Menopause: The Journal of The North American Menopause Society Vol. 15, No. 5, p. 1027-1029 DOI: 10.1097/gme.0b013e3181846cb6 * 2008 by The North American Menopause Society
LETTERS
TO THE
EDITOR
To the Editor: The article by Thurston et al1 on the association of abdominal adiposity and hot flashes among midlife has raised my severe concern. As we all know, body weight is closely related to the development of hypertension in middle-aged women.2 Before the age of 60 years, 30% to 50% of all women already have hypertension.3 Recent studies also indicate that hot flash symptoms are associated with higher blood pressure values.4 Therefore, I wonder whether further data from the Study of Women’s Health Across the Nation have any clinical value as long as blood pressure measurements are not included in the analyses. Angela H. E. M. Maas, MD, PhD Department of Cardiology Outpatient Women’s Clinic Isala Klinieken Zwolle, The Netherlands REFERENCES 1. Thurston RC, Sowers MR, Sutton-Tyrrell K, et al. Abdominal adiposity and hot flashes among midlife women. Menopause 2008;15:429-434. 2. Zanchetti A, Facchetti R, Casena GC, et al. Menopause-related blood pressure increase and its relationship to age and body mass index: the SIMONA epidemiological study. J Hypertens 2005;23:2269-2276. 3. Burt VL, Whelton P, Roccella EJ, et al. Prevalence of hypertension in the US adult population. Results from the Third National Health and Nutrition Examination Survey 1988-1991. Hypertension 1995;25: 305-313. 4. Gerber LM, Sievert LL, Warren K, et al. Hot flashes are associated with increased ambulatory blood pressure. Menopause 2007;14:308-315.
In Reply: We thank both Drs Maas and Reame1 for their commentaries on our recent publication Abdominal adiposity and hot flashes among midlife women.2 They provide a thoughtful analysis and raise several important questions. Dr Maas notes the (albeit inconsistent3,4) links between hot flashes and elevated blood pressure in previous research and questions whether differences in blood pressure may account for our observed associations between abdominal adiposity and hot flashes. In these Study of Women’s Health Across the Nation (SWAN) Heart participants, after accounting for age, neither systolic blood pressure nor diastolic blood pressure was significantly associated with hot flashes (P’s 9 0.25). Moreover, controlling for systolic blood pressure and diastolic blood pressure in multivariable models with other covariates did not reduce observed associations between abdominal adiposity and hot flashes (total adiposity: odds ratio = 1.26, 95% CI: 1.02-1.57, P = 0.04; subcutaneous adiposity: odds ratio = 1.28, 95% CI: 1.03-1.60, P = 0.03). Dr Reame observes that the relative distribution of visceral adipose tissue (VAT) versus subcutaneous adipose tissue
(SAT) varied between the African American and white women in SWAN Heart, with proportionately more SAT versus VAT among the African American women. She notes that VAT is the more metabolically active type of fat and is more strongly associated with risks such as diabetes than SAT (although not all SAT is so metabolically benign5). She indicates that we are silent on the paradox of these racial/ethnic differences in fat distribution, given that African American women are at increased risk for diseases such as diabetes. This is clearly an important issue. Given the focus of our publication on hot flashes, addressing racial/ethnic differences in fat distribution and metabolic risk was beyond the scope of our report. However, African American women are more likely to report hot flashes than white women.6 African American women also have proportionately more SAT than white women, which is most strongly related to hot flashes.2 We did not report but did examine whether racial differences in hot flashes were accounted for by these racial differences in fat distribution. We found that the differences in hot flashes between African American and white women were reduced by only 17% when accounting for differences in SAT. Racial differences in hot flashes may have a biological component, although the etiology of racial/ethnic health disparities is multifactorial, driven not only by biological differences but also by pronounced differences in social and economic conditions between groups.7 Although not the focus of our publication, better understanding of these racial/ ethnic differences is an important area for future research. Dr Reame also points out that VAT is more easily lost with behavioral interventions than SAT. Preferential loss of VAT may be the case with modest or initial weight loss. Whether these losses impact hot flashes remains to be seen. However, considering women’s health more broadly, with a majority of American adults being overweight or obese8 and the substantial health risk being associated with obesity, weight loss is clearly indicated for many. The Study of Women’s Health Across the Nation has taught us that women progressively gain weight,9 particularly fat,10 over midlife. Given that postmenopause is a time of heightened cardiovascular risk, minimizing gains is important. Appropriately designed behavioral interventions are effective in achieving at least modest weight loss that can impact key metabolic parameters.11 Maintaining these losses, as well as weight over time, is the challenge. Dr Reame cites our findings as Bone more tree in the forest,[ calling for a comprehensive model to integrate the diverse findings on hot flashes (from SWAN and elsewhere) and to guide future research. In short, we need a model to help us see the Bforest,[ rather than simply to describe one more tree. Such a model is important given the incomplete understanding of hot flashes etiology and dearth of effective and Menopause, Vol. 15, No. 5, 2008
Copyright @ 2008 The North American Menopause Society. Unauthorized reproduction of this article is prohibited.
