Hormones and Behavior 63 (2013) 636–645

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Hormones and Behavior
journal homepage: www.elsevier.com/locate/yhbeh

Hormonal predictors of sexual motivation in natural menstrual cycles
James R. Roney ⁎, Zachary L. Simmons
University of California, Santa Barbara, USAa r t i c l e

i n f oArticle history:
Received 18 December 2012
Revised 15 February 2013
Accepted 20 February 2013
Keywords:
Sexual motivation
Menstrual cycle
Estradiol
Testosterone
Progesteronea b s t r a c t
Little is known regarding which hormonal signals may best predict within- and between-women variance in sexualmotivation among naturally cycling women. To address this, we collected daily saliva samples across 1–2 menstrual
cycles from a sample of young women; assayed samples for estradiol, progesterone, and testosterone; and alsocollected daily diary reports of women's sexual behavior and subjective sexual desire. With respect to withincycle, day-to-day ﬂuctuations in subjective desire, we found evidence for positive effects of estradiol and negative
effects of progesterone. Desire exhibited a mid-cycle peak, similar to previous ﬁndings; measured progesterone
concentrations statistically mediated the fall in desire from mid-cycle to the luteal phase, but no combination of
hormone measures substantially mediated the follicular phase rise in desire, which suggests that other signals
may be implicated in this effect. Hormonal predictors of within-cycle ﬂuctuations in sexual behavior generally
reached only trend levels of statistical signiﬁcance, though the patterns again suggested positive effects of estradiol
and negative effects of progesterone. Between-women and within-women, between-cycle effects of hormone
concentrations were generally absent, although statistical power was more limited at these higher levels of analysis.
There were no signiﬁcant effects of testosterone concentrations when controlling for the effects of estradiol andprogesterone, which raises questions regarding the importance of this hormone for the regulation of sexual motivation in natural cycles. Our study is among the ﬁrst to identify hormonal predictors of within-cycle ﬂuctuations insexual motivation, and thus adds novel evidence regarding the endocrine correlates of human sexuality.
© 2013 Elsevier Inc. All rights reserved.

Introduction
Surprisingly little research has directly addressed the hormonal
predictors, if any, of women's sexual motivation in natural menstrual
cycles (Stuckey, 2008; Wallen, 2001). Although non-hormonal factors
undoubtedly play crucial roles in determining women's sexual motivation (e.g., Bodenmann et al., 2010; Dennerstein et al., 2005), variouslines of evidence support a signiﬁcant role for sex hormones as well.
Sexual motivation tends to drop after natural or surgical menopause(Alexander et al., 2004; Dennerstein et al., 1977, 2005; Gracia et al.,2007); a number of studies have reported increased sexual desire or
behavior near ovulation, which implicates a role for ovarian hormones(e.g., Adams et al., 1978; Bullivant et al., 2004; Dennerstein et al., 1994;
Diamond and Wallen, 2011; Harvey, 1987; Matteo and Rissman, 1984;
Pillsworth et al., 2004; Stanislaw and Rice, 1988; Wallen, 2001; Wilcox
et al., 2004; cf. Regan, 1996; Schreiner-Engel and Schiavi, 1981); thechemical suppression of ovarian hormones in a sample of naturally
cycling women led to large drops in sexual motivation (Schmidt et al.,2009); and evidence supports the efﬁcacy of hormone replacement⁎ Corresponding author at: Department of Psychological and Brain Sciences, University ofCalifornia, Santa Barbara, Santa Barbara, CA 93106-9660, USA. Fax: +1 805 893 2791.
E-mail address: roney@psych.ucsb.edu (J.R. Roney).
0018-506X/$ – see front matter © 2013 Elsevier Inc. All rights reserved.
http://dx.doi.org/10.1016/j.yhbeh.2013.02.013

therapy in increasing sexual motivation in menopausal women via useof various doses of estrogen (Dennerstein et al., 1980; Nathorst-Booset al., 1993; Sherwin, 1991; Wiklund et al., 1993), testosterone added to
estrogen (Braunstein et al., 2005; Floter et al., 2002; Sherwin et al.,1985), or testosterone alone (Davis et al., 2008).
Despite the above evidence for hormonal inﬂuences, there is as ofyet no clear model of the speciﬁc hormonal signals associated withwithin- and between-women variance in sexual motivation within
natural menstrual cycles. Only a handful of studies (Dennerstein et al.,
1994; Morris et al., 1987; Persky et al., 1978a,b; Van Goozen et al.,1997) have measured hormone concentrations across broad regions of
the menstrual cycle in order to test for associations with measures oflibido in premenopausal women. The only signiﬁcant ﬁndings reported
in these studies have been positive, between-women correlations between average or mid-cycle testosterone and some measures of sexualfrequency (Morris et al., 1987; Persky et al., 1978b; Van Goozen et al.,
1997; cf. Bancroft et al., 1983). No studies have reported signiﬁcant associations between within-women, day-to-day ﬂuctuations in hormonesand changes in sexual thoughts or behaviors, which leaves unknown
the physiological signals that may regulate cyclic patterns of libido.
The conclusiveness of the above studies that have tested hormonalcorrelates of sexual motivation is limited, however, by signiﬁcant methodological issues. Most of the studies were underpowered, and did not
exploit the power that can be gained from analyzing nested data via

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mixed-level regression modeling; hormone sampling was typicallyinfrequent (usually 2–3 times per week; cf. Van Goozen et al., 1997);
only univariate analyses were performed, with no studies having tested
the partial effects of hormones while controlling for the effects ofothers; and, ﬁnally, only same day associations between hormonesand dependent measures have been assessed, despite possible time delays for genomic effects of some hormones (see below). Summing up
the limitations of this literature, Wallen (2001) wrote: “… after morethan 30 years of study, there is still no human study that has correlated
daily changes in ovarian hormones with daily ratings of sexual desire
and looked at both estrogens and androgens” (p. 352). The present
study was designed in part to address this gap in the human literature.
Here we collected daily saliva samples across 1–2 menstrual cycles
from a sample of naturally cycling young women, as well as daily
diary reports of both sexual behavior and self-reported sexual desire.
Saliva samples were assayed for estradiol, testosterone, and progesterone every day across a nine day window surrounding the estimatedday of ovulation (see Methods section), and on alternating days outsideof this window. Mixed model regression analyses were employed,
allowing tests of within-cycle (Level-1) predictors of sexual motivation(e.g., do day-to-day ﬂuctuations in estradiol predict within-cycle
ﬂuctuations in libido?); within-women, between-cycle (Level-2)
predictors (e.g., does change in average estradiol across the same
woman's two cycles predict change in her average sexual motivation?);and between-women (Level-3) predictors (e.g., do women with higher
estradiol on average also experience higher sexual motivation on average?). Previous studies have sometimes confounded these three sourcesof variance, and no studies have systematically examined all three levelsof analysis within the same sample.
We hypothesized that estradiol would positively predict within-cycle;
between-cycle, within-women; and between-women variance in sexualmotivation. Estradiol indexes within-cycle fertility since it peaks nearovulation, but also indexes between-cycle fertility given evidence thatconception is more likely in cycles with higher estradiol (Lipson andEllison, 1996; Venners et al., 2006). We have proposed elsewhere(Roney, 2009; Roney and Simmons, 2008) on functional grounds theexistence of mechanisms that calibrate mating motivation to ﬂuctuations
in fertility, and the direct links between estradiol and fertility thus makethis hormone a logical signal to regulate this calibration. Progesterone,by contrast, could promote within-cycle links between fertility and sexualmotivation by acting as an inhibitory signal that reduces libido during thenon-fertile luteal phase, but such effects could undermine between-cycle
calibration of motivation to fertility since progesterone concentrations
tend to be higher in more fertile cycles characterized by favorable energetics (for review, see Ellison, 2001); if there were ﬁtness advantages
to the up-regulation of sexual motivation even during the luteal phasesof more vs. less fertile cycles (e.g., as a means of allocating greater attention to mate search, or to signal paternity conﬁdence to a partner via
greater sexual activity), then progesterone may have been a suboptimal
regulatory signal. The consistent, positive correlation between estradiol
and fertility at both within- and between-cycle time-scales, on
the other hand, suggests its potential efﬁciency as a regulator of sexualmotivation. In addition to these theoretical considerations, estradiol isknown to promote various aspects of sexual motivation among bothrodents (e.g., Carter, 1992; Pfaff et al., 2002) and nonhuman primates(e.g., Wallen et al., 1984; Zehr et al., 1998), although some evidence
in primates suggests inhibitory effects of progesterone (e.g., Wallen
et al., 1984), as well.
In assessing within-cycle predictors of sexual motivation, it is potentially important to account for possible time delays in the effects of ovarian hormones. Estradiol appears to affect sexual receptivity in femalerodents at a lag of approximately two days (with effects decaying rapidly
beyond two days without further doses of estrogen), whereas progesterone has effects within minutes to hours (Blaustein, 2008; Powers, 1970;
Whalen, 1974). To assess possible time delays, we tested the effects ofcurrent day, one day lag, and two day lag hormone concentrations, and,637

