title: The role of anthropometric and other predictors for diabetes among urban Tanzanians with tuberculosis.
abstract: BACKGROUND
  As diabetes impairs tuberculosis (TB) treatment outcomes, it is essential to identify diabetes among TB patients. While little is known about predictors of diabetes among healthy individuals in Africa, predictors among TB patients are almost non-existent.
  
  
  OBJECTIVE
  To  assess potential predictors for diabetes among newly diagnosed pulmonary TB patients in Tanzania.
  
  
  METHODS
  TB patients were tested for diabetes using an oral glucose tolerance test, demographic information was collected and anthropometric measurements taken. The association between diabetes  and possible predictors were examined using logistic regression analyses.
  
  
  RESULTS
  Of 1205 TB patients, 16.4% (n = 197) had diabetes, 9.0% (n = 108) were aged ≥55 years, 3.3% (n = 40) were overweight (body mass index [BMI] ≥ 25 kg/m(2)) and 12.7% (n  = 152) severely underweight (BMI < 16 kg/m(2)). Diabetes was most prevalent in the 45-55 year age group, and increasing weight, BMI and waist circumference were associated with diabetes. Severe underweight (BMI < 16 kg/m(2)) among male TB patients (sex-BMI  interaction, P = 0.02) was associated with diabetes (OR 2.52, P = 0.004).
  
  
  CONCLUSIONS
  Diabetes is a common comorbidity among TB patients. Although diabetes was associated with obesity and was more prevalent among the middle-aged, the majority of TB patients with diabetes comorbidity  were young and lean. With diabetes as a major risk factor for TB, and with the lack of strong predictors for diabetes, universal diabetes screening should be implemented in the TB programme.
authors.affiliation: Department of Human Nutrition, University of Copenhagen, Frederiksberg, Denmark. dfa@life.ku.dk
authors.forename: D
authors.initials: D
authors.lastname: Faurholt-Jepsen
authors.forename: N
authors.initials: N
authors.lastname: Range
authors.forename: G
authors.initials: G
authors.lastname: PrayGod
authors.forename: K
authors.initials: K
authors.lastname: Jeremiah
authors.forename: M
authors.initials: M
authors.lastname: Faurholt-Jepsen
authors.forename: M G
authors.initials: MG
authors.lastname: Aabye
authors.forename: J
authors.initials: J
authors.lastname: Changalucha
authors.forename: D L
authors.initials: DL
authors.lastname: Christensen
authors.forename: D R
authors.initials: DR
authors.lastname: Witte
authors.forename: A B
authors.initials: AB
authors.lastname: Andersen
authors.forename: H
authors.initials: H
authors.lastname: Friis
mesh_terms: D000328:Adult; D015992:Body Mass Index; D016009:Chi-Square Distribution; D015897:Comorbidity; D003920:Diabetes Mellitus / Q000175:diagnosis / Q000453:epidemiology*; D005260:Female; D005951:Glucose Tolerance Test; D006801:Humans; D016014:Linear Models; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D016017:Odds Ratio; D050177:Overweight / Q000175:diagnosis / Q000453:epidemiology*; D011237:Predictive Value of Tests; D015995:Prevalence; D012307:Risk Factors; D012737:Sex Factors; D013636:Tanzania / Q000453:epidemiology; D013851:Thinness / Q000175:diagnosis / Q000453:epidemiology*; D014397:Tuberculosis, Pulmonary / Q000175:diagnosis / Q000453:epidemiology*; D014504:Urban Health; D055105:Waist Circumference; D015430:Weight Gain; D055815:Young Adult