nor-motensive women who had a term

pregnancy (37 weeks) (n¼9855). The

model with SBP and weight as outcomes had 5 random-effect parameters for SBP: SBP at 8 weeks (baseline) and rate of SBP change at 8-18 weeks (early preg-nancy), 18-29 weeks (midpregpreg-nancy), 29-36 weeks (late pregnancy), and 36 weeks onward (very late pregnancy) and 4 random-effect parameters for weight: weight at 0 weeks (prepregnancy weight) and rate of GWG at 0-18 weeks (early pregnancy), 18-29 weeks (mid-pregnancy), and 29 weeks onward (late pregnancy). The model with DBP and weight as outcomes had the equivalent random-effects parameters for DBP as for SBP and the same weight parameters.

TABLE 1

Characteristics

of

the

cohort

and

subsamples

by

HDP

(continued) Maternal characteristic Full dataset (total n [ 12,522) mean (SD) or % Complete data for GWG at £ 18 weeks and HDP analysis (n [ 9536), mean (SD) or % Complete data for GWG and BP change analysis (n [ 7975) mean (SD) or % Normotensive (n[ 10,346) Gestational hypertension (n[ 1892) Preeclampsia (n [ 284) Normotensive (n [ 7869) Gestational hypertension (n[ 1466) Preeclampsia (n[ 201) Normotensive (n [ 7975) Offspring sex (n ¼ 10,346) (n ¼ 1892) (n ¼ 284) Male 51.29 53.17 51.76 51.14 52.59 53.73 50.51 Female 48.71 46.83 48.24 48.86 47.41 46.27 49.49 Prepregnancy weight, kg a (n ¼ 9855) (n ¼ 1795) (n ¼ 209) 59.19 (11.07) 67.59 (15.70) 67.76 (17.81) 59.49 (10.65) 67.32 (15.08) 66.38 (16.41) 59.25 (10.83) Average weight gain up to 18 wks, kg/wk a (n ¼ 9691) (n ¼ 1804) (n ¼ 265) (n ¼ 7186) 0.290 (0.129) 0.278 (0.148) 0.284 (0.149) 0.291 (0.131) 0.282 (0.150) 0.284 (0.143) 0.292 (0.132) Total weight gain, kg a (n ¼ 9855) (n ¼ 1795) (n ¼ 209) (n ¼ 7549) (n ¼ 1399) (n ¼ 155) 13.86 (4.49) 14.96 (5.20) 16.65 (5.59) 13.94 (4.46) 14.98 (5.20) 16.50 (5.77) 13.94 (4.42) BP , blood pressure; CSE , certificate of secondary education; GWG , gestational weight gain; HDP , hypertensive disorders of pregnancy; SD , standard deviation. aPrepregnancy weight is calculated from the predicted weight at 0 weeks’ gestation; average weight gain up to 18 weeks is calculated from the predicted rate of weight change between 0 and 18 weeks (for women who had a weight measurement prior to 18 weeks), and total weight gain is calculated as the predicted weight at 40 weeks’ gestation minus the predicted weight at 8 weeks’ gestation from univariate lin ear spline random effects models including each woman’s antenatal weight measurements. Macdonald-W allis. W eig ht gain and blood pressure in pregnancy . A m J Obstet G ynecol 2013.
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(Estimates of these parameters are shown in Supplementary Table 2.)

In the second stage, we used the bivariate multilevel models to derive associations of prepregnancy weight and GWG (exposures) with blood pressure change (outcome),26adjusting for ma-ternal height, age, parity, smoking, edu-cation, and offspring sex in model 1. In model 2 we additionally adjusted for baseline weight and SBP/DBP and GWG and SBP/DBP changes in periods of pregnancy prior to the exposure period. We then conceptualized GWG as the outcome with changes in blood pressure as a potential risk factor. We therefore derived associations of GWG in each period of gestation (outcome) with SBP/ DBP at 8 weeks and SBP/DBP change in previous periods of gestation (exposure). We adjusted for maternal character-istics in model 1. In model 2 we addi-tionally adjusted for baseline weight and SBP/DBP, GWG, and the SBP/DBP change in all periods prior to the expo-sure period and GWG in the expoexpo-sure period.

We completed sensitivity analyses, restricting to women who contributed at least 8 measurements of blood pressure and weight to the bivariate models (n¼ 6666), and second, restricting to women who contributed no more than 11 mea-surements (n¼6135). Thefindings were not meaningfully changed from those in the main analyses. We also performed a sensitivity analysis using an 8 week baseline for weight.

Statistical analyses were carried out using MLwiN version 2.25, STATA version 12.1 and runmlwin27 and reffadjust28 Stata commands (StataCorp, College Station, TX).

R

ESULTS

The characteristics of women in the full dataset, and subsets with complete data for each analysis, by categories of HDP are shown inTable 1, and distributions of prepregnancy BMI and early-pregnancy

GWG are shown in Supplementary

Figures 1and 2, respectively. Each sub-set had similar characteristics to the full dataset.

Nulliparous women, nonsmokers, and women aged over 35 years were more

likely to develop HDP (Supplementary Table 3). Gaining more than the IOM recommended weight was associated with an increased risk of gestational hy-pertension and preeclampsia compared with gaining within the recommended range (Figure; odds ratio [OR], 1.51; 95% confidence interval [CI], 1.32e1.73

and OR, 2.14; 95% CI, 1.46e3.12,

respectively). Also, lower than IOM-recommended GWG was associated with a reduced risk of gestational hyper-tension (OR, 0.75; 95% CI, 0.62e0.91) and preeclampsia (OR, 0.70; 95% CI, 0.38e1.27) compared with GWG within the recommended range (although the confidence interval was wide for pre-eclampsia and included the null). Early-pregnancy GWG and risk of HDP A higher prepregnancy weight was associated with an increased risk of developing gestational hypertension and preeclampsia (Table 2). This association was nonlinear, with evidence of a stronger association between prepreg-nancy weight and gestational hyperten-sion for women who weighed 90 kg or less than for those who weighed more than 90 kg before pregnancy, although associations with preeclampsia were similar in each group.

After adjustment for prepregnancy weight, greater early-pregnancy GWG was independently associated with an increased risk of developing gestational hypertension and preeclampsia (per 200 g/wk increase in GWG up to 18 weeks: OR, 1.26; 95% CI, 1.16e1.38

and OR, 1.31; 95% CI, 1.07e1.62,

respectively).