1027
LETTERS TO THE EDITOR
Rebecca C. Thurston, PhD Karen A. Matthews, PhD Department of Psychiatry University of Pittsburgh School of Medicine and Department of Epidemiology University of Pittsburgh Graduate School of Public Health Pittsburgh, PA FIG. 1. Biopsychosocial model of hot flashes.
widely accepted nonhormonal methods to manage hot flashes. We believe that the most appropriate model is a biopsychosocial one. As we present in Figure 1, biological, behavioral, psychological, and social factors, interacting over time, all influence the occurrence and reporting of hot flashes. For example, there are clearly biological correlates of hot flashes, with the most well-elucidated biological model being a thermoregulatory one. According to this model, hot flashes represent heat dissipation events occurring in the context of altered thermoregulatory functioning of women transitioning through menopause.12 There are also multiple other biological correlates of hot flashes, including (but not limited to) estrogen metabolism genetic polymorphisms,13 increases in follicular stimulating hormone and decreases in estradiol occurring during menopause,14 and changes in neurotransmitters such as norepinepherine15 and possibly serotonin.16 However, behavioral, psychological, and social influences on hot flashes cannot be ignored. For example, smoking is a well-known risk factor related to hot flashes,6 and obesity, now identified as a risk factor for hot flashes,2,6,17 clearly has a behavioral contribution.11 Furthermore, anxiety, even when assessed years before hot flashes, is a consistent predictor of hot flashes.6 Negative affect may be quite important to consider in the reporting or the perceived bother18 associated with hot flashes, particularly hot flashes reported but not detected physiologically.19 Finally, key social factors are related to hot flashes. Low socioeconomic status is a robust and consistent predictor of hot flashes,6 and socioeconomic status is known to be related to many of the behavioral and psychological risk factors detailed above. Notably, in a recent report in Menopause, we show that women exposed to childhood abuse or neglect were more likely to report hot flashes during the menopausal transition, an association persisting with adjustment for multiple confounding factors.20 Thus, the predictors of hot flashes are multiple, including physiological as well as social and psychological factors. Although yet to be fully elucidated, these factors likely operate in part through each other to impact health. Such a model implies that there may be multiple points of intervention to reduce hot flashes and improve the quality of life of midlife women. We hope that this model, as it is further elucidated, can provide a path through the forest, helping to guide and integrate future research on the etiology and treatment of menopausal hot flashes.
1028
Menopause, Vol. 15, No. 5, 2008
Susan A. Everson Rose, PhD, MPH Department of Medicine Program in Health Disparities Research University of Minnesota School of Medicine Minneapolis, MN REFERENCES 1. Reame NK. Adiposity and hot flashes: one more tree in the forest. Menopause 2008;15:408-409. 2. Thurston RC, Sowers MR, Sutton-Tyrrell K, et al. Abdominal adiposity and hot flashes among midlife women. Menopause 2008;15:429-434. 3. James GD, Sievert LL, Flanagan E. Ambulatory blood pressure and heart rate in relation to hot flash experience among women of menopausal age. Ann Hum Biol 2004;31:49-58. 4. Low DA, Davis SL, Keller DM, Shibasaki M, Crandall CG. Cutaneous and hemodynamic responses during hot flashes in symptomatic postmenopausal women. Menopause 2008;15:290-295. 5. Kelley DE, Thaete FL, Troost F, Huwe T, Goodpaster BH. Subdivisions of subcutaneous abdominal adipose tissue and insulin resistance. Am J Physiol Endocrinol Metab 2000;278:E941-E948. 6. Gold E, Colvin A, Avis N, et al. Longitudinal analysis of vasomotor symptoms and race/ethnicity across the menopausal transition: Study of Women’s Health Across the Nation (SWAN). Am J Public Health 2006;96:1226-1235. 7. Williams DR, Collins C. US socioeconomic and racial differences in health: patterns and explanations. Annu Rev Sociol 1995;21:349-386. 8. Flegal KM, Carroll MD, Ogden CL, Johnson CL. Prevalence and trends in obesity among US adults, 1999-2000. JAMA 2002;288:1723-1727. 