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Abstract

While life expectancy continues to increase, aging can bring several distinct endocrine and psychosocial changes. The study aimed to investigate the interplay between biopsychosocial factors of healthy aging in specifically healthy aging men. Ninety-seven healthy aging men were investigated at two time points spanning 4 years. Participants completed questionnaires measuring several psychosocial dimensions and gave saliva samples for hormone quantification during a laboratory appointment. The study applied a random intercept mixed-model approach. Age-related changes were found in most endocrine markers (cortisol, testosterone, dehydroepiandrosterone-sulfate, and progesterone), except for estradiol. Psychosocial measures remained stable, except for increased social support. Further, changes in endocrine and psychosocial measures were independent of each other. The results suggest that in healthy aging men, age-related endocrine changes occur, but do not necessarily determine a change in psychosocial measures. Potentially, preventive interventions can be derived from these results.

Keywords

healthy aging aging endocrine changes social support self-esteem male longitudinal men’s health

Advancements in the prevention and treatment of diseases as well as novel technologies in biomedicine have led modern societies to experience an unprecedented increase in life expectancy (United Nations, 2009). As a consequence, people are spending a substantial part of their lives in older age. There are currently 962 million individuals aged 60 years and older worldwide, and global projections indicate that this figure will reach almost 2.1 billion by 2050 (United Nations, 2017). While a longer life is a precious gift, aging comes with distinct changes in biopsychosocial markers, leading to multifaceted processes of adaptation and increased morbidity and mortality. Biological aging is therefore considered as a major risk factor for chronic diseases and disabling conditions, causing tremendous societal and economic burden (Barzilai et al., 2018). Although some influential pioneering studies have indicated the relevance of psychosocial factors for age-related health changes (Hawkley et al., 2006; Johnson et al., 1989; Weng et al., 2000), the role played by psychosocial factors regarding the age-related increase in morbidity and mortality has not yet been sufficiently recognized. Prolonging the health span and reducing health-care costs are emerging as central goals for modern societies, which can only be achieved by investigating the underlying biopsychosocial aging processes and identifying novel options to improve healthy aging (Beard et al., 2016).

Healthy aging can be defined as “the process of developing and maintaining the functional ability that enables well-being in older age” (World Health Organization, 2015). Aging is associated with distinct changes in hormone secretion. Throughout a man’s lifespan, endocrine systems undergo specific changes: Activity of the hypothalamic-pituitary-gonadal (HPG) axis decreases with age, whereas the hypothalamic-pituitary-adrenal (HPA) axis becomes hyperactive with higher age (Ebner et al., 2014). At around the age of 40 years, the function of the Leydig cells in the testes begins to decrease, diminishing the levels of sex steroids (Fiacco et al., 2018). Most prominently, testosterone (T) decreases, which can potentially lead to a deterioration of physical and mental health (Ford et al., 2016). An age-related T decrease has also been observed in specifically healthy aging men (Harman et al., 2001). While Sartorius et al. (2012) assume that very good health may prevent aging men from sex steroid decline, there is increasing evidence to support a continuous but decelerated age-related decline in T in healthy men (Feldman et al., 2002; Walther et al., 2016). Dehydroepiandrosterone (DHEA) and its sulfate (DHEAs) have also been identified to decrease in aging men due to the attrition of DHEA(s)-producing cells in the zona reticularis of the adrenal cortex (Ohlsson et al., 2010; Parker, et al., 1997). Age trends regarding progesterone (P) and estradiol (E2), however, are conflicting, with studies reporting that these hormones remain stable (Oettel & Mukhopadhyay, 2004; Sartorius et al., 2012), increase (Jasuja et al., 2013), or slightly decline (Lewerin et al., 2014; Zitzmann et al., 2005). Similarly to the case for androgens, good self-reported health has been suggested to buffer the potential age-related changes in P and E2 (Sartorius et al., 2012; Walther et al., 2016). Contrary to the suggested decline in sex steroids, cortisol (C) increases with age (Karlamangla et al., 2013). This is due on the one hand to changes in the number of mineralocorticoid and glucocorticoid receptors and a change in sensitivity of the negative feedback mechanisms of the HPA axis (Gupta & Morley, 2014) and on the other hand to an age-related increased number of corticotropin-releasing hormone (CRH) neurons and subsequently in CRH secretion, further increasing cortisol output of the HPA axis (Zhou & Swaab, 1999). Age-related changes in the endocrine system also harbor the risk of physical or psychological pathologies, if mechanisms of adaptation fail to buffer these changes.

Parallel to endocrine changes, psychosocial adaptations can also be observed during aging. Subjective health seems to be an important indicator of healthy aging (Han et al., 2015). Symptoms of aging in males, such as decreased potency, muscular strength, or energy, are exhibited naturally with higher age (Jakiel et al., 2015). Large population-based cohort studies have also demonstrated a decline in general mental health with age (Norman et al., 2009; Payne et al., 2014). This association is potentially strongly influenced by physical illness and its consequences (Lorem et al., 2017). Sexual function, as part of overall quality of life, decreases in aging men (Giovanni Corona et al., 2013; Walther et al., 2017). For instance, 61% of 40–69-year-old males have experienced erectile dysfunction at least once in their life, whereas this rate increases to 77% among ≥ 70-year-olds (Wagle et al., 2012). Psychological factors such as self-esteem and social support also undergo changes with age. With regard to self-esteem, the findings are conflicting, with some studies reporting that males’ self-esteem increases until their sixties and subsequently declines (Orth et al., 2015; Robins et al., 2002) and other studies indicating a relative stability until close to death (Wagner et al., 2015). Social support is an important resource associated with health, with findings suggesting that age-related changes in social networks occur voluntarily and that social support increases with age (Charles & Carstensen, 2009). Aging can also foster loneliness (Hawkley & Kocherginsky, 2018), which is associated with several negative health outcomes (Shankar et al., 2017; Tian, 2016) and increased mortality (Harris et al., 2015). Taken together, subjective good health is associated with healthy aging, aging symptoms, such as decreased potency, increase and sexual function decreases with higher age. Results on self-esteem are conflicting, showing either a decline or stability, while social support can be beneficial for health, and loneliness—the opposite of social support—can foster negative effects on health.

Endocrine parameters are emerging as promising markers for the continuous monitoring of healthy aging since changes in androgens and estrogens were reported to be predictive for all-cause and cause-specific mortality in men (Hsu et al., 2016). Psychosocial measures, on the other hand, have also been identified to predict the aging process (e.g., Dainese et al., 2011). Isolated views on either psychosocial or endocrine factors alone neglect the complex interactions between the two domains and potentially impede the investigation of healthy aging as a whole. An integrative biopsychosocial approach as first described by George and Engel (1980) could be beneficial, especially within the employed multidimensional framework of healthy aging.

According to the biopsychosocial model, endocrine markers and psychosocial measures potentially influence each other. For symptoms of aging in men, the literature identified more symptoms of aging in the case of lower T secretion (Handelsman et al., 2015). Low T secretion is also associated with a higher risk of age-related illnesses such as dementia (Ford et al., 2018). A cross-sectional study with specifically healthy aging men failed to link subjective health to T secretion (Dunbar et al., 2001). Lower T secretion can further elevate symptoms of sexual dysfunction in men (Corona et al., 2009) or moderate the association between age and sexual dysfunction (Walther et al., 2017). Findings regarding endocrine associations with psychosocial measures such as self-esteem and social support are scarce. A lack of social support has previously been associated with flatter diurnal C slopes (Friedman et al., 2012; Gaffey et al., 2016), while self-esteem has either been associated with increased morning C (Zorrilla et al., 1995) or has shown no direct association with C (Pruessner et al., 1999), although the latter study investigated stress-related C secretion while the former investigated basal C secretion. An influential review revealed that various further studies did not identify links between endocrine secretion and psychosocial measures (Campbell & Ehlert, 2012), thus underlining the need to further investigate these associations and highlighting the importance of assessing changes in both psychosocial measures and endocrine markers.