Thesefindings are further illustrated by Table 3, which shows the predicted probabilities of developing gestational hypertension or preeclampsia for dif-ferent prepregnancy weights and rates of early-pregnancy GWG. This shows clearly that, even among women with healthy prepregnancy weights (eg, 50 or 60 kg), those who gain more weight have important increases in the risk of gestational hypertension and pre-eclampsia. We found no evidence that associations of GWG up to 18 weeks with the risk of gestational hyperten-sion and preeclampsia differed by

prepregnancy BMI category (Pvalue for interaction¼.18).

Associations of prepregnancy weight and GWG with subsequent blood pressure change in normotensive women

Analysis of the mean differences in SBP and DBP change for a 200 g/wk increase in GWG in the same and preceding period of gestation are shown inTable 4. For completeness, associations of all possible combinations of prepregnancy weight and GWG in each gestational period with later SBP and DBP changes

are also shown in Supplementary

Tables 4and5, respectively.

In each period of pregnancy, GWG was positively associated with the changes in SBP and DBP that occurred during the same gestational period (Table 4). In addition, an increase in GWG in early pregnancy (up to 18 weeks) was associ-ated with a greater increase in SBP and DBP in the subsequent period of gestation (midpregnancy: 18-29 weeks) (Table 4). However, greater GWG in early pregnancy was also associated with a smaller increase in SBP and DBP in late pregnancy (Supplementary Tables 4and5). GWG in midpregnancy (18-29 weeks) was not associated with SBP or DBP change in late pregnancy (29-36 weeks) (Table 4).

Associations of blood pressure changes with subsequent GWG To assess whether rises in blood pressure may precede increases in edema and thus weight gain, even in these normotensive women, we also examined associations of changes in SBP and DBP with subsequent GWG (Table 5). All possible associations of baseline SBP and DBP and changes in SBP and DBP with GWG in later periods of gestation are shown inSupplementary Table 6. In fully-adjusted models, there were no associations between SBP or DBP change and GWG in subsequent periods of pregnancy. There was evidence of positive associations between SBP and DBP at baseline and GWG in early

pregnancy (Supplementary Table 6).

However, when we repeated the bivariate analyses with the baseline set at 8 weeks for weight, neither SBP nor DBP at

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baseline was associated with GWG in early pregnancy after adjustment for baseline weight (no otherfindings were changed in this sensitivity analysis).

C

OMMENT

In this large cohort, greater prepregnancy weight and GWG in early pregnancy were both independently associated with an increased risk of gestational hyper-tension and preeclampsia. We also found that, in normotensive women, gaining

more weight in early pregnancy was associated with a greater increase in blood pressure in the subsequent pe-riod of gestation. In addition, in each period of gestation, GWG was posi-tively associated with the change in blood pressure during the same gesta-tional period. These associations are unlikely to be explained by blood pressure increases leading to increased edema because we found little evi-dence that blood pressure changes

were associated with subsequent GWG in any period of pregnancy in these women.

The review of outcomes associated with GWG by Viswanathan et al15did not

find any strong evidence of an association of GWG with risk of HDP. Although the majority of studies reviewed reported a positive association, the review authors noted that the number of studies was limited and most were assessed to be of weak design.15Since the review, 2 studies have reported a positive relationship of excess GWG according to 1990 IOM recommendations with a risk of HDP

in 5377 Canadian29 and 1043 Latina

women,30 respectively, and others have reported positive associations between

net GWG and HDP risk.12,13 However,

because IOM criteria combine prepreg-nancy BMI and GWG over the whole of pregnancy, it is not possible using these criteria to distinguish the impact of pre-pregnancy BMI from GWG, and none of the studies have addressed whether it is edema associated with HDP that is driving the association.

Our study was limited by the use of routinely collected clinic blood pressure and weight measurements, which is likely to produce random measurement error but unlikely to introduce bias. It also has the advantage that our results could be translated into clinical practice if they are replicated because the mea-sures represent those obtained in clinical practice. Women who develop pre-eclampsia have reduced plasma volume FIGURE

ORs (95% CI) for gestational hypertension and preeclampsia associated

with IOM categories of total weight gain (n

[

9596)

a

CI, confidence interval;IOM, Institute of Medicine;OR, odds ratio.

aAdjusted value for maternal prepregnancy body mass index, age, parity, smoking, education, and offspring sex.

Macdonald-Wallis. Weight gain and blood pressure in pregnancy. Am J Obstet Gynecol 2013.

TABLE 2

Associations of prepregnancy weight and early-pregnancy GWG with HDP (n

[

9536)

a

Exposure variablesb Subgroup

Gestational hypertension Preeclampsia OR 95% CI OR 95% CI

Prepregnancy weight (10 kg) 90 kg prepregnancy weight 1.80 1.70e1.91 1.71 1.49e1.95 >90 kg prepregnancy weight 1.24 1.03e1.49 1.61 1.18e2.19 GWG up to 18 weeks (200 g/wk) All women 1.27 1.16e1.38 1.31 1.07e1.61

CI, confidence interval;GWG, gestational weight gain;HDP, hypertensive disorders of pregnancy;OR, odds ratio.

aBoth models are adjusted for maternal height (continuous; centered around the mean of 164 cm); age (reference, 25-29 years); parity (reference, nulliparous); smoking (reference, never smoked); education (reference, O level); and offspring sex (reference, male). The model with GWG up to 18 weeks as the exposure is additionally adjusted for prepregnancy weight (2 linear splines:90 kg and>90 kg);bPrepregnancy weight and GWG up to 18 weeks were obtained using the residuals from a linear multilevel model for weight change up to 18 weeks’ gestation. Because of strong evidence for nonlinear associations between prepregnancy weight and these outcomes, results are presented for subgroups of women in whom magnitudes of associations differ.

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expansion in early pregnancy compared with women who remain normoten-sive.17,31,32 However, studies have sug-gested that this is due to increased capillary permeability and a redistribu-tion of plasma to interstitial fluid.32,33

We were unable to account for plasma volume expansion in our analyses, but any bias in our findings resulting from the reduction in plasma volume would be expected to attenuate associations toward the null.

