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S T U D Y P R O T O C O L Open Access
The Swiss Perimenopause Study –study
protocol of a longitudinal prospective study
in perimenopausal women
Jasmine Willi
1,2†
, Hannah Süss
1,2†
and Ulrike Ehlert
1,2*
Abstract
Background: The perimenopause is associated with considerable biopsychosocial changes. The majority of women
manage to adjust to these changes and cope well with the shift from reproductive to non-reproductive life.
However, some women develop burdensome physical and psychological symptoms during the perimenopause. A
strong link between menopausal complaints and depressed mood has been shown in this regard. To date, the
decisive factors determining whether a woman will successfully achieve a healthy transition remain unclear. Thus,
the purpose of this study is to investigate a range of theory-based markers related to health in perimenopausal
women.
Methods: The Swiss Perimenopause Study comprises a sample of 135 healthy perimenopausal women aged 40–56.
A variety of health-related genetic, epigenetic, endocrinological, physiological, and psychosocial markers associated
with the menopausal transition are investigated over a period of 13 months.
Discussion: The Swiss Perimenopause Study will contribute to a better understanding of the biopsychosocial
processes associated with the perimenopause, which should help to improve the clinical care of women
undergoing the menopausal transition.
Keywords: Perimenopause, Menopausal transition, Reproductive aging, Women’s health, Resilience, Depression,
Depressed mood
Background
The perimenopause is related to substantial biological,
psychological and social changes [1–3]. It describes the
biological shift from reproductive to non-reproductive life,
which is associated with significant alterations in the fe-
male hormonal system. The perimenopause is considered
as a phase of strong fluctuations in sex hormones such as
estradiol and progesterone [4,5]. Endocrinological varia-
tions have been correlated with a higher risk of
burdensome physical and psychological symptoms [6–12],
subsumed under the term “menopausal complaints”.
These complaints are generally divided into psychological,
somato-vegetative, and urogenital symptoms. However, in
spite of the major biopsychosocial changes and challenges,
most women adjust well to the perimenopause, reporting
a good quality of life and an overall positive well-being
[13]. It is assumed that resilience might be a key factor in
determining whether or not a woman will be negatively af-
fected by menopausal symptoms [14]. Women with high
levels of resilience are believed to more effectively and
successfully adapt to the substantial changes in the peri-
menopause [15,16] compared to less resilient women. In
turn, women with lower levels of resilience are suggested
to be more affected by menopausal complaints like
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* Correspondence: u.ehlert@psychologie.uzh.ch
†
Jasmine Willi and Hannah Süss contributed equally to this work.
1
Clinical Psychology and Psychotherapy, University of Zurich,
Binzmühlestrasse 14, 8050 Zurich, Switzerland
2
URPP Dynamics of Healthy Aging Research Priority Program, University of
Zurich, Zurich, Switzerland
Willi et al. Women's Midlife Health (2020) 6:5
https://doi.org/10.1186/s40695-020-00052-1
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vasomotor symptoms or sleep disturbances. Such symp-
toms may then co-occur and have been shown to interact
with depressed mood [17–19], suggesting the perimeno-
pause as a window of vulnerability for mood disturbances
[20]. Indeed, prevalence rates of depressed mood during
the perimenopause are particularly high [21]. Conse-
quently, the investigation of depression in the course of
the menopausal transition has gained importance over the
last decades.
The attention paid to women’s health research has
gradually increased since the 1970s [22]. One of the first
longitudinal studies on the menopausal transition was
the Massachusetts Women’s Health Study (MWHS)
[23], followed by the Seattle Midlife Women’s Health
Study (SMWHS), which collected data over 23 years
[24]. In Norway, a large cohort study, the Nord-
Trøndelag Health Study (HUNT) [25], began in 1984
and is considered one of the largest health studies ever
performed. Further large studies on the menopausal
transition, such as the Study of Women’s Health Across
the Nation (SWAN) [26], the Penn Ovarian Aging Study
(POAS) [4], or the Harvard Study of Moods and Cycles
[27], followed in the US. Extensive research on women
in midlife has also been conducted in Australia, within
the Australian Longitudinal Study on Women’s Health
(ALSWH) [28] or the Melbourne Women’s Midlife
Health Project (MWMHP) [29]. Depressed mood was
one of the focal points across these studies, and all of
them highlighted the increased risk for new or recurrent
depressed mood, emphasizing the prevalence peak dur-
ing the menopausal transition. This previous research
formed an important basis for the understanding of de-
pressed mood in middle-aged women and the associated
changes and challenges.
Previous studies frequently included women across all
three menopausal stages, i.e. the pre-, the peri-, and the
postmenopause. Such a selection procedure seems to be
highly expedient in terms of identifying critical time
points in the development of symptoms in the progres-
sion from reproductive to non-reproductive life. More-
over, this sample selection also provides the opportunity
to compare the participants across the different meno-
pausal stages. However, in terms of investigating the
perimenopause as a critical window of increased biopsy-
chosocial changes and associated complaints, and in
order to specify the involved processes, it is essential to
focus specifically on the perimenopausal phase.
