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[Analysis of population attributable risk of large for gestational age].
Zhonghua Fu Chan Ke Za Zhi. 2019 Dec 25; 54(12):833-839.ZF

Abstract

Objective:

To examine the association of pre-pregnancy obesity, excessive gestational weight gain (GWG) and gestational diabetes mellitus (GDM) with the risk of large for gestational age (LGA), and assess the dynamic changes in population attributable risk percent (PAR%) for having these exposures.

Methods:

A retrospective cohort study was conducted to collect data on pregnant women who received regular health care and delivered in Beijing Obstetrics and Gynecology Hospital from January to December in 2011, 2014 and 2017, respectively. Information including baseline characteristics, metabolic indicators during pregnancy, pregnancy complications, and pregnancy outcomes were collected. Multivariate logistic regression model was constructed to assess their association with LGA delivery. Adjusted relative risk and prevalence of these factors were used to calculate PAR%and evaluate the comprehensive risk.

Results:

(1)The number of participants were 11 132, 13 167 and 4 973 in 2011, 2014 and 2017, respectively. Corresponding prevalence of LGA were 15.19% (1 691/11 132), 14.98% (1 973/13 167) and 16.21% (806/4 973). No significant change in the prevalence of LGA was observed across all years investigated (all P>0.05). (2)According to results from multivariate logistic regression model, advanced maternal age, multiparity, pre-pregnancy overweight or obesity, GWG,GDM and serum triglyceride level≥1.7 mmol/L in the first trimester were associated with high risk of LGA (all P<0.05). Among these factors, pre-pregnancy overweight or obesity, excessive GWG and multiparity were common risk factors of LGA. GDM was not associated with risk of LGA in 2017 database. (3) Dynamic change of PAR% in these years were notable. PAR% of GWG for LGA decreased (32.6%, 27.2% and 22.2% in 2011, 2014 and 2017, respectively), while PAR% of pre-pregnancy overweight or obesity showed an upward trend (4.2%, 3.3% and 8.4%). In addition, PAR% of multiparity increased as well (3.5%, 6.3% and 15.9%). (4) Further analysis showed that excessive GWG in the first and second trimesters contributed the most (20.2% and 19.0% in 2014 and 2017).

Conclusions:

Excessive GWG, pre-pregnancy overweight or obesity and multiparity are the important risk factors what contribute to LGA. PAR% of excessive GWG for LGA decrease in recent years. However, GWG in the first and second trimesters is a critical factor of LGA. Appropriate weight management in pre-pregnancy, the first or second trimester is the key point to reduce the risk of LGA.

Authors+Show Affiliations

Division of Endocrinology and Metabolism, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing 100026, China.Division of Endocrinology and Metabolism, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing 100026, China.Division of Endocrinology and Metabolism, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing 100026, China.Division of Endocrinology and Metabolism, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing 100026, China.Division of Endocrinology and Metabolism, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing 100026, China.Division of Endocrinology and Metabolism, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing 100026, China.Division of Endocrinology and Metabolism, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing 100026, China.Department of Obstetrics, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing 100026, China.

Pub Type(s)

Journal Article

Language

chi

PubMed ID

31874473

Citation

Zheng, W, et al. "[Analysis of Population Attributable Risk of Large for Gestational Age]." Zhonghua Fu Chan Ke Za Zhi, vol. 54, no. 12, 2019, pp. 833-839.
Zheng W, Zhang L, Tian ZH, et al. [Analysis of population attributable risk of large for gestational age]. Zhonghua Fu Chan Ke Za Zhi. 2019;54(12):833-839.
Zheng, W., Zhang, L., Tian, Z. H., Zhang, T., Wang, T., Yan, Q., Li, G. H., & Zhang, W. Y. (2019). [Analysis of population attributable risk of large for gestational age]. Zhonghua Fu Chan Ke Za Zhi, 54(12), 833-839. https://doi.org/10.3760/cma.j.issn.0529-567x.2019.12.007
Zheng W, et al. [Analysis of Population Attributable Risk of Large for Gestational Age]. Zhonghua Fu Chan Ke Za Zhi. 2019 Dec 25;54(12):833-839. PubMed PMID: 31874473.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - [Analysis of population attributable risk of large for gestational age]. AU - Zheng,W, AU - Zhang,L, AU - Tian,Z H, AU - Zhang,T, AU - Wang,T, AU - Yan,Q, AU - Li,G H, AU - Zhang,W Y, PY - 2019/12/26/entrez PY - 2019/12/26/pubmed PY - 2020/1/4/medline KW - Birth weight KW - Fetal macrosomia KW - Obesity KW - Pregnancy KW - Risk factors KW - Weight gain SP - 833 EP - 839 JF - Zhonghua fu chan ke za zhi JO - Zhonghua Fu Chan Ke Za Zhi VL - 54 IS - 12 N2 - Objective: To examine the association of pre-pregnancy obesity, excessive gestational weight gain (GWG) and gestational diabetes mellitus (GDM) with the risk of large for gestational age (LGA), and assess the dynamic changes in population attributable risk percent (PAR%) for having these exposures. Methods: A retrospective cohort study was conducted to collect data on pregnant women who received regular health care and delivered in Beijing Obstetrics and Gynecology Hospital from January to December in 2011, 2014 and 2017, respectively. Information including baseline characteristics, metabolic indicators during pregnancy, pregnancy complications, and pregnancy outcomes were collected. Multivariate logistic regression model was constructed to assess their association with LGA delivery. Adjusted relative risk and prevalence of these factors were used to calculate PAR%and evaluate the comprehensive risk. Results: (1)The number of participants were 11 132, 13 167 and 4 973 in 2011, 2014 and 2017, respectively. Corresponding prevalence of LGA were 15.19% (1 691/11 132), 14.98% (1 973/13 167) and 16.21% (806/4 973). No significant change in the prevalence of LGA was observed across all years investigated (all P>0.05). (2)According to results from multivariate logistic regression model, advanced maternal age, multiparity, pre-pregnancy overweight or obesity, GWG,GDM and serum triglyceride level≥1.7 mmol/L in the first trimester were associated with high risk of LGA (all P<0.05). Among these factors, pre-pregnancy overweight or obesity, excessive GWG and multiparity were common risk factors of LGA. GDM was not associated with risk of LGA in 2017 database. (3) Dynamic change of PAR% in these years were notable. PAR% of GWG for LGA decreased (32.6%, 27.2% and 22.2% in 2011, 2014 and 2017, respectively), while PAR% of pre-pregnancy overweight or obesity showed an upward trend (4.2%, 3.3% and 8.4%). In addition, PAR% of multiparity increased as well (3.5%, 6.3% and 15.9%). (4) Further analysis showed that excessive GWG in the first and second trimesters contributed the most (20.2% and 19.0% in 2014 and 2017). Conclusions: Excessive GWG, pre-pregnancy overweight or obesity and multiparity are the important risk factors what contribute to LGA. PAR% of excessive GWG for LGA decrease in recent years. However, GWG in the first and second trimesters is a critical factor of LGA. Appropriate weight management in pre-pregnancy, the first or second trimester is the key point to reduce the risk of LGA. SN - 0529-567X UR - https://www.unboundmedicine.com/medline/citation/31874473/[Analysis_of_population_attributable_risk_of_large_for_gestational_age]_ L2 - http://journal.yiigle.com/LinkIn.do?linkin_type=pubmed&amp;issn=0529-567X&amp;year=2019&amp;vol=54&amp;issue=12&amp;fpage=833 DB - PRIME DP - Unbound Medicine ER -