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✅ Using natural light or artificial lights with adequate illuminance and high correlated color temperature can increase the alertness and visual comfort to some extent and improve the sleep quality of day staff employers.
Lack of adequate lighting in the workplace can endanger the general health of employees by affecting the circadian rhythm and human visual system and cause a wide range of visual and non-visual problems [1]. Visual effects of lighting include visual comfort and non-visual effects include changes in level of consciousness, cognitive function and sleep quality, fatigue and occupational errors, decreased sleep quality at night, and consequently decreased job satisfaction and productivity and increased absenteeism [6-2]. High light intensity as the most important quantitative variable can not only increase vitality and mental alertness but can also objectively increase a person's performance [8]. Another characteristic of light affecting vision is the color rendering index and color temperature, which depend on the light spectrum [9]. Natural light is the best light source in terms of having full spectrum and sufficient intensity, which regulates physiological functions and improves general health [9].
On the one hand, architectural limitations for the optimal use of natural light and on the other hand, the use of various types of electric lights without color temperature and proper color rendering index is one of the problems of many office environments. However, the quantity and quality of lighting on the work surface varies over time depending on the type and duration of use of lamps, the type of lamps and related equipment, the reflection coefficients of interior surfaces and the presence or absence of natural light. The subject of this study was to study the quantity and quality of various types of artificial light sources in office environments and to compare them with each other, as well as comparing them with natural light and their relationship with mental performance, comfort and alertness of administrative staff in Hamadan University of Medical Sciences.
A descriptive-analytical study was conducted in the winter of 2017 on the educational campus of Hamadan University of Medical Sciences. A total of 81 administrative staff located in different rooms of the complex randomly participated in the research from different departments and faculties and moral consent was obtained from all participants. Lighting parameters in rooms with windows were measured in three shifts at the beginning (about 8 o'clock), the middle (around 11 o'clock) and the end of the work shift (around 14 o'clock) and the rooms without windows due to the dynamic state of the combined lighting. Brightness, color temperature and color rendering index were measured horizontally with a Sekonic-7000 spectrometer on the work surface and vertically on the eye surface. To evaluate mental performance, visual comfort, and mental alertness and sleep quality of employees, psychomotor vigilance task test of N-back type at simple level (1-back), Conlon visual comfort questionnaire, questionnaire The KSS Drowsiness Index and the Pittsburgh Sleep Quality Questionnaire were used, respectively.
The results on the types of lights used in the office rooms showed that some of the lights had a diffuser and some did not, and most of them had fluorescent lamps in the form of tubes, and FPL. Also, the degree of cleanliness and maintenance of the lights was very different. The results of measuring the quantities of light related to the technical and qualitative characteristics of the types of lamps widely used in laboratory conditions are described in Table 1. Also, as an example, the spectrogram of one of the lights is presented in Figure 1.
Figure 1. Spectrogram of linear fluorescent lamp with diffuser and daylight tube lamp
Comparison of the average color temperature of natural light with different types of fluorescent lamps in laboratory conditions showed that warm white fluorescent lamps have significantly lower color temperature than natural light (P = 0.01). The average intensity of artificial light on the work surface of rooms without windows was 276 Lx and the average intensity of combined light in rooms with windows at three hours 11, 8 and 14 was 724, 615 and 510 lux, respectively, which means that the intensity of combined light is higher than Artificial lighting is in all three hours (P = 0.001). The results showed that the type of lighting had a significant effect on the color temperature on the desktop, so that the average color temperature in the combined lighting was significantly higher than its value in artificial lighting (P = 0.001 and F = 23.215). The mean of the combined color temperature and the corresponding color manifestation index did not show a statistically significant difference in the three measurement times. However, the color index of artificial light at different hours of measurement was significantly lower than the combined light. This difference was more pronounced at 8 and 11 o'clock than at 2 o'clock (P14 = 0.033, P8,11 = 0.001). According to Fisher's exact test, the distribution of visual comfort in the two types of integrated and artificial lighting indicates more desirable visual comfort in people who are exposed to natural light. Thus, the ratio of people with moderate visual impairment to the total number of employees in the group of employees located in rooms without natural light was 4.7 times higher than the group with natural light (18.2% vs. 3.8%) (P = 0.04 and Chi2 = 4.74). The results of Pearson correlation coefficient test to calculate the relationship between the two variables of color temperature and visual comfort score indicated a negative and significant relationship between these two variables (r = 0.35, P = 0.002). Figure 2 is the diagram showing the correlation between the values of the visual comfort questionnaire and Indicates the color temperature.
Figure 2. Correlation diagram between color temperature in the office environment and visual comfort score
Tables 1 and 2 show the results of Pearson and Spearman correlation coefficient tests to estimate the relationship between individual variables with color temperature and light intensity at different times of the day, respectively. As can be seen from the data in the tables, only the drowsiness score at 8 and 11 o'clock had a significant relationship with color temperature and the rest were not statistically significant.
