Modeling and calibration for exposure to time-varying, modifiable risk factors: the example of smoking behavior in India.

ABSTRACT:

Background

Risk factors increase the incidence and severity of chronic disease. To examine future trends and develop policies addressing chronic diseases, it is important to capture the relationship between exposure and disease development, which is challenging given limited data.

Objective

To develop parsimonious risk factor models embeddable in chronic disease models, which are useful when longitudinal data are unavailable.

Design

The model structures encode relevant features of risk factors (e.g., time-varying, modifiable) and can be embedded in chronic disease models. Calibration captures time-varying exposures for the risk factor models using available cross-sectional data. We illustrate feasibility with the policy-relevant example of smoking in India.

Methods

SUBMITTER: Goldhaber-Fiebert JD 

PROVIDER: S-EPMC4115057 | biostudies-literature | 2015 Feb

REPOSITORIES: biostudies-literature