Spatially Predicting Disease: An Application of the California Public Health Assessment Model (CPHAM) to Madison, Wisconsin’s Regional Transportation Plan

In 2016, the California Public Health Assessment Model (CPHAM) was run outside of California for the first time in preparation for Madison, Wisconsin’s 2050 Regional Transportation Plan. To confirm CPHAM was appropriate in the Madison context, the demographic, built environment, and baseline health conditions found in Dane County, Wisconsin were compared to data from which CPHAM was built. With few exceptions, conditions found in Madison were within the variation found within the 30 California county-area that is the basis for CPHAM predictive equations.

CPHAM was used to predict physical activity, body mass index, and health outcomes (type 2 diabetes, hypertension, and cardiovascular disease) for baseline conditions in Madison. Baseline predictions were compared to known prevalence rates from national sources (National Household Travel Survey; National Behavior Risk Factors Surveillance Survey) and local sources (PHINEX data). CPHAM estimated adult BMI and obesity rates were within 10% of PHINEX data for Dane County, and hypertension and cardiovascular disease prevalence were within 10-25%. CPHAM under predicted diabetes rates: approximately half that of known senior rates and one third that of adult rates. This local data was used to calibrate CPHAM equations to match the central tendency of the predicted values to known surveillance data at baseline.

The PHINEX data provided a unique opportunity for a validation exercise for CPHAM calibrated diabetes rates – the health outcome that performed least well without calibration. Unlike the national surveillance survey data that has insufficient sample size or is not available at small geographies, PHINEX data for type 2 diabetes was available at the block group level for both adults and seniors. Comparing the CPHAM predicted block group rates (upper right figure) to known rates demonstrated that CPHAM accurately predicts the spatial distribution of disease. Over predictions tended to occur in exurban-rural areas (lower right figure) while under predictions were more likely closer to the city.

Table 1. Summary Statistics of Block Group Error (Difference between CPHAM Calibrated Predicted and Reference Values) for Type 2 Diabetes

ErrorStat-istic

Block Group Comparison 1:

Adults 18-64(CPHAM Calibrated Predicted rates –

PHINEX rates)

Block Group Comparison 2:Seniors 65+

(CPHAM Calibrated Predicted rates –

PHINEX rates)

Ave 0.4% -0.4%Med 0.5% -0.4%Min -10.5% -18.7%Max 9.7% 18.4%S.D. 2.6% 7.2%

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