Table 1. Results of Pearson correlation analysis between variables of color temperature, drowsiness and performance
Color temperature | Variables | |
r | P | |
-0.228* | 0.047 | KSS score at 8 o'clock |
-0.315* | 0.006 | KSS score at 11 o'clock |
-0.09 | 0.44 | KSS score at 14 o'clock |
-0.028 | 0.82 | PVT test response speed at 8 o'clock |
-0.08 | 0.50 | PVT test response speed at 11 o'clock |
-0.89 | 0.47 | PVT test response speed at 14 o'clock |
-0.115 | 0.33 | Percentage of correct answer of PVT test at 8 o'clock |
-0.147 | 0.22 | Percentage of correct answer of PVT test at 11 o'clock |
-0.065 | 0.6 | Percentage of correct answer of PVT test at 14 o'clock |
Table 2. Results of Pearson and Spearman correlation analysis between variables of light intensity, visual comfort and performance
Intensity of lighting | Variables | |
r | P | |
-0.049 | 0.68 | Visual Comfort Score |
-0.168 | 0.16 | Visual comfort class |
-0.025 | 0.86 | KSS score at 8 o'clock |
0.17 | 0.23 | KSS score at 11 o'clock |
0.088 | 0.54 | KSS score at 14 o'clock |
-0.004 | 0.98 | PVT test response speed at 8 o'clock |
0.126 | 0.30 | PVT test response speed at 11 o'clock |
0.181 | 0.14 | PVT test response speed at 14 o'clock |
-0.116 | 0.89 | Percentage of correct answer of PVT test at 8 o'clock |
0.141 | 0.25 | Percentage of correct answer of PVT test at 11 o'clock |
-0.004 | 0.98 | Percentage of correct answer of PVT test at 14 o'clock |
Table 3. Independent t-test to compare visual comfort status, response speed and correct response percentage
Type of lighting | Number of measurements | M | SD | T | P | |
KSS score | Merely artificial | 84 | 3.2 | 1.3 | 2.80 | 0.004 |
Natural | 156 | 7.2 | 1.4 | |||
PVT test response speed (Hundredth of a second) | Merely artificial | 69 | 476 | 50 | 0.56 | 0.580 |
Natural | 140 | 463 | 48 | |||
Percentage of correct answer of PVT test | Merely artificial | 74 | 96.4 | 2.4 | 1.07 | 0.202 |
Natural | 143 | 95.8 | 4.6 |
Table 4 compares the sleep quality class statistics according to PSQI, which shows the relatively better sleep quality of people living in rooms with natural light. But this difference was not statistically significant.
Table 4. Fisher test to compare the sleep quality of people in two groups of workplace lighting
Type of lighting | Chi2 | P | ||||
Combined | Merely artificial | |||||
Sleep quality | Good | Number of persons | 30 | 14 | 0.44 | 0.50 |
Percentage in lighting type group | 57.7 | 50 | ||||
Weak | 22 | 14 | ||||
42.3 | 50 | |||||
Total | 52 | 28 | ||||
100 | 100 |
The light produced by different types of lamps has incomplete light spectrum and non-uniform spectrum distribution and lower light intensity compared to natural light. Therefore, as expected, some visual and non-visual effects were observed in employees deprived of natural light in comparison with employees benefiting from this gift, which is in line with the general perception of review studies by Van Bommel and Stephen [1, 18].
The results obtained regarding the difference between color temperature and color index of natural and artificial light inside the building are according to the study of Borisuit et al.; that even in cloudy weather conditions, the values attributed to natural light are higher [20]. According to the results of this study, none of the employees had visual disturbances higher than the average. The result of this study in terms of the increasing effect of color temperature on visual comfort and the general relationship between these two variables was consistent with the study conducted by Shamul et al. and the study of Sivaji et al. [21, 22]. There was a direct and significant relationship between increasing color temperature and decreasing drowsiness at 8 and 11 o'clock, relying on some results of studies by some researchers such as Te Kulve [23]. However, this relationship was very weak for 14:00, which can be attributed to the increase in fatigue caused by intellectual workload during working hours [24]. Also, according to the Souman systematic review study, the effect of color temperature on alertness was not the same in all studies and some studies had conflicting results [25].
Examination of the correlation between light intensity variables with visual comfort and performance showed that there was no significant relationship between them. However, many studies, such as the study of Smolders et al., showed an increase in alertness with increasing light intensity [27]. One of the reasons for this contradiction is the lack of control over other variables affecting visual comfort and performance in this field study. The high proportion of people with moderate visual disturbance in the group of people living in rooms without natural light is consistent with the Borisuit study and indicates the desirability of using natural light in this regard [20, 28]. Although the quality of sleep of people with natural light was better than expected in rooms without natural light, as expected and in line with the results of a study by researchers such as Boubekri, this difference was not statistically significant [29].
Using natural light or artificial lights with adequate illuminance and high correlated color temperature can increase the alertness and visual comfort to some extent and improve the sleep quality of day staff employers.
The authors are grateful to all those who assisted in the writing of this article.
The authors declared no conflict of interest.
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