You are here

  • Home
  • Archive
  • Volume 8, Issue 1
  • Perinatal factors and early neonatal outcomes of abnormal birthweight infants in Hangzhou, China, 2015–2021: a retrospective cohort study

Article Text

Article menu
Epidemiology
Original research
Perinatal factors and early neonatal outcomes of abnormal birthweight infants in Hangzhou, China, 2015–2021: a retrospective cohort study
  1. Yiming Chen1,2,
  2. Huimin Zhang2,
  3. Yan Jiang3,
  4. Wenwen Ning2,4,
  5. Lingling Huang5,
  6. Yanan Wang6,
  7. Xuelian Chu6
  1. 1Department of Prenatal diagnosis and screening center, Hangzhou Women's Hospital (Hangzhou Maternity and Child Health Care Hospital), Hangzhou, Zhejiang, China
  2. 2The Fourth School of Clinical Medical, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China
  3. 3Department of Obstetrics, The First People’s Hospital of Linping District, Hangzhou, Zhejiang, China
  4. 4Department of Clinical Laboratory, Hangzhou Geriatric Hospital, Hangzhou, Zhejiang, People's Republic of China
  5. 5Department of Laboratory, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, Zhejiang, China
  6. 6Department of Laboratory, Maternal and Child Health Hospital of Linping District, Hangzhou, Zhejiang, China
  1. Correspondence to Dr Yiming Chen; cxy40344{at}163.com

Abstract

Background This study aimed to investigate the perinatal factors and early neonatal outcomes of abnormal birth weight (ABW) in Hangzhou, China from 2015 to 2021.

Methods A retrospective cohort study was designed to analyse the data of 76 847 newborns, in which the case groups included 3042 cases of low birth weight (LBW) and 2941 cases of fetal macrosomia (MAC), and 70 864 cases of normal weight were as the reference group.

Results The incidence of LBW and MAC was 3.96% and 3.83% in Hangzhou, China from 2015 to 2021. Prematurity (<37 weeks), multiple births, hospitalisation >7 days, fetal anomalies, caesarean section, pregnancy complications, maternal coinfection with pathogens and summer births would be correlated with the incidence of LBW (ORs=43.50, 7.60, 2.09, 1.89, 1.57, 1.28, 1.19 and 1.18, all p<0.05). Factors such as post-term pregnancy (>41 weeks), scarred uterus, anterior vaginal incision and gravidity ≥2 were correlated with decreased incidence of LBW, with ORs of 0.05, 0.54, 0.65 and 0.80. Moreover, caesarean delivery, post-term pregnancy (> 41 weeks), parity ≥1, lateral vaginal incision, gravidity ≥2, hospitalisation >7 days, winter births and pregnancy complications also have association with the incidence of MAC (ORs=3.92, 2.73, 2.19, 1.87, 1.22, 1.20, 1.17 and 1.13, all p<0.05) while prematurity (<37 weeks), scarred uterus and anterior vaginal incision have close association with decreased incidence of MAC, with ORs of 0.07, 0.21 and 0.74 (all p<0.05).

Conclusion There was a trend of yearly increase in ABW in Hangzhou, China from 2015 to 2021. Several neonatal and maternal-related variables such as caesarean section, pregnancy complications and hospitalisation >7 days are associated with the odds of LBW and MAC, however, factors such as pregnancy with scarred uterus relate to the decrease of ABW. Close monitoring and intervention during pregnancy are essential to reduce the occurrence of ABW.

  • Epidemiology
  • Infant

Data availability statement

Data are available on reasonable request. The datasets used and/or analysed in this study are obtained from the corresponding author according to reasonable requirements.

http://creativecommons.org/licenses/by-nc/4.0/

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

https://doi.org/10.1136/bmjpo-2023-002347

Statistics from Altmetric.com

    Request Permissions

    If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.

    WHAT IS ALREADY KNOWN ON THIS TOPIC

    • Abnormal birth weight (ABW) of newborns, including low birth weight and fetal macrosomia, is an important determinant of poor neonatal survival, disability, growth retardation and other long-term outcomes.

    WHAT THIS STUDY ADDS

    • There was an increasing tendency for ABW in Hangzhou, China from 2015 to 2021.