The study’s strengths are its large size, inclusion of women with a range of BMIs, the high number of repeated weight and blood pressure measure-ments, and longitudinal modeling of GWG and blood pressure changes in different periods of pregnancy. Because of the repeat measurements of blood pressure and proteinuria, we were able to apply a standard international definition of HDP to all women and not rely on clinical diagnoses.

Outside pregnancy, greater body mass is an established risk factor for high blood pressure,34,35and therefore, the associa-tion of greater GWG in early pregnancy with HDP and of GWG throughout pregnancy with blood pressure increases in women without HDP may reflect the effect of greater maternal pregnancy adiposity acquisition on blood pressure.36

Also, markers of inflammation,

interleukin-6 and C-reactive protein, are increased in obese pregnant women, and

this inflammation may contribute to

endothelial dysfunction.37 Infl amma-tion, measured by C-reactive protein concentrations, has been found in 1 study to mediate the association between prepregnancy BMI and preeclampsia risk.38In our study, we were unable to examine this mechanism. Alternatively, these associations may be partly ex-plained by biological changes related to

pregnancy influencing both GWG and

blood pressure change or from an TABLE 3

Predicted probabilities of HDP by prepregnancy weight and

early-pregnancy GWG (n

[

9536)

a Prepregnancy weight, kg GWG up to 18 wks, g/wk Probability of gestational hypertension, % (SE) Probability of Preeclampsia, % (SE) 50 200 11.5 (0.9) 1.8 (0.4) 400 14.1 (1.0) 2.3 (0.5) 600 17.0 (1.4) 2.9 (0.7) 60 200 19.4 (1.2) 2.9 (0.5) 400 23.2 (1.4) 3.6 (0.6) 600 27.3 (2.0) 4.4 (1.0) 70 200 30.7 (1.7) 4.4 (0.8) 400 35.4 (1.9) 5.3 (1.0) 600 40.4 (2.6) 6.2 (1.5) 80 200 44.2 (2.3) 6.0 (1.2) 400 49.3 (2.5) 7.0 (1.5) 600 54.1 (3.2) 7.9 (2.1) 90 200 57.9 (2.8) 7.5 (1.8) 400 62.3 (3.0) 8.4 (2.1) 600 66.1 (3.6) 9.2 (2.8)

GWG, gestational weight gain;HDP, hypertensive disorders of pregnancy;SE, standard error. a

Predicted probabilities are for a woman of average height (164 cm), age (25-29 years), nulliparous, having never smoked during pregnancy, O level educational qualification, and having a male offspring.

Macdonald-Wallis. Weight gain and blood pressure in pregnancy. Am J Obstet Gynecol 2013.

TABLE 4

Associations of GWG with subsequent blood pressure change (n

[

7975)

a,b

Exposure Average weight change (200 g/wk)

Outcome

Average SBP/DBP change (mm Hg/wk) in the same and subsequent periods of gestation

SBP change DBP change Mean difference 95% CI Mean Difference 95% CI Early pregnancy (0-18 wks)

Same period Early pregnancy (8-18 wks) 0.06 (0.02e0.10) 0.03 (0.00e0.05) Subsequent period Midpregnancy (18-29 wks) 0.04 (0.00e0.07) 0.03 (0.00e0.05) Midpregnancy

(18-29 wks)

Same period Midpregnancy (18-29 wks) 0.09 (0.06e0.12) 0.04 (0.01e0.06) Subsequent period Late pregnancy (29-36 wks) 0.00 (e0.06 to 0.06) 0.01 (e0.03 to 0.06) Late pregnancy

(29 wks)

Same period (2 parts) Late pregnancy (29-36 wks) 0.11 (0.06e0.16) 0.08 (0.04e0.12) Very late pregnancy (36 wks) 0.14 (0.03e0.25) 0.10 (0.01e0.18)

CI, confidence interval;DBP, diastolic blood pressure;GWG, gestational weight gain;SBP, systolic blood pressure.

aAdjusted for maternal height, age, parity, smoking, education, and offspring sex; prepregnancy weight; SBP/DBP at baseline; and weight and SBP/DBP change prior to the exposure period (equivalent to model 2 inSupplementary Tables 4and5);bEstimates were obtained from 2 bivariate multilevel spline models: one including all of the women’s weight and SBP measurements across pregnancy and the other including all of the women’s weight and DBP measurements across pregnancy, restricting to women who had normotensive pregnancies.

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underlying predisposition to obesity and cardiovascular risk.39

Although our observational data are not able to prove causality, they are a step change from the previous publications and demonstrate temporality by showing that GWG precedes the development of HDP and also a greater increase in blood pressure.

We have also adjusted for a wide range of potential confounders in our analyses. If GWG does have a causal influence on blood pressure change, the potential im-plications are that limiting GWG in pregnancy may be able to both reduce the incidence of HDP and the severity in those who develop HDP. A recent systematic review and metaanalysis of pregnancy interventions aimed at managing weight gain estimated a 33% reduction in the risk of preeclampsia and a 70% reduction in the risk of gestational hypertension had been achieved through interventions that limited GWG.18 However, the 2 largest included studies, which drove the associ-ations, included only women at high risk for gestational diabetes and an inter-vention aimed at preventing its develop-ment. Hence, it is unclear whether the decreased risk of HDP was achieved through the monitoring and management of gestational diabetes because the con-ditions are strongly linked.11

The clinical significance of ourfindings is indicated by the potential risk reduc-tion for preeclampsia that could be

achieved by optimizing GWG. Our results show that the risk of gestational hyper-tension and preeclampsia is markedly lower in women with lower GWG in all strata of prepregnancy weight (Table 3).

These results combined with evidence from recent trials showing that lifestyle interventions can effectively limit GWG, show the potential to prevent HDP by targeting GWG. Furthermore, the risk reduction that might be achieved by targeting GWG compares favorably with the relative risk reduction of 0.75 (95% CI, 0.66e0.85) observed with antiplate-let agents for the risk of preeclampsia and may be independent of this.6

How-ever, any benefits of limiting GWG

in terms of reducing HDP risk should be balanced with the potential adverse effects because there is evidence of an increased risk of preterm birth and small-for-gestational-age offspring at the lower end of the GWG distribution.15 We were unable to assess the optimum levels of GWG required to achieve this balance in this study.

