In the early MT (stage –2), a woman’s menstrual cycles remain regular, but the interval between cycles may be altered by 7 or more days. Typically, cycle lengths become shorter. Compared with younger women, FSH levels are elevated, and serum estrogen levels may be increased in the early follicular phase. Normal ovulatory cycles may be interspersed with anovulatory cycles during this transition, and conception can occur unexpectedly. The late MT (stage –1) is characterized by two or more skipped menses and at least one intermenstrual interval of 60 days or more due to longer and longer periods of anovulation (Soules, 2001). This overview of altered menstruation results from changes in several endocrine axes described next.
During the reproductive years, gonadotropin-releasing hormone (GnRH) is released in a pulsatile fashion by the arcuate nucleus of the medial basal hypothalamus. It binds to GnRH receptors on the pituitary gonadotropes to stimulate cyclic luteinizing hormone (LH) and FSH release. These gonadotropins, in turn, stimulate the production of the ovarian steroids: estrogen, progesterone, and also inhibin. Estrogen and progesterone exert positive and negative feedback on pituitary gonadotropin production and on the amplitude and frequency of GnRH release. Produced by granulosa cells, inhibin also exerts an important negative influence on FSH secretion from the pituitary. This tightly regulated endocrine system leads to regular, ovulatory menstrual cycles.
Beginning in the late 40s and in early MT (stage –2), FSH levels rise slightly and bring about an increased ovarian follicular response, which raises overall estrogen levels (Jain, 2005; Klein, 1996). The monotropic FSH rise is attributed to decreased ovarian inhibin secretion rather than diminished estradiol feedback. In perimenopausal women, estradiol production fluctuates with FSH levels and can reach higher concentrations than those observed in women younger than 35. Estradiol levels generally do not drop significantly until late in MT. Despite continuing regular cyclic menstruation, progesterone levels during the early MT are lower than in mid-reproductive aged women (Santoro, 2004). Testosterone levels do not vary appreciably during the MT. That said, sex hormone-binding globulin (SHBG) production declines after the menopause and may lead to relative increased levels of free or unbound estrogen and testosterone.
Women in late MT exhibit impaired folliculogenesis and an increasing incidence of anovulation compared with women in their mid-reproductive years. Also, during this time, ovarian follicles undergo an accelerated rate of loss until eventually, in late MT, the supply of follicles is depleted. These changes, including the earlier-described FSH level increase, reflect the reduced capability of aging follicles to secrete inhibin (Reyes, 1977; Santoro, 1996). As another indicator, antimüllerian hormone (AMH) is a glycoprotein secreted by the granulosa cells of secondary and preantral follicles and indirectly reflects the primordial follicle pool (Grynnerup, 2014). Circulating AMH concentrations remain relatively stable across the menstrual cycle in reproductive-aged women and correlate with the number of early antral follicles. AMH levels decrease markedly and progressively across MT (Hale, 2007). With ovarian failure in the menopause (stage +1b), ovarian steroid hormone release ceases, and the negative-feedback loop is opened. As a result, GnRH is released at maximal frequency and amplitude. In turn, circulating FSH and LH levels rise up to fourfold higher than those in the reproductive years (Klein, 1996).
Ovarian senescence is a process that has been shown to actually begin in utero within the embryonic ovary due to programmed oocyte atresia. From birth onward, primordial follicles continuously are activated, mature partially, and then regress. This follicular activation continues in a constant pattern that is independent of pituitary stimulation.
A more rapid depletion of ovarian follicles starts in the late 30s and early 40s and continues until a point at which the menopausal ovary is virtually devoid of follicles (Figs. 21-2 and 21-3). An average woman may experience about 400 ovulatory events during her reproductive lifetime. This represents a very small percentage of the 6 to 7 million oocytes present at the 20th week of gestation, or even the 1 to 2 million oocytes present at birth. The process of atresia of the nondominant cohort of follicles, largely independent of menstrual cyclicity, is the prime event that leads to the eventual loss of ovarian activity and menopause.
Transvaginal sonographic images of a pre- and postmenopausal ovary. A. In general, premenopausal ovaries have greater volume and contain follicles, which are seen as multiple, small, anechoic smooth-walled cysts. B. In comparison, postmenopausal ovaries have smaller volume and are characteristically devoid of follicular structures. (Used with permission from Dr. Elysia Moschos.)
Microscopic differences between a reproductive-age and menopausal ovary. A. Reproductive-age ovary. Note preponderance of primordial follicles. B. High-power image of primordial follicles. C. The menopausal ovary shows abundance of atretic follicles and persistent corpora albicans. (Used with permission from Dr. Raheela Ashfaq.)
As evidence, Richardson and colleagues (1987) performed a quantitative histologic study of the endometrium and ovaries of women in MT undergoing hysterectomy for benign indications. These were coupled with a single hormonal measurement and a reproductive history from the study women aged 44 to 55 years. The women who reported regular cycles had an average of 1700 follicles in a selected ovary compared with an average of 180 follicles in the ovaries of those who reported irregular cycles.
With advancing age, adrenal production of dehydroepiandrosterone sulfate (DHEAS) declines. In women aged 20 to 30 years, DHEAS concentrations peak, with an average of 6.2 μmol/L, and then decrease steadily. In women 70 to 80 years of age, DHEAS levels are diminished by 74 percent to 1.6 μmol/L. Other adrenal hormone levels fall with aging as well (Burger, 2000; Labrie, 1997). Androstenedione levels peak at ages 20 to 30 years and then decline to 62 percent of this peak level in women aged 50 to 60 years. Pregnenolone levels diminish by 45 percent from reproductive life to menopause. The ovary contributes to the production of these hormones during the reproductive years, but after menopause, only the adrenal gland continues this hormone synthesis.
Burger and associates (2000) prospectively studied 172 women during MT as a part of the Melbourne Women’s Midlife Health Project. By analyzing hormone levels longitudinally in these patients, no relationship between a woman’s final menstrual period and the decline in DHEAS levels was noted. Advancing age, regardless of menopausal status, determined DHEAS level decline.
Microscopic changes in the endometrium directly reflect systemic estrogen and progesterone levels and thus may change dramatically depending on the stage of MT. During early MT, the endometrium may reflect ovulatory cycles, which are prevalent during this time. During later MT stages, anovulation is common, and the endometrium will display an estrogenic effect that is unopposed by progesterone. Accordingly, proliferative changes or disordered proliferative changes are frequent findings on pathologic examination of endometrial biopsy samples. After menopause, the endometrium becomes atrophic due to lack of estrogen stimulation (Fig. 15-19).
During MT, abnormal uterine bleeding (AUB) is common, and Treloar (1981) found that menses were irregular in more than one half of all women in this transition. Paramsothy (2014) reported that AUB accounted for 14 percent of all hospitalizations from 1998 to 2005 among women aged 45 to 54. Anovulation is the most common cause of erratic bleeding during MT. However, because the time interval surrounding menopause is characterized by relatively high, acyclic estrogen levels and relatively low progesterone production, women in MT are at increased risk for developing endometrial hyperplasia or carcinoma. Estrogen-sensitive neoplasms, such as endometrial polyps and uterine leiomyomas, and pregnancy-related events are also considered. Many women in their late 40s do not consider themselves fertile and will cease contraception but will still have occasional ovulatory cycles. Contraception can be discontinued by all women at age 55. No spontaneous pregnancies above that age have been reported. Some women may still have menstrual bleeding above age 55, but ovulation is rare and any oocytes are likely poor quality and not viable (Gebbie, 2010).
In all women, regardless of menopausal status, the etiology of AUB should be determined as outlined in Chapter 8. As noted, endometrial cancer is suspected in any woman in MT with AUB. The overall incidence of endometrial cancer is approximately 0.1 percent of women in this group per year, but in women with AUB in MT, the risk increases to 10 percent (Lidor, 1986). Thus, endometrial biopsy is done to exclude malignancy.
Although endometrial neoplasia is the greatest concern during this time, endometrial biopsy frequently reveals a non-neoplastic endometrium displaying estrogen effects unopposed by progesterone. In premenopausal women, this results from anovulation. In postmenopausal women, unopposed estrogen may be derived from extragonadal endogenous estrogen production, which may result from increased aromatization of androgen to estrogen due to obesity. In addition, decreased SHBG levels lead to increased levels of free and therefore bioavailable estrogen (Moen, 2004). Less often, unopposed exogenous estrogen administration or an estrogen-producing ovarian tumor can also account for these effects in postmenopausal women.
