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Keywords:

  • Pre-eclampsia;
  • pregnancy;
  • super-obesity;
  • weight gain

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. References
  8. Journal Club
  9. Discussion points
  10. References

Please cite this paper as: Mbah A, Kornosky J, Kristensen S, August E, Alio A, Marty P, Belogolovkin V, Bruder K, Salihu H. Super-obesity and risk for early and late pre-eclampsia. BJOG 2010;117:997–1004.

Objective  To examine the association between obesity subtypes and risk of early and late pre-eclampsia.

Design  Population-based retrospective study.

Setting  State of Missouri maternally linked birth cohort files.

Population  All singleton live births in the state of Missouri from 1989 to 2005.

Methods  The body mass index (BMI) was used to classify women as normal weight (BMI = 18.5–24.9 kg/m2), class I obesity (BMI = 30–34.9 kg/m2), class II obesity (BMI = 35–39.9 kg/m2), class III obesity (BMI = 40–49.9 kg/m2) or super-obesity (BMI ≥ 50 kg/m2). Adjusted odds ratios (OR) and 95% confidence intervals (CI) for the association between obesity and the risk of pre-eclampsia were obtained from logistic regression models with adjustment for intracluster correlation.

Results  The rate of pre-eclampsia increased with increasing BMI, with super-obese women having the highest incidence (13.4%). Compared with normal weight women, obese women (BMI ≥ 30 kg/m2) had a higher risk for pre-eclampsia (OR = 2.59, 95% CI = 2.87–3.01). This risk remained approximately the same for late-onset pre-eclampsia (pre-eclampsia occurring at 34 weeks or more of gestation) and was slightly reduced for early-onset pre-eclampsia (pre-eclampsia occurring at 34 weeks or less of gestation). Within each BMI category, the risk of pre-eclampsia increased with the rate of weight gain. Compared with normal weight mothers with moderate weight gain, super-obese women with a high rate of weight gain had the greatest risk for pre-eclampsia (OR = 7.52, 95% CI = 2.70–21.0).

Conclusion  BMI and rate of weight gain are synergistic risk factors that amplify the burden of pre-eclampsia among super-obese women.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. References
  8. Journal Club
  9. Discussion points
  10. References

Pre-eclampsia affects about 2–8% of pregnancies worldwide and has a negative impact on maternal and neonatal morbidity and mortality.1,2 Several studies have identified maternal pre-pregnancy body mass index (BMI) as an important risk factor for pre-eclampsia, noting possible differences in the aetiologies of early and late pre-eclampsia, with the former generally being regarded as more severe in terms of maternal and fetal outcomes.2–4 However, not all studies have examined the relationship between BMI and the incidence of early and late pre-eclampsia independently. Furthermore, different classifications of pre-eclampsia have been used in previous studies, rendering comparisons difficult.5,6

Another important consideration in the current wave of the obesity epidemic is the disproportional increase in the rate of obesity by obesity subtypes. For example, it has been shown that, over the previous two decades, the proportion of ‘super-obese’ individuals (BMI ≥ 50 kg/m2) has quintupled.7 The term ‘super-obesity’ was first coined in 1987 to describe a special category of patients with BMI ≥ 50 kg/m2 undergoing surgical treatment as a result of the high rates of co-morbidity (hypertension, diabetes, sleep apnoea) associated with obesity.8,9 Despite the increasing trend for super-obese individuals in the USA, there are, to our knowledge, very few data on pregnancy outcomes among these potentially very-high-risk mothers. Such information is useful in informing clinical decision-making, as care providers will have to manage these patients more frequently as their relative numbers rise. In a recent study, we computed the incidence of super-obesity in the state of Florida (USA) to be 0.6%.10 In this study, we aimed to assess the following three hypotheses:

  • 1
     High maternal pre-pregnancy BMI is positively correlated with an incremental increase in the incidence of pre-eclampsia.
  • 2
     The association between pre-eclampsia and high maternal BMI varies across gestational age.
  • 3
     Excessive weight gain during pregnancy increases the risk of pre-eclampsia in a dose–response fashion.

