Eur J Endocrinol
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
QUICK SEARCH:   [advanced]


     

DOI: 10.1530/eje.1.02241
European Journal of Endocrinology, Vol 155, Issue 3, 443-452
Copyright © 2006 by European Society of Endocrinology
This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via ISI Web of Science (4)
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Mohr, B. A
Right arrow Articles by McKinlay, J. B
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Mohr, B. A
Right arrow Articles by McKinlay, J. B
CLINICAL STUDY

The effect of changes in adiposity on testosterone levels in older men: longitudinal results from the Massachusetts Male Aging Study

Beth A Mohr, Shalender Bhasin1, Carol L Link, Amy B O’Donnell and John B McKinlay

New England Research Institutes, 9 Galen Street, Watertown, Massachusetts 02472, USA, and 1 Section of Endocrinology, Diabetes, and Nutrition, Boston University School of Medicine, Boston Medical Center, Boston, Massachusetts 02118, USA

(Correspondence should be addressed to J B McKinlay; Email: jmckinlay{at}neriscience.com)


   Abstract
Top
 Abstract
Introduction
 Methods
 Results
 Discussion
 References
 
Objective: Changes in adiposity affecting total testosterone (TT) and free testosterone (FT) levels have not been examined in a population-based survey. We aimed to determine whether changes in adiposity predict follow-up levels and rates of change in TT, FT and sex hormone-binding globulin (SHBG) in men.

Design: The Massachusetts Male Aging Study is a randomly sampled, population-based cohort interviewed at baseline (T1, 1987–1989; n = 1709; aged 40–70 years) and followed-up approximately 9 years later (T2, 1995–1997; n = 1156). Men were categorized as overweight (body mass index (BMI) ≥ 25 kg/m2) or having obesity (BMI ≥ 30 kg/m2), waist obesity (waist circumference ≥ 102 cm), or waist-to-hip ratio (WHR) obesity (WHR>0.95). For each adiposity group, we constructed four categories to represent changes between T1 and T2: overweight (or obese, etc.) at neither wave, T1 only, T2 only, or both waves.

Results: After adjustment for confounding variables, men who were overweight at T2 only, or at both waves, had significantly lower mean T2 TT and SHBG levels than men in the neither group (P<0.05). Mean FT did not differ between any overweight group and the neither group. Men who were obese at both times, had the highest mean BMI, the highest fraction of severely obese men, and significantly greater rate of decline in FT than the neither group.

Conclusions: In men who become overweight, the greater rate of decline in TT, but not FT, is related mostly to a lesser age-related increase in SHBG. Since weight gain is highly prevalent in older men, over-reliance on TT levels in the diagnosis of androgen deficiency could result in substantial misclassification.


   Introduction
Top
 Abstract
 Introduction
Methods
 Results
 Discussion
 References
 
Obesity is widely recognized as an important public health problem, whose prevalence has increased substantially in the recent decades. The relationship between obesity and testosterone levels is one of the longest running controversies in endocrinology. Cross-sectional surveys – most of them conducted in relatively small, convenience samples – have suggested that there is an inverse correlation between total testosterone (TT) levels and body mass index (BMI) (1–5). However, inferences from these studies are complicated by the finding that sex hormone-binding globulin (SHBG) levels are also inversely correlated with adiposity (1, 3, 6, 7). In fact, all measures of adiposity (BMI, waist-to-hip ratio (WHR), and waist circumference) are strongly negatively correlated with SHBG levels. Other studies have suggested that higher insulin levels associated with adiposity suppress SHBG levels (8–11). Since a significant fraction of circulating testosterone is bound to SHBG, lower serum SHBG concentrations would be expected to lower TT levels. In many studies, free or non-SHBG-bound testosterone levels were found to be normal (2, 12), consistent with the notion that lower TT levels were mostly due to the lower SHBG levels in obese men.

Other investigations that included small samples of selected men with severe obesity reported that obese men had low free testosterone (FT) levels (13). One hypothesis to explain the association between extreme adiposity and low FT levels (true androgen deficiency) suggests that high estrogen levels are the culprit. Some speculate that in extremely obese men, high estradiol levels, generated by aromatization of testosterone in the adipose tissue (14, 15), suppress gonadotropin-releasing hormone and luteinizing hormone levels thereby suppressing testicular testosterone production (13, 16, 17).

In addition, some uncommon genetic syndromes are characterized by extreme adiposity and hypogonadotropic hypogonadism (18, 19). These syndromes are relatively uncommon and can be ignored in evaluating the association of obesity and testosterone levels in general populations.

Therefore, the central issue is not whether the development of obesity is associated with low TT levels – this might be expected because obesity lowers SHBG levels – but rather whether the development of obesity in men lowers free or bioavailable testosterone levels. This issue has largely remained unresolved. Few large epidemiological surveys have examined whether changes in adiposity impact TT, FT, and bioavailable testosterone levels longitudinally, and none have examined the association between weight increases and age-related rates of decline in these hormones.

