J Korean Med Sci.  2021 Nov;36(44):e281. 10.3346/jkms.2021.36.e281.

Validation of a Strict Obesity Definition Proposed for Asians to Predict Adverse Pregnancy Outcomes in Korean Pregnant Women

• Kim SY
• Oh Sy
• Sung JH
• Choi SJ
• Roh CR
• Lee SM
• Jun JK
• Lee MY
• Lee J
• Kim SH
• Cha DH
• Han YJ
• Kim MH
• Cho GJ
• Kwon HS
• Kim BJ
• Park MH
• Cho HY
• Ko HS
• Shim JY
• Ryu HM

• KMID: 2522360
• DOI: http://doi.org/10.3346/jkms.2021.36.e281

Abstract

Background
People are generally considered overweight and obese if their body mass index (BMI) is above 25 kg/m 2 and 30.0 kg/m 2 , respectively. The World Health Organization proposed stricter criteria for Asians (≥ 23 kg/m² : overweight, ≥ 25 kg/m² : obese). We aimed to verify whether this criteria could predict adverse pregnancy outcomes in Korean women.
Methods
We included 7,547 Korean women from 12 institutions enrolled between June 2016 and October 2018. Women with no pre-pregnancy BMI data, not Korean, or lost to followup were excluded, leaving 6,331. The subjects were categorized into underweight, normal, overweight, class I obesity, and class II/III obesity based on a pre-pregnancy BMI of < 18.5, 18.5–22.9, 23.0–24.9, 25.0–29.9, and ≥ 30.0 kg/m² , respectively.
Results
Overall, 13.4%, 63.0%, 11.8%, 9.1%, and 2.6% of women were underweight, normal, and overweight and had class I obesity and class II/III obesity, respectively. In the multivariable analysis adjusted for maternal age, a higher BMI significantly increased the risk of preeclampsia, gestational diabetes, preterm delivery caused by maternal-fetal indications, cesarean section, large for gestational age, and neonatal intensive care unit admission.
Conclusion
Adverse pregnancy outcomes started to increase in those with a pre-pregnancy BMI ≥ 23.0 kg/m² after adjusting for maternal age. The modified obesity criteria could help predict adverse pregnancy outcomes in Koreans.

Keyword

Pregnancy; Maternal Obesity; Asian; Obesity; Neonatal

Figure

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  Fig. 1 Adjusted odds ratios and 95% confidence intervals for each of the adverse pregnancy and neonatal outcomes according to the increase of maternal obesity: (A) Preeclampsia, (B) GDM, (C) Cesarean section, (D) large for gestational age, (E) birth weight of 4 kg or more, and (F) neonatal ICU admission.aOR = adjusted odds ratio, GDM = gestational diabetes mellitus, ICU = intensive care unit.

Reference

1. World Health Organization (WHO). Obesity and overweight. Updated 2020. Accessed April 2, 2021. https://www.who.int/news-room/fact-sheets/detail/obesity-and-overweight .

2. Hales CM, Carroll MD, Fryar CD, Ogden CL. Prevalence of obesity and severe obesity among adults: United States, 2017–2018. NCHS Data Brief. 2020; (360):1–8.

3. Korean Statistical Information Service (KOSIS). The annual birth data in Korea. Updated 2017. Accessed April 2, 2021. http://kosis.kr/statHtml/statHtml.do?orgId=350&tblId=TX_35001_A061&conn_path=I2 .

4. Long MT, Fox CS. The Framingham Heart Study--67 years of discovery in metabolic disease. Nat Rev Endocrinol. 2016; 12(3):177–183. PMID: 26775764.

5. Schummers L, Hutcheon JA, Bodnar LM, Lieberman E, Himes KP. Risk of adverse pregnancy outcomes by prepregnancy body mass index: a population-based study to inform prepregnancy weight loss counseling. Obstet Gynecol. 2015; 125(1):133–143. PMID: 25560115.

6. World Health Organization (WHO). Obesity: preventing and managing the global epidemic. Updated 2000. Accessed March 5, 2020. https://apps.who.int/iris/handle/10665/42330 .

7. Ko GT, Chan JC, Cockram CS, Woo J. Prediction of hypertension, diabetes, dyslipidaemia or albuminuria using simple anthropometric indexes in Hong Kong Chinese. Int J Obes Relat Metab Disord. 1999; 23(11):1136–1142. PMID: 10578203.

