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BACKGROUND: Various factors modulate circulating testosterone in men, affecting interpretation of testosterone measurements. PURPOSE: To clarify factors associated with variations in sex hormone concentrations. DATA SOURCES: Systematic literature searches (to July 2019). STUDY SELECTION: Prospective cohort studies of community-dwelling men with total testosterone measured using mass spectrometry. DATA EXTRACTION: Individual participant data (IPD) (9 studies; n = 21 074) and aggregate data (2 studies; n = 4075). Sociodemographic, lifestyle, and health factors and concentrations of total testosterone, sex hormone-binding globulin (SHBG), luteinizing hormone (LH), dihydrotestosterone, and estradiol were extracted. DATA SYNTHESIS: Two-stage random-effects IPD meta-analyses found a nonlinear association of testosterone with age, with negligible change among men aged 17 to 70 years (change per SD increase about the midpoint, -0.27 nmol/L [-7.8 ng/dL] [CI, -0.71 to 0.18 nmol/L {-20.5 to 5.2 ng/dL}]) and decreasing testosterone levels with age for men older than 70 years (-1.55 nmol/L [-44.7 ng/dL] [CI, -2.05 to -1.06 nmol/L {-59.1 to -30.6 ng/dL}]). Testosterone was inversely associated with body mass index (BMI) (change per SD increase, -2.42 nmol/L [-69.7 ng/dL] [CI, -2.70 to -2.13 nmol/L {-77.8 to -61.4 ng/dL}]). Testosterone concentrations were lower for men who were married (mean difference, -0.57 nmol/L [-16.4 ng/dL] [CI, -0.89 to -0.26 nmol/L {-25.6 to -7.5 ng/dL}]); undertook at most 75 minutes of vigorous physical activity per week (-0.51 nmol/L [-14.7 ng/dL] [CI, -0.90 to -0.13 nmol/L {-25.9 to -3.7 ng/dL}]); were former smokers (-0.34 nmol/L [-9.8 ng/dL] [CI, -0.55 to -0.12 nmol/L {-15.9 to -3.5 ng/dL}]); or had hypertension (-0.53 nmol/L [-15.3 ng/dL] [CI, -0.82 to -0.24 nmol/L {-23.6 to -6.9 ng/dL}]), cardiovascular disease (-0.35 nmol/L [-10.1 ng/dL] [CI, -0.55 to -0.15 nmol/L {-15.9 to -4.3 ng/dL}]), cancer (-1.39 nmol/L [-40.1 ng/dL] [CI, -1.79 to -0.99 nmol/L {-51.6 to -28.5 ng/dL}]), or diabetes (-1.43 nmol/L [-41.2 ng/dL] [CI, -1.65 to -1.22 nmol/L {-47.6 to -35.2 ng/dL}]). Sex hormone-binding globulin was directly associated with age and inversely associated with BMI. Luteinizing hormone was directly associated with age in men older than 70 years. LIMITATION: Cross-sectional analysis, heterogeneity between studies and in timing of blood sampling, and imputation for missing data. CONCLUSION: Multiple factors are associated with variation in male testosterone, SHBG, and LH concentrations. Reduced testosterone and increased LH concentrations may indicate impaired testicular function after age 70 years. Interpretation of individual testosterone measurements should account particularly for age older than 70 years, obesity, diabetes, and cancer. PRIMARY FUNDING SOURCE: Medical Research Future Fund, Government of Western Australia, and Lawley Pharmaceuticals. (PROSPERO: CRD42019139668).

Objective Sociodemographic, lifestyle, and medical variables influence total testosterone (T) and sex hormone-binding globulin (SHBG) concentrations. The relationship between these factors and "free" T remains unclear. We examined 21 sociodemographic, lifestyle, and medical predictors influencing calculated free T (cFT) in community-dwelling men across ages. Design This is a cross-sectional analysis in 20 631 participants in the Androgens in Men Study. Methods Individual participant data (IPD) were provided by 9 cohorts. Total T was determined using mass spectrometry, SHBG using immunoassays, and cFT using the Vermeulen formula. Associations were analyzed using 2-stage random effects IPD meta-analyses. Results Cohort median ages ranged from 40 to 76 years and median cFT concentrations from 174.3 to 422.8 pmol/L. In men aged 17-99 years, there was a linear inverse association of cFT with age (−57.2 pmol/L [95% confidence interval, −69.4, −44.9] per 1 SD increase in age). Calculated free T increased with increasing baseline body mass index (BMI) among men with BMI < 23.6 kg/m2, but decreased among men with BMI > 23.6 kg/m2 (−24.7 pmol/L [−29.1, −20.3] per 1 SD increase in the 25.4-29.6 kg/m2 BMI range). Calculated free T was lower in younger men, who were married or in a de facto relationship (−18.4 pmol/L [−27.6, −9.3]) and in men who formerly smoked (−5.7 pmol/L [−8.9, −2.6]), were in poor general health (−14.0 pmol/L [−20.1, −7.8]), and had diabetes (−19.6 pmol/L [−23.0, −16.3]), cardiovascular disease (−5.8 pmol/L [−8.3, −3.2]), or cancer (−19.2 pmol/L [−24.4, −14.1]). Conclusions Calculated free T was most prominently associated with age and BMI. The linear, inverse association with age, nonlinear association with BMI, and presence of diabetes, cancer, and sociodemographic factors should be considered when interpreting cFT values. [ABSTRACT FROM AUTHOR]

