MP78-01 Trends In Serum Testosterone Levels Among Adolescent And Young Adult Men In The United States

Soum D. Lokeshwar*Premal Patel, Richard Fantus, Joshua Halpern, Cecilia Chang, Atil Kargi, Ranjith Ramasamy

Background

• Testosterone deficiency:10-40% among adult males

• 20% among adolescent and young adult (AYA) men

– Men 15-39 years old

• Testosterone deficiency: Below 270-300 ng/dL

• Testosterone declining in men in the last few decades

Introduction• Overall male testosterone decline

– Rise in comorbidities– Aging population

• Trend in AYA males still not understood• Objective: Analyze serum TT levels in AYA males using data from the

National Health and Nutrition Examination Surveys (NHANES) 1999-2016

• Hypothesis: Serum TT levels in AYA men have decreased over time.

Methods• NHANES is a nationally representative cross-sectional

survey• Examines the US pop and oversamples targeted

populations• Utilized data cycles: values for serum TT and analyzed

changes in serum TT over time controlling for variables from 1999-2016

• Three different assays for serum TT• Biotin-Streptavidin from 1999-2004• IS-Liquid Chromatography from 2011-2012• High-Performance-Liquid-Chromatography Tandem Mass

Spectrometry 2013 -

Results

• 4,045 men had TT measured from 1999-2016

• TT was lower among men in the later (2011-2016) versus earlier (1999-2000) cycles (all p < 0.001)

• Mean TT decreased over time– 605.39 ng/dL 451.22 for years 1999-2000 & 2015-2016

respectively (p < 0.0001)

Testosterone over time

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99-00 03-04 11-12 13-14 15-16Avg

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Year of datasets15-19 20-29 30-39 15-19 20-29 30-39

Testosterone over time

0%

5%

10%

15%

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25%

1999-2000 2015-2016

Percent of TT <300 ng/dL

Testosterone and BMI

• Elevated BMI was associated with reduced TT levels (p < 0.0001)

• Mean BMI increased steadily from 25.83 in 99-00 to 27.96 in 15-16 (p = 0.0006)

• Men with a normal BMI (18.5-24.9), TT levels have declined (p < 0.05)

Testosterone and BMI

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99-00 03-04 11-12 13-14 15-16

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Year of datasetsBMI 18.5-24.9 BMI 18.5-24.9

• Obesity/BMI• CDC: 18.5% 2015-216 vs 13.9% 1999-2000

• Assay variations

• Diet/phytoestrogens

• Exercise/physical activity

• Declined over time

• Body composition: % Fat

• Marijuana

• Environmental toxins

Potential Causes

• T: comorbidities, mortality risk

• T: AYA with obesity may precocious cancer

• T: low libido and ED

• TT levels in AYA are utilized as the benchmark normal levels for TT

• Undertreatment of testosterone deficiency

Impact

• Significant decline in TT from 1999 to 2016 in AYA men• Significant when controlling for confounders• Elevated BMI was found to be an independent predictor of declining TT

levels with increasing BMI found among AYA men over time

Conclusion

References• [1] Peterson MD, Belakovskiy A, McGrath R, Yarrow JF. Testosterone Deficiency, Weakness, and Multimorbidity in Men. Scientific Reports. 2018;8:5897.• [2] Coccia PF. Overview of Adolescent and Young Adult Oncology. J Oncol Pract. 2019;15:235-7.• [3] Travison TG, Araujo AB, O'Donnell AB, Kupelian V, McKinlay JB. A population-level decline in serum testosterone levels in American men. J Clin Endocrinol

Metab. 2007;92:196-202.• [4] He Z, Bian J, Carretta HJ, Lee J, Hogan WR, Shenkman E, et al. Prevalence of Multiple Chronic Conditions Among Older Adults in Florida and the United

States: Comparative Analysis of the OneFlorida Data Trust and National Inpatient Sample. J Med Internet Res. 2018;20:e137-e.• [5] Hales CM, Carroll MD, Fryar CD, Ogden CL. Prevalence of obesity among adults and youth: United States, 2015–2016. 2017.• [6] Grossmann M. Low testosterone in men with type 2 diabetes: significance and treatment. J Clin Endocrinol Metab. 2011;96:2341-53.• [7] Hu TY, Chen YC, Lin P, Shih CK, Bai CH, Yuan KC, et al. Testosterone-Associated Dietary Pattern Predicts Low Testosterone Levels and Hypogonadism.

Nutrients. 2018;10.• [8] Kerr WC, Lui C, Ye Y. Trends and age, period and cohort effects for marijuana use prevalence in the 1984–2015 US National Alcohol Surveys. Addiction.

