Proximate Determinants of Fertility in Japan

  • Shoko Konishi
  • Emi Tamaki
Part of the SpringerBriefs in Population Studies book series (BRIEFSPOPULAT)


Proximate determinants link both social and biological factors to fertility. In this section, we will summarize available data related to proximate determinants of fertility in Japan while referring to some of the related literature targeting populations overseas. In addition to data from published studies, we present our original data collected in the biodemography project, an Internet-based cross-sectional survey on reproductive history conducted in 2014 targeting Japanese women between 20 and 44 years of age. Following Wood’s conceptualization, the specific components of the proximate determinants of fertility referred to in this chapter are lactational infecundability, fecund waiting time to conception, and fetal loss (both spontaneous and induced). Additionally, papers on factors that are expected to significantly affect fecund waiting time to conception, i.e., frequency of sexual intercourse, length and regularity of menstrual cycle, and use of contraception and infertility treatment, will be reviewed.


Internet-based survey Lactational amenorrhea Menstrual cycle Time to pregnancy (TTP) Assisted reproductive technology (ART) Japan 


  1. 1.
    Konishi, Shoko, and Emi Tamaki. 2016. Pregnancy intention and contraceptive use among married and unmarried women in Japan. Japanese Journal of Health and Human Ecology 82: 110–124.CrossRefGoogle Scholar
  2. 2.
    Slama, Rémy, Beatrice Ducot, Lisbeth Carstensen, Christine Lorente, Elise De La Rochebrochard, Henri Leridon, Niels Keiding, and Jean Bouyer. 2006. Feasibility of the current-duration approach to studying human fecundity. Epidemiology 17: 440–449.Google Scholar
  3. 3.
    Slama, R., O.K.H. Hansen, B. Ducot, A. Bohet, D. Sorensen, L. Giorgis Allemand, M.J.C. Eijkemans, et al. 2012. Estimation of the frequency of involuntary infertility on a nation-wide basis. Human Reproduction 27: 1489–1498.CrossRefGoogle Scholar
  4. 4.
    Huybrechts, Krista F., Ellen M. Mikkelsen, Tina Christensen, Anders H. Riis, Elizabeth E. Hatch, Lauren A. Wise, Henrik Toft Sørensen, and Kenneth J. Rothman. 2010. A successful implementation of e-epidemiology: The Danish pregnancy planning study “Snart-Gravid”. European Journal of Epidemiology 25: 297–304.CrossRefGoogle Scholar
  5. 5.
    Wise, Lauren A., Kenneth J. Rothman, Ellen M. Mikkelsen, Joseph B. Stanford, Amelia K. Wesselink, Craig McKinnon, Siobhan M. Gruschow, et al. 2015. Design and conduct of an Internet-based preconception cohort study in North America: Pregnancy Study Online. Paediatric and Perinatal Epidemiology 29: 360–371.CrossRefGoogle Scholar
  6. 6.
    Hatch, Elizabeth E., Kristen A. Hahn, Lauren A. Wise, Ellen M. Mikkelsen, Ramya Kumar, Matthew P. Fox, Daniel R. Brooks, Anders H. Riis, Henrik Toft Sorensen, and Kenneth J. Rothman. 2016. Evaluation of selection bias in an Internet-based study of pregnancy planners. Epidemiology 27: 98–104.CrossRefGoogle Scholar
  7. 7.
    Mita, Fusami. 1984. Methed of infant feeding and postpartum amenorrhea. (Nyuji no eiyo houho to sango no amenoria). Journal of Population Problems 169: 43–46. (in Japanese).Google Scholar
  8. 8.
    Smith, David P. 1985. Breastfeeding, contraception, and birth intervals in developing countries. Studies in Family Planning 16: 154–163.CrossRefGoogle Scholar
  9. 9.
    Iwasawa, Miho, and Fusami Mita. 2007. Delayed childbeaing and the changing age composition of women who desire children (Bansanka to Kyojikibo josei jinkou no koreika). Journal of Population Problems 63: 24–41. (in Japanese).Google Scholar
  10. 10.
    Ministry of Health, Labour and Welfare. 2016. Brief report on the National Nutrition Survey on preschool children, 2015 (Heisei 27 nendo nyuyoji eiyo chosa kekka no gaiyo). (in Japanese).Google Scholar
  11. 11.