Methods

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. References
  8. Journal Club
  9. Discussion points
  10. References

The Missouri maternally linked birth cohort files covering the period from 1989 to 2005 were used for this study. The data files contain information on birth linked to fetal/infant death. The Missouri Vital Records are very reliable, and have been used as a ‘gold standard’ in studies seeking to evaluate matching procedures in the USA.11,12 We selected live-born singleton infants between 20 and 44 weeks of gestation (n = 1 235 133). We excluded from the study 37 751 (3.1%) records with missing maternal pre-pregnancy BMI, 203 (0.02%) with missing birth weight and 692 (0.1%) with missing information on pre-eclampsia and eclampsia. In addition, 333 907 (27.0%) records representing underweight (BMI < 18.5 kg/m2) and overweight (BMI 25–29.9 kg/m2) women were excluded, as the focus of the study was obesity. BMI was calculated as the pre-pregnancy weight (kg)/height2 (m2). Furthermore, to reduce the confounding effect of hypertension in pregnancy, we did not include 8495 (0.7%) women who had chronic hypertension. The final study sample comprised 854 085 singleton live births.

The study population was divided into two groups on the basis of maternal pre-pregnancy BMI. Women with BMI values in the range 18.5–24.9 kg/m2 were considered to be normal weight and those with BMI ≥ 30 kg/m2 were considered to be obese. The obese population was then subclassified as class I obesity (BMI = 30–34.9 kg/m2), class II obesity (BMI = 35–39.9 kg/m2), class III obesity (BMI = 40–49.9 kg/m2) and super-obesity (BMI ≥ 50 kg/m2).13 In addition, weight gain during pregnancy (defined as weight gain in kilograms divided by gestational age in weeks) was used to evaluate the impact of gestational weight gain on the occurrence of pre-eclampsia. Weight gain was determined by taking the difference between maternal weight at delivery (measured) and the self-reported pre-pregnancy weight from the first prenatal care visit. The average rate of gestational weight gain was categorised into three groups across the BMI classes as reported previously: ≤0.22 kg/week (low weight gain), 0.23–0.68 kg/week (moderate weight gain) and ≥0.69 kg/week (high weight gain).14 Normal weight gravidas were used as the reference group for analyses across BMI subtypes. For analyses that assessed the impact of weight gain during pregnancy on the incidence of pre-eclampsia across obesity subtypes, mothers with normal pre-pregnancy BMI and moderate weight gain during pregnancy were the reference category.

The main outcome of interest was the occurrence of pre-eclampsia or eclampsia, referred to in this analysis as pre-eclampsia. Pre-eclampsia was defined as a new onset of hypertension (systolic blood pressure ≥ 140 mmHg or diastolic blood pressure ≥ 90 mmHg) after 20 weeks of gestation accompanied by proteinuria (0.3 g or greater in a 24-hour urine specimen). Eclampsia was defined as the occurrence of generalised convulsion and/or coma in the setting of pre-eclampsia, with no other neurological condition.15 Although no formal validation on the specific outcomes of pre-eclampsia and eclampsia was carried out in this study, previous studies have confirmed the validity of these outcomes in this dataset.16,17 Because of the importance of gestational age in predicting maternal and fetal outcomes, women who developed pre-eclampsia were further subdivided according to the onset of the disease: early-onset pre-eclampsia (defined as pre-eclampsia before 34 weeks of gestation) and late-onset pre-eclampsia (defined as pre-eclampsia occurring at 34 weeks and beyond).2–4,18,19 Gestational age was computed in weeks as the interval between the date of the last menstrual period and the date of delivery of the baby. In cases in which there was inconsistency between the menstrual estimate of gestational age and birth weight [e.g. very low birth weight (<1500 g) for a term singleton gestation], a clinical estimate of the gestational age was imputed.20 This method of computing the gestational age has been validated, with 84.2% agreement between the date of last menses among cases (very-low-birth-weight infants or neonatal deaths) and a randomly selected noncase population.21 It should be noted that ultrasound data were not available.

The following maternal characteristics were considered in our analyses: maternal age (younger than 35 years, 35 years or older), race (white, black, other), education (<12 years, 12 years or greater), tobacco use (yes, no), parity (nulliparous, multiparous), marital status (married, unmarried) and adequacy of prenatal care (adequate, inadequate). We also considered some selected maternal conditions and pregnancy complications as covariates, including anaemia, cardiac disease, insulin-dependent diabetes and other forms of diabetes, placental abruption, placenta praevia and renal disease. To adjust for these potential confounders, we constructed a composite variable defined as the occurrence of at least one of these conditions.

Adequacy of prenatal care was assessed with the revised graduated index algorithm.22 This scale was selected for its accuracy and utility in describing prenatal care utilisation among high-risk women. The graduated index algorithm uses information from the trimester in which prenatal care commenced, the number of visits and the gestational age of the infant at birth as part of the classification system.

