help button home button Endocrine Society JCEM
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
Journal of Clinical Endocrinology & Metabolism , doi:10.1210/jc.2006-0866
This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow Submit a related Letter to the Editor
Right arrow Alert me when this article is cited
Right arrow Alert me when eLetters are posted
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow Request Copyright Permission
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Bjørnerem, A.
Right arrow Articles by Berntsen, G. K. R.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Bjørnerem, A.
Right arrow Articles by Berntsen, G. K. R.
Related Collections
Right arrow Adrenal and Hypertension
Right arrow Neuroendocrinology and Pituitary
Right arrow Female Endocrinology
Right arrow Male Endocrinology
The Journal of Clinical Endocrinology & Metabolism Vol. 91, No. 10 3798-3802
Copyright © 2006 by The Endocrine Society

Seasonal Variation of Estradiol, Follicle Stimulating Hormone, and Dehydroepiandrosterone Sulfate in Women and Men

Åshild Bjørnerem, Bjørn Straume, Pål Øian and Gro K. R. Berntsen

Institute of Community Medicine (Å.B., B.S., G.K.R.B.), University of Tromsø, N-9037 Tromsø, Norway; and Department of Obstetrics and Gynecology (P.Ø.), University Hospital of North Norway, N-9038 Tromsø, Norway

Address all correspondence and requests for reprints to: Åshild Bjørnerem, M.D., Institute of Community Medicine, University of Tromsø, N-9037 Tromsø, Norway. E-mail: ashild.bjornerem{at}ism.uit.no.


   Abstract
Top
 Abstract
Introduction
 Subjects and Methods
 Results
 Discussion
 References
 
Context: Seasonal variation in daylight regulates reproduction in animals living at higher latitude, but the influence of season on the sex hormones in humans remains unclear.

Objective, Design, and Participants: A cross-sectional population-based study in Tromsø, Norway (70° N) included 1651 women and 1540 men aged 25–84 yr. Circulating total estradiol (and calculated free levels), FSH, and dehydroepiandrosterone sulfate (DHEAS) were measured between September 1994 and September 1995 and provided a unique opportunity to study effects of extreme seasonal variations in the daylight on hormone levels in an arctic population.

Main Outcome Measure: Circulating total and free estradiol, FSH, and DHEAS were measured.

Results: Total and free estradiol showed differences between monthly means, with peak in June in postmenopausal women (P < 0.001), and in May in men (P = 0.002 and P < 0.001) by analysis of covariance. By cosinor analysis, a seasonal variation in total and free estradiol was evident in women (P = 0.02 and P = 0.03) and men (P = 0.004 and P = 0.001), but only 0.2–0.9% of the variation in total and free estradiol was explained by season. FSH and DHEAS showed no obvious seasonal variation in either sex.

Conclusions: Seasonal variations should be considered while designing studies and interpreting results of estradiol measurements to avoid bias in comparative studies.


   Introduction
Top
 Abstract
 Introduction
Subjects and Methods
 Results
 Discussion
 References
 
SEX HORMONES ARE involved in the pathophysiology of common diseases such as fragility fractures and cancer (1, 2), which makes it important to understand factors influencing their levels. All hormones are characterized by some rhythmic secretion and the levels can vary through the year. Seasonal variation in daylight regulates reproduction in animals living at higher latitude (3, 4), whereas the influence of season on the sex hormones in humans remains unclear (5, 6, 7, 8).

If sex hormones vary systematically by season in some regions or for some subjects, this can cause misclassification bias in comparative studies. However, most studies involving hormone measurements do not take into account the time of measurement while designing studies or interpreting the results (9). Little information is available on seasonal variations in estradiol, FSH, and dehydroepiandrosterone sulfate (DHEAS) in both sexes. Despite having a longitudinal design, which lends them certain strength, previous studies are either small (n = 10–27) or based on selected hospital population, and the results are inconsistent (10, 11, 12, 13, 14, 15, 16, 17). To our knowledge, seasonal variations in circulating estradiol, FSH, or DHEAS have not been investigated in a population-based study.

