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Associations between Plasma 25-Hydroxyvitamin D, Hormonal Contraceptives, and Premenstrual Symptoms
by
Alicia Jarosz
A thesis submitted in conformity with the requirements for the degree of Master of Science (MSc)
Department of Nutritional Sciences University of Toronto
© Copyright by Alicia Jarosz 2017
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Associations between Plasma 25-Hydroxyvitamin D, Hormonal Contraceptives, and Premenstrual Symptoms
Alicia Jarosz
Master of Science (MSc)
Department of Nutritional Sciences
University of Toronto
2017
Abstract
Premenstrual symptoms are experienced by the majority of women and may cause significant
personal and professional impairment; however, little is known about their pathophysiology and
risk factors. The purpose of this thesis was to determine the prevalence of common premenstrual
symptoms in a multiethnic Canadian population and to explore the associations of plasma 25-
hydroxyvitamin D and hormonal contraceptive use with these symptoms. Symptom prevalence
was found to vary widely between common symptoms, ranging from 11% to 75%. Prevalence of
individual symptoms did not differ between ethnic groups, with the exception of cramps.
Hormonal contraceptive use was associated with a reduction in the risk of experiencing several
symptoms at moderate/severe severity. Plasma 25-hydroxyvitamin D was also inversely
associated with the prevalence and severity of several premenstrual symptoms. These findings
suggest HC use may be an effective targeted treatment and vitamin D status may be a risk factor
for individual premenstrual symptoms.
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Acknowledgments
First and foremost, I would like to thank my advisor Dr. Ahmed El-Sohemy for the
tremendous support and opportunities he has provided to me in the last two years. I am certain
that I could not have had a more encouraging supervisor. His guidance and knowledge were
crucial in helping me reach my academic and professional pursuits. Thank you, Ahmed. I had a
lot to learn as a young undergraduate student entering your lab and I am incredibly grateful for
your support and the countless learning opportunities you have created to encourage my
professional development.
I would like to thank my advisory committee, Dr. Joanne Kotsopoulos and Dr. Richard
Bazinet, for their guidance throughout the progression of this project. Their knowledgeable
advice and direction has benefited my thesis and their enthusiasm has encouraged me along the
way. Thank you, Dr. Kotsopoulos, for taking the time to help me with my academic writing. My
thesis and manuscripts have improved greatly thanks to you. I would also like to thank my
professors, Dr. Beatrice Boucher, Dr. Anthony Hanley, and Dr. Paul Corey. The research skills
they taught me in epidemiology and statistics helped me immensely with my thesis. Thank you,
Dr. Corey, for staying hours late after class to help me understand my data and find the best
statistical approach. Finally, thank you to Louisa Kung, who was always there to answer every
possible question I could have.
My time as a graduate student would not have been so enjoyable without my wonderful
El-Sohemy lab mates and colleagues in the Nutritional Sciences department. Thank you to
Ohood Alharbi, Neshat Deljoomanesh, Nanci Guest, Riva Sorkin, Sara Mahdavi, Joseph Jamnik,
Bryn Dhir, Katie Edmonds, and Daniel Noori. I am grateful to have had the chance to work
alongside such kind, helpful, and entertaining lab mates. I will forever look back fondly at the
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time we spent together. Thank you to my ‘honorary advisor’, Joseph Jamnik, for teaching me
everything I needed to know about SAS and TNH. You were there to help me through every
research obstacle I encountered and I could not have done this without you.
In many ways, I consider my successful completion of this thesis a team effort with my
friends and family who have supported me every step of the way. I would like to thank everyone
who has been a source of support and encouragement, and with whom I have celebrated all the
small accomplishments along this journey. I would especially like to thank my dad and sister,
Jerzy and Isabel, who have always been my biggest supporters in the pursuit of my educational
and career dreams. I would also like to thank my boyfriend, Razvan, for his unfaltering support
throughout my entire university education. You have all gotten me through the stressful and
hectic moments that are an inevitable part of any worthwhile endeavor, and celebrated my
triumphs as if they were your own. This accomplishment is as much yours as it is mine, and I am
eternally grateful to you all.
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Table of Contents
Abstract ........................................................................................................................................... ii
Acknowledgments .......................................................................................................................... iii
Table of Contents ............................................................................................................................ v
List of Tables ............................................................................................................................... viii
List of Figures ................................................................................................................................ ix
List of Abbreviations ...................................................................................................................... x
Chapter 1 Introduction ........................................................................................................... 11
1.1 Introduction ......................................................................................................................... 1
1.2 Premenstrual Symptoms ..................................................................................................... 1
1.2.1 Premenstrual Disorders ........................................................................................... 1
1.2.2 Etiology ................................................................................................................... 3
1.2.3 Treatment ................................................................................................................ 6
1.2.4 Risk Factors ............................................................................................................ 7
1.3 Hormonal Contraceptives ................................................................................................... 8
1.3.1 Introduction ............................................................................................................. 8
1.3.2 Mechanisms of Action ............................................................................................ 9
1.3.3 HCs and Premenstrual Symptoms ........................................................................ 10
1.4 Vitamin D .......................................................................................................................... 12
1.4.1 Background ........................................................................................................... 12
1.4.2 Vitamin D Metabolism ......................................................................................... 13
1.4.3 Functions of Vitamin D ........................................................................................ 14
1.4.4 Determinants of Vitamin D Status ........................................................................ 15
1.4.5 Measurement of 25(OH)D .................................................................................... 17
1.4.6 Vitamin D and Premenstrual Symptoms ............................................................... 18
1.5 Summary and Rationale .................................................................................................... 19
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1.6 Hypothesis and Objectives ................................................................................................ 20
Chapter 2 Prevalence of Premenstrual Symptoms and Associations with Use of
Hormonal Contraceptives ......................................................................................................... 21
2.1 Abstract ............................................................................................................................. 22
2.2 Introduction ....................................................................................................................... 24
2.3 Methods ............................................................................................................................. 25
2.3.1 Study Population ................................................................................................... 25
2.3.2 Hormonal Contraceptive Use ................................................................................ 26
2.3.3 Anthropometrics and Physical Activity ................................................................ 26
2.3.4 Premenstrual Symptoms ....................................................................................... 26
2.3.5 Plasma Samples and Vitamin D Measurement ..................................................... 27
2.3.6 Statistical Analysis ................................................................................................ 27
2.4 Results ............................................................................................................................... 28
2.4.1 Study Population ................................................................................................... 28
2.4.2 Prevalence of Premenstrual Symptoms ................................................................ 32
2.4.3 Premenstrual Symptom Associations with HC use .............................................. 35
2.5 Discussion ......................................................................................................................... 47
Chapter 3 Association between Plasma 25-Hydroxyvitamin D and Premenstrual
Symptoms ............................................................................................................................... 52
3.1 Abstract ............................................................................................................................. 53
3.2 Introduction ....................................................................................................................... 54
3.3 Materials and Methods ...................................................................................................... 55
3.3.1 Study Population ................................................................................................... 55
3.3.2 Hormonal Contraceptive Use ................................................................................ 55
3.3.3 Anthropometrics and Physical Activity ................................................................ 55
3.3.4 Premenstrual Symptoms ....................................................................................... 55
3.3.5 Plasma Samples and 25-Hydroxyvitamin D Analysis .......................................... 56
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3.3.6 Food Frequency Questionnaire ............................................................................. 56
3.3.7 Statistical Analysis ................................................................................................ 57
3.4 Results ............................................................................................................................... 57
3.5 Discussion ......................................................................................................................... 65
Chapter 4 Synopsis, Limitations and Future Directions ........................................................ 69
4.1 Synopsis ............................................................................................................................ 70
4.2 Limitations ........................................................................................................................ 71
4.3 Future Directions .............................................................................................................. 73
References ..................................................................................................................................... 74
Appendices .................................................................................................................................. 104
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List of Tables
Table 2-1 Subject Characteristics Stratified by Hormonal Contraceptive (HC) Use1,2 ................ 30
Table 2-2 Subject Characteristics Stratified by Hormonal Contraceptive (HC) Use1,2 ................ 31
Table 2-3 Premenstrual Symptom Prevalence by Ethnicity ......................................................... 33
Table 2-4 Associations between HC Use and Premenstrual Symptom Severity .......................... 37
Table 2-5 Associations between Duration of HC Use and Premenstrual Symptoms ................... 42
Table 3-6 Subject Characteristics Stratified by Vitamin D Status1,2 ............................................ 59
Table 3-7 Associations between Plasma 25-Hydroxyvitamin D and Premenstrual Symptom
Severity ......................................................................................................................................... 61
Table A-1 GHLQ Premenstrual Symptom Questionnaire .......................................................... 104
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List of Figures
Figure 2-1 Associations between HC Use and Mild Premenstrual Symptoms ............................ 40
Figure 2-2 Associations between HC Use and Moderate/Severe Premenstrual Symptoms ......... 41
Figure 2-3 Associations between Duration of HC Use and Mild Premenstrual Symptoms ......... 45
Figure 2-4 Associations between Duration of HC Use and Moderate/Severe Premenstrual
Symptoms ..................................................................................................................................... 46
Figure 3-5 Associations between Plasma 25-Hydroxyvitamin D and Premenstrual Symptom
Severity1,2 ...................................................................................................................................... 64
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List of Abbreviations
PMD - Premenstrual Disorder
PMS - Premenstrual Syndrome
PMDD - Premenstrual Dysphoric Disorder
ACOG - American College of Obstetricians and Gynecologists
GnRH - Gonadotropin-releasing hormone
CNS - Central nervous system
CRP - C-reactive protein
IL - Interleukin
PTH - Parathyroid hormone
1,25(OH)D - 1,25-hydroxyvitamin D
25(OH)D - 25-hydroxyvitamin D
SSRI - Selective serotonin uptake inhibitor
BMI - Body mass index
RCT - Randomized control trial
HC - Hormonal contraceptive
OC - Oral contraceptive
COC - Combined oral contraceptive
FSH - Follicle stimulating hormone
LH - Luteinizing hormone
DMPA - Depot medroxyprogesterone
UV - Ultraviolet
DBP - Vitamin d binding protein
VDR - Vitamin d receptor
RAAS - Renin-aldosterone-angiotensin-system
VTE - Venous thromboembolism
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Chapter 1 Introduction
1.1 Introduction
Premenstrual symptoms are a collection of physiological, behavioral, and psychological
symptoms that occur during the late luteal phase of a woman’s reproductive cycle. They are
characterized by their timing and by their cyclic nature, while the nature, number, and severity of
the symptoms varies between women1. Hundreds of symptoms have been described to date,
however, the most commonly experienced somatic symptoms are bloating, headache, fatigue,
and muscle cramps. Behavioral and psychological symptoms are also commonly experienced,
such as anxiety, mood swings, changes in appetite, and depression2.
The prevalence of experiencing premenstrual symptoms is estimated to be 85-98%, while
prevalence of individual symptoms varies widely between studies and populations2. The social
and economic burdens of premenstrual disorders are substantial. It is estimated that premenstrual
syndromes result in an increase of $59 and $4333 in American women’s individual direct and
indirect healthcare costs, respectively3. Furthermore, women with moderate or severe
premenstrual symptoms work fewer days and have reduced productivity compared to those
without symptoms3-5. Although premenstrual symptoms and disorders are common, there are few
treatments available for them and little research exists on the topic of dietary influences and risk
factors2. It is generally accepted that prevalence of premenstrual symptoms is influenced by
subject characteristics such as BMI, physical activity, and age, however, the effect of
race/ethnicity is inconsistent6.
1.2 Premenstrual Symptoms
1.2.1 Premenstrual Disorders
Premenstrual disorders (PMDs) are a group of disorders sharing the commonality of
regularly occurring premenstrual symptoms and include Premenstrual Syndrome (PMS) and
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Premenstrual Dysphoric Disorder (PMDD). Diagnosis of PMDs requires that premenstrual
symptoms are linked to the luteal phase. Symptoms must begin during the late luteal phase and
resolve within a few days following the onset of menses, with a clear symptom free interval
between cycles. The nature or number of the symptoms is not important, so long as the timing
and cyclicity criteria are met. PMDs are diagnosed prospectively using symptom diaries where
patients record their symptoms daily for at least 2 months. Differential diagnosis must also be
excluded, as premenstrual symptoms must be differentiated from exacerbations of underlying
disorders1.
PMS diagnosis criteria are defined by the American College of Obstetricians and
Gynecologists (ACOG)7. They require that 1 somatic and 1 affective symptom to be experienced
at moderate or severe severity for at least 2 consecutive cycles recorded by prospective
recording. Somatic symptoms include: bloating, breast tenderness, headache, joint or muscle
pain, swelling of extremities, and weight gain. Affective symptoms include: angry outbursts,
anxiety, confusion, depression, irritability, and social withdrawal. Symptoms must begin 5 days
prior to menses, subside within 4 days following the onset of menses, and be followed by at least
12 symptom-free days. Symptoms must be recorded in the absence of any pharmacological or
hormonal therapy, without use of drugs or alcohol, and be met with identifiable dysfunction in
everyday activities such as social or work related activities7. PMS has been estimated to occur in
20-32% of women1.
The most severe PMD is premenstrual dysphoric disorder (PMDD) which is defined in
the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM
IV)8. PMDD requires experiencing at least 5 premenstrual symptoms, with at least one affective
symptom at moderate/severe severity. Similar to PMS criteria, symptoms must cause identifiable
dysfunction in social or work activities, they must not be an exacerbation of other disorders, and
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must be confirmed using prospective symptom recording for 2 consecutive cycles. Prevalence of
PMDD has been found to be between 3-8%1.
1.2.2 Etiology
The etiology of premenstrual symptoms is not well understood, however, prevailing
theories attribute the occurrence of premenstrual symptoms to women’s individual responses to
normal fluctuations in gonadal steroid production that occur during the reproductive cycle9.
