The Association between Pre-Pregnancy BMI, Gestational Weight Gain and Pregnancy Outcomes: A Retrospective Cohort Study in Ahvaz, Iran

The Association between Pre-Pregnancy BMI, Gestational Weight Gain and Pregnancy Outcomes: A Retrospective Cohort Study in Ahvaz, Iran | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research article The Association between Pre-Pregnancy BMI, Gestational Weight Gain and Pregnancy Outcomes: A Retrospective Cohort Study in Ahvaz, Iran Kambiz Ahmadi Angali, Maryam Azhdari, Maria Cheraghi, parvin shahri, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-117813/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Maternal body mass index and maternal gestational weight gain can have positive effects on birth and maternal outcomes. We aimed to identify the effect of pre-pregnancy weight and gestational weight gain on birth outcomes. Methods: Data of this retrospective cohort study were extracted using the 1457 out of 1800 pair health records belonged to the pregnant mother and infant at Ahvaz health care centers, from 2010 to 2018. Result: The 3.18-fold increased risk for large for gestational age in overweight mothers, and a 2.9 fold increased risk for small for gestational age in those mothers with gestational weight gain below the guidelines. An increased risk of large for gestational age, low birth weight, and macrosomia were observed in overweight mothers with gestational weight gain out of the guidelines. The increased association was found between the maternal pre-body mass index and fasting blood sugar (p = 0.0001). Hence, hyperglycemia is related to a 3.58-fold incidence of macrosomia. Conclusion: Therefore, conducting more educational programs of lifestyle intervention with respect to reproductive health care is required for all women in childbearing age (before and during pregnancy), with the purpose of reducing the adverse pregnancy outcome. Health Economics & Outcomes Research Nutrition & Dietetics Hyperglycemias Mother Pre-pregnancy body mass index Pregnancy Outcomes Pregnancy Weight Gain Background: Maternal pre-pregnancy BMI( Body mass index) and maternal gestational weight gain (GWG) can have positive effects on birth and maternal outcomes [ 1 ]. The prevalence of overweight and obesity is increasing in all age groups worldwide, and it is related to non-communicable diseases [ 2 ]. Nonetheless, WHO reported more than half of the Iranian females are overweight or obese [ 3 ]. The global burden of overweight and obese pregnant women has increased in high income and middle income countries [ 4 ]. Additionally, the Islamic Republic of Iran was considered for the 20 high overweight burden countries[ 4 ]. Therefore, the pre-pregnancy BMI and GWG below or above the Institute of Medicine (IOM) guidelines are considered as two effective factors on pregnancy outcomes [ 1 ]. The prevalence of the adverse outcomes was reported as 37.2% in pregnant women, ranging from 34.7–61.1% among underweight and obese (grade3) women, respectively. Adverse maternal and infant outcomes were affected by maternal pre-pregnancy BMI more than incremental gestational weight gain [ 5 ]. The finding of some epidemiological studies [ 6 , 7 ] have reported a positive association between pre-pregnancy BMI and the prevalence of gestational diabetes mellitus (GDM), as well as higher risk of childhood obesity [ 8 ]. A meta-analysis in 2017 reported that a low GWG was positively related to small for gestational age (SGA) and preterm birth, and lower risk for large for gestational age (LGA) and macrosomia. Also, a higher risk for LGA, macrosomia, and cesarean delivery was found in excessive GWG [ 9 ]. The excessive GWG can result in adverse maternal outcomes such as cesarean delivery, GDM, preeclampsia, and postnatal weight retention [ 10 ]. In 2009, IOM has recommended the mean and range for the incremental weight gain during the 2nd and 3rd trimester by pre-pregnancy BMI class [ 11 ]. Despite the importance of adequate total GWG, the excessive GWG before 20 weeks was associated with a higher risk of LGA, regardless of total GWG [ 12 ]. Also, the early excessive GWG can lead to a higher prevalence of GDM, regardless of pre-pregnancy BMI (6). Several epidemiological studies have provided some evidence from different regions of Iran, in terms of the role of GWG and pre-pregnancy BMI and adverse pregnancy outcomes. Hence, low birth weight (LBW) [ 13 ] more prevalent in women with GWG less than the weight gain recommended by institute of medicine (IOM) and macrosomia [ 14 ] reported in women with GWG higher than the guideline. In addition, women with pre-pregnancy obesity were associated to macrosomic infants [ 15 ] [ 16 ]. Moreover, with a corresponding rise in overweigh and obesity among population, this lead to an increase in GWG and adverse pregnancy outcome. Therefore, the aim of this retrospective cohort study was to evaluate the relationship between maternal pre-pregnancy BMI, Gestational Weight Gain and pregnancy outcomes. Methods: Data of this retrospective cohort study were extracted using the pair health records of the pregnant mother and infant at Ahvaz health care centers from 2010 to 2018. The study was approved by the Ethics Committee of Ahvaz Jundishapur University of Medical Sciences (IR.AJUMS.REC.1396.80). The final sample size has 1457 participants out of 1800 based on GWG as the main variable. The trained research assistants were comprehensively collected information .Exclusion criteria were as follows; incomplete data for maternal during pregnancy and her offspring, multiple pregnancies, preeclampsia/ eclampsia and type 2 diabetes mellitus (T2DM), and preterm pregnancy. Information included 1: maternal characteristics (age, pre-pregnancy weight and height, pre-pregnancy BMI, GWG, last delivery mode, pregnancy history (GDM, lifestyle before and during pregnancy (alcohol consumption and smoking), fasting blood sugar (FBS), was categorized into ≥ 92 and < 92 according to International Association of Diabetes and Pregnancy Study Groups (IADPSG)[17], and 2: offspring characteristics comprise of gender, birth weight, small for gestational age ( SGA), large for gestational age(LGA), appropriate size for gestational age(AGA) at birth, low birth weight (LBW), normal birth weight, and macrosomia. Measurements: SGA and LGA new-born were defined as those whose birth weights for gestational age were 90 th percentiles. Macrosomia and LBW were defined by a birth weight > 4000g and < 2500g, respectively [18]. Pre-pregnancy BMI and GWG categories were estimated in terms of the IOM recommendations. Some variables were calculated as followings: Pre-pregnancy BMI (kg /m 2 ): the dividing pre-pregnancy self-reported body weight (kg) by height (m 2 ) was measured at the first antenatal visit, (weight (kg) / height 2 (m 2 )). Incremental weight gain (gr /week): the difference weight 2 and weight 1 divided by weeks between weights (weight 2 – weight 1) (gr) / follow up duration (week) [3]. Statistical analysis: SPSS statistical software package, version 18.0 (SPSS, Inc, Chicago, Illinois, USA) was used for statistical analyses. P values <.05 were considered as statistically significant using the 2-tailed tests. The analysis of continuous variables (maternal age, GWG rate during trimester 2 sd and 3 rd , birth weight) was performed by the means (standard deviations (SD)). The categorical variables (FBS, pre-pregnancy BMI, GWG, last delivery mode, disease history, birth weight, gender of infant, and adverse birth weight outcomes) were analyzed by frequency (number and (%)).The spearman's correlation was performed between FBS and pre-pregnancy BMI. Chi-square test was used to evaluate the relationship between FBS and macrosomia. The analysis of covariance (ANCOVA) with adjusting the baseline values (maternal age, maternal pre-BMI, and infant birth weight) was performed to compare the GWG during 2 nd and 3 rd trimester with FBS. The risk for adverse birth weight outcomes (macrosomia, LBW, SGA and LGA) in women with different pre-pregnancy BMIs and GWGs were tested using the multivariable multinomial logistic regression analysis to estimate adjusted odds ratios (aOR) and 95% confidence intervals (95% CI). The binary logistic regression was used to estimate the risk of macrosomia in women with different FBS levels. Results: This study included 1457 pairs of the mother and offspring. The characteristics of the samples are shown in Table 1 . The prevalence of maternal overweight and obesity were shown 56.8%. The proportion of underweight mothers was 3.5%. Table 1 Characteristics of the studied sample of mothers and their offspring. Maternal characteristics Maternal age (years), mean (SD) 28.36 (5.60) Pre-pregnancy BMI, N (%) • 30 kg/ m 2 43 (3.5) 491(39.7) 459 (37.2) 242 (19.6) GWG, N (%) • Below IOM guidelines • Within IOM guidelines • Above IOM guidelines 452 (36.6) 210 (17) 573 (46.4) last delivery mode • Cesarean • Vaginal 557 (47.2) 622 (52.8) Gestational Diabetes Mellitus N (%) 43 (3.5) Pre-pregnancy BMI, mean (SD) • Underweight • Normal • Overweight • Obesity Incremental GWG (kg/wk) 2nd trimester 3rd trimester 0.46 (0.243) 0.43 (0.643) 0.37 (0.408) 0.37 (0.553) 0.38 (0.336) 0.32 (0.561) 0.29 (0.340) 0.22 (0.616) • FBS Less than 92 (mg/dl) N(%) • FBS Equal /More than 92 (mg/dl) N(%) 1305 (90.6) 135 (9.4) Offspring characteristics Males, N (%) 692(52.6) Birth weight (kg), mean (SD) • LBW N (%) • Normal birth weight N (%) • Macrosomia N (%) • SGA N (%) • AGA N (%) • LGA N (%) 3271.37 (486.57) 65(4.5) 1286(89.3) 89(6.2%) 145 (10.1) 1166 (81) 129 (9) Data expressed as N (%) or mean (SD). BMI, Body Mass Index; GWG, Gestational weight gain; GDM, Gestational Diabetes Mellitus; FBS, fasting blood sugar; LBW, low birth weight; AGA, Appropriate for gestational age; SGA, small-for-gestational age; LGA, large -for-gestational age; 36.6% and 46.4% of mothers had GWG below and above IOM guidelines, respectively. The normal birth weight and appropriate gestational for age (AGA) were