To the knowledge of the authors, no previous study has investigated aging in specifically healthy men employing a wide range of biological, psychological, and social measures in a longitudinal design. The study aims to investigate how endocrine markers and psychosocial measures develop in the distinct population of healthy aging men over a time span of 4 years. The first hypothesis is that T and DHEAs would decrease with age, while C would increase, and E2 and P would remain stable. The second hypothesis is that health-related measures would decline, while self-esteem and social support would remain stable. The last hypothesis expects to find a buffering effect of self-esteem and social support on endocrine markers and that endocrine secretion would influence the development of all psychosocial measures since the literature suggests that endocrine development and psychosocial changes influence one another.

Materials and Methods

Participants

A total of 98 healthy men aged 40 years and over from the Men’s Health 40+ study (Walther et al., 2016) were investigated using a longitudinal design. At the beginning of the investigation, participants were aged between 40 and 75 years. An inclusion criterion for both time points of the study was a subjective health rating of “good”, “very good,” or “excellent” to enable a specific investigation of healthy individuals. This was assessed through the first question of the Short Form 36 Health Survey (SF-36, Bullinger et al., 1995), “How would you describe your current health condition?”, with response options ranging from “very bad” to “excellent”. Participants with self-reported acute and chronic medical conditions, psychiatric disorders, psychopharmacological treatment, or psychotherapy were screened out and all participants had to be fluent in German. The study was approved by the ethics committee of the Canton of Zurich in Switzerland. All participants accepted the terms of the study and gave their written informed consent.

Procedure

The study comprised a baseline measurement and a follow-up conducted 4 years after the initial investigation. At both time points, participants first underwent a screening to test whether all inclusion criteria were met. After being accepted for the study, participants subsequently completed three psychometric test batteries (in German), which consisted of various validated self-rating questionnaires. Each test battery required approximately 60 min to complete. Participants underwent a biological examination in the laboratory, during which various physiological (e.g., body composition) and endocrine parameters were obtained by trained study personnel between 8:00 and 8:15 am. Participants were instructed not to eat, drink, or consume cigarettes for 2 hr before the laboratory examination. They were asked to refrain from physical or sexual activity for 24 hr before the examination and alcohol or caffeine consumption for 48 hr before sampling (Stalder et al., 2016). Contaminated saliva samples (e.g., through prior coffee consumption or eating) produced missing values and could not be analyzed. In general, saliva samples, if collected under controlled conditions, are a reliable, noninvasive alternative to serum samples and have shown to be applicable for the analysis of steroid hormones (Gröschl, 2017). Detailed descriptions of the biological examination are described elsewhere (Walther et al., 2016).

Psychosocial Measures

Health-Related Quality of Life

To assess health-related quality of life, the Short Form 36 Health Survey (SF-36; Bullinger et al., 1995) and the more specific Aging Males’ Symptoms rating scale (AMS; Zimmermann et al., 1999) were used. The SF-36 is a 36-item self-report questionnaire which provides sum scores for eight subscales and two general scales. The general scale “physical health” was used in the present study. It has been used in multiple studies in a variety of fields over the last decades and is a well-established instrument for the assessment of health-related quality of life. Internal consistency for the present sample was α = .63.

The Aging Males’ Symptoms rating scale consists of a general sum score, which was used in the present study, and three distinct subscales. Participants rated the 17 symptom-related items in terms of severity from “no” to “very severe”. This questionnaire was specifically designed to assess male-specific symptoms of aging and thus to measure health-related quality of life for this population. It is a widely used and well-documented instrument within male-specific aging studies. Cronbach’s alpha for the current sample was α = .84.

Sexual Function

The German version of the International Index of Erectile Function (IIEF; Rosen, 1997; Wiltink et al., 2003) was used to measure erectile function with 15 items. The proposed German scoring was used for the present analyses. The IIEF consists of sum scores, including two distinct subscales: sexual function, which was used here, and sexual desire (Wiltink et al., 2003). The IIEF is a self-report measurement tool which is well-validated and widely used in clinical as well as epidemiological studies. Cronbach’s alpha for this sample was α = .64.

Mental Health

The Brief Symptom Inventory 18 (BSI-18) is a well-established 18-item self-report questionnaire measuring mental health on three subscales and a general sum scale, which was used in the present study (Spitzer et al., 2011). The BSI-18 is a time-efficient measurement tool which is widely used. The BSI-18 is a shortened version of the Brief Symptom Inventory (Franke & Derogatis, 2000). The questionnaire showed good internal consistency (α = .83) in the present sample.

Self-Esteem

The Multidimensional Self-Esteem Scale (MSWS; Schütz & Sellin, 2006) was used to assess self-esteem as a multidimensional construct. It investigates self-esteem as a trait. The questionnaire consists of 32 items which form a hierarchical structure of subscales, with two scales representing distinct factors for general self-esteem (used in the present study) and body-related self-esteem. Cronbach’s alpha for the current sample was α = .89.

Social Support

The Berlin Social Support Scale (BSS; Schwarzer & Schulz, 2003) is a well-established instrument to measure social support. The questionnaire consists of four subscales and a general score, which was used in this study. Internal consistency was α = .90 in the present sample.

Hormone Analyses

Saliva samples were obtained between 8:00 and 8:15 am under standardized laboratory conditions using SaliCaps (SaliCaps, IBL International GmbH, Hamburg, Germany). Samples were immediately stored at −20°C until required for biochemical analysis. Enzyme-linked immunoassays were used to analyze C, DHEAs, and P, while T and E2 were analyzed using luminescence immunoassay (Chiappin et al., 2007; Goncharov et al., 2006). All hormones were analyzed at the Biochemical Laboratory at the Institute of Psychology of the University of Zurich. The intra- and interassay variation was less than 10%, while sensitivity was 0.003 μg/dl for C, 1.8 pg/ml for T, 1.5pg/ml for DHEAs, 0.3 pg/ml for E2, and 2.6 pg/ml for P.

Statistical Analysis

Bootstrapped zero-order and partial Pearson correlations were conducted to examine direct cross-sectional and longitudinal associations between baseline and follow-up measures (detailed information is provided in the supplemental material). Partial correlations were controlled for physical activity, income, educational level, fat mass, and age to control for any potential bias. To examine changes in endocrine and psychosocial factors over time, a linear mixed-model approach with random intercepts was used, which enables a more specific analysis of the longitudinal effects than simple correlation and regression analyses. Visual inspection for normality of the residuals was performed for every single model; if normality of the residuals was violated, the respective variable was log-transformed (Sollberger & Ehlert, 2016). Linear mixed models were calculated in R (Version 3.4.3) using the package “lme4” (Bates et al., 2015). The analysis was conducted in two subsequent steps: first, a more general analysis of the change over time and second the specific moderation analyses. Within the first step, the dependent variables were the respective hormones or psychosocial measures, with the time variable as an independent fixed effect variable, displaying intraindividual changes between the two measurement time points. Within the current set of hypotheses, random effects (i.e., whether there are differences between the participants) are no priority in the current set of hypotheses and thus will not be reported or discussed in detail. All calculations were controlled for physical activity, educational level, and income. Endocrine and health-related measures were further controlled for fat mass. The aforementioned moderation analyses were conducted with not only the baseline values but the longitudinal data for both the dependent variables and the moderators, which enabled us to, additionally, investigate the changes in these variables. The model for the moderation analyses consisted of the respective dependent variable and as predictors, the time*moderator term as well as the covariates were included. For all mixed-model analyses, participants’ endocrine sampling adherence was included in the models, but none of the parameters were significant predictors and did not change the general results. To apply the principle of parsimony, they were therefore not included in the final analyses.

