Forecasts of cardiac and respiratory mortality in Tehran, Iran, using ARIMAX and CNN-LSTM models

An important issue is that the respiratory mortality may be a result of air pollution which can be measured by the following variables: temperature, relative humidity, carbon monoxide, sulfur dioxide, nitrogen dioxide, hydrocarbons, ozone, and particulates. The usual way is to fit a model using the ordinary least squares regression, which has some assumptions, also known as Gauss-Markov assumptions, on the error term showing white noise process of the regression model. However, in many applications, especially for this example, these assumptions are not satisfied. Therefore, in this study, a quantile regression approach is used to model the respiratory mortality using the mentioned explanatory variables. Moreover, improved estimation techniques such as preliminary testing and shrinkage strategies are also obtained when the errors are autoregressive. A Monte Carlo simulation experiment, including the quantile penalty estimators such as lasso, ridge, and elastic net, is designed to evaluate the performances of the proposed techniques. Finally, the theoretical risks of the listed estimators are given.

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Mortality Sensitivity of Cardiovascular, Cerebrovascular, and Respiratory Diseases to Warm Season Climate in Japanese Cities

Atmosphere ◽

10.3390/atmos12121546 ◽

2021 ◽

Vol 12 (12) ◽

pp. 1546

Author(s):

Yukitaka Ohashi ◽

Akari Miyata ◽

Tomohiko Ihara

Keyword(s):

Myocardial Infarction ◽

Heart Failure ◽

Acute Myocardial Infarction ◽

Respiratory Diseases ◽

Heart Diseases ◽

Warm Season ◽

Respiratory Mortality ◽

Ischemic Heart Diseases ◽

Mean Temperature ◽

Risk Ratios

We investigated decadal (2010–2019) cardiovascular, cerebrovascular, and respiratory mortality sensitivity to annual warm temperatures in major Japanese cities: Sapporo, Tokyo (23 wards), and Osaka. The summer mortalities (June–August) increased with the monthly mean temperature for acute myocardial infarction, other acute ischemic heart diseases, cerebral infarction, and pneumonia in the three cities. Monthly mean temperatures were an indicator of these disease mortalities in Japan. However, similar responses were not found for cardiac arrhythmia and heart failure (excluding Sapporo), subarachnoid hemorrhage, and intracerebral hemorrhage. The decadal sensitivities and risk ratios between the maximum and minimum monthly mean temperatures were calculated using a linear regression model. In Sapporo, Tokyo, and Osaka, for example, the analyses of acute myocardial infarction showed summer positive responses of 0.19–0.25, 0.13–0.18, and 0.12–0.30, respectively, as the mortality rate (per 100,000 population) per 1 °C of monthly mean temperature, which estimated increased risks (between the coolest and hottest months) of 37–65% in Sapporo, 31–42% in Tokyo, and 35–39% in Osaka.

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Relation between Concentration of Pollutants and Some Climatic Parameters on Cardiovascular and Respiratory Disease Mortality in Shiraz

Journal of Shahid Sadoughi University of Medical Sciences ◽

10.18502/ssu.v28i3.3744 ◽

2020 ◽

Author(s):

Kamal Omidvar ◽

Sepideh Shahaeian ◽

Mahbobeh Amiri Esfandegheh

Keyword(s):

Respiratory Diseases ◽

Correlation Coefficients ◽

Mortality Rates ◽

Climatic Parameters ◽

Medical Sciences ◽

Respiratory Mortality ◽

Daily Data ◽

Disease Mortality ◽

Different Seasons ◽

Cardio Vascular

Introduction: Industrialization and the growing of urbanization have increased the amount of contamination and have a devastating impact on the population health; the aim of this study was the relationship between pollutants and some climatic parameters on mortality of heart and respiratory diseases in Shiraz Methods: The study was an analytical one. Firstly, daily data on climate elements (temperature, humidity, pressure, wind) from Shiraz Meteorological Office (2004-2014), daily information on air pollutants (CO, PM, NO2, SO2, O3) from Shiraz General Environment Department and cardiovascular and respiratory mortality rates from Shiraz University of Medical Sciences was collected, respectively. Data were analyzed using software SPSS ver. 22; statistical methods and correlation coefficients of monthly, seasonal and monthly averages and mortality rates were investigated. Results: Results of this study indicated that there was a significant correlation between the parameters of the climate (humidity, pressure, temperature and wind) and deaths from cardio - vascular and respiratory diseases at the level of 0.99 and 0.95 (**=P<0/01, *=P<0/05). There was a statistical difference between the mortality rates in different seasons in Shiraz and the mortality rates caused by the cardio vascular and respiratory diseases were relatively more sensitive to climate parameters. Conclusion: In general, during the statistical period, no polluted day was observed in polluted O3, NO2 in Shiraz City, relationships between other pollutants and mortality rates were significant. This correlation is shown by a 1-5 day delay for pollutants of CO, PM10and 6-10 days for pollutants of SO2.