Tromsø, Norway, is located at 70° N and has extreme variations in the daylight exposure. The sun is below the horizon from November 28 to January 15 and does not set between May 17 and July 26. This study provided, therefore, a unique opportunity to test the hypothesis that extreme seasonal variations in the daylight affects the levels of sex hormones in women and men living at high latitude.


   Subjects and Methods
Top
 Abstract
 Introduction
 Subjects and Methods
Results
 Discussion
 References
 
Subjects

The Tromsø Osteoporosis Study (TROST) is part of the Tromsø Study, a single-center, population-based, prospective study of Tromsø in northern Norway. Between September 1994 and September 1995, TROST measured bone density in 7948 subjects aged 25–84 yr (response rate 78%) (18). Among them, a random sample of 3684 were selected for hormone assays, and 3514 of them had blood samples available for analyses (19). Included in this sample were also participants in the Family Intervention Study, not viewed as representative of the general population (20). However, exclusion of these 155 surplus Family Intervention Study participants did not alter the results, so they were retained in the analyses. We excluded 323 participants due to use of hormone medication (n = 240), pregnancy (n = 4), perimenopausal status (n = 32), or missing hormone values (n = 47). All participants gave informed written consent. The regional Committee of Research Ethics and the Norwegian Data Inspectorate approved the study.

Two self-administered questionnaires were answered. We included information on current smoking status and consumption of coffee and alcohol. A physical activity score was made by adding the hours per week of moderate and hard physical activity, giving the hours with hard activity double weight: score = moderate + 2 hard. To maximize the number of observations, our definition of menopausal status was based on the self-reported menstruation data and age (19). Briefly, women who had a menstrual period within the last 3 months (n = 205) or were younger than 45 yr with missing data (n = 25) were defined as premenopausal. Women who stopped menstruating more than a year ago (n = 989) or were 54 yr of age or older with missing data (n = 432) were defined as postmenopausal. These 432 women had a mean age of 70 yr (range 54–83), and 92% of them were 60 yr of age or older. This left 230 premenopausal and 1421 postmenopausal women and 1540 men to be included in the study. None were invited to participate in July due to summer vacation (Table 1Go).


View this table:
[in this window]
[in a new window]
  		TABLE 1. Numbers of participants by months of measurement: the Tromsø Study 1994–1995

 
Measurements

The Norwegian Meteorological Institute provided records of the monthly mean temperatures. The midmonth hours of daylight in Tromsø during the study period, were calculated as the hours between sunrise and sunset on the 15th day of each month (Fig. 1Go).


Figure 1
View larger version (13K):
[in this window]
[in a new window]
  		FIG. 1. Monthly geometric means with 95% confidence intervals of total and free estradiol, FSH, and DHEAS, adjusted for age, body mass index, smoking, alcohol and coffee drinking, physical activity, and election district by ANCOVAs in 1421 postmenopausal women and 1540 men. Monthly mean temperature and midmonth hours of daylight were used. The data are from the Tromsø Study 1994–1995.

 
Height and weight were measured in light clothing without shoes, and body mass index was calculated as weight divided by the square of height (kilograms per square meter).

Nonfasting blood samples were taken between 0800 and 1600 h, and serum was stored at –70 C for 6–7 yr until first thawed in 2001. All hormones and SHBG were measured on Immulite 2000 (Diagnostic Products Corp., Los Angeles, CA). Estradiol and DHEAS measurements were based on competitive immunoassays, whereas FSH and SHBG measurements were based on immunometric assays.

The intra- and interassay coefficients of variation for estradiol and DHEAS were between 4 and 15%. The intra- and interassay coefficients of variation for FSH and SHBG were between 2 and 9%. The lower limits of detection were 10 pmol/liter for estradiol, 0.5 IU/liter for FSH, 1.0 µmol/liter for DHEAS, and 1.0 nmol/liter for SHBG. Samples with values below limits of detection were given a value midway between zero and limit of detection: estradiol (333 women, 60 men) and DHEAS (364 women, 84 men). All assays were run within a few weeks of each other using the same lot of reagents and assay kits. We used the method of Vermeulen et al. (21) to calculate free estradiol from total estradiol and SHBG. A recent validation by Rinaldi et al. (22) found that method simple and reliable.