In summary, we found that greater GWG up to 18 weeks, independently of prepregnancy weight, was associated with a greater risk of developing HDP and in normal pregnancy was associated with a greater midpregnancy rise in blood pressure. GWG in all periods of gestation were positively associated with concur-rent rises in blood pressure. This suggests that interventions aimed at limiting

GWG from early pregnancy onward may have the potential to reduce the incidence of gestational hypertension and pre-eclampsia. Our results support estab-lishing randomized trials in nonspecific populations to assess the effectiveness of such interventions in the prevention of

these disorders.

-ACKNOWLEDGMENTS

We are extremely grateful to all of the families who took part in this study, the midwives for their help in recruiting them, and the whole ALSPAC team, which includes interviewers, computer and laboratory technicians, clerical workers, research scientists, volunteers, managers, re-ceptionists, and nurses.

REFERENCES

1.Lewis G, ed. The Confidential Enquiry into

Maternal and Child Health (CEMACH). Saving

mothers’ lives: reviewing maternal deaths to

make motherhood safer, 2003-2005. The

Sev-enth Report on Condential Enquiries into

Maternal Deaths in the United Kingdom. London

(UK): Confidential Enquiry into Maternal and

Child Health; 2007.

2.Steegers EA, von Dadelszen P, Duvekot JJ,

Pijnenborg R. Pre-eclampsia. Lancet 2010;376:

631-44.

3.Duley L. The global impact of pre-eclampsia

and eclampsia. Semin Perinatol 2009;33:130-7.

4.Hauth JC, Ewell MG, Levine RJ, et al.

Preg-nancy outcomes in healthy nulliparas who

developed hypertension. Obstet Gynecol

2000;95:24-8.

5.Buchbinder A, Sibai BM, Caritis S, et al.

Adverse perinatal outcomes are significantly

TABLE 5

Associations of blood pressure changes with subsequent GWG (n

[

7975)

a,b

Exposure Average SBP/DBP change (mm Hg/wk)

Outcome

Average weight change (200 g/wk) in the subsequent period of gestation

Mean

difference 95% CI

SBP change

Early pregnancy (8-18 wks) Subsequent period Midpregnancy (18-29 wks) 0.06 (e0.06 to 0.18) Midpregnancy (18-29 wks) Subsequent period Late pregnancy (29 wks) e0.01 (e0.17 to 0.15) DBP change

Early pregnancy (8-18 wks) Subsequent period Midpregnancy (18-29 wks) 0.02 (e0.18 to 0.24) Midpregnancy (18-29 wks) Subsequent period Late pregnancy (29 wks) 0.14 (e0.07 to 0.36)

CI, confidence interval;DBP, diastolic blood pressure;SBP, systolic blood pressure.

aAdjusted for maternal height, age, parity, smoking, education, and offspring sex; prepregnancy weight; SBP/DBP at baseline; weight; and SBP/DBP change in all periods of pregnancy prior to the exposure period and weight change in the exposure period (equivalent to model 2 inSupplementary Table 6);bEstimates were obtained from 2 bivariate multilevel spline models: one including all of the women’s weight and SBP measurements across pregnancy and the other including all of the women’s weight and DBP measurements across pregnancy, restricting to women who had normotensive pregnancies.

(9)

higher in severe gestational hypertension than in mild preeclampsia. Am J Obstet Gynecol 2002;

186:66-71.

6.National Institute for Health and Clinical Excellence. Hypertension in pregnancy: NICE Clinical Guideline CG107. 2010. Available at:

http://guidance.nice.org.uk/CG107. Accessed

March 20, 2013.

7.Thadhani R, Stampfer MJ, Hunter DJ,

Manson JE, Solomon CG, Curhan GC. High body mass index and hypercholesterolemia: risk of hypertensive disorders of pregnancy. Obstet

Gynecol 1999;94:543-50.

8.Duckitt K, Harrington D. Risk factors for

peclampsia at antenatal booking: systematic

re-view of controlled studies. BMJ 2005;330:565-7.

9.Poon LCY, Kametas NA, Maiz N, Akolekar R,

Nicolaides KH. First-trimester prediction of hy-pertensive disorders in pregnancy.

Hyperten-sion 2009;53:812-8.

10.O’Brien TE, Ray JG, Chan WS. Maternal

body mass index and the risk of preeclampsia: a systematic overview. Epidemiology 2003;14:

368-74.

11.Lawlor DA, Relton C, Sattar N, Nelson SM.

Maternal adiposity-a determinant of perinatal and offspring outcomes? Nat Rev Endocrinol

2012;8:679-88.

12.Heude B, Thiebaugeorges V, Goua V, et al.

Pre-pregnancy body mass index and weight gain during pregnancy: relations with gestational diabetes and hypertension, and birth outcomes.

Matern Child Health J 2012;16:355-63.

13.Gaillard R, Steegers EAP, Hofman A,

Jaddoe VWV. Associations of maternal obesity with blood pressure and the risks of gestational hypertensive disorders. The Generation R Study.

J Hypertens 2011;29:937-44.

14.Beyerlein A, Schiessl B, Lack N, von Kries R.

Associations of gestational weight loss with birth-related outcome: a retrospective cohort

study. Br J Obstet Gynaecol 2011;118:55-61.

15.Viswanathan M, Siega-Riz A, Moos MK,

et al. Outcomes of maternal weight gain. Evi-dence Report/Technology Assessment Num-ber168. AHRQ Publication Number 08-E009. Rockville (MD): Agency for Healthcare Research

and Quality; 2008.

16.Thomson AM, Hytten FE, Billewicz WZ. The

epidemiology of oedema during pregnancy. J Obstet Gynaecol Br Commonw 1967;74:

1-10.

17.IOM (Institute of Medicine) and NRC

(Na-tional Research Council). Weight gain during pregnancy: reexamining the guidelines. Wash-ington, DC: The National Academies Press;

2009.

18.Thangaratinam S, Rogozinska E, Jolly K,

et al. Effects of interventions in pregnancy on maternal weight and obstetric outcomes: meta-analysis of randomised evidence. Br Med J

2012;344:e2088.

19.Crowther CA, Hiller JE, Moss JR,

Mcphee AJ, Jeffries WS, Robinson JS. Effect of treatment of gestational diabetes mellitus on

pregnancy outcomes. N Engl J Med 2005;352:

2477-86.

20.Landon MB, Spong CY, Thom E, et al.

