Pregnancy Hypertension: An International Journal of Women’s Cardiovascular Health 2 (2012) 341–349
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Pregnancy Hypertension: An International Journal of Women’s Cardiovascular Health journal homepage: www.elsevier.com/locate/preghy
Review
Are antenatal weight management interventions effective in preventing pre-eclampsia? Systematic review of randomised control trials Lisa Cuiying Ho a, Karin Anna-Lovisa Saunders a, Deborah Jane Owen a, Umi Nursheila Nur Ibrahim a, Sohinee Bhattacharya b,⇑ a b
Department of Obstetrics and Gynaecology, University of Aberdeen, United Kingdom Epidemiology Group, Institute of Applied Health Sciences, University of Aberdeen, United Kingdom
a r t i c l e
i n f o
Article history: Received 4 November 2011 Accepted 1 March 2012 Available online 18 March 2012 Keywords: Obesity Overweight Body Mass Index Preeclampsia Systematic review
a b s t r a c t Introduction: Pre-eclampsia, defined as the development of hypertension and proteinuria after 20 weeks gestation, carries significant maternal and foetal risk. Pre-pregnancy BMI is the most useful predictor of pre-eclampsia. As the prevalence of obesity increases, prevention of pre-eclampsia by weight management strategies needs to be trialed. Aims and objectives: To review the randomised controlled trials studying clinical effectiveness of antenatal weight management interventions compared to routine care in decreasing the incidence of pre-eclampsia in women with BMI 26 kg/m2 or greater. Methods: Electronic bibliographic databases were searched using a systematic search strategy to identify relevant trials. All trials involving weight management during pregnancy were considered. Using pre-determined inclusion criteria, six trials were included in this review and were independently assessed using standardised evaluation criteria. Results: Three studies found a significant difference in gestational weight gain; amongst the intervention groups, the smallest was 5.0 kg, whereas the largest was 13.6 kg. In sub-group analysis, one trial found a significant difference in the incidence of pre-eclampsia between adherent (2/90) and non-adherent participants (5/26). However, no significant difference was found in the overall incidence of pre-eclampsia across all intervention and control groups. Conclusion: There was no evidence to suggest that antenatal weight management interventions were effective in reducing the incidence of pre-eclampsia in women with a BMI P 26 kg/m2. Ó 2012 International Society for the Study of Hypertension in Pregnancy. Published by Elsevier B.V. All rights reserved.
Introduction Government figures estimate that 50% of UK women could be obese by 2050, costing the economy £49.9 billion ⇑ Corresponding author. Address: Dugald Baird Centre for Research on Women’s Health, Aberdeen Maternity Hospital, Cornhill Road, Aberdeen AB25 2ZD, United Kingdom. Tel.: +44 (0)1224 554672; fax: +44 (0)1224 553708. E-mail address: [email protected] (S. Bhattacharya).
per annum [1,2]. Obesity is a risk factor for developing preeclampsia in pregnancy [3]; as the prevalence of obesity increases, a greater proportion of women will enter pregnancy overweight or obese [1,4]. Defined as the development of hypertension (P140/90 mmHg) and proteinuria (P300 mg/24 h) occurring after 20 weeks gestation [4], pre-eclampsia is the third highest cause of maternal death in the UK [5]. It is associated with reduced placental perfusion and is the leading cause of premature delivery and intrauterine growth restriction [3].
2210-7789/$ - see front matter Ó 2012 International Society for the Study of Hypertension in Pregnancy. Published by Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.preghy.2012.03.003
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High Body Mass Index (BMI) has been consistently shown to have strong associations with adverse pregnancy outcomes [6,7]. Bhattacharya et al. demonstrated that every step up in BMI category carries an increase in risk; morbidly obese women with BMI P 40 kg/m2 are 7.2 times more likely to develop pre-eclampsia than healthy weight women [6]. O’Brien et al. calculated that the risk of preeclampsia doubles for every 5–7 kg/m2 increase in BMI [8]. Interestingly, a protective relationship with BMI below 20 kg/m2 and pre-eclampsia was found by Bhattacharya et al. [6] and Sebire et al. [9]. The latter noted that low BMI was protective against both the development of gestational diabetes and pregnancy induced hypertension. Pre-pregnancy BMI remains the most useful predictor for the development of pre-eclampsia to date [10]. Current NICE guidelines advise against dieting during pregnancy as low gestational weight gain (GWG) potentially restricts foetal growth, however pre-pregnancy weight reduction is recommended to minimise the risk of foetal and obstetric complications [11]. To date, there are no European guidelines recommending appropriate weight gain during pregnancy. The American Institute of Medicine (IOM) has published recommended limits, which have been referenced in several international clinical trials [12]. Definitive treatment for pre-eclampsia is delivery of the foetus. Antihypertensives such as hydralazine or labetalol can be used with the addition of magnesium sulphate, preventing progression to eclampsia if the infant is too premature to consider delivery [4]. The management of pre-eclampsia with medications is associated with side-effects and affects maternal and perinatal outcomes [13]. Ideally pre-eclampsia should be prevented rather than treated. Calcium supplements and low-dose aspirin have all been shown to be effective prophylactic treatments but are currently not recommended to be used as routine management [14]. There is a clear association between an elevated BMI and the development of pre-eclampsia, thus it is important to assess whether antenatal weight management is more effective compared with routine antenatal care as a primary prevention strategy. Reviews into the effects of antenatal weight interventions have been conducted previously [15]. Dodd et al. conducted a review of 9 randomised control trials (RCTs) that aimed to alter the dietary and lifestyle habits of pregnant women. The primary outcome measure was large-for-gestational age infants with pre-eclampsia as a secondary outcome for 5 of the RCTs [15]. The secondary data were often minimal, with many of the included studies reporting pre-eclampsia in only 1 or 2 participants. Some studies indicated that interventions had no significant effect on the incidence of preeclampsia but supplied no quantitative data. The reporting of secondary outcomes was inconsistent across all the reviewed trials and different BMI categories were often not explicitly stated. Another concern with the review by Dodd et al. is that the RCTs generally did not have enough power to make reliable conclusions on the secondary outcomes. No systematic reviews into the effectiveness of antenatal weight management interventions that focus on preeclampsia as a primary outcome currently exist. It is logical
to hypothesise that weight management interventions should impact on the development of pre-eclampsia in women with high BMI. Hence this review aims to assess whether antenatal weight management techniques are more effective compared with routine antenatal care as primary prevention strategies for pre-eclampsia. Methods A protocol was developed to review the evidence for the clinical effectiveness of antenatal weight management interventions for preventing pre-eclampsia. The methodology of this review draws from the methods developed by National Health Service Centre for Reviews and Dissemination guidance for undertaking reviews in health care [16]. At first a focused review question was developed using PICO structure – ‘‘How effective are antenatal weight management interventions for preventing pre-eclampsia?’’ From the facets of this review question search terms and inclusion and exclusion criteria were derived. Literature search The literature search conducted for this review included publications from 1970 to May 2011. Six electronic bibliographic databases; EMBASE, PubMed, MEDLINE, Cochrane Database of Systematic Reviews, NHS eLibrary and ClinicalTrials.gov were searched systematically without limits on date. MeSH terms and key words including ‘pregnancy’, ‘pre-eclampsia’, ‘obesity’, ‘diet’, ‘weight loss’, ‘lifestyle’, and ‘randomised controlled trial’ were combined with the Cochrane Collaboration strategy for identifying primary studies. The MEDLINE search strategy was adapted for searching other databases. Reference lists of all articles were checked to identify other relevant studies. Searches were limited to English-language studies in humans. Due to time constraints, searching of grey literature and hand searching were not done, nor were any experts contacted. Study selection Inclusion and exclusion criteria were developed a priori based on the review question. All RCTs involving interventions designed to influence maternal weight during the antenatal period were included. No restrictions were placed on the nature (dietary, exercise, behavioural or awareness based), duration or intensity of the interventions. Interventions were considered whether delivered on a one-to-one basis or to groups of participants and compared to routine care, defined as no change in usual standard of care delivered. Studies conducted in any healthcare or community setting on any participants regardless of parity or co-morbidities were included. Trials were excluded if the intervention was not delivered to overweight or obese participants (BMI P 26 kg/m2 and BMI P 30 kg/m2 respectively as defined in all studies appraised). Studies were excluded if no data presented in tables, figures, or text allowed a quantitative measurement of the incidence of preeclampsia and effectiveness of the intervention.
