Skip to main content
Download PDF

A secular trend in age at menarche in Yunnan Province, China: a multiethnic population study of 1,275,000 women

BMC Public Health volume 21, Article number: 1890 (2021) Cite this article

Abstract

Background

Age at menarche (AAM) has shown different trends in women from different ethnic and economic regions in recent decades. Data on AAM among multiethnic women living in developing areas are scarce.

Methods

Data on AAM from 1,275,000 women among 26 ethnicities in Yunnan Province, China, who were born from 1965 to 2001 were obtained from the National Free Preconception Health Examination Project from 2010 to 2018. The patterns of AAM trends were analysed according to ethnic group, area of residence, and socioeconomic status.

Results

The mean AAM was 13.7 ± 1.21 years (95% CI 13.697–13.701), with a decrease from 14.12 (±1.41) among women born before 1970 to 13.3 (±1.04) among those born after 2000. The decline was 0.36 years per 10-year birth cohort, and the plateau has not yet been reached in Yunnan. A secular trend of earlier AAM was observed in all 26 ethnic groups. The fastest rate of decline was observed for the Bai ethnicity (0.36 years per decade). Consistent declining trends in AAM appeared among extreme-, middling-, and nonpoverty economic patterns from 1965 to 2001, with reductions of 1.19, 1.44, and 1.5 years, respectively (P < 0.001). The peak reduction among middling poverty and extreme poverty occurred in the early 2000s (0.4 and 0.32 years). Multivariate analysis showed a significant difference in the declining trends in AAM along rural/urban lines (P < 0.001).

Conclusion

There was a secular trend towards a younger AAM during the twentieth century and early twenty-first century birth cohorts in the Yunnan population. Considering the difference in AAM trends due to ethnic and socioeconomic status in Yunnan, the health authority should utilize flexible adjusted health care strategies in different regions.

Peer Review reports

Background

Age at menarche (AAM) is one of the markers that indicates the onset of puberty in girls. As an evolutionary adaptive mechanism, AAM balances early reproduction, large body size, fertility, and potential mortality risk in pregnancy [1]. AAM can be affected by genetic, economic, nutritional, and social environmental factors [2,3,4]. One study showed a secular trend towards earlier AAM in Europe and the United States (US), with a decrease from 15 to 16 years to 12–13 years during the nineteenth century to the middle of the twentieth century [5]. Several recent studies have suggested that the trend may be related to economic growth and social environment changes because these can directly benefit nutrition and health care [6,7,8]. Compared to 1955–1965, the trend for early AAM in Dutch women slowed down in 1965–1997 (3 months vs. less than 1 month per decade), while Netherland’s gross domestic product (GDP) grew by almost 20 times in later decades [9]. This result suggested that there was no linear relationship between economic growth and AAM, instead of remaining relatively stable when the threshold was reached. In fact, there are two different trends for AAM including continuous reduction and levelling off in different countries and regions [10,11,12,13].

Earlier AAM is an important indicator not only for sexual development but also for some diseases and social problems, such as obesity, diabetes, cardiovascular disease and adolescent psychological problems [14,15,16,17,18,19]. Therefore, it is critical to survey AAM with a regionally inclusive and large population sample to protect women’s health, and the information obtained can be used to adjust health management programmes, such as disease screening and intervention measures for the target age groups. Compared to European studies over two centuries on AAM, however, efforts are still scarce in certain disadvantaged areas of Asia and Africa. An investigation among students of 13 ethnic minorities showed that the median AAM ranged from 12.1 to 13.6 years in Southwest China in 2014 [20]. However, these data might not reflect the real AAM trend in some poverty-stricken areas, as Yunnan Province includes vast territory, a large population, and many diverse ethnicities.

There are 26 diverse ethnicities living in Yunnan Province, which is the most ethnically diverse area in China. Yunnan had approximately 47.2 million permanent residents and a GDP per capita of approximately 7977 dollars in 2020, while the GDP per capita was only approximately 314, 136, and 962 dollars in 1980, 1990 and 2000, respectively [21]. The economy continues to grow. Because early AAM is associated with women’s health problems in later adulthood, the analysis of AAM trends is useful for health authorities to update women’s health policies. Therefore, the investigation of AAM in this region has high reference value for less developed countries/regions and homogeneous ethnic regions (e.g., South Asia and Southeast Asia).

In this study, we aimed to investigate the trend in AAM over the twentieth century and early twenty-first century within a multiethnic large population study from Yunnan Province, China, hypothesizing that AAM has declined over time, in accordance with global trends. We also aimed to describe the patterns, magnitudes and rates of the change in AAM between groups defined by ethnic and socioeconomic states, and potential health risks in women were assessed.

Methods

Study design and recruitment

This study was a part of the National Free Preconception Health Examination Project (NFPHEP), which was launched by the National Health and Family Planning Commission and the Ministry of Finance of China in 2010. The project provided free preconception examinations in rural areas to fertile women who planned a pregnancy within the next 6 months. Detailed information on the project was described in previous reports [22, 23].

In our retrospective cohort, 1,293,028 women were recruited to join the NFPHEP from 1st January 2010 to 31st December 2018. It covered all areas in Yunnan Province, China (129 counties/districts in 16 cities).

Data collection

Data collection for this project was based on the primary health and family planning network in China. Baseline information (age, ethnicity, and address of residence) of participants and their husbands was collected during face-to-face interviews by trained and certified interviewers with a structured questionnaire. In the questionnaire, the participants were asked how old (in years) they were at the age of menarche. A total of 18,028 women whose questionnaires did not meet the integrality criterion were excluded.

