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The Journals of Gerontology Series A: Biological Sciences and Medical Sciences 60:385-390 (2005)
© 2005 The Gerontological Society of America

Age, Hormones, and Cognitive Functioning Among Middle-Aged and Elderly Men: Cross-Sectional Evidence From the Massachusetts Male Aging Study

Stephanie J. Fonda1,, Rosanna Bertrand2, Amy O'Donnell3, Christopher Longcope4 and John B. McKinlay3,

1 Harvard Medical School, Joslin Diabetes Center, Boston, Massachusetts.
2 Department of Epidemiology and Biostatistics, School of Public Health, Boston University Medical College, Massachusetts.
3 New England Research Institutes, Watertown, Massachusetts.
4 Department of Medicine, University of Massachusetts Medical Center, Worcester.

Address correspondence to: Dr. John B. McKinlay, New England Research Institutes, 9 Galen Street, Watertown, MA 02472 (E-mail: JohnM{at}neri.org) or Dr. Stephanie J. Fonda, Joslin Diabetes Center, One Joslin Place, Boston, MA 02215 (E-mail: stephanie.fonda{at}joslin.harvard.edu)


   Abstract
Top
 Abstract
Methods
 Results
 Discussion
 References
 
Background. This study examines interrelationships among age, hormones, and cognition for middle-aged and elderly men, and tests whether hormones predict lower cognitive functioning and mediate the age–cognition relationship.

Methods. We analyzed Time 2 data from the Massachusetts Male Aging Study, a population-based cohort study. Selection criteria included complete information on cognition and hormones (n = 981). Cognitive measures included working memory (Backward Digit Span test), speed/attention (Digit Symbol Substitution test), and spatial ability (Figural Relations test). Hormones included free testosterone, total testosterone, dehydroepiandrosterone (DHEA), dehydroepiandrosterone sulfate (DHEAS), androstanediol glucuronide (3 {alpha}-A-diol-gluc), luteinizing hormone (LH), follicle-stimulating hormone (FSH), sex hormone-binding globulin (alternatively known as a "binding protein") (SHBG), prolactin (PRL), estrone (E1), and cortisol (CRT). Age was measured in years. Adjusted analyses added educational attainment, health conditions and behaviors, body mass index, and depression.

Results. Older age was associated with lower cognitive functioning. In unadjusted models, logged free and total testosterone, DHEA, and DHEAS related to higher functioning in at least one cognitive domain; logged FSH, SHBG, and LH related to lower functioning in at least one cognitive domain; and logged E1, CRT, and PRL were not significant. In adjusted models, logged hormones did not relate to cognitive function except for logged E1and CRT, which had negative effects. Logged hormones did not mediate the age–cognition relationship.

Conclusions. The direct effects of hormones on cognition are not significant when salient factors are considered. Further, hormones do not mediate the age–cognition relationship; it is necessary to look to other explanatory pathways.

PREVIOUS research suggests a heterogeneous and complex relationship between age and cognition, with some people experiencing gains in cognition as they age, others experiencing mainly stability, many experiencing losses, and still others experiencing combinations of gains, stability, and losses, depending on the cognitive domain considered (1–8). A subset of age–cognition research explores whether hormones contribute to the complexity of the age–cognition relationship. Hormones may be a promising explanation for age–cognition patterns because several important hormone levels shift with age (9). Among men, testosterone, dehydroepiandrosterone (DHEA), DHEA sulfate (DHEAS), cortisol (CRT), and estrone (E1) decline gradually with age, whereas dihydrotestosterone, prolactin (PRL), luteinizing hormone (LH), follicle-stimulating hormone (FSH), and sex hormone-binding globulin (SHBG) increase (10–13). To illustrate, the average rate of decline for testosterone is about 3.2 ng/dL per year for men aged 23–91 (12) and about 11 ng/dL per year for men aged 61–87 (13).

One hypothesis is that higher levels of certain hormones (and metabolites) protect cognition (14,15). Among men, for example, several studies have shown that testosterone positively affected performance in certain cognitive domains such as memory and spatial ability (9,16–18). DHEAS and the ratio of insulin-like growth factor 1 to growth hormone have also been shown to correlate positively with higher functioning in certain cognitive domains (9). Among women, estrogen replacement therapy has been shown to reduce cognitive decline and the risk of developing Alzheimer's disease (19–21), and estradiol has been linked to better cognitive performance (22). Other studies have generally reported nonsignificant findings, however, including studies comparing cognitive differences among hypogonadal men who received testosterone supplementation or placebo (23–25), studies of estrogen replacement therapy (26,27), and studies of DHEAS (28). Some studies have reported findings opposite those of the hypothesis, such as a recent article indicating that hormone replacement therapy increased risk of Alzheimer's disease (29).

