Hum. Reprod. Advance Access originally published online on January 29, 2007
Human Reproduction 2007 22(4):1175-1185; doi:10.1093/humrep/del496
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Smoking, alcohol and caffeine in relation to ovarian age during the reproductive years
1 Research Foundation for Mental Hygiene, New York State Psychiatric Institute, New York, NY 10032, USA 2 Graduate School of Arts and Sciences, Columbia University, New York, NY 10016, USA 3 Epidemiology of Developmental Brain Disorders Department, New York State Psychiatric Institute, New York, NY 10032, USA 4 Mailman School of Public Health, Columbia University, New York, NY 10032, USA 5 Gertrude H. Sergievsky Center, Columbia University, New York, NY 10032, USA 6 Department of Obstetrics and Gynecology, Columbia University, New York, NY 10032, USA 7 Southwest Women's Sonography, Albuquerque, NM 87109, USA
8 To whom correspondence should be addressed at: c/o J. Kline, Psychiatric Institute, Epidemiology, 722 West 168th Street, Room 1607, New York, NY 10032, USA. E-mail: amk13{at}columbia.edu
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Abstract |
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BACKGROUND: We sought to determine whether smoking, alcohol and caffeine are related to four indicators of ovarian age: antral follicle count (AFC), follicle stimulating hormone (FSH), inhibin B and estradiol.
METHODS: Analyses drew on ultrasound scans and sera from 188 women, aged 22–49. We used least squares regression to estimate differences in AFC and hormone levels for women who smoke cigarettes or who drink alcohol or caffeine.
RESULTS: Current smoking is related to elevated FSH (
for ln(FSH) = 0.21, 95% CI 0.04, 0.39), but not to AFC, inhibin B or estradiol. Neither alcohol nor caffeine is related to any ovarian age indicator. Exploratory analyses suggest that the association of current smoking with FSH varies with age: comparing current with never smokers, at ages 30, 35, 40 and 45, estimated differences in mean FSH are 0.3, 1.3, 3.2 and 6.9 mIU/ml.
CONCLUSIONS: The association of current smoking with FSH may reflect accelerated oocyte atresia, impaired follicle quality or dysregulation of the hypothalamic–pituitary–ovarian axis. Identification of the causal mechanism has implications for prevention or treatment of conception delay, infertility and morbidity associated with early menopause.
Key words: antral follicles/epidemiology/FSH/inhibin B/smoking
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Introduction |
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The ability to conceive and to carry a pregnancy to term lessens as women grow older. At any given age, however, women vary in their fecundability and fertility. For women in their 30s and 40s, follicular and ovarian, rather than uterine, factors may be the primary determinants of fecundity (CDC, 2000
; Toner et al., 2002). It seems reasonable to infer, then, that variability in fecundability derives from differences in ovarian age that are tied to, but not entirely determined by, chronologic age. This paper examines whether or not cigarette smoking and, secondarily, two common exposures often correlated with smoking, alcohol and caffeine intake, are related to three indicators of ovarian age, namely, antral follicle count (AFC) and levels of follicle stimulating hormone (FSH) and inhibin B. We also examine associations with estradiol.
Several observations suggest that cigarette smoking is associated with older ovarian age. Current smoking is associated with earlier age at menopause (reviewed by Harlow and Signorello, 2000) and a shortened menopausal transition (McKinlay et al., 1992; Cooper et al., 1995). In a sample of women aged 35–54, the number of ovarian follicles is reduced among women who ever smoked (Westhoff et al., 2000). Smoking has been linked to increased levels of FSH (Cramer et al., 1994; Cooper et al., 1995; Backer et al., 1999; Cramer et al., 2002) and decreased levels of estrogen (MacMahon et al., 1982; Barbieri et al., 1986; Westhoff et al., 1996). Of two studies examining a possible relation between smoking and inhibin B, one (Freeman et al., 2005) showed no association, whereas the other (Lambert-Messerlian and Harlow, 2006) showed decreased levels among current smokers. Almost all of these observations derive from samples of women nearing the end of their reproductive prime (mid–30s or older). It is unclear whether or not the findings extend to younger women.
The observed associations between current smoking and indicators of advanced ovarian age might stem from effects on: oocyte quantity, e.g. accelerated oocyte atresia (Mattison and Thorgeirsson, 1978); oocyte quality, e.g. intrafollicular oxidative stress (Paszkowski et al., 2002) or disruption of endocrine function, e.g. activation of the aryl hydrocarbon receptor (reviewed by Valdez and Petroff, 2004). If smoking diminishes the size of the underlying oocyte pool, we might expect the number of recruited antral follicles to decrease accordingly, with a concomitant decrease in levels of inhibin B, a product of the antral follicles. Alternatively, if smoking alters oocyte or endocrine function, impairment might manifest in increased levels of FSH or decreased production of inhibin B even if no change is evident in the number of antral follicles. In either scenario, a critical threshold of the oocyte pool might confine associations to women of older chronologic age.
