Longitudinal relationships of circulating reproductive hormone with functional disability, muscle mass, and strength in community-dwelling older men: the Concord Health and Ageing in Men project.

ORIGINAL E n d o c r i n e

ARTICLE R e s e a r c h

Longitudinal Relationships of Circulating Reproductive Hormone With Functional Disability, Muscle Mass, and Strength in Community-Dwelling Older Men: The Concord Health and Ageing in Men Project Benjumin Hsu, Robert G. Cumming, Vasi Naganathan, Fiona M. Blyth, David G. Le Couteur, Markus J. Seibel, Louise M. Waite, and David J. Handelsman School of Public Health (B.H., R.G.C.), University of Sydney, Sydney 2006, New South Wales, Australia; Centre of Education and Research on Ageing (B.H., R.G.C., V.N., F.M.B., D.G.L.C., L.M.W.) and ANZAC Research Institute (R.G.C., D.G.L.C, M.J.S., D.J.H.), University of Sydney and Concord Hospital, Sydney 2139, New South Wales, Australia Context: The relationship between functional disability and reproductive hormones and whether it is mediated by muscle mass and strength in older men are unclear. Objectives: The objective of the study was to identify the relationships between hormones and change in functional disability over a 2-year follow-up and to examine whether muscle mass and strength explain any of the observed relationships. Design, Setting, and Participants: A total of 1318 men aged 70 years and older from the Concord Health and Ageing in Men Project study were assessed at both baseline and 2-year follow-up. T, DHT, estradiol (E2), and estrone (E1) were measured by liquid chromatography-tandem mass spectrometry and SHBG, LH, and FSH by immunoassay. Outcome Measures: Functional disability was measured by basic Activities of Daily Living scale at both time points. Grip and quadricep strength were measured using dynamometers and lean (muscle) mass was determined by dual X-ray absorptiometry. Results: All hormones were significantly associated with functional decline in univariate analyses. Only T, E2, E1, and calculated free T remained associated in multivariate analyses. Men in the lowest T quartile (vs the highest quartile) had an increased risk functional decline (odds ratio 1.96, 95% confidence interval 1.01–3.82). Similar associations were observed in E2, E1, and calculated free T. When muscle variables were added into the multivariate model, the associations between these hormones and functional decline were no longer statistically significant. Conclusion: Low T, E2, and E1 were significantly associated with prospective functional decline over 2 years. This relationship was no longer significant when muscle mass or strength were added, suggesting that the hormonal associations are mediated through their sequential effect on muscle mass and strength. (J Clin Endocrinol Metab 99: 3310 –3318, 2014)

ith increasing life expectancy, the number of older people with functional disability will increase dramatically (1, 2). Functional disability is strongly associ-

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ated with many medical conditions and adverse health outcomes, including chronic diseases (diabetes, arthritis, and osteoporosis), physical frailty indicators (gait speed,

ISSN Print 0021-972X ISSN Online 1945-7197 Printed in U.S.A. Copyright © 2014 by the Endocrine Society Received January 14, 2014. Accepted March 5, 2014. First Published Online March 14, 2014

Abbreviations: ADL, activity of daily living; BMI, body mass index; cFT, calculated free T; CI, confidence interval; CHAMP, Concord Health and Ageing in Men Project; E1, estrone; E2, estradiol; OR, odds ratio.

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J Clin Endocrinol Metab, September 2014, 99(9):3310 –3318

doi: 10.1210/jc.2014-1124

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doi: 10.1210/jc.2014-1124

and muscle strength), admission to long-term care institutions and mortality (3, 4). The age-related decline in serum T is associated with reduced muscle mass and strength (5, 6). It is also clear that lower muscle strength is associated with functional disability (7). However, there has been little research on the relationships between functional disability and serum T and other major reproductive hormones in men, and it is not clear whether the relationship between hormones and functional disability is mediated by muscle mass and strength. The Framingham Offspring Study reported longitudinal associations in which lower levels of calculated free T were associated with increased risk, or worsening of, mobility limitation (8). However, the Longitudinal Ageing Study Amsterdam, in analyses of cross-sectional data, found no relationship between either total T or estradiol by immunoassay and functional limitation (9). These studies are the only population-based epidemiological studies to date that have reported findings on this relationship. Furthermore, there have been no studies of other major reproductive hormones such as DHT and estrone (E1), in addition to T and estradiol (E2), and functional disability in older men. The objectives of our study were to do the following: 1) examine the relationships in older men between reproductive hormones and change in functional disability over 2 years; and 2) examine whether reduced muscle mass or strength explains any observed associations between reproductive hormones and functional disability. Our hypothesis was that reproductive hormones in men are causally related to functional disability, in which the relationship is mediated through muscle mass and strength.


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conducted between January 2007 and October 2009, with identical measurements as at baseline.

Reproductive hormone measurement Subjects had an early-morning fasting blood sample taken, with serum stored at ⫺80°C until assay. Measurements of serum T, DHT, E2, and E1 were by liquid chromatography-tandem mass spectrometry as validated elsewhere (11). Serum LH, FSH, and SHBG were measured by automated immunoassays (Roche Diagnostics Australia), with coefficients of variation between 1.0% and 2.0% (12). The calculated free T (cFT) levels were computed using an empirical formula recently validated in two large data sets consisting of more than 6000 blood samples (13, 14).

Outcome measurement Functional disability was defined using the Katz activity of daily living (ADL) questionnaire (15). The seven ADL questions were as follows: do you need help from another person or special equipment or device to do any of the following: walking across a small room, bathing or showering, personal grooming, dressing, eating, getting from a bed to a chair, and using the toilet. Participants were classified into different ADL stages, ranging from stage 0 to IV. Stages 0-IV indicate groups of people with increasing difficulties with ADLs. The classification of ADL stages was according to the definition given by Stineman et al (16); the ADL stage threshold definitions have been reported in detail elsewhere. Individuals in stage 0 have no difficulty in any of the ADLs. Stage I is mild difficulty, which included individuals able to eat and toilet without difficulty but may have some difficulty with the other ADLs. Stage II is moderate difficulty, which included individuals able to eat without difficulty but may have some difficulty with toilet, dress, or transfer and may be incapable to bathe or walk. Stage III is severe difficulty, which included individuals able to perform at least one ADL with or without assistance but not able to meet the stage II threshold definition. Stage IV is complete difficulty; this stage of total ADL limitation included individuals unable to perform any of the ADLs.

