Dataset Information

A novel nonparametric approach for estimating cut-offs in continuous risk indicators with application to diabetes epidemiology.

ABSTRACT:

Background

Epidemiological and clinical studies, often including anthropometric measures, have established obesity as a major risk factor for the development of type 2 diabetes. Appropriate cut-off values for anthropometric parameters are necessary for prediction or decision purposes. The cut-off corresponding to the Youden-Index is often applied in epidemiology and biomedical literature for dichotomizing a continuous risk indicator.

Methods

Using data from a representative large multistage longitudinal epidemiological study in a primary care setting in Germany, this paper explores a novel approach for estimating optimal cut-offs of anthropomorphic parameters for predicting type 2 diabetes based on a discontinuity of a regression function in a nonparametric regression framework.

Results

The resulting cut-off corresponded to values obtained by the Youden Index (maximum of the sum of sensitivity and specificity, minus one), often considered the optimal cut-off in epidemiological and biomedical research. The nonparametric regression based estimator was compared to results obtained by the established methods of the Receiver Operating Characteristic plot in various simulation scenarios and based on bias and root mean square error, yielded excellent finite sample properties.

Conclusion

It is thus recommended that this nonparametric regression approach be considered as valuable alternative when a continuous indicator has to be dichotomized at the Youden Index for prediction or decision purposes.

SUBMITTER: Klotsche J

PROVIDER: S-EPMC2754490 | biostudies-literature | 2009 Sep

REPOSITORIES: biostudies-literature

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Publications

A novel nonparametric approach for estimating cut-offs in continuous risk indicators with application to diabetes epidemiology.

Klotsche Jens J Ferger Dietmar D Pieper Lars L Rehm Jürgen J Wittchen Hans-Ulrich HU

BMC medical research methodology 20090910

<h4>Background</h4>Epidemiological and clinical studies, often including anthropometric measures, have established obesity as a major risk factor for the development of type 2 diabetes. Appropriate cut-off values for anthropometric parameters are necessary for prediction or decision purposes. The cut-off corresponding to the Youden-Index is often applied in epidemiology and biomedical literature for dichotomizing a continuous risk indicator.<h4>Methods</h4>Using data from a representative large ...[more]

PMID: 19744332

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Project description:BackgroundCharacteristics of picky eaters of different weight status have not been sufficiently investigated. We used two newly developed screening cut-offs for picky eating in the Food fussiness (FF) subscale of the Child Eating Behavior Questionnaire (CEBQ) to investigate the prevalence and characteristics of picky eaters in preschool-aged children with thinness, normal weight, overweight or obesity.MethodsData for 1272 preschoolers (mean age 4.9 years) were analyzed. The parent-reported FF subscale ranges from 1 to 5, and two screening cut-offs were applied to classify children as picky eaters (3.0 and 3.33). Structural Equation Modeling was used to study associations with other factors in the CEBQ, the Child Feeding Questionnaire (CFQ) and the Lifestyle Behavior Checklist (LBC). Scores were compared separately for each weight status group.ResultsNearly half of the children were classified as moderate or severe picky eaters (cut-off 3.0) and 30% as severe (cut-off 3.33). For both cut-offs, prevalence was significantly lower in the obesity group. Still, one-third of children with obesity met the cut-off of 3.0 and 17% met the cut-off of 3.33. While picky eaters displayed similar patterns across weight status groups, some differences emerged. Food responsiveness was lower for picky eaters, but the difference was significant only among children with obesity. Slowness in eating was not as pronounced among picky eaters in the obesity group. In the overweight and obesity groups, parents of picky eaters did not report as high pressure to eat, as compared to the thinness or normal weight groups; in the obesity group, parents of picky eaters also perceived their children's weight as lower. In all weight status groups, parents of picky eaters were more likely to report their children had too much screen time, complained about physical activity, and expressed negative affect toward food.ConclusionsPicky eating was less common but still prevalent among children with obesity. Future studies should investigate the potential influence of picky eating on childhood overweight and obesity. Moreover, as children with picky eating display higher emotional sensitivity, further research is needed to understand how to create positive eating environments particularly for children with picky eating and obesity.

Dataset Information

A novel nonparametric approach for estimating cut-offs in continuous risk indicators with application to diabetes epidemiology.

Background

Methods

Results

Conclusion

Publications

A novel nonparametric approach for estimating cut-offs in continuous risk indicators with application to diabetes epidemiology.

Similar Datasets

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