Shift work is associated with an increased risk of type 2 diabetes and elevated RBP4 level: cross sectional analysis from the OHSPIW cohort study

BACKGROUND

Shift work, with its growing prevalence globally, disrupts the body's inherent circadian rhythm. This disruption may escalate the risk of chronic diseasesxacerbate chronic disease risk by dysregulating physiological, behavioral, and psychosocial pathways. This study aimed to evaluate the effect of shift work on type 2 diabetes (T2DM) and Retinol binding protein 4 (RBP4) level.

METHODS

The current study employed a multi-stage stratified cluster sampling technique, examining 1499 oilfield workers from the OHSPIW cohort who participated in occupational health assessments between March 2017 and June 2018.The evaluation involved shift work, sleep quality, T2DM status with questionnaires and plasma RBP4 levels in blood samples. Statistical analysis includes, Chi-square tests, t-tests, multivariate logistic regression analyses, and multivariate linear mixed models.

RESULTS

The prevalence rate of T2DM in shift workers (6.56%) was significantly higher than in day workers (4.21%) (OR = 1.60, 95% CI: 1.01-2.53), with no significant difference found in the family history of diabetes, hypertension, or other chronic heart diseases (P = 0.378). The shift worker (6.89 ± 3.35) also exhibited distinctly higher PSQI scores than day workers (5.99 ± 2.87) (P < 0.001). Adjusting the age, gender, BMI, family income, tobacco smoking, alcohol drinking and PSQI, hailed shift work as a risk factor for T2DM (OR = 1.91, 95% CI: 1.17-3.14). The pairwise comparison revealed significant differences in RBP4 levels across different groups: shift and non-shift workers both with and without T2DM (P < 0.001). The RBP4 level of the shift group without T2DM was higher than the non-shift group without T2DM (P < 0.05). The levels of RBP4 level in shift and non-shift groups with T2DM was higher than those without T2DM (P < 0.05). The multivariate linear mixed model showed that when age, gender, BMI, diabetes, PSQI, family income, smoking and drinking remained unchanged, the RBP4 level of the shift workers increased by an average of 9.51 μg/mL compared with the day workers.

CONCLUSIONS

Shift work is associated with an increased risk of T2DM and high levels of RBP4. Follow-up of RBP4 could facilitateearly detection of T2DM among shift workers.

Association of lipid accumulation product and visceral adiposity index with the risk of hypertension among oil workers in Xinjiang, China

Background

To explore the relationship between lipid accumulation product (LAP) and visceral adiposity index (VAI) and hypertension in oil workers and to evaluate the predictive value of hypertension by gender.

Methods

A sample of 2,312 workers aged 18-60 years old with more than one year of service were selected by a whole-group random sampling method in six oil field bases in Karamay City, Xinjiang. Logistic regression combined with restricted cubic spline model was used to analyze the risk of hypertension in different LAP and VAI. The receiver operator characteristic curve (ROC) with different sex LAP and VAI predicting the risk of hypertension were drawn.

Results

(1) There were significant differences in age, smoking, alcohol consumption, hypertension, BMI, WC, WHtR, SBP, DBP, TC, TG, HDL, LDL, FPG and Scr among different gender groups (P < 0.001).The prevalence of hypertension was 10.1%, with 13.9% in men and 3.6% in women. The prevalence of hypertension with different individual characteristics was statistically significant (P < 0.05). (2) Lipid accumulation product and visceral adiposity index were positively associated with hypertension (P < 0.001). The risk of hypertension may increase with the increase of lipid accumulation product and visceral adiposity index. After adjusting for age, sex, BMI, Scr, FPG and other factors, the risk of hypertension in the fourth quartile was (OR = 5.69, 95% CI [2.72-11.8]) and (OR = 3.56, 95% CI [2.03-6.23]) compared with the first quartile of lipid accumulation product and visceral adiposity index. (3) ROC results showed: AUC values of 0.658 (95% CI [0.619-0.696]), 0.614 (95% CI [0.574-0.654]), 0.661 (95% CI [0.620-0.703]) and critical values of 43.25, 1.58, 0.13 for LAP, VAI and combined indicators in men; the AUC values of LAP, VAI and combined indicators for women were 0.787 (95% CI [0.710-0.865]), 0.732 (95% CI [0.640-0.825]), 0.792 (95% CI [0.719-0.864]) and the critical values were 35.73, 1.76 and 0.03. Restricted cubic splines showed a nonlinear dose-response relationship between LAP, VAI, and risk of hypertension prevalence (P < 0.01 for overall trend and P < 0.01 for nonlinearity).

