Long-term temporal trends and seasonal variations in Bell's Palsy and severity: an STL time-series approach

Bell's palsy is the most common form of acute peripheral facial palsy; however, its etiology remains unclear. Environmental and seasonal factors have been suggested as potential triggers, but previous studies have reported conflicting results. The aim of this study was to evaluate the long-term temporal and seasonal patterns of Bell's palsy using a 10-year dataset and seasonal-trend decomposition using locally estimated scatterplot smoothing time-series analysis.

This retrospective study analyzed data of patients with Bell's palsy who presented between 2015 and 2024. Bell's palsy severity according to the House-Brackmann scale and presentation dates were assessed by month, season, and year. Chi-Square tests and seasonal-trend decomposition using locally estimated scatterplot smoothing time-series analysis were used to assess temporal and seasonal patterns.

A total of 352 patients were included in the study (53.9% male; mean age, 46.5 ± 18.3 years). The highest frequency of presentations occurred in October, whereas the lowest occurred in February, with no significant monthly or seasonal differences (p > 0.05). Seasonal-trend decomposition suggested small recurring fluctuations, with a modest increase in March compared with February, and persistence through April and May. Paralysis severity showed no temporal variation.

In this single-center clinic-based study, Bell's palsy presentations showed no statistically significant monthly, seasonal, or annual variation, and severity was not associated with temporal categories. Seasonal-trend decomposition using locally estimated scatterplot smoothing time-series analysis suggested only minor recurrent fluctuations. Because direct meteorological and environmental exposure data were not analyzed, these findings should be interpreted as descriptive temporal presentation patterns rather than evidence supporting or refuting specific environmental triggers.