Estimating the global economic benefits of physically active populations over 30 years (2020-2050).

OBJECTIVES: We assess the potential benefits of increased physical activity for the global economy for 23 countries and the rest of the world from 2020 to 2050. The main factors taken into account in the economic assessment are excess mortality and lower productivity. METHODS: This study links three methodologies. First, we estimate the association between physical inactivity and workplace productivity using multivariable regression models with proprietary data on 120 143 individuals in the UK and six Asian countries (Australia, Malaysia, Hong Kong, Thailand, Singapore and Sri Lanka). Second, we analyse the association between physical activity and mortality risk through a meta-regression analysis with data from 74 prior studies with global coverage. Finally, the estimated effects are combined in a computable general equilibrium macroeconomic model to project the economic benefits of physical activity over time. RESULTS: Doing at least 150 min of moderate-intensity physical activity per week, as per lower limit of the range recommended by the 2020 WHO guidelines, would lead to an increase in global gross domestic product (GDP) of 0.15%-0.24% per year by 2050, worth up to US$314-446 billion per year and US$6.0-8.6 trillion cumulatively over the 30-year projection horizon (in 2019 prices). The results vary by country due to differences in baseline levels of physical activity and GDP per capita. CONCLUSIONS: Increasing physical activity in the population would lead to reduction in working-age mortality and morbidity and an increase in productivity, particularly through lower presenteeism, leading to substantial economic gains for the global economy.

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

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.

Individual, Workplace, and Combined Effects Modeling of Employee Productivity Loss.

OBJECTIVE: Systematically and simultaneously investigate a wide range of influences on workplace productivity loss. METHODS: Data were collected from 31,950 employees in the UK. Influences of employees' socioeconomic characteristics, lifestyle, commuting, physical and mental health, well-being, and job and workplace environment were assessed using structural equation models, allowing systematic decomposition of the complex network of influences and creating new, deeper insights. RESULTS: Mental health, physical health, job characteristics, and support from organization are the most important (direct or indirect) determinants of employees' productivity. 93% of the indirect influences are mediated through mental and/or physical health. Some influences that appear as strong predictors in simple models lose most of their explanatory power in more complex models with additional explanatory variables. CONCLUSIONS: There is a need for a more tailored strategy to improve employees' wellbeing as well as the overall organizational, work, and management culture.

Medical care savings from workplace wellness programs: what is a realistic savings potential?

BACKGROUND: : Workplace wellness programs have become increasingly popular despite large inconsistencies in the analyses of their ability to produce long-term medical care savings. OBJECTIVE: : To clarify the aforesaid situation by estimating potential long-term medical care savings linked to chronic disease. METHODS: : We combined data from the Global Burden of Disease Study and Medical Expenditure Panel Surveys to estimate the annual savings that would result from lowering risk factors typically managed by workplace wellness programs to their theoretical minimums. RESULTS: : Lowering risk factors to their theoretical minimums, if this were possible, would reduce average annual costs per working-age adult by 18.4%. CONCLUSION: : These findings have important implications for workplace wellness programs because they provide a robust estimate of potential savings.

Promoting prevention through the affordable care act: workplace wellness.

Public health in the United States can be improved by building workplace "cultures of health" that support healthy lifestyles. The Affordable Care Act (ACA), which includes the Prevention and Public Health Fund, will support a new focus on prevention and wellness, offering opportunities to strengthen the public's health through workplace wellness initiatives. This article describes the opportunity the ACA provides to improve worker wellness.