Literature DB >> 31342872

Effect of maternal weight gain according to the Institute of Medicine recommendations on pregnancy outcomes in a Chinese population.

Ping Guan1, Fei Tang1, Guoqiang Sun1, Wei Ren1.   

Abstract

Entities:  

Keywords:  Pregnancy; adverse outcome; birth weight; body mass index; complications; hypertensive disorder; macrosomia; weight gain

Mesh:

Year:  2019        PMID: 31342872      PMCID: PMC6753580          DOI: 10.1177/0300060519861463

Source DB:  PubMed          Journal:  J Int Med Res        ISSN: 0300-0605            Impact factor:   1.671


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Background

A peculiar phenomenon that two separate individuals (mother and fetus) have a mutually interactive dependency concerning their respective weight has been reported and intensively investigated.[1] Many researchers have concluded that appropriate pre-pregnancy body mass index (BMI) and weight gain during pregnancy are important for pregnant women and their offspring.[2-4] Increased pre-pregnancy maternal insulin resistance and accompanying hyperinsulinemia, inflammation, and oxidative stress appear to account for early placental and fetal dysfunction.[5] Unfortunately, accurate mechanisms of adverse perinatal outcomes affected by pre-pregnancy BMI and weight gain are unclear. Notably, the BMI is increasing in developed countries, as well as in some developing countries, and is increasingly becoming a worldwide health problem.[6,7] Some researchers have suggested that the incidence of overweight/obesity in pregnant women is as high as 30%. Approximately 40% of women gain excessive weight during pregnancy in Western countries.[8] However, gestational weight gain (GWG) is also increasing globally.[9,10] Maternal pre-pregnancy weight and GWG are major contributors to pregnancy and fetal health.[11] Excessive and insufficient maternal pre-pregnancy weight or GWG have a profound effect on pregnancy outcomes, such as macrosomia, cesarean delivery, gestational diabetes (GDM), small for gestational age (SGA), and large for gestational age (LGA).[12,13] Therefore, how to predict and effectively control the pre-pregnancy BMI and GWG have important clinical significance and social value, and they are the focus of maternal and child health work. The Institute of Medicine (IOM) updated the GWG guidelines in 2009 to effectively manage maternal weight and weight gain.[9] Although the undated guidelines verified the relationships between perinatal outcomes and maternal weight, these results were based on a lower general population BMI with limited ethnic diversity.[14] Notably, Asian women often have a lower BMI and smaller GWG than do European and American women.[6,7,15] Chinese women may be the leanest population. However, the prevalence of overweight and obesity in China is quickly increasing with its opening-up policy for promoting cultural exchange and economic development.[15,16] An increasing amount of women are enjoying the Westernized diet and lifestyle.[16,17] The prevalence of obesity increased from 3.1% to 6.1% from 1992 to 2002 in China.[18] However, there is still no official recommendation of GWG for Chinese pregnant women, and recent data on maternal pre-pregnancy BMI and GWG are rare.[19] Therefore, in the present study, we collected current data of maternal weight to analyze the effects of maternal weight on the incidence of pregnancy outcomes in Wuhan, China.

Material and methods

Study population

In this study, we retrospectively analyzed medical records in the Department of Obstetrics, Maternal and Child Health Hospital of Hubei Province, Wuhan, China. Eligibility criteria included the following: singleton pregnancy, primipara, older than 18 years old, spontaneous conception, no pre-existing diabetes mellitus or HIV infection, and no illicit drug use. From 1 January 2016 to 31 March 2016, 1593 women met the eligibility criteria. The research protocol for this study was approved by the Medical Ethics Committee of the Maternal and Child Health Hospital of Hubei Province. We only retrospectively extracted data on the patients’ weight and other basic information. We did not affect treatment decisions and the patients were not adversely affected. Therefore, we did not obtain written consent from each patient.

Data collection and evaluation

All useful information was retracted from the clinical records. Women included in this study were categorized by the recently developed Chinese BMI standard as follows: underweight (BMI <18.5 kg/m2), normal weight (BMI ≥18.5 kg/m2 and <24.0 kg/m2), overweight (BMI ≥24 kg/m2 and <28.0 kg/m2), obese (BMI ≥28.0 kg/m2). Maternal GWG was recorded as the weight gain from pre-pregnancy to the time just before delivery. Three categories of inadequate, adequate, and excessive GWG were defined according to the updated IOM guidelines.[20] Details of these categories are shown in Table 1. Because there were only 18 women with obesity, we integrated overweight and obese into one group (BMI ≥24.0 kg/m2).
Table 1.

Definitions of the pre-pregnancy BMI and GWG groups.

GroupsPre-pregnancy BMI (kg/m²)
GWG groups
Inadequate (kg)Adequate (kg)Excessive (kg)
Underweight<18.5<12.512.5–18.0>18.0
Normal weight18.5–23.9<11.511.5–16.0>16.0
Overweight24.0–27.9<7.07.0–11.5>11.5
Obese≥28.0<5.05.0–9.0>9.0

BMI: body mass index; GWG: gestational weight gain.

Definitions of the pre-pregnancy BMI and GWG groups. BMI: body mass index; GWG: gestational weight gain.

