Gestational weight gain in Chinese women -- results from a retrospective cohort in Changsha, China

Gestational weight gain in Chinese women -- results from a retrospective cohort in Changsha, China Background: The generalizability of the gestational weight gain (GWG) ranges recommended by the Institute of Medicine (IOM) to Chinese women is disputed. Methods: In 2016, 16,780 pregnant women who gave birth to live singletons in Changsha, China, were enrolled. First, subjects with optimal pregnancy outcomes were identified for the GWG percentile distribution description and for comparison to the IOM recommendations. Second, all subjects with optimal GWG according to the IOM body mass index (BMI) cutoffs and those with optimal GWG according to the Asian BMI cutoffs were selected. Pregnancy outcomes were compared between those two groups. Results: A total of 13,717 births with optimal pregnancy outcomes were selected to describe the GWG distribution. The height and central position of the GWG distributions determined by the Asian BMI cutoffs differed from those determined by the IOM BMI cutoffs among the overweight and obese groups. The recommended IOM GWG ranges were narrower than and shifted to the left of the observed distributions. In both BMI classification schemes, however, the IOM-recommended ranges were within the middle 70% (Pc 15th–85th) and 50% (Pc 25th–75th) of the observed distribution. A total of 6438 (38.37%) and 6110 (36.41%) women gained optimal GWG, according to the IOM and Asian BMI classifications, respectively. Compared with those with optimal GWG according to IOM BMI cutoffs, women with optimal GWG according to the Asian BMI cutoffs had lower risks of both macrosomia (adjusted OR = 0.79, 95%CI: 0.67–0.94) and large-for-gestational age (adjusted OR = 0.86, 95%CI: 0.76, 0.98). However, no significantly different risks of preterm, low birthweight, small-for-gestational age, pregnancy-induced hypertension, or gestational diabetes were found between them. Conclusions: The IOM-recommended GWG ranges are within the middle 70% of the distributions in Chinese women, and pre-pregnancy weight status should be determined by the Asian BMI cut-off points for monitoring and making GWG recommendations to Chinese women. Keywords: Body mass index, Gestational weight gain, Chinese women, Pregnancy * Correspondence: 615871972@qq.com; junlei.xy3yy@hotmail.com Chunmei Mi and Jun Lei contributed equally to this work. Department of Obstetrics and Gynecology, The Third Xiangya Hospital of Central South University, 138 Tongzipo Road, Yuelu District, Changsha 410013, Hunan, Province, China Full list of author information is available at the end of the article © The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Huang et al. BMC Pregnancy and Childbirth (2018) 18:185 Page 2 of 9 Background those with the optimal GWG determined using the IOM A nutritious diet during pregnancy maintains maternal BMI cut-off points. energy requirements, provides a substrate for the devel- opment of new fetal tissues, and builds energy reserves Methods for postpartum lactation [1]. Therefore, the importance Study population of nutrition in pregnancy cannot be overemphasized. Our population-based retrospective cohort study was con- Previous studies have proved that excessive or inad- ducted in Changsha city in Hunan Province. Changsha is equate weight gain during pregnancy has negative impli- a city with 6 urban districts (Yuelu, Tianxin, Kaifu, Yuhua, cations on pregnancy outcomes, putting the health of Furong, and Wangcheng district), 1 county (Changsha both mother and infant at risk [2–4]. county) and 2 county-level cities (Ningxiang and Liuyang To avoid maternal and infant adverse outcomes, in city). In 2016, a total of 116,336 pregnant women gave 2009, the Institute of Medicine (IOM), USA, published birth in Changsha. All pregnant women aged 18 years or revised recommended gestational weight gain (GWG) older (18,843) who resided in Yuelu or Tianxin district [5] and the revisions was based on pre-pregnancy weight and had a live birth from Jan to Dec 2016 were enrolled status. Since the effect of weight gain during pregnancy when they came to local maternity care units to apply for on fetal growth has found to be varied by maternal pre-- birth certificates. The sponsors of the study had no role in pregnancy body mass index (BMI) [6, 7] In Jan 2018, the study design, data collection, data analysis, data interpret- national prenatal care guideline for Chinese women was ation, or writing the report. The study protocol was officially published, but it just duplicated the IOM recom- reviewed and approved by the Ethical and Confidentiality mendations for GWG monitoring among Chinese [8]. Committee of Central-South University and by both insti- Those recommendations, however, were made based on tutional review boards (IRB) from the Maternity and Child Western populations, and their generalizability to Chinese Care Hospital of Yuelu District and Tianxin District. All women is under dispute [9–13]. participants provided signed written consent. Women One of the reasons for the conflict may be that BMI who had multiple births and/or had infants with birth de- cut-off points used in previous studies are inconsistent: fects, or who had chronic hypertension, diabetes, renal Yang et al. [9] used IOM-recommended BMI categories disease or cardiovascular diseases before pregnancy, or and concluded that IOM GWG recommendations are suit- were lacking data on GWG were excluded, which yielded able for Chinese; Zhou et al. [10]and Wong et al.[11]used a final eligible analytical sample size of 16,780. the Asian BMI cut-off points and found that the IOM GWG recommendations are inappropriate. The weight gain recommendations of the IOM are based on Western Data collection and variable definition BMI cut-off points [5]. However, the Asian BMI cut-off All data used in the present study were extracted from two points for determining overweight and obesity in Asian sources: antenatal care booklets and hospital discharge ab- populations are different [13] because researchers found stracts (including both maternal obstetrical delivery re- that Asian populations have different associations between cords and newborn hospital records). In China, medical BMI and health risks than do Western populations [14, 15]. information on antenatal care is routinely recorded by cer- Under different BMI cut-off points related to different rec- tified doctors or nurses in an antenatal care booklet begin- ommended weight gain ranges [5], some Chinese women ning with the first prenatal visit. The booklet is kept by the would be classified in lower pre-pregnancy BMI categories individual during pregnancy and must be returned to the and assigned to larger target weight gain ranges when the local maternity care unit, along with the hospital discharge IOM BMI cut-off points were used instead of the Asian abstract, before applying for an official birth certificate at BMI cut-off points. The appropriateness of using the the hospital. General information on maternal demo- IOM GWG recommendations for Chinese women graphic characteristics, pre-pregnancy weight and obstetric should be examined by describing the distributions of history were reported by the interviewee themselves, which GWG by pre-pregnant weight status, as determined could be obtained from antenatal care booklets. Informa- using both Asia and IOM BMI cut-off points. tion on weight at delivery, maternal complications and We therefore conducted a retrospective pregnancy co- neonatal outcomes was extracted from discharge abstracts. hort study in Changsha, China, 1) to describe the GWG Pre-pregnancy BMI was calculated as maternal distributions by BMI group, as determined using the IOM pre-pregnancy weight in kilograms divided by squared and Asian BMI cut-off points, and compare those distri- height in meters. GWG was calculated by subtracting butions to the IOM GWG recommended ranges among pre-pregnancy weight from maternal weight at delivery in women with optimal birth outcomes and 2) to compare kilograms. The optimal GWG was defined as the weight the pregnancy outcomes among those with the optimal gain during pregnancy within the IOM recommended range GWG determined using the Asian BMI cut-off points to by pre-pregnancy BMI category. Pre-pregnancy weight Huang et al. BMC Pregnancy and Childbirth (2018) 18:185 Page 3 of 9 status was categorized using both the Asian and IOM 25th, 50th, 75th, 