    • A variety of neonatal and maternal factors are associated with the development of ABW.

    HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

    • Factors such as caesarean section, pregnancy complications and hospitalisation >7 days could be considered to guide clinical intervention in the odds of ABW.

    Background

    Birth weight (BW) is a predictor of neonatal outcome and one of the critical indicators reflecting the health status of newborns at birth, and the trend of BW helps to assess the population’s health status.1 Abnormal birth weight (ABW) is defined as a low or high neonatal weight due to underlying diseases such as prematurity, malnutrition and maternal diabetes, including both low birth weight (LBW) and fetal macrosomia (MAC). They are important determinants of neonatal survival, disability, growth retardation and long-term adverse outcomes of non-communicable disease episodes over the life course.2 Therefore, appropriate public health interventions are required.

    LBW refers to newborns with BW <2500 g and preterm refers to newborns born at gestational age <37 weeks. Due to immaturity and LBW, preterm/LBW mortality is higher than that of full-term infants in the early postnatal and growth periods. Global estimates of prematurity and LBW range between 15% and 20%. It has been reported that an estimated 20.5 million live births were LBW in the world population in 2015, 91% of which were mainly from low-income and middle-income countries such as southern Asia (48%) and sub-Saharan Africa (24%).1 3 The prevalence of LBW is higher in Asia (India and Pakistan) compared with Africa and Central America.4 LBW is strongly associated with childhood mortality and long-term health and can lead to diseases associated with low immune function, poor growth, cognitive impairment, late-stage centripetal obesity, cardiovascular disease and type 2 diabetes.5 High rates of consanguinity, prematurity, increased number of older maternal pregnancies and lifestyle changes are significant factors associated with increased LBW rates.6

    MAC is a newborn with a BW >4000 g within 1 hour of birth. It is detrimental to neonatal health, and there is strong evidence that MAC is associated with an increased risk of maternal and neonatal complications. As BW increases, the likelihood of abnormal deliveries, difficult shoulders, birth trauma and permanent neonatal injuries increases.7 8 It not only increases the risk of intrauterine and puerperal infections during pregnancy but also leads to excessive growth after birth and increases the incidence of obesity and cardiometabolic diseases.7–9 The aetiology of MAC includes genetic and environmental factors. Extensive evidence suggests that maternal overweight and associated metabolic changes, including type 2 diabetes and gestational diabetes mellitus (GDM), may play a central role in the pathogenesis of MAC.7

    To some extent, LBW and MAC represent obstetric challenges. Preterm birth is the main cause of LBW while excessive gestational weight gain and GDM are significantly associated with MAC. Clinical interventions, while focusing on continuous monitoring of ABW, should also focus on appropriate gestational weight gain and reduction of preterm birth and GDM.10 When fetal LBW and MAC are suspected, there is no central consensus on whether expectant management, induction of labour or elective caesarean delivery is the best option.11 Therefore, to understand the perinatal factors and early neonatal outcomes of LBW and MAC in Hangzhou, China, we conducted a retrospective cohort study to analyse data from 76 847 pregnant women and newborns.

    Materials and methods

    Subjects

    A retrospective cohort study was conducted to collect data on a total of 76 847 pregnant women who were enrolled for inpatient delivery at Hangzhou Women’s Hospital, Hangzhou, Zhejiang Province between November 2014 and February 2022. There were 3042 cases of LBW, 2941 cases of MAC and 70 864 cases of BW normal. The cohort enrolment cases are shown in figure 1.

    Figure 1
    Figure 1

    Study cohort enrolment and exclusion flow chart.

    Diagnosis and exclusion criteria

    Case diagnosis

    BW refers to the weight of the neonate within 1 hour of birth. Neonates with BW <2500 g are LBW, neonates with BW >4000 g are MAC and neonates with BW between 2500 and 4000 g are normal birth weight (NBW).3 7 Infant weight in this study refers to median infant weight. Inclusion criteria: pregnant women and newborns born between November 2014 and February 2022 who were hospitalised in our hospital for delivery; and newborns alive at birth. We corrected for gestational age mainly by clinical assessment of the date of last menstrual period (LMP), ultrasound findings, other maternal characteristics and replacing possible errors in the LMP data with the results of the clinical assessment during our data collection and statistical process.