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Quality assessment and data extraction Included studies were reviewed and critically appraised independently by two of the authors. Studies were reviewed independently by a third party if any disagreement was found. Study quality was initially assessed using the critical appraisal skills programme (CASP) RCT appraisal tool then scored on quality using an in-house modified version of the SIGN 50 Checklist. The CASP tool [17] was used as a quick screening tool to determine if the study was of sufficient quality to be further evaluated. The published SIGN 50 checklist for RCTs [18] was modified to the specifics of the question set in this review. Briefly, we assessed the quality of all included studies in accordance with the following items: focus of the research, randomisation, concealment allocation, blinding, loss to follow-up, sample size, participant selection, comparability of groups, intention to treat analysis, categorisation and assessment of primary measures and outcomes. Results Study selection and quality assessment of included studies A total of 626 RCTs were identified using the previously outlined methodology (Fig. 1). Following the removal of duplicates 450 RCTs were considered for inclusion. After exclusions, six studies were finally included in the review and their quality assessed.
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Following the initial screening of each study using the CASP tool all six studies were of sufficient quality to warrant further assessment. The use of the modified SIGN checklist allowed the quality of each study to be designated a quality score. Wolff et al. and Rae et al. were considered high quality [19,20]. Guelinckx et al. received the lowest score principally due to a lack of reported data [21]. Study characteristics and detailed quality assessment of studies The characteristics and quality assessment of each study are presented in Tables 1 and 2 respectively. Six RCTs were analysed, with a total population of 867 pregnant women with age ranging from 18 to 45 years. Of the total population, 654 were of BMI P 26 kg/m2. As seen from Table 1, the studies by Wolff et al. [19] and Thornton et al. [22] had populations with BMI P 30 kg/ m2 while Polley et al. [23] and Jeffries et al. [24] recruited women with BMI P 19.8 kg/m2 and any BMI respectively. Each study had more than 100 participants except for one [21] (Table 2) and all but two studies were carried out at a single site [22,24]. The population in each study differed from one another as Table 1 shows; two studies [19,21] had purely Caucasian population and while Rae et al. [20] included diabetic women, three other studies excluded them [21,22,24]. All six study designs were parallel with two arms except for Guelinckx et al. [21], which ran three arms to compare passive and active interventions
Fig. 1. Flow chart of selection of studies for review.
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Table 1 Study characteristics. Population
Intervention
Secondary
Dietician-instructed non-restricted diabetic diet (approx. 8600–9500 kJ) n = 54 Standard care n = 53 (22 overweight)
Energy intake GWG Diabetes control
Maternal and obstetric outcomes
GWG Behavioural changes during pregnancy
Maternal, obstetric and birth outcomes Postpartum weight loss and weight retention
Ten 1 h consultation with dietician GWG restricted to 6–7 kg Energy intake restricted based on individual n = 23
No consultation with dietician No weight gain/intake restriction n = 27
Energy intake GWG Glucose metabolism
Maternal, obstetric and birth outcomes
Personalised weight gain recommendations n = 125 (20 overweight, 25 obese)
Standard care n = 111 (18 overweight, 21 obese)
GWG
Maternal, obstetric and neonatal outcomes
Active and behavioural intervention consisting of detailed dietary guidelines and daily self-recording of dietary intake n = 116 Passive intervention group: brochure n = 37 Active intervention group: brochure and three sessions with a nutritionist n = 42
Conventional prenatal guidelines n = 116
GWG Maternal, obstetric and birth outcomes Dietary habits Physical activity GWG
Comparison of primary outcomes between adherent and non-adherent participants in study group
Australia Inclusion: Diabetic BMI > 27.5 6 35 weeks gestation + 6 days Exclusion: Not stated
Dietician-instructed 6800–7600 kJ restricted diet n = 63
Polley et al. (2002)
USA Inclusion: low income BMI > 19.8 > 18 years old < 20 weeks gestation Exclusion: BMI < 19.8 Age 12 weeks gestation High risk pregnancy (drug abuse, chronic health problems, serious complications during pregnancy, multiple pregnancy) Denmark Inclusion: Caucasian BMI P 30 15 ± 3 weeks gestation Exclusion: Smoking Age 45 Multiple pregnancy Medical complications that affect foetal growth or contraindicate weight gain limitation Australia Inclusion: Any BMI 6 14 weeks gestation Exclusion: Age < 18 or age > 45 Diabetic Multiple pregnancy Non-English speaking USA Inclusion: BMI P 30 12–28 weeks gestation singleton Exclusion: Pre-existing diabetes, hypertension, chronic renal disease
Stepped-care behavioural intervention (i.e. more intensive interventions if women exceeded target weight) n = 57 (27 overweight)
Jeffries et al. (2009)
Thornton et al. (2009)
Guelinckx et al. (2009)
Belgium Inclusion: Caucasian BMI > 29.0 < 15 weeks gestation Exclusion: Pre-existing diabetes or developing GDM Multiple pregnancy Recruitment after 15 weeks gestation Delivery 29 kg/ m2. The overweight women in the intervention group gained 0.42 kg per week compared to the control group who gained 0.54 kg (p = 0.01) while in the obese group, the results were 0.4 kg and 0.33 kg respectively (p = 0.27). However, when the results were combined to measure total GWG, the statistical significance was lost [24]. This seems to imply that GWG per week could be a more sensitive way of detecting clinical effectiveness of weight interventions in pregnant women compared to total weight gain as it accounts for the heterogeneity of total gestation weeks. As shown in Table 3, there was a total of 25/308(8%) cases of pre-eclampsia in the entire population with BMI P 26 kg/m2 and in the intervention group. In addition, there were 6/125 cases of pre-eclampsia in the Jeffries et al. intervention group, although it is not certain how many of the 6 were of BMI P 26 kg/m2. In contrast, there