85th, and 95th) of GWG according to cut-off points (Table 1). both the Asian and IOM pre-pregnancy BMI cut-off Adverse pregnancy outcomes considered in this study in- points were compared. Observations regarding percentile cluded preterm (delivered at less than 37 weeks of gesta- trends were made on a descriptive basis, and statistical tion), low birthweight (LBW, birthweight < 2500 g), tests for trend were not reported. The middle 70% (Pc macrosomia (birthweight ≥4000 g), large-for-gestational 15th–85th) and 50% (Pc 25th–75th) of the observed age (LGA, birthweight >90th for gestational age and sex), GWG distribution was compared to the IOM ranges. small-for-gestational age (SGA, birthweight <10th percent- Second, to examine which BMI classification scheme ile for gestational age and sex), pregnancy-induced hyper- is more suitable for Chinese women, all subjects with an tension (PIH) and gestational diabetes mellitus (GDM). For optimal GWG determined by the IOM BMI cut-off infants born between 28 and 44 weeks of gestation, birth- points (n = 6438) and those with optimal GWG deter- weight reference percentiles for Chinese infants [16]were mined by the Asian BMI cut-off points (n = 6110) were used to define SGA and LGA. For infants born between 22 selected. Pregnancy outcomes were compared between and 27 weeks of gestation, a United States national refer- those two groups. The crude odds ratios (OR) and 95% ence was applied [17]. PIH included gestational hyperten- confidence intervals (CI) were calculated. Multivariate sion and preeclampsia which was defined as systolic BP logistic regression models were also adopted to calculate (SBP) ≥140 mmHg and/or diastolic BP (DBP) ≥90 mmHg, adjusted OR and 95%CI. Potential confounding variables occurring for the first time after 20 weeks of gestation, with included maternal age (< 25, 25–34, and ≥ 35 years, 25– or without proteinuria. Oral glucose tolerance test (OGTT) 34 as reference), parity (primiparous or multiparous), was routinely examined at 24–28 gestational weeks, and year of education (≤12 years or > 12 years) and smoking GDM was defined as diabetes that was first diagnosed dur- during pregnancy (yes or no). Subgroup analyses were ing pregnancy, with 3-h 100 g OGTT results exceeding conducted among subjects with a pre-pregnancy BMI in cut-offs for two or more values: fasting plasma glucose the 23–24.9 and 25–29.9 strata. Statistical significance ≥5.3 mmol/L, 1-h ≥ 10.0 mmol/ L, 2-h ≥ 8.6 mmol/ L and was assessed at the 0.05 level (two-tailed test). All ana- 3-h ≥ 7.8 mmol/ L). lyses were performed using the SAS software, version 9.2 (SAS Institute, Inc., Cary, NC). Statistical analysis Our analysis has two parts (the analytical scheme is Results shown in Fig. 1). First, to describe the GWG distribution A total of 16,780 qualified subjects were enrolled in our among Chinese women, subjects (n = 13,717) with an study. Of them, 603 (3.59%) mothers were diagnosed with optimal pregnancy outcome were identified. A subject PIH, and 176 (1.05%) were diagnosed with GDM; 1249 with an optimal outcome in our study was defined as a (7.44%) births were preterm, 1001 (5.97%) were low birth- pregnant woman without prenatal medical complica- weight, 1030 (6.14%) were macrosomia, 1389 (8.28%) were tions (such as GDM or PIH), giving live birth at term SGA and 1984 (11.82%) were LGA. (gestational age between 37 and 42 weeks), and with in- Based on IOM pre-pregnancy BMI cut-off points, there fant birth weight between 2500 and 3999 g. Among were 2651 (15.80%), 12,272 (73.13%), 1575 (9.39%) and 282 those with an optimal outcome, analysis of variance (1.68%) women defined as underweight, normal weight, (ANOVA) test was used to examine the central tendency overweight and obese, respectively, and 6438 (38.37%) and variability for GWG by different maternal character- women had an optimal GWG. According to Asian BMI istics, including maternal age, parity, year of education, cut-off points, there were 2651 (15.80%), 9897 (58.98%), smoking during pregnancy and pre-pregnancy BMI group. 2375 (14.15%) and 1857 (11.07%) women classified as The Student- Newman Keuls (SNK) test was adopted to underweight, normal weight, overweight and obese, respect- make multiple comparisons when group categories were ively, and 6110 (36.41%) women had an optimal GWG. greater than two. The percentile distributions (5th, 15th, Weight gain during pregnancy After excluding those with preterm, LBW, macrosomia, Table 1 IOM weight gain recommendations for pregnancy by PIH or GDM, 13,717 births with an optimal pregnancy out- pre-pregnancy weight status come were selected to describe the distribution of GWG. Weight IOM BMI Asian BMI IOM-recommended category category criteria category criteria weight gain Of them, the mean maternal age was 27.3 ± 4.44 years, the 2 2 mean infant birthweight was 3274.9 ± 780.24 g, the mean Underweight < 18.5 kg/m < 18.5 kg/m 12.5–18 kg 2 2 pre-pregnancy BMI was 21.3 ± 3.15 kg/m , and the mean Normal weight 18.5–24.9 kg/m 18.5–22.9 kg/m 11.5–16 kg GWG was 14.4 ± 5.39 kg. 2 2 Overweight 25.0–29.9 kg/m 23–24.9 kg/m 7–11.5 kg GWG was found to vary significantly by maternal age, 2 2 Obese ≥30 kg/m ≥25 kg/m 5–9kg parity, year of education, smoking during pregnancy, Huang et al. BMC Pregnancy and Childbirth (2018) 18:185 Page 4 of 9 Fig. 1 Analytical scheme of present study and both IOM and Asian pre-pregnancy BMI category compared to the GWG distributions observed for Chin- (Table 2). Mothers who were 25–34 years old, primipar- ese women. In the both BMI classification schemes, the ous, educated for less than 12 years, or smoked during IOM recommended ranges are within the middle 70 and pregnancy had a greater GWG than did the others. The 50% of the observed distributions. Among underweight relationship between GWG and pre-pregnancy BMI var- and normal weight women, the recommended IOM ied when different BMI classification schemes were used. GWG ranges fall near the middle of the distribution. Based on the Asian BMI classification scheme, the mean However, among overweight and obese women, the GWG decreased as pre-pregnancy BMI increased; the IOM recommended GWG ranges fall within the lower underweight group had the highest mean GWG, whereas half of the distribution (Fig. 2). the obese group had the lowest. However, when the IOM classification scheme was adopted, the relationship be- Adverse pregnancy outcomes and optimal GWG by tween GWG and pre-pregnancy BMI followed a U-shaped different BMI classification curve, and the overweight group had the lowest mean Compared with those with optimal GWG determined by GWG (Table 2). The GWG percentile distribution analysis IOM BMI cut-off points, women with optimal GWG de- showed the same results (Table 3). Compared with the termined by the Asian BMI cut-off points had lower IOM BMI classification schemes, the shape and width of risks of having macrosomia (crude OR = 0.79, 95%CI: the GWG distributions resulting from the Asian BMI clas- 0.67–0.94) and LGA infant (crude OR = 0.86, 95%CI: sification scheme were nearly identical for the under- 0.76, 0.97) (Table 4). After adjustments for maternal age, weight and normal weight groups, whereas curves for the education, parity and smoking status during pregnancy, overweight and obese groups differed in both height and the associations still significantly exist. No significantly the central position of the distribution (Table 3,Fig. 2). different risks of having preterm, LBW or SGA infants As shown in Table 3 and Fig. 2, the IOM recommen- or different risks of having PIH or GDM were found be- dations by pre-pregnancy weight status are very narrow tween women with an optimal GWG determined by Huang et al. BMC Pregnancy and Childbirth (2018) 18:185 Page 5 of 9 Table 2 Gestational weight gain by maternal characteristics among subjects with optimal pregnancy outcome in Changsha, Hunan, China, in 2016 Characteristics N (%) Gestational weight gain p Mean, kg SD Min/Max CV, % Overall subjects 13,717 (100%) 14.3 5.31 −4.5/ 48.5 37.00 Maternal age (years) ≤ 24 3669 (25.75) 13.3 5.74 −4.5/ 31.8 43.27 < 0.001 25–34 8724 (63.60) 14.8 5.11 −4.5/ 48.5 34.58 ≥ 35 1324 (9.65) 14.5 4.90 −3.0/ 34.0 33.87 Parity Primiparous 9549 (69.61) 14.9 4.93 −4.5/ 48.5 32.97 < 0.001 Multiparous 4168 (30.39) 12.9 5.85 −4.5/ 31.5 45.17 Education (years) ≤ 12 8701 (64.37) 15.3 4.60 −4.5/ 32.5 21.19 < 0.001 ≥ 13 5016 (36.57) 12.6 5.97 −4.5/ 48.5 47.29 Smoking during pregnancy Yes 1461 (10.65) 15.7 4.27 −3.5/ 