text:
aExact breakdown for exclusion not documented.
bThe Institute of Medicine 1990 guidelines differ from the 2009 guidelines. In the 1990 guidelines, the recommended weight gain range was 12.5 to 18 kg for women with a body mass index (BMI; calculated as weight in kilograms divided by height in meters squared) less than 19.8; 11.5 to 16 kg for women with a BMI of 19.8 to 26.0; 7 to 11.5 kg for women with a BMI between 26.0 and 29.0; and at least 6.8 kg for women with a BMI higher than 29.0.
Pooled ORs are shown for the association between gestational weight gain below (A) and above (B) guidelines with adverse outcomes. Reference group is women with recommended weight gain in each category of body mass index (BMI; calculated as weight in kilograms divided by height in meters squared). For each outcome, the sample size represents the total number of women in the studies that assessed the outcome. For each BMI category, the sample size represents the total number of women with gestational weight gain below or above the guidelines. LGA indicates large for gestational age; SGA, small for gestational age.
Pooled ORs are shown for the association between gestational weight loss (A), gestational weight gain below guidelines (B), and gestational weight gain above guidelines (C) with adverse outcomes. Obesity classes indicate body mass index (BMI; calculated as weight in kilograms divided by height in meters squared) as follows: class 1, BMI of 30 to 34.9; class 2, BMI of 35 to 39.9; and class 3, BMI of 40 or higher. Reference group is women with recommended weight gain in each category of BMI. For each outcome, the sample size represents the total number of women in the studies that assessed the outcome. For each obesity category, the sample size represents the total number of women with weight loss, gestational weight gain below the guidelines, or gestational weight gain above the guidelines.
Institute of Medicine. Nutrition During Pregnancy: Part I: Weight Gain, Part II Nutrient Supplements. Washington, DC: National Academies Press; 1990.
Rasmussen K, Yaktine AL, eds; Institute of Medicine; National Research Council. Weight Gain During Pregnancy: Reexamining the Guidelines. Washington, DC: National Academies Press; 2009.
Committee on Obstetric Practice, American College of Obstetricians and Gynecologists. Weight gain during pregnancy: committee opinion 548. January 2013, reaffirmed 2015. https://www.acog.org/-/media/Committee-Opinions/Committee-on-Obstetric-Practice/co548.pdf?dmc=1&ts=20160723T0702247216. Accessed July 23, 2016.
Monash Centre for Health Research and Implementation. Evidence Synthesis Program Template for Critical Appraisal of a Cohort Study. Melbourne, Australia: Monash Centre for Health Research and Implementation; 2014.
World Health Organization. WHO Recommendations on Antenatal Care for a Positive Pregnancy Experience. Geneva, Switzerland: World Health Organization; 2016.
Teede H, Harrison C, Lombard C, Boyle C, East C, Brown W. Case for Action proposal: obesity prevention through preventing excess weight gain during pregnancy and postpartum. September 2014. https://www.nhmrc.gov.au/research/research-translation/research-translation-faculty/ideas-research-translation-faculty-cases. Accessed August 31, 2016.
Question What is the association between gestational weight gain above or below the Institute of Medicine guidelines and maternal and infant outcomes?
Findings In this systematic review and meta-analysis of 1 309 136 pregnancies, gestational weight gain below recommendations (in 23% of women) was associated with higher risk of small for gestational age (odds ratio [OR], 1.53) and preterm birth (OR, 1.70) and lower risk of large for gestational age (OR, 0.59) and macrosomia (OR, 0.60). Gestational weight gain above recommendations (47%) was associated with lower risk of small for gestational age (OR, 0.66) and preterm birth (OR, 0.77) and higher risk of large for gestational age (OR, 1.85), macrosomia (OR, 1.95), and cesarean delivery (OR, 1.30).
Meaning Gestational weight gain below or above the Institute of Medicine guidelines was associated with higher risk of some adverse maternal and infant outcomes.
Importance Body mass index (BMI) and gestational weight gain are increasing globally. In 2009, the Institute of Medicine (IOM) provided specific recommendations regarding the ideal gestational weight gain. However, the association between gestational weight gain consistent with theIOM guidelines and pregnancy outcomes is unclear.
Objective To perform a systematic review, meta-analysis, and metaregression to evaluate associations between gestational weight gain above or below the IOM guidelines (gain of 12.5-18 kg for underweight women [BMI <18.5]; 11.5-16 kg for normal-weight women [BMI 18.5-24.9]; 7-11 kg for overweight women [BMI 25-29.9]; and 5-9 kg for obese women [BMI ≥30]) and maternal and infant outcomes.
Data Sources and Study Selection Search of EMBASE, Evidence-Based Medicine Reviews, MEDLINE, and MEDLINE In-Process between January 1, 1999, and February 7, 2017, for observational studies stratified by prepregnancy BMI category and total gestational weight gain.
Data Extraction and Synthesis Data were extracted by 2 independent reviewers. Odds ratios (ORs) and absolute risk differences (ARDs) per live birth were calculated using a random-effects model based on a subset of studies with available data.
Main Outcomes and Measures Primary outcomes were small for gestational age (SGA), preterm birth, and large for gestational age (LGA). Secondary outcomes were macrosomia, cesarean delivery, and gestational diabetes mellitus.
Results Of 5354 identified studies, 23 (n = 1 309 136 women) met inclusion criteria. Gestational weight gain was below or above guidelines in 23% and 47% of pregnancies, respectively. Gestational weight gain below the recommendations was associated with higher risk of SGA (OR, 1.53 [95% CI, 1.44-1.64]; ARD, 5% [95% CI, 4%-6%]) and preterm birth (OR, 1.70 [1.32-2.20]; ARD, 5% [3%-8%]) and lower risk of LGA (OR, 0.59 [0.55-0.64]; ARD, −2% [−10% to −6%]) and macrosomia (OR, 0.60 [0.52-0.68]; ARD, −2% [−3% to −1%]); cesarean delivery showed no significant difference (OR, 0.98 [0.96-1.02]; ARD, 0% [−2% to 1%]). Gestational weight gain above the recommendations was associated with lower risk of SGA (OR, 0.66 [0.63-0.69]; ARD, −3%; [−4% to −2%]) and preterm birth (OR, 0.77 [0.69-0.86]; ARD, −2% [−2% to −1%]) and higher risk of LGA (OR, 1.85 [1.76-1.95]; ARD, 4% [2%-5%]), macrosomia (OR, 1.95 [1.79-2.11]; ARD, 6% [4%-9%]), and cesarean delivery (OR, 1.30 [1.25-1.35]; ARD, 4% [3%-6%]). Gestational diabetes mellitus could not be evaluated because of the nature of available data.
Conclusions and Relevance In this systematic review and meta-analysis of more than 1 million pregnant women, 47% had gestational weight gain greater than IOM recommendations and 23% had gestational weight gain less than IOM recommendations. Gestational weight gain greater than or less than guideline recommendations, compared with weight gain within recommended levels, was associated with higher risk of adverse maternal and infant outcomes.
The purpose of this review and meta-analysis was to compare gestational weight gain with IOM guidelines from diverse international cohorts and to evaluate associations between gestational weight gain above and below guidelines with maternal and infant outcomes.
This systematic review, meta-analysis, and metaregression was prospectively registered with PROSPERO International Prospective Register of Systematic Reviews (PROSPERO identifier CRD42015023325).
A systematic search string of relevant terms was developed (eAppendix 1 in the Supplement). Searched databases in Ovid included EMBASE, all Evidence-Based Medicine Reviews, MEDLINE, and MEDLINE In-Process from January 1, 1999, to January 28, 2016 (Figure 1). The search was limited to articles from 1999 onward to represent more current populations. The search was later updated to February 7, 2017. Of 7 newly identified studies, 4 were included in the analyses. Three studies were excluded because the data were not in the required format, and there was insufficient time to obtain data from the authors. Bibliographies of included studies were reviewed to identify additional studies. Details of the search strategy and data extraction are shown in eAppendix 2 in the Supplement.
Observational studies published in English and assessing singleton pregnancies in women aged 18 years or older were included. Study sample sizes larger than 500 women were required to identify outcomes present across the BMI categories. We postulated that small studies would have insufficient sample size to detect outcomes within each BMI group. Studies were included if they presented data examining women by prepregnancy BMI category, stratified by the total gestational weight gain. Studies that categorized by mean weight gain per week were excluded. Only studies presenting odds ratios (ORs) stratified by maternal BMI and gestational weight gain were included. Studies that simultaneously adjusted for categories of BMI and gestational weight gain to estimate the independent associations of weight change with outcomes were excluded because the aim of this review was to assess the association of gestational weight gain (specific for each BMI category) and outcomes.
Studies meeting these criteria used different BMI categories (eg, Metropolitan Life Insurance Tables, WHO classifications, or Chinese classifications11 [BMI for underweight, <18.5; normal weight, 18.5-23.9; overweight, 24-28; and obese, ≥28]) and gestational weight gain categories (eg, 1990 IOM, 2009 IOM, population-specific, or study-specific categories) to classify participants. Additionally, some studies used a reference of normal gestational weight gain within each BMI group, whereas others used a reference of normal-weight women with normal weight gain.
In this review, BMI was defined by WHO categories and/or Chinese BMI categories. Gestational weight gain was defined by 2009 IOM criteria; thus, authors of identified studies were contacted to reanalyze data using these categories. The ORs were calculated using recommended gestational weight gain within each BMI category as the reference.
Gestational weight gain was defined as the difference between the final weight and the prepregnancy weight and was classified as below, within, or above the 2009 IOM guidelines. The prepregnancy weight was either self-reported (which correlates well with measured weight12,13) or measured at first antenatal visits. Final pregnancy weight was measured at the last antenatal visit or the time of delivery or was self-reported within 1 year of delivery.
Two authors assessed risk of bias (R.F.G. and S.K.A.). Discrepancies were resolved by consensus in discussion with a third reviewer (M.M.). Methodological quality of included studies was assessed using the Monash Centre for Health Research and Implementation evidence synthesis appraisal assessment tool.15,16 Individual quality items were assessed using a descriptive approach including exposure and outcome measures, reporting bias, confounding, and conflict of interest. Each study was classified as low, medium, or high risk of bias.
Findings were synthesized by target population characteristics, study type, and outcome. Outcome measures were produced for each study by calculating ORs and 95% confidence intervals, using recommended gestational weight gain within each BMI category as the reference. When 2 or more studies assessed the same outcome, results were pooled using both fixed- and random-effects meta-analysis. There were no significant differences between fixed- and random-effects analyses. Random effects are presented given heterogeneity among studies. Extracted pooled ORs for individual outcomes were combined to construct summary pooled ORs. Crude data were used where possible, given variable control for confounding factors. However, some articles presented adjusted ORs only.17-24 Absolute risk differences (ARDs) per live birth were calculated from event rates (available for a subset of studies) using random-effects meta-analysis.
Heterogeneity was assessed using the I2 statistic, where I2 > 50% indicated substantial heterogeneity.25 Metaregression was performed to investigate sources of heterogeneity (percentage of smokers during pregnancy, mean age, and percentage of nulliparous women). Race/ethnicity data were not available for the metaregression. Where 5 or more studies were available, publication bias was assessed using Egger test plots.26,27 Statistical significance was defined as 2-sided P < .05. Statistical analysis used Stata software version 14 (StataCorp LP).