Therefore, the Swiss Perimenopause Study employs a
longitudinal design examining women in the perimeno-
pause only and assessing a variety of genetic, epigenetic,
endocrinological, physiological and psychosocial factors.
As such, we aim to investigate psychosocial factors like
personality traits, self-esteem, self-compassion, perceived
stress, emotion regulation and coping, or social support.
Furthermore, physiological parameters like blood pres-
sure and pulse, heart rate variability, hand grip force, or
body composition are assessed as measures associated
with healthy aging. Body weight and body height are
captured in order to take into account participants’body
mass index (BMI) when investigating biomarkers. Add-
itionally, we measure the length of the index finger and
the ring finger in order to calculate the second to fourth
digit ratio (2D:4D). Recent research showed that a higher
2D:4D is associated with a higher age at menopause,
while a lower 2D:4D (interpreted as suggesting a higher
androgen exposure during the prenatal phase) is associ-
ated with a lower age at menopause [30]. As our work-
group has shown that looking younger than one’s actual
age can be related to a variety of health outcomes [31],
we take standardized facial photographs of all partici-
pants. The full list of biopsychosocial factors included in
this study is shown in Tables 1and 2. The comprehen-
sive investigation of possible predictors of physical and
psychological complaints appears particularly promising
regarding the detection of underlying processes such as
epigenetic variations or specific hormonal patterns.
Data concerning genetic and epigenetic markers asso-
ciated with the menopausal transition are still scarce.
However, valuable information might be gained by ana-
lyzing gene-environment interactions and the effect of
epigenetic modifications on the menopausal transition-
ing [66]. For this purpose, we aim to investigate the
estrogen receptor genes (ER1, ER2, GPER), the gluco-
corticoid receptor (NR3C1) as well as the serotonin
transporter (5-HTTLPR) and the respective relationships
with a resilient menopausal transition or the develop-
ment of depression in the perimenopause. For example,
a recent study by our workgroup found a positive rela-
tionship between the methylation of the ERαenhancer
and depressed mood in women around the menopause
[67]. Consequently, one goal is to investigate the auto-
regulation between estradiol and the estrogen receptor
genes with regard to methylation patterns and subse-
quent effects on the participants’mood.
Endocrinological parameters are commonly assessed
in studies on the menopausal transition. Previous re-
search in this regard showed a significant relationship
between sex steroids and menopausal complaints [68–
70]. Several studies by our workgroup showed that corti-
sol or alpha amylase play a key role in the reactivity of
physiological stress systems [71–73], and inflammatory
markers associated with various psychopathologies
change over the menopausal transition [74]. Therefore,
their assessment is included in this study. To maximize
the informative value and comparability of the forthcom-
ing results, the Swiss Perimenopause Study is designed
to conduct a close endocrinological monitoring of all
participants, enabling progression analyses of individual
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Table 1 Psychosocial measures included in the Swiss Perimenopause Study
Ref. Construct Assessment instrument Authors Items
[32] Body image Body Image Questionnaire (Fragebogen zum Körperbild; FKB-20) Clement & Löwe,
1996
20
[33] Chronic stress Trier Inventory for Chronic Stress, short version (TICS-K) Schulz et al., 2004 30
[34] General health General Health Questionnaire (GHQ-12) Schmitz et al., 1999 12
[35] Coping COPE Inventory, short version Knoll et al., 2005 28
[36] Depressive symptoms German Version of the Center of Epidemiological Studies Depression Scale (CES-
D; Allgemeine Depressionsskala; ADS-L)
Hautzinger & Bailer,
1993
20
[37] Emotional intelligence Emotional Intelligence Questionnaire, German version (TEIQue) Freudenthaler
et al., 2008
30
[38] Emotion regulation Emotion Regulation Questionnaire, German version (ERQ) Abler & Kessler,
2009
10
[39] Eating behavior Eating Disorder Examination Questionnaire (EDE-Q) Hilbert & Caffier,
2006
28
[40] Explicit motives Life Goal Questionnaire (GOALS) Pöhlmann &
Brunstein, 1997
24
[41] Intrasexual competition German version of the Scale for Intrasexual Competition (ICS) Fiacco et al., 2018 12
[42] Life events German version of the Life Experience Survey (LES) Pluess et al., 2012 57
[43] Life satisfaction Satisfaction with Life Scale (SWLS) Glaesmer et al.,
2011
5
[44] Mastery Pearlin Mastery Scale (PM) Pearlin et al., 1981 7
[45] Menopausal symptoms Menopause Rating Scale (MRS II) Hauser et al., 1999 11
[46] Physical and mental symptoms Brief Symptom Inventory (BSI-18) Spitzer, 2011 18
[47] Pessimism/Pessimism Life Orientation Tests (LOT-R) Glaesmer et al.,
2008
10
[48] Parental bonding German version of the Parental Bonding Instrument (PBI; Fragebogen zur
