Britton Trabert

Importance: Prescription medication use in the United States has increased over recent decades, with women consistently reporting higher use than men. However, limited research has examined use patterns among women, particularly those 40 years and older who face elevated risks for chronic disease. Objective: To assess prescription medication use among U.S. women 40 years and older. Design/Setting: Cross-sectional analysis of National Health and Nutrition Examination Survey (NHANES) data from 10 survey cycles spanning 1999–2020. Participants: A total of 18,686 women aged 40 years and older with complete prescription medication information. Exposure: Calendar year modeled as NHANES cycles. Main Outcome(s) and Measure(s): Prescription medication use in the past 30 days, overall and by therapeutic class, was estimated for each NHANES cycle. Joinpoint regression estimated average annual percent change (APC). Logistic regression assessed associations between covariates and medication use and polypharmacy (≥5 medications). Results: Polypharmacy among female participants rose from 17.9% in 1999–2000 to 26.0% in 2017–2020, demonstrating an increasing trend early (1999–2004 APC: 7.4, [95%CI: 1.9, 13.6]) followed by stable use (2004–2020 APC: 0.8 [−2.7, 1.9]). Increases in polypharmacy use occurred across racial and ethnic groups and were greatest among women aged 70–85 years. Cardiovascular (1999–2020 APC: 0.9 [0.4, 1.4]) and metabolic (1999–2006 APC: 7.9 [4.1, 15.8]) agent use increased across survey cycles while hormones/hormone modifier use declined (1999–2008 APC: −6.0 [−14.0, −1.3]). Conclusions and Relevance: Polypharmacy use increased among women 40 years and older, with notable shifts across therapeutic classes. These trends highlight the need for continued surveillance of medication patterns within this population.

Objective: To characterize associations between tattooing and health status. Methods: We used data from ∼27,000 respondents to the 2020–2022 Utah Behavioral Risk Factor Surveillance System (BRFSS). Multivariable Poisson regression was used to calculate prevalence ratios (PR) and 95% confidence intervals (CI) associating ever receiving a tattoo with physical/mental health status. Results: In this cross-sectional study, ever receiving a tattoo was associated with self-reported “poorer” vs. “excellent” overall health, particularly among women (PR=3.08 [95% CI: 2.26– 4.21]). Tattooing was also associated with obesity (women, PR=1.40 [95% CI: 1.22–1.61]; men, PR=1.21 [95% CI: 1.04–1.40]) and chronic pain (women, PR=1.59 [95% CI: 1.43–1.77]; men, PR=1.55 [95% CI: 1.37–1.76]). Tattooed individuals were more likely to have been diagnosed with a depressive disorder (women, PR=1.64 [95% CI: 1.53–1.75]; men, PR=1.55 [95% CI: 1.39–1.73]) and to have had six or more teeth removed, vs. none (women, PR=2.18 [95% CI: 1.61–2.96]; men, PR=2.88 [95% CI: 2.10–3.95]). Conclusions: Public health entities may consider partnering with tattoo studios and conventions to provide information about nutrition, exercise, dental care, mental health resources, and health screenings.

To understand how sample collection affects oral microbiome studies, we evaluated the comparability of unpreserved saliva, saliva in glycerol, and mouthwash samples, their room temperature stability, and intraindividual stability over 6 months. Saliva and mouthwash samples were collected from 20 healthy participants 6 months apart. Saliva was divided, with half preserved in glycerol. Some aliquots were frozen immediately, while others were stored at room temperature for a week. DNA was extracted using the PowerSoil Pro and 16S rRNA gene, and shotgun metagenomic sequencing was conducted. Intraclass correlation coefficients (ICCs) from taxonomic and functional tables were compared to assess variability. We estimated sample size requirements based on the intraindividual stability over 6 months. Saliva in glycerol appeared more similar to unpreserved saliva than mouthwash, with higher median ICCs at genus (0.88 vs 0.60), species (0.92 vs 0.64), and gene levels (0.84 vs 0.36; all P < 0.01). Room temperature storage affected saliva in glycerol more than mouthwash (median genus-level ICC = 0.65). No significant differences were observed at the gene level. Intraindividual stability over 6 months was moderate. To detect an odds ratio of 1.5 with one sample per individual, estimated sample sizes ranged from 665 (common species) to 219,547 (rare species). Oral microbiome stability varies by collection method; mouthwash provides greater room temperature stability and may be preferable when immediate freezing is not feasible. For epidemiological studies, consistent use of a single collection method and inclusion of longitudinal sampling can improve reproducibility and power to detect associations with health outcomes. IMPORTANCE: The oral microbiome plays a key role in health and disease, yet methodological inconsistencies in sample collection and processing can introduce variability and limit comparability across studies. This study investigates the impact of different oral sample collection methods on microbiome profiling and their stability over time. We demonstrate that sample type significantly influences taxonomic and functional microbiome profiles, with mouthwash showing greater stability during delayed processing and saliva in glycerol more closely resembling fresh saliva. Importantly, intraindividual microbial communities were only moderately stable over 6 months, emphasizing the need for consistent sampling protocols and consideration of temporal variation. These findings have direct implications for microbiome study design, highlighting that methodological choices can affect reproducibility, statistical power, and biological interpretation. Our results support the use of mouthwash as a practical alternative when freezing is delayed and underscore the value of longitudinal sampling for detecting biologically meaningful changes.