Using data from the Massachusetts Male Aging Study (MMAS), a prospective, community-based sample of older men, we investigated whether changes in adiposity over a 9-year period predict the follow-up TT, FT, and bioavailable testosterone levels. Since both adiposity and aging affect SHBG levels, which can influence TT levels, we also examined SHBG levels. In addition, we examined whether changes in adiposity affect the rates of change in these hormones.


   Methods
Top
 Abstract
 Introduction
 Methods
Results
 Discussion
 References
 
Design

The MMAS is a prospective, community-based, observational study of aging in older men. This report uses data from the first two waves (T1, 1987–1989; T2, 1995–1997). The design has been described previously (20). At baseline (T1), men aged 40–70 years from 11 municipalities in the Boston, Massachusetts area were randomly selected from annual state census listings. Age-stratified cluster sampling was used to obtain approximately equal age strata (40–49, 50–59, 60–69 years). As reported elsewhere (21), 1709 of the eligible men (52%) participated at T1. This response rate reflects, in part, the early morning phlebotomy, extensive in-home interview, and absence offinancial incentive. At T2, 1156 of the 1496 eligible men participated (conditional response rate of 77%).

Trained interviewers/phlebotomists administered a standardized, in-home interview, and obtained physical measures and blood samples. Unless noted, data collection methods were the same at both waves. The New England Research Institutes’ Institutional Review Board approved all protocols including written informed consent procedures.

Independent variables

Adiposity  Height and weight, and waist and hip circumferences were measured using standard techniques (22). We defined overweight as BMI ≥ 25 kg/m2, obesity as BMI ≥ 30kg/m2, and waist obesity as waist circumference ≥ 102 cm (40 in.) (23–25). WHR obesity was defined as WHR>0.95 (26). For each measure, we constructed four categories to represent the changes that occurred between T1 and T2: overweight (or obese, etc.) at neither wave, T1 only, T2 only, and both waves.

Confounders  Validated instruments were used to evaluate alcohol intake (27) and physical activity (Stanford Five-City Physical Activity Questionnaire) (28). Smoking and chronic diseases (diabetes, hypertension, and heart disease) were ascertained by self-report. The interviewers obtained medication data by copying the name and use from the label. Pharmacoepidemiologists coded the medications using a system based on the American Hospital Formulary Service (29), and an endocrinologist identified prescription medications believed to decrease hormone levels (29), as previously described (21).

Dependent variables

Hormones  Two non-fasting blood samples were collected within 4 h of the subject’s awakening to control for diurnal variations in hormone levels (30). Samples were drawn 30 min apart, pooled in equal aliquots to smooth episodic secretion (31), transported in ice-cooled containers, and centrifuged within 6 h. The samples were stored at –70 °C until assayed.

All the assays were performed at The Endocrine Laboratory, University of Massachusetts Medical School (Worcester, MA, USA) under Dr Christopher Longcope’s supervision. TT was determined by RIA kit (Diagnostic Products Corporation, Los Angeles, CA, USA). T1 TT was assayed in 1994 on sera stored since T1, and T2 TT shortly after collection. A structural equation model, equivalent to a Deming regression, showed negligible change due to assay drift or storage. The assay cross-reactivity with dihydrotestosterone was 2.8%. The T1 and T2 intra-assay coefficient of variation (CV) values for TT were 5.4 and 5.8%, and the inter-assay CV values were 8.0 and 9.0% respectively.

SHBG was measured by the same kit at T1 and T2 although distributors changed (T1; Farmos Diagnostica, Farmos Group Ltd, Oulunsalo, Finland and T2; Orion Diagnostica, Espoo, Finland). The intra-assay CV values of T1 and T2 SHBG were 8.0 and 4.5%, and the inter-assay CV values were 10.9 and 7.9% respectively.

The Södergard equation was used to calculate free and bioavailable testosterone, assuming a fixed albumin-bound concentration (32). The Södergard equation produces estimates of free and bioavailable testosterone, which closely approximate those obtained from equilibrium dialysis and ammonium sulfate precipitation respectively (33).

Statistical analysis

Out of the 1709 men recruited at T1, 1156 participated at both waves. Men who were missing T1 (n = 9) or T2 hormones (n = 114) or T1 (n = 0) or T2 (n = 24) adiposity data, were excluded, resulting in an analysis sample of 1009 men. The sample sizes for each variable vary with item non-response.

A t-test was used to determine whether mean T2 hormone levels differed by T1 categorical confounders. Associations between T2 and T1 hormones and continuous confounders were assessed using Pearson correlation coefficients.

