Hypothesis / aims of study
Limited qualitative and cross-sectional data suggest that cold weather and lesser sunlight worsen urologic chronic pelvic pain syndrome (UCPPS) symptoms and trigger UCPPS flares. However, no studies to date have tested this hypothesis prospectively. To address this gap, we linked publicly available weather data to our case-crossover study of UCPPS flare triggers in the Multidisciplinary Approach to the Study of Chronic Pelvic Pain Epidemiology and Phenotyping Study.
Study design, materials and methods
The MAPP Study was a one-year longitudinal study of UCPPS patients designed to study the “usual-care” natural history of UCPPS and to identify sub-groups of patients with possible differing etiology and clinical course. It included men with chronic prostatitis/chronic pelvic pain syndrome or interstitial cystitis/bladder pain syndrome and women with interstitial cystitis/bladder pain syndrome. Participants were followed biannually at in-person clinic visits and biweekly at online study assessments.
As part of an embedded case-crossover study of flare triggers, participants were asked whether they were currently “experiencing a flare of their urologic or pelvic pain symptoms […] meaning symptoms that are much worse than usual” at each biweekly online assessment. Those who replied affirmatively were asked an additional set of questions about their flare symptoms, flare start date, and exposures in the 3 days before their flare. These questions were asked for the first 3 flares and at 3 randomly selected times when participants did not report a flare. We linked these data to daily values of temperature, barometric pressure, relative humidity, and ultraviolet index (UVI) by participants’ 3-digit zip codes. Weather data were obtained from the National Oceanic and Atmospheric Administration and National Aeronautics and Space Administration Ozone Monitoring Instrument. Weather values in the 3 days before (day -1, day -2, and day -3) and the day of a flare (day 0), as well as daily changes in these values, were compared to corresponding non-flare values by conditional logistic regression. Time since the last high UVI (≥6) day was also analyzed. Differences in flare rates by astronomical season (winter, spring, summer, and fall) and season defined by vegetation index (to account for variations in climate across participating MAPP sites) were investigated in the full study population by Poisson regression. With a sample size of 290 case-crossover participants, we had at least 80% power to detect odds ratios (ORs) as small as 1.6 to 1.7, assuming 1:1 matching, a prevalence of exposure in controls of 20 to 30%, a correlation between observations from the same participant of 0.1 to 0.2, two-sided tests, and an α-level of 0.05.
573 flare and 792 non-flare observations (from 290 participants) were included in the analysis. Overall, no associations were observed for temperature, barometric pressure, relative humidity, or changes in these measures, in the 3 days before or the day of a flare and flare onset (Table 1). A suggestion of a protective association was observed for increases in UVI values in the 3 days before a flare, but none of these associations were statistically significant. Time since last high UVI day was not associated with flares. Finally, no differences in flare rates were observed by astronomical season: spring: OR=1.06 (95% confidence interval (CI): 0.91-1.24); summer: OR=1.04 (95% CI: 0.89-1.21); and fall: OR=1.05 (95% CI: 0.90-1.23) compared to winter; or by season defined by high vegetation index (OR=1.05 (95% CI: 0.92-1.20).
Interpretation of results
Overall, no associations were observed between weather and the onset or frequency of flares.