Of the many menopausal symptoms that may affect quality of life, the most frequent are those related to thermoregulation dysfunction. Kronenberg (1990) tabulated all of the published epidemiologic studies and determined that vasomotor symptoms, also variably termed hot flashes, hot flushes, and night sweats, developed in 11 to 60 percent of menstruating women during MT. In the Massachusetts Women’s Health Study, the incidence of hot flushes increased from 10 percent during the premenopausal period to approximately 50 percent after menses cessation (McKinlay, 1992). Hot flushes begin an average of 2 years before the FMP, and 85 percent of women who experience them will continue to experience them for more than 1 year. Of these women, 25 to 50 percent will have hot flushes for 5 years, and >15 percent may experience them for >15 years (Kronenberg, 1990). More recent studies of duration indicate that women can expect hot flushes to continue, on average, for nearly 5 years after the FMP, while more than one third of women who experience moderate/severe hot flushes will continue to have them for more than 10 years after the FMP (Freeman, 2014). Longitudinal studies show that hot flushes are associated with low exercise levels, smoking, high FSH and low estradiol levels, increasing BMI, ethnicity, lower socioeconomic status, and prior premenstrual dysphoric disorder (PMDD) or depression (Gold, 2006; Guthrie, 2005).
Thermoregulatory and cardiovascular changes that accompany a hot flush are well documented. An individual hot flush generally lasts 1 to 5 minutes, and skin temperatures rise because of peripheral vasodilation (Kronenberg, 1990). This change is particularly marked in the fingers and toes, where skin temperature can increase 10 to 15°C. Most women sense a sudden wave of heat that spreads over the body, particularly the upper body and face. Sweating begins primarily on the upper body, and it corresponds closely in time with an increase in skin conductance (Fig. 21-4). Sweating has been observed in women during 90 percent of hot flushes (Freedman, 2001).
Physiologic changes (means) during a hot flush. A. Core body temperature. B. Respiratory exchange ratio. C. Skin temperature. D. Sternal skin conductance. Time 0 is the beginning of the sternal skin conductance response. (Reproduced with permission from Freedman RR: Biochemical, metabolic, and vascular mechanisms in menopausal hot flashes. Fertil Steril 1998 Aug;70(2):332–337.)
Increases in both awake and sleep systolic blood pressure are noted with hot flushes (Gerber, 2007). In addition, heart rate rises 7 to 15 beats per minute at approximately the same time as peripheral vasodilatation and sweating. Heart rate and skin blood flow usually peak within 3 minutes of the hot flush onset. Simultaneously with sweating and peripheral vasodilation, the metabolic rate also significantly rises. Hot flushes can also be accompanied by palpitations, anxiety, irritability, and panic.
Five to 9 minutes after a hot flush begins, the core temperature declines 0.1 to 0.9°C due to heat loss from perspiration and increased peripheral vasodilation (Molnar, 1981). If heat loss and sweating are significant, a woman may experience chills. Skin temperature gradually returns to normal, sometimes taking 30 minutes or longer.
Pathophysiology of Vasomotor Symptoms
The underlying physiologic steps leading to hot flushes remain an enigma, and some dysfunction of the thermoregulatory nucleus of the hypothalamus is likely. This nucleus regulates perspiration and vasodilatation, which is the primary mechanism of heat loss in humans. If exposed to higher temperatures, the nucleus activates these heat dissipation mechanisms. This maintains core body temperature in a regulated normal range, called the thermoregulatory zone. It is hypothesized that women who experience more severe vasomotor symptoms have a narrower thermoregulatory zone than those without symptoms. In these women, minimal changes in core body temperature induce shivering or hot flush.
Various hormones and neurotransmitters modulate hot flush frequency. Of these, estrogens play a vital role. Although there is no clear correlation between the two, estrogen withdrawal or rapid fluctuation in levels, rather than a chronically low estrogen concentration, is suspected (Erlik, 1982; Overlie, 2002). This hypothesis is supported by the fact that women with gonadal dysgenesis (Turner syndrome), who lack normal estrogen levels, do not experience hot flushes unless first exposed to estrogen and then withdrawn from treatment.
In addition to estrogen, Freedman and colleagues (1998, 2014) hypothesized that altered neurotransmitter concentrations may create a narrow thermoregulatory zone and a lowered sweating threshold. Norepinephrine is thought to be the primary neurotransmitter responsible for lowering the thermoregulatory setpoint and triggering the heat loss mechanisms associated with hot flushes (Rapkin, 2007). Plasma levels of norepinephrine metabolites are increased before and during hot flushes. Moreover, research shows that norepinephrine injections can increase core body temperature and induce a heat loss response (Freedman, 1990). Conversely, medications that decrease norepinephrine levels, such as clonidine, may reduce vasomotor symptoms (Laufer, 1982).
Estrogens are known to modulate adrenergic receptors in many tissues. Freedman and colleagues (2001) suggested that menopause-related declines in estrogen levels lower hypothalamic α2-adrenergic receptor concentrations. In turn, a decline in presynaptic α2-adrenergic receptor levels leads to increased norepinephrine levels, thereby causing vasomotor symptoms.
Serotonin is likely another involved neurotransmitter (Slopien, 2003). Estrogen withdrawal is associated with a decreased blood serotonin level, which is followed by upregulation of serotonin receptors in the hypothalamus. Activation of specific serotonin receptors has been shown to mediate heat loss (Gonzales, 1993). However, the role of serotonin in central regulatory pathways is complex because binding at some serotonin receptors can exert negative feedback on other serotonin receptor types (Bachmann, 2005). Therefore, the effect of a change in serotonin activity depends on the type of receptor activated. Of other potential candidates, β-endorphins and other neurotransmitters affect the thermoregulatory center and make some women more prone to hot flashes (Pinkerton, 2009).
Genetic polymorphisms and vasomotor symptom prevalence and severity may also be linked. Some polymorphisms are variants of genes encoding estrogen receptor alpha (Crandall, 2006; Malacara, 2004). Others are single nucleotide polymorphisms involved in the synthesis or metabolism of estradiol or in its conversion to more- or less-potent estrogens. Currently, it is unknown whether these genetic determinants exert their effects centrally or peripherally (Al-Safi, 2014).
In sum, studies suggest that reductions and significant fluctuations in estradiol levels lead to a decline in inhibitory presynaptic α2-adrenergic receptor concentrations and an increase in hypothalamic norepinephrine and serotonin release. Norepinephrine and serotonin lower the setpoint in the thermoregulatory nucleus and allows heat loss mechanisms to be triggered by subtle changes in core body temperature. This current theory of hot flush pathogenesis underlies many of the treatment options discussed in Chapter 22.
Risk Factors for Vasomotor Symptoms
Several risk factors have been associated with an increased probability of hot flushes, including early menopause, surgical menopause, race/ethnicity, BMI, a sedentary lifestyle, smoking, and use of selective estrogen-receptor modulators (SERMs). Moreover, women exposed to high ambient temperatures may experience more frequent and severe hot flushes (Randolph, 2005). Of risks, surgical menopause is associated with a 90-percent probability of hot flushes during the first year after oophorectomy, and symptoms can be more abrupt and severe than those associated with natural menopause. Among racial and ethnic groups, hot flushes appear to be more common and more bothersome in African-American than in white women and are more common among white than among Asian women (Gold, 2001; Kuh, 1997; Thurston, 2008). These racial/ethnic differences in vasomotor symptoms persisted even after controlling for key factors such as BMI, estradiol level, hormone use, smoking, education level, and economic hardship (Al-Safi, 2014). The effect of BMI on hot flush frequency is not clear (Da Fonseca, 2013; Hunter, 2012; Wilbur, 1998).