Variables

Recalled AAM served as the dependent variable, according to year of birth (1965–2001), for the group participants’ birth cohorts (<1970s, 1970s, 1980s, 1990s, and early 2000s). Ethnic information was collected from individual household registration. According to the traditional definition, ethnic groups other than Han are ethnic minorities, accounting for less than 10% of China’s population. The socioeconomic status of participants was determined through the area of residence (rural and urban) and the degree of poverty in their regions (extreme poverty, middling poverty, and nonpoverty) as defined by the State Council Leading Group Office of Poverty Alleviation and Development. The standard of economic indicators for middling poverty was less than 211.5 dollars per year for GDP per capita in 1992. If large-scale regional poverty was sustained for more than 5 years (less than the dynamic standard, e.g., 528.9 dollars in 2020), then the corresponding regions were defined as experiencing extreme poverty [24, 25]. All data reflect the status of respondents at the time of interview.

Statistical analyses

All statistical analyses were performed using R4.0.2. For continuous variables, T test and ANOVA test were applied to calculate the mean AAM across birth cohorts, ethnicity, area of residence, and economic status. The linear regression was used in the comparison for the trends of different stratified subgroups (e.g. ethnicity, urban/rural, or economic group). Graphs were drawn by the ‘ggplot2’ package.

Results

Overall, 1,275,000 women met the inclusion criteria for this survey. The mean age was 27.03 ± 5.61 years, and the mean AAM was 13.7 ± 1.21 years (95% confidence interval [CI] 13.697–13.701). Our study has shown a secular trend towards an earlier AAM in Yunnan during the twentieth century and early twenty-first century, with large amounts of data showing a decrease from 14.12 (±1.41) for women born before 1970 to 13.3 (±1.04) for those born after 2000. There was a reduction of 1.35 years (16.2 months) over an interval of 38 years (from 1965 to 2001) (P < 0.001), with the decline occurring at 0.36 years (4.3 months) per 10-year birth cohort by linear regression (P < 0.001) (Fig. 1) The mean AAM data across birth cohorts, ethnicity, area of residence, and economic status among Yunnan women are shown in Table 1 and Supplement 1.

Fig. 1
figure 1

Secular trend of age at menarche in Yunnan Province, China

Full size image
Table 1 Mean Age At Menarche across birth cohorts, ethnicity, area of residence, and economic status among Yunnan women during the study period
Full size table

Age at menarche in ethnic groups

An overall consistent secular trend of earlier AAM is shown in all ethnic groups described in Table 2 and Supplement 1. However, the rates of decline have exhibited heterogeneity in different ethnic groups. Faster rates of decline were found in the Bai ethnicity (4.3 months per decade); a slower rate of decline was seen in the Lisu ethnicity (1.9 months per decade). The decline in the Han population, which has the largest population, was 2.5 months per decade.

Table 2 A secular trends in age at menarche among 1,275,000 women in Yunnan province according to birth cohorts
Full size table

Age at menarche by socioeconomic status

The socioeconomic effect of early AAM seemed to be continuously present in Yunnan across birth cohorts. In terms of patterns, the decline in AAM for poverty groups was relatively faster, with the peak of reduction among middle poverty and extreme poverty occurring in the early 2000s (0.4 and 0.32 years, respectively). In contrast, the decline of nonpoverty women was more gradual, with a peak for the 1970s cohort (0.28 years). Overall, the declining trends in AAM appeared among the three economic status patterns from 1965 to 2001, with reductions of 1.19, 1.44, and 1.5 years for extreme-, middling-, and nonpoverty, respectively (P < 0.001). The difference between the populations in extreme poverty and nonpoverty was on average 0.21 years (2.5 months) across birth cohorts, but that gap decreased significantly from 0.3 years (3.6 months) in the 1970s birth cohort to 0.1 years (1.2 months) in the early 2000s counterpart cohort. We also found that the gradual reduction in the AAM gap along rural/urban lines did not exhibit a distinct difference (from 0.3–0.26 years in the <1970s - 1990s birth cohort to 0.15 years in the early 2000s). Multivariate analysis showed a significant difference in the declining trends in AAM between different household registration statuses (P < 0.001). However, we noted that selective bias might be unavoidable in only 13 cases in the early 2000s birth cohort for the urban group (Table 2, Figs. 1 and 2).

Fig. 2
figure 2

Secular trend in age at menarche in Yunnan Province by area of residence

Full size image

Discussion

China’s large medical encyclopaedias recorded that the AAM of Chinese females was 14 years during the Tang dynasty period (618–906 AD) [26, 27]. In the second half of the twentieth century and early twenty-first century, AAM decreased to 12–13 years in most developed countries with the improvement of living conditions [28,29,30,31,32]. Recent Chinese pubertal surveys have shown that the median AAM values of schoolgirls were 12.11 and 12.10 years in two metropolises (Shanghai and Shenzhen), respectively, levels similar to developed countries [33, 34]. However, our study showed that the AAM of Yunnan women (13.7 ± 1.21) appeared much later than in those developed regions during the study period. There was a reduction of 1.35 years (16.2 months) over an interval of 38 years (from 1965 to 2001), and the AAM was 14.12 ± 1.41 for women born before 1970 and 13.3 ± 1.04 for those born after 2000. A secular trend towards earlier AAM was found in our study, suggesting that Yunnan could belong among the regions where AAM has not yet slowed down or stabilized. Simultaneously, our results show the decline in AAM, which exhibits important variations with respect to patterns, magnitudes and rates within different ethnic and socioeconomic populations and according to health risks.