2018;113:473-81.• [9] Kolodny RC, Masters WH, Kolodner RM, Toro G. Depression of plasma testosterone levels after chronic intensive marihuana use. The New England journal of

medicine. 1974;290:872-4.• [10] Holmboe SA, Skakkebaek NE, Juul A, Scheike T, Jensen TK, Linneberg A, et al. Individual testosterone decline and future mortality risk in men. Eur J

Endocrinol. 2018;178:123-30.• [11] Cohen J, Nassau DE, Patel P, Ramasamy R. Low Testosterone in Adolescents & Young Adults. Frontiers in Endocrinology. 2020;10.• [12] Herati AS, Cengiz C, Lamb DJ. Assays of Serum Testosterone. The Urologic clinics of North America. 2016;43:177-84.• [13] Wang C, Catlin DH, Demers LM, Starcevic B, Swerdloff RS. Measurement of total serum testosterone in adult men: comparison of current laboratory

methods versus liquid chromatography-tandem mass spectrometry. J Clin Endocrinol Metab. 2004;89:534-43.

The Association Between Guideline-based Exercise Thresholds and Low Testosterone Among Men in the

United States

Disclosures

• None

Low Testosterone Is Common

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Decade of LifeHarman et al JCEM 2001

• Losing weight or maintaining weight within recommended range + physical activity can reduce signs/symptoms associated with TD

• High BMI w/ LT puts patients at risk for cardiovascular events

• Overweight and obese patients should be counseled regarding weight loss programs

Mulhall et al J Urol 2018

Testosterone deficiency (TD) = low testosterone (LT) + symptomsAndrogen Deficiency in Aging Males

(ADAM) QuestionnaireDo you have a decrease in libido?

Do you have a lack of energy?

Do you have a decrease in strength and/or endurance?

Have you lost height?

Have you noticed a decreased "enjoyment of life”?

Are you sad and/or grumpy?

Are your erections less strong?Have you noticed a recent deterioration in your ability to play sports?

Are you falling asleep after dinner?

Has there been a recent deterioration in your work performance?Morley et al Metabolism 2000Mulhall et al J Urol 2018

In 2018 The Physical Activity Guideline Advisory Committee (PAGAC) set a target activity goal between 500-1000 MET minutes / week

MET = Metabolic Equivalent or amount of oxygen consumed while sitting at rest

Sedentary ≤1.5 METsSitting

Light activity 1.6-2.9 METsActivity that doesn’t change HR

Slowly walking, cooking

Moderate 3.0-5.9 METsActivity that doesn’t interrupt conversation

Walking > 3mph, mowing lawn

Vigorous ≥ 6 METsActivity that prohibits continuous conversation

Jogging, cycling uphill

Jette Clin Cardiol. 1990Verschuren et al Trans Stroke Research 2014

• Meeting PAGAC goal is associated with:• Decreased risk hypertension• Decreased risk DM• Improvements in cognitive function• Reduction in falls

• No comment on its effects on testosterone

Why Exercise?

Question: Are PAGAC activity thresholds associated with the likelihood of an individual having LT?

Hypothesis: Men at higher levels of activity levels are less likely to have LT.

Question / Hypothesis

CDC-sponsored survey to determine health of United States (US)

https://www.cdc.gov/nchs/nhanes/index.htm

• Included• Data cycles 2011-2016• Men age 18-80 with activity questionnaire and serum T level

• Excluded• Men with prostate cancer

Activity was categorized as work, recreational or for transportation

Activity in each category then divided into vigorous or moderate

Activity METs

Moderate work-related activity 4

Moderate leisure-time physical activity 4

Walking or bicycling for transportation 4

Vigorous work-related activity 8

Vigorous leisure-time physical activity 8cdc.gov/NChs/Nhanes/2011-2012/PAQ_G.htmcdc.gov/NChs/Nhanes/2013-2014/PAQ_H.htmcdc.gov/NChs/Nhanes/2015-2016/PAQ_I.htm

Activity thresholds determined by PAGAC guidelines

PAGAC Thresholds MET minutes per Week< Recommended <500Recommended 500-1000> Recomennded >1000

Cohort by PAGAC Activity Level

N=7372

59%

9%

32%

Greater Than RecommendedRecommendedLess Than Recommended

Men who did NOT meet 500 MET minutes per week activity threshold were

• Older• Higher BMIs• Higher likelihood of comorbidity• Higher likelihood of DM

• Average T of cohort = 413.1 ng/dL

• 2100 (28.5%) had LT

• Univariable analysis demonstrated men with LT (compared to those without) were more likely to be• Older• Obese• To have one or more comorbidities• Less physically active