9. Sternfeld B, Wang H, Quesenberry CP Jr, et al. Physical activity and changes in weight and waist circumference in midlife women: findings from the Study of Women’s Health Across the Nation. Am J Epidemiol 2004;160:912-922. 10. Sowers M, Zheng H, Tomey K, et al. Changes in body composition in women over six years at midlife: ovarian and chronological aging. J Clin Endocrinol Metab 2007;92:895-901. 11. National Institutes of Health National Heart Lung and Blood Institute, ed. Clinical guidelines on the identification, evaluation, and treatment of overweight and obesity in adults: the evidence report. Bethesda, MD: National Institutes of Health National Heart Lung and Blood Institute, 1998. 12. Freedman RR. Pathophysiology and treatment of menopausal hot flashes. Semin Reprod Med 2005;23:117-125. 13. Crandall CJ, Crawford SL, Gold EB. Vasomotor symptom prevalence is associated with polymorphisms in sex steroid-metabolizing enzymes and receptors. Am J Med 2006;119:S52-S60. 14. Randolph JF Jr, Sowers M, Bondarenko I, et al. The relationship of longitudinal change in reproductive hormones and vasomotor symptoms during the menopausal transition. J Clin Endocrinol Metab 2005; 90:6106-6112. 15. Freedman RR, Woodward S, Sabharwal SC. Alpha 2-adrenergic mechanism in menopausal hot flushes. Obstet Gynecol 1990;76:573-578. 16. Stearns V, Beebe KL, Iyengar M, Dube E. Paroxetine controlled release in the treatment of menopausal hot flashes: a randomized controlled trial. JAMA 2003;289:2827-2834. 17. Thurston RC, Sowers MR, Chang Y, et al. Adiposity and reporting of vasomotor symptoms among midlife women: the study of women’s health across the nation. Am J Epidemiol 2008;167:78-85. 18. Thurston R, Bromberger J, Joffe H, et al. Beyond frequency: who is most bothered by vasomotor symptoms? Menopause 2008;15:841-847. 19. Thurston RC, Blumenthal JA, Babyak MA, Sherwood A. Emotional antecedents of hot flashes during daily life. Psychosom Med 2005; 67:137-146. 20. Thurston RC, Bromberger J, Chang Y, et al. Childhood abuse or neglect is associated with increased vasomotor symptom reporting among midlife women. Menopause 2008;15:16-22. * 2008 by The North American Menopause Society
Copyright @ 2008 The North American Menopause Society. Unauthorized reproduction of this article is prohibited.
LETTERS TO THE EDITOR
To the Editor: I am surprised at the poor science and the disregard for the Health Belief Model, a well-recognized public health behavior theory, in the recent articleVBair YA, Gold EB, Zhang G, et al. Use of complementary and alternative medicine during the menopause transition: longitudinal results from the Study of Women’s Health Across the Nation. Menopause. 2008;15(1):32Y43. In their article, Bair et al demonstrate very poor methodology in selecting their study population and thus introduce multiple dissimilarities and potential confounding variables. Each ethnic group is recruited from a different part of the country, thus introducing geographical disparities in terms of town/city culture, access to and availability of complementary and alternative medicine (CAM), and representativeness of the chosen ethnic group to members of that group in other parts of the country. Los Angeles and Pittsburgh, for example, engender different liberal traditions, health attitudes, and ready access to and availability of CAM. The ethnic groups in the study also differed by educational levels, which is a particularly significant confounding variable, as education often plays a huge role in shaping values and health beliefs. Finally, Bair et al. give little regard to the elements of the Health Belief Model, which is central to public health behavior analysis. Health Belief Model proposes that people are motivated to take a health action based on perceived susceptibility, perceived severity, perceived benefit, perceived barriers, cues to action, and self-efficacy (ie, confidence in their ability to change/engage in a health behavior). The authors did well to discuss the external, or social and environmental, factors that might have affected their participants’ health choices, such as social support and health insurance. But they neglected to investigate interethnic motivations for seeking CAM, an important dimension of any health behavior study. They acknowledge this and allude to Bcultural differences[ in access to and perception of CAM, but this is not enough. Ashorkor Tetteh, BA Department of Epidemiology The George Washington University School of Public Health and Health Services Washington, DC
