The American Diabetes Association (ADA) “Standards of Medical Care in Diabetes” includes the ADA’s current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, a multidisciplinary expert committee (https://doi.org/10.2337/dc22-SPPC), are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA’s clinical practice recommendations, please refer to the Standards of Care Introduction (https://doi.org/10.2337/dc22-SINT). Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

For guidelines related to screening for increased risk for type 2 diabetes (prediabetes), please refer to Section 2, “Classification and Diagnosis of Diabetes” (https://doi.org/10.2337/dc22-S002). For guidelines related to screening, diagnosis, and management of type 2 diabetes in youth, please refer to Section 14, “Children and Adolescents” (https://doi.org/10.2337/dc22-S014).

Recommendation

  • 3.1 Monitor for the development of type 2 diabetes in those with prediabetes at least annually, modified based on individual risk/benefit assessment. E

Screening for prediabetes and type 2 diabetes risk through an informal assessment of risk factors (Table 2.3) or with an assessment tool, such as the American Diabetes Association risk test (Fig. 2.1), is recommended to guide providers on whether performing a diagnostic test for prediabetes (Table 2.5) and previously undiagnosed type 2 diabetes (Table 2.2) is appropriate (see Section 2, “Classification and Diagnosis of Diabetes,” https://doi.org/10.2337/dc22-S002). Testing high-risk patients for prediabetes is warranted because the laboratory assessment is safe and reasonable in cost, substantial time exists before the development of type 2 diabetes and its complications during which one can intervene, and there is an effective means of preventing type 2 diabetes in those determined to have prediabetes with an A1C 5.7–6.4% (39–47 mmol/mol), impaired glucose tolerance, or impaired fasting glucose. The utility of A1C screening for prediabetes and diabetes may be limited in the presence of hemoglobinopathies and conditions that affect red blood cell turnover. See Section 2, “Classification and Diagnosis of Diabetes” (https://doi.org/10.2337/dc22-S002), and Section 6, “Glycemic Targets” (https://doi.org/10.2337/dc22-S006), for additional details on the appropriate use and limitations of A1C testing.

Recommendations

  • 3.2 Refer adults with overweight/obesity at high risk of type 2 diabetes, as typified by the Diabetes Prevention Program (DPP), to an intensive lifestyle behavior change program consistent with the DPP to achieve and maintain 7% loss of initial body weight, and increase moderate-intensity physical activity (such as brisk walking) to at least 150 min/week. A

  • 3.3 A variety of eating patterns can be considered to prevent diabetes in individuals with prediabetes. B

  • 3.4 Given the cost-effectiveness of lifestyle behavior modification programs for diabetes prevention, such diabetes prevention programs should be offered to patients. A Diabetes prevention programs should be covered by third-party payers and inconsistencies in access should be addressed.

  • 3.5 Based on patient preference, certified technology-assisted diabetes prevention programs may be effective in preventing type 2 diabetes and should be considered. B

The Diabetes Prevention Program

Several major randomized controlled trials, including the Diabetes Prevention Program (DPP) (1), the Finnish Diabetes Prevention Study (DPS) (2), and the Da Qing Diabetes Prevention Study (Da Qing study) (3), demonstrate that lifestyle/behavioral therapy with individualized reduced-calorie meal plan is highly effective in preventing or delaying type 2 diabetes and improving other cardiometabolic markers (such as blood pressure, lipids, and inflammation) (4). The strongest evidence for diabetes prevention in the U.S. comes from the DPP trial (1). The DPP demonstrated that intensive lifestyle intervention could reduce the risk of incident type 2 diabetes by 58% over 3 years. Follow-up of three large studies of lifestyle intervention for diabetes prevention has shown sustained reduction in the risk of progression to type 2 diabetes: 39% reduction at 30 years in the Da Qing study (5), 43% reduction at 7 years in the Finnish DPS (2), and 34% reduction at 10 years (6) and 27% reduction at 15 years (7) in the U.S. Diabetes Prevention Program Outcomes Study (DPPOS).

The two major goals of the DPP intensive lifestyle intervention were to achieve and maintain a minimum of 7% weight loss and 150 min of physical activity per week similar in intensity to brisk walking. The DPP lifestyle intervention was a goal-based intervention: all participants were given the same weight loss and physical activity goals, but individualization was permitted in the specific methods used to achieve the goals (8). Although weight loss was the most important factor to reduce the risk of incident diabetes, it was also found that achieving the target behavioral goal of at least 150 min of physical activity per week, even without achieving the weight loss goal, reduced the incidence of type 2 diabetes by 44% (9).

