title: Adapting existing diabetes risk scores for an Asian population: a risk score for detecting undiagnosed diabetes in the Mongolian population.
abstract: BACKGROUND
  Most of the commonly used diabetes mellitus screening tools and risk scores have been developed with American or European populations in mind. Their applicability, therefore, to low and middle-income countries remains unquantified. Simultaneously, low and middle-income countries including Mongolia are currently witnessing rising diabetes prevalence. This research aims to develop and validate a diabetes risk score for the screening of undiagnosed type 2 diabetes mellitus in the Mongolian adult population.
  
  
  METHODS
  Blood glucose measurements from 1018 Mongolians, as well as information on demography and risk factors prevalence was drawn from 2009 STEPS data. Existing risk scores were applied, measuring sensitivity using area under ROC-curves. Logistic regression models were used to identify additional independent predictors for undiagnosed diabetes. Finally, a new risk score was developed and Hosmer-Lemeshow tests were used to evaluate the agreement between the observed and predicted prevalence.
  
  
  RESULTS
  The performance of existing risk scores to identify undiagnosed diabetes was moderate; with the area under ROC curves between 61-64 %. In addition to well-established risk factors, three new independent predictors for undiagnosed diabetes were identified. Incorporating these into a new risk score, the area under ROC curves increased to 77 % (95 % CI 71 %-82 %).
  
  
  CONCLUSIONS
  Existing European or American diabetes risk tools cannot be adopted in Asian countries without prior validation in the specific population. With this in mind, a low-cost, reliable screening tool for undiagnosed diabetes was developed and internally validated for Mongolians. The potential for cost and morbidity savings could be significant.
authors.affiliation: Public Health Institute, Ministry of Health, Ulaanbaatar, Mongolia. otgon_phi@hotmail.com.
authors.forename: Otgontuya
authors.initials: O
authors.lastname: Dugee
authors.affiliation: Public Health Institute, Ministry of Health, Ulaanbaatar, Mongolia. jobileg@gmail.com.
authors.forename: Oyunbileg
authors.initials: O
authors.lastname: Janchiv
authors.affiliation: Department of Health, National Institute for Health and Welfare (THL), Helsinki, Finland. pekka.jousilahti@thl.fi.
authors.forename: Pekka
authors.initials: P
authors.lastname: Jousilahti
authors.affiliation: Public Health Institute, Ministry of Health, Ulaanbaatar, Mongolia. ariunaa_s2004@yahoo.com.
authors.forename: Ariuntuya
authors.initials: A
authors.lastname: Sakhiya
authors.affiliation: Public Health Institute, Ministry of Health, Ulaanbaatar, Mongolia. p_enkhee2001@yahoo.com.
authors.forename: Enkhtuya
authors.initials: E
authors.lastname: Palam
authors.affiliation: Department of Epidemiology, School of Health Sciences, University of Tampere, Tampere, Finland. Pekka.Nuorti@uta.fi.
authors.forename: J Pekka
authors.initials: JP
authors.lastname: Nuorti
authors.affiliation: Department of Health, National Institute for Health and Welfare (THL), Helsinki, Finland. markku.peltonen@thl.fi.
authors.forename: Markku
authors.initials: M
authors.lastname: Peltonen
mesh_terms: D000328:Adult; D000368:Aged; D001208:Asia; D044466:Asian People / Q000706:statistics & numerical data; D003430:Cross-Sectional Studies; D003924:Diabetes Mellitus, Type 2 / Q000453:epidemiology*; D005260:Female; D006801:Humans; D008297:Male; D008403:Mass Screening; D008875:Middle Aged; D008986:Mongolia / Q000453:epidemiology; D015995:Prevalence; D012372:ROC Curve; D018570:Risk Assessment; D012307:Risk Factors