Pizarro-Mena Rafael Andrés, Duran-Aguero Samuel, Silva Andrés
Facultad de Ciencias de la Salud, Universidad San Sebastián, Los Leones, Santiago, Chile.
Facultad de Ciencias para el Cuidado de la Salud, Universidad San Sebastián, Los Leones, Santiago, Chile.
Sleep Sci. 2022 Jan-Mar;15(1):26-33. doi: 10.5935/1984-0063.20210023.
To associate the effects of the social outbreak with insomnia and daytime sleepiness according to the distance from the riots.
Cross-sectional analytical study; a non-probabilistic sampling was carried out at a national level. The Google Forms tool was used; a document was submitted using a national database. The instrument consisted of four sections: socio-demographic data, biopsychosocial symptoms, insomnia severity index (ISI), and the Epworth sleepiness scale (ESS). The data were analyzed using descriptive statistics and the zero-inflated negative binomial model.
Of a total of 2,532 surveyed people, 29% were male; 43% was younger than 30 years old. The 50% of the sample suffers from sleepiness and 71% shows some type of insomnia. The marginal effects of the zero-inflated negative binomial model show that women, people aged 51 or older, who are neither studying a healthcare degree nor working in the healthcare sector, that are exposed to 4 or more hours per day to the news and that live in areas near or very near the riots, have significantly higher ISI (marginal effect 1.356, SE 0.381, p-value 0.000) and ESS scores (marginal effect 0.693, SE 0.320, p-value 0.030). To live/work in rioting areas has the greater marginal effect compared to other determinants. Finally, neither employment status nor educational level are associated with significant effects in the aforementioned scales.
The riots occurred during the social outbreak of October 2019 in Chile had an effect on insomnia and daytime sleepiness. Particularly, to live/work in rioting areas has the greater marginal effect compared to other determinants.
根据与骚乱地区的距离,将社会骚乱的影响与失眠和日间嗜睡联系起来。
横断面分析研究;在全国范围内进行非概率抽样。使用谷歌表单工具;通过国家数据库提交一份文件。该工具由四个部分组成:社会人口统计学数据、生物心理社会症状、失眠严重程度指数(ISI)和爱泼华嗜睡量表(ESS)。使用描述性统计和零膨胀负二项式模型对数据进行分析。
在总共2532名受访者中,29%为男性;43%年龄小于30岁。50%的样本存在嗜睡问题,7