The key independent variable was change in adiposity between T1 and T2, defined using the four measures mentioned earlier: overweight, obesity, waist obesity, and WHR obesity. The dependent variables were T2 TT, FT, bioavailable testosterone, and SHBG. The hormones were examined in two ways: (a) T2 level (levels analysis) and (b) rate of change (change analysis). Rate of change was defined as T2–T1 hormone divided by T2–T1 age. For the analysis of levels, SHBG was log transformed to reduce the skew. Analysis of covariance (ANCOVA) was used to estimate the adjusted mean T2 hormone or rate of change by the adiposity change categories. Each adiposity change variable was modeled using three dummy variables. Pairwise comparisons between the neither group (i.e. not overweight, obese, etc. at T1 or T2) and the other adiposity change categories were adjusted for multiple comparisons using the Bonferroni procedure. Descriptive statistics were presented for free and bioavailable testosterone but model results for FT only. Since bioavailable testosterone is a multiple of FT, results from ANCOVA will produce identical conclusions.

All adjusted models included a term for T1 hormone and years between interviews. Confounding by the following T1 variables was examined: age, chronic illness (self-report of diabetes, heart disease and/or hypertension), prescription medications believed to decrease hormones, and lifestyle (smoking, alcohol intake and physical activity). Tests for interactions between each adiposity change variable and each independent variable were conducted to determine whether the relationship between hormone and adiposity change differed by the levels of these variables.


   Results
Top
 Abstract
 Introduction
 Methods
 Results
Discussion
 References
 
Baseline characteristics of participants

At baseline (T1), the original cohort (n = 1709) was predominantly white (95%), employed (78%), and high school educated (89%; data not shown). These demographics closely match the 1990 Massachusetts’ population. Men in the analysis sample were slightly younger at T1 (mean (S.D.), 53.8 (8.3) vs 55.2 (8.7); range for both 40–70 years), more likely to be employed (86%), and have a high school education (91%) than the original cohort.

At T1, 33% of men in the analysis sample reported diabetes, heart disease and/or hypertension (Table 1Go). Nine percent were on prescribed medications believed to lower hormone levels, and 22% smoked cigarettes.


View this table:
[in this window]
[in a new window]
  		Table 1 Characteristics of the analysis sample (n = 1009), Massachusetts Male Aging Study 1987–1997.
 
Unadjusted follow-up hormone levels

Mean TT levels declined from 18.0 to 15.7 nM, FT from 0.46 to 0.36 nM, and bioavailable testosterone from 8.8 to 6.8 nM from T1 to T2 (Table 1Go). Mean SHBG levels increased from 31.8 to 35.2 nM.

Men with chronic illness at T1 had significantly lower T2 TT, FT and bioavailable testosterone levels than men without chronic illness (Table 2Go). Men on medications affecting hormones at baseline had lower free and bioavailable testosterone, and higher SHBG at follow-up. Baseline hormone and follow-up hormone levels were positively correlated (P<0.0001 for all). All the hormones were inversely correlated with adiposity. Age was negatively correlated with T2 TT, FT, and bioavailable testosterone levels and positively correlated with SHBG levels. T1 physical activity was inversely correlated with T2 TT and SHBG levels; however, the correlations were small (–0.15 and –0.16 respectively). When controlling for BMI, the correlations became non-significant.


View this table:
[in this window]
[in a new window]
  		Table 2 Association between baseline (T1) health and lifestyle characteristics and follow-up (T2) hormone levels (n = 1009), Massachusetts Male Aging Study, 1987–1997.
 
Change in adiposity

The average time between T1 and T2 was 8.8 years (S.D. 0.72; range 7.1–10.4). During this period, 9% of men became overweight (T2 only group), and 64% were overweight at both waves (Table 3Go). Nearly 26% were obese at T2: 9% became obese and 17% were obese at both assessments. At T2, 45% had waist obesity, and 54% had WHR obesity. As expected, the both group with obesity had the highest BMI at T2 (34.5 compared with 25.6 kg/m2 in the neither group) and the highest fraction of men with severe obesity (33.7 compared with 0% in the neither group).


View this table:
[in this window]
[in a new window]
  		Table 3 Change in adiposity between baseline (T1) and follow-up (T2) (n = 1009), Massachusetts Male Aging Study, 1987–1997.
 
For all adiposity change variables, the T1 only group was small (range 3–11%). Many of these men had serious illness at follow-up. For example, among the 26 who were obese at T1 only, 17 (65%) reported at least one of the following at T2: cancer (lymphoma, prostate, kidney, or intestine), heart disease, diabetes, hypertension or HIV. In the T1 only group, for the other adiposity measures, the follow-up prevalence of at least one of these illnesses was also high: overweight 55%, waist obesity 60%, and WHR obesity 49%.

Adjusted follow-up hormone levels

Figure 1Go displays adjusted mean (S.E.M.) T2 hormone levels against adiposity change. The numbers above the means are Bonferroni adjusted P-values for the comparison between the respective adiposity change category and the neither group (referent group).


Figure 1
View larger version (16K):
[in this window]
[in a new window]
  		Figure 1 Adjusted follow-up (T2) mean (± S.E.M.) hormones in the four adiposity change groups (neither, T1, only, T2 only, both). BMI, body mass index; WHR, waist-to-hip ratio; TT, told testosterone; FT, free testosterone; SHBG, sex hormone-binding globulin.