reported as 89.3% and 81%, respectively. Also, no preterm birth was reported in the present study. Moreover, the prevalence of LBW, SGA, LGA and macrosomia were 4.5%, 10.1%, 9% and 6.2% respectively (Table 1 ). Also, GWG above IOM guidelines was found 56.3% and 51% in overweight and obese mothers, respectively. The prevalence of inadequate GWG and excessive weight gain in normal-weight mothers were 39.7% and 37.3%, respectively. The FBS level ≥ 92 mg/dl was 9.4%. The association was found between maternal pre-pregnancy BMI and FBS level (p = 0.0001). The increase in prevalence rate of macrosomia was found as 11.9% and 5.6% in the mothers with FBS ≥ and less than 92 mg/dl, respectively (p = 0.004). FBS ≥ 92 mg/dl is related to a higher incidence of macrosomia (OR 2.75, 95% CI 1.43 − 5.25), especially with adjusted variables (pre-pregnancy BMI, maternal age, hemoglobin, delivery mode, and GWG in the 2nd and 3rd trimester) (aOR 3.58, 95% CI 1.69 − 7.58). GWG during 2nd and 3rd trimester was higher in mothers with FBS ≥ 92 mg/dl in comparison to FBS less than 92 mg/dl (0.358 gr/week vs. 0.235 g/ week, p = 0.01). (Not present in table) In comparing normal weight mothers, overweight mothers were at increased risk of LGA Mothers with GWG below the IOM guideline were at the increased risk for compared to GWG within IOM guideline (Table 2 ). Table 2 Adverse birth weight outcomes associated with maternal pre-pregnancy BMI and Gestational Weight Gain according to Institute of Medicine guidelines. Pre-pregnancy BMI Macrosomia OR (95% CI) P LBW OR (95% CI) P LGA OR (95% CI) P SGA OR (95% CI) P Normal 1 1 1 1 Underweight 0.42 (0.05–3.68) 0.43 1.58 (0.39–6.33) 0.51 0.21 ( 0.02–1.74) 0.14 1.27 (0.3–4.95) 0.78 Overweight 0.52 (0.199–1.38) 0.19 1.93 (0.51–7.38) 0.33 3.18 (1.45–7.29) 0.007 1.26 (0.56–2.82) 0.56 Obese 0.77 (0.31–1.89) 0.56 1.63 (0.71–5.69) 0.45 1.1 (0.85–1.4) 0.12 1.21 (0.54–2.7) 0.63 GWG Within IOM guideline 1 1 1 1 Below IOM guideline 0.47 (0.125–1.79) 0.88 3.17 (0.77–13.14) 0.11 1.11 (0.4–3.07) 0.83 2.9 (1.16–7.45) 0.02 Above IOM guideline 1.09 (0.33–3.57) 0.27 0.855 (0.16–4.51) 0.85 0.46 (0.14–1.45) 0.18 1.7 (0.77–4.19) 0.17 Data presented as OR (95% CI) GWG ,Gestational Weight Gain; IOM, Institute of Medicine. Adjusted for gestational weight gain during trimester 2 sd and 3rd, maternal age, gravity, maternal fasting blood sugar, delivery mode and infant gender. The birth weight was increased along with higher pre-pregnancy BMI (p = 0.04)(Table 3 ). Table 3 The association between birth weight with pre-pregnancy BMI and Gestational Weight Gain according to Institute of Medicine guidelines. Pre-pregnancy BMI, (N) Birth weight, Mean (SD) Underweight (42) 3194.28 (398.16) Normal (488) 3244.54 (479.2) Overweight (456) 3265.13 (499.39) Obese (239) 3346.59 (508.13) p-value 0.04 GWG (N) Below IOM guideline 3265.90 (496.13) Within IOM guideline 3246.31(445.38) Above IOM guideline 3282.74 (503.37) p-value 0.64 Data presented as Mean (SD) GWG, Gestational Weight Gain; IOM, Institute of Medicine. GWG less than the IOM guidelines were associated with higher rates of SGA for mothers with a pre-pregnancy normal BMI. For overweight mothers, GWG less than the IOM guidelines were associated with higher rates of macrosomia, LBW and LGA, in comparison with the overweight mothers with GWG within the IOM guidelines. In addition, for overweight mothers, GWG above the IOM guidelines were associated with higher risks of macrosomia, LBW, and LGA in comparison to the overweight mothers with GWG within the IOM guidelines (Table 4 ). Table 4 The birth weight associated with gestational weight gain according to Institute of Medicine (IOM) guidelines in women with pre-pregnancy BMI. Maternal BMI Outcome Below IOM guidelines a Within IOM guidelines a Above IOM guidelines a Below vs. Within Adjusted OR (95% CI) b P above vs. Within Adjusted OR (95% CI) b P underweight Normal birth weight 0 0 0 - - - - Macrosomia 1 (4.8) 0 0 - - - - LBW 20 (95.2) 12 (100) 9 (100) - - - - AGA 17 (81) 2 (16.7) 0 - - - - SGA 2 (9.5) 10 (83.3) 9 (100) - - - - LGA 2 (9.5) 0 0 - - - - normal weight Normal birth weight 13 (6.7) 14 (12.5) 6 (3.3) 1 1 Macrosomia 8 (4.1) 4 (3.6) 13 (7.2) 1.204 (0.138–10.48) 0.86 0.845 (0.105–6.804) 0.87 LBW 174 (89.2) 105 (93.8) 162 (89.5) 5.98 (0.504–70.960) 0.15 0.351 (0.016–7.925) 0.51 AGA 27 (13.8) 13 (9) 14 (12.5) 1 1 SGA 156 (80) 117 (81.3) 94 (83.9) 5.4 (1.02–28.4) 0.04 0.418 (0.096–1.818) 0.24 LGA 12 (6.2) 14 (9.7) 4 (3.6) 0.665 (0.084–5.24) 0.69 2.48 (0.348–17.72) 0.36 Overweight Normal birth weight 6 (4.2) 2 (3.6) 13 (5.1) 1 1 Macrosomia 10 (6.9) 3 (5.5) 17 (6.6) 10.3 (7.84–54.01) < 0.001 13.3 (13.327–13.33) 0.0001 LBW 128 (88.9) 50 (90.9) 227 (88.3) 5.4 (2.73–32.7) < 0.001 11.23 (11.22–11.25) 0.0001 AGA 3 (9) 5 (9.1) 25 (9.7) 1 1 SGA 117 (85.5) 47 (85.5) 205 (79.8) 2.19 (0.38–12.67) 0.38 1.415 ( 0.254–7.88) 0.69 LGA 14 (9.7) 3 (5.5) 27 (10.5) 4.61 (2.91–8.53) 0.0001 6.6 ( 2.6–32.1) 0.0001 Obesity Normal birth weight 2 (2.3) 1 (3.4) 6 (4.9) 1 1 Macrosomia 10 (11.4) 3 (10.3) 6 (4.9) 0.605 (0.34–10.74) 0.73 4.01 (0.24–65.02) 0.33 LBW 76 (86.4) 25 (86.2) 110 (90.2) 1.2 (0.21–80.6) 0.9 0.064 (0.000–19.02) 0.34 AGA 7 (8) 5 (17.2) 10 (8.2) 1 1 SGA 70 (79.5) 20 (69) 98 (80.3) 2.3 (0.23–23.24) 0.47 0.036 (0.001–1.12) 0.05 LGA 11 (12.5) 4 (13.8) 14 (11.5) 0.387 ( 0.042–3.55) 0.4 2.21 (0.293–16.67) 0.44 multivariable multinomial logistic regression analysis. a Data presented as N (%). b Data presented as OR (95% CI). Adjusted for gestational weight gain during trimester 2 sd and 3rd, maternal age, gravity, maternal fasting blood sugar, delivery mode and infant gender. The mean (SD) of the maternal age was 28.36 (5.60) years old. The increasing trend of pre-pregnancy BMI was observed along with the increasing of maternal age. Female gender showed a positive association with LBW in pre-pregnancy normal-weight mothers (p = 0.04). Discussion: The findings of present retrospective cohort study indicated an increased risk for LGA, LBW and macrosomia in overweight mothers and an increased risk of SGA in the mothers with GWG below IOM guidelines. The average of GWG was similar to the IOM recommendations in normal BMI mothers during, the 2nd and 3rd trimester of pregnancy, and was different with IOM guidelines in other groups of pre-gestational BMI during mid- or late-pregnancy. Due to the little number of underweight mothers, it was not possible to make an association between GWG, pre-pregnancy BMI and birth weight status. In normal weight mothers, a high risk of SGA was significantly associated with inadequate GWG. In agreement with the previous studies, an increased risk of LGA[ 19 , 20 ], LBW[ 21 ], and macrosomia [ 21 , 22 ] was observed in overweight mothers with GWG outside guidelines, significantly. The prevalence of GWG above the IOM recommendations was more common, in comparison with the below one, which is in agreement with the results reported by Power et al.[ 20 ]. In our study 46.4% had weight gain greater than IOM recommendation. Also, in recent systematic meta-analysis reported 47% GWG above guidelines [ 9 ]. Inadequate GWG was related to a high risk of SGA and LBW, consistent with a longitudinal cohort studies in China [ 23 ], Taiwan[ 24 ], and higher pre-gestational BMI increased risk for LGA and macrosomia were reported in overweight/obese mothers [ 25 ], which are in agreement with the findings of the present study. in our study higher pre-BMI was associated with higher risk of adverse birth weight. In agreement, lima et al. [ 26 ], showed an increasing trend for the birth weight across higher pre-pregnancy BMI. Moreover, the prevalence of macrosomia (6.2%) was higher in Ahvaz than the mean of Iran (5.2%) [ 27 ] and lower than a pervious retrospective hospital- based (2007–2011) study conducted in Razi Hospital, Ahvaz city was reported 9% [ 15 ]. Likewise, increasing pre-pregnancy BMI was associated with the risk of higher fasting blood glucose between 24–28 weeks of pregnancy. In addition, higher risk of GDM was associated with higher rate of macrosomia. Consistent with our findings, a study among 256 pregnant women in the United Arabia Emirate reported that pre-pregnancy BMI ≥ 25 kg/m2 were at higher risk of having GDM [ 28 ]. In agreement with our findings, a meta-analysis of 33 observational studies indicated that risk of GDM is positively associated with pre-pregnancy BMI [ 29 ]. however, the result of a study on Asian indicated that obese Thai women were not at increased risk for gestational diabetes mellitus was in contrast with result of present study [ 30 ].The possible reason of this difference is due to the WHO’s recommended BMI for Asians was used to define obesity. In addition, our study and another studies [ 31 , 32 ] showed that gestational hyperglycemia had a positive association with macrosomia. The possible mechanisms of the high risk of adverse birth weight in high weight mothers could be due to the stimulating of insulin production in overweight mothers, therefore, lipogenesis and fat deposition would be increased in their offspring, so it can alter the growth of the fetus [ 33 ]. In the present study, we attempted for having large possible sample size from different health care centers to cover all ethnic groups together including Fars, Lure, Arab, and Bakhtiari. However, the exact number of different ethnic groups is not included in maternal records. So, we had limitation to explore ethnic differences in pre-pregnancy BMI, prevalence of GWG below or outside IOM guidelines and pregnancy outcomes. In addition, pairs of mother and child document since 2010 to 2018 were taken into account and it could be highly reflect the current situation. pre-pregnancy weight was recorded from antenatal records, and it may be measured by health member or self-reported leading to the risk of recall bias, which is in line with other studies [ 26 ]. However, they were valid to be used in epidemiologic study [ 34 ]. Moreover, in the current study the 2009 IOM guideline was applied