Another hypothesis is that higher levels of CRT reduce cognitive functioning. Tests of this hypothesis have tended to support it. For example, small community-based studies of elderly men and/or women have found that higher levels of CRT predicted poorer performance on tests of verbal memory and global cognitive functioning (30–32). Also, a community study comparing hormone–cognition differences in elderly men and women found that, for women, increasing CRT levels predicted poorer verbal memory at baseline and follow-up 2.5 years later (33).

For the present study, we asked four questions: First, is age related to cognition such that older men have lower levels of functioning? Second, are hormones related to cognition such that men with higher levels of certain hormones have higher functioning and men with higher CRT levels have lower functioning? Third, does this relationship persist after adjustment for known confounders? Fourth, do hormones mediate the effects of age on cognition? To address these questions, we analyzed a representative study of community-dwelling men and used a more comprehensive set of hormones than in many previous studies.


   METHODS
Top
 Abstract
 Methods
Results
 Discussion
 References
 
Participants
This study used the Massachusetts Male Aging Study (MMAS), a large population-based, random-sample cohort of men from communities in the Boston metropolitan area. Cognitive functioning was assessed in the MMAS only at Time 2 (T2) (1995–1997); thus, for these analyses, we use T2 data only. At T2, 1156 of the 1496 eligible and available men from Time 1 completed an interview (77%). We included participants with complete information on age, hormones, and cognition (n = 981).

Measures
Following protocols approved by the New England Research Institutes' Institutional Review Board, a certified phlebotomist/interviewer visited each MMAS participant in his home and obtained written informed consent, blood samples, anthropometrics, and detailed health information.

Cognition
The MMAS assessed working memory (ability to process and store information), speed/attention (ability to process information and conduct simple logic relatively quickly), and spatial ability (ability to rotate figures mentally). Working memory was measured using a Backward Digit Span exercise that required participants to listen to sequences of numbers and to reiterate them backwards up to eight times. Speed/attention was measured using a Digit Symbol Substitution test that required participants to review nine numbered boxes with corresponding symbols and then to insert the same symbols in empty, numbered boxes. Participants were permitted 90 seconds to perform this test with the aim of filling 93 boxes. Both the Backward Digit Span and Digit Symbol Substitution tests were adapted from the Wechsler Adult Intelligence Scale-Revised (34). Spatial ability was measured using a test that required participants to observe a figure and then identify the same figures in a row in which all figures were similar but rotated and/or drawn backwards. This test was borrowed and modified with permission from the Schaie–Thurstone Adult Mental Abilities Test (35). The MMAS initially used a 15-item version of this test and then implemented a 20-item version. Both versions were standardized and combined for analyses. For each test, responses were coded "1" if correct and "0" if incorrect.

Age
At T2, the MMAS participants ranged in age from approximately 48 to 80 years. We included years of age in the multivariate analyses.

Hormones
The MMAS obtained hormone samples by taking two nonfasting blood samples, 20 minutes apart, within 4 hours of the participant's awakening. The two blood samples were then pooled for analyses. This protocol controlled for the episodic secretions of hormones within the diurnal cycle. This study analyzed the following: free testosterone (or nonprotein-bound testosterone), total testosterone, DHEA, DHEAS, androstanediol glucuronide (3 {alpha}-A-diol-gluc), E1, CRT, LH, FSH, SHBG (a binding protein), and PRL. Details regarding assay methods and coefficients of variation from intra-assays have been described elsewhere (10). We logarithmically transformed the hormone concentrations to reduce skew.

