Health-care spending attributable to modifiable risk factors in the USA: an economic attribution analysis

Abstract

Background: There is a robust understanding of how specific behavioural, metabolic, and environmental risk factors increase the risk of health burden. However, there is less understanding of how these risks individually and jointly affect health-care spending. The objective of this study was to quantify health-care spending attributable to modifiable risk factors in the USA for 2016.

Methods: We extracted estimates of US health-care spending by condition, age, and sex from the Institute for Health Metrics and Evaluation's Disease Expenditure Study 2016 and merged these estimates with population attributable fraction estimates for 84 modifiable risk factors from the Global Burden of Diseases, Injuries, and Risk Factors Study 2017 to produce estimates of spending by condition attributable to these risk factors. Because not all spending can be linked to health burden, we adjusted attributable spending estimates downwards, proportional to the association between health burden and health-care spending across time and age for each aggregate health condition. We propagated underlying uncertainty from the original data sources by randomly pairing the draws from the two studies and completing our analysis 1000 times independently.

Findings: In 2016, US health-care spending attributable to modifiable risk factors was US$730·4 billion (95% uncertainty interval [UI] 694·6-768·5), corresponding to 27·0% (95% UI 25·7-28·4) of total health-care spending. Attributable spending was largely due to five risk factors: high body-mass index ($238·5 billion, 178·2-291·6), high systolic blood pressure ($179·9 billion, 164·5-196·0), high fasting plasma glucose ($171·9 billion, 154·8-191·9), dietary risks ($143·6 billion, 130·3-156·1), and tobacco smoke ($130·0 billion, 116·8-143·5). Spending attributable to risk factor varied by age and sex, with the fraction of attributable spending largest for those aged 65 years and older (45·5%, 44·2-46·8).

Interpretation: This study shows high spending on health care attributable to modifiable risk factors and highlights the need for preventing and controlling risk exposure. These attributable spending estimates can contribute to informed development and implementation of programmes to reduce risk exposure, their health burden, and health-care cost.

Funding: Vitality Institute.