Reproductive Biology and Endocrinology (Aug 2018)

Using appropriate pre-pregnancy body mass index cut points for obesity in the Chinese population: a retrospective cohort study

  • Yanxin Wu,
  • Wai-Kit Ming,
  • Dongyu Wang,
  • Haitian Chen,
  • Zhuyu Li,
  • Zilian Wang

DOI
https://doi.org/10.1186/s12958-018-0397-z
Journal volume & issue
Vol. 16, no. 1
pp. 1 – 7

Abstract

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Abstract Background Appropriate classification of obesity is vital for risk assessment and complication prevention during pregnancy. We aimed to explore which pre-pregnancy BMI cut-offs of obesity, either BMI ≥ 25 kg/m2 as recommended by the WHO for Asians or BMI ≥ 28 kg/m2 as suggested by the Working Group on Obesity in China (WGOC), best predicts the risk of adverse maternal and perinatal outcomes. Methods We retrospectively reviewed 11,494 medical records for live singleton deliveries in a tertiary center in Guangzhou, China, between January 2013 and December 2016. The primary outcomes included maternal obesity prevalence, adverse maternal and perinatal outcomes. Data were analyzed using the Chi-square test, logistic regression, and diagnostics tests. Results Among the study population, 824 (7.2%) were obese according to the WHO criteria for Asian populations, and this would be reduced to 198 (1.7%) based on the criteria of WGOC. Obesity-related adverse maternal and perinatal outcomes were gestational diabetes mellitus, preeclampsia, cesarean section, and large for gestational age (P < 0.05). Compared to the WGOC criterion, the WHO for Asians criterion had a higher Youden index in our assessment of its predictive value in identifying risk of obesity-related adverse outcomes for Chinese pregnant women. Women in the BMI range of 25 to 28 kg/m2 are at high risks for adverse maternal and perinatal outcomes, which were similar to women with BMI ≥ 28 kg/m2. Conclusions A lower pre-pregnancy BMI cutoff at 25 kg/m2 for defining obesity may be appropriate for pregnant women in South China. If WGOC standards are applied to pregnant Chinese populations, a significant proportion of at-risk patients may be missed.

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