In Reply: We appreciate the opportunity to respond to Ms Tetteh’s letter pointing out her concerns with our recently published study, BThe use of complementary and alternative medicine
during the menopause transition: Longitudinal results from the Study of Women’s Health Across the Nation.[ The first concern raised was Bvery poor methodology[ in selecting the study sample relating to the selection of ethnic groups from different regions of the country. As we explained in our paper, the Study of Women’s Health Across the Nation is a community-based, longitudinal observational study. The oversampling of ethnic groups at individual study sites is a study design that is often used to ensure adequate sample sizes for comparisons among ethnic groups. Furthermore, in all of our comparisons, we adjusted for geographic location to account for those differences that might be introduced by study site, rather than other factors of interest. The second concern was that our study did not consider the Health Belief Model for evaluating health behavior. Although it is reasonable that the Health Belief Model may have utility in the study of complementary and alternative medicine (CAM), it is but one of several health behavior models currently used in the study of conventional health behaviors, and its application to CAM has yet to be evaluated. SWAN is a longitudinal study of the natural progression of menopause in a community-based cohort. As such, evaluating factors related to use of CAM was not the primary objective of the study. Although it would be very interesting and informative to conduct an in-depth study of CAM use during the menopause transition using a health behavior or healthcare-seeking model as a framework, this study was not meant to be such an in-depth investigation. Our study serves as a preliminary look at factors associated with women’s use of CAM during menopause, within the framework of a longitudinal observational study of the many factors involved in the menopause transition. The factors that we find suggestive of cultural or behavioral differences in CAM use certainly merit further investigation. In the interim, our study is potentially informative to the clinical community because it highlights the pervasiveness of CAM use and the potentially significant cultural differences in women’s approaches to menopause and general health management. Yali A. Bair, PhD Ellen B. Gold, PhD Gail Greendale, MD Dawn Upchurch, PhD Jessica Utts, PhD Guili Zhang, PhD University of California, Davis Davis, CA
Menopause, Vol. 15, No. 5, 2008
Copyright @ 2008 The North American Menopause Society. Unauthorized reproduction of this article is prohibited.
1029
LETTERS
TO THE
EDITOR
To the Editor: The article by Thurston et al1 on the association of abdominal adiposity and hot flashes among midlife has raised my severe concern. As we all know, body weight is closely related to the development of hypertension in middle-aged women.2 Before the age of 60 years, 30% to 50% of all women already have hypertension.3 Recent studies also indicate that hot flash symptoms are associated with higher blood pressure values.4 Therefore, I wonder whether further data from the Study of Women’s Health Across the Nation have any clinical value as long as blood pressure measurements are not included in the analyses. Angela H. E. M. Maas, MD, PhD Department of Cardiology Outpatient Women’s Clinic Isala Klinieken Zwolle, The Netherlands REFERENCES 1. Thurston RC, Sowers MR, Sutton-Tyrrell K, et al. Abdominal adiposity and hot flashes among midlife women. Menopause 2008;15:429-434. 2. Zanchetti A, Facchetti R, Casena GC, et al. Menopause-related blood pressure increase and its relationship to age and body mass index: the SIMONA epidemiological study. J Hypertens 2005;23:2269-2276. 3. Burt VL, Whelton P, Roccella EJ, et al. Prevalence of hypertension in the US adult population. Results from the Third National Health and Nutrition Examination Survey 1988-1991. Hypertension 1995;25: 305-313. 4. Gerber LM, Sievert LL, Warren K, et al. Hot flashes are associated with increased ambulatory blood pressure. Menopause 2007;14:308-315.