elterlichen Bindung; FEB)
Lutz et al., 1995 25
[49] Personality Short version of the Big Five Inventory (BFI-K) Rammstedt & John,
2005
21
[50] Perceived stress German version of the Perceived Stress Scale (PSS-10) Klein, 2016 10
[51] Premenstrual symptoms PMS Inventory Ditzen et al., 2011 30
[52] Promiscuity Sociosexual Orientation Index (SOI-S) Penke & Asendorpf,
2008
9
[53] Relationship experiences Experiences in Close Relationships (ECR-RD 12) Ehrenthal, 2009 12
[54] Relationship quality German version of the Relationship Assessment Scale (RAS) Sander & Böcker,
1993
7
[55] Resilience Resilience Scale 11 (RS-11) Schumacher et al.,
2005
11
[56] Retrospectively assessed
relationship experiences
Sequence data analysis Abbott, 1995 10
[57] Self-compassion German Version of the Self-Compassion Scale (SCS-D) Hupfeld & Ruffieux,
2011
26
[58] Self-esteem Rosenberg Self-esteem Scale (RSE) von Collani &
Herzberg, 2003
10
[59] Sense of coherence Revised Sense of Coherence Scale (SOC-R) Bachem &
Maercker, 2016
13
[60] Sexual desire German version of the Decreased Sexual Desire Screener (DSDS) Clayton et al., 2009 5
[61] Sexual function Female Sexual Function Index (FSFI / FSFI-LL) Berner et al., 2004 19
[62] Sleep Pittsburgh Sleep Quality Index (PSQI) Backhaus, 2002 19
[63] Social support Berlin Social Support Scales (BSSS) Schulz &
Schwarzer, 2003
17
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hormone profiles. Standardized methods of analysis are
used, as described in the methods section.
By repeatedly assessing physiological data during the
night, it may be possible to address questions about the
relationship of sleep disturbances and vasomotor symp-
toms in women suffering from hot flushes and night
sweats. To the best of our knowledge, the Swiss Peri-
menopause Study represents the currently largest study
investigating such a wide range of health-related biopsy-
chosocial markers in perimenopausal women.
The purpose of the Swiss Perimenopause Study is to
gain a deeper understanding of the biopsychosocial
Table 1 Psychosocial measures included in the Swiss Perimenopause Study (Continued)
Ref. Construct Assessment instrument Authors Items
[64] Spirituality German version of the Expressions of Spirituality Inventory-Revised (ESI-R) Proyer & Laub,
2017
32
[65] Traumatic experiences Childhood Trauma Scale Short Form (CTQ-SF) Klinitzke et al., 2011 28
Table 2 Biological parameters included in the Swiss Perimenopause Study
Source Label Parameter
Saliva (SaliCaps) Endocrine parameters •Cortisol
•Alpha amylase
•Testosterone (T)
•Dehydroepiandrosterone sulfate (DHEA-S)
•Estradiol (E2)
•Progesterone (P)
Blood (DBS) Endocrine and inflammatory parameters •C-reactive protein (CRP)
•Interleukin-6 (IL-6)
•Sex hormone-binding globulin (SHBG)
•Luteinizing hormone (LH)
•Follicle-stimulating hormone (FSH)
Genetic and epigenetic parameters •Estrogen receptor genes (ER1, ER2, GPER)
•Glucocorticoid receptor (NR3C1)
•Serotonin transporter (5-HTTLPR)
Blood pressure monitor Peripheral physiological measures •Blood pressure (BP)
•Pulse
Ava bracelet Peripheral physiological nighttime measures •Skin temperature
•Ambient temperature
•Electrodermal activity (EDA)
•Heart rate (HR)
•Heart rate variability (HRV)
•Blood circulation of the skin
•Body acceleration
•Breathing rate
•Sleep phases
Body scale Anthropometric measures •Body weight
Scale •Height
BIA •Body composition
Vernier caliper •Finger lengths
Hand dynamometer •Grip force
Camera •Standardized facial photograph
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factors and processes associated with 1) resilience and
health in the perimenopause, and 2) the development of
new or recurrent depression. One key goal of this study
is to investigate biopsychosocial markers, determinants,
and processes related to a resilient menopausal transi-
tioning. In this regard, we aim to examine psychosocial
variables such as optimism, emotional stability, or self-
esteem as well as biological markers such as female sex
steroids and gonadotropins, stress hormones or inflam-
matory parameters and their relationship with well-
being and health. We assume that women with higher
psychosocial resilience (e.g. higher optimism, higher
emotional stability, higher self-esteem) and higher levels
of female sex steroids will be more successful in their
adaptation to changes and challenges associated with the
menopausal transition. A second key goal is to investi-
gate the biopsychosocial determinants and associations
of perimenopausal depression. To achieve this, we aim
to investigate specific risk factors for depressive symp-
toms in the perimenopause and to examine the effect of
endocrinological alterations and psychosocial changes
and their effect on the women’s mood. We assume that
a history of depression and fluctuations of sex steroids
are major risk factors for perimenopausal depression. As
such, it is our endeavor to expand and develop the exist-
ing knowledge on healthy menopausal transitioning. To
our knowledge, this is the first study to investigate both
depression and resilience within the perimenopause.