Statistical analysis

The SAS Software package (version 8.2; SAS Institute, Cary, NC), was used for both data management and analysis. The data were analyzed separately for premenopausal and postmenopausal women, and for men. The significance level was chosen at P < 0.05 and P values are two sided. Because of skewed distribution, we used log-transformed hormones in all statistical analysis. However, the presented monthly means and confidence limits were transformed back to the original units.

Analysis of covariance (ANCOVA) was used to investigate the variation in monthly mean values and test for overall differences between the monthly means over the year. The months were used as a categorical explanatory variable. We adjusted for age, body mass index, current smoking (yes/no), alcohol use (yes/no), coffee drinking, and physical activity known to be associated with sex hormones (19). Because participants from the town center and the countryside met at different times of the year, we also adjusted for election districts to avoid interaction from socioeconomic status related to place of living.

The cosinor analyses were used to test seasonality in hormone values (23). We used individual values of log-transformed hormones and adjusted for all above-mentioned covariates. The essence of the method is to fit a linear regression model in which some smooth variation over time is modeled by patterns consisting of sines and cosines. This analysis provides estimates of the mean hormone value and the nonlinear parameters amplitude (distance from mean to peak of the curve) and acrophase (timing of the peak). Seasonality in hormone values was evaluated by testing the null hypothesis of zero amplitude (24). The variation in hormones explained by seasonality was calculated from R2 in cosinor analyses.


   Results
Top
 Abstract
 Introduction
 Subjects and Methods
 Results
Discussion
 References
 
In premenopausal women, total and free estradiol peaked in June (425 and 8.4 pmol/liter), the nadir month was November (76 and 1.6 pmol/liter), but there was no overall significance for differences between monthly means (P = 0.08) (data not shown). FSH and DHEAS showed no differences in monthly means in ANCOVA. In the cosinor analyses, total and free estradiol showed no seasonal variation. FSH showed a small peak in June (P = 0.04), and DHEAS showed seasonality (P = 0.004), with the peak in January (Tables 2Go and 3Go).


View this table:
[in this window]
[in a new window]
  		TABLE 2. Characteristics of 230 premenopausal women, 1421 postmenopausal women, and 1540 men: the Tromsø Study 1994–1995

 

View this table:
[in this window]
[in a new window]
  		TABLE 3. The rhythm characteristics of log-transformed total and free estradiol, FSH, and DHEAS by cosinor analyses1 in 230 premenopausal and 1421 postmenopausal women and 1540 men: the Tromsø Study 1994–1995

 
In postmenopausal women, total and free estradiol showed differences between the monthly means (P < 0.001), with the peak in June (29.1 and 0.6 pmol/liter) and the nadir in October (14.8 and 0.3 pmol/liter), respectively, in ANCOVA (Fig. 1Go). FSH peaked in March (70.8 IU/liter), and the nadir occurred in May (61.3 IU/liter), but the variation by months was small (P = 0.03). In the cosinor analyses, no seasonal variation was detected when we included all postmenopausal women (Table 3Go). However, when we repeated the analyses after exclusion of the women 54 yr old or older with missing data on menopause (n = 432), the seasonal variation of total and free estradiol was significant (P = 0.02 and P = 0.04), and seasonality accounted for 0.2 and 0.3% of the variation in total and free estradiol (data not shown). FSH and DHEAS showed no detectable seasonality.

In men, total and free estradiol peaked in May (63.0 and 1.5 pmol/liter), and the nadir occurred October (38.0 and 0.9 pmol/liter), respectively, in ANCOVA (P = 0.002 and P < 0.001) (Fig. 1Go). FSH and DHEAS showed no detectable differences in monthly means. In the cosinor analyses, total and free estradiol showed a highly significant seasonality, with the peak in May (P = 0.004 and P = 0.001), and seasonality accounted for 0.7 and 0.9% of the variation in total and free estradiol, respectively.