The 7% weight loss goal was selected because it was feasible to achieve and maintain and likely to lessen the risk of developing diabetes. Participants were encouraged to achieve the 7% weight loss during the first 6 months of the intervention. Further analysis suggests maximal prevention of diabetes with at least 7–10% weight loss (9). The recommended pace of weight loss was 1–2 lb/week. Calorie goals were calculated by estimating the daily calories needed to maintain the participant’s initial weight and subtracting 500–1,000 calories/day (depending on initial body weight). The initial focus was on reducing total dietary fat. After several weeks, the concept of calorie balance and the need to restrict calories as well as fat was introduced (8).

The goal for physical activity was selected to approximate at least 700 kcal/week expenditure from physical activity. For ease of translation, this goal was described as at least 150 min of moderate-intensity physical activity per week similar in intensity to brisk walking. Participants were encouraged to distribute their activity throughout the week with a minimum frequency of three times per week and at least 10 min per session. A maximum of 75 min of strength training could be applied toward the total 150 min/week physical activity goal (8).

To implement the weight loss and physical activity goals, the DPP used an individual model of treatment rather than a group-based approach. This choice was based on a desire to intervene before participants had the possibility of developing diabetes or losing interest in the program. The individual approach also allowed for tailoring of interventions to reflect the diversity of the population (8).

The DPP intervention was administered as a structured core curriculum followed by a flexible maintenance program of individual counseling, group sessions, motivational campaigns, and restart opportunities. The 16-session core curriculum was completed within the first 24 weeks of the program and included sessions on lowering calories, increasing physical activity, self-monitoring, maintaining healthy lifestyle behaviors, and guidance on managing psychological, social, and motivational challenges. Further details are available regarding the core curriculum sessions (8).

Nutrition

Dietary counseling for weight loss in the DPP lifestyle intervention arm included a reduction of total dietary fat and calories (1,8,9). However, evidence suggests that there is not an ideal percentage of calories from carbohydrate, protein, and fat for all people to prevent diabetes; therefore, macronutrient distribution should be based on an individualized assessment of current eating patterns, preferences, and metabolic goals (10). Based on other intervention trials, a variety of eating patterns characterized by the totality of food and beverages habitually consumed (10,11) may also be appropriate for patients with prediabetes (10), including Mediterranean-style and low-carbohydrate eating plans (1215). Observational studies have also shown that vegetarian, plant-based (may include some animal products), and Dietary Approaches to Stop Hypertension (DASH) eating patterns are associated with a lower risk of developing type 2 diabetes (1619). Evidence suggests that the overall quality of food consumed (as measured by the Healthy Eating Index, Alternative Healthy Eating Index, and DASH score), with an emphasis on whole grains, legumes, nuts, fruits, and vegetables and minimal refined and processed foods, is also associated with a lower risk of type 2 diabetes (18,2022). As is the case for those with diabetes, individualized medical nutrition therapy (see Section 5, “Facilitating Behavior Change and Well-being to Improve Health Outcomes,” https://doi.org/10.2337/dc22-S005, for more detailed information) is effective in lowering A1C in individuals diagnosed with prediabetes (23).

Physical Activity

Just as 150 min/week of moderate-intensity physical activity, such as brisk walking, showed beneficial effects in those with prediabetes (1), moderate-intensity physical activity has been shown to improve insulin sensitivity and reduce abdominal fat in children and young adults (24,25). On the basis of these findings, providers are encouraged to promote a DPP-style program, including a focus on physical activity, to all individuals who have been identified to be at an increased risk of type 2 diabetes. In addition to aerobic activity, an exercise regimen designed to prevent diabetes may include resistance training (8,26,27). Breaking up prolonged sedentary time may also be encouraged, as it is associated with moderately lower postprandial glucose levels (28,29). The preventive effects of exercise appear to extend to the prevention of gestational diabetes mellitus (GDM) (30).

Delivery and Dissemination of Lifestyle Behavior Change for Diabetes Prevention

Because the intensive lifestyle intervention in the DPP was effective in preventing type 2 diabetes among those at high risk for the disease and lifestyle behavior change programs for diabetes prevention were shown to be cost-effective, broader efforts to disseminate scalable lifestyle behavior change programs for diabetes prevention with coverage by third-party payers ensued (3135). Group delivery of DPP content in community or primary care settings has demonstrated the potential to reduce overall program costs while still producing weight loss and diabetes risk reduction (3640).