Bone Structure and Metabolism
The skeleton consists of two bone types (Fig. 21-5). Cortical bone is the bone of the peripheral skeleton (arms and legs), and trabecular bone is the bone of the axial skeleton, which includes the vertebrae, pelvis, and proximal femur. Peak bone mass is influenced by genetic and endocrine factors, and opportunity in the younger years for acquiring bone mass is brief (American College of Obstetricians and Gynecologists, 2012). Almost all bone mass in the axial skeleton will be accumulated in young women by late adolescence, so the years immediately following menarche are especially important (Sabatier, 1996; Theintz, 1992). Calcium supplementation in prepubertal and pubertal girls improves bone accrual (Bonjour, 2001; Stear, 2003). Accordingly, osteoporosis prevention with weight-bearing exercise and vitamin D and calcium intake ideally begins in adolescence (Recker, 1992). Following adolescence, bone resorption is normally coupled to bone formation such that positive bone balance is achieved when skeletal maturity is attained, typically at age 25 to 35 years. Thereafter, bone mass declines at a slow, steady rate of approximately 0.4 percent each year. During menopause, the rate increases to 2 to 5 percent per year for the first 5 to 10 years and then slows to 1 percent per year. The subsequent risk of fracture from osteoporosis will depend on bone mass at the time of menopause and the rate of bone loss following menopause (Riis, 1996).
bone with trabecular and cortical bone labeled. (Reproduced with permission from Saladin KS: Anatomy & Physiology, 3rd edition. New York: McGraw-Hill; 2005.)
Normal bone is a dynamic, living tissue that is in a continuous process of destruction and rebuilding. This bone remodeling, also described as bone turnover, allows adaptation to mechanical changes in weight bearing and other physical activities. The process of bone remodeling involves a constant resorption of bone, carried out by multinucleated giant cells known as osteoclasts, and a concurrent process of bone formation, completed by osteoblasts (Fig. 21-6).
Bone remodeling. A. Osteoclasts resorb matrix, whereas osteoblasts deposit new lamellar bone. Osteoblasts that are trapped in the matrix become osteocytes. Others undergo apoptosis or form new, flattened osteoblast lining cells. Osteoblasts produce the proteins RANKL and OPG. When RANKL binds to RANK, the receptor on the surface of osteoclast progenitor cells, this promotes those cells’ development, activity, and survival as osteoclasts. This leads to bone resorption. OPG serves as a counterbalance. OPG binds to RANKL and thereby, RANKL is incapable of binding with RANK to promote osteoclast development. Through this mechanism, bone resorption is limited. B. With hypoestrogenism, RANKL production is increased. Excessive levels of RANKL outnumber those of OPG and osteoclast development and bone resorption is favored.
Activated osteoclasts secrete hydrochloric acid and collagen-degrading enzymes onto the bone surface, resulting in bone mineral dissolution and degradation of the organic matrix. After detaching from the organic matrix, the osteoclasts can relocate and begin resorption at another site on the bone surface or undergo apoptosis. Increased osteoclast activity in postmenopausal osteoporosis is mediated by the receptor activator of nuclear factor (RANK) ligand pathway. In this pathway, RANK, RANK ligand, and osteoprotegerin (OPG) are three major components (Table 21-2).
TABLE 21-2Key Components of the RANKL/RANK/OPG Pathway ||Download (.pdf) TABLE 21-2 Key Components of the RANKL/RANK/OPG Pathway
| RANK ligand (RANKL) |
Protein expressed by osteoblasts/bone lining cells
Binds to RANK on osteoclasts
Activation of RANK promotes osteoclast formation, function, survival
Expressed by osteoclasts and their precursor
Activated by RANKL binding
Protein secreted by osteoblasts/bone lining cells
Natural inhibitor of RANKL
Blocks RANKL-mediated activation of RANK to balance bone remodeling
Of these, RANK ligand is expressed by osteoblasts (Bar-Shavit, 2007). This ligand binds to the RANK receptor on osteoclasts and osteoclast precursors. Binding promotes osteoclast formation, function, and survival. RANK ligand is the common regulator of osteoclast activity and ultimately of bone resorption. OPG is also secreted by osteoblasts and is a natural inhibitor of RANK ligand. OPG blocks RANK ligand-mediated activation of RANK and thereby limits osteoclast resorption activity. This balances bone remodeling (Kostenuik, 2005). Many different factors can affect osteoclast activity, but RANK ligand is required to mediate their effects on bone resorption. Cytokines and certain hormones stimulate the expression of RANK ligand by osteoblasts and other cells. One negative regulator of this process is estrogen, which limits the expression of RANK ligand from osteoblasts. Another regulator is OPG, a natural inhibitor of RANK ligand that sequesters and neutralizes the effects of RANK ligand.
In healthy premenopausal women, estrogen limits osteoblast expression of RANK ligand. The OPG binds to RANK ligand to further limit its availability to stimulate osteoclasts. The remaining RANK ligand binds to osteoclast precursors, which fuse and form differentiated osteoclasts for bone resorption. This is followed by the appearance of osteoblasts resulting in bone formation. In sum, resorption and formation are balanced in premenopausal women.
In postmenopausal women, decreased estrogen levels lead to increased RANK ligand expression, which may overwhelm the natural activity of OPG. Studies show that estrogen may indirectly inhibit RANK ligand expression and stimulate OPG expression. Thus, the reduction in estrogen levels associated with menopause may lead to increased RANK ligand and decreased OPG. Bone resorption follows, but osteoblasts can only partially fill resorption cavities. This results in a chronic imbalance of formation and resorption, which leads to ongoing bone loss over time. Thus, increased RANK ligand after menopause leads to excessive bone resorption and potentially postmenopausal osteoporosis (Sambrook, 2006).
Osteopenia and Osteoporosis
Osteoporosis is a skeletal disorder that progressively reduces bone mass and strength (typically in trabecular bone) and leads to increased fracture risks. Changes to the microstructure of bone in women with postmenopausal osteoporosis include increased cortical porosity, decreased bone mass, disrupted trabecular architecture, reduced cortical thickness, and lower mineral content of bone. Osteopenia is a precursor to osteoporosis, and the National Osteoporosis Foundation (2014) estimates that more than 10 million Americans currently have osteoporosis and another 33.6 million have osteopenia of the femoral neck.
Fracture is a frequent consequence of osteoporosis. The vertebrae, femoral neck, and wrists are most commonly fractured, and epidemiologic studies estimate that the remaining lifetime risk of common fragility fractures in white women after age 50 approximates 15 percent at each of these sites (Holroyd, 2008; Kanis, 1994). Nearly 1.5 million Americans experience osteoporotic fractures each year. Worldwide, 9 million osteoporotic fractures are estimated per year (Johnell, 2006; Lund, 2008).
Fractures are associated with significant morbidity and mortality, and the risk of dying following a clinical fracture is reportedly twofold higher than for persons without fractures. The overall mortality rate from femoral neck fracture alone approximates 30 percent. In addition, only 40 percent of those who sustain a femoral neck fracture are capable of returning to their prefracture level of independence. As such, clinicians ideally educate patients regarding bone loss prevention, screen to identify bone loss early, and work with patients to implement effective management plans for osteoporosis or osteopenia.
A major proportion of bone strength is determined by bone mineral density (BMD), which is grams of mineral per area and volume of bone. However, bone quality, bone strength, and fracture risk are also affected by bone remodeling rates, bone size and geometry, microarchitecture, mineralization, damage accumulation, and matrix quality. Unfortunately, all of these are more difficult to accurately assess (Kiebzak, 2003).
Primary osteoporosis refers to bone loss associated with aging and menopausal estrogen deficiency. As estrogen levels fall after menopause, its regulatory effect on bone resorption is lost. As a result, bone resorption is accelerated and is usually not balanced by compensatory bone formation. This accelerated bone loss is most rapid in the early postmenopausal years (Gallagher, 2002). If osteoporosis is caused by other diseases or medications, the term secondary osteoporosis is used (Stein, 2003).
The amount of bone at any point in time reflects the balance of the osteoblastic (building) and osteoclastic (resorbing) activities, which are influenced by numerous stimulating and inhibiting agents (Canalis, 2007). As noted earlier, both aging and a loss of estrogen lead to a significant increase in osteoclastic activity. Also, decreased dietary calcium intake or impaired calcium absorption from the gut lowers the serum level of ionized calcium. This stimulates parathyroid hormone (PTH) secretion to mobilize calcium from bone by stimulation of osteoclastic activity (Fig. 21-7). Increased PTH levels stimulate vitamin D production. In turn, elevated vitamin D concentrations raise serum calcium levels by several effects: (1) stimulates osteoclasts to remove calcium from bone, (2) increases intestinal calcium absorption, (3) stimulates renal calcium reabsorption, and lowers PTH production by the parathyroid glands (Molina, 2013).