 
Men who became overweight between T1 and T2 (P = 0.0272) or who were overweight at both waves (P = 0.0001), had significantly lower T2 mean TT than the men who were not overweight at either assessment (Fig. 1aGo). The results were similar for SHBG (T2 only, P = 0.0007; both, P = 0.0008). However, FT levels were not significantly different between any of the overweight groups and the neither group.

For obesity change, the TT and SHBG results (Fig. 1bGo) were very similar to the overweight change except that men who were obese at both times did not have significantly lower SHBG than the neither group. FT levels in the ‘both’ group were significantly lower than in the ‘neither’ group (P = 0.0028).

Compared to the neither group, having waist obesity at both waves resulted in lower mean T2 levels of all three hormones (Fig. 1cGo). In addition, the T2 only group with waist obesity had lower SHBG levels than the neither group (P = 0.0034). For WHR obesity, the both group had lower mean T2 TT and SHBG (Fig. 1dGo). No significant differences were observed for FT.

For all comparisons, none of the means for the T1 only group were significantly different from those for the neither group.

Overall, 14% of the sample had TT <300 ng/dl (10.4 nM) and 37% had FT levels less than the lower limit of the normal range at T2. Importantly, men who became obese at T2 had a higher prevalence of TT levels <300 ng/dl than the group that was not obese at either time (18 vs 9% respectively). However, the prevalence of low FT levels was similar in both these groups (29 vs 34% respectively).

Unadjusted rates of change in hormone levels

Figure 2Go displays unadjusted mean hormone levels at T1 and T2 against adiposity change. Compared with the neither group, the T2 only and both groups tended to have lower baseline and follow-up mean hormone levels. All changes occurred in the expected direction; TT and FT declined over time, and SHBG increased, except that SHBG decreased in the T2 only group for overweight, obesity and waist obesity. For TT, the T2 only group experienced the fastest declines for overweight and obesity categories, whereas for waist and WHR obesity, the both group decreased most rapidly.


Figure 2
View larger version (26K):
[in this window]
[in a new window]
  		Figure 2 Unadjusted baseline (T1) and follow-up (T2) mean hormones against adiposity change. BMI, body mass index; WHR, waist-to-hip ratio; TT, total testosterone; FT, free testosterone; SHBG, sex hormone-binding globulin. To convert nM to ng/dl, divide by 0.0347. Massachusetts Male Aging Study, n = 1009, 1987–1997.

 
Adjusted rates of change in hormone levels

Table 4Go presents the adjusted rates of change (or slopes) in hormone levels (nM/year) between T1 and T2 against adiposity change. For TT, the rate of decline for the both group was more than double the rate for the neither group for all adiposity measures. For example, TT decreased by 0.43 nM/year for men who were obese at both waves compared with 0.21 nM/year for those obese at neither wave (P = 0.0008). For overweight and obesity, the T2 only group also experienced significantly steeper declines than the neither group (P = 0.0386 and 0.0032 respectively).


View this table:
[in this window]
[in a new window]
  		Table 4 Adjusted mean rate of change in hormone between baseline (T1) and follow-up (T2) in the four adiposity change categories (n = 1009), Massachusetts Male Aging study, 1987–1997.
 
For FT, the both group with obesity and waist obesity dropped significantly faster than the neither group (P = 0.0038 and 0.0046 respectively). No other rates were significantly different from the neither group.

Men who were overweight at both waves experienced a significantly smaller rate of increase in SHBG than in men who were overweight at neither wave: 0.25 vs 0.81 nM/year respectively (P = 0.0003). Similarly, the rate of change in SHBG for men who had WHR obesity at both waves was significantly different from the neither group. However, in this case, the mean increase for the both group was indistinguishable from zero (mean (95% confidence interval), 0.08 (–0.098, 0.26)), indicating that while SHBG for the neither group increased, it stayed about the same for the both group.

The T2 only group had significantly different rates of change in SHBG than the neither group for all measures except WHR obesity. SHBG in the neither group increased, but the rates of change for the T2 only group were not different from zero.


   Discussion
Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
References
 
Using data from the MMAS, a prospective, population-based survey, we found that T2 TT levels were significantly lower in men who became overweight by T2, or were overweight at both waves, compared with men who were not overweight at either wave. The same was true for obesity. However, T2 FT levels did not differ between overweight and non-overweight men, or between those who became obese and who were not obese at either wave.

Men who became overweight or obese are of particular interest because they provide insights into the effects of weight gain on changes in TT and FT. Compared with men who were not overweight or obese at either wave those who were overweight or obese experienced a greater rate of decline in TT levels and a lesser age-related increase in SHBG levels. However, their rate of decline in FT level was not significantly lower than men who were not obese or overweight at either time. Therefore, the larger rates of decline in TT levels in men who gained weight in the follow-up period than in men who did not can be attributed, in large part, to the differences in the rates of change in SHBG.