A subgroup analysis was performed in specific population groups identified a priori (studies using Chinese or Korean BMI categories, not presented herein). Obesity subclasses were included after reviewing studies that stratified by obesity class. Tests for trend based on the Cochran-Armitage test in Stata were used to assess trends in this subgroup analysis.
Of 5874 studies identified by the initial search, 302 were selected for full-text review; 261 of these were excluded, leaving 41 (Figure 1). These studies grouped women by prepregnancy BMI category, stratified by total gestational weight gain. One study28 did not meet inclusion criteria as published; however, prior collaboration had made data available in the required format. Of 41 identified studies, 18 were excluded because data could not be obtained in the required format. Of these 18 studies, authors of 15 were contacted and unable to reanalyze and authors of 3 were not contacted from the updated search because of insufficient time prior to publication (eAppendix 2 in the Supplement). Overall, 23 cohort studies17-24,28-42 were included, involving 1 309 136 women. Of these 23 studies, 7 were included without contacting the authors because data were in the required format. Of 16 authors contacted, 13 reanalyzed data and were included; 3 provided additional information, thereby avoiding reanalysis.
Table 2 and Table 3 list characteristics of the studies (descriptive characteristics are shown in eTable 1 in the Supplement). Eighteen studies were retrospective, and 5 were prospective.20,29,32,33,42 Ten were from the United States,18-20,23,28,31,35,38,40,41 8 were from Asia (4 from China,21,29,32,36 2 from Korea,34,39 and 1 each from Taiwan24 and Japan22), and 5 were from Europe (1 each from Norway,33 Belgium,30 Italy,37 Denmark,42 and Sweden17). Sample sizes ranged from 1034 to 570 672 women.
Underweight women composed 7% (n = 94 399); normal-weight women, 55% (n = 720 456); overweight women, 18% (n = 235 295); and obese women, 20% (n = 258 986). Gestational weight gain was below, within, or above guidelines in 23% (n = 300 723), 30% (n = 387 409), and 47% (n = 621 004), respectively.
Figure 2 shows pooled ORs for primary and secondary outcomes. eFigure 1 in the Supplement shows pooled ORs for individual outcomes. eTable 2 in the Supplement reports event rates. eTable 3 and eFigure 2 in the Supplement report ARDs and P values. The ARDs are expressed as percentage difference per live birth.
Across BMI categories, gestational weight gain below guidelines was associated with higher risk for SGA than gestational weight gain within guidelines (OR, 1.53 [95% CI, 1.44 to 1.64]; I2 = 82.8%; ARD, 5% [95% CI, 4% to 6%]). This association was greatest in lower prepregnancy BMI (underweight: OR, 1.89 [95% CI, 1.67 to 2.14]; ARD, 8% [95% CI, 6% to 11%]; normal weight: OR, 1.63 [95% CI, 1.54 to 1.71]; ARD, 5% [95% CI, 4% to 6%]; overweight: OR, 1.34 [95% CI, 1.24 to 1.44]; ARD, 3% [95% CI, 3% to 4%]; and obese: OR, 1.24 [95% CI, 1.06 to 1.45]; ARD, 2% [95% CI, 2% to 3%]).
Compared with gestational weight gain within guidelines, gain above guidelines was associated with lower risk for SGA (OR, 0.66 [95% CI, 0.63 to 0.69]; I2 = 56%; ARD, −3% [95% CI, −4% to −2%]). The association was similar across BMI categories (underweight: OR, 0.62 [95% CI, 0.53 to 0.72]; ARD, −6% [95% CI, −8% to −3%]; normal weight: OR, 0.65 [95% CI, 0.62 to 0.68]; ARD, −2% [95% CI, −3% to−1%]; overweight: OR, 0.65 [95% CI, 0.59 to 0.71]; ARD, −3% [95% CI, −4% to −2%]; and obese: OR, 0.72 [95% CI, 0.65 to 0.80]; ARD, −2% [95% CI, −3% to −1%]).
Compared with gestational weight gain within guidelines, weight gain below guidelines was associated with higher risk for preterm birth (OR, 1.70 [95% CI, 1.32 to 2.20]; I2 = 97.3%; ARD, 5% [95% CI, 3% to 8%]). This association was greatest with lower BMI (underweight: OR, 2.41 [95% CI, 1.01 to 5.73]; ARD, 8% [95% CI, 1% to 15%]; normal weight: OR, 1.96 [95% CI, 1.17 to 3.29]; ARD, 6% [95% CI, 0% to 11%]; overweight: OR, 1.55 [95% CI, 1.10 to 2.19]; ARD, 4% [95% CI, −1% to 9%]; and obese: OR, 1.20 [95% CI, 1.03 to 1.40]; ARD, 3% [95% CI, 1% to 5%]).
Gestational weight gain above guidelines was associated with lower risk for preterm birth (OR, 0.77 [95% CI, 0.69 to 0.86]; I2 = 78.7%; ARD, −2% [95% CI, −2% to −1%]). This association was significant for normal-weight and overweight women (underweight: OR, 0.80 [95% CI, 0.50 to 1.28]; ARD, −1% [95% CI, −3% to 0%]; normal weight: OR, 0.76 [95% CI, 0.59 to 0.97]; ARD, −1% [95% CI, −2% to 0%]; overweight: OR, 0.70 [95% CI, 0.53 to 0.93]; ARD, −3% [95% CI, −5% to −1%]; and obese: OR, 0.76 [95% CI, 0.62 to 0.93]; ARD, −2% [95% CI, −5% to 2%]).
Gestational weight gain below guidelines was associated with lower risk of LGA than gestational weight gain within guidelines (OR, 0.59 [95% CI, 0.55 to 0.64]; I2 = 78.9%; ARD, −2% [95% CI, −10% to −6%]). This was significant for underweight and normal-weight women (underweight: OR, 0.41 [95% CI, 0.34 to 0.50]; ARD, −3% [95% CI, −5% to −1%]; normal weight: OR, 0.58 [95% CI, 0.54-0.62]; ARD, −3% [95% CI, −4% to −2%]; overweight: OR, 0.66 [95% CI, 0.62 to 0.70]; ARD, −11% [95% CI, −33% to 10%]; and obese: OR, 0.70 [95% CI, 0.64 to 0.76]; ARD, 13% [95% CI, −34% to 60%]).
Gestational weight gain above guidelines was associated with higher risk of LGA (OR, 1.85 [95% CI, 1.76 to 1.95]; I2 = 74.6%; ARD, 4% [95% CI, 2% to 5%]). The association increased as BMI decreased (underweight: OR, 2.17 [95% CI, 1.81 to 2.60]; ARD, 4% [95% CI, 4% to 5%]; normal weight: OR, 1.95 [95% CI, 1.83 to 2.08]; ARD, 6% [95% CI, 5% to 7%]; overweight: OR, 1.79 [95% CI, 1.61 to 1.98]; ARD, −2% [95% CI, −14% to 9%]; and obese: OR, 1.63 [95% CI, 1.56 to 1.70]; ARD, 7% [95% CI, 5% to 8%]).
Gestational weight gain below guidelines was associated with lower risk of macrosomia (OR, 0.60 [95% CI, 0.52 to 0.68]; I2 = 66.3%; ARD, −2% [95% CI, −3% to −1%]). The association was strongest in underweight women (underweight: OR, 0.43 [95% CI, 0.27 to 0.69]; ARD, −1% [95% CI, −3% to 0%]; normal weight: OR, 0.54 [95% CI, 0.43 to 0.68]; ARD, −2% [95% CI, −5% to 1%]; overweight: OR, 0.73 [95% CI, 0.60 to 0.89]; ARD, −2% [95% CI, −6% to 2%]; and obese: OR, 0.70 [95% CI, 0.59 to 0.82]; ARD, −3% [−4% to −2%]).
Gestational weight gain above guidelines was associated with higher risk of macrosomia (OR, 1.95 [95% CI, 1.79 to 2.11]; I2 = 58.2%; ARD, 6% [95% CI, 4% to 9%]). This association was strongest in underweight women according to the ORs, and all associations were significant according to the ARDs (underweight: OR, 2.31 [95% CI, 1.62 to 3.29]; ARD, 3% [95% CI, 2% to 4%]; normal weight: OR, 2.01 [95% CI, 1.77 to 2.27]; ARD, 10% [95% CI, 5% to 15%]; overweight: OR, 1.90 [95% CI, 1.54 to 2.33]; ARD, 5% [95% CI, 1% to 10%]; and obese: OR, 1.83 [95% CI, 1.52 to 2.22]; ARD, 6% [95% CI, 1% to 12%]).
Eight studies assessed cesarean delivery. Seven included emergency and elective deliveries,22,28,29,33,36,37,39 and 1 did not specify.24 One study28 included repeated cesarean delivery (total cesarean deliveries), 1 included primary cesarean delivery only,24 and 6 did not distinguish these.
Gestational weight gain below guidelines was not significantly associated with cesarean delivery (OR, 0.98 [95% CI, 0.96 to 1.02]; I2 = 62.6%; ARD, 0% [−2% to 1%]).
Gestational weight gain above guidelines was associated with higher risk of cesarean delivery (OR, 1.30 [95 CI, 1.25 to 1.35]; I2 = 21.9%; ARD, 4% [95% CI, 3% to 6%]). The ARD was significant for underweight women only (underweight: OR, 1.45 [95% CI, 1.22 to 1.71]; ARD, 6% [95% CI, 1% to 12%]; normal weight: OR, 1.30 [95% CI, 1.24 to 1.36]; ARD, 0% [95% CI, −4% to 3%]; overweight: OR, 1.29 [95% CI, 1.21 to 1.39]; ARD, 1% [0% to 3%]; and obese: OR, 1.22 [95% CI, 1.05 to 1.42]; ARD, −2% [95% CI, −5% to 1%]).
Six studies assessed GDM, but they did not use consistent definitions and had different findings for gestational weight gain above guidelines and GDM risk. Black et al28 defined GDM by International Association of Diabetes in Pregnancy Study Groups criteria and included only women not treated for hyperglycemia (the center used different criteria in clinical practice and excluded those treated). They found no association between weight gain above guidelines and GDM in the underweight, normal-weight, and obese groups but reported lower risk in overweight women. Enomoto et al22 used International Association of Diabetes in Pregnancy Study Groups criteria, with higher risk in normal-weight women and lower risk in overweight women. Durst et al23 used Carpenter-Coustan criteria and found no association. Hung and Hsieh24 used Carpenter-Coustan and International Association of Diabetes in Pregnancy Study Groups criteria and found an association of gestational weight gain above guidelines with lower risk of GDM in overweight and obese women. Li et al36 included both impaired glucose tolerance and type 2 diabetes by WHO criteria, with weight gain above guidelines associated with lower risk of GDM in all groups except obese women. Shin and Song31 used self-reported GDM and found an association of gestational weight gain above guidelines with lower risk in all groups except underweight women.
An intended meta-analysis of gestational weight gain and its relationship to GDM could not be completed because of inconsistent definitions and treatments.
Obesity classes include the following: class 1, BMI of 30 to 34.9; class 2, BMI of 35 to 39.9; and class 3, BMI of 40 or higher. Obese studies generally included a subgroup-defined weight loss as well as gestational weight gain below, within, or above guidelines. Three studies assessed outcomes stratified by BMI classes 1 through 3.17,18,30 Another study35 investigated only superobese women (BMI ≥50) and was included in the obesity class 3 analysis. These 4 studies were included in the subgroup analysis only (not in the overall meta-analyses). Class 1 included 67% of women; class 2, 22%; and class 3, 11%. Weight loss and gestational weight gain below, within, or above recommendations occurred in 6%, 13%, 25%, and 57% of pregnancies, respectively.