Assessment of outcome

The primary outcome of this study was to assess the factors that affect pre-pregnancy BMI and GWG, and their effects on maternal and neonatal outcomes. A prenatal examination was defined as when pregnant women visited the hospital regularly for a maternity examination. The pregnancy outcomes included low birth weight ([LBW] <2500 g), macrosomia (≥4000 g), SGA, LGA, the characteristic of amniotic fluid, hypertensive disorders in pregnancy (HDP), preterm birth, GDM, and cesarean section. SGA and LGA were defined as those newborns whose birth weight was <10th percentile and >90th percentile for gestational age, respectively. SGA and LGA were determined by the Chinese criterion.[21]

Statistical analysis

Descriptive characteristics of variables are expressed as means and frequencies. Categorical variables were analyzed using the chi-square test. Logistic regression models were used to assess the risk of adverse pregnancy outcomes by calculating odds ratios (ORs) and 95% confidence intervals (CIs). Statistical analyses were carried out using SPSS software 19.0 (IBM, Armonk, NY, USA). Statistical significance was considered as P < 0.05 or if the 95% CI of OR did not include 1.

Results

Baseline characteristics of the study population

The sociodemographic characteristics of women who were included in this study are shown in Table 2. The mean pre-pregnancy BMI of 1593 pregnant women was 20.3 ± 2.5 kg/m2. There were 405 (25.4%) underweight women, 1054 (66.2%) normal weight women, and 134 (8.4%) women with overweight/obesity. The mean age of the women was 27.88 ± 3.41 years (range: 18–42 years), and the majority of pregnant women (74.6%) were aged between 25 and 34 years.
Table 2.

Maternal and fetal characteristics by pre-pregnancy BMI and GWG categories.

VariablesNumber (n = 1593)
Pre-pregnancy BMI categories (%)

GWG categories (%)
Underweight (n = 405, 25.4%)Normal weightOverweight/obeseP valueInadequateadequateExcessiveP value
(n = 1054, 66.2%)(n = 134, 8.4%)(n = 171, 10.7%)(n = 565, 35.5%)(n = 857, 53.8%)
Gestational age (weeks)37.97 ± 1.2838.0 ± 1.2637.99 ± 1.2737.68 ± 1.320.02137.42 ± 1.5037.98 ± 1.2738.08 ± 1.20<0.001
Age (years)27.88 ± 3.4126.83 ± 3.2228.12 ± 3.3829.17 ± 3.42<0.00127.78 ± 4.0927.75 ± 3.2827.98 ± 3.340.435
Age groups (years)
 ≤25348 (21.8)141 (34.8)194 (18.4)13 (9.7)<0.00149 (28.7)125 (22.1)174 (20.3)0.116
 25–29811 (50.9)197 (48.6)546 (51.8)68 (50.7)73 (42.6)289 (51.2)449 (52.4)
 ≥30434 (27.3)67 (16.5)314 (29.8)53 (39.6)49 (28.7)151 (26.7)234 (27.3)
Advanced maternal age (≥35 years)
 No1536 (96.4)396 (97.8)1016 (96.4)124 (92.5%)0.018159 (93.0)549 (97.2)828 (96.6)0.032
 Yes57 (3.6)9 (2.2)38 (3.6)10 (7.5%)12 (7.0)16 (2.8)29 (3.4)
Education (years)[#]
 >131223 (76.8)292 (72.1)831 (78.8)100 (74.6)0.02110 (64.3)443 (78.4)670 (78.2)<0.001
 ≤12370 (23.2)113 (27.9)223 (21.2)34 (25.4)61 (35.7)122 (21.6)187 (21.8)
Prenatal examination
 No770 (48.3)187(46.2)520 (49.3)63 (47.0)0.529118 (69.0)267 (47.3)385 (44.7)<0.001
 Yes823 (51.7)218 (53.8)534 (50.7)71 (53.0)53 (31.0)298 (52.7)472 (55.3)
Preterm birth (gestational weeks)
 <3760 (3.8)16 (4.0)37 (3.5)7 (5.2)0.60219 (11.1)22 (3.9)18 (1.8)<0.001
 ≥371533 (96.2)389 (96.0)1017 (96.5)127 (94.8)152 (88.9)543 (96.1)838 (98.2)
Birth weight (g)
 <250070 (4.4)23 (5.7)40 (3.8)7 (5.2)0.01825 (14.6)22 (3.9)23 (2.7)<0.001
 2500–40001426 (89.5)370 (91.4)937 (88.9)119 (88.8)141 (82.5)528 (93.4)757 (88.3)
 ≥400097 (6.1)12 (3.0)77 (7.3)8 (6.0)5 (2.9)15 (2.7)77 (9.0)
Fetal growth
 SGA77 (4.8)27 (6.7)45 (4.3)5 (3.7)0.00125 (14.6)26 (4.6)26 (3.0)<0.001
 AGA1285 (80.7)342 (84.4)840 (79.7)103 (76.9)133 (77.8)485 (85.8)667 (77.9)
 LGA231 (14.5)36 (8.9)169 (16.0)26 (11.3)13 (7.6)54 (9.6)164 (19.1)
GDM
 No1431 (89.8)380 (93.8)945 (89.7)106 (79.1)<0.001143 (83.6)500 (88.5)788 (92.0)0.002
 Yes162 (10.2)25 (6.2)109 (10.3)28 (20.9)28 (16.4)65 (11.5)69 (8.0)
Hypertensive disorders in pregnancy
 No1517 (95.2)391 (96.5)999 (94.8)127 (94.8)0.356164 (95.9)550 (97.3)803 (93.7)0.006
 Yes76 (4.8)14 (3.5)55 (5.2)7 (5.2)7 (4.1)15 (2.7)54 (6.3)
Characteristic of amniotic fluid
 Clear1276 (80.1)333 (82.2)830 (78.7)113 (84.3)0.145137 (80.0)459 (81.2)680 (79.3)0.682
 Abnormal317 (19.9)72 (17.8)224 (21.3)21 (15.7)34 (20.0)106 (18.8)177 (20.7)
Cesarean section
 No782 (49.1)234 (57.8)500 (47.4)48 (35.8)<0.00196 (56.1)301 (53.3)385 (44.9)0.001
 Yes811 (50.9)171 (42.2)554 (52.6)86 (64.2)75 (43.9)264 (46.7)472 (55.1)

