Large datasets for investigating vaginal flora change at frequent, repeated intervals are limited and graphical methods for exploring such data are inadequate. We report 2-year weekly vaginal flora changes based on Gram stain using lasagna plots.
Weekly vaginal flora patterns were evaluated among 211 sexually experienced women with ≥18 months of follow-up in Rakai, Uganda. Vaginal flora swabs were self-collected weekly and categorized by Nugent Gram stain criteria (0–3, normal; 4–6, intermediate; 7–10, bacterial vaginosis [BV]). Vaginal flora patterns were analyzed as the percentage of weekly observations with BV (longitudinal prevalence) and illustrated by lasagna plots. Characteristics of women were compared across tertiles of longitudinal prevalence of BV.
Ninety-five percent of women had at least 1 episode of BV over 2 years, with one-third of women spending more than half (52%–100%) of their time with BV. Vaginal pH >4.5 increased with increasing tertiles of longitudinal prevalence of BV (P < 0.001). Weekly fluctuation in vaginal flora states, as measured by a change in flora states from the before current visit, was highest in the middle (41.9%) compared with the lower (30.1%) and upper tertiles (27.8%, P < 0.001). HIV status and reported vaginal symptoms did not differ significantly across BV tertiles.
Women exhibited different patterns of vaginal flora changes over time, which could not be described by baseline behaviors. Lasagna plots aided in describing the natural history of BV within and across women and may be applied to future BV natural history studies.
Few factors differed between women with higher versus lower frequencies of bacterial vaginosis. Lasagna plots facilitated the visualization and interpretation of weekly vaginal flora patterns from a large sample of women.
From the *Department of Population, Family, and Reproductive Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; †Epidemiology Branch, Division of Epidemiology, Statistics, and Prevention Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Rockville, MD; ‡Makerere University School of Public Health, Kampala, Uganda; §Rakai Health Sciences Program, Kalisizo, Uganda; ¶Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; and ∥Makerere University College of Health Sciences, Kampala, Uganda
The authors thank Bruce Swihart for his feedback and assistance with lasagna plotting, including providing his program developed in R to generate the figures used in this paper.
Supported in part by the Intramural Research Program of the National Institutes of Health (NIH), Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), the NIH, NICHD grant R01AI47608 (to M.J.W.); the NIH, National Institute for Allergy and Infectious Diseases (NIAID) grant T32AI050056 (to J.M.Z.), the Cooperative Agreement number R36PS001104 (to M.E.T.) from the Center for Disease Control and Prevention (CDC).
Its contents are solely the responsibility of the authors and do not represent the official views of the CDC.
Correspondence: Marie Thoma, PhD, MHS, Epidemiology Branch/DESPR, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, 6100 Executive Blvd, Room 7B13E, Rockville, MD 20852. E-mail: firstname.lastname@example.org.
Received for publication February 14, 2011, and accepted June 1, 2011.