Effectiveness of workplace wellness programmes for dietary habits, overweight, and cardiometabolic health: a systematic review and meta-analysis

José L Peñalvo, Diana Sagastume, Elly Mertens, Irina Uzhova, Jessica Smith, Jason H Y Wu, Eve Bishop, Jennifer Onopa, Peilin Shi, Renata Micha, Dariush Mozaffarian, José L Peñalvo, Diana Sagastume, Elly Mertens, Irina Uzhova, Jessica Smith, Jason H Y Wu, Eve Bishop, Jennifer Onopa, Peilin Shi, Renata Micha, Dariush Mozaffarian

Abstract

Background: The workplace offers a unique opportunity for effective health promotion. We aimed to comprehensively study the effectiveness of multicomponent worksite wellness programmes for improving diet and cardiometabolic risk factors.

Methods: We did a systematic literature review and meta-analysis, following PRISMA guidelines. We searched PubMed-MEDLINE, Embase, the Cochrane Library, Web of Science, and Education Resources Information Center, from Jan 1, 1990, to June 30, 2020, for studies with controlled evaluation designs that assessed multicomponent workplace wellness programmes. Investigators independently appraised the evidence and extracted the data. Outcomes were dietary factors, anthropometric measures, and cardiometabolic risk factors. Pooled effects were calculated by inverse-variance random-effects meta-analysis. Potential sources of heterogeneity and study biases were evaluated.

Findings: From 10 169 abstracts reviewed, 121 studies (82 [68%] randomised controlled trials and 39 [32%] quasi-experimental interventions) met the eligibility criteria. Most studies were done in North America (57 [47%]), and Europe, Australia, or New Zealand (36 [30%]). The median number of participants was 413·0 (IQR 124·0-904·0), and median duration of intervention was 9·0 months (4·5-18·0). Workplace wellness programmes improved fruit and vegetable consumption (0·27 servings per day [95% CI 0·16 to 0·37]), fruit consumption (0·20 servings per day [0·11 to 0·28]), body-mass index (-0·22 kg/m2 [-0·28 to -0·17]), waist circumference (-1·47 cm [-1·96 to -0·98]), systolic blood pressure (-2·03 mm Hg [-3·16 to -0·89]), and LDL cholesterol (-5·18 mg/dL [-7·83 to -2·53]), and to a lesser extent improved total fat intake (-1·18% of daily energy intake [-1·78 to -0·58]), saturated fat intake (-0·70% of daily energy [-1·22 to -0·18]), bodyweight (-0·92 kg [-1·11 to -0·72]), diastolic blood pressure (-1·11 mm Hg [-1·78 to -0·44]), fasting blood glucose (-1·81 mg/dL [-3·33 to -0·28]), HDL cholesterol (1·11 mg/dL [0·48 to 1·74]), and triglycerides (-5·38 mg/dL [-9·18 to -1·59]). No significant benefits were observed for intake of vegetables (0·03 servings per day [95% CI -0·04 to 0·10]), fibre (0·26 g per day [-0·15 to 0·67]), polyunsaturated fat (-0·23% of daily energy [-0·59 to 0·13]), or for body fat (-0·80% [-1·80 to 0·21]), waist-to-hip ratio (-0·00 ratio [-0·01 to 0·00]), or lean mass (1·01 kg [-0·82 to 2·83]). Heterogeneity values ranged from 46·9% to 91·5%. Between-study differences in outcomes were not significantly explained by study design, location, population, or similar factors in heterogeneity analyses.

Interpretation: Workplace wellness programmes are associated with improvements in specific dietary, anthropometric, and cardiometabolic risk indicators. The heterogeneity identified in study designs and results should be considered when using these programmes as strategies to improve cardiometabolic health.

Funding: National Heart, Lung, and Blood Institute.

Conflict of interest statement

Declaration of interests JS is a current employee of General Mills, a food manufacturer; her contribution to this work took place during her affiliation with Tufts University. Her salary at the time of this work was supported by a postdoctoral fellowship from the Canadian Institutes of Health Research. RM reports grants to her institution from the Bill & Melinda Gates Foundation, Nestle, and Danone, outside the submitted work; and consulting fees from Development Initiatives, outside the submitted work. All other authors declare no competing interests.

Copyright © 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license. Published by Elsevier Ltd.. All rights reserved.

Figures

Figure 1:
Figure 1:
Study selection
Figure 2:. Forest plot of intake of…
Figure 2:. Forest plot of intake of fruits
Intervention domains correspond to screening (A), individual education (B), group education (C), food environment (D), labelling (E), financial incentives (F), physical activity (G), self-awareness (H), and others (I). Weights are from random-effects analysis. *Different intervention groups from the same study (Steenhuis 2004).
Figure 3:. Forest plot of waist circumference
Figure 3:. Forest plot of waist circumference
Intervention domains correspond to screening (A), individual education (B), group education (C), food environment (D), labelling (E), financial incentives (F), physical activity (G), self-awareness (H), and others (I). Weights are from random-effects analysis. *Different intervention groups from the same study (Rusali 2018). †Different intervention groups from the same study (Ryu 2017). ‡Different intervention groups from the same study (Geaney 2016). §Different intervention groups from the same study (Ribeiro 2014). ¶Different intervention groups from the same study (Viitasalo 2015).
Figure 4:. Forest plot of LDL cholesterol
Figure 4:. Forest plot of LDL cholesterol
Intervention domains correspond to screening (A), individual education (B), group education (C), food environment (D), labelling (E), financial incentives (F), physical activity (G), self-awareness (H), and others (I). Weights are from random-effects analysis. *Different intervention groups from the same study (Rusali 2018). †Different intervention groups from the same study (Viitasalo 2015).

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