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Lau Y, Wong SH, Chee DGH, Ng BSP, Ang WW, Han CY, Cheng LJ. Technology-delivered personalized nutrition intervention on dietary outcomes among adults with overweight and obesity: A systematic review, meta-analysis, and meta-regression. Obes Rev 2024; 25:e13699. [PMID: 38296771 DOI: 10.1111/obr.13699] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Revised: 01/01/2024] [Accepted: 01/02/2024] [Indexed: 02/02/2024]
Abstract
The prevalence of overweight and obesity has continued to increase globally, and one-size-fits-all dietary recommendations may not be suitable for different individual characteristics. A personalized nutrition intervention may be a potential solution. This review aims to evaluate the effects of the technology-delivered personalized nutrition intervention on energy, fat, vegetable, and fruit intakes among adults with overweight and obesity. A three-step comprehensive search strategy was performed from 10 databases and seven clinical registries in published and unpublished trials. A total of 46 randomized controlled trials (RCTs) involving 19,670 adults with overweight and obesity from 14 countries are included. Subgroup and meta-regression analyses were conducted. Meta-analyses showed a reduction of energy intake (-128.05, 95% CI: -197.08, -59.01) and fat intake (-1.81% energy/days, 95% CI: -3.38, -0.24, and -0.19 scores, 95% CI: -0.40, 0.02) in the intervention compared with the comparator. Significant improvements in vegetable and fruit intakes with 0.12-0.15 servings/day were observed in the intervention. Combined one- and two-way interactions had a greater effect on energy intake reduction compared with their counterparts. Meta-regression analyses revealed that no significant covariates were found. Given that the certainty of the evidence was rated as low or very low, further well-designed RCTs with long-term follow-up are warranted.
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Affiliation(s)
- Ying Lau
- The Nethersole School of Nursing, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China
| | | | | | - Brenda Sok Peng Ng
- Alice Lee Centre for Nursing Studies, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Wen Wei Ang
- Alice Lee Centre for Nursing Studies, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Chad Yixian Han
- Caring Futures Institute, College of Nursing and Health Sciences, Flinders University, Adelaide, South Australia, Australia
| | - Ling Jie Cheng
- Health Systems and Behavioural Science Domain, Saw Swee Hock School of Public Health, National University of Singapore, Singapore
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Grady A, Pearson N, Lamont H, Leigh L, Wolfenden L, Barnes C, Wyse R, Finch M, Mclaughlin M, Delaney T, Sutherland R, Hodder R, Yoong SL. The Effectiveness of Strategies to Improve User Engagement With Digital Health Interventions Targeting Nutrition, Physical Activity, and Overweight and Obesity: Systematic Review and Meta-Analysis. J Med Internet Res 2023; 25:e47987. [PMID: 38113062 PMCID: PMC10762625 DOI: 10.2196/47987] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Revised: 09/07/2023] [Accepted: 09/07/2023] [Indexed: 12/21/2023] Open
Abstract
BACKGROUND Digital health interventions (DHIs) are effective in improving poor nutrition, physical inactivity, overweight and obesity. There is evidence suggesting that the impact of DHIs may be enhanced by improving user engagement. However, little is known about the overall effectiveness of strategies on engagement with DHIs. OBJECTIVE This study aims to assess the overall effectiveness of strategies to improve engagement with DHIs targeting nutrition, physical activity, and overweight or obesity and explore associations between strategies and engagement outcomes. The secondary aim was to explore the impact of these strategies on health risk outcomes. METHODS The MEDLINE, Embase, PsycINFO, CINAHL, CENTRAL, Scopus, and Academic Source Complete databases were searched up to July 24, 2023. Eligible studies were randomized controlled trials that evaluated strategies to improve engagement with DHIs and reported on outcomes related to DHI engagement (use or user experience). Strategies were classified according to behavior change techniques (BCTs) and design features (eg, supplementary emails). Multiple-variable meta-analyses of the primary outcomes (usage and user experience) were undertaken to assess the overall effectiveness of strategies. Meta-regressions were conducted to assess associations between strategies and use and user experience outcomes. Synthesis of secondary outcomes followed the "Synthesis Without Meta-Analysis" guidelines. The methodological quality and evidence was assessed using the Cochrane risk-of-bias tool, and the Grading of Recommendations Assessment, Development, and Evaluation tool respectively. RESULTS Overall, 54 studies (across 62 publications) were included. Pooled analysis found very low-certainty evidence of a small-to-moderate positive effect of the use of strategies to improve DHI use (standardized mean difference=0.33, 95% CI 0.20-0.46; P<.001) and very low-certainty evidence of a small-to-moderate positive effect on user experience (standardized mean difference=0.29, 95% CI 0.07-0.52; P=.01). A significant positive association was found between the BCTs social support (effect size [ES]=0.40, 95% CI 0.14-0.66; P<.001) and shaping knowledge (ES=0.39, 95% CI 0.03-0.74; P=.03) and DHI use. A significant positive association was found among the BCTs social support (ES=0.70, 95% CI 0.18-1.22; P=.01), repetition and substitution (ES=0.29, 95% CI 0.05-0.53; P=.03), and natural consequences (ES=0.29, 95% CI 0.05-0.53; P=.02); the design features email (ES=0.29, 95% CI 0.05-0.53; P=.02) and SMS text messages (ES=0.34, 95% CI 0.11-0.57; P=.01); and DHI user experience. For secondary outcomes, 47% (7/15) of nutrition-related, 73% (24/33) of physical activity-related, and 41% (14/34) of overweight- and obesity-related outcomes reported an improvement in health outcomes. CONCLUSIONS Although findings suggest that the use of strategies may improve engagement with DHIs targeting such health outcomes, the true effect is unknown because of the low quality of evidence. Future research exploring whether specific forms of social support, repetition and substitution, natural consequences, emails, and SMS text messages have a greater impact on DHI engagement is warranted. TRIAL REGISTRATION PROSPERO CRD42018077333; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=77333.
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Affiliation(s)
- Alice Grady
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter New England Population Health, Hunter New England Local Health District, Wallsend, Australia
- Population Health Research Program, Hunter Medical Research Institute, New Lambton, Australia
- National Centre of Implementation Science, University of Newcastle, Callaghan, Australia
- College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, Australia
| | - Nicole Pearson
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter New England Population Health, Hunter New England Local Health District, Wallsend, Australia
- Population Health Research Program, Hunter Medical Research Institute, New Lambton, Australia
- College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, Australia
| | - Hannah Lamont
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter New England Population Health, Hunter New England Local Health District, Wallsend, Australia
- Population Health Research Program, Hunter Medical Research Institute, New Lambton, Australia
- College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, Australia
| | - Lucy Leigh
- Data Sciences, Hunter Medical Research Institute, New Lambton, Australia
| | - Luke Wolfenden
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter New England Population Health, Hunter New England Local Health District, Wallsend, Australia
- Population Health Research Program, Hunter Medical Research Institute, New Lambton, Australia
- National Centre of Implementation Science, University of Newcastle, Callaghan, Australia
- College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, Australia
| | - Courtney Barnes
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter New England Population Health, Hunter New England Local Health District, Wallsend, Australia
- Population Health Research Program, Hunter Medical Research Institute, New Lambton, Australia
- National Centre of Implementation Science, University of Newcastle, Callaghan, Australia
- College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, Australia
| | - Rebecca Wyse
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, Australia
- Equity in Health and Wellbeing Program, Hunter Medical Research Institute, New Lambton, Australia
| | - Meghan Finch
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Population Health Research Program, Hunter Medical Research Institute, New Lambton, Australia
- National Centre of Implementation Science, University of Newcastle, Callaghan, Australia
- College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, Australia
| | - Matthew Mclaughlin
- Telethon Kids Institute, University of Western Australia, Perth, Australia
| | - Tessa Delaney
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter New England Population Health, Hunter New England Local Health District, Wallsend, Australia
- Population Health Research Program, Hunter Medical Research Institute, New Lambton, Australia
- College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, Australia
| | - Rachel Sutherland
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter New England Population Health, Hunter New England Local Health District, Wallsend, Australia
- Population Health Research Program, Hunter Medical Research Institute, New Lambton, Australia
- National Centre of Implementation Science, University of Newcastle, Callaghan, Australia
- College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, Australia
| | - Rebecca Hodder
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter New England Population Health, Hunter New England Local Health District, Wallsend, Australia
- Population Health Research Program, Hunter Medical Research Institute, New Lambton, Australia
- National Centre of Implementation Science, University of Newcastle, Callaghan, Australia
- College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, Australia
| | - Sze Lin Yoong
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter New England Population Health, Hunter New England Local Health District, Wallsend, Australia
- Population Health Research Program, Hunter Medical Research Institute, New Lambton, Australia
- National Centre of Implementation Science, University of Newcastle, Callaghan, Australia
- College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, Australia
- Global Obesity Centre, Institute for Health Transformation, School of Health and Social Development, Deakin University, Melbourne, Australia
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