Background: Testicular germ cell tumors (TGCTs) are thought to be endocrine related, but the hypothesis has not been thoroughly investigated. As a result, prediagnostic serum samples from the US Servicemen’s Testicular Tumor Environmental and Endocrine Determinants study were analyzed to assess the relationship between hormones and gonadotropins to TGCT risk. Methods: The study included 517 men who subsequently developed a TGCT and 790 comparison men. The hormones and gonadotropins examined included testosterone; estradiol; sex hormone–binding globulin; 5α-androstane-3α,17β-diol glucuronide (3α-diol G); follicle-stimulating hormone (FSH); and luteinizing hormone (LH). Adjusted odds ratios (ORs) and 95% CIs were estimated using logistic regression. Analyses stratified by histology (seminoma, nonseminoma) were also conducted. Results: Compared with men in the middle quintile of LH concentrations, men with the lowest LH concentrations had an increased risk of TGCT (OR = 1.88, 95% CI = 1.31 to 2.70), as did men with FSH concentrations in the lowest (OR = 1.77, 95% CI = 1.21 to 2.60) and highest quintiles (OR = 2.20, 95% CI = 1.53 to 3.17). An increased risk of seminoma was found with both low and high LH and high FSH levels, whereas an increased risk of nonseminoma was found with low LH levels and both low and high FSH levels. Decreased levels of 3α-diol G were associated with increased risk of seminoma (OR = 1.65, 95% CI = 1.02 to 2.67). Conclusion: These results suggest that gonadotropin disruption may be a critical event in the development of TGCTs. Further examination of upstream and downstream metabolites in the hormone pathways may help elucidate the underlying mechanism that distinguishes men who develop TGCTs from men who do not.

Background:Prolonged sitting and physical inactivity are associated with higher circulating levels of estrogens. It is unknown whether these risk factors are associated with circulating androgens/androgen metabolites, another set of hormones implicated in the etiology of cancers in postmenopausal women.Methods:We conducted a cross-sectional analysis of 1,782 postmenopausal women in the Women's Health Initiative Observational Study. Serum concentrations of 12 androgens/androgen metabolites were quantified using liquid chromatography-tandem mass spectrometry. Physical activity and sitting time were self-reported at baseline. We performed linear regression to estimate geometric means (GM) of androgen/androgen metabolite concentrations (pmol/L) according to physical activity and sitting time, adjusting for potential confounders and stratified by menopausal hormone therapy (MHT) use.Results:Physical activity (≥15 vs. 0 MET-h/wk) was inversely associated with estrogen-to-androgen ratios among never/former MHT users (adj-GM = 37.5 vs. 49.6 unconjugated estrone:androstenedione; 20.2 vs. 30.3 unconjugated estradiol:testosterone; all Ptrend ≤ 0.03) but was not associated among current MHT users. Prolonged sitting (≥10 vs. ≤5 h/d) was positively associated with these ratios among both never/former (adj-GM = 44.2 vs. 38.3, Ptrend = 0.10; adj-GM = 23.4 vs. 20.2, Ptrend = 0.17; respectively) and current MHT users (adj-GM = 197 vs. 147; 105 vs. 75.5; respectively; all Ptrend ≤0.02), but the associations were statistically significant among current MHT users only. The associations persisted after adjustment for BMI. After adjustment for adrenal androgens, physical activity and sitting were not associated with androgen metabolites.Conclusions:Physical activity and sitting were associated with serum estrogen-to-androgen ratios but not androgen metabolites.Impact:This study contributes to our understanding of the link between physical activity, sitting, and cancer risk in postmenopausal women.

Supplementary Table 1 shows population characteristics among current MHT users; Supplementary Table 2 shows relative proportions of adrenal androgens and estrogens; Supplementary Table 3-6 show the associations with adjustment for waist-to-hip ratio; Supplementary Table 7-10 show the associations stratified by current BMI

Hazard ratios (HR) and 95% confidence intervals (95%CI) of kidney related markers measured in urine and ovarian cancer risk by histological subtype in the UK Biobank.

Hazard ratios (HR) and 95% confidence intervals (95%CI) of kidney related markers measured in blood and ovarian cancer risk by C Reactive Protein (CRP) in the UK Biobank.