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PURPOSE: To better understand the effects of aging, metabolic syndrome, diurnal variation, and seasonal variation on serum testosterone levels in the context of current guideline statements on testosterone deficiency. METHODS: This cross-sectional study utilized the United Kingdom Biobank. Physical examination, anthropomorphic measurements, and laboratory evaluation were performed at the time of enrollment from 2006 to 2010. The primary outcomes were the effect of age, the presence of metabolic syndrome, the time of day, and the month of the year on serum testosterone levels. RESULTS: Among 197,883 included men, the 5th, 25th, 50th, 75th and 95th percentile testosterone levels in men without metabolic syndrome were significantly higher than those in men with metabolic syndrome at every decade of life (p < 0.001). The average testosterone level within each group (men without metabolic syndrome vs. men with) was clinically similar across decade of life (12.43 in 40's 12.29 in 50's 12.24 in 60's vs. 10.69 in 40's 10.56 in 50's 10.63 in 60's respectively). Average testosterone levels decreased with blood draws later in the day ranging from 10.91 to 12.74 nmol/L (p < 0.01). Similarly, there was seasonal variation in serum testosterone ranging from 11.86 to 12.18 nmol/L (p < 0.01). CONCLUSIONS: We found significant variation in serum testosterone according to the presence of metabolic syndrome and time of laboratory draw, but not according to age. These data challenge the prior dogma of age-related hypogonadism and favor an individualized approach towards serum testosterone measurement and interpretation. However, further studies are needed to correlate these population-based data with individuals' hypogonadal symptoms.
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INTRODUCTION: Our study examines the factors associated with urologist availability for younger and older men across the country over a period of 18 years from 2000 to 2018. METHODS: The Area Health Resource Files and US Census Data were analyzed from 2000, 2010, and 2018. The younger male population was defined as men aged 20 to 49, and the older male population was defined as ages 50 to 79. Urologist availability was determined by county at all time points. Logistic regression analysis and geographically weighted regression was completed. RESULTS: Over an 18-year period, overall urologist availability decreased for men by 19.6%. Access to urologist availability for men in metropolitan and rural counties decreased by 9.4% and 29.5%, respectively. Among the younger male cohort, urologist availability increased in metropolitan counties by 4%, but decreased by 16% in rural counties. There was an overall decrease in urologist availability of 28% and 43% in metropolitan and rural counties in the older male population. Multiple logistic regression analysis demonstrated that metropolitan status was the most significant factor associated with urologist availability for both male populations. The odds of each independent factor predicting urologist availability for the younger and older male population is dependent on geography. CONCLUSIONS: The majority of the male population has seen a decline in urologist availability. This is especially true for the older male residing in a rural county. Predictors of urologist availability depend on geographical regions, and understanding these regional drivers may allow us to better address disparities in urological care.