Population levels of BMI (HLBMI) impact IFs forecasts of adult (over 30 years) mortality related to cardiovascular disease and diabetes.  Both the distal driver and full model formulations are initialized using a multiplicative shift factor to match historic data; these shift factors are kept constant over time.  Given the lack of historical data, all regressions were created using 2005 estimates.  

Full model formulations for females and males, respectively, use calories per capita (CLPC) as the driver. The parameter hlbmim can be used to modify the result:

Distal driver formulations are based on GDP per capita at PPP (GDPPCP) and years of formal education for adults 25 and older (EDYRSAG25):

In order to use the PAF methodology, we assume a normal distribution of BMI around the mean with a standard deviation of 10% of the mean.  BMI has a normal distribution where we forecast the mean, and assume a standard deviation of 10% of the mean.

Another Help topic describes the use of BMI in forecasting diabetes-related mortality.  For cardiovascular disease, the relative risk of mortality increases with every unit of BMI.  The calculation of relative risk uses a continuous formulation based on BMI level:

The constant (CONSTANT) depends on age category: 1.14 for 30-44 year olds, 1.09 for 45-59 year olds, 1.09 for 60-69 year olds, and 1.05 for 70-79 year olds. ^[1]

From BMI it is possible also to compute the portion of a population that is obese (HLOBESITY).  The model does that as a function of HLBMI by using separate table functions for females (BMI Versus Female Obesity % (CRA) Quad) and males (BMI Versus Male) Obesity % (CRA) Quad).  The parameter hlobesitym can be used for modification in scenario analysis.