Moderation analysis was conducted for the influence of social support and self-esteem on endocrine markers and for the influence of all endocrine markers separately on the psychosocial markers. All calculations, again, were controlled for physical activity, educational level, and income. Endocrine and health-related measures were further controlled for fat mass. The Akaike information criterion (AIC) was used to assess model quality for the change over time, as well as the moderation analyses. For all calculations within this study, the Benjamini–Hochberg procedure was applied to the p values to control the false discovery rate (Benjamini & Hochberg, 1995).

Results

Descriptive Data

Out of 271 participants from the baseline assessment, 130 (48%) completed the screening and 98 (36%) attended the follow-up assessment (Figure 1). The participants were initially informed that they would be participating in a cross-sectional study. Three years after the baseline assessment, participants were asked whether they would like to participate in a follow-up assessment. Twenty-two (8%) of the 271 participants had an invalid e-mail address and 60 (22%) did not respond to repeated e-mails. Out of the 130 participants who completed the screening, 15 (12%) were no longer eligible to participate due to physical illnesses and 17 (13%) were no longer interested in participating. Finally, 98 (75%) participants participated in the follow-up assessment, 97 (99%) of whom completed the laboratory assessment.

Figure 1.

Flow Chart of Participant Participation

Descriptive data of these 97 participants are presented in Table 1. Participants’ mean age was 61.26 years (SD = 10.02) at baseline and 65.18 (SD = 9.98) at follow-up. Most participants were in a relationship (N = 8, 8.25%) or married (N = 70, 72.16%) throughout the complete study. The largest proportion of participants had a university degree and an annual income between 50,000 and 150,000 Swiss Francs. A total of 84.54% (N = 82) reported being nonsmokers at baseline and 86.46% (N = 83) at follow-up. Around 60% (N = 59) of the participants did not take any medication at baseline, while 53% (N = 51) were medication-free at follow-up. Antihypertensives were the most commonly taken medication type (46% for both time points, N = 23/28), followed by the category “Other”, which mostly comprised cholesterol medication and bowel-regulating medications. The largest proportion of participants (Baseline: N = 40,41%; Follow-up: N = 51, 53%) reported undertaking 4–6 hr of physical activity per weeks.

Table 1.

Sample Characteristics.

	Baseline			Follow-up
	N	M/Freq.	SD/%	N	M/Freq.	SD/%
Age	97	61.26	10.02	97	65.18	9.98
Fat mass in percent (%)	95	22.42	5.43	97	20.58	7.03
C (nmol/L)	95	4.77	8.99	97	6.76	9.28
T (pg/ml)	93	42.53	18.44	96	37.88	26.28
DHEAs (ng/ml)	95	1.95	1.31	97	1.31	1.06
E2 (pg/ml)	94	1.46	1.06	97	1.63	1.69
P (pg/ml)	94	34.29	13.04	97	45.03	36.08
AMS—main score	89	26.22	6.93	94	26.74	6.68
SF-36—physical health	97	65.47	3.93	96	65.36	4.09
BSI—main score	97	22.43	5.28	94	21.90	3.74
IIEF—sexual function	96	28.61	6.98	94	28.10	6.73
MSWS—main score	96	179.80	20.68	94	180.21	19.89
BSSS—main score	96	3.44	0.51	94	3.52	0.43
Marital status (%)	97			96
Single		8	8.25		5	5.21
In relationship		8	8.25		10	10.42
Married		70	72.16		70	72.92
Divorced		10	10.31		10	10.42
Widowed		1	1.03		1	1.04
Education (%)	97			96
Lower-track secondary school		8	8.25		9	9.38
Medium-track secondary school		23	23.7		23	23.96
Higher-tracker secondary school		7	7.22		7	7.29
University degree		43	44.33		46	47.92
Other		16	16.49		11	11.46
Income (in CHF, %)	97			96
No income		1	1.03		1	1.04
Up to 30,000		3	3.09		3	3.13
30,001–50,000		7	7.22		4	4.17
50,001–100,000		35	36.08		38	39.58
100,001–150,000		35	36.08		38	39.58
150,001–200,000		12	12.37		7	7.29
More than 200,000		4	4.12		5	5.21
Number of children (%)	97			96
0		20	20.62		19	19.79
1		14	14.43		15	15.63
2		42	43.30		40	41.67
3		18	18.56		18	18.75
4		2	2.06		3	3.13
5 or more		1	1.03		1	1.04
Smoking (%)	97			96
Nonsmoking		82	84.54		83	86.46
Smoking		15	15.46		13	13.54
Medication (%)	97			96
No		59	60.08		51	53.13
Yes		38	39.18		45	46.88
Type of medication^a (%)	38			45
Antihypertensives		23	45.09		28	45.16
Vitamins and minerals		1	1.96		5	8.06
Other		27	52.94		29	46.77
Physical activity (%)	97			96
Less than 1 hr		1	1.03		1	1.04
1–3 hr		32	32.99		20	20.83
4–6 hr		40	41.24		51	53.13
7 hr or more		24	24.74		24	25.00

Participants could indicate more than one medication.

Note. N = number of participants; M = mean; Freq. = frequency; SD = standard deviation; % = percent; C = cortisol; T = testosterone; DHEAs = dehydroepiandrosterone-sulfate; E2 = estradiol; P = progesterone; AMS = Aging Males’ Symptoms scale; SF-36 = Short-Form 36; BSI = brief symptom inventory; IIEF = International Index of Erectile Function; MSWS = Multidimensional Self-Esteem Scale; BSSS = Berlin Social Support Scale; CHF = Swiss Francs.

Analyses comparing differences between the participants who participated at both time points and those who only participated at the first time point showed that the former were older and healthier overall, thus supporting the aim to investigate participants who were able to maintain their health. There were no significant differences in endocrine measures between participants of T1+T2 and only T1, with the exception of P, which was significantly lower for participants who did not return. Further analyses comparing eligible and ineligible participants who returned at the second time point showed that the eligible participants were indeed healthier, although they reported higher values with regard to pain. Overall, the aim to investigate healthy participants was supported (detailed information in the supplemental materials). Correlations between all parameters can be found in the supplemental materials.

Changes Over Time

Changes over time for endocrine markers and psychosocial measures are displayed in Figure 2. Linear mixed-model analyses with random intercepts yielded significant changes over time (Table 2). Longitudinal effects for endocrine secretion showed significant decreases in T (b = −0.3, p < .001, −3.07% per year) and DHEAs (b = −0.47, p < .001, −12.18% per year). Furthermore, C (b = 0.44, p =.01, 7.36% per year) and P (b = 02, p = .001, 5.96% per year) increased, while E2 (b = 0.07, p = .623, 2.51% per year) did not change significantly. It was decided to interpret the change in C despite a slightly worse model fit because the covariates were entered in a theory-based manner. After excluding educational level, which was not a significant predictor of C, the model fit improved.

Figure 2.