A multicenter, randomized trial of treatment for mild gestational diabetes. N Engl J Med 2009;

361:1339-48.

21.Macdonald-Wallis C, Tilling K, Fraser A,

Nelson SM, Lawlor DA. Established pre-eclampsia risk factors are related to patterns of blood pressure change in normal term

preg-nancy: findings from the Avon Longitudinal

Study of Parents and Children (ALSPAC).

J Hypertens 2011;29:1703-11.

22.Robertson EG. The natural history of

oedema during pregnancy. J Obstet Gynaecol

Br Commonw 1971;78:520-9.

23.Fraser A, Macdonald-Wallis C, Tilling K, et al.

Cohort profile: The Avon Longitudinal Study of

Parents and Children: ALSPAC mothers cohort.

Int J Epidemiol 2013;42:97-110.

24.Brown MA, Lindheimer MD, de Swiet M,

Van Assche A, Moutquin JM. The classification

and diagnosis of the hypertensive disorders of pregnancy: statement from the International Society for the Study of Hypertension in Preg-nancy (ISSHP). Hypertens PregPreg-nancy 2001;20:

IX-XIV.

25.Fraser A, Tilling K, Macdonald-Wallis C,

Hughes R, et al. Associations of gestational weight gain with maternal body mass index,

waist circumference, and blood pressure

measured 16 y after pregnancy: the Avon Lon-gitudinal Study of Parents and Children. Am J

Clin Nutr 2011;93:1285-92.

26.Macdonald-Wallis C, Lawlor DA, Palmer T,

Tilling K. Multivariate multilevel spline models for parallel growth processes: application to weight and mean arterial pressure in pregnancy. Stat

Med 2012;31:3147-64.

27.Leckie G, Charlton C. runmlwin: Stata

module forfitting multilevel models in the MLwiN

software package. Bristol (UK): Centre for

Multilevel Modelling, University of Bristol; 2011.

28.Palmer T, Macdonald-Wallis C. REFFAD-JUST: Stata module to estimate adjusted regression coefficients for the association be-tween two random effects variables. 2012. Available at: http://ideas.repec.org/c/boc/

bocode/s457403.html. Accessed March 20,

2013.

29.Crane JM, White J, Murphy P, Burrage L,

Hutchens D. The effect of gestational weight gain by body mass index on maternal and neonatal outcomes. J Obstet Gynaecol Can

2009;31:28-35.

30.Fortner RT, Pekow P, Solomon CG,

Markenson G, Chasan-Taber L. Prepregnancy body mass index, gestational weight gain, and risk of hypertensive pregnancy among Latina women. Am J Obstet Gynecol 2009;200:167.

e1-7.

31.Gallery ED. Pregnancy-associated

hyper-tension: interrelationships of volume and blood pressure changes. Clin Exp Hypertens B

1982;1:39-47.

32.Brown MA, Zammit VC, Mitar DM.

Extra-cellularuid volumes in pregnancy-induced

hy-pertension. J Hypertens 1992;10:61-8.

33.Brown MA, Zammit VC, Lowe SA. Capillary

permeability and extracellular fluid volumes in

pregnancy-induced hypertension. Clin Sci

1989;77:599-604.

34.Stamler R, Stamler J, Riedlinger WF,

Algera G, Roberts RH. Weight and

blood-pressurefindings in hypertension screening of

1 million Americans. JAMA 1978;240:1607-10.

35.Yong LC, Kuller LH, Rutan G, Bunker C.

Longitudinal study of blood pressure—changes

and determinants from adolescence to middle

age: the Dormont-High-School

Follow-Up-Study, 1957-1963 to 1989-1990. Am J

Epi-demiol 1993;138:973-83.

36.Nelson SM, Matthews P, Poston L. Maternal

metabolism and obesity: modiable

de-terminants of pregnancy outcome. Hum Reprod

Update 2010;16:255-75.

37.Ramsay JE, Ferrell WR, Crawford L,

Wallace AM, Greer IA, Sattar N. Maternal obesity is associated with dysregulation of metabolic,

vascular, and inflammatory pathways. J Clin

Endocrinol Metab 2002;87:4231-7.

38.Bodnar LM, Ness RB, Harger GF,

Roberts JM. Inflammation and triglycerides

partially mediate the effect of prepregnancy body mass index on the risk of preeclampsia.

Am J Epidemiol 2005;162:1198-206.

39.Callaway LK, Mclntyre HD, O’Callaghan M,

Williams GM, Najman JM, Lawlor DA. The as-sociation of hypertensive disorders of pregnancy with weight gain over the subsequent 21 years:

findings from a prospective cohort study. Am J

Epidemiol 2007;166:421-8.

A

PPENDIX

Supplemental Methods

Development of the bivariate linear spline random-effects models

The data were divided into 2 week in-tervals by gestational age, starting from 4 weeks’gestation, and in cases in which an individual had multiple weight or blood pressure measurements within any 2 week interval, 1 weight and 1 blood pressure measurement was chosen at random from this interval for inclusion in the sample for analysis. This was to prevent individuals with a high number of antenatal visits from having too great an influence on the models. After this process, there remained a median of 10 weight measurements per woman, with a range of 1e17, and a median of 10 blood pressure measurements per woman, with a range of 1e17.

(10)

Univariate linear spline models have previously beenfitted to systolic blood pressure (SBP), diastolic blood pressure (DBP)1 and weight.2 Separate models were fitted with SBP, DBP, and weight as the outcome variables (Y), and for each model, gestational age in weeks was used as the exposure variable (X). The models had 2 levels: antenatal visit and individual because there were multiple antenatal visits per woman. The knot points (indicating changes in slope) for these models were deter-mined by initially fitting fractional

polynomial curves3 to each of SBP,

DBP, and weight to describe the shape of the average patterns of change with gestational age. Models with 2 or 3

knots were considered and the final

positioning and number of knots was selected as that which optimally

ful-filled the criteria of a high model log likelihood, a close fit to the fractional polynomial curve, and good fit of the model predicted values to observed values over the whole course of preg-nancy. The best-fitting models for both SBP and DBP had 3 knots at 18, 30, and 36 weeks’gestation, and the model for weight had 2 knots at 18 and 28 weeks’ gestation. Each contained individual-level random effects for the intercept and each of the splines.