The chi-squared test was used to compute differences in sociodemographic characteristics and maternal pregnancy complications between normal weight and obese mothers. During the study, 128 566 (28%) mothers had more than one pregnancy. Therefore, to account for intraclass correlation, we applied the generalised estimating equations (GEE).23 In addition to maternal characteristics and pregnancy complications, we included gender and year of birth as covariates in the adjusted analyses.

Regression models and goodness-of-fits were assessed using aggregates of residuals.24–26 This was realised by comparing plots of the cumulative sums of the model residuals against the exposure variable (whose distribution under the null hypothesis of correct model specification was approximated by a zero-mean Gaussian process) with the number of realisations from a Gaussian process (obtained by simulation). The GENMOD procedure in SAS (SAS Institute, Inc., Cary, NC, USA; version 9.1) was used to conduct this analysis. All tests of hypotheses were two-tailed with a type 1 error rate fixed at 5%.

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. References
  8. Journal Club
  9. Discussion points
  10. References

Of the 854 085 singleton births included in the analysis, the majority of births were to normal weight mothers (78.6%), with the remaining 21.4% to obese gravidas. The distribution of births to obese women by subtype of obesity was as follows: 12.4%, class I obesity (n = 105 950); 5.5%, class II obesity (n = 47 379); 3.1%, class III obesity (n = 26 712); 0.4%, super-obese (n = 3001). The distributions of selected demographic characteristics and obstetric complications of obese mothers compared with normal weight gravidas are presented in Table 1. A greater percentage of obese relative to normal weight mothers were 35 years of age or older (10.8% versus 9.7%), unmarried (32.8% versus 30.8%), black (19.8% versus 12.9%) and more likely to have adequate prenatal care (53.3% versus 50.3%). By contrast, normal weight women were more likely than obese women to be white (84.6% versus 78.9%), nulliparous (43.1% versus 33.9%), to have 12 or more years of education (18.2% versus 16.6%) and to report prenatal smoking (19.4% versus 18.6%). Obstetric complications, such as insulin-dependent diabetes and other forms of diabetes, were more prevalent in the obese group, whereas the prevalence of anaemia, placenta abruption and placenta praevia was more frequent among normal weight women. There was no difference in the risk of renal disease between the two groups.

Table 1.   Comparison of normal weight and obese mothers by selected sociodemographic characteristics and obstetric complications using chi-squared test
 Normal weight (n = 671 043) (%)Obese (n = 183 042) (%)P
Maternal age (≥35 years)9.710.8<0.01
Nulliparous43.133.9<0.01
Unmarried30.832.8<0.01
Race
White84.678.9<0.01
Black12.919.8
Other2.61.3
Education (≥12 years)18.216.6<0.01
Prenatal smoking19.418.6<0.01
Adequate prenatal care50.353.3<0.01
Anaemia1.41.3<0.01
Insulin-dependent diabetes0.42.0<0.01
Other forms of diabetes1.45.2<0.01
Placental abruption0.80.7<0.01
Placenta praevia0.40.3<0.01
Renal disease0.20.20.77

Pre-eclampsia affected 4.5% of all pregnancies (n = 38 038), comprising 22 081 (rate = 3.3%) in normal weight women and 15 957 (rate = 8.7%) in obese mothers. In our study sample, 8056 (21.2%) women with pre-eclampsia were primiparous. Furthermore, 1794 (0.2%) women in our study sample had recurrent pre-eclampsia. The rate of pre-eclampsia increased with increasing BMI (P for trend, <0.01), with super-obese women having the highest rate (13.4%). Women with class I, class II or class III obesity also had higher rates of pre-eclampsia (7.7%, 9.5% and 10.9%, respectively) than normal weight women (3.3%). A plot of the crude frequencies of pre-eclampsia and its onset by obesity subtypes is presented in Figure 1.

image

Figure 1.  Incidence of pre-eclampsia by obesity subtype.

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Of the 4.5% of women diagnosed with pre-eclampsia, 34 901 (4.1%) had late-onset pre-eclampsia and the remaining 3137 (0.4%) had early-onset pre-eclampsia. Mothers with early-onset pre-eclampsia had a significantly higher pre-pregnancy BMI than did mothers with late-onset pre-eclampsia [mean (±SD) = 27.5 kg/m2 (±7.9 kg/m2) versus 24.6 kg/m2 (±6.3 kg/m2), respectively, P < 0.01].