Ethnic groups

An American cohort study found that AAM before 12 years was more common in black girls than in their white counterparts (46% vs. 26%, P < 0.001) [2]. Across birth cohorts in Mexico over the twentieth century, nonindigenous residents on average reached the AAM earlier than their indigenous counterparts for both urban and rural women [4]. Towne et al. [35] confirmed that approximately 50% of the variation (heritability 0.49) in menstrual timing can be attributed to genetic factors that were also found to be associated with pubertal development parameters, such as weight and height in adolescents [36]. More than 450,000 ethnic minority women were included in the present study, and the proportion of Han ethnic and minority ethnic groups was approximately 2:1. Compared with Han ethnicity, the AAM of most minority women is different from that of Han ethnic women by approximately 3 months. This may be attributed to these ethnic groups; Han residents have been mixed for a long time, and living habits and cultural traditions have tended to assimilate. In our survey, women of the Lisu ethnicity were the group with the latest mean AAM (14.06 ± 1.37 years) and the least decreased magnitude (− 0.5878 years), respectively 4.7 months later and 2.4 months less than those of the Han ethnicity. These women are mainly distributed in southwest China, northern and central Burma, and the mountains of northern Thailand. Whether in China or Thailand, education, socioeconomic development, and health care are generally at low levels [37]. This suggests that it may be necessary to augment investment in health services in heavily populated Lisu ethnic areas. The earliest mean AAM group was Hui ethnic women, who experienced AAM 3.4 months earlier than Han ethnic women. Individuals of the Hui ethnicity are the most widely distributed ethnic minority group in China. Apart from mixed living with the Han ethnic group, beef and mutton intake in the Hui ethnic group is much greater than in other ethnicities because they adhere to Islamic customs and pork is forbidden. These animal proteins may cause earlier menarche by stimulating the release of insulin-like growth factor-1, which can regulate human growth and development [38, 39]. This finding suggests that the Hui ethnicity may need to be given priority in adolescent reproductive health education.

In fact, it is difficult to precisely distinguish the influence of either genetic or environmental factors. For example, earlier puberty was associated with earlier maternal puberty, but environmental changes usually occur simultaneously between family members. Additionally, some studies also observed earlier AAM among people who migrated from less to more economically developed countries [11]. This observation seemed to reflect environmental changes rather than ethnic factors.

Women of different socioeconomic statuses encounter varying degrees of risk

Social and economic status inequalities remain prominent in developing countries and regions; they might be responsible for important shifts in AAM within and among countries [40]. In developed regions, the declining trend seems to slow down or level off after AAM reaches a certain threshold [26], such as among French (from 12.78 to 12.6 years among girls born in 1979–1994) [28], American (from 12.5 to 12.3 years among girls born in 1939–1993) [32], Dutch (13.15 years in 1997 to 13.05 years in 2009) [31], and Greek women (from 12.27 years in 1996 to 12.29 years in 2006) [30]. The AAM in Yunnan women was obviously later than that of the women of America [41,42,43], Finland [44], Sweden [45, 46], Denmark [47], the United Kingdom [48], Germany [49], the Netherlands [50], Belgium [51], Switzerland [52], Italy [53], Spain [54], and Greece [55] at the same time during our study period. Compared to the well-off populations in some Asian regions, such as China [56], Japan [57], India [58], and Thailand [59], in the same period, the lag time in AAM of Yunnan women appeared to be more evident. This result indicated that the downward trend of AAM in Yunnan may be likely to continue.

With economic growth and social environment changes, improvements in women’s nutritional status may be the main reason for earlier puberty. Good nutritional status, especially adequate intake of protein, can improve the function of the pituitary and thyroid glands and increase the secretion of growth hormone and thyroxine, with the age of growth subsequently shifted earlier. The AAM of Polish women showed an earlier trend with the rapid development of society and the economy from 1966 to 1978, whereas the AAM was delayed during the next decade of political turmoil [8].

Our findings echo previous studies with respect to significant differences in socioeconomic status: the average AAM in nonpoverty areas was 0.21 years ahead of that in areas with extreme poverty. A closer inspection by economic status and area of residence across birth cohorts reveals important variation within the Yunnan population in magnitude and rates of secular decline. The secular decline in AAM of the poverty and rural populations was more apparent than that of the nonpoverty and urban populations, with the gap between groups decreasing significantly (Figs. 1 and 2). The average AAM for women born into extreme poverty in the 1980s is significantly older than that of their nonpoverty counterparts in the same cohort. With the implementation of the Chinese government’s poverty alleviation policy, health services, nutritional status, social security and living conditions were continuously improving. These changes were reflected in the trend of a rapid decrease in AAM among women living in poverty and rural areas. From the public health perspective, however, the influence of early menarche age on women’s health should be given more attention by health management departments.

Earlier age at menarche and women’s health risks

Many Mendelian randomization studies have shown a potential effect of earlier AAM on a broad range of health-related traits [60,61,62,63]. AAM less than 12 years can be considered as an indicator in adolescent health interventions [64]. Given the robust correlation between early AAM and women’s health risks, the trend of AAM in the previous study provides an alert to health authorities, and women’s health management should be adjusted to respond to the related disease threat.