Changes Over Time for Endocrine Markers and Psychosocial Measures. (A) Shows the changes over time for endocrine measures. DHEAs = dehydroepiandrosterone-sulfate; E2 = estradiol. Changes on percent scale with higher values are shown as 100%. (B) Shows the change over time of psychosocial measures. Scale shows percent of maximum achievable value on respective questionnaire scale. For mean and SD see Table 2.

Table 2.

Linear Mixed Model Results Over Time.

	AIC₀	AIC	Estimate	SE_b	p	p _corr	95% CI_lower	95% CI_upper
C	573.9	579.7	0.44	0.15	0.003	0.01	0.144	1.114
T	375.9	370.4	−0.3	0.08	< .001	< .001	−0.457	−0.147
DHEAs	409.6	358.7	−0.47	0.05	< .001	< .001	−0.587	−0.36
E2	433.6	447.5	0.07	0.09	0.413	0.623	−1.102	0.247
P	189.1	187.6	0.2	0.05	< .001	0.001	0.1	0.302
AMS	−59	−51.9	0.03	0.02	0.104	0.19	−0.006	0.067
SF-36	1042	1050.3	−0.32	0.38	0.403	0.506	−1.081	0.431
BSI	1116.3	1122.4	−0.04	0.55	0.47	0.623	−1.5	0.7
IIEF	1254	1258.4	−0.91	0.76	0.234	0.368	−2.411	0.595
MSWS	1608.5	1621.1	−0.6	1.45	0.682	0.682	−2.85	3.06
BSSS	193.4	206.1	0.09	0.04	0.019	0.042	0.015	0.16

Note. N = 97; AIC₀ = Akaike information criterion of the null model; AIC = Akaike information criterion; SE = standard error; p = p value; p_corr = corrected p value; CI = confidence interval; C = cortisol; T = testosterone; DHEAs = dehydroepiandrosterone-sulfate; E2 = estradiol; P = progesterone; AMS = Aging Males’ Symptoms scale; SF-36 = Short-Form 36; BSI = brief symptom inventory; IIEF = International Index of Erectile Function; MSWS = Multidimensional Self-Esteem Scale; BSSS = Berlin Social Support Scale. All calculations controlled for physical activity, educational level, and income; endocrine and health-related measures further controlled for fat mass.

The results for the psychosocial measures show no significant changes in male aging symptoms (b = 0.03, p = .190), physical health (b = −0.32, p = .506), mental health (b = −0.04, p = .623), sexual function (b = −0.91, p = .368), and self-esteem (b = −0.6, p = .682). Social support significantly increased over time (b = 0.09, p = .042). Similarly to C, the change in social support was interpreted despite slightly worse model fit, since covariates were selected in a theory-based manner.

Moderation Analyses

Results of the moderation analyses showed that by trend, social support moderated the age-related change in C (b = 0.544, p = .087) and in DHEAs (b = 0.010, p = .079). As a further trend, C (b = 0.198, p = .055) and T (b = 1.410, p = .054) moderated the change in sexual function over time. Social support was found to significantly moderate the change in C over time (b = 0.013, p = .012), insofar as higher social support was associated with lower C secretion. This finding did not remain significant after adjusting for the false discovery rate (Table 3). In conclusion, no significant moderation effects were identified.

Table 3.

Linear Mixed Model Results for All Moderation Analyses.

	AIC₀	AIC	Estimate	SE	p	p _corr	95% CI_lower	95% CI_upper
MSWS*C	573.9	577.1	0.002	0.007	0.736	0.897	−0.012	0.017
BSSS*C	573.9	573.9	0.544	0.316	0.087^†	0.696	−0.078	1.165
MSWS*T	375.9	346.5	−0.003	0.004	0.346	0.865	−0.011	0.004
BSSS*T	375.9	342.2	0.214	0.164	0.195	0.865	−0.114	0.537
MSWS*DHEAs	409.6	359.7	0.001	0.003	0.791	0.897	−0.007	0.005
BSSS*DHEAs	409.6	359.7	0.010	0.126	0.079^†	0.696	−0.239	0.260
MSWS*E2	433.6	445.8	0.001	0.004	0.323	0.865	−0.007	0.010
BSSS*E2	433.6	443.8	−0.112	0.191	0.559	0.897	−0.489	0.267
MSWS*P	189.1	185.0	−0.001	0.003	0.665	0.897	−0.006	0.004
MSWS*P	189.1	187.6	0.013	0.111	0.908	0.908	−0.230	0.198
C*SF36	1042	1053.3	0.051	0.051	0.319	0.865	−0.049	0.152
T*SF36	1042	1037.0	−0.020	0.021	0.333	0.865	−0.062	0.021
DHEAs*SF36	1042	1051.2	−0.261	0.337	0.440	0.880	−0.926	0.401
E2*SF36	1042	1049.7	0.100	0.339	0.291	0.865	−0.571	0.769
P*SF36	1042	1045.0	−0.039	0.026	0.134	0.865	−0.091	0.012
C*AMS	−59	−48.9	0.002	0.002	0.341	0.865	−0.003	0.007
T*AMS	−59	−45.9	0.002	0.001	0.884	0.908	−0.002	0.002
DHEAs*AMS	−59	−48.4	−0.011	0.016	0.525	0.897	−0.043	0.022
E2*AMS	−59	−46.2	0.004	0.018	0.803	0.897	−0.030	0.039
P*AMS	−59	−46.6	0.0004	0.001	0.748	0.897	−0.002	0.003
C*BSI	1116.3	1125.8	−0.036	0.069	0.602	0.897	−0.172	0.010
T*BSI	1116.3	1111.5	−0.011	0.029	0.704	0.897	−0.068	0.046
DHEAs*BSI	1116.3	1125.0	−0.519	0.489	0.291	0.865	−1.485	0.448
E2*BSI	1116.3	1119.5	0.673	0.470	0.154	0.865	−0.256	1.600
P*BSI	1116.3	1119.4	−0.019	0.035	0.580	0.897	−0.089	0.511
C*IIEF	1254	1284.8	0.198	0.102	0.055^†	0.696	−0.007	0.399
T*IIEF	1254	1267.4	0.030	0.042	0.481	0.897	−0.054	0.114
DHEAs*IIEF	1254	1287.0	1.410	0.723	0.054^†	0.696	−0.026	2.835
E2*IIEF	1254	1284.0	0.174	0.715	0.807	0.897	−1.274	1.590
P*IIEF	1254	1282.5	0.011	0.054	0.839	0.907	−0.096	0.117
C*MSWS	1608.5	1616.8	0.062	0.205	0.762	0.897	−0.341	0.472
T*MSWS	1608.5	1595.3	−0.072	0.084	0.400	0.872	−0.241	0.094
DHEAs*MSWS	1608.5	1617.8	−0.551	1361	0.686	0.897	−3.234	2.160
E2*MSWS	1608.5	1610.1	0.162	1.362	0.906	0.908	−2.525	2.867
P*MSWS	1608.5	1610.1	−0.089	0.109	0.414	0.872	−0.306	0.126
C*BSSS	193.4	204.1	0.013	0.005	0.012^*	0.480	0.003	0.023
T*BSSS	193.4	205.4	−0.001	0.002	0.657	0.897	−0.005	0.003
DHEAs*BSSS	193.4	208.5	0.046	0.034	0.176	0.865	−0.021	0.113
E2*BSSS	193.4	207.7	0.028	0.034	0.412	0.872	−0.039	0.095
P*BSSS	193.4	208.2	−−0.001	0.003	0.627	0.897	−0.007	0.004

Note. N = 97; AIC₀ = Akaike information criterion of the null model; AIC = Akaike information criterion; SE = standard error; p = p value; p_corr = corrected p value; CI = confidence interval; C = cortisol; T = testosterone; DHEAs = dehydroepiandrosterone-sulfate; E2 = estradiol; P = progesterone; SF36 = Short-Form 36; AMS = Aging Males’ Symptoms scale; BSI = brief symptom inventory; IIEF = International Index of Erectile Function; MSWS = Multidimensional Self-esteem Scale; BSSS = Berlin Social Support Scale. All calculations controlled for physical activity, educational level, and income; endocrine and health-related measures further controlled for fat mass.