    Exclusion criteria

    Abortion; fetuses delivered at home and those with incomplete information; inconsistent records among LMP, ultrasound findings, other maternal characteristics and gestational age.

    Pregnancy complications

    Pregnancy complications include hypertensive disorders of pregnancy, GDM, intrahepatic cholestasis of pregnancy, hyperlipidaemia, pregnancy-associated anaemia, etc12–15; pregnancy copathogenic infections are coinfections with hepatitis B virus or carriers, syphilis, AIDS, mycoplasma, chlamydia, streptococcus and other pathogens.16–18 All pregnancy complications and pregnancy outcomes were obtained from clinical records diagnosed by hospital obstetricians according to the corresponding Chinese guidelines.

    Statistical analysis

    IBM-SPSS V.21.0 statistics (IBM-SPSS) was used for statistical processing. If the data were skewed, they were expressed as median and percentile (M (P25, P75)). The Mann-Whitney U test or χ2 test was conducted for univariate analysis of continuous or categorical data. A p<0.10 was used as the screening criterion for inclusion in the multiple logistic regression analysis. Whether or not LBW and MAC were used as dependent variables (1, LBW, 2, MAC, 3, NBW) and NBW was as a reference. Moreover, factors such as infant sex, year of birth, season of birth, fetal abnormality, gestational weeks (days), mode of delivery, age of delivery, gravidity, parity, multiple births, in vitro fertilisation (test tube), scarred uterus, permanent residence, pregnancy complications, pregnancy copathogenic infections and hospitalisation >7 days as covariates. Multinomial logistic regression analysis was performed to screen the variable ratio (OR) and 95% (CI) of each relevant influencing factor, and the difference was considered statistically significant at p<0.05.

    Results

    Demographic characteristics of 76 847 pregnant women and newborns

    Among the 76 847 maternal and neonatal data collected, there were more male infants (52.25%) than female infants (47.75%), and the median BW of male infants was heavier than that of female infants (3340 g vs 3220 g). In addition, the preterm birth rate (5.9%), caesarean section rate (35.4%) and maternal comorbidity (50.1%) were higher in male than in female infants (5.3%, 33.5% and 48.8%), with statistically significant differences between the sexes (all p<0.001). The prevalence of gravidity ≥2, parity ≥1 and scarred uterus was higher in male infants than in female infants (52.7%, 34.0% and 14.2% vs 51.9%, 33.0% and 13.5%), with statistically significant differences between sex (all p<0.05). However, there were no statistically significant differences between male and female infants in other factors such as maternal age, permanent residence, hospitalisation, maternal coinfection with pathogens, in vitro fertilisation, year of birth and season of birth (all p>0.05), as shown in table 1.

    View this table:
    Table 1

    General demographic characteristics in the study population (n (%), M (P25–P75)

    Trend of birth weight change

    The trend of neonatal BW change from 2015 to 2021 was between 3250 (2346–4100) g and 3300 (2300–4100) g, with a decreasing trend of BW year by year (Z=105.881, p<0.001). Moreover, the trend of neonatal BW change for male infants was between 3320 (2352–4110) g and 3350 (2300–4150) g while the fluctuation of female infants was between 3200 (2300–4000) g and 3250 (2250–4050) g, which might be related to physiological weight differences between male and female (see figure 2).

    Figure 2
    Figure 2

    Trend of BW change in Hangzhou, China, 2015–2021. BW, birth weight.

    Trends of the incidence of ABW

    The incidence of LBW and MAC in Hangzhou was 3.96% and 3.83%, respectively, with an increasing tendency year by year. In more detail, the incidence of LBW in female infants was higher than that in male infants (1.83% vs 2.13%, p<0.001) while the incidence of MAC was exactly the opposite of the above (1.27% vs 2.56%, p<0.001) (see figure 3A,B).

    Figure 3
    Figure 3

    Trends in the Incidence of ABW in Hangzhou, China, 2015–2021 (A) Trends of LBW; (B) Trends of MAC. ABW, abnormal birth weight; LBW, low birth weight; MAC, macrosomia.