Methods
Design
The Swiss Perimenopause Study is an exploratory,
longitudinal, single-center, national study examining
different facets of female menopausal development
over 13 months. Data are being collected between
June 2018 and January 2021. The study is divided
into a screening phase and a study phase. After the
application of the strict inclusion criteria, interested
women were screened for about 2 months for our
study purposes. Subsequently, the actual study phase
began, which will last for 11 months. Relevant genetic,
epigenetic, endocrinological, physiological, and psy-
chological aspects of the menopausal transition are
investigated by means of different measurement
methods. The participation includes two visits to our
laboratory at the Institute of Psychology, University of
Zurich. The standardized lab visits include blood
sampling and the assessment of different peripheral
physiological (blood pressure, pulse) and anthropo-
metric parameters (body weight, body height, bioelec-
trical impedance analysis (BIA), second to fourth digit
ratio, grip strength, standardized facial photograph).
During the months between the two lab visits, partici-
pants independently collect saliva samples at home,
measure various physiological parameters with the
Ava bracelet (Ava AG, Zürich, Switzerland), complete
a menstrual cycle and mood diary, and answer a set
of different psychosocial questionnaires. An overview
of the study design can be found in Fig. 1. To date,
the screening phase and t
1
have been completed.
Sample
The population-based sample of 135 perimenopausal
women aged 40–56 were recruited through mailing lists,
social media, context-specific online forums, flyers as
well as newspaper and magazine articles. For the sample
size estimation of the planned project, we performed an
a priori sample size estimation analysis using G*Power
3.1 for different statistical analyses such as correlation
analysis, linear regression analysis, linear multiple regres-
sion analysis, or Wilcoxon signed-rank test with an α-
level < .05 [75].
From June 2018 to December 2019, a total of 1121
women showed interest in participating in the Swiss
Perimenopause Study by completing an online screening
questionnaire. The eligibility for study participation was
checked by following inclusion and exclusion criteria
(Table 3).
Major reasons for exclusion included pre- or postmen-
opausal status (n= 717), poor subjective health (n= 97),
age below 40 or above 60 years (n= 58), hormone ther-
apy in the last 6 months (n= 34), acute or chronic som-
atic or mental illness (n= 22), and psychiatric or
psychotropic drug use (n= 11). The sample inclusion
and elimination process is displayed in Fig. 2. Participants
eligible for the study were granted access to the online
menstrual cycle and mood diary for the two-month
screening phase. Within this phase, the perimenopausal
status was ensured. The perimenopausal status was de-
fined according to the Stages of Reproductive Aging
Workshop +10(STRAW) criteria, representing the most
frequently used classification system [76]:
1. Early menopausal transition: increased variability in
menstrual cycle length, defined as a persistent
difference of ≤7 days in the length of 10 consecutive
cycles.
2. Late menopausal transition: the occurrence of
amenorrhea of 60 days or longer.
In addition to the exclusion criteria, the screening
questionnaire also recorded whether the currently sub-
jectively healthy participants show a history of depres-
sion. In this regard, prior depression must either have
been previously diagnosed by an expert, or as self-
report, in accordance with the criteria for major depres-
sion according to the Diagnostic and Statistical Manual
of Mental Disorders, Fifth Edition (DSM-5).
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Retention efforts
Numerous efforts have been undertaken to retain the
eligible participants throughout the study. These include
personal and consistent contact from the research staff,
daily accessibility to the research staff, annual Christmas
cards, reminders about the data collection by text mes-
sage or telephone calls, and regular menopause-specific
information on our homepage and social media profiles.
Furthermore, participants were given an individual
health profile after the evaluation phase and are given
various incentives throughout the different time points
during the study (e.g. vouchers for massage, wellness
and spa treatments, free gym subscription, cosmetics,
food vouchers).
Data collection
During the entire screening and study phase, partici-
pants are asked to mark bleeding days in their individual
paper-and-pencil cycle calendar. This provides an easily
accessible method to remember the days of bleeding for
the biweekly online mood and cycle diary. Every 2
weeks, participants are reminded to complete the online
cycle and mood diary, which assesses specific cycle con-
ditions, menopausal complaints, and mood disturbances
over the last 2 weeks. At the beginning of the study
phase (t
1
), further demographic data (e.g. marital status,
occupation) and a variety of psychosocial factors were
assessed via online questionnaires. Psychosocial mea-
sures include psychological traits, physical and mental
health outcomes, behavioral aspects, and interpersonal
factors. The validated self-report questionnaires assessed
in the course of the study can be found in Table 1,
which lists the measured constructs, the name of the as-
sessment instrument, the authors, and the number of
items of the instrument (Table 1). The questionnaires
are completed at the beginning and at the end of the
Fig. 1 Project Design
Table 3 Inclusion and exclusion criteria
Inclusion criteria
•Female sex
•Age 40 to 60 years
•Perimenopausal status
•Good knowledge of the German language
•Good to excellent self-reported health condition
Exclusion criteria
•Acute or chronic somatic disease
•Acute or chronic mental disorder
•Psychiatric drug use
•Psychotropic drug use in the last 2 months
•More than two standard units of alcoholic beverages a day
•Pregnancy in the last 6 months
•Current use of oral contraceptives or hormone therapy in the last 6
months
•Postmenopausal status (no menstrual period in the last 12 months)
•Premenopausal status (regular menstrual cycle)
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study (t
1
and t
3
). Participants receive the respective links
by e-mail. All questionnaires need to be completed
consecutively.
