Search Results
Sleep apnea-hypopnea quantification by cardiovascular data analysis
2014, Camargo, S., Riedl, M., Anteneodo, C., Kurths, J., Penzel, T., Wessel, N.
Sleep disorders are a major risk factor for cardiovascular diseases. Sleep apnea is the most common sleep disturbance and its detection relies on a polysomnography, i.e., a combination of several medical examinations performed during a monitored sleep night. In order to detect occurrences of sleep apnea without the need of combined recordings, we focus our efforts on extracting a quantifier related to the events of sleep apnea from a cardiovascular time series, namely systolic blood pressure (SBP). Physiologic time series are generally highly nonstationary and entrap the application of conventional tools that require a stationary condition. In our study, data nonstationarities are uncovered by a segmentation procedure which splits the signal into stationary patches, providing local quantities such as mean and variance of the SBP signal in each stationary patch, as well as its duration L. We analysed the data of 26 apneic diagnosed individuals, divided into hypertensive and normotensive groups, and compared the results with those of a control group. From the segmentation procedure, we identified that the average duration 〈L〉, as well as the average variance 〈σ2〉, are correlated to the apnea-hypoapnea index (AHI), previously obtained by polysomnographic exams. Moreover, our results unveil an oscillatory pattern in apneic subjects, whose amplitude S∗ is also correlated with AHI. All these quantities allow to separate apneic individuals, with an accuracy of at least 79%. Therefore, they provide alternative criteria to detect sleep apnea based on a single time series, the systolic blood pressure.
Global, regional, and national burden of mortality associated with non-optimal ambient temperatures from 2000 to 2019: a three-stage modelling study
2021, Zhao, Qi, Guo, Yuming, Ye, Tingting, Gasparrini, Antonio, Tong, Shilu, Overcenco, Ala, Urban, Aleš, Schneider, Alexandra, Entezari, Alireza, Vicedo-Cabrera, Ana Maria, Zanobetti, Antonella, Analitis, Antonis, Zeka, Ariana, Tobias, Aurelio, Nunes, Baltazar, Alahmad, Barrak, Armstrong, Ben, Forsberg, Bertil, Pan, Shih-Chun, Íñiguez, Carmen, Ameling, Caroline, De la Cruz Valencia, César, Åström, Christofer, Houthuijs, Danny, Dung, Do Van, Royé, Dominic, Indermitte, Ene, Lavigne, Eric, Mayvaneh, Fatemeh, Acquaotta, Fiorella, de'Donato, Francesca, Di Ruscio, Francesco, Sera, Francesco, Carrasco-Escobar, Gabriel, Kan, Haidong, Orru, Hans, Kim, Ho, Holobaca, Iulian-Horia, Kyselý, Jan, Madureira, Joana, Schwartz, Joel, Jaakkola, Jouni J. K., Katsouyanni, Klea, Hurtado Diaz, Magali, Ragettli, Martina S., Hashizume, Masahiro, Pascal, Mathilde, de Sousa Zanotti Stagliorio Coélho, Micheline, Valdés Ortega, Nicolás, Ryti, Niilo, Scovronick, Noah, Michelozzi, Paola, Matus Correa, Patricia, Goodman, Patrick, Nascimento Saldiva, Paulo Hilario, Abrutzky, Rosana, Osorio, Samuel, Rao, Shilpa, Fratianni, Simona, Dang, Tran Ngoc, Colistro, Valentina, Huber, Veronika, Lee, Whanhee, Seposo, Xerxes, Honda, Yasushi, Guo, Yue Leon, Bell, Michelle L., Li, Shanshan
Background: Exposure to cold or hot temperatures is associated with premature deaths. We aimed to evaluate the global, regional, and national mortality burden associated with non-optimal ambient temperatures. Methods: In this modelling study, we collected time-series data on mortality and ambient temperatures from 750 locations in 43 countries and five meta-predictors at a grid size of 0·5° × 0·5° across the globe. A three-stage analysis strategy was used. First, the temperature–mortality association was fitted for each location by use of a time-series regression. Second, a multivariate meta-regression model was built between location-specific estimates and meta-predictors. Finally, the grid-specific temperature–mortality association between 2000 and 2019 was predicted by use of the fitted meta-regression and the grid-specific meta-predictors. Excess deaths due to non-optimal temperatures, the ratio between annual excess deaths and all deaths of a year (the excess death ratio), and the death rate per 100 000 residents were then calculated for each grid across