Values are mean±standard deviation or number (%).

P values in bold indicate that the difference was significant.

After 12 years of study, women graduated from high school in China.

BMI: body mass index; GWG: gestational weight gain; SGA: small for gestational age; AGA: average for gestational age; LGA: large for gestational age; GDM: gestational diabetes mellitus; HDP: hypertensive disorders in pregnancy.

Maternal and fetal characteristics by pre-pregnancy BMI and GWG categories. Values are mean±standard deviation or number (%). P values in bold indicate that the difference was significant. After 12 years of study, women graduated from high school in China. BMI: body mass index; GWG: gestational weight gain; SGA: small for gestational age; AGA: average for gestational age; LGA: large for gestational age; GDM: gestational diabetes mellitus; HDP: hypertensive disorders in pregnancy. Differences in maternal age and gestational age among pre-pregnancy BMI groups were significant (all P < 0.05). The proportion of mothers who were older than 30 years in the overweight group was significantly higher than that in the other groups (P < 0.001). Women with a high education were more likely to have a normal pregnancy weight than those in the other groups (P = 0.02). Differences in birth weight and fetal growth among the pre-pregnancy BMI groups were significant (all P < 0.05). Additionally, the incidence of GDM among the pre-pregnancy BMI groups was significant, with the highest incidence in the overweight/obese group (P < 0.001). As expected, the rate of cesarean section among the pre-pregnancy BMI groups was significant, with the highest rate in the overweight/obese group (P < 0.001). Maternal pre-pregnancy BMI had no significant effects on prenatal examinations, preterm birth, HDP, and amniotic fluid. The mean GWG was 17.2 ± 4.9 kg. Women with an advanced maternal age were more likely to gain inadequate weight (P = 0.032). Gestational age at delivery was significantly different among the GWG groups in which maternal GWG was significantly associated with a shorter gestational age (P < 0.001). The proportion of pregnant women with a low education in the inadequate GWG group was higher than that in those in the adequate and excessive GWG groups (P < 0.01). The incidence of preterm birth (<37 weeks) significantly decreased from the inadequate GWG group to the excessive GWG group (P < 0.05). Furthermore, differences in LBW, SGA, GDM, and HDP were significantly different among the groups (all P < 0.05).

Effects of pre-pregnancy BMI and GWG on pregnancy outcomes

Variables with significant differences among the pre-pregnancy BMI and GWG groups were included in further analysis. The relationships between abnormal pre-pregnancy BMI and adverse pregnancy outcomes are shown in Table 3. The risks of macrosomia (OR = 0.387, 95% CI: 0.209–0.720), LGA (OR = 0.511, 95% CI: 0.349–0.747), GDM (OR = 0.57, 95% CI: 0.363–0.895), and cesarean section (OR = 0.66, 95% CI: 0.523–0.831) were significantly lower in the underweight group compared with the normal weight group (all P < 0.05). The risks of GDM (OR = 2.229, 95% CI: 1.444–3.632) and cesarean section (OR = 1.617, 95% CI: 1.113–2.349) were significantly higher in the overweight/obese group compared with the normal weight group (both P < 0.05).
Table 3.

Effects of pre-pregnancy BMI and GWG on maternal and fetal outcomes (n = 1593).


Pre-pregnancy BMI categories[#]