The Centers for Disease Control and Prevention (CDC) developed the National Diabetes Prevention Program (National DPP), a resource designed to bring such evidence-based lifestyle change programs for preventing type 2 diabetes to communities (www.cdc.gov/diabetes/prevention/index.htm). This online resource includes locations of CDC-recognized diabetes prevention lifestyle change programs (available at www.cdc.gov/diabetes/prevention/find-a-program.html). To be eligible for this program, patients must have a BMI in the overweight range and be at risk for diabetes based on laboratory testing, a previous diagnosis of GDM, or a positive risk test (available at www.cdc.gov/prediabetes/takethetest/). Results from the CDC’s National DPP during the first 4 years of implementation are promising and demonstrate cost-efficacy (41). The CDC has also developed the Diabetes Prevention Impact Tool Kit (available at nccd.cdc.gov/toolkit/diabetesimpact) to help organizations assess the economics of providing or covering the National DPP lifestyle change program (42). In an effort to expand preventive services using a cost-effective model that began in April 2018, the Centers for Medicare & Medicaid Services expanded Medicare reimbursement coverage for the National DPP lifestyle intervention to organizations recognized by the CDC that become Medicare suppliers for this service (at innovation.cms.gov/innovation-models/medicare-diabetes-prevention-program). The locations of Medicare DPPs are available online at innovation.cms.gov/innovation-models/medicare-diabetes-prevention-program/mdpp-map. To qualify for Medicare coverage, patients must have BMI >25 kg/m2 (or BMI >23 kg/m2 if self-identified as Asian) and laboratory testing consistent with prediabetes in the last year. Medicaid coverage of the DPP lifestyle intervention is also expanding on a state-by-state basis.

While CDC-recognized behavioral counseling programs, including Medicare DPP services, have met minimum quality standards and are reimbursed by many payers, there have been lower retention rates reported for younger adults and racial/ethnic minority populations (43). Therefore, other programs and modalities of behavioral counseling for diabetes prevention may also be appropriate and efficacious based on patient preferences and availability. The use of community health workers to support DPP efforts has been shown to be effective and cost-effective (44,45) (see Section 1, “Improving Care and Promoting Health in Populations,” https://doi.org/10.2337/dc22-S001, for more information). The use of community health workers may facilitate adoption of behavior changes for diabetes prevention while bridging barriers related to social determinants of health, though coverage by third-party payers remains problematic. Counseling by registered dietitians/registered dietitian nutritionists (RDNs) has been shown to help individuals with prediabetes improve eating habits, increase physical activity, and achieve 7–10% weight loss (10,4648). Individualized medical nutrition therapy (see Section 5, “Facilitating Behavior Change and Well-being to Improve Health Outcomes,” https://doi.org/10.2337/dc22-S005, for more detailed information) is also effective in improving glycemia in individuals diagnosed with prediabetes (23,46). Furthermore, trials involving medical nutrition therapy for patients with prediabetes found significant reductions in weight, waist circumference, and glycemia. Individuals with prediabetes can benefit from referral to an RDN for individualized medical nutrition therapy upon diagnosis and at regular intervals throughout their treatment regimen (48,49). Other allied health professionals, such as pharmacists and diabetes care and education specialists, may be considered for diabetes prevention efforts (50,51).

Technology-assisted programs may effectively deliver the DPP program (5257). Such technology-assisted programs may deliver content through smartphone, web-based applications, and telehealth and may be an acceptable and efficacious option to bridge barriers, particularly for low-income and rural patients; however, not all programs are effective in helping people reach targets for diabetes prevention (52,5860). The CDC Diabetes Prevention Recognition Program (DPRP) (www.cdc.gov/diabetes/prevention/requirements-recognition.htm) certifies technology-assisted modalities as effective vehicles for DPP-based programs; such programs must use an approved curriculum, include interaction with a coach, and attain the DPP outcomes of participation, physical activity reporting, and weight loss. Therefore, providers should consider referring patients with prediabetes to certified technology-assisted DPP programs based on patient preference.

Recommendations

  • 3.6 Metformin therapy for prevention of type 2 diabetes should be considered in adults with prediabetes, as typified by the Diabetes Prevention Program, especially those aged 25–59 years with BMI ≥35 kg/m2, higher fasting plasma glucose (e.g., ≥110 mg/dL), and higher A1C (e.g., ≥6.0%), and in women with prior gestational diabetes mellitus. A

  • 3.7 Long-term use of metformin may be associated with biochemical vitamin B12 deficiency; consider periodic measurement of vitamin B12 levels in metformin-treated patients, especially in those with anemia or peripheral neuropathy. B

Because weight loss through behavior changes in diet and exercise alone can be difficult to maintain long term (6), people being treated with weight loss therapy may benefit from support and additional pharmacotherapeutic options, if needed. Various pharmacologic agents used to treat diabetes have been evaluated for diabetes prevention. Metformin, α-glucosidase inhibitors, liraglutide, thiazolidinediones, testosterone (61), and insulin have been shown to lower the incidence of diabetes in specific populations (6267), whereas diabetes prevention was not seen with nateglinide (68). In addition, several weight loss medications like orlistat and phentermine topiramate have also been shown in research studies to decrease the incidence of diabetes to various degrees in those with prediabetes (69,70). Studies of other pharmacologic agents have shown some efficacy in diabetes prevention with valsartan but no efficacy in preventing diabetes with ramipril or anti-inflammatory drugs (7174). Although the Vitamin D and Type 2 Diabetes (D2d) prospective randomized controlled trial showed no significant benefit of vitamin D versus placebo on the progression to type 2 diabetes in individuals at high risk (75), post hoc analyses and meta-analyses suggest a potential benefit in specific populations (7578). Further research is needed to define patient characteristics and clinical indicators where vitamin D supplementation may be of benefit (61).