Figure 3 summarizes pooled ORs for primary (SGA and LGA) and secondary (macrosomia and cesarean delivery) outcomes. eFigure 3 in the Supplement shows pooled ORs for individual outcomes. eTable 4 in the Supplement reports ARDs and P values. Only 1 study35 assessed preterm birth and GDM in the obese subgroups, preventing meta-analysis. Kominiarek et al18 provided separate ORs for nulliparous and multiparous women (multiparous values used herein), whereas other studies combined women with different parity into 1 group.
Weight loss and weight gain below guidelines were associated with higher SGA risk (weight loss: OR, 1.79 [95% CI, 1.56 to 2.05]; I2 = 0%; ARD, 3% [95% CI, 1% to 5%]; weight gain below guidelines: OR, 1.27 [95% CI, 1.14 to 1.41]; I2 = 20.7%; ARD, 1% [95% CI, 1% to 1%]). Gestational weight gain above guidelines was associated with lower SGA risk (OR, 0.62 [95% CI, 0.57 to 0.67]; I2 = 13.5%; ARD, −1% [−2% to 0%]). Weight gain in class 1 had the strongest association with lower SGA risk (lowest OR, 0.58; 95% CI, 0.53 to 0.72]; P for trend < .001).
Weight loss and gestational weight gain below guidelines were associated with lower LGA risk (weight loss: OR, 0.58 [95% CI, 0.52 to 0.66]; I2 = 11.6%; ARD, −5% [95% CI, −7% to −3%]; weight gain below guidelines: OR, 0.77 [95% CI, 0.71 to 0.84]; I2 = 0%; ARD, −2% [95% CI, −3% to −1%]). Weight loss in class 3 had the strongest association with lower LGA risk (lowest OR, 0.53 [95% CI, 0.41 to 0.67]; P for trend < .001). Weight gain above guidelines was associated with higher LGA risk (OR, 1.79 [95% CI, 1.70 to 1.89]; I2 = 69.3%; ARD, 5% [95% CI, 5% to 6%]). LGA was most strongly associated with class 1 obesity compared with the other classes (highest OR, 1.87 [95% CI, 1.75 to 2.00]; P for trend < .001).
Three studies assessed macrosomia, defined as birth weight greater than 4000 g in 1 study,30 greater than 4500 g in 1 study,18 and both greater than 4000 g and greater than 4500 g in 1 study.35 Meta-analysis used data for birth weight greater than 4000 g.
Weight loss and gestational weight gain below guidelines were associated with lower macrosomia risk (weight loss: OR, 0.46 [95% CI, 0.36 to 0.58]; I2 = 34.0%; ARD, −5% [95% CI, −9% to −2%]; weight gain below guidelines: OR, 0.76 [95% CI, 0.68 to 0.86]; I2 = 0%; ARD, −2% [95% CI, −3% to 0%]). Low weight gain in class 3 had the strongest association with lower macrosomia risk (lowest OR, 0.64 [95% CI, 0.49 to 0.85]; P for trend = .046). Gestational weight gain above guidelines was associated with higher risk of macrosomia (OR, 1.60 [95% CI, 1.46 to 1.75]; I2 = 66.9%; ARD, 3% [95% CI, 0% to 6%]).
Four studies assessed cesarean delivery. They included emergency,30 emergency and elective,18,35 and undefined17 indications for cesarean delivery.
Weight loss and gestational weight gain below guidelines were associated with lower risk of cesarean delivery (weight loss: OR, 0.78 [95% CI, 0.72 to 0.85]; I2 = 34.3%; ARD, −4% [95% CI, −6% to −3%]; weight gain below guidelines: OR, 0.87 [95% CI, 0.82 to 0.93]; I2 = 0%; ARD, −2% [95% CI, −3% to −1%]). Gestational weight gain above guidelines was associated with higher risk of cesarean delivery (OR, 1.21 [95% CI, 1.16 to 1.25]; I2 = 0%; ARD, 2% [95% CI, 0% to 3%]).
Substantial heterogeneity (I2 > 50%) was present for gestational weight gain below and above guidelines for SGA, preterm birth, LGA, and macrosomia and for gestational weight gain above guidelines for cesarean delivery. When sufficient data were available, metaregression analysis was performed to investigate possible sources of heterogeneity: percentage of smokers during pregnancy, mean age, and percentage of nulliparous women (eTable 5 in the Supplement). The obese subgroups had insufficient studies to perform metaregression.
Gestational weight gain above guidelines and LGA demonstrated a source for heterogeneity (P = .04); specifically, there was an association between the treatment effect and the covariate smoking (P = .02). For gestational weight gain below guidelines and preterm birth, mean maternal age was the only covariate associated with outcome, where the risk for preterm birth varied by maternal age due to the heterogeneity in maternal age in included studies (P = .03); however, the overall P value was not significant (P = .09). Heterogeneity was unexplained for remaining outcomes.
There was no evidence of publication bias for SGA, LGA, macrosomia or cesarean delivery (eFigure 4 in the Supplement). Assessment for publication bias was not performed for preterm births (<5 studies).
Participants were selected from maternity clinics or from large data sets (Table 4). Apart from 3 studies,19,23,32 inclusion and exclusion criteria were adequately described. Performance bias (a potential difference in the care provided between BMI groups) was difficult to assess. Very few studies provided information regarding diet and/or exercise advice given and whether this differed between groups. Overweight and obese women were possibly treated more intensively, which could introduce bias.
Three studies demonstrated moderate bias risk19,21,31 and 20 demonstrated low bias risk.17,18,20,22-24,28-30,32-42 Reasons for moderate bias risk included self-reported final weight (detection bias), self-reported outcome measures (detection bias), failure to report all outcomes (report bias), and insufficient adjustment for confounding variables (confounding bias). Nineteen studies reported no conflict of interest.
Quiz Ref IDIn this analysis of 1 309 136 pregnancies from diverse international cohorts, gestational weight gain below or above 2009 IOM guidelines among women across the BMI range was associated with greater risk for maternal and infant adverse outcomes. Underweight women composed 7%; normal-weight women, 55%; overweight women, 18%; and obese women, 20%. For gestational weight gain, 23% gained below and 47% gained above guidelines. Compared with recommended gestational weight gain, gain below guidelines was associated with 5% higher risk of both SGA and preterm birth and 2% lower risk of both LGA and macrosomia. Weight gain above guidelines was associated with 3% lower risk of SGA and 2% lower risk of preterm birth and 4%, 6%, and 4% higher risk of LGA, macrosomia, and cesarean delivery, respectively.
Gestational weight gain below guidelines was associated with higher SGA risk, with greatest risk in underweight women, as shown previously.43,44 Obesity was associated with higher risk of SGA, with weight loss and gestational weight gain below guidelines increasing risks, similar to prior systematic reviews.26,45,46 Underweight status combined with gestational weight gain below recommendations as well as obese status combined with gestational weight loss present the highest risk groups for SGA, at 8% and 3%, respectively.
Gestational weight gain below guidelines was associated with lower risks of LGA and macrosomia. This association was lowest in underweight women. Weight gain above guidelines was associated with higher risks of LGA and macrosomia, with ARDs of 4% and 6% greater risks, respectively. Underweight status was associated with the greatest risk. This is similar to the 2009 IOM report6 that stated, “the lower the prepregnancy BMI, the stronger the association between increased gestational weight gain and birthweight”; it may be related to higher absolute weight gain in underweight women.1 Animal studies suggest that baseline maternal BMI and gestational weight gain are associated with changes in the hormonal milieu, including insulin resistance.50 Similarly, excess weight gain in underweight women may be associated with greater changes in the hormonal milieu and placental function than in normal-weight or overweight women. Weight gain above guidelines was associated with increased risk of cesarean delivery across the BMI spectrum.
Quiz Ref IDSimilarly, within the obese subgroups, weight loss was associated with a 5% lower risk for both LGA and macrosomia and 4% lower risk for cesarean delivery. Weight gain below guidelines was associated with 2% lower risk across all these outcomes. Class 3 obesity combined with weight loss was associated with the greatest LGA risk reduction. Gestational weight gain above guidelines was associated with increased LGA risk. Class 1 obesity was associated with the greatest risk for LGA, which may be partly due to higher absolute weight gain in less obese women.10 While other systematic reviews have assessed gestational weight gain below guidelines,26 to our knowledge, this is the first review exploring relationships between weight gain above guidelines and outcomes within obesity classes.
While GDM has adverse maternal and infant outcomes51 and is related to maternal BMI and possibly to gestational weight gain, associations could not be assessed because of heterogeneity of diagnosis and treatment as well as the potential effect of GDM treatment on gestational weight gain. Prior systematic reviews have not demonstrated that healthy lifestyle and gestational weight gain reduced rates of GDM,14 even in high-risk populations.52 Consistent diagnostic criteria and reporting of gestational weight gain at GDM diagnosis are needed to study associations between gestational weight gain and GDM.
Lifestyle interventions in pregnancy can help women attain recommended gestational weight gain.14 Optimal interventions and effects on outcomes are currently being studied in a large-scale international individual patient data meta-analysis.53 The WHO has prioritized achievement of ideal BMI prior to conception and prevention of excess gestational weight gain.54 Identification of women prior to conception and implementing healthy lifestyle strategies before and during pregnancy have yet to be integrated into routine health care,55 requiring research implementation.
Strengths of this review are the inclusion of common maternal and infant risks associated with gestational weight gain below and above the 2009 IOM guidelines in women across the prepregnancy BMI spectrum and across international cohorts. Four databases were searched, a risk of bias appraisal was performed, and reanalyses were undertaken, allowing inclusion of data from more than 1.3 million pregnant women globally. Collaboration with other authors facilitated more homogeneous data, data integration, and meta-analysis.
This study has limitations. It lacks studies from developing countries and excluded non-English-language articles. Fifteen of 31 authors contacted were unable to reanalyze data, so these studies were excluded from the meta-analysis. A meta-analysis could not be performed for GDM because of inconsistent primary data. Some outcomes were assessed in only 1 study, precluding meta-analysis. Inconsistent definitions of preterm birth, cesarean delivery, and macrosomia limited interpretation of findings. Study heterogeneity may have affected reliability of results, although the metaregression did not identify characteristics responsible for this heterogeneity. Studies published before 2009 IOM guidelines were included, and gestational weight gain targets before and after these guidelines may have differed. Preterm birth was not adjusted for gestational age, potentially resulting in less total gestational weight gain than would have been otherwise attained. Spontaneous and induced preterm birth were not clearly differentiated, and studies did not distinguish between emergency and elective or primary and repeated cesarean deliveries. These factors may limit interpretation and underscore the importance of improving outcome definition reporting. Event rates were not available for all studies, limiting interpretation of ARDs. Findings from this review are based on observational data and no causal links may be concluded. They may be applicable on a population level, but recommendations need to be individualized when applied clinically.
Quiz Ref IDIn this systematic review and meta-analysis of more than 1 million pregnant women, 47% had gestational weight gain greater than IOM recommendations and 23% had gestational weight gain less than IOM recommendations. Gestational weight gain greater than or less than guideline recommendations, compared with gestational weight gain within recommended levels, was associated with higher risk of adverse maternal and infant outcomes.