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Table 3 Detailed results of outcomes of the trials. Reference
Rae et al. (2000)
Polley et al. (2002)
Wolff et al. (2008)
Jeffries et al. (2009)
Thornton et al. (2009)
Guelinckx et al. (2009)
Study outcomes (intervention vs control group) Weight management
Pre-eclampsia incidence
Intake: Intervention: 6579 kJ Control: 6845 kJ p = 0.263 Total weight gain: Intervention: 11.56 kg (SE 1.32, range 7.50–0.00) Control: 9.68 kg (SE 1.45, range 5.00–0.00) p = 0.338 Total weight gain: (Normal weight) Intervention: 15.4 ± 7.1 kg (2.7–32.7 kg) Control: 16.4 ± 4.8 kg (6.8–30.9 kg) (Overweight) Intervention: 13.6 ± 7.2 kg (1.4–29.1 kg) Control: 10.1 ± 6.2 kg ( 0.9 to 26.4 kg) Intake: Intervention: 8619 ± 224 kJ/day Control: 9223 ± 1829 kJ/day p = 0.001 Total weight gain: Intervention: 6.6 ± 5.5 kg Control: 13.3 ± 7.5 kg p = 0.002 CI: 2.6–10.8 kg Total weight gain: (Overweight) Intervention: 10 kg (3.63SD) Control: 13.3 kg (3.57SD) p = 0.33 (Obese) Intervention: 9.5 kg (5.17SD) Control: 8.2 kg (3.02SD) p = 0.52 Weight gain per week: (Overweight) Intervention: 0.42 kg (0.153SD) Control: 0.54 kg (0.123SD) p = 0.01; 95% CI 0.03–0.22 (Obese) Intervention: 0.4 kg (0.226SD) Control: 0.33 kg (0.145SD) p = 0.27; 95% CI -0.18–0.05 Mean weight gain: Intervention: 11 lbs (14.96SD) 95% CI 8.59–14.10 Control: 31 lbs (16.31SD) 95% CI 27.82–33.82 p < 0.001 Pre-eclampsia: Intervention: 7/116 Control: 11/116 p = 0.326 Weight gain: Passive intervention: 10.9 ± 5.6 kg Active intervention: 9.8 ± 7.6 kg Control: 10.6 ± 6.9 kg p = 0.749
Intervention: 14/67 Control:13/58 p = 0.838
were 29/262 (11%) in the total study population with BMI P 26 kg/m2 and in the control group. There were 2/111 cases of pre-eclampsia in the study by Jeffries et al. but as mentioned before, it is uncertain how many of them were of BMI P 26 kg/m2 [24]. None of the studies found a statistically significant difference in the incidence of pre-eclampsia.
(Overweight) Intervention: 2/27 Control: 3/22 (Normal weight) Intervention: 0/30 Control: 0/31 Intervention: 0/23 Control: 1/27
Intervention: 6/125 Control: 2/111 p = 0.29; RR 2.68, CI 0.55–13.0
Adherent participants: 2/90 Non-adherent participants: 5/26 p < 0.01
Passive intervention: 0/37 Active intervention: 2/42 Control: 1/43 p = 0.436
Significant results for pre-eclampsia were, however, obtained by Thornton et al. when the intervention group was further analysed to compare those who were more compliant with the intervention than those who were not. The adherent group had a significantly decreased incidence (p < 0.01) of pre-eclampsia compared to the non-adherent group (Table 3). Although, when the intervention group
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was compared as a whole to the control group, the difference in the incidence of pre-eclampsia was not statistically significant (p = 0.326) [22] (Table 3). This could account for the apparent lack of effect of the weight reduction on preeclampsia incidence seen in the rest of the trials as the lack of adherence within the intervention groups could have led to the effect being lost.
Relationship between GWG and pre-eclampsia The relationship between mean GWG and incidence of pre-eclampsia across the six studies is presented in Fig. 2. We expected to see a proportional correlation between mean GWG and incidence of pre-eclampsia. Yet, when results from the intervention group were compared, the study with the highest mean GWG [23] did not have the highest percentage of pre-eclampsia patients in the intervention group and vice versa. This might be accounted for by the heterogeneity between the studies’ population. The study by Rae et al. consisted of a diabetic population, which is an additional risk factor for pre-eclampsia, hence it may account for their study having the highest preeclampsia incidence [20]. Similarly, when we compared the control groups’ results, we expected to see a significant increase in the incidence of pre-eclampsia. However, there were irregularities in the results. Despite Rae and Polley et al.’s [20,23] control group having a lower mean GWG than the intervention group, the former still had more women developing pre-eclampsia. On the other hand, Jeffries et al.’s [24] control population had fewer cases of pre-eclampsia even though they had a higher mean GWG than their intervention group. As seen in Fig. 2 and Table 3, there is little difference between the incidence of pre-eclampsia in the intervention group and the control group. Given the heterogeneity of the population and intervention, this seems to imply that weight reduction in overweight and obese women has
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little success in decreasing the incidence of pre-eclampsia effectively in clinical practice. Discussion Principal findings Cumulatively, the six trials examined 377 participants in the control group of which 31 (8.22%) women developed pre-eclampsia. In the intervention group 437 participants were studied and of these 31 (7.09%) participants developed pre-eclampsia. Overall, no statistically significant difference was found between the incidence of pre-eclampsia in the intervention group and the control. Some significant results were found in sub-group analyses, but the results often lacked sufficient power to support any conclusions. The evidence gathered for this review supports the null hypothesis – there is insufficient evidence to suggest that antenatal weight management interventions are effective in reducing the incidence of pre-eclampsia in women with a BMI P 26 kg/m2. Comparison with literature The lack of effectiveness of dietary interventions on preeclampsia has been observed previously. In 1975 Campbell and MacGillivray [25] showed that a calorie controlled diet had no effect on the incidence of pre-eclmapsia. In 2010 Dodd et al. [15] published a systematic review and metaanalysis of antenatal interventions for overweight or obese pregnant women. Pre-eclampsia was assessed as a secondary outcome. The outcome of the meta-analysis indicated that weight management interventions were not effective in altering mean GWG (overall effect p = 0.25; 95% CI 8.32 to 2.13) or the incidence of pre-eclampsia. The authors concluded that heterogeneity (I2 = 93%) between the studies, primarily in intervention, resulted in this effect.