GWG categories*
Outcomes
Underweight

Overweight/obese

Inadequate

Excessive
OR (95% CI)P valueOR (95% CI)P valueOR (95% CI)P valueOR (95% CI)P value
LBW1.526 (0.902–2.583)0.1151.397 (0.613–3.185)0.4264.428 (2.410–8.134) <0.001 0.681 (0.376–1.233)0.205
Macrosomia0.387 (0.209–0.720) 0.003 0.806 (0.380–1.708)0.5731.102 (0.395–3.078)0.8523.62 (2.060–6.361) <0.001
SGA0.624 (0.382–1.021)0.061.151 (0.449–2.951)0.073.543 (1.986–6.320) <0.001 0.649 (0.373–1.129)0.126
LGA0.511 (0.349–0.747) 0.001 1.261 (0.797–1.994)0.3220.779 (0.414–1.464)0.4372.239 (1.613–3.109) <0.001
Preterm birth0.885 (0.486–1.608)0.6880.660 (0.288–1.512)0.3263.085 (1.627–5.849) 0.001 0.560 (0.300–1.044)0.068
HDP0.65 (0.358–1.183)0.1591.001 (0.446–2.246)0.9981.565 (0.627–3.903)0.3372.466 (1.377–4.414) 0.002
GDM0.57 (0.363–0.895) 0.015 2.229 (1.444–3.632) <0.001 1.506 (0.932–2.435)0.0950.674 (0.471–0.962) 0.03
Cesarean section0.66 (0.523–0.831) <0.001 1.617 (1.113–2.349) 0.012 0.891 (0.631–1.257)0.511.398 (1.129–1.730) 0.002

The normal weight group was the reference group.

The adequate GWG group was the reference group.

P values in bold indicate that the difference was significant.

BMI: body mass index; GWG: gestational weight gain; OR: odds ratio; CI: confidence interval; LBW: low birth weight; SGA: small for gestational age; LGA: large for gestational age; GDM: gestational diabetes mellitus; HDP: hypertensive disorders in pregnancy.

Effects of pre-pregnancy BMI and GWG on maternal and fetal outcomes (n = 1593). The normal weight group was the reference group. The adequate GWG group was the reference group. P values in bold indicate that the difference was significant. BMI: body mass index; GWG: gestational weight gain; OR: odds ratio; CI: confidence interval; LBW: low birth weight; SGA: small for gestational age; LGA: large for gestational age; GDM: gestational diabetes mellitus; HDP: hypertensive disorders in pregnancy. The risks of LBW (OR = 4.428, 95% CI: 2.410–8.134) and SGA (OR = 3.543, 95% CI: 1.986–6.320) were significantly higher in the inadequate GWG group compared with the adequate GWG group (both P < 0.05). The risk of preterm birth was also significantly higher in the inadequate GWG group compared with the adequate GWG group (OR = 3.085, 95% CI: 1.627–5.849, P = 0.001). GWG over the guidelines was related to a higher risk of macrosomia (OR = 3.620, 95% CI: 2.060–6.361), LGA (OR = 2.239, 95% CI: 1.613–3.109), cesarean section (OR = 1.398, 95% CI: 1.129–1.730), and HDP (OR = 2.466, 95% CI: 1.377–4.414) than GWG within the guidelines (all P < 0.05). However, the risk of GDM (OR = 0.674, 95% CI: 0.471–0.962) was significantly lower in the excessive GWG group compared with the adequate GWG group (P = 0.03).

Distribution and heterogeneity of the study population (GWG according to pre-pregnancy BMI category)

In this study, more than 50% of women had excessive weight during the pregnancy period. The percentages of women with adequate GWG and inadequate GWG were 35.5% and 10.7%, respectively. The rate of women who gained optimal weight significantly varied by pre-pregnancy BMI, with the highest percentage in the underweight group and the lowest in the overweight/obese group (P = 0.001). Most women in the normal weight and overweight/obese groups had excessive GWG (Table 4).
Table 4.

Gestational weight gain according to pre-pregnancy body mass index category.

VariableTotal (n = 1593), n (%)Underweight (n = 405), n (%)Normal (n = 1054), n (%)Overweight/obese (n = 134), n (%)P value
Inadequate171 (10.7)43 (10.6)121 (11.5)7 (5.2)0.001
Adequate565 (35.5)191 (47.2)353 (33.5)21 (15.7)<0.001
Excessive857 (53.8)171 (42.2)580 (55.0)106 (79.1)<0.001
Gestational weight gain according to pre-pregnancy body mass index category. The distribution of the study population is shown in Table 5. A synergistic reaction between pre-pregnancy BMI and GWG was observed. Women in the underweight group who had inadequate GWG showed the highest incidence of LBW, SGA, and preterm birth among the groups (all P < 0.01). The incidence of LBW, SGA, and preterm birth in the whole study population was 4.4%, 4.8%, and 3.8%, respectively. Women in the overweight group who gained excessive GWG showed the highest incidence of LGA and cesarean section among the groups. The incidence of LGA and cesarean section in the whole study population was 14.5% and 50.9%, respectively. However, even for women who had adequate GWG, the prevalence of adverse pregnancy outcomes was significantly different among the pre-pregnancy BMI groups, including LBW, macrosomia, LGA, SGA, GDM, and preterm birth (all P < 0.001). Therefore, the study population showed heterogeneity either by pre-pregnancy BMI or GWG categories. Additionally, an antagonistic effect was observed. The incidence of preterm birth was 11.1% in women with inadequate GWG in the underweight group, and was lower with adequate (4.7%) and excessive (1.2%) GWG in the underweight group. This trend was similar for macrosomia, LGA, SGA, and preterm birth. Therefore, weight gain during pregnancy can balance the risk of abnormal pre-pregnancy BMI.
Table 5.

Distribution of the study population.