for GWG based on pre-pregnancy BMI. Furthermore, the recent meta-analysis [ 35 ] included 23 studies, explored ethnic differences based on IOM guidelines and regional guidelines in maternal pre-pregnancy BMI and GWG on pregnancy outcome across the USA, Western Europe and East Asia. However, there was data restriction from Middle East. In fact, the IOM approaches are primarily based on USA-dwelling, showed limited data on ethnic differences in associations between GWG and pregnancy outcomes. Then, led to heterogeneity and diminished the chance of comparisons across regions. Asia is the most inhabitant of the world’s population. In 2004 WHO consultation group [ 36 ] reported, Asians may have higher odds of disease at a BMI cut-off (lower than 25 kg/m2). Likewise, Asians are likely to have a higher percent of adipose tissue, especially visceral adiposity, at lower BMI cut-off points than that stated by the WHO as standard cut-off points [ 37 ]. In particular, finding of recent study showed that Iranians are at higher risks of morbidity related to metabolic factors at a lower BMI cut-off with an estimated 38.8% of the population having metabolic syndrome [ 38 ]. Importantly, the significant difference in Asian countries is based on ethnic and cultural subgroups, degrees of urbanization, social and economic conditions, and nutrition transitions [ 36 ].Therefore, establishing a new guideline and GWG recommendation for Asian populations is necessary for optimal risk reduction during pregnancy [ 24 ]. In the present study the information related to socio-demographic and lifestyle characteristics (alcohol consumption and smoking) were not accurate due to their social beliefs. According to the literature, this is the first study in public health care centers in South-west of Iran that present the association between GWG and pre-pregnancy BMI with adverse pregnancy outcome. Thus, screening for overweight and obesity is an important preventive approach. It seems that along with all gestational monitoring and nutrition counseling, more educational programs in the health care centers are vital, due to the presence of multiple ethnic groups in Ahvaz city with different cultural habits. Conclusion: The important results of this study were the higher prevalence of maternal overweight, obesity, and excessive GWG. The most adverse birth weight was observed in overweight mothers with inappropriate GWG. Accordingly, the expanded programs of the healthy lifestyle education are required for the women in childbearing age (before and during pregnancy) to improve the pregnancy outcomes. Abbreviations Body mass index; BMI, gestational weight gain;GWG, gestational diabetes mellitus;GDM, ,large for gestational age; LGA, small for gestational age;SGA, appropriate size for gestational age;AGA, low birth weight;LBW, type 2 diabetes mellitus;T2DM, fasting blood sugar;FBS, IOM;institute of medicine, standard deviations;SD, analysis of covariance;ANCOVA, adjusted odds ratios;aOR, International Association of Diabetes and Pregnancy Study Groups;IADPSG Declarations Ethics approval and consent to participate: This study is retrospective cohort which has been approved with ethical number (IR.AJUMS.REC. 1396.80) by Research Deputy of Ahvaz Jundishapur University of Medical Sciences and Social Determinants of Health Research Center. Consent for publication: the present retrospective study has been approved by Ethic committee of Jundishapur University of medical sciences. Availability of data and materials: The data that support the findings of this study are available on request from the corresponding author. Competing interests : All authors report no conflicts of interests and have no relevant disclosures. Funding: This research was supported by the Research Deputy of Ahvaz Jundishapur University of Medical Sciences and Social Determinants of Health Research Center to provide the funding of this research project (IR.AJUMS.REC. 1396.80). Author Contributions: F Borazjani designed the study question, supervised data collection, data analysis,assisted in writing the manuscript ,M Azhdari cooperate in data collection and assisted in writing the manuscript ; P Shahri cooperate in data collection and conducted the literature review; K.A. Angali designed the study and all statistical modelling and interpretation of data; M Cheraghi supervise data collection and assisted in research design; S Salmanzadeh managed data collection and conducted the literature review. All authors in concept and design of study, revising it critically for important intellectual content and final approval of manuscript. Acknowledgments: We highly appreciate the Research Deputy of Ahvaz Jundishapur University of Medical Sciences and Social Determinants of Health Research Center to approve this research project (IR.AJUMS.REC. 1396.80). References Xiao L, Ding G, Vinturache [i] A, et al. Associations of maternal pre-pregnancy body mass index and gestational weight gain with birth outcomes in Shanghai, China. Sci Rep. 2017;7:41073. WHO Fact sheet: obesity and overweight. http://www.who.int/news-room/fact-sheets/detail/obesity-and-overweight.: WHO; 2018 Gilmore LA, Redman LM. 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Association of prepregnancy body mass index, rate of gestational weight gain with pregnancy outcomes in Chinese urban women. Nutr Metab (Lond). 2019;16:54. Chen C-N, Chen H-S, Hsu H-C. Maternal Prepregnancy Body Mass Index, Gestational Weight Gain, and Risk of Adverse Perinatal Outcomes in Taiwan: A Population-Based Birth Cohort Study. Int J Environ Res Public Health. 2020;17(4):1221. Zhao RF, Zhou L, Zhang WY. Identifying appropriate pre-pregnancy body mass index classification to improve pregnancy outcomes in women of childbearing age in Beijing, China: a retrospective cohort study. Asia Pac J Clin Nutr. 2019;28(3):567-76. Lima RJCP, Batista RFL, Ribeiro MRC, et al. Prepregnancy body mass index, gestational weight gain, and birth weight in the BRISA cohort. Rev Saude Publica. 2018;52:46. Maroufizadeh S, Almasi-Hashiani A, Esmaeilzadeh A, etal. Prevalence of Macrosomia in Iran: A Systematic Review and Meta-Analysis. Int J Pediatr. 2017;5(9):5617-29. Hashim M, Radwan H, Hasan H, et al. Gestational weight gain and gestational diabetes among Emirati and Arab women in the United Arab Emirates: results from the MISC cohort. BMC Pregnancy and Childbirth. 2019;19(1):463. Najafi F, Hasani J, Izadi N, et al. The effect of prepregnancy body mass index on the risk of gestational diabetes mellitus: A systematic review and dose-response meta-analysis. Obes Rev. 2019;20(3):472-86. Kongubol A, Phupong V. Prepregnancy obesity and the risk of gestational diabetes mellitus. BMC pregnancy and childbirth. 2011;11(1):59. Tabrizi R, Asemi Z, Lankarani KB, et al. Gestational diabetes mellitus in association with macrosomia in Iran: a meta-analysis. J Diabetes Metab Disord. 2019:1-10. Zhang Y, Chen Z, Cao Z, et al. Associations of maternal glycemia and prepregnancy BMI with early childhood growth: a prospective cohort study. Ann N Y Acad Sci. 2019. Muhlhausler BS, Vithayathil MA. Impact of maternal obesity on offspring adipose tissue: lessons for the clinic. ExpertRev Endocrinol Metab. 2014;9(6):615-27. Fonseca Mde J, Faerstein E, Chor D, etal. [Validity of self-reported weight and height and the body mass index within the "Pro-saude" study]. Rev Saude Publica. 2004;38(3):392-8. Goldstein RF, Abell SK, Ranasinha S, et al. Gestational weight gain across continents and ethnicity: systematic review and meta-analysis of maternal and infant outcomes in more than one million women. BMC Med. 2018;16(1):153. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet . 2004;363(9403):157-63. Zeng Q, He Y, Dong S, et al. Optimal cut-off values of BMI, waist circumference and waist: height ratio for defining obesity in Chinese adults. Br J Nutr. 2014;112(10):1735-44. Babai MA, Arasteh P, Hadibarhaghtalab M, et al. Defining a BMI cut-off point for the Iranian population: the Shiraz Heart Study. PloS one. 2016;11(8). Supplementary Files STROBEchecklistcrosssectional.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-117813","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research article","associatedPublications":[],"authors":[{"id":5487037,"identity":"17605348-1d44-44a1-ba89-638ffc16c3f9","order_by":0,"name":"Kambiz Ahmadi Angali","email":"","orcid":"","institution":"Ahvaz Jundishapur University of Medical Sciences: Ahvaz Jondishapour University of Medical Sciences","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Kambiz","middleName":"Ahmadi","lastName":"Angali","suffix":""},{"id":5487038,"identity":"4c1ea6ef-e6a4-4e69-afb6-52efe7de8c3d","order_by":1,"name":"Maryam Azhdari","email":"","orcid":"","institution":"Ahvaz Jundishapur University of Medical Sciences: Ahvaz Jondishapour University of Medical Sciences","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Maryam","middleName":"","lastName":"Azhdari","suffix":""},{"id":5487039,"identity":"2fd3700a-daaf-42b8-ac5b-8c0fb5e1473e","order_by":2,"name":"Maria Cheraghi","email":"","orcid":"","institution":"Ahvaz Jundishapur University of Medical Sciences: Ahvaz Jondishapour University of Medical Sciences","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Maria","middleName":"","lastName":"Cheraghi","suffix":""},{"id":5487040,"identity":"cff70cc7-573d-47b6-9116-f13ae710418a","order_by":3,"name":"parvin shahri","email":"","orcid":"","institution":"Ahvaz Jundishapur University of Medical Sciences: Ahvaz Jondishapour University of Medical Sciences","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"parvin","middleName":"","lastName":"shahri","suffix":""},{"id":5487041,"identity":"2f2a80da-8cf8-4ce0-8e45-4d7c676f568c","order_by":4,"name":"shokrolah salmanzadeh","email":"","orcid":"","institution":"Ahvaz Jundishapur University of Medical Sciences: Ahvaz Jondishapour University of Medical