Two standardized laboratory visits to the Institute of
Psychology, University of Zurich are planned within the
study phase, at t
1
and t3. Women are instructed a) not
to drink caffeinated drinks (e.g. coffee, black or green
tea, energy drinks) or alcohol for at least 48 h (2 days)
prior to the visit, b) not to engage in intensive physical
activity for at least 24 h (1 day) prior to the visit, and c)
not to eat, drink or engage in physical effort (e.g., cyc-
ling) on the morning of the examination. The laboratory
sessions are standardized. Participants arrive at the la-
boratory at 7:45 am. At the first laboratory visit (t
1
), a
well-instructed psychologist first conducted the German
Version of the Structured Clinical Interview for DSM-IV
[77] to ensure that all the participants were mentally
healthy at the beginning of the study. Otherwise, partici-
pants were excluded.
At both laboratory visits (t
1
and t
3
), small capillary
blood samples are drawn from the participant’s finger.
Blood pressure and pulse (Medisana MTV upper arm
blood pressure instrument) are measured and body
height and weight are assessed. In addition, the body
composition is determined using bioelectrical impedance
analysis (BIA, Biocorpus RX4000, Idiag AG, Fehraltdorf,
Switzerland). This instrument is a fully digital, phase-
sensitive, four-channel impedance-measuring device.
Each channel applies a 50 kHz alternating current to
measure resistance, reactance and phase angle. To meas-
ure the second to fourth digit ratio (2D:4D), the length
of the index finger and the ring finger is measured
(Digital Caliper Micrometer Vernier Gauge Tool).
Accordingly, the grip strength is assessed (Baseline
Hydraulic Hand Dynamometer). The laboratory sessions
also include a standardized facial photograph. These
photos are used for self-rated attractiveness as well as
externally rated attractiveness. For the latter, independ-
ent and external examiners (N= 10) rate the standard-
ized facial photographs of the participants according to
the perceived age, attractiveness and health on a scale
from 0 to 100. The assessments are conducted via pres-
entation of the photographs on a computer screen. The
examiners have signed a binding declaration of
confidentiality.
Within all laboratory sessions, the investigator also
asks a short, standardized set of questions about factors
and activities potentially biasing the current hormone
concentrations. Subjects are instructed to autonomously
collect saliva samples in a non-invasive manner with sal-
iva sampling tubes (SaliCaps, IBL International GmbH,
Hamburg, Germany). Furthermore, the participants
Fig. 2 Sample inclusion and elimination process
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receive written instructions for each step of the saliva
sampling. The participants have been provided with 100
SaliCaps (IBL International GmbH, Hamburg, Germany)
to collect one daily morning saliva sample for 3 months
in total (i.e. 28 daily samples per month during t
1
,t
2
and
t
3
) under standardized conditions. To investigate the
cortisol awakening response (CAR) as well as fluctua-
tions throughout the day, four additional saliva samples
are collected on the first 2 days of the month of t
2
and
t
3
. The additional saliva samples are timed 30 and 60
min after the first saliva sample, at 12:00 pm and before
going to bed. The exact sampling times as well as spe-
cific information on caffeine or alcohol consumption,
sports or current gum bleeding are recorded in a proto-
col. Participants are reminded to start the saliva sam-
pling at the beginning of t
1,
t
2
, and t
3
.
During the first lab visit, the participants were also in-
troduced to the Ava bracelet (Ava AG, Zürich,
Switzerland), which they were asked to wear at night for
a total of 6 months. The Ava bracelet assesses raw data
of nine different nighttime peripheral physiological pa-
rameters: skin temperature, ambient temperature, elec-
trodermal activity, heart rate, heart rate variability, blood
circulation of the skin, body acceleration, breathing rate,
and sleep phases.
An overview of all biological parameters assessed in
the course of the study can be found in Table 2, which
lists the sources of the parameters, the label, and the
name of the specific parameter (Table 2).
Data handling
A link for the online screening was provided on the
study homepage. Women interested in participation
were led to the online platform Unipark, where they
were asked to provide initial, brief information followed
by a declaration of consent. All questionnaires at base-
line, t
1
and t
3
(www.unipark.com), the data analysis of
retrospectively assessed relationship experiences (www.
qualtrics.com), as well as the mood and cycle diary
(www.findmind.ch), are completed online. The partici-
pants were explicitly informed about the study design,
the aims, the procedure and the expected duration of
each part of the assessment. Data security is ensured at
all times. All calendars and protocols are paper-and-
pencil-based. The online platform Unipark is reliably
protected from any external access. The BSI-certified
(Bundesamt für Sicherheit in der Informationstechnik
[Federal Office for Information Security]) data center is
subject to requirements of high data protection and
safety in conformity with ISO (International
Organization for Standardization) 27,001 based on the
IT basic protection. Qualtrics is hosted by trusted data
centers that are independently audited using the indus-
try standard Statement on Standards for Attestation
Engagements no. 16 (SSAE 16) method. HITECH-up-
dated (Health Information Technology for Economic
and Clinical Health Act) HIPAA (Health Insurance Port-
ability and Accountability Act) rules are applied to en-
sure data protection and security of all customer data.
