Lifetime cumulative number of menstrual cycles and serum sex hormone levels in postmenopausal women Objective Lifetime cumulative number of menstrual cycles is related to breast cancer risk . The aim of this study is to investigate the relation between this index and serum sex hormone levels in postmenopausal women . Introduction Breast cancer is strongly related to various hormonal factors . We know that different hormones play a key role in the pathogenesis of invasive breast cancer in both , premenopausal and postmenopausal women -LSB- 1 -- 4 -RSB- , likely representing a direct effect of circulating hormones -LSB- 5 -- 7 -RSB- . The patterns of risk associated with reproductive history suggest that a prolonged exposure to ovarian hormones increases breast cancer occurrence -LSB- 8 -RSB- . It has been well established that early age at menarche , late age at menopause , null parity and late age at first full term pregnancy -LRB- FFTP -RRB- are important risk factors for breast cancer -LSB- 9 -- 11 -RSB- . These characteristics may have long lasting effects on hormone metabolism , although data regarding reproductive characteristics and hormone levels are still inconclusive -LSB- 12 -- 16 -RSB- In an effort to measure the lifetime exposure to endogenous hormones , the concept of the `` lifetime cumulative number of menstrual cycles '' was introduced as an index that could reflect total ovarian exposure -LSB- 17 , 18 -RSB- . The `` lifetime cumulative number of cycles '' summarizes information such as menarche , parity , menopause , regularity pattern , breast feeding and oral contraceptive -LRB- OC -RRB- use . In previous studies we , but also others , related the cumulative numbers of menstrual cycles to breast cancer risk -LSB- 17 , 18 -RSB- . Ovarian function , and therefore , `` lifetime number of menstrual cycles '' is defined by age at menopause , and age at menopause is related to postmenopausal estrogen levels -LSB- 19 -RSB- ; with this rationale we studied the association between the `` lifetime number of menstrual cycles '' and hormone levels after the menopause . The hypothesis fits in , where a common factor at hypothalamic level may affect the speed by which oocytes are being used , increasing postmenopausal gonoadothopin levels and maybe , stimulating ovarian testosterone release from the remaining theca cells , as well as non ovarian estrogens from adrenal origin . The aim of this study was to evaluate the relation between the `` lifetime cumulative number of menstrual cycles '' and the reproductive characteristics that contribute to this estimate on one side , and plasma concentrations of sex hormones on the other side , in order to elucidate the mechanism by which reproductive risk factors could influence hormone-related cancers . Study design and methods The Prospect-EPIC study is one of the two Dutch cohorts participating in the European Prospective Investigation into Cancer and Nutrition ; a multi-center prospective study carried out in 23 centers from 10 European countries -LSB- 20 -RSB- . A detailed description of the study population and data collection of the Prospect-EPIC study has been published elsewhere -LSB- 21 -RSB- . Briefly , 17,357 women aged 49 -- 70 , residing in Utrecht and its surroundings were recruited through a regional , population-based , breast cancer screening program between 1993 and 1997 . Base-line characteristics were collected on the basis of two self-administered questionnaires -LRB- regarding lifestyle and nutrition -RRB- . The lifestyle questionnaire contains information on demographic characteristics , family history , past and current morbidity , reproductive history -LRB- gynecologic and obstetric -RRB- , smoking habits , and physical activity . In addition , anthropometric measurements -LRB- height , weight , and waist and hip circumference -RRB- were taken as well as a 30 ml blood sample . Within 24 h , samples of 4 ml serum , 9 ml citrate plasma , 2 ml white blood cells , and 2 ml red blood cells were fractionated into 0.5 ml aliquots and stored at − 196 °C . Blood samples were successfully drawn from 97.5 % of the participants -LSB- 21 -RSB- . All women signed a written informed consent and the study was approved by the Institutional Review Board of the University Medical Center Utrecht . Of all Prospect-EPIC participants a 10 % random sample -LRB- n = 1736 -RRB- was taken and hormone measurements were done . For the present study , participants who used hormone replacement therapy -LRB- HRT -RRB- or OC in the previous twelve months were excluded -LRB- n = 311 -RRB- , as well as those women with history any cancer other than non-melanoma cancer -LRB- n = 25 -RRB- . From the remaining 1,400 participants only those who underwent natural menopause were eligible -LRB- n = 860 -RRB- because only in them we had reliable information about ovarian activity not masked by the absence of menstrual cycles due to hysterectomy . Natural menopause was defined as the complete cessation of menstrual bleeding for 12 months preceding enrollment due to natural causes -LRB- according to self-report -RRB- . We computed the `` lifetime cumulative number of menstrual cycles '' of the women in this study . For parous women , the number of menstrual cycles before a FFTP was also estimated as we previously described -LSB- 17 -RSB- . Briefly , the `` lifetime cumulative number of menstrual cycles '' was computed from age at first menstrual period to age at menopause . Ages at menarche , at menopause and at FFTP were recorded as continuous variables . Age at regularization of cycles was computed according to the time between menarche and the establishment of regular periods -LRB- immediately after menarche , after 1 , 2 , 3 , 5 , or 10 years , after FFTP or never regular -RRB- . The regularity pattern was defined categorically as 24 , 26 , 28 , 30 and 32 day cycles , or always irregular . Information about OC use included : age at start , number of years of use and age at last use . Data about number of and age at each pregnancy , stillbirth , miscarriage and abortion , if any , were available , as well as the number of weeks of breastfeeding for each pregnancy . We took all the previously mentioned variables into account when computing the `` lifetime cumulative number of menstrual cycles '' , considering that each pregnancy , stillbirth , miscarriage or abortion , resulted in an absence of cycles for a period of 36 , 28 and 12 weeks respectively . We assumed that lactation results in a 6-week absence of cycles -LSB- 22 -RSB- . Menstrual cycles due to OC use were computed as 28 days duration -LRB- see Appendix -RRB- . Considering that irregular cycles are a combination of long and short menstrual periods , the number of irregular cycles was computed according to each participant 's regularity pattern ; the total number of irregular years was recorded in order to make further adjustments . The number of menstrual cycles was impossible to compute in the participants who reported to be always irregular or never having regular periods , therefore we added the `` irregular '' category as such in the analysis -LRB- See appendix -RRB- . Bounded levels of estrogens and androgens were measured , levels of estrone -LRB- E1 -RRB- , estradiol -LRB- E2 -RRB- , androstenedione , testosterone , sex hormone binding globulin -LRB- SHBG -RRB- and dehydroepiandrostenedione sulfate -LRB- DHEAS -RRB- were measured in plasma using commercially available double-antibody radioimmunoassay -LRB- RIA -RRB- kits -LRB- Diagnostic System Laboratories Inc. , Webster , TX , USA -RRB- . The following kits were used : E1 : DSL-8700 , E2 : DSL-39100 , androstenedione : DSL-4200 , TST : DSL-4100 SHBG : DSL-6300 and DHEAS : DSL-2700 . The intra-assay coefficients of variation were 5.6 % , 3.9 % , 4.3 % , 7.7 % , 3.0 % and 5.2 % respectively . The inter-assay coefficients of variation were 11.1 % , 4.1 % , 6.3 % , 8.1 % , 4.0 % and 5.3 % respectively . All hormone assays were performed by the laboratory of the Hormones and Cancer group at the International Agency for Research on Caner -LRB- IARC -RRB- . Although technically SHBG is not a hormone , for reasons of convenience it will be referred as such . We calculated the free-androgen index -LRB- FAI -RRB- dividing testosterone by SHBG and multiplying by 100 , the SHGB/E2 index was calculated dividing SHBG by E2 . Data analysis Means with their standard deviation -LRB- SD -RRB- values , or frequencies of baseline characteristics were calculated . Concentrations of all hormones were logarithmically transformed to produce approximately normal distributions . To make the results easily interpretable , we transformed the mean and its 95 % confidence interval -LRB- CI -RRB- back to their original scale , resulting in geometric means and 95 % CIs . Geometric mean levels and 95 % CIs were calculated for each hormone -LRB- SHBG , E1 , E2 , androstenedione , testosterone , DHEAS -RRB- , SHBG/estradiol index -LRB- SHBG/E2 -RRB- and free androgen index -LRB- FAI -RRB- . Using analysis of covariance models , geometric mean hormone levels were calculated for the different categories of cumulative number of menstrual cycles -LRB- lifetime and before a FFTP -RRB- . The same analysis was also used for categories of age at menarche , age at menopause , parity , number of children and age of FFTP . In order to build the adjusted model we classified confounders in three categories as follows : Group A contained characteristics clearly related to hormone levels such as age , years since menopause and body mass index -LRB- BMI -RRB- ; Group B contained factors possibly related to hormone levels like OC and HRT use , smoking habits , physical activity and alcohol consumption ; group C contained characteristics unlikely related to hormone levels such as marital status , education level and family history of breast cancer . We first adjusted for all confounders of type A , B , and C , then we built models by deleting B and C types of characteristics , without affecting validity but increasing precision . In the final model we included confounders in group A and B , therefore we adjusted for age at intake as a continuous variable , number of years from menopause to inclusion in the study , BMI at examination , use of HRT ever -LRB- Y/N -RRB- , use of OC ever -LRB- Y/N -RRB- , smoking habits , alcohol consumption and physical activity . Information on current alcohol use was obtained from the food frequency questionnaire , total alcohol consumption in grams per day was calculated from questions in the number of glasses of wine , beer , fortified wines , and liquor/spirits per day , week , month or year . One glass of any alcoholic beverage was assumed to contain 10g of alcohol . With the daily physical activity data from the general questionnaire , the Voorrips score was calculated -LRB- and was entered in the model as a continuous variable -RRB- , this score has been developed and validated especially for women in this age group -LSB- 23 -RSB- . For analysis of the `` lifetime cumulative number of menstrual cycles '' and the `` number of cycles before a FFTP '' variables , we also adjusted for more than one year of irregular cycles -LRB- Y/N -RRB- . Given that age at menopause can be determined using age at intake in combination of years since menopause ; when analyzing age at menopause , the covariate years since menopause was not entered in the model . To test the significance of the models ' linearity , median values in each category for every variable were computed accordingly . Subsequently these values were included as a continuous variable in a linear regression model to test for linear trends . Because there is no clear natural hierarchy , the `` always irregular '' category was not included when testing for trend for the `` lifetime number of menstrual cycles '' and the `` number of menstrual cycles before a FFTP '' variables . Additional mutual adjustments for reproductive characteristics did not show any difference in the observed trends . The Statistical Package for Social Sciences for WINDOWS , version 14.0 -LRB- Chicago , IL -RRB- , was used for all statistical analysis , and all tests were two sided . Results General and reproductive characteristics of the Prospect-EPIC women that were included in this study are shown on Table 1 . On average , participants were 60.2 years old at enrollment ; had a BMI of 26.2 kg/m2 and the majority of them -LRB- 69.4 % -RRB- had at least low technical-secondary education . 113 -LRB- 13.1 % -RRB- were nulliparous , and for the parous , the mean age for a FFTP was 25.5 years old . Mean age at menarche and menopause were 13.6 and 49.6 years old respectively , the time from menopause to inclusion , was on average 10.6 years . In 786 participants -LRB- 91.4 % -RRB- the lifetime cumulative number of cycles was calculated , as we had incomplete data regarding reproductive history in 74 women . The median number of lifetime menstrual cycles was 451.3 , corresponding to 34.7 years of menstrual activity if considering an average of 13 cycles per year . From the 747 parous participants , 64 had incomplete data to compute the number of menstrual cycles before a FFT , in the remaining 683 participants -LRB- 91.4 % -RRB- , the median number of menstrual cycles before a FFTP was 146.7 -LRB- approximately 11.3 years of menstrual activity -RRB- . These results are consistent with the previous data on such estimates for a larger sample of the Prospect-EPIC participants as we previously published -LSB- 17 -RSB- . Table 2 shows the geometric mean hormone levels for all participants with 95 % CIs of SHBG , E1 , E2 , androstenedione , testosterone , DHEAS , SHBG/E2 and FAI.Table 1General and reproductive characteristics of the study participants -LRB- n = 860 -RRB- Mean -LRB- SD -RRB- General characteristicsAge at enrollment60 .2 -LRB- 5.5 -RRB- BMI26 .2 -LRB- 4.2 -RRB- Waist Hip ratio0 .797 -LRB- 0.59 -RRB- Length -LRB- cm -RRB- 163.7 -LRB- 6.1 -RRB- Weight -LRB- Kg -RRB- 70.1 -LRB- 11.9 -RRB- Educational level -LRB- % -RRB- - Primary education263 -LRB- 30.6 -RRB- - Low technical , secondary384 -LRB- 44.6 -RRB- - High technical , secondary98 -LRB- 11.4 -RRB- - Academic115 -LRB- 13.4 -RRB- Ever married -LRB- % -RRB- 805 -LRB- 93.6 -RRB- Cigarette smoking habits -LRB- % -RRB- - Never smoked402 -LRB- 46.7 -RRB- - Past smoker275 -LRB- 32 -RRB- - Current smoker183 -LRB- 21.3 -RRB- Mother or sister with BC -LRB- % -RRB- 123 -LRB- 14.3 -RRB- Reproduction characteristicsAge at menarche13 .6 -LRB- 1.6 -RRB- Nulliparous -LRB- % -RRB- 113 -LRB- 13.1 -RRB- Age at FFTPa25 .46 -LRB- 3.8 -RRB- Number live born childrena2 .9 -LRB- 1.4 -RRB- Age at menopause49 .6 -LRB- 4.0 -RRB- Years since menopause10 .6 -LRB- 6.0 -RRB- Oral contraceptive use -LRB- % -RRB- 384 -LRB- 44.6 -RRB- Years of OC useb6HRT use -LRB- % -RRB- 66 -LRB- 7.7 -RRB- Years of HRT usec1Lifetime number of menstrual cycles -LRB- n = 786 -RRB- 165 -LRB- 21.0 -RRB- ≤ 415177 -LRB- 22.5 -RRB- 416 -- 453171 -LRB- 21.8 -RRB- 454 -- 490161 -LRB- 20.5 -RRB- ≥ 491112 -LRB- 14.2 -RRB- Always irregulardNumber of menstrual cycles beforeFFTP -LRB- n = 683 -RRB- ≤ 118167 -LRB- 25.5 -RRB- 119 -- 147160 -LRB- 23.4 -RRB- 148 -- 185118 -LRB- 17.3 -RRB- ≥ 186143 -LRB- 20.9 -RRB- Always irregulard95 -LRB- 13.9 -RRB- a Among parous womenb Median , Among OC usersc Median , Among HRT usersd Participants in the always irregular category , reported to be never regularTable 2Geometric mean serum sex hormone and SHBG levelsHormoneMean , -LRB- 95 % CI -RRB- SHBG μg/ml18 .1 -LRB- 17.2 -- 19.2 -RRB- Estrone pg/ml15 .2 -LRB- 14.48 -- 16.0 -RRB- Estradiol pg/ml8 .5 -LRB- 8.2 -- 8.8 -RRB- Androstenedione ng/ml0 .47 -LRB- 0.45 -- 0.49 -RRB- Testosterone total ng/ml0 .26 -LRB- 0.25 -- 0.27 -RRB- DHEAS ng/ml455 .1 -LRB- 432.9 -- 478.4 -RRB- SHBG - Estradiol index -LRB- μg/pg -RRB- 0.47 -LRB- 0.44 -- 0.50 -RRB- Free androgen index -LSB- -LRB- Testosterone / SHBG * 100 -LRB- ng/μg * 100 -RRB- -RSB- 4.6 -LRB- 4.4 -- 5.0 -RRB- Table 3 shows the unadjusted geometric mean hormone levels and 95 % CI for each hormone according to some general and reproductive characteristics . When testing for trend participants in the lower quartile of `` lifetime cumulative of menstrual cycles '' had higher levels of SHBG , androstenedione , testosterone and DHEAS than the participants with the highest quartile -LRB- P trend = 0.015 , 0.003 , 0.052 and 0.035 respectively -RRB- , and lower levels of SHBG/E2 -LRB- P trend = 0.031 -RRB- . Table 3Hormones unadjusted means -LRB- 95 % CI -RRB- according to patient characteristics SHBG -LRB- μg/ml -RRB- Estrone -LRB- pg/ml -RRB- Estroidal -LRB- pg/ml -RRB- Androstenedione -LRB- ng/ml -RRB- Testosterone -LRB- ng/ml -RRB- DHEAS -LRB- ng/ml -RRB- SHBG/E2-indexFA-indexLifetime number of menstrual cycles < = 41519.8 -LRB- 17.3 -- 22.5 -RRB- 15.6 -LRB- 13.9 -- 17.4 -RRB- 8.5 -LRB- 7.8 -- 9.2 -RRB- 0.56 -LRB- 0.50 -- 0.64 -RRB- 0.29 -LRB- 0.26 -- 0.31 -RRB- 515.3 -LRB- 458.6 -- 579.1 -RRB- 0.431 -LRB- 0.366 -- 0.509 -RRB- 4.7 -LRB- 4.05 -- 5.46 -RRB- 416 -- 45319.5 -LRB- 17.1 -- 22.1 -RRB- 13.5 -LRB- 12.1 -- 15.0 -RRB- 8.5 -LRB- 7.8 -- 9.2 -RRB- 0.45 -LRB- 0.39 -- 0.50 -RRB- 0.25 -LRB- 0.23 -- 0.27 -RRB- 448.1 -LRB- 400.3 -- 501.5 -RRB- 0.435 -LRB- 0.371-0.511 -RRB- 4.3 -LRB- 3.73 -- 4.97 -RRB- 454 -- 49017.4 -LRB- 15.3 -- 19.8 -RRB- 16.1 -LRB- 14.4 -- 17.9 -RRB- 8.8 -LRB- 8.1 -- 9.5 -RRB- 0.43 -LRB- 0.39 -- 0.49 -RRB- 0.25 -LRB- 0.23 -- 0.27 -RRB- 436.4 -LRB- 389.1 -- 489.3 -RRB- 0.504 -LRB- 0.428 -- 0.593 -RRB- 4.7 -LRB- 4.09 -- 5.49 -RRB- > = 49115.9 -LRB- 13.9 -- 18.2 -RRB- 15.9 -LRB- 14.2 -- 17.9 -RRB- 8.7 -LRB- 7.9 -- 9.4 -RRB- 0.44 -LRB- 0.39 -- 0.50 -RRB- 0.25 -LRB- 0.23 -- 0.27 -RRB- 434.8 -LRB- 386.4 -- 489.3 -RRB- 0.542 -LRB- 0.458 -- 0.641 -RRB- 5.1 -LRB- 4.36 -- 5.89 -RRB- Always irregular § 16.6 -LRB- 14.1 -- 19.5 -RRB- 14.9 -LRB- 13.04 -- 17.1 -RRB- 7.9 -LRB- 7.1 -- 8.7 -RRB- 0.49 -LRB- 0.40 -- 0.54 -RRB- 0.26 -LRB- 0.23 -- 0.28 -RRB- 425.4 -LRB- 69.2 -- 490.2 -RRB- 0.476 -LRB- 0.389 -- 0.582 -RRB- 4.9 -LRB- 4.07 -- 5.85 -RRB- P-trend0.150 .4550.6480.0030.0520.0350.0310.406 Number of menstrual