The cost of health risk factors: quantifying the potential health and economic returns of prevention
Abstract
Background: Population exposure to modifiable risk factors in Poland remains above the EU average, generating substantial health losses, healthcare costs, and economic inefficiencies. Yet prevention is rarely evaluated through a cross-sector lens. This study presents a framework to quantify the societal returns of reducing risk factor exposure, translating epidemiological effects into outcomes relevant for patients, healthcare systems, and the economy.
Methods: We apply a comparative risk assessment approach using the Potential Impact Fractions to simulate counterfactual scenarios of reduced exposure to key risk factors - tobacco, alcohol, obesity, low physical activity, unhealthy diet, and PM2.5. Baseline exposure (2024) and relative risks were linked to ICD-10 outcomes. Impacts were measured as avoided healthcare costs (payer perspective), reduced absenteeism/productivity gains (human capital approach), and premature mortality reductions.
Results: Obesity reduction yielded the largest annual healthcare savings (up to 2.1bn PLN), followed by smoking and unhealthy diet. The greatest absenteeism reductions were observed for obesity (up to 3.3M days), smoking, and PM2.5. From a patient perspective, the largest mortality reductions were linked to decreased smoking (up to 56.4k deaths), increased physical activity, and reduced air pollution. These findings highlight the scale of avoidable burden associated with current exposure levels and demonstrate significant returns for the patient, the healthcare system and the economy achievable through prevention.
Conclusions: This framework integrates epidemiological and economic evidence to frame health promotion as a high-value investment. By highlighting population-wide burdens, it provides a transparent tool to align resources allocation with health and economic gains, strengthening the case for cross-sector action and equity-oriented prevention.
Key messages: • This versatile tool uses impact fractions to simulate risk facotr reduction, translating into health gains, healthcare savings and increased economic productivity.
• Tackling key risks by cutting obesity and substances use saves lives, boosts productivity, and drives the economy through significant fiscal savings.
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BibTeX
@article{michalowski2026cost,
title = {{The cost of health risk factors: quantifying the potential health and economic returns of prevention}},
author = {JC Michałowski and M Raczyńska and S Torzecka and M Wasążnik and B Więckowska and M Dąbkowska},
journal = {The European Journal of Public Health},
year = {2026},
month = oct,
doi = {10.1093/eurpub/ckag169.331},
url = {https://doi.org/10.1093/eurpub/ckag169.331},
note = {CC BY-NC 4.0},
}
RIS
TY - JOUR
TI - The cost of health risk factors: quantifying the potential health and economic returns of prevention
AU - JC Michałowski
AU - M Raczyńska
AU - S Torzecka
AU - M Wasążnik
AU - B Więckowska
AU - M Dąbkowska
PY - 2026
DA - 2026/10/01
JO - The European Journal of Public Health
DO - 10.1093/eurpub/ckag169.331
UR - https://doi.org/10.1093/eurpub/ckag169.331
AB - Background: Population exposure to modifiable risk factors in Poland remains above the EU average, generating substantial health losses, healthcare costs, and economic inefficiencies. Yet prevention is rarely evaluated through a cross-sector lens. This study presents a framework to quantify the societal returns of reducing risk factor exposure, translating epidemiological effects into outcomes relevant for patients, healthcare systems, and the economy. Methods: We apply a comparative risk assessment approach using the Potential Impact Fractions to simulate counterfactual scenarios of reduced exposure to key risk factors - tobacco, alcohol, obesity, low physical activity, unhealthy diet, and PM2.5. Baseline exposure (2024) and relative risks were linked to ICD-10 outcomes. Impacts were measured as avoided healthcare costs (payer perspective), reduced absenteeism/productivity gains (human capital approach), and premature mortality reductions. Results: Obesity reduction yielded the largest annual healthcare savings (up to 2.1bn PLN), followed by smoking and unhealthy diet. The greatest absenteeism reductions were observed for obesity (up to 3.3M days), smoking, and PM2.5. From a patient perspective, the largest mortality reductions were linked to decreased smoking (up to 56.4k deaths), increased physical activity, and reduced air pollution. These findings highlight the scale of avoidable burden associated with current exposure levels and demonstrate significant returns for the patient, the healthcare system and the economy achievable through prevention. Conclusions: This framework integrates epidemiological and economic evidence to frame health promotion as a high-value investment. By highlighting population-wide burdens, it provides a transparent tool to align resources allocation with health and economic gains, strengthening the case for cross-sector action and equity-oriented prevention. Key messages: • This versatile tool uses impact fractions to simulate risk facotr reduction, translating into health gains, healthcare savings and increased economic productivity. • Tackling key risks by cutting obesity and substances use saves lives, boosts productivity, and drives the economy through significant fiscal savings.
SN - 1101-1262
SN - 1464-360X
ER -