Prevalence and lifestyle-associated risk factors of metabolic syndrome among commercial motor vehicle drivers in a metropolitan city in Ghana

Introduction

commercial motor vehicle drivers are at risk of metabolic syndrome (MetS) due to the nature of their work as they tend to go to work early, work for more hours, have irregular dietary habits and patterns, have little sleep and live sedentary lifestyle. The study sought to determine the prevalence and lifestyle-related risk factors of MetS among commercial taxi drivers around Kwame Nkrumah University of Science and Technology (KNUST) campus, in the Kumasi metropolis, Ghana.

Methods

a cross-sectional survey was conducted among 100 commercial taxi drivers in 3 selected taxi ranks around KNUST campus. Fasting blood lipid and fasting blood glucose levels, blood pressure and anthropometric characteristics were determined using WHO and NCEP-ATP III criteria. Lifestyle-related risk factors of MetS were assessed using a semi-structured questionnaire and dietary pattern was assessed using food frequency questionnaire. Bivariate analysis and linear correlation were used to determine the relationship between lifestyle practices and MetS.

Results

the prevalence of diabetes, high blood pressure, dyslipidemia, overweight and obesity were 12%, 63%, 40%, 32% and 13% respectively. The prevalence of MetS was 5% according to NCEP-ATP III (2005) criteria. The lifestyle behaviours of the drivers were, alcohol intake, irregular dietary pattern, long working hours, lack of exercise and tiredness due to driving. Tobacco use (R = 0.405, p = 0.041) and time of supper (R = 0.931, p = 0.047) were related with MetS among the participants.

Conclusion

though prevalence of MetS (5%) was low among the drivers, the need for intervention to promote positive lifestyle change and curb the high prevalence of overweight/obesity, diabetes, high blood pressure and dyslipidemia is necessary to improve the health of the drivers and the safety of passengers.

Screening for Obstructive Sleep Apnea in Commercial Drivers Using EKG-Derived Respiratory Power Index

STUDY OBJECTIVES

Obstructive sleep apnea (OSA) is common in commercial motor vehicle operators (CMVOs); however, polysomnography (PSG), the gold-standard diagnostic test, is expensive and inconvenient for screening. OSA is associated with changes in heart rate and voltage on electrocardiography (EKG). We evaluated the utility of EKG parameters in identifying CMVOs at greater risk for sleepiness-related crashes (apnea-hypopnea index [AHI] ≥ 30 events/h).

METHODS

In this prospective study of CMVOs, we performed EKGs with concurrent PSG, and calculated the respiratory power index (RPI) on EKG, a surrogate for AHI calculated from PSG. We evaluated the utility of two-stage predictive models using simple clinical measures (age, body mass index [BMI], neck circumference, Epworth Sleepiness Scale score, and the Multi-Variable Apnea Prediction [MVAP] score) in the first stage, followed by RPI in a subset as the second-stage. We assessed area under the receiver operating characteristic curve (AUC), sensitivity, and negative posttest probability (NPTP) for this two-stage approach and for RPI alone.

RESULTS

The best-performing model used the MVAP, which combines BMI, age, and sex with three OSA symptoms, in the first stage, followed by RPI in the second. The model yielded an estimated (95% confidence interval) AUC of 0.883 (0.767-0.924), sensitivity of 0.917 (0.706-0.962), and NPTP of 0.034 (0.015-0.133). Predictive characteristics were similar using a model with only BMI as the first-stage screen.

CONCLUSIONS

A two-stage model that combines BMI or the MVAP score in the first stage, with EKG in the second, had robust discriminatory power to identify severe OSA in CMVOs.