Zhang Yadi, Jiang Fan, Song Zhenyao, Lian Jintao, Han Licun
Department of Disease Control and Prevention, Air Force Medical Center, Air Force Medical University, PLA, 30# Fucheng Road, Haidian District, Beijing, 100142, China.
Section of Health, No. 94804 Unit of the Chinese People's Liberation Army, Shanghai, 200434, China.
J Physiol Anthropol. 2025 Nov 7;44(1):28. doi: 10.1186/s40101-025-00411-9.
The thermos-physiological characteristics of medical personnel wearing protective clothing during prolonged activities under low oxygen pressure (LOP) and normal oxygen pressure (NOP) are crucial.
The average age of the 24 participants was 22.13 ± 1.849 years, with an average height of 168.58 ± 6.268 cm, an average weight of 61.62 ± 8.128 kg, and an average BMI of 21.59 ± 1.761 kg/m. Participants were first exposed to an LOP environment. The 6-h experiment involved a three-phase cycle (sitting, walking, and cardiopulmonary resuscitation (CPR)) repeated every hour. After a 2-week washout period, 24 participants were exposed to a NOP environment and repeated the aforementioned experimental procedure. Logistic regression and Cox analysis were used to assess the relationship between different oxygen pressures and human indicators. Restricted cubic spline (RCS) analysis was employed to examine the temporal changes in physiological indicators, and the Kaplan-Meier (K-M) method was used to plot survival curves.
Each observation time point identified 120 min as the optimal protection time, with the greatest intergroup differences observed for both continuous (5/8 variables) and categorical (8/12 variables) parameters at this time point. Stepwise Regression analyses combining logistic and Cox regression identified six significant variables (P < 0.05): temperature, SpO₂, pulse pressure, thermal sensation vote (TSV), sultriness, and rating of perceived exertion (RPE). K-M analysis revealed significantly higher probabilities of adverse outcomes in the LOP group compared to the NOP group: SpO₂ abnormalities (HR = 1.439, 95% CI: 1.026-2.017; log-rank P = 0.022), High TSV scores (HR = 2.463 [1.537-3.946]; P < 0.001), High sultriness scores (HR = 1.603 [1.260-2.040]; P < 0.001). RCS analysis of LOP group data showed significant temporal effects: RPE exhibited a nonlinear upward trend (overall P < 0.001; nonlinear P = 0.002), reaching an inflection point at 200 min. SpO₂ demonstrated linear decline (P = 0.002/0.143; inflection point = 200 min). Pulse pressure showed covariate-dependent effects: nonsignificant before adjustment (P = 0.430) but significant after adjustment (P = 0.008/0.891; inflection point = 200 min).
Our research shows that 120 ~ 200 min is an optimal working time that does not affect the work efficiency of medical personnel.
医务人员在低氧压力(LOP)和正常氧压力(NOP)下长时间活动时穿着防护服的热生理特征至关重要。
24名参与者的平均年龄为22.13±1.849岁,平均身高为168.58±6.268厘米,平均体重为61.62±8.128千克,平均体重指数为21.59±1.761千克/米。参与者首先暴露于低氧压力环境。为期6小时的实验包括每小时重复一次的三相循环(坐着、行走和心肺复苏(CPR))。经过2周的洗脱期后,24名参与者暴露于正常氧压力环境并重复上述实验程序。采用逻辑回归和Cox分析评估不同氧压力与人体指标之间的关系。使用受限立方样条(RCS)分析来检查生理指标的时间变化,并使用Kaplan-Meier(K-M)方法绘制生存曲线。
每个观察时间点确定120分钟为最佳保护时间,此时连续(5/8个变量)和分类(8/12个变量)参数的组间差异最大。结合逻辑回归和Cox回归的逐步回归分析确定了六个显著变量(P<0.05):体温、血氧饱和度(SpO₂)、脉压、热感觉投票(TSV)、闷热感和自觉运动强度分级(RPE)。K-M分析显示,与正常氧压力组相比,低氧压力组不良结局的概率显著更高:SpO₂异常(风险比(HR)=1.439,95%置信区间:1.026-2.017;对数秩检验P=0.022)、高TSV评分(HR=2.463[1.537-3.946];P<0.001)、高闷热感评分(HR=1.603[1.260-2.040];P<0.001)。对低氧压力组数据的RCS分析显示出显著的时间效应:RPE呈非线性上升趋势(总体P<0.001;非线性P=0.002),在200分钟时达到拐点。SpO₂呈线性下降(P=0.002/0.143;拐点=200分钟)。脉压显示出协变量依赖性效应:调整前不显著(P=0.430),但调整后显著(P=0.008/0.891;拐点=200分钟)。
我们的研究表明,120~200分钟是不影响医务人员工作效率的最佳工作时间。