Corresponding Author: Helena J. Teede, MBBS, FRACP, PhD, Monash University, 43-51 Kanooka Dr, Clayton, Melbourne, Victoria 3168, Australia (helena.teede@monash.edu).
Accepted for Publication: May 10, 2017.
Author Contributions: Dr Goldstein and Mr Ranasinha had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
Concept and design: Goldstein, Abell, Ranasinha, Misso, Teede.
Acquisition, analysis, or interpretation of data: Goldstein, Abell, Ranasinha, Boyle, Black, Li, Hu, Corrado, Rode, Y. J. Kim, Haugen, Song, M. H. Kim, Bogaerts, Devlieger, Chung, Teede.
Drafting of the manuscript: Goldstein, Teede.
Administrative, technical, or material support: Goldstein, Ranasinha, Teede.
Conflict of Interest Disclosures: All authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Dr Boyle reported serving on the Women’s Health Global Advisory Board for Pfizer. No other disclosures were reported.
Funding/Support: Dr Goldstein is supported by a Research Training Program scholarship from the Department of Education and Training. Dr Abell is supported by a scholarship from the National Health and Medical Research Council. Drs Boyle and Teede are supported by fellowships from the National Health and Medical Research Council.
Additional Contributions: Tiffany Moore Simas, MD (University of Massachusetts Medical School, Worcester), Sohyun Park, PhD (National Center for Chronic Disease Prevention and Health Promotion, Atlanta, Georgia), and Michelle Kominiarek, MD (University of Illinois at Chicago), assisted in providing additional data.

tokenized:
aExact breakdown for exclusion not documented .
 bThe Institute of Medicine 1990 guidelines differ from the 2009 guidelines . In the 1990 guidelines , the recommended weight gain range was 12.5 to 18 kg for women with a body mass index ( BMI ; calculated as weight in kilograms divided by height in meters squared ) less than 19.8 ; 11.5 to 16 kg for women with a BMI of 19.8 to 26.0 ; 7 to 11.5 kg for women with a BMI between 26.0 and 29.0 ; and at least 6.8 kg for women with a BMI higher than 29.0 .
 Pooled ORs are shown for the association between gestational weight gain below ( A ) and above ( B ) guidelines with adverse outcomes . Reference group is women with recommended weight gain in each category of body mass index ( BMI ; calculated as weight in kilograms divided by height in meters squared ) . For each outcome , the sample size represents the total number of women in the studies that assessed the outcome . For each BMI category , the sample size represents the total number of women with gestational weight gain below or above the guidelines . LGA indicates large for gestational age ; SGA , small for gestational age .
 Pooled ORs are shown for the association between gestational weight loss ( A ) , gestational weight gain below guidelines ( B ) , and gestational weight gain above guidelines ( C ) with adverse outcomes . Obesity classes indicate body mass index ( BMI ; calculated as weight in kilograms divided by height in meters squared ) as follows : class 1 , BMI of 30 to 34.9 ; class 2 , BMI of 35 to 39.9 ; and class 3 , BMI of 40 or higher . Reference group is women with recommended weight gain in each category of BMI . For each outcome , the sample size represents the total number of women in the studies that assessed the outcome . For each obesity category , the sample size represents the total number of women with weight loss , gestational weight gain below the guidelines , or gestational weight gain above the guidelines .
 Institute of Medicine . Nutrition During Pregnancy : Part I : Weight Gain , Part II Nutrient Supplements . Washington , DC : National Academies Press ; 1990 .
 Rasmussen K , Yaktine AL , eds ; Institute of Medicine ; National Research Council . Weight Gain During Pregnancy : Reexamining the Guidelines . Washington , DC : National Academies Press ; 2009 .
 Committee on Obstetric Practice , American College of Obstetricians and Gynecologists . Weight gain during pregnancy : committee opinion 548 . January 2013 , reaffirmed 2015 . https://www.acog.org/-/media/Committee-Opinions/Committee-on-Obstetric-Practice/co548.pdf?dmc=1&ts=20160723T0702247216 . Accessed July 23 , 2016 .
 Monash Centre for Health Research and Implementation . Evidence Synthesis Program Template for Critical Appraisal of a Cohort Study . Melbourne , Australia : Monash Centre for Health Research and Implementation ; 2014 .
 World Health Organization . WHO Recommendations on Antenatal Care for a Positive Pregnancy Experience . Geneva , Switzerland : World Health Organization ; 2016 .
 Teede H , Harrison C , Lombard C , Boyle C , East C , Brown W. Case for Action proposal : obesity prevention through preventing excess weight gain during pregnancy and postpartum . September 2014 . https://www.nhmrc.gov.au/research/research-translation/research-translation-faculty/ideas-research-translation-faculty-cases . Accessed August 31 , 2016 .
 Question What is the association between gestational weight gain above or below the Institute of Medicine guidelines and maternal and infant outcomes ?
 Findings In this systematic review and meta - analysis of 1   309   136 pregnancies , gestational weight gain below recommendations ( in 23 % of women ) was associated with higher risk of small for gestational age ( odds ratio [ OR ] , 1.53 ) and preterm birth ( OR , 1.70 ) and lower risk of large for gestational age ( OR , 0.59 ) and macrosomia ( OR , 0.60 ) . Gestational weight gain above recommendations ( 47 % ) was associated with lower risk of small for gestational age ( OR , 0.66 ) and preterm birth ( OR , 0.77 ) and higher risk of large for gestational age ( OR , 1.85 ) , macrosomia ( OR , 1.95 ) , and cesarean delivery ( OR , 1.30 ) .
 Meaning Gestational weight gain below or above the Institute of Medicine guidelines was associated with higher risk of some adverse maternal and infant outcomes .
 Importance Body mass index ( BMI ) and gestational weight gain are increasing globally . In 2009 , the Institute of Medicine ( IOM ) provided specific recommendations regarding the ideal gestational weight gain . However , the association between gestational weight gain consistent with theIOM guidelines and pregnancy outcomes is unclear .
 Objective To perform a systematic review , meta - analysis , and metaregression to evaluate associations between gestational weight gain above or below the IOM guidelines ( gain of 12.5 - 18 kg for underweight women [ BMI < 18.5 ] ; 11.5 - 16 kg for normal - weight women [ BMI 18.5 - 24.9 ] ; 7 - 11 kg for overweight women [ BMI 25 - 29.9 ] ; and 5 - 9 kg for obese women [ BMI ≥30 ] ) and maternal and infant outcomes .
 Data Sources and Study Selection Search of EMBASE , Evidence - Based Medicine Reviews , MEDLINE , and MEDLINE In - Process between January 1 , 1999 , and February 7 , 2017 , for observational studies stratified by prepregnancy BMI category and total gestational weight gain .
 Data Extraction and Synthesis Data were extracted by 2 independent reviewers . Odds ratios ( ORs ) and absolute risk differences ( ARDs ) per live birth were calculated using a random - effects model based on a subset of studies with available data .
 Main Outcomes and Measures Primary outcomes were small for gestational age ( SGA ) , preterm birth , and large for gestational age ( LGA ) . Secondary outcomes were macrosomia , cesarean delivery , and gestational diabetes mellitus .
 Results Of 5354 identified studies , 23 ( n   =   1   309   136 women ) met inclusion criteria . Gestational weight gain was below or above guidelines in 23 % and 47 % of pregnancies , respectively . Gestational weight gain below the recommendations was associated with higher risk of SGA ( OR , 1.53 [ 95 % CI , 1.44 - 1.64 ] ; ARD , 5 % [ 95 % CI , 4%-6 % ] ) and preterm birth ( OR , 1.70 [ 1.32 - 2.20 ] ; ARD , 5 % [ 3%-8 % ] ) and lower risk of LGA ( OR , 0.59 [ 0.55 - 0.64 ] ; ARD , −2 % [ −10 % to −6 % ] ) and macrosomia ( OR , 0.60 [ 0.52 - 0.68 ] ; ARD , −2 % [ −3 % to −1 % ] ) ; cesarean delivery showed no significant difference ( OR , 0.98 [ 0.96 - 1.02 ] ; ARD , 0 % [ −2 % to 1 % ] ) . Gestational weight gain above the recommendations was associated with lower risk of SGA ( OR , 0.66 [ 0.63 - 0.69 ] ; ARD , −3 % ; [ −4 % to −2 % ] ) and preterm birth ( OR , 0.77 [ 0.69 - 0.86 ] ; ARD , −2 % [ −2 % to −1 % ] ) and higher risk of LGA ( OR , 1.85 [ 1.76 - 1.95 ] ; ARD , 4 % [ 2%-5 % ] ) , macrosomia ( OR , 1.95 [ 1.79 - 2.11 ] ; ARD , 6 % [ 4%-9 % ] ) , and cesarean delivery ( OR , 1.30 [ 1.25 - 1.35 ] ; ARD , 4 % [ 3%-6 % ] ) . Gestational diabetes mellitus could not be evaluated because of the nature of available data .
 Conclusions and Relevance In this systematic review and meta - analysis of more than 1 million pregnant women , 47 % had gestational weight gain greater than IOM recommendations and 23 % had gestational weight gain less than IOM recommendations . Gestational weight gain greater than or less than guideline recommendations , compared with weight gain within recommended levels , was associated with higher risk of adverse maternal and infant outcomes .
 The purpose of this review and meta - analysis was to compare gestational weight gain with IOM guidelines from diverse international cohorts and to evaluate associations between gestational weight gain above and below guidelines with maternal and infant outcomes .
 This systematic review , meta - analysis , and metaregression was prospectively registered with PROSPERO International Prospective Register of Systematic Reviews ( PROSPERO identifier CRD42015023325 ) .
 A systematic search string of relevant terms was developed ( eAppendix 1 in the Supplement ) . Searched databases in Ovid included EMBASE , all Evidence - Based Medicine Reviews , MEDLINE , and MEDLINE In - Process from January 1 , 1999 , to January 28 , 2016 ( Figure 1 ) . The search was limited to articles from 1999 onward to represent more current populations . The search was later updated to February 7 , 2017 . Of 7 newly identified studies , 4 were included in the analyses . Three studies were excluded because the data were not in the required format , and there was insufficient time to obtain data from the authors . Bibliographies of included studies were reviewed to identify additional studies . Details of the search strategy and data extraction are shown in eAppendix 2 in the Supplement .
 Observational studies published in English and assessing singleton pregnancies in women aged 18 years or older were included . Study sample sizes larger than 500 women were required to identify outcomes present across the BMI categories . We postulated that small studies would have insufficient sample size to detect outcomes within each BMI group . Studies were included if they presented data examining women by prepregnancy BMI category , stratified by the total gestational weight gain . Studies that categorized by mean weight gain per week were excluded . Only studies presenting odds ratios ( ORs ) stratified by maternal BMI and gestational weight gain were included . Studies that simultaneously adjusted for categories of BMI and gestational weight gain to estimate the independent associations of weight change with outcomes were excluded because the aim of this review was to assess the association of gestational weight gain ( specific for each BMI category ) and outcomes .
 Studies meeting these criteria used different BMI categories ( eg , Metropolitan Life Insurance Tables , WHO classifications , or Chinese classifications11 [ BMI for underweight , < 18.5 ; normal weight , 18.5 - 23.9 ; overweight , 24 - 28 ; and obese , ≥28 ] ) and gestational weight gain categories ( eg , 1990 IOM , 2009 IOM , population - specific , or study - specific categories ) to classify participants . Additionally , some studies used a reference of normal gestational weight gain within each BMI group , whereas others used a reference of normal - weight women with normal weight gain .