Fig. 2. Relationship between mean GWG and pre-eclampsia across studies.
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Strengths and limitations Strengths of this review featured in the approach of our methodology structured by a clearly focused review question with specific exclusion and inclusion criteria. Only RCTs were included as we wanted to compare the effectiveness of the intervention to that of a control group. To identify appropriate studies an exhaustive search strategy was used. To minimise bias these studies were independently critically appraised by two authors and then assessed with a standardised modified checklist. Due to time constraints and limited resources, we were unable to follow-up on unpublished trials and papers that did not publish all of their data. It is unlikely that our results would have been affected as the findings of the studies were consistent with ours. Furthermore, the papers were not RCTs and would have possibly been excluded on the basis of study design. Interpretation of review findings Antenatal weight management has the potential to reduce the incidence of pre-eclampsia but the observed effect is not reliable as weight management was not achieved. Intervention design in terms of timing, nonadherence and heterogeneity amongst studies may also contribute to this finding. For example, Rae et al. included women just prior to 35 weeks gestation, which would have been insufficient time to achieve relevant weight management [20]. Thornton et al. showed in a sub-group analysis a significant difference between adherent participants and non-adherent participants, although the total numbers were small [22] adding weight to this hypothesis. Implications for future research and clinical practice Our findings implicate that other more specific factors could contribute to the achievement of appropriate weight management in overweight pregnant women. Ideally, programs should commence prior to conception. Studies should also incorporate a non-specific baseline demographic. Despite the overall results of this review, particular findings can be viewed as relevant to clinical practice. Policies focusing more on the quality of methods used to encourage compliance to the guided GWG than the quantity of weight restriction could yield a higher success rate. Behavioural modification in combination with dietary and exercise regimes may have a greater effect in influencing adherence. Moreover, weight can be managed just as effectively using passive intervention without expending an excess of resource and time as seen in Guelinckx et al. and Polley et al. [21,23]. Bariatric surgery is a future option for achieving weight reduction in the obese population however it is currently conducted only prior to pregnancy due to health concerns [26]. Future trials investigating the efficacy of weight management at preventing pre-eclampsia in overweight women should be conducted in a multi-disciplinary, multi-centred setting and in a larger scale to achieve clinically significant results. Additionally, the intervention programs
studied have shown that weight management during pregnancy is safe for women with a BMI P 26 kg/m2, therefore a review of present UK and IOM guidelines should be considered with the view to limiting GWG. Conclusion This review found no evidence to suggest that antenatal weight management interventions were effective in reducing the incidence of pre-eclampsia in women with a BMI P 26 kg/m2. Conflict of Interest The authors declare that they have no conflict of interest. Author contribution L.C.H. wrote the first draft, L.C.H., K.A.S., D.J.O. and U.N.N.I. conducted the literature search, evaluated the papers and extracted data. S.B. conceived the review question and was responsible for overall supervision. All authors contributed to this manuscript. References [1] Department of Innovation Universities and Skills, Government Office for Science. Tacking obesities: future choices – summary of key messages; 2007. [WWW document, cited 10.05. 2011]. [2] National Health Service. NHS obesity – NHS choices introduction; 2011. [WWW document cited 11.05.2011]. [3] Walsh SW. Obesity: a risk factor for preeclampsia. Trends Endocrinol Metab 2007;18:365–70. [4] Symonds EM, Symonds IM. Essential obstetrics and gynaecology. 4th ed. London: Churchill Livingstone; 2004. [5] Draycott T, Lewis G, Stephens I. Saving mothers’ lives 2006–2008: executive summary. BJOG 2011;118:e12–21. [6] Bhattacharya S, Campbell DM, Liston WA, Bhattacharya S. Effect of Body Mass Index on pregnancy outcomes in nulliparous women delivering singleton babies. BMC Public Health 2007;7:168. [7] Duckitt K, Harrington D. Risk factors for pre-eclampsia at antenatal booking: systematic review of controlled studies. BMJ 2005;330:549–50. [8] O’Brien TE, Ray JG, Chan W. Maternal BMI and the risk of preeclampsia: a systematic overview. Epidemiology 2003;14:368–74. [9] Sebire NJ, Jolly M, Harris JP, Wadsworth J, Joffe M, Beard RW, Regan L, Robinson S. Maternal obesity and pregnancy outcome: a study of 287,213 pregnancies in London. Int J Obes 2001;25:1175–82. [10] Modder J, Fitzsimons KJ. CMACE/RCOG joint guideline. Management of women with obesity in pregnancy; 2010. [WWW document, cited 09.05.2011]. [11] National Institute for Health and Clinical Excellence, NICE public health guidance 27. Dietary interventions and physical activity interventions for weight management before, during and after pregnancy; 2011. . [12] Rasmussen KM, Yaktine AL. Weight gain during pregnancy: reexamining the guidelines. 1st ed. Washington, DC: The National Academies Press; 2009. [13] Magee LA, Cham C, Waterman EJ, Ohlsson A, Von Dadelszen P. Hydralazine for treatment of severe hypertension in pregnancy: meta-analysis. BMJ 2003;327:1–10. [14] Meads CA, Cnossen JS, Meher S, Juarez-Garcia A, ter Riet G, Duley L, Roberts TE, Mol BW, van der Post JA, Leeflang MM, Barton PM, Hyde CJ, Gupta JK, Khan KS. Methods of Prediction and Prevention of Preeclampsia: systematic reviews of accuracy and effectiveness literature with economic modelling. Health Technol Assess 2008;12:1–270.