   Discussion
Top
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
References
 
The main finding from this study was a seasonal variation in estradiol in women and men, but only 0.2–0.9% of the variation in estradiol was explained by seasonality. Estradiol showed differences between monthly means in postmenopausal women and men. However, the cosinor analyses is a better way to test for seasonality, compared with a traditional ANOVA testing, in which any order of the months will give the same result.

Most studies on the variations in reproductive hormones by season are from northern Europe with participants younger than 50 yr (10, 11, 12, 13, 14, 15). The estradiol levels have shown seasonality in studies on premenopausal women (10, 11). In this study, variability in the cyclic nature of hormonal measurements in premenopausal women and small numbers in most of the months may contribute to failure to detect significant variation in estradiol in this group. For the same reasons, we believe that the significant seasonality in DHEAS in this group may be a spurious finding. In this study, estradiol showed seasonality in postmenopausal women when we included only women who reported age at menopause. This weak association was blunted when we used a loose definition of menopause and included 432 women with missing data on menopause who were 54 yr of age or older. In a previous study on 14 elderly women, estradiol levels showed no seasonality (17). Otherwise, little is known about the seasonality of hormones among elderly women.

To our knowledge, the intriguing finding of coinciding seasonality in estradiol levels in men and postmenopausal women has not been reported previously. In agreement with results from a longitudinal study of 24 men from north Finland (13), in which the duration of daylight in summer and midwinter is comparable with Tromsø, estradiol levels peaked in May and had nadir levels in October. Others have reported no seasonality in estradiol among men (14) or women (17). The effects of seasonal variation in daylight may be blunted by the amount of artificial light in modern society. Although hormone levels peaked during the months of increased daylight (spring and early summer), the nadir levels were not found during the darkest season.

In animals living at higher latitudes, seasonal variation in daylight regulates reproductive function by altering the secretion of melatonin from the pineal gland (3, 4). Humans are nonseasonal breeders. Nevertheless, rhythmic seasonal variation in birth and conception rates are reported (25, 26). Although timing of human conception is mainly influenced by social factors, biological seasonal components still exist. Studies carried out at higher latitudes found higher levels of melatonin or longer duration of melatonin secretion during the dark season, compared with the light season (11, 12, 13, 27). This was not the case at lower latitudes (7, 8). In northern Finland, reproductive hormones have been shown to exhibit significant seasonal variation in men (13) and women (10, 11), with an increase in pituitary-gonadal function in late spring and early summer. However, these differences were small. Further evidence that biological factors contribute to increased fertility in the spring comes from studies of in vitro fertilization (28, 29). It is clear that the human pineal gland has retained the ability to respond to daylight duration, although the functional significance of this mechanism remains uncertain (7, 30). Many other factors than day length could lead to the small changes in estradiol levels, and one possible explanation is that temperature contributes. Whether seasonality in estradiol is an effect of daylight mediated by levels of melatonin could not be tested in this study because melatonin was not measured.

Epidemiological data indicate low risks for breast and prostate cancers in the arctic regions, and winter darkness and higher melatonin levels might have a protective effect against hormone-dependent tumors (6, 31). At higher latitudes, the duration of melatonin secretion has been reported to be longer in winter than summer but not at lower latitudes (7, 8). Melatonin could act as a naturally occurring antiestrogen as demonstrated on in vivo models of animal mammary tumors as well as in vitro human breast cancer cells (32, 33, 34). This melatonin hypothesis may explain the lower level of estradiol in the darkest season in the arctic regions. If estradiol levels are lower among the Norwegian population than people at lower latitudes, this may contribute in explaining the high incidence of fragility fractures in Norway (35). This hypothesis was supported by our findings of seasonality in estradiol levels in women and men in the population in Tromsø. We need comparative studies among people from different geographic locations to clarify this issue.