Lower SHBG levels in obese men have been attributed in part to the hyperinsulinemia associated with obesity (4, 34–37). Cross-sectional surveys have consistently demonstrated an inverse association between BMI and SHBG levels (34, 38). Obesity and weight gain are associated with higher insulin levels, which suppress hepatic SHBG production (39–41). In contrast, aging and chronic inflammatory conditions are associated with higher SHBG levels (5, 42–44). Thus, in obese, middle-aged and older men, the effects of adiposity are attenuated by those of age and illness. Not surprisingly, in our cohort, the rates of age-related increase in SHBG were lower in men who gained weight than in men who did not.

Unlike cross-sectional studies, the longitudinal design of the MMAS allowed us to evaluate the effects of changes in obesity on changes in hormones. In addition, we controlled for confounding by age, co-morbid conditions, and lifestyle. Our analysis demonstrates that both groups of obese men – those who were obese at both waves and those who became obese during the follow-up period – had greater rates of decline in TT levels and lower rates of increase in SHBG level than could be accounted for by aging alone.

The MMAS data on sex hormone levels are consistent with previous reports (43, 45–47). TT and SHBG levels correlated inversely with BMI, waist circumference, and WHR. Age correlated inversely with TT and FT levels and directly with SHBG levels. As expected the men with chronic illness also had lower TT, FT, and bioavailable testosterone levels than men who did not report a chronic illness. Smokers had higher TT, FT, and bioavailable testosterone levels, consistent with some previous reports (48, 49) but not with others (50, 51). Some of the inconsistencies across studies of androgens and smoking may be attributed to differences in the population (healthy versus not), and some studies adjusted for confounding factors, while others did not.

Nine percent of the MMAS cohort became overweight between T1 and T2, and 64% were overweight at both time points. Twenty-six percent either became obese by T2 or were obese at both time points. Therefore, a significant proportion of middle-aged and older men were obese at T2; furthermore, a substantial proportion gained weight and became obese. A small proportion of the cohort (3–11%) was overweight or obese and lost weight during the follow-up period, so that they were no longer overweight or obese at T2. Most of these men developed serious health problems, such as cancer or heart disease. Their illness may have caused them to lose weight, or their physicians may have urged them to lose weight due to their illness.

The men who became obese at T2 had a higher prevalence of TT levels < 300 ng/dl than the group that was not obese at either time (18 vs 9% respectively). However, the prevalence of low FT levels was similar in the two groups (29 vs 34% respectively). The clinical implication of these findings is that the evaluation of androgen deficiency in middle-aged and older men is complicated by the high prevalence of obesity and other confounding factors, such as chronic illness, lifestyle, and medications, all of which can affect TT levels through their effects on SHBG and/or hypothalamic–pituitary–testicular function. In any individual patient, the effects of obesity and weight gain on SHBG levels and TT levels are superimposed upon, and may not be easily distinguishable from, the effects of age and associated co-morbid conditions on testicular testosterone production rates. Therefore, in middle-aged and older obese men, the measurement of FT or bioavailable testosterone levels using a reliable assay system that is not affected by the prevalent SHBG concentrations is essential in making a correct diagnosis of androgen deficiency. Exclusive reliance on TT alone in the diagnostic work-up of androgen deficiency could result in misclassification and inappropriate treatment choices. Owing to the high prevalence of obesity and weight gain in the general population of middle-aged and older men, as indicated by this and other surveys, this misclassification of men being evaluated for possible androgen deficiency could have significant clinical consequences.


   Funding
 
This work was supported by the following grants: AG 04673 from the National Institute on Aging, and by grants DK 44995, DK 51345 from the National Institute of Diabetes and Digestive and Kidney Disorders.


   References
Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 References
 

    1. De Moor P & Joossens JV. An inverse relation between body weight and the activity of the steroid binding -globulin in human plasma. Steroidologia 1970 1 129–136.[Medline]

    2. Glass AR, Swerdloff RS, Bray GA, Dahms WT & Atkinson RL. Low serum testosterone and sex-hormone-binding-globulin in massively obese men. Journal of Clinical Endocrinology and Metabolism 1977 45 1211–1219.[ISI][Medline]

    3. Amatruda JM, Harman SM, Pourmotabbed G & Lockwood DH. Depressed plasma testosterone and fractional binding of testosterone in obese males. Journal of Clinical Endocrinology and Metabolism 1978 47 268–271.[Abstract]

    4. Giagulli Va KJ & Vermeulen A. Pathogenesis of the decreased androgen levels in obese men. Journal of Clinical Endocrinology and Metabolism 1993 79 997–1000.