Discussion

In the present study examining 97 healthy men at baseline and 4-year follow-up, an age-related decrease in T and DHEAs and an increase in P and C was identified. No significant change in E2 was detected within this period of time. Scores on all health-related psychosocial measures such as self-reported health, mental health, self-esteem, and sexual function remained stable, while social support increased. No moderation effects of longitudinal self-esteem scores and social support on endocrine changes were found, and there were no moderation effects of endocrine markers on psychosocial measures. Therefore, in the healthy aging men examined, age-related changes in endocrine markers did not match changes in psychosocial measures. These findings reveal that despite age-related changes in hormones, it is still possible to maintain or even increase a high quality of life, mental health, sexual function, self-esteem, and social support.

The results for endocrine measures are mostly in line with the literature. An increase in C and a decrease in T and DHEAs, as previously reported by other studies (Ford et al., 2016; Gupta & Morley, 2014) was identified. Findings for E2 are also in accordance with previous studies, which showed either stability or a slight decrease, as described in a detailed review by Fiacco et al. (2018). However, the increase in P in the present study is in contrast to previous research demonstrating either stability or a decline with age (Oettel & Mukhopadhyay, 2004). As P is synthesized not only in the Leydig cells, which decrease in function with age, but also in the adrenal glands, which are also crucial for male secretion of P (Oettel & Mukhopadhyay, 2004; Schumacher et al., 2014), the adrenal glands might attempt to compensate for the reduced Leydig cell function by producing more P. This could explain the increase in P despite the decline in T, which is also synthesized in the testes.

Interestingly, health-related measures remained stable in the present study, which is yet to be discussed. Various studies reported that different aspects of quality of life such as mental health (e.g., Payne et al., 2014) or sexual function (Corona et al., 2013) decreased with age while symptoms of aging increased (Jakiel et al., 2015). Previous studies predominantly investigated general or clinical populations rather than specifically healthy individuals as in the present study. The current findings therefore add valuable insights into the healthy aging process. Moreover, the present results give rise to the question of whether the decrease in psychosocial parameters is natural or whether it is due to physical illnesses. The latter was also proposed by Lorem et al. (2017), and is further supported by the stability of subjective physical health in this sample of healthy aging men.

The finding of maintained self-esteem in healthy aging men is partially in line with the literature, which reported that self-esteem increases until the age of around 60 and then shows a steady but slow decline until old age (Orth et al., 2010, 2012). Another recent study reported that self-esteem remains stable until very old age and only declines shortly before death (Wagner et al., 2015). An explanation for the current findings of this study might lie in the specific sampling of healthy participants, because as Wagner et al. (2015) stated, low subjective health and its potential constraints are important factors that negatively influence self-esteem. Furthermore, a high educational level increases self-esteem (Orth et al., 2012), which is relevant since 44.33% of this sample had a university degree.

This healthy aging sample reported increasing levels of social support over time. Due to the lack of studies specifically investigating subjective social support over the lifespan, and given the heterogeneity of methods used to assess social support, integrating the findings into the existing literature is challenging. As older individuals play an active role in designing their social networks (Charles & Carstensen, 2009), the significant increase found in the present study might indicate that healthy aging men indeed actively manage their social networks. It is crucial to mention that the size of the social networks themselves was not assessed, but rather measured subjective, self-rated social support using a validated questionnaire. It cannot reliably be concluded that the social network itself changed, although a change in the subjective perception of social support can be concluded. Scholz et al. (2012) further reported that for older individuals, social support was associated with higher (emotional) well-being.

The current study showed that age-related endocrine changes and changes in psychosocial measures are independent in healthy aging men. Three potential explanations for this can be suggested: First, most previous studies investigated general populations or participants with illnesses. In this respect, it is important to discuss by way of example that the decline in T did not have any effects on mental health in this study, in contrast to a previous study in a randomly selected sample and therefore also including individuals with disorders or potentially in a premorbid state (Ford et al., 2016). This premorbid state might have led to biological changes prior to the manifestation of the respective illness, which were not present in this healthy sample. Another study with subjectively healthy aging men further failed to link T to subjective health, although the analyses were cross-sectional (Dunbar et al., 2001). Second, there may be a dissociation between physiological and psychological measures in healthy aging men, as discussed for psychoendocrine research in general by Campbell and Ehlert (2012). Third, the associations might have been influenced by a potential confounding variable that was not assessed, as also proposed by Campbell and Ehlert (2012). Nevertheless, associations between endocrine markers and social support (Friedman et al., 2012) have previously been observed in the general population, whereas the literature on the associations between self-esteem and endocrine markers remains conflicting (Pruessner et al., 1999; Zorrilla et al., 1995).

Some limitations of the present study need to be noted, the strongest of which is the aforementioned high dropout rate. This was mostly due to the fact that information about the follow-up was only provided 3 years after the baseline. It is further important to note that compared to other European countries, residents of Switzerland have a rather high income and level of education (BfS, 2015), which limits the ability to generalize the findings to other countries. Income and educational level were added as covariates in all calculations. The study design did not include an unhealthy group, rendering direct comparisons impossible and thus limiting potential conclusions beyond healthy aging populations. To increase the validity and reliability, it can be beneficial to employ a design with more than one hormone sample for each time point. Reliable and valid results can also be obtained with single or two-time measurements while controlling for sampling time and presample behavior, as also applied within the current study (Barrett-Connor et al., 1999; Clifton et al., 2016; Feldman et al., 2002). Similarly, the assessment of more than two time points within the 4 years of the study duration, or even expanding the study with a study design of more than 4 years would increase the potential conclusions that could be derived. Finally, for the questionnaires on sexual function and subjective health-related quality of life, internal consistency was rather low, possibly because most questionnaires were predominantly developed to measure dysfunctions in nonhealthy populations. Accordingly, they may have been less applicable to healthy participants, therefore decreasing the reliability for this population.

Nevertheless, the present study also entailed several strengths. First, a sample which was able maintain their health between the two time points was investigated. Second, the use of longitudinal data enabled a more detailed investigation of age-related changes compared to cross-sectional data. Further strengths of the study include the use of validated questionnaires, strict inclusion criteria, and standardized procedures for endocrine measurements and for the overall study procedure.

Future studies should incorporate more data (e.g., experience sampling and more time points) and include a nonhealthy group within a larger overall sample. To enable reliable use in healthy aging participants, it would be beneficial to develop health-focused rather than illness-focused questionnaires.

Conclusion

In this sample of healthy aging men, levels of psychosocial measures were maintained despite age-related endocrine changes. These age-related endocrine changes were not associated with changes in psychosocial measures or vice versa. While C and P increased, DHEAs and T decreased, and E2 remained stable. In terms of psychosocial measures, levels of subjective health, sexual function, mental health, self-esteem, and social support were maintained or even increased, despite the age-related endocrine changes. These findings are of crucial interest for the public. Since more people are experiencing better health with higher age, the current finding that endocrine changes are independent of psychosocial changes is encouraging. It is therefore important to continue to integrate biological and psychosocial parameters into definitions of healthy aging and to take into account the potential independence of their developmental course in (healthy) aging. As a novel area of research, studies could aim to investigate the potential for maintaining high levels of protective psychosocial factors to help prolong general health into old age.

