key: cord-0934275-cvkdpnn3 authors: Díaz, Julio; Antonio-López-Bueno, José; Culqui, Dante; Asensio, César; Sánchez-Martínez, Gerardo; Linares, Cristina title: Does Exposure to Noise Pollution Influence the Incidence and Severity of COVID-19? date: 2021-01-23 journal: Environ Res DOI: 10.1016/j.envres.2021.110766 sha: 6e6de1ef5225b095f7cefee3489901256f376289 doc_id: 934275 cord_uid: cvkdpnn3 Research that analyzes the effect of different environmental factors on the impact of COVID-19 focus primarily on meteorological variables such as humidity and temperature or on air pollution variables. However, noise pollution is also a relevant environmental factor that contributes to the worsening of chronic cardiovascular diseases and even diabetes. This study analyzes the role of short-term noise pollution levels on the incidence and severity of cases of COVID-19 in Madrid from February 1 to May 31, 2020. The following variables were used in the study: daily noise levels averaged over 14 days; daily incidence rates, average cumulative incidence over 14 days; hospital admissions, Intensive Care Unit (ICU) admissions and mortality due to COVID-19. We controlled for the effect of the pollutants PM(10) and NO(2) as well as for variables related to seasonality and autoregressive nature. GLM models with Poisson regressions were carried out using significant variable selection (p<0.05) to calculate attributable RR. The results of the modeling using a single variable show that the levels of noise (leq24h) were related to the incidence rate, the rate of hospital admissions, the ICU admissions and the rate of average cumulative incidence over 14 days. These associations presented lags, and the first association was with incidence (lag 7 and lag 10), then with hospital admissions (lag 17) and finally ICU admissions (lag 22). There was no association with deaths due to COVID-19. In the results of the models that included PM1(0), NO(2), Leq24h and the control variables simultaneously, we observed that only Leq24h went on to become a part of the models using COVID-19 variables, including the 14-day average cumulative incidence. These results show that noise pollution is an important environmental variable that is relevant in relation to the incidence and severity of COVID-19 in the Province of Madrid. In analyzing the impact of different environmental factors on the incidence and severity of The objective of this study was to analyze the possible daily relationship that exists over the 83 short-term between noise levels registered and 14-day averages in Madrid and rates of 84 incidence, 14-day average cumulative incidence, hospital admissions, Intensive Care Unit (ICU) 85 admissions and deaths due to COVID-19 during the period of February 1 to May 31, 2020. We 86 controlled for the effect of the pollutants PM 10 and NO 2 and for different confounding In the case of ICU admissions and deaths, rates per million inhabitants were used, to result in a 6 The independent variables were made up of noise levels and data on air pollution. Noise level data refer to 24-hour average values (Leq24h) in A-weighted dB-dB(A) (Leq24h) - The lags considered were those of up to 28 days, given that the average time between NO 2 ) and took into account the aforementioned control variables. A weekly distributed lag model was used. In a first step, the lags were introduced for the 155 independent variables from 0-7 days. In a second step, the lags corresponding to 8-14 days 156 were introduced, while maintaining the lag variables that were statically significant in the first Based on the values of the estimators, relative risks were calculated (RR) in the form RR = e β 159 with β being the value of the estimator obtained in the Poisson modeling. A negative coefficient in the estimator indicates that an increase in the value of the 161 independent variable is associated with a decrease in the value of the dependent variable. The Table 1 shows the descriptive statistics for the incidence rates, rates of hospital admission and 170 ICU admission, death rate and the average incidence over 14 days. Figures 1A and 1B show the 171 time evolution during the period analyzed, which corresponds to the so called "first wave," as 172 can be observed. The descriptive statistics of the independent variables also appear in Table 1 Leq24h, whereas the correlation between PM 10 and Leq24h is slightly lower (0.391). 182 Table 3 shows the results of the single variable modeling in relation to the average daily 183 values. The noise measured via Leq24h is related both to the incidence rate as well as the 184 hospital admission rate, ICU admissions and the cumulative incidence rate over 14 days. These 185 associations show time lags, the first of which is associated with incidence (lag 7 and 10), and 186 later hospital admissions (lag 17), and finally ICU admissions (lag 22). There was no association 187 with deaths due to COVID-19. Table 3 also shows the single variable models for PM 10 and NO 2 . 190 Table 5 shows the models with all of the variables, which simultaneously include PM 10 In terms of the meteorological variables, the GLM models show that the coefficients related to 220 COVID-19 variables are negative. That is to say, low and humid temperatures are related to 221 higher incidence rates. On the other hand, the serological study of the prevalence of SARS- This added effect of noise pollution that is similar to the short-term effect of NO 2 or PM 10 306 could explain why noise shows associations with all of the COVID variables considered (with 307 the exception of mortality), which is something that does not occur in the case of the air 308 pollutants, as shown in Table 3 . The results in Table 4 In addition, for much of the analysis period, the population was confined to their homes. Estimates of the 551 severity of coronavirus disease 2019: a model-based analysis Methodological Considerations for Epidemiological 554 Studies of Air Pollution and the SARS and COVID-19 Coronavirus Outbreaks 556 58. WHO. World Health Organization. Regional Office for Europe. Environmental noise 557 guidelines for the European Regio Association of particulate matter pollution and case 561 fatality rate of COVID-19 in 49 Chinese cities Direct effects 564 of airborne PM2.5 exposure on macrophage polarizations Clinical course and risk factors for 568 mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort 569 study