    5. Leifke E, Gorenoi V, Wichers C, Von Zur Muhlen A, Von Buren E & Brabant G. Age-related changes of serum sex hormones, insulin-like growth factor-1 and sex-hormone binding globulin levels in men: cross-sectional data from a healthy male cohort. Clinical Endocrinology 2000 53 689–695.[CrossRef][Medline]

    6. Barrett-Connor E & Khaw KT. Endogenous sex hormones and cardiovascular disease in men. A prospective population-based study. Circulation 1988 78 539–545.[Abstract/Free Full Text]

    7. Khaw KT & Barrett-Connor E. Lower endogenous androgens predict central adiposity in men. Annals of Epidemiology 1992 2 675–682.[Medline]

    8. Peiris AN, Sothmann MS, Aiman EJ & Kissebah AH. The relationship of insulin to sex hormone-binding globulin: role of adiposity. Fertility and Sterility 1989 52 69–72.[ISI][Medline]

    9. Haffner SM, Katz MS, Stern MP & Dunn JF. The relationship of sex hormones to hyperinsulinemia and hyperglycemia. Metabolism 1988 37 683–688.[CrossRef][ISI][Medline]

    10. Haffner SM. Sex hormone-binding protein, hyperinsulinemia, insulin resistance and noninsulin-dependent diabetes. Hormone Research 1996 45 233–237.[ISI][Medline]

    11. Pasquali R, Casimirri F, De Iasio R, Mesini P, Boschi S, Chierici R, Flamia R, Biscotti M & Vicennati V. Insulin regulates testosterone and sex hormone-binding globulin concentrations in adult normal weight and obese men. Journal of Clinical Endocrinology and Metabolism 1995 80 654–658.[Abstract]

    12. Segal KR, Dunaif A, Gutin B, Albu J, Nyman A & Pi-Sunyer FX. Body composition, not body weight, is related to cardiovascular disease risk factors and sex hormone levels in men. Journal of Clinical Investigation 1987 80 1050–1055.[ISI][Medline]

    13. Kley HK, Deselaers T & Peerenboom H. Evidence for hypogonadism in massively obese males due to decreased free testosterone. Hormone and Metabolic Research 1981 13 639–641.[ISI][Medline]

    14. Schneider G, Kirschner MA, Berkowitz R & Ertel NH. Increased estrogen production in obese men. Journal of Clinical Endocrinology and Metabolism 1979 48 633–638.[Abstract]

    15. Zumoff B, Miller LK & Strain GW. Reversal of the hypogonadotropic hypogonadism of obese men by administration of the aromatase inhibitor testolactone. Metabolism 2003 52 1126–1128.[ISI][Medline]

    16. Strain GW, Zumoff B, Kream J, Strain JJ, Deucher R, Rosenfeld RS, Levin J & Fukushima DK. Mild hypogonadotropic hypogonadism in obese men. Metabolism 1982 31 871–875.[CrossRef][ISI][Medline]

    17. Strain GW, Zumoff B, Miller LK, Rosner W, Levit C, Kalin M, Hershcopf RJ & Rosenfeld RS. Effect of massive weight loss on hypothalamic–pituitary–gonadal function in obese men. Journal of Clinical Endocrinology and Metabolism 1988 66 1019–1023.[Abstract]

    18. Bray GA, Dahms WT, Swerdloff RS, Fiser RH, Atkinson RL & Carrel RE. The Prader–Willi syndrome: a study of 40 patients and a review of the literature. Medicine 1983 62 59–80.[Medline]

    19. Farooqi IS. Leptin and the onset of puberty: insights from rodent and human genetics. Seminars in Reproductive Medicine 2002 20 139–144.[CrossRef][ISI][Medline]

    20. O’Donnell AB, Araujo AB & McKinlay JB. The health of normally aging men: the Massachusetts Male Aging Study (1987–2004). Experimental Gerontology 2004 39 975–984.[CrossRef][ISI][Medline]

    21. Mohr BA, Guay AT, O’Donnell AB & McKinlay JB. Normal, bound and nonbound testosterone levels in normally ageing men: results from the Massachusetts Male Ageing Study. Clinical Endocrinology 2005 62 64–73.[CrossRef][Medline]

    22. McKinlay SM, Kipp DM, Johnson P, Downey K & Carelton RA. A field approach for obtaining physiological measures in surveys of general populations: response rates, reliability and costs. In: Proceedings of the Fourth Conference on Health Survey Research Methods. Washington, DC: USDHHS-PHS Publication 84-3346, 1984.

    23. National Institutes of Health. Clinical guidelines on the identification, evaluation, and treatment of overweight and obesity in adults – the evidence report. Obesity Research 1998 6 51S–209S.[ISI][Medline]

    24. Chobanian AV, Bakris GL, Black HR, Cushman WC, Green LA, Izzo JL Jr, Jones DW, Materson BJ, Oparil S, Wright JT Jr & Roccella EJ on behalf of the Joint National Committee on Prevention, Detection, Evaluation and Treatment of High Blood Pressure, National Heart, Lung and Blood Institute and National High Blood Pressure Education Program Coordinating Committee. Seventh report of the Joint National Committee on Prevention, Detection, Evaluation and Treatment of High Blood Pressure. Hypertension 2003 42 1206–1252.[Abstract/Free Full Text]

    25. World Health Organization Obesity: preventing and managing the Global Epidemic. Report of a WHO consultation. World Health Organization Technical Report Series 894 1–253.