Evidence relating alcohol and caffeine to ovarian age is sparse. For alcohol, primary observations relate to a possible association with increased estrogen levels (Valimaki et al., 1983; Mendelson et al., 1987, 1988, 1989; Gavaler et al., 1987; Reichman et al., 1993; Muti et al., 1998), a result consistent with studies suggesting that age at menopause may be later among women who drink alcohol (Torgerson et al., 1997; Cooper et al., 2001; Brett and Cooper, 2003; Kinney et al., 2006). For caffeine, one study (Lucero et al., 2001) of women aged 36–45 shows an association between caffeine and increased estradiol levels. Other evidence derives from studies (Wilcox et al., 1988; Christiansonet al., 1989; Williams et al., 1990; Grodstein et al., 1993; Hatch and Bracken, 1993; Spinelli et al., 1997) that show an association with infertility [although not all studies (Joesoef et al., 1990; Florack et al., 1994; Curtis et al., 1997) confirm this finding].
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Materials and methods |
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Participants
Selection criteria and the protocol for this study are described in detail elsewhere (Kline et al., 2004
). The sample derives from a study designed to test the hypothesis that the association between advancing chronologic age and trisomic pregnancy reflects an association between the size of the oocyte pool and trisomy, with risk higher in women with fewer oocytes. AFC and hormone levels were similar for women with trisomic losses, women with nontrisomic chromosomally abnormal losses, women with chromosomally normal losses and women with live births. Briefly, from September 1998 to April 2001, we identified women aged 18 or older with singleton prefetal losses (developmental age less than 9 weeks) whose products of conception were submitted to the Pathology Department of a hospital in New York State. We asked permission to karyotype the abortus. If a woman's loss was successfully karyotyped, we asked her to complete a short telephone interview to determine her eligibility. Eligible women who consented to the protocol completed a more extensive telephone interview and made two visits to the study hospital during the first week of their second or later menstrual cycle, the first on day 1–4 for a blood draw and the second on day 5–7 for transvaginal sonography.
To obtain valid ovarian age measures, we required: no pituitary disorder or hormonal disorder related to ovarian function, no oophorectomy, no hormonal medication, no pregnancy at the time of ultrasound, breastfeeding no more than once per day during the menstrual cycle preceding the study assessments. We required that any diagnosis be current, the report of the diagnostic work-up informative and the clinical symptoms and treatment consistent with the diagnosis.
Women with pregnancy losses
Of the 244 women with karyotyped losses, 127 (52%) completed the protocol. The principal reasons for not completing the protocol were ineligibility (25%), primarily due to use of hormonal contraceptives or pregnancy soon after the index loss, and refusal (22%). Six women were excluded because of hormonal conditions and another six were excluded due to use of fertility drugs, although only two had experienced conception delay longer than 1 year prior to the study pregnancy. To maintain independence of observations, analyses exclude repeat study entrances of four women.
Women who completed the protocol were on average older than women who did not. The age difference arose chiefly because younger women were more likely to begin hormonal contraception immediately after their loss. Among the 207 women who completed the eligibility interview, adjusting for age, the odds of completing the protocol did not differ with education, parity or number of prior induced abortions; completion rates were significantly higher for women with one or more prior losses than for women with no prior losses (74% versus 56%).
Women with live births
For each woman with a trisomic loss who completed the study, we selected an age-matched control with a chromosomally and anatomically normal live birth 
1800 g, no pregnancy loss since the index pregnancy and no known trisomic pregnancy. They were selected from the hospital delivery log of women who delivered during the 7–13 months preceding the date of selection. Live birth controls were matched to trisomy cases for projected age ( ± 6 months) at the sonography visit. If a selected control was ineligible for the study or refused to participate, we replaced her. The protocol for women with live births was identical to the protocol for women with prefetal losses.
In total, we selected 219 women with live births, 65 of whom (30%) completed the protocol. The principal reasons for not completing the protocol were ineligibility (37%), primarily due to use of hormonal contraceptives or breastfeeding, and refusal (30%). Two women were excluded because of hormonal conditions.
Women who completed the protocol were on average older, though not significantly so, than women who did not. Among the 144 women who completed the eligibility interview, the odds of completing the protocol did not differ with educational attainment, parity, number of prior induced abortions or number of prior losses.
Characteristics of the sample (Table I)
Among the 188 women, 123 had an index pregnancy ending in loss and 65 an index pregnancy ending in live birth. Average age at ultrasound was 34 years (range 22–48). The majority were white (95%) and had completed high school (97%). Ninety-five percent completed the blood and sonography protocols after the second or third menstrual period following the index loss or, for women with live births, the introductory letter.
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Indicators of ovarian age
Antral follicle count
We used four transducers over the course of the study: the first two, Acuson EXP 128, operated at a frequency of 7 MHz; the second two, Acuson Sequoia (8–10 MHz) were usually used at 10 MHz. A sonography technician scanned each ovary in transverse and longitudinal views at a subjectively constant velocity, repeating scans, as needed, until she obtained an optimal scan.
For eight women, we were able to scan only one ovary even though, based on history and transabdominal scans, each woman was known to have two ovaries. Four additional women had conditions—three a cyst and one an endometrioma—which might have obscured the follicle count. For these 12 women, we imputed the total number of follicles in the ovary not scanned from regression equations that included age and the number of follicles in the contralateral ovary.