Vitamin D metabolism. Provitamin D (7-dehydrocholesterol) in the skin is converted to cholecalciferol by ultraviolet (UV) light. Cholecalciferol and ergocalciferol (from plants) are transported to the liver, where they undergo hydroxylation to form the major circulating form of vitamin D. A second hydroxylation step occurs in the kidney and results in the hormonally active vitamin D [1,25(OH)2D3], also known as calcitriol. This activation step is mediated by 1α-hydroxylase and is regulated by parathyroid hormone (PTH), Ca2+ levels, and vitamin D [1,25(OH)2D3]. The activity of 1α-hydroxylase is stimulated by PTH and inhibited by sufficient levels of Ca2+ and 1,25(OH)2D3. Vitamin D increases bone resorption, Ca2+ absorption from the intestine, and renal Ca2+ reabsorption, but it decreases PTH production by the parathyroid glands. The overall effect of vitamin D is to increase plasma Ca2+ concentrations. This rise in plasma Ca2+ levels inhibits 1α-hydroxylase and favors hydroxylation at C-24. This leads to synthesis of an inactive vitamin D metabolite—24,25(OH)2D3. (Reproduced with permission from Molina PE: Endocrine Physiology, 4th ed. New York: McGraw-Hill; 2013.)
In normal premenopausal women, this series of events leads to increased serum calcium levels, and PTH levels return to normal. In menopausal women, estrogen deficiency creates a greater responsiveness of bone to PTH. Thus, for any given PTH level, relatively more calcium is removed from bone.
BMD is the standard used for bone mass determination and is assessed with dual-energy x-ray absorptiometry (DEXA) of the lumbar vertebrae, radius, and femoral neck (Fig. 21-8) (Marshall, 1996). The lumbar vertebrae contain primarily trabecular bone, and this bone type forms 20 percent of the skeleton. Trabecular bone is less dense than cortical bone and has a faster bone remodeling rate. Therefore, early rapid bone loss can be determined by evaluation of this site. Cortical bone is denser and more compact bone and makes up 80 percent of the skeleton. It is most abundant in the long-bone shafts of the appendicular skeleton. The greater trochanter and femoral neck contain both cortical and trabecular bone, and these sites are ideal for the prediction of femoral neck fracture risk in older women (Miller, 2002).
Dual-energy x-ray absorptiometry (DEXA) scans. A. DEXA report describing normal hip density. B. DEXA report describing osteopenia of the hip. C. DEXA report describing normal vertebral body density. D. DEXA report describing vertebral body osteoporosis. BMC = bone mineral content; BMD = bone mineral density.
Normative bone mineral density values for sex, age, and ethnicity have been determined. For diagnostic purposes, results of BMD testing are reported as T-scores. These measure in standard deviations (SDs) the variance of an individual’s BMD from that expected for a person of the same sex at peak bone mass (25 to 30 years). A T-score of –2.0 in a woman, for example, means that her BMD is two SDs below the average peak bone mass for a young woman. Definitions include those found in Table 21-3. The fourth category, “severe osteoporosis,” describes patients who have a T-score below –2.5 and who have also suffered a fragility fracture. These are fractures caused by a fall from standing height or lower.
TABLE 21-3WHO Criteria for Bone Disease Based on Bone Mineral Density (BMD) ||Download (.pdf) TABLE 21-3 WHO Criteria for Bone Disease Based on Bone Mineral Density (BMD)
|Normal BMD : T-score between +2.5 and −1.0 |
Osteopenia: T-score between −1.0 and −2.5
Osteoporosis : T-score at or below −2.5
Severe or established osteoporosis: T-score at or below −2.5 with one or more fractures
Patients are also assigned a Z-score, which is the standard deviation between the patient’s measurement and average bone mass for a patient with the same age and weight. Z-scores lower than –2.0 (2.5 percent of the normal population of the same age) require diagnostic evaluation for secondary osteoporosis (Faulkner, 1999). Similarly, any patient with osteoporosis is screened for other conditions that lead to osteoporosis (Table 21-4).
TABLE 21-4Secondary Causes of Osteoporosis and Recommended Testing ||Download (.pdf) TABLE 21-4 Secondary Causes of Osteoporosis and Recommended Testing
|Primary hyperparathyroidism ||Serum levels of: |
| || parathyroid hormone |
|Secondary hyperparathyroidism from chronic renal failure ||Renal function tests |
|Hyperthyroidism or excess thyroid hormone treatment ||Thyroid function tests |
|Increased calcium excretion ||24-hour urine collection for calcium and creatinine concentrations |
|Hypercortisolism, alcohol abuse, and metastatic cancer ||Careful history and when indicated appropriate laboratory studies |
|Osteomalacia ||Serum levels of: |
| || calcium |
The relation between BMD and fracture risk has been calculated in numerous studies. A metaanalysis by Marshall and coworkers (1996) showed that BMD is still the most readily quantifiable predictor of fracture risk for those who have not yet suffered a fragility fracture. For each standard deviation of BMD below a baseline level (either mean peak bone mass or mean for the reference population of the person’s age and sex), the fracture risk approximately doubles (National Osteoporosis Foundation, 2002).
Recognizing the difficulty in measuring bone mass and bone quality accurately, the World Health Organization (WHO) developed the Fracture Risk Assessment Tool (FRAX) to assess an individual’s 10-year fracture risk. The algorithm, however, is applicable only for patients who have not received pharmacotherapy. The FRAX tool is accessible online and is available for multiple countries and in different languages (http://www.shef.ac.uk/FRAX/). The online tool incorporates 11 risk factors and the femoral neck raw BMD value in g/cm2 to calculate the 10-year fracture risk. The site also offers downloadable charts for calculating fracture risks using BMI or BMD. The FRAX algorithm identifies patients who might benefit from pharmacotherapy and is most useful for recognizing those with BMD in the osteopenic category.
As predictors of osteoporotic fracture, the most important factors are BMD in combination with age, fracture history, ethnicity, various drug treatments, weight loss, and physical fitness. The presence of a key risk factor alerts a clinician to the need for further assessment and possibly active intervention, such as calcium and vitamin D therapy coupled with weight-bearing exercise or pharmacologic therapy (Tables 21-5 and 21-6). Treatment options for osteoporosis are discussed in Chapter 22.
TABLE 21-5Osteoporosis Risk Factors ||Download (.pdf) TABLE 21-5 Osteoporosis Risk Factors
|Major Risk Factors ||Minor Risk Factors |
|Age >65 years |
Vertebral compression fracture
Fragility fracture after age 40
Family history of osteoporotic fracture
Systemic glucocorticoid therapy for >3 months
Propensity to fall
Osteopenia apparent on radiography
Early menopause (before age 45)
|Rheumatoid arthritis |
History of clinical hyperthyroidism
Chronic anticonvulsant therapy
Low dietary calcium intake
Excessive alcohol intake
Excessive caffeine intake
Weight <57 kg
>10 percent weight loss at age 25
Chronic heparin therapy
TABLE 21-6General Guidelines for Prevention of Osteoporosis in Postmenopausal Women ||Download (.pdf) TABLE 21-6 General Guidelines for Prevention of Osteoporosis in Postmenopausal Women
|Counsel on osteoporosis risks |
Check for secondary causes (see Table 21-4)
For women 51 and older, encourage diet containing calcium 1200 mg daily and vitamin D 800–1000 IU daily. Add supplement if diet is incomplete
Recommend regular weight-bearing and muscle-strengthening exercise
Advise against tobacco smoking and excess alcohol intake
Assess for fall risks (see Table 21-7) and modify as possible
Measure height annually
In women ≥65 years, recommend BMD testing
In postmenopausal women aged 50–65 years, recommend BMD testing based on the risk factor profile (see Table 21-5)
In those >50 with a new fracture, recommend BMD testing to determine degree of disease severity
For patients on pharmacotherapy, perform BMD testing 2 years after initiating therapy and every 2 years thereafter. However, testing frequency may be tailored to clinical situations
Risk factors for osteoporotic fracture are not independent of one another. They are additive and are considered in the context of baseline age and sex-related fracture risk. For example, a 55-year-old woman with low BMD is at significantly less risk than a 75-year-old woman with the same low BMD. Similarly, a woman with low BMD and a prior fragility fracture is at considerably greater risk than another person with the same low BMD and no prior fracture.