29.0 27.21 < 0.001 No 12,256 (89.35) 14.2 5.40 −4.5/ 48.5 38.05 IOM pre-pregnancy BMI category Underweight 2261 (16.48) 15.8 4.36 −4.5/ 31.5 27.54 < 0.001 Normal weight 10,114 (73.73) 14.3 5.19 −4.5/ 40.0 36.20 Overweight 1149 (8.38) 11.8 6.54 −4.5/ 48.5 55.52 Obese 193 (1.41) 13.1 7.01 −4.0/ 29.5 53.66 Asian pre-pregnancy BMI category Underweight 2261 (16.48) 15.8 4.36 −4.5/ 31.5 27.54 < 0.001 Normal weight 8273 (60.31) 14.7 5.04 −4.0/ 40.0 34.29 Overweight 1841 (13.42) 12.7 5.56 −4.5/ 32.5 43.62 Obese 1342 (9.78) 12.0 6.62 −4.5/ 48.5 55.35 IOM BMI category: underweight (BMI < 18.5), normal weight (BMI 18.5–24.9), overweight (BMI 25–29.9), obese (BMI ≥ 30) Asian BMI category: underweight (BMI < 18.5), normal weight (BMI 18.5–22.9), overweight (BMI 23–24.9), obese (BMI ≥ 25) Optimal outcome was defined as woman who has no prenatal medical complications (such as GDM or PIH), giving live birth at a gestational age between37 and 42 weeks, and infant birth weight between 2500 and 3999 g SNK test showed significant differences between each other, p < 0.05 different BMI cut-off points (Table 4). The subgroup ana- Weight gain during pregnancy among Chinese women lysis in the pre-pregnancy BMI 23.0–24.9 and 25–29.9 The GWG guidelines issued by the IOM are intended for strata showed the same results (Additional file 1: Table S1 use among American women but not for other women and Additional file 2: Table S2). who are substantially shorter or thinner than American women [5, 18–20]. Studies validating these guidelines among Chinese women are emerging and have reached Discussion inconclusive results [9–13]. Yang et al. [9], using the Our data found that the GWG distribution for Chinese IOM-recommended BMI cut-off points and combining women varied with the use of different BMI classifica- the overweight and obese groups, concluded that IOM tion schemes. The recommended IOM weight gain GWG recommendations are suitable for Chinese women. ranges are narrower than and shifted to the left of the Jiang et al.[12] also used IOM BMI cut-off points but con- actual distributions of GWG for Chinese women. We cluded, however, that the IOM-recommended GWG support the use of the Asian BMI categories to recom- range is too high for the Chinese population pregnant mend and monitor target weight gains for Chinese preg- with singletons. Zhou et al.[10] and Wong et al. [11], using nancies since lower risks of macrosomia and LGA were Asian BMI cut-off points, found that the IOM GWG rec- observed among those with an optimal GWG deter- ommendations are narrower than observed among Chinese mined by the Asian BMI cut-off points. women. Yang S [13] enrolled 76,854 women in Wuhan and Huang et al. BMC Pregnancy and Childbirth (2018) 18:185 Page 6 of 9 Table 3 Distribution of gestational weight gain by pre-pregnancy BMI among subjects with optimal pregnancy outcomes in Changsha, Hunan, China, in 2016 Subgroups Gestational weight gain (kg) by percentile IOM recommend 5th 15th 25th 50th 75th 85th 95th ranges (kg) Overall subjects (n = 12,564) 5.0 9.0 11.0 15.0 18.0 19.0 22.5 IOM pre-pregnancy BMI category Underweight (n = 2002) 9.0 11.5 13.0 16.0 18.5 20.0 23.0 12.5–18.0 Normal weight (n = 9308) 5.0 9.0 11.0 15.0 17.5 19.0 22.5 11.5–16.0 Overweight (n = 1084) 0.0 4.5 7.5 12.5 16.0 18.0 21.5 7.0–11.5 Obese (n = 170) 2.5 5.0 8.0 13.0 17.5 20.0 26.0 5.0–9.0 Asian pre-pregnancy BMI category Underweight (n = 2002) 9.0 11.5 13.0 16.0 18.5 20.0 23.0 12.5–18.0 Normal weight (n = 7564) 6.0 10.0 11.6 15.0 18.0 19.0 22.8 11.5–16.0 Overweight (n = 1744) 3.0 7.0 9.5 13.0 16.5 18.0 21.0 7.0–11.5 Obese (n = 1254) 0.4 5.0 7.5 12.5 16.0 18.0 22.5 5.0–9.0 : IOM pre-pregnancy BMI category: underweight (BMI < 18.5), normal weight (BMI 18.5–24.9), overweight (BMI 25–29.9), obese (BMI ≥ 30); : Asian pre-pregnancy BMI category: underweight (BMI < 18.5), normal weight (BMI 18.5–22.9), overweight (BMI 23–24.9), obese (BMI ≥ 25) Note: Shaded areas represent the 2009 IOM gestational weight gain ranges Fig. 2 Comparison of gestational weight gain distribution by pre-pregnancy weight status to Institute of Medicine recommended ranges among Chinese with optimal pregnancy outcome. Vertical reference lines represent the lower and upper limit of the IOM gestational weight gain ranges for each pre-pregnancy body mass index (BMI) category Huang et al. BMC Pregnancy and Childbirth (2018) 18:185 Page 7 of 9 Table 4 Comparison of adverse pregnancy outcomes between subjects with optimal GWG determined by the Asian BMI cut-offs and those with optimal GWG determined by the IOM BMI cut-offs Outcomes Subjects with optimal GWG according to Subjects with optimal GWG according to Crude OR Adjusted OR # # a Asian BMI category IOM BMI category (95%CI) (95%CI) N% N% Preterm Yes 434 7.10 450 6.99 1.02(0.89, 1.17) 1.03(0.90, 1.19) No 5676 5988 Reference Birth weight LBW 351 5.74 370 5.75 0.99(0.85, 1.15) 1.01(0.87, 1.17) Macrosomia 242 3.96 319 4.95 0.79(0.67, 094) 0.79(0.67, 0.94) Normal 5517 5749 Birth weight by gestational age SGA 520 8.51 530 8.23 1.02(0.90, 1.16) 1.02(0.90, 1.16) LGA 530 8.67 641 9.96 0.86(0.76, 0.97) 0.86(0.76, 0.98) Normal 5060 5267 PIH Yes 165 2.70 190 2.95 0.91(0.74, 1.13) 0.93(0.75, 1.15) No 5945 6248 GDM Yes 57 0.93 57 0.89 1.05(0.73, 1.52) 1.06(0.73, 1.53) No 6053 6381 Adjustment covariates are maternal age, parity, education and smoking during pregnancy Optimal gestational weight gain determined by pre-pregnancy BMI category is listed in Table 1 compared the ORs for abnormal birth weight and abnormal based on the IOM BMI classification, we found that the GWG determined using the IOM-recommended ranges relationship between GWG and pre-pregnancy BMI and abnormal GWG determined using the quartile ranges followed a U-shaped curve, which is inconsistent with observed from the study sample. He concluded that a GWG Jiang’s result [12]. The sample sizes of women with a above the IOM recommendations might not be helpful for pre-pregnancy BMI greater than 30 strata in our study Chinese women. Our data support his finding that the IOM (n = 170) and Jiang’s study (n = 58) are both small. The recommendations are narrower than the observed dis- reason for this inconsistency needs further research. tribution and that the upper limits of the distribution are too restrictive for Chinese women. However, the BMI classification for GWG monitoring among Chinese IOM-recommended GWG ranges are still within the women middle 70% of Chinese GWG distributions in both Before 2018, no universal BMI cut-off points were rec- BMI classification schemes. Elevating the upper limit ommended in China, and there were potential differ- of the GWG ranges may lead to long-term adverse ences in the care of different BMI groups at the outcomes, including postpartum weight retention and participating hospitals. The recommended weight gain future overweight and obesity in mother or offspring. ranges during pregnancy would vary when using differ- Neither the previous studies [9–13] nor our study include ent pre-pregnancy BMI cut-off points [5]. Our study data on postpartum outcomes. Therefore, whether Chin- found that women with an optimal GWG determined by ese women could gain more above the upper end of the the Asian BMI cut-off points had lower risks of macro- IOM guidelines needs further investigation. somia (OR = 0.78, 95%CI: 0.67, 0.94) and LGA (OR = Previous researchers found that the GWG distribution 0.86, 95%CI: 0.76, 0.98) than women with an optimal among specific populations would vary by different GWG determined by IOM BMI cut-off points suggests pre-pregnancy BMI classification schemes [21, 22]. Our that the Asian BMI cut-off points are more appropriate study found that this distribution variation also exists for Chinese women. In 2004, WHO experts declared among Chinese women. This is consistent with previous that Asian populations have different associations be- findings [10, 11] that, based on the Asian BMI classifica- tween BMI and health risks than Western populations tion, found that the mean GWG among Chinese women do [23]. Recommending GWG ranges based on the IOM decreased as pre-pregnancy BMI increased. However, BMI cut-off points would classify some Chinese women Huang et al. BMC Pregnancy and Childbirth (2018) 18:185 Page 8 of 9 in lower pre-pregnancy BMI categories and suggest Additional files 2: Table S2. Subgroup analysis of comparison of them gain more weight than necessary, which may put adverse pregnancy outcome between different gestational weight