 In this review , BMI was defined by WHO categories and/or Chinese BMI categories . Gestational weight gain was defined by 2009 IOM criteria ; thus , authors of identified studies were contacted to reanalyze data using these categories . The ORs were calculated using recommended gestational weight gain within each BMI category as the reference .
 Gestational weight gain was defined as the difference between the final weight and the prepregnancy weight and was classified as below , within , or above the 2009 IOM guidelines . The prepregnancy weight was either self - reported ( which correlates well with measured weight12,13 ) or measured at first antenatal visits . Final pregnancy weight was measured at the last antenatal visit or the time of delivery or was self - reported within 1 year of delivery .
 Two authors assessed risk of bias ( R.F.G. and S.K.A. ) . Discrepancies were resolved by consensus in discussion with a third reviewer ( M.M. ) . Methodological quality of included studies was assessed using the Monash Centre for Health Research and Implementation evidence synthesis appraisal assessment tool.15,16 Individual quality items were assessed using a descriptive approach including exposure and outcome measures , reporting bias , confounding , and conflict of interest . Each study was classified as low , medium , or high risk of bias .
 Findings were synthesized by target population characteristics , study type , and outcome . Outcome measures were produced for each study by calculating ORs and 95 % confidence intervals , using recommended gestational weight gain within each BMI category as the reference . When 2 or more studies assessed the same outcome , results were pooled using both fixed- and random - effects meta - analysis . There were no significant differences between fixed- and random - effects analyses . Random effects are presented given heterogeneity among studies . Extracted pooled ORs for individual outcomes were combined to construct summary pooled ORs . Crude data were used where possible , given variable control for confounding factors . However , some articles presented adjusted ORs only.17 - 24 Absolute risk differences ( ARDs ) per live birth were calculated from event rates ( available for a subset of studies ) using random - effects meta - analysis .
 Heterogeneity was assessed using the I2 statistic , where I2   >   50 % indicated substantial heterogeneity.25 Metaregression was performed to investigate sources of heterogeneity ( percentage of smokers during pregnancy , mean age , and percentage of nulliparous women ) . Race / ethnicity data were not available for the metaregression . Where 5 or more studies were available , publication bias was assessed using Egger test plots.26,27 Statistical significance was defined as 2 - sided P   <   .05 . Statistical analysis used Stata software version 14 ( StataCorp LP ) .
 A subgroup analysis was performed in specific population groups identified a priori ( studies using Chinese or Korean BMI categories , not presented herein ) . Obesity subclasses were included after reviewing studies that stratified by obesity class . Tests for trend based on the Cochran - Armitage test in Stata were used to assess trends in this subgroup analysis .
 Of 5874 studies identified by the initial search , 302 were selected for full - text review ; 261 of these were excluded , leaving 41 ( Figure 1 ) . These studies grouped women by prepregnancy BMI category , stratified by total gestational weight gain . One study28 did not meet inclusion criteria as published ; however , prior collaboration had made data available in the required format . Of 41 identified studies , 18 were excluded because data could not be obtained in the required format . Of these 18 studies , authors of 15 were contacted and unable to reanalyze and authors of 3 were not contacted from the updated search because of insufficient time prior to publication ( eAppendix 2 in the Supplement ) . Overall , 23 cohort studies17 - 24,28 - 42 were included , involving 1   309   136 women . Of these 23 studies , 7 were included without contacting the authors because data were in the required format . Of 16 authors contacted , 13 reanalyzed data and were included ; 3 provided additional information , thereby avoiding reanalysis .
 Table 2 and Table 3 list characteristics of the studies ( descriptive characteristics are shown in eTable 1 in the Supplement ) . Eighteen studies were retrospective , and 5 were prospective.20,29,32,33,42 Ten were from the United States,18 - 20,23,28,31,35,38,40,41 8 were from Asia ( 4 from China,21,29,32,36 2 from Korea,34,39 and 1 each from Taiwan24 and Japan22 ) , and 5 were from Europe ( 1 each from Norway,33 Belgium,30 Italy,37 Denmark,42 and Sweden17 ) . Sample sizes ranged from 1034 to 570   672 women .
 Underweight women composed 7 % ( n   =   94   399 ) ; normal - weight women , 55 % ( n   =   720   456 ) ; overweight women , 18 % ( n   =   235   295 ) ; and obese women , 20 % ( n   =   258   986 ) . Gestational weight gain was below , within , or above guidelines in 23 % ( n   =   300   723 ) , 30 % ( n   =   387   409 ) , and 47 % ( n   =   621   004 ) , respectively .
 Figure 2 shows pooled ORs for primary and secondary outcomes . eFigure 1 in the Supplement shows pooled ORs for individual outcomes . eTable 2 in the Supplement reports event rates . eTable 3 and eFigure 2 in the Supplement report ARDs and P values . The ARDs are expressed as percentage difference per live birth .
 Across BMI categories , gestational weight gain below guidelines was associated with higher risk for SGA than gestational weight gain within guidelines ( OR , 1.53 [ 95 % CI , 1.44 to 1.64 ] ; I2   =   82.8 % ; ARD , 5 % [ 95 % CI , 4 % to 6 % ] ) . This association was greatest in lower prepregnancy BMI ( underweight : OR , 1.89 [ 95 % CI , 1.67 to 2.14 ] ; ARD , 8 % [ 95 % CI , 6 % to 11 % ] ; normal weight : OR , 1.63 [ 95 % CI , 1.54 to 1.71 ] ; ARD , 5 % [ 95 % CI , 4 % to 6 % ] ; overweight : OR , 1.34 [ 95 % CI , 1.24 to 1.44 ] ; ARD , 3 % [ 95 % CI , 3 % to 4 % ] ; and obese : OR , 1.24 [ 95 % CI , 1.06 to 1.45 ] ; ARD , 2 % [ 95 % CI , 2 % to 3 % ] ) .
 Compared with gestational weight gain within guidelines , gain above guidelines was associated with lower risk for SGA ( OR , 0.66 [ 95 % CI , 0.63 to 0.69 ] ; I2   =   56 % ; ARD , −3 % [ 95 % CI , −4 % to −2 % ] ) . The association was similar across BMI categories ( underweight : OR , 0.62 [ 95 % CI , 0.53 to 0.72 ] ; ARD , −6 % [ 95 % CI , −8 % to −3 % ] ; normal weight : OR , 0.65 [ 95 % CI , 0.62 to 0.68 ] ; ARD , −2 % [ 95 % CI , −3 % to−1 % ] ; overweight : OR , 0.65 [ 95 % CI , 0.59 to 0.71 ] ; ARD , −3 % [ 95 % CI , −4 % to −2 % ] ; and obese : OR , 0.72 [ 95 % CI , 0.65 to 0.80 ] ; ARD , −2 % [ 95 % CI , −3 % to −1 % ] ) .
 Compared with gestational weight gain within guidelines , weight gain below guidelines was associated with higher risk for preterm birth ( OR , 1.70 [ 95 % CI , 1.32 to 2.20 ] ; I2   =   97.3 % ; ARD , 5 % [ 95 % CI , 3 % to 8 % ] ) . This association was greatest with lower BMI ( underweight : OR , 2.41 [ 95 % CI , 1.01 to 5.73 ] ; ARD , 8 % [ 95 % CI , 1 % to 15 % ] ; normal weight : OR , 1.96 [ 95 % CI , 1.17 to 3.29 ] ; ARD , 6 % [ 95 % CI , 0 % to 11 % ] ; overweight : OR , 1.55 [ 95 % CI , 1.10 to 2.19 ] ; ARD , 4 % [ 95 % CI , −1 % to 9 % ] ; and obese : OR , 1.20 [ 95 % CI , 1.03 to 1.40 ] ; ARD , 3 % [ 95 % CI , 1 % to 5 % ] ) .
 Gestational weight gain above guidelines was associated with lower risk for preterm birth ( OR , 0.77 [ 95 % CI , 0.69 to 0.86 ] ; I2   =   78.7 % ; ARD , −2 % [ 95 % CI , −2 % to −1 % ] ) . This association was significant for normal - weight and overweight women ( underweight : OR , 0.80 [ 95 % CI , 0.50 to 1.28 ] ; ARD , −1 % [ 95 % CI , −3 % to 0 % ] ; normal weight : OR , 0.76 [ 95 % CI , 0.59 to 0.97 ] ; ARD , −1 % [ 95 % CI , −2 % to 0 % ] ; overweight : OR , 0.70 [ 95 % CI , 0.53 to 0.93 ] ; ARD , −3 % [ 95 % CI , −5 % to −1 % ] ; and obese : OR , 0.76 [ 95 % CI , 0.62 to 0.93 ] ; ARD , −2 % [ 95 % CI , −5 % to 2 % ] ) .
 Gestational weight gain below guidelines was associated with lower risk of LGA than gestational weight gain within guidelines ( OR , 0.59 [ 95 % CI , 0.55 to 0.64 ] ; I2   =   78.9 % ; ARD , −2 % [ 95 % CI , −10 % to −6 % ] ) . This was significant for underweight and normal - weight women ( underweight : OR , 0.41 [ 95 % CI , 0.34 to 0.50 ] ; ARD , −3 % [ 95 % CI , −5 % to −1 % ] ; normal weight : OR , 0.58 [ 95 % CI , 0.54 - 0.62 ] ; ARD , −3 % [ 95 % CI , −4 % to −2 % ] ; overweight : OR , 0.66 [ 95 % CI , 0.62 to 0.70 ] ; ARD , −11 % [ 95 % CI , −33 % to 10 % ] ; and obese : OR , 0.70 [ 95 % CI , 0.64 to 0.76 ] ; ARD , 13 % [ 95 % CI , −34 % to 60 % ] ) .
 Gestational weight gain above guidelines was associated with higher risk of LGA ( OR , 1.85 [ 95 % CI , 1.76 to 1.95 ] ; I2   =   74.6 % ; ARD , 4 % [ 95 % CI , 2 % to 5 % ] ) . The association increased as BMI decreased ( underweight : OR , 2.17 [ 95 % CI , 1.81 to 2.60 ] ; ARD , 4 % [ 95 % CI , 4 % to 5 % ] ; normal weight : OR , 1.95 [ 95 % CI , 1.83 to 2.08 ] ; ARD , 6 % [ 95 % CI , 5 % to 7 % ] ; overweight : OR , 1.79 [ 95 % CI , 1.61 to 1.98 ] ; ARD , −2 % [ 95 % CI , −14 % to 9 % ] ; and obese : OR , 1.63 [ 95 % CI , 1.56 to 1.70 ] ; ARD , 7 % [ 95 % CI , 5 % to 8 % ] ) .
 Gestational weight gain below guidelines was associated with lower risk of macrosomia ( OR , 0.60 [ 95 % CI , 0.52 to 0.68 ] ; I2   =   66.3 % ; ARD , −2 % [ 95 % CI , −3 % to −1 % ] ) . The association was strongest in underweight women ( underweight : OR , 0.43 [ 95 % CI , 0.27 to 0.69 ] ; ARD , −1 % [ 95 % CI , −3 % to 0 % ] ; normal weight : OR , 0.54 [ 95 % CI , 0.43 to 0.68 ] ; ARD , −2 % [ 95 % CI , −5 % to 1 % ] ; overweight : OR , 0.73 [ 95 % CI , 0.60 to 0.89 ] ; ARD , −2 % [ 95 % CI , −6 % to 2 % ] ; and obese : OR , 0.70 [ 95 % CI , 0.59 to 0.82 ] ; ARD , −3 % [ −4 % to −2 % ] ) .