the world. Grids were divided according to regional groupings of the UN Statistics Division. Findings: Globally, 5 083 173 deaths (95% empirical CI [eCI] 4 087 967–5 965 520) were associated with non-optimal temperatures per year, accounting for 9·43% (95% eCI 7·58–11·07) of all deaths (8·52% [6·19–10·47] were cold-related and 0·91% [0·56–1·36] were heat-related). There were 74 temperature-related excess deaths per 100 000 residents (95% eCI 60–87). The mortality burden varied geographically. Of all excess deaths, 2 617 322 (51·49%) occurred in Asia. Eastern Europe had the highest heat-related excess death rate and Sub-Saharan Africa had the highest cold-related excess death rate. From 2000–03 to 2016–19, the global cold-related excess death ratio changed by −0·51 percentage points (95% eCI −0·61 to −0·42) and the global heat-related excess death ratio increased by 0·21 percentage points (0·13–0·31), leading to a net reduction in the overall ratio. The largest decline in overall excess death ratio occurred in South-eastern Asia, whereas excess death ratio fluctuated in Southern Asia and Europe. Interpretation: Non-optimal temperatures are associated with a substantial mortality burden, which varies spatiotemporally. Our findings will benefit international, national, and local communities in developing preparedness and prevention strategies to reduce weather-related impacts immediately and under climate change scenarios. Funding: Australian Research Council and the Australian National Health and Medical Research Council. © 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license
Short term associations of ambient nitrogen dioxide with daily total, cardiovascular, and respiratory mortality: multilocation analysis in 398 cities
2021, Meng, Xia, Liu, Cong, Chen, Renjie, Sera, Francesco, Vicedo-Cabrera, Ana Maria, Milojevic, Ai, Guo, Yuming, Tong, Shilu, Coelho, Micheline de Sousa Zanotti Stagliorio, Saldiva, Paulo Hilario Nascimento, Lavigne, Eric, Correa, Patricia Matus, Ortega, Nicolas Valdes, Osorio, Samuel, Garcia, null, Kyselý, Jan, Urban, Aleš, Orru, Hans, Maasikmets, Marek, Jaakkola, Jouni J. K., Ryti, Niilo, Huber, Veronika, Schneider, Alexandra, Katsouyanni, Klea, Analitis, Antonis, Hashizume, Masahiro, Honda, Yasushi, Ng, Chris Fook Sheng, Nunes, Baltazar, Teixeira, João Paulo, Holobaca, Iulian Horia, Fratianni, Simona, Kim, Ho, Tobias, Aurelio, Íñiguez, Carmen, Forsberg, Bertil, Åström, Christofer, Ragettli, Martina S., Guo, Yue-Liang Leon, Pan, Shih-Chun, Li, Shanshan, Bell, Michelle L., Zanobetti, Antonella, Schwartz, Joel, Wu, Tangchun, Gasparrini, Antonio, Kan, Haidong
Objective To evaluate the short term associations between nitrogen dioxide (NO2) and total, cardiovascular, and respiratory mortality across multiple countries/regions worldwide, using a uniform analytical protocol. Design Two stage, time series approach, with overdispersed generalised linear models and multilevel meta-analysis. Setting 398 cities in 22 low to high income countries/regions. Main outcome measures Daily deaths from total (62.8 million), cardiovascular (19.7 million), and respiratory (5.5 million) causes between 1973 and 2018. Results On average, a 10 μg/m3 increase in NO2 concentration on lag 1 day (previous day) was associated with 0.46% (95% confidence interval 0.36% to 0.57%), 0.37% (0.22% to 0.51%), and 0.47% (0.21% to 0.72%) increases in total, cardiovascular, and respiratory mortality, respectively. These associations remained robust after adjusting for co-pollutants (particulate matter with aerodynamic diameter ≤10 μm or ≤2.5 μm (PM10 and PM2.5, respectively), ozone, sulfur dioxide, and carbon monoxide). The pooled concentration-response curves for all three causes were almost linear without discernible thresholds. The proportion of deaths attributable to NO2 concentration above the counterfactual zero level was 1.23% (95% confidence interval 0.96% to 1.51%) across the 398 cities. Conclusions This multilocation study provides key evidence on the independent and linear associations between short term exposure to NO2 and increased risk of total, cardiovascular, and respiratory mortality, suggesting that health benefits would be achieved by tightening the guidelines and regulatory limits of NO2.