gain groups in the pre-pregnancy BMI 25–29.9 strata. (DOC 47 kb) them at an unnecessarily higher risk for macrosomia and LGA [3]. In our sample, 13.42% of the women were Abbreviations misclassified as normal weight, and 8.37% were misclassi- BMI: Body mass index; CI: Confidence intervals; DBP: Diastolic blood pressure; fied as overweight if the pre-pregnancy weight status was GDM: Gestational diabetes mellitus; GWG: Gestational weight gain; determined by the IOM BMI cut-off points instead of the IOM: Institute of Medicine; LGA: Large-for-gestational age; OR: Odds ratio; PIH: Pregnancy-induced hypertension; SBP: Systolic blood pressure; Asian cut-off points. In Jan 2018, the national GWG SGA: Small-for-gestational age guideline for Chinese women was published [8], and a universal recommendation with the IOM criteria may re- Acknowledgements We thank the health workers in the Maternity and Child Care Hospital in the sult in more misclassification and unnecessary weight gain Tianxin and Yuelu districts for their assistance in the fieldwork. The first author among pregnant Chinese women in the future. Xin Huang is a new investigator in Hunan Normal University. Ethical approval and consent to participate Strengths and limitations This study was reviewed by the Ethical and Confidentiality Committee of Strengths and limitations should be considered when Central-South University (Reference 14/SPH/1005 (approved on 20th Oct interpreting the study findings. Information on birth 2015)), both institution review boards (IRB) from the Maternity and Child Care Hospital (MCCH) of Yuelu District (IRB of MCCH of Yuelu District) weight and maternal complications was obtained from and Tianxin District (IRB of MCCH of Tianxin District). Written consent medical records, which minimized the potential misclassi- has been signed by all participants. All personal information has been fication of the outcomes. Information on gestational age recoded with initials or numbers which guaranteed no information of the participants can be identified in data analysis. and infant gender was available, which allowed us to not only control for gestational age when studying the rela- Funding tionship with LBW and macrosomia but also examine the This work was funded by Natural Science Foundation of Hunan Province association with SGA and LGA. Furthermore, the data (2017JJ3215), Open Project of Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical contained detailed information on maternal demographic University (GMU-2017-005) and Zhishan Plan Program of the Third Xiangya information, which allowed adjusting for several import- Hospital, Central South University ([2017]15). The funding had no role in ant potential confounding factors simultaneously. How- study design, data collection, data analysis, data interpretation, or writing the report. ever, the limitation of our study should be considered when interpreting the study findings. Although weight at Availability of data and materials delivery was measured at the hospital and extracted from The datasets used and analyzed during the current study are available from the corresponding author on reasonable request. discharge abstracts, pre-pregnancy weight was recorded based on self-reported information. There is a potential Authors’ contributions misclassification for pre-pregnancy BMI status. However, XH, HT, and JL designed the research; XH, TS, MC and CM conducted the cohort study; XH performed statistical analysis; XH, HT, TS, MC, CM and JL high correlations were found between self-report and wrote the first draft and all authors contributed to the final draft and measured pre-pregnancy weight [24]. Our data are not approved the manuscript. from a nationally representative sample, we only used a retrospective cohort study in Changsha, which is in the Competing interests The authors declare that they have no competing interests. central region of China, to eliminate the potential for se- lection bias. The generalizability of our findings and the Publisher’sNote appropriateness of the GWG guidelines by the Chinese Springer Nature remains neutral with regard to jurisdictional claims in Society of Gynecology and Obstetrics need further published maps and institutional affiliations. investigation. Author details Department of Preventive Medicine, School of Medicine, Hunan Normal Conclusion 2 University, Changsha, Hunan, China. Department of Epidemiology and The IOM-recommended GWG ranges are within the Health Statistics, Xiangya School of Public Health, Central South University, Changsha, Hunan, China. Maternity and Child Care Hospital of Yuelu District, middle 70% of the distributions in Chinese women. Changsha, Hunan, China. Maternity and Child Care Hospital of Tianxin Pre-pregnancy weight status should be determined using 5 District, Changsha, Hunan, China. Department of Obstetrics and Gynecology, the Asian BMI cut-off points when applying IOM GWG The Third Xiangya Hospital of Central South University, 138 Tongzipo Road, Yuelu District, Changsha 410013, Hunan, Province, China. recommendations to Chinese women. Received: 21 January 2018 Accepted: 17 May 2018 Additional files References Additional files 1: Table S1. Subgroup analysis of comparison of 1. Adair LS. Long-term consequences of nutrition and growth in early adverse pregnancy outcomes between different gestational weight gain childhood and possible preventive interventions. Nestlé Nutr Inst Workshop groups in the pre-pregnancy BMI 23.0–24.9 strata. (DOC 47 kb) Ser. 2014;78:111–20. Huang et al. 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Deurenberg-Yap M, Chew SK, Lin FP, van Staveren WA, Deurenberg P. Relationships between indices of obesity and its comorbidities among Chinese, Malays and Indians in Singapore. Int J Obes. 2001;25:1554–62. 16. Dai L, Deng C, Li Y, Zhu J, Mu Y, Deng Y, et al. Birth weight reference percentiles for Chinese. PLoS One. 2014;9(8):e104779. 17. Duryea EL, Hawkins JS, McIntire DD, Casey BM, Leveno KJ. A revised birth weight reference for the United States. Obstet Gynecol. 2014;124(1):16–22. 18. Khanolkar AR, Hanley GE, Koupil I, Janssen PA. 2009 IOM guidelines for gestational weight gain: how well do they predict outcomes across ethnic groups? Ethn Health. 2017;13:1–16. 19. Choi SK, Lee G, Kim YH, Park IY, Ko HS, Shin JC. Determining optimal gestational weight gain in the Korean population: a retrospective cohort study. Reprod Biol Endocrinol. 2017;15(1):67. 20. Nomura K, Kido M, Tanabe A, Nagashima K, Takenoshita S, Ando K. Investigation of optimal weight gain during pregnancy for Japanese women. Sci Rep. 2017;7(1):2569. 21. Olson CM, Strawderman MS, Hinton PS, Pearson TA. Gestational weight gain and postpartum behaviors associated with weight change from early pregnancy to 1 y postpartum. Int J Obes Relat Metab Disord. 2003;27:117e127. 22. Fernandez ID, Hoffmire CA, Olson CM. Gestational weight gain in adolescents: a comparison to the new Institute of Medicine recommendations. J Pediatr Adolesc Gynecol. 2011;24(6):368–75. 23. WHO Expert Consultation. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet. 2004;363(9403):157–63. 24. Headen I, Cohen AK, Mujahid M, Abrams B. The accuracy of self-reported pregnancy-related weight: a systematic review. Obes Rev. 2017;18(3):350–69. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png BMC Pregnancy and Childbirth Springer Journals

Gestational weight gain in Chinese women -- results from a retrospective cohort in Changsha, China

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Medicine & Public Health; Reproductive Medicine; Maternal and Child Health; Gynecology
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Abstract