cycles before a FFTP * < = 11819.5 -LRB- 17.1 -- 22.2 -RRB- 14.8 -LRB- 13.2 -- 16.6 -RRB- 8.3 -LRB- 7.6 -- 8.9 -RRB- 0.48 -LRB- 0.42 -- 0.54 -RRB- 0.27 -LRB- 0.24 -- 0.24 -RRB- 472.1 -LRB- 420.1 -- 530.6 -RRB- .426 -LRB- .362-.500 -RRB- 4.5 -LRB- 3.86 -- 5.15 -RRB- 119 -- 14718.2 -LRB- 15.9 -- 20.8 -RRB- 14.9 -LRB- 13.2 -- 16.7 -RRB- 8.6 -LRB- 7.9 -- 9.3 -RRB- 0.48 -LRB- 0.42 -- 0.54 -RRB- 0.26 -LRB- 0.23 -- 0.23 -RRB- 488.8 -LRB- 433.8 -- 550.7 -RRB- .471 -LRB- .399-.555 -RRB- 4.6 -LRB- 3.96 -- 5.32 -RRB- 148 -- 18517.3 -LRB- 14.8 -- 20.1 -RRB- 15.9 -LRB- 13.9 -- 18.2 -RRB- 9.2 -LRB- 8.3 -- 10.0 -RRB- 0.43 -LRB- 0.37 -- 0.50 -RRB- 0.26 -LRB- 0.23 -- 0.23 -RRB- 425.1 -LRB- 369.9 -- 488.4 -RRB- .529 -LRB- .437-.641 -RRB- 4.9 -LRB- 4.17 -- 5.89 -RRB- > = 18618.8 -LRB- 16.3 -- 21.6 -RRB- 14.5 -LRB- 12.8 -- 16.4 -RRB- 8.3 -LRB- 7.6 -- 8.9 -RRB- 0.45 -LRB- 0.39 -- 0.51 -RRB- 0.25 -LRB- 0.22 -- 0.22 -RRB- 419.4 -LRB- 369.6 -- 475.7 -RRB- 0.440 -LRB- 0.370 -- 0.524 -RRB- 4.4 -LRB- 3.76 -- 5.15 -RRB- Always irregular § 15.5 -LRB- 13.1 -- 18.4 -RRB- 14.8 -LRB- 12.7 -- 17.2 -RRB- 8.0 -LRB- 7.2 -- 8.8 -RRB- 0.48 -LRB- 0.40 -- 0.56 -RRB- 0.27 -LRB- 0.24 -- 0.24 -RRB- 440.3 -LRB- 377.1 -- 513.9 -RRB- 0.515 -LRB- 0.416-.638 -RRB- 5.5 -LRB- 4.51 -- 6.62 -RRB- P-trend0.5740 .9920.9330.3490.3330.0870.5650.999 Age at intake < = 5418.8 -LRB- 16.5 -- 21.5 -RRB- 15.9 -LRB- 14.3 -- 17.8 -RRB- 9.4 -LRB- 8.7 -- 10.2 -RRB- 0.53 -LRB- 0.47 -- 0.60 -RRB- 0.28 -LRB- 0.26 -- 0.31 -RRB- 611.5 -LRB- 547.5 -- 682.9 -RRB- 0.499 -LRB- 0.424 -- 0.587 -RRB- 4.9 -LRB- 4.19 -- 5.62 -RRB- 55 -- 5918.9 -LRB- 16.9 -- 21.2 -RRB- 15.45 -LRB- 14.1 -- 16.9 -RRB- 8.6 -LRB- 8.0 -- 9.2 -RRB- 0.46 -LRB- 0.42 -- 0.51 -RRB- 0.25 -LRB- 0.23 -- 0.27 -RRB- 493.4 -LRB- 448.6 -- 542.7 -RRB- 0.453 -LRB- 0.394 -- 0.522 -RRB- 4.5 -LRB- 3.92 -- 5.04 -RRB- 60 -- 6417.3 -LRB- 15.6 -- 19.3 -RRB- 14.3 -LRB- 13.0 -- 15.6 -RRB- 8.3 -LRB- 7.8 -- 8.8 -RRB- 0.47 -LRB- 0.43 -- 0.52 -RRB- 0.26 -LRB- 0.24 -- 0.28 -RRB- 424.3 -LRB- 387.5 -- 464.5 -RRB- 0.480 -LRB- 0.419 -- 0.548 -RRB- 4.8 -LRB- 4.26 -- 5.42 -RRB- > = 6517.7 -LRB- 15.8 -- 19.8 -RRB- 15.4 -LRB- 14.0 -- 16.9 -RRB- 7.9 -LRB- 7.4 -- 8.5 -RRB- 0.44 -LRB- 0.39 -- 0.49 -RRB- 0.25 -LRB- 0.23 -- 0.27 -RRB- 363.9 -LRB- 330.9 -- 400.4 -RRB- 0.450 -LRB- 0.391 -- 0.518 -RRB- 4.6 -LRB- 4.04 -- 5.20 -RRB- P-trend0.3030 .4490.0020.0410.106 < 0.00010.4990.834 Age at menarche < = 1118.9 -LRB- 15.3 -- 23.3 -RRB- 15.2 -LRB- 12.7 -- 18.2 -RRB- 8.0 -LRB- 7.0 -- 9.1 -RRB- 0.47 -LRB- 0.39 -- 0.57 -RRB- 0.28 -LRB- 0.24 -- 0.33 -RRB- 437.1 -LRB- 363.9 -- 525.2 -RRB- 0.423 -LRB- 0.325 -- 0.550 -RRB- 4.9 -LRB- 3.93 -- 6.29 -RRB- 1215.9 -LRB- 14.1 -- 18.1 -RRB- 14.5 -LRB- 13.0 -- 16.1 -RRB- 8.8 -LRB- 8.1 -- 9.4 -RRB- 0.47 -LRB- 0.42 -- 0.52 -RRB- 0.26 -LRB- 0.24 -- 0.28 -RRB- 439.4 -LRB- 393.6 -- 490.5 -RRB- 0.549 -LRB- 0.469 -- 0.643 -RRB- 4.2 -LRB- 4.51 -- 5.99 -RRB- 1317.5 -LRB- 15.6 -- 19.7 -RRB- 15.9 -LRB- 14.4 -- 17.5 -RRB- 8.3 -LRB- 7.7 -- 8.8 -RRB- 0.47 -LRB- 0.42 -- 0.52 -RRB- 0.26 -LRB- 0.24 -- 0.28 -RRB- 461.7 -LRB- 417.2 -- 510.9 -RRB- 0.472 -LRB- 0.408 -- 0.546 -RRB- 4.7 -LRB- 4.10 -- 5.32 -RRB- 1418.8 -LRB- 16.6 -- 21.3 -RRB- 15.1 -LRB- 13.5 -- 16.7 -RRB- 8.6 -LRB- 8.0 -- 9.3 -RRB- 0.44 -LRB- 0.38 -- 0.48 -RRB- 0.24 -LRB- 0.22 -- 0.26 -RRB- 447.9 -LRB- 401.7 -- 499.4 -RRB- 0.458 -LRB- 0.392 -- 0.536 -RRB- 4.2 -LRB- 3.69 -- 4.88 -RRB- 1520.8 -LRB- 17.7 -- 24.5 -RRB- 15.9 -LRB- 13.9 -- 18.2 -RRB- 8.5 -LRB- 7.7 -- 9.3 -RRB- 0.49 -LRB- 0.42 -- 0.57 -RRB- 0.28 -LRB- 0.25 -- 0.31 -RRB- 490.6 -LRB- 426.2 -- 564.7 -RRB- 0.408 -LRB- 0.334 -- 0.499 -RRB- 4.4 -LRB- 3.70 -- 5.32 -RRB- > = 1618.8 -LRB- 16.1 -- 21.9 -RRB- 14.6 -LRB- 12.7 -- 16.6 -RRB- 8.5 -LRB- 7.7 -- 9.3 -RRB- 0.53 -LRB- 0.46 -- 0.61 -RRB- 0.27 -LRB- 0.24 -- 0.29 -RRB- 457.1 -LRB- 399.0 -- 523.5 -RRB- 0.452 -LRB- 0.372 -- 0.549 -RRB- 4.6 -LRB- 3.86 -- 5.47 -RRB- P-trend0.0690 .9430.8050.2620.9060.4140.1820.147 Reproductive status Parous17 .5 -LRB- 14.9 -- 20.4 -RRB- 16.9 -LRB- 14.8 -- 19.4 -RRB- 8.8 -LRB- 8.02 -- 9.70 -RRB- 0.52 -LRB- 0.45 -- 0.60 -RRB- 0.26 -LRB- 0.23 -- 0.29 -RRB- 461.5 -LRB- 402.0 -- 529.7 -RRB- 0.506 -LRB- 0.415 -- 0.616 -RRB- 4.8 -LRB- 4.0 -- 5.7 -RRB- Nulliparous18 .2 -LRB- 17.2 -- 19.414.9 -LRB- 14.2 -- 15.7 -RRB- 8.5 -LRB- 8.13 8.76 -RRB- 0.47 -LRB- 0.44 -- 0.49 -RRB- 0.26 -LRB- 0.25 -- 0.27 -RRB- 454.1 -LRB- 430.4 -- 479.1 -RRB- 0.463 -LRB- 0.429 -- 0.500 -RRB- 4.7 -LRB- 4.3 -- 4.9 -RRB- P-equality of means0 .6080.0830.4070.1680.8530.8310.4180.770 Age at FFTP * < = 2119.5 -LRB- 16.5 -- 22.9 -RRB- 15.7 -LRB- 13.6 -- 18.1 -RRB- 8.5 -LRB- 7.6 -- 9.3 -RRB- 0.48 -LRB- 0.41 -- 0.56 -RRB- 0.26 -LRB- 0.23 -- 0.29 -RRB- 481.3 -LRB- 416.4 -- 556.4 -RRB- 0.434 -LRB- 0.355 -- 0.531 -RRB- 4.4 -LRB- 3.63 -- 5.23 -RRB- 22 -- 2416.2 -LRB- 14.3 -- 18.2 -RRB- 14.7 -LRB- 13.3 -- 16.3 -RRB- 8.8 -LRB- 8.2 -- 9.4 -RRB- 0.47 -LRB- 0.42 -- 0.52 -RRB- 0.27 -LRB- 0.25 -- 0.29 -RRB- 468.1 -LRB- 421.1 -- 520.3 -RRB- 0.544 -LRB- 0.470 -- 0.631 -RRB- 5.2 -LRB- 4.57 -- 5.96 -RRB- 25 -- 2718.5 -LRB- 16.5 -- 20.3 -RRB- 15.2 -LRB- 13.8 -- 16.6 -RRB- 8.2 -LRB- 7.6 -- 8.7 -RRB- 0.47 -LRB- 0.42 -- 0.52 -RRB- 0.26 -LRB- 0.24 -- 0.27 -RRB- 454.9 -LRB- 414.8 -- 498.8 -RRB- 0.445 -LRB- 0.391 -- 0.506 -RRB- 4.6 -LRB- 4.12 -- 5.19 -RRB- > = 2819.7 -LRB- 17.4 -- 22.2 -RRB- 14.5 -LRB- 13.06 -- 16.6 -RRB- 8.5 -LRB- 7.8 -- 9.1 -RRB- 0.45 -LRB- 0.40 -- 0.50 -RRB- 0.25 -LRB- 0.23 -- 0.27 -RRB- 425.6 -LRB- 382.4 -- 473.6 -RRB- 0.429 -LRB- 0.370 -- 0.498 -RRB- 4.3 -LRB- 3.75 -- 4.90 -RRB- P-trend0.2960 .4970.5450.4140.3380.1380.2580.337 Number of liveborn 017.4 -LRB- 14.9 -- 20.4 -RRB- 16.9 -LRB- 14.8 -- 19.3 -RRB- 8.8 -LRB- 8.0 -- 9.7 -RRB- 0.52 -LRB- 0.45 -- 0.60 -RRB- 0.26 -LRB- 0.23 -- 0.29 -RRB- 461.5 -LRB- 401.9 -- 529.7 -RRB- 0.506 -LRB- 0.415 -- 0.616 -RRB- 4.8 -LRB- 4.00 -- 5.71 -RRB- 117.5 -LRB- 14.1 -- 21.8 -RRB- 15.7 -LRB- 13.1 -- 18.9 -RRB- 7.9 -LRB- 7.0 -- 9.1 -RRB- 0.41 -LRB- 0.33 -- 0.50 -RRB- 0.24 -LRB- 0.21 -- 0.28 -RRB- 424.9 -LRB- 351.1 -- 514.3 -RRB- .456 -LRB- .346-.600 -RRB- 4.5 -LRB- 3.48 -- 5.69 -RRB- 2185 -LRB- 16.7 -- 20.3 -RRB- 14.8 -LRB- 13.6 -- 16.1 -RRB- 8.8 -LRB- 8.2 -- 9.2 -RRB- 0.48 -LRB- 0.43 -- 0.52 -RRB- 0.26 -LRB- 0.24 -- 0.28 -RRB- 474.9 -LRB- 436.4 -- 516.8 -RRB- 0.473 -LRB- 0.419 -- 0.534 -RRB- 4.7 -LRB- 4.21 -- 5.23 -RRB- 318.2 -LRB- 16.2 -- 20.5 -RRB- 14.9 -LRB- 13.4 -- 16.4 -RRB- 8.4 -LRB- 7.7 -- 8.9 -RRB- 0.45 -LRB- 0.40 -- 0.50 -RRB- 0.26 -LRB- 0.24 -- 0.28 -RRB- 459.1 -LRB- 414.4 -- 508.6 -RRB- 0.458 -LRB- 0.395 -- 0.531 -RRB- 4.6 -LRB- 4.00 -- 5.21 -RRB- > = 418.1 -LRB- 15.9 -- 20.4 -RRB- 15.0 -LRB- 13.5 -- 16.6 -RRB- 8.2 -LRB- 7.6 -- 8.8 -RRB- 0.48 -LRB- 0.43 -- 0.54 -RRB- 0.27 -LRB- 0.24 -- 0.29 -RRB- 425.7 -LRB- 381.8 -- 474.6 -RRB- 0.455 -LRB- 0.389 -- 0.532 -RRB- 4.7 -LRB- 4.10 -- 5.43 -RRB- P-trend0.7700 .1740.2890.6240.6680.4320.4370.946 BMI < = 24.925.8 -LRB- 23.7 -- 28.2 -RRB- 13.3 -LRB- 12.3 -- 14.4 -RRB- 7.5 -LRB- 7.1 -- 7.9 -RRB- 0.45 -LRB- 0.41 -- 0.49 -RRB- 0.23 -LRB- 0.22 -- 0.25 -RRB- 459.5 -LRB- 459.5 -- 498.5 -RRB- 0.291 -LRB- 0.262 -- 0.323 -RRB- 3.1 -LRB- 2.81 -- 3.41 -RRB- 25 -- 29.916.8 -LRB- 15.5 -- 18.2 -RRB- 15.7 -LRB- 14.6 -- 16.8 -RRB- 8.6 -LRB- 8.1 -- 9.0 -RRB- 0.47 -LRB- 0.44 -- 0.51 -RRB- 0.27 -LRB- 0.25 -- 0.28 -RRB- 449.1 -LRB- 449.1 -- 484.2 -RRB- 0.509 -LRB- 0.461-0.561 -RRB- 5.1 -LRB- 4.70 -- 5.63 -RRB- 30 -- 34.910.5 -LRB- 9.1 -- 12.1 -RRB- 17.7 -LRB- 15.5 -- 20.1 -RRB- 10.0 -LRB- 9.1 -- 10.9 -RRB- 0.51 -LRB- 0.44 -- 0.58 -RRB- 0.31 -LRB- 0.28 -- 0.34 -RRB- 467.4 -LRB- 467.4 -- 535.0 -RRB- 0.957 -LRB- 0.803 -- 1.14 -RRB- 8.5 -LRB- 7.24 -- 9.98 -RRB- > = 359.9 -LRB- 7.6 -- 12.7 -RRB- 21.5 -LRB- 17.0 -- 27.0 -RRB- 13.5 -LRB- 11.6 -- 15.8 -RRB- 0.56 -LRB- 0.43 -- 0.72 -RRB- 0.31 -LRB- 0.26 -- 0.37 -RRB- 439.8 -LRB- 439.8 -- 559.9 -RRB- 1.37 -LRB- 1.00 -- 1.87 -RRB- 9.0 -LRB- 6.77 -- 12.03 -RRB- P-trend < 0.0001 < 0.0001 < 0.00010.052 < 0.00010.959 < 0.0001 < 0.0001 OC use ever yes17 .6 -LRB- 16.2 -- 19.2 -RRB- 15.5 -LRB- 14.4 -- 16.6 -RRB- 8.4 -LRB- 8.0 -- 8.9 -RRB- 0.47 -LRB- 0.43 -- 0.51 -RRB- 0.26 -LRB- 0.25 -- 0.28 -RRB- 494.7 -LRB- 459.4 -- 532.7 -RRB- 0.480 -LRB- 0.431 -- 0.533 -RRB- 4.9 -LRB- 4.4 -- 5.3 -RRB- no18 .6 -LRB- 17.2 -- 20.1 -RRB- 14.9 -LRB- 14.1 -- 16.0 -RRB- 8.5 -LRB- 8.1 -- 8.9 -RRB- 0.47 -LRB- 0.44 -- 0.51 -RRB- 0.26 -LRB- 0.24 -- 0.27 -RRB- 424.8 -LRB- 397.1 -- 454.3 -RRB- 0.460 -LRB- 0.417 -- 0.507 -RRB- 4.5 -LRB- 4.1 -- 4.9 -RRB- P equality of means0 .3540.5530.7270.9380.6250.0030.5640.258 HRT use ever yes17 .9 -LRB- 14.5 -- 21.9 -RRB- 18.5 -LRB- 15.5 -- 22.0 -RRB- 11.9 -LRB- 10.5 -- 13.4 -RRB- 0.52 -LRB- 0.4 -- 0.6 -RRB- 0.26 -LRB- 0.2 -- 0.3 -RRB- 488.8 -LRB- 408.1 -- 585.5 -RRB- 0.667 -LRB- 0.515 -- 0.863 -RRB- 4.6 -LRB- 3.6 -- 5.8 -RRB- no18 .2 -LRB- 17.1 -- 19.3 -RRB- 14.9 -LRB- 14.2 -- 15.7 -RRB- 8.3 -LRB- 7.9 -- 8.5 -RRB- 0.47 -LRB- 0.4 -- 0.5 -RRB- 0.26 -LRB- 0.2 -- 0.3 -RRB- 452.4 -LRB- 429.4 -- 476.5 -RRB- .455 -LRB- .422-.490 -RRB- 4.7 -LRB- 4.4 - 4.9 -RRB- P-equality of means0 .8750.021 < 0.00050.2990.8480.4180.0050.870 Age at menopause < = 4718.4 -LRB- 16.33 -- 20.6 -RRB- 14.7 -LRB- 13.3 -- 16.2 -RRB- 8.5 -LRB- 7.9 -- 9.1 -RRB- 0.51 -LRB- 0.46 -- 0.57 -RRB- 0.28 -LRB- 0.26 -- 0.30 -RRB- 471.3 -LRB- 425.7 -- 521.9 -RRB- 0.465 -LRB- 0.402 -- 0.539 -RRB- 4.9 -LRB- 4.3 -- 5.6 -RRB- 48 -- 5019.8 -LRB- 17.94 -- 21.8 -RRB- 15.3 -LRB- 14.1 -- 16.6 -RRB- 8.6 -LRB- 8.1 -- 9.1 -RRB- 0.49 -LRB- 0.44 -- 0.53 -RRB- 0.26 -LRB- 0.24 -- 0.27 -RRB- 485.1 -LRB- 445.4 -- 528.4 -RRB- 0.433 -LRB- 0.383 -- 0.490 -RRB- 4.3 -LRB- 3.8 -- 4.8 -RRB- 51 -- 5217.5 -LRB- 15.49 -- 19.8 -RRB- 16.1 -LRB- 14.5 -- 17.9 -RRB- 8.3 -LRB- 7.7 -- 8.9 -RRB- 0.47 -LRB- 0.42 -- 0.52 -RRB- 0.26 -LRB- 0.24 -- 0.28 -RRB- 460.4 -LRB- 413.4 -- 512.7 -RRB- 0.476 -LRB- 0.408 -- 0.556 -RRB- 4.8 -LRB- 4.2 -- 5.5 -RRB- > = 5316.0 -LRB- 14.15 -- 18.2 -RRB- 0.15914.6 -LRB- 13.1 -- 16.2 -RRB- 8.5 -LRB- 7.8 -- 9.1 -RRB- 0.41 -LRB- 0.37 -- 0.46 -RRB- 0.24 -LRB- 0.22 -- 0.26 -RRB- 389.2 -LRB- 348.9 -- 434.1 -RRB- 0.527 -LRB- 0.450-0.616 -RRB- 4.9 -LRB- 4.3 -- 5.7 -RRB- P-trend0.7020 .7390.0140.0170.0390.3350.950 Time since menopause -LRB- years -RRB- < 618.7 -LRB- 16.7 -- 20.9 -RRB- 16.0 -LRB- 14.5 -- 17.6 -RRB- 9.2 -LRB- 8.6 -- 9.9 -RRB- 0.51 -LRB- 0.46 -- 0.57 -RRB- 0.27 -LRB- 0.25 -- 0.29 -RRB- 567.5 -LRB- 514.6 -- 625.9 -RRB- 0.493 -LRB- 0.427 -- 0.568 -RRB- 4.7 -LRB- 4.14 -- 5.35 -RRB- 10-Jun17.9 -LRB- 15.9 -- 20.0 -RRB- 14.4 -LRB- 13.1 -- 15.9 -RRB- 8.6 -LRB- 8.1 -- 9.3 -RRB- 0.46 -LRB- 0.42 -- 0.51 -RRB- 0.25 -LRB- 0.23 -- 0.27 -RRB- 450.6 -LRB- 408.0 -- 497.7 -RRB- 0.484 -LRB- 0.419 -- 0.559 -RRB- 4.6 -LRB- 3.99 -- 5.19 -RRB- 15-Nov17.9 -LRB- 15.9 -- 20.1 -RRB- 15.5 -LRB- 13.9 -- 17.1 -RRB- 8.2 -LRB- 7.6 -- 8.8 -RRB- 0.45 -LRB- 0.40 -- 0.50 -RRB- 0.27 -LRB- 0.24 -- 0.29 -RRB- 432.7 -LRB- 390.7 -- 479.2 -RRB- 0.457 -LRB- 0.394 -- 0.530 -RRB- 4.7 -LRB- 4.13 -- 5.39 -RRB- > = 1618.1 -LRB- 16.2 -- 20.2 -RRB- 14.9 -LRB- 13.6 -- 16.4 -RRB- 8.1 -LRB- 7.5 -- 8.6 -RRB- 0.47 -LRB- 0.42 -- 0.52 -RRB- 0.26 -LRB- 0.24 -- 0.28 -RRB- 390.1 -LRB- 354.9 -- 428.9 -RRB- 0.443 -LRB- 0.386 -- 0.509 -RRB- 4.7 -LRB- 4.13 -- 5.29 -RRB- P-trend0.7250 .4890.0030.2330.828 < 0.00010.2460.960 * Among parous participants § The always irregular category was not included when testing for trend In table 4 adjusted geometric means for each hormone according to the reproductive characteristics are shown . Participants in the lowest quartile of cumulative number of menstrual cycles tended to have higher SHBG -LRB- P trend = 0.013 -RRB- and lower SHBG/E2 -LRB- P trend = 0.050 -RRB- levels . Androstenedione and DHEAS levels increased with increasing age at menarche -LRB- P trend = 0.027 and 0.022 respectively -RRB- , a similar tendency was observed for E2 , although the P for trend did not reach statistical significance -LRB- P trend = .058 -RRB- . Women with more children , tended to have higher SBHG levels -LRB- P trend = 0.030 -RRB- , number of children was also related to lower SHBG/E2 -LRB- p trend = 0.010 -RRB- levels . No association was found between number of cycles before a FFTP , parity , age at FFTP and any of the hormones . Age at menopause related inversely with androstenedione and testosterone ; women with older age at menopause tend to have lower levels of such hormones -LRB- p trend = 0.024 and 0.015 respectively -RRB- . Table 4Hormones adjusted means † -LRB- 95 % CI -RRB- for serum sex hormones and SHBG levels according to reproductive characteristics SHBG -LRB- μg/ml -RRB- Estrone -LRB- pg/ml -RRB- Estradiol -LRB- pg/ml -RRB- Androstenedione -LRB- ng/ml -RRB- Testosterone -LRB- ng/ml -RRB- DHEAS -LRB- ng/ml -RRB- SBHG/E2 - INDEXFA-INDEXLifetime number of menstrual cycles < = 41519.50 -LRB- 16.86 -- 22.46 -RRB- 15.75 -LRB- 13.83 -- 17.94 -RRB- 8.62 -LRB- 7.89 -- 9.43 -RRB- 0.571 -LRB- 0.495 -- 0.659 -RRB- 0.285 -LRB- 0.256 -- 0.317 -RRB- 519.57 -LRB- 454.41 -- 594.67 -RRB- 0.444 -LRB- 0.373 -- 0.528 -RRB- 4.76 -LRB- 4.06 -- 5.59 -RRB- 416 -- 45319.79 -LRB- 17.51 -- 22.35 -RRB- 13.28 -LRB- 11.88 -- 14.83 -RRB- 8.39 -LRB- 7.78 -- 9.04 -RRB- 0.448 -LRB- 0.396 -- 0.506 -RRB- 0.253 -LRB- 0.231 -- 0.278 -RRB- 436.16 -LRB- 388.77 -- 488.82 -RRB- 0.424 -LRB- 0.365 -- 0.492 -RRB- 4.27 -LRB- 3.72 -- 4.89 -RRB- 454 -- 49016.99 -LRB- 14.98 -- 19.26 -RRB- 16.26 -LRB- 14.51 -- 18.23 -RRB- 8.72 -LRB- 8.06 -- 9.41 -RRB- 0.434 -LRB- 0.383 -- 0.493 -RRB- 0.251 -LRB- 0.228 -- 0.276 -RRB- 427.96 -LRB- 380.31 -- 481.06 -RRB- 0.513 -LRB- 0.440 -- 0.597 -RRB- 4.76 -LRB- 4.14 -- 5.48 -RRB- > = 49115.94 -LRB- 13.82 -- 18.39 -RRB- 16.02 -LRB- 14.07 -- 18.24 -RRB- 8.53 -LRB- 7.81 -- 9.32 -RRB- 0.443 -LRB- 0.384 -- 0.511 -RRB- 0.257 -LRB- 0.231 -- 0.287 -RRB- 447.64 -LRB- 391.51 -- 511.83 -RRB- 0.535 -LRB- 0.450 -- 0.636 -RRB- 5.15 -LRB- 4.39 -- 6.04 -RRB- Always irregular § 16.48 -LRB- 13.87 -- 19.57 -RRB- 15.21 -LRB- 13.01 -- 17.78 -RRB- 8.04 -LRB- 7.24 -- 8.94 -RRB- 0.462 -LRB- 0.389 -- 0.548 -RRB- 0.255 -LRB- 0.224 -- 0.290 -RRB- 427.09 -LRB- 363.58 -- 501.69 -RRB- 0.488 -LRB- 0.397 -- 0.601 -RRB- 4.93 -LRB- 4.07 -- 5.96 -RRB- P-trend0.0130 .4740.8420.0890.4460.3490.0500.192 Number of menstrual cycles before a FFTP * < = 11819.83 -LRB- 17.51 -- 22.47 -RRB- 15.15 -LRB- 13.49 -- 17.01 -RRB- 8.22 -LRB- 7.61 -- 8.87 -RRB- 0.474 -LRB- 0.416 -- 0.540 -RRB- 0.265 -LRB- 0.241 -- 0.292 -RRB- 468.25 -LRB- 415.30 -- 527.42 -RRB- 0.414 -LRB- 0.356 -- 0.482 -RRB- 4.37 -LRB- 3.81 -- 5.02 -RRB- 119 -- 14718.41 -LRB- 16.18 -- 20.95 -RRB- 14.47 -LRB- 12.83 -- 16.33 -RRB- 8.38 -LRB- 7.75 -- 9.07 -RRB- 0.480 -LRB- 0.419 -- 0.550 -RRB- 0.253 -LRB- 0.229 -- 0.280 -RRB- 475.80 -LRB- 420.31 -- 538.61 -RRB- 0.455 -LRB- 0.389 -- 0.533 -RRB- 4.53 -LRB- 3.92 -- 5.22 -RRB- 148 -- 18516.09 -LRB- 13.81 -- 18.76 -RRB- 15.66 -LRB- 13.57 -- 18.06 -RRB- 8.85 -LRB- 8.05 -- 9.72 -RRB- 0.420 -LRB- 0.358 -- 0.493 -RRB- 0.258 -LRB- 0.229 -- 0.290 -RRB- 402.22 -LRB- 347.23 -- 465.91 -RRB- 0.549 -LRB- 0.456 -- 0.662 -RRB- 5.17 -LRB- 4.36 -- 6.13 -RRB- > = 18618.43 -LRB- 16.13 -- 21.05 -RRB- 14.86 -LRB- 13.13 -- 16.83 -RRB- 8.54 -LRB- 7.88 -- 9.27 -RRB- 0.461 -LRB- 0.401 -- 0.529 -RRB- 0.253 -LRB- 0.228 -- 0.280 -RRB- 445.86 -LRB- 392.29 -- 506.74 -RRB- 0.463 -LRB- 0.394 -- 0.545 -RRB- 4.54 -LRB- 3.92 -- 5.27 -RRB- Always irregular § 15.52 -LRB- 12.92 -- 18.65 -RRB- 14.81 -LRB- 12.49 -- 17.57 -RRB- 8.04 -LRB- 7.19 -- 8.99 -RRB- 0.467 -LRB- 0.386 -- 0.566 -RRB- 0.267 -LRB- 0.232 -- 0.307 -RRB- 438.34 -LRB- 367.97 -- 522.69 -RRB- 0.518 -LRB- 0.415 -- 0.648 -RRB- 5.39 -LRB- 4.397 -- 6.60 -RRB- P-trend0.2820 .9290.4160.6050.5730.4230.1960.522 Age at menarche < = 1119.26 -LRB- 15.72 -- 23.67 -RRB- 14.67 -LRB- 12.23 -- 17.58 -RRB- 7.56 -LRB- 6.67 -- 8.55 -RRB- 0.440 -LRB- 0.360 -- 0.538 -RRB- 0.272 -LRB- 0.234 -- 0.316 -RRB- 424.54 -LRB- 352.13 -- 511.83 -RRB- 0.392 -LRB- 0.307 -- 0.502 -RRB- 4.71 -LRB- 3.75 -- 5.90 -RRB- 1218.10 -LRB- 16.04 -- 20.43 -RRB- 13.98 -LRB- 12.55 -- 15.58 -RRB- 8.53 -LRB- 7.93 -- 9.19 -RRB- 0.454 -LRB- 0.403 -- 0.512 -RRB- 0.249 -LRB- 0.228 -- 0.272 -RRB- 423.27 -LRB- 378.42 -- 472.95 -RRB- 0.471 -LRB- 0.407 -- 0.546 -RRB- 4.51 -LRB- 3.94 -- 5.16 -RRB- 1316.35 -LRB- 14.58 -- 18.32 -RRB- 15.52 -LRB- 14.01 -- 17.18 -RRB- 8.17 -LRB- 7.63 -- 8.77 -RRB- 0.458 -LRB- 0.409 -- 0.513 -RRB- 0.254 -LRB- 0.233 -- 0.276 -RRB- 444.52 -LRB- 400.21 -- 493.74 -RRB- 0.500 -LRB- 0.436 -- 0.574 -RRB- 4.87 -LRB- 4.29 -- 5.53 -RRB- 1417.79 -LRB- 15.78 -- 20.06 -RRB- 15.41 -LRB- 13.85 -- 17.15 -RRB- 8.58 -LRB- 7.98 -- 9.23 -RRB- 0.440 -LRB- 0.391 -- 0.496 -RRB- 0.248 -LRB- 0.227 -- 0.271 -RRB- 448.99 -LRB- 402.22 -- 501.69 -RRB- 0.482 -LRB- 0.417 -- 0.558 -RRB- 4.58 -LRB- 4.01 -- 5.23 -RRB- 1519.73 -LRB- 16.91 -- 23.01 -RRB- 17.06 -LRB- 14.86 -- 19.57 -RRB- 9.02 -LRB- 8.21 -- 9.90 -RRB- 0.518 -LRB- 0.444 -- 0.603 -RRB- 0.286 -LRB- 0.255 -- 0.320 -RRB- 516.98 -LRB- 448.54 -- 595.26 -RRB- 0.457 -LRB- 0.379 -- 0.550 -RRB- 4.78 -LRB- 4.03 -- 5.67 -RRB- > = 1618.58 -LRB- 15.99 -- 21.58 -RRB- 15.06 -LRB- 13.16 -- 17.22 -RRB- 8.78 -LRB- 8.02 -- 9.63 -RRB- 0.553 -LRB- 0.476 -- 0.641 -RRB- 0.276 -LRB- 0.247 -- 0.308 -RRB- 494.23 -LRB- 430.09 -- 567.36 -RRB- 0.473 -LRB- 0.395 -- 0.567 -RRB- 4.79 -LRB- 4.05 -- 5.66 -RRB- P-trend0.5770 .1810.0580.0270.1940.0220.6210.739 Ever pregnant yes18 .17 -LRB- 17.13 -- 19.28 -RRB- 14.94 -LRB- 14.17 -- 15.75 -RRB- 8.41 -LRB- 8.12 -- 8.72 -RRB- 0.463 -LRB- 0.437 -- 0.491 -RRB- 0.258 -LRB- 0.247 -- 0.269 -RRB- 452.59 -LRB- 428.80 -- 478.18 -RRB- 0.463 -LRB- 431 -- 497 -RRB- 4.62 -LRB- 4.33 -- 4.94 -RRB- no16 .56 -LRB- 14.19 -- 19.34 -RRB- 17.12 -LRB- 4.91 -- 19.65 -RRB- 8.88 -LRB- 8.08 -- 9.76 -RRB- 0.528 -LRB- 0.453 -- 0.616 -RRB- 0.273 -LRB- 0.244 -- 0.306 -RRB- 466.85 -LRB- 405.05 -- 538.08 -RRB- 0.536 -LRB- 0.445 -- 0.646 -RRB- 5.21 -LRB- 4.39 -- 6.18 -RRB- P-equality of means0 .2730.0720.2990.1190.8020.6930.1520.204 Age at FFTP * < = 2119.89 -LRB- 16.98 -- 23.29 -RRB- 15.53 -LRB- 13.45 -- 17.94 -RRB- 8.26 -LRB- 7.50 -- 9.08 -RRB- 0.454 -LRB- 0.386 -- 0.534 -RRB- 0.248 -LRB- 0.220 -- 0.280 -RRB- 451.24 -LRB- 388.77 -- 523.74 -RRB- 4.05 -LRB- 3.39 -- 4.82 -RRB- 0.415 -LRB- 0.343 -- 0.503 -RRB- 22 -- 2417.46 -LRB- 15.52 -- 19.63 -RRB- 14.41 -LRB- 12.96 -- 16.04 -RRB- 8.46 -LRB- 7.88 -- 9.07 -RRB- 0.466 -LRB- 0.413 -- 0.526 -RRB- 0.264 -LRB- 0.242 -- 0.289 -RRB- 