Outcomes
Underweight (n = 405), n (%)

Normal weight (n = 1054), n (%)

Overweight (n = 134), n (%)
Inadequate (n = 43 )Adequate (n = 191)Excessive (n = 171) P Inadequate (n = 121)Adequate (n = 353)Excessive (n = 580) P Inadequate (n = 7)Adequate (n = 21)Excessive (n = 106) P
LBW
 No35 (81.4)180 (94.2)167 (97.7)<0.001104 (86.0)342 (96.9)568 (97.9)<0.0017 (100)21 (100) 99 (93.4) 0.377
 Yes8 (18.6)11 (5.8)4 (2.3)17 (14.0)11 (3.1)12 (2.1)0 (0)0 (0) 7 (6.6)
Macrosomia
 No43 (100)187 (97.9)163 (100)0.158116 (95.9)342 (96.9)519 (89.5)<0.0017 (100)21 (100)98 (92.5)0.325
 Yes0 (0)4 (2.1)0 (0)5 (4.1)11 (3.1)61 (10.5)0 (0)0 (0)8 (7.5)
SGA
 No34 (79.1)179 (93.7)165 (96.5)0.001105 (86.8)340 (96.3)564 (97.2)<0.0017 (100)20 (95.2)102 (96.2)0.846
 Yes9 (20.9)12 (6.3)6 (3.5)16 (13.2)13 (3.7)16 (2.8)0 (0)1 (4.8)4 (3.8)
LGA
 No43 (100)175 (91.6)151 (88.3)0.51109 (90.1)317 (89.8)459 (79.1)<0.0016 (85.7)19 (90.5)83 (78.3)0.41
 Yes0 (0)16 (8.4)20 (11.7)12 (9.9)36 (10.2)121 (20.9)1 (14.3)2 (9.5)23 (21.7)
Preterm birth
 No38 (88.3)182 (95.3)169 (98.8)0.005107 (88.4)340 (96.3)570 (98.3)<0.0017 (100)21 (100)99 (93.4)0.377
 Yes5 (11.6)9 (4.7)2 (1.2)14 (11.6)13 (3.7)10 (1.7)0 (0)0 (0)7 (6.6)
HDP
 No41 (95.3)188 (98.4)162 (94.7)0.143116 (95.9)341 (96.6)542 (93.4)0.0947 (100)21 (100)99 (93.4)0.377
 Yes2 (4.7)3 (1.6)39 (5.3)5 (4.1)12 (3.4)38 (6.6)0 (0)0 (0)7 (6.6)
GDM
 No41 (95.3)179 (93.7)160 (93.6)0.90797 (80.2)310 (87.8)538 (92.8)<0.0015 (71.4)11 (52.4) 90 (84.9) 0.003
 Yes2 (4.7)12 (6.3)11 (6.4)24 (19.8)43 (12.2)42 (7.2)2 (28.6)10 (47.6) 16 (15.1)
Cesarean section
 No28 (65.1)114 (59.7)92 (53.8)0.3164 (52.9)176 (49.9)260 (44.8)0.1454 (57.1)11 (52.4)33 (31.1)0.086
 Yes15 (34.9)77 (40.3)79 (46.2)57 (47.1)177 (50.1)320 (55.2)3 (42.9)10 (47.6)73 (68.9)
Prenatal examination
 No25 (58.1)95 (49.7)67 (39.2)0.03387 (71.9)163 (46.2)270 (46.6)<0.0016 (85.7)9 (42.9)48 (45.3)0.106
 Yes18 (41.9)96 (50.3)104 (60.8)34 (28.1)190 (53.8)310 (53.4)1 (14.3)12 (57.1)58 (54.7)
Education (years)
 No16 (37.2)50 (26.2)47 (27.5)0.34242 (34.7)63 (17.8)118 (20.3)<0.0013 (42.9)9 (42.9)22 (20.8)0.057
 Yes27 (62.8)141 (73.8)124 (72.5)79 (65.3)290 (82.2)462 (79.7)4 (57.1)12 (57.1)84 (79.2)
Advanced maternal age (≥35 years)
 <3541 (95.3)187 (97.9)168 (98.2)0.508111 (91.7)343 (97.2)562 (96.9)0.0147 (100)19 (90.5)98 (92.5)0.707
 ≥352 (4.7)4 (2.1)3 (1.8)10 (8.3)10 (2.8)18 (3.1)0 (0)2 (9.5)8 (7.5)

P values in bold indicate that the difference was significant.

LBW: low birth weight; SGA: small for gestational age; LGA: large for gestational age; GDM: gestational diabetes mellitus; HDP: hypertensive disorders in pregnancy.

Distribution of the study population. P values in bold indicate that the difference was significant. LBW: low birth weight; SGA: small for gestational age; LGA: large for gestational age; GDM: gestational diabetes mellitus; HDP: hypertensive disorders in pregnancy.

Combined effects of pre-pregnancy BMI and GWG on adverse pregnancy outcomes

In underweight pregnant women, inadequate GWG was significantly associated with LBW (OR = 3.740, 95% CI: 1.404–9.966), SGA (OR = 3.949, 95% CI: 1.544–10.096), and the characteristic of amniotic fluid (OR = 2.326, 95% CI: 1.089–4.966) (all P < 0.05), whereas excessive GWG had no significant association with adverse outcomes compared with optimal GWG (Table 6). These results are slightly different from those in Table 3, which showed that excessive GWG was significantly associated with adverse outcomes.
Table 6.

