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Epidemiology of Perimenopause in China

  • Ling Xu
  • Heng Zhao
  • Qin-sheng Ge
Part of the Clinical Perspectives in Obstetrics and Gynecology book series (CPOG)

Abstract

Due to the lack of information about the menopause in China, an epidemiologic survey among perimenopausal women aged 40–65 was conducted in Beijing from May to December 1990. Over 5000 women were selected by random sampling. An unified questionnaire was completed by face to face interview. 5134 women were included in the analysis. Among them 54.4% were postmenopausal, 10% in 40–49 age group, 87.8% in 50–59 and 99.3% in 60–65 age group. 93.8% were natural menopause, 5.4% after hysterectomy and 0.8% after drug or radiation. The mean age at natural menopause is 49 (22–61), not very different from other reports. Premature menopause before 40 is 3.1%. The incidence of menopausal symptoms varies between 45.6%–10.1%. Irritability, sweating and not flushing were the most frequent ones, but they were usually mild, only about 20% were severe and other symptoms were severe in about 10%. Late menopause are related with heavy menstrual bleeding, use of oral contraceptives, obesity and multigravida; while early menopause are related with smoking and accidents or happenings during premenopausal period. Only 4 women in this sample used estrogen replacement therapy for more than half a year, 0.14% of the menopausal women. In this study, menopause following surgery, menopausal symptoms and hormone replacement therapy all are lower than the western countries but similar to that of the eastern countries. Four hundred and ten fractures were reported, the prevalence was 7.99%. Age specific rates of fractures in this population in 1989 were 4.89, 6.12, and 11.42 per 1000 women in 40–49, 50–59 and 60–65 age groups respectively.

Keywords

Menopausal Woman Menopausal Symptom Estrogen Replacement Therapy Perimenopausal Woman Natural Menopause 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Copyright information

© Springer-Verlag New York, Inc. 1994

Authors and Affiliations

  • Ling Xu
  • Heng Zhao
  • Qin-sheng Ge

There are no affiliations available

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