The DOI matches its Crossref record; 45 of the 46 references it cites were found in a registry or an index.
Reach and use of diabetes prevention services in the United States, 2016-2017.
Open accessAbstract
Importance: Coordinated efforts by national organizations in the United States to implement evidence-based lifestyle modification programs are under way to reduce type 2 diabetes (hereinafter referred to as diabetes) and cardiovascular risks. Objective: To provide a status report on the reach and use of diabetes prevention services nationally. Design, Setting, and Participants: This nationally representative, population-based cross-sectional analysis of 2016 and 2017 National Health Interview Survey data was conducted from August 3, 2017, through November 15, 2018. Nonpregnant, noninstitutionalized, civilian respondents 18 years or older at high risk for diabetes, defined as those with no self-reported diabetes diagnosis but with diagnosed prediabetes or an elevated American Diabetes Association (ADA) risk score (>5), were included in the analysis. Analyses were conducted for adults with (and in sensitivity analyses, for those without) elevated body mass index. Main Outcomes and Measures: Absolute numbers and proportions of adults at high risk with elevated body mass index receiving advice about diet, physical activity guidance, referral to weight loss programs, referral to diabetes prevention programs, or any of these, and those affirming engagement in each (or any) activity in the past year were estimated. To identify where gaps exist, a prevention continuum diagram plotted existing vs desired goal achievement. Variation in risk-reducing activities by age, sex, race/ethnicity, educational attainment, insurance status, history of gestational diabetes mellitus, hypertension, or body mass index was also examined. Results: This analysis included 50 912 respondents (representing 223.0 million adults nationally) 18 years or older (mean [SE] age, 46.1 [0.2] years; 48.1% [0.3%] male) with complete data and no self-reported diabetes diagnosis by their health care professional. Of the represented population, 36.0% (80.0 million) had either a physician diagnosis of prediabetes (17.9 million), an elevated ADA risk score (73.3 million), or both (11.3 million). Among those with diagnosed prediabetes, 73.5% (95% CI, 71.6%-75.3%) reported receiving advice and/or referrals for diabetes risk reduction from their health care professional, and, of those, 35.0% (95% CI, 30.5%-39.8%) to 75.8% (95% CI, 73.2%-78.3%) reported engaging in the respective activity or program in the past year. Half of adults with elevated ADA risk scores but no diagnosed prediabetes (50.6%; 95% CI, 49.5%-51.8%) reported receiving risk-reduction advice and/or referral, of whom 33.5% (95% CI, 30.1%-37.0%) to 75.2% (95% CI, 73.4%-76.9%) reported engaging in activities and/or programs. Participation in diabetes prevention programs was exceedingly low. Advice from a health care professional, age range from 45 to 64 years, higher educational attainment, health insurance status, gestational diabetes mellitus, hypertension, and obesity were associated with higher engagement in risk-reducing activities and/or programs. Conclusions and Relevance: Among adults at high risk for diabetes, major gaps in receiving advice and/or referrals and engaging in diabetes risk-reduction activities and/or programs were noted. These results suggest that risk perception, health care professional referral and communication, and insurance coverage may be key levers to increase risk-reducing behaviors in US adults. These findings provide a benchmark from which to monitor future program availability and coverage, identification of prediabetes, and referral to and retention in programs.
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“Travel (for in-person DPPs), scheduling conflicts, and limited cohort availability constrain participation.8”
From An AI-Powered Lifestyle Intervention vs Human Coaching in the Diabetes Prevention Program: A Randomized Clinical Trial (2025) · cites this paper as [8]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Despite these large-scale investments, evidence suggests that among U.S. adults at high risk for diabetes, only half reported receiving any diabetes risk-reduction advice or referral”
From Effects of a Digital Diabetes Prevention Program: An RCT (2022) · cites this paper as [4]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Thus, the current DPP infrastructure is underutilized, and more methods that increase access and engagement are needed.”
From Effects of a Digital Diabetes Prevention Program: An RCT (2022) · cites this paper as [4]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“Conventional Type 2 diabetes (T2D) prevention programs provide key educational components but are significantly underutilized (Ali et al., 2019)”
From A Randomized Controlled Trial of an Acceptance and Commitment Therapy-Informed Diabetes Prevention Program Reduces Body Shame and Distress. (2025) · cites this paper as Ali et al., 2019
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“of those receiving advice/referral, only 34% reported participating in a weight loss program”
From Effects of a Digital Diabetes Prevention Program: An RCT (2022) · cites this paper as [4]
The cited source says what the claim attributes to it.
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“and 40% reported participating in DPP.”