ORs for the associations between GWG and adverse pregnancy outcomes in the normal weight and underweight groups.

Outcomes
Underweight group (n = 405)

Normal weight group (n = 1054)

Inadequate

Excessive

Inadequate

Excessive
OR (95% CI) P OR (95% CI) P OR (95% CI) P OR (95% CI) P
LBW3.740 (1.404–9.966) 0.008 0.392 (0.122–1.255)0.3925.082 (2.308–11.193) <0.001 0.657 (0.287–1.505)0.32
MacrosomiaUnavailable2.294 (0.678–7.760)0.1821.34 (0.456–3.938)0.5943.654 (1.896–7.045) <0.001
SGA3.949 (1.544–10.096) 0.004 0.542 (0.199–1.478)0.2323.985 (1.857–8.555) <0.001 0.742 (0.353–1.561)0.432
LGAUnavailable1.449 (0.725–2.895)0.2940.969 (0.487–1.930)0.932.231 (1.558–3.458) <0.001
Preterm birth2.661 (0.844–8.384)0.0950.239 (0.051–1.123)0.073.422 (1.56–7.507) 0.002 0.459 (0.199–1.058)0.068
Characteristic of amniotic fluid2.326 (1.089–4.966) 0.029 1.096 (0.627–1.915)0.7470.76 (0.441–1.309)0.3221.119 (0.810–1.545)0.495
HDP3.057 (0.495–18.882)0.2293.481 (0.927–13.077)0.0651.225 (0.423–3.551)0.7091.992 (1.027–3.866) 0.042
GDM0.728 (0.157–3.377)0.6851.026 (0.440–2.389)0.9531.784 (1.030–3.089) 0.039 0.563 (0.360–0.881) 0.012
Cesarean section0.793 (0.398–1.582)0.5111.271 (0.838–1.929)0.2590.886 (0.586–1.339)0.5651.224 (0.939–1.595)0.135

P values in bold indicate that the difference was significant.

OR: odds ratio; CI: confidence interval; SGA: small for gestational age; LGA: large for gestational age; GDM: gestational diabetes mellitus; HDP: hypertensive disorders in pregnancy.

ORs for the associations between GWG and adverse pregnancy outcomes in the normal weight and underweight groups. P values in bold indicate that the difference was significant. OR: odds ratio; CI: confidence interval; SGA: small for gestational age; LGA: large for gestational age; GDM: gestational diabetes mellitus; HDP: hypertensive disorders in pregnancy. The risks of LBW (OR = 5.082, 95% CI: 2.308–11.193), SGA (OR = 3.985, 95% CI: 1.857–8.555), and GDM (OR = 1.784, 95% CI: 1.030–3.089) were significantly higher in women with normal weight and inadequate GWG compared with those with normal weight and adequate GWG (all P < 0.05). Furthermore, the risk of preterm birth (OR = 3.422, 95 CI%: 1.560–7.507) was significantly higher in women with normal weight and inadequate GWG compared with those with normal weight and adequate GWG (P = 0.002). The risks of macrosomia (OR = 3.654, 95% CI: 1.896–7.045), LGA (OR = 2.231, 95% CI: 1.558–3.458), and HDP (OR = 1.992, 95 CI%: 1.027–3.866) were significantly higher in women with normal weight and excessive GWG compared with women with normal weight and adequate GWG (all P < 0.05). However, the risk of GDM (OR = 0.563, 95% CI: 0.360–0.881) was significantly decreased with normal weight and excessive GWG (P = 0.012). Because some subgroups in the overweight/obese group had no adverse pregnancy outcomes, we were unable to evaluate the combined effects in overweight women. For overweight women, excessive GWG was significantly negatively associated with GDM (OR = 0.196; 95% CI: 0.071–0.536).

