Dataset Information

Early-pregnancy weight gain and the risk of preeclampsia: A case-cohort study.

ABSTRACT:

Objective

To investigate the association between early-pregnancy weight gain and risk of preeclampsia to inform pregnancy weight gain recommendations.

Study design

We performed a case-cohort study using a hospital database including 80,812 singleton deliveries from Magee-Womens Hospital, Pittsburgh, Pennsylvania (1998-2011). In each of 6 prepregnancy body mass index (BMI) groups, we abstracted serial antenatal weight measurements from the records of up to 339 preeclampsia cases and 1254 randomly selected pregnancies. Early gestational weight gain (16-19?weeks' gestation) was standardized for gestational duration using BMI-specific z-score charts. Multivariable log-binomial regression was used to assess the association between weight gain z-score and risk of preeclampsia. We determined the impact of preeclampsia misclassification using probabilistic bias analysis.

Main outcome measure

Risk of preeclampsia.

Results

For normal weight women, there was a steady increase in preeclampsia risk with increasing early gestational weight gain z-score. For example, compared with a weight gain of 1.2?kg (z-score?=?-1 SD), a 7.2-kg weight gain (z-score?=?+1 SD) at 16?weeks was associated with 1.3 (0.50, 2.2) excess preeclampsia cases per 100 deliveries. Weight loss at 16-19?weeks among grade 2 or 3 obese women was associated with a reduced risk of preeclampsia. Associations were null among overweight and grade 1 obese women. The bias analysis supported the validity of the conventional analysis.

Conclusions

Early-pregnancy weight gain may be associated with preeclampsia in some BMI groups. Future revisions of pregnancy weight gain recommendations should account for preeclampsia risks from this and additional studies.

SUBMITTER: Bodnar LM

PROVIDER: S-EPMC7879463 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature

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Publications

Early-pregnancy weight gain and the risk of preeclampsia: A case-cohort study.

Bodnar Lisa M LM Himes Katherine P KP Abrams Barbara B Parisi Sara M SM Hutcheon Jennifer A JA

Pregnancy hypertension 20181015

<h4>Objective</h4>To investigate the association between early-pregnancy weight gain and risk of preeclampsia to inform pregnancy weight gain recommendations.<h4>Study design</h4>We performed a case-cohort study using a hospital database including 80,812 singleton deliveries from Magee-Womens Hospital, Pittsburgh, Pennsylvania (1998-2011). In each of 6 prepregnancy body mass index (BMI) groups, we abstracted serial antenatal weight measurements from the records of up to 339 preeclampsia cases an ...[more]

PMID: 30527113

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Project description:IntroductionDespite the important clinical significance, limited data on the joint contribution of prepregnancy body mass index (BMI) and gestational weight gain (GWG) to preeclampsia, the second leading cause of maternal mortality worldwide. This study aimed to estimate the risk of preeclampsia by GWG among women with varied prepregnancy BMI.MethodsWe conducted a retrospective cohort study using data of 117 738 singleton pregnant women aged 18-49 years from 150 maternity hospitals in China between 2015 and 2018. GWG was calculated as the measured weight at the time of preeclampsia assessment minus prepregnancy weight; GWG velocity was calculated as the GWG divided by the gestational age at weighing. The non-linear associations of GWG with preeclampsia were examined by restricted cubic spline regression analysis according to prepregnancy BMI. The association of the GWG categories with preeclampsia was further examined by performing robust Poisson regression stratified by the prepregnancy BMI categories.ResultsAmong participants, 2426 (2.06%) were diagnosed with preeclampsia. Compared to women with normal BMI, those who were overweight and obese had 1.92- fold (95%CI, 1.73-2.14) and 5.06- fold (95%CI, 4.43-5.78) increased risks for preeclampsia, respectively. The association of GWG velocity with preeclampsia was presented as a J-shaped curve with the varied inflexion point (where the rate of preeclampsia was 2%), which was 0.54, 0.38, and 0.25 kg/week in women with normal BMI, overweight, and obesity, respectively; a steep risk rise was observed along with GWG velocity beyond the inflexion points. The overall adjusted relative risk for preeclampsia was calculated among women with the different GWG categories of GWG.ConclusionsThe findings highlight that high prepregnancy BMI and exceed GWG contributed to increased risk of preeclampsia with a superimposed effect and underscore the need to optimize the recommendations for GWG for women with different prepregnancy BMI.

