Exploring static and dynamic relationships between burden of disease and research funding in the United States

Abstract Background The relationship between burden of disease and research funding has been examined cross-sectionally, but temporal patterns have not been investigated. It is logical to assume that temporal improvements in disability-adjusted life-years (DALYs) reflect benefits from research funding; such assumptions are tempered by an unknown lag time for emergence of benefits from research. Methods We studied National Institutes of Health (NIH) research fund allocations and United States DALY estimates for overlapping disease categories (matched disease categories, MDC, N = 38). Using a general linear model, we separately analysed DALYs for MDCs in 2017 in relation to NIH research allocations in 2017 and 2007. We also examined how changes in DALYs were related to cumulative NIH research funding (2006–2017). After regressing DALY change on summed funding, we obtained model residuals as estimates of the discrepancy for each MDC between observed and expected change in burden, given funding. Results In 2017, there was a positive association between NIH research fund allocations and DALYs for the same year (F 1,36 = 16.087, p = 0.0002921; slope = 0.35020; model R 2 = 0.3088), suggesting proportionate allocation. There was a positive association between 2017 DALYs and 2007 NIH research allocation, implying a beneficial impact of research (F 1,36 = 15.754, p = 0.0003; slope = 0.8845; model R 2 = 0.3044). In contrast, there was a nonsignificant association between summed NIH funding and percent change in DALYs over 2006–2017 (F 1,36 = 0.199; p = 0.65; beta coefficient = −1.144). When MDCs were ordered based on residuals, HIV/AIDS ranked first. Mental, neurologic or substance abuse (MNS) disorders comprised most residuals in the lower half. Conclusions NIH fund allocation is proportional to DALYs for MDCs. Temporal changes in DALYs vary by MDCs, but they are not significantly related to cumulative research outlays. Further analysis of temporal changes in DALYs could help to inform research outlays for MDCs and to study the impact of research.