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PM2.5 exposure on daily cardio-respiratory mortality in Lima, Peru, from 2010 to 2016.

10.21203/rs.2.23559/v2 ◽

2020 ◽

Author(s):

Vilma Tapia ◽

Kyle Steenland ◽

Bryan Vu ◽

Yang Liu ◽

Vanessa Vasquez ◽

...

Keyword(s):

Air Pollution ◽

Cardiovascular Diseases ◽

Poisson Regression ◽

Age Groups ◽

Age Group ◽

Respiratory Mortality ◽

Pm 2.5 ◽

Air Pollution Exposure ◽

Pm2.5 Exposure ◽

Pollution Exposure

Abstract Background: There have been no studies of air pollution and mortality in Lima, Peru. We evaluate whether daily environmental PM 2.5 exposure is associated to respiratory and cardiovascular mortality in Lima during 2010 to 2016. Methods: We analyzed 86,970 deaths from respiratory and cardiovascular diseases in Lima from 2010-2016. Estimated daily PM 2.5 was assigned based on district of residence. Poisson regression was used to estimate associations between daily district-level PM 2.5 exposures and daily counts of deaths. Results: An increase in 10 µg/m 3 PM 2.5 on the day before was significantly associated with daily all-cause (respiratory and circulatory) mortality (RR 1.029; CI 95% CI: 1.01 – 1.05) across all ages and in the age group over 65 (RR 1.04; 95% CI: 1.005 – 1.09) which included 74% of all deaths. We also observed associations with circulatory deaths for all age groups (RR 1.06; 95% CI: 1.01 – 1.11), and those over 65 (RR 1.06; 95% CI 1.00 - 1.12). A borderline significant trend was seen (RR 1.05; 95% CI 0.99 – 1.06; p = 0.10) for respiratory deaths in persons aged over 65. Trends were driven by the highest quintile of exposure. Conclusions: PM 2.5 exposure is associated with daily all-cause, cardiovascular and respiratory mortality in Lima, especially for older people. Our data suggest that the existing limits on air pollution exposure are too high.

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Short-Term Effect of Temperature Change on Non-Accidental Mortality in Shenzhen, China

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18168760 ◽

2021 ◽

Vol 18 (16) ◽

pp. 8760

Author(s):

Yao Xiao ◽

Chengzhen Meng ◽

Suli Huang ◽

Yanran Duan ◽

Gang Liu ◽

...

Keyword(s):

Temperature Change ◽

Linear Models ◽

Cumulative Effect ◽

The Elderly ◽

Apparent Temperature ◽

Effect Of Temperature ◽

Surface Model ◽

Susceptible Population ◽

Respiratory Mortality ◽

Increased Risk

Temperature change is an important meteorological indicator reflecting weather stability. This study aimed to examine the effects of ambient temperature change on non-accidental mortality using diurnal temperature change (DTR) and temperature change between neighboring days (TCN) from two perspectives, intra-day and inter-day temperature change, and further, to explore seasonal variations of mortality, identify the susceptible population and investigate the interaction between temperature change and apparent temperature (AT). We collected daily data on cause-specific mortality, air pollutants and meteorological indicators in Shenzhen, China, from 1 January 2013 to 29 December 2017. A Quasi-Poisson generalized linear regression combined with distributed lag non-linear models (DLNMs) were conducted to estimate the effects of season on temperature change-related mortality. In addition, a non-parametric bivariate response surface model was used to explore the interaction between temperature change and AT. The cumulative effect of DTR was a U-shaped curve for non-accidental mortality, whereas the curve for TCN was nearly monotonic. The overall relative risks (RRs) of non-accidental, cardiovascular and respiratory mortality were 1.407 (95% CI: 1.233–1.606), 1.470 (95% CI: 1.220–1.771) and 1.741 (95% CI: 1.157–2.620) from exposure to extreme large DTR (99th) in cold seasons. However, no statistically significant effects were observed in warm seasons. As for TCN, the effects were higher in cold seasons than warm seasons, with the largest RR of 1.611 (95% CI: 1.384–1.876). The elderly and females were more sensitive, and low apparent temperature had a higher effect on temperature change-related non-accidental mortality. Temperature change was positively correlated with an increased risk of non-accidental mortality in Shenzhen. Both female and elderly people are more vulnerable to the potential adverse effects, especially in cold seasons. Low AT may enhance the effects of temperature change.

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