Cardiometabolic risk factor changes observed in diabetes prevention programs in US settings: A systematic review and meta-analysis
Open accessAbstract
BACKGROUND: The Diabetes Prevention Program (DPP) study showed that weight loss in high-risk adults lowered diabetes incidence and cardiovascular disease risk. No prior analyses have aggregated weight and cardiometabolic risk factor changes observed in studies implementing DPP interventions in nonresearch settings in the United States. METHODS AND FINDINGS: In this systematic review and meta-analysis, we pooled data from studies in the United States implementing DPP lifestyle modification programs (focused on modest [5%-7%] weight loss through ≥150 min of moderate physical activity per week and restriction of fat intake) in clinical, community, and online settings. We reported aggregated pre- and post-intervention weight and cardiometabolic risk factor changes (fasting blood glucose [FBG], glycosylated hemoglobin [HbA1c], systolic or diastolic blood pressure [SBP/DBP], total [TC] or HDL-cholesterol). We searched the MEDLINE, EMBASE, Cochrane Library, and Clinicaltrials.gov databases from January 1, 2003, to May 1, 2016. Two reviewers independently evaluated article eligibility and extracted data on study designs, populations enrolled, intervention program characteristics (duration, number of core and maintenance sessions), and outcomes. We used a random effects model to calculate summary estimates for each outcome and associated 95% confidence intervals (CI). To examine sources of heterogeneity, results were stratified according to the presence of maintenance sessions, risk level of participants (prediabetes or other), and intervention delivery personnel (lay or professional). Forty-four studies that enrolled 8,995 participants met eligibility criteria. Participants had an average age of 50.8 years and body mass index (BMI) of 34.8 kg/m2, and 25.2% were male. On average, study follow-up was 9.3 mo (median 12.0) with a range of 1.5 to 36 months; programs offered a mean of 12.6 sessions, with mean participant attendance of 11.0 core sessions. Sixty percent of programs offered some form of post-core maintenance (either email or in person). Mean absolute changes observed were: weight -3.77 kg (95% CI: -4.55; -2.99), HbA1c -0.21% (-0.29; -0.13), FBG -2.40 mg/dL (-3.59; -1.21), SBP -4.29 mmHg (-5.73, -2.84), DBP -2.56 mmHg (-3.40, 1.71), HDL +0.85 mg/dL (-0.10, 1.60), and TC -5.34 mg/dL (-9.72, -0.97). Programs with a maintenance component achieved greater reductions in weight (additional -1.66kg) and FBG (additional -3.14 mg/dl). Findings are subject to incomplete reporting and heterogeneity of studies included, and confounding because most included studies used pre-post study designs. CONCLUSIONS: DPP lifestyle modification programs achieved clinically meaningful weight and cardiometabolic health improvements. Together, these data suggest that additional value is gained from these programs, reinforcing that they are likely very cost-effective.
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The FBG findings align with previous findings.
“We found significant pre/post reductions in FBG within intervention participants and larger reductions among intervention than among control participants, which aligns with previous findings (10,11).”
From Global diabetes prevention interventions: A systematic review and network meta-analysis of the real-world impact on incidence, weight, and glucose (2018) · cites this paper as [10]
The Outcomes section reports a significant mean pre/post FBG reduction of 2.40 mg/dl across 21 studies. It also says there were insufficient data to compare intervention and control groups for outcomes other than weight, so this source does not establish the claimed larger FBG reduction versus controls. (LLM, conf=0.90)
Experimental — accuracy not yet measuredExisting meta-analyses show that lifestyle modification strategies to prevent type 2 diabetes delivered under real-world conditions are effective for promoting weight loss.
“Existing meta-analyses show that LSM strategies to prevent type 2 diabetes that are delivered under real-world conditions are effective for promoting weight loss (7–11)”
From Global diabetes prevention interventions: A systematic review and network meta-analysis of the real-world impact on incidence, weight, and glucose (2018) · cites this paper as [10]
Effects of real-world lifestyle modification strategies on glucose outcomes are mixed, with both positive and null estimates obtained.
“Effects on glucose outcomes are mixed, with both positive and null estimates having been obtained (7,10,11).”
From Global diabetes prevention interventions: A systematic review and network meta-analysis of the real-world impact on incidence, weight, and glucose (2018) · cites this paper as [10]
The authors' weight-loss findings are consistent with other meta-analyses showing a pre/post weight loss of 2.3-3.8 kg and a between-group weight loss difference of 1.6-2.7 kg.