The menstrual cycle and mood diary is recorded via the
online platform Findmind (www.findmind.ch). Findmind
treats data as confidential information, strives to ensure
the privacy of the data and does not share information
with third parties. It is operated exclusively on servers in
Switzerland and stores all user data. For the dried blood
spots (DBS), a sterile disposable lancet (Accu-Chek®
Safe-T-Pro Plus) is used to collect up to five drops of
blood (about 50 μL per drop), which are spotted onto
standardized filter paper (No. 903 Whatman®, DBS Pro-
tein Saver Card). The samples are dried and subse-
quently stored in the laboratory freezer of the Institute
of Psychology, University of Zurich at −20 °C. DBS sam-
ples are analyzed in the biochemical laboratory of the
Department of Clinical Psychology and Psychotherapy,
University of Zurich, Switzerland (genetic and epigenetic
analyses) and the Cytolab laboratory in Regensdorf,
Switzerland (FSH and LH).
Saliva samples are collected with SaliCap sampling
tubes of 2 mL capacity (IBL International GmbH, Ham-
burg, Germany). Participants are instructed to drool into
the tube using a polypropylene straw (passive drool
method). After collecting a full month of saliva samples,
these can be returned directly to the Institute of Psych-
ology during the study phase or stored at home in the
freezer until the second laboratory appointment. The
saliva samples are then thawed and centrifuged prior to
biochemical analysis, using IBL Saliva Immunoassays
(IBL International GmbH, Hamburg, Germany). All sal-
iva samples are analyzed at the Cytolab laboratory in
Regensdorf, Switzerland.
The Ava bracelet and its accompanying software is a
CE-certified, Class 1 medical device approved by the
Food and Drug Administration. It is worn at night on
the wrist like a regular watch. The synchronization takes
place every morning after waking up, with the corre-
sponding application (Ava fertility tracker). The software
runs on Apple and Android phones. The login for the
Ava fertility tracker app corresponds to the subjects’
study ID number (personal code). Participants without a
smartphone have been provided with an Android phone
during the study phase by the University Research Prior-
ity Program Dynamics of Healthy Aging (funding
source). The data recorded by the Ava bracelet are
treated confidentially and in accordance with the privacy
policy. Members of the Ava AG have signed a binding
declaration of confidentiality. All data handling is subject
to the data protection provisions approved by the Swiss
Ethics Committee.
Willi et al. Women's Midlife Health (2020) 6:5 Page 8 of 13
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Biochemical data analyses
Our biochemical laboratory at the Institute of Psych-
ology, University of Zurich, performs the salivary and
DBS analyses. As listed in Table 2, most endocrine pa-
rameters are assessed in saliva. Thawed saliva samples
are centrifuged and analyzed using enzyme-linked im-
munosorbent assay (ELISA; IBL International GmbH,
Hamburg, Germany). FSH and LH levels are determined
in DBS samples (Table 2) using the MILLIPLEX MAP
Human Pituitary Magnetic Bead Panel 1 (Merck, Darm-
stadt, Germany). Intra-assay variation for this kit for
FSH and LH is less than 10% and inter-assay variation
less than 15%. Sensitivity is 6.40 pg/mL for FSH and
1.34 pg/mL for LH. Sex hormone-binding globulin
(SHBG) can be measured in DBS using Human SHBG
ELISA Kit (DRG International, Marburg Germany) with
intra- and inter-assay coefficients of variability of less
than 10% [78]. In terms of immune markers, the Quanti-
kine HS ELISA Human IL-6 (HS600B, R&D Systems,
Minneapolis, MN) is recommended for analyzing inter-
leukin 6 (IL- 6; 37) and the sandwich ELISA (BioCheck,
Inc., Foster City, CA) for investigating C-reactive protein
[79]. Intra- and inter-assay variation for these kits for IL-
6 and CRP are less than 15%. Detection rates of these as-
says are 0.67 pg/ml for IL-6 and 3.00 mg/L for CRP.
The DNA extraction is assessed from DBS samples, as
described in Table 2. The Qiagen QIAamp DNA Investi-
gator Kit (Qiagen, Hombrechtikon, Switzerland) is used to
extract genomic DNA from three (each 3 mm in diameter)
punches of blood-soaked filter paper. These punches are
then eluted in 30 μl of RNase-free water, and the DNA
concentration is assessed using the Qubit Fluorometer
(Thermo Fischer Scientific, Reinach, Switzerland). For epi-
genetic analyses, we perform a bisulfite conversion of
DNA using the EZ 96-DNA Methylation-Gold Kit (Zymo
Research, Luzern, Switzerland). The procedure for the
next-generation sequencing (NGS) library preparation is
described elsewhere by our research group [80].