    Multinomial logistic regression analysis of factors associated with the incidence of ABW

    With the Pearson’s χ2 significance value of 0.135 for the goodness-of-fit test, the original hypothesis is valid, indicating that the model’s fit to the original data passes the test. The three pseudo R2 values (similar to the coefficient of determination) listed in sequence are all low, with a maximum of 0.306, indicating that the model explains the variation in the original variables to an average degree. It also has been tested that there was no multicollinearity between the independent variables in this study (all tolerance>0.2, Variance Inflation Factor (VIF)>5).

    Online supplemental table 1 shows that the odds of LBW in male infants were lower than in female infants (OR=0.64, 95% CI 0.58 to 0.70) and the ORs for prematurity (<37 weeks): 43.50 (95% CI 39.53 to 47.88), multiple births: 7.60 (95% CI 6.22 to 9.29), hospitalisation >7 days: 2.09 (95% CI 1.83 to 2.38), fetal anomalies: 1.89 (95% CI 1.18 to 3.01), caesarean section: 1.57 (95% CI 1.40 to 1.77), pregnancy complications: 1.28 (95% CI 1.16 to 1.41), maternal coinfection with pathogens: 1.19 (95% CI 1.05 to 1.34) and summer births were 1.18 (95% CI 1.03 to 1.34). In contrast, the ORs for post-term pregnancy (>41 weeks) were 0.05 (95% CI 0.02 to 0.13), scarred uterus: 0.54 (95% CI 0.46 to 0.65), anterior vaginal incision: 0.65 (95% CI 0.49 to 0.87) and gravidity ≥2 were 0.80 (95% CI 0.70 to 0.90), which might be related to the decreased incidence of LBW. On the other hand, the odds of MAC were higher in male than in female infants (OR 1.86, 95% CI 1.72 to 2.01), with ORs for caesarean delivery: 3.92 (95% CI 3.55 to 4.33), post-term pregnancy (> 41 weeks): 2.73 (95% CI 2.45 to 3.04), parity ≥1: 2.19 (95% CI 1.94 to 2.47), lateral vaginal incision: 1.87 (95% CI 1.62 to 2.15); gravidity ≥2: 1.22 (95% CI 1.10 to 1.35), hospitalisation >7 days: 1.20 (95% CI 1.05 to 1.37), winter births: 1.17 (95% CI 1.05 to 1.30) and pregnancy complications: 1.13 (95% CI 1.05 to 1.22). All the above mentioned were associated with the odds of MAC. On the contrary, prematurity (<37 weeks) (OR 0.07, 95% CI 0.04 to 0.14), scarred uterus (OR 0.21, 95% CI 0.18 to 0.24) and anterior vaginal incision (OR 0.74, 95% CI 0.57 to 0.97) were associated with the decreased odds of MAC.

    Supplemental material

    Discussion

    The main finding of this study was that the trend of neonatal BW in Hangzhou, Zhejiang, China ranged from 3250 (2346–4100) g to 3300 (2300–4100) g, with a decreasing trend year by year. The incidence of LBW and MAC was 3.96% and 3.83%, respectively, and also increased year by year. The incidence of LBW in male infants was lower than that in female infants. Prematurity (<37 weeks), multiple births, hospitalisation >7 days, fetal anomalies, caesarean section, pregnancy complications, maternal coinfection with pathogens and summer births would be associated with the odds of LBW. Factors such as post-term pregnancy (>41 weeks), scarred uterus, anterior vaginal incision and gravidity ≥2 are associated with the decrease of LBW. On the other hand, the odds of MAC were higher in male than in female infants. Caesarean delivery, post-term pregnancy (>41 weeks), parity ≥1, lateral vaginal incision, gravidity ≥2, hospitalisation >7 days, winter births and pregnancy complications have an association with the odds of MAC while prematurity (<37 weeks), scarred uterus and anterior vaginal incision are closely related to the decrease of MAC.

