Optimal cut-off for obesity and markers of metabolic syndrome for Ethiopian adults

Background

Metabolic syndrome (MetS) is defined as the presence of central obesity plus any two of the following markers: high triglycerides (>?150 mg/dl), low high density lipoprotein (HDL) cholesterol <?40 mg/dl in men and?<?50 mg/dl in women, hypertension (blood pressure?>?130/85 mmHg or use of antihypertensive medication), high fasting blood glucose (>?100 mg/dl or use of treatment for diabetes mellitus). Since recently, metabolic syndrome and obesity have become emerging problems of both low and middle income countries, although they have been the leading cause of morbidity and mortality in high income countries for the past decades. It has been indicated that the international anthropometric cut-off for detecting obesity is not appropriate for Ethiopians. This study developed optimal cut off values for anthropometric indicators of obesity and markers of metabolic syndrome for Ethiopian adults to enhance preventive interventions.

Methods

A total of 704 employees of Jimma University were randomly selected using their payroll as a sampling frame. Data on socio-demographic, anthropometry, clinical and blood samples were collected from February to April 2015. Receiver Operating Characteristic Curve analyses were used to determine optimal anthropometric cut-off values for obesity and markers of the metabolic syndrome. WHO indicators of obesity based on body fat percent (>?25% for males and?>?35% for females) were used as binary classifiers for developing anthropometric cut-offs. Optimal cut-off values were presented using sensitivity, specificity and area under the curve.

Results

The optimal cut-off for obesity using body mass index was 22.2 k/m² for males and 24.5 kg/m² for females. Similarly, the optimal waist circumference cut-off for obesity was 83.7 cm for males and 78.0 cm for females. The cut-off values for detecting obesity using waist to hip ratio and waist to height ratio were: WHR (0.88) and WHtR (0.49) for males, while they were 0.82 and 0.50 for females, respectively. Anthropometric cut-off values for markers of metabolic syndrome were lower compared to the international values. For females, the optimal BMI cut-offs for metabolic syndrome markers ranged from 24.8 kg/m² (triglycerides) to 26.8 kg/m² (fasting blood sugar). For WC the optimal cut-off ranged from of 82.1 cm (triglyceride) to 96.0 cm(HDL); while for WHtR the optimal values varied from 0.47(HDL) to 0.56(fasting blood sugar). Likewise, the optimal cut-offs of WHR for markers of metabolic syndrome ranged from 0.78(fasting blood sugar) to 0.89(HDL and blood pressure). For males, the optimal BMI cut-offs for metabolic syndrome markers ranged from 21.0 kg/m² (HDL) to 23.5 kg/m² (blood pressure). For WC, the optimal cut-off ranged from 85.3 cm (triglyceride) to 96.0 cm(fasting blood sugar); while for WHtR the optimal values varied from 0.47(BP, FBS and HDL) to 0.53(Triglyceride). Similarly, the optimal cut-offs of WHR form markers of metabolic syndrome ranged from 0.86(blood pressure) to 0.95(fasting blood sugar).

Conclusion

The optimal anthropometric cut-offs for obesity and markers of metabolic syndrome in Ethiopian adults are lower than the international values. The findings imply that the international cut-off for WC, WHtR, WHR and BMI underestimate obesity and metabolic syndrome markers among Ethiopian adults, which should be considered in developing intervention strategies. It is recommended to use the new cut-offs for public health interventions to curb the increasing magnitude of obesity and associated metabolic syndrome and diet related non-communicable diseases in Ethiopia.

     

Effects of excessive speeding and falling asleep while driving on crash injury severity in Ethiopia: A generalized ordered logit model analysis

The severity of injury from vehicle crash is a result of a complex interaction of factors related to drivers’ behavior, vehicle characteristics, road geometric and environmental conditions. Knowing to what extent each factor contributes to the severity of an injury is very important. The objective of the study was to assess factors that contribute to crash injury severity in Ethiopia. Data was collected from June 2012 to July 2013 on one of the main and busiest highway of Ethiopia, which extends from the capital Addis Ababa to Hawassa. During the study period a total of 819 road crashes was recorded and investigated by trained crash detectors. A generalized ordered logit/partial proportional odds model was used to examine factors that might influence the severity of crash injury. Model estimation result suggested that, alcohol use (Coef. = 0.5565; p-value = 0.017), falling asleep while driving (Coef. = 1.3102; p-value = 0.000), driving at night time in the absence of street light (Coef. = 0.3920; p-value = 0.033), rainfall (Coef. = 0.9164; p-value = 0.000) and being a minibus or vans (Coef. = 0.5065; p-value = 0.013) were found to be increased crash injury severity. On the other hand, speeding was identified to have varying coefficients for different injury levels, its highest effects on sever and fatal crashes. In this study risky driving behaviors (speeding, alcohol use and sleep/fatigue) were a powerful predictor of crash injury severity. Therefore, better driver licensing and road safety awareness campaign complimented with strict police enforcement can play a pivotal role to improve road safety. Further effort needed as well to monitor speed control strategies like; using the radar control and physical speed restraint measures (i.e., rumble strips).