No pharmacologic agent has been approved by the U.S. Food and Drug Administration specifically for diabetes prevention. The risk versus benefit of each medication must be weighed. Metformin has the strongest evidence base (1) and demonstrated long-term safety as pharmacologic therapy for diabetes prevention (79). For other drugs, cost, side effects, treatment goals, and durable efficacy require consideration.

Metformin was overall less effective than lifestyle modification in the DPP, though group differences declined over time in the DPPOS (7), and metformin may be cost-saving over a 10-year period (33). During initial follow-up in the DPP, metformin was as effective as lifestyle modification in participants with BMI ≥35 kg/m2 and in younger participants aged 25–44 years (1). In the DPP, for women with a history of GDM, metformin and intensive lifestyle modification led to an equivalent 50% reduction in diabetes risk (80), and both interventions remained highly effective during a 10-year follow-up period (81). By the time of the 15-year follow-up (DPPOS), exploratory analyses demonstrated that participants with a higher baseline fasting glucose (≥110 mg/dL vs. 95–109 mg/dL), those with a higher A1C (6.0–6.4% vs. <6.0%), and women with a history of GDM (vs. women without a history of GDM) experienced higher risk reductions with metformin, identifying subgroups of participants that benefitted the most from metformin (82). In the Indian Diabetes Prevention Program (IDPP-1), metformin and the lifestyle intervention reduced diabetes risk similarly at 30 months; of note, the lifestyle intervention in IDPP-1 was less intensive than that in the DPP (83). Based on findings from the DPP, metformin should be recommended as an option for high-risk individuals (e.g., those with a history of GDM or those with BMI ≥35 kg/m2). Consider periodic monitoring of vitamin B12 levels in those taking metformin chronically to check for possible deficiency (84,85) (see Section 9, “Pharmacologic Approaches to Glycemic Treatment,” https://doi.org/10.2337/dc22-S009, for more details).

Recommendation

  • 3.8 Prediabetes is associated with heightened cardiovascular risk; therefore, screening for and treatment of modifiable risk factors for cardiovascular disease are suggested. B

People with prediabetes often have other cardiovascular risk factors, including hypertension and dyslipidemia (86), and are at increased risk for cardiovascular disease (87,88). Evaluation for tobacco use and referral for tobacco cessation, if indicated, should be part of routine care for those at risk for diabetes. Of note, the years immediately following smoking cessation may represent a time of increased risk for diabetes (8991), a time when patients should be monitored for diabetes development and receive the concurrent evidence-based lifestyle behavior change for diabetes prevention described in this section. See Section 5, “Facilitating Behavior Change and Well-being to Improve Health Outcomes” (https://doi.org/10.2337/dc22-S005), for more detailed information. The lifestyle interventions for weight loss in study populations at risk for type 2 diabetes have shown a reduction in cardiovascular risk factors and the need for medications used to treat these cardiovascular risk factors (92,93). In longer-term follow-up, lifestyle interventions for diabetes prevention also prevented the development of microvascular complications among women enrolled in the DPPOS and in the study population enrolled in the China Da Qing Diabetes Prevention Outcome Study (7,94). The lifestyle intervention in the latter study was also efficacious in preventing cardiovascular disease and mortality at 23 and 30 years of follow-up (3,5). Treatment goals and therapies for hypertension and dyslipidemia in the primary prevention of cardiovascular disease for people with prediabetes should be based on their level of cardiovascular risk, and increased vigilance is warranted to identify and treat these and other cardiovascular risk factors (95).

Recommendation

  • 3.9 In adults with overweight/obesity at high risk of type 2 diabetes, care goals should include weight loss or prevention of weight gain, minimizing progression of hyperglycemia, and attention to cardiovascular risk and associated comorbidites. B

Individualized risk/benefit should be considered in screening, intervention, and monitoring for the prevention or delay of type 2 diabetes and associated comorbidities. Multiple factors, including age, BMI, and other comorbidities, may influence risk of progression to diabetes and lifetime risk of complications (96,97). In the DPP, which enrolled high-risk individuals with impaired glucose tolerance, elevated fasting glucose, and elevated BMI, the crude incidence of diabetes within the placebo arm was 11.0 cases per 100 person-years, with a cumulative 3-year incidence of diabetes of 28.9% (1). In the community-based Atherosclerosis Risk in Communities (ARIC) study, observational follow-up of older adults (mean age 75 years) with laboratory evidence of prediabetes (based on A1C 5.7–6.4% and/or fasting glucose 100–125 mg/dL) but not meeting specific BMI criteria found much lower progression to diabetes over 6 years: 9% of those with A1C-defined prediabetes, 8% with impaired fasting glucose (97).