The relationship between testosterone and related hormones and cardiovascular and mortality outcomes is debated. The authors of this study obtained individual patient–level data from 9 cohort studies and aggregate data from 11 studies in total. These data enabled them to describe the associations of testosterone, sex hormone–binding globulin (SHBG), luteinizing hormone (LH), dihydrotestosterone (DHT), and estradiol with all-cause mortality, cardiovascular death, and incident cardiovascular events while accounting for other cardiac risk factors. Background: Whether circulating sex hormones modulate mortality and cardiovascular disease (CVD) risk in aging men is controversial. Purpose: To clarify associations of sex hormones with these outcomes. Data Sources: Systematic literature review to July 2019, with bridge searches to March 2024. Study Selection: Prospective cohort studies of community-dwelling men with sex steroids measured using mass spectrometry and at least 5 years of follow-up. Data Extraction: Independent variables were testosterone, sex hormone–binding globulin (SHBG), luteinizing hormone (LH), dihydrotestosterone (DHT), and estradiol concentrations. Primary outcomes were all-cause mortality, CVD death, and incident CVD events. Covariates included age, body mass index, marital status, alcohol consumption, smoking, physical activity, hypertension, diabetes, creatinine concentration, ratio of total to high-density lipoprotein cholesterol, and lipid medication use. Data Synthesis: Nine studies provided individual participant data (IPD) (255 830 participant-years). Eleven studies provided summary estimates (n = 24 109). Two-stage random-effects IPD meta-analyses found that men with baseline testosterone concentrations below 7.4 nmol/L (<213 ng/dL), LH concentrations above 10 IU/L, or estradiol concentrations below 5.1 pmol/L had higher all-cause mortality, and those with testosterone concentrations below 5.3 nmol/L (<153 ng/dL) had higher CVD mortality risk. Lower SHBG concentration was associated with lower all-cause mortality (median for quintile 1 [Q1] vs. Q5, 20.6 vs. 68.3 nmol/L; adjusted hazard ratio [HR], 0.85 [95% CI, 0.77 to 0.95]) and lower CVD mortality (adjusted HR, 0.81 [CI, 0.65 to 1.00]). Men with lower baseline DHT concentrations had higher risk for all-cause mortality (median for Q1 vs. Q5, 0.69 vs. 2.45 nmol/L; adjusted HR, 1.19 [CI, 1.08 to 1.30]) and CVD mortality (adjusted HR, 1.29 [CI, 1.03 to 1.61]), and risk also increased with DHT concentrations above 2.45 nmol/L. Men with DHT concentrations below 0.59 nmol/L had increased risk for incident CVD events. Limitations: Observational study design, heterogeneity among studies, and imputation of missing data. Conclusion: Men with low testosterone, high LH, or very low estradiol concentrations had increased all-cause mortality. SHBG concentration was positively associated and DHT concentration was nonlinearly associated with all-cause and CVD mortality. Primary Funding Source: Medical Research Future Fund, Government of Western Australia, and Lawley Pharmaceuticals. (PROSPERO: CRD42019139668) [ABSTRACT FROM AUTHOR]