Conclusions

Lipid accumulation product and visceral adiposity index may be risk factors for hypertension in oil workers. LAP and VAI have certain predictive value for hypertension.

Association of sleep duration and sleep quality with hypertension in oil workers in Xinjiang

Objective

The aim of this study is to explore sleep status and hypertension among oil workers in Xinjiang, China. It may provide new ideas and basis for the precise prevention and treatment of hypertension in occupational population.

Methods

Sleep status and hypertension were investigated in 3,040 workers by a multi-stage cluster sampling method in six oil field bases in Karamay City, Xinjiang. The Pittsburgh Sleep Quality Index was used to evaluate the sleep status of workers. Logistic regression was used to analyze the relationship between sleep duration and sleep quality, and hypertension. Stratified analysis was also performed.

Results

Our results show: 1. Insufficient sleep duration (OR = 1.51, 95% CI [1.19–1.90]) and poor sleep quality (OR = 1.78, 95% CI [1.33–2.38] were positively associated with hypertension. 2. Stratified analysis indicated insufficient sleep duration was associated with increased risk of hypertension in females (OR = 1.54, 95% CI [1.16–2.04]) than males (OR = 1.49, 95% CI [1.00–2.23]), and the risk of hypertension in the group <30 years old (OR = 9.03, 95% CI [2.32–35.15]) was higher than that in the group of 30–45 years old (OR = 1.59, 95% CI [1.14–2.20]). However, in the group > 45 years old, sleeping > 8 h was associated with increased risk of hypertension (OR = 3.36, 95% CI [1.42–7.91]). Oil workers doing shift work had a higher risk of hypertension (OR = 1.55, 95% CI [1.16–2.07]) to no shift work (OR = 1.48, 95% CI [1.02–2.15]). The risk of hypertension in the group with < 10 years of service (OR = 4.08, 95% CI [1.92–8.83]) was higher than that in the group with length of service of 10–20 years (OR = 2.79, 95% CI [1.59–4.86]). Poor sleep quality was associated with risk for hypertension in females (OR = 1.78, 95% CI [1.26–2.49]), those doing shift work (OR = 1.70, 95% CI [1.17–2.47]), those with length of service of > 20 years (OR = 1.64, 95% CI [1.18–2.27]). The risk of hypertension in the group 30–45 years old is higher than that in the group > 45 years old (OR_{30–45 years old} = 1.71, 95% CI [1.10–2.66]; OR > 45 years old = 1.60, 95% CI [1.09–2.34]).

Conclusion

Insufficient sleep duration and poor sleep quality are the potential factors affecting hypertension in Xinjiang oil workers.

Development and internal validation of risk prediction model of metabolic syndrome in oil workers

Background

The prevalence of metabolic syndrome continues to rise sharply worldwide, seriously threatening people’s health. The optimal model can be used to identify people at high risk of metabolic syndrome as early as possible, to predict their risk, and to persuade them to change their adverse lifestyle so as to slow down and reduce the incidence of metabolic syndrome.

Methods

Design existing circumstances research. A total of 1468 workers from an oil company who participated in occupational health physical examination from April 2017 to October 2018 were included in this study. We established the Logistic regression model, the random forest model and the convolutional neural network model, and compared the prediction performance of the models according to the F1 score, sensitivity, accuracy and other indicators of the three models.

Results

The results showed that the accuracy of the three models was 82.49,95.98 and 92.03%, the sensitivity was 87.94,95.52 and 90.59%, the specificity was 74.54, 96.65 and 94.14%, the F1 score was 0.86,0.97 and 0.93, and the area under ROC curve was 0.88,0.96 and 0.92, respectively. The Brier score of the three models was 0.15, 0.08 and 0.12, Observed-expected ratio was 0.83, 0.97 and 1.13, and the Integrated Calibration Index was 0.075,0.073 and 0.074, respectively, and explained how the random forest model was used for individual disease risk score.

Conclusions

The study showed that the prediction performance of random forest model is better than other models, and the model has higher application value, which can better predict the risk of metabolic syndrome in oil workers, and provide corresponding theoretical basis for the health management of oil workers.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-020-09921-w.