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European Journal of Epidemiology

, Volume 34, Issue 3, pp 235–246 | Cite as

Premenopausal cardiovascular disease and age at natural menopause: a pooled analysis of over 170,000 women

  • Dongshan ZhuEmail author
  • Hsin-Fang Chung
  • Nirmala Pandeya
  • Annette J. Dobson
  • Rebecca Hardy
  • Diana Kuh
  • Eric J. Brunner
  • Fiona Bruinsma
  • Graham G. Giles
  • Panayotes Demakakos
  • Jung Su Lee
  • Hideki Mizunuma
  • Kunihiko Hayashi
  • Hans-Olov Adami
  • Elisabete Weiderpass
  • Gita D. Mishra
META-ANALYSIS

Abstract

Early menopause is associated with an increased risk of subsequent cardiovascular disease (CVD). Few studies have investigated the converse. We examined whether premenopausal CVD events are associated with early age at menopause. We pooled the individual data of 177,131 women from nine studies. We used multinomial logistic regression models to estimate multivariable relative risk ratios (RRR) and 95% confidence intervals (CI) for the associations between age at onset of premenopausal CVD events—including coronary heart disease (CHD) and stroke—and age at natural menopause. Altogether 1561 (0.9%) premenopausal participants reported CVD events (including 1130 CHD and 469 stroke) at a mean age of 41.3 years. Compared with women without any premenopausal CVD events, women who experienced a first CVD event before age 35 years had a twofold risk of menopause before age 45 years (early menopause); adjusted RRR (95% CI) of 1.92 (1.17, 3.14) for any CVD, 1.86 (1.01, 3.43) for CHD and 2.17 (1.43, 3.30) for stroke. Women who experienced a first premenopausal CVD event after age 40 years underwent a natural menopause at the expected age (around 51 years). These associations were robust to adjustment for smoking status, BMI, educational level, race/ethnicity, age at menarche, parity, hypertension and family history of CVD. For premenopausal women, a first CVD event before age 35 years is associated with a doubling of the risk of an early menopause, while a first CVD event occurred after 35 years indicates a normal menopause at around 51 years. Shared genetic and environmental factors (such as smoking), as well as compromised vasculature following CVD events, may contribute to this outcome.

Keywords

Premenopausal Cardiovascular disease Age at menopause Pooled analysis 

Notes

Acknowledgements

The data on which this research is based were drawn from 9 observational studies. The research included data from the ALSWH, the University of Newcastle, Australia, and the University of Queensland, Australia. We are grateful to the Australian Government Department of Health for funding and to the women who provided the survey data. MCCS was supported by VicHealth and the Cancer Council, Victoria, Australia. WLHS was funded by a grant from the Swedish Research Council (Grant No. 521-2011-2955). NSHD has core funding from the UK Medical Research Council (MC UU 12019/1). NCDS is funded by the Economic and Social Research Council. ELSA is funded by the National Institute on Aging (Grants 2RO1AG7644 and 2RO1AG017644-01A1) and a consortium of UK government departments. The Whitehall II study has been supported by grants from the Medical Research Council. Baseline survey of the JNHS was supported in part by a Grant-in-Aid for Scientific Research (B: 14370133, 18390195) from the Japan Society for the Promotion of Science, and by the grants from the Japan Menopause Society. This research has been conducted using the UK Biobank resource under application 26629. All studies would like to thank the participants for volunteering their time to be involved in the respective studies. The findings and views in this paper are not necessarily those of the original studies or their respective funding agencies.

Author’s contribution

GDM and DZ conceptualized the study. GDM interpreted the results, and revised the manuscript critically. DZ analysed and interpreted data, and drafted the manuscript. HFC and NP harmonised the data and revised the manuscript. AJD, RH, DK, EJB, FB, GGG, PD, JSL, HM, KH, HOA, EW provided study data and revised the manuscript.

Funding

InterLACE project is funded by the Australian National Health and Medical Research Council Project Grant (APP1027196). GDM is supported by Australian National Health and Medical Research Council Principal Research Fellowship (APP1121844). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary material

10654_2019_490_MOESM1_ESM.docx (72 kb)
Supplementary material 1 (DOCX 71 kb)

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Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  • Dongshan Zhu
    • 1
    Email author
  • Hsin-Fang Chung
    • 1
  • Nirmala Pandeya
    • 1
    • 2
  • Annette J. Dobson
    • 1
  • Rebecca Hardy
    • 3
  • Diana Kuh
    • 3
  • Eric J. Brunner
    • 4
  • Fiona Bruinsma
    • 5
  • Graham G. Giles
    • 5
    • 6
  • Panayotes Demakakos
    • 4
  • Jung Su Lee
    • 7
  • Hideki Mizunuma
    • 8
  • Kunihiko Hayashi
    • 9
  • Hans-Olov Adami
    • 10
    • 11
  • Elisabete Weiderpass
    • 10
    • 12
    • 13
    • 14
  • Gita D. Mishra
    • 1
  1. 1.School of Public HealthUniversity of QueenslandBrisbaneAustralia
  2. 2.Department of Population HealthQIMR Berghofer Medical Research InstituteBrisbaneAustralia
  3. 3.Medical Research Council Unit for Lifelong Health and Ageing at UCLLondonUK
  4. 4.Department of Epidemiology and Public HealthUniversity College LondonLondonUK
  5. 5.Cancer Epidemiology and Intelligence DivisionCancer Council VictoriaMelbourneAustralia
  6. 6.Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global HealthThe University of MelbourneMelbourneAustralia
  7. 7.Department of Public Health, Graduate School of MedicineThe University of TokyoTokyoJapan
  8. 8.Fukushima Medical Center for Children and WomenFukushima Medical UniversityFukushimaJapan
  9. 9.School of Health SciencesGunma UniversityMaebashi CityJapan
  10. 10.Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
  11. 11.Clinical Effectiveness Research Group, Institute of Health and SocietyUniversity of OsloOsloNorway
  12. 12.Genetic Epidemiology Group, Folkhälsan Research Center, Faculty of MedicineUniversity of HelsinkiHelsinkiFinland
  13. 13.Department of Community Medicine, Faculty of Health SciencesUniversity of Tromsø, The Arctic University of NorwayTromsøNorway
  14. 14.Department of Research, Cancer Registry of NorwayInstitute of Population-Based Cancer ResearchOsloNorway

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