Background: The generalizability of the gestational weight gain (GWG) ranges recommended by the Institute of Medicine (IOM) to Chinese women is disputed. Methods: In 2016, 16,780 pregnant women who gave birth to live singletons in Changsha, China, were enrolled. First, subjects with optimal pregnancy outcomes were identified for the GWG percentile distribution description and for comparison to the IOM recommendations. Second, all subjects with optimal GWG according to the IOM body mass index (BMI) cutoffs and those with optimal GWG according to the Asian BMI cutoffs were selected. Pregnancy outcomes were compared between those two groups. Results: A total of 13,717 births with optimal pregnancy outcomes were selected to describe the GWG distribution. The height and central position of the GWG distributions determined by the Asian BMI cutoffs differed from those determined by the IOM BMI cutoffs among the overweight and obese groups. The recommended IOM GWG ranges were narrower than and shifted to the left of the observed distributions. In both BMI classification schemes, however, the IOM-recommended ranges were within the middle 70% (Pc 15th–85th) and 50% (Pc 25th–75th) of the observed distribution. A total of 6438 (38.37%) and 6110 (36.41%) women gained optimal GWG, according to the IOM and Asian BMI classifications, respectively. Compared with those with optimal GWG according to IOM BMI cutoffs, women with optimal GWG according to the Asian BMI cutoffs had lower risks of both macrosomia (adjusted OR = 0.79, 95%CI: 0.67–0.94) and large-for-gestational age (adjusted OR = 0.86, 95%CI: 0.76, 0.98). However, no significantly different risks of preterm, low birthweight, small-for-gestational age, pregnancy-induced hypertension, or gestational diabetes were found between them. Conclusions: The IOM-recommended GWG ranges are within the middle 70% of the distributions in Chinese women, and pre-pregnancy weight status should be determined by the Asian BMI cut-off points for monitoring and making GWG recommendations to Chinese women. Keywords: Body mass index, Gestational weight gain, Chinese women, Pregnancy * Correspondence: 615871972@qq.com; junlei.xy3yy@hotmail.com Chunmei Mi and Jun Lei contributed equally to this work. Department of Obstetrics and Gynecology, The Third Xiangya Hospital of Central South University, 138 Tongzipo Road, Yuelu District, Changsha 410013, Hunan, Province, China Full list of author information is available at the end of the article © The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Huang et al. BMC Pregnancy and Childbirth (2018) 18:185 Page 2 of 9 Background those with the optimal GWG determined using the IOM A nutritious diet during pregnancy maintains maternal BMI cut-off points. energy requirements, provides a substrate for the devel- opment of new fetal tissues, and builds energy reserves Methods for postpartum lactation [1]. Therefore, the importance Study population of nutrition in pregnancy cannot be overemphasized. Our population-based retrospective cohort study was con- Previous studies have proved that excessive or inad- ducted in Changsha city in Hunan Province. Changsha is equate weight gain during pregnancy has negative impli- a city with 6 urban districts (Yuelu, Tianxin, Kaifu, Yuhua, cations on pregnancy outcomes, putting the health of Furong, and Wangcheng district), 1 county (Changsha both mother and infant at risk [2–4]. county) and 2 county-level cities (Ningxiang and Liuyang To avoid maternal and infant adverse outcomes, in city). In 2016, a total of 116,336 pregnant women gave 2009, the Institute of Medicine (IOM), USA, published birth in Changsha. All pregnant women aged 18 years or revised recommended gestational weight gain (GWG) older (18,843) who resided in Yuelu or Tianxin district [5] and the revisions was based on pre-pregnancy weight and had a live birth from Jan to Dec 2016 were enrolled status. Since the effect of weight gain during pregnancy when they came to local maternity care units to apply for on fetal growth has found to be varied by maternal pre-- birth certificates. The sponsors of the study had no role in pregnancy body mass index (BMI) [6, 7] In Jan 2018, the study design, data collection, data analysis, data interpret- national prenatal care guideline for Chinese women was ation, or writing the report. The study protocol was officially published, but it just duplicated the IOM recom- reviewed and approved by the Ethical and Confidentiality mendations for GWG monitoring among Chinese [8]. Committee of Central-South University and by both insti- Those recommendations, however, were made based on tutional review boards (IRB) from the Maternity and Child Western populations, and their generalizability to Chinese Care Hospital of Yuelu District and Tianxin District. All women is under dispute [9–13]. participants provided signed written consent. Women One of the reasons for the conflict may be that BMI who had multiple births and/or had infants with birth de- cut-off points used in previous studies are inconsistent: fects, or who had chronic hypertension, diabetes, renal Yang et al. [9] used IOM-recommended BMI categories disease or cardiovascular diseases before pregnancy, or and concluded that IOM GWG recommendations are suit- were lacking data on GWG were excluded, which yielded able for Chinese; Zhou et al. [10]and Wong et al.[11]used a final eligible analytical sample size of 16,780. the Asian BMI cut-off points and found that the IOM GWG recommendations are inappropriate. The weight gain recommendations of the IOM are based on Western Data collection and variable definition BMI cut-off points [5]. However, the Asian BMI cut-off All data used in the present study were extracted from two points for determining overweight and obesity in Asian sources: antenatal care booklets and hospital discharge ab- populations are different [13] because researchers found stracts (including both maternal obstetrical delivery re- that Asian populations have different associations between cords and newborn hospital records). In China, medical BMI and health risks than do Western populations [14, 15]. information on antenatal care is routinely recorded by cer- Under different BMI cut-off points related to different rec- tified doctors or nurses in an antenatal care booklet begin- ommended weight gain ranges [5], some Chinese women ning with the first prenatal visit. The booklet is kept by the would be classified in lower pre-pregnancy BMI categories individual during pregnancy and must be returned to the and assigned to larger target weight gain ranges when the local maternity care unit, along with the hospital discharge IOM BMI cut-off points were used instead of the Asian abstract, before applying for an official birth certificate at BMI cut-off points. The appropriateness of using the the hospital. General information on maternal demo- IOM GWG recommendations for Chinese women graphic characteristics, pre-pregnancy weight and obstetric should be examined by describing the distributions of history were reported by the interviewee themselves, which GWG by pre-pregnant weight status, as determined could be obtained from antenatal care booklets. Informa- using both Asia and IOM BMI cut-off points. tion on weight at delivery, maternal complications and We therefore conducted a retrospective pregnancy co- neonatal outcomes was extracted from discharge abstracts. hort study in Changsha, China, 1) to describe the GWG Pre-pregnancy BMI was calculated as maternal distributions by BMI group, as determined using the IOM pre-pregnancy weight in kilograms divided by squared and Asian BMI cut-off points, and compare those distri- height in meters. GWG was calculated by subtracting butions to the IOM GWG recommended ranges among pre-pregnancy weight from maternal weight at delivery in women with optimal birth outcomes and 2) to compare kilograms. The optimal GWG was defined as the weight the pregnancy outcomes among those with the optimal gain during pregnancy within the IOM recommended range GWG determined using the Asian BMI cut-off points to by pre-pregnancy BMI category. Pre-pregnancy weight Huang et al. BMC Pregnancy and Childbirth (2018) 18:185 Page 3 of 9 status was categorized using both the Asian and IOM 25th, 50th, 75th, 85th, and 95th) of GWG according to cut-off points (Table 1). both the Asian and IOM pre-pregnancy BMI cut-off Adverse pregnancy outcomes considered in this study in- points were compared. Observations regarding percentile cluded preterm (delivered at less than 37 weeks of gesta- trends were made on a descriptive basis, and statistical tion), low birthweight (LBW, birthweight < 2500 g), tests for trend were not reported. The middle 70% (Pc macrosomia (birthweight ≥4000 g), large-for-gestational 15th–85th) and 50% (Pc 25th–75th) of the observed age (LGA, birthweight >90th for gestational age and sex), GWG distribution was compared to the IOM ranges. small-for-gestational age (SGA, birthweight <10th percent- Second, to examine which BMI classification scheme ile for gestational age and sex), pregnancy-induced hyper- is more suitable for Chinese women, all subjects with an tension (PIH) and gestational diabetes mellitus (GDM). For optimal GWG determined by the IOM BMI cut-off infants born between 