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What is the effect of a multicomponent workplace wellness program on health and economic outcomes?
In this cluster randomized trial involving 32 974 employees at a large US warehouse retail company, worksites with the wellness program had an 8.3-percentage point higher rate of employees who reported engaging in regular exercise and a 13.6-percentage point higher rate of employees who reported actively managing their weight, but there were no significant differences in other self-reported health and behaviors; clinical markers of health; health care spending or utilization; or absenteeism, tenure, or job performance after 18 months.
Employees exposed to a workplace wellness program reported significantly greater rates of some positive health behaviors compared with those who were not exposed, but there were no significant effects on clinical measures of health, health care spending and utilization, or employment outcomes after 18 months.
Employers have increasingly invested in workplace wellness programs to improve employee health and decrease health care costs. However, there is little experimental evidence on the effects of these programs.
To evaluate a multicomponent workplace wellness program resembling programs offered by US employers.
Design, Setting, and Participants
This clustered randomized trial was implemented at 160 worksites from January 2015 through June 2016. Administrative claims and employment data were gathered continuously through June 30, 2016; data from surveys and biometrics were collected from July 1, 2016, through August 31, 2016.
There were 20 randomly selected treatment worksites (4037 employees) and 140 randomly selected control worksites (28 937 employees, including 20 primary control worksites [4106 employees]). Control worksites received no wellness programming. The program comprised 8 modules focused on nutrition, physical activity, stress reduction, and related topics implemented by registered dietitians at the treatment worksites.
Main Outcomes and Measures
Four outcome domains were assessed. Self-reported health and behaviors via surveys (29 outcomes) and clinical measures of health via screenings (10 outcomes) were compared among 20 intervention and 20 primary control sites; health care spending and utilization (38 outcomes) and employment outcomes (3 outcomes) from administrative data were compared among 20 intervention and 140 control sites.
Among 32 974 employees (mean [SD] age, 38.6 [15.2] years; 15 272 [45.9%] women), the mean participation rate in surveys and screenings at intervention sites was 36.2% to 44.6% (n = 4037 employees) and at primary control sites was 34.4% to 43.0% (n = 4106 employees) (mean of 1.3 program modules completed). After 18 months, the rates for 2 self-reported outcomes were higher in the intervention group than in the control group: for engaging in regular exercise (69.8% vs 61.9%; adjusted difference, 8.3 percentage points [95% CI, 3.9-12.8]; adjusted P = .03) and for actively managing weight (69.2% vs 54.7%; adjusted difference, 13.6 percentage points [95% CI, 7.1-20.2]; adjusted P = .02). The program had no significant effects on other prespecified outcomes: 27 self-reported health outcomes and behaviors (including self-reported health, sleep quality, and food choices), 10 clinical markers of health (including cholesterol, blood pressure, and body mass index), 38 medical and pharmaceutical spending and utilization measures, and 3 employment outcomes (absenteeism, job tenure, and job performance).
Conclusions and Relevance
Among employees of a large US warehouse retail company, a workplace wellness program resulted in significantly greater rates of some positive self-reported health behaviors among those exposed compared with employees who were not exposed, but there were no significant differences in clinical measures of health, health care spending and utilization, and employment outcomes after 18 months. Although limited by incomplete data on some outcomes, these findings may temper expectations about the financial return on investment that wellness programs can deliver in the short term.
ClinicalTrials.gov Identifier: NCT03167658
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Corresponding Author: Zirui Song, MD, PhD, Department of Health Care Policy, Harvard Medical School, 180A Longwood Ave, Boston, MA 02115 (firstname.lastname@example.org).
Accepted for Publication: March 6, 2019.
Correction: This article was corrected on April 16, 2019, for data errors in the Abstract and Figure and for omissions to the Additional Contributions section.
Author Contributions: Drs Song and Baicker had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
Concept and design, acquisition, analysis, or interpretation of data, drafting of the manuscript, critical revision of the manuscript for important intellectual content, statistical analysis, obtained funding, administrative, technical, or material support, and supervision: Both authors.
Conflict of Interest Disclosures: Dr Song reported no disclosures. Dr Baicker reported receiving personal fees from Eli Lilly outside the submitted work and reported serving on the board of directors of Eli Lilly.
Funding/Support: This work was supported by the National Institute on Aging (R01 AG050329; P30 AG012810 through the National Bureau of Economic Research), Robert Wood Johnson Foundation (grant 72611), and Abdul Latif Jameel Poverty Action Lab North America. BJ’s Wholesale Club provided in-kind logistical and personnel support for the fielding of the wellness program.
Role of the Funder/Sponsor: The funders had no role in the design or conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; or decision to submit the manuscript for publication.
Additional Contributions: We thank José Zubizarreta, PhD, Harvard Medical School, for his statistical guidance and contributions to the sample weights, without financial compensation. We thank Sherri Rose, PhD, Harvard Medical School, for her statistical guidance on randomization, without financial compensation. We thank David Molitor, PhD, and Julian Reif, PhD, University of Illinois at Urbana-Champaign, for guidance on the statistical software for multiple inference adjustment they created in the University of Illinois wellness study, which was used in this study, without financial compensation. We thank Ozlem Blakeley, MA, an employee of Harvard Medical School, and Kathryn Clark, BA, BS, and Bethany Maylone, MEd, employees of the Harvard T.H. Chan School of Public Health, for research assistance and project management. We also thank Josephine Fisher, BA, Jack Huang, AB, Harlan Pittell, BS, and Artemis (Yuanxiaoyue) Yang, BA, employees of the Harvard T.H. Chan School of Public Health, for research assistance. We thank Luke Sonnet, BS, University of California, Los Angeles, for replicating the study results through the Abdul Latif Jameel Poverty Action Lab’s Research Transparency and Reproducibility Initiative, without financial compensation. We thank the study partners, BJ’s Wholesale Club, and Wellness Workdays for collaboration and assistance in the design and fielding of the workplace wellness program. We thank seminar participants at the 7th Conference of the American Society of Health Economists, the Department of Nutrition at the Harvard T.H. Chan School of Public Health, and the Department of Health Care Policy at Harvard Medical School for comments and suggestions, without financial compensation.
Data Sharing Statement: See Supplement 3.
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