“Regarding weight loss, our findings are consistent with those from other meta-analyses showing a pre/post weight loss of 2.3–3.8 kg (9,10) and a between-group weight loss difference of 1.6–2.7 kg (7,9,10,14).”
From Global diabetes prevention interventions: A systematic review and network meta-analysis of the real-world impact on incidence, weight, and glucose (2018) · cites this paper as [10]
In this meta-analysis, each study was assessed using a set of quality indicators previously used in meta-analyses of translation studies.
“In this meta-analysis, we assessed each study using a set of quality indicators previously used in meta-analyses of translation studies (8,10).”
From Global diabetes prevention interventions: A systematic review and network meta-analysis of the real-world impact on incidence, weight, and glucose (2018) · cites this paper as [10]
Positive effects on A1C have been observed in a previous meta-analysis of translation studies and another meta-analysis synthesizing interventions translating the U.S. DPP model.
“Null effects were also observed for the nine studies reporting A1C, while positive effects have been observed in a previous meta-analysis of translation studies (14) and another one synthesizing interventions translating the U.S. DPP model (10).”
From Global diabetes prevention interventions: A systematic review and network meta-analysis of the real-world impact on incidence, weight, and glucose (2018) · cites this paper as [10]
Incorporating very low-calorie diets and meal substitutes into an overall dietary plan is effective for achieving greater weight loss.
“To accomplish weight loss, the incorporation of very lowecalorie diets and meal substitutes into an overall dietary plan has been shownto be effective in achieving greater degrees of weight loss.689,860”
From American Association of Clinical Endocrinology Clinical Practice Guideline: Developing a Diabetes Mellitus Comprehensive Care Plan-2022 Update. (2022) · cites this paper as [860]
The Introduction reports weight loss in programs that included calorie-restricted diets, but does not address very low-calorie diets or meal substitutes. Searches for those terms found no passage assessing whether incorporating them into a dietary plan produces greater weight loss. (LLM, conf=0.76)
Experimental — accuracy not yet measuredThe literature on d-DPPs is plagued by inconsistent effects of d-DPPs on HbA1c.
“It has been noted that this literature is plagued by (1) patchwork combinations of remote technologies; (2) a dearth of evidence testing d-DPPs in specific subpopulations, such as older adults; and (3) the inconsistent effects of d-DPPs on HbA1c.”
From Effects of a Digital Diabetes Prevention Program: An RCT (2022) · cites this paper as [13]
The Statistical Analysis section says HbA1c data were insufficient to compare delivery formats, including electronic media. The Conclusion reports an overall HbA1c decrease across DPP-based lifestyle programs, but our copy does not assess whether digital DPPs had inconsistent effects on HbA1c. (LLM, conf=0.75)
Experimental — accuracy not yet measuredThe literature on d-DPPs is plagued by a dearth of evidence testing d-DPPs in specific subpopulations, such as older adults.
“It has been noted that this literature is plagued by (1) patchwork combinations of remote technologies; (2) a dearth of evidence testing d-DPPs in specific subpopulations, such as older adults; and (3) the inconsistent effects of d-DPPs on HbA1c.”
From Effects of a Digital Diabetes Prevention Program: An RCT (2022) · cites this paper as [13]
The Study Selection and Statistical Analysis sections cover DPP adaptations, including electronic delivery, but do not assess whether digital DPPs have been tested in older adults. A search for older-adult subpopulations found an overall mean age, not a statement that evidence for this subgroup is scarce. No page numbers are available in our copy. (LLM, conf=0.70)
Experimental — accuracy not yet measuredThe literature on d-DPPs is plagued by patchwork combinations of remote technologies.
“It has been noted that this literature is plagued by (1) patchwork combinations of remote technologies; (2) a dearth of evidence testing d-DPPs in specific subpopulations, such as older adults; and (3) the inconsistent effects of d-DPPs on HbA1c.”
From Effects of a Digital Diabetes Prevention Program: An RCT (2022) · cites this paper as [13]
The Limitations section describes heterogeneity in DPP delivery formats, and the Discussion mentions electronic delivery and remote maintenance. Neither says that digital DPP studies are plagued by patchwork combinations of remote technologies. A search for that phrase and related technology terms found no passage making the attributed criticism; page numbers were not available in our copy. (LLM, conf=0.74)
Experimental — accuracy not yet measuredModest, sustained weight loss can delay the progression from prediabetes to type 2 diabetes.