Covariates
Educational attainment, health conditions, body mass index (BMI), certain health behaviors, and depression are important covariates of cognitive functioning and/or hormone levels. The measures for educational attainment indicated whether the participant had less than a high school education, completed high school, or received some postsecondary education. Health conditions were by self-report and indicated the presence of diabetes, high blood pressure, heart disease, arthritis, and cancer. Self-report of health conditions has generally been shown to be accurate (36) and was verified by the MMAS through medical records abstraction. BMI was obtained by weighing and measuring the MMAS participants and calculating kg/m2. We logarithmically transformed the BMI variable for the analyses to reduce skew. Measures of health behaviors incorporated alcohol consumption and smoking status. Alcohol consumption was assessed using the Khavari formula (37) and summarized to indicate whether participants drank <.5 oz of alcohol per day,.5–1.5 oz per day, or >1.5 oz per day. Smoking status variables indicated whether participants currently smoked, previously smoked, or never smoked. Depression was measured using the Center for Epidemiologic Studies–Depression (CES–D) scale (38), recoded to indicate whether the CES–D score ≥16.

Analyses
The analyses proceeded in four steps, each using ordinary least squares regression. First, we regressed hormones on age to determine whether age was associated with hormone levels adjusting for all covariates. Second, we regressed cognition on age to test whether age related to cognitive functioning, adjusting for all covariates but excluding hormones. Third, we regressed cognition on hormones (only) as a benchmark for the adjusted analyses. Fourth, we regressed cognition on age and hormones, adjusting for all covariates. The first, second, and fourth steps follow the recommendations of Baron and Kenny (39) for testing mediational hypotheses. Mediation is established if age is associated with hormones (Step 1), age is associated with cognition (Step 2), and hormones are associated with cognition with the association between age and cognition attenuating compared to Step 2 (Step 4).


   RESULTS
Top
 Abstract
 Methods
 Results
Discussion
 References
 
Descriptive information on the study variables is shown in Table 1. The average age of the MMAS participants was 62.66 years. Overall, the MMAS participants were well educated—76% reported educational attainment beyond high school. They reported having each of the health conditions at rates similar to those documented in the second National Health and Nutrition Examination Survey. Most participants had never smoked or quit (79%), and most reported drinking <.5 oz of alcohol per day (57%). The distributions of the hormones are largely congruent with other reports.


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  		Table 1. Means/Proportions and Ranges for Study Variables, T2 MMAS (N = 981).

 
Table 2 presents the results of the analysis concerning age and logged hormones. Except for logged CRT and PRL, age was associated with significant differences in logged hormone levels, but the direction of the age-logged hormone relation was not the same in every case. Older age related to lower levels of logged free testosterone, total testosterone, DHEA, DHEAS, 3 {alpha}-A-diol-gluc, and E1. By contrast, older age related to higher levels of logged SHBG, FSH, and LH. Details on age trends in hormone levels are provided elsewhere (9–13).


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  		Table 2. Estimated Net Effects of Age on Logged Hormones (OLS Estimates), T2 MMAS (N = 981).

 
Table 3 shows the results of the analyses linking age to cognitive functioning. The table shows one column of results for each domain of cognitive functioning. Age was highly significant in all three models, assuming educational attainment and various aspects of health, health behaviors, and depression were held constant.


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  		Table 3. Estimated Net Effects of Age on Cognitive Functioning (OLS Estimates), T2 MMAS (N = 981).

 
The next step regressed cognition on unadjusted, logged hormone levels (in 33 separate regressions). Estimates are not shown but are available from the authors upon request. Logged E1, CRT, and PRL were not related to any of the three cognitive domains assessed. Logged SHBG and FSH were associated with a decrease in score on each of the cognition batteries. Logged total testosterone was associated with an increase in working memory (but was not associated with speed/attention or spatial relations), logged 3 {alpha}-A-diol-gluc was associated with an increase in speed/attention, and logged LH was associated with decreases in speed/attention and spatial relations. Logged free testosterone, DHEA, and DHEAS were associated with increases in each cognitive domain.

Table 4 shows the estimated net effects of age and logged hormones on cognition. These regression models incorporated all covariates as well as age and logged hormones. This final step in our analyses, when compared to the previous regression analyses, addressed our question about whether hormones mediate the relationship between age and cognition. We found that age significantly predicted cognition score in every model, and that the sizes of the coefficients and the p values for age in these fully adjusted models were nearly identical to those reported in Table 2. With the addition of age and covariates, any significance present in the unadjusted hormone–cognition models summarized above was lost. The relationships of logged E1 and CRT to certain domains became significant in these fully controlled models, however; logged E1 was negatively related to scores for spatial relations and logged CRT was negatively related to scores for speed/attention.


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  		Table 4. Estimated Net Effects of Age on Cognitive Functioning (OLS Estimates), T2 MMAS (N = 981).