In Reply: We thank both Drs Maas and Reame1 for their commentaries on our recent publication Abdominal adiposity and hot flashes among midlife women.2 They provide a thoughtful analysis and raise several important questions. Dr Maas notes the (albeit inconsistent3,4) links between hot flashes and elevated blood pressure in previous research and questions whether differences in blood pressure may account for our observed associations between abdominal adiposity and hot flashes. In these Study of Women’s Health Across the Nation (SWAN) Heart participants, after accounting for age, neither systolic blood pressure nor diastolic blood pressure was significantly associated with hot flashes (P’s 9 0.25). Moreover, controlling for systolic blood pressure and diastolic blood pressure in multivariable models with other covariates did not reduce observed associations between abdominal adiposity and hot flashes (total adiposity: odds ratio = 1.26, 95% CI: 1.02-1.57, P = 0.04; subcutaneous adiposity: odds ratio = 1.28, 95% CI: 1.03-1.60, P = 0.03). Dr Reame observes that the relative distribution of visceral adipose tissue (VAT) versus subcutaneous adipose tissue
(SAT) varied between the African American and white women in SWAN Heart, with proportionately more SAT versus VAT among the African American women. She notes that VAT is the more metabolically active type of fat and is more strongly associated with risks such as diabetes than SAT (although not all SAT is so metabolically benign5). She indicates that we are silent on the paradox of these racial/ethnic differences in fat distribution, given that African American women are at increased risk for diseases such as diabetes. This is clearly an important issue. Given the focus of our publication on hot flashes, addressing racial/ethnic differences in fat distribution and metabolic risk was beyond the scope of our report. However, African American women are more likely to report hot flashes than white women.6 African American women also have proportionately more SAT than white women, which is most strongly related to hot flashes.2 We did not report but did examine whether racial differences in hot flashes were accounted for by these racial differences in fat distribution. We found that the differences in hot flashes between African American and white women were reduced by only 17% when accounting for differences in SAT. Racial differences in hot flashes may have a biological component, although the etiology of racial/ethnic health disparities is multifactorial, driven not only by biological differences but also by pronounced differences in social and economic conditions between groups.7 Although not the focus of our publication, better understanding of these racial/ ethnic differences is an important area for future research. Dr Reame also points out that VAT is more easily lost with behavioral interventions than SAT. Preferential loss of VAT may be the case with modest or initial weight loss. Whether these losses impact hot flashes remains to be seen. However, considering women’s health more broadly, with a majority of American adults being overweight or obese8 and the substantial health risk being associated with obesity, weight loss is clearly indicated for many. The Study of Women’s Health Across the Nation has taught us that women progressively gain weight,9 particularly fat,10 over midlife. Given that postmenopause is a time of heightened cardiovascular risk, minimizing gains is important. Appropriately designed behavioral interventions are effective in achieving at least modest weight loss that can impact key metabolic parameters.11 Maintaining these losses, as well as weight over time, is the challenge. Dr Reame cites our findings as Bone more tree in the forest,[ calling for a comprehensive model to integrate the diverse findings on hot flashes (from SWAN and elsewhere) and to guide future research. In short, we need a model to help us see the Bforest,[ rather than simply to describe one more tree. Such a model is important given the incomplete understanding of hot flashes etiology and dearth of effective and Menopause, Vol. 15, No. 5, 2008
Copyright @ 2008 The North American Menopause Society. Unauthorized reproduction of this article is prohibited.
1027
LETTERS TO THE EDITOR
Rebecca C. Thurston, PhD Karen A. Matthews, PhD Department of Psychiatry University of Pittsburgh School of Medicine and Department of Epidemiology University of Pittsburgh Graduate School of Public Health Pittsburgh, PA FIG. 1. Biopsychosocial model of hot flashes.
widely accepted nonhormonal methods to manage hot flashes. We believe that the most appropriate model is a biopsychosocial one. As we present in Figure 1, biological, behavioral, psychological, and social factors, interacting over time, all influence the occurrence and reporting of hot flashes. For example, there are clearly biological correlates of hot flashes, with the most well-elucidated biological model being a thermoregulatory one. According to this model, hot flashes represent heat dissipation events occurring in the context of altered thermoregulatory functioning of women transitioning through menopause.12 There are also multiple other biological correlates of hot flashes, including (but not limited to) estrogen metabolism genetic polymorphisms,13 increases in follicular stimulating hormone and decreases in estradiol occurring during menopause,14 and changes in neurotransmitters such as norepinepherine15 and possibly serotonin.16 However, behavioral, psychological, and social influences on hot flashes cannot be ignored. For example, smoking is a well-known risk factor related to hot flashes,6 and obesity, now identified as a risk factor for hot flashes,2,6,17 clearly has a behavioral contribution.11 Furthermore, anxiety, even when assessed years before hot flashes, is a consistent predictor of hot flashes.6 Negative affect may be quite important to consider in the reporting or the perceived bother18 associated with hot flashes, particularly hot flashes reported but not detected physiologically.19 Finally, key social factors are related to hot flashes. Low socioeconomic status is a robust and consistent predictor of hot flashes,6 and socioeconomic status is known to be related to many of the behavioral and psychological risk factors detailed above. Notably, in a recent report in Menopause, we show that women exposed to childhood abuse or neglect were more likely to report hot flashes during the menopausal transition, an association persisting with adjustment for multiple confounding factors.20 Thus, the predictors of hot flashes are multiple, including physiological as well as social and psychological factors. Although yet to be fully elucidated, these factors likely operate in part through each other to impact health. Such a model implies that there may be multiple points of intervention to reduce hot flashes and improve the quality of life of midlife women. We hope that this model, as it is further elucidated, can provide a path through the forest, helping to guide and integrate future research on the etiology and treatment of menopausal hot flashes.