L.C. Ho et al. / Pregnancy Hypertension: An International Journal of Women’s Cardiovascular Health 2 (2012) 341–349 [15] Dodd JM, Grivell RM, Crowther CA, Robinson JA. Antenatal interventions for overweight pregnant women: a systematic review of randomised trials. BJOG 2010;117:1316–26. [16] Centre for Reviews and Dissemination. Systematic reviews: CRD’s guidance for undertaking reviews in health care. University of York, York: CRD; 2009. [17] National Health Service (NHS). Solutions for public health. Critical appraisal skills programme; 2010. [WWW document, cited 08.05.2011]. [18] Scottish Intercollegiate Guidelines Network. Annex C. Methodology Checklist 2: randomised controlled trials. In: Scottish Intercollegiate Guidelines Network, Sign 50: a guideline developer’s handbook. 1st ed. Edinburgh: Scottish Intercollegiate Guidelines Network; 2008. p. 56–7. [19] Wolff S, Legarth J, Vangsgaard K, Toubro S, Astrup A. A randomized trial of the effects of dietary counseling on gestation weight gain and glucose metabolism in obese pregnant women. Int J Obes 2008;32:495–501. [20] Rae A, Bond D, Sharon E, North F, Roberman B, Walters B. A randomised controlled trial of dietary energy restriction in the
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management of obese women with gestational diabetes. Aust NZ J Obstet Gynaecol 2000;40:416–22. Guelinckx I, Devlieger R, Mullie P, Vansant G. Effect of lifestyle intervention on dietary habits, physical activity, and gestational weight gain in obese pregnant women: a randomized controlled trial. Am J Clin Nutr 2009;91:373–80. Thornton YS, Smarkola C, Kopacz SM, Ishoof SB. Perinatal outcomes in nutritionally monitored obese pregnant women: a randomised controlled trial. J Natl Med Assoc 2009;101:569–77. Polley BA, Wing RR, Sims CJ. Randomized controlled trial to prevent excessive weight gain in pregnant women. Int J Obes Relat Metab Disord 2002;26:1494–502. Jeffries K, Shub A, Walker S, Hiscock R, Permezel M. Reducing excessive weight gain in pregnancy: a randomised controlled trial. Med J Aust 2009;191:429–33. Campbell DM, MacGillivray I. The effect of a low calorie diet or a thiazide diuretic on the incidence of pre-eclampsia and on birth weight. Br J Obstet Gynaecol 1975;82:572–7. Germain A, Brunaud L. Visceral surgery and pregnancy. J Visc Surg 2010;147:182–9.
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Pregnancy Hypertension: An International Journal of Women’s Cardiovascular Health journal homepage: www.elsevier.com/locate/preghy
Review
Are antenatal weight management interventions effective in preventing pre-eclampsia? Systematic review of randomised control trials Lisa Cuiying Ho a, Karin Anna-Lovisa Saunders a, Deborah Jane Owen a, Umi Nursheila Nur Ibrahim a, Sohinee Bhattacharya b,⇑ a b
Department of Obstetrics and Gynaecology, University of Aberdeen, United Kingdom Epidemiology Group, Institute of Applied Health Sciences, University of Aberdeen, United Kingdom
a r t i c l e
i n f o
Article history: Received 4 November 2011 Accepted 1 March 2012 Available online 18 March 2012 Keywords: Obesity Overweight Body Mass Index Preeclampsia Systematic review
a b s t r a c t Introduction: Pre-eclampsia, defined as the development of hypertension and proteinuria after 20 weeks gestation, carries significant maternal and foetal risk. Pre-pregnancy BMI is the most useful predictor of pre-eclampsia. As the prevalence of obesity increases, prevention of pre-eclampsia by weight management strategies needs to be trialed. Aims and objectives: To review the randomised controlled trials studying clinical effectiveness of antenatal weight management interventions compared to routine care in decreasing the incidence of pre-eclampsia in women with BMI 26 kg/m2 or greater. Methods: Electronic bibliographic databases were searched using a systematic search strategy to identify relevant trials. All trials involving weight management during pregnancy were considered. Using pre-determined inclusion criteria, six trials were included in this review and were independently assessed using standardised evaluation criteria. Results: Three studies found a significant difference in gestational weight gain; amongst the intervention groups, the smallest was 5.0 kg, whereas the largest was 13.6 kg. In sub-group analysis, one trial found a significant difference in the incidence of pre-eclampsia between adherent (2/90) and non-adherent participants (5/26). However, no significant difference was found in the overall incidence of pre-eclampsia across all intervention and control groups. Conclusion: There was no evidence to suggest that antenatal weight management interventions were effective in reducing the incidence of pre-eclampsia in women with a BMI P 26 kg/m2. Ó 2012 International Society for the Study of Hypertension in Pregnancy. Published by Elsevier B.V. All rights reserved.
Introduction Government figures estimate that 50% of UK women could be obese by 2050, costing the economy £49.9 billion ⇑ Corresponding author. Address: Dugald Baird Centre for Research on Women’s Health, Aberdeen Maternity Hospital, Cornhill Road, Aberdeen AB25 2ZD, United Kingdom. Tel.: +44 (0)1224 554672; fax: +44 (0)1224 553708. E-mail address: [email protected] (S. Bhattacharya).
per annum [1,2]. Obesity is a risk factor for developing preeclampsia in pregnancy [3]; as the prevalence of obesity increases, a greater proportion of women will enter pregnancy overweight or obese [1,4]. Defined as the development of hypertension (P140/90 mmHg) and proteinuria (P300 mg/24 h) occurring after 20 weeks gestation [4], pre-eclampsia is the third highest cause of maternal death in the UK [5]. It is associated with reduced placental perfusion and is the leading cause of premature delivery and intrauterine growth restriction [3].
2210-7789/$ - see front matter Ó 2012 International Society for the Study of Hypertension in Pregnancy. Published by Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.preghy.2012.03.003
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High Body Mass Index (BMI) has been consistently shown to have strong associations with adverse pregnancy outcomes [6,7]. Bhattacharya et al. demonstrated that every step up in BMI category carries an increase in risk; morbidly obese women with BMI P 40 kg/m2 are 7.2 times more likely to develop pre-eclampsia than healthy weight women [6]. O’Brien et al. calculated that the risk of preeclampsia doubles for every 5–7 kg/m2 increase in BMI [8]. Interestingly, a protective relationship with BMI below 20 kg/m2 and pre-eclampsia was found by Bhattacharya et al. [6] and Sebire et al. [9]. The latter noted that low BMI was protective against both the development of gestational diabetes and pregnancy induced hypertension. Pre-pregnancy BMI remains the most useful predictor for the development of pre-eclampsia to date [10]. Current NICE guidelines advise against dieting during pregnancy as low gestational weight gain (GWG) potentially restricts foetal growth, however pre-pregnancy weight reduction is recommended to minimise the risk of foetal and obstetric complications [11]. To date, there are no European guidelines recommending appropriate weight gain during pregnancy. The American Institute of Medicine (IOM) has published recommended limits, which have been referenced in several international clinical trials [12]. Definitive treatment for pre-eclampsia is delivery of the foetus. Antihypertensives such as hydralazine or labetalol can be used with the addition of magnesium sulphate, preventing