    In this study, we found that the median BW of newborns in Hangzhou, China was 3280 g. The trend of BW changed to the lowest in 2017 at 3250 (2346–4100) g and the highest in 2015 at 3300 (2300–4100) g. The median BW of male infants was 3340 g heavier than that of female infants at 3220 g, with a decreasing trend, which resembles the trend of BW in Zhoushan, China from 2002 to 2015,19 but different from the trend of neonatal BW in Ezhou, China, from 2006 to 2011.20 We also found that even though male infants were born at higher gestational weeks than female infants, the median BW of female infants was lower than that of male infants, and the odds of LBW in female infants were higher than those of male infants (OR=0.64), meanwhile, the odds of MAC were lower than that of male infants (OR=1.86), which is consistent with the findings of other studies.19–21 Similarly, Mengesha et al22 found that gestational age and fetal sex were common risk factors for LBW and MAC. The reason for this may be due to different endocrine metabolism in male and female fetuses due to androgenic effects or antigenic differences between male fetuses and their mothers, which makes the mean risk of BW and MAC greater in male than in female infants.23 24

    This study suggests that the incidence of LBW and MAC in the neonatal population of Hangzhou was 3.96% and 3.83%, respectively, which is lower than the 5.15% of LBW and 7.35% of MAC in children under 6 years of age in China in 2013 after accounting for potential BW accumulation.25 The incidence of ABW varies widely across geographic and ethnic populations. It has been reported that the incidence of LBW in the Volta Region was 9.69% and the MAC was 3.03%.26 In addition, the incidence of LBW was around 4.0% and the mean percentage of MAC children was 7.6% in Beijing, China.10 The incidence of LBW in this study was much lower than that reported in the literature19 26 but higher than another report25 and was similar to 4.0% in Beijing,10 Moreover, the incidence of MAC was higher than that reported in the literature26 but lower than 7.6% in Beijing.10

    The results of this study showed that prematurity (<37 weeks), multiple births, hospitalisation >7 days, fetal anomalies, caesarean section, pregnancy complications, maternal coinfection with pathogens and summer births were associated with the increased odds of LBW, which is associated with maternal age <20 years, low maternal education, previous adverse pregnancy history and pregnancy complications, such as hypertensive disorders of pregnancy, anaemia, oligohydramnios, premature rupture of membranes and GDM.27 Maternal-related variables such as maternal age, maternal nationality, mode of delivery (vaginal, caesarean) and neonatal-related variables such as infant sex were significantly associated with LBW.28 Mohammed et al29 reported findings of LBW-related influences including preterm birth, pregnancy complications or comorbidities, advanced maternal age (≥35 years), first-born infants and female infants in the Jordanian region were similar. Similarly, Kim et al30 revealed some Korean perinatal factors including preterm birth rate, LBWI, multiple births and maternal age were related to mean weight. All the above-mentioned results reported in the literature have similarities with this study.

    Premature rupture of membranes, placental abnormalities, gestational combined hypertension, whether singleton, history of adverse pregnancy and delivery, maternal prepregnancy body mass index (BMI), weight gain during pregnancy, monthly household income, maternal smoking history during pregnancy, nutritional supplements and maternal literacy may be relevant influencing factors for LBW. Weight gain during pregnancy, daily staple food intake, gestational weeks, GDM, maternal prepregnancy BMI, paternal smoking during pregnancy, whether menstrual daily livestock and poultry meat intake and maternal age at menarche may be relevant influencing factors for MAC.31 The results of this study suggested that pregnancy complications and hospitalisation >7 days were common risk factors for LBW and MAC, and scarred uterus was a common protective factor. It has been acknowledged that GDM increases the incidence of adverse neonatal outcomes, especially large for gestational age, preterm birth and poor Apgar score. Therefore, the prevention of GDM is essential to improve neonatal outcomes.32

    This is a study of ABW and perinatal characteristics in Hangzhou, Zhejiang, China. There are several limitations to this study. First, we included a large sample size, but these findings are only representative of the Hangzhou area, and there is regional, period and ethnic variability in ABW. Second, this study lacked information on maternal height and weight, and the impact of maternal prognosis on BMI was not analysed. It had been indicated that prepregnancy BMI, GDM and weight gain during pregnancy were significantly associated with an increased risk of neonatal MAC.33 34 Third, this study was a retrospective study that included a large sample size of nearly 70 000, providing sufficient data for analysis and extrapolation to a subsample. However, it is worth pointing out that the small p values in the results of this study lead to potential statistical significance worth pondering. Because of the lack of specific information on COVID-19 during the pandemic in our data, we did not focus on the effects of COVID-19 on pregnant women and fetuses, which is also one of the limitations of our study. Future studies should include longer follow-up periods, more variables and larger sample sizes and should pay more attention to the practical significance of the findings and properly assess the validity of statistical significance.