Age is one major contributor to fracture risk. As summarized by Kanis and associates (2001), the 10-year probability of experiencing a fracture of forearm, humerus, vertebra, or femoral neck increases as much as eightfold between ages 45 and 85 years for women. Osteoporotic fractures occur most commonly in men and women older than 65 years. Medical interventions have been demonstrated to be effective only in preventing fractures in populations with an average age older than 65 years. However, most currently approved osteoporosis therapies prevent or reverse bone loss if initiated at, or soon after, age 50. Therefore, it seems prudent to begin the identification of people at high risk for osteoporosis in their 50s. As noted, BMD is currently the best quantifiable predictor of osteoporotic fracture, and screening guidelines are discussed on page 482.
As noted, a prior fragility fracture places a person at increased risk for another fracture. The increased risk is 1.5- to 9.5-fold depending on age at assessment, number of prior fractures, and site of prior fracture (Melton, 1999). Vertebral fractures are the best studied, and a vertebral fracture increases the risk of a second such fracture at least fourfold. The placebo group of a major clinical trial showed that 20 percent of those who experienced a vertebral fracture during the study period had a second vertebral fracture within 1 year (Lindsay, 2001). Vertebral fractures also indicate vulnerability at other sites, such as the femoral neck. Similarly, wrist fractures predict vertebral and femoral neck fractures.
Another nonmodifiable risk factor is race, and osteoporosis is most common in menopausal white women. In 2002, the National Osteoporosis Foundation found that 20 percent of these women have osteoporosis, and 52 percent have low BMD. Although persons of any ethnicity can develop osteoporosis, data from the Third National Health and Nutrition Examination Survey (NHANES III) show that the risk is highest among non-Hispanic white and Asian women and lowest among non-Hispanic black women. Racial and ethnic differences are important in counseling and management because fracture rates do not always correlate with BMD across ethnic groups. For example, Chinese American women typically have lower BMD than white American women, but lower rates of femoral neck and forearm fracture (Walker, 2011). It is postulated that greater cortical density and thicker trabeculae compensate for fewer trabeculae in smaller bones. Thus, both BMD and microarchitecture appear to play distinct roles in fracture vulnerability (American College of Obstetricians and Gynecologists, 2012).
Genetic influence on osteoporosis and BMD is important, and heredity is estimated to account for 50 to 80 percent of BMD variability (Ralston, 2002). The Study of Osteoporotic Fractures, for example, identified that maternal femoral neck fracture was a predictor for femoral neck fracture in a population of elderly women (Cummings, 1995). An affected maternal grandmother also raises a woman’s fracture risk. Several genes have been associated with osteoporosis, but these discoveries have yet to translate into clinical application.
Of these, exercise, in the form of progressive resistance training, may result in clinically relevant benefits to femoral neck BMD and lumbar vertebral BMD in postmenopausal women (Kelly, 2012). Greater improvements in bone mass were also associated with increases in static balance. These associations may be particularly important for reducing fall risks. Exercise results in other general health benefits that are not totally realized with pharmacological and nutritional interventions. For example, investigators note that greater increases in femoral neck BMD and lumbar vertebral BMD are also associated with declines in BMI and percent body fat (Bouchard, 2013).
Fractures are frequently associated with falls. Thus, a history of falls or factors that increase fall rates are included in a risk assessment (Table 21-7). Factors include those associated with general frailty, such as reduced muscle strength, impaired balance, low body mass, and diminished visual acuity (Delaney, 2006). Alcohol and sedative drug use are other important risks.
TABLE 21-7Fall Risk Factors ||Download (.pdf) TABLE 21-7 Fall Risk Factors
|Physiologic changes |
Reduced muscle mass
|Comorbid conditions || |
|Loose rugs |
No bathroom support bars
Therapy with glucocorticoids lasting more than 2 to 3 months is a major risk factor for bone loss and fracture, particularly among postmenopausal women. The National Osteoporosis Foundation guidelines (2014) describe a chronic daily dose of prednisone that is ≥5 mg as the threshold for assessment and clinical intervention to prevent or treat glucocorticoid-induced osteoporosis.
After assessment of all potential risk factors, BMD measurement is a prominent component of strategies to confirm osteoporosis and determine disease severity. BMD testing is recommended for all menopausal women who: (1) are aged 65 years or older, (2) have one or more risk factors for osteoporosis, or (3) sustain fractures (see Table 21-5). Additionally, screening is considered for perimenopausal women if they have a specific risk factor such as prior low-trauma fracture, have a low BMI, or are taking a medication known to accelerate bone loss. Many vertebral fractures are asymptomatic, and vertebral imaging is recommended for women aged ≥70 years with a T-score ≤ –1.0 or those 65 to 69 years with a score ≤ –1.5 (National Osteoporosis Foundation, 2014). Unfortunately, Schnatz and associates (2011) found that many women are not properly screened or treated for osteoporosis and that inappropriate screening may also lead to improper management of osteoporosis and its associated complications. If therapy to increase BMD is instituted, BMD should be monitored.
Less commonly, bone markers of resorption and formation are used as an adjunct to BMD. These can be used to assess osteoporosis risk or to monitor treatment. During remodeling, osteoblasts synthesize several cytokines, peptides, and growth factors that are released into the circulation. Their concentrations thus reflect the rate of bone formation. Serum bone formation markers include osteocalcin, bone-specific alkaline phosphatase, and procollagen I carboxy-terminal propeptide (PICP). Osteoclasts produce bone degradation products that are also released into the circulation and are eventually cleared via the kidney. Main bone resorption markers include urinary deoxypyridinoline (u-DPD), urinary collagen type I cross-linked N telopeptide (u-NTX) and serum collagen type I cross-linked C telopeptide (s-CTX).
These markers of bone formation and resorption can estimate bone-remodeling rates and may help identify fast bone losers. As evaluated by these markers, bone remodeling rates increase at menopause and remain elevated and correlate negatively with BMD.
That said, most prospective studies analyzing the relationship between bone remodeling and rates of bone loss have been short-term and have been limited by the precision error of densitometry. Garnero and colleagues (1994) prospectively evaluated over 4 years the utility of bone markers to identify fast bone losers in a large cohort of healthy menopausal women. They found that higher levels of bone formation and resorption markers were significantly associated with faster and possibly greater BMD loss.
Markers of bone resorption may also be useful predictors of fracture risk and bone loss. Elevation of these markers may be associated with an increased fracture risk in elderly women, although data are not uniform. The association of markers of bone resorption with femoral neck fracture risk is independent of BMD, but a low BMD combined with high bone resorption biomarker doubles the risk associated with either of these factors alone. However, biomarker measurements are currently limited by their high variability within individuals. Additional studies with fracture endpoints are needed to confirm the usefulness of these markers in individual patients.
Biomarkers may also have value in predicting and monitoring response to potent antiresorptive therapy in clinical trials. Normalization of bone formation and resorption marker levels following therapy has been observed in prospective trials. Reduction in biochemical marker levels appears in some studies to be correlated with a decrease in vertebral fracture incidence but is not necessarily always predictive of response to therapies.
Bone remodeling markers are not yet used for routine clinical management. Additional studies are needed to confirm their use in individual patients. However, with refinement of assay technology and better understanding of biological variability, it is likely that they will become a useful adjunct in the future for risk assessment and management.
In women older than 50 years, atherosclerotic cardiovascular disease (CVD) remains the leading cause of death. CVD accounts for approximately 40 percent of deaths in women compared with about 5 percent due to breast cancer. Before menopause, women have a much lower risk for cardiovascular events compared with men their same age. Reasons for protection from CVD in premenopausal women are complex, but a significant contribution is assigned to greater high-density lipoprotein (HDL) levels in younger women, which is an effect of estrogen. However, after menopause, this benefit disappears over time such that a 70-year-old woman begins to have a CVD risk identical to that of a male of comparable age (Matthews, 1989). The risk of CVD increases exponentially for women as they enter menopause and as estrogen levels decline (Matthews, 1994; van Beresteijn, 1993). This becomes vitally important for women in MT, when preventive measures can significantly improve both life quality and quantity.
