Post-graduate Program in Health and Nutrition, Nutrition School, Federal University of Ouro Preto, Ouro Preto, Minas Gerais, Brazil.
School of Nutrition, Federal University of Ouro Preto, Ouro Preto, Minas Gerais, Brazil.
Sleep Breath. 2024 Mar;28(1):531-537. doi: 10.1007/s11325-023-02928-8. Epub 2023 Sep 28.
To analyze the association between changes in body adiposity and length of service on a schedule of rotating shifts.
The study was a cross-sectional investigation conducted during the years 2012, 2015, and 2018, involving individuals engaged in rotating shifts at a company involved in iron ore extraction situated within the Iron Quadrangle region of Minas Gerais and the southeastern region of Pará, Brazil. Sociodemographic and behavioral data were collected along with anthropometric parameters in order to calculate body mass index (BMI) and the waist-to-height ratio (WHtR). For data analysis, a multivariate logistic regression was employed to explore potential associations between indicators of body adiposity and the duration of shift work, employing a hierarchical determination model.
The findings showed that in the multivariate model, controlling for confounding factors, workers with 5 to 10, 10 to 15, and more than 15 years of shift work had 41 to 96% greater odds of being overweight (BMI > 25.0 kg/m), 71 to 82% of having altered neck circumference (> 40 cm), 33 to 120% of altered WC (>102 cm), and 57 to 214% of having altered WHtR (> 0.5 cm).
The findings suggest that time spent in work has a significant effect on anthropometric indicators of body adiposity, especially if the worker has a previously established comorbidity such as dyslipidemia or hypertension and is frequently exposed to night work.
分析体脂变化与轮班工作时长之间的关系。
这是一项横断面研究,于 2012 年、2015 年和 2018 年进行,研究对象为在巴西米纳斯吉拉斯州铁四角地区和帕拉州东南部从事铁矿开采工作的轮班工人。研究收集了社会人口学和行为数据以及人体测量参数,以计算体重指数(BMI)和腰高比(WHtR)。采用多变量逻辑回归分析来探索体脂指标与轮班工作时长之间的潜在关联,并采用分层确定模型进行分析。
在多变量模型中,控制混杂因素后,工作 5-10 年、10-15 年和 15 年以上的工人超重(BMI>25.0kg/m)的几率增加 41%至 96%,颈围异常(>40cm)的几率增加 71%至 82%,腰围异常(>102cm)的几率增加 33%至 120%,腰高比异常(>0.5cm)的几率增加 57%至 214%。
工作时间对体脂的人体测量指标有显著影响,尤其是对于已经存在血脂异常或高血压等合并症且经常上夜班的工人。