 

   DISCUSSION
Top
 Abstract
 Methods
 Results
 Discussion
References
 
This article answers questions regarding age, hormones, and cognition. Is age related to cognition such that older men have lower levels of functioning? We found significant age differences in the domains of cognition investigated—working memory, speed/attention, and spatial relations. Older age predicted lower levels of cognitive functioning. This is consistent with previous research (1–8), which shows that, although decline is only one of several cognitive trajectories in late life, it is the predominant one.

Are hormones related to cognition such that men with higher levels of certain sex hormones have higher functioning and participants with higher CRT levels have lower functioning? Certain logged hormones, particularly logged free testosterone, total testosterone, DHEA, and DHEAS, initially (in the unadjusted models) predicted higher levels of functioning among MMAS participants in one or more of the three cognitive domains. Logged FSH, SHBG, and LH initially predicted lower levels of cognitive functioning in one or more of the domains. Logged E1, CRT, and PRL were not associated with cognitive functioning among the MMAS participants in the unadjusted models. Several logged hormones related to particular aspects of cognition but not others. Although there may be a biologic basis for hormones relating to some cognitive domains but not others, the discussion of this basis is beyond the scope of this article.

Do the hormone–cognition relationships remain after adjustment for relevant covariates? We found that most of the significant effects observed in analyses for the second question disappeared after the addition of age and covariates. This result differs from studies that have reported persistent and positive effects of hormones on cognition (16–18). However, several studies of serum levels of DHEAS (28), hormone supplementation in hypogonadal men (23–25), and hormone replacement in women (26,27) reported patterns similar to what we observed.

We also found that the relationships of logged E1 and CRT to certain cognitive domains became significant and negative in the fully controlled models. The significant estimate for logged CRT in the controlled model is congruent with the results from previous studies (30,31) and gives credence to the hypothesis that CRT has negative consequences for cognition. The negative result for logged E1, however, contradicts the hypothesis of a protective effect for estrogenic hormones and gives further support to the recent finding that estrogens can harm cognition (29).

Do hormones mediate the effects of age on cognition? This aspect of our analysis developed from the idea that hormones are pathways for the effect of age on cognition because certain hormones change with aging (9–13). Our results show that such a relationship did not exist or that other mediators of the age–cognition relation overpowered the lesser effects of logged hormones. The implication is that, among aging men, it is necessary to look to mediators of cognitive decline other than endogenous hormones. Further, exogenously administered hormones apparently are not the solution for reducing this decline (23–25).

This study offered several methodological advancements on previous research. It used a random sample of community-dwelling participants as the basis for our hypothesis tests, augmenting the generality of our results. Additionally, the size of our sample permitted control for a comparatively comprehensive set of confounders, and thereby minimized omitted variable bias. The reduction in bias may account for why we documented few significant hormone–cognition relationships in our fully adjusted models while other studies with fewer controls have reported positive findings [see Fillenbaum and colleagues (27) for a similar conclusion]. Finally, this study included a complete set of hormone measurements obtained following a rigorous protocol. This broadened our results and allowed comparison with a wide range of studies on hormones and cognition, which have tended to focus on one or two hormones at a time.

The interpretability of the results may be influenced by several factors. Although the MMAS is a longitudinal cohort study, cognition was assessed only at T2, so the present analysis is cross-sectional and cannot address causation. Although longitudinal data are neither necessary nor sufficient for causal inference, they would be helpful for examining how changes in hormone levels over time explain the age–cognition relationship or predict cognitive functioning more strongly than do contemporaneous hormone levels. Moreover, other domains of cognitive function were not measured in the MMAS due to the practical constraints of a large, community study. Inasmuch as hormones have been shown to relate to only certain cognitive domains, our conclusions are limited to the domains measured. These analyses also did not include medication use because of concern with the high correlation between physical health conditions and medicines, precluding unique parameter estimates. But certain medications have been shown to affect cognitive functioning and may modify endocrine function as well. This suggests next steps for understanding the hormone–cognition relationship.


   Acknowledgments
 
Support was provided through NIA Grant No. DK-44995 (Dr. McKinlay, PI). An earlier version of this paper was presented at the Annual Cognitive Aging Conference, April 2002. We thank Ms. C. Franz for technical assistance with the hormone assays.


   Footnotes
 
Decision Editor: John E. Morley, MB, BCh

Received September 26, 2003

Accepted October 31, 2003


   References
Top
 Abstract
 Methods
 Results
 Discussion
 References
 

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