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1.
Andrology ; 4(3): 465-72, 2016 05.
Artículo en Inglés | MEDLINE | ID: mdl-26991734

RESUMEN

Testosterone levels and physical activity each play important roles in men's health, but the relationship between the two remains unclear. We evaluated the cross-sectional association between self-reported total physical activity and serum testosterone levels in 738 men (mean age 42.4 years, range 20-≥85 years) who participated in National Health and Nutrition Examination Survey 1999-2004. We compared geometric mean testosterone concentrations measured by radioimmunoassay (RIA) and calculated the odds ratio (OR) of having low or low normal testosterone (≤3.46 ng/mL) across tertiles of total physical activity in all men, and men stratified by age (20-49, ≥50 years), and obesity status (BMI < 30, ≥30 kg/m(2) ). The geometric mean testosterone concentration was 5.31 ng/mL; 18.6% of the men had low or low normal serum testosterone levels. Physical activity tertiles were not associated with testosterone levels overall, or when stratified by age or obesity status. Similarly, there was no association between physical activity tertiles and the odds of low or low normal testosterone, overall or by age. However, among non-obese men, those in the highest physical activity tertile were significantly less likely to have low or low normal testosterone than those in the lowest tertile (OR 0.50; 95% CI = 0.26-0.95); there was no association among obese men. Greater physical activity was not associated with testosterone levels, but may be associated with a reduced odds of low or low normal testosterone in non-obese men, but not in obese men.


Asunto(s)
Ejercicio Físico/fisiología , Testosterona/sangre , Adulto , Anciano , Anciano de 80 o más Años , Estudios Transversales , Humanos , Masculino , Persona de Mediana Edad , Encuestas Nutricionales , Obesidad/sangre , Estados Unidos , Adulto Joven
2.
Br J Cancer ; 112(4): 769-76, 2015 Feb 17.
Artículo en Inglés | MEDLINE | ID: mdl-25562437

RESUMEN

BACKGROUND: Recent large-scale prospective studies suggest that long telomeres are associated with an increase cancer risk, counter to conventional wisdom. METHODS: To further clarify the association between leukocyte telomere length (LTL) and prostate cancer, and assess genetic variability in relation to both LTL and prostate cancer, we performed a nested case-control study (922 cases and 935 controls). The participants provided blood in 1993-1995 and were followed through August 2004 (prostate cancer incidence) or until 28 February 2013 (lethal or fatal prostate cancer). Relative LTL was measured by quantitative PCR and was calculated as the ratio of telomere repeat copy number to a single gene (36B4) copy number (T/S). Genotyping was performed using the TaqMan OpenArray SNP Genotyping Platform. Logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) of all prostate cancer and subtypes defined by Gleason grade, stage and lethality (metastasis or death). RESULTS: We observed a positive association between each s.d. increase in LTL and all (multivariable-adjusted OR 1.11, 95% CI: 1.01-1.22), low-grade (OR 1.13, 95% CI:1.01-1.27), and localised (OR 1.12, 95% CI:1.01-1.24) prostate cancer. Associations for other subtypes were similar, but did not reach statistical significance. In subgroup analyses, associations for high grade and advanced stage (OR=2.04, 95% CI 1.00-4.17; Pinteraction=0.06) or lethal disease (OR=2.37, 95% CI 1.19-4.72; Pinteraction=0.01) were stronger in men with a family history of the disease compared with those without. The minor allele of SNP, rs7726159, which has previously been shown to be positively associated with LTL, showed an inverse association with all prostate cancer risk after correction for multiple testing (P=0.0005). CONCLUSION: In this prospective study, longer LTL was modestly associated with higher risk of prostate cancer. A stronger association for more aggressive cancer in men with a family history of the disease needs to be confirmed in larger studies.