Statistical data analyses
A variety of statistical analytic strategies are planned for
the different measures. Variables will be tested for nor-
mal distribution (Kolmogorov-Smirnov test) and homo-
geneity (Levene’s test). Skewed biological data will be
logarithmically transformed [81]. Effect sizes will be esti-
mated using eta-squared [82]. When investigating asso-
ciations, correlation or partial correlation analyses will
be conducted. If assumptions are violated, non-
parametric methods will be applied. Regression analyses
will be conducted to investigate the strength and form of
associations between the various biopsychosocial
markers and determinants and resilience- or depression-
related factors. Analyses of variance, t-tests or Mann-
Whitney U tests, depending on the level of
measurement, are planned for the investigation of group
differences between participants with and without a his-
tory of depression regarding different outcome measures
associated with the menopausal transition. Furthermore,
factor analyses will be used [81,83] to examine which of
the assessed variables related to resilience can be
assigned to a common factor. For the longitudinal data
evaluation of specific predictors of perimenopausal de-
pression, multilevel analyses will be conducted [81]. In
addition to inference methods, unsupervised methods
(e.g. time series clustering methods [84,85], machine
learning algorithms [86]) will be necessary to analyze the
massive volume of big data generated by the Ava
bracelet.
The level of significance will be two-sided with p< .05,
if not stated otherwise. The analysis will be run via the
statistical software SPSS 25.0 (IBM, Armonk, NY, USA)
and the open source software R (foundation for Statis-
tical Computing, Vienna, Austria).
Results
Of the 1121 women interested in participating in the
Swiss Perimenopause Study, a total of 265 (23.64%) were
found to be eligible for the study after applying the in-
clusion and exclusion criteria. Of these, 177 declared
their consent to participate. Up until December 2019, 42
women (23.73% of the participants) were reported as
dropouts. Excessive effort for study participation was
stated as a major cause for dropping out. Hence, the
total sample consisted of 135 perimenopausal women.
The sociodemographic data of the participants are
shown in Table 4. The participants’age at the point of
study enrollment ranged from 40 to 56 years, with a
mean of 48.60 years. Most of the women were Swiss
(85.2%) and married (56.3%). With regard to highest
educational attainment, 43.0% had completed university
education and 37.0% had completed secondary school.
In accordance with the STRAW criteria [76], a total of
43.7% were in the early phase of the menopausal transi-
tion, while 56.3% were in the late phase at the point of
screening. Overall, 60.0% of the women showed no prior
depression and 40.0% of the participants reported a his-
tory of depression.
Discussion
The Swiss Perimenopause Study was established to in-
vestigate specific health-related markers associated with
the menopausal transition. The aim of this large longitu-
dinal study is to address the limited scientific under-
standing of the factors determining whether a woman
undergoing the menopausal transition develops clinically
relevant symptoms, such as those of a depressive dis-
order, or whether she manages to successfully adapt to
the predominant biopsychosocial changes. Successful
Willi et al. Women's Midlife Health (2020) 6:5 Page 9 of 13
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
adaptation can be defined on a continuum of, for ex-
ample, higher life satisfaction, lower psychological dis-
tress, better general psychological health, and milder
menopausal complaints [14]. Thus, the study focuses on
the perimenopause as the phase of strong hormonal
fluctuations and the prevalence peak of burdensome
symptoms.
Strengths of the Swiss Perimenopause Study include
the longitudinal design and the in-depth investigation
of the perimenopausal stage. Strict inclusion and ex-
clusion criteria are deployed. All participants reported
good to excellent subjective health at baseline. The
gold-standard STRAW criteria were used to identify
perimenopausal women on the basis of bleeding pat-
terns. Individual menstrual cycle data are collected
throughout the entire screening and study phase and
matched with the assessment of mood changes. An
extensive symptom assessment is carried out. Genetic
and epigenetic analyses provide the opportunity to in-
vestigate inherited physical characteristics as well as
gene-environment interactions. Repeated physiological
data assessment enables the examination of patterns
related to sleep disturbances and vasomotor symp-
toms. Furthermore, a comprehensive inspection of
endocrine processes is planned, to complement the
various psychosocial questionnaires applied in our
study. Participants were randomly identified from the
general population and represent an eligible sample
for this longitudinal study on health-related factors of
the menopausal transition.
There are a few limitations to consider: The study in-
cludes a predominantly well-educated sample, despite
efforts to recruit women with different socioeconomic
backgrounds. Additionally, the sample mostly consists
of Caucasian women, although this corresponds to the
distribution of the Swiss population. The initial goal to
recruit a balanced sample size of women with and with-
out a history of depression, with a sample size of 80
participants in each group, had to be discarded due to
difficulties in enrolling eligible participants with prior
depression. A total of 54 (40.0%) women with and 81
(60.0%) women without a history of depression were in-
cluded in the final sample. Compared to the SWAN or
the SMWHS studies, only a relatively small sample size
and shorter study duration could be accomplished.