The relationship between menopause and CVD incidence was first examined in the Framingham cohort of 2873 women (Kannel, 1987). A trend showed a two- to sixfold higher incidence of CVD in postmenopausal women compared with premenopausal women in the same age range. Moreover, the increases in CVD associated with the MT are observed regardless of the age at menopause. These and other data indicate that withdrawal of estrogen may be associated with an increased CVD risk. Nonetheless, questions of whether estrogen deficiency accelerates development of CVD and whether menopausal hormone treatment can ameliorate CVD risk remain unanswered (Harman, 2014).
Cardiovascular Disease Prevention
CVD risk factors are the same for men and women and include nonmodifiable risk factors such as age and family history of CVD. Modifiable elements are hypertension, dyslipidemia, obesity, diabetes/glucose intolerance, smoking, poor diet, and lack of physical activity. Because most CVD risk factors are modifiable, significant reductions in cardiovascular morbidity and mortality rates are feasible. Since data question the widespread use of hormone treatment to avert this common problem, other strategies must be considered (Chap. 22). Modifying strategies are discussed fully in Chapter 1, and some are briefly summarized here.
Of these, physical activity and its cardiovascular benefits were studied in the Women’s Health Initiative (WHI). Manson and colleagues (2002) determined that walking or vigorous exercise reduced the risk of cardiovascular events in postmenopausal women regardless of their age, BMI, or ethnic background. As expected, a sedentary lifestyle correlated directly with an elevated risk for coronary events (McKechnie, 2001).
As another CVD risk factor, central fat distribution, also termed truncal obesity, in women correlates positively with increases in total cholesterol, triglyceride, and low-density lipoprotein (LDL) cholesterol levels, and negatively correlates with HDL levels (Haarbo, 1989). This atherogenic lipid profile associated with abdominal adiposity is at least partly mediated through interplay with insulin and estrogen. A strong correlation exists between the magnitude of the worsening in cardiovascular risk factors (lipid and lipoprotein changes, blood pressure, and insulin levels) and the amount of weight gained during MT (Wing, 1991).
Favorable lipoprotein profiles in young women are maintained in part by physiologic estrogen levels. Specifically, throughout adulthood HDL levels are approximately 10 mg/dL higher in women. Moreover, total cholesterol and LDL levels are lower in premenopausal women than in men (Jensen, 1990; Matthews, 1989). After menopause and with the subsequent declines in estrogen levels, this favorable effect on lipids is lost. HDL levels decrease and total cholesterol levels increase. After menopause, the risk of coronary heart disease doubles for women, and at approximately age 60, the atherogenic lipids reach levels higher than those in men. Despite these changes in atherogenic lipids following menopause, total cholesterol and LDL levels can be favorably reduced by dietary modifications, estrogen treatment, and lipid-lowering medications (Matthews, 1994).
Last, clotting parameters are known to changes with aging. Fibrinogen, plasminogen activator inhibitor-1, and factor VII levels increase and cause a relatively hypercoagulable state. This is thought to contribute to increases in CVD and cerebrovascular disease rates in older women. Aspirin is effective in the secondary prevention of CVD in both men and women (Antithrombotic Trialists’ Collaboration, 2002). However, as discussed in Chapter 1, aspirin is not recommended for primary prevention of heart disease in women younger than 65 unless individual health benefits are judged to outweigh risks. These counterbalancing risks primarily involve aspirin-related bleeding episodes such as hemorrhagic stroke and gastrointestinal bleeding (Lund, 2008).
Weight Gain and Fat Distribution
Weight gain is a common complaint among women during MT. With aging, a woman’s metabolism slows, reducing her caloric requirements. If eating and exercise habits are not altered, weight is gained (Matthews, 2001). Specifically, Espeland and associates (1997) characterized the weight and fat distribution of 875 women in the Postmenopausal Estrogen/Progestin Interventions (PEPI) trial and correlated the effects of lifestyle, clinical, and demographic factors. Women aged 45 to 54 years had significantly greater increases in weight and in hip circumference than those aged 55 to 65 years. These investigators reported that overall baseline physical activity and baseline leisure and work activities were strongly related to weight gain in the PEPI cohort. Women who reported more activity gained less weight than less active women.
Weight gain during this period is associated with fat deposition in the abdomen, increased amounts of visceral fat, and body fat redistribution (Kim, 2014). These raise the likelihood of developing insulin resistance and subsequent diabetes mellitus and heart disease (Dallman, 2004; Wing, 1991). This stems from associated alterations in cardiometabolic risks due to hormone-related declines in energy expenditure and fat oxidation (Jull, 2014). In addition, data from the Rosetta Study and the New Mexico Aging Process Study show that older adults have higher percentages of body fat than younger adults at any age due to muscle mass loss with aging (Baumgartner, 1995).
Numerous other factors underlie weight gain and include genetic factors, neuropeptides, and adrenergic nervous system activity (Milewicz, 1996). Although many women believe that noncontraceptive estrogen therapy causes weight gain, results from clinical trials and epidemiologic studies indicate that the effect of menopausal hormone therapy on body weight and girth, if any, is to blunt slightly the rate of age-related increases.
Lifestyle interventions to minimize gains in fat mass and changes in body composition and body fat distribution during MT predominantly include exercise and healthy nutrition. As discussed in Chapter 1, specific interventions include encouraging individuals to set realistic lifestyle goals, referral to weight loss programs, pharmacotherapy, or surgical interventions (Jull, 2014). Women exposed to a program of combined exercise and calorie-restricting dietary interventions for 54 weeks had improved body weight and reduced abdominal adiposity compared with usual activities in the control group (Simkin-Silverman, 2007). As well, significant reductions in waist circumference and body fat were maintained beyond 4 years. Hagner and coworkers (2009) found that a Nordic walking program reduced weight gain during MT.
Skin changes that may develop during MT include hyperpigmentation (age spots), wrinkles, and itching. These are caused in part by skin aging, which results from the synergistic effects of intrinsic aging and photo-aging (Guinot, 2005). Hormonal aging of the skin is also thought to be responsible for many dermal changes. These include a reduced thickness due to lower collagen content, diminished sebaceous gland secretion, loss of elasticity, and decreased blood supply (Wines, 2001). Although the effect of hormone deficiency on skin aging has been widely studied, distinguishing its contribution from those of intrinsic aging, photo-aging, and other environmental insults is difficult.
Dental problems may also develop as estrogen levels wane in late MT. The buccal epithelium atrophies due to estrogen deprivation, resulting in decreased saliva and sensation. A bad taste in the mouth, increased incidence of cavities, and tooth loss also may occur (Krall, 1994). Oral alveolar bone loss is strongly positively correlated with osteoporosis and can lead to tooth loss. Even in women without osteoporosis, vertebral BMD correlates positively with the number of teeth. In turn, the beneficial effect of estrogen on skeletal bone mass is also manifested in oral bone.
The breast undergoes change during MT mainly because of hormonal withdrawal. In premenopausal women, estrogen and progesterone exert proliferative effects on ductal and glandular structures, respectively. At menopause, withdrawal of estrogen and progesterone leads to a relative reduction in breast proliferation. A significant reduction in the volume and tissue density is seen during mammography as these areas become replaced with adipose tissue. Mammography is advisable for women older than age 40, and breast imaging is fully discussed in Chapter 12.
Sleep Dysfunction and Fatigue
Sleep quality declines with age, but the menopausal transition appears to contribute to this decline in women. Women may wake several times during the night and may be drenched in sweat. The relationship between hot flushes and impaired sleep has been studied. Hollander and associates (2001) studied late reproductive-aged women and found that women with a greater incidence of hot flushes were more likely to report poor sleep than were women with fewer vasomotor symptoms. Self-reported poor sleep rates increase as women traverse MT, and it was reported in 38 percent of the 12,603 women who participated in the cross-sectional survey of the SWAN Study (Hall, 2009). As with most menopausal symptoms, severity and prevalence seem to peak during late MT, when women have prolonged amenorrhea.