8. Deurenberg P, Yap M, van Staveren WA. Body mass index and percent body fat: a meta analysis among different ethnic groups. Int J Obes Relat Metab Disord. 1998; 22(12):1164–1171. PMID: 9877251.

9. World Health Organization (WHO). The Asia-Pacific perspective: redefining obesity and its treatment. Updated 2000. Accessed March 5, 2020. https://apps.who.int/iris/handle/10665/206936 .

10. Korean Diabetes Association. Treatment Guideline for Diabetes 2019. 6th ed. Seoul, Korea: Korean Diabetes Association;2019.

11. Korean Society for the Study of Obesity. Guideline for the Management of Obesity 2019. 6th ed. Seoul, Korea: Korean Society for the Study of Obesity;2018.

12. WHO Expert Consultation. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet. 2004; 363(9403):157–163. PMID: 14726171.

13. Park JH, Lee BE, Park HS, Ha EH, Lee SW, Kim YJ. Association between pre-pregnancy body mass index and socioeconomic status and impact on pregnancy outcomes in Korea. J Obstet Gynaecol Res. 2011; 37(2):138–145. PMID: 21159038.

14. Lim J, Han K, Kim SY, Cho YH, Yoon YS, Park HS, et al. Effects of central obesity on maternal complications in Korean women of reproductive age. Obes Res Clin Pract. 2019; 13(2):156–163. PMID: 30910529.

15. Kim SY, Lee SM, Jun JK, Han YJ, Kim MH, Shim JY, et al. Prospective observations study protocol to investigate cost-effectiveness of various prenatal test strategies after the introduction of noninvasive prenatal testing. BMC Pregnancy Childbirth. 2018; 18(1):307. PMID: 30041617.

16. Fenton TR, Kim JH. A systematic review and meta-analysis to revise the Fenton growth chart for preterm infants. BMC Pediatr. 2013; 13(1):59. PMID: 23601190.

17. Misra A, Khurana L. Obesity-related non-communicable diseases: South Asians vs White Caucasians. Int J Obes. 2011; 35(2):167–187.

18. Goel K, Misra A, Vikram NK, Poddar P, Gupta N. Subcutaneous abdominal adipose tissue is associated with the metabolic syndrome in Asian Indians independent of intra-abdominal and total body fat. Heart. 2010; 96(8):579–583. PMID: 20357386.

19. Araneta MR, Kanaya AM, Hsu WC, Chang HK, Grandinetti A, Boyko EJ, et al. Optimum BMI cut points to screen Asian Americans for type 2 diabetes. Diabetes Care. 2015; 38(5):814–820. PMID: 25665815.

20. Lin WY, Lee LT, Chen CY, Lo H, Hsia HH, Liu IL, et al. Optimal cut-off values for obesity: using simple anthropometric indices to predict cardiovascular risk factors in Taiwan. Int J Obes Relat Metab Disord. 2002; 26(9):1232–1238. PMID: 12187401.

21. Ito H, Nakasuga K, Ohshima A, Maruyama T, Kaji Y, Harada M, et al. Detection of cardiovascular risk factors by indices of obesity obtained from anthropometry and dual-energy X-ray absorptiometry in Japanese individuals. Int J Obes Relat Metab Disord. 2003; 27(2):232–237. PMID: 12587004.

22. Morisaki N, Nagata C, Jwa SC, Sago H, Saito S, Oken E, et al. Pre-pregnancy BMI-specific optimal gestational weight gain for women in Japan. J Epidemiol. 2017; 27(10):492–498. PMID: 28579106.

23. Chen CN, Chen HS, Hsu HC. Maternal prepregnancy body mass index, gestational weight gain, and risk of adverse perinatal outcomes in Taiwan: a population-based birth cohort study. Int J Environ Res Public Health. 2020; 17(4):E1221. PMID: 32074959.

24. Liu P, Xu L, Wang Y, Zhang Y, Du Y, Sun Y, et al. Association between perinatal outcomes and maternal pre-pregnancy body mass index. Obes Rev. 2016; 17(11):1091–1102. PMID: 27536879.

25. Kesavan K, Devaskar SU. Intrauterine growth restriction: postnatal monitoring and outcomes. Pediatr Clin North Am. 2019; 66(2):403–423. PMID: 30819345.