Trend and risk factors of low birth weight and macrosomia in south China, 2005-2017: a retrospective observational study

Scientific Reports
Jiaming RaoZhengping Liu

Abstract

The percentages of low birth weight (LBW) increased from 7.7% in 2005 to 11.3% in 2011 and declined to 8.1% in 2017. For very low birth weight (VLBW) individuals, the proportion declined -1.0% annually, from 2.5% in 2005 to 1.4% in 2017. Among moderately low birth weight (MLBW) individuals, the proportion first increased 12.8% annually, from 5.0% in 2005 to 9.3% in 2011, and then declined -3.8% annually, from 9.4% in 2011 to 7.0% in 2017. The percentages of macrosomia monotone decreased from 4.0% in 2005 to 2.5% in 2017, an annual decline of -4.0%. Multiple regression analyses showed that boys, maternal age, hypertensive disorders complicating pregnancy (HDCP), and diabetes were significant risk factors for LBW. Boys, maternal age, gestational age, HDCP, diabetes, and maternal BMI were significant risk factors for macrosomia. Although the relevant figures declined slightly in our study, it is likely that LBW and macrosomia will remain a major public health issue over the next few years in China. More research aimed at control and prevention of these risk factors for LBW and macrosomia and their detrimental outcome in the mother and perinatal child should be performed in China.

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Citations

Jan 11, 2019·The Journal of Maternal-fetal & Neonatal Medicine : the Official Journal of the European Association of Perinatal Medicine, the Federation of Asia and Oceania Perinatal Societies, the International Society of Perinatal Obstetricians·Hongdan BaoXiaohong Xu
Apr 20, 2021·The Journal of Maternal-fetal & Neonatal Medicine : the Official Journal of the European Association of Perinatal Medicine, the Federation of Asia and Oceania Perinatal Societies, the International Society of Perinatal Obstetricians·Yanjie PengXietong Wang
Jun 11, 2021·The Journal of Obstetrics and Gynaecology Research·Louise HarveyEline M van der Beek

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Methods Mentioned

BETA
cesarean section

Software Mentioned

Joinpoint Regression Program ( )
R
Join point Regression Program ( )

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