Multivariable models created to determine associations with LT, controlling for age, BMI, diet, comorbidities, and time of lab draw

Only men who performed >1000 MET minutes per week were less likely to have LT compared to men performing < 500 MET minutes per weekOR 0.631 (95% CI 0.549-0.725, p < 0.001)

To better understand BMI’s relationship with Exercise and testosterone we stratified the population into normal, overweight and obese categories by BMI

Using the same covariates (except BMI), the association between activity level and LT only remained statistically significant in the obese group

BMI < 25 BMI 25-30 BMI ≥ 30

OR 95% CI P OR 95% CI P OR 95% CI P

Total Physical Activity

< Recommended (reference) - - - - - - - - -

Recommended 1.064 0.424-2.671 0.893 0.899 0.511-1.582 0.706 0.847 0.452-1.59 0.599

> Recommended 0.754 0.477-1.19 0.219 0.774 0.575-1.044 0.091 0.523 0.409-0.669 <0.001

So why only in obese men?

The effects of exercise on T are intimately related with weight loss

AACE suggests 5-10% weight loss can improve T

Multiple small trials corroborate this

Kumagai J Clin Biochem Nutr 2016Garvey Endocr Pract Off J Am Coll Endocrinol Am Assoc Clin Endocrinol 2016Vaamonde Eur J Appl Physiol 2012

Limitations

• Cross-sectional study design

• Self-reported activity à recall bias

• Testosterone levels only measured once

• No data on participants’ symptoms

Strengths

• Largest study of its kind

• Generalizable cohort

• NHANES has good data fidelity

• T measured with gold standard tandem MS-LC

Conclusions

• Exercise is an important lifestyle modification that should be offered to everyone

• When counseling men regarding LT and exercise, our data suggest that there is an inverse association between the risk of LT and exercising > 1000 MET minutes per week in the obese population (compared to < 500)

Questions

Linda My Huynh, Karren Liang, Mohammad M Osman, Farouk M El-Khatib, Sharmin Dianatnejad, Natalie Roberts, Faysal A. Yafi

Organic Diet and Intermittent Fasting are Associated with Improved Erectile Function

April 27, 2020

Introduction & Objective• Erectile dysfunction (ED) effects 30-52% of men above the age of 40. • Men with metabolic comorbidities such as diabetes mellitus, CVD/CAD,

and obesity, are at 30-70% increased lifetime risk for ED. • These comorbidity profiles are largely modifiable by lifestyle

intervention and diet, of which a number have become increasingly popular over recent years: organic foods, intermittent fasting, veganism, keto, paleo, etc.

• The present study seeks to explore associations between dietary habits and ED in a cohort of patients presenting to a high-volume men’s health clinic.

Materials and Methods • Between July 2018 and May 2019, 271 patients presenting to our men’s

health clinic were evaluated for their dietary habits and screened with the IIEF-5 and ADAM questionnaires.

• Patients on testosterone therapy, had penile implants, and/or refused to complete questionnaires were excluded from this cohort.

• Clinical demographics, reason for visit, and test results were prospectively collected from EMR.

• Primary outcome measure was the impact of dietary habits on ED, defined as IIEF-5<22. Stepwise logistic regressions were used to control for patient characteristics and relevant comorbidities.

Results – Cohort DescriptivesN %

Reason for Visit*Erectile Dysfunction 110 40.6%Peyronie’s Disease 30 11.1%Hypogonadism 39 14.4%Ejaculatory Dysfunction 2 <1%Elevated PSA 10 3.7%BPH/LUTS 80 29.5%Infertility Disease 18 6.6%Varicocele 22 8.1%Other 80 29.5%

Comorbidities*Diabetes 35 12.9%Hypertension 63 23.2%CVD/CAD 16 6.6%CKD 9 3.3%Liver Disease 7 2.6%

• Age: 53.3 ± 17.6• BMI: 27.6 ± 5.1• IIEF-5: 16.7 ± 7.8• 41% of patients had ED listed

as the primary reason for visit. • An additional 20% of patients

screened <22 on the IIEF-5 and were included in analysis.

• 42% of the total cohort had DM, CVD/CAD, and HTN.