 Gestational weight gain above guidelines was associated with higher risk of macrosomia ( OR , 1.95 [ 95 % CI , 1.79 to 2.11 ] ; I2   =   58.2 % ; ARD , 6 % [ 95 % CI , 4 % to 9 % ] ) . This association was strongest in underweight women according to the ORs , and all associations were significant according to the ARDs ( underweight : OR , 2.31 [ 95 % CI , 1.62 to 3.29 ] ; ARD , 3 % [ 95 % CI , 2 % to 4 % ] ; normal weight : OR , 2.01 [ 95 % CI , 1.77 to 2.27 ] ; ARD , 10 % [ 95 % CI , 5 % to 15 % ] ; overweight : OR , 1.90 [ 95 % CI , 1.54 to 2.33 ] ; ARD , 5 % [ 95 % CI , 1 % to 10 % ] ; and obese : OR , 1.83 [ 95 % CI , 1.52 to 2.22 ] ; ARD , 6 % [ 95 % CI , 1 % to 12 % ] ) .
 Eight studies assessed cesarean delivery . Seven included emergency and elective deliveries,22,28,29,33,36,37,39 and 1 did not specify.24 One study28 included repeated cesarean delivery ( total cesarean deliveries ) , 1 included primary cesarean delivery only,24 and 6 did not distinguish these .
 Gestational weight gain below guidelines was not significantly associated with cesarean delivery ( OR , 0.98 [ 95 % CI , 0.96 to 1.02 ] ; I2   =   62.6 % ; ARD , 0 % [ −2 % to 1 % ] ) .
 Gestational weight gain above guidelines was associated with higher risk of cesarean delivery ( OR , 1.30 [ 95 CI , 1.25 to 1.35 ] ; I2   =   21.9 % ; ARD , 4 % [ 95 % CI , 3 % to 6 % ] ) . The ARD was significant for underweight women only ( underweight : OR , 1.45 [ 95 % CI , 1.22 to 1.71 ] ; ARD , 6 % [ 95 % CI , 1 % to 12 % ] ; normal weight : OR , 1.30 [ 95 % CI , 1.24 to 1.36 ] ; ARD , 0 % [ 95 % CI , −4 % to 3 % ] ; overweight : OR , 1.29 [ 95 % CI , 1.21 to 1.39 ] ; ARD , 1 % [ 0 % to 3 % ] ; and obese : OR , 1.22 [ 95 % CI , 1.05 to 1.42 ] ; ARD , −2 % [ 95 % CI , −5 % to 1 % ] ) .
 Six studies assessed GDM , but they did not use consistent definitions and had different findings for gestational weight gain above guidelines and GDM risk . Black et al28 defined GDM by International Association of Diabetes in Pregnancy Study Groups criteria and included only women not treated for hyperglycemia ( the center used different criteria in clinical practice and excluded those treated ) . They found no association between weight gain above guidelines and GDM in the underweight , normal - weight , and obese groups but reported lower risk in overweight women . Enomoto et al22 used International Association of Diabetes in Pregnancy Study Groups criteria , with higher risk in normal - weight women and lower risk in overweight women . Durst et al23 used Carpenter - Coustan criteria and found no association . Hung and Hsieh24 used Carpenter - Coustan and International Association of Diabetes in Pregnancy Study Groups criteria and found an association of gestational weight gain above guidelines with lower risk of GDM in overweight and obese women . Li et al36 included both impaired glucose tolerance and type 2 diabetes by WHO criteria , with weight gain above guidelines associated with lower risk of GDM in all groups except obese women . Shin and Song31 used self - reported GDM and found an association of gestational weight gain above guidelines with lower risk in all groups except underweight women .
 An intended meta - analysis of gestational weight gain and its relationship to GDM could not be completed because of inconsistent definitions and treatments .
 Obesity classes include the following : class 1 , BMI of 30 to 34.9 ; class 2 , BMI of 35 to 39.9 ; and class 3 , BMI of 40 or higher . Obese studies generally included a subgroup - defined weight loss as well as gestational weight gain below , within , or above guidelines . Three studies assessed outcomes stratified by BMI classes 1 through 3.17,18,30 Another study35 investigated only superobese women ( BMI ≥50 ) and was included in the obesity class 3 analysis . These 4 studies were included in the subgroup analysis only ( not in the overall meta - analyses ) . Class 1 included 67 % of women ; class 2 , 22 % ; and class 3 , 11 % . Weight loss and gestational weight gain below , within , or above recommendations occurred in 6 % , 13 % , 25 % , and 57 % of pregnancies , respectively .
 Figure 3 summarizes pooled ORs for primary ( SGA and LGA ) and secondary ( macrosomia and cesarean delivery ) outcomes . eFigure 3 in the Supplement shows pooled ORs for individual outcomes . eTable 4 in the Supplement reports ARDs and P values . Only 1 study35 assessed preterm birth and GDM in the obese subgroups , preventing meta - analysis . Kominiarek et al18 provided separate ORs for nulliparous and multiparous women ( multiparous values used herein ) , whereas other studies combined women with different parity into 1 group .
 Weight loss and weight gain below guidelines were associated with higher SGA risk ( weight loss : OR , 1.79 [ 95 % CI , 1.56 to 2.05 ] ; I2   =   0 % ; ARD , 3 % [ 95 % CI , 1 % to 5 % ] ; weight gain below guidelines : OR , 1.27 [ 95 % CI , 1.14 to 1.41 ] ; I2   =   20.7 % ; ARD , 1 % [ 95 % CI , 1 % to 1 % ] ) . Gestational weight gain above guidelines was associated with lower SGA risk ( OR , 0.62 [ 95 % CI , 0.57 to 0.67 ] ; I2   =   13.5 % ; ARD , −1 % [ −2 % to 0 % ] ) . Weight gain in class 1 had the strongest association with lower SGA risk ( lowest OR , 0.58 ; 95 % CI , 0.53 to 0.72 ] ; P for trend   <   .001 ) .
 Weight loss and gestational weight gain below guidelines were associated with lower LGA risk ( weight loss : OR , 0.58 [ 95 % CI , 0.52 to 0.66 ] ; I2   =   11.6 % ; ARD , −5 % [ 95 % CI , −7 % to −3 % ] ; weight gain below guidelines : OR , 0.77 [ 95 % CI , 0.71 to 0.84 ] ; I2   =   0 % ; ARD , −2 % [ 95 % CI , −3 % to −1 % ] ) . Weight loss in class 3 had the strongest association with lower LGA risk ( lowest OR , 0.53 [ 95 % CI , 0.41 to 0.67 ] ; P for trend   <   .001 ) . Weight gain above guidelines was associated with higher LGA risk ( OR , 1.79 [ 95 % CI , 1.70 to 1.89 ] ; I2   =   69.3 % ; ARD , 5 % [ 95 % CI , 5 % to 6 % ] ) . LGA was most strongly associated with class 1 obesity compared with the other classes ( highest OR , 1.87 [ 95 % CI , 1.75 to 2.00 ] ; P for trend   <   .001 ) .
 Three studies assessed macrosomia , defined as birth weight greater than 4000 g in 1 study,30 greater than 4500 g in 1 study,18 and both greater than 4000 g and greater than 4500 g in 1 study.35 Meta - analysis used data for birth weight greater than 4000 g.
 Weight loss and gestational weight gain below guidelines were associated with lower macrosomia risk ( weight loss : OR , 0.46 [ 95 % CI , 0.36 to 0.58 ] ; I2   =   34.0 % ; ARD , −5 % [ 95 % CI , −9 % to −2 % ] ; weight gain below guidelines : OR , 0.76 [ 95 % CI , 0.68 to 0.86 ] ; I2   =   0 % ; ARD , −2 % [ 95 % CI , −3 % to 0 % ] ) . Low weight gain in class 3 had the strongest association with lower macrosomia risk ( lowest OR , 0.64 [ 95 % CI , 0.49 to 0.85 ] ; P for trend   =   .046 ) . Gestational weight gain above guidelines was associated with higher risk of macrosomia ( OR , 1.60 [ 95 % CI , 1.46 to 1.75 ] ; I2   =   66.9 % ; ARD , 3 % [ 95 % CI , 0 % to 6 % ] ) .
 Four studies assessed cesarean delivery . They included emergency,30 emergency and elective,18,35 and undefined17 indications for cesarean delivery .
 Weight loss and gestational weight gain below guidelines were associated with lower risk of cesarean delivery ( weight loss : OR , 0.78 [ 95 % CI , 0.72 to 0.85 ] ; I2   =   34.3 % ; ARD , −4 % [ 95 % CI , −6 % to −3 % ] ; weight gain below guidelines : OR , 0.87 [ 95 % CI , 0.82 to 0.93 ] ; I2   =   0 % ; ARD , −2 % [ 95 % CI , −3 % to −1 % ] ) . Gestational weight gain above guidelines was associated with higher risk of cesarean delivery ( OR , 1.21 [ 95 % CI , 1.16 to 1.25 ] ; I2   =   0 % ; ARD , 2 % [ 95 % CI , 0 % to 3 % ] ) .
 Substantial heterogeneity ( I2   >   50 % ) was present for gestational weight gain below and above guidelines for SGA , preterm birth , LGA , and macrosomia and for gestational weight gain above guidelines for cesarean delivery . When sufficient data were available , metaregression analysis was performed to investigate possible sources of heterogeneity : percentage of smokers during pregnancy , mean age , and percentage of nulliparous women ( eTable 5 in the Supplement ) . The obese subgroups had insufficient studies to perform metaregression .
 Gestational weight gain above guidelines and LGA demonstrated a source for heterogeneity ( P   =   .04 ) ; specifically , there was an association between the treatment effect and the covariate smoking ( P   =   .02 ) . For gestational weight gain below guidelines and preterm birth , mean maternal age was the only covariate associated with outcome , where the risk for preterm birth varied by maternal age due to the heterogeneity in maternal age in included studies ( P   =   .03 ) ; however , the overall P value was not significant ( P   =   .09 ) . Heterogeneity was unexplained for remaining outcomes .
 There was no evidence of publication bias for SGA , LGA , macrosomia or cesarean delivery ( eFigure 4 in the Supplement ) . Assessment for publication bias was not performed for preterm births ( < 5 studies ) .
 Participants were selected from maternity clinics or from large data sets ( Table 4 ) . Apart from 3 studies,19,23,32 inclusion and exclusion criteria were adequately described . Performance bias ( a potential difference in the care provided between BMI groups ) was difficult to assess . Very few studies provided information regarding diet and/or exercise advice given and whether this differed between groups . Overweight and obese women were possibly treated more intensively , which could introduce bias .
 Three studies demonstrated moderate bias risk19,21,31 and 20 demonstrated low bias risk.17,18,20,22 - 24,28 - 30,32 - 42 Reasons for moderate bias risk included self - reported final weight ( detection bias ) , self - reported outcome measures ( detection bias ) , failure to report all outcomes ( report bias ) , and insufficient adjustment for confounding variables ( confounding bias ) . Nineteen studies reported no conflict of interest .