As the improvements in education and healthcare level often lag behind the economy in impoverished areas, the declining trend in AAM reflected the needs of an increasingly younger youth group in Yunnan Province. Adolescent girls with earlier AAM are at a higher risk of depression, anxiety, substance abuse, smoking, bullying, and psychosocial problems. It may be necessary to provide health education and psychological counselling for adolescent girls experiencing poverty. Increases in BMI, weight and body fat percentage, waist circumference, and waist-hip ratio were also associated with AAM, with values of 0.19 kg/m2, 0.33%, 0.38 cm and 0.002 per 1 year of earlier AAM in China [65]. Improved nutritional intake can reduce the risks of obesity and T2DM in women [66, 67]. Moreover, studies have demonstrated that genetic regulation of puberty timing is linked with fatal disease susceptibility, such as breast and endometrial cancers [68, 69]. There are fewer health checkups among residents in poverty and rural areas that have experienced lower diagnosis and treatment levels at present in Yunnan. Therefore, people with cancers may be placed at higher risk of death. Regular screening for high-risk cancers should be encouraged among women in poverty and rural areas.

Limitations

There are several limitations of this large sample survey. First, memory bias may be unavoidable in the retrospective study of AAM. Prospective investigation is ideal, but it is not thought to be feasible in our study population. A national survey from the United Kingdom [70] showed that 412/946 (43.6%) of participants had recalled exactly the same AAM in women aged 48 years as had been recorded during the medical examination at ages of 14–15 years. Overall, the recalled AAM values of 195 (20.6%) and 199 (21.0%) women were 1 year older and younger in middle age than those recorded in adolescence, respectively, suggesting that there was no systematic underreporting or overreporting of AAM in middle age. Additionally, the entrance school age and length of schooling are relatively regular (6 years old) in China. The grade attended at AAM can provide additional memory information. For example, if menarche occurs in the sixth grade, then 12 years of age can usually be extrapolated. Second, potential social desirability bias should not be ignored in self-reported studies. Participants likely tend to respond in a socially expected manner in regard to potentially sensitive personal questions, such as race, drug and sex issues. Recently, the meta-analyses pooled 29 studies demonstrated that the pooled correlations with social desirability were generally small (ranging from 0.06–0.11) [71]. The surveys of AAM may be less susceptible to social desirability bias because AAM is not a social pattern to be followed and is not considered as good or bad. Third, there is a potential selection bias of the sample size for women born before 1970 (0.3%) and after 2000 (0.4%). Although the proportions were very small, there were 3380 and 4985 women born before 1970 and after 2000, respectively, and enough samples were included for both groups. Fourth, a similar problem appeared for participants in the urban area (3.4%), which included 43,094 women. In fact, the proportions of the rural population were 82.6, 82.2, 79.0 and 73.3% in 1970, 1980, 1990, and 2000 in China, respectively. With the development of the economy, a large number of rural people flowed into cities, and the proportion of urban to rural residents rose to approximately 3:2 in 2019. However, most of those migrants are still classified as rural residents because of the policy restrictions of urban household registration of alteration. Finally, the population was only from Yunnan Province, although our survey covered 26 diverse ethnicities. In homogeneous ethnicities of other countries, some features of AAM may be heteromorphic, with environmental conditions and genetic susceptibility changes [72]. In summary, we do not believe that these factors would affect our findings. The present study provides a health warning for women born from 1965 to 2001 with a secular trend towards an earlier AAM in the Yunnan multiethnic population based on available evidence.

Conclusions

Our study has shown a secular trend towards an earlier AAM during the twentieth century and early twenty-first century, and the plateau has not yet been reached in Yunnan Province, China. The magnitude and rate of variation were significantly affected by ethnicity, economic status, and area of residence. Early menarche age is associated with a variety of women’s health risks, especially in the context of low socioeconomic status. Considering the current AAM differences due to ethnic and socioeconomic status in Yunnan, we suggest that the health authority should flexibly adjust health care strategies in different regions to defend against potential health risks in women.

Availability of data and materials

The data presented in this study are available on request from the corresponding author. The data are not publicly available because our data represent a part of the NFPHEP project, which will not be exposed until the end of the project.

Abbreviations

AAM:

The Age at Menarche

GDP:

Gross Domestic Product

NFPHEP:

National Free Preconception Health Examination Project

CI:

Confidence Interval

References

  1. Hochberg Z. Evo-devo of child growth III: premature juvenility as an evolutionary trade-off. Horm Res Paediatr. 2010;73(6):430–7. https://doi.org/10.1159/000282109.

    Article  PubMed  CAS  Google Scholar 

  2. Braithwaite D, Moore DH, Lustig RH, Epel ES, Ong KK, Rehkopf DH, et al. Socioeconomic status in relation to early menarche among black and white girls. Cancer Causes Control. 2009;20(5):713–20. https://doi.org/10.1007/s10552-008-9284-9.

    Article  PubMed  Google Scholar 

  3. Garenne M. Trends in age at menarche and adult height in selected African countries (1950-1980). Ann Hum Biol. 2020;47(1):25–31. https://doi.org/10.1080/03014460.2020.1716994.

    Article  PubMed  Google Scholar 

  4. Marván ML, Castillo-López RL, Del-Callejo-Canal DD, Canal-Martínez ME, Núñez-de la Mora A. Secular trends in age at menarche in 20th century Mexico: Differences by ethnicity, area of residency, and socioeconomic status. Am J Hum Biol. 2020;32(6):e23404. https://doi.org/10.1002/ajhb.23404.