Discussion

The IOM recommendations regarding GWG were developed in 1990. To be more effective, the updated IOM guidelines in 2009 incorporated information on BMI and recommended GWG for different women.[20] Although many studies have evaluated the clinical applicability of IOM recommendations during the previous 10 years, the relationship between GWG that is consistent with the IOM guidelines and pregnancy outcomes is unclear.[22] Many of the findings vary by countries and ethnic diversity.[22,23] This study was performed to examine the relationships among pre-pregnancy BMI, GWG, and pregnancy outcomes for Chinese pregnant women. IOM weight gain recommendations have been criticized by Asian scholars (Chinese, Koreans, and Japanese) as being ill-adapted for Asian women.[14,22] However, we wanted to test these recommendations in our population. Notably, we performed this testing with an “adapted Asian IOM recommendation” because our definitions of overweight and obesity are different from the original definition (i.e., obesity: ≥28 kg/m2, overweight: 24.0–27.9 kg/m2). Furthermore, the mean BMI of our population was 20.3 kg/m2. Therefore, for 20 kg/m2, the IOM recommendation is a weight gain of 11.5–16 kg. In our population, the mean GWG was 17.8 kg. Therefore, there appears to be a mismatch at low BMIs. However, we were able to analyze our results using this tool. In the current study, 66.2% of Chinese women had a normal weight, and only 25.4% of women were underweight before pregnancy. Because the criterion of overweight and obesity for Chinese women is lower than World Health Organization recommendations, pregnant women with obesity in China are relatively uncommon. Our results are optimistic because a normal BMI is the primary factor in achieving good pregnancy outcomes. However, the rate of adequate GWG is too low (35.5%). Excessive GWG was observed in most normal weight women (55.0%) and in those who were overweight/obese (79.1%). These findings indicate that weight management during the perinatal period is required in China. Neonatal birth weight is not only an important indicator of nutrition during pregnancy, but also reflects the intrauterine environment exposed by the fetus.[24] This predictive factor includes four primary variables: LBW, macrosomia, LGA, and SGA.[25] This study showed that mothers with a low BMI appeared to have a lower risk of delivering a neonate who was LGA and had macrosomia than mothers with a normal BMI. Additionally, mothers who had an inadequate weight had a higher risk of delivering a neonate with LBW and SGA, even if the pre-pregnancy BMI was normal. A study from Japan that included 1336 women also showed that pregnant women who were underweight before pregnancy were independently associated with delivery of LBW infants.[26] A systematic review showed that pregnant patients who obtain inadequate weight compared with the IOM recommendations have a higher odds of SGA and lower odds of LGA than GWG within the guidelines.[13] Macri and her colleagues highlighted pre-pregnant BMI and excessive GWG as independent risk factors for LGA and macrosomia.[27] However, their study was performed in women with gestational diabetes, not in the general population, as in the present study. When combined with an inadequate pre-pregnant BMI, excessive GWG is a synergistic risk factor for poor outcome. Many studies have shown that when obesity occurs, an optimal GWG can guarantee a better pregnancy outcome.[10] Apart from neonatal birth weight, other adverse pregnancy outcomes are commonly evaluated, including HDP, GDM, preterm birth, and cesarean section.[12,28] Several epidemiological studies have shown that BMI, GWG, anemia, and lower education are convertible risk factors for these adverse outcomes.[29] In this study, the prevalence of HDP, preterm birth, and cesarean section was 4.8%, 3.8%, and 50.9%, respectively. Additionally, mothers in the overweight/obese group or excessive GWG group were more likely to have HDP and cesarean section. Mothers in the inadequate GWG group had a higher risk of having preterm birth. The mechanism for this finding could be that inadequate weight gain induces secretion of epinephrine and cortisol, which then results in an elevation in corticosterone-releasing-hormone and prostaglandin production. These are all key factors for premature delivery. Furthermore, impaired immunity and potential uterine infection may result from inadequate maternal nutrition.[30,31] Another common complication during pregnancy is GDM, which is diagnosed in >8.3% of pregnancies worldwide. The rate of GDM in this study was 10.2%. Increasing BMI appears to account for an increased prevalence of GDM in the USA.[32] Interestingly, we found that mothers with a high pre-pregnancy BMI were more likely to have GDM, and the risk of GDM was significantly lower in the excessive GWG group compared with the adequate GWG group. Additionally, the effect of GWG on GDM was stronger than that of pre-pregnancy BMI. Previous studies on the role of GWG in GDM are contradictory.[33,34] These contradictory results may be attributed to dietary regulation and exercise of pregnant women after being diagnosed with GDM.[35-37] In this study, many pregnant women gained more weight than that recommended by the IOM guidelines, especially for women who were overweight and obese. The effects of GWG on adverse pregnancy outcomes were stronger than those of pre-pregnancy BMI. We urgently need to improve management of GWG of pregnant women in China, especially to prevent excessive GWG. However, the combined effect of pre-pregnancy BMI and GWG on birth weight of newborns should also be considered. Guiding individualized GWG when the pregnancy weight is known would be helpful. We also identified some controllable risk factors of pre-pregnancy and GWG, such as conception age, education, and prenatal examinations. Conception age is a risk factor of abnormal GWG.[38,39] More women with a high education appeared to have a normal pregnancy weight than women with a low education. This finding could have resulted from better economic factors in women with a high education.[17] Although patients with advanced maternal age are notable, more attention should be paid to women older than 30 years or younger than 25 years in terms of weight control. The dietary schedule should be evidence-based and pluralistic.[31] In conclusion, this study shows that abnormal maternal weight and inappropriate GWG are related to an increased risk of adverse perinatal outcomes. Distinguishing pregnant women at risk of adverse pregnancy outcomes by using current BMI and GWG classifications is of clinical value. GWG should be the top priority in gestational weight management. Furthermore, more research should focus on the requirement for GWG standards suited to Chinese characteristics. There are specific Chinese birthweight curves for neonates.[21] Therefore, with knowledge of the 10th percentile (SGA) and the 90th percentile (LGA) of newborns, we could test the proposed “maternal-fetal-corpulence symbiosis”, which was recently proposed by Robillard et al.,[1] in the future.
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1.  [Chinese neonatal birth weight curve for different gestational age].

