The Born in Guangzhou Cohort Study (BIGCS)

Abstract

The Born in Guangzhou Cohort Study (BIGCS) is a large-scale prospective observational study investigating the role of social, biological and environmental influences on pregnancy and child health and development in an urban setting in southern China. Pregnant women who reside in Guangzhou and who attend Guangzhou Women and Children’s Medical Center (GWCMC) for antenatal care in early pregnancy (<20 weeks’ gestation) are eligible for inclusion. Study recruitment commenced in February 2012, with an overall participation rate of 76.3%. Study recruitment will continue until December 2018 to achieve the target sample size of 30,000 mother–child pairs. At 30 April 2016, a total of 75,422 questionnaires have been collected, while 14,696 live births have occurred with planned follow-up of cohort children until age 18 years. During the same period a total of 1,053,000 biological samples have been collected from participants, including maternal, paternal and infant blood, cord blood, placenta, umbilical cord, and maternal and infant stool samples. The dataset has been enhanced by record linkage to routine health and administrative records. We plan future record linkage to school enrolment and national examination records.

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References

  1. 1.

    Wang Y, Li X, Zhou M, Luo S, Liang J, Liddell CA, et al. Under-5 mortality in 2851 Chinese counties, 1996–2012: a subnational assessment of achieving MDG 4 goals in China. Lancet. 2015;387(10015):273-83. doi:10.1016/S0140-6736(15)00554-1.

    Article  PubMed  Google Scholar 

  2. 2.

    Kassebaum NJ, Bertozzi-Villa A, Coggeshall MS, Shackelford KA, Steiner C, Heuton KR, et al. Global, regional, and national levels and causes of maternal mortality during 1990-2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet. 2014;384(9947):980–1004. doi:10.1016/S0140-6736(14)60696-6.

    Article  PubMed  PubMed Central  Google Scholar 

  3. 3.

    National Health and Family Planning Commission of the People’s Republic of China. Statistics of Health and Family Planning in 2015. http://www.nhfpc.gov.cn/ewebeditor/uploadfile/2016/0820160805160410398 pdf. (in Chinese). Accessed 11 Aug 2016.

  4. 4.

    Statistics Bureau of Guangzhou Municipality. Principal Aggregate Indicators on National Economic and Social Development and Growth Rates in Annual Statistics of 2015. http://data.gzstats.gov.cn/gzStat1/chaxun/njsj.jsp. Accessed 16 April 2016.

  5. 5.

    Qiu J, He X, Cui H, Zhang C, Zhang H, Dang Y, et al. Passive smoking and preterm birth in urban China. Am J Epidemiol. 2014;180(1):94–102. doi:10.1093/aje/kwu092.

    Article  PubMed  PubMed Central  Google Scholar 

  6. 6.

    Tao FB, Hao JH, Huang K, Su PY, Cheng DJ, Xing XY, et al. Cohort Profile: the China-Anhui birth cohort study. Int J Epidemiol. 2013;42(3):709–21. doi:10.1093/ije/dys085.

    Article  PubMed  Google Scholar 

  7. 7.

    Yuan MY, He JR, Chen NN, Lu JH, Shen SY, Xiao WQ, et al. Validity and reproducibility of a dietary questionnaire for consumption frequencies of foods during pregnancy in the born in Guangzhou Cohort Study (BIGCS). Nutrients. 2016;. doi:10.3390/nu8080454.

    Google Scholar 

  8. 8.

    Zung WW. A self-rating depression scale. Arch Gen Psychiatry. 1965;12:63–70.

    CAS  Article  PubMed  Google Scholar 

  9. 9.

    Zung WW. A rating instrument for anxiety disorders. Psychosomatics. 1971;12(6):371–9. doi:10.1016/s0033-3182(71)71479-0.

    CAS  Article  PubMed  Google Scholar 

  10. 10.

    Lee DT, Yip SK, Chiu HF, Leung TY, Chan KP, Chau IO, et al. Detecting postnatal depression in Chinese women. Validation of the Chinese version of the Edinburgh Postnatal Depression Scale. Br J Psychiatry J Mental Sci. 1998;172:433–7.

    CAS  Article  Google Scholar 

  11. 11.

    Wei M, Bian X, Squires J, Yao G, Wang X, Xie H, et al. Studies of the norm and psychometrical properties of the ages and stages questionnaires, third edition, with a Chinese national sample. Chin J Pediatrics. 2015;53(12):913–8.