Thus, it is important to individualize the risk/benefit of intervention and consider person-centered goals. Risk models have explored risk-based benefit, in general finding higher benefit of intervention in those at highest risk (9). Diabetes prevention and observational studies highlight several key principles, which may guide patient-centered goals. In the DPP, which enrolled a high-risk population meeting criteria for overweight/obesity, weight loss was an important mediator of diabetes prevention or delay, with greater metabolic benefit generally seen with greater weight loss (9,98). In the DPP/DPPOS, progression to diabetes, duration of diabetes, and mean level of glycemia were important determinants of development of microvascular complications (7). Furthermore, ability to achieve normal glucose regulation, even once, during the DPP was associated with a lower risk of diabetes and lower risk of microvascular complications (99). Observational follow up of the Da Qing study also showed that regression from impaired glucose tolerance to normal glucose tolerance or remaining with impaired glucose tolerance rather than progressing to type 2 diabetes at the end of the 6-year intervention trial resulted in significantly lower risk of cardiovascular disease and microvascular disease over 30 years (100). Prediabetes is associated with increased cardiovascular disease and mortality (88), emphasizing the importance of attending to cardiovascular risk in this population.

*

A complete list of members of the American Diabetes Association Professional Practice Committee can be found at https://doi.org/10.2337/dc22-SPPC.

Suggested citation: American Diabetes Association Professional Practice Committee. 3. Prevention or delay of type 2 diabetes and associated comorbidities: Standards of Medical Care in Diabetes—2022. Diabetes Care 2022;45(Suppl. 1):S39–S45