We videotaped the sonography scan. The study sonographer (M.L.R) identified the optimal scan, converted it to a digitized format and exported it to Matrox Inspector software for follicle counting and measurement. The scans were counted in randomized batches. The randomization procedure was unknown to the sonographer.
Each sonolucency interpreted as a follicle was followed through the scan to identify its maximum size. Its largest diameter was measured in the vertical plane using the centimetre scale generated by the ultrasound machine. To assess the reliability of the counting procedure, we counted again the follicles in 40 ovaries (Kline et al., 2004). The intraclass correlation coefficient was 0.92. Analyses use the second count for women whose scans were counted twice.
Among the 176 women with both ovaries scanned, counts ranged from 2 to 70 (median 15, mean 18.7, SD 12.8). The mean difference between counts in the left and right ovaries was 0.2 (SD 5.5, range – 15 to 28). The correlation between them was 0.71 (P < 0.0001).
Hormone levels
Blood samples were processed in a refrigerated centrifuge and, after separation, sera were frozen at – 25°C at the study hospital. They were then shipped to New York City and stored at – 20°C. FSH and estradiol were measured by solid–phase chemiluminescent enzyme immunoassays (Immulite, Diagnostic Products Co., Los Angeles, CA, USA). Inhibin B was measured by radioimmunoassay (Oxford Bio-Innovation Ltd., Upper Heyford, Oxfordshire, England). For FSH, sensitivity (the minimum detection limit) was 0.1 mIU/ml; intra- and inter-assay coefficients of variation (CV) were 9.3% and 10.5%, respectively. For inhibin B, sensitivity was 20 pg/ml; intra- and inter-assay CV were 5.1% and 6.2%, respectively. For estradiol, sensitivity was 20 pg/ml; intra- and inter-assay CV were 1.9% and 5%, respectively.
Smoking, alcohol and caffeine
Data on smoking, alcohol and caffeine were obtained by telephone interview shortly after a woman's eligibility status had been determined. The data were updated during a face-to-face interview at the time of the ultrasound. Smoking history was classified by status (never smoked, former smoker and current smoker) at the time of the ultrasound. Alcohol and caffeine intake were based on consumption during the month before the telephone interview. This time period ended, on average, 38.4 days (SD 26.1 days) before the ultrasound. We chose the month before the telephone interview rather than the week before ultrasound as the relevant exposure period on the assumption that chronic, rather than acute, exposure is most apropos. The correlations for intake levels of alcohol and caffeine during the month before the telephone interview compared with the week before ultrasound were 0.64 (P < 0.0001) and 0.90 (P < 0.0001), respectively.
Smoking
We asked each woman if she currently smoked and, if so, how many cigarettes she usually smoked. Women who were not current smokers were asked if they had ever smoked and, if so, the number of cigarettes they usually smoked and their age when they stopped smoking for the last time. Analyses classified women in three categories: never smoked, former smoker and current smoker. There were too few smokers to classify women by the number of cigarettes smoked.
We also asked each woman if her mother had ever smoked and, if yes, if her mother had smoked during the time she was pregnant with her.
Alcohol
We asked each woman on how many days per week she usually drank alcohol and the number of drinks per occasion. One drink was defined as 5 oz of wine, 12 oz of wine cooler, 12 oz of beer or 1.5 oz of liquor. The primary analyses defined alcohol consumption as the number of days per week a woman drank. We also examined alcohol exposure as days per week defined categorically (0, 1, 2 + ) and by the number of drinks per week. Among women who reported drinking alcohol, average intake was 10 drinks per month, equivalent to about 120 g of absolute alcohol.
We selected the number of days per week that women drank as the exposure of interest rather than the number of drinks per week [even though these variables are highly correlated (r = 0.8)] on the grounds that, at least among temperate drinkers, the relevant exposure is regular, moderate consumption (i.e. one drink every day is not equivalent to seven drinks on one day) (Purohit, 1998).
Caffeine
We asked about the usual frequency of consumption and size of serving for caffeinated coffee, decaffeinated coffee, caffeinated tea, caffeinated cola and caffeinated noncola. We estimated caffeine content as 135 mg 8 oz–1 cup of caffeinated coffee, 5 mg 8 oz–1 cup of decaffeinated coffee, 50 mg 8 oz–1 cup of caffeinated tea, 37.6 mg 12 oz–1can of caffeinated cola and 48.5 mg 12 oz–1 can of caffeinated noncola (Barone and Roberts, 1996; Beverage Digest, 2005; The Coca-Cola Company, 2004; The Pepsi Cola Company, 2004). The primary analyses defined caffeine exposure as the number of milligrams per day consumed. We also examined exposure in three categories of milligrams per day (0 to < 30, 30 to < 160 and 160 + ). Among women who reported drinking caffeinated beverages, average intake was 156 mg day–1, equivalent to slightly more than one cup of coffee.
The statistical analysis
The ovarian age indicators are related to chronologic age. For each exposure, therefore, we show the geometric means of the indicators within strata defined by chronologic age (22 to < 30, 30 to < 35, 35 to < 40, 40 to < 49).