Even women with few vasomotor symptoms may experience insomnia and associated menopause-related mood symptoms (Erlik, 1982; Woodward, 1994). As women age, they are more likely to experience lighter sleep and are awakened more easily by pain, sound, or bodily urges. Health issues and other chronic conditions experienced by women or by their spouse or bedmate are likely to further disrupt sleep. Arthritis, carpal tunnel syndrome, chronic lung disease, heartburn, and certain medications that are known to disrupt sleep may dramatically lower the quality and quantity of restful sleep. Nocturia, urinary frequency, and urgency, all of which are more common in menopausal women, are other notable factors.
Sleep disordered breathing (SDB), which includes various degrees of pharyngeal obstruction, is much more common in menopausal women and their mates. In women, SDB is often associated with increased BMI and declining estrogen and progesterone levels. Loud snoring can follow partial upper airway obstruction that ranges in severity from upper airway resistance to obstructive sleep apnea (Gislason, 1993).
Disturbed sleep can lead to fatigue, irritability, depressive symptoms, cognitive dysfunction, and impaired daily functioning. Commonsense education for patients during MT may prove valuable (Table 21-8). Importantly, although fatigue may stem from night sweats and poor sleep, other common potential etiologies, such as anemia or thyroid disease, among others, are also considered. In all these examples, treatment of underlying health conditions is the main focus to improve patient sleep. At times, short-term use of pharmacologic sleep aids is indicated, and these are listed in Table 1-16.
TABLE 21-8Fatigue Prevention Instructions ||Download (.pdf) TABLE 21-8 Fatigue Prevention Instructions
|Obtain adequate sleep every night |
Exercise regularly to reduce stress
Avoid long work hours and maintain your personal schedule
If stress is environmental, take vacations, switch jobs, or approach your company or family to help resolve sources of stress
Limit intake of alcohol, drugs, and nicotine
Eat a healthy, well-balanced diet
Drink adequate amounts water (8 to 10 glasses) during the early part of the day
Consider seeing a specialist in menopausal medicine
Memory declines with advancing age. Although no direct effect of lowered estrogen levels on memory and cognition has been determined, many investigators suspect a relationship between the two. Cognitive functioning was assessed in a cohort study of reproductive-aged and postmenopausal women not using hormone replacement therapy. In postmenopausal patients, cognitive performance declined with advancing age. This was not the case for reproductive-aged women. Premenopausal women in their 40s were less likely to exhibit cognitive decline compared with postmenopausal patients in the same decade of life. These researchers concluded that deterioration of some forms of cognitive function is accelerated after menopause (Halbreich, 1995).
In another study, Henderson and coworkers (2013) studied 643 healthy postmenopausal women not using hormone therapy who were recruited as early (<6 years after menopause) and late (>10 years after menopause) groups. Women were administered a comprehensive neuropsychological battery. Concurrently, serum free estradiol, estrone, progesterone, free testosterone, and SHBG levels were measured. Cognitive outcomes were standardized composite measures of verbal memory, executive functions, and global cognition. Endogenous sex steroid levels were unassociated with cognitive composites, but SHBG levels were positively associated with verbal memory. Results for early and late groups did not differ significantly, although progesterone concentrations were significantly positively associated with verbal memory and global cognition in early group women. Hormone levels were not significantly related to mood.
Factors accelerating cerebral degenerative changes represent potentially modifiable risks for cognitive decline (Kuller, 2003; Meyer, 1999). Investigators have studied putative risk factors and have correlated them with measures of cerebral atrophy, computed tomography (CT) densitometry, and cognitive testing among neurologically and cognitively normal, aging volunteers. Risk factors for decreased cerebral perfusion and thinning of gray and white matter densities include prior transient ischemic attacks (TIAs), hyperlipidemia, hypertension, smoking, excess alcohol consumption, and male gender, which would imply lack of estrogen. The authors encourage interventions to modify many of these risks.
Women have long been recognized as carrying a higher lifetime risk of developing depression than men. The World Health Organization has consistently ranked depression as a leading cause of disability in women. The risk of developing a major depressive disorder is 1.5 to 1.7 times higher in women than in men, particularly during reproductive years. A prior depressive episode (particularly if related to reproductive events) remains the strongest predictor of mood symptoms or depression during midlife. Vasomotor symptoms, anxiety, and other health-related issues also modulate depression risks (Soares, 2014).
Contemporary findings have dispelled myths that natural menopause itself is associated with depressed mood (Ballinger, 1990; Busch, 1994). However, an increased risk of depressive symptoms during MT has been repeatedly observed in population-based studies. In the Penn Ovarian Aging Study, the risk was nearly three times higher in women in MT compared with premenopausal women. Moreover, women with no history of depression were two and a half times more likely to report depressed mood during MT than during the premenopausal period (Freeman, 2004). Other cohort studies report similar findings (Bromberger, 2011; Cohen, 2006; Dennerstein, 2004; Woods, 2008). Moreover, there are a high percentage of subjects with recurrent depression during MT (Freeman, 2007). Thus, a screen for depression is prudent for women in this transition, and tools are described in Chapter 13.
It has been suggested that the hormonal fluctuations during early MT are responsible, in part, for this affective instability. Similarly, surgical menopause induces mood changes because of the rapid hormonal loss at this time. Soares (2005) hypothesizes that a major component of the reported emotional distress during MT may be causally related to high and erratic estradiol levels. For example, Ballinger and colleagues (1990) showed that increases in stress hormones (and probably symptoms that are stress related) are physiologically linked with high estrogen levels. They also reported that women with abnormal psychometric test scores early after menopause had higher estradiol levels than women with lower scores. Spinelli and associates (2005) showed that estrogen levels are correlated with the intensity of menopausal symptoms. A randomized, placebo-controlled menopause treatment study evaluated administered standard doses of conjugated equine estrogen (0.625 mg/d), which significantly improved sleep, but also showed an estrogen-related increase of inward-directed hostility (Schiff, 1980).
Importantly, the MT is a complex sociocultural as well as a hormonal event, and psychosocial factors may contribute to mood and cognitive symptoms. For example, women entering MT may face emotional stress from onset of a major illness, caring for an adolescent or aging parent, divorce or widowhood, and career change or retirement (LeBoeuf, 1996). Lock (1991) suggests that part of the stress reported by Western women is clearly culture-specific. Western culture emphasizes beauty and youth, and as women grow older, some suffer from a perceived loss of status, function, and control (LeBoeuf, 1996). However, the end of predictable menstruation and the end of fertility may be significant to a woman simply because it is a change, no matter how aging and the end of reproductive life are viewed by that woman and by her culture (Frackiewicz, 2000). For some women, the approach of menopause may also be perceived as a significant loss, both to women who have accepted childbearing and rearing as their major life roles and those who are childless, perhaps not by choice. For these reasons, impending menopause may be perceived as a time of loss, when depression and other psychological disorders may develop (Avis, 2000).
Although the relationship between circulating hormones and libido has been extensively investigated, definitive data are lacking. Many studies demonstrate that other factors besides menopause may account for libido changes (Gracia, 2007). Avis and associates (2000) studied sexual function in a subgroup of 200 women in the Massachusetts Women’s Health Study II who underwent natural menopause. None took hormone treatment, and all these women had sexual partners. Menopausal status was observed to be significantly related to decreased sexual interest. However, after adjustment for physical and mental health, smoking, and marital satisfaction, menopausal status no longer had a significant relationship to libido. Dennerstein (2005) prospectively evaluated 438 Australian women during 6 years of their menopausal transition. Menopause was significantly associated with dyspareunia and indirectly with sexual response. Feelings for one’s partner, stress, and other social factors also indirectly affected sexual functioning.
Other investigators have demonstrated that sexual problems are more prevalent after menopause. A longitudinal study of women during MT until at least 1 year after the final menstrual period demonstrated a significant decrease in the rate of weekly coitus. Patients reported a significant decline in the number of sexual thoughts, sexual satisfactions, and vaginal lubrication after becoming menopausal (McCoy, 1985). In a study of 100 naturally menopausal women, both sexual desire and activity decreased compared with that during the premenopausal period. Women reported loss of libido, dyspareunia, and orgasmic dysfunction, with 86 percent reporting no orgasms after menopause (Tungphaisal, 1991).