1
Knowler
WC
,
Barrett-Connor
E
,
Fowler
SE
, et al.;
Diabetes Prevention Program Research Group
.
Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin
.
N Engl J Med
2002
;
346
:
393
403
2
Lindström
J
,
Ilanne-Parikka
P
,
Peltonen
M
, et al.;
Finnish Diabetes Prevention Study Group
.
Sustained reduction in the incidence of type 2 diabetes by lifestyle intervention: follow-up of the Finnish Diabetes Prevention Study
.
Lancet
2006
;
368
:
1673
1679
3
Li
G
,
Zhang
P
,
Wang
J
, et al
.
Cardiovascular mortality, all-cause mortality, and diabetes incidence after lifestyle intervention for people with impaired glucose tolerance in the Da Qing Diabetes Prevention Study: a 23-year follow-up study
.
Lancet Diabetes Endocrinol
2014
;
2
:
474
480
4
Nathan
DM
,
Bennett
PH
,
Crandall
JP
, et al.;
DPP Research Group
.
Does diabetes prevention translate into reduced long-term vascular complications of diabetes?
Diabetologia
2019
;
62
:
1319
1328
5
Gong
Q
,
Zhang
P
,
Wang
J
, et al.;
Da Qing Diabetes Prevention Study Group
.
Morbidity and mortality after lifestyle intervention for people with impaired glucose tolerance: 30-year results of the Da Qing Diabetes Prevention Outcome Study
.
Lancet Diabetes Endocrinol
2019
;
7
:
452
461
6
Knowler
WC
,
Fowler
SE
,
Hamman
RF
, et al.;
Diabetes Prevention Program Research Group
.
10-year follow-up of diabetes incidence and weight loss in the Diabetes Prevention Program Outcomes Study
.
Lancet
2009
;
374
:
1677
1686
7
Diabetes Prevention Program Research Group
;
Nathan
DM
,
Barrett-Connor
E
,
Crandall
JP
, et al
.
Long-term effects of lifestyle intervention or metformin on diabetes development and microvascular complications: the DPP Outcomes Study
.
Lancet Diabetes Endocrinol
2015
;
3
:
866
875
8
Diabetes Prevention Program (DPP) Research Group
.
The Diabetes Prevention Program (DPP): description of lifestyle intervention
.
Diabetes Care
2002
;
25
:
2165
2171
9
Hamman
RF
,
Wing
RR
,
Edelstein
SL
, et al
.
Effect of weight loss with lifestyle intervention on risk of diabetes
.
Diabetes Care
2006
;
29
:
2102
2107
10
Evert
AB
,
Dennison
M
,
Gardner
CD
, et al
.
Nutrition therapy for adults with diabetes or prediabetes: a consensus report
.
Diabetes Care
2019
;
42
:
731
754
11
U.S. Department of Agriculture and U.S. Department of Health and Human Services. Dietary Guidelines for Americans, 2020–2025
.
9th Edition. December 2020. Accessed 30 October 2021. Available from https://www.dietaryguidelines.gov/resources/2020-2025-dietary-guidelines-online-materials
12
Salas-Salvadó
J
,
Guasch-Ferré
M
,
Lee
C-H
,
Estruch
R
,
Clish
CB
,
Ros
E
.
Protective effects of the Mediterranean diet on type 2 diabetes and metabolic syndrome
.
J Nutr
2016
;
146
:
920S
927S
13
Bloomfield
HE
,
Koeller
E
,
Greer
N
,
MacDonald
R
,
Kane
R
,
Wilt
TJ
.
Effects on health outcomes of a Mediterranean diet with no restriction on fat intake: a systematic review and meta-analysis
.
Ann Intern Med
2016
;
165
:
491
500
14
Estruch
R
,
Ros
E
,
Salas-Salvadó
J
, et al.;
PREDIMED Study Investigators
.
Primary prevention of cardiovascular disease with a Mediterranean diet supplemented with extra-virgin olive oil or nuts
.
N Engl J Med
2018
;
378
:
e34
15
Stentz
FB
,
Brewer
A
,
Wan
J
, et al
.
Remission of pre-diabetes to normal glucose tolerance in obese adults with high protein versus high carbohydrate diet: randomized control trial
.
BMJ Open Diabetes Res Care
2016
;
4
:
e000258
16
Chiu
THT
,
Pan
W-H
,
Lin
M-N
,
Lin
C-L
.
Vegetarian diet, change in dietary patterns, and diabetes risk: a prospective study
.
Nutr Diabetes
2018
;
8
:
12
17
Lee
Y
,
Park
K
.
Adherence to a vegetarian diet and diabetes risk: a systematic review and meta-analysis of observational studies
.
Nutrients
2017
;
9
:
E603
18
Qian
F
,
Liu
G
,
Hu
FB
,
Bhupathiraju
SN
,
Sun
Q
.
Association between plant-based dietary patterns and risk of type 2 diabetes: a systematic review and meta-analysis
.
JAMA Intern Med
2019
;
179
:
1335
1344
19
Esposito
K
,
Chiodini
P
,
Maiorino
MI
,
Bellastella
G
,
Panagiotakos
D
,
Giugliano
D
.
Which diet for prevention of type 2 diabetes? A meta-analysis of prospective studies
.
Endocrine
2014
;
47
:
107
116
20
Ley
SH
,
Hamdy
O
,
Mohan
V
,
Hu
FB
.
Prevention and management of type 2 diabetes: dietary components and nutritional strategies
.
Lancet
2014
;
383
:
1999
2007
21
Jacobs
S
,
Harmon
BE
,
Boushey
CJ
, et al
.
A priori-defined diet quality indexes and risk of type 2 diabetes: the Multiethnic Cohort
.
Diabetologia
2015
;
58
:
98
112
22
Chiuve
SE
,
Fung
TT
,
Rimm
EB
, et al
.
