Investigating the seasonality pattern of ultrasound requests and its association with photoperiod: A cross-sectional retrospective study

Seasonal variations in healthcare utilization, particularly in medical imaging services such as ultrasound (US), are gaining interest because of their potential links with environmental factors such as photoperiod. Although previous research has documented seasonal changes in healthcare activities, the seasonality of imaging requests remains underexplored, which could impact resource planning. This study aimed to investigate the seasonal patterns of US requests and their association with the photoperiod. We analyzed a 3-year dataset of 20,142 US requests from Samtah General Hospital in Jazan. The photoperiod, defined as daily daylight hours, was calculated using the "season" package in R based on the coordinates of the hospital. Statistical analyses included Cox generalized linear regression to assess seasonality, multinomial regression to explore the relationship between US requests and photoperiod, and binomial logistic regression to evaluate the association between order priority and photoperiod. Significant seasonality was noted for all US requests, peaking in August and November. The subtypes varied in seasonal amplitudes, with abdominal and pelvic scans exhibiting the highest fluctuations. A positive correlation was identified between the photoperiod and the 3D US scan subtype. Additionally, the US order priority showed seasonal patterns, with routine cases peaking in December and urgent cases in September. This study highlights the seasonality of ultrasound requests and their correlation with the photoperiod in the Jazan region. Understanding these patterns is essential for effective health care planning and resource allocation. Future research should integrate more contextual factors to clarify the relationship between seasonality and diagnostic practices, optimize healthcare services, and improve patient outcomes in Jazan.