Effectiveness of wearable technology‐based physical activity interventions for adults with type 2 diabetes mellitus: A systematic review and meta‐regression
Open accessAbstract
Type 2 diabetes mellitus (T2DM) is a chronic metabolic disorder with the increasing prevalence of a modern sedentary lifestyle. Wearable technology‐based physical activity interventions (WT‐BPAI) might provide a channel to improve diabetic self‐management. The study aimed to (1) evaluate the effectiveness of WT‐BPAI on PA levels, glycemic levels, and other outcomes (blood pressure [BP], body mass index [BMI], and serum lipid profile) in adults with T2DM, and (2) investigate the potential covariates affecting aforementioned outcomes. Eight databases were searched thoroughly using three steps from inception until January 16, 2024. The quality of the studies and overall evidence were evaluated. The package meta of the R software program version 4.3.1. was utilized for meta‐analyses, subgroup analyses, and meta‐regression analyses. A total of 19 randomized controlled trials (RCTs) were found. Meta‐analyses revealed that WT‐BPAI significantly increased 1583 steps per day and decreased systolic BP (SBP) by 2.46 mmHg. Subgroup and meta‐regression analyses found that function, duration of intervention, and age were significant covariates. According to the risk of bias version 2, more than half of the trials raised some concerns about the randomization process, deviations from the intended intervention, and missing outcome data. The certainty of the evidence was very low for all outcomes based on the Grading of Recommendations Assessment, Development and Evaluation (GRADE) criteria. WT‐BPAI can be considered a supplementary intervention to increase the steps per day and decrease SBP, especially when used for short periods in young adults with T2DM. However, we need more well‐designed research with long‐term outcomes. image
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Wearable device-related interventions improved BMI (moderate-quality evidence).
“Two reviews [43, 45] indicated that wearable device‐related interventions improved BMI (moderate‐quality evidence) but had no significant effect on body weight (low‐quality evidence).”
From Effectiveness of Wearable Devices for Diabetes Management: An Overview of Systematic Reviews and Meta‐Analyses (2026) · cites this paper as [45]
The Results section (BP, BMI, and serum lipid profile) reports a significant but very small reduction in BMI effect size, while finding no significant difference in mean BMI between intervention and control groups. The Results section (Certainty of evidence and publication bias) rates the evidence for all outcomes as very low, not moderate. (LLM, conf=0.90)
Experimental — accuracy not yet measuredWearable activity trackers significantly increased daily step counts in patients with T2D (p < 0.05), with low evidence certainty.
“Three reviews evaluated the effect of wearable activity trackers on daily step counts in patients with T2D [42, 43, 45], all reporting statistically significant increases in the intervention group (p < 0.05) but with low evidence certainty.”
From Effectiveness of Wearable Devices for Diabetes Management: An Overview of Systematic Reviews and Meta‐Analyses (2026) · cites this paper as [45]
The Results (Physical activity) report a significant increase of 1,583 steps per day with wearable-based interventions (p < 0.05). However, the Results (Certainty of evidence and publication bias) rate the evidence for all outcomes as very low under GRADE, rather than low. (LLM, conf=0.88)
Experimental — accuracy not yet measuredWearable device-based interventions reduced systolic blood pressure.
“and one [45] reported reduced systolic blood pressure (both moderate‐quality evidence).”
From Effectiveness of Wearable Devices for Diabetes Management: An Overview of Systematic Reviews and Meta‐Analyses (2026) · cites this paper as [45]
The Results (BP, BMI, and serum lipid profile) report a significant reduction in systolic blood pressure with wearable interventions. However, the Results (Certainty of evidence and publication bias) rate all outcomes as very low-certainty evidence, not the moderate-quality evidence stated in the citing sentence. (LLM, conf=0.90)
Experimental — accuracy not yet measuredWearable device-related interventions had no significant effect on body weight (low-quality evidence).
“Two reviews [43, 45] indicated that wearable device‐related interventions improved BMI (moderate‐quality evidence) but had no significant effect on body weight (low‐quality evidence).”
From Effectiveness of Wearable Devices for Diabetes Management: An Overview of Systematic Reviews and Meta‐Analyses (2026) · cites this paper as [45]
The Results (BP, BMI, and serum lipid profile; page unavailable) report no significant difference in mean BMI between intervention and control groups, but do not report a body-weight result. The Results (Certainty of evidence and publication bias; page unavailable) rate the evidence for all outcomes as very low, not low. (LLM, conf=0.82)
Experimental — accuracy not yet measuredPedometers and smart wristbands effectively increase daily step counts and physical activity levels, contributing to improvements in lipid profiles and blood pressure.
“In exercise management, pedometers and smart wristbands effectively increase daily step counts and physical activity levels, contributing to improvements in lipid profiles and blood pressure [42–45].”
From Effectiveness of Wearable Devices for Diabetes Management: An Overview of Systematic Reviews and Meta‐Analyses (2026) · cites this paper as [45]
The Results (Physical activity; page not supplied) report a significant increase of 1,583 steps per day, but not a significant increase in moderate-to-vigorous physical activity. The Discussion (Blood pressure) reports reduced systolic, but not diastolic, blood pressure. Contrary to the lipid-profile portion of the claim, the Discussion (Serum lipid profile) reports no significant lipid differences. (LLM, conf=0.90)
Experimental — accuracy not yet measured
Wearable-based exercise management interventions (e.g., pedometers with daily step targets) effectively improve physical activity and lipid profiles.
“In exercise management, wearable‐based exercise management interventions (e.g., pedometers with daily step targets) effectively improve physical activity and lipid profiles [42, 43, 45].”
From Effectiveness of Wearable Devices for Diabetes Management: An Overview of Systematic Reviews and Meta‐Analyses (2026) · cites this paper as [45]
The Results (Physical activity; page unavailable) report a significant increase of 1,583 steps per day with wearable-based interventions in adults with type 2 diabetes. But the Results (BP, BMI, and serum lipid profile; page unavailable) found no significant differences in HDL or LDL between intervention and control groups, so the claimed improvement in lipid profiles is not supported. (LLM, conf=0.91)
Experimental — accuracy not yet measured
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“We found 11 arms of 9 RCTs 53,55,56,62,63,65 – 67,70 with 1076 participants for steps per day (Figure 3).”
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“We found 11 arms of 9 RCTs 53,55,56,62,63,65 – 67,70 with 1076 participants for steps per day (Figure 3).”
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- Authors
- Chua, R. E. C., Lau, Y., Ang, W. W., Boey, A. A. Y. F., & Lau, S. T.
- Affiliations
- SingHealth (SG)
- Chinese University of Hong Kong (HK)
- National University of Singapore (SG)
- Corresponding author
- Lau, Ying
- Venue
- Journal of Diabetes
- Publisher
- Wiley
- Published
- 2024-10
- Volume
- 16
- Issue
- 10
- Pages
- e70002-e70002
- ISSN
- 1753-0393 (ISSN-L)
- 1753-0407
- PMC
- PMC11450597
- OpenAlex
- W4403134747
- Cited by
- 14
- References
- 80
- Citations by year
- 2026: 11 · 2025: 3
- FWCI
- 0.80
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Journal of Diabetes (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Health Sciences › Medicine › Physiology › Physical Activity and Health
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Keywords
- type 2 diabetes, wearable devices, physical activity interventions, step count, glycemic control, systolic blood pressure, body mass index, lipid profile, diabetes self-management, intervention duration, young adults
- MeSH terms
- Wearable Electronic Devices, Adult, Blood Pressure, Diabetes Mellitus, Type 2, Exercise Therapy, Humans, Exercise, Treatment Outcome
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