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Which anthropometric measures best indicate type 2 diabetes among Russian, Somali and Kurdish origin migrants in
Natalia Skogberg1,2, Tiina Laatikainen3,4,5, Annamari Lundqvist3
1Department of Public Health, University of Helsinki, Helsinki, Finland.
Objectives:
To compare the performance of body mass index (BMI), waist-to-height ratio (WHtR), waist circumference (WC) and waist-to-hip ratio (WHR) in detecting type 2 diabetes among Russian, Somali and Kurdish (born in Iraq/Iran) origin migrants and Finns.
Design And Participants:
Cross-sectional study comparing health examination survey data of Russian, Somali and Kurdish origin migrants (n=917) aged 30-64 years who took part in the Migrant Health and Wellbeing Survey with the general Finnish population in the Health 2011 Survey (n=887). Participants were randomly selected from the National Population Register.
Setting:
Six cities in Finland, where a substantial majority of migrants live.
Outcome Measures:
Anthropometric measures included objectively measured BMI, WHtR, WC and WHR. Type 2 diabetes was defined based on self-report, laboratory measures of glycated haemoglobin and register data. Test performance was assessed using receiver operating characteristics curves, using area under the curve (AUC) as a measure of accuracy.
Results:
Among Finns, test performance was highest for WC (AUC=0.81, 95% CI 0.74 to 0.87) and WHtR (AUC=0.81, 95% CI 0.75 to 0.87). Test performance was similar for BMI (AUC=0.80, 95% CI 0.67 to 0.92), WC (AUC=0.79, 95% CI 0.67 to 0.91) and WHtR (AUC=0.70, 95% CI 0.66 to 0.93) among Russians. WC and WHtR had highest test performance also among Somali (AUC=0.74, 95% CI 0.64 to 0.84 for WC and AUC=0.75, 95% CI 0.65 to 0.85 for WHtR) and Kurds (AUC=0.71, 95% CI 0.61 to 0.81 for WC and AUC=0.70, 95% CI 0.59 to 0.80 for WHtR).Among migrants, WHR had the poorest test performance.
Conclusion:
WC and WHtR performed overall the best across all study groups, however, accuracy of detection was lower particularly among Somali and Kurds. Currently used diabetes risk assessment tools assume a strong association between anthropometrics and diabetes. These tools need to be validated among non-Western populations.
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