| Literature DB >> 34280977 |
Hui Liu1, Jie Li2, Hongyang Li3,4,5, He Li6, Peng Mao1, Jingfeng Yuan7.
Abstract
To reduce harm caused by occupational health risks of construction workers exposed to working environments, especially those for interior decoration, it is crucial for them to actively recognize and prevent these risks. Therefore, how to improve their occupational health risks perception and regulate their coping behaviors should be of great concern. However, most prior studies target construction worker safety, and little research focuses on risk analysis from the psychological level of workers. Hence, construction workers' occupational health risk perception level and coping behavior level in Nanjing and the influencing factors were analyzed through statistical analysis with 341 valid questionnaires. Bootstrapping was applied to test the mediating effects of risk perception on the proposed factors and coping behaviors. This study revealed that construction workers have a high-level of occupational health risk perception, yet low-level coping behavior. Gender, age, education level, and unit qualification cause differences in individual risk perception level. Personal knowledge and group effects significantly affect the level of risk perception, which subsequently affect coping behavior. Education level, monthly income, and personal knowledge influence the coping behavior through risk perception. Recommendations were put forward for risk perception and coping behavior improvement from the perspectives of construction workers themselves, enterprises, and governments. This study sheds new light for research areas of occupational health and risk management and provides beneficial practice for improving construction workers' responses to occupational health risks.Entities:
Keywords: construction workers; health risks; occupational health; risk coping behavior; risk perception
Year: 2021 PMID: 34280977 PMCID: PMC8297174 DOI: 10.3390/ijerph18137040
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 3.390
Figure 1The model of occupational health risk perception–coping behavior.
Figure 2The methodology framework in the study.
Specific indicators of construction workers’ risk perceptions and risk coping behaviors on occupational health risk.
| Categories | Indicator | Literature Sources |
|---|---|---|
| Risk | Hazardous substances are generated | Li et al. (2019) [ |
| Dust exposure leads to pneumoconiosis | Chen et al. (2019) [ | |
| Formaldehyde causes chronic respiratory diseases | Zhuo (2018) [ | |
| Inhalation of irritant gas causes headache | Chong et al. (2018) [ | |
| Materials with less pollution reduce the probability of illness | Cincinelli et al. (2017) [ | |
| Protective equipment (dust masks, gas masks, etc.) reduces harm caused by pollution | Li et al. (2017) [ | |
| Ventilation reduces harm of formaldehyde, benzene, and dust to the body | Weidman et al. (2016) [ | |
| Decoration pollution can be prevented | Li et al. (2016) [ | |
| More exercise and less smoking can reduce the probability of illness | Tadesse et al. (2016) [ | |
| Coping | Maintain ventilation | Yan (2017) [ |
| Wear dust mask | Shepherd et al. (2010) [ | |
| Wear labor protection shoes | Goto et al. (2017) [ | |
| Use other personal protective equipment | Kohlman et al. (2014) [ | |
| Avoid eating and resting on site | Yi et al. (2016) [ | |
| Pay insurance and carry out physical examination | Kim et al. (2010) [ |
Demographic information of survey respondents.
| Variable | Classification | NO. | Proportion | Variable | Classification | NO. | Proportion |
|---|---|---|---|---|---|---|---|
| Gender | Male | 321 | 94.10% | Education level | Junior middle school or below | 188 | 55.10% |
| Female | 20 | 5.90% | Technical secondary school or high school | 111 | 32.60% | ||
| Marital status | Married | 307 | 90.00% | Junior college or above | 42 | 12.30% | |
| Single | 34 | 10.00% | Monthly income | ≤5000 | 47 | 13.80% | |
| Trades | Carpenters | 76 | 22.30% | 5000–7000 | 164 | 48.10% | |
| Bricklayers | 70 | 20.50% | 7000–9000 | 109 | 32.00% | ||
| Electricians | 70 | 20.50% | ≥9000 | 21 | 6.20% | ||
| Plumbers | 45 | 13.20% | Unit | Level A | 79 | 23.20% | |
| Painters | 66 | 19.40% | Level B | 40 | 11.70% | ||
| Other | 14 | 4.10% | Level C | 23 | 6.70% | ||
| Age | ≤30 | 35 | 10.30% | No qualification | 78 | 22.90% | |
| 30~50 | 243 | 71.30% | Unclear | 121 | 35.50% | ||
| ≥50 | 63 | 18.50% |
Note: (1) respondents (total = 341); (2) the qualification of interior decoration construction units is divided into three levels: A, B and C. Units with level A qualification are the best, followed by level B and level C.
Validity and reliability analysis.
| Variable | Item | Factors | Cronbach’s α a | |||
|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | |||
| Occupational health risk perception | B1 | 0.682 | 0.872 | |||
| B2 | 0.767 | |||||
| B3 | 0.754 | |||||
| B4 | 0.707 | |||||
| B5 | 0.467 | |||||
| B6 | 0.628 | |||||
| B7 | 0.602 | |||||
| B8 | 0.523 | |||||
| B9 | 0.561 | |||||
| Coping behaviors | C1 | 0.277 | 0.668 | |||
| C2 | 0.531 | |||||
| C3 | 0.531 | |||||
| C4 | 0.699 | |||||
| C5 | 0.347 | |||||
| C6 | 0.669 | |||||
| Personal knowledge | D1 | 0.699 | 0.834 | |||
| D2 | 0.854 | |||||
| D3 | 0.854 | |||||
| D4 | 0.744 | |||||
| D5 | 0.294 | |||||
| D6 | 0.688 | |||||
| D7 | 0.675 | |||||
| Social influence factors | E1 | 0.877 | 0.936 | |||
| E2 | 0.882 | |||||
| E3 | 0.721 | |||||
| E4 | 0.884 | |||||
| E5 | 0.712 | |||||
| E6 | 0.737 | |||||
| E7 | 0.791 | |||||
| E8 | 0.795 | |||||
| E9 | 0.851 | |||||
| E10 | 0.493 | |||||
| E11 | 0.688 | |||||
| KMO = 0.889, Bartlett Χ2(df) = 6298.903(528) *** | ||||||
Note: a Overall Cronbach’s α = 0.879. *** p < 0.001.
Perception of construction workers to occupational health risks.
| Variable | Mean ± SD |
|---|---|
| Hazardous substances are generated | 4.28 ± 0.88 |
| Dust exposure leads to pneumoconiosis | 4.29 ± 0.86 |
| Formaldehyde causes chronic respiratory diseases | 4.19 ± 0.93 |
| Inhalation of irritant gas causes headache | 3.92 ± 1.00 |
| Materials with less pollution reduce the probability of illness | 3.93 ± 1.14 |
| Protective equipment (dust masks, gas masks, etc.) reduces harm caused by pollution | 3.86 ± 1.00 |
| Ventilation reduces harm of formaldehyde, benzene, and dust to the body | 4.10 ± 0.92 |
| construction pollution can be prevented | 4.05 ± 0.97 |
| More exercise and less smoking can reduce the probability of illness | 3.77 ± 1.24 |
| Risk perception | 4.03 ± 0.70 |
Coping behavior of construction workers to occupational health risks.
| Variable | Mean ± SD |
|---|---|
| Maintain ventilation | 3.97 ± 0.93 |
| Wear dust mask | 3.33 ± 1.19 |
| Wear labor protection shoes | 3.53 ± 1.13 |
| Use other personal protective equipment | 2.40 ± 1.23 |
| Avoid eating and resting on site | 3.36 ± 1.16 |
| Pay insurance and carry out physical examination | 2.25 ± 1.24 |
| Coping behavior | 3.15 ± 0.70 |
Risk perception differences among construction workers.
| Variable | Classification | Mean ± SD | Levene’s Test (Sig) | |||
|---|---|---|---|---|---|---|
| Gender | Male | 4.02 ± 0.71 | 0.051 | 0.035 | / | −2.116 |
| Female | 4.36 ± 0.54 | |||||
| Age | ≤30 | 4.32 ± 0.72 | 0.274 | 0.007 | 5.083 | / |
| 30–50 | 3.97 ± 0.69 | |||||
| ≥50 | 4.17 ± 0.71 | |||||
| Marital status | Married | 4.05 ± 0.72 | 0.044 | 0.194 | 1.319 | |
| Single | 3.91 ± 0.55 | |||||
| Education level | Junior middle school or below | 3.87 ± 0.76 | 0.000 | 0.000 | 15.109 | / |
| Technical secondary school or high school | 4.21 ± 0.60 | |||||
| Junior college or above | 4.32 ± 0.48 | |||||
| Monthly income | <5000 | 3.63 ± 0.95 | 0.000 | 0.033 | 3.055 | / |
| 5000–7000 | 4.04 ± 0.69 | |||||
| 7000–9000 | 4.10 ± 0.62 | |||||
| >9000 | 4.23 ± 0.67 | |||||
| Unit qualification | Level A | 4.20 ± 0.64 | 0.000 | 0.002 | 4.636 | / |
| Level B | 4.03 ± 0.61 | |||||
| Level C | 3.86 ± 0.52 | |||||
| No qualification | 3.76 ± 0.85 | |||||
| Unclear | 4.15 ± 0.64 |
The results of the impacts of personal knowledge on risk perception.
| Model | Non-Standardized Coefficient | Standardized Coefficient |
| ||
|---|---|---|---|---|---|
| B | SE | β | |||
| Constant | 2.858 | 0.111 | 25.849 | 0.000 | |
| personal knowledge | 2.069 | 0.185 | 0.519 | 11.182 | 0.000 |
Dependent variable: risk perception.
The results of the impacts of social influencing factors on risk perception.
| Model | Standardized Coefficient |
| |
|---|---|---|---|
| Constant | 30.985 | 0.000 | |
| Unit training | −0.090 | −0.944 | 0.346 |
| Related rules and regulations | −0.093 | −0.823 | 0.411 |
| Manager’s attitude | −0.161 | −1.784 | 0.075 |
| Group effect | 0.268 | 3.201 |
|
| Family environment | 0.034 | 0.466 | 0.642 |
Dependent variable: coping behavior. a Bold represents a significant correlation.
The results of the impacts of risk perception on coping behavior.
| Model | Non-Standardized Coefficient | Standardized Coefficient |
| ||
|---|---|---|---|---|---|
| B | SE | β | |||
| Constant | 1.822 | 0.212 | 8.578 | 0.000 | |
| Risk perception | 0.325 | 0.052 | 0.323 | 6.278 | 0.000 |
Dependent variable: coping behavior.
Mediating effects of occupational health risk perception.
| Independent Variable (Xi1) | Model 1 | Model 2 | Model 3 (Y: Coping Behavior) | Boot95%CI | |||||
|---|---|---|---|---|---|---|---|---|---|
| Xi1 | Xi1 | Xi1 | Xi2 = Risk Perception | ||||||
| β |
| β |
| β |
| β |
| ||
| Gender | 0.35 | 1.5070.133 | |||||||
| Age | −0.07 | −1.2330.222 | |||||||
| Marital status | 0.24 | 1.3350.183 | |||||||
| Education level | 0.22 | 4.188 *** | 0.25 | 4.69 *** | 0.15 | 2.883 ** | 0.29 | 5.437 *** | (0.036, 0.098) |
| Monthly income | 0.18 | 3.283 ** | 0.18 | 3.287 ** | 0.12 | 2.364 * | 0.30 | 5.806 *** | (0.016, 0.081) |
| Unit qualification | −0.25 | −4.757 *** | −0.05 | −0.9740.331 | −0.23 | −4.679 *** | 0.31 | 6.212 *** | (−0.021, 0.010) |
| Personal knowledge | 0.26 | 4.86 *** | 0.52 | 11.18 *** | 0.12 | 2.01 * | 0.26 | 4.35 *** | (0.315, 0.789) |
| Unit training | 0.33 | 6.472 *** | 0.07 | −1.3530.177 | 0.36 | 7.468 *** | 0.35 | 7.295 *** | (−0.034, 0.005) |
| Related rules and regulations | 0.39 | 7.903 *** | −0.09 | −1.5920.112 | 0.43 | 9.207 *** | 0.36 | 7.778 *** | (−0.044, 0.003) |
| Manager’s attitude | 0.34 | 6.651 *** | −0.11 | −1.9470.052 | 0.38 | 7.952 *** | 0.36 | 7.628 *** | (−0.044, 0.001) |
| Group effect | 0.38 | 7.542 *** | 0.06 | 1.1300.260 | 0.36 | 7.561 *** | 0.30 | 6.302 *** | (−0.009, 0.037) |
| Family environment | 0.35 | 6.866 *** | 0.01 | 0.1680.867 | 0.35 | 7.232 *** | 0.32 | 6.670 ** | (−0.018, 0.022) |
Note: * p < 0.05, ** p < 0.01, *** p < 0.001.
Mediating effect test of Bootstrap.
| Hypothesized Paths | Effect Type | Effect Value | BootSE | Boot95%CI | Percentage |
|---|---|---|---|---|---|
| Education level→risk perception→coping behavior | Total effect | 0.202 | 0.058 | (0.122, 0.352) | |
| Direct effect | 0.138 | 0.056 | (0.031, 0.250) | 68.32% | |
| Indirect effect | 0.064 | 0.016 | (0.036, 0.098) | 31.68% | |
| Monthly income→risk perception→coping behavior | Total effect | 0.158 | 0.052 | (0.053, 0.259) | |
| Direct effect | 0.110 | 0.049 | (0.015, 0.205) | 69.62% | |
| Indirect effect | 0.048 | 0.017 | (0.016, 0.081) | 30.38% | |
| Personal knowledge→risk perception→coping behavior | Total effect | 1.025 | 0.192 | (0.654, 1.406) | |
| Direct effect | 0.482 | 0.225 | (0.050, 0.929) | 47.02% | |
| Indirect effect | 0.543 | 0.122 | (0.315, 0.789) | 52.98% |