28 and 44 weeks of gestation, birth- points (n = 6438) and those with optimal GWG deter- weight reference percentiles for Chinese infants [16]were mined by the Asian BMI cut-off points (n = 6110) were used to define SGA and LGA. For infants born between 22 selected. Pregnancy outcomes were compared between and 27 weeks of gestation, a United States national refer- those two groups. The crude odds ratios (OR) and 95% ence was applied [17]. PIH included gestational hyperten- confidence intervals (CI) were calculated. Multivariate sion and preeclampsia which was defined as systolic BP logistic regression models were also adopted to calculate (SBP) ≥140 mmHg and/or diastolic BP (DBP) ≥90 mmHg, adjusted OR and 95%CI. Potential confounding variables occurring for the first time after 20 weeks of gestation, with included maternal age (< 25, 25–34, and ≥ 35 years, 25– or without proteinuria. Oral glucose tolerance test (OGTT) 34 as reference), parity (primiparous or multiparous), was routinely examined at 24–28 gestational weeks, and year of education (≤12 years or > 12 years) and smoking GDM was defined as diabetes that was first diagnosed dur- during pregnancy (yes or no). Subgroup analyses were ing pregnancy, with 3-h 100 g OGTT results exceeding conducted among subjects with a pre-pregnancy BMI in cut-offs for two or more values: fasting plasma glucose the 23–24.9 and 25–29.9 strata. Statistical significance ≥5.3 mmol/L, 1-h ≥ 10.0 mmol/ L, 2-h ≥ 8.6 mmol/ L and was assessed at the 0.05 level (two-tailed test). All ana- 3-h ≥ 7.8 mmol/ L). lyses were performed using the SAS software, version 9.2 (SAS Institute, Inc., Cary, NC). Statistical analysis Our analysis has two parts (the analytical scheme is Results shown in Fig. 1). First, to describe the GWG distribution A total of 16,780 qualified subjects were enrolled in our among Chinese women, subjects (n = 13,717) with an study. Of them, 603 (3.59%) mothers were diagnosed with optimal pregnancy outcome were identified. A subject PIH, and 176 (1.05%) were diagnosed with GDM; 1249 with an optimal outcome in our study was defined as a (7.44%) births were preterm, 1001 (5.97%) were low birth- pregnant woman without prenatal medical complica- weight, 1030 (6.14%) were macrosomia, 1389 (8.28%) were tions (such as GDM or PIH), giving live birth at term SGA and 1984 (11.82%) were LGA. (gestational age between 37 and 42 weeks), and with in- Based on IOM pre-pregnancy BMI cut-off points, there fant birth weight between 2500 and 3999 g. Among were 2651 (15.80%), 12,272 (73.13%), 1575 (9.39%) and 282 those with an optimal outcome, analysis of variance (1.68%) women defined as underweight, normal weight, (ANOVA) test was used to examine the central tendency overweight and obese, respectively, and 6438 (38.37%) and variability for GWG by different maternal character- women had an optimal GWG. According to Asian BMI istics, including maternal age, parity, year of education, cut-off points, there were 2651 (15.80%), 9897 (58.98%), smoking during pregnancy and pre-pregnancy BMI group. 2375 (14.15%) and 1857 (11.07%) women classified as The Student- Newman Keuls (SNK) test was adopted to underweight, normal weight, overweight and obese, respect- make multiple comparisons when group categories were ively, and 6110 (36.41%) women had an optimal GWG. greater than two. The percentile distributions (5th, 15th, Weight gain during pregnancy After excluding those with preterm, LBW, macrosomia, Table 1 IOM weight gain recommendations for pregnancy by PIH or GDM, 13,717 births with an optimal pregnancy out- pre-pregnancy weight status come were selected to describe the distribution of GWG. Weight IOM BMI Asian BMI IOM-recommended category category criteria category criteria weight gain Of them, the mean maternal age was 27.3 ± 4.44 years, the 2 2 mean infant birthweight was 3274.9 ± 780.24 g, the mean Underweight < 18.5 kg/m < 18.5 kg/m 12.5–18 kg 2 2 pre-pregnancy BMI was 21.3 ± 3.15 kg/m , and the mean Normal weight 18.5–24.9 kg/m 18.5–22.9 kg/m 11.5–16 kg GWG was 14.4 ± 5.39 kg. 2 2 Overweight 25.0–29.9 kg/m 23–24.9 kg/m 7–11.5 kg GWG was found to vary significantly by maternal age, 2 2 Obese ≥30 kg/m ≥25 kg/m 5–9kg parity, year of education, smoking during pregnancy, Huang et al. BMC Pregnancy and Childbirth (2018) 18:185 Page 4 of 9 Fig. 1 Analytical scheme of present study and both IOM and Asian pre-pregnancy BMI category compared to the GWG distributions observed for Chin- (Table 2). Mothers who were 25–34 years old, primipar- ese women. In the both BMI classification schemes, the ous, educated for less than 12 years, or smoked during IOM recommended ranges are within the middle 70 and pregnancy had a greater GWG than did the others. The 50% of the observed distributions. Among underweight relationship between GWG and pre-pregnancy BMI var- and normal weight women, the recommended IOM ied when different BMI classification schemes were used. GWG ranges fall near the middle of the distribution. Based on the Asian BMI classification scheme, the mean However, among overweight and obese women, the GWG decreased as pre-pregnancy BMI increased; the IOM recommended GWG ranges fall within the lower underweight group had the highest mean GWG, whereas half of the distribution (Fig. 2). the obese group had the lowest. However, when the IOM classification scheme was adopted, the relationship be- Adverse pregnancy outcomes and optimal GWG by tween GWG and pre-pregnancy BMI followed a U-shaped different BMI classification curve, and the overweight group had the lowest mean Compared with those with optimal GWG determined by GWG (Table 2). The GWG percentile distribution analysis IOM BMI cut-off points, women with optimal GWG de- showed the same results (Table 3). Compared with the termined by the Asian BMI cut-off points had lower IOM BMI classification schemes, the shape and width of risks of having macrosomia (crude OR = 0.79, 95%CI: the GWG distributions resulting from the Asian BMI clas- 0.67–0.94) and LGA infant (crude OR = 0.86, 95%CI: sification scheme were nearly identical for the under- 0.76, 0.97) (Table 4). After adjustments for maternal age, weight and normal weight groups, whereas curves for the education, parity and smoking status during pregnancy, overweight and obese groups differed in both height and the associations still significantly exist. No significantly the central position of the distribution (Table 3,Fig. 2). different risks of having preterm, LBW or SGA infants As shown in Table 3 and Fig. 2, the IOM recommen- or different risks of having PIH or GDM were found be- dations by pre-pregnancy weight status are very narrow tween women with an optimal GWG determined by Huang et al. BMC Pregnancy and Childbirth (2018) 18:185 Page 5 of 9 Table 2 Gestational weight gain by maternal characteristics among subjects with optimal pregnancy outcome in Changsha, Hunan, China, in 2016 Characteristics N (%) Gestational weight gain p Mean, kg SD Min/Max CV, % Overall subjects 13,717 (100%) 14.3 5.31 −4.5/ 48.5 37.00 Maternal age (years) ≤ 24 3669 (25.75) 13.3 5.74 −4.5/ 31.8 43.27 < 0.001 25–34 8724 (63.60) 14.8 5.11 −4.5/ 48.5 34.58 ≥ 35 1324 (9.65) 14.5 4.90 −3.0/ 34.0 33.87 Parity Primiparous 9549 (69.61) 14.9 4.93 −4.5/ 48.5 32.97 < 0.001 Multiparous 4168 (30.39) 12.9 5.85 −4.5/ 31.5 45.17 Education (years) ≤ 12 8701 (64.37) 15.3 4.60 −4.5/ 32.5 21.19 < 0.001 ≥ 13 5016 (36.57) 12.6 5.97 −4.5/ 48.5 47.29 Smoking during pregnancy Yes 1461 (10.65) 15.7 4.27 −3.5/ 29.0 27.21 < 0.001 No 12,256 (89.35) 14.2 5.40 −4.5/ 48.5 38.05 IOM pre-pregnancy BMI category Underweight 2261 (16.48) 15.8 4.36 −4.5/ 31.5 27.54 < 0.001 Normal weight 10,114 (73.73) 14.3 5.19 −4.5/ 40.0 36.20 Overweight 1149 (8.38) 11.8 6.54 −4.5/ 48.5 55.52 Obese 193 (1.41) 13.1 7.01 −4.0/ 29.5 53.66 Asian pre-pregnancy BMI category Underweight 2261 (16.48) 15.8 4.36 −4.5/ 31.5 27.54 < 0.001 Normal weight 8273 (60.31) 14.7 5.04 −4.0/ 40.0 34.29 Overweight 1841 (13.42) 12.7 5.56 −4.5/ 32.5 43.62 Obese 1342 (9.78) 12.0 6.62 −4.5/ 48.5 55.35 IOM BMI category: underweight (BMI < 18.5), normal weight (BMI 18.5–24.9), overweight (BMI 25–29.9), obese (BMI ≥ 30) Asian BMI category: underweight (BMI < 18.5), normal weight (BMI 18.5–22.9), overweight (BMI 23–24.9), obese (BMI ≥ 25) Optimal outcome was defined as woman who has no prenatal medical complications (such as GDM or PIH), giving live birth at a gestational age between37 and 42 weeks, and infant birth weight between 2500 and 3999 g SNK test showed significant differences between each other, p < 0.05 different BMI cut-off points (Table 4). The subgroup ana- Weight gain during pregnancy among Chinese women lysis in the pre-pregnancy BMI 23.0–24.9 and 25–29.9 The GWG guidelines issued by the IOM are intended for strata showed the same results (Additional file 1: Table S1 use among American women but not for other women and Additional file 2: Table S2). who are substantially shorter or thinner than American women [5, 18–20]. Studies validating these guidelines among Chinese women are emerging and have reached Discussion inconclusive results [9–13]. Yang et al. [9], using the Our data found that the GWG distribution for Chinese IOM-recommended BMI cut-off points and combining women varied with the use of different BMI classifica- the overweight and obese groups, concluded that IOM tion schemes. The recommended IOM weight gain GWG recommendations are suitable for Chinese women. ranges are narrower than and shifted to the left of the Jiang et al.