Alternative dietary indices both strongly predict risk of chronic disease
.
J Nutr
2012
;
142
:
1009
1018
23
Parker
AR
,
Byham-Gray
L
,
Denmark
R
,
Winkle
PJ
.
The effect of medical nutrition therapy by a registered dietitian nutritionist in patients with prediabetes participating in a randomized controlled clinical research trial
.
J Acad Nutr Diet
2014
;
114
:
1739
1748
24
Fedewa
MV
,
Gist
NH
,
Evans
EM
,
Dishman
RK
.
Exercise and insulin resistance in youth: a meta-analysis
.
Pediatrics
2014
;
133
:
e163
e174
25
Davis
CL
,
Pollock
NK
,
Waller
JL
, et al
.
Exercise dose and diabetes risk in overweight and obese children: a randomized controlled trial
.
JAMA
2012
;
308
:
1103
1112
26
Sigal
RJ
,
Alberga
AS
,
Goldfield
GS
, et al
.
Effects of aerobic training, resistance training, or both on percentage body fat and cardiometabolic risk markers in obese adolescents: the Healthy Eating Aerobic and Resistance Training in Youth randomized clinical trial
.
JAMA Pediatr
2014
;
168
:
1006
1014
27
Dai
X
,
Zhai
L
,
Chen
Q
, et al
.
Two-year-supervised resistance training prevented diabetes incidence in people with prediabetes: a randomised control trial
.
Diabetes Metab Res Rev
2019
;
35
:
e3143
28
Thorp
AA
,
Kingwell
BA
,
Sethi
P
,
Hammond
L
,
Owen
N
,
Dunstan
DW
.
Alternating bouts of sitting and standing attenuate postprandial glucose responses
.
Med Sci Sports Exerc
2014
;
46
:
2053
2061
29
Healy
GN
,
Dunstan
DW
,
Salmon
J
, et al
.
Breaks in sedentary time: beneficial associations with metabolic risk
.
Diabetes Care
2008
;
31
:
661
666
30
Russo
LM
,
Nobles
C
,
Ertel
KA
,
Chasan-Taber
L
,
Whitcomb
BW
.
Physical activity interventions in pregnancy and risk of gestational diabetes mellitus: a systematic review and meta-analysis
.
Obstet Gynecol
2015
;
125
:
576
582
31
Herman
WH
,
Hoerger
TJ
,
Brandle
M
, et al.;
Diabetes Prevention Program Research Group
.
The cost-effectiveness of lifestyle modification or metformin in preventing type 2 diabetes in adults with impaired glucose tolerance
.
Ann Intern Med
2005
;
142
:
323
332
32
Chen
F
,
Su
W
,
Becker
SH
, et al
.
Clinical and economic impact of a digital, remotely-delivered intensive behavioral counseling program on Medicare beneficiaries at risk for diabetes and cardiovascular disease
.
PLoS One
2016
;
11
:
e0163627
33
Diabetes Prevention Program Research Group
.
The 10-year cost-effectiveness of lifestyle intervention or metformin for diabetes prevention: an intent-to-treat analysis of the DPP/DPPOS
.
Diabetes Care
2012
;
35
:
723
730
34
Alva
ML
,
Hoerger
TJ
,
Jeyaraman
R
,
Amico
P
,
Rojas-Smith
L
.
Impact of the YMCA of the USA Diabetes Prevention Program on Medicare spending and utilization
.
Health Aff (Millwood)
2017
;
36
:
417
424
35
Zhou
X
,
Siegel
KR
,
Ng
BP
, et al
.
Cost-effectiveness of diabetes prevention interventions targeting high-risk individuals and whole populations: a systematic review
.
Diabetes Care
2020
;
43
:
1593
1616
36
Ackermann
RT
,
Finch
EA
,
Brizendine
E
,
Zhou
H
,
Marrero
DG
.
Translating the Diabetes Prevention Program into the community. The DEPLOY Pilot Study
.
Am J Prev Med
2008
;
35
:
357
363
37
Balk
EM
,
Earley
A
,
Raman
G
,
Avendano
EA
,
Pittas
AG
,
Remington
PL
.
Combined diet and physical activity promotion programs to prevent type 2 diabetes among persons at increased risk: a systematic review for the Community Preventive Services Task Force
.
Ann Intern Med
2015
;
163
:
437
451
38
Li
R
,
Qu
S
,
Zhang
P
, et al
.
Economic evaluation of combined diet and physical activity promotion programs to prevent type 2 diabetes among persons at increased risk: a systematic review for the Community Preventive Services Task Force
.
Ann Intern Med
2015
;
163
:
452
460
39
Gilmer
T
,
O’Connor
PJ
,
Schiff
JS
, et al
.
Cost-effectiveness of a community-based Diabetes Prevention Program with participation incentives for Medicaid beneficiaries
.
Health Serv Res
2018
;
53
:
4704
4724
40
Ackermann
RT
,
Kang
R
,
Cooper
AJ
, et al
.
Effect on health care expenditures during nationwide implementation of the Diabetes Prevention Program as a health insurance benefit
.
Diabetes Care
2019
;
42
:
1776
1783
41
Ely
EK
,
Gruss
SM
,
Luman
ET
, et al
.
A national effort to prevent type 2 diabetes: participant-level evaluation of CDC’s National Diabetes Prevention Program
.
Diabetes Care
2017
;
40
:
1331
1341
42
Lanza
A
,
Soler
R
,
Smith
B
,
Hoerger
T
,
Neuwahl
S
,
Zhang
P
.
The Diabetes Prevention Impact Tool Kit: an online tool kit to assess the cost-effectiveness of preventing type 2 diabetes
.
J Public Health Manag Pract