Lower Reproductive Tract Changes
Estrogen receptors have been identified in the vulva, vagina, bladder, urethra, pelvic floor musculature, and endopelvic tissues. These structures thus share a similar hormonal responsiveness and are susceptible to estrogen deprivation. To reflect this common link, the International Society for the Study of Women’s Sexual Health (ISSWSH) and The North American Menopause Society adopted the term genitourinary syndrome of menopause (GSM) to encompass the constellation of signs and symptoms that affect the genitourinary system after menopause (Table 21-9). As such, GSM is a syndrome that may include genital symptoms of dryness, burning, and irritation; sexual symptoms of absent lubrication, dyspareunia, and dysfunction; and urinary symptoms of urgency, dysuria, and recurrent urinary tract infections (UTIs) (Portman, 2014).
TABLE 21-9Genitourinary Syndrome of Menopause Characteristics ||Download (.pdf) TABLE 21-9 Genitourinary Syndrome of Menopause Characteristics
|Symptoms ||Signs |
|Genital dryness ||Labia minora resorption |
|Poor lubrication ||Narrowed introitus |
|Dyspareunia ||Absent hymenal tags |
|Postcoital bleeding ||Tissue pallor or erythema |
|Poor arousal, orgasm, desire ||Urethral eversion |
|Vulvovaginal: ||Urethral prolapse |
| irritation, burning, itching ||Prominent urethral meatus |
|Dysuria ||Recurrent UTI |
|Urinary frequency ||Absent rugae |
|Urinary urgency ||Fragile or fissured tissue |
| ||Petechial hemorrhages |
| ||Scant vaginal secretions |
| ||Poor elasticity |
Without estrogen’s trophic influence, the vagina loses collagen, adipose tissue, and ability to retain water (Sarrel, 2000). As vaginal walls shrink, rugae flatten, and the vagina attains a smooth-walled, pale-pink appearance. The surface epithelium thins to only a few cell layers. This markedly reduces the ratio of superficial to basal cells, described on page 489. Moreover, the thin vaginal surface is friable and prone to submucosal petechial hemorrhages or bleeding with minimal trauma. The blood vessels in the vaginal walls narrow, and over time the vagina itself contracts and loses flexibility.
In addition, vaginal pH becomes more alkaline and a pH greater than 4.5 is typically observed with estrogen deficiency (Caillouette, 1997; Roy, 2004). An alkaline pH creates a vaginal environment less hospitable to lactobacilli and more susceptible to infection by urogenital and fecal pathogens. Hoffmann and colleagues (2014) found that the prevalence of bacterial vaginosis ranged from 23 to 38 percent in postmenopausal women, and rates increased with age. In contrast, Candida species were noted in 5 to 6 percent of these same women, and rates declined with aging.
In addition to vaginal changes, the vulvar epithelium gradually atrophies and secretions from sebaceous glands diminish. Subcutaneous fat in the labia majora is lost, which leads to shrinkage and retraction of clitoral prepuce and the urethra, fusion of the labia minora, and introital narrowing and then stenosis (Mehta, 2008).
Symptoms of vulvovaginal atrophy include vaginal dryness, itching, irritation, and dyspareunia. These are common complaints during MT, and prevalence estimates range from 10 to 50 percent (Levine, 2008). Treatment options include topical or systemic estrogen, SERMs, and vaginal moisturizers, which are all discussed in Chapter 22.
Dyspareunia and Sexual Dysfunction
Menopausal patients often note dyspareunia and other forms of sexual dysfunction. In one study, 25 percent of postmenopausal women noted some degree of dyspareunia (Laumann, 1999). These same investigators found that painful intercourse correlated with sexual problems, including lack of libido, arousal disorder, and anorgasmia. Although dyspareunia in this population is generally attributed to vaginal dryness and mucosal atrophy secondary estrogen deficiency, prevalence studies suggest that a decrement in all aspects of female sexual function is associated with midlife (Dennerstein, 2005).
Levine and associates (2008) studied 1480 sexually active postmenopausal women and found that the prevalence of vulvovaginal atrophy and of female sexual dysfunction each approximated 55 percent. They found that women with female sexual dysfunction were 3.84 times more likely to have vulvovaginal atrophy than women without such dysfunction. Estrogen deficiency diminishes vaginal lubrication, blood flow, and vasocongestion with sexual activity. These changes are coupled with the structural atrophy described in that last section. Reduced testosterone levels have been implicated in genital atrophy as well, but the relationship between testosterone and sexuality during MT remains obscure. Circulating testosterone levels decline gradually with age from the mid-reproductive years and have dropped by 50 percent by age 45. Paradoxically, studies have been unable to demonstrate that sexual dysfunction is related to decreased androgen levels in MT (O’Neil, 2011).
Urogenital conditions such as prolapse or incontinence correlate strongly with sexual dysfunction (Barber, 2002; Salonia, 2004). Patients with urinary incontinence are likely to have pelvic-floor hypotonus dysfunction, which may cause pain on deep penetration due to pelvic support instability. Hypertonic or dyssynergic pelvic-floor muscles, which are commonly seen in patients with urinary frequency, constipation, and vaginismus, are often associated with superficial pain and friction during intercourse (Handa, 2004). The presence of organ prolapse contributes to dyspareunia, as does a history of a gynecologic surgical procedure that may cause dyspareunia by shortening the vagina (Goldberg, 2001).
Menopause is also a time of life when significant psychosocial and physiological changes occur simultaneously, and concomitant illnesses arise. It is understandable that such major life changes influence sexual functioning. In the longitudinal Melbourne Midlife Study, Dennerstein and associates (1993) confirmed a significant decline in sexual functioning during MT. Sexual responsivity, libido, sexual frequency, positive feelings for a partner, and a partners’ sexual performance all typically decreased, and vaginal dyspareunia rates typically increased. Other medical conditions such as arthritis, hip or lumbar joint pain, or fibromyalgia may contribute to vaginal or pelvic pain with intercourse. Pain may be due to radiation of pain from trigger points in the trunk, buttocks, or pelvic-floor muscles, or from possible pudendal nerve entrapment. Chronic pelvic pain may also contribute to sexual dysfunction as discussed in Chapter 11.
As part of GSM, urinary symptoms can include dysuria, urgency, urethral eversion or prolapse, and recurrent UTIs (Portman, 2014: Trutnovsky, 2014). Specifically, thinning of urethral and bladder mucosa underlie these. For these complaints, vaginal estrogen, discussed in Chapter 22, is a reasonable first option (Rahn, 2014).
The association between declining estrogen levels and incontinence is more controversial. In support of a causal link, urethral shortening associated with menopausal atrophic changes may result in genuine stress urinary incontinence. For example, Bhatia and colleagues (1989) showed that estrogen therapy may improve or cure stress urinary incontinence in more than 50 percent of treated women, presumably by exerting a direct effect on urethral mucosa coaptation (Chap. 23). Accordingly, a trial of hormone therapy may be considered in select patients prior to surgical correction of incontinence in women with vaginal atrophy.
That said, Waetjen and coworkers (2009) evaluated women in MT and found a slight increase in stress and urge incontinence. They did find, however, a more robust association with worsening anxiety symptoms, a high baseline BMI, weight gain, and new-onset diabetes. Their conclusion was that from a public health stand point, clinicians and women should focus first on these modifiable risk factors. Other studies have also failed to find links between incontinence and menopausal status. Sherburn and colleagues (2001) performed a cross-sectional study of Australian women aged 45 to 55 years. In this population, they identified a 15-percent prevalence of incontinence. Associated risk factors included gynecologic surgery, higher BMI, UTIs, constipation, and multiparity. Subsequently, these investigators studied a subset of 373 premenopausal females to determine if MT itself was associated with an increased incidence of incontinence. In this group of women, the overall incidence was 35 percent, with no increase associated with menopause. Incontinence was most closely related to hysterectomy. More recently, Trutnovsky and associates (2014) explored the effects of menopause and hormone therapy both on stress and urge urinary incontinence. In the 382 women evaluated, the length of menopause showed no significant relationship with urinary incontinence.
In addition to incontinence, pelvic organ prolapse rates increase with advancing age. Importantly, vaginal relaxation with anterior wall, posterior wall, or apical prolapse is not a direct consequence of estrogen deprivation, as many factors play a role in pelvic floor relaxation (Chap. 24).