[12] also used IOM BMI cut-off points but con- actual distributions of GWG for Chinese women. We cluded, however, that the IOM-recommended GWG support the use of the Asian BMI categories to recom- range is too high for the Chinese population pregnant mend and monitor target weight gains for Chinese preg- with singletons. Zhou et al.[10] and Wong et al. [11], using nancies since lower risks of macrosomia and LGA were Asian BMI cut-off points, found that the IOM GWG rec- observed among those with an optimal GWG deter- ommendations are narrower than observed among Chinese mined by the Asian BMI cut-off points. women. Yang S [13] enrolled 76,854 women in Wuhan and Huang et al. BMC Pregnancy and Childbirth (2018) 18:185 Page 6 of 9 Table 3 Distribution of gestational weight gain by pre-pregnancy BMI among subjects with optimal pregnancy outcomes in Changsha, Hunan, China, in 2016 Subgroups Gestational weight gain (kg) by percentile IOM recommend 5th 15th 25th 50th 75th 85th 95th ranges (kg) Overall subjects (n = 12,564) 5.0 9.0 11.0 15.0 18.0 19.0 22.5 IOM pre-pregnancy BMI category Underweight (n = 2002) 9.0 11.5 13.0 16.0 18.5 20.0 23.0 12.5–18.0 Normal weight (n = 9308) 5.0 9.0 11.0 15.0 17.5 19.0 22.5 11.5–16.0 Overweight (n = 1084) 0.0 4.5 7.5 12.5 16.0 18.0 21.5 7.0–11.5 Obese (n = 170) 2.5 5.0 8.0 13.0 17.5 20.0 26.0 5.0–9.0 Asian pre-pregnancy BMI category Underweight (n = 2002) 9.0 11.5 13.0 16.0 18.5 20.0 23.0 12.5–18.0 Normal weight (n = 7564) 6.0 10.0 11.6 15.0 18.0 19.0 22.8 11.5–16.0 Overweight (n = 1744) 3.0 7.0 9.5 13.0 16.5 18.0 21.0 7.0–11.5 Obese (n = 1254) 0.4 5.0 7.5 12.5 16.0 18.0 22.5 5.0–9.0 : IOM pre-pregnancy BMI category: underweight (BMI < 18.5), normal weight (BMI 18.5–24.9), overweight (BMI 25–29.9), obese (BMI ≥ 30); : Asian pre-pregnancy BMI category: underweight (BMI < 18.5), normal weight (BMI 18.5–22.9), overweight (BMI 23–24.9), obese (BMI ≥ 25) Note: Shaded areas represent the 2009 IOM gestational weight gain ranges Fig. 2 Comparison of gestational weight gain distribution by pre-pregnancy weight status to Institute of Medicine recommended ranges among Chinese with optimal pregnancy outcome. Vertical reference lines represent the lower and upper limit of the IOM gestational weight gain ranges for each pre-pregnancy body mass index (BMI) category Huang et al. BMC Pregnancy and Childbirth (2018) 18:185 Page 7 of 9 Table 4 Comparison of adverse pregnancy outcomes between subjects with optimal GWG determined by the Asian BMI cut-offs and those with optimal GWG determined by the IOM BMI cut-offs Outcomes Subjects with optimal GWG according to Subjects with optimal GWG according to Crude OR Adjusted OR # # a Asian BMI category IOM BMI category (95%CI) (95%CI) N% N% Preterm Yes 434 7.10 450 6.99 1.02(0.89, 1.17) 1.03(0.90, 1.19) No 5676 5988 Reference Birth weight LBW 351 5.74 370 5.75 0.99(0.85, 1.15) 1.01(0.87, 1.17) Macrosomia 242 3.96 319 4.95 0.79(0.67, 094) 0.79(0.67, 0.94) Normal 5517 5749 Birth weight by gestational age SGA 520 8.51 530 8.23 1.02(0.90, 1.16) 1.02(0.90, 1.16) LGA 530 8.67 641 9.96 0.86(0.76, 0.97) 0.86(0.76, 0.98) Normal 5060 5267 PIH Yes 165 2.70 190 2.95 0.91(0.74, 1.13) 0.93(0.75, 1.15) No 5945 6248 GDM Yes 57 0.93 57 0.89 1.05(0.73, 1.52) 1.06(0.73, 1.53) No 6053 6381 Adjustment covariates are maternal age, parity, education and smoking during pregnancy Optimal gestational weight gain determined by pre-pregnancy BMI category is listed in Table 1 compared the ORs for abnormal birth weight and abnormal based on the IOM BMI classification, we found that the GWG determined using the IOM-recommended ranges relationship between GWG and pre-pregnancy BMI and abnormal GWG determined using the quartile ranges followed a U-shaped curve, which is inconsistent with observed from the study sample. He concluded that a GWG Jiang’s result [12]. The sample sizes of women with a above the IOM recommendations might not be helpful for pre-pregnancy BMI greater than 30 strata in our study Chinese women. Our data support his finding that the IOM (n = 170) and Jiang’s study (n = 58) are both small. The recommendations are narrower than the observed dis- reason for this inconsistency needs further research. tribution and that the upper limits of the distribution are too restrictive for Chinese women. However, the BMI classification for GWG monitoring among Chinese IOM-recommended GWG ranges are still within the women middle 70% of Chinese GWG distributions in both Before 2018, no universal BMI cut-off points were rec- BMI classification schemes. Elevating the upper limit ommended in China, and there were potential differ- of the GWG ranges may lead to long-term adverse ences in the care of different BMI groups at the outcomes, including postpartum weight retention and participating hospitals. The recommended weight gain future overweight and obesity in mother or offspring. ranges during pregnancy would vary when using differ- Neither the previous studies [9–13] nor our study include ent pre-pregnancy BMI cut-off points [5]. Our study data on postpartum outcomes. Therefore, whether Chin- found that women with an optimal GWG determined by ese women could gain more above the upper end of the the Asian BMI cut-off points had lower risks of macro- IOM guidelines needs further investigation. somia (OR = 0.78, 95%CI: 0.67, 0.94) and LGA (OR = Previous researchers found that the GWG distribution 0.86, 95%CI: 0.76, 0.98) than women with an optimal among specific populations would vary by different GWG determined by IOM BMI cut-off points suggests pre-pregnancy BMI classification schemes [21, 22]. Our that the Asian BMI cut-off points are more appropriate study found that this distribution variation also exists for Chinese women. In 2004, WHO experts declared among Chinese women. This is consistent with previous that Asian populations have different associations be- findings [10, 11] that, based on the Asian BMI classifica- tween BMI and health risks than Western populations tion, found that the mean GWG among Chinese women do [23]. Recommending GWG ranges based on the IOM decreased as pre-pregnancy BMI increased. However, BMI cut-off points would classify some Chinese women Huang et al. BMC Pregnancy and Childbirth (2018) 18:185 Page 8 of 9 in lower pre-pregnancy BMI categories and suggest Additional files 2: Table S2. Subgroup analysis of comparison of them gain more weight than necessary, which may put adverse pregnancy outcome between different gestational weight gain groups in the pre-pregnancy BMI 25–29.9 strata. (DOC 47 kb) them at an unnecessarily higher risk for macrosomia and LGA [3]. In our sample, 13.42% of the women were Abbreviations misclassified as normal weight, and 8.37% were misclassi- BMI: Body mass index; CI: Confidence intervals; DBP: Diastolic blood pressure; fied as overweight if the pre-pregnancy weight status was GDM: Gestational diabetes mellitus; GWG: Gestational weight gain; determined by the IOM BMI cut-off points instead of the IOM: Institute of Medicine; LGA: Large-for-gestational age; OR: Odds ratio; PIH: Pregnancy-induced hypertension; SBP: Systolic blood pressure; Asian cut-off points. In Jan 2018, the national GWG SGA: Small-for-gestational age guideline for Chinese women was published [8], and a universal recommendation with the IOM criteria may re- Acknowledgements We thank the health workers in the Maternity and Child Care Hospital in the sult in more misclassification and unnecessary weight gain Tianxin and Yuelu