Sciences","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"shokrolah","middleName":"","lastName":"salmanzadeh","suffix":""},{"id":5487042,"identity":"f27a4790-16fe-4f07-8bfa-2ecd9127e336","order_by":5,"name":"fatemeh borazjani","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9klEQVRIiWNgGAWjYBAC9gYGNjCDsYGB4cAHIIONnYAWngNIWg7OAGlhJlYLCDDzgElCWtgPsD34uMfOnrn97MHDNr+2yfMxMzB++JiDRwtPArvhjGfJzIw9eQmHc/tuG7YxMzBLztyGW4s9QwKbNM8BZjbGhhyDw7k9txmBWtiYefFo4eF/ANJSz8PY/8bgsGXPbXvCWiTAthyWYJwBtIXhx+1EIrQ8bDecceC4AeOMNwYHextuJ7cxMzbj9QsPf/KxBx8OVNsb9ucYf/jx57bt/Pbmgx8+4tECiUMgMARRjG1IIgSBPJj8Q5ziUTAKRsEoGFkAAEyjTj1KykU3AAAAAElFTkSuQmCC","orcid":"","institution":"Ahvaz Jundishapur University of Medical Sciences: Ahvaz Jondishapour University of Medical Sciences","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"fatemeh","middleName":"","lastName":"borazjani","suffix":""}],"badges":[],"createdAt":"2020-11-28 14:50:50","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-117813/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-117813/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":13625512,"identity":"0b88612a-97dc-4f79-b531-eb6006d2b6d3","added_by":"auto","created_at":"2021-09-17 07:26:40","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":418347,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-117813/v1/f4bb534e-4f18-41ed-8e9e-33289a573777.pdf"},{"id":4020025,"identity":"cdce9413-1ee3-452e-8f18-06c32d252bcc","added_by":"auto","created_at":"2020-12-04 16:42:47","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":29229,"visible":true,"origin":"","legend":"","description":"","filename":"STROBEchecklistcrosssectional.docx","url":"https://assets-eu.researchsquare.com/files/rs-117813/v1/0700f31c0865331cf3b7513e.docx"}],"financialInterests":"","formattedTitle":"The Association between Pre-Pregnancy BMI, Gestational Weight Gain and Pregnancy Outcomes: A Retrospective Cohort Study in Ahvaz, Iran","fulltext":[{"header":"Background:","content":" \u003cp\u003eMaternal pre-pregnancy BMI( Body mass index) and maternal gestational weight gain (GWG) can have positive effects on birth and maternal outcomes [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The prevalence of overweight and obesity is increasing in all age groups worldwide, and it is related to non-communicable diseases [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Nonetheless, WHO reported more than half of the Iranian females are overweight or obese [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. The global burden of overweight and obese pregnant women has increased in high income and middle income countries [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Additionally, the Islamic Republic of Iran was considered for the 20 high overweight burden countries[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Therefore, the pre-pregnancy BMI and GWG below or above the Institute of Medicine (IOM) guidelines are considered as two effective factors on pregnancy outcomes [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The prevalence of the adverse outcomes was reported as 37.2% in pregnant women, ranging from 34.7\u0026ndash;61.1% among underweight and obese (grade3) women, respectively. Adverse maternal and infant outcomes were affected by maternal pre-pregnancy BMI more than incremental gestational weight gain [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe finding of some epidemiological studies [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] have reported a positive association between pre-pregnancy BMI and the prevalence of gestational diabetes mellitus (GDM), as well as higher risk of childhood obesity [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eA meta-analysis in 2017 reported that a low GWG was positively related to small for gestational age (SGA) and preterm birth, and lower risk for large for gestational age (LGA) and macrosomia. Also, a higher risk for LGA, macrosomia, and cesarean delivery was found in excessive GWG [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. The excessive GWG can result in adverse maternal outcomes such as cesarean delivery, GDM, preeclampsia, and postnatal weight retention [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. In 2009, IOM has recommended the mean and range for the incremental weight gain during the 2nd and 3rd trimester by pre-pregnancy BMI class [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDespite the importance of adequate total GWG, the excessive GWG before 20 weeks was associated with a higher risk of LGA, regardless of total GWG [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Also, the early excessive GWG can lead to a higher prevalence of GDM, regardless of pre-pregnancy BMI (6). Several epidemiological studies have provided some evidence from different regions of Iran, in terms of the role of GWG and pre-pregnancy BMI and adverse pregnancy outcomes. Hence, low birth weight (LBW) [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] more prevalent in women with GWG less than the weight gain recommended by institute of medicine (IOM) and macrosomia [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] reported in women with GWG higher than the guideline. In addition, women with pre-pregnancy obesity were associated to macrosomic infants [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMoreover, with a corresponding rise in overweigh and obesity among population, this lead to an increase in GWG and adverse pregnancy outcome. Therefore, the aim of this retrospective cohort study was to evaluate the relationship between maternal pre-pregnancy BMI, Gestational Weight Gain and pregnancy outcomes.\u003c/p\u003e "},{"header":"Methods:","content":"\u003cp\u003eData of this retrospective cohort study were extracted using the pair health records of the pregnant mother and infant at Ahvaz health care centers from 2010 to 2018. The study was approved by the Ethics Committee of Ahvaz Jundishapur University of Medical Sciences (IR.AJUMS.REC.1396.80).\u003c/p\u003e\n\u003cp\u003eThe final sample size has 1457 participants out of 1800 based on GWG as the main variable. The trained research assistants were comprehensively collected information .Exclusion criteria were as follows; incomplete data for maternal during pregnancy and her offspring, multiple pregnancies, preeclampsia/ eclampsia and type 2 diabetes mellitus (T2DM), and preterm pregnancy. Information included\u0026nbsp; 1: maternal characteristics (age, pre-pregnancy weight and height, pre-pregnancy BMI, GWG, last delivery mode, pregnancy history (GDM, lifestyle before and during pregnancy (alcohol consumption and smoking), fasting blood sugar (FBS), was categorized into \u0026ge; 92 and \u0026lt; 92 according to International Association of Diabetes and Pregnancy Study Groups (IADPSG)[17], and 2: offspring characteristics comprise of gender, birth weight, small for gestational age ( SGA), large for gestational age(LGA), appropriate size for gestational age(AGA) at birth, low birth weight (LBW), normal birth weight, and macrosomia.\u003c/p\u003e\n\u003ch2\u003eMeasurements:\u003c/h2\u003e\n\u003cp\u003eSGA and LGA new-born were defined as those whose birth weights for gestational age were \u0026lt; 10\u003csup\u003eth\u003c/sup\u003e and \u0026gt; 90\u003csup\u003eth\u003c/sup\u003e percentiles. Macrosomia and\u0026nbsp; LBW were defined by a birth weight \u0026gt; 4000g and \u0026lt; 2500g, respectively [18]. Pre-pregnancy BMI and GWG categories were estimated in terms of the IOM recommendations. Some variables were calculated as followings:\u003c/p\u003e\n\u003cp\u003ePre-pregnancy BMI (kg /m\u003csup\u003e2\u003c/sup\u003e): the dividing pre-pregnancy self-reported body weight (kg) by height (m\u003csup\u003e2\u003c/sup\u003e) was measured at the first antenatal visit, (weight (kg) / height\u003csup\u003e2 \u003c/sup\u003e(m\u003csup\u003e2\u003c/sup\u003e)).\u003c/p\u003e\n\u003cp\u003eIncremental weight gain (gr /week): the difference weight 2 and weight 1 divided by weeks between weights (weight 2 \u0026ndash; weight 1) (gr) / follow up duration (week) [3].\u003c/p\u003e\n\u003ch2\u003eStatistical analysis:\u003c/h2\u003e\n\u003cp\u003eSPSS statistical software package, version 18.0 (SPSS, Inc, Chicago, Illinois, USA) was used for statistical analyses. P values \u0026lt;.05 were considered as statistically significant using the 2-tailed tests. The analysis of continuous variables (maternal age, GWG rate during trimester 2\u003csup\u003esd\u003c/sup\u003e and 3\u003csup\u003erd\u003c/sup\u003e, birth weight) was performed by the means (standard deviations (SD)). The categorical variables (FBS, pre-pregnancy BMI, GWG, last delivery mode, disease history, birth weight, gender of infant, and adverse birth weight outcomes) were analyzed by frequency (number and (%)).The spearman's correlation was performed between FBS and pre-pregnancy BMI. Chi-square test was used to evaluate the relationship between FBS and macrosomia.\u003c/p\u003e\n\u003cp\u003eThe analysis\u0026nbsp;of\u0026nbsp;covariance\u0026nbsp;(ANCOVA)\u0026nbsp;with\u0026nbsp;adjusting\u0026nbsp;the\u0026nbsp;baseline\u0026nbsp;values (maternal age, maternal pre-BMI, and infant birth weight) was performed to compare the GWG during 2\u003csup\u003end\u003c/sup\u003e and 3\u003csup\u003erd\u003c/sup\u003e trimester with FBS.\u0026nbsp; The risk for adverse birth weight outcomes (macrosomia, LBW, SGA and LGA) in women with different pre-pregnancy BMIs and GWGs were tested using the multivariable multinomial logistic regression analysis to estimate adjusted odds ratios (aOR) and 95% confidence intervals (95% CI). The binary logistic regression was used to estimate the risk of macrosomia in women with different FBS levels.\u003c/p\u003e"},{"header":"Results:","content":"\u003cp\u003eThis study included 1457 pairs of the mother and offspring. The characteristics of the samples are shown in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. The prevalence of maternal overweight and obesity were shown 56.8%. The proportion of underweight mothers was 3.5%.