Supplemental Material

RevisedSupplemental_Material_Paper1_TL – Supplemental material for Age-Related Alterations in Endocrine Markers Do Not Match Changes in Psychosocial Measures: Findings From the Men’s Health 40+ Longitudinal Study

Supplemental material, RevisedSupplemental_Material_Paper1_TL for Age-Related Alterations in Endocrine Markers Do Not Match Changes in Psychosocial Measures: Findings From the Men’s Health 40+ Longitudinal Study by T.J. Lacker, A. Walther and U. Ehlert in American Journal of Men’s Health

Footnotes

Acknowledgements

The authors would like to thank the Men’s Health 40+ study team, namely Nina Chiastra, Rahel Furrer, Anja Vandersmissen, and all interns, without whom the study would not have been possible. They are also grateful to Dr Firouzeh Fahramand for her extraordinary work in performing all hormone analyses. The authors further thank all participants for their time and motivation to join the study.

Authors’ Contributions

T.J.L. and U.E. designed the concept of the study. T.J.L. and A.W. organized and conducted the study and collected the data. T.J.L. wrote the first draft of the manuscript. U.E. and A.W. contributed with important intellectual content and edited subsequent versions of the manuscript.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The study was funded by the University Research Priority Program (URPP) “Dynamics of Healthy Aging” of the University of Zurich awarded to UE. The funding organization played no role in the design, analysis, or interpretation of the current study.

ORCID iD

U. Ehlert

Supplemental Material

Supplemental material for this article is available online.

References

Barrett-Connor

Von Mühlen

D. G.

Kritz-Silverstein

(1999). Bioavailable testosterone and depressed mood in older men: The rancho bernardo study. Journal of Clinical Endocrinology and Metabolism, 84(2), 573–577. https://doi.org/10.1210/jcem.84.2.5495

Barzilai

Cuervo

A. N.

Austad

(2018). Aging as a biological target for prevention and therapy. JAMA - Journal of the American Medical Association, 320(13), 1321–1322. https://doi.org/10.1016/j

Bates

Mächler

Bolker

B. M.

Walker

S. C.

(2015). Fitting linear mixed-effects models using lme4. Journal of Statistical Software, 67(1), 1–51. https://doi.org/10.18637/jss.v067.i01

Beard

J. R.

Officer

De Carvalho

I. A.

Sadana

Pot

A. M.

Michel

J. P.

Lloyd-Sherlock

Epping-Jordan

J. E.

Peeters

G. M. E. E.G.

Mahanani

W. R.

Thiyagarajan

J. A.

Chatterji

(2016). The World report on ageing and health: A policy framework for healthy ageing. The Lancet, 387(10033), 2145–2154. https://doi.org/10.1016/S0140-6736(15)00516-4

Benjamini

Hochberg

(1995). Controlling the false discovery rate: A practical and powerful approach to multiple testing. Journal of the Royal Statistical Society: Series B (Methodological), 57(1), 289–300.

Bullinger

Kirchberger

Ware

(1995). Der deutsche SF-36 Health Survey Übersetzung und psychometrische Testung eines krankheitsübergreifenden Instruments zur Erfassung der gesundheitsbezogenen Lebensqualität. Zeitschrift Für Gesundheitswissenschaften = Journal of Public Health, 3(1), 21–36. https://doi.org/10.1007/BF02959944

Campbell

Ehlert

(2012). Acute psychosocial stress: Does the emotional stress response correspond with physiological responses? Psychoneuroendocrinology, 37(8), 1111–1134. https://doi.org/10.1016/j.psyneuen.2011.12.010

Charles

S. T.

Carstensen

L. L.

(2009). Social and emotional aging. Annual Reviews in Psychology, 61(1), 383–409. https://doi.org/10.1146/annurev.psych.093008.100448

Chiappin

Antonelli

Gatti

Elio

(2007). Saliva specimen: A new laboratory tool for diagnostic and basic investigation. Clinica Chimica Acta, 383(1–2), 30–40.

10.

Clifton

Macdowall

Copas

A. J.

Tanton

Keevil

B. G.

Lee

D. M.

Mitchell

K. R.

Field

Sonnenberg

Bancroft

Mercer

C. H.

Wallace

A. M.

Johnson

A. M.

Wellings

F. C.

(2016). Salivary testosterone levels and health status in men and women in the British general population: Findings from the third national survey of sexual attitudes and lifestyles (natsal-3). Journal of Clinical Endocrinology and Metabolism, 101(11), 3939–3951. https://doi.org/10.1210/jc.2016-1669

11.

Corona

Mannucci

Ricca

Lotti

Boddi

Bandini

Forti

Maggi

(2009). The age-related decline of testosterone is associated with different specific symptoms and signs in patients with sexual dysfunction. International Journal of Andrology, 32(6), 720–728. https://doi.org/10.1111/j.1365-2605.2009.00952.x

12.

Corona

Rastrelli

Maseroli

Forti

Maggi

(2013). Sexual function of the ageing male. Best Practice and Research: Clinical Endocrinology and Metabolism, 27(4), 581–601. https://doi.org/10.1016/j.beem.2013.05.007

13.

Dainese

S. M.

Allemand

Ribeiro

Bayram

Martin

Ehlert

(2011). Protective factors in midlife. GeroPsych, 24(1), 19–29. https://doi.org/10.1024/1662-9647/a000032

14.

Dunbar

Gruman

Reisine

Kenny

(2001). Comparison of two health status measures and their associations with testosterone levels in older men. Aging Male, 4(1), 1–7. https://doi.org/10.1080/tam.4.1.1.7

15.

Ebner

N. C.

Kamin

Diaz

Cohen

R. A.

MacDonald

(2014). Hormones as “difference makers” in cognitive and socioemotional aging processes. Frontiers in Psychology, 5, 1595. https://doi.org/10.3389/fpsyg.2014.01595

16.

George

Engel

(1980). The american journal of psychiatry the clinical application of the biopsychosocial model. Am J Psychiatry, 137(5), 535–544.

17.

Feldman

H. A.

Longcope

Derby

C. A.

Johannes

C. B.

Araujo

A. B.

Coviello

A. D.

Bremner

W. J.

McKinlay

J. B.

(2002). 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, 87(2), 589–598. https://doi.org/10.1210/jcem.87.2.8201

18.

Fiacco

Walther

Ehlert

(2018). Steroid secretion in healthy aging. Psychoneuroendocrinology, (June), 0–1. https://doi.org/10.1016/j.psyneuen.2018.09.035

19.

Ford

A. H.

Yeap

B. B.

Flicker

Hankey

G. J.

Chubb

S. A. P.

Golledge

Almeida

O. P.

(2018). Sex hormones and incident dementia in older men: The health in men study. Psychoneuroendocrinology, 98, 139–147. https://doi.org/10.1016/j.psyneuen.2018.08.013

20.

Ford

A. H.

Yeap

B. B.

Flicker

Hankey

G. J.

Chubb

S. A. P.

Handelsman

D. J.

Golledge

Almeida

O. P.

(2016). Prospective longitudinal study of testosterone and incident depression in older men: The health in men study. Psychoneuroendocrinology, 64, 57–65. https://doi.org/10.1016/j.psyneuen.2015.11.012

21.