Premenstrual symptoms are absent during non-ovulatory cycles, menopause, pregnancy, and
following oophorectomy10, when production of the corpus luteum does not occur thus
eliminating rises in estrogen and progesterone in the luteal phase. Increased severity of
symptoms is likely due to the sensitivity of some women to changes in hormone production,
rather than to differences in hormone concentrations11. Premenstrual symptoms are absent during
pregnancy despite high levels of both estrogen and progesterone, and concentrations of these
hormones have not been shown to differ between those with PMS compared to controls.
However, inducing a chemical menopause using gonadotropin-releasing hormone (GnRH)
agonist was shown to abolish symptoms in women with PMS11. Following this GnRH agonist
treatment with introduction of exogenous estrogen or progesterone caused symptoms to return in
women with PMS but not in controls11. This work strongly suggests the occurrence of
premenstrual symptoms to be a result of abnormal responses to normal hormonal fluctuations
during the luteal phase.
Estrogen and progesterone, as well as their metabolites, are involved in the regulation of
various physiological processes in the body, some of which have been theorized to be implicated
in the pathophysiology of PMDs. Progesterone is metabolized in the brain and ovary to form
neuroactive steroids 3-alpha-hydroxy-5-alpha-pregnane-20-one (ALLO) and 3-alpha-hydroxy-
5beta-pregnane-20-one (pregnanolone)12. ALLO and pregnanolone act as positive allosteric
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modulators of the GABA neurotransmitter system. GABA receptors are widely distributed in the
central nervous system (CNS) and are important regulators of anxiety, alertness, stress, and
vigilance12. ALLO binds GABAA receptors and alters their sensitivity to neurosteroids, making
them temporarily insensitive to GABA12. Acute ALLO treatment has been shown to produce
anxiolytic and antidepressant effects in the short term, however, long term exposure has been
shown to increase anxiety13. PMS women have been found to have reduced luteal phase ALLO
concentrations compared to controls and some studies have shown an association with
premenstrual mood symptoms14, 15.
The serotonergic system has also been implicated for its role in PMS. Premenstrual
symptoms are very similar to those experienced with reduction of serotonin transmission, such as
mood swings, anxiety, depression, irritability, carbohydrate cravings, and difficulty
concentrating16. Ovarian sex steroids are involved in the metabolism of serotonin, as well as its
turnover, uptake, binding, and transport16. Animal studies have demonstrated increased whole-
brain serotonin as well as increased serotonin synthesis and decreased re-uptake in the midbrain,
hypothalamus, and amygdala in rats following acute and chronic ethynyl estradiol
administration17-19. Serotonergic function has been found to be altered during the luteal phase in
PMS women compared to controls, with PMS women having reducing platelet uptake of
serotonin and lower whole-blood serotonin levels20, 21. The high efficacy of selective serotonin
reuptake inhibitors (SSRIs) in the treatment of PMS and PMDD22 further supports the
involvement of the serotonergic system in PMDs.
In addition to theories of neurotransmitter involvement in the etiology of PMDs,
inflammation has also been linked to the occurrence of premenstrual symptoms. Multiple studies
have demonstrated an association between increased inflammatory markers such as c-reactive
protein (CRP), and pro-inflammatory cytokines including interleukin (IL)-2, IL-4, IL-10, IL-12,
5
and interferon-gamma in PMS women compared to controls23-25. The observed increase in CRP
found in PMS women was reproduced in another cross-sectional study and associated with
symptoms of anxiety and mood changes, muscle aches and cramps, increased appetite and
bloating, and breast pain26. Inflammation has a plausible role in the development of premenstrual
symptoms as it is already involved in other aspects of reproductive function such as ovulation,
endometrial repair, and follicular recruitment27. Inflammatory markers, such as CRP, IL-6, IL-
1β, and tumor necrosis factor-α, fluctuate throughout the female reproductive cycle with rises in
concentration following ovulation and peaking during menstruation28.
It has been suggested that some premenstrual symptoms may occur as a result of
dysregulation in calcium homeostasis and secondary hyperparathyroidism29. Serum calcium,
parathyroid hormone (PTH), and 1,25-hydroxyvitamin D (1,25(OH)D) have been shown to
fluctuate across the menstrual cycle30, 31. Serum calcium levels drop at three stages of the
menstrual cycle: during menses, midcycle, and during the late luteal phase30. Fluctuations in
these hormones may differ in women with PMDs, as suggested by two studies, one of which
demonstrated that women with PMDD had significantly different fluctuation patterns from
controls in 1,25(OH)D, ionized calcium, and urinary calcium30. Similarly, menstrual cycle
fluctuations in PTH, 25(OH)D, and 1,25(OH)D were found to differ in PMS women compared to
controls32. PTH showed midcycle elevations in PMS women but not controls, suggesting that
they may be experiencing transient, secondary hyperparathyroidism32.
Higher calcium intake may be protective against these fluctuations, as multiple studies
have reported decreased calcium intake in women with PMDs compared to controls33, 34.
Furthermore, clinical studies have demonstrated calcium supplementation reduces the severity of
premenstrual symptoms35-39. There are similarities between hypocalcaemia symptoms and
common premenstrual symptoms, such as those of anxiety, depression, fatigue, impaired
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intellectual capacity, personality disturbances, and muscle cramps29. Further supporting the
hypothesized involvement of calcium in PMS etiology is the observed increased risk of
osteoporosis after menopause in women with PMS40, 41.
1.2.3 Treatment
The current first line treatment for PMDs is the use of selective serotonin uptake
inhibitors (SSRIs)42. Studies have demonstrated a reduction in premenstrual symptoms with the
use of SSRIs with a response rate of 60-90%43. A 2013 Cochrane review analyzing 31 RCTs
found that continuous or luteal-phase SSRIs are effective for premenstrual symptom relief
compared to placebo44. SSRIs have been shown to effectively reduce both premenstrual mood
symptoms as well as somatic symptoms such as bloating, breast tenderness, and appetite
changes45. SSRI’s are, however, are accompanied by many adverse side effects such as nausea,
fatigue, and decreased libido44 which may make them unsuitable treatment options for some
women.
PMDs may also be effectively treated by inhibiting ovarian cyclicity through the use of
GnRH agonists or through bilateral oophorectomy43, 46. GnRH agonists act by interrupting the
normal pituitary-hypothalamus-gonadal cyclicity which triggers ovulation and premenstrual
symptoms. GnRH agonists are considered quite effective in treating somatic and psychological
premenstrual symptoms46 but result in a medically-induced menopause which is accompanied by
menopausal symptoms that must also be managed9. Furthermore, to reduce the risk of
cardiovascular disease and hypoestrogenic bone loss resulting from long-term GnRH agonist use,
add-back therapy with estrogen and progesterone must often be added which risks reintroducing
premenstrual symptoms2. Surgical bilateral oophorectomy is also effective in abolishing
premenstrual symptoms47 but is considered too invasive of a procedure for a majority of
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patients9. Although SSRIs and GnRH agonists are effective in treating PMDs, they are either
highly invasive or likely to cause severe adverse effects. Consequently, more research into
potential therapies and the etiology of premenstrual symptoms is necessary to develop much
needed novel therapeutic remedies.
Other treatments may be considered when managing premenstrual symptoms such as
lifestyle changes to reduce stress and increase exercise, calcium supplementation, hormonal
contraceptives, anxiolytics, and herbal preparations2. Although there is some evidence for the
efficacy of these treatments, there is not enough evidence to conclude they are effective in
treating premenstrual symptoms2.
1.2.4 Risk Factors
Several factors have been identified that put women at risk for experiencing premenstrual
symptoms or disorders, and these include age, body mass index (BMI), and physical activity.
Regular physical activity is considered a protective factor against premenstrual symptoms and
has been inversely associated with the severity of premenstrual symptoms in several
epidemiological studies48, 49, as well as randomized control trials (RCT)50-52. For example, a
recent RCT demonstrated the efficacy of engaging in regular aerobic exercise three times per
week for reducing several individual premenstrual symptoms in young women50.
BMI has been similarly associated with premenstrual symptoms, where those with higher BMI
were more likely to be experiencing symptoms at greater severity53. This was especially
pronounced in obese women with BMIs greater than 27.5 kg/m254, 55. Lastly, increasing age may
be a risk factor for premenstrual symptoms, with symptom prevalence peaking at age 366.
Ethnic background may also be a contributing risk factor to premenstrual symptomology,
however this has not been consistently shown. A couple studies have shown differences in the
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prevalence of premenstrual symptoms between Caucasian and African American women living
in America, where Caucasians reported a lower prevalence of some symptoms56, 57. Similarly,
Asians have reported a lesser severity of premenstrual symptoms relative to Caucasians in a
previous study58. However, some cross-sectional studies have not observed any ethnic
differences in the prevalence of premenstrual symptoms or PMS. The reason for these ethnic
differences in prevalence of symptoms is not known. It is hypothesized that they may be due to
underlying genetic or cultural differences58, 59.
1.3 Hormonal Contraceptives
1.3.1 Introduction
Hormonal contraceptives (HC) are formulations of synthetic estrogen and progesterone
derivatives which prevent ovulation. They were first introduced to the North American market in
the 1960’s as combined oral contraceptives containing first-generation estrogen and progesterone
analogues60. Since that time, their formulations have evolved to include options containing
second and third-generation analogues as well as various modes of administration. Rather than
taken orally, HCs can now also be administered in skin patches, intra-muscular injections,
implants, vaginal rings, or intra-uterine systems. There are numerous HC options available on the
Canadian market, whose formulations differ in dose and type of estrogen or progestin used. Oral
contraceptives (OC) are used by 16% of Canadian women and are the most common form of HC
used in Canada 61. OCs typically contain both an estrogen and progestin (called a combined oral
contraceptive (COC)) but may also be composed of only progestin (called a progestin-only pill).
Contraceptives were first created to mimic the natural 28-day ovarian cycle by administering
COCs for 21 days, followed by 7 days of a dose-free interval during which menstruation took
place. However, COCs can also be taken in extended or continuous regimens which delay or
eliminate menstruation, respectively. Their formulations may be monophasic, in which the
9
estrogen or progestin dose remains constant, or biphasic or triphasic, in which the estrogen or
progestin are administered in two or three different doses throughout the cycle, respectively.
Biphasic and triphasic regimens have formulations which periodically increase the dose of
estrogen of progestin, and were created with the intention of reducing the amount of exogenous
hormones administered.
1.3.2 Mechanisms of Action
Although the forms of HCs are varied, they are united in their primary mechanism of
action being their ability to inhibit ovulation by exerting an inhibitory effect at the hypothalamic
and pituitary levels 62. COCs block the normal production of GnRH and may also act directly on
the pituitary gland63. This exerts an inhibitory effect on the production of follicle-stimulating
hormone (FSH) and luteinizing hormone (LH) in the pituitary gland, especially on the midcycle
surge of these hormones which would typically induce ovulation64. These effects inhibit the
production of new follicles during the follicular phase and ovulation62. This prevents the
development of the corpus luteum and thus the luteal phase rise in estrogen and progesterone.
The progestin component of the COCs is especially effective at preventing this midcycle rise in
LH. The estrogen component of the COC amplifies this effect in addition to preventing irregular
shedding of the endometrium62, 65. FSH and LH secretion returns immediately following the
discontinuation of COCs. In fact, follicles begin to develop again during the 7-day dose-free
interval66.
Other forms on HCs have similar mechanism of action to COCs whereby they suppress
follicular development and inhibit ovulation. It is not necessary to administer both estrogen and
progestin to suppress ovulation, as either on its own is sufficient to inhibit pre-ovulatory spikes
in FSH and LH and thus prevent ovulation62. The most commonly used progestin-only injectable
contraceptive is depot medroxyprogesterone (DMPA). This long-acting progestin interrupts
10
ovulation by mechanisms similar to those of COCs, where it prevents the midcycle LH surge by
acting at hypothalamic and pituitary levels67. HCs also prevent pregnancy through secondary
mechanisms such as thickening of the cervical mucus, affecting peristalsis and secretion within
the fallopian tube, and by affecting the uterine lining making it unsuitable for implantation68-72.
HCs also exert several other biologic effects in the body that are unrelated to their
contraceptive action. HCs have been shown to impact bone mass73, vitamin D status74, the
cardiovascular system75-77, cognitive outcomes78, inflammatory markers79, as well as many other
physiological processes. Their physiological effects can be dependant on the type of HC used.
For example, while COCs have been associated with increased 1,25-hydroxyvitamin D
concentrations due to the estrogenic effect on vitamin D metabolism, formulations containing
medroxyprogesterone acetate did not exert the same effects on 1,25-hydroxyvitamin D
concentrations. HC formulations using newer formulations also have a more net-estrogenic effect
than early generation progestins since the new progestins have very little androgenic activity80, 81,
and also exert an anti-aldosterone effect82.
COCs have also been associated with increased risk of adverse cardiovascular outcomes,
such as increased risk of venous thromboembolism (VTE) and altered lipid profiles75, 83, 84. This
effect is also dependent on the COC formulation used, as rates of VTE differ between
formulations75, 76, 85. There is also evidence that these cardiovascular outcomes may be dependent
on the duration of use of hormonal contraceptives. Risk of VTE is highest in the first few months
of use and then declines75, 84. Similarly, total serum lipids are observed to increase with the start
of HC use but return to baseline following 24 months of use83.
1.3.3 HCs and Premenstrual Symptoms
Hormonal contraceptive use may be effective in treating premenstrual symptoms by
preventing ovulation and stabilizing fluctuations in estrogen and progesterone during the luteal
11
phase. Since premenstrual symptoms have been observed to be absent during non-ovulatory
cycles9, preventing ovulation may be an effective therapeutic strategy for premenstrual
syndromes. This relationship, however, is complicated by the addition of exogenous estrogens
and progestins with HCs as well as by the minor fluctuations in hormones that occur during the
pill-free days9. This is supported by evidence showing the comparatively improved efficacy of
extended HC regimens in treating premenstrual symptoms86. Due to their widespread use and the
inconsistency of the available research it is important to determine whether HCs are useful in
treating premenstrual symptoms and, if so, for which symptoms they are effective.