464.05 -LRB- 415.71 -- 518.53 -RRB- 4.84 -LRB- 4.26 -- 5.52 -RRB- 0.484 -LRB- 0.420 -- 0.558 -RRB- 25 -- 2717.32 -LRB- 15.67 -- 19.16 -RRB- 15.01 -LRB- 13.69 -- 16.44 -RRB- 8.06 -LRB- 7.58 -- 8.57 -RRB- 0.463 -LRB- 0.417 -- 0.513 -RRB- 0.257 -LRB- 0.238 -- 0.277 -RRB- 445.41 -LRB- 405.05 -- 489.80 -RRB- 4.84 -LRB- 4.33 -- 5.41 -RRB- 0.465 -LRB- 0.412 -- 0.526 -RRB- > = 2818.67 -LRB- 16.63 -- 20.99 -RRB- 15.07 -LRB- 13.56 -- 16.76 -RRB- 8.84 -LRB- 8.24 -- 9.48 -RRB- 0.466 -LRB- 0.414 -- 0.525 -RRB- 0.258 -LRB- 0.237 -- 0.282 -RRB- 452.59 -LRB- 405.45 -- 504.72 -RRB- 4.59 -LRB- 4.04 -- 5.22 -RRB- 0.473 -LRB- 0.411 -- 0.545 -RRB- P-trend0.7410 .9880.3890.8580.8230.8500.4830.444 Number of liveborn 016.56 -LRB- 14.18 -- 19.32 -RRB- 17.12 -LRB- 14.91 -- 19.67 -RRB- 8.87 -LRB- 8.08 -- 9.76 -RRB- 0.527 -LRB- 0.452 -- 0.615 -RRB- 0.273 -LRB- 0.244 -- 0.306 -RRB- 466.85 -LRB- 404.64 -- 538.08 -RRB- 0.536 -LRB- 0.445 -- 0.646 -RRB- 5.21 -LRB- 4.39 -- 6.18 -RRB- 116.14 -LRB- 13.05 -- 19.94 -RRB- 16.39 -LRB- 13.56 -- 19.81 -RRB- 8.33 -LRB- 7.32 -- 9.49 -RRB- 0.411 -LRB- 0.333 -- 0.508 -RRB- 0.237 -LRB- 0.203 -- 0.277 -RRB- 438.78 -LRB- 361.04 -- 533.79 -RRB- 0.517 -LRB- 0.400 -- 0.667 -RRB- 4.69 -LRB- 3.71 -- 5.95 -RRB- 217.57 -LRB- 15.99 -- 19.32 -RRB- 14.88 -LRB- 13.68 -- 16.20 -RRB- 8.71 -LRB- 8.22 -- 9.23 -RRB- 0.471 -LRB- 0.429 -- 0.517 -RRB- 0.257 -LRB- 0.240 -- 0.276 -RRB- 456.69 -LRB- 418.63 -- 498.19 -RRB- 0.496 -LRB- 0.443 -- 0.555 -RRB- 4.85 -LRB- 4.37 -- 5.39 -RRB- 318.05 -LRB- 16.13 -- 20.19 -RRB- 14.73 -LRB- 13.33 -- 16.29 -RRB- 8.28 -LRB- 7.73 -- 8.86 -RRB- 0.448 -LRB- 0.401 -- 0.502 -RRB- 0.259 -LRB- 0.239 -- 0.282 -RRB- 453.05 -LRB- 408.71 -- 502.70 -RRB- 0.459 -LRB- 0.401 -- 0.525 -RRB- 4.62 -LRB- 4.07 -- 5.23 -RRB- > = 420.18 -LRB- 17.85 -- 22.83 -RRB- 14.83 -LRB- 13.28 -- 16.56 -RRB- 8.12 -LRB- 7.53 -- 8.76 -RRB- 0.486 -LRB- 0.430 -- 0.550 -RRB- 0.263 -LRB- 0.240 -- 0.288 -RRB- 449.89 -LRB- 401.82 -- 504.21 -RRB- 0.402 -LRB- 0.346 -- 0.467 -RRB- 4.23 -LRB- 3.69 - 4.85 -RRB- P-trend0.0300 .0800.1170.5780.9330.7800.0100.064 Age at FFTP * < = 2119.89 -LRB- 16.98 -- 23.29 -RRB- 15.53 -LRB- 13.45 -- 17.94 -RRB- 8.26 -LRB- 7.50 -- 9.08 -RRB- 0.454 -LRB- 0.386 -- 0.534 -RRB- 0.248 -LRB- 0.220 -- 0.280 -RRB- 451.24 -LRB- 388.77 -- 523.74 -RRB- 0.405 -LRB- 0.339 -- 0.482 -RRB- 4.15 -LRB- 3.43 -- 5.03 -RRB- 22 -- 2417.46 -LRB- 15.52 -- 19.63 -RRB- 14.41 -LRB- 12.96 -- 16.04 -RRB- 8.46 -LRB- 7.88 -- 9.07 -RRB- 0.466 -LRB- 0.413 -- 0.526 -RRB- 0.264 -LRB- 0.242 -- 0.289 -RRB- 464.05 -LRB- 415.71 -- 518.53 -RRB- 0.484 -LRB- 0.426 -- 0.552 -RRB- 4.84 -LRB- 4.20 -- 5.58 -RRB- 25 -- 2717.32 -LRB- 15.67 -- 19.16 -RRB- 15.01 -LRB- 13.69 -- 16.44 -RRB- 8.06 -LRB- 7.58 -- 8.57 -RRB- 463 -LRB- 0.417 -- 0.513 -RRB- 0.257 -LRB- 0.238 -- 0.277 -RRB- 445.41 -LRB- 405.05 -- 489.80 -RRB- 0.484 -LRB- 0.433 -- 0.541 -RRB- 4.65 -LRB- 4.12 -- 5.26 -RRB- > = 2818.67 -LRB- 16.63 -- 20.99 -RRB- 15.07 -LRB- 13.56 -- 16.76 -RRB- 8.84 -LRB- 8.24 -- 9.48 -RRB- 0.466 -LRB- 0.414 -- 0.525 -RRB- 0.258 -LRB- 0.237 -- 0.282 -RRB- 452.59 -LRB- 405.45 -- 504.72 -RRB- 0.459 -LRB- 0.404 -- 0.522 -RRB- 4.73 -LRB- 4.11 -- 5.45 -RRB- P-trend0.7410 .9880.3890.8580.8230.8500.4830.444 Age at menopause ∞ < = 4718.16 -LRB- 16.20 - 20.37 -RRB- 14.74 -LRB- 13.30 -- 16.33 -RRB- 8.38 -LRB- 7.81 -- 8.98 -RRB- 0.511 -LRB- 0.456 -- 0.572 -RRB- 0.281 -LRB- 0.258 -- 0.306 -RRB- 445.41 -LRB- 401.01 -- 494.72 -RRB- 0.461 -LRB- 0.402 -- 0.530 -RRB- 4.94 -LRB- 4.35 -- 5.61 -RRB- 48 -- 5019.26 -LRB- 17.53 -- 21.16 -RRB- 15.41 -LRB- 14.17 -- 16.76 -RRB- 8.61 -LRB- 8.12 -- 9.15 -RRB- 0.484 -LRB- 0.441 -- 0.532 -RRB- 0.259 -LRB- 0.241 -- 0.277 -RRB- 481.06 -LRB- 441.42 -- 524.79 -RRB- 0.447 -LRB- 0.399 -- 0.501 -RRB- 4.38 -LRB- 3.95 -- 4.86 -RRB- 51 -- 5216.76 -LRB- 14.86 -- 8.89 -RRB- 16.23 -LRB- 14.57 -- 18.06 -RRB- 8.36 -LRB- 7.77 -- 8.99 -RRB- 0.472 -LRB- 0.419 -- 0.532 -RRB- 0.261 -LRB- 0.238 -- 0.285 -RRB- 462.20 -LRB- 413.64 -- 516.46 -RRB- 0.499 -LRB- 0.431 -- 0.577 -RRB- 5.01 -LRB- 4.38 -- 5.72 -RRB- > = 5316.96 -LRB- 15.01 -- 19.18 -RRB- 14.47 -LRB- 12.96 -- 16.13 -RRB- 8.50 -LRB- 7.88 -- 9.15 -RRB- 0.411 -LRB- 0.364 -- 0.464 -RRB- 0.238 -LRB- 0.217 -- 0.261 -RRB- 416.55 -LRB- 372.41 -- 466.38 -RRB- 0.501 -LRB- 0.432 -- 0.580 -RRB- 4.65 -LRB- 4.06 -- 5.33 -RRB- P-trend0.3360 .7700.8540.0240.0150.6450.3740.690 † Adjusted for age at intake , years since menopause , body mass index -LRB- BMI -RRB- at examination , use of hormone replacement therapy -LRB- HRT -RRB- ever -LRB- Y/N -RRB- , use of oral contraceptive -LRB- OC -RRB- ever -LRB- Y/N -RRB- , smoking habits , total alcohol consumption -LRB- g/day as a continuous variable -RRB- and physical activity -LRB- Voorrips total score as a continuous variable -RRB- . For analysis of the `` lifetime cumulative number of menstrual cycles '' and `` number of cycles before a FFTP '' variables , we also adjusted for more than one year of irregular cycles -LRB- Y/N -RRB- § The always irregular category was not included when testing for trend * Among parous participants ∞ Number of years since menopause was not included in the model Discussion The results of the present study suggest that the `` lifetime cumulative number of cycles '' is related to SHBG and that some reproductive characteristics are also associated to postmenopausal serum sex hormone levels . We noted significant associations after adjusting for important confounders , the `` lifetime cumulative number of menstrual cycles '' related inversely with levels of SHBG and positively with SHBG/E2 . Age at menarche directly relates to both DHEAS and androstenedione . Number of children had a significant relation with levels of SHBG and SHBG/E2 and age at menopause was indirectly associated to androstenedione and testosterone . Several studies have investigated the relation between reproductive risk factors and endogenous sex hormone levels in postmenopausal women , but with conflicting results -LSB- 6 , 13 , 15 , 24 -- 27 -RSB- . The patterns of risk associated with reproductive history suggest that prolonged exposure to ovarian hormones increases breast cancer occurrence -LSB- 8 , 28 , 29 -RSB- . The cumulative number of menstrual cycles has been used as a proxy for ovarian activity , women in the highest quartile of the `` lifetime cumulative number of menstrual cycles '' estimate , have an increased breast cancer risk when compared with women in the lowest quartile -LSB- 17 , 18 -RSB- . A significant inverse relation between number of menstrual cycles and SHBG was observed in our study . It has been previously described that SHBG decrease the proportion of E2 that is able to leave the circulation and enter the cells , and an inverse relation between concentration of SHBG and breast cancer has been observed in epidemiological studies -LSB- 1 , 10 -RSB- . Our findings suggest therefore , that postmenopausal free levels of estrogens or androgens may be related to the `` lifetime cumulative number of menstrual cycles '' reflecting lifetime exposure to ovarian hormones . Early age at menarche and late age at menopause have long being recognized as risk factors for breast cancer . A 1-year delay in the onset of menarche is associated with a 5 % reduction in risk for developing breast cancer in later life -LSB- 30 -RSB- . We found that age at menarche has a direct relation with serum levels of DHEAS and androstenedione measured after the menopause . Androgens have been associated with breast cancer risk , women with breast cancer tend to have higher levels of DHEAS and androstenedione -LSB- 2 , 4 , 31 , 32 -RSB- . It has been proposed that in postmenopausal women DHEAS might act as a moderate estrogen agonist , through competitive binding of its metabolite 5-androstene-3B ,17 B-diol -LSB- 33 -RSB- . It is also well known that the peripheral conversion of adrenal androstenedione is the principal source of E1 in postmenopausal women -LSB- 34 -RSB- , therefore we would expect an inverse association between both DHEAS and androstenedione and age at menarche . Madigan et al. showed , after adjusting for BMI and years since menopause , that young age at menarche , was associated with higher levels of androstenedione , but also of E1 and E2 -LSB- 15 -RSB- . Our results are in conflict with such findings , however several studies have found no association between age at menarche and SHBG , estrogens or androgens -LSB- 14 , 16 , 35 , 36 -RSB- . Childbearing and a young age at FFTP protect against breast cancer and additional pregnancies further reduce the risk -LSB- 7 , 10 , 37 , 38 -RSB- . We found that parous women tend to have lower levels of E1 , however this difference was not statistically significant -LRB- P = .072 -RRB- . Lamar et al. -LSB- 14 -RSB- found that nulliparous women had higher testosterone levels , a finding that could contribute to the increased risk of breast cancer in nulliparous women . Our findings also showed that the number of live births is directly related to SHBG , and indirectly to SHBG/E2 and FAI -LRB- P for trend for FAI did not reach statistical significance , P = 0.064 -RRB- . This