Other measurement

Materials and Methods Study subjects The Concord Health and Ageing in Men Project (CHAMP) is a longitudinal, observational study of the epidemiology of male aging conducted among men living within the three local government areas (Burwood, Canada Bay, and Strathfield) surrounding Concord Hospital in Sydney, New South Wales, Australia (10). Men were selected from the New South Wales electoral roll; enrollment is compulsory in Australia. Potential subjects were community-dwelling men aged at least 70 years, with no other inclusion or exclusion criteria. A total of 1705 subjects were enrolled in the CHAMP study. The study design has been reported in detail elsewhere (10). Baseline measurements were conducted between January 2005 and June 2007; data were collected using self-reported questionnaires, interviewer-administered questionnaires, and a wide range of clinical assessments. Follow-up assessments were

Tobacco usage status (current, ex-, or never smoker) was assessed through the self-reported questionnaires. Subjects were also asked whether a doctor or other health care provider had have ever told them that they had any of 19 disorders listed in the questionnaire: diabetes, thyroid dysfunction, osteoporosis, Paget’s disease, stroke, Parkinson’s disease, kidney stone, dementia, depression, epilepsy, hypertension, myocardial infarction, angina, congestive heart failure, intermittent claudication, chronic lung disease, liver disease, chronic kidney disease, or arthritis. A comorbidity score was calculated as the total of all the conditions reported. Body mass index (BMI) was calculated from clinic measurements of height, using a Harpenden stadiometer, and weight. Handgrip strength was measured with a Jamar dynamometer (Promedics). Participants performed two trials on each hand, and the mean value of the two trials was obtained. The maximum strength in either hand was used as the handgrip strength for analyses. Quadricep strength was measured using a spring gauge; only one trial was performed on each leg. The highest quadriceps strength on either leg was used. Data for quadriceps strength


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Sex Hormones, Muscle, and Functional Disability

were missing for 445 men at baseline. This mainly occurred because measurement of quadricep strength was added to the study protocol after 171 men had already completed their baseline assessments and another 203 men could not do the quadriceps strength test because of significant knee pain. Muscle mass was measured using dual X-ray absorptiometry (Discovery-W scanner; Hologic). The method details have been reported elsewhere (17).

Statistical analysis The primary analysis examined the longitudinal association between baseline reproductive hormone levels and functional decline. Of the 1705 men, a total of 1318 men (77%) were included in longitudinal analyses in this paper. This excluded men with missing data for ADL (n ⫽ 21) or reproductive hormones (n ⫽ 25) or androgen or antiandrogen treatment (n ⫽ 20). Ninetynine men died before the 2-year follow-up visit and 222 living men declined to attend the follow-up clinic visit. Men were categorized into quartiles according to their baseline level of each of the studied reproductive hormones. Functional decline was defined as change in one or more ADL stage levels (moving from stage 0 to I, I to II, etc). Logistic regressions models were used to examine the relationships between baseline hormone quartiles and functional decline (no change/improvement vs decline in ADL stages). The secondary analyses first examined cross-sectionally (n ⫽ 1685) the associations between reproductive hormones and muscle strength (handgrip strength and quadriceps strength) and lean muscle mass (arm and leg) using multivariate linear regression models. The muscle mass and strength variables, both baseline measure and changes over the 2-year follow-up, were then added to the logistic regression models looking at the longitudinal relationships between reproductive hormones and functional decline. The same subjects were used for each pair of models for each muscle-mediator variable (grip strength, quadriceps strength, arm lean mass, and leg lean mass) to compare odds ratios with and without the respective muscle-mediator variables. This reduces the risk of adding selection bias as an explanation for any observed differences in results if the analyses were conducted on different subjects for each pair of models. The model ⫽ building strategy for all analyses included covariates of significance and relevance: age, BMI, smoking status, and comorbidity. All analyses were repeated fitting the reproductive hormones as continuous variables to verify our findings using quartiles of hormone levels. Models were fit using SPSS software version 20 (IBM Corp) and SAS software version 9.2 (SAS Institute Inc).

Ethics approval CHAMP was approved by the Concord Hospital Human Research Ethics Committee, and study participants provided written informed consent for all procedures.

Results The men in our analytic sample had a mean age of 76 ⫾ 5.1 years (range 70 –97 y), a mean BMI of 28 kg/m2, and most had more than two comorbidities (Table 1). Five percent


Table 1. Characteristic of Analytical Sample (n ⫽ 1318) Analytic Sample Mean (SD) or n, % Age (mean) BMI (mean) Comorbidity (mean) Comorbidity, n None One Two Three Four or more Smoking status Nonsmoker Ex-smoker Current smoker T, ng/mL SHBG, nmol/L DHT, ng/mL FSH, IU/L LH, IU/L E2, pg/mL E, pg/mL cFT, pmol/L Functional decline Handgrip strength, kg Quadricep strength, kg

