Financial implications of New York City's weight management initiative.

• Main Authors: Sagun Agrawal, Alexis C Wojtanowski, Laura Tringali, Gary D Foster, Eric A Finkelstein
• Format: Article
• Language: English
• Published: Public Library of Science (PLoS) 2021-01-01
• Series: PLoS ONE
• Online Access: https://doi.org/10.1371/journal.pone.0246621

<h4>Purpose</h4>To estimate potential annual savings in medical expenditures from a subsidized weight management program from the NYC Government perspective.<h4>Design</h4>Longitudinal observational study.<h4>Setting</h4>Employees of New York City (NYC) government and enrolled dependents.<h4>Sample</h4>14,946 participants with overweight and obesity.<h4>Intervention</h4>WW (formerly Weight Watchers®) 'Workshop' and 'Digital' programs.<h4>Measures</h4>Participation rate, enrollment duration, weight change, and predicted gross and net total and per capita medical expenditure savings and return on investment (ROI).<h4>Analysis</h4>Participation rate, enrollment duration, weight change, and program costs are based on direct observation. Predicted savings are simulated based on published data relating weight loss to medical expenditure reductions.<h4>Results</h4>In total, 47% of participating employees and 50% of participating dependents lost weight during the enrollment period. Mean (median) enrollment duration for employees was 7.1 months (7.0) and for dependents was 6.9 months (6.0). Mean (median) weight losses for the employees in 'Workshops' and 'Digital' was 6.6 lbs (2.80) and 6.3 lbs (0.0). For dependents, weight losses were 7.4 lbs (3.59) and 11.6 lbs (2.0). Per capita and total predicted net savings to NYC Government from employees was estimated to be $120 and $1,486,102 for an ROI of 143%. Including dependents, predicted net savings increases to $1,963,431 for an ROI of 189%. Over 80% of savings came from participants in the Obese III category.<h4>Conclusion</h4>An evidence-based weight management program has the potential to generate a positive ROI for employers. Future studies should validate these estimates using actual data and more rigorous designs.