    Kono, Shigemi, and Yoshikazu Watanabe. 1983. Bio-demographic conditions of fertility: An analysis of the 1981 field survey of fertility. Journal of Population Problems 167: 1–17. (in Japanese).Google Scholar
  12. 12.
    Tsuya, Noriko. 2009. Why does Japanese population decrease? Women, low fertility, and singlehood (Naze wagakuni no jinko wa gensho surunoka –josei, shosika, mikonka. In Population decline and Japanese economy (Jinko gensho to nihon keizai), ed. Noriko Tsuya, and Yoshio Higuchi, 3–52. Tokyo: Nikkei Publishing Inc.Google Scholar
  13. 13.
    Inoue, Madoka, Colin W. Binns, Keiko Otsuka, Masamine Jimba, and Manami Matsubara. 2012. Infant feeding practices and breastfeeding duration in Japan: A review. International Breastfeeding Journal 7: 15.
  14. 14.
    Victora, Cesar G., Rajiv Bahl, Aluísio J.D. Barros, Giovanny V.A. França, Susan Horton, Julia Krasevec, Simon Murch, Mari Jeeva Sankar, Neff Walker, and Nigel C. Rollins. 2016. Breastfeeding in the 21st century: epidemiology, mechanisms, and lifelong effect. The Lancet 387: 475–490.CrossRefGoogle Scholar
  15. 15.
    Shinoda, Tadasu. 1939. Fecundability and infertility among Japanese women (Honpou fujin no ninnyouritsu tokuni funinsho ni tsuite). Chiryou oyobi shohou 20: 99–103. (in Japanese).Google Scholar
  16. 16.
    Arakawa, Chikako. 2005. Effect of environmental chemical exposure on fecundity through fish consumption: A study using time to pregnancy. Dissertation, The University of Tokyo.Google Scholar
  17. 17.
    Arakawa, Chikako, Jun Yoshinaga, Kunihiro Okamura, Kunihiko Nakai, and Hiroshi Satoh. 2006. Fish consumption and time to pregnancy in Japanese women. International Journal of Hygiene and Environmental Health 209: 337–344.CrossRefGoogle Scholar
  18. 18.
    Juhl, M., A.M. Nyboe Andersen, M. Grønbaek, and J. Olsen. 2001. Moderate alcohol consumption and waiting time to pregnancy. Human Reproduction 16: 2705–2709.CrossRefGoogle Scholar
  19. 19.
    Tuntiseranee, P., J. Olsen, V. Chongsuvivatwong, and S. Limbutara. 1998. Fecundity in Thai and European regions: Results based on waiting time to pregnancy. Human Reproduction 13: 471–477. (Oxford University Press).CrossRefGoogle Scholar
  20. 20.
    Konishi, Shoko, Soyoko Sakata, Mari S. Oba, and Kathleen A. O’Connor. Age and time to pregnancy for the first child among couples in Japan. The Journal of Population Studies (in press).Google Scholar
  21. 21.
    Moriki, Yoshie, Kenji Hayashi, and Rikiya Matsukura. 2015. Sexless marriages in Japan: Prevalence and reasons. In Low fertility and reproductive health in East Asia, ed. Naohiro Ogawa, and Iqbal H. Shah, 161–186. Dordrecht: Springer.Google Scholar
  22. 22.
    Eisenberg, Michael L., Alan W. Shindel, James F. Smith, Benjamin N. Breyer, and Larry I. Lipshultz. 2010. Socioeconomic, anthropomorphic, and demographic predictors of adult sexual activity in the United States: Data from the National Survey of Family Growth. The Journal of Sexual Medicine 7: 50–58.CrossRefGoogle Scholar
  23. 23.
    Hassan, Mohamed A.M., and Stephen R. Killick. 2004. Negative lifestyle is associated with a significant reduction in fecundity. Fertility and Sterility 81: 384–392.CrossRefGoogle Scholar
  24. 24.
    Rothman, Kenneth J., Lauren A. Wise, Henrik T. Sørensen, Anders H. Riis, Ellen M. Mikkelsen, and Elizabeth E. Hatch. 2013. Volitional determinants and age-related decline in fecundability: A general population prospective cohort study in Denmark. Fertility and Sterility 99: 1958–1964.CrossRefGoogle Scholar
  25. 25.
    Tsukamoto, Yutaka. 1955. Actual situation of sex life among married women in agricultural villages (Noson kikonfujin seiseikatsu no jittai). Sanfujinka no sekai 7: 57–64. (in Japanese).Google Scholar
  26. 26.
    Sato, Ryuzaburo, and Miho Iwasawa. 2015. The sexual behavior of adolescents and young adults in Japan. In Low fertility and reproductive health in East Asia, ed. Naohiro Ogawa, and Iqbal H. Shah, 137–159. Dordrecht: Springer.Google Scholar
