1 Julius Center for Health Sciences and Primary Care, 2 Department of Reproductive Medicine and 3 Department of Medical Genetics, University Medical Center Utrecht, Utrecht, The Netherlands
4 To whom correspondence should be addressed at: Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, HP nr Str 6.131, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands. e-mail: H.S.Kok{at}jc.azu.nl
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Abstract |
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Key words: age at menopause/epidemiology/ovarian ageing/reproductive life/subfertility
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Introduction |
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Subjects and methods |
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In Figure 1 the selection procedure of our study population is outlined. Natural menopause was defined as proposed by the World Health Organization Scientific Group (1996) as 12 consecutive months of amenorrhoea not due to surgery or other obvious causes. Women for whom age at natural menopause could not be determined were excluded. Natural menopause occurred in 6411 women of the initial sample. Women who were aged <58 years at time of recruitment were excluded (n = 2374) to avoid bias due to differential inclusion of women with an early age at menopause. Allowing women under this age into the study population would lead to a distortion of the age distribution of menopause. The number of women with a late age at menopause will be underestimated simply because women who were younger at the time of recruitment can only be included in the study population if they had an early menopause. At age 58 years, 97.8% of all women had reached menopause. Finally, we excluded women who had a unilateral oophorectomy pre-menopausally (n = 217) and women who ever used oral contraceptives (OC) or an intrauterine device (IUD) pre-menopausally (n = 1427). Our final study population thus consisted of 2393 women.
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Confounders
Because of the potential for confounding, all analyses are adjusted for smoking and socio-economic status. Women were defined as smokers if they reported smoking pre-menopausally until time of menopause. Educational level was used to adjust for socio-economic status. In The Netherlands, the majority of women of this generation were not educated to their capacity nor gainfully employed, but usually stayed home to take care of household and children. In the case of married women, educational attainment of the husband is considered a better indicator for socio-economic status of the household to which a woman belongs (Shinberg, 1999). So, for married women adjustments were made for the educational level of their spouse.
Statistical methods
Numbers and percentages of all reproductive correlates according to categories of menopausal age were computed. Six separate logistic regression analyses were performed producing an odds ratio (OR) and corresponding 95% confidence interval (CI) for each association between a subfertility measure and age at menopause. All analyses were performed using SPSS 10.1 for Windows. Age at menopause was collapsed into a variable with a 5-year difference in menopausal age per unit. This new variable was used as a continuous variable in the analyses. Therefore results can be interpreted as follows: the OR represent the risk for having the outcome variable, i.e. reduced reproductive potential, per unit change in menopausal age, e.g. a 5 year difference in age at menopause.
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Results |
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Discussion |
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To appreciate the findings, some aspects of the study need to be discussed. An irregular menstrual cycle pattern has previously been described as a strong predictor for reduced fertility (Kolstad et al., 1999). Unfortunately, it appears that no unequivocal description is available to define an irregular menstrual cycle pattern. Comparisons of results between studies should therefore be made with care.
This study is the first to report data on age at menopause in relation to reduced fertility as defined by having consulted a physician for fertility problems. The group of women who sought medical advice for fertility problems is possibly heterogeneous as for underlying cause resulting in their sub- or infertility. However, this misclassification of sub- or infertile women occurred independently of menopausal age and is thus non-differential. Non-differential misclassification leads to an underestimation of the true association.
To assess the relationship between menopausal age and nulliparity, a major advantage of our study is that the group of nulliparous women excluded women who by choice remained nulliparous and thus consisted only of women who reported that they tried to conceive. Still, non-differential misclassification could have been introduced due to a male factor resulting in nulliparity of a couple. In general, this leads to underestimation of the effect.
Two previous studies described the relationship between miscarriages and subfertility. Both concluded that women with a history of subfertility, defined as failure to conceive within 1 year and difficulty achieving conception and seeking a physicians help respectively, have increased rates of (subclinical) early pregnancy loss, relative to women without such a history (Hakim et al., 1995; Gray and Wu, 2000
).
Time to pregnancy is widely used to estimate the degree of subfertility (Baird et al., 1986; Greenhall and Vessey, 1990
). The outcome variable time interval between birth of first and second child is a substitute for time to pregnancy as we were unable to directly determine time to pregnancy. A consequence is that subfertility in this analysis is of relatively minor magnitude, because all women in this studied subpopulation were able to conceive at least twice. However, since we were able to exclude all oral contraceptive users and all intrauterine device users, the interval between first and second child comprises for a major part unintentional waiting time.