progression to eclampsia if the infant is too premature to consider delivery [4]. The management of pre-eclampsia with medications is associated with side-effects and affects maternal and perinatal outcomes [13]. Ideally pre-eclampsia should be prevented rather than treated. Calcium supplements and low-dose aspirin have all been shown to be effective prophylactic treatments but are currently not recommended to be used as routine management [14]. There is a clear association between an elevated BMI and the development of pre-eclampsia, thus it is important to assess whether antenatal weight management is more effective compared with routine antenatal care as a primary prevention strategy. Reviews into the effects of antenatal weight interventions have been conducted previously [15]. Dodd et al. conducted a review of 9 randomised control trials (RCTs) that aimed to alter the dietary and lifestyle habits of pregnant women. The primary outcome measure was large-for-gestational age infants with pre-eclampsia as a secondary outcome for 5 of the RCTs [15]. The secondary data were often minimal, with many of the included studies reporting pre-eclampsia in only 1 or 2 participants. Some studies indicated that interventions had no significant effect on the incidence of preeclampsia but supplied no quantitative data. The reporting of secondary outcomes was inconsistent across all the reviewed trials and different BMI categories were often not explicitly stated. Another concern with the review by Dodd et al. is that the RCTs generally did not have enough power to make reliable conclusions on the secondary outcomes. No systematic reviews into the effectiveness of antenatal weight management interventions that focus on preeclampsia as a primary outcome currently exist. It is logical
to hypothesise that weight management interventions should impact on the development of pre-eclampsia in women with high BMI. Hence this review aims to assess whether antenatal weight management techniques are more effective compared with routine antenatal care as primary prevention strategies for pre-eclampsia. Methods A protocol was developed to review the evidence for the clinical effectiveness of antenatal weight management interventions for preventing pre-eclampsia. The methodology of this review draws from the methods developed by National Health Service Centre for Reviews and Dissemination guidance for undertaking reviews in health care [16]. At first a focused review question was developed using PICO structure – ‘‘How effective are antenatal weight management interventions for preventing pre-eclampsia?’’ From the facets of this review question search terms and inclusion and exclusion criteria were derived. Literature search The literature search conducted for this review included publications from 1970 to May 2011. Six electronic bibliographic databases; EMBASE, PubMed, MEDLINE, Cochrane Database of Systematic Reviews, NHS eLibrary and ClinicalTrials.gov were searched systematically without limits on date. MeSH terms and key words including ‘pregnancy’, ‘pre-eclampsia’, ‘obesity’, ‘diet’, ‘weight loss’, ‘lifestyle’, and ‘randomised controlled trial’ were combined with the Cochrane Collaboration strategy for identifying primary studies. The MEDLINE search strategy was adapted for searching other databases. Reference lists of all articles were checked to identify other relevant studies. Searches were limited to English-language studies in humans. Due to time constraints, searching of grey literature and hand searching were not done, nor were any experts contacted. Study selection Inclusion and exclusion criteria were developed a priori based on the review question. All RCTs involving interventions designed to influence maternal weight during the antenatal period were included. No restrictions were placed on the nature (dietary, exercise, behavioural or awareness based), duration or intensity of the interventions. Interventions were considered whether delivered on a one-to-one basis or to groups of participants and compared to routine care, defined as no change in usual standard of care delivered. Studies conducted in any healthcare or community setting on any participants regardless of parity or co-morbidities were included. Trials were excluded if the intervention was not delivered to overweight or obese participants (BMI P 26 kg/m2 and BMI P 30 kg/m2 respectively as defined in all studies appraised). Studies were excluded if no data presented in tables, figures, or text allowed a quantitative measurement of the incidence of preeclampsia and effectiveness of the intervention.
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Quality assessment and data extraction Included studies were reviewed and critically appraised independently by two of the authors. Studies were reviewed independently by a third party if any disagreement was found. Study quality was initially assessed using the critical appraisal skills programme (CASP) RCT appraisal tool then scored on quality using an in-house modified version of the SIGN 50 Checklist. The CASP tool [17] was used as a quick screening tool to determine if the study was of sufficient quality to be further evaluated. The published SIGN 50 checklist for RCTs [18] was modified to the specifics of the question set in this review. Briefly, we assessed the quality of all included studies in accordance with the following items: focus of the research, randomisation, concealment allocation, blinding, loss to follow-up, sample size, participant selection, comparability of groups, intention to treat analysis, categorisation and assessment of primary measures and outcomes. Results Study selection and quality assessment of included studies A total of 626 RCTs were identified using the previously outlined methodology (Fig. 1). Following the removal of duplicates 450 RCTs were considered for inclusion. After exclusions, six studies were finally included in the review and their quality assessed.
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Following the initial screening of each study using the CASP tool all six studies were of sufficient quality to warrant further assessment. The use of the modified SIGN checklist allowed the quality of each study to be designated a quality score. Wolff et al. and Rae et al. were considered high quality [19,20]. Guelinckx et al. received the lowest score principally due to a lack of reported data [21]. Study characteristics and detailed quality assessment of studies The characteristics and quality assessment of each study are presented in Tables 1 and 2 respectively. Six RCTs were analysed, with a total population of 867 pregnant women with age ranging from 18 to 45 years. Of the total population, 654 were of BMI P 26 kg/m2. As seen from Table 1, the studies by Wolff et al. [19] and Thornton et al. [22] had populations with BMI P 30 kg/ m2 while Polley et al. [23] and Jeffries et al. [24] recruited women with BMI P 19.8 kg/m2 and any BMI respectively. Each study had more than 100 participants except for one [21] (Table 2) and all but two studies were carried out at a single site [22,24]. The population in each study differed from one another as Table 1 shows; two studies [19,21] had purely Caucasian population and while Rae et al. [20] included diabetic women, three other studies excluded them [21,22,24]. All six study designs were parallel with two arms except for Guelinckx et al. [21], which ran three arms to compare passive and active interventions
Fig. 1. Flow chart of selection of studies for review.