Authors:  Li Zhu; Rong Zhang; Shulian Zhang; Wenjing Shi; Weili Yan; Xiaoli Wang; Qin Lyu; Ling Liu; Qin Zhou; Quanfang Qiu; Xiaoying Li; Haiying He; Jimei Wang; Ruichun Li; Jiarong Lu; Zhaoqing Yin; Ping Su; Xinzhu Lin; Fang Guo; Hui Zhang; Shujun Li; Hua Xin; Yanqing Han; Hongyun Wang; Dongmei Chen; Zhankui Li; Huiqin Wang; Yinping Qiu; Huayan Liu; Jie Yang; Xiaoli Yang; Mingxia Li; Wenjing Li; Shuping Han; Bei Cao; Bin Yi; Yihui Zhang; Chao Chen
Journal:  Zhonghua Er Ke Za Zhi       Date:  2015-02

2.  Risk of adverse pregnancy outcomes by prepregnancy body mass index: a population-based study to inform prepregnancy weight loss counseling.

Authors:  Laura Schummers; Jennifer A Hutcheon; Lisa M Bodnar; Ellice Lieberman; Katherine P Himes
Journal:  Obstet Gynecol       Date:  2015-01       Impact factor: 7.661

Review 3.  Can we safely recommend gestational weight gain below the 2009 guidelines in obese women? A systematic review and meta-analysis.

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4.  [The prevalence of body overweight and obesity and its changes among Chinese people during 1992 to 2002].

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5.  Maternal gestational weight gain and offspring risk for childhood overweight or obesity.

Authors:  Sneha B Sridhar; Jeanne Darbinian; Samantha F Ehrlich; Margot A Markman; Erica P Gunderson; Assiamira Ferrara; Monique M Hedderson
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Journal:  Int J Obes (Lond)       Date:  2014-10-07       Impact factor: 5.095

7.  ATLANTIC-DIP: excessive gestational weight gain and pregnancy outcomes in women with gestational or pregestational diabetes mellitus.

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Journal:  J Clin Endocrinol Metab       Date:  2013-12-20       Impact factor: 5.958

8.  Maternal pre-pregnancy BMI and gestational weight gain, offspring DNA methylation and later offspring adiposity: findings from the Avon Longitudinal Study of Parents and Children.

Authors:  Gemma C Sharp; Debbie A Lawlor; Rebecca C Richmond; Abigail Fraser; Andrew Simpkin; Matthew Suderman; Hashem A Shihab; Oliver Lyttleton; Wendy McArdle; Susan M Ring; Tom R Gaunt; George Davey Smith; Caroline L Relton
Journal:  Int J Epidemiol       Date:  2015-04-08       Impact factor: 7.196

9.  Patterns of gestational weight gain related to fetal growth among women with overweight and obesity.

Authors:  Janet M Catov; Diane Abatemarco; Andrew Althouse; Esa M Davis; Carl Hubel
Journal:  Obesity (Silver Spring)       Date:  2015-04-10       Impact factor: 5.002

10.  Associations of pre-pregnancy body mass index and gestational weight gain with pregnancy outcome and postpartum weight retention: a prospective observational cohort study.

Authors:  Margaretha Haugen; Anne Lise Brantsæter; Anna Winkvist; Lauren Lissner; Jan Alexander; Bente Oftedal; Per Magnus; Helle Margrete Meltzer
Journal:  BMC Pregnancy Childbirth       Date:  2014-06-11       Impact factor: 3.007

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1.  Gestational weight gain and its effect on birth outcomes in sub-Saharan Africa: Systematic review and meta-analysis.

Authors:  Fekede Asefa; Allison Cummins; Yadeta Dessie; Andrew Hayen; Maralyn Foureur
Journal:  PLoS One       Date:  2020-04-23       Impact factor: 3.240

2.  The First-Trimester Gestational Weight Gain Associated With de novo Hypertensive Disorders During Pregnancy: Mediated by Mean Arterial Pressure.

Authors:  Zhichao Yuan; Hai-Jun Wang; Tao Su; Jie Yang; Junjun Chen; Yuanzhou Peng; Shuang Zhou; Heling Bao; Shusheng Luo; Hui Wang; Jue Liu; Na Han; Yuelong Ji
Journal:  Front Nutr       Date:  2022-04-13

3.  Antepartum sleep quality, mental status, and postpartum depressive symptoms: a mediation analysis.

Authors:  Yu Wang; Han Liu; Chen Zhang; Cheng Li; Jing-Jing Xu; Chen-Chi Duan; Lei Chen; Zhi-Wei Liu; Li Jin; Xian-Hua Lin; Chen-Jie Zhang; Han-Qiu Zhang; Jia-Le Yu; Tao Li; Cindy-Lee Dennis; Hong Li; Yan-Ting Wu
Journal:  BMC Psychiatry       Date:  2022-08-02       Impact factor: 4.144

4.  Maternal Dietary Patterns during Pregnancy and Their Association with Gestational Weight Gain and Nutrient Adequacy.

Authors:  Naomi Cano-Ibáñez; Juan Miguel Martínez-Galiano; Miguel Angel Luque-Fernández; Sandra Martín-Peláez; Aurora Bueno-Cavanillas; Miguel Delgado-Rodríguez
Journal:  Int J Environ Res Public Health       Date:  2020-10-28       Impact factor: 3.390

5.  Pre-pregnancy maternal BMI as predictor of neonatal birth weight.

Authors:  Rafia Gul; Samar Iqbal; Zahid Anwar; Saher Gul Ahdi; Syed Hamza Ali; Saima Pirzada
Journal:  PLoS One       Date:  2020-10-28       Impact factor: 3.240

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