based on the rodent ﬁndings, speciﬁcally hypothesized that estradiol
concentrations from two days earlier will positively predict indices ofwomen's current day sexual motivation. Although our a priori expectation was that estradiol would be the crucial signal, our design allowed
tests for effects of testosterone and progesterone as well. Finally, ourdesign also allowed us to add time variables (proximity to ovulation,
weekend timing) to models that included hormonal predictors.
Methods
Participants
Women were recruited from a subject pool website run by the
Department of Psychology at UCSB. Pregnancy, lactation, or any use ofhormonal contraceptives within the last six months were exclusion
criteria, as were self-reported menstrual cycles longer than 40 days.
Fifty-two eligible women enrolled in the study and completed datacollection for the ﬁrst menstrual cycle. Of these women, 37 returned fora second cycle (n = 7 declined to continue, n = 2 transferred schools,
n = 1 started taking hormonal contraceptives, n = 2 were not invitedback due to poor compliance in cycle 1, n = 1 dropped out after initiallystarting cycle 2, and n = 2 failed to menstruate within ﬁve weeks of thestart of cycle 2 data collection). Hormones were assayed from 43 of thewomen in cycle 1 (to save costs, we did not assay hormones from 9 of
the cycle 1 women who did not return for cycle 2, but assayed hormonesfrom 6 of the women who did not return but had high rates of compliancein cycle 1), and from 36 of 37 women in cycle 2 (one woman with many
missing samples was excluded from the assays); as such, we obtained
hormone data from 43 total women, with 36 contributing two cyclesof data and 7 contributing one. Mean age of these 43 women was
18.76 ± 1.15 years, and all self-reported a heterosexual orientation.
Fourteen of the 43 women reported that they were within a romantic
relationship in cycle 1, whereas 10 out of 36 women reported being in a
relationship during cycle 2. Women were paid $100 per cycle if theymissed fewer than three daily log-in sessions in a given cycle, and were
paid lower, pro-rated amounts if they had more missing data. Participants
provided written, informed consent for their participation, and all procedures were in accordance with the Code of Ethical Principles for Medical
Research Involving Human Subjects of the World Medical Association(Declaration of Helsinki).
Procedure
Women participants were ﬁrst directed to a secure website on
which they indicated daily whether they had started a new menstruation; upon an afﬁrmative answer, they were directed to a new link
and instructed to complete the survey found there each morning until
the end of their cycle (women also indicated in that survey whether
bleeding occurred on each response day). This survey included theitems that comprise the dependent variables in the present report.
Subjective desire was measured via the item: “How much did you desire sexual contact yesterday?” (1–7 scale). Our primary behavioral dependent variable read as follows: “Did you engage in sexual activity(intercourse or other forms of genital stimulation) with another person
yesterday?” (Y/N). Because sexual behavior may occur in response topartners' desires and thus imperfectly index sexual motivation, we
also examined two secondary behavioral variables. In cases in which
sex occurred, women were also asked: “Who initiated the sexual activity? (You, Other person, Both).” Our initial intention was to analyze
cases initiated exclusively by the woman, but there were too few suchcases—a total of 15 across the entire study—to do so. Instead, we computed a measure of woman-initiated sexual behavior that was coded
1 if sex occurred and the woman indicated that she or both she andher partner had initiated it, and was coded zero otherwise. The ﬁnal
behavioral measure assessed autosexual behavior: “Did you engage inself-stimulation (masturbation) yesterday?” Because the items referred

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to “yesterday,” responses were aligned with hormone concentrations
from the previous day.
Women were also instructed to collect a saliva sample each morning. They were asked to do so at least 30 min after any eating or
drinking, ideally upon ﬁrst waking. Collection was via passive drool(a few minutes after rinsing with clean water) into pre-labeled polypropylene vials. Women stored these vials in home freezers and thendelivered them weekly to our research lab, at which time they were
given a new batch of vials. Saliva samples were then stored at −80 C until being shipped for assay. The same procedures describedabove were repeated in cycle 2 for those women who returned for asecond cycle; the two cycles were separated by 1–2 months.
Hormone assays
Saliva samples were shipped on dry ice to the Endocrine Core
Laboratory at the California Regional Primate Research Center, Davis,
CA. Samples were centrifuged at 3000 rpm for 20 min. to separate theaqueous component from other particles. Concentrations of progesterone were estimated in duplicate using commercial radioimmunoassay
kits (Siemens Health Diagnostics, Inc., Los Angeles, CA). Assay procedures were modiﬁed to accommodate overall lower levels of progesterone in human saliva relative to plasma as follows: 1) standards werediluted to concentrations ranging from 0.05 to 4.0 ng/mL; and 2) sample
volume was increased to 200 μl. The progesterone assay has a least
detectable dose of 0.00914 ng/ml; intra- and inter-assay CVs were
4.57% and 7.36%, respectively. Concentrations of testosterone were
estimated in duplicate using double-antibody commercial radioimmunoassay kits (Beckman Coulter Inc., Webster, TX.). The assay procedures
were those outlined in Granger et al. (1999). The testosterone assay has
a least detectable dose of 1.3697 pg/ml; intra- and inter-assay CVs were
5.20% and 9.83%, respectively. Estradiol concentrations were estimatedin duplicate using the high sensitivity salivary 17β-estradiol enzyme
immunoassay kit (Salimetrics LLC, State College, PA). The estradiol assay
has a least detectable dose of 0.1 pg/ml; intra- and inter-assay CVs were
4.52% and 8.15%, respectively.
Data analyses
Cycle phase estimation
Prior to shipping saliva for assay, we estimated the day of ovulationas 15 days prior to the end of each cycle. All saliva samples in a nine day
window centered on this day were sent for assay, as well as samples
from alternating days outside of this window (N = 3621 total assays).
We then used the hormone data to re-estimate the day of ovulation
based on the conjunction of the mid-cycle estradiol drop and the initiation of the luteal phase progesterone increase (see Gann et al., 2001;
Lipson and Ellison, 1996): we computed a three day moving averagefor progesterone concentrations and then assigned the day of ovulation(day zero) as the day with the largest drop in estradiol from the previous day that occurred within two days of a 20% or greater increase in
the moving average for progesterone, conditional on this day being
followed by a sustained elevation in progesterone (for cycles without
sustained progesterone elevations—see below—we designated day zeroas the day with the largest drop in estradiol that occurred near midcycle). The “fertile window” (i.e. cycle days when conception is possible)
was then deﬁned as the estimated day of ovulation and the preceding ﬁve
days (Wilcox et al., 1998); the follicular phase was deﬁned as ending on
the day of ovulation, with all subsequent days deﬁned as luteal. Notethat ovulatory timing was primarily used for graphical purposes, andonly affected statistical tests that included the fertile window variable;
the main tests of hormonal predictors of sexual motivation directly
assessed associations between measured hormone concentrations andoutcome variables and did not rely on the accuracy of ovulatory timing
estimation.