76.3 (5.1) 27.8 (4.0) 2.4 (1.7) 137 (10%) 278 (21%) 338 (26%) 240 (19%) 325 (24%) 500 (39%) 731 (56%) 69 (5%) 4.3 (1.8) 49.1 (20.1) 0.4 (0.2) 14.3 (14.7) 9.3 (8.1) 25.4 (12.7) 40.1 (15.2) 60.5 (21.7) 111 (9%) 35.0 (7.4) 31.3 (8.0)

of men were current smokers and 56% were ex-smokers. One hundred eleven men (9%) had functional decline, assessed by change in ADL stage levels, over the 2-year follow-up period. Two percent of the men had reported improvement in functional disability; these men were categorized with the men with no change in functional disability because the two groups had no difference in their baseline characteristics (results not shown). The men not included in the analyses were more likely to have some difficulties with one or more ADLs at baseline. There were no differences in the mean T, E2, and E1 levels between the men excluded and the analyzed sample (results not shown). The excluded men had significantly lower cFT levels (mean of 56.2 pmol/L), were older (79 y), had more comorbidities, and were more likely to be a current or ex-smoker. There were no important differences between the 99 men who died and the 222 living men who did not return for the follow-up. The longitudinal associations between baseline reproductive hormones and functional decline are presented in Table 2. Levels of all reproductive hormones measured in this study were significantly associated with functional decline in unadjusted univariate analyses. For example, compared with men in the highest hormone quartile, men in the lowest T quartile had an unadjusted odds ratio (OR) of 2.85 [95% confidence interval (CI) 1.53–5.31] and men in the lowest E2 quartile have an OR of 2.23 (95% CI


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Table 2. Unadjusted, Age-Adjusted, and Multivariable-Adjusted ORs for Associations Between Reproductive Hormone Quartiles and Functional Decline From Baseline to 2-Year Follow-Up (n ⫽ 1318)a Unadjusted

ⴙAge

ⴙBMI, Smoking

ⴙComorbidity

1.00 2.08 (1.10 –3.93) 1.51 (0.78 –2.96) 2.85 (1.53–5.31)

1.00 2.01 (1.05–3.83) 1.58 (0.80 –3.12) 2.62 (1.39 – 4.94)

1.00 1.90 (0.99 –3.64) 1.37 (0.69 –2.73) 2.17 (1.13– 4.18)

1.00 1.83 (0.95–3.52) 1.30 (0.65–2.59) 1.96 (1.01–3.82)

1.00 0.83 (0.48 –1.44) 0.61 (0.34 –1.11) 0.84 (0.49 –1.45)

1.00 1.02 (0.57–1.80) 0.95 (0.51–1.76) 1.40 (0.78 –2.51)

1.00 0.98 (0.55–1.77) 0.85 (0.45–1.61) 1.15 (0.63–2.13)

1.00 0.98 (0.54 –1.77) 0.83 (0.44 –1.58) 1.07 (0.58 –1.99)

1.00 1.53 (0.83–2.83) 1.47 (0.79 –2.72) 2.04 (1.13–3.71)

1.00 1.56 (0.84 –2.92) 1.66 (0.88 –3.11) 1.98 (1.08 –3.64)

1.00 1.43 (0.76 –2.70) 1.54 (0.81–2.90) 1.61 90.85–3.05)

1.00 1.33 (0.70 –2.51) 1.43 (0.75–2.71) 1.38 (0.72–2.63)

1.00 0.74 (0.44 –1.26) 0.65 (0.38 –1.13) 0.44 (0.24 – 0.80)

1.00 0.93 (0.54 –1.60) 0.90 (0.51–1.59) 0.64 (0.34 –1.21)

1.00 0.90 (0.52–1.57) 0.90 (0.51–1.61) 0.63 (0.33–1.20)

1.00 0.93 (0.53–1.64) 0.95 (0.53–1.71) 0.68 (0.36 –1.30)

1.00 0.54 (0.31– 0.93) 0.63 (0.37–1.05) 0.38 (0.21– 0.70)

1.00 0.69 (0.39 –1.21) 0.94 (0.54 –1.62) 0.60 (0.32–1.14)

1.00 0.68 (0.38 –1.20) 0.92 (0.53–1.62) 0.58 (0.30 –1.11)

1.00 0.69 (0.38 –1.22) 1.02 (0.58 –1.79) 0.61 (0.32–1.17)

1.00 1.43 (0.77–2.65) 1.33 (0.71–2.49) 2.23 (1.24 – 4.03)

1.00 1.60 (0.86 –3.01) 1.49 (0.79 –2.82) 2.44 (1.34 – 4.47)

1.00 1.62 (0.85–3.06) 1.57 (0.82–2.99) 2.43 (1.31– 4.51)

1.00 1.65 (0.87–3.13) 1.55 (0.81–2.96) 2.22 (1.19 – 4.16)

1.00 1.26 (0.67–2.38) 1.31 (0.70 –2.44) 2.52 (1.41– 4.50)

1.00 1.24 (0.65–2.37) 1.37 (0.73–2.59) 2.50 (1.38 – 4.52)

1.00 1.31 (0.68 –2.51) 1.37 (0.72–2.62) 2.64 (1.44 – 4.84)

1.00 1.34 (0.70 –2.59) 1.36 (0.71–2.61) 2.49 (1.35– 4.59)

1.00 2.00 (1.03–3.87) 1.69 (0.86 –3.35) 3.30 (1.75– 6.22)

1.00 1.99 (1.02–3.88) 1.71 (0.86 –3.42) 2.59 (1.35– 4.97)

1.00 1.92 (0.98 –3.76) 1.44 (0.71–2.92) 2.21 (1.13– 4.31)

1.00 1.85 (0.94 –3.65) 1.38 (0.68 –2.80) 1.98 (1.01–3.91)

T Highest Third Second Lowest SHBG Highest Third Second Lowest DHT Highest Third Second Lowest FSH Highest Third Second Lowest LH Highest Third Second Lowest E2 Highest Third Second Lowest E1 Highest Third Second Lowest cFT Highest Third Second Lowest a

Functional decline was defined as change in one or more ADL stage levels (moving from stage 0 to I, I to II, etc).

