印尼三宝垄市热暴露工人尿液结晶

Diki Bima Prasetio, Eli Sahiroh, Nasya Adelia Putri, S. Haryani, Shinta Dwi Surya Pramesti, Ruli Syaifani Fajri
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引用次数: 0

摘要

高温的工作环境条件会导致工人体液流失,从而导致尿量减少,从而使尿液变得集中。如果这种情况持续很长时间,可能会导致尿液饱和。本研究采用横断面设计,选取三宝垄市潭塘村豆腐厂工人32人作为调查对象。最相关的变量是高温工作环境会影响员工体液流失,导致尿量减少,从而尿量变得集中。如果这种情况持续很长时间,就会出现尿饱和。本研究采用横断面设计,以三宝垄市潭塘村豆腐厂32名员工为调查对象。与尿结晶最相关的变量是饮水量,而饮水量是尿结晶发生的最大影响变量。饮水量不足的员工与饮水量较少的员工相比,尿液结晶的概率为41.80%,即尿液结晶的概率为98.81。由这个方程可以解释为员工尿结晶的风险为0.4230倍。从研究的8个变量中,有4个变量(年龄、饮水量、热密度和脱水程度)与尿结晶有统计学上显著的关系。同时,根据logistic回归检验,空气消耗是最主要的变量。尿结晶是饮水量,而饮水量是影响尿结晶实施的最大变量。饮用足够饮水的工人尿液结晶的概率为41.80%。高温的工作环境对员工的影响使员工遇到体液流失,导致尿量减少,从而尿量变得集中。如果长期不考虑这种情况,就会引起尿饱和。本研究采用横断面设计,以三宝垄市潭塘村豆腐厂32名员工为调查对象。与尿结晶最相关的变量是饮水量,而饮水量是尿结晶发生的最大影响变量。饮水量不足的员工与饮水量较少的员工相比,尿液结晶的概率为41.80%,即尿液结晶的概率为98.81。由这个方程可以解释为员工尿结晶的风险为0.4230倍。从研究的8个变量中,有4个变量(年龄、饮水量、热密度和脱水程度)与尿结晶有统计学上显著的关系。同时,logistic回归检验的最主导变量是空气消耗与饮水消耗较少的工人配对,即尿液结晶概率为98.81。由这个方程可以解释为工人尿液结晶的风险为0.4230倍。在研究的八种变量中,共情变量(年龄、空气消耗、热压和脱水程度)与尿结晶有统计学上显著的关系。同时,根据logistic回归检验,空气消耗是最主要的变量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Urine Crystallization in Heat Exposed Workers in Semarang City, Indonesia
Work environment conditions with high temperatures cause workers to experience fluid loss which can cause urine production to decrease so that the urine produced becomes concentrated. If this condition is left for a long time, it can cause saturation of the urine. This study used a cross-sectional design and had 32 respondents as tofu factory workers in Tandang Village, Semarang. The variable most related A working environment with high temperatures impacts the employees to encounter fluid loss which leads to the reduction of urine production, thus the urine production becomes concentrated. If this condition lasts for a long time, there will be saturation of the urine. This present study used a cross-sectional design with 32 employees of the tofu factory as the respondent in Tandang Village, Semarang. The most related variable with urine crystallization is water drinking consumption which is the most influential variable in the occurrence of urine crystallization. Employees who consume water drinking insufficient amounts have a probability crystallization of 41.80% compared to employees who consume less water drinking, namely the probability of urine crystallization of 98.81. From this equation, it can be interpreted that employees have a risk of urine crystallization of 0.4230 times. From the eight variables studied, there are four variables (age, water drinking consumption, heat density, and the level of dehydration) that had a statistically significant relationship with urine crystallization. Meanwhile, the most dominant variable based on the logistic regression test is air consumption. to urine crystallization is drinking water consumption which is the most influential variable in the implementation of urine crystallization. Workers who consume enough drinking water have a probability of urine crystallization of 41.80% comA working environment with high temperatures impact on the employees to encounter with the fluid loss which lead to the reduction of urine production, thus the urine production becomes concentrated. If this condition is not taken into account for a long period, it caused the saturation of urine. This present study used a cross-sectional design with 32 employees of the tofu factory as the respondent in Tandang Village, Semarang. The most related variable with urine crystallization is water drinking consumption which is the most influential variable in the occurrence of urine crystallization. Employees who consume water drinking insufficient amounts have a probability crystallization of 41.80% compared to employees who consume less water drinking, namely the probability of urine crystallization of 98.81. From this equation, it can be interpreted that employees have a risk of urine crystallization of 0.4230 times. From the eight variables studied, there are four variables (age, water drinking consumption, heat density, and the level of dehydration) that had a statistically significant relationship with urine crystallization. Meanwhile, the most dominant variable based on the logistic regression test is air consumption paired to workers who consume less drinking water, namely the probability of urine crystallization of 98.81. From this equation, it can be interpreted that workers have a risk of urine crystallization of 0.4230 times. Of the eight types of variables studied, empathy variables (age, air consumption, heat pressure, and degree of dehydration) had a statistically significant relationship with urine crystallization. Meanwhile, the most dominant variable based on the logistic regression test is air consumption.
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