districts for their assistance in the fieldwork. The first author among pregnant Chinese women in the future. Xin Huang is a new investigator in Hunan Normal University. Ethical approval and consent to participate Strengths and limitations This study was reviewed by the Ethical and Confidentiality Committee of Strengths and limitations should be considered when Central-South University (Reference 14/SPH/1005 (approved on 20th Oct interpreting the study findings. Information on birth 2015)), both institution review boards (IRB) from the Maternity and Child Care Hospital (MCCH) of Yuelu District (IRB of MCCH of Yuelu District) weight and maternal complications was obtained from and Tianxin District (IRB of MCCH of Tianxin District). Written consent medical records, which minimized the potential misclassi- has been signed by all participants. All personal information has been fication of the outcomes. Information on gestational age recoded with initials or numbers which guaranteed no information of the participants can be identified in data analysis. and infant gender was available, which allowed us to not only control for gestational age when studying the rela- Funding tionship with LBW and macrosomia but also examine the This work was funded by Natural Science Foundation of Hunan Province association with SGA and LGA. Furthermore, the data (2017JJ3215), Open Project of Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical contained detailed information on maternal demographic University (GMU-2017-005) and Zhishan Plan Program of the Third Xiangya information, which allowed adjusting for several import- Hospital, Central South University ([2017]15). The funding had no role in ant potential confounding factors simultaneously. How- study design, data collection, data analysis, data interpretation, or writing the report. ever, the limitation of our study should be considered when interpreting the study findings. Although weight at Availability of data and materials delivery was measured at the hospital and extracted from The datasets used and analyzed during the current study are available from the corresponding author on reasonable request. discharge abstracts, pre-pregnancy weight was recorded based on self-reported information. There is a potential Authors’ contributions misclassification for pre-pregnancy BMI status. However, XH, HT, and JL designed the research; XH, TS, MC and CM conducted the cohort study; XH performed statistical analysis; XH, HT, TS, MC, CM and JL high correlations were found between self-report and wrote the first draft and all authors contributed to the final draft and measured pre-pregnancy weight [24]. Our data are not approved the manuscript. from a nationally representative sample, we only used a retrospective cohort study in Changsha, which is in the Competing interests The authors declare that they have no competing interests. central region of China, to eliminate the potential for se- lection bias. The generalizability of our findings and the Publisher’sNote appropriateness of the GWG guidelines by the Chinese Springer Nature remains neutral with regard to jurisdictional claims in Society of Gynecology and Obstetrics need further published maps and institutional affiliations. investigation. Author details Department of Preventive Medicine, School of Medicine, Hunan Normal Conclusion 2 University, Changsha, Hunan, China. Department of Epidemiology and The IOM-recommended GWG ranges are within the Health Statistics, Xiangya School of Public Health, Central South University, Changsha, Hunan, China. Maternity and Child Care Hospital of Yuelu District, middle 70% of the distributions in Chinese women. Changsha, Hunan, China. Maternity and Child Care Hospital of Tianxin Pre-pregnancy weight status should be determined using 5 District, Changsha, Hunan, China. Department of Obstetrics and Gynecology, the Asian BMI cut-off points when applying IOM GWG The Third Xiangya Hospital of Central South University, 138 Tongzipo Road, Yuelu District, Changsha 410013, Hunan, Province, China. recommendations to Chinese women. Received: 21 January 2018 Accepted: 17 May 2018 Additional files References Additional files 1: Table S1. Subgroup analysis of comparison of 1. Adair LS. Long-term consequences of nutrition and growth in early adverse pregnancy outcomes between different gestational weight gain childhood and possible preventive interventions. Nestlé Nutr Inst Workshop groups in the pre-pregnancy BMI 23.0–24.9 strata. (DOC 47 kb) Ser. 2014;78:111–20. Huang et al. BMC Pregnancy and Childbirth (2018) 18:185 Page 9 of 9 2. Shao Y, Qiu J, Huang H, Mao B, Dai W, He X, et al. Pre-pregnancy BMI, gestational weight gain and risk of preeclampsia: a birth cohort study in Lanzhou, China. BMC Pregnancy Childbirth. 2017;17(1):400. 3. Baugh N, Harris DE, Aboueissa AM, Sarton C, Lichter E. The impact of maternal obesity and excessive gestational weight gain on maternal and infant outcomes in Maine: analysis of pregnancy risk assessment monitoring system results from 2000 to 2010. J Pregnancy. 2016;2016:5871313. 4. Davis RR, Hofferth SL. The association between inadequate gestational weight gain and infant mortality among U.S. infants born in 2002. Matern Child Health J. 2012;16(1):119–24. 5. Institute of Medicine (US) and National Research Council (US) Committee to Reexamine IOM Pregnancy Weight Guidelines, Rasmussen KM, Yaktine AL. Weight gain during pregnancy: reexamining the Guidelines. Washington, DC: National Academies Press (US); 2009. 6. Parker JD, Abrams B. Prenatal weight gain advice: an examination of the recent prenatal weight gain recommendations of the Institute of Medicine. Obstet Gynecol. 1992;79:664e669. 7. Edwards LE, Hellerstedt WL, Alton IR, Story M, Himes JH. Pregnancy complications and birth outcomes in obese and normal-weight women: effects of gestational weight change. Obstet Gynecol. 1996;87:389e394. 8. Obstetrics Subgroup, Chinese Society of Obstetrics and Gynecology, Chinese Medical Association. Guideline of preconception and prenatal care (2018) (Article in Chinese). Zhonghua Fu Chan Ke Za Zhi. 2018;53(1):7–13. 9. Yang YD, Yang HX. Investigation into the clinical suitability of Institute of Medicine 2009 guidelines regarding weight gain during pregnancy for women with full term singleton fetus in China. Zhonghua Fu Chan Ke Za Zhi. 2012;47(9):646–50. 10. Zhou YB, Li HT, Ye RW, Li ZW, Zhang YL, Zhang L, et al. Gestational weight gain, cesarean delivery, and cesarean delivery on maternal request: a cohort analysis of Chinese nulliparous women. Ann Epidemiol. 2017;27(2):96–102.e3. 11. Wong W, Tang NL, Lau TK, Wong TW. A new recommendation for maternal weight gain in Chinese women. J Am Diet Assoc. 2000;100(7):791–6. 12. Jiang X, Liu M, Song Y, Mao J, Zhou M, Ma Z, et al. The Institute of Medicine recommendation for gestational weight gain is probably not optimal among non-American pregnant women: a retrospective study from China. J Matern Fetal Neonatal Med. 2017;27:1–6. 13. Yang S, Peng A, Wei S, Wu J, Zhao J, Zhang Y, et al. Pre-pregnancy body mass index, gestational weight gain, and birth weight: a cohort study in China. PLoS One. 2015;10(6):e0130101. 14. Ko GTC, Chan JC, Cockram CS, Woo J. Prediction of hypertension, diabetes, dyslipidaemia or albuminuria using simple anthropometric indexes in Hong Kong Chinese. Int J Obes. 1999;23:1136–42. 15. Deurenberg-Yap M, Chew SK, Lin FP, van Staveren WA, Deurenberg P. Relationships between indices of obesity and its comorbidities among Chinese, Malays and Indians in Singapore. Int J Obes. 2001;25:1554–62. 16. Dai L, Deng C, Li Y, Zhu J, Mu Y, Deng Y, et al. Birth weight reference percentiles for Chinese. PLoS One. 2014;9(8):e104779. 17. Duryea EL, Hawkins JS, McIntire DD, Casey BM, Leveno KJ. A revised birth weight reference for the United States. Obstet Gynecol. 2014;124(1):16–22. 18. Khanolkar AR, Hanley GE, Koupil I, Janssen PA. 2009 IOM guidelines for gestational weight gain: how well do they predict outcomes across ethnic groups? Ethn Health. 2017;13:1–16. 19. Choi SK, Lee G, Kim YH, Park IY, Ko HS, Shin JC. Determining optimal gestational weight gain in the Korean population: a retrospective cohort study. Reprod Biol Endocrinol. 2017;15(1):67. 20. Nomura K, Kido M, Tanabe A, Nagashima K, Takenoshita S, Ando K. 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Journal

BMC Pregnancy and ChildbirthSpringer Journals

Published: May 29, 2018

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