title: [Estimation on the risk of 5-years obesity development among adults aged 30 - 59, based on the Taiwan MJ Health-checkup Database].
abstract: OBJECTIVE
  This study aimed to provide an epidemiological modeling in evaluating the risk of developing obesity within 5 years in Taiwan population aged 30 - 59 years.
  
  
  METHODS
  After excluding 918 individuals who were observed at baseline, a cohort of 14 167 non-obesity subjects aged 30 - 59 years in the initial year during 1998 - 2006, was formed to derive a Risk Score which could predict the incident obesity (IO). Multivariate logistic regression was used to derive the risk functions, using the check-up center (Taipei training cohort, n = 8104) of the overall cohort. Rules based on these risk functions were evaluated in the left three centers (testing cohort, n = 6063). Risk functions were produced to detect the IO on a training sample using the multivariate logistic regression models. Starting with variables that could predict the IO through univariate models, we constructed multivariable logistic regression models in a stepwise manner which eventually could include all the variables. We evaluated the predictability of the model by the area under the receiver-operating characteristic (ROC) curve (AUC) and to testify its diagnostic property on the testing sample. Once the final model was defined, the next step was to establish rules to characterize 4 different degrees of risk based on the cut points of these probabilities after transforming into normal distribution by log-transformation.
  
  
  RESULTS
  At baseline, the range of the proportion of normal weight, overweight and obesity were 50.00% - 60.00%, 26.47% - 31.11% and 5.76% - 7.24% respectively in four check-up centers of Taiwan. After excluding 918 obesity individuals at baseline, we ascertained 386 (2.73%, 386/14 167) cases having IO and 2.66% - 2.91% of them having centered obesity in the four check-up centers respectively. Final multivariable logistic regression model would include five risk factors: sex, age, history of diabetes, weight deduction ≥ 4 kg within 3 months and waist circumference. The area under the ROC curve (AUC) was 0.898 (95%CI, 0.884 - 0.912) that could predict the development of obesity within 5 years. The curve also had adequate performance in testing the sample [AUC = 0.881 (95%CI, 0.862 - 0.900)]. After labeling the four risk degrees, 16.0% and 2.9% of the total subjects were in the mediate and high risk populations respectively and were 7.8 and 16.6 times higher, when comparing with the population at risk in general.
  
  
  CONCLUSIONS
  The predictability and reliability of our obesity risk score model, derived based on Taiwan MJ Longitudinal Health-checkup-based Population Database, were relatively satisfactory, with its simple and practicable predictive variables and the risk degree form. This model could help individuals to self assess the situation of risk on obesity and could also guide the community caretakers to monitor the trend of obesity development.
authors.affiliation: Department of Epidemiology and Biostatistics, School of Public Health; Department of Pharmacy Administration and Clinical Pharmacy, School of Pharmaceutical, Peking University, Beijing 100191, China; Department of Preventive Medicine, Shihezi University School of Medicine.
authors.forename: Feng
authors.initials: F
authors.lastname: Sun
authors.forename: Qing-mei
authors.initials: QM
authors.lastname: Tao
authors.forename: Qiu-shan
authors.initials: QS
authors.lastname: Tao
authors.forename: Xing-hua
authors.initials: XH
authors.lastname: Yang
authors.forename: Chun-keng
authors.initials: CK
authors.lastname: Cao
authors.forename: Si-yan
authors.initials: SY
authors.lastname: Zhan
mesh_terms: D000328:Adult; D019540:Area Under Curve; D005260:Female; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D009765:Obesity / Q000453:epidemiology*; D010808:Physical Examination; D012372:ROC Curve; D018570:Risk Assessment; D012307:Risk Factors; D013624:Taiwan / Q000453:epidemiology