  27. 27.
    Genda, Yuji, and Atsushi Kawakami. 2006. Employment bipolarization and sexual behavior (Shugyo nikyokuka to seikodo). Nihon rodo kenkyu zasshi 556: 80–91. (in Japanese).Google Scholar
  28. 28.
    Wise, Lauren A., Ellen M. Mikkelsen, Kenneth J. Rothman, Anders H. Riis, Henrik Toft Sørensen, Krista F. Huybrechts, and Elizabeth E. Hatch. 2011. A prospective cohort study of menstrual characteristics and time to pregnancy. American Journal of Epidemiology 174: 701–709.CrossRefGoogle Scholar
  29. 29.
    Harlow, Siobán D. 2000. Menstruation and menstrual disorders. The epidemiology of menstruation and menstrual dysfunction. In Women and health, ed. M.B. Goldman, and M.C. Hatch, 99–113. San Diego, CA: Academic Press.CrossRefGoogle Scholar
  30. 30.
    Small, Chanley M., Amita K. Manatunga, Mitchel Klein, Heather S. Feigelson, Celia E. Dominguez, Ruth McChesney, and Michele Marcus. 2006. Menstrual cycle characteristics: Associations with fertility and spontaneous abortion. Epidemiology 17: 52–60.CrossRefGoogle Scholar
  31. 31.
    Mutsaerts, M.A.Q., H. Groen, H.G. Huiting, W.K.H. Kuchenbecker, P.J.J. Sauer, J.A. Land, R.P. Stolk, and A. Hoek. 2012. The influence of maternal and paternal factors on time to pregnancy—A Dutch population-based birth-cohort study: The GECKO Drenthe study. Human Reproduction 27: 583–593.CrossRefGoogle Scholar
  32. 32.
    Japan Society of Obstetrics and Gynecology. 2013. Glossary of obstetrics and gynecology. Tokyo: Japan Society of Obstetrics and Gynecology.Google Scholar
  33. 33.
    Matsumoto, Seiichi, Yasuji Nogami, and Shigeo Ohkuri. 1962. Statistical studies on menstruation; a criticism on the definition of normal menstruation. Gunma Journal of Medical Sciences 11: 294–318.Google Scholar
  34. 34.
    Jensen, T.K., T. Scheike, and N. Keiding. 1999. Fecundability in relation to body mass and menstrual cycle patterns. Epidemiology 10: 422–428.CrossRefGoogle Scholar
  35. 35.
    Wesselink, Amelia K., Lauren A. Wise, Elizabeth E. Hatch, Kenneth J. Rothman, Ellen M. Mikkelsen, Joseph B. Stanford, Craig J. McKinnon, and Shruthi Mahalingaiah. 2016. Menstrual cycle characteristics and fecundability in a North American preconception cohort. Annals of Epidemiology 26: 482–487.CrossRefGoogle Scholar
  36. 36.
    Rowland, Andrew S., Donna Day Baird, Stuart Long, Ganesa Wegienka, Siobán D. Harlow, Michael Alavanja, and Dale P. Sandler. 2002. Influence of medical conditions and lifestyle factors on the menstrual cycle. Epidemiology 13: 668–674.CrossRefGoogle Scholar
  37. 37.
    Mihm, M., S. Gangooly, and S. Muttukrishna. 2011. The normal menstrual cycle in women. Animal Reproduction Science 124: 229–236.CrossRefGoogle Scholar
  38. 38.
    Harlow, S.D., and S.A. Ephross. 1995. Epidemiology of menstruation and its relevance to women’s health. Epidemiologic Reviews 17: 265–286.CrossRefGoogle Scholar
  39. 39.
    National Institute of Population and Social Security Research. 2016. 15th Japanese national fertility survey. Tokyo: National Institute of Population and Social Security Research.Google Scholar
  40. 40.
    Japan Family Planning Association, Inc. 2012. The 6th survey on lifestyle and awareness of men and women.Google Scholar
  41. 41.
    Raymo, J.M., and M. Iwasawa. 2008. Bridal pregnancy and spouse pairing patterns in Japan. Journal of Marriage and Family 70: 847–860.CrossRefGoogle Scholar
  42. 42.
    Veltman-Verhulst, Susanne M., Edward Hughes, Reuben Olugbenga Ayeleke, and Ben J. Cohlen. 2016. Intra-uterine insemination for unexplained subfertility. In Cochrane database of systematic reviews, ed. Susanne M. Veltman-Verhulst.
  43. 43.
    Pandian, Zabeena, Ahmed Gibreel, and Siladitya Bhattacharya. 2015. In vitro fertilisation for unexplained subfertility. In Cochrane database of systematic reviews, ed. Zabeena Pandian.