1.24 – 4.03) for functional decline. In multivariable models adjusted for age, BMI, smoking status, and comorbidities, only T, E2, E1, and cFT remained associated with functional decline. The adjusted ORs for functional decline when compared with men in the highest hormone quartile were 1.96 (95% CI 1.01–3.82) for men in the lowest T quartile, 2.22 (95% CI 1.19 – 4.16) for men in the lowest E2 quartile, 2.49 (95% CI 1.35– 4.59) for men in the lowest E1 quartile, and 1.98 (95% CI 1.01–3.91) for men the lowest cFT quartile. The cross-sectional relationship between T, E2, E1, and cFT and muscle mass and strength at baseline are presented in Table 3. Only T, E2, and cFT were significantly associated with handgrip strength, with T having a stronger association than E2. In the unadjusted model, each

1-SD increase in T was associated with a 0.1-kg increase in handgrip strength. This association was weaker in the multivariable adjusted model adjusted for age, BMI, smoking status, and comorbidities, with each 1-SD increase in T associated with a 0.07-kg increase in handgrip strength. Only E1 was statistically significantly associated with quadriceps strength. In the multivariable adjusted model, each 1-SD increase in E1 was associated with a 0.05-kg increase in quadricep strength. T, E2, E1, and cFT were all statistically significantly associated with arm and leg muscle mass. E1 was also significantly associated with change in quadriceps strength, and cFT was associated with change in leg muscle mass from baseline to 2 years, whereas T and E2 were not associated with change in either muscle mass or strength (results not shown).


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Table 3. Cross-Sectional Associations Between Reproductive Hormones, Handgrip and Quadricep Strength, and Arm and Leg Lean Mass (n ⫽ 1685) Unadjusted ␤ (95% CI)

ⴙAge ␤ (95% CI)

ⴙBMI, Smoking ␤ (95% CI)

ⴙComorbidity ␤ (95% CI)

0.101 (0.051, 0.151) ⫺0.007 (⫺0.066, 0.052) ⫺0.008 (⫺0.057, 0.041) ⫺0.067 (⫺0.116, ⫺0.018)

0.072 (0.026, 0.118) ⫺0.016 (⫺0.070, 0.038) ⫺0.031 (⫺0.076, 0.153) ⫺0.085 (⫺0.132, ⫺0.038)

0.087 (0.039, 0.13) 0.039 (⫺0.016, 0.094) 0.094 (0.051, 0.137) 0.062 (0.020, 0.104)

0.066 (0.018, 0.114) 0.024 (⫺0.030, 0.079) 0.083 (0.040, 0.126) 0.051 (0.010, 0.093)

0.051 (0.002, 0.100) 0.019 (⫺0.037, 0.074) 0.074 (0.026, 0.122) 0.072 (0.023, 0.120)

0.054 (0.008, 0.098) 0.030 (⫺0.024, 0.084) 0.078 (0.032, 0.124) 0.075 (0.028, 0.122)

0.051 (0.005, 0.099) 0.018 (⫺0.034, 0.070) 0.074 (0.033, 0.115) 0.068 (0.028, 0.109)

0.041 (⫺0.005, 0.087) 0.012 (⫺0.042, 0.067) 0.069 (0.028, 0.110) 0.063 (0.023, 0.103)

0.046 (⫺0.004, 0.096) 0.058 (0.002, 0.116) 0.092 (0.044, 0.140) 0.102 (0.054, 0.150)

0.036 (⫺0.011, 0.083) 0.061 (0.008, 0.114) 0.086 (0.039, 0.133) 0.097 (0.050, 0.144)

0.032 (⫺0.015, 0.077) 0.060 (0.006, 0.114) 0.073 (0.030, 0.114) 0.078 (0.038, 0.118)

0.018 (⫺0.029, 0.065) 0.053 (0.002, 0.104) 0.065 (0.023, 0.108) 0.072 (0.031, 0.112)

0.132 (0.084, 0.183) 0.037 (⫺0.020, 0.097) 0.049 (0.001, 0.098) ⫺0.031 (⫺0.079, 0.018)

0.072 (0.024, 0.117) 0.003 (⫺0.054, 0.060) ⫺0.003 (⫺0.060, 0.054) ⫺0.073 (⫺0.120, ⫺0.025)

0.087 (0.039, 0.135) 0.054 (0.000, 0.111) 0.113 (0.069, 0.155) 0.062 (0.020, 0.103)

0.064 (0.015, 0.113) 0.038 (⫺0.016, 0.090) 0.102 (0.060, 0.147) 0.052 (0.010, 0.094)

T Handgrip Quadriceps Arm lean Leg lean E2 Handgrip Quadriceps Arm lean Leg lean E1 Handgrip Quadriceps Arm lean Leg lean cFT Handgrip Quadriceps Arm lean Leg lean

␤-Value is for 1-SD increase in reproductive hormone levels in relation to handgrip strength, quadricep strength, arm lean mass, and leg lean mass.

We determined whether the observed associations between reproductive hormones and functional decline were mediated by muscle mass or strength. Table 4 shows the effect on ORs for the reproductive hormone-functional decline associations when muscle strength was added to the multivariable models. The magnitude of association between T, E2, E1, and cFT and functional decline were greatly reduced and no longer statistically significant when quadricep strength was added into models. Compared with men in the highest E1 quartile, the OR for men in the lowest E1 quartile reduced from 2.23 (95% CI 1.06 – 4.67) in the multivariable model to 1.48 (95% CI 0.56 –3.95) in the quadricep strength-added model. Similarly, when adjusted for quadricep strength, the OR reduced from 2.00 (95% CI 1.01– 4.22) to 1.44 (95% CI 0.50 – 4.15) for men in the lowest cFT quartile. The results for E2 were similar to cFT. The magnitude of association in T did not change greatly in quadricep strength-added model, but the association was no longer statistically significant (P ⫽ .21). The magnitude of associations between T, E2, E1, and cFT and functional decline did not change in the grip strength-added models. Similar findings were revealed when muscle mass from the dual X-ray absorptiometry measurements were substituted for muscle strength (Table 4). The magnitude of association reduced slightly to an OR of 1.81 (95% CI 0.93–3.52) for men in the lowest T quartile and to 1.75 (95% CI 0.88 –3.47) for men in the lowest cFT quartile in arm muscle mass-added model. Similar findings were ob-