observation is in conflict with the known association between low SBGH levels and breast cancer risk , and the protective effect that the number of pregnancies has on breast cancer -LSB- 28 , 29 , 38 , 39 -RSB- . It is important to mention that a woman 's genetic and environmental profile may influence both , her ability to have children and her postmenopausal sex hormone concentrations , making these observations difficult to interpret . It has been hypothesized that the overall effect of parity is due to a protective effect of a young age at FFTP -LSB- 40 -RSB- , another proposed mechanism is through lactation , as breastfeeding induces final differentiation of the terminal duct epithelium making it relatively insensitive to hormonal stimulation -LSB- 41 , 42 -RSB- . Despite these observations we found no relation between age at FFTP and any of the hormones . No relation between parity , number of pregnancies or age at FFTP and serum hormone levels was reported by several studies . -LSB- 12 , 14 -- 16 , 43 , 44 -RSB- . We observed an indirect association between age at menopause and both , androstenedione and testosterone . Several studies have failed in finding an association between age at menopause and sex hormones -LSB- 12 , 14 , 16 -RSB- , however a direct association with menopause and androstenedione has been reported -LSB- 15 -RSB- , as well as a relation between age at menopause and E2 in a group of 173 postmenopausal overweight women -LSB- 13 -RSB- . To appreciate the findings of our study , some strengths and limitations need to be mentioned . The main advantage is our large sample size , to the best of our knowledge this is the largest study assessing the relationship between reproductive risk factors and serum sex hormone levels in naturally menopausal women and the first one evaluating the relationship between sex hormones and an index that can be used as a proxy of ovarian exposure . Another advantage is that we attempted to adjust for all relevant covariates , in order to obtain fully adjusted estimates . The participants in this cross-sectional study originated from a random sample of a large cohort , and blood samples where drawn from 97.5 % of the 17,357 participants , favoring the generalization of our results . Given the prospective nature of the Prospect-EPIC study , and because participants were recruited through an existing population-based breast cancer screening program , we included only disease-free participants at baseline blood collection . A limitation of this study is that only a single blood sample was assayed per participant , however it has been shown that a single measure provides substantial information in postmenopausal women for E1 , E2 and SHBG -LSB- 45 -RSB- . Serial measurements of serum hormones in postmenopausal women suggest that a single measurement can reliably categorize women , at least over the short term . Intraclass correlation coefficients of hormone measurements in serum collected over a 3-year period were reported to be between 0.68 and 0.78 for the estrogens , 0.66 and 0.88 for the androgens , and 0.92 for SHBG -LSB- 46 -RSB- . We did not have information regarding premenopausal sex hormone concentrations in the participants of this study ; it remains unknown whether some underlying hormonal profile could have influenced both , reproductive capabilities and postmenopausal sex hormone concentrations . It is also possible that premenopausal hormone levels are more related to reproductive factors than postmenopausal levels , and that is as a proxy for premenopausal levels that postmenopausal levels relate to reproductive characteristics . We should consider that the data used regarding reproductive characteristics are prone to recall errors . However , it is unlikely that recall errors are related to endogenous hormone levels themselves , if any misclassification occurred , it would have been non-differential . In summary , in this group of naturally postmenopausal women , the `` lifetime cumulative number menstrual cycles '' was related only to SHBG , suggesting that free levels of estrogens or androgens may be related to this index , reflecting lifetime exposure to ovarian hormones . Our findings show that some reproductive characteristics are related to postmenopausal serum sex hormone levels , however we do not find clear evidence to explain the mechanism by which reproductive risk factors influence hormone-related cancers in naturally postmenopausal women . It seems that reproductive and menstrual characteristics do not affect postmenopausal breast cancer risk via a long-term effect on sex hormone levels . The association of reproductive risk factors and breast cancer could be a result of prolonged exposure to ovarian hormones , and not only the product of a direct , long-lasting effect of sex hormone serum concentrations . Further research is needed in order to unravel the biological mechanisms through which reproductive characteristics relate to breast cancer risk .

O B I I I I O O O O O O O O O O B I I I I O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O B I O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I I I O O O B I O O O O O O O O O O O O O B I O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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reproductive characteristics
breast cancer
sex hormones
cumulative number of menstrual cycles
risk factors


Is diagnosing exposed dentine a suitable tool for grading erosive loss ? Quantifying tooth wear in general and erosion in particular mostly is made by distinguishing between lesions restricted to enamel and lesions reaching the underlying dentine . Various scores for grading have been used , but in all systems , higher scores are given in cases of exposed dentine , thus , indicating a more severe stage of the condition . Clinical diagnosis of exposed dentine is made by assessing changes in colour or optical properties of the hard tissues . This paper aims to review the literature and discuss critically problems arising form this approach . It appears that classifying the severity of erosion by the area or depth of exposed dentine is difficult and poorly reproducible , and taking into account the variation of enamel thickness , the amount of tissue lost often is not related simply to the area of exposed dentine . There has still been very little longitudinal investigation of the significance of exposed dentine as a prognostic indicator . Further work and discussion is needed to reevaluate the explanative power of current grading procedures . Introduction This review illustrates the problems that clinicians and researchers have experienced in quantifying tooth erosion . Assessing the degree of erosion in an individual may be difficult -LSB- 32 -RSB- , but is important , as it reflects net exposure to the erosive forces and the opposing forces of protection , for example from saliva . Grading erosion present plays a part in the assessment of the problem , the need for treatment and , potentially , may indicate means for prevention of further tooth wear . If a reliable method for assessing the loss in vivo of tooth substance were available , then it might be possible to determine if erosion was continuing or had been halted , for example by preventive actions . Whilst some assessment of enamel erosion might be possible by assessing the progressive loss of anatomical contour , this is more difficult when erosion has reached the dentine . The diagnosis of exposed dentine is made by assessing changes in colour -LSB- 43 -RSB- or changes in the optical properties of the hard tissues , the validity of which , however , has not yet been investigated . This paper will consider the following main points : Does dentine exposure correlate with the severity of erosion?Can dentine exposure be reliably and reproducibly diagnosed?What is the interplay of factors causing tooth wear and how can other forms of tooth wear be distinguished from erosion when the wear has reached dentine?Are the parameters used for grading tooth erosion applicable to both the primary and secondary dentitions?Could symptoms of dentine hypersensitivity assist in the grading of erosive loss ? Does dentine exposure correlate with the severity of erosion ? For grading , the overwhelming majority of tooth wear and erosion indices use the differentiation between lesions restricted to enamel and lesions reaching the underlying dentine . The rationale for linking severity of erosion to extension into dentine probably stems from experience with dental caries and restorative procedures , but has not yet been critically discussed . It is an interesting question whether the progression of erosion from enamel into dentine has any significance in terms of disease , although it may well have a bearing in terms of treatment and , sometimes , the presence of symptoms of hypersensitivity felt by the patient . One of the most widely used indices for assessing tooth erosion is that of Lussi et al. -LSB- 30 -RSB- , albeit sometimes modified -LSB- 6 -RSB- . This index