When compared with normal weight women, obese gravidas had about a three-fold increased risk of developing pre-eclampsia (OR = 2.94; 95% CI = 2.87–3.01), even after adjusting for potential confounders (Table 2). This risk remained approximately the same for late-onset pre-eclampsia (OR = 2.97; 95% CI = 2.90–3.04), and was slightly reduced for early-onset pre-eclampsia (OR = 2.22; 95% CI = 2.06–2.40). Furthermore, the incidence of pre-eclampsia in obese women increased with increasing pre-pregnancy BMI in a dose-dependent manner (P for trend, <0.01), with super-obese women having the highest incidence, about five-fold higher (OR = 4.71; 95% CI = 4.20–5.28) (Table 2). A similar pattern of risk was observed for early- and late-onset pre-eclampsia, although the increase was more pronounced for late- than early-onset pre-eclampsia. As weight gain during pregnancy could have an impact on pregnancy outcome, which is independent of pre-pregnancy BMI, we examined the association between pre-eclampsia and obesity across obesity classes defined by rate of maternal weight gain (Table 3). The majority of normal weight women had moderate weight gain (88.2%). Very few normal weight women had high weight gain (3.4%). The following incidence was observed: class I obesity (3.2%), class II obesity (2.7%), class III obesity (2.5%) and super-obesity (3.2%). Among obese women, 61.5% had moderate weight gain, 2.9% had high weight gain and 35.5% had low weight gain. Within each of the BMI categories, the incidence of pre-eclampsia increased as the rate of weight gain increased (P < 0.01). Normal weight gravidas with a low rate of weight gain had the lowest incidence of pre-eclampsia (OR = 0.53; 95% CI = 0.50–0.57). Normal weight women with very high weight gain were three times more likely to develop pre-eclampsia (OR = 3.02; 95% CI = 2.88–3.16) than normal weight gravidas with moderate weight gain. The incidence of pre-eclampsia increased with both increasing pre-pregnancy BMI and increasing rate of weight gain. Therefore, super-obese women with a high rate of weight gain had the highest incidence of pre-eclampsia (OR = 13.40; 95% CI = 7.93–22.70) when all categories were considered. The risk for pre-eclampsia in obese women with high weight gain relative to obese women with moderate weight gain was almost double (OR = 1.73; 95% CI = 1.64–1.81).

Table 2.   Adjusted odds ratio for the association between obesity, obesity subtype and pre-eclampsia
 Adjusted odds ratio*,** (95% confidence interval)
Overall pre-eclampsia*** (n = 38 052)Early pre-eclampsia*** (= 3142)Late pre-eclampsia*** (n = 34 910)
  1. BMI, body mass index.

  2. *For all analyses, normal weight mothers were the reference.

  3. **Adjusted odds ratios were generated after controlling for year of birth, maternal age, race, education, tobacco use, parity, marital status, adequacy of prenatal care, gender of the infant and a composite variable which included the occurrence of at least one of the following maternal complications: anaemia, cardiac disease, insulin-dependent diabetes and other forms of diabetes, placental abruption, placenta praevia and renal disease.

  4. ***P for trend, <0.01.

  5. ****Includes class I obesity, class II obesity, class III obesity and super-obesity.

Obese**** (n = 80 205)2.94 (2.87–3.01)2.22 (2.06–2.40)2.97 (2.90–3.04)
Class I (BMI = 30.0–34.9 kg/m2) (n = 105 950)2.59 (2.52–2.66)2.03 (1.85–2.23)2.62 (2.54–2.69)
Class II (BMI = 35.0–39.9 kg/m2) (n = 47 379)3.20 (3.09–3.32)2.37 (2.10–2.67)3.24 (3.12–3.36)
Class III (BMI = 40.0–49.9 kg/m2) (= 26 712)3.75 (3.59–3.92)2.63 (2.28–3.05)3.80 (3.63–3.97)
Super-obesity (BMI ≥ 50 kg/m2) (n = 3001)4.71 (4.20–5.28)2.97 (2.07–4.26)4.79 (4.26–5.39)
Table 3.   Gestational weight gain and the risk of preeclampsia by obesity status
Rate of weight gain (kg/week)Adjusted odds ratio** (95% confidence interval)
Normal weight (BMI = 18.5–24.9  kg/m2)Overall obesity* (BMI ≥ 30.0  kg/m2)Class I (BMI = 30.0–34.9  kg/m2)Class II (BMI = 35.0–39.9  kg/m2)Class III (BMI = 40.0–49.9  kg/m2)Super-obesity (BMI > 50  kg/m2)
  1. *This includes all classes of obesity [body mass index (BMI) ≥ 30.0 kg/m2].

