Association between lifestyle and hematological parameters: A study of Chinese male steelworkers.

BACKGROUND: Increasing evidence suggests an association between lifestyle and white blood cell (WBC) count; however, no study has examined the effects of lifestyle associations on hematological parameters. The aim of this study was to examine the association between lifestyle factors and hematological parameters in a large population-based sample of Chinese male steelworkers. METHODS: This study included 3189 male workers at a steel plant who responded to a cross-sectional questionnaire on basic attributes, lifestyle, and sleep. All workers in the plant underwent periodic health checkups. Hematological parameters were also examined at the checkup. RESULTS: Stepwise linear regression analyses showed that smoking, poor sleep, shift work, and obesity were all significant factors associated with WBC count. Obesity was independently associated with RBC count. Furthermore, smoking and obesity were associated with hemoglobin, and smoking, poor sleep, and obesity were independently associated with hematocrit. Moreover, smoking was the main factor associated with MCV and MCH. When the subjects were divided into quartiles according to WBC count, RBC count, hemoglobin, hematocrit, MCV, MCH, and increased WBC count were associated with smoking, poor sleep, shift work, and obesity. Increased hemoglobin was associated with smoking and obesity. Furthermore, an increased RBC count was associated with obesity, and increased hematocrit was associated with smoking, poor sleep, and obesity. Similarly, increased MCV and MCH were also associated with smoking. CONCLUSION: This study indicates that lifestyle factors may exert an important effect on hematological parameters (eg, WBC count, RBC count, hemoglobin, hematocrit, MCV, and MCH).

BSRS-5 (5-item Brief Symptom Rating Scale) scores affect every aspect of quality of life measured by WHOQOL-BREF in healthy workers.

PURPOSE: This study aims to evaluate and quantify the possible effect of psychological symptoms on healthy workers' quality of life (QOL). METHODS: The workers were recruited from a factory in south Taiwan. We assessed their psychological symptoms with a 5-item brief symptom rating scale (BSRS-5) and measured the QOL using the Taiwanese version of the World Health Organization Quality of Life (WHOQOL)-BREF. Multiple linear regression analysis was conducted to explore the association between the two tools after control of confounding by other predictors. RESULTS: A total of 1,080 workers, who attended a physical examination, completed questionnaires and informed consent forms. Scores on the BSRS-5 significantly predicted scores in each domain and items of the WHOQOL-BREF. The magnitude of psychological domain score seemed to be affected the most; every 1 point increase in BSRS-5 was associated with a 0.39 raw score (equivalent to 2.44 percentile) decrease in QOL. The sleep facet of WHOQOL appeared to have the highest association, followed by items of negative feelings, energy, and concentration. CONCLUSIONS: The BSRS-5 score is predictive for scores of all four domains and 26 items of the Taiwanese version of the WHOQOL-BREF for regular factory workers.

Shift work is associated with metabolic syndrome in male steel workers-the role of resistin and WBC count-related metabolic derangements.

AIMS: There is increasing evidence linking a shift work schedule with various adverse health effects. The present study aimed to examine the relationship between shift work and the metabolic syndrome (MetS) in male steel workers, and also the possible mechanism of shift work-related metabolic derangements. METHODS: A total of 1732 men aged 42 ± 8 years were enrolled in this cross-sectional study, including 862 day workers and 870 shift workers. Circulating levels of resistin were measured by ELISA using monoclonal specific antibodies. RESULTS: The shift workers had higher rates of MetS and its components (central obesity, hypertension, and hypertriglyceridemia) than the day workers. In multiple logistic regression analysis, shift work was independently associated with MetS. In further analysis, the shift workers had elevated circulating levels of resistin (13 ± 10 vs. 10 ± 7 ng/mL) and total white blood cell (WBC) count (6.865 ± 1.819 vs. 6.304 ± 1.547 109/L) than the day workers. In addition, both resistin level and total WBC count were significantly associated with shift work, MetS, and its components (body mass index, fasting glucose, triglyceride, and high-density lipoprotein-cholesterol levels), and plasma resistin levels were significantly associated with total WBC count (ß = 0.34, p < 0.0001). CONCLUSION: Shift work was independently associated with MetS in male steel workers. Resistin and WBC count were associated with shift work-related metabolic derangements.

The association between low levels of lead in blood and occupational noise-induced hearing loss in steel workers.

As the use of leaded gasoline has ceased in the last decade, background lead exposure has generally been reduced. The aim of this study was to examine the effect of low-level lead exposure on human hearing loss. This study was conducted in a steel plant and 412 workers were recruited from all over the plant. Personal information such as demographics and work history was obtained through a questionnaire. All subjects took part in an audiometric examination of hearing thresholds, for both ears, with air-conducted pure tones at frequencies of 500, 1000, 2000, 3000, 4000, 6000 and 8000 Hz. Subjects' blood samples were collected and analyzed for levels of manganese, copper, zinc, arsenic, cadmium and lead with inductive couple plasma-mass spectrometry. Meanwhile, noise levels in different working zones were determined using a sound level meter with A-weighting network. Only subjects with hearing loss difference of no more than 15 dB between both ears and had no congenital abnormalities were included in further data analysis. Lead was the only metal in blood found significantly correlated with hearing loss for most tested sound frequencies (p<0.05 to p<0.0001). After adjustment for age and noise level, the logistic regression model analysis indicated that elevated blood lead over 7 microg/dL was significantly associated with hearing loss at the sound frequencies of 3000 through 8000 Hz with odds ratios raging from 3.06 to 6.26 (p<0.05-p<0.005). We concluded that elevated blood lead at level below 10 microg/dL might enhance the noise-induced hearing loss. Future research needs to further explore the detailed mechanism.