Birth weight percentile curves of singleton neonates with different gestational ages among native populations of 14 provinces in China
HUANG Xiaoyun1, ZHU Yuanfang1, LIU Huilong1, FU Mianai2, LIU Chuanyong3, ZENG Dingyuan4, HE Jun5, SHI Qingxi6, CHEN Changshui7, ZHU Bin8, WANG Gaoxiong9, SHI Hao10, LU Haohua11
1. Baoan District Maternal and Child Health Care Hospital, Shenzhen, Guangdong 518102, China; 2. Haikou Municipal Maternal and Child Health Care Hospital, Haikou, Hainan 571103, China; 3. Wanzhou District Maternal and Child Health Care Hospital, Chongqing 400010, China; 4. Liuzhou Municipal Maternal and Child Health Care Hospital, Liuzhou, Guangxi 545001, China; 5. Changsha Municipal Maternal and Child Health Care Hospital, Changsha, Hunan 410007, China; 6. Lianyungang Municipal Maternal and Child Health Care Hospital, Lianyungang, Jiangsu 222006, China; 7. Ningbo Municipal Maternal and Child Health Care Hospital, Ningbo, Zhejiang 315012 China; 8. Panyu District Maternal and Child Health Care Hospital, Guangzhou, Guangdong 511402, China; 9. Quanzhou Municipal Maternal and Child Health Care Hospital, Quanzhou, Fujian 362017, China; 10. Jinniu District Maternal and Child Health Care Hospital, Chengdu, Sichuan 610031, China; 11. Guilin Municipal Maternal and Child Health Care Hospital, Guilin, Guangxi 541001, China
Abstract：Objective To develop the birth weight curves of singleton neonates with different gestational ages according to the populations' provincial birthplaces, and to study the differences in provincial birthplaces. Methods We collected the data concerning all live singleton neonates delivered in 11 maternal and child health care hospitals in 11 cities (including Haikou, Guangzhou, Shenzhen, Liuzhou, Guilin, Quanzhou, Chongqing, Chengdu, Changsha, Ningbo and Lianyungang) in China from January 1, 2017 to December 31, 2020, and selected 323,462 singleton neonates with the data regarding mothers' provincial birthplaces, and developed the birth weight curves of singleton neonates with different gestational ages based on classification of the populations' provincial birthplaces. Results We established the reference values of birth weight percentiles (the 3rd-97th) of singleton neonates with different gestational ages based on native populations of 14 provinces (autonomous regions and municipalities), including Guangdong, Guangxi, Hainan, Fujian, Hunan, Hubei, Sichuan, Chongqing, Guizhou, Jiangxi, Zhejiang, Anhui, Hebei and Henan, and drew the birth weight percentile curves (the 10th, 50th and 90th). The birth weight curve level of singleton neonates with different gestational ages based on native populations of 10 provinces (autonomous regions and municipalities) including Guangdong, Guangxi, Hainan, Fujian, Guizhou, Sichuan, Hunan, Chongqing, Hubei and Jiangxi was close to the average level of singleton neonates with different gestational ages based on the 11 cities of China. The birth weight curve level of singleton neonates with different gestational ages for native populations of 4 provinces including Zhejiang, Anhui, Hebei, and Henan was higher than the average level of singleton neonates with different gestational ages based on the 11 cities of China. Conclusion We develops the reference values of birth weight percentiles (the 3rd-97th) of singleton neonates withdifferent gestational ages based on native populations of 14 provinces in China, which can be used as a reference standard for evaluating the intrauterine growth of singleton neonates with different gestational ages for native populations of the related provinces. There are differences in the intrauterine growth level among native populations of the 14 provinces.
黄小云, 朱元方, 刘惠龙, 符免艾, 刘传永, 曾定元, 贺骏, 施庆喜, 陈长水, 朱斌, 王高雄, 石浩, 卢浩华. 中国14个省籍贯人口不同胎龄单胎儿出生体重百分位曲线[J]. 实用预防医学, 2023, 30(7): 769-774.
HUANG Xiaoyun, ZHU Yuanfang, LIU Huilong, FU Mianai, LIU Chuanyong, ZENG Dingyuan, HE Jun, SHI Qingxi, CHEN Changshui, ZHU Bin, WANG Gaoxiong, SHI Hao, LU Haohua. Birth weight percentile curves of singleton neonates with different gestational ages among native populations of 14 provinces in China. , 2023, 30(7): 769-774.
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2023, Vol. 30 
