Noncancerous Genitourinary Conditions as a Public Health Priority: Conceptualizing the Hidden Burden

OBJECTIVE

To provide a conceptual framework to guide investigations into burdens of noncancerous genitourinary conditions (NCGUCs), which are extensive and poorly understood.

METHODS

The National Institute of Diabetes and Digestive and Kidney Diseases convened a workshop of diverse, interdisciplinary researchers and health professionals to identify known and hidden burdens of NCGUCs that must be measured to estimate the comprehensive burden. Following the meeting, a subgroup of attendees (authors of this article) continued to meet to conceptualize burden.

RESULTS

The Hidden Burden of Noncancerous Genitourinary Conditions Framework includes impacts across multiple levels of well-being and social ecology, including individual (ie, biologic factors, lived experience, behaviors), interpersonal (eg, romantic partners, family members), organizational/institutional (eg, schools, workplaces), community (eg, public restroom infrastructure), societal (eg, health care and insurance systems, national workforce/economic output), and ecosystem (eg, landfill waste) effects. The framework acknowledges that NCGUCs can be a manifestation of underlying biological dysfunction, while also leading to biological impacts (generation and exacerbation of health conditions, treatment side effects).

CONCLUSION

NCGUCs confer a large, poorly understood burden to individuals and society. An evidence-base to describe the comprehensive burden is needed. Measurement of NCGUC burdens should incorporate multiple levels of well-being and social ecology, a life course perspective, and potential interactions between NCGUCs and genetics, sex, race, and gender. This approach would elucidate accumulated impacts and potential health inequities in experienced burdens. Uncovering the hidden burden of NCGUCs may draw attention and resources (eg, new research and improved treatments) to this important domain of health.

The Inflection Point Model: a Model to Explore the Hidden Burdens of Non-Cancerous Genitourinary Conditions

OBJECTIVE

To propose a conceptual model to identify points along the condition course where actions or inaction affect downstream burdens of non-cancerous genitourinary conditions (NCGUC).

MATERIALS AND METHODS

The National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) convened an interdisciplinary meeting to comprehensively consider the burdens of NCGUCs. Subsequently, the authors met monthly to conceptualize the model.

RESULTS

Inflection points (IP) describe time points during a condition course that are sensitive to change. Our proposed Inflection Point Model (IPM) helps conceptualize burden/benefit trade-offs in any related decision and provides a platform to identify the downstream aggregate burden of a NCGUC across multiple socio-ecological levels at a single time point, which may be summed across the condition course to measure cumulative burden. Two personae demonstrate the utility of this model to better understand impacts of two common NCGUCs.

CONCLUSIONS

The IPM may be applied in multiple contexts: narrowly to explore burden of a single NCGUC at a single IP; or more broadly, to address multiple conditions, multiple IPs, or multiple domains/levels of social ecology. Applying the IPM may entail combining population data describing prevalence of NCGUCs, associated behaviors, and resulting outcome patterns that can be combined with suitable mathematical models to quantify aggregate and cumulative burden. The IPM challenges stakeholders to expand from the individual to include broader levels of social ecology. Application of the IPM will undoubtedly identify data gaps and research needs that must be fulfilled to delineate and address the burden of NCGUCs.

Defining the relationship between vaginal and urinary microbiomes

BACKGROUND

Although the vaginal and urinary microbiomes have been increasingly well-characterized in health and disease, few have described the relationship between these neighboring environments. Elucidating this relationship has implications for understanding how manipulation of the vaginal microbiome may affect the urinary microbiome and treatment of common urinary conditions.

OBJECTIVE

To describe the relationship between urinary and vaginal microbiomes using 16S rRNA gene sequencing. We hypothesized that the composition of the urinary and vaginal microbiomes would be significantly associated, with similarities in predominant taxa.

STUDY DESIGN

This multicenter study collected vaginal swabs and catheterized urine samples from 186 women with mixed urinary incontinence enrolled in a parent study and 84 similarly aged controls. Investigators decided a priori that if vaginal and/or urinary microbiomes differed between continent and incontinent women, the groups would be analyzed separately; if similar, samples from continent and incontinent women would be pooled and analyzed together. A central laboratory sequenced variable regions 1-3 (v1-3) and characterized bacteria to the genus level. Operational taxonomic unit abundance was described for paired vaginal and urine samples. Pearson's correlation characterized the relationship between individual operational taxonomic units of paired samples. Canonical correlation analysis evaluated the association between clinical variables (including mixed urinary incontinence and control status) and vaginal and urinary operational taxonomic units, using the Canonical correlation analysis function in the Vegan package (R version 3.5). Linear discriminant analysis effect size was used to find taxa that discriminated between vaginal and urinary samples.

RESULTS

Urinary and vaginal samples were collected from 212 women (mean age 53±11 years) and results from 197 paired samples were available for analysis. As operational taxonomic units in mixed urinary incontinence and control samples were related in canonical correlation analysis and since taxa did not discriminate between mixed urinary incontinence or controls in either vagina or urine, mixed urinary incontinence and control samples were pooled for further analysis. Canonical correlation analysis of vaginal and urinary samples indicated that that 60 of the 100 most abundant operational taxonomic units in the samples largely overlapped. Lactobacillus was the most abundant genus in both urine and vagina (contributing on average 53% to an individual's urine sample and 64% to an individual's vaginal sample) (Pearson correlation r=0.53). Although less abundant than Lactobacillus, other bacteria with high Pearson correlation coefficients also commonly found in vagina and urine included: Gardnerella (r=0.70), Prevotella (r=0.64), and Ureaplasma (r=0.50). Linear discriminant analysis effect size analysis identified Tepidimonas and Flavobacterium as bacteria that distinguished the urinary environment for both mixed urinary incontinence and controls as these bacteria were absent in the vagina (Tepidimonas effect size 2.38, P<.001, Flavobacterium effect size 2.15, P<.001). Although Lactobacillus was the most abundant bacteria in both urine and vagina, it was more abundant in the vagina (linear discriminant analysis effect size effect size 2.72, P<.001).

CONCLUSION

Significant associations between vaginal and urinary microbiomes were demonstrated, with Lactobacillus being predominant in both urine and vagina. Abundance of other bacteria also correlated highly between the vagina and urine. This inter-relatedness has implications for studying manipulation of the urogenital microbiome in treating conditions such as urgency urinary incontinence and urinary tract infections.