“There is strong and consistent evidence that modest, sustained weight loss can delay the progression from prediabetes to type 2 diabetes (97-99) (see Section 3, “Prevention or Delay of Type 2 Diabetes and Associated Comorbidities”) and is beneficial for the management of type 2 diabetes (see Section 8, “Obesity and Weight Management for the Prevention and Treatment of Type 2 Diabetes”).”
From 5. Facilitating Positive Health Behaviors and Well-being to Improve Health Outcomes:<i>Standards of Care in Diabetes—2023</i> (2023) · cites this paper as [98]
Modest, sustained weight loss is beneficial for the management of type 2 diabetes.
“There is strong and consistent evidence that modest, sustained weight loss can delay the progression from prediabetes to type 2 diabetes (97-99) (see Section 3, “Prevention or Delay of Type 2 Diabetes and Associated Comorbidities”) and is beneficial for the management of type 2 diabetes (see Section 8, “Obesity and Weight Management for the Prevention and Treatment of Type 2 Diabetes”).”
From 5. Facilitating Positive Health Behaviors and Well-being to Improve Health Outcomes:<i>Standards of Care in Diabetes—2023</i> (2023) · cites this paper as [98]
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Outcomes of a Church-based Diabetes Prevention Program Delivered by Peers
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An Outpatient-Based Clinical Program For Diabetes Prevention: an Update
Swanson, C. M., Bersoux, S., Larson, M. H., Aponte-Furlow, R. T., Flatten, S. S., Olsen, C. L., LaRosa, C. S., Verona, P. M., Jameson, K. A., & Cook, C. B. (2011) · Endocrine Practice · doi:10.4158/ep11226.or · Cited by 6 · see citing works
Sattin, R. W., Williams, L. B., Dias, J. W., et al. (2014) · Cited by 1 · see citing works
Flagged first, then by citations
Research works printed but not linked: 1
- [23]23. American Diabetes Association. Standard of Medical Care in Diabetes. Diabetes care. 2015; 38, 1.
Cited by
Sorted by citations
5. Lifestyle Management:<i>Standards of Medical Care in Diabetes—2019</i>
American Diabetes Association (2019) · Diabetes Care · doi:10.2337/dc19-s005 · Cited by 700 · see citing works
4. Lifestyle Management: <i>Standards of Medical Care in Diabetes—2018</i>
American Diabetes Association (2018) · Diabetes Care · doi:10.2337/dc18-s004 · Cited by 563 · see citing works
Blonde, L., Umpierrez, G. E., Reddy, S. S., McGill, J. B., Berga, S. L., Bush, M., Chandrasekaran, S., DeFronzo, R. A., Einhorn, D., Galindo, R. J., et al. (2022) · Endocrine Practice · doi:10.1016/j.eprac.2022.08.002 · Cited by 507 · see citing works
ElSayed, N. A., Aleppo, G., Aroda, V. R., Bannuru, R. R., Brown, F. M., Bruemmer, D., Collins, B. S., Hilliard, M. E., Isaacs, D., Johnson, E. L., et al. (2023) · Diabetes Care · doi:10.2337/dc23-s005 · Cited by 362 · see citing works
American Diabetes Association Professional Practice Committee (2022) · Diabetes Care · doi:10.2337/dc22-s005 · Cited by 445 · see citing works
Galaviz, K. I., Weber, M. B., Straus, A., Haw, J. S., Narayan, K. M. V., & Ali, M. K. (2018) · Diabetes Care · doi:10.2337/dc17-2222 · Cited by 289 · see citing works
Self-citationAmerican Diabetes Association (2017) · Diabetes Care · doi:10.2337/dc17-s007 · Cited by 281 · see citing works
American Association of Diabetes Educators (2020) · The Diabetes Educator · doi:10.1177/0145721719894903 · Cited by 184 · see citing works
Reach and use of diabetes prevention services in the United States, 2016-2017.
