Estimation on the risk of 5-years obesity development among adults aged 30-59, based on the Taiwan MJ Health-checkup Database
10.3760/cma.j.issn.0254-6450.2012.09.010
- VernacularTitle:台湾地区30～59岁健康体检人群肥胖5年发病风险预测模型
- Author:
Feng SUN
1
,
2
,
3
;
Qing-Mei TAO
;
Qiu-Shan TAO
;
Xing-Hua YANG
;
Chun-Keng CAO
;
Si-Yan ZHAN
Author Information
1. 100191,北京大学公共卫生学院流行病与卫生统计学系
2. 100191,北京大学公共卫生学院药学院药事管理与临床药学系
3. 新疆石河子大学医学院预防医学系
- Keywords:
Obesity;
Risk predictive model;
Longitudinal data
- From:
Chinese Journal of Epidemiology
2012;33(9):921-925
- CountryChina
- Language:Chinese
-
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 obesitive 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 4different 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 tour 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 respectivcly.Final multivariable logistic regression model would include five risk lactors: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.Conclusion 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.