Because the second knot point for SBP and DBP (at 30 weeks) was in a similar

location to the second knot for weight (28 weeks), for the bivariate spline models, we shifted this knot point 1 week earlier for SBP and DBP and 1 week later for weight and used knots at 18, 29, and 36 weeks for SBP and DBP and knots at 18 and 29 weeks for weight. This was for simplicity and interpretability so that thefirst 2 periods of blood pres-sure change and gestational weight gain (GWG) had the same endpoints and did not substantially alter the fit of the models.

Few measurements were available prior to 8 weeks so the baseline was set at 8 weeks’gestation for SBP and DBP

because blood pressure begins to

decrease early in pregnancy but was set at 0 weeks for weight because weight changes little in very early pregnancy. The coefficients from these unadjusted bivariate models model are shown in Supplementary Table 2.

We then added the maternal charac-teristics of height (continuous), age (<20, 20-24, 25-29, 30-34, 35 years), parity

(nulliparous, multiparous), smoking

(never, before pregnancy/first trimester/ throughout pregnancy), education (cer-tificate of secondary education [CSE]/ vocational, O level, A level, degree), and offspring sex (male/female) into each of these models as main effects and in-teractions with each of the splines, with separate effects for SBP/DBP and weight.

Derivation of associations of changes in weight with changes in blood pressure from the bivariate multilevel spline models

We derived associations of the weight and GWG parameters with baseline SBP/ DBP and SBP/DBP change parameters using the variance-covariance matrix of random effects from each of the models using formulae described by

Macdonald-Wallis et al4 implemented

using the REFFADJUST package in STATA (StataCorp, College Station, TX).5 Adjustment for previous GWG and

SBP/DBP changes was also made

using the variance-covariance matrix of random effects. Because the variances and covariances of the random effects were estimated with uncertainty in the bivariate models, for both of the models, we generated 10,000 realizations of each of the variances and covariances of the random effects from a multivariate normal distribution using the means, variances, and covariances of these estimates calculated by the bivariate random-effects models. We then aver-aged regression coefficients over the 10,000 realizations and formed 95% confidence intervals for the regression coefficients using the 2.5th and 97.5th percentiles of the distributions of these regression coefficients over the 10,000 realizations to fully incorporate the un-certainty in the estimation procedure.4

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SUPPLEMENTARY TABLE 2

Blood pressure and weight parameters from unadjusted bivariate models (n

[

9855)

Blood pressure/weight variable Mean Between-individual SD 95% CI reference range

SBP and weight model

SBP at 8 wks, mm Hg 111.00 7.75 (95.82e126.18) SBP change, mm Hg/wk 8-18 wks e0.177 0.601 (e1.356 to 1.001) 18-29 wks 0.133 0.449 (e0.747 to 1.014) 29-36 wks 0.177 0.625 (e1.048 to 1.401) 36 wks 0.967 1.119 (e1.227 to 3.161) Prepregnancy weight, kg 59.11 11.33 (36.90e81.32) Weight change, kg/wk 0-18 wks 0.317 0.228 (e0.129 to 0.763) 18-29 wks 0.525 0.190 (0.154e0.897) 29 wks 0.448 0.213 (0.030e0.865) DBP and weight model

DBP at 8 wks, mm Hg 65.39 5.48 (54.65e76.13) DBP change, mm Hg/wk 8-18 wks e0.204 0.410 (e1.008 to 0.599) 18-29 wks 0.078 0.326 (e0.560 to 0.717) 29-36 wks 0.313 0.516 (e0.698 to 1.324) 36 wks 1.082 1.008 (e0.893 to 3.058) Prepregnancy weight, kg 59.11 11.33 (36.90e81.32) Weight change, kg/wk 0-18 wks 0.317 0.228 (e0.129 to 0.763) 18-29 wks 0.525 0.190 (0.154e0.897) 29 wks 0.448 0.213 (0.030e0.865)

CI, confidence interval;DBP, diastolic blood pressure;SBP, systolic blood pressure;SD, standard deviation.

Macdonald-Wallis. Weight gain and blood pressure in pregnancy. Am J Obstet Gynecol 2013.

SUPPLEMENTARY TABLE 1

IOM-recommended total GWG by prepregnancy BMI category

Prepregnancy BMI category Recommended absolute weight gain, kg

Underweight (<18.5 kg/m2) 12.5-18 Normal weight (18.5-24.9 kg/m2) 11.5-16 Overweight (25.0-29.9 kg/m2) 7-11.5 Obese (30.0 kg/m2) 5-9

BMI, body mass index;GWG, gestational weight gain;IOM, Institute of Medicine.

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SUPPLEMENTARY TABLE 3

Associations of maternal characteristics with HDP

Maternal characteristic

Gestational hypertension Preeclampsia

Unadjusted Mutually adjusted Unadjusted Mutually adjusted

Height (per cm) (n¼11002) 1.02 (1.01e1.03) 1.02 (1.01e1.03) 0.98 (0.96e1.00) 0.98 (0.96e1.00) Age (n¼12,522), y <20 0.77 (0.59e0.99) 0.58 (0.40e0.82) 1.76 (1.11e2.79) 1.09 (0.54e2.20) 20-24 1.13 (0.99e1.29) 1.13 (0.96e1.32) 1.53 (1.13e2.08) 1.86 (1.30e2.66) 25-29 1 1 1 1 30-34 0.87 (0.77e0.99) 0.97 (0.84e1.11) 0.71 (0.50e1.00) 0.86 (0.58e1.27) 35 1.07 (0.90e1.28) 1.20 (0.98e1.46) 1.48 (1.01e2.18) 1.90 (1.20e3.02) Parity (n¼11,623) Nulliparous 1 1 1 1 Multiparous 0.56 (0.50e0.62) 0.53 (0.48e0.60) 0.30 (0.23e0.40) 0.28 (0.20e0.38) Smoking in pregnancy (n¼11,740) Never 1 1 1 1

Before pregnancy/first trimester 1.02 (0.88e1.18) 0.91 (0.78e1.08) 1.06 (0.76e1.49) 0.94 (0.65e1.36) Throughout 0.68 (0.59e0.79) 0.67 (0.57e0.79) 0.39 (0.26e0.60) 0.31 (0.18e0.53) Highest qualification (n¼11,202) CSE/vocational 0.90 (0.79e1.02) 1.01 (0.88e1.16) 0.85 (0.62e1.18) 0.98 (0.69e1.39) O Level 1 1 1 1 A Level 0.88 (0.76e1.01) 0.82 (0.70e0.95) 0.96 (0.68e1.34) 0.90 (0.63e1.30) Degree 0.94 (0.80e1.11) 0.81 (0.67e0.97) 0.83 (0.54e1.28) 0.82 (0.51e1.32) Offspring sex (n¼12,522) Male 1 1 1 1 Female 0.93 (0.84e1.02) 0.92 (0.82e1.03) 0.98 (0.77e1.24) 0.94 (0.71e1.23)

CI, confidence interval;CSE, Certificate of Secondary Education;HDP, hypertensive disorders of pregnancy;OR, odds ratio.