*selections were not mutually exclusive

Results – Cohort DescriptivesN %

Reason for Visit*Erectile Dysfunction 110 40.6%Peyronie’s Disease 30 11.1%Hypogonadism 39 14.4%Ejaculatory Dysfunction 2 <1%Elevated PSA 10 3.7%BPH/LUTS 80 29.5%Infertility Disease 18 6.6%Varicocele 22 8.1%Other 80 29.5%

Comorbidities*Diabetes 35 12.9%Hypertension 63 23.2%CVD/CAD 16 6.6%CKD 9 3.3%Liver Disease 7 2.6%

• Age: 53.3 ± 17.6• BMI: 27.6 ± 5.1• IIEF-5: 16.7 ± 7.8• 41% of patients had ED listed

as the primary reason for visit. • An additional 20% of patients

screened <22 on the IIEF-5 and were included in analysis.

• 42% of the total chort had DM, CVD/CAD, and HTN.

*selections were not mutually exclusive

N %

Organic Foods Only 105 38.7%

No Processed Foods 51 18.8%

Intermittent Fasting 77 28.4%

Food Group Avoidance

Whole Food Only 11 4.1%

Low-Carb / Keto 11 4.1%

Vegetarian / Pescatarian 8 3.0%

Low-Fat 11 4.1%

Other 3 1.1%

Results – Organic Diet on EDUnivariate Multivariate - Demographics Multivariate - Comorbidities

OR (95% CI) p OR (95%CI) p OR (95%CI) p

Organic Diet 1.788 (1.074-2.976) 0.025 1.836 (1.071-3.417) 0.027 1.809 (1.023-3.198) 0.042

Age [<65 [ref] vs. >65] 0.349 (0.197-0.617) 0.000 0.346 (0.188-0.636) 0.001 0.557 (0.289-1.076) 0.082

Body Mass Index 0.947 (0.897-1.000) 0.050 0.937 (0.884-0.993) 0.027 0.957 (0.897-1.020) 0.177

Diabetes Mellitus [0 [ref] vs 1] 0.110 (0.033-0.369) <0.001 - - 0.219 (0.060-0.795) 0.021

Hypertension [0 [ref] vs 1] 0.145 (0.066-0.321) <0.001 - - 0.141 (0.141-0.812) 0.015

CVD/CAD [0 [ref] vs 1] 0.198 (0.24-1.630) 0.110 - - - 0.998

• In univariate analysis, organic diet, age, BMI, DM, and HTN were significant predictors of ED.

Results – Organic Diet on EDUnivariate Multivariate - Demographics Multivariate - Comorbidities

OR (95% CI) p OR (95%CI) p OR (95%CI) p

Organic Diet 1.788 (1.074-2.976) 0.025 1.836 (1.071-3.417) 0.027 1.809 (1.023-3.198) 0.042

Age [<65 [ref] vs. >65] 0.349 (0.197-0.617) 0.000 0.346 (0.188-0.636) 0.001 0.557 (0.289-1.076) 0.082

Body Mass Index 0.947 (0.897-1.000) 0.050 0.937 (0.884-0.993) 0.027 0.957 (0.897-1.020) 0.177

Diabetes Mellitus [0 [ref] vs 1] 0.110 (0.033-0.369) <0.001 - - 0.219 (0.060-0.795) 0.021

Hypertension [0 [ref] vs 1] 0.145 (0.066-0.321) <0.001 - - 0.141 (0.141-0.812) 0.015

CVD/CAD [0 [ref] vs 1] 0.198 (0.24-1.630) 0.110 - - - 0.998

• After adjusting for age and BMI as demographics, we found organic diet to be an independent predictor of ED. Age and BMI still remained significant.

Results – Organic Diet on ED Univariate Multivariate - Demographics Multivariate - Comorbidities

OR (95% CI) p OR (95%CI) p OR (95%CI) p

Organic Diet 1.788 (1.074-2.976) 0.025 1.836 (1.071-3.417) 0.027 1.809 (1.023-3.198) 0.042

Age [<65 [ref] vs. >65] 0.349 (0.197-0.617) 0.000 0.346 (0.188-0.636) 0.001 0.557 (0.289-1.076) 0.082

Body Mass Index 0.947 (0.897-1.000) 0.050 0.937 (0.884-0.993) 0.027 0.957 (0.897-1.020) 0.177

Diabetes Mellitus [0 [ref] vs 1] 0.110 (0.033-0.369) <0.001 - - 0.219 (0.060-0.795) 0.021

Hypertension [0 [ref] vs 1] 0.145 (0.066-0.321) <0.001 - - 0.141 (0.141-0.812) 0.015

CVD/CAD [0 [ref] vs 1] 0.198 (0.24-1.630) 0.110 - - - 0.998

• Finally, in the last step of the model, we added DM and HTN as comorbidities, significant from the univariate model.