does indeed attempt to grade the severity of erosion by assessing the degree of dentine exposure in a simple and , presumably reproducible , way as shown in Table 1 . As can be seen , grades 2 and 3 record increased severity of erosion on facial surfaces by judging the area of exposed dentine , rather than loss of dentine . On other surfaces , grade 2 requires the involvement of dentine . Table 1Use of the Lussi Index for grading the severity of dentine loss -LRB- in bold text -RRB- Index ScoreObservationFacial surfaces0No erosion , glazed appearance , absence of developmental ridges possible1Loss of surface enamel , dentine not involved2Erosion into dentine < 50 % of affected surface3Erosion into dentine > 50 % of affected surfaceOther surfaces0No erosion , glazed appearance , absence of developmental ridges possible1Slight erosion , rounded cusps , restorations stand proud of enamel , no dentine erosion2Severe erosion , more pronounced than score 1 , dentine involved Other indices use thirds of the affected surface with exposed dentine as thresholds -LSB- 13 , 35 , 41 -RSB- or score the severity of lesions using a more detailed grading with respect to depth of the lesion , as enamel loss only as code 1 or 2 , loss of enamel with exposure of dentine with the enamel dentine junction -LRB- EDJ -RRB- visible as code 3 , loss of enamel and dentine beyond EDJ as code 4 and loss of enamel and dentine with exposure of pulp as code 5 -LSB- 36 -RSB- . Despite variations in the definition of scores , all indices give higher scores when dentine is exposed , thus , indicating a more severe stage of the condition . This suggests that the amount of tissue loss must be higher when dentine is exposed than when enamel coverage is still present . When considering the thickness of enamel , however , it is obvious that this is not always the case . Enamel gradually thickens from the cervical region occlusally . At the coronal third of the crown , the enamel thickness is about 1.5 mm , in the cervical third , about 0.5 mm and becomes increasingly thinner towards the enamel cementum junction -LSB- 26 -RSB- . Thus , when the entire smooth surface of a tooth is exposed to acid , the dentine will be first exposed in the cervical region . At the occlusal area , enamel is thickest at the functional cusps , in upper molars . In lower molars , however , the enamel is thinnest at the mesiobuccal cusp , and is progressively thicker in order from the mesiolingual and distolingual to the distobuccal cusp tips -LSB- 26 -RSB- . This would explain the finding that lower first molars , particularly the mesio-buccal cusp tip , is the region where exposed dentine occurs most often . Taking into account the gross variation in enamel thickness , it is not surprising that the correlation between exposed dentine and the severity of wear is weak . A comparison of the amount of tissue loss assessed visually and histological findings revealed that the percentage of teeth with exposed dentine was high even in cases with minor substance loss and , in contrast , that enamel can be present in teeth with moderate to severe substance loss . Furthermore , dentine was exposed in all cases of cupping or grooving even if only minor substance loss occurred -LSB- 17 -RSB- . Similar results have been found in a study investigating primary teeth -LSB- 5 -RSB- . This showed that in 31 teeth with visually diagnosed wear , only three had enamel present histologically , and even in one of ten teeth in which no wear was diagnosed visually , the histological examination revealed exposed dentine . Once dentine is exposed , it is more prone than enamel to abrasion -LSB- 25 , 21 -RSB- since its microhardness is much lower than that of enamel -LSB- 33 -RSB- . When the severity of lesions is defined by the degree of exposure of dentine , the severity score could assume that tooth wear will progress more rapidly in the future . However , this has not been proven in incidence studies . The predictive value of a diagnosis of exposed dentine to future dental erosion or other forms of tooth wear is far from clear , and longitudinal studies are urgently needed to determine the progression , particularly of erosion , at different sites in the dentition . Can dentine exposure be reliably and reproducibly diagnosed ? Cupping of the cusp tips on molar teeth is one of the most common presentations of erosion , for example in teenagers -LRB- Fig. 1 -RRB- . This has been found in a recent epidemiological study of erosion in Iceland -LSB- 6 -RSB- and was also reported in other studies -LSB- 16 , 30 , 42 -RSB- . Fig. 1Cupping of the cusp tips on the molar teeth is an early sign of erosion where extension of erosion into dentine is difficult to determine One major problem in assessing the degree of erosion in cupping is whether or not the dentine has been exposed at the base of the lesion . Because labial and palatal enamel surfaces have a greater surface area , the observer better appreciates their surface anatomy than with a narrow cup-like lesion formed into a tooth cusp tip . Thus , grading the severity of cuppings is more difficult than perhaps it is for labial and palatal surfaces . Ganss et al. -LSB- 17 -RSB- demonstrated that when compared with histological examination , only 65 % of areas with exposed dentine , 88 % of areas with enamel present and 67 % of all areas examined had been diagnosed correctly . Clinicians demonstrated relatively poor reliability and reproducibility in their diagnosis of dentine exposure regardless of their professional experience . Al Malik et al. -LSB- 5 -RSB- have also shown that while grading erosion from visual and photographic records gave comparable scores , the degree of erosion was underestimated compared with the degree of tooth wear determined histologically . One way to increase the reliability of indices is to keep the grading scheme simple because minor differences in severity are difficult to assess , at least with the naked eye . For example , in a study from van Rijkom et al. -LSB- 43 -RSB- , two scores for enamel and dentine tissue loss each were used scoring slight enamel wear as 1 , deep enamel wear as 2 , wear into dentine as 3 and wear into dentine for more than one half of smooth surfaces as 4 , and the Kappa values achieved were low . Larsen et al. -LSB- 28 -RSB- , in contrast , attempted a prevalence study of tooth erosion using seven examiners and only three clear criteria defining grade 1 as erosion limited to the enamel , erosion exposing the dentine less than 50 % of the area of the surface as 2 and erosion exposing dentine in more than 50 % of the surface as 3 . Despite a careful calibration , including a thorough discussion of the criteria and the experience gained during the study , substantial inter-examiner differences in diagnosis were found . On the other hand , a good strength of agreement was achieved with an index proposed by Larsen et al. -LSB- 27 -RSB- where five scores for incisal/occlusal surfaces were used . Further investigations specifically aimed at assessing the reliability and reproducibility of scoring the involvement of dentine in the grading of erosion is necessary , should this criterion be included a clinical index of erosion . One future perspective could be the development of instrument-supported approaches . A recent report of optical techniques involving nitrogen-laser-induced fluorescence -LSB- 42 -RSB- appeared to offer the possibility of differentiating accurately between erosion into enamel and into dentine . This method may , according to the authors , even be applicable in vivo , although the reported studies were in vitro . What is the interplay of factors causing tooth wear and how can other forms of tooth wear be distinguished from erosion when the wear has reached dentine ? Factors leading to tooth wear , including erosive agents , such as dietary and gastric acid interact with protective factors from the diet , oral hygiene procedures and , particularly , saliva . Interestingly , one study of the relationship between erosion , soft drink consumption and reflux disease found the consumption of Coca-Cola ® three times per week to be the dominant factor in the development of molar erosion -LSB- 24 -RSB- , but the interplay of factors is often complex . Although the net outcome of erosive and reparative factors does not necessarily have to be tooth wear , it appears that once tooth wear has started , the interaction of these factors becomes ever more complex , not least by the time tooth wear has reached the dentine . Thus , the interplay of physical and chemical factors and the relevance of this to dentine wear will be considered together . Relevant physical forces are attrition and abrasion either from mastication or from oral hygiene procedures . Frequent exposure to dietary or gastric acid will lead to a softening of the dental hard tissues , making it easier for forces of attrition and abrasion to contribute significantly to the overall wear on the teeth . Whilst the effects of acids on enamel are relatively simple , leading