In previous studies, several of these indicators of reproductive potential were shown to be related to age at menopause (Stanford et al., 1987; Whelan et al., 1990
; Parazzini et al., 1992
; Cramer et al., 1995a
; Bromberger et al., 1997
; Hardy and Kuh, 1999
; Gold et al., 2001
). These studies imply a causative relationship between the factor and menopausal age. We hypothesize that both are related to (a) common factor(s), causing accelerated ovarian ageing.
Inconsistent results have been reported on menstrual cycle pattern and age at menopause (Stanford et al., 1987; Whelan et al., 1990
; Bromberger et al., 1997
). In our data, early menopause was related to a higher risk for an irregular cycle pattern. The lack of agreement can be due to differences in defining irregular menstrual cycle pattern. Our data on menstrual cycle pattern concern the age period of 3040 years, while earlier studies based their results on the menstrual cycle pattern at an earlier age. It is however unlikely that the results are distorted by this, because the median age of inception of peri-menopause is at age 4748 years and lasts for 45 years ( McKinlay et al., 1992
; Den Tonkelaar et al., 1998
; Hardy and Kuh, 1999
). For the majority of women, the menstrual cycle pattern between ages 30 and 40 years represents their normal pre-menopausal pattern. This is endorsed by the fact that excluding women with menopause before 45 years from the analysis did not change the results.
Most studies agree on parity delaying menopause. The proposed mechanism for this is that during pregnancy and lactation, oocytes are saved and menstrual cycles continue longer (Stanford et al., 1987; Whelan et al., 1990
; Cramer et al., 1995b
). We suggest two alternative explanations. Firstly, following our hypothesis, women subjected to accelerated ovarian ageing are likely to have fewer children. Accelerated ovarian ageing is also reflected in an earlier age at menopause and consequently low parity is correlated with earlier age at menopause and high parity with later age at menopause. The second explanation is methodological. Relating two age-dependent factors may induce bias: women experiencing menopause at higher age by definition had more chance of having more children. In this study, we bypassed this problem because we examined the risk of having only one child in parous women.
Fertility declines with increasing age in all women ( Krey et al., 2001). Therefore, the relationship between age at menopause and the time interval between birth of first and second child was tested for effect modification by age at first child birth, but was found to be absent. Analogous with the reasoning described for parity, a positive relationship is expected between age at menopause and the time interval, even in absence of a true association. Again, this is because both are age-dependent. To illustrate, women with a later age at menopause have by definition had more chance to have a large time interval between birth of the children. Our results show an opposite relationship, a higher age at menopause decreases the risk of a large time interval, emphasizing the strength of this relationship.
The use of age at menopause in our analyses as a determinant may be confusing because it is a parameter that can only chronologically be assessed after the outcome. Indeed it would have been better to use a measure of ovarian ageing that preceded the fertility problems. Unfortunately, such a measure is not available. In the cohort we included women that had all reached menopause. Consequently, an ultimate measure for ovarian ageing, age at menopause, could be used. If age at menopause may indeed be used as a measure for accelerated ovarian ageing, and if the aim is to explore the role of accelerated ovarian ageing in (causing) fertility problems, then it makes sense to consider it a determinant in a relationship in which fertility problems are the outcome.
The question remains what determines ovarian ageing. The most consistently reported environmental factor to influence age at menopause is smoking. Smoking is proposed to decrease the size of the follicle pool ( Westhoff et al., 2000), to interfere with the pituitaryovarian axis, and to have an effect on the metabolism of sex hormones (Midgette and Baron, 1990
). Also, it has been found that chemicals in cigarette smoke up-regulate a pro-apoptosis gene resulting in enhanced follicular damage and premature ovarian failure in mice (Matikainen et al., 2001
). All mechanisms are plausible to accelerate ovarian ageing. Smoking and other factors that might influence the oocyte pool explain only a small part of the large variation in menopausal age ( Van Noord et al., 1997
). Other arguments for the possible underlying mechanisms of accelerated ovarian ageing such as the importance of the fetal period, selection and growth of oocytes/follicles from the follicle pool, possible endocrine pathways and genetic determinants have recently been reviewed (te Velde and Pearson, 2002
). Twin studies (Snieder et al., 1998
; Treloar et al., 1998
) and a sibling study (De Bruin et al., 2001
) have shown age at menopause to be heritable to a large extent. Genes, or genes in interaction with environmental factors, are therefore good candidates to have a major impact on ovarian ageing. Identifying these genes and their function will help us understand female reproductive ageing.
In conclusion, the results of this study show that fertility problems are frequently followed by early menopause. The findings support the view that both are an expression of accelerated ovarian ageing.
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Acknowledgements |
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References |
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Submitted on July 17, 2002; resubmitted on October 15, 2002; accepted on November 26, 2002.