We used ordinary least squares regression analysis to assess the associations of smoking, alcohol and caffeine with the four indicators of ovarian age. To meet the normal error assumption of least squares regression, we used a logarithmic transformation for all ovarian age indicators. For AFC, we used the transformation ln(1 + count) because, in theory, a woman might have no antral follicles. Thus, 100 x (e – 1) gives the percentage change in the geometric mean of the ovarian age indicator per unit change in the exposure.
All analyses adjusted for the design variable, outcome of the index pregnancy (loss versus live birth), although pregnancy outcome [whether defined by karyotype (Kline et al., 2004) or by loss versus live birth] is not associated with the ovarian age indicators. For each exposure, we tested whether associations with the ovarian age indicators varied with outcome of the index pregnancy (at 
= 0.01 to control Type I error). They did not.
All analyses adjusted for chronologic age. We fit models with linear and quadratic terms for age, retaining the quadratic term if it significantly improved the proportion of variance explained and visual inspection of the data suggested that the association with age was not log-linear.
We hypothesized that associations with older ovarian age might be evident only when the total oocyte pool falls below some critical threshold. Therefore, if the primary analyses suggested an association between an exposure and an ovarian age indicator, we carried out secondary analyses to test whether or not associations vary with chronologic age (using chronologic age as a surrogate measure for the size of the oocyte pool). We present the results of these analyses but, because the number of exposed women in the older age categories is small, we view them as exploratory.
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Results |
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Table II sets out the geometric means of the ovarian age indicators within categories of the three exposures and chronologic age.
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Main effects regression models (Table III)
Former smoking is not associated with any ovarian age indicator. Current smoking is not associated with AFC, inhibin B or estradiol. Serum FSH is elevated an estimated 23% in current smokers compared with women who never smoked [
for ln(FSH) = 0.21, 95% CI 0.04, 0.39].
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Smoking by the mother of the study participant, ever or during the time she was pregnant with the participant, is not related to any ovarian age indicator (data not shown).
Neither days per week of drinking alcohol nor milligrams per day of caffeine intake, defined continuously (Table III) or categorically (not shown), is associated with any of the ovarian age indicators. Alcohol drinks per week, defined continuously or categorically, is not associated with any of the ovarian age indicators (data not shown).
Current smoking and variations with chronologic age (Table IV)
For FSH, our data suggest that associations with current smoking increase with chronologic age. For example, we estimate that serum FSH for a 30-year-old current smoker is 
0.3 mIU/ml higher than serum FSH for a 30-year-old never smoker. At ages 35, 40 and 45, estimated differences are 1.3, 3.2 and 6.9 mIU/ml.
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Discussion |
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Current cigarette smoking is related to FSH level, but not to AFC or to levels of inhibin B or estradiol. The model with age x smoking interaction terms suggests that the strength of association between current smoking and FSH increases with advancing age, although the small number of exposed women at older ages precludes secure interpretation of the finding. Former smoking is not related to any ovarian age indicator. Neither alcohol nor caffeine intake at moderate levels is related to any ovarian age indicator.
Both the number of oocytes in the underlying pool and the number of antral follicles that develop during each cycle decline with age. This similarity led us to hypothesize that if smoking affects ovarian age by accelerating atresia (Mattison and Thorgeirsson, 1978), we would observe an association between smoking and AFC. Specifically, we expected that current smokers would have fewer antral follicles than former smokers and that former smokers would have fewer than never smokers.
Our data, however, show no association of either current or former smoking with the number of antral follicles. (We can, with 95% confidence, rule out decreases of more than about 23%.) Thus, if AFC is, in fact, a good measure of the size of the underlying oocyte pool, these data suggest that smoking does not accelerate oocyte atresia. Alternatively, AFC may not be a good indicator of the size of the pool. In rats, the number of antral follicles remains normal in animals with artificially depleted pools of primordial follicles (Hirshfield, 1994). A classic study of autopsy specimens (Block, 1952) suggests that in humans, too, with advancing age the developing follicles constitute an increasing proportion of the total oocyte pool, indicating possible preservation of the antral cohort despite depletion of the underlying pool.
Current smoking is unrelated to levels of inhibin B or estradiol. These results are biologically coherent with the absence of an association between current smoking and AFC. Age-adjusted correlations, however, of AFC with inhibin B (0.24) and estradiol (0.08) are modest (Kline et al., 2005), suggesting that the three indicators may not measure the same underlying biologic process. Our results for inhibin B and estradiol add to an inconsistent literature regarding associations with smoking.
Current smoking is associated with increased FSH level, a result consistent with previous studies (Cramer et al., 1994; Cooper et al., 1995; Backer et al., 1999, Cramer et al., 2002), most of which drew on women in their mid-30s or older. The regression coefficient for ln(FSH), 0.21, indicates that the estimated geometric mean for current smokers is 23% greater than the mean for never smokers. Moreover, our data suggest that the difference in FSH level between current and never smokers increases with advancing age. The predicted level for a 30-year-old current smoker is about 7% higher than the predicted level for a 30-year-old never smoker (95% CI for increase factor 0.88, 1.30); by age 45, the predicted level is almost 100% higher (95% CI for increase factor 1.39, 2.86). This result, too, is consistent with a study (Cooper et al. 1995) which showed, among women aged 38–49, an age-related increase in differences in FSH for current smokers compared with nonsmokers. In other words, the age-related rate of increase in FSH is steeper for current smokers than for nonsmokers. Our data extend these observations to young women, all of whom were recently pregnant.