• Overall, organic diet still remained an independent and protective against ED. DM and HTN were also independent predictors.

Results – Intermittent Fasting on EDUnivariate Multivariate - Demographics Multivariate - Comorbidities

OR (95% CI) p OR (95%CI) p OR (95%CI) p

Intermittent Fasting 1.997 (1.043-3.823) 0.037 2.111 (1.054-4.227) 0.035 2.425 (1.132-4.725) 0.023

Age [<65 [ref] vs. >65] 0.349 (0.197-0.617) <0.001 0.329 (0.178-0.607) <0.001 0.548 (0.281-0.983) 0.078

Body Mass Index 0.947 (0.897-1.000) 0.050 0.932 (0.897-0.989) 0.02 0.955 (0.895-1.023) 0.173

Diabetes Mellitus [0 [ref] vs 1] 0.110 (0.033-0.369) <0.001 - - 0.248 (0.067-0.828) 0.036

Hypertension [0 [ref] vs 1] 0.145 (0.066-0.321) <0.001 - - 0.301 (0.125-0.603) 0.007

CAD/CVD [0 [ref] vs 1] 0.198 (0.24-1.630) 0.110 - - - 0.998

• Similar results were found with intermittent fasting, with fasting, DM, and HTN as significant and independent predictors of ED.

Results – Intermittent Fasting on EDUnivariate Multivariate - Demographics Multivariate - Comorbidities

OR (95% CI) p OR (95%CI) p OR (95%CI) p

Intermittent Fasting 1.997 (1.043-3.823) 0.037 2.111 (1.054-4.227) 0.035 2.425 (1.132-4.725) 0.023

Age [<65 [ref] vs. >65] 0.349 (0.197-0.617) <0.001 0.329 (0.178-0.607) <0.001 0.548 (0.281-0.983) 0.078

Body Mass Index 0.947 (0.897-1.000) 0.050 0.932 (0.897-0.989) 0.02 0.955 (0.895-1.023) 0.173

Diabetes Mellitus [0 [ref] vs 1] 0.110 (0.033-0.369) <0.001 - - 0.248 (0.067-0.828) 0.036

Hypertension [0 [ref] vs 1] 0.145 (0.066-0.321) <0.001 - - 0.301 (0.125-0.603) 0.007

CAD/CVD [0 [ref] vs 1] 0.198 (0.24-1.630) 0.110 - - - 0.998

• Similar results were found with intermittent fasting, with fasting, DM, and HTN as significant and independent predictors of ED.

Results – Intermittent Fasting on EDUnivariate Multivariate - Demographics Multivariate - Comorbidities

OR (95% CI) p OR (95%CI) p OR (95%CI) p

Intermittent Fasting 1.997 (1.043-3.823) 0.037 2.111 (1.054-4.227) 0.035 2.425 (1.132-4.725) 0.023

Age [<65 [ref] vs. >65] 0.349 (0.197-0.617) <0.001 0.329 (0.178-0.607) <0.001 0.548 (0.281-0.983) 0.078

Body Mass Index 0.947 (0.897-1.000) 0.050 0.932 (0.897-0.989) 0.02 0.955 (0.895-1.023) 0.173

Diabetes Mellitus [0 [ref] vs 1] 0.110 (0.033-0.369) <0.001 - - 0.248 (0.067-0.828) 0.036

Hypertension [0 [ref] vs 1] 0.145 (0.066-0.321) <0.001 - - 0.301 (0.125-0.603) 0.007

CAD/CVD [0 [ref] vs 1] 0.198 (0.24-1.630) 0.110 - - - 0.998

• Similar results were found with intermittent fasting, with fasting, DM, and HTN as significant and independent predictors of ED.

Discussion & Limitations• Patients adhering to organic diet or intermittent

fasting were 1.8 and 2.4 times more likely to report normal EF.

• Other diet regimens mentioned were <5% of the total cohort of patients & could not be assessed.

• Extent / control of comorbidities was not available • Retrospective and correlative study with hypothesis-

generated results, encouraging prospective trials

Conclusions• Comorbidities of DM and HTN persist as important

contributors to ED, perhaps not entirely modifiable via the diets discussed here.

• We caution the conclusion that it is organic diet or intermittent fasting alone that benefit EF in aging men. • Rather, we presume these choices to be part of an extensive

process of increased awareness in food consumption, their nutritional value, and overall health-consciousness.

Summary • This is the first study suggesting organic diet and

intermittent fasting to be protective against ED.

• This benefit is independent of age and BMI, although dependent on comorbidity status.

• Results are hypothesis-generating and encourage prospective trials exploring the impact of diet on ED.