Forecasting risk factor distributions by sex and age in any country, 1990 to 2050: A

BackgroundEstimating future health impacts of preventive interventions requires forecasting risk factor distributions. This paper presents a method to generate business-as-usual (BAU) forecasts of risk factor distributions using Global Burden of Disease (GBD) summary exposure values (SEVs). MethodSEVs from the GBD are a relative risk of disease weighted summary of risk factor exposure, ranging from 0 (everyone below the theoretical minimum risk exposure level) to 1 (everyone above the 95th percentile of global exposure). Given the known inputs to calculate SEVs, with one additional assumption of the coefficient of variation of the risk factor, it is possible to generate parametric distributions (e.g. log-normal, gamma) of risk factor exposures. We demonstrate this method by sex, age and year for body mass index, systolic blood pressure (SBP), low density lipoproteins and fasting plasma glucose in Australia, for both: forecast SEVs to forecast risk factor distributions to 2050; and comparison of past SEV-generated risk factor distributions with observed distributions in the Australian National Health Survey data.ResultsOur method generates plausible age- and sex- specific risk factor distribution forecasts for Australia. Past SEV-generated risk factor distributions agree reasonably well with historic risk factor data, although some SEV-generate distributions (e.g. SBP) are shifted to the right compared to historic data.ConclusionOur method to derive risk factor distributions from GBD SEVs is applicable to any country or demographic group. To facilitate broader use of this method, we recommend further cross-validation studies and making key data publicly available.