Asunto(s)
Leucocitos/metabolismo , Neoplasias de la Próstata/genética , Telómero , Adulto , Anciano , Estudios de Casos y Controles , Predisposición Genética a la Enfermedad , Humanos , Masculino , Persona de Mediana Edad , Invasividad Neoplásica , Polimorfismo de Nucleótido Simple , Neoplasias de la Próstata/mortalidad , Neoplasias de la Próstata/patología , Factores de Riesgo , Homeostasis del Telómero/genética
3.
Andrology ; 1(6): 919-28, 2013 Nov.
Artículo en Inglés | MEDLINE | ID: mdl-24124163

RESUMEN

Sex steroid hormones and inflammatory biomarkers are both associated with the development and progression of chronic diseases, but their interrelationship is relatively uncharacterized. We examined the association of sex hormones and sex hormone-binding globulin (SHBG) with biomarkers of inflammation, C-reactive protein (CRP) and white blood cell (WBC) count. The study included data from 809 adult men in the National Health and Nutrition Examination Survey 1999-2004. Geometric means and 95% confidence intervals were estimated separately for CRP and WBC concentrations by sex steroid hormones and SHBG using weighted linear regression models. Higher concentrations of total (slope per one quintile in concentration, -0.18; p-trend, 0.001) and calculated free (slope, -0.13; p-trend, 0.03) testosterone were statistically significantly associated with lower concentrations of CRP, but not with WBC count. Men in the bottom quintile of total testosterone (≤3.3 ng/mL), who might be considered to have clinically low testosterone, were more likely to have elevated CRP (≥3 mg/L) compared with men in the top four quintiles (OR, 1.61; 95% CI, 1.00-2.61). Total and calculated free estradiol (E2) were positively associated with both CRP (Total E2: slope, 0.14; p-trend, <0.001; Free E2: slope, 0.15; p-trend, <0.001) and WBC (Total E2: slope, 0.02; p-trend, 0.08; Free E2: slope, 0.02; p-trend, 0.02) concentrations. SHBG concentrations were inversely associated with WBC count (slope, -0.03; p-trend, 0.04), but not with CRP. These cross-sectional findings are consistent with the hypothesis that higher androgen and lower oestrogen concentrations may have an anti-inflammatory effect in men.


Asunto(s)
Biomarcadores/sangre , Proteína C-Reactiva/metabolismo , Estradiol/sangre , Testosterona/sangre , Adulto , Estudios Transversales , Hormonas Esteroides Gonadales/sangre , Humanos , Inflamación/fisiopatología , Trastornos Leucocíticos , Modelos Lineales , Masculino , Encuestas Nutricionales , Globulina de Unión a Hormona Sexual/metabolismo
4.
J Epidemiol Community Health ; 62(3): 202-8, 2008 Mar.
Artículo en Inglés | MEDLINE | ID: mdl-18272734

RESUMEN

INTRODUCTION: Growing evidence suggests the built environment impacts obesity within urban areas; however, little research has investigated these relationships across levels of urbanisation in diverse and representative populations. This study aimed to determine whether personal and neighbourhood barriers differ by the level of urbanisation and the relative importance of personal barriers, neighbourhood barriers and land-use development patterns measured by a county-level sprawl index. METHODS: Population-based, cross-sectional telephone survey data were collected on 1818 United States adults of diverse ethnicity and income level. Primary analyses were stratified by the level of urbanisation at the county level (large metropolitan, small metropolitan, non-metro, rural). Associations between obesity and neighbourhood and personal barriers were estimated with logistic regression, controlling for demographic variables. Within metropolitan areas, the association between body mass index (BMI) and county-level sprawl was estimated using hierarchical linear modelling, controlling for individual-level neighbourhood and personal barriers and demographic variables and then assessing cross-level interaction. RESULTS: The prevalence of neighbourhood, but not personal, barriers differed widely across levels of urbanisation. Specific neighbourhood (eg traffic, unattended dogs) and personal (eg time, injury) barriers differentially correlated with obesity across strata. The impact of sprawl on BMI (B = -0.005) was consistent with previous findings; standardised coefficients indicate that personal (beta = 0.10) and neighbourhood (beta = 0.05) barriers had a stronger association than sprawl (beta = -0.02). Furthermore, the effect of sprawl on BMI increased by -0.006 with each additional personal barrier. CONCLUSIONS: Future intervention planning and policy development should consider that personal barriers and built environment characteristics may interact with each other and influence obesity differently across urbanisation levels.


Asunto(s)
Obesidad/epidemiología , Características de la Residencia/estadística & datos numéricos , Salud Urbana/estadística & datos numéricos , Adolescente , Adulto , Anciano , Índice de Masa Corporal , Planificación Ambiental , Femenino , Conductas Relacionadas con la Salud , Encuestas Epidemiológicas , Humanos , Masculino , Persona de Mediana Edad , Obesidad/etiología , Factores de Riesgo , Estados Unidos/epidemiología
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