    Article  PubMed  Google Scholar 

  5. Wyshak G, Frisch RE. Evidence for a secular trend in age of menarche. N Engl J Med. 1982;306(17):1033–5. https://doi.org/10.1056/NEJM198204293061707.

    Article  PubMed  CAS  Google Scholar 

  6. Harris M, Prior J, Koehoorn M. Age at menarche in the Canadian population: secular trends and relationship to adulthood BMI. J Adolesc Health. 2008;43(6):548–54. https://doi.org/10.1016/j.jadohealth.2008.07.017.

    Article  PubMed  Google Scholar 

  7. Wronka I. Association between BMI and age at menarche in girls from different socio-economic groups. Anthropol Anz. 2010;68(1):43–52. https://doi.org/10.1127/0003-5548/2010/0066.

    Article  PubMed  Google Scholar 

  8. Gomula A, Koziel S. Secular trend and social variation in age at menarche among Polish schoolgirls before and after the political transformation. Am J Hum Biol. 2018;30(1). https://doi.org/10.1002/ajhb.23048.

  9. Mul D, Fredriks AM, van Buuren S, Oostdijk W, Verloove-Vanhorick SP, Wit JM. Pubertal development in the Netherlands 1965-1997. Pediatr Res. 2001;50(4):479–86. https://doi.org/10.1203/00006450-200110000-00010.

    Article  PubMed  CAS  Google Scholar 

  10. Ong KK, Ahmed ML, Dunger DB. Lessons from large population studies on timing and tempo of puberty (secular trends and relation to body size): the European trend. Mol Cell Endocrinol. 2006;254-255:8–12. https://doi.org/10.1016/j.mce.2006.04.018.

    Article  PubMed  CAS  Google Scholar 

  11. Hui LL, Leung GM, Lam TH, Schooling CM. Inter-generational influences on age at onset of puberty: Hong Kong’s ‘Children of 1997′ birth cohort. Int J Epidemiol. 2012;41(1):292–300. https://doi.org/10.1093/ije/dyr163.

    Article  PubMed  CAS  Google Scholar 

  12. Forman MR, Mangini LD, Thelus-Jean R, Hayward MD. Life-course origins of the ages at menarche and menopause. Adolesc Health Med Ther. 2013;4:1–21. https://doi.org/10.2147/AHMT.S15946.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Inter LST. Variations in reproductive events across life: a pooled analysis of data from 505 147 women across 10 countries. Hum Reprod. 2019;34(5):881–93. https://doi.org/10.1093/humrep/dez015.

    Article  Google Scholar 

  14. Dreyfus JG, Lutsey PL, Huxley R, Pankow JS, Selvin E, Fernandez-Rhodes L, et al. Age at menarche and risk of type 2 diabetes among African-American and white women in the atherosclerosis risk in communities (ARIC) study. Diabetologia. 2012;55(9):2371–80. https://doi.org/10.1007/s00125-012-2616-z.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  15. Farahmand M, Ramezani Tehrani F, Khalili D, Cheraghi L, Azizi F. Is there any association between age at menarche and anthropometric indices? A 15-year follow-up population-based cohort study. Eur J Pediatr. 2020;179(9):1379–88. https://doi.org/10.1007/s00431-020-03575-x.

    Article  PubMed  Google Scholar 

  16. Collaborative Group on Hormonal Factors in Breast C. Menarche, menopause, and breast cancer risk: individual participant meta-analysis, including 118 964 women with breast cancer from 117 epidemiological studies. Lancet Oncol. 2012;13(11):1141–51. https://doi.org/10.1016/S1470-2045(12)70425-4.

    Article  Google Scholar 

  17. Copeland W, Shanahan L, Miller S, Costello EJ, Angold A, Maughan B. Outcomes of early pubertal timing in young women: a prospective population-based study. Am J Psychiatry. 2010;167(10):1218–25. https://doi.org/10.1176/appi.ajp.2010.09081190.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Canoy D, Beral V, Balkwill A, Wright FL, Kroll ME, Reeves GK, et al. Age at menarche and risks of coronary heart and other vascular diseases in a large UK cohort. Circulation. 2015;131(3):237–44. https://doi.org/10.1161/CIRCULATIONAHA.114.010070.

    Article  PubMed  Google Scholar 

  19. Yang L, Li L, Millwood IY, Lewington S, Guo Y, Sherliker P, et al. Adiposity in relation to age at menarche and other reproductive factors among 300 000 Chinese women: findings from China Kadoorie biobank study. Int J Epidemiol. 2017;46(2):502–12. https://doi.org/10.1093/ije/dyw165.

    Article  PubMed  Google Scholar 

  20. Lei YT, Ma J, Hu PJ, Dong B, Zhang B, Song Y. The status of spermarche, menarche and corresponding relationships with nutritional status among students of 13 ethnic minorities in Southwest China in 2014. Zhonghua Yu Fang Yi Xue Za Zhi. 2019;53(5):492–6. https://doi.org/10.3760/cma.j.issn.0253-9624.2019.05.011.

    Article  PubMed  CAS  Google Scholar 

  21. ChinaNBoSo: [The annual statistics in 2020] http://data.stats.gov.cn/easyquery.htm?cn=C01. 2021.

    Google Scholar 

  22. Zhang S, Wang Q, Shen H. Design of the national free proception health examination project in China. Zhonghua Yi Xue Za Zhi. 2015;95(3):162–5.