The few placebo-controlled randomized trials that have been conducted on this topic have
obtained mixed results. Some randomized control trials (RCTs) did not find HCs to be effective
in treating premenstrual symptoms87, 88, while others found them to be effective for some
premenstrual symptoms but not others89, 90. Numerous open-label studies found hormonal
contraceptives to be effective in decreasing the severity of some premenstrual symptoms, but not
all91-93. There is also evidence that more recent HC formulations may be more effective in
treating premenstrual symptoms than older formulations, such as those containing
drospirenone94.
Observational studies conducted on the topic and have also obtained conflicting results.
Three large observational studies have found a substantially lesser prevalence of premenstrual
symptoms in women using HCs compared to non-users58, 95. An analysis of a health maintenance
organization found an inverse relationship between hormonal contraceptive use and both the
number and severity of emotional premenstrual symptoms (p<0.01), but not physical
symptoms58. Similarly, investigations of a large multiethnic US cohort of premenopausal women
as well as a large French cohort showed significantly lower prevalence of PMS in HC users96, 97.
Conversely, a small nested case-control study within a US cohort found no difference in total
12
symptom prevalence between HC users and non-users98. Furthermore, one study instigating
premenstrual symptom associations with HC use among women with PMDD found an increase
in the prevalence of some individual symptoms in HC users compared to non-users99. Symptoms
that were more prevalent among HC users included: anxiety, anger, avoided social activities,
weight gain, joint/muscle pain, and difficulty concentrating99. Novel studies assessing the effects
of newer HC formulations on individual premenstrual symptoms may elucidate the conflicting
findings.
To date, no studies have investigated whether duration of HC use plays a role in their
effect on premenstrual symptoms. The effects of HCs on risk of VTE, lipid profiles and
cholesterol metabolism have been shown to be related to be dependent on duration of HC use75,
83, 84, 100. The decline in VTE risk occurs after a few months75, 84 and lipid profiles return to
baseline after two years84, although the mechanisms for this are unknown. Current trials
investigating the effect of HCs on premenstrual symptoms have been conducted no longer than
6-8 months. It is possible that HCs may become more or less effective in the treatment of
premenstrual symptoms with time.
1.4 Vitamin D
1.4.1 Background
Vitamin D status is determined by a combination of dietary Vitamin D consumption and
cutaneous production101. Since vitamin D can be synthesized in the skin with sun exposure and it
is not necessary to obtain it in the diet, it is technically a prohormone rather than a vitamin102. It
is produced in the skin phytochemically from 7-dehydrocholesterol and has a structure similar to
that of classic steroid hormones such as estradiol, aldosterone, and cortisol102. Vitamin D is
found in two forms- ergocalciferol (vitamin D2) and cholecalciferol (vitamin D3). Ergocalciferol
and cholecalciferol are very similar in structure, the only difference being the existence of a
13
double bond at carbons 22-23 and a methyl group on carbon 24 in ergocalciferol103.
Ergocalciferol is obtained from plant and fungal sources while cholecalciferol can be obtained
from animal sources or endogenous production, and both are found in supplements102.
Although vitamin D may be obtained from the diet, most circulating vitamin D is derived from
cutaneous production104. Those living in Canada are at risk of vitamin D deficiency resulting
from inadequate sun exposure due to its high latitude101. According to the most recent Canadian
Health Measures Survey (CHMS), a third of Canadians had vitamin D levels below the cut-off
for sufficiency, and this number increased to about 40% during wintertime months105. In
response to the widespread vitamin D deficiency in Canada, laws now mandate the fortification
of margarine, milk and plant-based beverages with vitamin D101. Nevertheless, dietary vitamin D
consumption accounts for about 148–236 IU of daily vitamin D104 which in Canada is mostly
derived from fortified dairy products and fruit juices101. Few foods naturally contain vitamin D,
the largest sources are eggs, liver, and oily fish which can provide 250-950 IU/serving106.
1.4.2 Vitamin D Metabolism
Vitamin D consumed in the diet is absorbed in the small intestine by enterocytes and
subsequently packed into chylomicrons with other lipids for delivery to the liver102, 107. While
ergocalciferol and cholecalciferol can be obtained from foods and supplements, cholecalciferol
can also be synthesized in the body103. 7-dehydrocholesterol is embedded in the plasma
membrane and is converted to previtamin D3 in response to ultraviolet (UV) B exposure. Since
previtamin D3 is thermodynamically unstable, it is quickly converted to cholecalciferol via
rearrangement of its double bonds103. As a consequence of this reaction, cholecalciferol is ejected
from the plasma membrane and diffuses into the dermal capillary. Here it becomes bound to its
transport protein, vitamin D binding protein (DBP), which has a very strong affinity for
cholecalciferol, and is transported to the liver103. In the liver, cholecalciferol is hydroxylated by
14
25-hydroxylase (CYP27A1) to form the main circulating vitamin D metabolite, 25-
hydroxyvitamin D (25(OH)D)108. 25(OH)D is thought to be biologically inert and its half-life is
about 3 to 4 weeks102, 109.
25(OH)D can be converted into its active form of 1,25-dihydroxyvitamin D (1,25(OH)D)
in the kidneys and other target tissues such as the brain102. This conversion is done by the
mitochondrial enzyme 1-hydroxylase (CYP27B1)102, 110. 1,25(OH)D is a steroid hormone which
regulates gene transcription and affects various signal transduction pathways through vitamin D
receptor (VDR) binding111. Its half-life is about 24 hours112. Unlike 25(OH)D, the production of
1,25(OH)D is very tightly regulated, with 1,25(OH)D and high calcium levels decreasing its
production and PTH and calcitonin increasing its production113. Low calcium levels cause an
increase in PTH production which leads to both and increase in 1,25(OH)D production as well as
increased calcium absorption in the intestine113, 114.
1.4.3 Functions of Vitamin D
Vitamin D is a fat-soluble vitamin which behaves like a steroid hormone. 1,25(OH)D
exerts a majority of its biological actions by binding to the vitamin D receptor (VDR) and
regulating gene transcription115. VDRs and CYP27B1 are expressed widely throughout the body,
suggesting that vitamin D has widespread roles in many biologic systems such as the immune
system, brain, bone, and skin116. It plays an important in bone health and regulating calcium
homeostasis. 1,25(OH)D stimulates calcium and phosphorous absorption in the intestine in
response to low calcium levels117. 1,25(OH)D stimulates the proliferation and differentiation of
osteoblasts, as well as increases bone mineralization118-120. Vitamin D deficiency is associated
with low bone mineral density and increased fractures101. It is also associated with decreased
falls121, 122, which is attributed to improvements in muscle strength and lower-extremity function
15
with vitamin D supplementation123. VDRs are located on fast-twitch muscle fibers124 and vitamin
D deficiency is associated with muscle weakness and myopathy125, 126.
In recent years, vitamin D research has extended to areas beyond the skeletal system
which has given some insight into its widespread effects in the body. Vitamin D appears to exert
beneficial effects on the cardiovascular system, where 25(OH)D has been inversely associated
with risk of heart disease and hypertension in several large observational studies127-130. These
cardiovascular effects of vitamin D are thought to be mediated by vasculoprotection, decreased
inflammation, beneficial effects on calcium homeostasis, and suppression of the RAAS131.
Vitamin D has shown anti-inflammatory properties in vitro132, 133 and has been associated with
lower levels of inflammation in some134-136, but not all137, 138, observational studies. Lastly,
vitamin D may be involved in disorders affecting the neurological system. 1,25(OH)D is a
neurosteroid which can cross the blood-brain barrier and act on most areas of the brain through
VDRs117, and vitamin D deficiency has been associated with depression and cognitive
impairment139, 140.
1.4.4 Determinants of Vitamin D Status
Vitamin D status can be influenced by several lifestyle, demographic, and biologic
factors. The main factors known to influence 25(OH)D levels include UV exposure, body
composition, dietary consumption, medications, ethnocultural status, and genetics. Since
cholecalciferol in synthesized in the body in response to UVB exposure, any factor affecting the
degree of UVB exposure can influence an individual’s vitamin D status. This includes time spent
outdoors, skin pigmentation, clothing, use of sunscreen, and environmental factors influencing
the strength of UVB radiation141. UVB radiation is diminished in environments with latitudes
farther from the equator, and is also affected by weather, time of day, altitude, and season141.
Generally, vitamin D can not be synthesized by those living in regions above 33˚ north latitude
16
during wintertime months of November to March or between the hours of 3pm and 10am142.
Similarly, increased skin pigmentation can act as a natural sunscreen by absorbing UVB rays and
prevent the synthesis of cholecalciferol143. For this reason, ethnic groups with increased skin
pigmentation produce less vitamin D in response to sun exposure and are at risk of vitamin D
deficiency144, 145. Dietary vitamin D intake can also contribute to circulating levels of 25(OH)D,
although, their correlations range from r=0.2 to r=0.7 suggesting that other factors are
contributing significantly to vitamin D status101, 146.
Other factors, such as body mass, genetics, and medication use, can also affect circulating
levels of 25(OH)D by affecting its bioavailability, sequestration, and rate of breakdown. Obesity
has been reported to be inversely associated with 25(OH)D in several cross-sectional studies147-
149 and this is thought to be the result of sequestration of vitamin D by adipose tissue149, 150.
Similarly, some common medications are known to affect vitamin D metabolism, such as those
containing sex-hormones151, 152. HC use is positively associated with 25(OH)D levels and it is
thought that this effect is mediated by the estrogen component74, 152, 153 Estrogen has been shown
in animal and in vitro studies to upregulate CYP27B1 and downregulate CYP24A1, enzymes
responsible for the conversion of 25(OH)D to 1,25(OH)D and the catabolism of 25(OH)D as
well as 1,25(OH)D, respectively154, 155. Estrogen is also associated with elevated DBP
concentrations and may upregulate VDR expression153, 156. A recent cross-sectional study found
HC users to have significantly higher 25(OH)D concentrations than non-users, who had similar
levels to men74. Finally, several common genetic variants along the vitamin D metabolic pathway
have been associated with vitamin D status including those in CYP27B1157, CYP24A1158, and
VDR159. Heritability estimates for plasma 25(OH)D concentrations based on twin studies range
between 45% and 75%160-162, suggesting genetic variation may be an important factor in
determining an individual’s vitamin D status.
17
1.4.5 Measurement of 25(OH)D
Vitamin D status is measured by serum concentrations of the main circulating vitamin D
metabolite, 25(OH)D, which is the best indicator of functional vitamin D status as it takes into
account contributions from dietary intake and cutaneous production163. In comparison to
1,25(OH)D, 25(OH)D has a much longer half-life, is present in much higher concentrations, and
its formation is not regulated, thus making it a better estimate of vitamin D status112.
Approximately 85% of 25(OH)D is bound to DBP, while 15% is bound to albumin and 0.03% is
free164.
There are several methods available for measuring 25(OH)D including by
radioimmunoassay (RIA), high-performance liquid chromatography (HPLC), and LC MS/MS112.
The strengths and limitations of each of these methods differ, but HPLC with UV detection and
LC MS/MS may be considered the gold standard methods because of their abilities to
differentiate between 25(OH)D2 and 25(OH)D3, their precision, and their accuracy165-167.
25(OH)D concentration cut points determining vitamin D status were suggested by the
Institute of Medicine (IOM), and according to these criteria, deficient, inadequate, and sufficient
vitamin D statuses correspond to plasma 25(OH)D concentrations of <30 nmol/l, 30–50 nmol/l,
and >50 nmol/l163. These criteria were largely based on maintaining optimal bone health163. The
IOM criteria for determining vitamin D status have been controversial and widely criticized as
overly conservative by not considering the important role of vitamin D in health outcomes
beyond bone metabolism168-170. Many investigators as well as the Canadian Osteoporosis Society
(COS) and the Endocrine Society (ES) have proposed that optimal vitamin D status should be
considered at 25(OH)D plasma concentrations >75 nmol/l101, 170-172.
18
1.4.6 Vitamin D and Premenstrual Symptoms
The evidence of calcium homeostasis dysregulation and luteal-phase calcium deficiency
playing a role in the etiology of premenstrual symptoms has prompted the investigation of
associations between vitamin D and premenstrual symptoms. It is proposed that vitamin D may
be protective again premenstrual symptoms through its involvement in the regulation of calcium
homeostasis29. Plasma calcium and 1,25(OH)D concentrations have been shown to fluctuate
during the menstrual cycle, with levels of calcium decreasing and 1,25(OH)D increasing during
the luteal phase30, 32. 25(OH)D concentrations were not shown to fluctuate throughout the
menstrual cycle30.
Alternative theories for the involvement of vitamin D in premenstrual symptoms include
its role in reducing inflammation as well as its direct effect on the brain. 1,25(OH)D can cross
the blood-brain-barrier and is capable of binding to VDRs located in the brain173-175. VDRs are
distributed throughout areas of the brain known to be involved in mood and psychologic
disorders, such as depression, which share common symptoms with PMS including depression,
loss of appetite, and insomnia173-175. Furthermore, vitamin D plays a role in immune regulation
and is associated with a reduction in inflammation176, 177. Since premenstrual symptoms have
been associated with elevated inflammatory markers26, vitamin D may reduce symptoms through
this pathway.
Investigations into the role of dietary vitamin D have shown relatively consistent inverse
associations between vitamin D intake and premenstrual symptoms. Analysis of the Nurse’s
Health Study II data has revealed an association between high dietary intake of vitamin D and a
decreased risk of PMS33. High vitamin D intakes have also been associated with decreased
severity of premenstrual symptoms in the general population178. Few studies have examined the
association between vitamin D status and premenstrual symptoms, but those that have report
19
conflicting results. Most found no association between 25(OH)D and risk of premenstrual
symptoms34, 178-180, while one larger study found a negative association between 25(OH)D and
symptoms of breast tenderness, fatigue, diarrhea and/or constipation, and depression181. This
negative association between 25(OH)D and premenstrual symptoms was observed in a large
prospective cohort which examined the Nurses’ Health Study II data and evaluated premenstrual
symptoms individually181. Conversely, all other observational studies examined the association
between plasma 25(OH)D and PMS, without assessing symptoms or symptom severities
individually34, 178-180. Discrepancies in the analysis of individual and grouped symptoms may
help explain these conflicting findings, as it has been previously shown that treatment response
may be specific to the premenstrual symptom182.