Several caveats are in order. First, our sample over-represents women with pregnancy losses. We do not believe this feature limits generalizability, however, because spontaneous abortion is unrelated to these ovarian age indicators (Kline et al., 2004). All analyses adjusted for the outcome of the index pregnancy. Furthermore, all participants were of demonstrated fecundability: 73% of the women (59% of the women with losses) had at least one live birth. Second, because all women had conceived recently (0.3–2.5 years prior to the study sonogram, mean 0.9 years), at older ages (the late 30s and 40s) our sample may over-represent women of high fecundability. This over-representation may alter the patterns of change observed at older ages; specifically, our data may underestimate associations with current smoking at older ages. Third, the study was not designed to detect associations between the exposures and the ovarian age indicators. Detectable effects (power = 80%, = 0.05, two-tailed) were moderate, ranging from 26% to 52% of a standard error of the regression coefficient. For example, for AFC, at the median count of 15, for current smoking versus never smoked, power was sufficient to detect a decrease to 11 follicles—roughly equivalent to the estimated change in median count between chronologic ages 35 and 39 (Kline et al., 2005). Fourth, the small number of women in some exposure categories limits the precision of estimates. Our data are also too small to analyse refined exposure categories. However, all ovarian age indicators were assessed without knowledge of maternal age or smoking history and reliability was excellent for all measures.
Finally, we did not obtain measures from several menstrual cycles. It is uncertain, however, that replicate measures would improve our estimates of ovarian age. For AFC, one study of women of proven fertility (Scheffer et al., 1999) suggests only modest improvement from replicate measures: the correlations with chronologic age of count from a single cycle and from the mean of two cycles were comparable. Moreover, because more than a third of the sample was aged 41–46, this study may overestimate intercycle variability among women of reproductive age. For FSH and inhibin B, the literature provides no evidence about intercycle variability in fertile women. Data from a sample of infertile women (Fanchin et al., 2005) with regular menstrual cycles showed, over three consecutive cycles, moderate reproducibility [intraclass correlation coefficient (ICC) 0.55] for FSH and good reproducibility (ICC 0.76) for inhibin B. Low intercycle variability (mean standard deviation 2.6 ± 0.2 mIU/ml) was observed in another sample of infertile women (Scott et al., 1990) provided the mean basal FSH level was < 15 mIU/ml. (In our sample, 98% of women had FSH levels < 15 mIU/ml.) It is unclear, however, that evidence from samples of women undergoing assisted reproduction can be extrapolated to fertile women.
A countervailing strength of our study is that we measured several different indicators of ovarian age. Three criteria—reliability, validity and biologic plausibility—support the assumption that these measures accurately reflect the size of the oocyte pool. The procedure for counting antral follicles was repeatable; the intra- and inter-assay CV for the hormone assays were excellent. The indicators were each associated, in the expected directions, with each other and with chronologic age (Kline et al., 2004).
Our observation that current smoking is related to elevated FSH is unlikely to reflect confounding. Although FSH may be elevated for reasons [e.g. familial dizygotic twinning (Lambalk et al., 1998) or FSH receptor subtype (De Koning et al., 2006)] which are not thought to be related to ovarian reserve, such factors are unlikely to have produced spurious results, as they can introduce confounding only if they are also associated with smoking. We know of no such evidence. With respect to our sample composition, some studies of women with recurrent losses or women undergoing assisted reproduction (Nasseri et al., 1999; Van Montfrans et al., 1999) report an association between elevated FSH and increased rates of aneuploidy or spontaneous abortion. It is unclear, however, whether these findings can be generalized to fertile women. One study of fertile women found no association between FSH and spontaneous abortion (Van Montfrans et al., 2004), a result consistent with observations in our sample (Kline et al., 2004).
The association of current smoking with FSH may reflect accelerated oocyte atresia, impaired follicle quality or dysregulation of the hypothalamic–pituitary–ovarian axis.
In support of an atresia mechanism is the observation that benzo[a]pyrene, a constituent of cigarette smoke, destroys primordial follicles in mice (Mattison and Thorgiersson, 1978). A study of surgically removed ovaries (Westhoff et al., 2000) confirms that, among women aged 35–54, both current and former smokers have fewer follicles than never smokers. In this scenario, elevated FSH might reflect an endocrine effort to recruit a sufficient number of antral follicles from a depleted oocyte pool. Because oocyte depletion is irreversible, we would expect, under an atresia mechanism, that the age at menopause of former smokers would lie intermediate between the age of current and never smokers. However, most epidemiologic studies of age at menopause (Kaufman et al., 1980; Adena and Gallagher, 1982; Willett et al., 1983; Kato et al., 1998; Cooper et al., 1999; Hardy et al., 2000; Van Asselt et al., 2004; Kinney et al., 2006) find that former smokers reach menopause at an age similar to the age of never smokers. This observation is difficult to reconcile with smoking-induced accelerated atresia.