    PubMed  CAS  Google Scholar 

  23. Sun L, Wang Q, Shen H, Liu M, Ma X, Ye H, et al. Evaluation and trend analysis of prepregnancy nutrition in Chinese women of reproductive age during 2010-2012. Zhonghua Yi Xue Za Zhi. 2015;95(3):181–6.

    PubMed  Google Scholar 

  24. [Explanation on the publication of the national list of counties in poverty-stricken areas in 2012]. http://www.cpad.gov.cn/art/2012/6/14/art_50_23717.html

  25. Jia Y. Lift the Seriously Impoverished Areas out of Poverty in a High-Quality Manner. Frontiers. 2018;14:26–33.

    Google Scholar 

  26. Papadimitriou A. The evolution of the age at menarche from prehistorical to modern times. J Pediatr Adolesc Gynecol. 2016;29(6):527–30. https://doi.org/10.1016/j.jpag.2015.12.002.

    Article  PubMed  Google Scholar 

  27. Medvei VC. The ancient Chinese. In: A History of Endocrinology. Springer seminars in immunopathology; 1982. p. 15–8. https://doi.org/10.1007/978-94-009-7304-6_3.

    Chapter  Google Scholar 

  28. Lalys L, Pineau JC. Age at menarche in a group of French schoolgirls. Pediatr Int. 2014;56(4):601–4. https://doi.org/10.1111/ped.12296.

    Article  PubMed  Google Scholar 

  29. Gohlke B, Woelfle J. Growth and puberty in German children: is there still a positive secular trend? Dtsch Arztebl Int. 2009;106(23):377–82. https://doi.org/10.3238/arztebl.2009.0377.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Papadimitriou A, Fytanidis G, Douros K, Bakoula C, Nicolaidou P, Fretzayas A. Age at menarche in contemporary Greek girls: evidence for levelling-off of the secular trend. Acta Paediatr. 2008;97(6):812–5. https://doi.org/10.1111/j.1651-2227.2008.00806.x.

    Article  PubMed  Google Scholar 

  31. Talma H, Schonbeck Y, van Dommelen P, Bakker B, van Buuren S, Hirasing RA. Trends in menarcheal age between 1955 and 2009 in the Netherlands. PLoS One. 2013;8(4):e60056. https://doi.org/10.1371/journal.pone.0060056.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  32. Finer LB, Philbin JM. Trends in ages at key reproductive transitions in the United States, 1951-2010. Womens Health Issues. 2014;24(3):e271–9. https://doi.org/10.1016/j.whi.2014.02.002.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Rong HHMH, Wang HM, Cao M, Song W. Menarche age and its related factors among girls of primary and secondary schools. Shanghai J Prev Med. 2019;31(7):607–10.

    Google Scholar 

  34. Wang LSZ, Wang Q, Liu J, Zhou L, Wang C. A survey of pubertal development among 6~16 years old children in Shenzhen. Chines J Child Health Care. 2020;28(4):57–60.

    Google Scholar 

  35. Towne B, Czerwinski SA, Demerath EW, Blangero J, Roche AF, Siervogel RM. Heritability of age at menarche in girls from the Fels longitudinal study. Am J Phys Anthropol. 2005;128(1):210–9. https://doi.org/10.1002/ajpa.20106.

    Article  PubMed  Google Scholar 

  36. Tu W, Wagner EK, Eckert GJ, Yu Z, Hannon T, Pratt JH, et al. Associations between menarche-related genetic variants and pubertal growth in male and female adolescents. J Adolesc Health. 2015;56(1):66–72. https://doi.org/10.1016/j.jadohealth.2014.07.020.

    Article  PubMed  Google Scholar 

  37. Hou X, Zhang G. The origin of Lisus in Thailand and its social culture. Around Southeast Asia. 2008;9:31–4.

    Google Scholar 

  38. Jin C, Li N, Li Z, Zhang L. The risk factors and health effects of early menarche. Chinese J Reprod Health. 2018;29:386–8.

    Google Scholar 

  39. Qiao H, Li X. Investigation and analysis of menarche and the age of first spermatorrhea among Hui and Han students in Ningxia. Chinese J School Health. 1998;2:116–7.

    Google Scholar 

  40. Eveleth P, Tanner J. Worldwide Variation in Human Growth. 2nd ed. New York: Cambridge University Press; 1991. p. 397.

    Book  Google Scholar 

  41. Wu T, Mendola P, Buck GM. Ethnic differences in the presence of secondary sex characteristics and menarche among US girls: the third National Health and nutrition examination survey, 1988-1994. Pediatrics. 2002;110(4):752–7. https://doi.org/10.1542/peds.110.4.752.

    Article  PubMed  Google Scholar 

  42. Chumlea WC, Schubert CM, Roche AF, Kulin HE, Lee PA, Himes JH, et al. Age at menarche and racial comparisons in US girls. Pediatrics. 2003;111(1):110–3. https://doi.org/10.1542/peds.111.1.110.

    Article  PubMed  Google Scholar 

  43. Anderson SE, Dallal GE, Must A. Relative weight and race influence average age at menarche: results from two nationally representative surveys of US girls studied 25 years apart. Pediatrics. 2003;111(4 Pt 1):844–50. https://doi.org/10.1542/peds.111.4.844.