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Table 1 Study characteristics. Population
Intervention
Secondary
Dietician-instructed non-restricted diabetic diet (approx. 8600–9500 kJ) n = 54 Standard care n = 53 (22 overweight)
Energy intake GWG Diabetes control
Maternal and obstetric outcomes
GWG Behavioural changes during pregnancy
Maternal, obstetric and birth outcomes Postpartum weight loss and weight retention
Ten 1 h consultation with dietician GWG restricted to 6–7 kg Energy intake restricted based on individual n = 23
No consultation with dietician No weight gain/intake restriction n = 27
Energy intake GWG Glucose metabolism
Maternal, obstetric and birth outcomes
Personalised weight gain recommendations n = 125 (20 overweight, 25 obese)
Standard care n = 111 (18 overweight, 21 obese)
GWG
Maternal, obstetric and neonatal outcomes
Active and behavioural intervention consisting of detailed dietary guidelines and daily self-recording of dietary intake n = 116 Passive intervention group: brochure n = 37 Active intervention group: brochure and three sessions with a nutritionist n = 42
Conventional prenatal guidelines n = 116
GWG Maternal, obstetric and birth outcomes Dietary habits Physical activity GWG
Comparison of primary outcomes between adherent and non-adherent participants in study group
Australia Inclusion: Diabetic BMI > 27.5 6 35 weeks gestation + 6 days Exclusion: Not stated
Dietician-instructed 6800–7600 kJ restricted diet n = 63
Polley et al. (2002)
USA Inclusion: low income BMI > 19.8 > 18 years old < 20 weeks gestation Exclusion: BMI < 19.8 Age 12 weeks gestation High risk pregnancy (drug abuse, chronic health problems, serious complications during pregnancy, multiple pregnancy) Denmark Inclusion: Caucasian BMI P 30 15 ± 3 weeks gestation Exclusion: Smoking Age 45 Multiple pregnancy Medical complications that affect foetal growth or contraindicate weight gain limitation Australia Inclusion: Any BMI 6 14 weeks gestation Exclusion: Age < 18 or age > 45 Diabetic Multiple pregnancy Non-English speaking USA Inclusion: BMI P 30 12–28 weeks gestation singleton Exclusion: Pre-existing diabetes, hypertension, chronic renal disease
Stepped-care behavioural intervention (i.e. more intensive interventions if women exceeded target weight) n = 57 (27 overweight)
Jeffries et al. (2009)
Thornton et al. (2009)
Guelinckx et al. (2009)
Belgium Inclusion: Caucasian BMI > 29.0 < 15 weeks gestation Exclusion: Pre-existing diabetes or developing GDM Multiple pregnancy Recruitment after 15 weeks gestation Delivery 29 kg/ m2. The overweight women in the intervention group gained 0.42 kg per week compared to the control group who gained 0.54 kg (p = 0.01) while in the obese group, the results were 0.4 kg and 0.33 kg respectively (p = 0.27). However, when the results were combined to measure total GWG, the statistical significance was lost [24]. This seems to imply that GWG per week could be a more sensitive way of detecting clinical effectiveness of weight interventions in pregnant women compared to total weight gain as it accounts for the heterogeneity of total gestation weeks. As shown in Table 3, there was a total of 25/308(8%) cases of pre-eclampsia in the entire population with BMI P 26 kg/m2 and in the intervention group. In addition, there were 6/125 cases of pre-eclampsia in the Jeffries et al. intervention group, although it is not certain how many of the 6 were of BMI P 26 kg/m2. In contrast, there
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Table 3 Detailed results of outcomes of the trials. Reference
Rae et al. (2000)
Polley et al. (2002)
Wolff et al. (2008)
Jeffries et al. (2009)
Thornton et al. (2009)
Guelinckx et al. (2009)
Study outcomes (intervention vs control group) Weight management
Pre-eclampsia incidence
Intake: Intervention: 6579 kJ Control: 6845 kJ p = 0.263 Total weight gain: Intervention: 11.56 kg (SE 1.32, range 7.50–0.00) Control: 9.68 kg (SE 1.45, range 5.00–0.00) p = 0.338 Total weight gain: (Normal weight) Intervention: 15.4 ± 7.1 kg (2.7–32.7 kg) Control: 16.4 ± 4.8 kg (6.8–30.9 kg) (Overweight) Intervention: 13.6 ± 7.2 kg (1.4–29.1 kg) Control: 10.1 ± 6.2 kg ( 0.9 to 26.4 kg) Intake: Intervention: 8619 ± 224 kJ/day Control: 9223 ± 1829 kJ/day p = 0.001 Total weight gain: Intervention: 6.6 ± 5.5 kg Control: 13.3 ± 7.5 kg p = 0.002 CI: 2.6–10.8 kg Total weight gain: (Overweight) Intervention: 10 kg (3.63SD) Control: 13.3 kg (3.57SD) p = 0.33 (Obese) Intervention: 9.5 kg (5.17SD) Control: 8.2 kg (3.02SD) p = 0.52 Weight gain per week: (Overweight) Intervention: 0.42 kg (0.153SD) Control: 0.54 kg (0.123SD) p = 0.01; 95% CI 0.03–0.22 (Obese) Intervention: 0.4 kg (0.226SD) Control: 0.33 kg (0.145SD) p = 0.27; 95% CI -0.18–0.05 Mean weight gain: Intervention: 11 lbs (14.96SD) 95% CI 8.59–14.10 Control: 31 lbs (16.31SD) 95% CI 27.82–33.82 p < 0.001 Pre-eclampsia: Intervention: 7/116 Control: 11/116 p = 0.326 Weight gain: Passive intervention: 10.9 ± 5.6 kg Active intervention: 9.8 ± 7.6 kg Control: 10.6 ± 6.9 kg p = 0.749
Intervention: 14/67 Control:13/58 p = 0.838
were 29/262 (11%) in the total study population with BMI P 26 kg/m2 and in the control group. There were 2/111 cases of pre-eclampsia in the study by Jeffries et al. but as mentioned before, it is uncertain how many of them were of BMI P 26 kg/m2 [24]. None of the studies found a statistically significant difference in the incidence of pre-eclampsia.
(Overweight) Intervention: 2/27 Control: 3/22 (Normal weight) Intervention: 0/30 Control: 0/31 Intervention: 0/23 Control: 1/27
Intervention: 6/125 Control: 2/111 p = 0.29; RR 2.68, CI 0.55–13.0
Adherent participants: 2/90 Non-adherent participants: 5/26 p < 0.01
Passive intervention: 0/37 Active intervention: 2/42 Control: 1/43 p = 0.436
Significant results for pre-eclampsia were, however, obtained by Thornton et al. when the intervention group was further analysed to compare those who were more compliant with the intervention than those who were not. The adherent group had a significantly decreased incidence (p < 0.01) of pre-eclampsia compared to the non-adherent group (Table 3). Although, when the intervention group
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was compared as a whole to the control group, the difference in the incidence of pre-eclampsia was not statistically significant (p = 0.326) [22] (Table 3). This could account for the apparent lack of effect of the weight reduction on preeclampsia incidence seen in the rest of the trials as the lack of adherence within the intervention groups could have led to the effect being lost.