This study has some limitations. Although we used an assay with low limit of detection, estradiol values were below the limit in 23% of postmenopausal women. However, results did not differ substantially, whether or not women with values below the limit of detection were included. Delayed analyses of stored serum samples and daytime variation were previously discussed and results found unlikely to bias our results (19). Adjustment for sampling hour did not change any result. The characteristics of the subgroup with hormone measurements were compared with the total TROST population in a previous paper (19). The subgroup of women was 1 yr older with higher prevalence of cardiovascular diseases, whereas the men did not differ in any characteristics. The potential for selection bias is therefore assumed to be small. The cross-sectional estimates of seasonal variation of hormone levels are not true measures of longitudinal changes, and individual variations cannot be identified. A longitudinal design following up the same participants throughout the year would have been preferable. However, true seasonal variations would be expected to be evident in this study due to a large sample size, despite the cross-sectional design.

A weak but significant seasonal variation of estradiol, most of all in men, indicates that seasonality can be a source of bias in comparative studies in populations at higher latitudes. Possible seasonal variation should therefore be considered when designing studies and analyzing and interpreting results of estradiol measurements. Cases and controls should preferably have the hormones measured at the same time of the year, and recording of blood sampling time to allow adjustment in the analyses to avoid bias. Further studies, preferably longitudinal, are needed to confirm our findings in populations at similar latitudes and test the validity of these results for other latitudes.


   Acknowledgments
 
We thank the National Health Screening Service and participants of the Tromsø Study for their help. The authors thank Tom Wilsgaard for statistical assistance.


   Footnotes
 
This work was supported by grants from the Research Council of Norway, the Norwegian Foundation for Health and Rehabilitation, and the University Hospital of North Norway.

Disclosure statement: the authors have nothing to disclose.

First Published Online July 11, 2006

Abbreviations: ANCOVA, Analysis of covariance; DHEAS, dehydroepiandrosterone sulfate; TROST, Tromsø Osteoporosis Study.

Received April 21, 2006.

Accepted July 3, 2006.