As commercial fishing activity shifts to target different grounds over time, spatial gaps can be created in catch rate data, leading to biases in derived indices of fish abundance. Imputation has been shown to reduce such biases. In this study, the relative performance of several imputation methods was assessed using simulated catch rate data sets. Simulations were carried out for three fish stocks targeted by a commercial hook-and-line fishery off the southwestern coast of Australia: snapper (Chrysophrys auratus), West Australian dhufish (Glaucosoma hebraicum), and baldchin groper (Choerodon rubescens). For high-growth scenarios, the mean squared errors (MSEs) of geometric and linear imputations were lower, indicating higher accuracy and precision than that for base method (constant value) imputations. For low-growth scenarios, the lowest MSEs were achieved for base method imputations. However, for the final standardized and imputed abundance indices, the base method index consistently demonstrated the largest biases. Our results demonstrate the importance of selecting an appropriate imputation method when standardizing catch rates from a commercial fishery that has changed its spatial pattern of fishing over time. Quand des activites de peche commerciale changent dans le temps pour cibler differents lieux de peche, des lacunes spatiales dans les donnees sur les taux de prises peuvent en resulter et mener a des biais dans les indices d'abondance de poissons en decoulant. Il a ete demontre que l'imputation reduit ce type de biais. Dans la presente etude, la performance relative de plusieurs methodes d'imputation a ete evaluee en utilisant des ensembles de donnees sur les taux de prises simules. Des simulations ont ete realisees pour trois stocks de poissons vises par une peche a la ligne au large de la cote sud -ouest de l'Australie, le vivaneau (Chrysophrys auratus), le merou geant (Glaucosoma hebraicum) et le labre (Choerodon rubescens). Pour les scenarios de forte croissance, les erreurs quadratiques moyennes (EQMs) des imputations geometriques et lineaires etaient plus faibles, indiquant de plus grandes exactitude et precision, que celles des imputations par la methode de base (valeur constante). Pour les scenarios de faible croissance, les EQM les plus faibles ont ete obtenues pour les imputations par la methode de base. Toutefois, pour les indices d'abondance normalisee et imputee finaux, l'indice de la methode de base etait uniformement caracterise par les plus grands biais. Les resultats demontrent l'importance du choix d'une methode d'imputation convenable pour la normalisation des taux de prises d'une peche commerciale dont la repartition spatiale a change au fil du temps. [Traduit par la Redaction], Introduction Conventional statistical methods, including generalized linear models (GLMs), are routinely used to standardize commercial catch per unit effort (CPUE) data into indices of relative fish abundance for stock assessment. [...]

Abstract--Demographic parameters were derived from sectioned otoliths of John's Snapper (Lutjanus johnii) from 4 regions across 9° of latitude and 23° of longitude in northern Australia. Latitudinal variation in size [...]

Abstract--Demographic parameters from seven exploited coral reef lutjanid species were compared as a case study of the implications of intra-family variation in life histories for multispecies harvest management. Modal lengths [...]

Abstract: Fish ages estimated from increments in otoliths are uncertain because of various sources of error, including increment interpretation. Interpretation error is often addressed by reading each otolith multiple times [...]

Summary: Objective: Testosterone and sex hormone‐binding globulin (SHBG) concentrations are reported to decline during male ageing, but whether these changes reflect physiological ageing or age‐related comorbidities remains uncertain. We examined longitudinal changes in serum testosterone and SHBG concentrations in middle‐aged to older men, concordance between baseline and follow‐up values and relationships with concomitant changes in lifestyle and medical factors. Design: Population‐based longitudinal cohort study. Participants: Community‐dwelling men aged 40–69 years. Measurements: Immunoassay serum total testosterone (n = 7812) and SHBG (n = 6491) at baseline (2006–2010) and follow‐up (2012–2013). Free testosterone (cFT) was calculated. Bland–Altman analyses and concordance correlation of repeated measurements were conducted. Associations of changes in hormone concentrations with lifestyle and medical factors were explored using Spearman's rank correlation. Results: Over 4.3 years follow‐up, there was a negligible mean change (±SE) in serum total testosterone concentration (+0.06 ± 0.03 nmol/L), whereas mean SHBG concentration increased (+3.69 ± 0.12 nmol/L) and cFT decreased (−10.7 ± 0.7 pmol/L). Concordance estimates were 0.67 (95% confidence interval [CI]: 0.66–0.69) for total testosterone, 0.83 (CI = 0.82–0.84) for SHBG and 0.56 (CI = 0.54–0.58) for cFT. Changes in serum total testosterone correlated with changes in SHBG (Spearman's rank ρ = 0.33, CI = 0.30–0.35), and inversely with changes in body mass index (BMI) (ρ = −0.18, CI = −0.20 to −0.16) and waist circumference (ρ = −0.13, CI = −0.15 to −0.11) and in SHBG with changes in BMI (ρ = −0.34, CI = −0.36 to −0.32) and waist circumference (ρ = −0.21, CI = −0.24 to −0.19). Conclusion: In relatively healthy middle‐aged to older men, mean serum total testosterone concentration is stable with ageing, while mean SHBG concentration increases. Both total testosterone and SHBG concentrations were highly concordant over time. [ABSTRACT FROM AUTHOR]