  2. **Adjusted odds ratios were generated after controlling for year of birth, maternal age, race, education, tobacco use, parity, marital status, adequacy of prenatal care, gender of the infant and a composite variable which included the occurrence of at least one of the following maternal complications: anaemia, cardiac disease, insulin-dependent diabetes and other forms of diabetes, placental abruption, placenta praevia and renal disease.

Low (<0.22) (n = 117 903)0.53 (0.50–0.57)1.28 (1.24–1.33)1.83 (1.73–1.94)2.66 (2.50–2.83)3.16 (2.95–3.40)3.90 (3.21–4.74)
Moderate (0.22–0.68) (n = 692 295)Reference3.12 (3.04–3.21)3.02 (2.93–3.12)3.84 (3.67–4.02)4.78 (4.51–5.07)6.50 (5.52–7.64)
High (>0.68) (n = 27 714)3.02 (2.88–3.16)5.39 (5.00–5.81)5.26 (4.78–5.79)6.42 (5.53–7.46)8.19 (6.71–10.0)13.4 (7.93–22.7)

Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. References
  8. Journal Club
  9. Discussion points
  10. References

In this study, we found that obese mothers were almost three times more likely to develop pre-eclampsia than women with a normal body mass index. In addition, with increased BMI, we noted a progressive incremental increase in the incidence of pre-eclampsia. This finding supports our first hypothesis that high maternal pre-pregnancy BMI is positively correlated with an incremental increase in the incidence of pre-eclampsia. These findings are in agreement with those of previous investigators.5–7 However, in one of these studies,10 a bell-shaped relationship between pre-eclampsia and BMI group was detected, with risk estimates declining beyond a maternal BMI of 35 kg/m2. To our knowledge, our study is the first to examine the risk of pre-eclampsia at extreme obesity subtypes (40–49 and ≥50 kg/m2).

An important strength of this study is the large population of women from which our cases were selected. Unlike many other studies, our large sample size enabled us to detect disparity in risk between early- and late-onset pre-eclampsia among obese mothers. Moreover, to the best of our knowledge, our study is the first to examine the classification of pre-eclampsia by gestational age in super-obese mothers, and therefore makes an important contribution to the literature on super-obesity and the associated increased risk of development of pre-eclampsia. Our results may provide important information for clinicians treating and advising obese patients about weight gain and the risk of developing pre-eclampsia, especially in the light of the increasing trend for super-obesity in the USA.

As with other retrospective database studies, this study has several limitations. Women in the Missouri database were followed for 17 years. Although we controlled for the year of birth of their infants, the different cohorts across the long period of observation could have induced some bias into our results. However, by adjusting for the year of birth, this bias will have been minimised. Another significant source of bias could result from maternal pre-pregnancy weight values, as this information was based on self-reported data. It is reasonable to expect that women with high pre-pregnancy BMI would be more likely to under-report their weight than nonobese women, leading to different weight classifications. If this assumption is correct, the relationship between BMI and the development of pre-eclampsia will have been underestimated. In addition, recall bias may also have introduced bias into the self-reported BMI data. However, this is unlikely to have affected the results in this study because information on pre-pregnancy BMI was obtained at the first prenatal care visit before the occurrence/detection of the outcomes (pre-eclampsia). Even after the inclusion of other important covariates, such as previous pre-eclampsia and inter-pregnancy interval > 8 years, the results of our analyses remained the same.

The role of pregnancy or medical complications as either confounders or intermediary variables remains controversial with varying degrees of opinion. Some regard these as confounders because they are associated with both the exposure (high BMI) and outcome of interest (pre-eclampsia). For instance, BMI could cause pre-eclampsia without necessarily causing placental abruption or renal disease or diabetes during pregnancy. It is most likely that these medical/obstetric complications are not in the causal pathway, because high BMI could still lead to pre-eclampsia without these medical complications being present to effect causality. Consequently, we treated them as confounders and adjusted for them.