Project description:OBJECTIVE:To evaluate the capacity of multivariable prediction of preeclampsia during pregnancy, based on detailed routinely collected early pregnancy data in nulliparous women. DESIGN AND SETTING:A population-based cohort study of 62 562 pregnancies of nulliparous women with deliveries 2008-13 in the Stockholm-Gotland Counties in Sweden. METHODS:Maternal social, reproductive and medical history and medical examinations (including mean arterial pressure, proteinuria, hemoglobin and capillary glucose levels) routinely collected at the first visit in antenatal care, constitute the predictive variables. Predictive models for preeclampsia were created by three methods; logistic regression models using 1) pre-specified variables (similar to the Fetal Medicine Foundation model including maternal factors and mean arterial pressure), 2) backward selection starting from the full suite of variables, and 3) a Random forest model using the same candidate variables. The performance of the British National Institute for Health and Care Excellence (NICE) binary risk classification guidelines for preeclampsia was also evaluated. The outcome measures were diagnosis of preeclampsia with delivery <34, <37, and ?37 weeks' gestation. RESULTS:A total of 2 773 (4.4%) nulliparous women subsequently developed preeclampsia. The pre-specified variables model was superior the other two models, regarding prediction of preeclampsia with delivery <34 and <37 weeks, both with areas under the curve of 0.68, and sensitivity of 30.6% (95% CI 24.5-37.2) and 29.2% (95% CI 25.2-33.4) at a 10% false positive rate, respectively. The performance of these customizable multivariable models at the chosen false positive rate, was significantly better than the binary NICE-guidelines for preeclampsia with delivery <37 and ?37 weeks' gestation. CONCLUSION:Multivariable models in early pregnancy had a modest performance, although providing advantages over the NICE-guidelines, in predicting preeclampsia in nulliparous women. Use of a machine learning algorithm (Random forest) did not result in superior prediction.

Project description:BackgroundGestational weight gain (GWG) has important health implications for both the mother and offspring. Maternal diet during pregnancy may play an important role in achieving adequate GWG, although its precise role is unclear.ObjectivesAssociations between maternal dietary components (fruits and vegetables, added sugar, percentage energy from fat, dairy) and GWG were examined in 327 pregnant women from the Archive for Research on Child Health cohort.MethodsSelf-reported usual dietary intake was assessed with validated dietary screening tools at the first prenatal visit. GWG was obtained from the birth certificate and was categorized as inadequate, adequate, or excessive according to the Institute of Medicine recommendations. Associations between dietary components and GWG were assessed using multivariable regression models, stratified by maternal prepregnancy BMI category.ResultsOnly 31.5% of women had adequate GWG, with 24.8% gaining insufficient weight and 43.7% gaining excessively. Women who consumed more fruits and vegetables were suggestively less likely to have excessive GWG (OR: 0.86; 95% CI: 0.75, 1.00) in the minimally adjusted model, but the association became nonsignificant after adjusting for covariates (OR: 0.89; 95% CI: 0.77, 1.03). In stratified models, higher fruit and vegetable intake was linked to lower likelihood of excessive GWG among women with obesity (OR: 0.77; 95% CI: 0.60, 0.97), whereas higher added sugar intake was linked to a slight reduction in likelihood of excessive GWG (OR: 0.91; 95% CI: 0.84, 0.99) among women with a prepregnancy BMI in the normal range. Other dietary components were not significantly associated with GWG.ConclusionsThese results suggest that consuming fruits and vegetables during pregnancy may reduce risk of excessive GWG among women with obesity. With the rising prevalence of obesity among women of reproductive age, interventions to increase fruit and vegetable intake during pregnancy may have broad public health impact by improving maternal and child health outcomes.

Dataset Information

Early-pregnancy weight gain and the risk of preeclampsia: A case-cohort study.

Objective

Study design

Main outcome measure

Results

Conclusions

Publications

Early-pregnancy weight gain and the risk of preeclampsia: A case-cohort study.

Similar Datasets

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