   References
Top
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
 References
 

  1. Riggs BL, Khosla S, Melton LJ 2002 Sex steroids and the construction and conservation of the adult skeleton. Endocr Rev 23:279–302[Abstract/Free Full Text]
  2. Endogenous Hormones and Breast Cancer Collaborative Group 2003 Body mass index, serum sex hormones, and breast cancer risk in postmenopausal women. J Natl Cancer Inst 95:1218–1226[Abstract/Free Full Text]
  3. Bittman EL, Karsch FJ 1984 Nightly duration of pineal melatonin secretion determines the reproductive response to inhibitory day length in the ewe. Biol Reprod 30:585–593[Abstract]
  4. Reiter RJ 1991 Neuroendocrine effects of light. Int J Biometeorol 35:169–175
  5. Reiter RJ 1998 Melatonin and human reproduction. Ann Med 30:103–108[Medline]
  6. Rohr UD, Herold J 2002 Melatonin deficiencies in women. Maturitas 41(Suppl 1):S85–S104
  7. Wehr TA 2001 Photoperiodism in humans and other primates: evidence and implications. J Biol Rhythms 16:348–364[Abstract/Free Full Text]
  8. Bronson EH 2004 Are humans seasonally photoperiodic? J Biol Rhythms 19:180–192[Abstract/Free Full Text]
  9. Panico S, Pisani P, Muti P, Recchione C, Cavalleri A, Totis A, Berrino F 1990 Diurnal variation of testosterone and estradiol: a source of bias in comparative studies on breast cancer. J Endocrinol Invest 13:423–426[Medline]
  10. Kauppila A, Pakarinen A, Kirkinen P, Makila U 1987 The effect of season on the circulating concentrations of anterior pituitary, ovarian and adrenal cortex hormones and hormone binding proteins in the subarctic area: evidence of increased activity of the pituitary-ovarian axis in spring. Gynecol Endocrinol 1:137–150[Medline]
  11. Kauppila A, Kivela A, Pakarinen A, Vakkuri O 1987 Inverse seasonal relationship between melatonin and ovarian activity in humans in a region with a strong seasonal contrast in luminosity. J Clin Endocrinol Metab 65:823–828[Abstract/Free Full Text]
  12. Kivela A, Kauppila A, Ylostalo P, Vakkuri O, Leppaluoto J 1988 Seasonal, menstrual and circadian secretions of melatonin, gonadotropins and prolactin in women. Acta Physiol Scand 132:321–327[Medline]
  13. Martikainen H, Tapanainen J, Vakkuri O, Leppaluoto J, Huhtaniemi I 1985 Circannual concentrations of melatonin, gonadotropins, prolactin and gonadal-steroids in males in a geographical area with a large annual variation in daylight. Acta Endocrinol 109:446–450
  14. Andersson AM, Carlsen E, Petersen JH, Skakkebaek NE 2003 Variation in levels of serum inhibin B, testosterone, estradiol, luteinizing hormone, follicle-stimulating hormone, and sex hormone-binding globulin in monthly samples from healthy men during a 17-month period: possible effects of seasons. J Clin Endocrinol Metab 88:932–937[Abstract/Free Full Text]
  15. Garde AH, Hansen AM, Skovgaard LT, Christensen JM 2000 Seasonal and biological variation of blood concentrations of total cholesterol, dehydroepiandrosterone sulfate, hemoglobin A(1c), IgA, prolactin, and free testosterone in healthy women. Clin Chem 46:551–559[Abstract/Free Full Text]
  16. Meriggiola MC, Noonan EA, Paulsen CA, Bremner WJ 1996 Annual patterns of luteinizing hormone, follicle stimulating hormone, testosterone and inhibin in normal men. Hum Reprod 11:248–252
  17. Nicolau GY, Lakatua D, Sackett-Lundeen L, Haus E 1984 Circadian and circannual rhythms of hormonal variables in elderly men and women. Chronobiol Int 1:301–319[Medline]
  18. Berntsen GKR, Fønnebø V, Tollan A, Søgaard AJ, Magnus JH 2001 Forearm bone mineral density by age in 7,620 men and women: the Tromsø study, a population-based study. Am J Epidemiol 153:465–473[Abstract/Free Full Text]
  19. Bjørnerem Å, Straume B, Midtby M, Fønnebø V, Sundsfjord J, Svartberg J, Acharya G, Øian P, Berntsen GKR 2004 Endogenous sex hormones in relation to age, sex, lifestyle factors, and chronic diseases in a general population: the Tromsø Study. J Clin Endocrinol Metab 89:6039–6047[Abstract/Free Full Text]
  20. Knutsen SF, Knutsen R 1989 The Tromsø Heart Study: family approach to intervention on CHD. Feasibility of risk factor reduction in high-risk persons—project description. Scand J Soc Med 17:109–119[Medline]
  21. Vermeulen A, Verdonck L, Kaufman JM 1999 A critical evaluation of simple methods for the estimation of free testosterone in serum. J Clin Endocrinol Metab 84:3666–3672[Abstract/Free Full Text]
  22. Rinaldi S, Geay A, Déchaud H, Biessy C, Zeleniuch-Jacquotte A, Akhmedkhanov A, Shore RE, Riboli E, Toniolo P, Kaaks R 2002 Validity of free testosterone and free estradiol determinations in serum samples from postmenopausal women by theoretical calculations. Cancer Epidemiol Biomarkers Prev 11:1065–1071[Abstract/Free Full Text]
  23. Cugini P 1993 Chronobiology: principles and methods. Ann Ist Super Sanita 29:483–500[Medline]
  24. Mikulich SK, Zerbe GO, Jones RH, Crowley TJ 2003 Comparing linear and nonlinear mixed model approaches to cosinor analysis. Stat Med 22:3195–3211[CrossRef][Medline]
  25. Roenneberg T, Aschoff J 1990 Annual rhythm of human reproduction: II. Environmental correlations. J Biol Rhythms 5:217–239[Abstract/Free Full Text]
  26. Roenneberg T, Aschoff J 1990 Annual rhythm of human reproduction: I. Biology, sociology, or both? J Biol Rhythms 5:195–216[Abstract/Free Full Text]
  27. Stokkan KA, Reiter RJ 1994 Melatonin rhythms in arctic urban residents. J Pineal Res 16:33–36[Medline]
  28. Ossenbuhn S 1998 Exogenous influences on human fertility: fluctuations in sperm parameters and results of in vitro fertilization coincide with conceptions in the normal population. Hum Reprod 13:2165–2171[Abstract/Free Full Text]
  29. Rojansky N, Benshushan A, Meirsdorf S, Lewin A, Laufer N, Safran A 2000 Seasonal variability in fertilization and embryo quality rates in women undergoing IVF. Fertil Steril 74:476–481[CrossRef][Medline]
  30. Macchi MM, Bruce JN 2004 Human pineal physiology and functional significance of melatonin. Front Neuroendocrinol 25:177–195[CrossRef][Medline]
  31. Erren TC, Piekarski C 1999 Does winter darkness in the Arctic protect against cancer? The melatonin hypothesis revisited. Med Hypotheses 53:1–5[CrossRef][Medline]
  32. Sanchez-Barcelo EJ, Cos S, Fernandez R, Mediavilla MD 2003 Melatonin and mammary cancer: a short review. Endocr Relat Cancer 10:153–159[Abstract]
  33. Blask DE, Dauchy RT, Sauer LA, Krause JA, Brainard GC 2003 Growth and fatty acid metabolism of human breast cancer (MCF-7) xenografts in nude rats: impact of constant light-induced nocturnal melatonin suppression. Breast Cancer Res Treat 79:313–320[CrossRef][Medline]
  34. Kiefer T, Ram PT, Yuan L, Hill SM 2002 Melatonin inhibits estrogen receptor transactivation and cAMP levels in breast cancer cells. Breast Cancer Res Treat 71:37–45[CrossRef][Medline]
  35. Lofthus CM, Osnes EK, Falch JA, Kaastad TS, Kristiansen IS, Nordsletten L, Stensvold I, Meyer HE 2001 Epidemiology of hip fractures in Oslo, Norway. Bone 29:413–418[Medline]



