title: Anthropometric indexes in the prediction of type 2 diabetes mellitus, hypertension and dyslipidaemia in a Mexican population.
abstract: OBJECTIVE
  To determine values of simple anthropometric measurements which are associated with the presence of type 2 diabetes mellitus, hypertension and dyslipidaemia and to assess anthropometric cut-off values for predicting the likelihood of these chronic conditions in a Mexican population.
  
  
  METHODS
  The data were obtained from PRIT (Prevalence of Cardiovascular Risk Factors in General Hospital Workers) surveys from 1994 to 2000 adjusted to the structure of the overall Mexican population.
  
  
  METHODS
  A total of 2426 men and 5939 women aged 38.99+/-7.11 and 39.11+/-14.25 y, respectively.
  
  
  METHODS
  The optimal sensitivity and specificity of using various cut-off values of BMI (body mass index), WHR (waist-to-hip ratio), WC (waist circumference) and WTH (waist-to-height ratio) to predict type 2 diabetes mellitus (DM), hypertension (HT), or dyslipidaemia were examined by receiver operating characteristic curve (ROC) analysis. The likelihood ratios for having diabetes, hypertension and dyslipidaemia in subjects with various cut-off values of BMI, WHR, WC and WTH were calculated. Multiple step-wise logistic regression analysis was used to examine the independent relationship between the anthropometric indexes, age and smoking, and the odds ratio of having chronic conditions.
  
  
  RESULTS
  The BMI cut-off to predict DM, HT, or dyslipidaemia varied from 25.2 to 26.6 kg/m2 in both men and women. The optimal WC cut-offs were 90 cm in men and 85 cm in women. The WHR cut-off was about 0.90 in men and 0.85 in women, and the optimal WTH cut-off was 52.5 in men and varied from 53 to 53.5 in women. The cut-off levels for WC, WHR and WTH corresponded to the inflexion points in the likelihood ratio graphs. In the case of BMI likelihood ratio graphs, we found a significant increase in the risk for chronic conditions from 22 to 23 BMI levels in both genders. Logistic regression analyses disclosed that only BMI and age were included in all the models as well as the influence of smoking in DM and dyslipidaemia in men.
  
  
  CONCLUSIONS
  Although these results may not be readily applied to the rest of the Mexican population or to other Hispanic populations, they point to the necessity of similar studies with large randomized samples to find the cut-off levels for chronic conditions in different populations.
authors.affiliation: Servicio de Endocrinología del Hospital General de México, Organo Descentralizado, Mexico City, Mexico. arturoberber@aol.com
authors.forename: A
authors.initials: A
authors.lastname: Berber
authors.forename: R
authors.initials: R
authors.lastname: Gómez-Santos
authors.forename: G
authors.initials: G
authors.lastname: Fanghänel
authors.forename: L
authors.initials: L
authors.lastname: Sánchez-Reyes
mesh_terms: D000328:Adult; D000367:Age Factors; D000886:Anthropometry; D001824:Body Constitution; D002318:Cardiovascular Diseases / Q000209:etiology; D003924:Diabetes Mellitus, Type 2 / Q000175:diagnosis* / Q000453:epidemiology / Q000209:etiology; D005260:Female; D006306:Health Surveys; D006801:Humans; D006949:Hyperlipidemias / Q000175:diagnosis* / Q000453:epidemiology / Q000209:etiology; D006973:Hypertension / Q000175:diagnosis* / Q000453:epidemiology / Q000209:etiology; D016013:Likelihood Functions; D008297:Male; D008800:Mexico / Q000453:epidemiology; D009765:Obesity / Q000150:complications* / Q000453:epidemiology; D016017:Odds Ratio; D012016:Reference Values; D012307:Risk Factors; D012680:Sensitivity and Specificity; D012907:Smoking