Abstract Rationale Snoring is common among adults and may impair partneŕs sleep quality. The occurrence of snoring may be influenced by anthropometric and ambient factors, but their individual contributions remain unclear. This study investigated the impact of atmospheric conditions and clinical factors on snoring. We hypothesized that lower temperature and relative humidity(RH), and higher air pollution, obesity, alcohol ingestion, and nasal congestion are independently associated with increased snoring duration. Methods We analyzed snoring data derived from a smartphone-based home sleep apnea test (Biologix Sleep Test®, Biologix Sistemas) between January 2022 and August 2025 in the state of São Paulo, Brazil. Only studies of subjects without OSA treatment that were performed in cities with available air-quality monitoring data were included. The primary outcome was snoring time (ST(%) = (total snoring duration/total recording time)×100). Snoring duration from each test was linked to local temperature, RH, air pollution (PM10,PM2.5,CO,NO2,O3) of the study date, with up to 30-day lags. Seasonality was assessed using cosinor models for ST (%) and atmospheric variables. Significance of the circannual component was confirmed by the p-value of the combined sine-cosine terms. Associations were further examined through lagged univariate and multivariate regressions adjusted for clinical covariates, including age, sex, body-mass index, and self-reported nasal congestion. Regression coefficients (β) indicate the change in ST(%) per unit change in each predictor. Seasonal effect sizes (ΔST) were estimated as β × 2×the amplitude from the cosinor model. A final model was built combining all atmospheric and clinical predictors, excluding variables with VIF2.5. Results Data from 56,855 subjects were analyzed. Median ST(%) was 18.6(3.1-48.8)%. Cosinor analysis confirmed circannual variation (mesor=27.8%;amplitude=4.3%;p0.001) peaking in June (winter) and decreasing in December (summer). Univariate linear regression showed that temperature was the strongest predictor (lag 0;β=-0.77), with its seasonal swing (5.8 °C) predicting a 4.5% decrease in ST(%). O3 (lag 1;β=-0.11;ΔST=-2.0%) and RH (lag 6;β=-0.05;ΔST=-0.6%) showed an inverse association, while PM10 (lag 10;β=0,04), PM2.5(lag 9;β=0.07), CO (lag 9;β=2.15), and NO2 (lag 10;β=0.02) were positively associated (ΔST∼0.5-1%). After adjusting for clinical covariates, all those associations remained significant, with temperature remaining the dominant independent predictor (β=-0.85;p0.001). In the final models, temperature(β=-0.48;ΔST=-2.8%), O3(β=-0.06;ΔST=-1.1%), and PM10(β = 0.03;ΔST = +0.8%) remained significant, while alcohol use was the strongest clinical covariate (β = 1.99;ΔST = +2%). Conclusions Snoring exhibited a significant seasonal pattern. Atmospheric conditions including lower temperature and humidity and air pollution and alcohol ingestion contributed independently to snoring time. These findings highlight the influence of environmental and clinical factors on snoring variability. This abstract is funded by: Presenting author
Strutz et al. (Fri,) studied this question.