    Conclusion

    There was a yearly decreasing trend in neonatal BW while the incidence of LBW and MAC increased yearly (3.96% and 3.83%) during 2015–2021 in Hangzhou, China.

    Prematurity (<37 weeks), multiple births, hospitalisation >7 days, fetal anomalies, caesarean section, pregnancy complications, maternal coinfection with pathogens and summer births are associated with the odds of LBW. Furthermore, caesarean delivery, post-term pregnancy (> 41 weeks), parity ≥1, anterior vaginal incision, gravidity ≥2, hospitalisation >7 days, winter births and pregnancy complications are associated with the odds of MAC. Noteworthy, caesarean section, pregnancy complications and hospitalisation >7 days are common related factors for LBW and MAC. Factors such as post-term pregnancy (>41 weeks), scarred uterus, anterior vaginal incision and gravidity ≥2 have an association with decreased odds of LBW, and preterm labour (<37 weeks), scarred uterus and anterior vaginal incision might correlate with lower odds of MAC. Close monitoring and intervention of these factors during pregnancy are critical to ensure a positive pregnancy course, especially to reduce the incidence of ABW.

    Data availability statement

    Data are available on reasonable request. The datasets used and/or analysed in this study are obtained from the corresponding author according to reasonable requirements.

    Ethics statements

    Patient consent for publication

    Ethics approval

    This study involves human participants and the study has been conducted under the approval of the Human Research Ethics Committee of the Hangzhou Women’s Hospital ((2024) Medical Ethics Review A 005), and the procedures have been performed by the Declaration of Helsinki. Informed consent was obtained from all participants, and for participants under 16 years of age, informed consent was obtained from their parents or legal guardians. Participants gave informed consent to participate in the study before taking part.

    Acknowledgments

    The authors are grateful to all of the participants and contributors. We would like to thank Songhe Chen from the Record room of Hangzhou Women’s Hospital for helping to collect the data.