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab1\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eCharacteristics of the studied sample of mothers and their offspring.\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eMaternal characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMaternal age (years), mean (SD)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e28.36 (5.60)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePre-pregnancy BMI, N (%)\u003c/p\u003e\n\u003cp\u003e\u0026bull; \u0026lt;\u0026thinsp;18.5\u0026nbsp;kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e\u0026bull; 18.5\u0026ndash;24.9\u0026nbsp;kg/ m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e\u0026bull; 25-29.9\u0026nbsp;kg/ m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e\u0026bull; \u0026gt;\u0026thinsp;30\u0026nbsp;kg/ m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e43 (3.5)\u003c/p\u003e\n\u003cp\u003e491(39.7)\u003c/p\u003e\n\u003cp\u003e459 (37.2)\u003c/p\u003e\n\u003cp\u003e242 (19.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eGWG, N (%)\u003c/p\u003e\n\u003cp\u003e\u0026bull; Below IOM guidelines\u003c/p\u003e\n\u003cp\u003e\u0026bull; Within IOM guidelines\u003c/p\u003e\n\u003cp\u003e\u0026bull; Above IOM guidelines\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e452 (36.6)\u003c/p\u003e\n\u003cp\u003e210 (17)\u003c/p\u003e\n\u003cp\u003e573 (46.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003elast delivery mode\u003c/p\u003e\n\u003cp\u003e\u0026bull; Cesarean\u003c/p\u003e\n\u003cp\u003e\u0026bull; Vaginal\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e557 (47.2)\u003c/p\u003e\n\u003cp\u003e622 (52.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eGestational Diabetes Mellitus N (%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e43 (3.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePre-pregnancy BMI, mean (SD)\u003c/p\u003e\n\u003cp\u003e\u0026bull; Underweight\u003c/p\u003e\n\u003cp\u003e\u0026bull; Normal\u003c/p\u003e\n\u003cp\u003e\u0026bull; Overweight\u003c/p\u003e\n\u003cp\u003e\u0026bull; Obesity\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eIncremental GWG (kg/wk)\u003c/p\u003e\n\u003cp\u003e2nd trimester 3rd trimester\u003c/p\u003e\n\u003cp\u003e0.46 (0.243) 0.43 (0.643)\u003c/p\u003e\n\u003cp\u003e0.37 (0.408) 0.37 (0.553)\u003c/p\u003e\n\u003cp\u003e0.38 (0.336) 0.32 (0.561)\u003c/p\u003e\n\u003cp\u003e0.29 (0.340) 0.22 (0.616)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026bull; FBS Less than 92 (mg/dl) N(%)\u003c/p\u003e\n\u003cp\u003e\u0026bull; FBS Equal /More than 92 (mg/dl) N(%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1305 (90.6)\u003c/p\u003e\n\u003cp\u003e135 (9.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eOffspring characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMales, N (%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e692(52.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBirth weight (kg), mean (SD)\u003c/p\u003e\n\u003cp\u003e\u0026bull; LBW N (%)\u003c/p\u003e\n\u003cp\u003e\u0026bull; Normal birth weight N (%)\u003c/p\u003e\n\u003cp\u003e\u0026bull; Macrosomia N (%)\u003c/p\u003e\n\u003cp\u003e\u0026bull; SGA N (%)\u003c/p\u003e\n\u003cp\u003e\u0026bull; AGA N (%)\u003c/p\u003e\n\u003cp\u003e\u0026bull; LGA N (%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3271.37 (486.57)\u003c/p\u003e\n\u003cp\u003e65(4.5)\u003c/p\u003e\n\u003cp\u003e1286(89.3)\u003c/p\u003e\n\u003cp\u003e89(6.2%)\u003c/p\u003e\n\u003cp\u003e145 (10.1)\u003c/p\u003e\n\u003cp\u003e1166 (81)\u003c/p\u003e\n\u003cp\u003e129 (9)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\"\u003e\n\u003cp\u003eData expressed as N (%) or mean (SD).\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\"\u003e\n\u003cp\u003eBMI, Body Mass Index; GWG, Gestational weight gain; GDM, Gestational Diabetes Mellitus; FBS, fasting blood sugar; LBW, low birth weight; AGA, Appropriate for gestational age; SGA, small-for-gestational age; LGA, large -for-gestational age;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e36.6% and 46.4% of mothers had GWG below and above IOM guidelines, respectively. The normal birth weight and appropriate gestational for age (AGA) were reported as 89.3% and 81%, respectively. Also, no preterm birth was reported in the present study. Moreover, the prevalence of LBW, SGA, LGA and macrosomia were 4.5%, 10.1%, 9% and 6.2% respectively (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eAlso, GWG above IOM guidelines was found 56.3% and 51% in overweight and obese mothers, respectively. The prevalence of inadequate GWG and excessive weight gain in normal-weight mothers were 39.7% and 37.3%, respectively.\u003c/p\u003e\n\u003cp\u003eThe FBS level\u0026thinsp;\u0026ge;\u0026thinsp;92\u0026nbsp;mg/dl was 9.4%. The association was found between maternal pre-pregnancy BMI and FBS level (p\u0026thinsp;=\u0026thinsp;0.0001). The increase in prevalence rate of macrosomia was found as 11.9% and 5.6% in the mothers with FBS\u0026thinsp;\u0026ge;\u0026thinsp;and less than 92\u0026nbsp;mg/dl, respectively (p\u0026thinsp;=\u0026thinsp;0.004). FBS\u0026thinsp;\u0026ge;\u0026thinsp;92\u0026nbsp;mg/dl is related to a higher incidence of macrosomia (OR 2.75, 95% CI 1.43 \u0026minus;\u0026thinsp;5.25), especially with adjusted variables (pre-pregnancy BMI, maternal age, hemoglobin, delivery mode, and GWG in the 2nd and 3rd trimester) (aOR 3.58, 95% CI 1.69 \u0026minus;\u0026thinsp;7.58). GWG during 2nd and 3rd trimester was higher in mothers with FBS\u0026thinsp;\u0026ge;\u0026thinsp;92\u0026nbsp;mg/dl in comparison to FBS less than 92\u0026nbsp;mg/dl (0.358 gr/week vs. 0.235\u0026nbsp;g/ week, p\u0026thinsp;=\u0026thinsp;0.01). (Not present in table)\u003c/p\u003e\n\u003cp\u003eIn comparing normal weight mothers, overweight mothers were at increased risk of LGA Mothers with GWG below the IOM guideline were at the increased risk for compared to GWG within IOM guideline (Table\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab2\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eAdverse birth weight outcomes associated with maternal pre-pregnancy BMI and Gestational Weight Gain according to Institute of Medicine guidelines.\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003ePre-pregnancy BMI\u003c/strong\u003e\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eMacrosomia\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOR (95% CI)\u003c/strong\u003e\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eLBW\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOR (95% CI)\u003c/strong\u003e\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eLGA\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOR (95% CI)\u003c/strong\u003e\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eSGA\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOR (95% CI)\u003c/strong\u003e\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNormal\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eUnderweight\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.42 (0.05\u0026ndash;3.68)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.43\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.58 (0.39\u0026ndash;6.33)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.51\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.21 ( 0.02\u0026ndash;1.74)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.27 (0.3\u0026ndash;4.95)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.78\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eOverweight\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.52 (0.199\u0026ndash;1.38)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.19\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.93 (0.51\u0026ndash;7.38)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.33\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.18 (1.45\u0026ndash;7.29)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.007\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.26 (0.56\u0026ndash;2.82)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.56\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eObese\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.77 (0.31\u0026ndash;1.89)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.56\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.63 (0.71\u0026ndash;5.69)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.45\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.1 (0.85\u0026ndash;1.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.21 (0.54\u0026ndash;2.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.63\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eGWG\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"8\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eWithin IOM guideline\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBelow IOM guideline\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.47 (0.125\u0026ndash;1.79)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.88\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.17 (0.77\u0026ndash;13.14)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.11\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.11 (0.4\u0026ndash;3.07)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.83\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.9 (1.16\u0026ndash;7.45)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.02\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAbove IOM guideline\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.09 (0.33\u0026ndash;3.57)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.27\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.855 (0.16\u0026ndash;4.51)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.85\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.46 (0.14\u0026ndash;1.45)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.18\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.7 (0.77\u0026ndash;4.19)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.17\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"9\"\u003e\n\u003cp\u003eData presented as OR (95% CI)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"9\"\u003e\n\u003cp\u003eGWG ,Gestational Weight Gain; IOM, Institute of Medicine.