    Article  PubMed  Google Scholar 

  44. Rimpelä AH, Rimpelä MK. Towards an equal distribution of health? Socioeconomic and regional differences of the secular trend of the age of menarche in Finland from 1979 to 1989. Acta paediatrica (Oslo, Norway : 1992). 1993;82(1):87–90.

    Article  Google Scholar 

  45. Lindgren GW, Degerfors IL, Fredriksson A, Loukili A, Mannerfeldt R, Nordin M, et al. Menarche 1990 in Stockholm schoolgirls. Acta Paediatr Scand. 1991;80(10):953–5. https://doi.org/10.1111/j.1651-2227.1991.tb11758.x.

    Article  PubMed  CAS  Google Scholar 

  46. Lindgren G. Pubertal stages 1980 of Stockholm schoolchildren. Acta paediatrica (Oslo, Norway : 1992). 1996;85(11):1365–7. https://doi.org/10.1111/j.1651-2227.1996.tb13927.x.

    Article  CAS  Google Scholar 

  47. Helm P, Grølund L. A halt in the secular trend towards earlier menarche in Denmark. Acta Obstet Gynecol Scand. 1998;77(2):198–200. https://doi.org/10.1034/j.1600-0412.1998.770213.x.

    Article  PubMed  CAS  Google Scholar 

  48. Rubin C, Maisonet M, Kieszak S, Monteilh C, Holmes A, Flanders D, et al. Timing of maturation and predictors of menarche in girls enrolled in a contemporary British cohort. Paediatr Perinat Epidemiol. 2009;23(5):492–504. https://doi.org/10.1111/j.1365-3016.2009.01055.x.

    Article  PubMed  Google Scholar 

  49. Engelhardt L, Willers B, Pelz L. Sexual maturation in East German girls. Acta paediatrica (Oslo, Norway : 1992). 1995;84(12):1362–5.

    Article  CAS  Google Scholar 

  50. Fredriks A, van Buuren S, Burgmeijer RJ, Meulmeester JF, Beuker RJ, Brugman E, et al. Continuing positive secular growth change in the Netherlands 1955-1997. Pediatr Res. 2000;47(3):316–23. https://doi.org/10.1203/00006450-200003000-00006.

    Article  PubMed  CAS  Google Scholar 

  51. Vercauteren M, Susanne C. The secular trend of height and menarche in Belgium: are there any signs of a future stop? Eur J Pediatr. 1985;144(4):306–9. https://doi.org/10.1007/BF00441769.

    Article  PubMed  CAS  Google Scholar 

  52. Largo RH, Prader A. Pubertal development in Swiss girls. Helv Paediatr Acta. 1983;38(3):229–43.

    PubMed  CAS  Google Scholar 

  53. Borneman MVA, Tommaseo M, Capucci E. Menarcheal age and environmental factors in a sample from the province of Rome. Acta Med Auxol. 1995;27:97–104.

    Google Scholar 

  54. de la Puente M, Canela J, Alvarez J, Salleras L, Vicens-Calvet E. Cross-sectional growth study of the child and adolescent population of Catalonia (Spain). Ann Hum Biol. 1997;24(5):435–52. https://doi.org/10.1080/03014469700005202.

    Article  PubMed  Google Scholar 

  55. Papadimitriou A, Gousia E, Pitaouli E, Tapaki G, Philippidis P. Age at menarche in Greek girls. Ann Hum Biol. 1999;26(2):175–7. https://doi.org/10.1080/030144699282877.

    Article  PubMed  CAS  Google Scholar 

  56. Huen KF, Leung SS, Lau JT, Cheung AY, Leung NK, Chiu MC. Secular trend in the sexual maturation of southern Chinese girls. Acta paediatrica (Oslo, Norway : 1992). 1997;86(10):1121–4.

    Article  CAS  Google Scholar 

  57. Murata M, Hibi I. Nutrition and the secular trend of growth. Horm Res. 1992;38(Suppl 1):89–96. https://doi.org/10.1159/000182578.

    Article  PubMed  Google Scholar 

  58. Rao S, Joshi S, Kanade A. Height velocity, body fat and menarcheal age of Indian girls. Indian Pediatr. 1998;35(7):619–28.

    PubMed  CAS  Google Scholar 

  59. Chompootaweep S, Tankeyoon M, Poomsuwan P, Yamarat K, Dusitsin N. Age at menarche in Thai girls. Ann Hum Biol. 1997;24(5):427–33. https://doi.org/10.1080/03014469700005192.

    Article  PubMed  CAS  Google Scholar 

  60. Magnus MC, Guyatt AL, Lawn RB, Wyss AB, Trajanoska K, Kupers LK, et al. Identifying potential causal effects of age at menarche: a Mendelian randomization phenome-wide association study. BMC Med. 2020;18(1):71. https://doi.org/10.1186/s12916-020-01515-y.

    Article  PubMed  PubMed Central  Google Scholar 

  61. Trajanoska K, Morris JA, Oei L, Zheng HF, Evans DM, Kiel DP, et al. Assessment of the genetic and clinical determinants of fracture risk: genome wide association and mendelian randomisation study. BMJ. 2018;362:k3225. https://doi.org/10.1136/bmj.k3225.

    Article  PubMed  PubMed Central  Google Scholar 

  62. Gill D, Sheehan NA, Wielscher M, Shrine N, Amaral AFS, Thompson JR, et al. Age at menarche and lung function: a Mendelian randomization study. Eur J Epidemiol. 2017;32(8):701–10. https://doi.org/10.1007/s10654-017-0272-9.