    References

    1. ↵
      1. Cunningham SA,
      2. Mehlawat U
      . Birthweight: an early beacon of children’s growth Indian Pediatr 2023;60:96–7.
      OpenUrl
    2. ↵
      1. WHO Recommendations for Care of the Preterm or Low-Birth-Weight Infant
      . Geneva: World Health Organization, 2022.
    3. ↵
      1. Darmstadt GL,
      2. Al Jaifi NH,
      3. Ariff S, et al
      . New WHO recommendations for the care of Preterm or low birthweight infants have the potential to transform maternal and newborn health-care delivery. The Lancet 2022;400:1828–31. doi:10.1016/S0140-6736(22)02186-9
      OpenUrl
    4. ↵
      1. Marete I,
      2. Ekhaguere O,
      3. Bann CM, et al
      . Regional trends in birth weight in Low- and middle-income countries 2013-2018. Reprod Health 2020;17:176. doi:10.1186/s12978-020-01026-2
    5. ↵
      1. Yan H,
      2. Zhai B,
      3. Feng R, et al
      . Prevalence of congenital heart disease in Chinese children with different birth weights and its relationship to the neonatal birth weight. Front Pediatr 2022;10:828300. doi:10.3389/fped.2022.828300
    6. ↵
      1. Islam MM
      . Increasing incidence of infants with low birth weight in Oman. Sultan Qaboos Univ Med J 2015;15:e177–83.
      OpenUrl
    7. ↵
      Macrosomia: ACOG Practice Bulletin Summary, Number 216. Obstetrics & Gynecology 2020;135:246–8. doi:10.1097/AOG.0000000000003607
      OpenUrl
    8. ↵
      1. Grossman L,
      2. Pariente G,
      3. Baumfeld Y, et al
      . Trends of changes in the specific contribution of selected risk factors for shoulder Dystocia over a period of more than two decades. J Perinat Med 2020;48:567–73. doi:10.1515/jpm-2019-0463
      OpenUrl
    9. ↵
      Practice bulletin No.173 summary: fetal Macrosomia. Obstet Gynecol 2016;128:1191–2.
      OpenUrl
    10. ↵
      1. Shan X,
      2. Chen F,
      3. Wang W, et al
      . Secular trends of low birthweight and Macrosomia and related maternal factors in Beijing, China: a longitudinal trend analysis. BMC Pregnancy Childbirth 2014;14:105. doi:10.1186/1471-2393-14-105
      OpenUrlPubMed
    11. ↵
      1. Rossi AC,
      2. Mullin P,
      3. Prefumo F
      . Prevention, management, and outcomes of Macrosomia: a systematic review of literature and meta-analysis. Obstet Gynecol Surv 2013;68:702–9. doi:10.1097/01.ogx.0000435370.74455.a8
      OpenUrlPubMed
    12. ↵
      1. Obstetrics Subgroup CSoO, Gynecology CMA
      . Guidelines for diagnosis and treatment of Intrahepatic cholestasis of pregnancy. Chin J Obstet Gynaecol 2015;50:481.
      OpenUrl
    13. ↵
      1. Chinese Medical Association Obstetrics and Gynecology Branch Pregnancy Hypertension Disease Group
      . Guidelines for diagnosis and treatment of hypertension during pregnancy. Chin J Obstet Gynaecol 2015;50:721–8.
      OpenUrl
    14. ↵
      1. International Association of Diabetes and Pregnancy Study Groups Consensus Panel,
      2. Metzger BE,
      3. Gabbe SG, et al
      . International Association of diabetes and pregnancy study groups recommendations on the diagnosis and classification of hyperglycemia in pregnancy. Diabetes Care 2010;33:676–82. doi:10.2337/dc09-1848
      OpenUrlFREE Full Text
    15. ↵
      1. Ehsanipoor R
      . Premature rupture of membranes. Obstet Gynecol 2013;122:918–30. doi:10.1097/01.AOG.0000435415.21944.8f
      OpenUrlCrossRefPubMed
    16. ↵
      1. Chinese Society of Hepatology and Chinese Society of Infectious Diseases, Chinese Medical Association
      . The guideline of prevention and treatment for chronic hepatitis B: A 2015 up-date. Clin J Viral Dis 2015;5:401–24.
      OpenUrl
    17. ↵
      1. WS 273-2007 syphilis diagnostic criteria
      . Industry Standards-Health. Chinese Standard. 2007-04-17(2007-10-15), 16P. A4. 2007.
    18. ↵
      1. Perinatal Medicine Branch of the Chinese Medical Association, Obstetrics and Gynecology Section of the Chinese Medical Association
      . Expert consensus on the prevention of perinatal group B Streptococcal disease (China). Chin J Perinat Med 2021;24:561–6.
      OpenUrl
    19. ↵
      1. Ding HY,
      2. Xamusiye M,
      3. Li MC, et al
      . Analysis of birth weight change and adverse birth outcomes and influencing factors in Zhoushan city from 2002-2015. Chin J Dis Control 2018;22:380–5.
      OpenUrl
    20. ↵
      1. Hu J,
      2. Li YP
      . Analysis of birth weight Dynamics of newborns in Ezhou city from 2006-2011. Pub Health Pre Med 2013;24:49–51.