served when leg muscle mass was added to the multivariable model. However, adding muscle mass to models did not change the magnitude of associations between the estrogens, E2 and E1, and functional decline. The findings using hormone levels as continuous (linear) variables verified the findings using quartiles (results not shown). For each 1-SD reduced in T, our men have an OR of 1.11 (95% CI 1.05–1.17) more likely to have functional decline. Similarly, for each 1-SD reduced in circulating levels, men have an OR of 1.06 (95% CI 1.01–1.13) for E2, 1.09 (95% CI 1.05–1.14) for E1, and 1.12 (95% CI 1.06 –1.18) for cFT to have functional decline. When quadricep strength were added to the model, these hormones all became statistically insignificant. The association for E2 and cFT was also no longer statistically significant when grip strength was added to the model. However, the association between T, E2, E1, and cFT and functional decline remained statistically significant when muscle mass was added to the model. Although the previous models have adjusted for comorbidity as a continuous variable, additional analyses stratified for comorbidity have been performed (results not shown). Because only 10% had no comorbidity and nearly 70% had more than one comorbidity (Table 1), we dichotomized comorbidity into the top vs other quartiles (⬍4 vs ⱖ4). Men with low comorbidity burden in the lowest quartile of T have an OR of 2.23 (95% CI 1.03– 4.83) and in the lowest quartile of E1 have an OR of 2.34 (95% CI 1.07–5.16) for functional decline. Similarly, with


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Table 4. Multivariable-Adjusted, Grip Strength-Adjusted and Quadricep Strength-Adjusted, and Arm Lean Mass-Adjusted and Leg Lean Mass-Adjusted ORs for Associations Between Reproductive Hormones Quartiles and Functional Decline From Baseline to 2-Year Follow-Upa Grip Strength (n ⴝ 1269)b

Quadricep Strength (n ⴝ 1009)b

Multivariable

Multivariable ⴙ ⌬Grip Strength ⴙ Grip Strengthc Multivariable

Multivariable ⴙ ⌬Quadricep Strength ⴙ Quadricep Strengthc

1.00 1.97 (0.99 –3.94) 1.44 (0.70 –2.98) 2.02 (1.00 – 4.06)

1.00 2.06 (0.89 – 4.77) 1.56 (0.66 –3.67) 2.32 (1.02–5.28)

1.00 1.40 (0.67–2.91) 0.95 (0.43–2.09) 2.19 (1.08 –2.09)

1.00 1.63 (0.83–3.21) 1.65 (0.84 –3.27) 2.20 (1.14 – 4.23)

1.00 1.35 (0.62–2.94) 1.37 (0.63–2.95) 2.16 (1.05– 4.42)

1.00 1.50 (0.75–3.01) 1.51 (0.75–3.03) 2.70 (1.41–5.20) 1.00 2.02 (0.98 – 4.13) 1.56 (0.74 –3.27) 1.98 (1.00 – 4.13)

Arm Lean Mass (n ⴝ 1308)b

Leg Lean Mass (n ⴝ 1308)b

Multivariable

Multivariable ⴙ ⌬Arm Lean Mass ⴙ Arm Lean Massd

Multivariable

Multivariable ⴙ ⌬Leg Lean Mass ⴙ Leg Lean Massd

1.00 1.30 (0.45–3.78) 0.52 (0.15–1.81) 1.92 (0.69 –5.31)

1.00 1.79 (0.93–3.46) 1.33 (0.66 –2.66) 1.98 (1.02–3.84)

1.00 1.76 (0.91–3.41) 1.26 (0.63–2.53) 1.81 (0.93–3.52)

1.00 1.79 (0.93–3.46) 1.33 (0.66 –2.66) 1.98 (1.02–3.84)

1.00 1.81 (0.93–3.50) 1.21 (0.60 –2.43) 1.85 (0.95–3.61)

1.00 2.17 (1.01– 4.67) 1.89 (0.86 – 4.15) 2.39 (1.07–5.34)

1.00 1.77 (0.65– 4.85) 1.04 (0.35–3.12) 1.89 (0.66 –5.38)

1.00 1.79 (0.92–3.47) 1.69 (0.87–3.31) 2.49 (1.31– 4.75)

1.00 1.87 (0.96 –3.64) 1.74 (0.89 –3.40) 2.33 (1.22– 4.46)

1.00 1.79 (0.92–3.47) 1.69 (0.87–3.31) 2.49 (1.31– 4.75)

1.00 1.87 (0.96 –3.64) 1.70 (0.87–3.34) 2.31 (1.21– 4.46)

1.00 1.09 (0.49 –2.42) 1.31 (0.59 –2.89) 2.54 (1.24 –5.20)

1.00 1.65 (0.78 –3.51) 1.59 (0.75–3.36) 2.23 (1.06 – 4.67)

1.00 1.11 (0.40 –3.05) 0.94 (0.34 –2.61) 1.48 (0.56 –3.95)

1.00 1.40 (0.72–2.72) 1.38 (0.71–2.70) 2.66 (1.43– 4.95)

1.00 1.45 (0.74 –2.82) 1.39 (0.71–2.71) 2.46 (1.32– 4.60)

1.00 1.40 (0.72–2.72) 1.38 (0.71–2.70) 2.66 (1.43– 4.95)

1.00 1.42 (0.73–2.76) 1.34 (0.68 –2.62) 2.41 (1.29 – 4.52)

1.00 2.25 (0.97–5.21) 1.23 (0.51–2.95) 2.00 (0.87– 4.59)

1.00 1.36 (0.63–2.91) 0.98 (0.44 –2.20) 2.00 (1.01– 4.22)

1.00 1.06 (0.35–3.21) 0.69 (0.22–2.17) 1.44 (0.50 – 4.15)

1.00 1.79 (0.91–3.54) 1.35 (0.67–2.76) 1.98 (1.02–3.89)

1.00 1.77 (0.89 –3.49) 1.28 (0.63–2.61) 1.75 (0.88 –3.47)

1.00 1.79 (0.91–3.54) 1.35 (0.67–2.76) 1.98 (1.02–3.89)

1.00 1.78 (0.90 –3.53) 1.28 (0.63–2.61) 1.81 (0.91–3.57)

T Highest Third Second Lowest E2 Highest Third Second Lowest E1 Highest Third Second Lowest cFT Highest Third Second Lowest a

Functional decline was defined as change in one or more ADL stage levels (moving from stage 0 to I, I to II, etc).

b

The same subjects were used for the models to compare the multivariable model with and without their respective muscle-mediator variables.

c

Both baseline muscle strength measure and change in muscle strength over 2-year follow-up were added to the multivariable model.

d

Both baseline lean mass measure and change in lean mass over 2-year follow-up were added to the multivariable model.

high comorbidity burden, men in the lowest quartile of T have a OR of 2.46 (95% CI 0.63–9.59) and in the lowest quartile of E1 have an OR of 2.76 (95% CI 1.02–7.45). Similar findings were observed in E2 and cFT.