    26. Lemieux S, Prud’homme D, Bouchard C, Tremblay A & Despres JP. A single threshold value of waist girth identifies normal-weight and overweight subjects with excess visceral adipose tissue. American Journal of Clinical Nutrition 1996 64 685–693.[Abstract/Free Full Text]

    27. Khavari KA & Farber PD. A profile instrument for the quantification and assessment of alcohol consumption. The Khavari alcohol test. Journal of Studies on Alcohol 1978 39 1525–1539.[ISI][Medline]

    28. Sallis JF, Haskell WL, Wood PD, Fortmann SP, Rogers T, Blair SN & Paffenbarger RS, Jr. Physical activity assessment methodology in the Five-City Project. American Journal of Epidemiology 1985 121 91–106.[Abstract/Free Full Text]

    29. Mcevoy G. American Hospital Formulary Service Drug Information. Bethesda, MD: American Society of Hospital Pharmacists, 1989.

    30. Bremner WJ, Vitiello MV & Prinz PN. Loss of circadian rhythmicity in blood testosterone levels with aging in normal men. Journal of Clinical Endocrinology and Metabolism 1983 56 1278–1281.[Abstract]

    31. Brambilla DJ, McKinlay SM, McKinlay JB, Weiss SR, Johannes CB, Crawford SL & Longcope C. Does collecting repeated blood samples from each subject improve the precision of estimated steroid hormone levels? Journal of Clinical Epidemiology 1996 49 345–350.[CrossRef][ISI][Medline]

    32. Sodergard R, Backstrom T, Shanbhag V & Carstensen H. Calculation of free and bound fractions of testosterone and estradiol-17 beta to human plasma proteins at body temperature. Journal of Steroid Biochemistry 1982 16 801–810.[CrossRef][ISI][Medline]

    33. Vermeulen A, Verdonck L & Kaufman JM. A critical evaluation of simple methods for the estimation of free testosterone in serum. Journal of Clinical Endocrinology and Metabolism 1999 84 3666–3672.[Abstract/Free Full Text]

    34. Heald AH, Anderson SG, Ivison F, Riste L, Laing I, Cruickshank JK & Gibson JM. Low sex hormone binding globulin is a potential marker for the metabolic syndrome in different ethnic groups. Experimental and Clinical Endocrinology and Diabetes 2005 113 522–528.

    35. Pasquali R, Vicennati V, Bertazzo D, Casimirri F, Pascal G, Tortelli O & Labate AM. Determinants of sex hormone-binding globulin blood concentrations in premenopausal and postmenopausal women with different estrogen status. Virgilio-Menopause-Health Group. Metabolism 1997 46 5–9.[ISI][Medline]

    36. Laing I, Olukoga AO, Gordon C & Boulton AJ. Serum sex-hormone-binding globulin is related to hepatic and peripheral insulin sensitivity but not to beta-cell function in men and women with type 2 diabetes mellitus. Diabetic Medicine 1998 15 473–479.

    37. Birkeland KI, Hanssen KF, Torjesen PA & Vaaler S. Level of sex hormone-binding globulin is positively correlated with insulin sensitivity in men with type 2 diabetes. Journal of Clinical Endocrinology and Metabolism 1993 76 275–278.[Abstract]

    38. Phillips GB. Relationship between serum sex hormones and the glucose–insulin–lipid defect in men with obesity. Metabolism 1993 42 116–120.[CrossRef][ISI][Medline]

    39. Plymate SR, Matej LA, Jones RE & Friedl KE. Inhibition of sex hormone-binding globulin production in the human hepatoma (Hep G2) cell line by insulin and prolactin. Journal of Clinical Endocrinology and Metabolism 1988 67 460–464.[Abstract]

    40. Browne-Martin K & Longcope C. Regulation of sex hormone-binding globulin secretion in human hepatoma G2 cells. Steroids 2001 66 605–607.[ISI][Medline]

    41. Crave JC, Lejeune H, Brebant C, Baret C & Pugeat M. Differential effects of insulin and insulin-like growth factor I on the production of plasma steroid-binding globulins by human hepatoblastoma-derived (Hep G2) cells. Journal of Clinical Endocrinology and Metabolism 1995 80 1283–1289.[Abstract]

    42. Feldman HA, Longcope C, Derby CA, Johannes CB, Araujo AB, Coviello AD, Bremner WJ & McKinlay JB. Age trends in the level of serum testosterone and other hormones in middle-aged men: longitudinal results from the Massachusetts Male Aging Study. Journal of Clinical Endocrinology and Metabolism 2002 87 589–598.[Abstract/Free Full Text]

