Correlations between geomagnetic field and global occurrence of cardiovascular diseases: evidence from 204 territories in different latitude.

BACKGROUND: The correlation between stable geomagnetic fields and unstable geomagnetic activities with mortality, incidence, and prevalence of cardiovascular diseases (CVDs) remains ambiguous. METHOD: To investigate the correlations between geomagnetic field (GMF) intensity and geomagnetic disturbance (GMD) and CVDs events in global, long-period scale, global and 204 countries and territories were included on the base of 2019 Global Burden of Disease study (GBD 2019). Data of GMF intensity, GMD frequency, CVDs events, weather and health economic indicators from 1996 to 2019 of included locations were collected. Linear regression and panel data modelling were conducted to identify the correlations between GMF intensity and CVDs events, multi-factor panel data analysis was also generated to adjust the effect of confounding factors. RESULTS: For the average data during 1996-2019, linear regression model revealed consistent positive correlations between total GMF (tGMF) intensity and mortality of total CVDs [coef = 0.009, (0.006,0.011 95%CI)], whereas negative correlations were found between horizonal GMF (hGMF) intensity and total CVD mortality [coef = -0.010 (-0.013, -0.007 95%CI)]. When considering the time trend, panel data analysis still demonstrated positive correlation between tGMF and total CVDs mortality [coef = 0.009, (0.008,0.009 95%CI)]. Concurrently, the hGMF negatively correlated with total CVDs mortality [coef = -0.008, (-0.009, -0.007 95%CI)]. When the panel models were adjusted for confounding factors, no reverse of correlation tendency was found between tGMF, hGMF and CVDs events. In high-income territories, positive correlation was found between geomagnetic storm (GMS) frequency and mortality of total CVDs [coef = 14.007,(2.785, 25.229 95%CI)], however, this positive trend faded away gradually with the latitude decreasing from polar to equator. CONCLUSIONS: Stable and long-term horizontal component of GMF may be beneficial to cardiac health. Unstable and short-term GMF called GMD could be a hazard to cardiac health. Our results suggest the importance of regular GMF in maintaining cardio-health state and the adverse impacts of GMD on cardiac health.

Multidimensional assessment and cluster analysis for OSA phenotyping.

STUDY OBJECTIVES: Obstructive sleep apnea (OSA) is a heterogeneous disease with varying phenotype. A cluster analysis based on multidimensional disease characteristics, including symptoms, anthropometry, polysomnography, and craniofacial morphology, in combination with auto-continuous positive airway pressure titration response and comorbidity profiles, was conducted within a well-characterized cohort of patients with OSA, with the aim to refine the current phenotypic expressions of OSA with clinical implications. METHODS: Two hundred ninety-one patients with a new diagnosis of moderate to severe OSA referred for auto-continuous positive airway pressure titration to the sleep center were included for analysis. In-laboratory polysomnography and craniofacial computed tomography scanning were performed, followed by an auto-continuous positive airway pressure titration. The symptom of excessive daytime sleepiness was assessed using the Epworth Sleepiness Scale. RESULTS: Three patient phenotypes-normal weight, nonsleepy, moderate OSA; obese, nonsleepy, severe OSA; and obese, sleepy, very severe OSA with craniofacial limitation-were identified. Among the polysomnography parameters, only percentage of N3 time of total sleep time (N3%) and mean pulse oxygen saturation were found to be associated with the Epworth Sleepiness Scale score, and they only explained a small fraction of the variation (R2 = .136). Neck circumference and craniofacial limitation were associated with the more severe phenotype, which had a higher prevalence of hypertension and metabolic syndrome, greater diurnal blood gas abnormalities, and worse positive airway pressure titration response. CONCLUSIONS: Three OSA phenotypes were identified according to multiple aspects of clinical features in patients with moderate to severe OSA, who differed in their prevalence of hypertension, metabolic syndrome, diurnal blood gas parameters, and continuous positive airway pressure titration response. Self-reported excessive daytime sleepiness was not related with the severity of sleep breathing disturbance, and craniofacial limitation was associated with the more severe phenotype. These findings highlight the necessity of integrating multiple disease characteristics into phenotyping to achieve a better understanding of the clinical features of OSA. CITATION: Zhang XL, Zhang L, Li YM, et al. Multidimensional assessment and cluster analysis for OSA phenotyping. J Clin Sleep Med. 2022;18(7):1779-1788.