1028
Menopause, Vol. 15, No. 5, 2008
Susan A. Everson Rose, PhD, MPH Department of Medicine Program in Health Disparities Research University of Minnesota School of Medicine Minneapolis, MN REFERENCES 1. Reame NK. Adiposity and hot flashes: one more tree in the forest. Menopause 2008;15:408-409. 2. Thurston RC, Sowers MR, Sutton-Tyrrell K, et al. Abdominal adiposity and hot flashes among midlife women. Menopause 2008;15:429-434. 3. James GD, Sievert LL, Flanagan E. Ambulatory blood pressure and heart rate in relation to hot flash experience among women of menopausal age. Ann Hum Biol 2004;31:49-58. 4. Low DA, Davis SL, Keller DM, Shibasaki M, Crandall CG. Cutaneous and hemodynamic responses during hot flashes in symptomatic postmenopausal women. Menopause 2008;15:290-295. 5. Kelley DE, Thaete FL, Troost F, Huwe T, Goodpaster BH. Subdivisions of subcutaneous abdominal adipose tissue and insulin resistance. Am J Physiol Endocrinol Metab 2000;278:E941-E948. 6. Gold E, Colvin A, Avis N, et al. Longitudinal analysis of vasomotor symptoms and race/ethnicity across the menopausal transition: Study of Women’s Health Across the Nation (SWAN). Am J Public Health 2006;96:1226-1235. 7. Williams DR, Collins C. US socioeconomic and racial differences in health: patterns and explanations. Annu Rev Sociol 1995;21:349-386. 8. Flegal KM, Carroll MD, Ogden CL, Johnson CL. Prevalence and trends in obesity among US adults, 1999-2000. JAMA 2002;288:1723-1727. 9. Sternfeld B, Wang H, Quesenberry CP Jr, et al. Physical activity and changes in weight and waist circumference in midlife women: findings from the Study of Women’s Health Across the Nation. Am J Epidemiol 2004;160:912-922. 10. Sowers M, Zheng H, Tomey K, et al. Changes in body composition in women over six years at midlife: ovarian and chronological aging. J Clin Endocrinol Metab 2007;92:895-901. 11. National Institutes of Health National Heart Lung and Blood Institute, ed. Clinical guidelines on the identification, evaluation, and treatment of overweight and obesity in adults: the evidence report. Bethesda, MD: National Institutes of Health National Heart Lung and Blood Institute, 1998. 12. Freedman RR. Pathophysiology and treatment of menopausal hot flashes. Semin Reprod Med 2005;23:117-125. 13. Crandall CJ, Crawford SL, Gold EB. Vasomotor symptom prevalence is associated with polymorphisms in sex steroid-metabolizing enzymes and receptors. Am J Med 2006;119:S52-S60. 14. Randolph JF Jr, Sowers M, Bondarenko I, et al. The relationship of longitudinal change in reproductive hormones and vasomotor symptoms during the menopausal transition. J Clin Endocrinol Metab 2005; 90:6106-6112. 15. Freedman RR, Woodward S, Sabharwal SC. Alpha 2-adrenergic mechanism in menopausal hot flushes. Obstet Gynecol 1990;76:573-578. 16. Stearns V, Beebe KL, Iyengar M, Dube E. Paroxetine controlled release in the treatment of menopausal hot flashes: a randomized controlled trial. JAMA 2003;289:2827-2834. 17. Thurston RC, Sowers MR, Chang Y, et al. Adiposity and reporting of vasomotor symptoms among midlife women: the study of women’s health across the nation. Am J Epidemiol 2008;167:78-85. 18. Thurston R, Bromberger J, Joffe H, et al. Beyond frequency: who is most bothered by vasomotor symptoms? Menopause 2008;15:841-847. 19. Thurston RC, Blumenthal JA, Babyak MA, Sherwood A. Emotional antecedents of hot flashes during daily life. Psychosom Med 2005; 67:137-146. 20. Thurston RC, Bromberger J, Chang Y, et al. Childhood abuse or neglect is associated with increased vasomotor symptom reporting among midlife women. Menopause 2008;15:16-22. * 2008 by The North American Menopause Society
Copyright @ 2008 The North American Menopause Society. Unauthorized reproduction of this article is prohibited.