 Quiz Ref IDIn this analysis of 1   309   136 pregnancies from diverse international cohorts , gestational weight gain below or above 2009 IOM guidelines among women across the BMI range was associated with greater risk for maternal and infant adverse outcomes . Underweight women composed 7 % ; normal - weight women , 55 % ; overweight women , 18 % ; and obese women , 20 % . For gestational weight gain , 23 % gained below and 47 % gained above guidelines . Compared with recommended gestational weight gain , gain below guidelines was associated with 5 % higher risk of both SGA and preterm birth and 2 % lower risk of both LGA and macrosomia . Weight gain above guidelines was associated with 3 % lower risk of SGA and 2 % lower risk of preterm birth and 4 % , 6 % , and 4 % higher risk of LGA , macrosomia , and cesarean delivery , respectively .
 Gestational weight gain below guidelines was associated with higher SGA risk , with greatest risk in underweight women , as shown previously.43,44 Obesity was associated with higher risk of SGA , with weight loss and gestational weight gain below guidelines increasing risks , similar to prior systematic reviews.26,45,46 Underweight status combined with gestational weight gain below recommendations as well as obese status combined with gestational weight loss present the highest risk groups for SGA , at 8 % and 3 % , respectively .
 Gestational weight gain below guidelines was associated with lower risks of LGA and macrosomia . This association was lowest in underweight women . Weight gain above guidelines was associated with higher risks of LGA and macrosomia , with ARDs of 4 % and 6 % greater risks , respectively . Underweight status was associated with the greatest risk . This is similar to the 2009 IOM report6 that stated , “ the lower the prepregnancy BMI , the stronger the association between increased gestational weight gain and birthweight ” ; it may be related to higher absolute weight gain in underweight women.1 Animal studies suggest that baseline maternal BMI and gestational weight gain are associated with changes in the hormonal milieu , including insulin resistance.50 Similarly , excess weight gain in underweight women may be associated with greater changes in the hormonal milieu and placental function than in normal - weight or overweight women . Weight gain above guidelines was associated with increased risk of cesarean delivery across the BMI spectrum .
 Quiz Ref IDSimilarly , within the obese subgroups , weight loss was associated with a 5 % lower risk for both LGA and macrosomia and 4 % lower risk for cesarean delivery . Weight gain below guidelines was associated with 2 % lower risk across all these outcomes . Class 3 obesity combined with weight loss was associated with the greatest LGA risk reduction . Gestational weight gain above guidelines was associated with increased LGA risk . Class 1 obesity was associated with the greatest risk for LGA , which may be partly due to higher absolute weight gain in less obese women.10 While other systematic reviews have assessed gestational weight gain below guidelines,26 to our knowledge , this is the first review exploring relationships between weight gain above guidelines and outcomes within obesity classes .
 While GDM has adverse maternal and infant outcomes51 and is related to maternal BMI and possibly to gestational weight gain , associations could not be assessed because of heterogeneity of diagnosis and treatment as well as the potential effect of GDM treatment on gestational weight gain . Prior systematic reviews have not demonstrated that healthy lifestyle and gestational weight gain reduced rates of GDM,14 even in high - risk populations.52 Consistent diagnostic criteria and reporting of gestational weight gain at GDM diagnosis are needed to study associations between gestational weight gain and GDM .
 Lifestyle interventions in pregnancy can help women attain recommended gestational weight gain.14 Optimal interventions and effects on outcomes are currently being studied in a large - scale international individual patient data meta - analysis.53 The WHO has prioritized achievement of ideal BMI prior to conception and prevention of excess gestational weight gain.54 Identification of women prior to conception and implementing healthy lifestyle strategies before and during pregnancy have yet to be integrated into routine health care,55 requiring research implementation .
 Strengths of this review are the inclusion of common maternal and infant risks associated with gestational weight gain below and above the 2009 IOM guidelines in women across the prepregnancy BMI spectrum and across international cohorts . Four databases were searched , a risk of bias appraisal was performed , and reanalyses were undertaken , allowing inclusion of data from more than 1.3 million pregnant women globally . Collaboration with other authors facilitated more homogeneous data , data integration , and meta - analysis .
 This study has limitations . It lacks studies from developing countries and excluded non - English - language articles . Fifteen of 31 authors contacted were unable to reanalyze data , so these studies were excluded from the meta - analysis . A meta - analysis could not be performed for GDM because of inconsistent primary data . Some outcomes were assessed in only 1 study , precluding meta - analysis . Inconsistent definitions of preterm birth , cesarean delivery , and macrosomia limited interpretation of findings . Study heterogeneity may have affected reliability of results , although the metaregression did not identify characteristics responsible for this heterogeneity . Studies published before 2009 IOM guidelines were included , and gestational weight gain targets before and after these guidelines may have differed . Preterm birth was not adjusted for gestational age , potentially resulting in less total gestational weight gain than would have been otherwise attained . Spontaneous and induced preterm birth were not clearly differentiated , and studies did not distinguish between emergency and elective or primary and repeated cesarean deliveries . These factors may limit interpretation and underscore the importance of improving outcome definition reporting . Event rates were not available for all studies , limiting interpretation of ARDs . Findings from this review are based on observational data and no causal links may be concluded . They may be applicable on a population level , but recommendations need to be individualized when applied clinically .
 Quiz Ref IDIn this systematic review and meta - analysis of more than 1 million pregnant women , 47 % had gestational weight gain greater than IOM recommendations and 23 % had gestational weight gain less than IOM recommendations . Gestational weight gain greater than or less than guideline recommendations , compared with gestational weight gain within recommended levels , was associated with higher risk of adverse maternal and infant outcomes .
 Corresponding Author : Helena J. Teede , MBBS , FRACP , PhD , Monash University , 43 - 51 Kanooka Dr , Clayton , Melbourne , Victoria 3168 , Australia ( helena.teede@monash.edu ) .
 Accepted for Publication : May 10 , 2017 .
 Author Contributions : Dr Goldstein and Mr Ranasinha had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis .
 Concept and design : Goldstein , Abell , Ranasinha , Misso , Teede .
 Acquisition , analysis , or interpretation of data : Goldstein , Abell , Ranasinha , Boyle , Black , Li , Hu , Corrado , Rode , Y. J. Kim , Haugen , Song , M. H. Kim , Bogaerts , Devlieger , Chung , Teede .
 Drafting of the manuscript : Goldstein , Teede .
 Administrative , technical , or material support : Goldstein , Ranasinha , Teede .
 Conflict of Interest Disclosures : All authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest . Dr Boyle reported serving on the Women ’s Health Global Advisory Board for Pfizer . No other disclosures were reported .
 Funding / Support : Dr Goldstein is supported by a Research Training Program scholarship from the Department of Education and Training . Dr Abell is supported by a scholarship from the National Health and Medical Research Council . Drs Boyle and Teede are supported by fellowships from the National Health and Medical Research Council .
 Additional Contributions : Tiffany Moore Simas , MD ( University of Massachusetts Medical School , Worcester ) , Sohyun Park , PhD ( National Center for Chronic Disease Prevention and Health Promotion , Atlanta , Georgia ) , and Michelle Kominiarek , MD ( University of Illinois at Chicago ) , assisted in providing additional data .


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misterCope earned the Second Anniversary badge .
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text: Avaya IP Office is an all-in-one solution specially designed to meet the communications challenges facing small and medium sized businesses. Due to its modular design, Avaya IP Office can scale from 2 to 360 extensions to meet the needs of home offices, standalone businesses, and networked branch and head offices. Built on Avaya latest advancements in converged voice and data technology, small to mid-sized businesses can benefit from many of the advantages Avaya IP Office sophisticated communications deliver to their operations. Avaya IP Office supports a wide range of telephones but the 9000 series digital phones have been specifically designed to work with Avaya IP Office and provide small and medium sized businesses with a choice of solutions to meet business efficiency and customer service requirements.

tokenized: Avaya IP Office is an all - in - one solution specially designed to meet the communications challenges facing small and medium sized businesses . Due to its modular design , Avaya IP Office can scale from 2 to 360 extensions to meet the needs of home offices , standalone businesses , and networked branch and head offices . Built on Avaya latest advancements in converged voice and data technology , small to mid - sized businesses can benefit from many of the advantages Avaya IP Office sophisticated communications deliver to their operations . Avaya IP Office supports a wide range of telephones but the 9000 series digital phones have been specifically designed to work with Avaya IP Office and provide small and medium sized businesses with a choice of solutions to meet business efficiency and customer service requirements .


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This is a placeholder page for Sandy Aaba , which means this person is not currently on this site . We do suggest using the tools below to find Sandy Aaba .
 You are visiting the placeholder page for Sandy Aaba . This page is here because someone used our placeholder utility to look for Sandy Aaba . We created this page automatically in hopes Sandy Aaba would find it . If you are not Sandy Aaba , but are an alumni of Hilo High School , register on this site for free now .


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check the media info of your file ,note the bit rate ,frame rates, and other details then use a video converter of your choice (any will do) while converting be sure to match the frame rates ,bitrates and other details with the original file but remember avi will take a lot of space ,just play with the advance settings to get the best results... 20/07/2018�� (2018-07-17, 19:39) JohnPlayerSpecial Wrote: I read almost everything on the Internet fromFunny, that's actually the first time I read that. (2018-07-17, 19:39) JohnPlayerSpecial Wrote: I put a BD-Rip in mkvtoolnix and simply let the tool change FPS from 23,976 to 25.
Step 3: Set parameters. 3. If you want to further customize the parameters of the output profile after you are done choosing the output profile, Hit �Edit� button on the left of the �Change� button to enter the parameter setting panel where you can adjust the values of video and audio like Bitrate, Frame Rate, Resolution, Aspect Ratio, etc. how to connect philips bluetooth headphones However, the fact remains that from release to release, the MKVToolNix (toolkit / platform / whatever you want to call it) has, I believe, been badly managed. It�s noble of you to state that you didn�t change the ID numbering scheme on a whim.
23/08/2016�� Download Free Video FPS Converter for free. A little tool to change the frame rate of a video file. A little tool to change the frame rate of a video file. V0.0.9.6 adds: - delete .ffindex file in source directory after conversion V0.0.9.5 adds: - framerate is kept if -f is not used V0.0.9.4 adds: - bugfixes V0.0.9.3 adds how to change user word 6/05/2009�� Im trying to change 24p and 23.975,also i have one that is 24.001 fps,but when i encode those files with rip bot i get green tint and the screen just keeps going up.Also sync issues but im not worried about the audio i can fix that.Im encoding the mkv files to avchd playing them on 160gb ps3.
6/05/2009�� Im trying to change 24p and 23.975,also i have one that is 24.001 fps,but when i encode those files with rip bot i get green tint and the screen just keeps going up.Also sync issues but im not worried about the audio i can fix that.Im encoding the mkv files to avchd playing them on 160gb ps3.
20/07/2018�� (2018-07-17, 19:39) JohnPlayerSpecial Wrote: I read almost everything on the Internet fromFunny, that's actually the first time I read that. (2018-07-17, 19:39) JohnPlayerSpecial Wrote: I put a BD-Rip in mkvtoolnix and simply let the tool change FPS from 23,976 to 25.
Interframe works fine with constant frame rates, but if i record a winde with my phone video has variable framerate between 24 and 30. If i prepare script for 30, video is lagging when 24 fps part. Opposite is happening if i prepare for 24.