Alternatively, the association of current smoking with FSH may reflect impaired follicle quality or dysregulation of the hypothalamic–pituitary–ovarian axis. FSH is a gonadotropin under negative feedback control of inhibin and estradiol (Burger, 1994, 2000). Elevated FSH may, therefore, derive from compromised follicle quality or function (inability to suppress FSH) or an altered sensitivity of the hypothalamic-pituitary-axis to ovarian hormones. Although we did not detect an effect of current smoking in relation to inhibin B, the observed data (Table II) are not inconsistent with an age-mediated association: in women under 30 years of age, mean inhibin B levels (pg/ml) for never and current smokers are 73.6 and 71.5, respectively, whereas in women 40 years or older, the mean levels are 58.9 and 22.5. This phenomenon, if observed in other studies, favours a mechanism related to follicle function.
Our finding of an age-mediated effect of current smoking on FSH, although based on small numbers, accords with a similar observation from a study of older women (Cooper et al., 1995). Identification of the causal mechanism has implications for prevention or treatment of conception delay, infertility and morbidity associated with early menopause.
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Acknowledgements |
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We acknowledge our co-investigators, Drs Dorothy Warburton and Michel Ferin, who collaborated in the design and implementation of the study. We thank Dr Grace Jorgensen, who welcomed and facilitated this study; we thank her and her colleagues for their help in providing access to their patients. We acknowledge Maria Bautista, Jennifer Cassin, Terry Fox, the late Kris Keough and Donna West, who facilitated our work at the study hospital, and Rebecca Russell and Jeannie Small-Fish, who obtained the sonography scans. We thank Megan Meldrum, who carried out the fieldwork of the study, and Renée Davenport, who assisted in data processing and checking. This research would not have been possible without the help of the women who participated in it. This work was supported by a grant from the National Institute on Aging (R01 AG 15386).
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References |
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TopAbstractIntroductionMaterials and methodsResultsDiscussionAcknowledgementsReferences |
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Adena MA and Gallagher HG. (1982) Cigarette smoking and the age at menopause. Ann Hum Biol 9:121–130.[CrossRef][Web of Science][Medline]
Backer LC, Rubin CS, Marcus M, Kieszak SM, Schober SE. (1999) Serum follicle-stimulating hormone and luteinizing hormone levels in women aged 35–60 in the U.S. population: the Third National Health and Nutrition Examination Survey (NHANES III, 1988–1994). Menopause 6:29–35.[Web of Science][Medline]
Barbieri RL, McShane PM, Ryan KJ. (1986) Constituents of cigarette smoke inhibit human granulosa cell aromatase. Fertil Steril 46:232–236.[Web of Science][Medline]
Barone JJ and Roberts HR. (1996) Caffeine consumption. Food Chem Toxicol 34:119–129.[CrossRef][Web of Science][Medline]
Beverage Digest. (2005) Top-10 CSD Companies and Brands 2000.
Block E. (1952) Quantitative morphological investigations of the follicular system in women: variations at different ages. Acta Anat 14:108–123.[Web of Science][Medline]
Brett KM and Cooper GS. (2003) Associations with menopause and menopausal transition in a nationally representative US sample. Maturitas 45:89–97.[CrossRef][Web of Science][Medline]
Burger HG. (1994) Diagnostic role of follicle-stimulating hormone (FSH) measurements during the menopausal transition—an analysis of FSH, oestradiol and inhibin. Eur J Endocrinol 130:38–42.
Burger HG. (2000) Inhibin and reproductive aging. Exp Gerontol 35:33–39.[Medline]
CDC (Centers for Disease Control and Prevention). (2000) Assisted Reproductive Technology Success Rates, 2000.
Christianson RE, Oechsli FW, van den Berg BJ. (1989) Caffeinated beverages and decreased fertility. Lancet 1:378.[Web of Science][Medline]
Cooper GS, Baird DD, Darden FR. (2001) Measures of menopausal status in relation to demographic, reproductive, and behavioral characteristics in a population-based study of women aged 35–49 years. Am J Epidemiol 153:1159–1165.
Cooper GS, Baird DD, Hulka BS, Weinberg CR, Savitz DA, Hughes CL. (1995) Follicle-stimulating hormone concentrations in relation to active and passive smoking. Obstet Gynecol 85:407–411.[CrossRef][Web of Science][Medline]
Cooper GS, Sandler DP, Bohlig M. (1999) Active and passive smoking and the occurrence of natural menopause. Epidemiology 10:771–773.[CrossRef][Web of Science][Medline]
Cramer DW, Barbieri RL, Xu H, Reichardt JK. (1994) Determinants of basal follicle-stimulating hormone levels in premenopausal women. J Clin Endocrinol Metab 79:1105–1109.[Abstract]
Cramer DW, Barbieri RL, Fraer AR, Harlow BL. (2002) Determinants of early follicular phase gonadotrophin and estradiol concentrations in women of late reproductive age. Hum Reprod 17:221–227.
Curtis KM, Savitz DA, Arbuckle TE. (1997) Effects of cigarette smoking, caffeine consumption, and alcohol intake on fecundability. Am J Epidemiol 146:32–41.