From Effects of a Digital Diabetes Prevention Program: An RCT (2022) · cites this paper as [4]
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Citations
Cites
Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin
(2002) · New England Journal of Medicine · doi:10.1056/nejmoa012512 · Cited by 19,011
Tuomilehto, J., Lindström, J., Eriksson, J. G., Valle, T. T., Hämäläinen, H., Ilanne-Parikka, P., Keinänen-Kiukaanniemi, S., Laakso, M., Louheranta, A., Rastas, M., et al. (2001) · New England Journal of Medicine · doi:10.1056/nejm200105033441801 · Cited by 10,873
Pan, X.-R., Li, G.-W., Hu, Y.-H., Wang, J.-X., Yang, W.-Y., An, Z.-X., Hu, Z.-X., Juan-Lin, Xiao, J.-Z., Cao, H.-B., et al. (1997) · Diabetes Care · doi:10.2337/diacare.20.4.537 · Cited by 4,320
Economic Costs of Diabetes in the U.S. in 2002
American Diabetes Association (2003) · Diabetes Care · doi:10.2337/diacare.26.3.917 · Cited by 4,147
Economic Costs of Diabetes in the U.S. in 2017
American Diabetes Association (2018) · Diabetes Care · doi:10.2337/dci18-0007 · Cited by 2,528
Poor Control of Risk Factors for Vascular Disease Among Adults With Previously Diagnosed Diabetes
Saydah, S. H. (2004) · JAMA · doi:10.1001/jama.291.3.335 · Cited by 1,357
(2015) · The Lancet Diabetes & Endocrinology · doi:10.1016/s2213-8587(15)00291-0 · Cited by 1,029
Achievement of Goals in U.S. Diabetes Care, 1999–2010
Ali, M. K., Bullard, K. M., Saaddine, J. B., Cowie, C. C., Imperatore, G., & Gregg, E. W. (2013) · New England Journal of Medicine · doi:10.1056/nejmsa1213829 · Cited by 979
Self-citationFinancial Incentive–Based Approaches for Weight Loss: A Randomized Trial
Volpp, K. G., John, L. K., Troxel, A. B., Norton, L., Fassbender, J., & Loewenstein, G. (2008) · JAMA · doi:10.1001/jama.2008.804 · Cited by 923
Herman, W. H., Hoerger, T. J., Brandle, M., Hicks, K., Sorensen, S., Zhang, P., Hamman, R. F., Ackermann, R. T., Engelgau, M. M., Ratner, R. E., et al. (2005) · Annals of Internal Medicine · doi:10.7326/0003-4819-142-5-200503010-00007 · Cited by 703
Flagged first, then by citations
1 of the 46 references couldn’t be matched to a known paper.
Research works printed but not linked: 2
- Economic costs of diabetes in the US in 2017, Diabetes Care, 2018
- BergS. 7 steps to get prediabetic patients the preventive help they need. https://www.ama-assn.org/delivering-care/diabetes/7-steps-get-prediabetic-patients-preventive-help-they-need. Published October 4, 2018. Accessed April 4, 2019.
Cited by
Sorted by citations
Prediabetes and what it means: the epidemiological evidence
Echouffo-Tcheugui, J. B., & Selvin, E. (2021) · Annual Review of Public Health · doi:10.1146/annurev-publhealth-090419-102644 · Cited by 406
Gregg, E. W., Buckley, J., Ali, M. K., Davies, J. I., Flood, D., Mehta, R., Griffiths, B., Lim, L., Manne‐Goehler, J., Pearson‐Stuttard, J., et al. (2023) · The Lancet · doi:10.1016/s0140-6736(23)00001-6 · Cited by 267
Self-citationGruss, S. M., Nhim, K., Gregg, E., Bell, M., Luman, E., & Albright, A. (2019) · Current Diabetes Reports · doi:10.1007/s11892-019-1200-z · Cited by 179
Self-citationEffects 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
“One limitation of the study is that although the comparison group received more care than what is typical for patients with prediabetes, it was not a direct comparison with an in-person DPP.”
BackgroundInfluentialEvidence 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
Metadata
- Authors
- Ali, M. K., McKeever Bullard, K., Imperatore, G., Benoit, S. R., Rolka, D. B., Albright, A. L., & Gregg, E. W.
- Affiliations
- Centers for Disease Control and Prevention (US)
- Division of Diabetes Translation, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia
- Corresponding author
- Ali, Mohammed K.
- Venue
- JAMA Network Open
- Publisher
- American Medical Association (AMA)
- Published
- 2019-05-10
- Volume
- 2
- Issue
- 5
- Pages
- e193160
- ISSN
- 2574-3805 (ISSN-L)
- PMC
- PMC6512285
- OpenAlex
- W2943880671
- Cited by
- 153
- References
- 46
- Citations by year
- 2026: 13 · 2025: 21 · 2024: 25 · 2023: 24 · 2022: 26 · 2021: 27 · 2020: 14 · 2019: 3
- FWCI
- 14.21
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- JAMA Network Open (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Spiral (Imperial College London) (submittedVersion, cc-by)
- Funders
- National Institute of Diabetes and Digestive and Kidney Diseases (P30DK111024)
- 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 › Public Health, Environmental and Occupational Health › Health Promotion and Cardiovascular Prevention
- Keywords
- type 2 diabetes prevention, prediabetes, Diabetes Prevention Program, lifestyle modification, physician referral, slimming program, exercise recommendations, dietary recommendations, body mass index, diabetes risk score, health care access disparities, health insurance status, cardiovascular risk reduction, United States adults
- MeSH terms
- Adult, Aged, Cross-Sectional Studies, Diabetes Mellitus, Type 2, Female, Health Promotion, Health Surveys, Humans, Male, Middle Aged, Obesity, Prediabetic State, United States, Health Behavior, Case-Control Studies, Risk Reduction Behavior, Young Adult
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