    43. Harman SM, Metter EJ, Tobin JD, Pearson J & Blackman MR. Longitudinal effects of aging on serum total and free testosterone levels in healthy men. Baltimore Longitudinal Study of Aging. Journal of Clinical Endocrinology and Metabolism 2001 86 724–731.[Abstract/Free Full Text]

    44. Plymate SR, Tenover JS & Bremner WJ. Circadian variation in testosterone, sex hormone-binding globulin, and calculated non-sex hormone-binding globulin bound testosterone in healthy young and elderly men. Journal of Andrology 1989 10 366–371.[Abstract/Free Full Text]

    45. Ferrini RL & Barrett-Connor E. Sex hormones and age: a cross-sectional study of testosterone and estradiol and their bioavailable fractions in community-dwelling men. American Journal of Epidemiology 1998 147 750–754.[Abstract/Free Full Text]

    46. Lamberts SW, Van Den Beld AW & Van Der Lely AJ. The endocrinology of aging. Science 1997 278 419–424.[Abstract/Free Full Text]

    47. Morley JE, Kaiser FE, Perry HM, III, Patrick P, Morley PM, Stauber PM, Vellas B, Baumgartner RN & Garry PJ. Longitudinal changes in testosterone, luteinizing hormone, and follicle-stimulating hormone in healthy older men. Metabolism 1997 46 410–413.[CrossRef][ISI][Medline]

    48. Dai WS, Gutai JP, Kuller LH & Cauley JA. Cigarette smoking and serum sex hormones in men. American Journal of Epidemiology 1988 128 796–805.[Abstract/Free Full Text]

    49. Vermeulen A, Kaufman JM & Giagulli VA. Influence of some biological indexes on sex hormone-binding globulin and androgen levels in aging or obese males. Journal of Clinical Endocrinology and Metabolism 1996 81 1821–1826.[Abstract]

    50. English KM, Pugh PJ, Parry H, Scutt NE, Channer KS & Jones TH. Effect of cigarette smoking on levels of bioavailable testosterone in healthy men. Clinical Science (London) 2001 100 661–665.

    51. Lindholm J, Winkel P, Brodthagen U & Gyntelberg F. Coronary risk factors and plasma sex hormones. American Journal of Medicine 1982 73 648–651.[CrossRef][ISI][Medline]

Received 21 February 2006
Accepted 3 July 2006




This article has been cited by other articles:


Home page
 Eur J EndocrinolHome page
B Lapauw, S Goemaere, H Zmierczak, I Van Pottelbergh, A Mahmoud, Y Taes, D De Bacquer, S Vansteelandt, and J M Kaufman
The decline of serum testosterone levels in community-dwelling men over 70 years of age: descriptive data and predictors of longitudinal changes
Eur. J. Endocrinol., October 1, 2008; 159(4): 459 - 468.
[Abstract] [Full Text] [PDF]

Home page
 Cancer Epidemiol. Biomarkers Prev.Home page
N. Parekh, Y. Lin, S. Marcella, A. K. Kant, and G. Lu-Yao
Associations of Lifestyle and Physiologic Factors with Prostate-Specific Antigen Concentrations: Evidence from the National Health and Nutrition Examination Survey (2001-2004)
Cancer Epidemiol. Biomarkers Prev., September 1, 2008; 17(9): 2467 - 2472.
[Abstract] [Full Text] [PDF]

Home page
 J. Clin. Endocrinol. Metab.Home page
F. C. W. Wu, A. Tajar, S. R. Pye, A. J. Silman, J. D. Finn, T. W. O'Neill, G. Bartfai, F. Casanueva, G. Forti, A. Giwercman, et al.
Hypothalamic-Pituitary-Testicular Axis Disruptions in Older Men Are Differentially Linked to Age and Modifiable Risk Factors: The European Male Aging Study
J. Clin. Endocrinol. Metab., July 1, 2008; 93(7): 2737 - 2745.
[Abstract] [Full Text] [PDF]

Home page
 J. Clin. Endocrinol. Metab.Home page
A. B. Araujo, G. R. Esche, V. Kupelian, A. B. O'Donnell, T. G. Travison, R. E. Williams, R. V. Clark, and J. B. McKinlay
Prevalence of Symptomatic Androgen Deficiency in Men
J. Clin. Endocrinol. Metab., November 1, 2007; 92(11): 4241 - 4247.
[Abstract] [Full Text] [PDF]

Home page
 Eur J EndocrinolHome page
B. B Yeap, O. P Almeida, Z. Hyde, P. E Norman, S A P. Chubb, K. Jamrozik, and L. Flicker
In men older than 70 years, total testosterone remains stable while free testosterone declines with age. The Health in Men Study
Eur. J. Endocrinol., May 1, 2007; 156(5): 585 - 594.
[Abstract] [Full Text] [PDF]

This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via ISI Web of Science (4)
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Mohr, B. A
Right arrow Articles by McKinlay, J. B
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Mohr, B. A
Right arrow Articles by McKinlay, J. B

HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS