Key result
Latent class analysis identifies 4 distinct cardiovascular risk clusters among industrial workers.
Cross-Sectional (n=2,616)
PURPOSE: The purpose of this study was to identify subgroups of the physical and behavioral risk profiles for cardiovascular disease among industrial workers, and to examine predicting factors for the subgroups. SAMPLE AND METHOD: Health records of 2,616 male and female workers aged 19-56 years who were employed in an airplane manufacturing industry were analyzed. Data were analyzed using the Latent class cluster analysis. RESULTS: Four different clusters (two high-risk groups, one low-risk group, and one normal group) were found and these clusters were significantly different by age, gender, and work type (p<.05). The two high-risk groups had higher chances of drinking alcohol, elevated BMI, FBS, total cholesterol, having hypertension, and were significantly older, and had relatively high chances of being day workers rather than other groups. The low-risk group had higher chances of drinking alcohol, higher BMI and total cholesterols compared to normal group, and highest portions of current smokers and shift workers in the four clusters and their mean BP was within prehypertension criteria. CONCLUSION: Industrial nurses should guide the lifestyle behaviors and risk factors of the high risk groups for CVD and need to intervene early for behavioral change for the low-risk group who are young and shift workers. Age, and work environment should be considered in planning for targeted preventive interventions for industrial workers.
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Hwang et al. (2005) conducted a cross-sectional in Cardiovascular disease risk profiles (n=2,616). Physical and behavioral cardiovascular risk factors and work type vs. Normal risk cluster was evaluated on Latent class clusters of cardiovascular disease risk profiles (p=<.05). Latent class cluster analysis of 2,616 industrial workers identified 4 cardiovascular risk clusters differing significantly by age, gender, and work type (p<.05).
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