\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"9\"\u003e\n\u003cp\u003eAdjusted for gestational weight gain during trimester 2\u003csup\u003esd\u003c/sup\u003e and 3rd, maternal age, gravity, maternal fasting blood sugar, delivery mode and infant gender.\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eThe birth weight was increased along with higher pre-pregnancy BMI (p\u0026thinsp;=\u0026thinsp;0.04)(Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab3\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eThe association between birth weight with pre-pregnancy BMI and Gestational Weight Gain according to Institute of Medicine guidelines.\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003ePre-pregnancy BMI, (N)\u003c/strong\u003e\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eBirth weight, Mean (SD)\u003c/strong\u003e\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eUnderweight (42)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3194.28 (398.16)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNormal (488)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3244.54 (479.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eOverweight (456)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3265.13 (499.39)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eObese (239)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3346.59 (508.13)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.04\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eGWG\u003c/strong\u003e (N)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBelow IOM guideline\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3265.90 (496.13)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eWithin IOM guideline\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3246.31(445.38)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAbove IOM guideline\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3282.74 (503.37)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.64\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\"\u003e\n\u003cp\u003eData presented as Mean (SD)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\"\u003e\n\u003cp\u003eGWG, Gestational Weight Gain; IOM, Institute of Medicine.\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eGWG less than the IOM guidelines were associated with higher rates of SGA for mothers with a pre-pregnancy normal BMI. For overweight mothers, GWG less than the IOM guidelines were associated with higher rates of macrosomia, LBW and LGA, in comparison with the overweight mothers with GWG within the IOM guidelines. In addition, for overweight mothers, GWG above the IOM guidelines were associated with higher risks of macrosomia, LBW, and LGA in comparison to the overweight mothers with GWG within the IOM guidelines (Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab4\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eThe birth weight associated with gestational weight gain according to Institute of Medicine (IOM) guidelines in women with pre-pregnancy BMI.\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eMaternal BMI\u003c/strong\u003e\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eOutcome\u003c/strong\u003e\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eBelow IOM guidelines \u003csup\u003ea\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eWithin IOM guidelines \u003csup\u003ea\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eAbove IOM guidelines \u003csup\u003ea\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eBelow vs. Within Adjusted OR (95% CI) \u003csup\u003eb\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eabove vs. Within Adjusted OR (95% CI) \u003csup\u003eb\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eunderweight\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNormal birth weight\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMacrosomia\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1 (4.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLBW\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20 (95.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e12 (100)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e9 (100)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAGA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e17 (81)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2 (16.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSGA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2 (9.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e10 (83.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e9 (100)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLGA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2 (9.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003enormal weight\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNormal birth weight\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e13 (6.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e14 (12.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6 (3.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMacrosomia\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8 (4.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4 (3.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e13 (7.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.204 (0.138\u0026ndash;10.48)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.86\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.845 (0.105\u0026ndash;6.804)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.87\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLBW\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e174 (89.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e105 (93.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e162 (89.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.98 (0.504\u0026ndash;70.960)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.15\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.351 (0.016\u0026ndash;7.925)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.51\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAGA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e27 (13.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e13 (9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e14 (12.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSGA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e156 (80)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e117 (81.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e94 (83.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.4 (1.02\u0026ndash;28.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.04\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.418 (0.096\u0026ndash;1.818)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.24\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLGA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e12 (6.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e14 (9.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4 (3.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.665 (0.084\u0026ndash;5.24)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.69\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.48 (0.348\u0026ndash;17.72)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.36\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eOverweight\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNormal birth weight\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6 (4.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2 (3.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e13 (5.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMacrosomia\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e10 (6.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3 (5.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e17 (6.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e10.3 (7.84\u0026ndash;54.01)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e13.3 (13.327\u0026ndash;13.33)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.0001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLBW\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e128 (88.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e50 (90.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e227 (88.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.4 (2.73\u0026ndash;32.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e11.23 (11.22\u0026ndash;11.25)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.0001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAGA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3 (9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5 (9.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e25 (9.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSGA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e117 (85.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e47 (85.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e205 (79.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.19 (0.38\u0026ndash;12.67)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.38\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.415 ( 0.254\u0026ndash;7.88)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.69\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLGA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e14 (9.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3 (5.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e27 (10.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.61 (2.91\u0026ndash;8.53)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.0001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6.6 ( 2.6\u0026ndash;32.