Ali, M. K., McKeever Bullard, K., Imperatore, G., Benoit, S. R., Rolka, D. B., Albright, A. L., & Gregg, E. W. (2019) · JAMA Network Open · doi:10.1001/jamanetworkopen.2019.3160 · Cited by 153 · see citing works
Self-citationEngagement and outcomes in a digital Diabetes Prevention Program: 3-year update
Sepah, S. C., Jiang, L., Ellis, R. J., McDermott, K., & Peters, A. L. (2017) · BMJ Open Diabetes Research & Care · doi:10.1136/bmjdrc-2017-000422 · Cited by 122 · see citing works
Effects of a Digital Diabetes Prevention Program: An RCT
Katula, J. A., Dressler, E. V., Kittel, C. A., Harvin, L. N., Almeida, F. A., Wilson, K. E., Michaud, T. L., Porter, G. C., Brito, F. A., Goessl, C. L., et al. (2022) · American Journal of Preventive Medicine · doi:10.1016/j.amepre.2021.10.023 · Cited by 86 · see citing works
Evidence and challenges for translation and population impact of the Diabetes Prevention Program.
Ackermann, R. T., & O’Brien, M. J. (2020) · Current Diabetes Reports · doi:10.1007/s11892-020-1293-4 · Cited by 62 · see citing works
Svensson, C. K., Larsen, J. R., Vedtofte, L., Jakobsen, M. S. L., Jespersen, H. R., Jakobsen, M. I., Koyuncu, K., Schjerning, O., Nielsen, J., Ekstrøm, C. T., et al. (2019) · Acta Psychiatrica Scandinavica · doi:10.1111/acps.12982 · Cited by 66 · see citing works
Khatlani, K., Njike, V., & Costales, V. C. (2019) · Metabolic Syndrome and Related Disorders · doi:10.1089/met.2019.0049 · Cited by 20 · see citing works
Is the Current Lifestyle Modification Approach to Diabetes Prevention in the U.S. a Success?
Echouffo-Tcheugui, J. B., Chakkalakal, R. J., & Ali, M. K. (2025) · Diabetes Care · doi:10.2337/dci24-0040 · Cited by 11 · see citing works
Self-citationFitzpatrick, S. L., Mayhew, M., Rawlings, A. M., Smith, N., Nyongesa, D. B., Vollmer, W. M., Stevens, V. J., Grall, S. K., & Fortmann, S. P. (2022) · Clinical Diabetes · doi:10.2337/cd21-0114 · Cited by 5 · see citing works
- Authors
- Mudaliar, U., Zabetian, A., Goodman, M., Echouffo-Tcheugui, J. B., Albright, A. L., Gregg, E. W., & Ali, M. K.
- Affiliations
- Emory University (US)
- Harvard University (US)
- Centers for Disease Control and Prevention (US)
- Corresponding author
- Mudaliar, Uma
- Venue
- PLOS Medicine
- Publisher
- Public Library of Science (PLoS)
- Published
- 2016-07-26
- Volume
- 13
- Issue
- 7
- Pages
- e1002095
- ISSN
- 1549-1277 (ISSN-L)
- 1549-1676
- PMC
- PMC4961455
- OpenAlex
- W2491346741
- Cited by
- 146
- References
- 75
- Citations by year
- 2026: 4 · 2025: 6 · 2024: 4 · 2023: 16 · 2022: 17 · 2021: 19 · 2020: 20 · 2019: 14 · 2018: 24 · 2017: 20 · 2016: 2
- FWCI
- 2.94
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- public-domain
- creativecommons.org/publicdomain/zero/1.0/ (vor)
- Locations
- PLoS Medicine (publishedVersion, public-domain)
- Europe PMC (PubMed Central) (publishedVersion, public-domain)
- PubMed Central (publishedVersion, public-domain)
- PubMed (publishedVersion)
- Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Figshare (submittedVersion, cc-by)
- Spiral (Imperial College London) (submittedVersion, public-domain)
- Topics
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes, Cardiovascular Risks, and Lipoproteins
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Education
- Health Sciences › Medicine › Physiology › Physical Activity and Health
- Keywords
- Diabetes Prevention Program, lifestyle modification, weight loss, cardiometabolic risk factors, prediabetes, type 2 diabetes prevention, glycemic control, HbA1c, fasting blood glucose, blood pressure, cholesterol, online intervention, community-based intervention, lay health workers, physical activity, dietary fat restriction
- MeSH terms
- Cardiovascular Diseases, Diabetes Mellitus, Type 2, Female, Humans, Male, Middle Aged, Risk Factors, United States, Treatment Outcome, Risk Reduction Behavior
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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