    Article  PubMed  PubMed Central  Google Scholar 

  63. Bell JA, Carslake D, Wade KH, Richmond RC, Langdon RJ, Vincent EE, et al. Influence of puberty timing on adiposity and cardiometabolic traits: a Mendelian randomisation study. PLoS Med. 2018;15(8):e1002641. https://doi.org/10.1371/journal.pmed.1002641.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  64. Yu EJ, Choe SA, Yun JW, Son M. Association of Early Menarche with adolescent health in the setting of rapidly decreasing age at menarche. J Pediatr Adolesc Gynecol. 2020;33(3):264–70. https://doi.org/10.1016/j.jpag.2019.12.006.

    Article  PubMed  Google Scholar 

  65. La Vecchia C, Negri E. Thyroid cancer: the thyroid cancer epidemic - overdiagnosis or a real increase? Nat Rev Endocrinol. 2017;13(6):318–9. https://doi.org/10.1038/nrendo.2017.53.

    Article  PubMed  Google Scholar 

  66. Zhang L, Li Y, Zhou W, Wang C, Dong X, Mao Z, et al. Mediation effect of BMI on the relationship between age at menarche and hypertension: the Henan rural cohort study. J Hum Hypertens. 2019;34(6):448–56. https://doi.org/10.1038/s41371-019-0247-2.

    Article  PubMed  Google Scholar 

  67. Elks C, Ong KK, Scott RA, van der Schouw YT, Brand JS, Wark PA, et al. Age at menarche and type 2 diabetes risk: the EPIC-InterAct study. Diabetes Care. 2013;36(11):3526–34. https://doi.org/10.2337/dc13-0446.

    Article  PubMed  PubMed Central  Google Scholar 

  68. Day FR, Thompson DJ, Helgason H, Chasman DI, Finucane H, Sulem P, et al. Genomic analyses identify hundreds of variants associated with age at menarche and support a role for puberty timing in cancer risk. Nat Genet. 2017;49(6):834–41. https://doi.org/10.1038/ng.3841.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  69. Burgess S, Thompson DJ, Rees JMB, Day FR, Perry JR, Ong KK. Dissecting causal pathways using Mendelian randomization with summarized genetic data: application to age at menarche and risk of breast Cancer. Genetics. 2017;207(2):481–7. https://doi.org/10.1534/genetics.117.300191.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  70. Cooper R, Blell M, Hardy R, Black S, Pollard TM, Wadsworth ME, et al. Validity of age at menarche self-reported in adulthood. J Epidemiol Community Health. 2006;60(11):993–7. https://doi.org/10.1136/jech.2005.043182.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  71. Vesely S, Klockner CA. Social desirability in environmental psychology research: three Meta-analyses. Front Psychol. 2020;11:1395. https://doi.org/10.3389/fpsyg.2020.01395.

    Article  PubMed  PubMed Central  Google Scholar 

  72. Parent A-S, Teilmann G, Juul A, Skakkebaek NE, Toppari J, Bourguignon J-P. The timing of normal puberty and the age limits of sexual precocity: variations around the world, secular trends, and changes after migration. Endocr Rev. 2003;24(5):668–93. https://doi.org/10.1210/er.2002-0019.

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

Not applicable.

Funding

This research was funded by the National Natural Science Foundation of China [grant numbers 81660545, 81960592, 82073569], the Outstanding Youth Science Foundation of Yunnan Basic Research Project [202001AW070021], the Reserve Talent Project for Young and Middle-aged Academic and Technical Leaders [2012005 AC160023], and the Innovative Research Team of Yunnan Province [202005AE160002].

Author information

Author notes

  1. Wen Liu and Xuejing Yan contributed equally to this work.

Authors and Affiliations

  1. Department of Thyroid Surgery, the First Affiliated Hospital of Kunming Medical University, Kunming, 650032, China

    Wen Liu

  2. Department of Management of Chronic Non-communicable Diseases, Yunnan Center for Diseases Control and Prevention, Kunming, 650032, China

    Xuejing Yan

  3. School of Public Health, Kunming Medical University, Kunming, 650500, China

    Chengyu Li, Meng Chen, Le Cai & Dingyun You

  4. No. 1 School of Clinical Medicine, Kunming Medical University, Kunming, 650032, China

    Qi Shu

Authors
  1. Wen Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xuejing Yan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Chengyu Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Qi Shu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Meng Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Le Cai
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Dingyun You
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

DY conceptualized and designed the study. WL and XY contributed to writing of the report. QS and CL contributed to the statistical analysis. MC and LC performed the data analyses. All authors reviewed the results and approved the final version of the manuscript.

Corresponding author

Correspondence to Dingyun You.

Ethics declarations

Ethics approval and consent to participate

The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Institutional Review Board of the Chinese Association of Maternal and Child Health Studies (No. AMCHS-2014-4). Informed consent was obtained from all subjects involved in the study.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Additional file 1: Supplementary 1.

Secular trends in AAM among other ethnic minorities*.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Liu, W., Yan, X., Li, C. et al. A secular trend in age at menarche in Yunnan Province, China: a multiethnic population study of 1,275,000 women. BMC Public Health 21, 1890 (2021). https://doi.org/10.1186/s12889-021-11951-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12889-021-11951-x

Keywords

BMC Public Health

ISSN: 1471-2458

Contact us