Objective: Serum testosterone concentrations are affected by factors unrelated to hypothalamo‐pituitary‐testicular axis pathology. We evaluated the impact of sociodemographic, lifestyle and medical factors, on serum testosterone and sex hormone–binding globulin (SHBG) in men aged 40‐69 years. Design: Cross‐sectional analysis of 208,677 community‐dwelling men from the UK Biobank. Measurements: We analysed associations of different factors with serum testosterone and SHBG (immunoassays) and calculated free testosterone (cFT), using smoothed centile plots, linear mixed models and effect size estimates. Results: Median (interquartile range) for serum testosterone was 11.6 (9.4‐14.1) nmol/L, SHBG 36.9 (27.9‐48.1) nmol/L and cFT 213 (178‐255) pmol/L. Age and BMI were inversely associated with testosterone and cFT, while SHBG was associated with age and inversely with BMI (all P <.001). Living with a partner, (South) Asian ethnicity, never or previous smoker and some medical conditions were associated with lower testosterone. Poultry or fish eater, and higher physical activity were associated with higher testosterone (all P <.001). Testosterone was lowered by ~0.5 nmol/L across ages, ~1.5 nmol/L for BMI 30 vs 25 kg/m2, ~2 nmol/L for (South) Asian ethnicity, living with partner, college/university qualifications, low red meat eater, insufficient physical activity and 0.3‐1.0 nmol/L with cardiovascular disease or diabetes. Different combinations of these factors varied serum testosterone by ~4 nmol/L, SHBG by ~30 nmol/L and cFT by ~60 pmol/L. Conclusions: The identified modifiable risk factors support lifestyle‐based interventions in men with low testosterone concentrations. Considering sociodemographic, lifestyle and medical factors facilitates more personalized interpretation of testosterone testing results with respect to existing reference ranges. [ABSTRACT FROM AUTHOR]

Introduction This study aims to clarify the role(s) of endogenous sex hormones to influence health outcomes in men, specifically to define the associations of plasma testosterone with incidence of cardiovascular events, cancer, dementia and mortality risk, and to identify factors predicting testosterone concentrations. Data will be accrued from at least three Australian, two European and four North American population-based cohorts involving approximately 20 000 men. Methods and analysis Eligible studies include prospective cohort studies with baseline testosterone concentrations measured using mass spectrometry and 5 years of follow-up data on incident cardiovascular events, mortality, cancer diagnoses or deaths, newonset dementia or decline in cognitive function recorded. Data for men, who were not taking androgens or drugs suppressing testosterone production, metabolism or action; and had no prior orchidectomy, are eligible. Systematic literature searches were conducted from 14 June 2019 to 31 December 2019, with no date range set for searches. Aggregate level data will be sought where individual participant data (IPD) are not available. One-stage IPD random-effects meta-analyses will be performed, using linear mixed models, generalised linear mixed models and either stratified or frailty-augmented Cox regression models. Heterogeneity in estimates from different studies will be quantified and bias investigated using funnel plots. Effect size estimates will be presented in forest plots and non-negligible heterogeneity and bias investigated using subgroup or meta-regression analyses. Ethics and dissemination Ethics approvals obtained for each of the participating cohorts state that participants have consented to have their data collected and used for research purposes. The Androgens In Men Study has been assessed as exempt from ethics review by the Human Ethics office at the University of Western Australia (file reference number RA/4/20/5014). Each of the component studies had obtained ethics approvals; please refer to respective component studies for details. Research findings will be disseminated to the scientific and broader community via the publication of four research articles, with each involving a separate set of IPD meta-analyses (articles will investigate different, distinct outcomes), at scientific conferences and meetings of relevant professional societies. Collaborating cohort studies will disseminate findings to study participants and local communities. [ABSTRACT FROM AUTHOR]

Demographic parameters from seven exploited coral reef lutjanid species were compared as a case study of the implications of intra- family variation in life histories for multispecies harvest management. Modal lengths varied by 4 cm among four species (Lutjanus fulviflamma, L. vitta, L. carponotatus, L. adetii), which were at least 6 cm smaller than the modal lengths of the largest species (L. gibbus, Symphorus nematophorus, Aprion virescens). Modal ages, indicat- ing ages of full selection to fishing gear, were 10 years or less for all species, but maximum ages ranged from 12 (L. gibbus) to 36 years (S. nematophorus). Each species had a unique growth pattern, with differences in length-at-age and mean asymptotic fork length (L∞), but smaller species generally grew fast during the first 1-2 years of life and larger species grew more slowly over a longer period. Total mortality rates varied among species; L. gibbus had the highest mortality and L. fulviflamma, the lowest mortality. The variability in life history strategies of these tropical lutjanids makes generalizations about lutjanid life histories difficult, but the fact that all seven had characteristics that would make them particularly vulnerable to fishing indicates that harvest of tropical lutjanids should be managed with caution. [ABSTRACT FROM AUTHOR]