Climatic determinants of rheumatic and autoimmune musculoskeletal pain: a fourteen-year primary care time-series study.

Climatic variability has been proposed as a modulator of musculoskeletal and rheumatic pain; however, long-term population-based evidence examining healthcare utilization remains limited. To evaluate the association between climatic variables and primary care consultations for autoimmune and immune-mediated musculoskeletal pain over a fourteen-year period, and to explore potential modification by sex and diagnostic category. A retrospective ecological time-series study was conducted using electronic health records from three primary care centers in the Community of Madrid (Spain) between January 2010 and December 2023. The weekly consultation counts for fibromyalgia, myalgia, and combined autoimmune pain processes were analyzed. Meteorological data were obtained from the Spanish State Meteorological Agency (AEMET). Associations were assessed using Time Series Generalized Linear Models (TSGLM) with a negative binomial distribution, adjusting for autocorrelation, seasonality, age, and the COVID-19 period. Effects were expressed as Incidence Rate Ratios (IRR) with Holm-Bonferroni correction. Across 728 weeks, we recorded 6715 primary care consultations related to autoimmune pain processes (mean 9.23 consultations/week, 62.07% female). Myalgia accounted for 94.83% of the consultations. Clinically relevant biometeorological trends were identified across several stratified models, particularly for diurnal temperature range and barometric pressure. No significant climatic effects were observed in the aggregated models. No significant climatic effects were observed in the aggregated models. Forecasting analyses suggest the stabilization of consultation volumes over the next four years. Climatic influences on primary care consultations for autoimmune musculoskeletal pain were statistically detectable, but modest and heterogeneous. Intra-daily temperature variability appears to be more relevant than absolute temperature values. These findings underscore the complexity of the climate-pain relationship and the importance of stratified time-series modeling in biometeorological research.