Franke

G. H.

Derogatis

L. R.

(2000). Brief symptom inventory: BSI;(Kurzform der SCL-90-R). Beltz Test.

22.

Friedman

E. M.

Karlamangla

A. S.

Almeida

D. M.

Seeman

T. E.

(2012). Social strain and cortisol regulation in midlife in the US. Social Science and Medicine, 74(4), 607–615. https://doi.org/10.1016/j.socscimed.2011.11.003

23.

Gaffey

A. E.

Bergeman

C. S.

Clark

L. A.

Wirth

M. M.

(2016). Aging and the HPA axis: Stress and resilience in older adults. Neuroscience and Biobehavioral Reviews, 68, 928–945. https://doi.org/10.1016/j.neubiorev.2016.05.036

24.

Goncharov

Katsya

Dobracheva

Nizhnik

Kolesnikova

Herbst

Westermann

(2006). Diagnostic significance of free salivary testosterone measurement using a direct luminescence immunoassay in healthy men and in patients with disorders of androgenic status. Aging Male, 9(2), 111–122. https://doi.org/10.1080/13685530600713060

25.

Gröschl

(2017). Saliva: A reliable sample matrix in bioanalytics. Bioanalysis, 9(8), 655–668. https://doi.org/10.4155/bio-2017-0010

26.

Gupta

Morley

J. E.

(2014). Hypothalamic-pituitary-adrenal (HPA) axis and aging. Comprehensive Physiology, 4(4), 1495–1510. https://doi.org/10.1002/cphy.c130049

27.

Han

Lee

Han

Kim

(2015). Psychosocial factors for influencing healthy aging in adults in Korea. Health and Quality of Life Outcomes, 13(1), 31. https://doi.org/10.1186/s12955-015-0225-5

28.

Handelsman

D. J.

Yeap

B. B.

Flicker

Martin

Wittert

G. A.

L. P.

(2015). Age-specific population centiles for androgen status in men. European Journal of Endocrinology, 173(6), 809–817. https://doi.org/10.1530/EJE-15-0380

29.

Harman

S. M.

Metter

E. J.

Tobin

J. D.

Pearson

Blackman

M. R.

(2001). Longitudinal effects of aging on serum total and free testosterone levels in healthy men. Journal of Clinical Endocrinology and Metabolism, 86(2), 724–731. https://doi.org/10.1210/jcem.86.2.7219

30.

Harris

Baker

Holt-Lunstad

Stephenson

Smith

T. B.

(2015). Loneliness and Social Isolation as Risk Factors for Mortality. Perspectives on Psychological Science, 10(2), 227–237. https://doi.org/10.1177/1745691614568352

31.

Hawkley

L. C.

Kocherginsky

(2018). Transitions in loneliness among older adults: A 5-year follow-up in the national social life, health, and aging project. Research on Aging, 40(4), 365–387. https://doi.org/10.1177/0164027517698965

32.

Hawkley

L. C.

Masi

C. M.

Berry

J. D.

Cacioppo

J. T.

(2006). Loneliness is a unique predictor of age-related differences in systolic blood pressure. Psychology and Aging, 21(1), 152.

33.

Hsu

Cumming

R. G.

Naganathan

Blyth

F. M.

Le Couteur

D. G.

Hirani

Waite

L. M.

Seibel

M. J.

Handelsman

D. J.

(2016). Temporal changes in androgens and estrogens are associated with all-cause and cause-specific mortality in older men. Journal of Clinical Endocrinology and Metabolism, 101(5), 2201–2210. https://doi.org/10.1210/jc.2016-1025

34.

Jakiel

Makara-Studzińska

Ciebiera

Słabuszewska-Jóźwiak

(2015). Andropause-state of the art 2015 and review of selected aspects. Przeglad Menopauzalny, 14(1), 1–6. https://doi.org/10.5114/pm.2015.49998

35.

Jasuja

G. K.

Travison

T. G.

Davda

Murabito

J. M.

Basaria

Zhang

Kushnir

M. M.

Rockwood

A. L.

Meikle

Pencina

M. J.

Coviello

Rose

A. J.

D’Agostino

Vasan

R. S.

(2013). Age trends in estradiol and estrone levels measured using liquid chromatography tandem mass spectrometry in community-dwelling men of the framingham heart study. Journals of Gerontology - Series A Biological Sciences and Medical Sciences, 68(6), 733–740. https://doi.org/10.1093/gerona/gls216

36.

Johnson

J. V.

Hall

E. M.

Theorell

(1989). Combined effects of job strain and social isolation on cardiovascular disease morbidity and mortality in a random sample of the Swedish male working population. Scandinavian Journal of Work, Environment and Health, 15(4), 271–279. https://doi.org/10.5271/sjweh.1852

37.

Karlamangla

A. S.

Friedman

E. M.

Seeman

T. E.

Stawksi

R. S.

Almeida

D. M.

(2013). Daytime trajectories of cortisol: Demographic and socioeconomic differences-findings from the national study of daily experiences. Psychoneuroendocrinology, 38(11), 2585–2597. https://doi.org/10.1016/j.psyneuen.2013.06.010

38.

Lewerin

Nilsson-Ehle

Jacobsson

Johansson

Sundh

Karlsson

M. K.

Lorentzon

Barrett-Connor

Vandenput

Ohlsson

Mellström

(2014). Serum estradiol associates with blood hemoglobin in elderly men: THE MROS Sweden study. Journal of Clinical Endocrinology and Metabolism, 99(7), 2549–2556. https://doi.org/10.1210/jc.2013-4111

39.

Lorem

G. F.

Schirmer

Wang

C. E. A.

Emaus

(2017). Ageing and mental health: Changes in self-reported health due to physical illness and mental health status with consecutive cross-sectional analyses. BMJ Open, 7(1), e013629. https://doi.org/10.1136/bmjopen-2016-013629

40.

Norman

P. E.

Flicker

Almeida

O. P.

Hankey

G. J.

Hyde

Jamrozik

(2009). Cohort profile: The Health In Men Study (HIMS). International Journal of Epidemiology, 38(1), 48–52. https://doi.org/10.1093/ije/dyn041

41.

Oettel

Mukhopadhyay

A. K.

(2004). Progesterone: The forgotten hormone in men? Aging Male, 7(3), 236–257. https://doi.org/10.1080/13685530400004199

42.

Ohlsson

Labrie

Barrett-Connor

Karlsson

M. K.

Ljunggren

Ö.

Vandenput

Mellström

Tivesten

. (2010). Low serum levels of dehydroepiandrosterone sulfate predict all-cause and cardiovascular mortality in elderly Swedish men. Journal of Clinical Endocrinology and Metabolism, 95(9), 4406–4414. https://doi.org/10.1210/jc.2010-0760

43.

Orth

Maes

Schmitt

(2015). Self-esteem development across the life span: A longitudinal study with a large sample from Germany. Developmental Psychology, 51(2), 248–259. https://doi.org/10.1037/a0038481

44.

Orth

Robins

R. W.

Widaman

K. F.

(2012). Life-span development of self-esteem and its effects on important life outcomes. Journal of Personality and Social Psychology, 102(6), 1271–1288. https://doi.org/10.1037/a0025558

45.

Orth

Trzesniewski

K. H.

Robins

R. W.

(2010). Self-esteem development from young adulthood to old age: A cohort-sequential longitudinal study. Journal of Personality and Social Psychology, 98(4), 645–658. https://doi.org/10.1037/a0018769

46.

Parker

C. R. Mixon

R. L.

Brissie

R. M.

Grizzle

W. E.

(1997). Aging alters zonation in the adrenal cortex of men. The Journal of Clinical Endocrinology & Metabolism, 82(11), 3898–3901.