(13)

Associations of prepregnancy weight and GWG with subsequent SBP change (n

[

7975)

Weight variable SBP at 8 wks, mm Hg Average SBP change, mm Hg/wk Early pregnancy (8-18 wks) Mid-pregnancy (18-29 wks) Late pregnancy (29-36 wks)

Very late pregnancy (‡36 wks) Mean difference 95% CI Mean difference 95% CI Mean difference 95% CI Mean difference 95% CI Mean difference 95% CI Prepregnancy weight (10 kg) Model 1 2.01 (1.70e2.33) 0.04 (0.00e0.08) e0.07 (e0.09 toe0.04) 0.02 (e0.02 to 0.06) e0.05 (e0.12 to 0.02) Average weight change

(200 g/wk)

Early pregnancy (0-18 wks) Model 1 0.02 (e0.02 to 0.07) 0.05 (0.02e0.08) e0.09 (e0.14 toe0.04) 0.07 (e0.02 to 0.16) Model 2 0.06 (0.02e0.10) 0.04 (0.00e0.07) e0.10 (e0.15 toe0.05) 0.07 (e0.02 to 0.16) Midpregnancy (18-29 wks) Model 1 0.10 (0.07e0.14) e0.03 (e0.08 to 0.02) 0.07 (e0.02 to 0.16) Model 2 0.09 (0.06e0.12) 0.00 (e0.06 to 0.06) 0.04 (e0.06 to 0.14) Late pregnancy (29 wks) Model 1 0.08 (0.03e0.12) 0.13 (0.05e0.21)

Model 2 0.11 (0.06e0.16) 0.14 (0.03e0.25)

CI, confidence interval;GWG, gestational weight gain;SBP, systolic blood pressure.

aModel 1 was adjusted for maternal height, age, parity, smoking, education, and offspring sex. Model 2 was adjusted also for prepregnancy weight and SBP at 8 weeks (except for models with prepregnancy weight as the exposure) and GWG and SBP change prior to the exposure period.

Macdonald-Wallis. Weight gain and blood pressure in pregnancy. Am J Obstet Gynecol 2013.

Obstetrics

Research

OCTOBER 2013 American Journal of Obstetrics & Gynecolo gy 327.e13
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SUPPLEMENTARY TABLE 5

Associations of prepregnancy weight and GWG with subsequent DBP change (n

[

7975)

a

Weight variable DBP at 8 wks, mm Hg Average DBP change, mm Hg/wk Early pregnancy (8-18 wks) Midpregnancy (18-29 wks) Late pregnancy (29-36 wks)

Very late pregnancy (‡36 wks) Mean difference 95% CI Mean difference 95% CI Mean difference 95% CI Mean difference 95% CI Mean difference 95% CI Prepregnancy weight (10 kg) Model 1 1.58 (1.35e1.81) 0.01 (e0.02 to 0.04) e0.05 (e0.07 toe0.03) 0.02 (e0.01 to 0.05) e0.04 (e0.09 to 0.02) Average weight change

(200 g/wk)

Early pregnancy (0-18 wks) Model 1 0.01 (e0.03 to 0.04) 0.04 (0.02e0.06) e0.04 (e0.08 toe0.01) 0.01 (e0.06 to 0.08) Model 2 0.03 (0.00e0.05) 0.03 (0.00e0.05) e0.05 (e0.08 toe0.01) 0.01 (e0.07 to 0.08) Midpregnancy (18-29 wks) Model 1 0.05 (0.02e0.07) 0.00 (e0.04 to 0.03) 0.03 (e0.04 to 0.10) Model 2 0.04 (0.01e0.06) 0.01 (e0.03 to 0.06) 0.01 (e0.07 to 0.10)

Late pregnancy (29 wks) Model 1 0.05 (0.02e0.08) 0.08 (0.02e0.15)

Model 2 0.08 (0.04e0.12) 0.10 (0.01e0.18)

CI, confidence interval;DBP, diastolic blood pressure;GWG, gestational weight gain.

aModel 1 was adjusted for maternal height, age, parity, smoking, education, and offspring sex. Model 2 was also adjusted for prepregnancy weight and DBP at 8 weeks (except for models with prepregnancy weight as the exposure) and GWG and DBP change prior to the exposure period.

Macdonald-Wallis. Weight gain and blood pressure in pregnancy. Am J Obstet Gynecol 2013.

Obstetrics

www.AJOG

.org

American Journal of Obstetrics & Gynecology OCTOBER 2013
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SUPPLEMENTARY TABLE 6

Associations of baseline blood pressure and changes in blood pressure with subsequent GWG (n

[

7975)

a

Blood pressure variable

Mean difference in average weight change, 200 g/wk

Early pregnancy (0-18 wks) Mid-pregnancy (18-29 wks) Late pregnancy (‡29 wks)

SBP at 8 wks (baseline), 5 mm Hg

Model 1 e0.05 (e0.08 toe0.01) e0.04 (e0.07 toe0.02) e0.02 (e0.05 to 0.02) Model 2 0.04 (e0.00 to 0.07) e0.02 (e0.05 to 0.01) e0.01 (e0.05 to 0.02) SBP change, mm Hg/wk

Early pregnancy (8-18 wks) Model 1 0.08 (e0.03 to 0.20) 0.05 (e0.08 to 0.18) Model 2 0.06 (e0.06 to 0.18) 0.03 (e0.09 to 0.16) Midpregnancy (18-29 wks) Model 1 0.21 (0.07e0.37) Model 2 e0.01 (e0.17 to 0.15) DBP at 8 wks (baseline) (5 mmHg) Model 1 e0.07 (e0.13 toe0.02) e0.06 (e0.11 toe0.02) e0.05 (e0.10 toe0.00) Model 2 0.06 (0.00e0.12) e0.03 (e0.08 to 0.02) e0.04 (e0.10 to 0.01) DBP change, mm Hg/wk