  44. 44.
    Dyer, S., G.M. Chambers, J. de Mouzon, K.G. Nygren, F. Zegers-Hochschild, R. Mansour, O. Ishihara, M. Banker, and G.D. Adamson. 2016. International Committee for Monitoring Assisted Reproductive Technologies world report: Assisted Reproductive Technology 2008, 2009 and 2010. Human Reproduction 31: 1588–1609.CrossRefGoogle Scholar
  45. 45.
    National Institute of Population and Social Security Research. 2011. The 14th National Fertility Survey: Summary of the couple survey.Google Scholar
  46. 46.
    Hayashi, Reiko. 2015. Demographic impact of assisted reproductive technology (Seishoku hojo iryo no jinkougakuteki inpakuto). Igaku no Ayumi 254: 185–188. (in Japanese).Google Scholar
  47. 47.
    Japan Society of Obstetrics and Gynecology. 2012. ART Data Book 2012. Accessed 13 Oct 2017.
  48. 48.
    Leridon, Henri. 2004. Can assisted reproduction technology compensate for the natural decline in fertility with age? A model assessment. Human Reproduction 19: 1548–1553.CrossRefGoogle Scholar
  49. 49.
    Juul, Svend, Niels Keiding, Mads Tvede, and European Infertility. 2000. Retrospectively sampled time-to-pregnancy data may make age-decreasing fecundity look increasing. Epidemiology 11: 717–719.CrossRefGoogle Scholar
  50. 50.
    Steiner, Anne Z., and Anne Marie Z. Jukic. 2016. Impact of female age and nulligravidity on fecundity in an older reproductive age cohort. Fertility and Sterility 105: 1584–1588.CrossRefGoogle Scholar
  51. 51.
    World Health Organization. 2016. Maternal, newborn, child and adolescent health. Stillbirths. Accessed 27 Sept 2016.
  52. 52.
    Centers for Disease Control and Prevention. 2016. Facts about Stillbirth. Accessed 27 Sept.
  53. 53.
    Senda, Yukiko. 2011. Increasing pregnancy attempt age and decreasing children -fertility decline as an unintended consequence. Journal of Population Problems 67: 22–38.Google Scholar
  54. 54.
    National Institute of Population and Social Security Research. 2016. Marriage and Childbirth in Japan Today: The fifteenth Japanese national fertility survey, 2015 (Results of singles and married couples survey). Tokyo: National Institute of Population and Social Security Research. (in Japanese).Google Scholar
  55. 55.
    Sedgh, Gilda, Susheela Singh, Iqbal H. Shah, Elisabeth Ahman, Stanley K. Henshaw, and Akinrinola Bankole. 2012. Induced abortion: Incidence and trends worldwide from 1995 to 2008. Lancet 379: 625–632.CrossRefGoogle Scholar
  56. 56.
    Ministry of Internal Affairs and Communications. 2015. Table 2-12 Population 15 years old and over by age group and marital status (1975–2010). Accessed 23 Feb 2015.
  57. 57.
    National Institute of Population and Social Security Research. 2011. The fourteenth Japanese National Fertility Survey in 2010: Attitudes toward marriage and family among Japanese singles (November 2011). Tokyo: National Institute of Population and Social Security Research. Accessed 13 Oct 2017.
  58. 58.
    National Institute of Population and Social Security Research. 2007. Report on the thirteenth Japanese National Fertility Survey in 2005, volume I Marriage process and fertility of Japanese married couples, 203–207. Tokyo: National Institute of Population and Social Security Research. (in Japanese). Accessed 13 Oct 2017.
  59. 59.
    Nybo Andersen, A.M., J. Wohlfahrt, P. Christens, J. Olsen, and M. Melbye. 2000. Maternal age and fetal loss: Population based register linkage study. BMJ 320: 1708–1712.CrossRefGoogle Scholar

Copyright information

© The Author(s) 2018

Authors and Affiliations

  • Shoko Konishi
    • 1
    • 3
  • Emi Tamaki
    • 2
  1. 1.Department of Human Ecology, School of International Health, Graduate School of MedicineThe University of TokyoTokyoJapan
  2. 2.Faculty of International Social SciencesGakushuin UniversityTokyoJapan
  3. 3.Department of AnthropologyUniversity of WashingtonSeattleUSA

Personalised recommendations