This article has been cited by other articles:


Home page
 J EndocrinolHome page
D. R Lemos, J. L Downs, M. N Raitiere, and H. F Urbanski
Photoperiodic modulation of adrenal gland function in the rhesus macaque: effect on 24-h plasma cortisol and dehydroepiandrosterone sulfate rhythms and adrenal gland gene expression
J. Endocrinol., May 1, 2009; 201(2): 275 - 285.
[Abstract] [Full Text] [PDF]

Home page
 J AndrolHome page
J. D. Meeker, A. M. Calafat, and R. Hauser
Urinary Metabolites of Di(2-ethylhexyl) Phthalate Are Associated With Decreased Steroid Hormone Levels in Adult Men
J Androl, May 1, 2009; 30(3): 287 - 297.
[Abstract] [Full Text] [PDF]

Home page
 J. Clin. Endocrinol. Metab.Home page
D. J. Brambilla, A. B. O'Donnell, A. M. Matsumoto, and J. B. McKinlay
Lack of Seasonal Variation in Serum Sex Hormone Levels in Middle-Aged to Older Men in the Boston Area
J. Clin. Endocrinol. Metab., November 1, 2007; 92(11): 4224 - 4229.
[Abstract] [Full Text] [PDF]

This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow Submit a related Letter to the Editor
Right arrow Alert me when this article is cited
Right arrow Alert me when eLetters are posted
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow Request Copyright Permission
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Bjørnerem, A.
Right arrow Articles by Berntsen, G. K. R.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Bjørnerem, A.
Right arrow Articles by Berntsen, G. K. R.
Related Collections
Right arrow Adrenal and Hypertension
Right arrow Neuroendocrinology and Pituitary
Right arrow Female Endocrinology
Right arrow Male Endocrinology

HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
Endocrinology Endocrine Reviews J. Clin. End. & Metab.
Molecular Endocrinology Recent Prog. Horm. Res. All Endocrine Journals