Discussion This study provides a comprehensive examination of associations between all the major bioactive reproductive hormones and functional decline in older men together with exploring whether associations were mediated by reductions in muscle mass or strength. Men with low levels of serum T, E2, E1, and cFT were approximately twice as likely, as shown in Table 2, to have functional decline over the 2-year period compared with men with higher circulating levels of these hormones. Other reproductive hormones or glycoproteins (FSH, LH, DHT, and SHBG) were not associated with functional disability. Muscle strength, particularly quadricep strength, explained much of the relationships we observed between serum T, E2, and E1and functional disability in older men. The observed associations in this study are generally consistent with findings from the Framingham study (8), which used similar methods as this study to measure cir-

culating T and SHBG but calculated cFT using a different formula. Both the Framingham and CHAMP studies found that functional decline was associated with low levels of cFT but not with SHBG. The Framingham study did not find associations with T, perhaps because men were younger (mean age of 61 y) and a different measure (Rosow-Breslau) was used to define functional disability (18). The Longitudinal Ageing Study Amsterdam study reported no statistically significant relationships crosssectionally between self-reported functional limitation and either T or E2 (9). This may be because of the crosssectional design, different measure of functional disability, or because they measured steroids levels using direct sex steroid immunoassays, the accuracy of which is poor especially at low circulating levels (19 –22). T in men is important for muscle mass and strength (23, 24). In this paper, as expected, we have shown in Table 3 that men with higher levels of T had greater muscle mass and strength, in terms of both upper (handgrip) strength and lower (quadriceps) limb strength. We previously reported CHAMP data showing that muscle strength, particularly quadriceps strength, was strongly associated with functional disability in ADL (25). This may explain why adjusting for quadricep strength reduced the magni-


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tude of associations between reproductive hormones and functional decline, but adjusting for grip strength did not. Our finding shown in Table 4 suggests that the observed associations were more strongly mediated by the lower extremity strength. Muscle mass was also shown to partly explain the observed relationship between T and functional decline. This suggests the relationship with T is due to its stimulation of muscle mass, which is the basis for increased muscle strength. Thus, muscle mass and strength should be considered as coextensive and parallel variables in the pathway of T effects on functional ability of older men. Furthermore, we found that the associations between serum E1 and functional decline were greatly reduced when quadriceps strength was taken into account as shown in Table 4. These findings confirm that muscle weakness explains, at least in part, the observed relationship between low levels of serum T, E2, E1, and cFT and functional decline over time, which supports the interpretation that the relationship we found between serum T and E2 as well as the proestrogen E1 with functional disability is causal. However, whether functional decline can be reduced by hormone therapy warrants examination in carefully designed, randomized, placebo-controlled trials. Although our findings did not revealed any significant linear trend across T, E2, E1, and cFT quartiles in relation to functional decline, analyses using hormones as continuous variables did reveal an increase in odds of functional decline with these hormones. Thus, although the ORs for T, E2, and cFT in the second quartiles were lower than the third quartiles, this may be because the men in the interquartile range have similar characteristics and may be consider to be at an equivalent, optimal range. Functional disability in older men has multiple causes, of which muscle weakness is only one. The data in this study are complementary to a previous report from the CHAMP study in which we showed that age-related changes in serum T and estrogen contribute to the development and progression of frailty in older men (26). Functional disability in ADLs and frailty are overlapping, but different, concepts, with frailty being a risk factor for disability (3). The effects of estrogens on muscle mass and strength are not well understood, especially in men. Yet in women, muscle mass and strength increase markedly during puberty when circulating E2 increases without the increased circulating T seen during male puberty (27–30). Similarly, muscle mass and strength decrease after menopause with the menopausal deficit rectified by estrogen replacement therapy (31), and these changes are corroborated by experimental findings in rodents (32–34). These findings suggest that E2 effects on muscle mass and function may

warrant further investigation, especially in older men, although noting that systemic estrogen therapy would cause medical castration with unacceptable side effects. Our study has also revealed a positive association between E1, a proestrogen capable of conversion to E2 by 17␤-steroid dehydrogenase, with lower extremity muscle strength (35). This also warrants research into the regulation of the conversion of the proestrogen E1 into the potent estrogen E2 and its effects on muscle mass and strength, especially among older men. A major strength of our study was that we were able to use longitudinal data, which enabled us to investigate the possible causal direction of relationships between reproductive hormones and functional decline. Another strength was the use of the liquid chromatography-tandem mass spectrometry, the current gold standard for steroid assays as well as an accurate formula for cFT (12, 13, 36, 37). Direct immunoassay methods, which do not include extraction and chromatography, have poor accuracy in measuring low levels of sex steroids, which is particularly problematic for measuring circulating T, E2, and E1 in older men (19 –22). We measured functional disability using a change in the ADL level. The ADL scale we used (Katz) covers the basic activities required for older men to be capable of independent living. We also measured and analyzed both muscle mass and strength as mediator variables to help explain the linkage between decline in circulating hormones and functional disability. A further strength is that CHAMP includes a large and representative group of older Australian men, as demonstrated by similar sociodemographic and health characteristics in CHAMP men compared with older men in the nationally representative Men in Australia Telephone Survey study (38). Limitations of our study include the short follow-up period of 2 years and the 20% loss to follow-up. However, loss to follow-up in cohort studies of older people is inevitable because of the high mortality rate, which accounted for nearly 30% of the loss in our cohort. Another limitation for this study was the large amount of missing data for quadricep strength. Fasting morning samples were taken to minimize variation, given that a single sample only was collected (39). Our findings add to evidence that low circulating T, E2, and E1 concentrations may be either important contributors to or biomarkers for functional decline, which impairs the independence of older men. The observed associations between T, E2, and E1 and functional disability appear to be mediated through the sequential effects of hormones on muscle mass and thereby strength. Whether hormone therapy has any role in reducing functional de-


doi: 10.1210/jc.2014-1124

cline of older men remains to be evaluated by randomized, placebo-controlled trials of adequate size and duration.