One clinical trial has been conducted in which adolescent patients with severe vitamin D
deficiency were supplemented with 25,000 IU biweekly vitamin D for four months and this was
found to be effective in reducing their mean premenstrual symptom severity scores as well as the
severity of all individual premenstrual symptoms studied, which included anxiety, irritability,
crying easily, and sadness183. One RCT has examined the effect of 200 mg daily vitamin D
supplementation on premenstrual symptoms in an Iranian population. Their findings showed that
after two months of supplementation symptom scores significantly decreased in the intervention
group compared to placebo for all symptoms studied, which included depression, cravings, water
retention, anxiety, and somatic changes184.
1.5 Summary and Rationale
Premenstrual symptoms are common in the North American population however their
prevalence has not been determined previously in a Canadian population. Few suitable
treatments are available for symptoms, particularly for those at mild or moderate symptom
severity. Hormonal contraceptives may be effective in treating many common symptoms, but
20
this research is inconsistent. Furthermore, it is not clear for which symptoms and severities they
are most effective. Little is also known about dietary associations with premenstrual symptoms.
Women are advised to improve diet and lifestyle, but not enough evidence exists for specific
claims. Vitamin D has been shown to be associated with the prevalence of premenstrual
symptoms in some studies, but this has not been researched in relation to the severity of
individual premenstrual symptoms.
1.6 Hypothesis and Objectives
The objectives of this dissertation were to characterize the prevalence of common
premenstrual symptoms in a Canadian population and to determine their associations with use of
hormonal contraceptives and vitamin D status. It was hypothesized that HC use and plasma
25(OH)D concentrations are inversely associated premenstrual symptom prevalence and
severity.
Chapter-specific objectives are as follows:
Objective 1: To determine the prevalence of premenstrual symptoms in a multiethnic population
and to investigate their associations with use of hormonal contraceptives.
Objective 2: To determine the associations between plasma 25-hydroxyvitamin D concentrations
and the prevalence and severity of premenstrual symptoms.
21
Chapter 2 Prevalence of Premenstrual Symptoms and Associations with
Use of Hormonal Contraceptives
22
2.1 Abstract
Background: Hormonal contraceptive (HC) use may be associated with a reduction in some
premenstrual symptoms, however, the evidence remains equivocal.
Objective: To determine the prevalence of premenstrual symptoms in a multiethnic population
of women and to investigate the association between hormonal contraceptive use and
premenstrual symptoms.
Methods: 1,048 women participating in the Toronto Nutrigenomics and Health Study provided
data on their premenstrual symptoms and HC use. Severity of symptoms was classified as none,
mild, moderate, or severe. Logistic regressions were used to calculate the relative risk (RR) and
95% confidence interval (CI) to determine the associations between HC use and duration of HC
use with premenstrual symptoms, adjusting for ethnicity and other covariates.
Results: Prevalence of individual symptoms varied, and the most commonly reported were
cramps (75%), bloating (75%), mood swings (73%), increased appetite (64%), and acne (62%).
Prevalence of cramps differed between ethnic groups (p<0.05). Use of HCs was associated with
a lower RR (95% CI) of experiencing moderate/severe: cramps (0.82, 0.72-0.93), clumsiness
(0.22, 0.07-0.73), confusion (0.22, 0.09-0.54) and desire to be alone (0.45, 0.28-0.73). HC use
was not associated with the risk of premenstrual symptoms at mild severity. HC use was not
associated with symptoms of anxiety, bloating, mood swings, increased appetite, acne, fatigue,
sexual desire, depression, nausea, headache and insomnia. Premenstrual symptoms of acne,
mood swings, bloating, increased appetite, headache, insomnia, nausea, clumsiness, and sexual
desire were not associated with HC use. Each year of HC use was associated with a decreased
RR of experience mild confusion (0.85, 0.74-0.98), and insomnia (0.77, 0.61-0.97), as well as
moderate/severe fatigue (0.89, 0.80-0.99), and mood swings (0.91, 0.85-0.98), although these did
23
not meet Benjamini-Yekutieli criteria for multiple comparisons. Other premenstrual symptoms
were not associated with duration of HC use.
Conclusion: This study demonstrates that the prevalence of some premenstrual symptoms differs
between ethnic groups and that HC use is associated with a lower risk of experiencing many, but
not all premenstrual symptoms, only at moderate/severe severity. It also suggests that duration of
HC use is not associated with the severity of premenstrual symptoms.
24
2.2 Introduction
Premenstrual symptoms include a wide range of physical, psychological and behavioral
symptoms, which occur in the late luteal phase of a woman’s reproductive cycle and subside a
few days following the onset of menses 1. Many symptoms have been described to date, and a
few most commonly experienced somatic symptoms are bloating, headache, fatigue, and muscle
cramps. Behavioural and psychological symptoms are also commonly experienced, such as
anxiety, mood swings, changes in appetite, and depression 2, 185. It is estimated that more than
80% of women regularly experience premenstrual symptoms, however, prevalence varies
between studies and populations 186-192. It is generally accepted that the prevalence is influenced
by factors such as body weight and age, however, the association with ethnicity has been
inconsistent 58, 193.
Little is known about the pathophysiology of premenstrual symptoms, and consequently,
few effective therapies have been developed for them 1. Due to the timing of the symptoms,
changes in plasma levels of progesterone and estradiol are thought to be involved in their
etiology 1. Stabilizing fluctuations of these hormones during the luteal phase with the use of
hormonal contraceptives may be effective in treating premenstrual symptoms 1, but the studies
have been inconsistent 1, 2. Furthermore, the physiological effects of HCs have previously been
shown to vary with their duration of use, such as in their effects on plasma lipid levels and VTE
risk75, 83, 84. This suggests that the effects of HCs on premenstrual symptoms may also differ with
time, although this has not been previously investigated.
Due to the large variations in frequencies of reported symptoms and their possible
associations with ethnicity and hormonal contraceptive use, the objectives of this study were to
25
determine the prevalence of various premenstrual symptoms in a multiethnic Canadian
population and to assess their associations with hormonal contraceptive use.
2.3 Methods
2.3.1 Study Population
Subjects included 1,636 men and women aged 20-29 years who participated in the
Toronto Nutrigenomics and Health (TNH) study, which is a cross-sectional examination of
young adults investigating genetics, lifestyle, and biomarkers of health 194, 195. Recruitment
occurred between 2004 and 2010. Participants completed a general health and lifestyle
questionnaire (GHLQ), a physical activity questionnaire, and a food frequency questionnaire
(FFQ). Overnight fasting blood samples were also collected for genotyping and biomarker
analysis. Exclusion criteria included current pregnancy or breastfeeding. The study protocol was
approved by the Ethics Review Board of the University of Toronto and participants provided
written informed consent.
From the initial 1,636 subjects, 520 men were excluded, 10 subjects were excluded due to
missing GHLQ information, and 4 were excluded for lack of blood samples. The remaining
1,102 subjects were categorized into four ethnic groups based on self-reported ethnic status:
Caucasian (n=514), East Asian (n=401), South Asian (n=105), or Other (n=82), as described
previously 196. Caucasians included those self-reported as European, Middle Eastern, or
Hispanic. East Asians consisted of Chinese, Japanese, Korean, Filipino, Vietnamese, Thai, and
Cambodian. South Asians included Bangladeshi, Indian, Pakistani, and Sri Lankan. The Other
category included self-reported ethnicities of Aboriginal Canadians, Afro-Caribbeans, and those
who self-reported belonging to ≥2 ethnic groups not included in the same category.
26
2.3.2 Hormonal Contraceptive Use
Hormonal contraceptive use was self-reported in the GHLQ. Subjects were categorized as
HC users (n=320) and non-users (n=782). HC users included subjects indicating current use of
HCs, regardless of HC type or delivery method (transdermal, oral, vaginal, injection, etc.). HC
users also indicated how long they have been using HCs. Subjects also reported use of any
medications in the past month. Use of anti-depressants, analgesics, or anxiolytics was considered
in the present study as ‘PMS medication use’, due to their effects on premenstrual symptoms.
2.3.3 Anthropometrics and Physical Activity
Subjects’ height and weight were measured using the protocol previously described by
Garcia-Bailo et al. (2012) 197. Subjects wore light clothing and removed their shoes during the
measurements. Body mass index (BMI) was subsequently calculated in kg/m2. Subjects self-
reported their physical activity in the GHLQ by estimating the amount of time they spent
sleeping and engaging in light, moderate, and vigorous activity. Values were then converted into
metabolic equivalent (MET) levels.
2.3.4 Premenstrual Symptoms
Premenstrual symptoms and severities were self-reported in a questionnaire included in
the GHLQ. The questionnaire included the following symptoms: cramps/skin blemish;
bloating/swelling/breast tenderness; mood swings/crying easily/irritability/angry outbursts;
increased appetite/food cravings; acne; sexual desire/activity change; fatigue;
anxiety/tension/nervousness; depression; desire to be alone; confusion/difficulty
concentrating/forgetfulness; nausea; insomnia; headache; and clumsiness. Symptom severities
were classified as none, mild, moderate, or severe. Subjects indicated the severity at which they
experienced each symptom, within the 5 days before the onset of their period and ending by the
27
4th day of their period. Subjects could also list other premenstrual symptoms experienced,
however, due to the scarcity of other symptoms they were not included in the analyses.
2.3.5 Plasma Samples and Vitamin D Measurement
Participants provided blood samples following a minimum 12-hour overnight fast.
Participants experiencing a temporary inflammatory condition (including a recent piercing or
tattoo, acupuncture, a medical or dental procedure, a vaccination or immunization, flu, an
infection, or a fever) underwent a two-week recovery period prior to providing blood samples.
Samples were collected at LifeLabs Medical Laboratory Services (Toronto, Ontario, Canada),
and 25(OH)D levels were measured at the University Health Network Specialty Lab at Toronto
General Hospital (Toronto, Ont., Canada). Plasma 25(OH)D was measured by high-performance
liquid chromatography–tandem mass spectrometry.
2.3.6 Statistical Analysis
All statistical analyses were conducted using SAS (version 9.4; SAS Institute Inc, Cary,
NC, USA). The α was set at 0.05 and all reported p-values are 2-sided. Subject characteristics
were compared between HC users and non-users by chi-square analysis for categorical variables
and t-tests for continuous variables. Distribution of continuous variables was assessed prior to
analysis and log-transformed BMI was used in all subsequent analyses. Crude mean BMI values
were reported for ease of interpretation.
The prevalence of premenstrual symptoms was defined as the frequency of subjects
experiencing the symptoms at any severity (mild, moderate, or severe). Prevalence was
calculated for each symptom in the total population, and separately for the major ethnic groups:
Caucasians (n=514), East Asians (n=401), South Asians (n=104), and Other (n=82). Logistic
regressions were used to determine differences in the prevalence of symptoms between the four
28
ethnic groups. P-values were calculated in both unadjusted models as well as adjusted models
which included the following covariates: age, BMI, HC use, physical activity, PMS medication
use and plasma 25(OH)D concentrations. Benjamini-Yekutieli adjustments for multiple
comparisons were applied (15 tests, α = 0.05: p<0.015). Differences in the prevalence of each
symptom between each pair of ethnic groups were also examined (Caucasians vs East Asians;
Caucasians vs South Asians; Caucasians vs Other; East Asians vs South Asians; East Asians vs
Other; South Asians vs Other) using logistic regressions.
Logistic regressions were used to examine the associations between HC use and
premenstrual symptom severities. The proc genmod procedure was conducted with a binomial
distribution and a log link function. Moderate and severe symptom severities were combined due
to the small number of subjects reporting severe symptoms. Relative risks (RR) and 95%
confidence intervals (CI) were reported for associations between HC use and premenstrual
symptoms. Univariate models were first used in Model 1, followed by multivariate models in
Model 2 which adjusted for ethnicity, BMI, physical activity, PMS medication use and age.
Covariates were selected based on their associations with HC use or premenstrual symptoms in
the TNH study population and previous studies. Benjamini-Yekutieli adjustments for multiple
comparisons were applied (30 tests, α = 0.05: p<0.013).
2.4 Results
2.4.1 Study Population
Subject characteristics are reported in Table 2-1 Subject Characteristics Stratified by
Hormonal Contraceptive (HC) Use1,2. The mean age of participants was 22.6 years. HC users
were on average older (23 years) than non-users (22.4 years) (p=0.0006). HC use differed
between ethnic groups (p<0.0001), with Caucasian women reporting the greatest use of HCs
29
(43%), followed by Other (34%), South Asians (17%) and East Asians (13.0%). Reported
physical activity was greater for HC users (8.1 met-hours/week) than non-users (7.5 met-
hours/week) (p=0.003). Log-transformed BMI did not differ between HC users and non-users.
The distribution of HC types in the study population is reported in Table 2-2 Subject
Characteristics Stratified by Hormonal Contraceptive (HC) Use1,2. The most commonly used
HC brand was Tri-Cyclen (25%) followed by Alesse (22%). Yasmin, Diane35, and Marvelon
were each used by 9% of participants. Evra was used by 3% of participants, while Demulen,
Triphasel, and Triquillar were used by 1% of participants. All the aforementioned HC’s are
combinations of ethinyl estradiol and various progestins in varying doses which are administered
orally. Depo-provera, which was used by 1% of participants, is an injectable progestin-only HC
containing 150 mg medroxyprogesterone.
30
Table 2-1 Subject Characteristics Stratified by Hormonal Contraceptive (HC) Use1,2
HC Non-Users (%) HC Users (%) p-value
N
Age (years)
782
22.4±0.1
320
23.0±0.1 0.0006
Ethnicity (%) <0.0001
Caucasian 293 (57) 221 (43)
East Asian 348 (87) 53 (13)
South Asian 87 (83) 18 (17)
Other 54 (66) 28 (34)
Body mass index (kg/m2)* 22.4±0.1 22.7±0.2 0.11
Physical activity (met-h/wk) 7.5±0.1 8.1±0.2 0.003
Medication Use 205 (26) 68 (21) 0.08
Physical activity (met-h/wk) 7.5±0.1 8.2±0.2 0.003
1 Shown are crude means and standard errors of continuous variables, and n (%) of categorical variables
2 P-values were obtained using chi-square tests for categorical variables and t-tests for continuous variables.
* Indicates log-transformed variable was used for obtaining p-value
31
Table 2-2 Subject Characteristics Stratified by Hormonal Contraceptive (HC) Use1,2
HC Brand N (%) Estrogen (mg) Progestin (mg)
Tri-Cyclen1 71 (25) Ethinyl Estradiol
(0.035)
Norgestimate
(0.18 ,0.215, 0.25)
Alesse 63 (22) Ethinyl Estradiol
(0.02)
Levonorgestrel
(0.1)
Other3 41 (14) - -
Yasmin 27 (9) Ethinyl Estradiol
(0.03)
Drospirenone
(3)
Diane 35 25 (9) Ethinyl Estradiol
(0.035)
Cyproterone Acetate
(2)
Marvelon 25 (9) Ethinyl Estradiol
(0.03)
Desogestrel
(0.15)
Cyclen 13 (5) Ethinyl Estradiol
(0.035)
Norgestimate
(0.25)
Evra 9 (3) Ethinyl Estradiol
(0.02)
Norgestimate
(0.15)
Demulen 4 (1) Ethinyl Estradiol
(0.03)
Ethynodiol diacetate
(2)
Triphasel1 4 (1) Ethinyl Estradiol
(0.03, 0.04, 0.03)
Levonorgestrel
(0.05, 0.075, 0.125)
Depo-provera2 2 (1) - Medroxyprogesterone
(150)
Triquillar1 2 (1) Ethinyl Estradiol
(0.03, 0.04, 0.03)
Levonorgestrel
(0.05, 0.075, 0.125)
1 Indicates triphasic HCs, with dose of hormone reported in the order of administration 2 HC administered in the form of an intra-muscular injection every 3 months 3 Category composed of various HC formulations each used by <1% of subjects
* 3% of subjects did not report type of HC used
32
2.4.2 Prevalence of Premenstrual Symptoms
Prevalence of experiencing any premenstrual symptoms in the total population was 99%,
and did not differ significantly between ethnic groups (p=0.11). Prevalence of each premenstrual
symptom in the total population as well as stratified by ethnicity is shown in Table 2-3
Premenstrual Symptom Prevalence by Ethnicity. The most common symptoms experienced were
cramps (75%), bloating (75%), mood swings (73%), increased appetite (64%), and acne (62%).
Other premenstrual symptoms experienced were fatigue (55%), sexual desire (50%), anxiety
(37%), desire to be alone (33%), depression (29%), headache (27%), confusion (21%),
clumsiness (15%), nausea (15%), and insomnia (11%).
In the unadjusted model symptom prevalence differed between ethnic groups for
symptoms of cramps, bloating, sexual desire, headache, and confusion (p<0.05). However, after
adjustments for age, BMI, HC use, physical activity, medication use, and plasma 25(OH)D
concentrations, only the prevalence of cramps differed between ethnic groups (p<0.05). This
association met adjustments for multiple comparisons (p<0.015), where East Asians reported a
lower prevalence of cramps than Caucasians and South Asians. Prevalence of bloating, mood
swings, increased appetite, acne, fatigue, sexual desire, anxiety, desire to be alone, depression,
headache, confusion, clumsiness, nausea, and insomnia did not differ between ethnic groups in
the adjusted model.
33
Table 2-3 Premenstrual Symptom Prevalence by Ethnicity
Symptom Total (%)
N=1048
Caucasian (%)
N=46
East Asian (%)
N=395
South Asian (%)
N=100
Other (%)
N=78
Model 1
p-value
Model 2
p-value
Cramps 75 79a 67b 84a 78ab <0.0001 <0.0001
Bloating/Swelling/Breast
Tenderness 75 79 70 70 78 0.01 0.16
Mood Swings/Irritability 73 73 72 74 67 0.68 0.68
Increased Appetite/Food
Cravings 64 65 63 64 62 0.9 0.86
Acne 62 66 60 52 57 0.05 0.18
Fatigue 55 52 56 58 65 0.15 0.13
Sexual Desire/Activity Change 50 55 42 48 56 0.001 0.11
Anxiety/Tension/Nervousness 37 36 38 34 34 0.85 0.87
Desire to be alone 33 30 33 42 39 0.06 0.23
Depression 29 30 27 33 28 0.57 0.63
Headache 27 27 23 37 29 0.03 0.15
Confusion/Difficulty
Concentrating/Forgetfulness 21 18 26 24 18 0.02 0.17
Clumsiness 15 14 18 15 11 0.26 0.27
Nausea 15 16 11 20 17 0.05 0.21
Insomnia 11 9 11 16 13 0.16 0.63
34
Sorted by total premenstrual symptom prevalence. Letters indicate prevalence values which differed significantly from each other in the adjusted model (p<0.05).
35
2.4.3 Premenstrual Symptom Associations with HC use
Associations between premenstrual symptoms and HC use is shown in Table 2-4
Associations between HC Use and Premenstrual Symptom Severity and displayed graphically in
Figure 2-1 Associations between HC Use and Mild Premenstrual Symptoms and Figure 2-2
Associations between HC Use and Moderate/Severe Premenstrual Symptoms. In the unadjusted
model, HC use was associated with a lower risk of experiencing mild acne and the following
symptoms at moderate/severe severity: cramps, fatigue, anxiety, clumsiness, confusion, nausea,
depression, and desire to be alone. In Model 2, which adjusted for ethnicity, BMI, physical
activity, PMS medication use and age, HC use was not associated with any symptoms at mild
severity. HC use was associated with a lower RR (95% CI) of experiencing moderate/severe:
cramps (0.81, 0.71-0.92), anxiety (0.62, 0.41-0.93), clumsiness (0.13, 0.07-0.73), confusion
(0.22, 0.09-0.54), depression (0.55, 0.33-0.89), and desire to be alone (0.45, 0.28-0.73). All
symptoms with the exception of depression met Benjamini-Yekutieli criteria for multiple
comparisons (30 tests, α = 0.05: p<0.013). Premenstrual symptoms of bloating, mood swings,
increased appetite, acne, fatigue, sexual desire, headache, and insomnia were not associated with
HC use in Model 2. Low sample size precluded calculations of adjusted relative risks for
moderate/severe nausea, where unadjusted RRs were: 0.53 (0.25, 1.13).
Associations between duration of HC use and premenstrual symptoms severities are
reported in Table 2-5 Associations between Duration of HC Use and Premenstrual Symptoms
and displayed graphically in Figure 2-3 Associations between Duration of HC Use and Mild
Premenstrual Symptomsand Figure 2-4 Associations between Duration of HC Use and
Moderate/Severe Premenstrual Symptoms. In Model 1, duration of HC use was associated with a
decreased risk of experiencing mild insomnia and cramps. In Model 2, after adjustments for
36
ethnicity, BMI, physical activity, PMS medication use, and age, each year of HC use was
associated with a lower risk of mild cramps (0.94, 0.88-0.99), confusion (0.89, 0.79-1.00) and
insomnia (0.79, 0.64-0.98), as well as moderate/severe fatigue (0.89, 0.80-0.98). None of these
associations met Benjamini-Yekutieli criteria for multiple comparisons. Low sample size
precluded calculations of adjusted RRs for moderate/severe symptoms of confusion, insomnia,
and nausea, where unadjusted RRs were: 0.63 (0.33,1.18), 0.53 (0.16,1.82), and 0.69
(0.44,1.08), respectively.
37
Table 2-4 Associations between HC Use and Premenstrual Symptom Severity
Symptom Severity HC Non-Users
(%)
N = 782
HC Users
(%)
N = 320
Model 1
Relative Risk
Model 1
p-value
Model 2 Relative
Risk
Model 2
p-value
Acne /
Skin Blemish
None 310 (40) 111 (35) REF REF
Mild 318 (41) 161 (50) 1.17 (1.03,1.33) 0.02 1.12 (0.98,1.28) 0.10
Moderate/Severe 154 (20) 48 (15) 0.91 (0.69,1.19) 0.49 0.84 (0.63,1.12) 0.23
Bloating /
Swelling / Breast
Tenderness
None 207 (26) 71 (22) REF REF
Mild 309 (40) 143 (45) 1.12 (0.99,1.26) 0.07 1.07 (0.95,1.22) 0.27
Moderate/Severe 266 (34) 106 (33) 1.06 (0.92,1.23) 0.39 1.00 (0.86,1.16) 0.99
Cramps
None 185 (24) 89 (28) REF REF
Mild 256 (33) 128 (40) 1.02 (0.89,1.16) 0.82 0.93 (0.81,1.07) 0.29
Moderate/Severe 341 (44) 103 (32) 0.83 (0.72,0.96) 0.01 0.82 (0.71,0.93) 0.002
Mood Swings /
Crying Easily /
Irritability /Angry
Outbursts
None 212 (27) 92 (29) REF REF
Mild 287 (37) 128 (40) 1.01 (0.88,1.16) 0.87 1.02 (0.88,1.18) 0.80
Moderate/Severe 283 (36) 100 (31) 0.91 (0.78,1.06) 0.24 0.89 (0.76,1.06) 0.19
Increased
Appetite / Food
Cravings
None 282 (36) 112 (35) REF REF
Mild 232 (30) 107 (33) 1.08 (0.91,1.28) 0.35 1.06 (0.89,1.27) 0.49
Moderate/Severe 268 (34) 101 (32) 0.97 (0.82,1.15) 0.75 0.97 (0.82,1.16) 0.76
Fatigue None 342 (44) 153 (48) REF REF
Mild 245 (31) 107 (33) 0.99 (0.83,1.17) 0.87 1.00 (0.83,1.20) 0.97
38
Symptom Severity HC Non-Users
(%)
N = 782
HC Users
(%)
N = 320
Model 1
Relative Risk
Model 1
p-value
Model 2 Relative
Risk
Model 2
p-value
Moderate/Severe 195 (25) 60 (19) 0.78 (0.61,0.99) 0.04 0.82 (0.64,1.05) 0.11
Headache
None 575 (74) 231 (72) REF REF
Mild 131 (17) 58 (18) 1.08 (0.82,1.43) 0.58 1.11 (0.84,1.49) 0.46
Moderate/Severe 76 (10) 31 (10) 1.01 (0.68,1.50) 0.95 1.01 (0.67,1.51) 0.97
Anxiety / Tension
/ Nervousness
None 480 (61) 220 (69) REF REF
Mild 201 (26) 73 (23) 0.84 (0.67,1.06) 0.15 0.88 (0.69,1.13) 0.31
Moderate/Severe 101 (13) 27 (8) 0.63 (0.42,0.94) 0.02 0.63 (0.42,0.95) 0.03
Clumsiness
None 655 (84) 278 (87) REF REF
Mild 90 (12) 39 (12) 1.02 (0.72,1.45) 0.92 1.07 (0.74,1.56) 0.71
Moderate/Severe 37 (5) 3 (1) 0.20 (0.06,0.64) 0.007 0.22 (0.07,0.73) 0.01
Confusion /
Difficulty
Concentrating /
Forgetfulness
None 599 (77) 267 (83) REF REF
Mild 121 (15) 48 (15) 0.91 (0.67,1.23) 0.53 1.00 (0.72,1.38) 1.00
Moderate/Severe 62 (8) 5 (2) 0.20 (0.08,0.48) 0.0004 0.22 (0.09,0.54) 0.001
Sexual Desire /
Activity Change
None 407 (52) 147 (46) REF REF
Mild 233 (30) 112 (35) 1.19 (1.00,1.41) 0.05 1.14 (0.95,1.37) 0.16
Moderate/Severe 142 (18) 61 (19) 1.13 (0.88,1.46) 0.33 0.96 (0.74,1.23) 0.74
Insomnia None 688 (88) 293 (92) REF REF
Mild 75 (10) 25 (8) 0.80 (0.52,1.23) 0.31 0.91 (0.57,1.43) 0.68
39
Symptom Severity HC Non-Users
(%)
N = 782
HC Users
(%)
N = 320
Model 1
Relative Risk
Model 1
p-value
Model 2 Relative
Risk
Model 2
p-value
Moderate/Severe 19 (2) 2 (1) 0.25 (0.06,1.08) 0.06 0.23 (0.05,0.99) 0.05
Nausea*
None 664 (85) 277 (87) REF REF
Mild 81 (10) 35 (10) 1.03 (0.71,1.50) 0.87 0.95 (0.64,1.41) 0.80
Moderate/Severe 37 (5) 8 (3) 0.53 (0.25,1.13) 0.10 N/A N/A
Depression
None 543 (69) 236 (74) REF REF
Mild 150 (19) 65 (20) 1.00 (0.77,1.29) 0.99 0.96 (0.73,1.26) 0.77
Moderate/Severe 89 (11) 19 (6) 0.53 (0.33,0.85) 0.008 0.55 (0.34,0.90) 0.02
Desire to be alone
None 499 (64) 238 (75) REF REF
Mild 180 (23) 62 (19) 0.78 (0.60,1.01) 0.06 0.80 (0.62,1.04) 0.10
Moderate/Severe 103 (13) 19 (6) 0.43 (0.27,0.69) 0.0004 0.45 (0.28,0.73) 0.001
Model 1 contains unadjusted relative risks and p-values
Model 2 contains relative risks and p-values adjusted for ethnicity, log-transformed BMI, physical activity, age, and medication use
* indicates no values obtained in Model 2 due to low sample size
40
Figure 2-1 Associations between HC Use and Mild Premenstrual Symptoms
Contains relative risks and confidence intervals of experiencing each mild premenstrual symptom in HC users, adjusted for ethnicity, log-transformed BMI, physical
activity, age, and medication use
41
Figure 2-2 Associations between HC Use and Moderate/Severe Premenstrual Symptoms
Contains relative risks and confidence intervals of experiencing each moderate/severe premenstrual symptom in HC users, adjusted for ethnicity, log-transformed
BMI, physical activity, age, and medication use
42
Table 2-5 Associations between Duration of HC Use and Premenstrual Symptoms
Symptom Severity Mean
Duration of
Use (Years)1
N = 1,102
Model 1 Per
Year RR
Model 1
p-value
Model 2
Per Year RR
Model 2
p-value
Acne /
Skin Blemish
None 2.9 ± 0.2 REF REF
Mild 3.3 ± 0.2 1.03 (0.99,1.06) 0.17 1.02 (0.98,1.06) 0.36
Moderate/Severe 2.6 ± 0.3 0.95 (0.85,1.07) 0.41 0.98 (0.87,1.10) 0.70
Bloating / Swelling
/ Breast Tenderness
None 3.0 ± 0.3 REF REF
Mild 3.4 ± 0.2 1.02 (0.98,1.05) 0.30 1.00 (0.96,1.03) 0.91
Moderate/Severe 2.7 ± 0.3 1.00 (0.96,1.03) 0.91 0.98 (0.94,1.01) 0.22
Cramps
None 3.6 ± 0.3 REF REF
Mild 3.1 ± 0.2 0.93 (0.88,0.99) 0.02 0.94 (0.88,0.99) 0.03
Moderate/Severe 2.6 ± 0.2 0.97 (0.93,1.01) 0.17 0.98 (0.83,1.03) 0.45
Mood Swings /
Crying Easily /
Irritability /Angry
Outbursts
None 3.4 ± 0.3 REF REF
Mild 3.1 ± 0.3 0.98 (0.94,1.03) 0.47 0.96 (0.91,1.01) 0.11
Moderate/Severe 2.7 ± 0.3 0.97 (0.93,1.01) 0.17 0.94 (0.88,1.01) 0.09
Increased Appetite
/ Food Cravings
None 3.1 ± 0.2 REF REF
Mild 3.3 ± 0.3 1.01 (0.97,1.06) 0.58 1.01 (0.95,1.06) 0.82
Moderate/Severe 2.8 ± 0.3 0.97 (0.92,1.03) 0.32 0.98 (0.92,1.05) 0.62
Fatigue
None 3.4 ± 0.2 REF REF
Mild 2.9 ± 0.2 0.96 (0.90,1.02) 0.17 0.94 (0.88,1.01) 0.08
Moderate/Severe 2.7 ± 0.3 0.93 (0.85,1.02) 0.13 0.89 (0.80,0.98) 0.02
43
Symptom Severity Mean
Duration of
Use (Years)1
N = 1,102
Model 1 Per
Year RR
Model 1
p-value
Model 2
Per Year RR
Model 2
p-value
Headache
None 3.1 ± 0.2 REF REF
Mild 2.8 ± 0.3 0.99 (0.90,1.08) 0.81 0.99 (0.89,1.09) 0.80
Moderate/Severe 3.0 ± 0.3 0.95 (0.83,1.09) 0.44 0.92 (0.80,1.06) 0.23
Anxiety / Tension /
Nervousness
None 3.2 ± 0.2 REF REF
Mild 2.8 ± 0.3 0.95 (0.88,1.03) 0.21 0.94 (0.86,1.02) 0.13
Moderate/Severe 3.0 ± 0.5 0.97 (0.85,1.11) 0.67 0.98 (0.84,1.14) 0.82
Clumsiness
None 3.1 ± 0.2 REF REF
Mild 2.7 ± 0.4 0.94 (0.84,1.06) 0.32 0.93 (0.82,1.06) 0.27
Moderate/Severe 3.5 ± 1.0 1.04 (0.74,1.47) 0.81 0.94 (0.66,1.33) 0.73
Confusion /
Difficulty
Concentrating /
Forgetfulness*
None 3.2 ± 0.2 REF REF
Mild 2.6 ± 0.4 0.92 (0.82,1.03) 0.14 0.89 (0.79,1.00) 0.05
Moderate/Severe 1.4 ± 0.9 0.63 (0.33,1.18) 0.15 N/A N/A
Sexual Desire /
Activity Change
None 3.3 ± 0.2 REF REF
Mild 3.0 ± 0.3 0.98 (0.93,1.03) 0.43 0.96 (0.90,1.01) 0.13
Moderate/Severe 2.8 ± 0.3 0.95 (0.87,1.04) 0.29 0.94 (0.85,1.04) 0.22
Insomnia*
None 3.2 ± 0.2 REF REF
Mild 1.9 ± 0.4 0.78 (0.64,0.96) 0.02 0.79 (0.64,0.98) 0.03
Moderate/Severe 1.1 ± 0.4 0.53 (0.16,1.82) 0.31 N/A N/A
44
Symptom Severity Mean
Duration of
Use (Years)1
N = 1,102
Model 1 Per
Year RR
Model 1
p-value
Model 2
Per Year RR
Model 2
p-value
Nausea*
None 3.1 ± 0.2 REF REF
Mild 3.3 ± 0.5 1.02 (0.91,1.14) 0.72 1.02 (0.91,1.15) 0.72
Moderate/Severe 1.5 ± 0.5 0.69 (0.44,1.08) 0.11 N/A N/A
Depression
None 3.2 ± 0.2 REF REF
Mild 3.0 ± 0.3 0.98 (0.91,1.06) 0.62 0.97 (0.90,1.06) 0.55
Moderate/Severe 2.6 ± 0.6 0.92 (0.77,1.11) 0.38 0.93 (0.77,1.12) 0.42
Desire to be alone
None 3.2 ± 0.2 REF REF
Mild 2.9 ± 0.3 0.96 (0.88,1.05) 0.42 0.95 (0.86,1.04) 0.28
Moderate/Severe 2.5 ± 0.6 0.90 (0.75,1.09) 0.29 0.90 (0.70,1.09) 0.27
1 Shown are crude means ± standard errors
Model 1 contains unadjusted per-year relative risks and p-values
Model 2 contains adjusted per-year relative risks and p-values. Adjusted for ethnicity, log-transformed BMI, physical activity, age, and medication use
* indicates no values obtained in Model 2 due to low sample size
45
Figure 2-3 Associations between Duration of HC Use and Mild Premenstrual Symptoms
Contains per-year relative risks and confidence intervals of experiencing each mild premenstrual symptom with each year of HC use, adjusted for ethnicity, log-
transformed BMI, physical activity, age, and medication use
46
Figure 2-4 Associations between Duration of HC Use and Moderate/Severe Premenstrual Symptoms
Contains per-year relative risks and confidence intervals of experiencing each moderate/severe premenstrual symptom with each year of HC use, adjusted for
ethnicity, log-transformed BMI, physical activity, age, and medication use
47
2.5 Discussion
In this study, we investigated the prevalence of 15 common premenstrual symptoms and
their associations with hormonal contraceptive use in a multiethnic population of young adults
living in Canada. Our findings show that the prevalence of individual premenstrual symptoms
varies widely between the symptoms, and we observed ethnic differences in the prevalence of
several symptoms. We also found that HC use was associated with a lower risk of experiencing
several, but not all, premenstrual symptoms at moderate/severe severity. No associations were
observed between HC use and the risk of experiencing mild premenstrual symptoms. Duration of
HC use was also inversely associated with experiencing some, but not all, premenstrual
symptoms.
In our population 99% of the subjects reported experiencing premenstrual symptoms. The
same prevalence estimates were found in female university students in Thailand and Iran 190, 191.
Prevalence reported in other studies have been slightly lower and have ranged from 80% to 95%
186-189, 198. These variations in prevalence estimates may be explained by differences in symptom
assessment, subject population, and subject characteristics such as age 199. For example, the
lowest prevalence of 80% was reported in a German community survey which included
adolescent subjects aged 14-24 years 188. The inclusion of adolescents could explain the lower
prevalence, as was shown in a previous study which found that subjects under 20 or over 45
years of age had the lowest symptom prevalence, with prevalence peaking at age 35 192.
Alternatively, a survey of only married Iranian women from health clinics aged 20-45 reported a
prevalence of 86% 198. Two previous studies that included women of similar age as in the present
study reported similar prevalence for the various premenstrual symptoms 190, 191.
48
The most commonly experienced symptoms in the present study were cramps (75%),
bloating (75%), irritability (73%), increased appetite (64%), and acne (62%). These differed
from those reported in other studies, and as expected, investigations into the nature of the most
commonly experienced symptoms have yielded varying results depending on the population
studied 198, 200, 201. In a recent survey of Iranian women, the most common symptoms reported
were tiredness (70%), backache (68%), headache (59%), and insomnia (50%) 198. The most
common premenstrual symptoms reported in a population of Turkish medical students were
bloating (90%), irritability (88%), breast tenderness (83%), and anxiety (74%) 200. However, a
study involving a Mexican population demonstrated abdominal cramping to be the most
prevalent symptom (54%), while only 8% of women reported irritability 201. Discrepancies in the
prevalence of symptoms may be explained by several factors including variations in
premenstrual symptom questionnaires, BMI, age, cultural factors, and environmental exposures.
The questionnaire used in the present study differed from those used by others 198, 200, 201, which
could account for some of the variation in symptom reporting. For example, the questionnaire
used by Goker et al did not include symptoms of acne, appetite changes, or cramps which were
among the five most commonly experienced symptoms in the present population 200.
The effect of ethnicity in relation to premenstrual symptoms remains controversial.
Sternfeld et al. showed that relative to Whites, Hispanics reported a greater severity of
premenstrual symptoms whereas Asians reported a lesser severity 58. Several studies involving
US populations have shown significant differences in symptom prevalence between White and
Black women, but these racial differences were not present for all symptoms 56, 57, 202. This is in
line with the results of the present study which revealed ethnic differences in the prevalence of
some, but not all, symptoms and no ethnic differences in the total prevalence. In the present
study, many symptoms were observed to differ by ethnicity in our unadjusted models but after
49
adjustments for potential confounding variables these differences were no longer significant.
Following adjustments, ethnic differences in prevalence were observed only for cramps, which
remained significant after adjustments for multiple comparisons. East Asian participants reported
a lower prevalence of cramps compared to all other ethnic groups. Although this may reflect
differences in genetics or cultural factors that may put East Asians at lesser risk of some
premenstrual symptoms, it could also be explained by cultural differences in the interpretation
and reporting of symptoms59. Ethnic differences in premenstrual symptom reporting have been
previously observed and it was suggested that differences in the clustering of symptoms in
Chinese women compared to Western women may be a result of differences in the
conceptualization of the integration of organ systems and their relation to health and disease
influenced by Traditional Chinese Medicine59. Nonetheless, these findings may guide researchers
and healthcare practitioners in determining high-risk populations for premenstrual symptoms,
and should be supported by future large-scale studies on Canadian populations.
In the present study, hormonal contraceptive use was associated with a lower risk of
experiencing moderate/severe cramps, depression, desire to be alone, confusion, and anxiety.
Use of hormonal contraceptives was not associated with mild premenstrual symptoms. These
findings are in agreement with three previous studies that found a decrease in the overall
prevalence of symptoms as well as a decrease in the number and severity of emotional symptoms
in women using oral contraceptives 58, 95, 97. Two studies found no association between HC use
and premenstrual symptoms 98, 192. One study sampling 400 Iranian women observed a greater
prevalence of several premenstrual symptoms in HC users versus non-users 198. These studies,
however, assessed the effects of HC use on grouped symptom prevalence and severity, while the
present study identified specific premenstrual symptoms and severities which are associated with
HC use. Grouping of symptoms likely accounted for these discrepancies in findings of
50
associations between HC use and premenstrual symptoms. As shown in the present study, not all
symptoms are associated with HC use and including their prevalence likely impacted previous
findings. The present findings emphasize the importance of examining individual premenstrual
symptoms in research investigating the efficacy of treatments for PMDs. Furthermore, future
research into PMD treatment considering individual premenstrual symptom and severity will
help guide clinicians in making individualized treatment decisions for patients.
Duration of HC use was associated with a lower risk of moderate/severe fatigue and mild
cramps, confusion, and insomnia, but not after adjustments for multiple comparisons. This
suggests that our findings may have been due to chance and do not represent a true effect of
duration of use. Results from the present study should be confirmed by future analysis, as to our
knowledge, this is the first study that has examined the relationship between duration of HC use
and premenstrual symptoms. Other health outcomes have previously been associated with
duration of HC use, such as risk of VTE, lipid profiles, and cognitive outcomes75, 78, 83. The
mechanisms of these effects are not known and may be outcome-specific. The associations
observed between duration of HC use and some premenstrual symptoms in the present study do
not support any clinical recommendations as our findings did not meet the threshold for multiple
comparisons and should be confirmed in future studies.
The observed improvement of premenstrual symptoms with HC use has largely been
attributed to stabilizing ovarian sex steroid fluctuations during the reproductive cycle 43.
Treatments preventing ovulation, such as long-acting GnRH agonists and bilateral
oophorectomy, have been highly effective in diminishing premenstrual symptoms 43. HCs may
present a more favorable option for the management of premenstrual symptoms as they are
accompanied by far fewer and less severe side effects 1. Some HCs also possess anti-aldosterone
and anti-androgenic properties that likely enhance their effects on premenstrual symptoms 1, 203.
51
There is some evidence that the effect of HC use on premenstrual symptoms is dependent on the
HC formulation and regimen 86, 204. In the present study, sample size limitations precluded the
ability to study the effects of different HC formulations on premenstrual symptoms.
Interestingly, HC use is associated with a higher concentration of pro-inflammatory proteins 79
which have also been linked to an increase in the severity of some premenstrual symptoms 23, 26.
This cross-sectional examination of a young multiethnic population of Canadian women
found that 99% of women experienced some type of premenstrual symptom and that prevalence
of individual symptoms differed across ethnic groups. The present study identifies the most
common premenstrual symptoms in a Canadian population, and reports those symptoms that are
more common in some ethnic groups than in others. The findings also show that HC use was
associated with a lower risk of experiencing several premenstrual symptoms.
52
Chapter 3 Association between Plasma 25-Hydroxyvitamin D and
Premenstrual Symptoms
53
3.1 Abstract
Background: Premenstrual symptoms are experienced by up to 95% of women and little is
known about dietary risk factors. Previous studies suggest that 25(OH)D may be inversely
associated with the severity of premenstrual symptoms, but the findings have been inconclusive.
Objective: The objective of this study was to determine whether plasma 25(OH)D is associated
with premenstrual symptoms.
Methods: 1,051 women aged 20-29 years participating in the cross-sectional Toronto
Nutrigenomics and Health Study provided data on their premenstrual symptoms and fasting
blood samples were collected for plasma 25(OH)D analysis. Multinomial logistic regressions
were used to determine the association between vitamin D and the severity of individual
premenstrual symptoms. Adjustments were made for age, BMI, ethnicity, physical activity,
hormonal contraceptive use, season of blood draw, use of anxiolytics, antidepressants, or
analgesics, and calcium intake.
Results: Significant inverse associations were found between 25-hydroxyvitamin D and the
severity of premenstrual cramps, depression, and confusion (p<0.05). Only confusion met
Benjamini-Yekutieli adjustment for multiple comparisons (p<0.015). Plasma 25-hydroxyvitamin
D was not associated with any of the other premenstrual symptoms (acne, bloating, mood
swings, increased appetite, fatigue, headache, anxiety, sexual desire, insomnia, nausea,
clumsiness, or desire to be alone).
Conclusion: Our findings indicate that plasma 25-hydroxyvitamin D status is inversely
associated with some, but not all, premenstrual symptoms.
54
3.2 Introduction
Few treatments are available for premenstrual symptoms and little is known about their
risk factors, particularly when considering dietary recommendations 43. Calcium has been the
most well-studied nutrient in relation to premenstrual symptoms and there is strong evidence that
calcium supplementation may improve premenstrual symptoms9, 37, 205, 206. Similarly, low dietary
calcium intake has been shown to put women at risk of experiencing premenstrual symptoms33.
Vitamin D, which aids the absorption of calcium, has also recently been investigated for its role
in premenstrual symptoms. Evidence has suggested an association between vitamin D and
premenstrual symptoms, where those with lower vitamin D intakes experienced more severe
premenstrual symptoms 33, 178. Examinations of Nurse’s Health Study II data indicated that
consumption of an average of 400 IU of vitamin D per day was associated with a 40% decreased
risk of developing premenstrual syndrome (PMS) compared to those consuming an average of
100 IU per day. 33. This was supported by the findings of a small intervention trial showing that
administration of 25,000 IU of vitamin D for two weeks reduced the severity of premenstrual
symptoms in adolescents with severe hypovitaminosis 183.
Vitamin D status is determined by a combination of dietary vitamin D consumption and
cutaneous production, and is measured by the main circulating vitamin D metabolite 25-
hydroxyvitamin D (25(OH)D). Insufficient vitamin D status is particularly prevalent in high-
latitude countries such as Canada due to low wintertime sun exposure 207 and this may put
Canadian women at risk for increased premenstrual symptoms. Research evaluating the
association between 25(OH)D and premenstrual symptoms has been inconsistent 34, 179-181. Few
of these studies have measured the association between 25(OH)D and individual premenstrual
symptoms, and no studies have characterised these associations by symptom severity. Treatment
55
response rates have been shown to vary significantly between individual premenstrual symptoms
182, and findings from objective 1 demonstrated that associations between hormonal
contraceptives and premenstrual symptoms differed by symptom severity, suggesting that these
may be important parameters to consider. Therefore, the objective of this study was to determine
whether plasma 25(OH)D is associated with the prevalence or severity of individual
premenstrual symptoms.
3.3 Materials and Methods
3.3.1 Study Population
Refer to Chapter 2, section 2.3.1.
Additional exclusion criteria were applied in Study 2. From the 1,102 subjects remaining
following Study 1 exclusion criteria, 51 were excluded due to current smoking. The remaining
1,051 subjects in Study 2 were categorized into four ethnic groups based on self-reported
ethnicity: Caucasian (n=481), East Asian (n=391), South Asian (n=101), or Other (n=78).
3.3.2 Hormonal Contraceptive Use
Refer to Chapter 2, section 2.3.2.
3.3.3 Anthropometrics and Physical Activity
Refer to Chapter 2, section 2.3.3.
3.3.4 Premenstrual Symptoms
Refer to Chapter 2, section 2.3.4.
56
3.3.5 Plasma Samples and 25-Hydroxyvitamin D Analysis
Participants provided blood samples following a minimum 12-hour overnight fast.
Participants experiencing a temporary inflammatory condition (including a recent piercing or
tattoo, acupuncture, a medical or dental procedure, a vaccination or immunization, flu, an
infection, or a fever) underwent a two-week recovery period prior to providing blood samples.
Samples were collected at LifeLabs Medical Laboratory Services (Toronto, Ontario, Canada),
and 25(OH)D levels were measured at the University Health Network Specialty Lab at Toronto
General Hospital (Toronto, Ont., Canada). Plasma 25(OH)D was measured by high-performance
liquid chromatography–tandem mass spectrometry, as described previously 208. Reported plasma
25(OH)D concentrations are the sum of measured 25(OH)D3 and 25(OH)D2.
The season of blood draw was classified as follows based on month of blood draw: spring
(March, April, May), summer (June, July, August), fall (September, October, November), and
winter (December, January, February). Vitamin D status categories were created based on
recommendations from the Canadian Osteoporosis Society, the Endocrine Society, and the
Institute of Medicine163, 171, 172. Deficient vitamin D status was defined as 25(OH)D <30 nmol/L,
insufficiency was 30-49.9 nmol/L, sufficiency was 50-74.9 nmol/L, and optimal status was ≥75
nmol/L.
3.3.6 Food Frequency Questionnaire
Participants completed a 196-item Toronto-Modified Willett Food Frequency
Questionnaire (FFQ), which was used to estimate their dietary intakes of various foods,
beverages, and supplements, including calcium-containing foods and supplements. Subjects
estimated their consumption of a preassigned portion of each item over the past month by
choosing from several frequency options. Responses were then converted to estimate daily
57
averages of total calcium intake from foods and supplements. 329 participants reported currently
consuming calcium or vitamin D containing supplements.
3.3.7 Statistical Analysis
All statistical analyses were conducted using SAS (version 9.4; SAS Institute Inc, Cary,
NC, USA). The α was set at 0.05 and all reported p-values are 2-sided. Distribution of
continuous variables was assessed prior to analysis and non-normally distributed variables were
log-transformed (BMI) or square root-transformed (25(OH)D). P-values are reported from
analyses using transformed variables, while untransformed means and standard errors are
reported for ease of interpretation.
Subject characteristics were compared between subjects in four vitamin D status
categories (deficient, insufficient, sufficient, optimal) using chi-square tests for categorical
variables and ANOVA for continuous variables. Multinomial logistic regressions were used to
determine the associations between 25(OH)D and the severity of premenstrual symptoms.
Moderate and severe symptom severities were combined due to the small number of subjects
reporting severe symptoms. Univariate associations between 25(OH)D and premenstrual
symptom severities were calculated in Model 1. Multivariate models were conducted in Model 2,
which included adjustments for age, BMI, ethnicity, physical activity, season of blood draw, total
calcium intake, and use of hormonal contraceptives, anxiolytics, anti-depressants and analgesics.
Benjamini-Yekutieli adjustments for multiple comparisons were applied (15 tests, α = 0.05:
p<0.015).
3.4 Results
Subject characteristics are reported in Table 3-6 Subject Characteristics Stratified by
Vitamin D Status1,2. The distribution of vitamin D status differed between ethnic groups. The
58
majority of Caucasian (75%) and Other (51%) participants had a sufficient or optimal vitamin D
status, while only 37% of East Asian and 25% of South Asian participants had sufficient or
optimal vitamin D status. HC use was highest among those with optimal vitamin D status and
lowest in those with deficient status. Age, physical activity, and calcium intake were also highest
in those with optimal vitamin D status. BMI and use of anti-depressants, anxiolytics, or
analgesics did not significantly differ by vitamin D status.
Mean plasma 25(OH)D of subjects was 58.7 nmol/L, which represents a sufficient
vitamin D status according to criteria by the Institute of Medicine and the Canadian Osteoporosis
Society 101, 163. According to these criteria, 14% of participants had a deficient vitamin D status
(<30 nmol/L), 31% had an insufficient status (30-49.9 nmol/L), 31% had a sufficient status (50-
74.9 nmol/L), and 24% had optimal status (>75 nmol/L). Mean total calcium intake was 1,019
mg/day, which is above the Recommended Dietary Allowance (RDA) of 1000 mg/day
determined by the Canadian Osteoporosis Society for premenopausal women aged 19-50 163.
59
Table 3-6 Subject Characteristics Stratified by Vitamin D Status1,2
Deficient
n (%)
Insufficient
n (%)
Sufficient
n (%)
Optimal
n (%)
p-value
N 147 (14) 323 (31) 331 (31) 250 (24)
Age (years) 22.3 ± 0.2 22.2 ± 0.1 22.7 ± 0.1 23.1 ± 0.2 <.0001
Ethnicity <0.001
Caucasian 22 (5) 96 (20) 160 (33) 203 (42)
East Asian 69 (18) 177 (45) 117 (30) 28 (7)
South Asian 43 (43) 33 (33) 21 (21) 4 (4)
Other 13 (17) 17 (22) 33 (42) 15 (19)
HC Users 18 (12) 47 (15) 92 (28) 147 (59) <0.001
Medication Users3 37 (25) 79 (24) 68 (21) 69 (28) 0.25
BMI, (kg/m2) 22.6 ± 0.4 22.2 ± 0.2 22.6 ± 0.2 22.5 ± 0.2 0.40
Calcium, (mg/d) 788 ± 33 979 ± 28 1094 ± 26 1109 ± 31 <0.001
1 Shown are crude means ± standard errors of continuous variables, and n (%) of categorical variables. P-
values are from tests using log- transformed BMI to improve fit
2 Differences between groups were compared using chi-square tests for categorical variables and ANOVA
for continuous variables
HC: hormonal contraceptive; BMI: body mass index
60
Associations between 25(OH)D and premenstrual symptom severities are shown in Table
3-7 Associations between Plasma 25-Hydroxyvitamin D and Premenstrual Symptom Severity
and graphically in Figure 3-5 Associations between Plasma 25-Hydroxyvitamin D and
Premenstrual Symptom Severity1,2. Model 1 includes unadjusted associations and adjusted
associations are shown in Model 2. In Model 1, significant inverse associations were observed
between 25(OH)D and premenstrual symptoms of acne, cramps, clumsiness, confusion, and
desire to be alone (p<0.05). However, following adjustments for age, BMI, ethnicity, physical
activity, season of blood draw, calcium intake, and use of hormonal contraceptives, analgesics,
anxiolytics and antidepressants, only symptoms of cramps, confusion, and depression remained
significantly inversely associated with 25(OH)D concentrations (p<0.05). 25(OH)D
concentrations were significantly associated with the prevalence of confusion, where
experiencing confusion at any severity was associated with decreased 25(OH)D concentrations.
Decreased 25(OH)D concentrations were also observed in those experiencing depression at mild
severity, and moderate/severe cramps. No other symptoms were associated with 25(OH)D.
Following Benjamini-Yekutieli adjustments for multiple comparisons, only confusion remained
significantly associated with 25(OH)D (p<0.015). Results were similar within all major ethnic
groups (data not shown).
61
Table 3-7 Associations between Plasma 25-Hydroxyvitamin D and Premenstrual Symptom Severity
Symptom Severity Plasma 25(OH)D nmol/L ± SE
N = 999
Model 1 p-value
Model 2 p-value
Acne /
Skin Blemish
None 55.8 ± 1.4 0.036 0.34
Mild 60.8 ± 1.5
Moderate/Severe 59.8 ± 2.1
0.36 0.86
Bloating / Swelling /
Breast Tenderness
None 56.8 ± 1.8
Mild 58.6 ± 1.4
Moderate/Severe 60.2 ± 1.7
0.010 0.029
Cramps
None 60.3 ± 1.9a
Mild 61.2 ± 1.6a
Moderate/Severe 55.5 ± 1.4b
0.46 0.41
Mood Swings / Crying
Easily / Irritability /Angry
Outbursts
None 57.9 ± 1.7
Mild 60.2 ± 1.6
Moderate/Severe 57.6 ± 1.5
0.63 0.81
Increased Appetite / Food
Cravings
None 59.0 ± 1.5
Mild 59.6 ± 1.7
Moderate/Severe 57.5 ± 1.6
0.15 0.35
Fatigue
None 59.9 ± 1.4
Mild 59.0 ± 1.7
Moderate/Severe 55.8 ± 1.9
62
Symptom Severity Plasma 25(OH)D nmol/L ± SE
N = 999
Model 1 p-value
Model 2 p-value
0.88 0.43
Headache
None 58.5 ± 1.0
Mild 59.9 ± 2.5
Moderate/Severe 57.8 ± 3.0
0.29 0.30
Anxiety / Tension /
Nervousness
None 59.4 ± 1.1
Mild 58.5 ± 1.9
Moderate/Severe 55.2 ± 2.7
0.027 0.08
Clumsiness
None 59.4 ± 1.1
Mild 56.0 ± 2.9
Moderate/Severe 49.5 ± 4.7
<.0001 0.0037
Confusion / Difficulty
Concentrating /
Forgetfulness
None 60.5 ± 1.0a
Mild 54.4 ± 2.3b
Moderate/Severe 46.6 ± 3.4b
0.67 0.13
Sexual Desire / Activity
Change
None 58.0 ± 1.3
Mild 59.9 ± 1.7
Moderate/Severe 58.3 ± 2.0
0.10 0.41
Insomnia
None 59.4 ± 1.0
Mild 53.2 ± 2.4
Moderate/Severe 51.0 ± 5.4
0.69 0.55
63
Symptom Severity Plasma 25(OH)D nmol/L ± SE
N = 999
Model 1 p-value
Model 2 p-value
Nausea
None 59.0 ± 1.4
Mild 58.0 ± 2.7
Moderate/Severe 53.9 ± 3.6
0.12 0.046
Depression
None 59.9 ± 1.1a
Mild 56.0 ± 1.8b
Moderate/Severe 55.0 ± 3.1ab
0.007 0.31
Desire to be alone
None 60.3 ± 1.2
Mild 57.1 ± 1.8
Moderate/Severe 51.5 ± 2.5
Model 1 contains unadjusted p-values
Model 2 contains p-values adjusted for ethnicity, log-transformed BMI, physical activity, age, season of blood draw, use of anxiolytics, anti-depressants, or
analgesics, and total calcium intake.
Letters indicate means which significantly differed in Model 2
64
Figure 3-5 Associations between Plasma 25-Hydroxyvitamin D and Premenstrual Symptom Severity1,2
1Shown are mean plasma 25(OH)D concentrations and standard errors 2 P-values are adjusted for ethnicity, log-transformed BMI, physical activity, age, season of blood draw, use of anxiolytics, anti-depressants, or analgesics, and total
calcium intake. Letters indicate means which significantly differed
65
3.5 Discussion
The present cross-sectional examination of a multiethnic population of young women
investigated the association between vitamin D status and 15 common premenstrual symptoms.
Our findings show an inverse association between 25-hydroxyvitamin D and the prevalence and
severity of premenstrual cramps, depression, and confusion. These associations remained
significant after adjustments for calcium intake and other factors known to influence
premenstrual symptoms.
The present study indicates that individual symptoms may respond differently to
25(OH)D levels and, to our knowledge, is the first study to report the association of 25(OH)D
with the prevalence and severity of individual premenstrual symptoms. Only three premenstrual
symptoms were significantly associated with 25(OH)D in the present study, and the associations
between 25(OH)D and symptom severity differed between the symptoms. 25(OH)D levels were
significantly lower in those reporting moderate/severe premenstrual cramps compared to those
reporting mild severity or no cramps. Premenstrual depression, however, may be more
responsive to vitamin D status as even participants experiencing mild depression were observed
to have significantly lower 25(OH)D. Although 25(OH)D levels were lower in those
experiencing moderate/severe depression than those with mild depression, this difference was
not significant. This may be due to the low sample size of the moderate/severe groups
contributing to their large standard errors. 25(OH)D was also inversely associated with the
prevalence of confusion at any severity.
The observed inverse association between 25(OH)D and several premenstrual symptoms
is in agreement with some 181, but not all 34, 179, 180, previous observational studies. All previous
66
studies, with the exception of one 181, examined the association of 25(OH)D with prevalence of
premenstrual syndrome (PMS), not individual premenstrual symptoms. It is important to evaluate
the effects on symptoms and symptom clusters separately, as the various somatic and affective
symptoms may have different etiologies, which could impact their association with vitamin D. A
review of the various pharmacological treatments available for PMS concluded that their
effectiveness was dependent on symptom clusters 182. For example, selective serotonin reuptake
inhibitors were found to be effective in treating mood and behavioral symptom clusters, but not
physical symptoms 182. Furthermore, the studies that did not find an association with 25(OH)D
were conducted on populations with very low 25(OH)D levels and a high rate of vitamin D
deficiency 179, 180. The population used in the present study had an approximately equal
distribution between sufficient and insufficient vitamin D statuses.
Previous examinations of data collected in the Nurse’s Health Study II have shown
inverse associations between the incidence of PMS with vitamin D intake 33 or 25(OH)D
concentrations 181. Specifically, 25(OH)D concentrations measured prior to PMS diagnosis were
inversely associated with symptoms of depression, diarrhea, fatigue, and breast ache. In the
present study, we also observed an association between 25(OH)D and premenstrual depression,
although an association with fatigue did not reach significance. Findings from the present study
should be supported by more large-scale observational studies as well as RCTs before any
clinical or public health recommendations can be made. Our findings support the analysis of
premenstrual symptoms individually in future studies, as we have shown symptom-specific
associations with plasma 25(OH)D. RCTs examining the effect of vitamin D supplements on the
severity of individual premenstrual symptom would confirm a causal relationship. Currently, two
intervention trials have been conducted which examined the effect of vitamin D supplementation
on premenstrual symptom scores183, 184. Both studies report a decrease in premenstrual symptom
67
severity scores with vitamin D supplementation183, 184, supporting the existence of a causal
relationship underlying the associations observed in the present study.
Previous examinations of data collected in the Nurse’s Health Study II have shown
inverse associations between the incidence of PMS with vitamin D intake 33 or 25(OH)D
concentrations 181. Specifically, 25(OH)D concentrations measured prior to PMS diagnosis were
inversely associated with symptoms of depression, diarrhea, fatigue, and breast ache. In the
present study, we also observed an association between 25(OH)D and premenstrual depression,
although an association with fatigue did not reach significance.
It has been suggested that premenstrual symptoms may occur as a result of calcium
dysregulation, hyperparathyroidism, and vitamin D deficiency 29, 30, 32, 37. Calcium and
1,25(OH)vitamin D have been shown to fluctuate throughout the menstrual cycle in response to
fluctuations in estradiol, with significant drops in calcium occurring in the luteal phase along
with increased metabolism of 25(OH)D into 1,25(OH)D 30, 32. Higher Vitamin D status may exert
a protective effect on premenstrual symptoms when these fluctuations occur. Findings from the
present study support this hypothesis, as the symptoms found to be associated with lower
25(OH)D levels are similar to those experienced in hypocalcemia such as depression, cramps,
forgetfulness, and impaired concentration 29. Other common symptoms of hypocalcemia such as
fatigue and anxiety 29, showed similar associations with 25(OH)D in the present study, where
25(OH)D levels decreased with increasing symptom severities. These associations did not meet
the threshold for significance in the adjusted models, perhaps due to adjustments for calcium
intake.
Vitamin D may be directly affecting premenstrual symptoms through its actions as a
neurosteroid 209, 210. 25(OH)D and 1,25(OH)D are able to cross the blood-brain barrier and
vitamin D receptors (VDRs) are distributed in areas of the brain associated with various mood
68
disorders, such as depression and seasonal affective disorder 173-175. Several epidemiological and
animal studies suggest a link between vitamin D and depression as well as anxiety 211. In keeping
with this hypothesis, the present study found 25(OH)D levels to be significantly lower in women
experiencing premenstrual depression. 25(OH)D levels were also lower in women experiencing
premenstrual anxiety and desire to be alone, although these associations did not reach
significance. These results are consistent with two recent intervention trials which observed
significant decreases in premenstrual mood symptoms, including depression and anxiety, with
administration of vitamin D supplements 183, 184.
Growing evidence indicates increased inflammation may play a role in the etiology of
premenstrual symptoms 212. This is supported by associations found between premenstrual
symptoms and increased levels of inflammatory factors such as C-reactive protein (CRP), IL-12
and interferon-gamma 23, 24, 26. Elevated CRP was found to be associated with symptoms of
anxiety and mood swings, cramps, increased appetite and bloating, and breast pain 212. Vitamin
D is involved in the modulation of immune function and inflammation 176, 177 and may reduce
premenstrual symptoms through this pathway. In the present study, no associations were found
between 25(OH)D and the premenstrual symptoms that have been associated with the
inflammation pathway including mood swings, breast pain and appetite changes. 25(OH)D was
associated with premenstrual cramps, which were shown in one study to be associated with
inflammation 26.
In summary, we found that low vitamin D status may be a risk factor for experiencing
premenstrual symptoms of cramps, depression, and confusion. No associations were observed for
many of the other premenstrual symptoms studied, suggesting there may be different
pathophysiological mechanisms underlying individual symptoms.
.
69
Chapter 4 Synopsis, Limitations and Future Directions
70
4.1 Synopsis
Few treatments are available for premenstrual symptoms which are experienced by a
majority of women. Hormonal contraceptive use may present an effective treatment option, but
more research is needed to confirm for which symptoms it is most effective. Research examining
dietary associations with premenstrual symptoms is limited. There is some preliminary evidence
that vitamin D may be associated with premenstrual symptoms, but this has not been examined
in relation to the severity of individual symptoms. The present dissertation aims to address these
gaps in knowledge.
Objective 1: To determine the prevalence of premenstrual symptoms in a multiethnic population
and to investigate their associations with use of hormonal contraceptives.
Results: Our examination of the prevalence of premenstrual symptoms in a multiethnic
Canadian population showed that premenstrual symptoms were experienced by most women and
that the prevalence of individual symptoms varied widely. Ethnicity was not associated with the
prevalence of symptoms in our population, with the exception of cramps. Hormonal
contraceptive use was associated with a reduced risk of experiencing several common
premenstrual symptoms at moderate/severe severity. HC use was not associated with
premenstrual symptoms at mild severity. Duration of HC use was associated with the risk of
experiencing mild premenstrual confusion and insomnia, as well as moderate/severe
premenstrual cramps and mood swings, although these associations did not meet adjustments for
multiple comparisons.
71
Objective 2: To determine the associations between plasma 25-hydroxyvitamin D concentrations
and the prevalence and severity of premenstrual symptoms.
Results: Plasma 25(OH)D was inversely associated with the prevalence and severity of
premenstrual cramps and confusion. 25(OH)D concentrations were also inversely associated with
a lower prevalence of depression. After adjustments for multiple comparisons, 25(OH)D was
only associated with the prevalence and severity of premenstrual confusion. Other premenstrual
symptoms were not associated with plasma 25(OH)D. These findings were replicated in all
major ethnic groups.
Our findings demonstrate that the associations of premenstrual symptoms with HC use
and 25(OH)D are symptom and severity-specific. It has been previously shown that premenstrual
symptoms may respond differently to treatments, and our results support this finding. These
findings emphasize the importance of examining associations between treatments and
premenstrual symptoms individually.
4.2 Limitations
The present study has some limitations. Firstly, the present study utilized a cross-
sectional study design, which precludes any determinations of causality or the directionality of
the associations observed and for this reason, our results should be interpreted with caution. It is
possible that mechanisms could exist whereby HC use or 25(OH)D are influenced by
premenstrual symptoms. Previous research in the field supports the associations observed in the
present study and provides support for the directionality of these relationships. Furthermore, the
large amount of information collected in the TNH study allowed for adjustments of many factors
known to influence premenstrual symptoms, minimizing the likelihood of residual confounding
72
and distinguishing between the effects of calcium and vitamin D. Of course, it is not possible for
all confounding variables to be accounted for in the present study and it is possible that observed
associations were driven by residual confounding. Although the sample size of the present study
was large, we were unable to examine the effects of various HC formulations due to sample size
constraints. The TNH study population was limited to young and educated women, so the results
of the present study can not be generalized to the overall population or other age groups. Finally,
a large number of tests were conducted in the present study and thus the results observed could
have been due to chance, although we attempted to control for this using adjustments for
multiple comparisons.
Our premenstrual symptom questionnaire was self-developed and has not been previously
validated. The questionnaire did not specify a retrospective time-frame for experiencing the
listed premenstrual symptoms, which may have resulted in an under-reporting or over-reporting
of symptoms depending on the participant’s interpretation of the question. Furthermore, the
present study relied on retrospective symptom reporting which may result in an over-reporting of
premenstrual symptoms. This may have inflated the prevalence estimates reported in the present
study, as it has been previously reported that retrospective premenstrual symptom reporting can
result in an overestimation of symptom prevalence 213. Our questionnaire was, however,
representative of common premenstrual symptoms and included questions regarding the severity
of premenstrual symptoms which allowed for unique analyses in the present study. This likely
did not impact the associations observed with HC use or 25(OH)D, as there is no evidence that
symptom over-reporting would vary by vitamin D status or between HC users and non-users.
73
4.3 Future Directions
Findings from our large cross-sectional study suggest that HC use and vitamin D are
associated with the severity of some premenstrual symptoms. However, a causal relationship can
not be determined from our data and more longitudinal research with prospective symptom
reporting is required. There is evidence that the effect of HC use on premenstrual symptoms is
dependent on the HC formulation being used. Due to sample size constraints, we were unable to
address this research question in our study. Future studies comparing the effects of different HCs
on individual premenstrual symptoms would provide useful information for clinicians and could
lead to targeted clinical approaches in the treatment of premenstrual symptoms.
Our findings suggest plasma 25(OH)D may be inversely associated with some
premenstrual symptoms. Future RCTs examining the effect of vitamin D supplementation in the
treatment of premenstrual symptoms would confirm a causal relationship and aid in the
understanding of the etiology of premenstrual symptoms. Furthermore, variation in individuals’
DBP concentrations can affect the bioavailability of 25(OH)D 214 which may impact the
relationship between vitamin D and premenstrual symptoms. Additionally, recent research
suggests that genetic variants in the vitamin D pathway, such as variants in VDR, may modify
the relationship between vitamin D and disease outcomes 215. Next steps in our research are to
examine whether common variants in VDR and DBP concentrations modify the relationship
between vitamin D and premenstrual symptoms.
74
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Appendices
Table A-1 GHLQ Premenstrual Symptom Questionnaire