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.0001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eObesity\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNormal birth weight\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2 (2.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1 (3.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6 (4.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMacrosomia\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e10 (11.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3 (10.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6 (4.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.605 (0.34\u0026ndash;10.74)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.73\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.01 (0.24\u0026ndash;65.02)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.33\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLBW\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e76 (86.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e25 (86.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e110 (90.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.2 (0.21\u0026ndash;80.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.064 (0.000\u0026ndash;19.02)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.34\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAGA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7 (8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5 (17.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e10 (8.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSGA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e70 (79.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20 (69)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e98 (80.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.3 (0.23\u0026ndash;23.24)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.47\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.036 (0.001\u0026ndash;1.12)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.05\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLGA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e11 (12.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4 (13.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e14 (11.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.387 ( 0.042\u0026ndash;3.55)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.21 (0.293\u0026ndash;16.67)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.44\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"9\"\u003emultivariable multinomial logistic regression analysis.\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"9\"\u003e\u003csup\u003ea\u003c/sup\u003e Data presented as N (%).\u003csup\u003eb\u003c/sup\u003e Data presented as OR (95% CI).\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"9\"\u003e\n\u003cp\u003eAdjusted for gestational weight gain during trimester 2\u003csup\u003esd\u003c/sup\u003e and 3rd, maternal age, gravity, maternal fasting blood sugar, delivery mode and infant gender.\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eThe mean (SD) of the maternal age was 28.36 (5.60) years old. The increasing trend of pre-pregnancy BMI was observed along with the increasing of maternal age. Female gender showed a positive association with LBW in pre-pregnancy normal-weight mothers (p\u0026thinsp;=\u0026thinsp;0.04).\u003c/p\u003e"},{"header":"Discussion:","content":" \u003cp\u003eThe findings of present retrospective cohort study indicated an increased risk for LGA, LBW and macrosomia in overweight mothers and an increased risk of SGA in the mothers with GWG below IOM guidelines.\u003c/p\u003e \u003cp\u003eThe average of GWG was similar to the IOM recommendations in normal BMI mothers during, the 2nd and 3rd trimester of pregnancy, and was different with IOM guidelines in other groups of pre-gestational BMI during mid- or late-pregnancy.\u003c/p\u003e \u003cp\u003eDue to the little number of underweight mothers, it was not possible to make an association between GWG, pre-pregnancy BMI and birth weight status. In normal weight mothers, a high risk of SGA was significantly associated with inadequate GWG. In agreement with the previous studies, an increased risk of LGA[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], LBW[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], and macrosomia [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] was observed in overweight mothers with GWG outside guidelines, significantly.\u003c/p\u003e \u003cp\u003eThe prevalence of GWG above the IOM recommendations was more common, in comparison with the below one, which is in agreement with the results reported by Power et al.[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. In our study 46.4% had weight gain greater than IOM recommendation. Also, in recent systematic meta-analysis reported 47% GWG above guidelines [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eInadequate GWG was related to a high risk of SGA and LBW, consistent with a longitudinal cohort studies in China [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], Taiwan[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], and higher pre-gestational BMI increased risk for LGA and macrosomia were reported in overweight/obese mothers [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], which are in agreement with the findings of the present study.\u003c/p\u003e \u003cp\u003ein our study higher pre-BMI was associated with higher risk of adverse birth weight. In agreement, lima et al. [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], showed an increasing trend for the birth weight across higher pre-pregnancy BMI.\u003c/p\u003e \u003cp\u003eMoreover, the prevalence of macrosomia (6.2%) was higher in Ahvaz than the mean of Iran (5.2%) [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] and lower than a pervious retrospective hospital- based (2007\u0026ndash;2011) study conducted in Razi Hospital, Ahvaz city was reported 9% [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eLikewise, increasing pre-pregnancy BMI was associated with the risk of higher fasting blood glucose between 24\u0026ndash;28 weeks of pregnancy. In addition, higher risk of GDM was associated with higher rate of macrosomia. Consistent with our findings, a study among 256 pregnant women in the United Arabia Emirate reported that pre-pregnancy BMI\u0026thinsp;\u0026ge;\u0026thinsp;25\u0026nbsp;kg/m2 were at higher risk of having GDM [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. In agreement with our findings, a meta-analysis of 33 observational studies indicated that risk of GDM is positively associated with pre-pregnancy BMI [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. however, the result of a study on Asian indicated that obese Thai women were not at increased risk for gestational diabetes mellitus was in contrast with result of present study [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].The possible reason of this difference is due to the WHO\u0026rsquo;s recommended BMI for Asians was used to define obesity.\u003c/p\u003e \u003cp\u003eIn addition, our study and another studies [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e] showed that gestational hyperglycemia had a positive association with macrosomia.\u003c/p\u003e \u003cp\u003eThe possible mechanisms of the high risk of adverse birth weight in high weight mothers could be due to the stimulating of insulin production in overweight mothers, therefore, lipogenesis and fat deposition would be increased in their offspring, so it can alter the growth of the fetus [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn the present study, we attempted for having large possible sample size from different health care centers to cover all ethnic groups together including Fars, Lure, Arab, and Bakhtiari. However, the exact number of different ethnic groups is not included in maternal records. So, we had limitation to explore ethnic differences in pre-pregnancy BMI, prevalence of GWG below or outside IOM guidelines and pregnancy outcomes.\u003c/p\u003e \u003cp\u003eIn addition, pairs of mother and child document since 2010 to 2018 were taken into account and it could be highly reflect the current situation. pre-pregnancy weight was recorded from antenatal records, and it may be measured by health member or self-reported leading to the risk of recall bias, which is in line with other studies [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. However, they were valid to be used in epidemiologic study [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Moreover, in the current study the 2009 IOM guideline was applied for GWG based on pre-pregnancy BMI. Furthermore, the recent meta-analysis [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] included 23 studies, explored ethnic differences based on IOM guidelines and regional guidelines in maternal pre-pregnancy BMI and GWG on pregnancy outcome across the USA, Western Europe and East Asia. However, there was data restriction from Middle East. In fact, the IOM approaches are primarily based on USA-dwelling, showed limited data on ethnic differences in associations between GWG and pregnancy outcomes. Then, led to heterogeneity and diminished the chance of comparisons across regions. Asia is the most inhabitant of the world\u0026rsquo;s population. In 2004 WHO consultation group [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e] reported, Asians may have higher odds of disease at a BMI cut-off (lower than 25\u0026nbsp;kg/m2). Likewise, Asians are likely to have a higher percent of adipose tissue, especially visceral adiposity, at lower BMI cut-off points than that stated by the WHO as standard cut-off points [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. In particular, finding of recent study showed that Iranians are at higher risks of morbidity related to metabolic factors at a lower BMI cut-off with an estimated 38.8% of the population having metabolic syndrome [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Importantly, the significant difference in Asian countries is based on ethnic and cultural subgroups, degrees of urbanization, social and economic conditions, and nutrition transitions [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e].Therefore, establishing a new guideline and GWG recommendation for Asian populations is necessary for optimal risk reduction during pregnancy [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn the present study the information related to socio-demographic and lifestyle characteristics (alcohol consumption and smoking) were not accurate due to their social beliefs.