      OpenUrl
    21. ↵
      1. Zhang XM,
      2. Zhao P,
      3. Chen SC, et al
      . Factors influencing adverse birth outcomes in live-born newborns in Guiping, Guangxi, 2016-2020. Chin J Dis Control 2022;26:1050–6.
      OpenUrl
    22. ↵
      1. Mengesha HG,
      2. Wuneh AD,
      3. Weldearegawi B, et al
      . Low birth weight and Macrosomia in Tigray, northern Ethiopia: who are the mothers at risk BMC Pediatr 2017;17:144. doi:10.1186/s12887-017-0901-1
    23. ↵
      1. Elshibly EM,
      2. Schmalisch G
      . Differences in Anthropometric measurements between Sudanese newborn twins and Singletons. Twin Res Hum Genet 2010;13:88–95. doi:10.1375/twin.13.1.88
      OpenUrlPubMed
    24. ↵
      1. Dasinger JH,
      2. Alexander BT
      . Gender differences in developmental programming of cardiovascular diseases. Clin Sci (Lond) 2016;130:337–48. doi:10.1042/CS20150611
      OpenUrlCrossRefPubMed
    25. ↵
      1. Shen L,
      2. Wang J,
      3. Duan Y, et al
      . Prevalence of low birth weight and Macrosomia estimates based on Heaping adjustment method in China. Sci Rep 2021;11:15016. doi:10.1038/s41598-021-94375-2
    26. ↵
      1. Agbozo F,
      2. Abubakari A,
      3. Der J, et al
      . Prevalence of low birth weight, Macrosomia and Stillbirth and their relationship to associated maternal risk factors in Hohoe municipality, Ghana. Midwifery 2016;40:200–6:S0266-6138(16)30106-1. doi:10.1016/j.midw.2016.06.016
      OpenUrl
    27. ↵
      1. Chen Y,
      2. Li G,
      3. Ruan Y, et al
      . An Epidemiological survey on low birth weight infants in China and analysis of outcomes of full-term low birth weight infants. BMC Pregnancy Childbirth 2013;13:242. doi:10.1186/1471-2393-13-242
      OpenUrl
    28. ↵
      1. Hüseyin Çam H,
      2. Harunoğulları M,
      3. Polat Y
      . A study of low birth weight prevalence and risk factors among newborns in a public-hospital at Kilis, Turkey. Afr H Sci 2020;20:709–14. doi:10.4314/ahs.v20i2.22
      OpenUrl
    29. ↵
      1. Mohammed K,
      2. Shaban I,
      3. Al-Akour N, et al
      . Low birth weight in Jordan: a hospital-based study. J Matern Fetal Neonatal Med 2020;33:3050–5. doi:10.1080/14767058.2019.1567707
      OpenUrl
    30. ↵
      1. Kim HE,
      2. Song IG,
      3. Chung SH, et al
      . Trends in birth weight and the incidence of low birth weight and advanced maternal age in Korea between 1993 and 2016. J Korean Med Sci 2019;34:e34. doi:10.3346/jkms.2019.34.e34
    31. ↵
      1. Song D
      . A Case-Control Study on the Factors Influencing Low Birth Weight and Large Babies. Master, Tianjin Medical University, 2008.
    32. ↵
      1. Muche AA,
      2. Olayemi OO,
      3. Gete YK
      . Gestational diabetes mellitus increased the risk of adverse neonatal outcomes: A prospective cohort study in Northwest Ethiopia. Midwifery 2020;87. doi:10.1016/j.midw.2020.102713
    33. ↵
      1. Agudelo-Espitia V,
      2. Parra-Sosa BE,
      3. Restrepo-Mesa SL
      . Factors associated with fetal Macrosomia. Rev Saude Publica 2019;53:100. doi:10.11606/s1518-8787.2019053001269
    34. ↵
      1. Chen Y-H,
      2. Chen W-Y,
      3. Chang C-Y, et al
      . Association between maternal factors and fetal Macrosomia in full-term Singleton births. J Chin Med Assoc 2023;86:324–9. doi:10.1097/JCMA.0000000000000871
      OpenUrl

    Supplementary materials

    • Supplementary Data

      This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.

    Footnotes

    • YC, HZ and YJ contributed equally.

    • Contributors YC had substantial contributions to the conception or design of the work. LH, XC and YW were responsible for the acquisition, analysis, interpretation of data for the work. YJ and HZ draft the work and revised it critically for important intellectual content. YC and WN made the final approval of the version to be published. All authors have accepted responsibility for the entire content of this manuscript and approved its submission. The guarantor (YC) accepts full responsibility for the work and the conduct of the study, had access to the data, and controlled the decision to publish.

    • Funding Thia study was funded by Hangzhou Health Science and Technology Plan Project (A202301168).

    • Competing interests No, there are no competing interests.

    • Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.