However, a sufficiently large number of women has
been achieved for all planned analyses, with adequate
statistical power. Furthermore, the self-reported nature
of all validated psychosocial questionnaires used might
lead to a response bias and socially desirable answers.
Thus, the evaluation of self-reported data using object-
ive measures, where feasible, will be essential. More-
over, the strict inclusion and exclusion criteria applied
in the Swiss Perimenopause Study offers the chance to
investigate the actual changes and challenges associated
with the perimenopause. However, as this is a very spe-
cific sample, the results cannot be applied to other sub-
groups of the general population such as younger
women or postmenopausal women. Additionally, a se-
lection bias has to be considered when interpreting the
results. Women agreeing to participate in such a com-
prehensive examination about the menopausal transi-
tion might suffer more from menopausal symptoms,
and women with a higher socioeconomic status might
show a higher interest in participating in a scientific
project.
There has been an increased scientific effort to ad-
dress questions on the development of menopausal
symptoms and depressed mood within the meno-
pausal transition. Longitudinal data on specific factors
associated with the menopausal transition are essen-
tial to foster our understanding of changes and symp-
toms experienced by middle-aged women. The Swiss
Perimenopause Study, as one of the large studies in-
vestigating the menopausal transition, aims to con-
tribute to increased scientific information about the
biopsychosocial processes associated with this vulner-
able time frame in a woman’s life and thus improve
the clinical care of midlife women.
Table 4 Baseline sample characteristics
N (%) M (SD)
Age 48.60 (3.87)
Nationality
Swiss 115 (85.2%)
German 17 (12.6%)
Other 3 (2.1%)
Marital status
Single 34 (25.2%)
Married 76 (56.3%)
Registered partnership 4 (3%)
Divorced 18 (13.3%)
Widowed 3 (2.2%)
Highest educational attainment
Secondary school 50 (37.0%)
Grammar school 27 (20.0%)
University 58 (43.0%)
Menopausal stage
Early MT 59 (43.7%)
Late MT 76 (56.3%)
History of depression
No 81 (60.0%)
Yes 54 (40.0%)
Note. N sample size, Mmean, SD standard deviation, MT menopausal transition
Willi et al. Women's Midlife Health (2020) 6:5 Page 10 of 13
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Abbreviations
2D:4D: Second to Fourth Digit Ratio; ALSWH: Australian Longitudinal Study
on Women’s Health; App: Application; BIA: Bioelectrical Impedance Analysis;
BMI: Body Mass Index; BSI: Federal Office for Information Security (Bundesamt
für Sicherheit in der Informationstechnik); CAR: Cortisol Awakening Response;
DBS: Dried Blood Spots; DSM: Diagnostic and Statistical Manual of Mental
Disorders; ELISA: Enzyme-Linked Immunosorbent Assay; HIPAA: Health
Insurance Portability and Accountability Act; HITECH: Health Information
Technology for Economic and Clinical Health Act; HUNT: Nord-Trøndelag
Health Study; IBL: Immuno Biological Laboratories; ISO: International
Organization for Standardization; kHz: Kilohertz; LH: Luteinizing Hormone
(LH); MWMHP: Melbourne Women’s Midlife Health Project;
MWHS: Massachusetts Women’s Health Study; NGS: Next-Generation
Sequencing; POAS: Penn Ovarian Aging Study; SHBG: Sex hormone-binding
globulin; SMWHS: Seattle Midlife Women’s Health Study; SSAE: Statement on
Standards for Attestation Engagements; STRAW: Stages of Reproductive
Aging Workshop; SWAN: Study of Women’s Health Across the Nation
Acknowledgements
We acknowledge the contribution of the participants who have provided
data for the Swiss Perimenopause Study. We wish to thank Jessica Grub and
our research team for their great support in recruiting the participants for
the study. Finally, we warmly thank Sarah Mannion for proof reading the
article.
Authors’contributions
Conception: UE, JW / HS. Acquisition of data: JW / HS. Drafting the
manuscript: JW / HS. Critical revision: UE. Jasmine Willi and Hannah Süss are
shared first authors. The author(s) read and approved the final manuscript.
Authors’information
UE: Project leader of the Swiss Perimenopause Study.
JW and HS: Principal investigators of the Swiss Perimenopause Study.
Funding
This research was funded by the University Research Priority Program
Dynamics of Healthy Aging of the University of Zurich in Switzerland.
Availability of data and materials
Not available.
Ethics approval and consent to participate
Ethical approval for the study protocol of the Swiss Perimenopause Study
was provided by the Swiss Ethics Committee (KEK-ZH-Nr. 2018–00555).
Approved informed consent forms were obtained from each participant of
the study before the screening phase (online) and before the study phase
(paper and pencil). All participants were informed about the detailed study
procedure, the estimated duration of the individual steps, data protection,
and the aims of the study.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interest.
Received: 17 January 2020 Accepted: 13 July 2020
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