Our second specific aim examined the hypothesis that the association between pre-eclampsia and high maternal BMI varies across gestational age. We observed a 0.75 absolute difference in incidence between late- and early-onset pre-eclampsia in obese women, with a stronger association between BMI and late-onset pre-eclampsia than between BMI and early-onset pre-eclampsia. Furthermore, we observed a widening of the absolute difference in incidence between late- and early-onset pre-eclampsia from 0.59-fold for class I obesity to about two-fold for super-obesity. The difference in strength of association between the subtypes of pre-eclampsia and obesity status may suggest that pre-eclampsia is a heterogeneous disease with different pathogenic processes, as discussed previously by other authors.18,25

Another important finding in this study is the association between gestational weight gain and the incremental increase in the incidence of pre-eclampsia. We observed an increase in the incidence of pre-eclampsia from 28% in obese women with low weight gain to more than four-fold in obese women with high weight gain. These observations are in concordance with previous findings reported in the literature.26–29 Importantly, our analysis also demonstrated that weight gain and obesity act synergistically to amplify the risk of development of pre-eclampsia. The inclusion of a group of super-obese women makes our findings unique, as this is an important subpopulation that is dramatically increasing in size in the USA.7,29,30 Super-obese women with high weight gain had more than a 13-fold (OR = 13.4; 95% CI = 7.93–22.7) increase in the risk of pre-eclampsia relative to normal weight women with moderate weight gain, and a more than four-fold (OR = 4.29; 95% CI = 2.60–7.07) increase in risk of pre-eclampsia relative to obese women with moderate weight gain. These findings support our third hypothesis that excessive weight gain during pregnancy in this group of women further increased the risk of pre-eclampsia. Hence, in addition to encouraging and promoting a reduction in pre-pregnancy BMI, counselling of obese women should address optimal weight gain during pregnancy as a means to minimise the risk for pre-eclampsia. Also of importance is the observation that very few normal weight women gained excessive weight during pregnancy (3.4%), with an even smaller proportion of excessive weight gain observed in obese women (2.9%). These rates are smaller than those reported in the literature (11.6% for normal weight women and 3.1% for obese women).14,28,32 This is encouraging, as excessive weight gain has been associated with poor pregnancy outcome, especially in obese women.14,33

Disclosure of interest

There are no financial interests, commercial affiliations or possible conflicts of interest involved in this study.

Contribution to authorship

All authors participated meaningfully in the conception and design of the research, and in the writing and approval of the manuscript: AKM, conceptualisation, design and assistance in writing the final paper; JLK, assistance in writing the manuscript; SK, significant advice and consultation; EMA, significant advice and consultation; APA, significant advice, improvement in study design and conceptualisation of the study; PJM, significant advice and consultation; VB, significant advice and consultation; KB, significant advice and consultation; HMS, conceptualisation and design of the study.

Details of ethics approval

The Institutional Review Board at the University of South Florida approved this study.

Funding

This work was supported by a grant from the Flight Attendant Medical Research Institute (FAMRI) and the Kellogg Foundation (Grant #P0126278) to Hamisu Salihu. The funding agencies did not play any role in any aspect of the study.

Acknowledgements

We thank the Missouri Department of Health and Senior Services for providing the data files used in this study.

References

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. References
  8. Journal Club
  9. Discussion points
  10. References
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Discussion points

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. References
  8. Journal Club
  9. Discussion points
  10. References
  • 1
     Background: What is the prevalence of obesity in pregnancy in your region and is it increasing or decreasing? Do you expect the prevalence of super-obesity (body mass index > 50) to be similar to that in Florida or different? Describe the three main hypotheses in this study.
  • 2
     Methods: The study is a retrospective analysis of data from a large registry. Can you think of any disadvantages of this approach, with particular reference to data relating to gestational age, diagnosis of pre-eclampsia and adequacy of antenatal care? Discuss the method to determine weight gain in pregnancy in this study, and the possible sources and effects of bias.
  • 3
     Results: Discuss the differences in descriptive characteristics between normal-weight and obese women. Pay particular attention to the relation between parity and obesity, with reference to the fact that the study has assessed births, not women (who might have given birth more than once in the study period). Describe the association between obesity class and/or rate of weight gain, and early/late pre-eclampsia.
  • 4
     Implications: What are the implications for the antenatal care of super-obese women? Compare your conclusions with those by Heslehurst et al.1 Do you think that a higher rate of intervention or more intensive care for obese or super-obese women might have occurred and influenced the findings of this study – how? Is weight control or reduction preferred for obese women during pregnancy? Is it possible?2 What would your advice be for obese women postpartum? Are you aware of any obstetric and medical adverse effects of further postpartum weight gain? ▮

D Siassakos

Chilterns, Women's Health, Southmead Hospital, BS10 5NB, Bristol, UK Email jsiasakos@gmail.com

References

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. References
  8. Journal Club
  9. Discussion points
  10. References