Acknowledgments Address all correspondence and requests for reprints to: Professor D. J. Handelsman, ANZAC Research Institute, Sydney, New South Wales 2139, Australia. E-mail: [email protected]. The CHAMP study is supported by the National Health and Medical Research Council Project Grant 301916, the Sydney Medical School Foundation, and the Ageing and Alzheimer’s Research Foundation. B.H. is supported by the Sydney Medical School Foundation. Disclosure Summary: B.H., V.N., F.M.B., D.G.L.C., M.J.S., L.M.W., and D.J.H. have nothing to declare. R.G.C. received an honorarium from Eli Lilly Australia for an education event.


14.

15.

16.

17.

18. 19.

20.

References 1. Fries JF. Successful aging—an emerging paradigm of gerontology. Clin Geriatr Med. 2002;18:371–382. 2. Population Division Department of Economic and Social Affairs. United Nations World Population Ageing, 1950 –2050. http:// www.un.org/esa/population/publications/worldageing19502050/. Accessed January 14, 2014. 3. Fried LP, Ferruci L, Darer J, Williamson JD, Anderson G. Untangling the concepts of disability, frailty, and comorbidity: implications for improved targeting and care. J Gerontol A Biol Sci Med Sci. 2004;59:255–263. 4. Luppa M, Luck T, Weyerer S, Konig HH, Brahler E, Riedel-Heller SG. Prediction of institutionalization in the elderly. A systematic review. Age Ageing. 2010;39:31–38. 5. Isidori AM, Giannetta E, Greco EA, et al. Effects of testosterone on body composition, bone metabolism and serum lipid profile in middle-aged men: a meta-analysis. Clin Endocrinol (Oxf). 2005;63: 280 –293. 6. Herbst KL, Bhasin S. Testosterone action on skeletal muscle. Curr Opin Clin Nutr Metab Care. 2004;7:271–277. 7. Rantanen T. Muscle strength, disability and mortality. Scand J Med Sci Sports. 2003;13:3– 8. 8. Krasnoff JB, Basaria S, Pencina MJ, et al. Free testosterone levels are associated with mobility limitation and physical performance in community-dwelling men: the Framingham Offspring Study. J Clin Endocrinol Metab. 2010;95:2790 –2799. 9. Schaap LA, Pluijm SMF, Smit JH, et al. The association of sex hormone levels with poor mobility, low muscle strength and incidence of falls among older men and women. Clin Endocrinol (Oxf). 2005; 63:152–160. 10. Cumming RG, Handelsman D, Seibel MJ, et al. Cohort profile: the Concord Health and Ageing in Men Project (CHAMP). Int J Epidemiol. 2009;38:374 –378. 11. Harwood DT, Handelsman DJ. Development and validation of a sensitive liquid chromatography-tandem mass spectrometry assay to simultaneously measure androgens and estrogens in serum without derivatization. Clin Chim Acta. 2009;409:78 – 84. 12. Ly LP, Sartorius G, Hull L, Leung A, et al. Accuracy of calculated free testosterone formulae in men. Clin Endocrinol (Oxf). 2010;73:382– 388. 13. McNamara KM, Harwood DT, Simanainen U, Walters KA, Jimenez M, Handelsman DJ. Measurement of sex steroids in murine blood and reproductive tissues by liquid chromatography-tandem

21.

22.

23.

24.

25.

26.

27.

28.

29.

30.

31.

32.

3317

mass spectrometry. J Steroid Biochem Mol Biol. 2010;121:611– 618. Sartorius G, Ly LP, Sikaris K, McLachlan R, Handelsman DJ. Predictive accuracy and sources of variability in calculated free testosterone estimates. Ann Clin Biochem. 2009;46:137–143. Smith LA, Branch LG, Scherr PA, et al. Short-term variability of measures of physical function in older people. J Am Geriatr Soc. 1990;28:993–998. Stineman MG, Xie D, Pan Q, Kurichi J, Saliba D, Streim J. Activity of daily living staging, chronic health conditions, and perceived lack of home accessibility features for elderly people living in the community. J Am Geriatr Soc. 2011;59:454 – 462. Bleicher K, Cumming RG, Naganathan V, Travison TG, Sambrook PN, Blyth FM. The role of fat and lean mass in bone loss in older men: findings from the CHAMP study. Bone. 2011;49: 1299 –1305. Rosow I, Breslau N. A Guttman health scale for the aged. J Gerontol. 1966;21:556 –559. Rosner W, Hankinson SE, Sluss PM, Vesper HW, Wierman ME. Challenges to the measurement of estradiol: an Endocrine Society position statement. J Clin Endocrinol Metab. 2013;98:1376 – 1387. Rosner W, Auchus RJ, Azziz R, Sluss PM, Raff H. Position statement: utility, limitations, and pitfalls in measuring testosterone: an Endocrine Society position statement. J Clin Endocrinol Metab. 2007;92:405– 413. Sikaris K, McLachlan RI, Kazlauskas R, de Kretser D, Holden CA, Handelsman DJ. Reproductive hormone reference intervals for healthy fertile young men: evaluation of automated platform assays. J Clin Endocrinol Metab. 2005;90:5928 –5936. Handelsman DJ, Newman JD, Jimenez M, McLachlan R, Sartorius G, Jones GR. Performance of direct estradiol immunoassays with human male serum samples. Clin Chem. 2014;60:3. Baumgartner RN, Waters DL, Gllagher D, Morley JE, Garry PJ. Predictors of skeletal muscle mass in elderly men and women. Mech Ageing Dev. 1999;107:123–136. Roy TA, Blackman MR, Harman SM, Tobin JD, Schrager M, Metter EJ. Interrelationships of serum testosterone and free testosterone index with FFM and strength in aging men. Am J Physiol Endocrinol Metab. 2002;283:284 –294. Hairi NH, Cumming RG, Naganathan V, et al. Loss of muscle strength, mass (sarcopenia), and quality (specific force) and its relationship with functional limitation and physical disability: the Concord Health and Ageing in Men Project. J Am Geriatr Soc. 2010;58:2055–2062. Travison TG, Nguyen AH, Naganathan V, et al. Changes in reproductive hormone concentrations predict the prevalence and progression of the frailty syndrome in older men: the concord health and ageing in men project. J Clin Endocrinol Metab. 2011;96:2464 – 2474. Neu CM, Rauch F, Rittweger J, Manz F, Schoenau E. Influence of puberty on muscle development at the forearm. Am J Physiol Endocrinol Metab. 2002;283:E103–E107. Rauch F, Bailey DA, Baxter-Jones A, Mirwald R, Faulkner R. The ’muscle-bone unit’ during the pubertal growth spurt. Bone. 2004; 34:771–775. Xu L, Nicholson P, Wang Q, Alen M, Cheng S. Bone and muscle development during puberty in girls: a seven-year longitudinal study. J Bone Miner Res. 2009;24:1693–1698. Xu L, Wang Q, Wang Q, et al. Concerted actions of insulin-like growth factor 1, testosterone, and estradiol on peripubertal bone growth: a 7-year longitudinal study. J Bone Miner Res. 2011;26: 2204 –2211. Greising SM, Baltgalvis KA, Lowe DA, Warren GL. Hormone therapy and skeletal muscle strength: a meta-analysis. J Gerontol A Biol Sci Med Sci. 2009;64:1071–1081. Moran AL, Nelson SA, Landisch RM, Warren GL, Lowe DA. Estradiol replacement reverses ovariectomy-induced muscle contrac-