    Google Scholar 

  12. 12.

    Group BMDC. Gesell developmental diagnosis scale. Beijing: Beijing Mental Development Cooperative Group; 1985.

    Google Scholar 

  13. 13.

    Nation Bureau of Statistics of China. Annual data. http://data.stats.gov.cn/index.htm. Accessed 15 Feb 2017.

  14. 14.

    Metzger BE, Lowe LP, Dyer AR, Trimble ER, Chaovarindr U, Coustan DR, et al. Hyperglycemia and adverse pregnancy outcomes. N Engl J Med. 2008;358(19):1991–2002. doi:10.1056/NEJMoa0707943.

    Article  PubMed  Google Scholar 

  15. 15.

    Metzger BE, Gabbe SG, Persson B, Buchanan TA, Catalano PA, Damm P, et al. International association of diabetes and pregnancy study groups recommendations on the diagnosis and classification of hyperglycemia in pregnancy. Diabetes Care. 2010;33(3):676–82. doi:10.2337/dc09-1848.

    Article  PubMed  Google Scholar 

  16. 16.

    Shen S, Lu J, Zhang L, He J, Li W, Chen N, et al. Single fasting plasma glucose measurement compared with 75 g oral glucose-tolerance test in prediction of adverse perinatal outcomes: a prospective cohort study from China. Lancet. 2016;388(Suppl 1):S8. doi:10.1016/S0140-6736(16)31935-3.

    Article  PubMed  Google Scholar 

  17. 17.

    Zhang C, Ning Y. Effect of dietary and lifestyle factors on the risk of gestational diabetes: review of epidemiologic evidence. Am J Clin Nutr. 2011;94(6 Suppl):1975S–9S. doi:10.3945/ajcn.110.001032.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  18. 18.

    He JR, Yuan MY, Chen NN, Lu JH, Hu CY, Mai WB, et al. Maternal dietary patterns and gestational diabetes mellitus: a large prospective cohort study in China. Br J Nutr. 2015;113(8):1292–300. doi:10.1017/S0007114515000707.

    CAS  Article  PubMed  Google Scholar 

  19. 19.

    Shen SY, Lu JH, He JR, Liu Y, Chen NN, Yuan MY, et al. Progesterone use in early pregnancy: a prospective birth cohort study in China. Lancet. 2015;. doi:10.1016/S0140-6736(15)00639-X.

    Google Scholar 

  20. 20.

    He JR, Liu Y, Lu JH, Shen SY, Li WD, Guo Y, et al. Passive smoking during pregnancy undermines maternal mental health: results from the Born in Guangzhou Cohort Study, China. Poster Abstract. The Lancet and Chinese Academy of Medical Sciences (CAMS) Health Summit; Beijing, China; 2015.

  21. 21.

    Lu JH, Guo Y, Shen SY, Hu F, Chen NN, Wu YF, et al. Association between inflammatory reaction at late pregnancy and the risk of postpartum depression: a prospective cohort stud. Chin J Woman Child Health Res. 2014;25(3):391–3.

    Google Scholar 

  22. 22.

    Swanson JM, Entringer S, Buss C, Wadhwa PD. Developmental origins of health and disease: environmental exposures. Sem Reprod Med. 2009;27(5):391–402. doi:10.1055/s-0029-1237427.

    CAS  Article  Google Scholar 

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Acknowledgements

We are grateful to the pregnant women who have participated in BIGCS and all obstetric care providers who have assisted us in the implementation of the study. We especially want to thank Professor Charles Larson for useful comments on the project. BIGCS study is supported by the National Natural Science Foundation of China (81673181), the Guangzhou Science Technology and Innovation Commission (201508030037, 2014A020213022), and the Guangdong Provincial Department of Science and Technology (2012J5100038).

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Correspondence to Kar Keung Cheng or Hui-Min Xia.

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The authors declare that they have no conflict of interest.

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Xiu Qiu, Jin-Hua Lu and Jian-Rong He have contributed equally to this work.

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Qiu, X., Lu, J., He, J. et al. The Born in Guangzhou Cohort Study (BIGCS). Eur J Epidemiol 32, 337–346 (2017). https://doi.org/10.1007/s10654-017-0239-x

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Keywords

  • Design
  • Cohort study
  • Child
  • Pregnancy
  • Record linkage