to the dissolution of mineral and surface softening , the results on dentine are more complex . Chronic exposure to acids not only leads to an increasing loss of mineral but also to a progressive exposure of the organic dentine matrix , the effects of which , however , are not well known . The most investigated interplay between erosion and physical forces is the abrasive effect of toothbrushing . An increased wear of eroded enamel and dentine was demonstrated in a number of studies -LSB- 7 -- 9 , 14 , 21 , 38 , 45 -RSB- , even if one study did not prove this effect for dentine -LSB- 18 -RSB- . Azzopardi et al. -LSB- 11 -RSB- have also shown that a combination of erosion and abrasion causes more tooth wear than either tooth wear force on its own . Results of epidemiological studies are ambiguous in demonstrating only weak -LSB- 2 , 29 -RSB- or no -LSB- 3 , 37 , 39 -RSB- association between the occurrence of erosion and oral hygiene habits . With respect to abrasion from mastication , the occlusal surfaces are at particular risk . When dentine is exposed , abrasive foods and oral hygiene products tend to hollow out softer surface regions -LSB- 31 -RSB- . This can take place when an abrasive diet is consumed or in cases of acid-weakened dental tissues where a less abrasive bolus could also have similar effects . Clinically , the shape of occlusal lesions can be remarkably similar , making the diagnosis of the predominant aetiological factor difficult to determine . Perhaps commonest among these non-erosive factors contributing to tooth wear is attrition -LSB- 12 -RSB- . There is little information about the relative prevalence of facets in relation to different aetiological factors for wear and their progression when dentine is reached . It appears , however , that attrition tends to be superimposed on abrasion in cases of abrasive diet , as facets seldom occur in ancient remains and are not more prevalent in subjects with acidic diet when compared to subjects with an average western diet -LSB- 15 -RSB- . The problems of measuring tooth erosion in an individual presenting with tooth wear as shown in Figs. 2 , 3 and 4 are considerable , as not only is it difficult to envisage how much dentine and enamel has been lost but it is also increasingly difficult to attribute the loss of tissue to one particular aetiological factor or another as the tooth wear progresses . Even in clear cases of acid erosion , there may be a combination of intrinsic and extrinsic acid contributing to the clinical appearance . Fig. 2Clinical case to illustrate the difficulties of attributing diagnosis of tooth wear . This example of severe tooth wear was thought to be attrition , superimposed on erosion , of the occlusal surfaces of posterior teeth and palatal surfaces of maxillary teethFig . 3Erosion of the palatal cusps of maxillary molar and premolar teeth in a patient with gastro-oesophageal reflux disease . Note that dentine is visible on the mesio-palatal cusp of the first molar toothFig . 4Typical appearance of erosion in a patient with gastro-oesophageal reflux disease showing palatal erosion of the maxillary tooth cusps and buccal erosion of the mandibular tooth cusps . The degree of tooth wear and the presence of restorations make grading difficult Are the parameters used for grading tooth erosion applicable to both the primary and secondary dentitions ? One particularly difficult problem is assessing tooth wear in the deciduous dentition where the tooth structure withstands the forces of tooth wear somewhat less than the permanent dentition . An example is shown in Fig. 5 of a case where the aetiology of considerable erosion was never clear even when it continued into the permanent dentition . Indices used for the permanent dentition have also been used in the primary dentition -LSB- 3 , 35 -RSB- , but also , a special index for children has also been developed -LSB- 36 -RSB- . Fig. 5Clinical appearance of severe erosion , probably combined with other forms of tooth wear , in the deciduous dentition of a patient in whom no pathological reflux disease was recorded . The reported diet was relatively normal but erosion later appeared in the first permanent molar teeth The prevalence of erosive wear in the deciduous dentition varies between 6 and 100 % , and the percentage of children with erosion into dentine varies between 1 and 50 % -LSB- 4 , 10 , 20 , 23 , 46 -RSB- . The high prevalence of erosive wear in the deciduous dentition is remarkable when the short period in function is considered , but could be explained by the softer nature of the primary tooth substance leading to increased wear from physical impacts . The susceptibility to acids , in contrast , is probably not greater than for primary than for permanent dental tissues -LSB- 22 -RSB- . The enamel of deciduous teeth , however , is much thinner than that of permanent teeth -LSB- 19 -RSB- , which will lead to the rapid exposure of dentine . These factors will tend to make scores greater for deciduous teeth , and the links with known aetiological factors seem less clear . Studies using the same criteria for the primary and permanent dentition revealed higher prevalence data for the primary than for the permanent dentition when lesions involving dentine are regarded -LSB- 3 , 35 -RSB- . It is unclear if these data really reflect more severe tissue loss occurring in children or if the thin deciduous enamel leads to early exposure of dentine also in cases of minor wear , which would mean an overestimation of the condition . Perhaps the more relevant question is whether tooth erosion in the deciduous dentition is a prognostic indicator of likely erosion in the permanent dentition , as was the case in the subject illustrated in Fig. 5 . Meurman and ten Cate -LSB- 34 -RSB- have pointed out that there were no longitudinal clinical studies of progression of erosion in the deciduous teeth nor does the continuing of erosion into the permanent dentition appear to have received wide attention . In the last decade , only one study has demonstrated an increased risk of erosion in the permanent dentition when erosion had been present in the primary dentition . As study models were used , the relevance of exposed dentine was , however , not assessed -LSB- 16 -RSB- . Identifying the cause of erosion in the deciduous dentition may enable preventive measures , or treatment in the case of reflux disease , that could eliminate the risk of erosion in the permanent dentition . The UK National Guidelines in Paediatric Dentistry -LSB- 40 -RSB- notes the importance of recording the probable aetiological factors but notes specifically the unsuitability of the Smith and Knight Index -LSB- 41 -RSB- for measuring small longitudinal changes in tooth erosion and the problems of the complex interaction of causative and protective factors that make tooth erosion a more complex diagnostic and prognostic problem than would perhaps be thought initially to be the case . Could symptoms of dentine hypersensitivity assist in the grading of erosive loss ? Once tooth wear has extended into dentine , there is a possibility that the patient will experience symptoms of hypersensitivity -LSB- 44 -RSB- . There are numerous causes of dentine hypersensitivity and , therefore , great care is needed in diagnosing hypersensitivity as a result of tooth erosion reaching dentine . The mechanisms underlying hypersensitivity -LSB- 44 -RSB- strongly suggest that exposure of dentine tubules to the mouth will cause hypersensitivity in some , but not all , subjects . Consequently , the presence of symptoms of dentine hypersensitivity in a patient with signs of tooth erosion is strongly suggestive of extension of the erosion into dentine . While acidic drinks may expose the dentine tubules and remove early plaque formed on the dentine , thus leading to the symptoms of hypersensitivity , other factors such as toothbrushing may also contribute to this -LSB- 1 -RSB- . In conclusion , distinctions are commonly made between erosion into enamel and erosion into dentine . Methods of scoring are derived from parameters associated more with dental caries and restorative procedures for that disease rather than specifically for tooth wear . The interplay of tooth wear factors is complex and requires further research . Classifying the severity of erosion by the area or depth of exposed dentine is difficult and poorly reproducible and , particularly with respect to the variation of enamel thickness , the amount of tissue lost often is not related to dentine exposure . There has still been very little longitudinal investigation of the significance of exposed dentine as a prognostic indicator . Further work is needed to reevaluate the explanative power of current grading procedures .

O O O B O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O B O O O O O O O O O O O O B I O O O O O O B I O O O O O O O O O O O O O O O B I O O O O O O O O O O B O O O O O O O O O O B O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O B 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