Early pregnancy (8-18 wks) Model 1 0.08 (e0.11 to 0.27) 0.12 (e0.09 to 0.34) Model 2 0.02 (e0.18 to 0.24) 0.06 (e0.15 to 0.30) Midpregnancy (18-29 wks) Model 1 0.29 (0.08e0.50)

Model 2 0.14 (e0.06 to 0.36)

CI, confidence interval;DBP, diastolic blood pressure;GWG, gestational weight gain;SBP, systolic blood pressure.

aModel 1 was adjusted for maternal height, age, parity, smoking during pregnancy, education, and offspring sex. Model 2 was also adjusted for prepregnancy weight and SBP/DBP at 8 weeks, GWG and SBP/DBP in all periods of pregnancy prior to the exposure period, and GWG in the exposure period.

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SUPPLEMENTARY FIGURE 1

Distribution of prepregnancy BMI (n

[

10,411)

0 500 1000 1500 F requency 10 20 30 40 50 60 Pre-pregnancy BMI (kg/m²)

BMI, body mass index.

Macdonald-Wallis. Weight gain and blood pressure in pregnancy. Am J Obstet Gynecol 2013.

SUPPLEMENTARY FIGURE 2

Distribution of GWG up to 18 weeks (n

[

11,760)

0 1000 2000 3000 4000 -1 -.5 0 .5 1

Gestational weight gain up to 18 weeks (kg/week)

F

requency

GWG, gestational weight gain.

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SUPPLEMENTARY REFERENCES

1.Macdonald-Wallis C, Tilling K, Fraser A,

Nelson SM, Lawlor DA. Established pre-eclampsia risk factors are related to patterns of blood pressure change in normal term

preg-nancy: findings from the Avon Longitudinal

Study of Parents and Children (ALSPAC).

J Hypertens 2011;29:1703-11.

2.Fraser A, Tilling K, Macdonald-Wallis C, et al.

Associations of gestational weight gain with maternal body mass index, waist circumference, and blood pressure measured 16 y after pregnancy: the Avon Longitudinal Study of Parents and Children. Am J Clin Nutr 2011;93:

1285-92.

3.Royston P, Altman DG. Regression using

fractional polynomials of continuous

cova-riates—parsimonious parametric modeling.

J Roy Stat Soc C App 1994;43:429-67.

4.Macdonald-Wallis C, Lawlor DA, Palmer T,

Tilling K. Multivariate multilevel spline models for parallel growth processes: application to weight and mean arterial pressure in pregnancy.

Stat Med 2012;31:3147-64.

5.Palmer T, Macdonald-Wallis C. REFFADJUST: Stata module to estimate adjusted regression coefficients for the association between two random effects variables; 2012. Available at:

http://ideas.repec.org/c/boc/bocode/s457403. html. Accessed March 20, 2013.

http://dx.doi.org/10.1016/j.ajog.2013.05.042 www.AJOG www.bris.ac.uk/alspac Lewis G, ed. The Confi 631-44. Duley L. The global impact of pre-eclampsiaand eclampsia. Semin Perinatol 2009;33:130-7 2000;95:24-8 186:66-71. http://guidance.nice.org.uk/CG107 Thadhani R, Stampfer MJ, Hunter DJ,Manson JE, Solomon CG, Curhan GC. High Duckitt K, Harrington D. Risk factors for p eclampsia at antenatal booking: systematic Poon LCY, Kametas NA, Maiz N, Akolekar R,Nicolaides KH. First-trimester prediction of O’ Lawlor DA, Relton C, Sattar N, Nelson SM.Maternal adiposity-a determinant of perinatal Heude B, Thiebaugeorges V, Goua V, et al.Pre-pregnancy body mass index and weight Gaillard R, Steegers EAP, Hofman A,Jaddoe VWV. Associations of maternal obesity Beyerlein A, Schiessl B, Lack N, von Kries R.Associations of gestational weight loss with Viswanathan M, Siega-Riz A, Moos MK,et al. Outcomes of maternal weight gain. Thomson AM, Hytten FE, Billewicz WZ. Theepidemiology of oedema during pregnancy. 2009. 2012;344:e2088 CrowtherCA, Landon MB, Spong CY, Thom E, et al.A multicenter, randomized trial of treatment for Macdonald-Wallis C, Tilling K, Fraser A,Nelson SM, Lawlor DA. Established Robertson EG. The natural history ofoedema during pregnancy. J Obstet Gynaecol Fraser A, Macdonald-Wallis C, Tilling K, et al.Cohort pro Brown MA, Lindheimer MD, de Swiet M,Van Assche A, Moutquin JM. The classi Fraser A, Tilling K, Macdonald-Wallis C,Hughes R, et al. Associations of gestational Macdonald-Wallis C, Lawlor DA, Palmer T,Tilling K. Multivariate multilevel spline models for Leckie G, Charlton C. runmlwin: Statamodule for http://ideas.repec.org/c/boc/bocode/s457403.html 2009;31:28-35. Fortner RT, Pekow P, Solomon CG,Markenson G, Chasan-Taber L. Prepregnancy Gallery ED. Pregnancy-associated hyper-tension: interrelationships of volume and blood Brown MA, Zammit VC, Mitar DM. Extra-cellular 1989;77:599-604 Stamler R, Stamler J, Riedlinger WF,Algera G, Roberts RH. Weight and Yong LC, Kuller LH, Rutan G, Bunker C.Longitudinal study of blood pressure Nelson SM, Matthews P, Poston L. Maternalmetabolism Ramsay JE, Ferrell WR, Crawford L,Wallace AM, Greer IA, Sattar N. Maternal obesity BodnarLM, Callaway LK, Mclntyre HD, O’ Macdonald-Wallis C, Tilling K, Fraser A,Nelson SM, Lawlor DA. Established 1285-92 Royston P, Altman DG. Regression usingfractional polynomials of continuous Macdonald-Wallis C, Lawlor DA, Palmer T,Tilling K. Multivariate multilevel spline models

References

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