De Koning CH, Benjamins T, Harms P, Homburg R, van Montfrans JM, Gromoll J, Simoni M, Lambalk CB. (2006) The distribution of FSH receptor isoforms is related to basal FSH levels in subfertile women with normal menstrual cycles. Hum Reprod 21:443–446.
Fanchin R, Taieb J, Lozano DH, Ducot B, Frydman R, Bouyer J. (2005) High reproducibility of serum anti-Mullerian hormone measurements suggests a multi-staged follicular secretion and strengthens its role in the assessment of ovarian follicular status. Hum Reprod 20:923–927.
Florack EI, Zielhuis GA, Rolland R. (1994) Cigarette smoking, alcohol consumption, and caffeine intake and fecundability. Prev Med 23:175–180.[CrossRef][Web of Science][Medline]
Freeman EW, Sammel MD, Gracia CR, Kapoor S, Lin H, Liu L, Nelson DB. (2005) Follicular phase hormone levels and menstrual bleeding status in the approach to menopause. Fertil Steril 83:383–392.[CrossRef][Web of Science][Medline]
Gavaler JS, Imhoff AF, Pohl CR, Rosenblum ER, Van Thiel DH. (1987) Alcoholic beverages: a source of estrogenic substances? Alcohol Alcohol (Suppl 1), 545–549.
Grodstein F, Goldman MB, Ryan L, Cramer DW. (1993) Relation of female infertility to consumption of caffeinated beverages. Am J Epidemiol 137:1353–1360.
Hardy R, Kuh D, Wadsworth M. (2000) Smoking, body mass index, socioeconomic status and the menopausal transition in a British national cohort. Int J Epidemiol 29:845–851.
Harlow BL and Signorello LB. (2000) Factors associated with early menopause. Maturitas 35:3–9.[CrossRef][Web of Science][Medline]
Hatch EE and Bracken MB. (1993) Association of delayed conception with caffeine consumption. Am J Epidemiol 138:1082–1092.
Hirshfield AN. (1994) Relationship between the supply of primordial follicles and the onset of follicular growth in rats. Biol Reprod 50:421–428.[Abstract]
Joesoef MR, Beral V, Rolfs RT, Aral SO, Cramer DW. (1990) Are caffeinated beverages risk factors for delayed conception? Lancet 335:136–137.[CrossRef][Web of Science][Medline]
Kato I, Toniolo P, Akhmedkhanov A, Koenig KL, Shore R, Zeleniuch-Jacquotte A. (1998) Prospective study of factors influencing the onset of natural menopause. J Clin Epidemiol 51:1271–1276.[CrossRef][Web of Science][Medline]
Kaufman DW, Slone D, Rosenberg L, Miettinen OS, Shapiro S. (1980) Cigarette smoking and age at natural menopause. Am J Public Health 70:420–422.
Kinney A, Kline J, Levin B. (2006) Alcohol, caffeine and smoking in relation to age at menopause. Maturitas 54:(1)27–38.[CrossRef][Web of Science][Medline]
Kline J, Kinney A, Kelly A, Reuss ML, Levin B. (2005) Predictors of antral follicle count during the reproductive years. Hum Reprod 20:2179–2989.
Kline J, Kinney A, Reuss ML, Kelly A, Levin B, Ferin M, Warburton D. (2004) Trisomic pregnancy and the oocyte pool. Hum Reprod 19:1633–1643.
Lambalk CB, de Koning CH, Bratt DD. (1998) The endocrinology of dizygotic twinning in the human. Mol Cell Endocrinol 145:97–102.[CrossRef][Web of Science][Medline]
Lambert-Messerlian GM and Harlow BL. (2006) The influence of depression, body mass index, and smoking on serum inhibin B levels in late reproductive-aged women. J Clin Endocrinol Metab 91:1495–1500.
Lucero J, Harlow BL, Barbieri RL, Sluss P, Cramer DW. (2001) Early follicular phase hormone levels in relation to patterns of alcohol, tobacco, and coffee use. Fertil Steril 76:723–729.[CrossRef][Web of Science][Medline]
MacMahon B, Trichopoulos D, Cole P, Brown J. (1982) Cigarette smoking and urinary estrogens. N Engl J Med 307:1062–1065.[Web of Science][Medline]
Mattison DR and Thorgeirsson SS. (1978) Smoking and industrial pollution, and their effects on menopause and ovarian cancer. Lancet 1:187–188.[Web of Science][Medline]
McKinlay SM, Brambilla DJ, Posner JG. (1992) The normal menopause transition. Maturitas 14:103–115.[CrossRef][Web of Science][Medline]
Mendelson JH, Lukas SE, Mello NK, Amass L, Ellingboe J, Skupny A. (1988) Acute alcohol effects on plasma estradiol levels in women. Psychopharmacology (Berl) 94:464–467.[CrossRef][Medline]
Mendelson JH, Mello NK, Cristofaro P, Ellingboe J, Skupny A, Palmieri SL, Benedikt R, Schiff I. (1987) Alcohol effects on naloxone-stimulated luteinizing hormone, prolactin and estradiol in women. J Stud Alcohol 48:287–294.[Web of Science][Medline]
Mendelson JH, Mello NK, Teoh SK, Ellingboe J. (1989) Alcohol effects on luteinizing hormone releasing hormone-stimulated anterior pituitary and gonadal hormones in women. J Pharmacol Exp Ther 250:902–909.
Muti P, Trevisan M, Micheli A, Krogh V, Bolelli G, Sciajno R, Schunemann HJ, Berrino F. (1998) Alcohol consumption and total estradiol in premenopausal women. Cancer Epidemiol Biomarkers Prev 7:189–193.[Abstract]
Nasseri A, Mukherjee T, Grifo JA, Noyes N, Krey L, Copperman AB. (1999) Elevated day 3 serum follicle stimulating hormone and/or estradiol may predict fetal aneuploidy. Fertil Steril 71:715–718.[CrossRef][Web of Science][Medline]
Paszkowski T, Clarke RN, Hornstein MD. (2002) Smoking induces oxidative stress inside the Graafian follicle. Hum Reprod 17:921–925.
Purohit V. (1998) Moderate alcohol consumption and estrogen levels in postmenopausal women: a review. Alcohol Clin Exp Res 22:994–997.[CrossRef][Web of Science][Medline]
Reichman ME, Judd JT, Longcope C, Schatzkin A, Clevidence BA, Nair PP, Campbell WS, Taylor PR. (1993) Effects of alcohol consumption on plasma and urinary hormone concentrations in premenopausal women. J Natl Cancer Inst 85:722–727.
Scheffer GJ, Broekmans FJ, Dorland M, Habbema JD, Looman CW, te Velde ER. (1999) Antral follicle counts by transvaginal ultrasonography are related to age in women with proven natural fertility. Fertil Steril 72:845–851.[CrossRef][Web of Science][Medline]
Scott RT Jr, Hofmann GE, Oehninger S, Muasher SJ. (1990) Intercycle variability of day 3 follicle-stimulating hormone levels and its effects on stimulation quality in in vitro fertilization. Fertil Steril 54:297–302.[Web of Science][Medline]
Spinelli A, Figa-Talamanca I, Osborn J. (1997) Time to pregnancy and occupation in a group of Italian women. Int J Epidemiol 26:601–609.
The Coca-Cola Company. (2004).
The Pepsi Cola Company. (2004).
Toner JP, Grainger DA, Frazier LM. (2002) Clinical outcomes among recipients of donated eggs: an analysis of the U.S. national experience, 1996–1998. Fertil Steril 78:1038–1045.[CrossRef][Web of Science][Medline]
Torgerson DJ, Thomas RE, Campbell MK, Reid DM. (1997) Alcohol consumption and age of maternal menopause are associated with menopause onset. Maturitas 26:21–25.[CrossRef][Web of Science][Medline]
Valdez KE and Petroff BK. (2004) Potential roles of the aryl hydrocarbon receptor in female reproductive senescence. Reprod Biol 4:243–258.[Medline]
Valimaki M, Harkonen M, Ylikahri R. (1983) Acute effects of alcohol on female sex hormones. Alcohol Clin Exp Res 7:289–293.[Web of Science][Medline]
Van Asselt KM, Kok HS, van der Schouw YT, Grobbee DE, te Velde ER, Pearson PL, Peeters PH. (2004) Current smoking at menopause rather than duration determines the onset of natural menopause. Epidemiology 15:634–639.[CrossRef][Web of Science][Medline]
Van Montfrans JM, Dorland M, Oosterhuis GJ, van Vugt JM, Rekers-Mombarg LT, Lambalk CB. (1999) Increased concentrations of follicle-stimulating hormone in mothers of children with Down's syndrome. Lancet 353:1853–1854.[CrossRef][Web of Science][Medline]
Van Montfrans JM, van Hoof MH, Huirne JA, Tanhatoe SJ, Sadrezadeh S, Martens F, van Vugt JM, Lambalk CB. (2004) Basal FSH concentrations as a marker of ovarian ageing are not related to pregnancy outcome in a general population of women over 30 years. Hum Reprod 19:430–434.
Westhoff C, Gentile G, Lee J, Zacur H, Helbig D. (1996) Predictors of ovarian steroid secretion in reproductive-age women. Am J Epidemiol 144:381–388.
Westhoff C, Murphy P, Heller D. (2000) Predictors of ovarian follicle number. Fertil Steril 74:624–628.[CrossRef][Web of Science][Medline]
Wilcox A, Weinberg C, Baird D. (1988) Caffeinated beverages and decreased fertility. Lancet 2:1453–1456.[CrossRef][Web of Science][Medline]
Willett W, Stampfer MJ, Bain C, Lipnick R, Speizer FE, Rosner B, Cramer D, Hennekens CH. (1983) Cigarette smoking, relative weight, and menopause. Am J Epidemiol 117:651–658.
Williams MA, Monson RR, Goldman MB, Mittendorf R, Ryan KJ. (1990) Coffee and delayed conception. Lancet 335:1603.[Web of Science][Medline]
Submitted on March 5, 2006; resubmitted on October 13, 2006; resubmitted on November 29, 2006; accepted on December 5, 2006.
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