Urban Noise Exposure and Cardiometabolic Diseases: An Exploratory Cross-Sectional Study in Lisbon

城市噪声暴露与心血管代谢疾病:里斯本的一项探索性横断面研究

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Abstract

INTRODUCTION: Urban noise pollution has been associated with an increased risk of developing metabolic syndrome. Nevertheless, existing observational studies relating to noise exposure and metabolic syndrome are based on non-generalizable cohorts. Lisbon remains a noisy city where this association has not been evaluated, and for this reason, we studied the relationship between exposure to urban noise and the prevalence of type 2 diabetes mellitus, obesity, and hypertension. METHODS: Diurnal, evening and nocturnal noise emission levels were obtained for each street in the city from the Lisbon noise map. After allocation of all roads to the respective parish of Lisbon, the noise emission for each parish was averaged for each day period. The number of adult patients with type 2 diabetes mellitus, obesity and hypertension in 2014, 2015 and 2016 in each parish of Lisbon was obtained from the Regional Health Administration of Lisbon and Tagus Valley. Prevalence as a percentage of the population was determined using the number of residents in each parish determined in the 2011 population census. Spearman's non-parametric correlation coefficient was used due to the non-normal distribution of the variables, at the 5% significance level (α = 0.05). RESULTS: No correlations were found between daytime, afternoon or night-time noise exposure and the prevalence of type 2 diabetes mellitus, obesity or hypertension, although correlations were found between the cardiometabolic variables. Nevertheless, noise levels in Lisbon were above the legally established limit and the World Health Organization guidelines for environmental noise exposure in the European region. CONCLUSION: Our results do not agree with previous studies and should be faced as preliminary due to a strong biological plausibility for an association between noise exposure and cardiometabolic diseases and to encourage further studies, with longitudinal cohorts.

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