LETTERS TO THE EDITOR
To the Editor: I am surprised at the poor science and the disregard for the Health Belief Model, a well-recognized public health behavior theory, in the recent articleVBair YA, Gold EB, Zhang G, et al. Use of complementary and alternative medicine during the menopause transition: longitudinal results from the Study of Women’s Health Across the Nation. Menopause. 2008;15(1):32Y43. In their article, Bair et al demonstrate very poor methodology in selecting their study population and thus introduce multiple dissimilarities and potential confounding variables. Each ethnic group is recruited from a different part of the country, thus introducing geographical disparities in terms of town/city culture, access to and availability of complementary and alternative medicine (CAM), and representativeness of the chosen ethnic group to members of that group in other parts of the country. Los Angeles and Pittsburgh, for example, engender different liberal traditions, health attitudes, and ready access to and availability of CAM. The ethnic groups in the study also differed by educational levels, which is a particularly significant confounding variable, as education often plays a huge role in shaping values and health beliefs. Finally, Bair et al. give little regard to the elements of the Health Belief Model, which is central to public health behavior analysis. Health Belief Model proposes that people are motivated to take a health action based on perceived susceptibility, perceived severity, perceived benefit, perceived barriers, cues to action, and self-efficacy (ie, confidence in their ability to change/engage in a health behavior). The authors did well to discuss the external, or social and environmental, factors that might have affected their participants’ health choices, such as social support and health insurance. But they neglected to investigate interethnic motivations for seeking CAM, an important dimension of any health behavior study. They acknowledge this and allude to Bcultural differences[ in access to and perception of CAM, but this is not enough. Ashorkor Tetteh, BA Department of Epidemiology The George Washington University School of Public Health and Health Services Washington, DC
In Reply: We appreciate the opportunity to respond to Ms Tetteh’s letter pointing out her concerns with our recently published study, BThe use of complementary and alternative medicine
during the menopause transition: Longitudinal results from the Study of Women’s Health Across the Nation.[ The first concern raised was Bvery poor methodology[ in selecting the study sample relating to the selection of ethnic groups from different regions of the country. As we explained in our paper, the Study of Women’s Health Across the Nation is a community-based, longitudinal observational study. The oversampling of ethnic groups at individual study sites is a study design that is often used to ensure adequate sample sizes for comparisons among ethnic groups. Furthermore, in all of our comparisons, we adjusted for geographic location to account for those differences that might be introduced by study site, rather than other factors of interest. The second concern was that our study did not consider the Health Belief Model for evaluating health behavior. Although it is reasonable that the Health Belief Model may have utility in the study of complementary and alternative medicine (CAM), it is but one of several health behavior models currently used in the study of conventional health behaviors, and its application to CAM has yet to be evaluated. SWAN is a longitudinal study of the natural progression of menopause in a community-based cohort. As such, evaluating factors related to use of CAM was not the primary objective of the study. Although it would be very interesting and informative to conduct an in-depth study of CAM use during the menopause transition using a health behavior or healthcare-seeking model as a framework, this study was not meant to be such an in-depth investigation. Our study serves as a preliminary look at factors associated with women’s use of CAM during menopause, within the framework of a longitudinal observational study of the many factors involved in the menopause transition. The factors that we find suggestive of cultural or behavioral differences in CAM use certainly merit further investigation. In the interim, our study is potentially informative to the clinical community because it highlights the pervasiveness of CAM use and the potentially significant cultural differences in women’s approaches to menopause and general health management. Yali A. Bair, PhD Ellen B. Gold, PhD Gail Greendale, MD Dawn Upchurch, PhD Jessica Utts, PhD Guili Zhang, PhD University of California, Davis Davis, CA
Menopause, Vol. 15, No. 5, 2008
Copyright @ 2008 The North American Menopause Society. Unauthorized reproduction of this article is prohibited.
1029