28/01/2010�� You can also use Yamb with mp4box to extract all streams to raw format, then create a new mp4 file with the audio and video tracks. You can change the framerate when creating the new file by selecting the video stream and clicking the Properties button.

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check the media info of your file , note the bit rate , frame rates , and other details then use a video converter of your choice ( any will do ) while converting be sure to match the frame rates , bitrates and other details with the original file but remember avi will take a lot of space , just play with the advance settings to get the best results ... 20/07/2018 � � ( 2018 - 07 - 17 , 19:39 ) JohnPlayerSpecial Wrote : I read almost everything on the Internet fromFunny , that 's actually the first time I read that . ( 2018 - 07 - 17 , 19:39 ) JohnPlayerSpecial Wrote : I put a BD - Rip in mkvtoolnix and simply let the tool change FPS from 23,976 to 25 .
 Step 3 : Set parameters . 3 . If you want to further customize the parameters of the output profile after you are done choosing the output profile , Hit � Edit � button on the left of the � Change � button to enter the parameter setting panel where you can adjust the values of video and audio like Bitrate , Frame Rate , Resolution , Aspect Ratio , etc . how to connect philips bluetooth headphones However , the fact remains that from release to release , the MKVToolNix ( toolkit / platform / whatever you want to call it ) has , I believe , been badly managed . It � s noble of you to state that you didn � t change the ID numbering scheme on a whim .
 23/08/2016 � � Download Free Video FPS Converter for free . A little tool to change the frame rate of a video file . A little tool to change the frame rate of a video file . V0.0.9.6 adds : - delete .ffindex file in source directory after conversion V0.0.9.5 adds : - framerate is kept if -f is not used V0.0.9.4 adds : - bugfixes V0.0.9.3 adds how to change user word 6/05/2009 � � I m trying to change 24p and 23.975,also i have one that is 24.001 fps , but when i encode those files with rip bot i get green tint and the screen just keeps going up . Also sync issues but i m not worried about the audio i can fix that . Im encoding the mkv files to avchd playing them on 160 gb ps3 .
 6/05/2009 � � I m trying to change 24p and 23.975,also i have one that is 24.001 fps , but when i encode those files with rip bot i get green tint and the screen just keeps going up . Also sync issues but i m not worried about the audio i can fix that . Im encoding the mkv files to avchd playing them on 160 gb ps3 .
 20/07/2018 � � ( 2018 - 07 - 17 , 19:39 ) JohnPlayerSpecial Wrote : I read almost everything on the Internet fromFunny , that 's actually the first time I read that . ( 2018 - 07 - 17 , 19:39 ) JohnPlayerSpecial Wrote : I put a BD - Rip in mkvtoolnix and simply let the tool change FPS from 23,976 to 25 .
 Interframe works fine with constant frame rates , but if i record a winde with my phone video has variable framerate between 24 and 30 . If i prepare script for 30 , video is lagging when 24 fps part . Opposite is happening if i prepare for 24 .
 28/01/2010 � � You can also use Yamb with mp4box to extract all streams to raw format , then create a new mp4 file with the audio and video tracks . You can change the framerate when creating the new file by selecting the video stream and clicking the Properties button .


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China will have its own "NBA-like" e-sport matches within 5 to 10 years as the game market is set to continue to boom, game industry officials said on Sunday.
Xiao Hong, chief executive officer of Shenzhen-listed game firm Perfect World, said that China will develop e-sport matches along the lines of NBA in the U.S. amid a booming market which supports a big pool of players.
In 2017, the worldwide e-sport market revenue was U.S..5 billion and the figure is set to rise to U.S..3 billion in 2020, according to researcher SuperData.
Perfect World has set up a special team for e-sport to take care of management, intellectual property development and professional training, Xiao said during the DAC (DOTA 2 Asia Championship) held in Shanghai.
DOTA 2, one of the top MOBA (multiplayer online battle arena) games, offered U.S..1 million as total e-sport prize pool in 2017. Perfect World, distributor of DOTA 2 in China, is the major organizer of DAC in Shanghai and it has identified e-sport as one of its "top strategies".
Sixteen game teams, including from Russia and Malaysia, attended the DAC in Shanghai with prize pool of U.S. million.

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China will have its own " NBA - like " e - sport matches within 5 to 10 years as the game market is set to continue to boom , game industry officials said on Sunday .
 Xiao Hong , chief executive officer of Shenzhen - listed game firm Perfect World , said that China will develop e - sport matches along the lines of NBA in the U.S. amid a booming market which supports a big pool of players .
 In 2017 , the worldwide e - sport market revenue was U.S .. 5 billion and the figure is set to rise to U.S .. 3 billion in 2020 , according to researcher SuperData .
 Perfect World has set up a special team for e - sport to take care of management , intellectual property development and professional training , Xiao said during the DAC ( DOTA 2 Asia Championship ) held in Shanghai .
 DOTA 2 , one of the top MOBA ( multiplayer online battle arena ) games , offered U.S .. 1 million as total e - sport prize pool in 2017 . Perfect World , distributor of DOTA 2 in China , is the major organizer of DAC in Shanghai and it has identified e - sport as one of its " top strategies " .
 Sixteen game teams , including from Russia and Malaysia , attended the DAC in Shanghai with prize pool of U.S. million .


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Eldon is a leading manufacturer in the market offering one of the largest ranges of stainless steel enclosures available. Ideally suited for more demanding applications where maximum hygiene is essential, like the food and pharmaceutical industries and the harsh environment of petrochemical plants and offshore environments.
Our Stainless Steel range of enclosures provides high corrosion resistance in aggressive environments.
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Eldon is a leading manufacturer in the market offering one of the largest ranges of stainless steel enclosures available . Ideally suited for more demanding applications where maximum hygiene is essential , like the food and pharmaceutical industries and the harsh environment of petrochemical plants and offshore environments .
 Our Stainless Steel range of enclosures provides high corrosion resistance in aggressive environments .
 Now supplied in the new 240s surface finish , which provides improved performance , ideally suited for the food industry and external applications providing increased corrossion resistance .
 Additionally , we offer a range of products in an Electro - polished finish , which further enhances hygiene and anti - corrosion properties .
 Eldon offer a comprehensive range of wall mounting , terminal , floorstanding and console systems , which will meet most requirements . An in depth product range , unmatched by most of our rivals is available directly from stock .
 A flexible approach to customer needs means we are able to provide enclosure solutions for most applications . Offering a service of modified and special enclosures meeting your customers specific needs .
 Competitively priced , conforming to industry standards and testing , Eldon offers the ideal solution for a variety of applications .
 Low maintenance ; more economical in the long run .
 Resists attacks from many aggressive materials .
 Suffers only cosmetic damage from scratches with no detrimental effect to performance .
 Can be regularly washed down .
 Forms an ideal base for providing EMC solutions .
 Can be fully earthed , unlike insulated enclosures .
 Does not age like most plastics .
 Rigid construction . High quality finish .
 4 ( Din 1.4301 ) & AISI 316 ( Din1.4404 ) .
 Also available , a range of Electro - polished enclosures .
 240s Fine grain finish , suitable for food and other specialist , harsh environments .
 ‘ Smooth ’ design to avoid dirt traps and aid cleaning .
 Comprehensive in - depth range of ‘ Ex - stock ’ products available .
 Customized & special enclosures to customers ’ specified modifications .
 Approved to a range of industry standards IP55 - IP66 , IK10 , Nema , UL CSA , Nema Lloyds register of shipping etc .


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On 01/02/2019, REIL announced Job notification to hire candidates who completed ITI, Diploma, B.Tech/B.E for the position of Technician, Technical Assistant, Engineer.
1. Qualification: The incumbent should be an ITI (NCVT) in Electronics Mechanical/ Radio & TV/ Electrical/PASSA/’O’ Level Computer course equivalent to Foundation Level course with minimum 60% marks with one year Apprenticeship under the Apprenticeship Act, 1961, as applicable. The candidate should have minimum 02 years or more post qualification experience in Industry. Candidates having Computer Course equivalent to Advanced Diploma in Computer Applications shall be given added advantage; the incumbent should be computer savvy.
1. Qualification: The incumbent should be 3 years Diploma in Electrical/ Electronics & Communication Engineering from a recognised Institution/University with minimum 60% marks. The candidate should have minimum 02 years or more post qualification experience in Industry. Candidates having Computer Course equivalent to Advanced Diploma in Computer Applications shall be given added advantage; the incumbent should be computer savvy.
1. Qualification: The incumbent should be a graduate engineer in Electronics and Communication/ Electrical/ Computer Science branch, with minimum 60% marks from a recognized University/Institution; the incumbent should be computer savvy.
The candidates are required to submit their applications as per the prescribed format only, available on Website, with copies of proof of date of birth, qualifications, experience, caste and a recent passport size photograph etc., in hard copy. The scanned copy of the application alongwith required documents may be sent to the e-mail id given in the advertisement. However, the hard copy of the application along with all supporting documents should reach to the following address within 21 days of this advertisement. The application(s) received after the due date will not be considered. The application(s) so received shall be acknowledged and application number shall be allotted, and accordingly application no. of the shortlisted candidates and finally selected candidates shall be hosted on Company’s website. Candidates working with Government, PSU or Autonomous bodies etc. should forward their application through proper channel. Relaxation to SC,ST,OBC,PH,EWSs, Ex-Serviceman and Sports person would be given as per Government guidelines.

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On 01/02/2019 , REIL announced Job notification to hire candidates who completed ITI , Diploma , B.Tech / B.E for the position of Technician , Technical Assistant , Engineer .
 1 . Qualification : The incumbent should be an ITI ( NCVT ) in Electronics Mechanical/ Radio & TV/ Electrical / PASSA/’O ’ Level Computer course equivalent to Foundation Level course with minimum 60 % marks with one year Apprenticeship under the Apprenticeship Act , 1961 , as applicable . The candidate should have minimum 02 years or more post qualification experience in Industry . Candidates having Computer Course equivalent to Advanced Diploma in Computer Applications shall be given added advantage ; the incumbent should be computer savvy .
 1 . Qualification : The incumbent should be 3 years Diploma in Electrical/ Electronics & Communication Engineering from a recognised Institution / University with minimum 60 % marks . The candidate should have minimum 02 years or more post qualification experience in Industry . Candidates having Computer Course equivalent to Advanced Diploma in Computer Applications shall be given added advantage ; the incumbent should be computer savvy .
 1 . Qualification : The incumbent should be a graduate engineer in Electronics and Communication/ Electrical/ Computer Science branch , with minimum 60 % marks from a recognized University / Institution ; the incumbent should be computer savvy .
 The candidates are required to submit their applications as per the prescribed format only , available on Website , with copies of proof of date of birth , qualifications , experience , caste and a recent passport size photograph etc . , in hard copy . The scanned copy of the application alongwith required documents may be sent to the e - mail i d given in the advertisement . However , the hard copy of the application along with all supporting documents should reach to the following address within 21 days of this advertisement . The application(s ) received after the due date will not be considered . The application(s ) so received shall be acknowledged and application number shall be allotted , and accordingly application no . of the shortlisted candidates and finally selected candidates shall be hosted on Company ’s website . Candidates working with Government , PSU or Autonomous bodies etc . should forward their application through proper channel . Relaxation to SC , ST , OBC , PH , EWSs , Ex - Serviceman and Sports person would be given as per Government guidelines .