3318

33. 34.

35. 36.

Hsu et al



tile and myosin dysfunction in mature female mice. J Appl Physiol. 2007;102:1387–1393. Enns DL, Tiidus PM. The influence of estrogen on skeletal muscle: sex matters. Sports Med. 2010;40:41–58. Greising SM, Baltgalvis KA, Kosir AM, Moran AL, Warren GL, Lowe DA. Estradiol’s beneficial effect on murine muscle function is independent of muscle activity. J Appl Physiol. 2011;110:109 –115. Gordon EE, Villee CA. An in vitro assay for estradiol-17␤ and estrone. Endocrinology. 1956;58:150 –157. Grebe SK, Singh RJ. LC-MS/MS in the clinical laboratory—where to from here? Clin Biochem Rev. 2011;32:5–31.

37. Kushnir MM, Rockwood AL, Roberts WL, Yue B, Bergquist J, Meikle AW. Liquid chromatography tandem mass spectrometry for analysis of steroids in clinical laboratories. Clin Biochem. 2011;44: 77– 88. 38. Holden CA, McLachlan RI, Pitts M, et al. Men in Australia Telephone Survey (MATeS): a national survey of the reproductive health and concerns of middle-aged and older Australian men. Lancet. 2005;366:218 –224. 39. Brambilla DJ, Matsumoto AM, Araujo AB, McKinlay JB. The effect of diurnal variation on clinical measurement of serum testosterone and other sex hormone levels in men. J Clin Endocrinol Metab. 2009;94:907–913.


The longitudinal relationship of sexual function and androgen status in older men: the Concord Health and Ageing in Men Project.

Associations between circulating reproductive hormones and SHBG and prevalent and incident metabolic syndrome in community-dwelling older men: the Concord Health and Ageing in Men Project.

Alcohol consumption and tobacco smoking among community-dwelling older Australian men: the Concord Health and Ageing in Men Project.

Swimming and other sporting activities and the rate of falls in older men: longitudinal findings from the Concord Health and Ageing in Men Project.

Reproductive Hormones and Longitudinal Change in Bone Mineral Density and Incident Fracture Risk in Older Men: The Concord Health and Aging in Men Project.

Relative Validity of a Diet History Questionnaire Against a Four-Day Weighed Food Record among Older Men in Australia: The Concord Health and Ageing in Men Project (CHAMP).

Longitudinal and cross-sectional relationships of circulating reproductive hormone levels to self-rated health and health-related quality of life in community-dwelling older men.

Associations between serum 25-hydroxyvitamin D concentrations and multiple health conditions, physical performance measures, disability, and all-cause mortality: the Concord Health and Ageing in Men Project.

Sexual Health and Well-being Among Older Men and Women in England: Findings from the English Longitudinal Study of Ageing.

Hyperglycemia Is Associated with Impaired Muscle Quality in Older Men with Diabetes: The Korean Longitudinal Study on Health and Aging.

Ageing influence in the evolution of strength and muscle mass in women with fibromyalgia: the al-Ándalus project.

Lean mass, muscle strength and gene expression in community dwelling older men: findings from the Hertfordshire Sarcopenia Study (HSS).

Strength training and determinants of VO2max in older men.

Low muscle mass in older men: the role of lifestyle, diet and cardiovascular risk factors.

Prevalence and risk factors for falls in older men and women: The English Longitudinal Study of Ageing.

Anthropometric estimation of muscle mass in men.

Sleep Duration and Disturbances Were Associated With Testosterone Level, Muscle Mass, and Muscle Strength--A Cross-Sectional Study in 1274 Older Men.

Bone mineral density, muscle strength, and recreational exercise in men.

Gonadotropin-releasing hormone receptor mutations in ageing men.

Impact of body mass index, age and varicocele on reproductive hormone profile from elderly men.

Insulin resistance and depressive symptoms in older men: the health in men study.

Sexual and reproductive health and rights of older men and women: addressing a policy blind spot.

Muscle strength, muscle mass, and physical disability in women with systemic lupus erythematosus.

Effects of Growth Hormone Administration on Muscle Strength in Men over 50 Years Old.