Because a fertile window exists only in ovulatory cycles, the fertile
window analyses were restricted to the set of cycles judged ovulatory.
Following Ellison et al. (1987), we deﬁned as anovulatory any cycle that
did not achieve a maximum progesterone value of at least 300 pmol/L;this criterion identiﬁed 53 out of 79 total cycles as ovulatory (33% anovulatory, compared to 41% among undergraduates in Ellison et al., 1987).
This was likely a conservative criterion for ovulation that may have classiﬁed some ovulatory cases of luteal insufﬁciency as anovulatory, but had
the advantage of employing an objective cut-off point that ensured thatthe fertile window analyses were truly restricted to ovulatory cycles.
Our primary regression analyses testing hormonal predictors of sexualmotivation included all cycles, since hormone concentrations may still
predict outcomes in anovulatory cycles, and because cycles with smaller
hormone ﬂuctuations provide data relevant to the computation of theoverall effects of hormone ﬂuctuations across all cycles.
Outlier removal
We identiﬁed hormone outliers in a phase-speciﬁc manner by dividing the cycle into bins relative to the estimated day of ovulation (day 0):days −10 to −7, −6 to −4, -3 to −1, 0 to +1, +2 to +4, +5 to +7,+8 to +10, and all days outside of −10 to +10; hormone values
greater than 3 SD from the respective bin-speciﬁc means were thenremoved (although no statistical conclusions were altered by inclusionof the outliers). This procedure avoids misidentifying phase-speciﬁcpeaks (e.g., the pre-ovulatory estradiol peak) as outliers relative to the
grand mean. Outliers comprised 1.4%, 1.7%, and 1.5% of estradiol, progesterone, and testosterone values, respectively.
Statistical models
Our analysis strategy employed mixed regression models in SPSS
v19: these models are ideally suited for the analysis of nested datawith correlated error terms (Raudenbush and Bryk, 2002). In the present
case, daily variables (Level-1) were nested within cycles (Level-2), whichwere nested within women (Level-3). Hormone concentrations wereﬁrst z-scored so that all three hormones were placed on the same scale.
Separate models were constructed at Level-1 to test the within-cycle effects of current day hormones, hormones measured one day before theresponse day, and hormones measured two days before the responseday (missing data for days without assays precluded entering all timelags into the same model); hormone concentrations were group-meancentered in these models, such that the intercepts represent estimatedvalues for the dependent variables when hormones were at theirrespective cycle means. We constructed separate mixed regression
models to test Level-2 (within-women, between-cycle) and Level-3(between-women) effects of hormones. At Level-2, for the set of
women with two cycles of hormone data (n = 36), we centered mean
hormone concentrations within each cycle relative to each woman's
overall mean and then entered these scores into mixed regression
models: as such, these models assessed whether changes in mean hormone concentrations within-women, between-cycles predicted changes
in the intercepts of the dependent variables across the two cycles. At
Level-3, we entered women's mean hormone concentrations across theentire study into mixed regression models in order to test whether
women with higher overall hormone concentrations also scored higher
on the dependent measures. Equations for the mixed models appear in
Appendix A. A ﬁrst-order autoregressive error structure was speciﬁed
at Level-1 to account for autocorrelation in the dependent measures.
Linear mixed models were employed for the continuous measure of desire for sex, but mixed binary logistic models were used for the dichotomous sexual behavior variables.
Results
A total of 1905 daily log-in responses were obtained from the 43
women with hormone data out of 2079 eligible cycle days, for an overall
compliance rate of 91.6%. After selection of saliva samples from

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639

Fig. 1. Mean testosterone, estradiol, and progesterone concentrations aligned against estimated day of cycle (day 0 represents the estimated day of ovulation) and aggregated acrossall women. Values are standardized with respect to the grand means. Error bars are ± SEM.

alternating days outside of mid-cycle, and after outlier removal, measured
hormone concentrations were available for 1181, 1179, and 1208 of the
log-in days for estradiol, progesterone, and testosterone, respectively.
Mean hormone concentrations aggregated across women and aligned
against day of cycle reproduced prototypical hormone curves (Fig. 1),
thus providing evidence for validity of the hormone assays. Table 1
demonstrates that the three hormone concentrations were all positively
correlated with one another within-cycles, whereas mean testosterone
and mean estradiol concentrations were positively correlated betweenwomen.
Sexual desire
Within-cycle analyses
Table 2 presents results of mixed regression models testing the effectsof all three hormones on sexual desire at three different time-scales;
because visual inspection of the data revealed a strong positive effect ofweekend timing (deﬁned as Friday or Saturday), a binary weekend
timing variable was also included in each of the models. Progesterone
was a signiﬁcant negative predictor of desire in all three models, withthe strongest effects observed at a two day time lag. Estradiol measured
two days earlier was a signiﬁcant positive predictor of sexual desire,and current day estradiol exhibited a trend toward a positive effect.
There were no effects of testosterone at any time-scale in the full models;a positive zero-order effect of testosterone at a two day lag (γ = 0.11,
p = 0.047) dropped out when estradiol was added to the model,suggesting that this effect was an artifact of the positive within-cycle
correlation between these hormones (see Table 1). Weekend timing
had a signiﬁcant positive effect in all three models, but was independentof the effects of hormone concentrations as removal of this variable
Table 1
Correlations between hormone concentrations.
Estradiol
Estradiol
Progesterone
Testosterone

.21⁎⁎
.35⁎⁎

Progesterone

Testosterone

.11

.38⁎
.03

.15⁎⁎

Note. Values below the diagonal are within-cycle correlations (hormone concentrations were standardized within-cycles, then correlated across all data points); values
above the diagonal are between-women correlations (subject mean hormone values
were correlated with each other).
⁎⁎ p b 0.01.
⁎ p b 0.05.

produced negligible changes in the parameter estimates for the hormone
variables, and vice-versa. There were no signiﬁcant interactions between
any of the predictor variables in Table 2.
We next examined the effect of fertile window timing on sexualdesire (only ovulatory cycles were included in these analyses). Whenconsidering all cases for which desire ratings were available, thezero-order, within-cycle relationship between fertile window timing
and desire for sex was signiﬁcant, γ = 0.26, p = 0.023, with greater
desire inside the estimated fertile window (mean = 3.74 ± 0.20)
than on other days (mean = 3.48 ± 0.18). Fig. 2 plots desire ratings
against day of the cycle (the progesterone curve is included in order
to visually depict the relationship between progesterone and desire);
the highest mean desire ratings occurred on the estimated day of ovulation, and a clear drop in desire was evident in the luteal phase beginningon post-ovulatory day ﬁve. A positive effect of fertile window timing
was found both when analyses were restricted to follicular phasedays, γ = 0.32, p = 0.012, and when restricted to fertile window plus
luteal phase days, γ = 0.28, p = 0.027, which demonstrates that theeffect included both a rise in desire from the early to late follicularphase and a fall in desire from the late follicular phase to the luteal
phase.
The results presented in Table 2 in conjunction with the fertile window analyses suggest the possibility that the follicular phase rise indesire may be mediated by increasing estradiol concentrations, whereas the luteal phase drop in desire may be mediated by elevated progesterone. When analyses were restricted to fertile window plus luteal phasedays for those days on which hormone assays were available, thezero-order effect of fertile window timing was γ = 0.29, p = 0.064. Addition of current day progesterone to this model reduced the fertile
window effect to γ = 0.03, p = 0.85 (progesterone effect: γ = −0.19,
p = 0.008), whereas addition of estradiol or testosterone as the only
other predictor had negligible effects on the parameter estimates for fertile window timing (γs = 0.28 and 0.32, respectively); similar evidence
for exclusive mediation by progesterone was found for the one and two
day lag hormone models. When analyses were restricted to the follicularphase, the zero-order effect of fertile window timing for those days withhormones measured two days earlier (since the two day lag model
included the only signiﬁcant estradiol effect; see Table 2) was γ = 0.35,
p = 0.032. Addition of two day lag estradiol to this model caused onlya small drop in the magnitude of the fertile window effect, γ = 0.28,
p = 0.094; likewise, neither addition of the other individual hormones
nor any combination of hormones caused a substantial drop in the sizeof the fertile window coefﬁcient. Similar lack of mediation was found640

J.R. Roney, Z.L. Simmons / Hormones and Behavior 63 (2013) 636–645

Table 2Mixed regression models testing within-cycle predictors of desire for sex.
2-day lagIntercept
Progesterone
Estradiol
Testosterone
Weekend

1-day lagCurrent day

γ (df)

p-valueγ (df)

p-valueγ (df)

p-value

3.54 (44)−0.20 (503)0.16 (824)0.07 (797)
0.35 (808)b0.0010.00010.01
0.20
0.0002

3.51 (43)−0.11 (501)0.05 (862)0.02 (843)0.39 (843)b0.001
0.04
0.37
0.69
b0.0001

3.52 (44)−0.13 (584)0.09 (888)−0.07 (888)0.40 (875)b0.001
0.01
0.096
0.22
b0.0001

Note. Hormone variables were standardized (relative to their respective grand means) and then group-mean centered within-cycles; as such, coefﬁcients represent the within-cyclechange in sexual desire associated with a 1 SD change in hormone concentrations. Weekend was dummy coded. DF reﬂects the Satterthwaite correction as generated by the SPSS
program. Bold font highlights statistically signiﬁcant predictors.

when testing the effects of one day lag and current day hormones; thisabsence of mediation also persisted if we excluded day 0 (a low estradiolday) from our deﬁnition of the fertile window. In sum, we found that thedrop in desire from the fertile window to the luteal phase was statisticallymediated by measured progesterone concentrations, but were unable todemonstrate substantial hormonal mediation of the rise in desire during
the follicular phase.

Within-women, between-cycle analyses
A mixed regression model for those women with two cycles of hormone data (n = 36) tested the within-women effects of cycle mean
estradiol, testosterone, and progesterone on mean sexual desire acrossthe two cycles. There were no signiﬁcant effects, but the coefﬁcient formean estradiol was negative, γ = −0.33, p = 0.12, contrary to our prediction. As an intuitive check on these results, we also computed correlations between within-women changes in mean hormone concentrations
and within-women changes in mean desire; no effects were signiﬁcant.
The correlation for estradiol was r = −0.24, p = 0.15; approximately
68 subjects would be necessary to detect this effect size as statisticallysigniﬁcant. There were no interactions between the cycle mean hormone
concentrations in the prediction of sexual desire (all ps > 0.30).
Restricted variance within-women, between-cycles may help explain
the null effects at this level of analysis. Only 2.7% of the variance in sexualdesire was within-women, between-cycles, for example, whereas 31.4%
was between-women and 65.9% was within-cycles. Likewise, 10.7, 14.2,
and 2.6% of the variance in estradiol, testosterone, and progesterone,
respectively, was within-women, between-cycles; this similarity inhormone concentrations across cycles within the same women may

have limited our ability to detect reliable effects at the between-cycle
time-scale.
Between-women analyses
Subjects' mean concentrations of estradiol, testosterone, andprogesterone over the full study were entered as predictors of
sexual desire in a mixed regression model; there were no signiﬁcant effects (all ps > 0.20). A multiple regression analysis with subject mean
desire regressed onto subject mean hormones provides essentially thesame information, but may be more intuitive for some readers. This
analysis produced the following standardized regression coefﬁcientsfor the three hormones: for estradiol, β = 0.21, p = 0.22; for testosterone, β = 0.10, p = 0.57; for progesterone, β = −0.10, p = 0.53.
There were no signiﬁcant interactions between the three mean hormone
variables in the prediction of desire (all ps > 0.10).
Sexual behavior
The within-women (Level-1) and within-women, between-cycle(Level-2) analyses for the sexual behavior variables were restricted
to the subsets of women who reported nonzero frequencies of the respective behaviors, since there was otherwise no variance to explain
at Level-1 or Level-2 (between-women analyses included all women).
A total of 178 episodes of sexual behavior with a partner were reported
across 29 women; among these episodes, 85 involved female initiation,
distributed across 21 of the sexually active women. One hundred thirtytwo of the 178 cases of sexual behavior occurred among women who
reported that they were currently in a relationship; relationship status

Fig. 2. Mean desire for sex and mean progesterone concentrations aligned against estimated day of cycle (day 0 represents the estimated day of ovulation) for the set of ovulatory
cycles. Desire values are standardized within-cycles such that zero on the primary y-axis represents the mean desire for sex within a given cycle. Error bars are ± SEM.

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641

Table 3Mixed regression models testing within-cycle predictors of sexual behavior.
2-day lagγ (Exp b)

1-day lagp-value(n = 586)
Progesterone
Estradiol
Testosterone
Weekend−0.09 (0.92)
0.17 (1.19)
0.19 (1.21)
1.10 (3.01)

γ (Exp b)

Current day
p-value(n = 621)
0.47
0.23
0.18
b0.0001

0.02 (1.02)
0.02 (1.02)
0.15 (1.16)
0.67 (1.95)

γ (Exp b)

p-value(n = 642)
0.87
0.91
0.32
0.01

0.02 (1.02)
0.30 (1.34)−0.05 (0.95)
1.15 (3.17)

0.87
0.02
0.76
b0.0001

Note. Hormone variables were standardized (relative to their respective grand means) and then group-mean centered within-cycles; as such, coefﬁcients represent the within-cycle change inthe odds ratio for sexual behavior (Exp b) associated with a 1 SD change in hormone concentrations. Weekend was dummy coded. Bold font highlights statistically signiﬁcant predictors.

did not interact with any of the other predictor variables in the mixed
regression models, and thus the sexual behavior analyses were collapsed
across single and partnered women. A total of 186 episodes of masturbation were reported, distributed across 23 women.
Within-cycle analyses
Mixed model binary logistic regression was employed to model the
probability of sexual behavior (i.e. genital contact with another person)
on a given day for the set of women with hormone data who reported
any sex (n = 29). Table 3 presents models testing the effects of hormones measured the same day, one day earlier, and two days earlier.
There was a signiﬁcant effect of current day estradiol: for each one
standard deviation increase in estradiol, the odds of sexual behavior
increased by 34% relative to other days in the same cycle. No othermain effects of hormones were signiﬁcant, although there was a positive interaction between current day testosterone and progesterone(p = 0.013) such that progesterone had more positive effects when
testosterone was high than when testosterone was low; given the number of interactions tested in an exploratory manner, though, this effectshould be interpreted with caution. Weekend timing was a strong, positive predictor of sexual activity in all three models; considered acrossall cases (i.e. whether or not hormone data were available on a givenday), the probability of sex on weekend days was 22% versus 9% onother days. As with sexual desire, the effects of weekend timing wereindependent of the effects of hormone concentrations.
The same models depicted in Table 3 were re-run with womaninitiated sex as the dependent variable, which restricted the analysis to a
subset of the sexual behavior events. These models identiﬁed only two
trends among the hormone variables: a positive effect for current day
estradiol (γ = 0.35, p = 0.08, Exp b = 1.43), and a negative effect for
current day progesterone (γ = −0.45, p = 0.06, Exp b = 0.64).
Similarly, when masturbation was entered as the dependent variable(analyses were restricted to the 23 women who reported any

masturbation), a trend toward a positive effect of current day estradiol(γ = 0.28, p = 0.06, Exp b = 1.33) was the only result that approachedsigniﬁcance.
Whether a response day fell within the fertile window did notpredict the odds of sexual contact, woman-initiated sexual contact,or masturbation (all ps > 0.10). Fig. 3 plots the mean probability ofsexual contact by cycle day; mean estradiol concentrations are also
depicted, given the positive relationship between current day estradiol
and odds of sex (see Table 3). Visual inspection of the ﬁgure suggests
the absence of any clear mid-cycle peak in sexual frequency.
On the recommendation of a reviewer, we also examined whether
menstrual bleeding or premenstrual timing affected the within-cycle prediction of sexual behavior; in principle, hormone effects could be artifactsof avoidance of sexual activity due to discomfort associated with these
events. Dummy variables were created indicating whether a woman
reported bleeding on a given response day, and whether a response day
was one of the last four days before onset of next menses. These variables
were ﬁrst entered into mixed regression models that included weekend
timing but not the hormone variables: premenstrual timing did not
signiﬁcantly predict any of the sexual behavior variables; menstrual
bleeding was associated with lower odds of sexual behavior with apartner (γ = − 1.26, p = 0.001, Exp b = 0.28), and with lower
odds of woman-initiated sexual contact (γ = −1.14, p = 0.016, Expb = 0.32). Addition of these variables to the models that tested thewithin-cycle effects of hormone concentrations, however, had minimal
effects on the coefﬁcients for the hormone variables: the only statistical conclusion altered by the addition of these terms was themarginally signiﬁcant effect of estradiol on the odds of masturbation (see above), which became statistically signiﬁcant (γ = 0.35,
p = 0.024, Exp b = 1.42), although even in this case the change inodds ratio was small. The signiﬁcant effect of current day estradiol on
the probability of sexual behavior with a partner was basically unaffected by addition of these variables (γ = 0.31, p = 0.022, Exp b = 1.36;

Fig. 3. Mean probability of sexual contact and mean estradiol concentrations aligned against estimated day of cycle (day 0 represents the estimated day of ovulation) for the set of
ovulatory cycles in which sexual behavior was reported. Error bars are ± SEM.

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J.R. Roney, Z.L. Simmons / Hormones and Behavior 63 (2013) 636–645

compare Table 3). Likewise, neither bleeding nor premenstrual timing
signiﬁcantly predicted the sexual desire variable, and addition of thesevariables to the models depicted in Table 2 had minimal effects on the
coefﬁcients for the hormone variables.
Between-cycle and between-women analyses
For the sexual contact variable, in a mixed logistic model testing theeffects of all three hormones, cycle mean progesterone was a negative
predictor of the odds of sex (γ = −1.01, p = 0.047, Exp b = 0.36),
meaning that, within-women, change in average progesterone fromcycle 1 to cycle 2 was negatively associated with change in the meanfrequency of sex across the two cycles. A separate model testing theeffects of subject mean hormone concentrations across the full study
revealed no signiﬁcant effects (all ps > 0.15); this means that women
who had sex more frequently did not differ in average hormone concentrations from women who had sex less frequently. Parallel models
revealed no signiﬁcant between-cycle or between-women effects ofmean hormone concentrations for either woman-initiated sex or
masturbation.
Discussion
Sexual desire
Although many studies had implicated a role for ovarian hormonesin the regulation of women's sexual motivation via cycle phase shifts
in desire (for a review, see Wallen, 2001), past attempts to document
hormonal predictors of within-cycle shifts in libido had produced null
results (e.g., Dennerstein et al., 1994; Morris et al., 1987; Persky et al.
1978a,b; Van Goozen et al., 1997). Here, with a much larger sample
size and the use of more powerful mixed regression techniques, we identiﬁed two hormone variables with opposite effects: estradiol measured
two days earlier positively predicted within-cycle ﬂuctuations in sexualdesire, as predicted, whereas progesterone was a consistent negative
predictor across the current day, one day lag, and two day lag regression
models. These effects are consistent with patterns demonstrated in
nonhuman primates, as both correlational (e.g., Wallen et al., 1984) andexperimental (e.g., Kendrick and Dixson, 1985; Zehr et al., 1998) studies
support excitatory and inhibitory effects of estradiol and progesterone,
respectively, on measures of female sexual motivation.
Our results also demonstrated higher subjective desire inside the estimated fertile window than at other times in the cycle. Although a numberof previous studies had likewise demonstrated such effects, the extant
literature was not entirely consistent on this point, as some studies
had failed to report mid-cycle peaks (for a review, see Regan, 1996).
Only a few of the studies on this topic had, like the current study, usedhormone assays (either luteinizing hormone (LH) tests or frequent ovarian hormone sampling) to conﬁrm ovulatory timing, however, and resultsfrom those studies point more consistently toward peri-ovulatory peaks
in measures of sexual motivation (Bullivant et al., 2004; Dennerstein
et al., 1994; Diamond and Wallen, 2011; Hedricks et al., 1994; Wilcox
et al., 2004). As such, although a formal meta-analysis of this issue may
be warranted, the weight of the current evidence appears to argue strongly for mid-cycle increases in measures of women's sexual motivation.
Positive effects of estradiol and negative effects of progesterone could
efﬁciently explain such mid-cycle peaks in sexual desire given typical
patterns of hormone secretion across the menstrual cycle (see Fig. 1).
With respect to the drop in sexual desire when moving from ovulation
to the luteal phase, we did in fact ﬁnd strong evidence for statistical
mediation by progesterone; because estradiol and testosterone bothtend to drop between ovulation and the luteal phase, it was possiblethat these hormones would mediate the luteal phase drop in desire, but
in fact the fertile window effect was just as strong when these hormones
were added to the regression model, whereas the fertile window effect
dropped out entirely after the addition of progesterone. These patterns
argue for progesterone acting as a within-cycle stop signal that produces

luteal phase reductions in sexual desire. With respect to the follicularphase increase in desire when moving from menstruation to the fertile
window, though, we were unable to demonstrate substantial hormonal
mediation, despite the positive effects of estradiol on desire. This suggests
the possibility that other signals of ovulatory timing may play importantroles in producing the increases in measures of sexual motivation that areoften found just before ovulation (see Fig. 2; Bullivant et al., 2004; Wilcox
et al., 2004). Luteinizing Hormone Releasing Hormone (LHRH) and LH are
signals associated with impending ovulation, and LHRH in particular has
been experimentally linked to higher sexual motivation in nonhumanspecies (e.g., Barnett et al., 2006; Mauk et al., 1980); likewise, someevidence in humans supports higher oxytocin near mid-cycle, as well
positive associations between oxytocin and measures of sexual function(e.g., Salonia et al., 2005). Empirical tests of whether these or other signals
may help mediate the ovulatory increase in sexual motivation may haveimportant clinical implications for the possible treatment of hypoactive
sexual desire.
Peri-ovulatory increases in sexual motivation may have various
biological functions. Promotion of conception is obvious, but chronicallyhigh sexual motivation could achieve the same thing, so that the realquestion here is why motivation drops at other times of the cycle.
Sexual behavior has likely entailed ﬁtness costs over the course ofevolution—from risk of sexually transmitted infection to opportunity
costs in terms of alternative behaviors—and thus the beneﬁt-cost ratioof sexuality may have been greater on average when conception was
possible than at other times of the cycle. Fessler (2003) has argued
that the competing attentional demands of mating and feeding tend
to be resolved in favor of mating during the late follicular phase, and, ingeneral, the progesterone-mediated drop in sexual desire seen in theluteal phase of the present sample (see Fig. 2) could reﬂect the operationof mechanisms that increase the relative motivation for non-mating tasks
during infertile regions of the cycle.
A similar argument for motivational re-prioritization could apply at
longer time-scales, and led us to hypothesize between-cycle correlations between estradiol and sexual motivation. Women in humanancestral environments likely often experienced multi-year stretchesof suppressed fertility and low ovarian hormones associated with
events like lactation and food shortage, and only rarely experienced
fertile cycles with higher estradiol (see Ellison, 2001; Lancaster andKaplan, 2009; Strassmann, 1997); suppression of sexual motivation
during these infertile periods could have promoted greater allocationof attention and motivation to more pressing tasks such as maternalcare or foraging, with rising estradiol associated with the resumption offertile cycles then causing the up-regulation of sexual motivation (seeRoney, 2009; Roney and Simmons, 2008). Our current data failed to conﬁrm a within-women, between-cycle association between estradiol andsexual desire, however, and the direction of the relationship was
actually negative. Restricted variance in estradiol concentrations
and the desire variable between the two cycles within the same
women likely limited our ability to detect any such effects. Consistent
with our hypothesis, though, studies that have followed women longitudinally through the menopausal transition have in fact reported withinwomen, between-cycle correlations between estradiol and measures ofsexual motivation (Dennerstein et al., 2005; Freeman et al., 2007;
McCoy, 1990). Demonstration of similar within-women, between-cycle
effects in premenopausal women may require following the same
women across cycles with larger differences in hormone concentrations than those observed in the present study.
Our data also produced null results with respect to between-womenassociations between mean hormone concentrations and mean sexualdesire, although the power of our design was fairly modest at the
between-women level of analysis. The zero-order correlation between
subject mean estradiol and mean sexual desire was r = 0.23, but approximately 75 subjects would be necessary to meet conventional levels of
statistical signiﬁcance for this effect size, as compared to the 43 womenin the current design.

J.R. Roney, Z.L. Simmons / Hormones and Behavior 63 (2013) 636–645

Finally, weekend timing was a consistent within-cycle predictor ofwomen's self-reported sexual desire. This effect was independent of
the effects of hormone concentrations, which suggests that desire may
respond independently to both endogenous ﬂuctuations in hormone
concentrations and to external social stimuli that are likely associatedwith weekend timing in an undergraduate population.
Sexual behavior
Only a subset of the women in our sample were sexually active,
which may have limited our ability to detect hormonal predictors of
sexual behavior. Although effects were less consistent than for sexualdesire, the within-cycle patterns were similar: positive effects for estradiol, a negative trend for progesterone, and null effects for testosterone.
The only effect to reach signiﬁcance was the association between current day estradiol and the probability of sexual contact: within-cycles,
women were more likely to have sex on high estradiol days than on
low estradiol days. Effects of current day estradiol on woman-initiatedsex and masturbation were positive but marginally signiﬁcant, andcurrent day progesterone had a marginally signiﬁcant negative effecton the odds of woman-initiated sex. The effects of weekend timing on
sexual behavior were very strong, with weekend days associated witha doubling or tripling of the odds ratios for sexual contact in thewithin-cycle models (see Table 3). The temporal constraints associatedwith class schedules and partner availability may have inﬂated theeffects of weekend timing (and obscured the effects of hormonal predictors) in this sample relative to women who cohabit with their partners. Thus, although the overall pattern of results suggests that thepositive effects of estradiol and negative effects of progesterone in thewithin-cycle prediction of sexual desire may also extend to the predictionof sexual behavior, the evidence here is far from deﬁnitive and future research that selectively targets women within sexual relationships may
facilitate the acquisition of clearer evidence on this issue.
All of the signiﬁcant or trend-level effects for the behavior variables
pertained to current day hormone measures, whereas the strongest
effects for sexual desire were found at a two-day lag (see Table 2). The
reasons for this pattern are unclear. Genomic effects of hormones
may produce synaptic changes at time lags, but hormones like estradiol can also act at shorter time-scales via non-genomic mechanisms(e.g., Stefano et al., 2000); as such, different outcomes could be differentially associated with alternative mechanisms of hormone action. A combination of time-lagged and current day hormone concentrations could
provide the strongest prediction of sexual variables if processes of receptor induction need to be combined with current receptor occupation to
produce phenotypic outcomes. We were unable to test this possibility
in the present study due to missing data associated with days without
assays, but such tests represent an interesting direction for future
research.
Within-women, between-cycle and between-women effects of hormones on sexual behavior were generally absent, save for a negative
effect of cycle mean progesterone on the mean frequency of sex acrossthe two cycles within the same women. This effect was not predicted,
but if reliable would suggest that the within-cycle inhibitory effects ofprogesterone may extend between-cycles, as well. The null results atthe between-cycle and between-women levels of analysis for sexual
behavior are subject to the same caveats regarding restricted hormone
variance and modest power as were explained above for the sexualdesire variable.
Null effects of testosterone
We found no signiﬁcant effects of testosterone on any variable at any
time-scale. This is potentially noteworthy given evidence that exogenous
testosterone treatment can improve measures of sexual motivation inmenopausal women (e.g., Braunstein et al., 2005; Davis et al., 2008;
Floter et al., 2002; Sherwin et al., 1985), and given the common belief

643

that androgens are the primary regulators of libido in women. Similarnull effects for testosterone have been found for correlates of sexual
behavior in naturally cycling, group-living rhesus macaques (Wallen
et al., 1984). Exogenous testosterone may therefore have pharmacological effects on sexual motivation despite the fact that endogenous testosterone does not play an important role in the regulation of libido innatural menstrual cycles. If sexual motivation in women were regulatedby androgens via the androgen receptor, one would expect positive correlations between desire and free testosterone concentrations in natural
menstrual cycles since estradiol could not act through this receptor.
Exogenous testosterone, on the other hand, could act indirectly via estrogen receptors either by conversion to estradiol (via aromatase) or by theregulation of binding proteins in such a way as to increase the bioavailable concentrations of estradiol (see Wallen, 2001). The absence of testosterone effects in natural cycles thus argues against substantial regulationof libido by androgen receptors in women (normal libido in androgen
insensitivity syndrome women suggests the same; see Wisniewski
et al., 2000), though more direct empirical evidence regarding receptor
involvement is clearly needed.
Conclusion
The present study replicated peri-ovulatory peaks in women's subjective sexual desire, but also identiﬁed hormonal predictors of within-cycle
ﬂuctuations in desire. Progesterone had a consistent negative effect ondesire across time-lags, and appears to act as an inhibitory signal forsexual motivation; estradiol had a positive effect on desire at a two-day
lag. Effects for sexual behavior were less clear, but also implicated positiveeffects of estradiol and negative effects for progesterone. Signiﬁcantlimitations of the present study include its use of an undergraduate
population that may differ in important ways both hormonally and behaviorally compared to older women, and our inability to assay samples
from every day of the study due to ﬁnancial constraints, which precluded
testing multiple time lags in the same regression models. Collection ofcomplete hormone data from more representative, community-based
samples of women thus represents an important direction for future
research.
Acknowledgments
The authors thank Haylie Barlow, Lindsay Best, Kim Botts, Christine
Fitch, Sarah Hat, Juliette Hatﬁeld, Sarah Huxster, Rhonda Jarrar, Amanda
Lane, Danielle Moffett, Courtney Moore, Anna Plumlee, Erica Ramos,
Sandra Short, Lola Stanton, Bryana Turner, Vanessa Volpicelli, and Joy
Wyckoff for assistance with data collection. Funding for this research
was provided by a Hellman Family Faculty Fellowship and UCSB
Academic Senate Grant to J.R.R., and by a grant from the Global COE
Program (“Center for the Sociality of Mind”) of Hokkaido University to
the Center for Evolutionary Psychology at UCSB. Funding sources had
no role in data collection, analysis, writing, or the decision to publish.
Appendix A
The formal regression equations for the mixed models, using the current day model depicted in Table 2 (main text) as an example, were as
follows:
Level-1 model:
Yijk = π0jk + π1jk ∗ (weekend) + π2jk ∗ (estradiol) + π3jk ∗(progesterone) + π4jk ∗ (testosterone) + εijk
WhereYijk = Sexual desire rating on day i in cycle j for person k
π0jk = Intercept for sexual desire within cycle j for person k
π1jk … π4jk = Regression slopes for predictor variables in cycle
j for person k

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J.R. Roney, Z.L. Simmons / Hormones and Behavior 63 (2013) 636–645

εijk = Error term (residual) associated with day i in cycle j forperson k
Level-2 model:
π0jk = β0k + r0jk
π1jk = β10k
π2jk = β20k
π3jk = β30k
π4jk = β40k
Whereβ0k = Intercept for sexual desire for person k
r0jk = Error term for cycle mean sexual desire in cycle j forperson k
β10k … β40k = Average regression slopes for predictor variables for person k
Level-3 model:
β0k = γ000 + μ00k
β10k = γ100
β20k = γ200
β30k = γ300
β40k = γ400
Where
γ000 = Grand mean for sexual desire
μ00k = Error term for person k mean sexual desire
γ100 … γ400 = Average regression slopes for predictor variables
computed across all cycles and subjects using maximum likelihood
estimation
Mixed model:
Yijk = γ000 + μ00k + r0jk + γ100 ∗ (weekend) + γ200 ∗(estradiol) + γ300 ∗ (progesterone) + γ400 ∗ (testosterone) + εijk
The within-cycle models included only Level-1 predictors (see above)since within-women, between-cycle effects could only be tested
for women with two cycles of hormone data, such that addition of
Level-2 predictors would have led to information loss at Level-1. We
then constructed separate models with only Level-2 or Level-3 predictors to test within-women, between-cycle and between-women effects.
Within-women, between-cycle effects were tested by entering cyclecentered mean hormone variables (e.g., cycle mean estradiol minus
subject mean estradiol) as predictors of π0jk in the Level-2 model.
Between-women effects were tested by entering subject mean hormone
concentrations as predictors of β0k in the Level-3 model. By entering
predictors at only one level, the higher level models were able to include all days for which survey responses were available (e.g., subject
mean estradiol was tested for prediction of subject mean desire computed across all survey days instead of only those days with hormone
assays), which maximized use of available information; however, thenull effects of higher level variables reported in the text were stillfound if Level-2 and Level-3 predictors were added to models that included the Level-1 predictors and thus restricted analyses to thosedays with hormone assays.

References
Adams, D.B., Gold, A.R., Burt, A.D., 1978. Rise in female-initiated sexual activity at ovulationand its suppression by oral contraceptives. N. Engl. J. Med. 299, 1145–1150.
Alexander, J.L., Kotz, K., Dennerstein, L., Kutner, S.J., Wallen, K., Notelovitz, M., 2004.
The effects of postmenopausal hormone therapies on female sexual functioning:a review of double-blind, randomized controlled trials. Menopause 11, 749–765.
Bancroft, J., Sanders, D., Davidson, D., Warner, P., 1983. Mood, sexuality, hormones, andthe menstrual cycle. III. Sexuality and the role of androgens. Psychosom. Med. 45,
509–516.
Barnett, D.K., Bunnell, T.M., Millar, R.P., Abbott, D.H., 2006. Gonadotropin-releasing
hormone II stimulates female sexual behavior in marmoset monkeys. Endocrinology
147, 615–623.
Blaustein, J.D., 2008. Neuroendocrine regulation of feminine sexual behavior: lessons
from rodent models and thoughts about humans. Annu. Rev. Psychol. 59, 93–118.

Bodenmann, G., Atkins, D.C., Schar, M., Poffet, V., 2010. The association between dailystress and sexual activity. J. Fam. Psychol. 24, 271–279.
Braunstein, G.D., Sundwall, D.A., Katz, M., Shifren, J.L., Buster, J.E., Simon, J.A., Bachman,G., Aguirre, O.A., Lucas, J.D., Rodenberg, C., Buch, A., Watts, N.B., 2005. Safety and efﬁcacy
of a testosterone patch for the treatment of hypoactive sexual desire disorder insurgically menopausal women. Arch. Intern. Med. 165, 1582–1589.
Bullivant, S.B., Sellegren, S.A., Stern, K., Spencer, N.A., Jacob, S., Mennella, J.A., McClintock,
M.K., 2004. Women's sexual desire during the menstrual cycle: identiﬁcation of thesexual phase by noninvasive measurement of luteinizing hormone. J. Sex Res. 41,
82–93.
Carter, C.S., 1992. Neuroendocrinology of sexual behavior in the female. In: Becker, J.B.,
Breedlove, S.M., Crews, D. (Eds.), Behavioral Endocrinology. MIT Press, Cambridge,
MA, pp. 71–95.
Davis, S.R., Moreau, M., Kroll, R., Bouchard, C., Panay, N., Gass, M., Braunstein, G.D.,
Hirschberg, A.L., Rodenberg, C., Pack, S., Koch, H., Moufarege, A., Studd, J., 2008.
Testosterone for low libido in postmenopausal women not taking estrogen. N.
Engl. J. Med. 359, 2005–2017.
Dennerstein, L., Wood, C., Burrows, G.D., 1977. Sexual response following hysterectomy
and oophorectomy. Obstet. Gynecol. 49, 92–96.
Dennerstein, L., Burrows, G.D., Wood, C., Hyman, G., 1980. Hormones and sexuality:
effect of estrogen and progesterone. Obstet. Gynecol. 56, 316–322.
Dennerstein, L., Gotts, G., Brown, J.B., Morse, C.A., Farley, T.M.M., Pinol, A., 1994. The
relationship between the menstrual cycle and female sexual interest in womenwith PMS complaints and volunteers. Psychoneuroendocrinology 19, 293–304.
Dennerstein, L., Lehert, P., Burger, H., 2005. The relative effects of hormones and relationship factors on sexual function of women through the natural menopausal
transition. Fertil. Steril. 84, 174–180.
Diamond, L.M., Wallen, K., 2011. Sexual minority women's sexual motivation aroundthe time of ovulation. Arch. Sex. Behav. 40, 237–246.
Ellison, P.T., 2001. On Fertile Ground. Harvard University Press, Cambridge, MA.
Ellison, P.T., Lager, C., Calfee, J., 1987. Low proﬁles of salivary progesterone among college
undergraduate women. J. Adolesc. Health Care 8, 204–207.
Fessler, D.M.T., 2003. No time to eat: an adaptationist account of periovulatory behavioral changes. Q. Rev. Biol. 78, 3–21.
Floter, A., Nathorst-Boos, J., Carlstrom, K., von Schoultz, B., 2002. Addition of testosterone
to estrogen replacement therapy in oophorectomized women: effects on sexuality
and well-being. Climacteric 5, 357–365.
Freeman, E.W., Sammel, M.D., Lin, H., Gracia, C.R., Pien, G.W., Nelson, D.B., Sheng, L.,2007. Symptoms associated with menopausal transition and reproductive hormones in midlife women. Obstet. Gynecol. 110, 230–240.
Gann, P.H., Giovanazzi, S., Van Horn, L., Branning, A., Chatterton, R.T., 2001. Saliva asa medium for investigating intra- and interindividual differences in sex hormone levels in premenopausal women. Cancer Epidemiol. Biomarkers Prev.
10, 59–64.
Gracia, C.R., Freeman, E.W., Sammel, M.D., Lin, H., Mogul, M., 2007. Hormones andsexuality during the transition to menopause. Obstet. Gynecol. 109, 831–840.
Granger, D.A., Schwartz, E.B., Booth, A., Arentz, M., 1999. Salivary testosterone determination in studies of child health and development. Horm. Behav. 35, 18–27.
Harvey, S.M., 1987. Female sexual behavior: ﬂuctuations during the menstrual cycle.
J. Psychosom. Res. 31, 101–110.
Hedricks, C.A., Schramm, W., Udry, J.R., 1994. Effects of creatinine correction to urinary
LH levels on the timing of the LH peak and distribution of coitus within the humanmenstrual cycle. Ann. N. Y. Acad. Sci. 709, 204–206.
Kendrick, K.M., Dixson, A.F., 1985. Effects of oestradiol 17B, progesterone and testosterone upon proceptivity and receptivity in ovariectomized common marmosets(Callithrix jacchus). Physiol. Behav. 34, 123–128.
Lancaster, J., Kaplan, H., 2009. The endocrinology of the human adaptive complex. In:
Ellison, P.T., Gray, P.B. (Eds.), Endocrinology of Social Relationships. Harvard University Press, Cambridge MA, pp. 95–118.
Lipson, S.F., Ellison, P.T., 1996. Comparison of salivary steroid proﬁles in naturally
occurring conception and non-conception cycles. Hum. Reprod. 11, 2090–2096.
Matteo, S., Rissman, E.F., 1984. Increased sexual activity during the midcycle portion of
the human menstrual cycle. Horm. Behav. 18, 249–255.
Mauk, M.D., Olson, G.A., Kastin, A.J., Olson, R.D., 1980. Behavioral effects of LH–RH.
Neurosci. Biobehav. Rev. 4, 1–8.
McCoy, N.L., 1990. Estrogen levels in relation to self-reported symptoms and sexuality
in perimenopausal women. Ann. N. Y. Acad. Sci. 592, 450–452.
Morris, N.M., Udry, R.J., Khan-Dawood, F., Dawood, M.Y., 1987. Marital sex frequency
and midcycle female testosterone. Arch. Sex. Behav. 16, 27–37.
Nathorst-Boos, J., Wiklund, I., Mattsson, L.A., Sandin, K., von Schoultz, B., 1993. Is sexual
life inﬂuenced by transdermal estrogen therapy? A double blind placebo controlled
study in postmenopausal women. Acta Obstet. Gynecol. Scand. 72, 656–660.
Persky, H., Charney, N., Lief, H.I., O'Brien, C.P., Miller, W.R., Strauss, D., 1978a. The relationships of plasma estradiol level to sexual behavior in young women.
Psychosom. Med. 40, 523–535.
Persky, H., Lief, H.I., Strauss, D., Miller, W.R., O'Brien, C.P., 1978b. Plasma testosterone
level and sexual behavior of couples. Arch. Sex. Behav. 7, 157–173.
Pfaff, D., Frohlich, J., Morgan, M., 2002. Hormonal and genetic inﬂuences on arousal—
sexual and otherwise. Trends Neurosci. 25, 45–50.
Pillsworth, E.G., Haselton, M.G., Buss, D.M., 2004. Ovulatory shifts in female sexual desire.
J. Sex Res. 41, 55–65.
Powers, J.B., 1970. Hormonal control of sexual receptivity during the estrous cycle of
the rat. Physiol. Behav. 5, 831–835.
Raudenbush, S.W., Bryk, A.S., 2002. Hierarchical Linear Models. Sage, Thousand Oaks, CA.
Regan, P.C., 1996. Rhythms of desire: the association between menstrual cycle phases
and female sexual desire. Can. J. Hum. Sex. 5, 145–156.

J.R. Roney, Z.L. Simmons / Hormones and Behavior 63 (2013) 636–645
Roney, J.R., 2009. The role of sex hormones in the initiation of human mating relationships. In: Ellison, P.T., Gray, P.B. (Eds.), Endocrinology of Social Relationships. Harvard
University Press, Cambridge, MA, pp. 246–269.
Roney, J.R., Simmons, Z.L., 2008. Women's estradiol predicts preference for facial cuesof men's testosterone. Horm. Behav. 53, 14–19.
Salonia, A., Nappi, R.E., Pontillo, M., Daverio, R., Smeraldi, A., Briganti, A., Fabbri, F.,
Zanni, G., Rigatti, P., Montorsi, F., 2005. Menstrual cycle-related changes in plasma
oxytocin are relevant to normal sexual function in healthy women. Horm. Behav.
47, 164–169.
Schmidt, P.J., Steinberg, E.M., Negro, P.P., Haq, N., Gibson, C., Rubinow, D.R., 2009. Pharmacologically induced hypogonadism and sexual function in healthy young womenand men. Neuropsychopharmacology 34, 565–576.
Schreiner-Engel, P., Schiavi, R.C., 1981. Sexual arousability and the menstrual cycle.
Psychosom. Med. 43, 199–214.
Sherwin, B.B., 1991. The impact of different doses of estrogen and progestin on moodand sexual behavior in postmenopausal women. J. Clin. Endocrinol. Metab. 72,
336–343.
Sherwin, B.B., Gelfand, M.M., Brender, W., 1985. Androgen enhances sexual motivationin females: a prospective, crossover study of sex steroid administration in the surgicalmenopause. Psychosom. Med. 47, 339–351.
Stanislaw, H., Rice, F.J., 1988. Correlation between sexual desire and menstrual cycle
characteristics. Arch. Sex. Behav. 17, 499–508.
Stefano, G.B., Prevot, V., Beauvillain, J.C., Cadet, P., Fimiani, C., Welters, I., Fricchione, G.L.,
Breton, C., Lassalle, P., Salzet, M., Bilﬁnger, T.V., 2000. Cell-surface estrogen receptors
mediate calcium-dependent nitric oxide release in human endothelia. Circulation 101,
1594–1597.
Strassmann, B.I., 1997. The biology of menstruation in Homo sapiens: total lifetime menses,
fecundity, and nonsynchrony in a natural-fertility population. Curr. Anthropol. 38,
123–129.

645

Stuckey, B.G.A., 2008. Female sexual function and dysfunction in the reproductive years:
the inﬂuence of endogenous and exogenous sex hormones. J. Sex. Med. 5, 2282–2290.
Van Goozen, S.H.M., Wiegant, V.M., Endert, E., Helmond, F.A., Van de Poll, N.E., 1997.
Psychoneuroendocrinological assessment of the menstrual cycle: the relationshipbetween hormones, sexuality, and mood. Arch. Sex. Behav. 26, 359–382.
Venners, S.A., Liu, X., Perry, M.J., Korrick, S.A., Li, Z., Yang, F., Yang, J., Lasley, B.L., Xu, X.,
Wang, X., 2006. Urinary estrogen and progesterone metabolite concentrations inmenstrual cycles of fertile women with non-conception, early pregnancy loss or
clinical pregnancy. Hum. Reprod. 21, 2272–2280.
Wallen, K., 2001. Sex and context: hormones and primate sexual motivation. Horm.
Behav. 40, 339–357.
Wallen, K., Winston, L.A., Gaventa, S., Davis-DaSilva, M., Collins, D.C., 1984. Periovulatorychanges in female sexual behavior and patterns of ovarian steroid secretion in groupliving rhesus monkeys. Horm. Behav. 18, 431–450.
Whalen, R.E., 1974. Estrogen-progesterone induction of mating in female rats. Horm.
Behav. 5, 157–162.
Wiklund, I., Karlberg, J., Mattsson, L.A., 1993. Quality of life of postmenopausal women
on a regimen of transdermal estradiol therapy: a double-blind placebo-controlled
study. Am. J. Obstet. Gynecol. 168, 824–830.
Wilcox, A.J., Weinberg, C.R., Baird, D.D., 1998. Post-ovulatory ageing of the humanoocyte and embryo failure. Hum. Reprod. 13, 394–397.
Wilcox, A.J., Baird, D.D., Dunson, D.B., McConnaughey, D.R., Kesner, J.S., Weinberg, C.R.,
2004. On the frequency of intercourse around ovulation: evidence for biological inﬂuences. Hum. Reprod. 19, 1539–1543.
Wisniewski, A.B., Migeon, C.J., Meyer-Bahlburg, H.F.L., Gearhart, J.P., Berkovitz, G.D., Brown,
T.R., Money, J., 2000. Complete androgen insensitivity syndrome: long-term medical,
surgical, and psychosexual outcome. J. Clin. Endocrinol. Metab. 85, 2664–2669.
Zehr, J.L., Maestripieri, D., Wallen, K., 1998. Estradiol increases female sexual initiation
independent of male responsiveness in rhesus monkeys. Horm. Behav. 33, 95–103.