47.

Payne

Hedberg

E. C.

Kozloski

Dale

McClintock

M. K.

(2014). Using and interpreting mental health measures in the national social life, health, and aging project. Journals of Gerontology - Series B Psychological Sciences and Social Sciences, 69(Suppl_2), S99–S116. https://doi.org/10.1093/geronb/gbu100

48.

Pruessner

J. C.

Hellhammer

D. H.

Kirschbaum

(1999). Low self-esteem, induced failure and the adrenocortical stress response. Personality and Individual Differences, 27(3), 477–489. https://doi.org/10.1016/S0191-8869(98)00256-6

49.

Robins

R. W.

Trzesniewski

K. H.

Tracy

J. L.

Gosling

S. D.

Potter

(2002). Global self-esteem across the life span. Psychology and Aging, 17(3), 423–434. https://doi.org/10.1037/0882-7974.17.3.423

50.

Rosen

R. C.

(1997). The international index of erectile function (IIEF): A multidimensional scale for assessment of erectile dysfunction, 4295(97). https://doi.org/10.1016/S0090-4295(97)00238-0

51.

Sartorius

Spasevska

Idan

Turner

Forbes

Zamojska

Allan

C. A.

L. P.

Conway

A. J.

McLachlan

R. I.

Handelsman

D. J.

(2012). Serum testosterone, dihydrotestosterone and estradiol concentrations in older men self-reporting very good health: The healthy man study. Clinical Endocrinology, 77(5), 755–763. https://doi.org/10.1111/j.1365-2265.2012.04432.x

52.

Scholz

Kliegel

Luszczynska

Knoll

(2012). Associations between received social support and positive and negative affect : Evidence for age differences from a daily-diary study, 9(4), 361–371. https://doi.org/10.1007/s10433-012-0236-6

53.

Schumacher

Mattern

Ghoumari

Oudinet

J. P.

Liere

Labombarda

Sitruk-Ware

De Nicola

A. F.

Guennoun

(2014). Revisiting the roles of progesterone and allopregnanolone in the nervous system: Resurgence of the progesterone receptors. Progress in Neurobiology, 113, 6–39.

54.

Schütz

Sellin

(2006). Die Multidimensionale Selbstwertskala (MSWS). Diagnostica, 54(3), 166. https://doi.org/10.1026/0012-1924.54.3.166

55.

Schwarzer

Schulz

(2003). Soziale Unterstützung bei der Krankheitsbewältigung: Die Berliner Social Support Skalen (BSSS) Social Support in Coping with Illness: Zusammenfassung. Diagnostica, 1–31. http://www.psycontent.com/index/J68T3312853W4189.pdf

56.

Shankar

McMunn

Demakakos

Hamer

Steptoe

(2017). Social isolation and loneliness: Prospective associations with functional status in older adults. Health Psychology, 36(2), 179–187. https://doi.org/10.1037/hea0000437

57.

Sollberger

Ehlert

(2016). How to use and interpret hormone ratios. Psychoneuroendocrinology, 63, 385–397. https://doi.org/10.1016/j.psyneuen.2015.09.031

58.

Spitzer

Hammer

Löwe

Grabe

H. J.

Barnow

Rose

Wingenfeld1

Freyberger

H. J.

Franke

G. H.

(2011). Die Kurzform des Brief Symptom Inventory (BSI-18): Erste Befunde zu den psychometrischen Kennwerten der deutschen Version. Fortschritte Der Neurologie Psychiatrie, 79(9), 517–523. https://doi.org/10.1055/s-0031-1281602

59.

Stalder

Kirschbaum

Kudielka

B. M.

Adam

E. K.

Pruessner

J. C.

Wüst

Dockray

Smyth

Evans

Hellhammer

D. H.

Miller

Wetherell

M. A.

Lupien

S. J.

Clow

(2016). Assessment of the cortisol awakening response: Expert consensus guidelines. Psychoneuroendocrinology, 63, 414–432. https://doi.org/10.1016/j.psyneuen.2015.10.010

60.

Statistik

für (Bfs). (2015). Schweizerische Lohnstruk-turerhebung 2012. https://www.bfs.admin.ch/bfs/de/home/statistiken/arbeit-erwerb/loehne-erwerbseinkommen-arbeitskosten/lohnniveau-schweiz/kaderloehne-tiefloehne.assetdetail.349377.html

61.

Tian

(2016). Intergeneration social support affects the subjective well-being of the elderly: Mediator roles of self-esteem and loneliness. Journal of Health Psychology, 21(6), 1137–1144. https://doi.org/10.1177/1359105314547245

62.

United Nations, P. D. D. of E. and S. A. (2017). World Aging Population 2017. United Nations. https://doi.org/10.1049/el:20000788

63.

Wagle

K. C.

Carrejo

M. H.

Tan

R. S.

(2012). The implications of increasing age on erectile dysfunction. American Journal of Men’s Health, 6(4), 273–279. https://doi.org/10.1177/1557988311431629

64.

Wagner

Hoppmann

Ram

Gerstorf

(2015). Self-esteem is relatively stable late in life: The role of resources in the health, self-regulation, and social domains. Developmental Psychology, 51(1), 136–149. https://doi.org/10.1037/a0038338

65.

Walther

Mahler

Debelak

Ehlert

(2017). Psychobiological protective factors modifying the association between age and sexual health in men: Findings from the men’s health 40+ study. American Journal of Men’s Health, 11(3), 737–747. https://doi.org/10.1177/1557988316689238

66.

Walther

Philipp

Lozza

Ehlert

(2016). The rate of change in declining steroid hormones: A new parameter of healthy aging in men? Oncotarget, 7(38), 60844. https://doi.org/10.18632/oncotarget.11752

67.

Weng

Coppini

D. V.

Sönksen

P. H.

(2000). Geographic and social factors are related to increased morbidity and mortality rates in diabetic patients. Diabetic Medicine, 17(8), 612–617. https://doi.org/10.1046/j.1464-5491.2000.00352.x

68.

Wiltink

Hauck

E. W.

Pha

(2003). Validation of the German version of the International Index of Erectile Function (IIEF) in patients with erectile dysfunction, Peyronie’s disease and controls, (November 2002), 192–197. https://doi.org/10.1038/sj.ijir.3900997

69.

World Health Organization. (2015). World report on ageing and health. World Health Organization.

70.

Zhou

J. N.

Swaab

D. F.

(1999). Activation and degeneration during aging: A morphometric study of the human hypothalamus. Microscopy Research and Technique, 44(1), 36–48. https://doi.org/10.1002/(SICI)1097-0029(19990101)44:1<36::AID-JEMT5>3.0.CO;2-F

71.

Zimmermann

Vermeulen

Thiel

Hummel

(1999). A new ‘aging males’ symptoms ’rating scale, 5538. https://doi.org/10.3109/13685539909003173

72.

Zitzmann

Erren

Kamischke

Simoni

Nieschlag

(2005). Endogenous progesterone and the exogenous progestin norethisterone enanthate are associated with a proinflammatory profile in healthy men. Journal of Clinical Endocrinology and Metabolism, 90(12), 6603–6608. https://doi.org/10.1210/jc.2005-0847

73.

Zorrilla

E. P.

DeRubeis

R. J.

Redei

(1995). High self-esteem, hardiness and affective stability are associated with higher basal pituitary-adrenal hormone levels. Psychoneuroendocrinology, 20(6), 591–601. https://doi.org/10.1016/0306-4530(95)00005-9

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