Relationship between GWG and pre-eclampsia The relationship between mean GWG and incidence of pre-eclampsia across the six studies is presented in Fig. 2. We expected to see a proportional correlation between mean GWG and incidence of pre-eclampsia. Yet, when results from the intervention group were compared, the study with the highest mean GWG [23] did not have the highest percentage of pre-eclampsia patients in the intervention group and vice versa. This might be accounted for by the heterogeneity between the studies’ population. The study by Rae et al. consisted of a diabetic population, which is an additional risk factor for pre-eclampsia, hence it may account for their study having the highest preeclampsia incidence [20]. Similarly, when we compared the control groups’ results, we expected to see a significant increase in the incidence of pre-eclampsia. However, there were irregularities in the results. Despite Rae and Polley et al.’s [20,23] control group having a lower mean GWG than the intervention group, the former still had more women developing pre-eclampsia. On the other hand, Jeffries et al.’s [24] control population had fewer cases of pre-eclampsia even though they had a higher mean GWG than their intervention group. As seen in Fig. 2 and Table 3, there is little difference between the incidence of pre-eclampsia in the intervention group and the control group. Given the heterogeneity of the population and intervention, this seems to imply that weight reduction in overweight and obese women has
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little success in decreasing the incidence of pre-eclampsia effectively in clinical practice. Discussion Principal findings Cumulatively, the six trials examined 377 participants in the control group of which 31 (8.22%) women developed pre-eclampsia. In the intervention group 437 participants were studied and of these 31 (7.09%) participants developed pre-eclampsia. Overall, no statistically significant difference was found between the incidence of pre-eclampsia in the intervention group and the control. Some significant results were found in sub-group analyses, but the results often lacked sufficient power to support any conclusions. The evidence gathered for this review supports the null hypothesis – there is insufficient evidence to suggest that antenatal weight management interventions are effective in reducing the incidence of pre-eclampsia in women with a BMI P 26 kg/m2. Comparison with literature The lack of effectiveness of dietary interventions on preeclampsia has been observed previously. In 1975 Campbell and MacGillivray [25] showed that a calorie controlled diet had no effect on the incidence of pre-eclmapsia. In 2010 Dodd et al. [15] published a systematic review and metaanalysis of antenatal interventions for overweight or obese pregnant women. Pre-eclampsia was assessed as a secondary outcome. The outcome of the meta-analysis indicated that weight management interventions were not effective in altering mean GWG (overall effect p = 0.25; 95% CI 8.32 to 2.13) or the incidence of pre-eclampsia. The authors concluded that heterogeneity (I2 = 93%) between the studies, primarily in intervention, resulted in this effect.
Fig. 2. Relationship between mean GWG and pre-eclampsia across studies.
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Strengths and limitations Strengths of this review featured in the approach of our methodology structured by a clearly focused review question with specific exclusion and inclusion criteria. Only RCTs were included as we wanted to compare the effectiveness of the intervention to that of a control group. To identify appropriate studies an exhaustive search strategy was used. To minimise bias these studies were independently critically appraised by two authors and then assessed with a standardised modified checklist. Due to time constraints and limited resources, we were unable to follow-up on unpublished trials and papers that did not publish all of their data. It is unlikely that our results would have been affected as the findings of the studies were consistent with ours. Furthermore, the papers were not RCTs and would have possibly been excluded on the basis of study design. Interpretation of review findings Antenatal weight management has the potential to reduce the incidence of pre-eclampsia but the observed effect is not reliable as weight management was not achieved. Intervention design in terms of timing, nonadherence and heterogeneity amongst studies may also contribute to this finding. For example, Rae et al. included women just prior to 35 weeks gestation, which would have been insufficient time to achieve relevant weight management [20]. Thornton et al. showed in a sub-group analysis a significant difference between adherent participants and non-adherent participants, although the total numbers were small [22] adding weight to this hypothesis. Implications for future research and clinical practice Our findings implicate that other more specific factors could contribute to the achievement of appropriate weight management in overweight pregnant women. Ideally, programs should commence prior to conception. Studies should also incorporate a non-specific baseline demographic. Despite the overall results of this review, particular findings can be viewed as relevant to clinical practice. Policies focusing more on the quality of methods used to encourage compliance to the guided GWG than the quantity of weight restriction could yield a higher success rate. Behavioural modification in combination with dietary and exercise regimes may have a greater effect in influencing adherence. Moreover, weight can be managed just as effectively using passive intervention without expending an excess of resource and time as seen in Guelinckx et al. and Polley et al. [21,23]. Bariatric surgery is a future option for achieving weight reduction in the obese population however it is currently conducted only prior to pregnancy due to health concerns [26]. Future trials investigating the efficacy of weight management at preventing pre-eclampsia in overweight women should be conducted in a multi-disciplinary, multi-centred setting and in a larger scale to achieve clinically significant results. Additionally, the intervention programs
studied have shown that weight management during pregnancy is safe for women with a BMI P 26 kg/m2, therefore a review of present UK and IOM guidelines should be considered with the view to limiting GWG. Conclusion This review found no evidence to suggest that antenatal weight management interventions were effective in reducing the incidence of pre-eclampsia in women with a BMI P 26 kg/m2. Conflict of Interest The authors declare that they have no conflict of interest. Author contribution L.C.H. wrote the first draft, L.C.H., K.A.S., D.J.O. and U.N.N.I. conducted the literature search, evaluated the papers and extracted data. S.B. conceived the review question and was responsible for overall supervision. All authors contributed to this manuscript. References [1] Department of Innovation Universities and Skills, Government Office for Science. Tacking obesities: future choices – summary of key messages; 2007. [WWW document, cited 10.05. 2011]. [2] National Health Service. NHS obesity – NHS choices introduction; 2011. [WWW document cited 11.05.2011]. [3] Walsh SW. Obesity: a risk factor for preeclampsia. Trends Endocrinol Metab 2007;18:365–70. [4] Symonds EM, Symonds IM. Essential obstetrics and gynaecology. 4th ed. London: Churchill Livingstone; 2004. [5] Draycott T, Lewis G, Stephens I. Saving mothers’ lives 2006–2008: executive summary. BJOG 2011;118:e12–21. [6] Bhattacharya S, Campbell DM, Liston WA, Bhattacharya S. Effect of Body Mass Index on pregnancy outcomes in nulliparous women delivering singleton babies. BMC Public Health 2007;7:168. [7] Duckitt K, Harrington D. Risk factors for pre-eclampsia at antenatal booking: systematic review of controlled studies. BMJ 2005;330:549–50. [8] O’Brien TE, Ray JG, Chan W. Maternal BMI and the risk of preeclampsia: a systematic overview. Epidemiology 2003;14:368–74. [9] Sebire NJ, Jolly M, Harris JP, Wadsworth J, Joffe M, Beard RW, Regan L, Robinson S. Maternal obesity and pregnancy outcome: a study of 287,213 pregnancies in London. Int J Obes 2001;25:1175–82. [10] Modder J, Fitzsimons KJ. CMACE/RCOG joint guideline. Management of women with obesity in pregnancy; 2010. [WWW document, cited 09.05.2011]. [11] National Institute for Health and Clinical Excellence, NICE public health guidance 27. Dietary interventions and physical activity interventions for weight management before, during and after pregnancy; 2011. . [12] Rasmussen KM, Yaktine AL. Weight gain during pregnancy: reexamining the guidelines. 1st ed. Washington, DC: The National Academies Press; 2009. [13] Magee LA, Cham C, Waterman EJ, Ohlsson A, Von Dadelszen P. Hydralazine for treatment of severe hypertension in pregnancy: meta-analysis. BMJ 2003;327:1–10. [14] Meads CA, Cnossen JS, Meher S, Juarez-Garcia A, ter Riet G, Duley L, Roberts TE, Mol BW, van der Post JA, Leeflang MM, Barton PM, Hyde CJ, Gupta JK, Khan KS. Methods of Prediction and Prevention of Preeclampsia: systematic reviews of accuracy and effectiveness literature with economic modelling. Health Technol Assess 2008;12:1–270.
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