\u003c/p\u003e \u003cp\u003eAccording to the literature, this is the first study in public health care centers in South-west of Iran that present the association between GWG and pre-pregnancy BMI with adverse pregnancy outcome.\u003c/p\u003e \u003cp\u003eThus, screening for overweight and obesity is an important preventive approach. It seems that along with all gestational monitoring and nutrition counseling, more educational programs in the health care centers are vital, due to the presence of multiple ethnic groups in Ahvaz city with different cultural habits.\u003c/p\u003e "},{"header":"Conclusion:","content":" \u003cp\u003eThe important results of this study were the higher prevalence of maternal overweight, obesity, and excessive GWG. The most adverse birth weight was observed in overweight mothers with inappropriate GWG. Accordingly, the expanded programs of the healthy lifestyle education are required for the women in childbearing age (before and during pregnancy) to improve the pregnancy outcomes.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eBody mass index; BMI, gestational weight gain;GWG, gestational diabetes mellitus;GDM, ,large for gestational age; LGA, small for gestational age;SGA, appropriate size for gestational age;AGA, low birth weight;LBW, type 2 diabetes mellitus;T2DM, fasting blood sugar;FBS, IOM;institute of medicine, standard deviations;SD, analysis of covariance;ANCOVA, adjusted odds ratios;aOR, International Association of Diabetes and Pregnancy Study Groups;IADPSG\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eEthics approval and consent to participate:\u003c/h2\u003e\n\u003cp\u003eThis study is retrospective cohort which has been approved with ethical number (IR.AJUMS.REC. 1396.80) by Research Deputy of Ahvaz Jundishapur University of Medical Sciences and Social Determinants of Health Research Center.\u003c/p\u003e\n\u003ch2\u003eConsent for publication:\u003c/h2\u003e\n\u003cp\u003ethe present retrospective study has been approved by Ethic committee of Jundishapur University of medical sciences.\u003c/p\u003e\n\u003ch2\u003eAvailability of data and materials:\u003c/h2\u003e\n\u003cp\u003eThe data that support the findings of this study are available on request from the corresponding author.\u003c/p\u003e\n\u003ch2\u003eCompeting interests :\u003c/h2\u003e\n\u003cp\u003eAll authors report no conflicts of interests and have no relevant disclosures.\u003c/p\u003e\n\u003ch2\u003eFunding:\u003c/h2\u003e\n\u003cp\u003eThis research was supported by the Research Deputy of Ahvaz Jundishapur University of Medical Sciences and Social Determinants of Health Research Center to provide the funding of this research project (IR.AJUMS.REC. 1396.80).\u003c/p\u003e\n\u003ch2\u003eAuthor Contributions:\u003c/h2\u003e\n\u003cp\u003eF Borazjani designed the study question, supervised data collection, data analysis,assisted in writing the manuscript ,M Azhdari cooperate in data collection and assisted in writing the manuscript ; P Shahri cooperate in data collection and conducted the literature review; K.A. Angali designed the study and all statistical modelling and interpretation of data; M Cheraghi supervise data collection and assisted in research design; S Salmanzadeh managed data collection and conducted the literature review. All authors in concept and design of study, revising it critically for important intellectual content and final approval of manuscript.\u003c/p\u003e\n\u003ch2\u003eAcknowledgments:\u003c/h2\u003e\n\u003cp\u003eWe highly appreciate the Research Deputy of Ahvaz Jundishapur University of Medical Sciences and Social Determinants of Health Research Center to approve this research project (IR.AJUMS.REC. 1396.80).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eXiao L, Ding G, Vinturache \u003ca href=\"#_edn1\" name=\"_ednref1\"\u003e[i]\u003c/a\u003eA, et al. Associations of maternal pre-pregnancy body mass index and gestational weight gain with birth outcomes in Shanghai, China. 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Rev\u0026nbsp;Saude\u0026nbsp;Publica. 2018;52:46.\u003c/li\u003e\n\u003cli\u003eMaroufizadeh S, Almasi-Hashiani A, Esmaeilzadeh A, etal. Prevalence of Macrosomia in Iran: A Systematic Review and Meta-Analysis. Int J Pediatr. 2017;5(9):5617-29.\u003c/li\u003e\n\u003cli\u003eHashim M, Radwan H, Hasan H, et al. Gestational weight gain and gestational diabetes among Emirati and Arab women in the United Arab Emirates: results from the MISC cohort. BMC Pregnancy and Childbirth. 2019;19(1):463.\u003c/li\u003e\n\u003cli\u003eNajafi F, Hasani J, Izadi N, et al. The effect of prepregnancy body mass index on the risk of gestational diabetes mellitus: A systematic review and dose-response meta-analysis. Obes Rev. 2019;20(3):472-86.\u003c/li\u003e\n\u003cli\u003eKongubol A, Phupong V. Prepregnancy obesity and the risk of gestational diabetes mellitus. BMC pregnancy and childbirth. 2011;11(1):59.\u003c/li\u003e\n\u003cli\u003eTabrizi R, Asemi Z, Lankarani KB, et al. Gestational diabetes mellitus in association with macrosomia in Iran: a meta-analysis. J\u0026nbsp;Diabetes\u0026nbsp;Metab Disord. 2019:1-10.\u003c/li\u003e\n\u003cli\u003eZhang Y, Chen Z, Cao Z, et al. Associations of maternal glycemia and prepregnancy BMI with early childhood growth: a prospective cohort study. Ann N Y Acad Sci. 2019.\u003c/li\u003e\n\u003cli\u003eMuhlhausler BS, Vithayathil MA. Impact of maternal obesity on offspring adipose tissue: lessons for the clinic. ExpertRev Endocrinol Metab. 2014;9(6):615-27.\u003c/li\u003e\n\u003cli\u003eFonseca Mde J, Faerstein E, Chor D, etal. [Validity of self-reported weight and height and the body mass index within the \"Pro-saude\" study]. Rev Saude Publica. 2004;38(3):392-8.\u003c/li\u003e\n\u003cli\u003eGoldstein RF, Abell SK, Ranasinha S, et al. Gestational weight gain across continents and ethnicity: systematic review and meta-analysis of maternal and infant outcomes in more than one million women. BMC Med. 2018;16(1):153.\u003c/li\u003e\n\u003cli\u003eAppropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet . 2004;363(9403):157-63.\u003c/li\u003e\n\u003cli\u003eZeng Q, He Y, Dong S, et al. Optimal cut-off values of BMI, waist circumference and waist: height ratio for defining obesity in Chinese adults. Br J Nutr. 2014;112(10):1735-44.\u003c/li\u003e\n\u003cli\u003eBabai MA, Arasteh P, Hadibarhaghtalab M, et al. Defining a BMI cut-off point for the Iranian population: the Shiraz Heart Study. PloS one. 2016;11(8).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Hyperglycemias; Mother, Pre-pregnancy body mass index, Pregnancy Outcomes, Pregnancy Weight Gain","lastPublishedDoi":"10.21203/rs.3.rs-117813/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-117813/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Maternal body mass index and maternal gestational weight gain can have positive effects on birth and maternal outcomes. We aimed to identify the effect of pre-pregnancy weight and gestational weight gain on birth outcomes.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e Data of this retrospective cohort study were extracted using the 1457 out of 1800 pair health records belonged to the pregnant mother and infant at Ahvaz health care centers, from 2010 to 2018.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eResult:\u003c/strong\u003e The 3.18-fold increased risk for large for gestational age in overweight mothers, and a 2.9 fold increased risk for small for gestational age in those mothers with gestational weight gain below the guidelines. An increased risk of large for gestational age, low birth weight, and macrosomia were observed in overweight mothers with gestational weight gain out of the guidelines.\u0026nbsp;The increased association was found between the maternal pre-body mass index and fasting blood sugar (p = 0.0001). Hence, hyperglycemia is related to a 3.58-fold incidence of macrosomia. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e Therefore, conducting more\u0026nbsp;educational programs of lifestyle intervention with respect to reproductive health care is required for all women in childbearing age (before and during pregnancy), with the purpose of reducing the adverse pregnancy outcome.\u0026nbsp;\u003c/p\u003e","manuscriptTitle":"The Association between Pre-Pregnancy BMI, Gestational Weight Gain and Pregnancy Outcomes: A Retrospective Cohort Study in Ahvaz, Iran","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2020-12-04 16:06:11","doi":"10.21203/rs.3.rs-117813/v1","editorialEvents":[{"type":"communityComments","content":2}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"16be2ee1-72e9-4f90-b11c-2276304bd1a2","owner":[],"postedDate":"December 4th, 2020","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":1329310,"name":"Health Economics \u0026 Outcomes Research"},{"id":1329311,"name":"Nutrition \u0026 Dietetics"}],"tags":[],"updatedAt":"2021-03-19T13:18:44+00:00","versionOfRecord":[],"versionCreatedAt":"2020-12-04 16:06:11","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-117813","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-117813","identity":"rs-117813","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}