2019
;
25
:
E1
E5
43
Cannon
MJ
,
Masalovich
S
,
Ng
BP
, et al
.
Retention among participants in the National Diabetes Prevention Program lifestyle change program, 2012–2017
.
Diabetes Care
2020
;
43
:
2042
2049
44
The Community Guide
.
Diabetes Prevention: Interventions Engaging Community Health Workers, 2016
.
45
Jacob
V
,
Chattopadhyay
SK
,
Hopkins
DP
, et al
.
Economics of community health workers for chronic disease: findings from Community Guide systematic reviews
.
Am J Prev Med
2019
;
56
:
e95
e106
46
Raynor
HA
,
Davidson
PG
,
Burns
H
, et al
.
Medical nutrition therapy and weight loss questions for the Evidence Analysis Library prevention of type 2 diabetes project: systematic reviews
.
J Acad Nutr Diet
2017
;
117
:
1578
1611
47
Sun
Y
,
You
W
,
Almeida
F
,
Estabrooks
P
,
Davy
B
.
The effectiveness and cost of lifestyle interventions including nutrition education for diabetes prevention: a systematic review and meta-analysis
.
J Acad Nutr Diet
2017
;
117
:
404
421.e36
48
Briggs Early
K
,
Stanley
K
.
Position of the Academy of Nutrition and Dietetics: the role of medical nutrition therapy and registered dietitian nutritionists in the prevention and treatment of prediabetes and type 2 diabetes
.
J Acad Nutr Diet
2018
;
118
:
343
353
49
Powers
MA
,
Bardsley
JK
,
Cypress
M
, et al
.
Diabetes self-management education and support in adults with type 2 diabetes: a consensus report of the American Diabetes Association, the Association of Diabetes Care & Education Specialists, the Academy of Nutrition and Dietetics, the American Academy of Family Physicians, the American Academy of PAs, the American Association of Nurse Practitioners, and the American Pharmacists Association
.
Diabetes Care
2020
;
43
:
1636
1649
50
Hudspeth
BD
.
Power of prevention: the pharmacist’s role in prediabetes management
.
Diabetes Spectr
2018
;
31
:
320
323
51
Butcher
MK
,
Vanderwood
KK
,
Hall
TO
,
Gohdes
D
,
Helgerson
SD
,
Harwell
TS
.
Capacity of diabetes education programs to provide both diabetes self-management education and to implement diabetes prevention services
.
J Public Health Manag Pract
2011
;
17
:
242
247
52
Grock
S
,
Ku
J-H
,
Kim
J
,
Moin
T
.
A Review of technology-assisted interventions for diabetes prevention
.
Curr Diab Rep
2017
;
17
:
107
53
Sepah
SC
,
Jiang
L
,
Peters
AL
.
Translating the Diabetes Prevention Program into an online social network: validation against CDC standards
.
Diabetes Educ
2014
;
40
:
435
443
54
Bian
RR
,
Piatt
GA
,
Sen
A
, et al
.
The effect of technology-mediated diabetes prevention interventions on weight: a meta-analysis
.
J Med Internet Res
2017
;
19
:
e76
55
Sepah
SC
,
Jiang
L
,
Peters
AL
.
Long-term outcomes of a web-based diabetes prevention program: 2-year results of a single-arm longitudinal study
.
J Med Internet Res
2015
;
17
:
e92
56
Moin
T
,
Damschroder
LJ
,
AuYoung
M
, et al
.
Results from a trial of an online Diabetes Prevention Program intervention
.
Am J Prev Med
2018
;
55
:
583
591
57
Michaelides
A
,
Major
J
,
Pienkosz
E
Jr
,
Wood
M
,
Kim
Y
,
Toro-Ramos
T
.
Usefulness of a novel mobile Diabetes Prevention Program delivery platform with human coaching: 65-week observational follow-up
.
JMIR Mhealth Uhealth
2018
;
6
:
e93
58
Kim
SE
,
Castro Sweet
CM
,
Cho
E
,
Tsai
J
,
Cousineau
MR
.
Evaluation of a digital diabetes prevention program adapted for low-income patients, 2016-2018
.
Prev Chronic Dis
2019
;
16
:
E155
59
Vadheim
LM
,
Patch
K
,
Brokaw
SM
, et al
.
Telehealth delivery of the Diabetes Prevention Program to rural communities
.
Transl Behav Med
2017
;
7
:
286
291
60
Fischer
HH
,
Durfee
MJ
,
Raghunath
SG
,
Ritchie
ND
.
Short message service text message support for weight loss in patients with prediabetes: pragmatic trial
.
JMIR Diabetes
2019
;
4
:
e12985
61
Wittert
G
,
Bracken
K
,
Robledo
KP
, et al
.
Testosterone treatment to prevent or revert type 2 diabetes in men enrolled in a lifestyle programme (T4DM): a randomised, double-blind, placebo-controlled, 2-year, phase 3b trial
.
Lancet Diabetes Endocrinol
2021
;
9
:
32
45
62
Chiasson
J-L
,
Josse
RG
,
Gomis
R
,
Hanefeld
M
,
Karasik
A
;
STOP-NIDDM Trail Research Group
.
Acarbose for prevention of type 2 diabetes mellitus: the STOP-NIDDM randomised trial
.
Lancet
2002
;
359
:
2072
2077
63
le Roux
CW
,
Astrup
A
,
Fujioka
K
, et al.;
SCALE Obesity Prediabetes NN8022-1839 Study Group
.
3 years of liraglutide versus placebo for type 2 diabetes risk reduction and weight management in individuals with prediabetes: a randomised, double-blind trial
.
Lancet
2017
;
389
:
1399
1409
64
Gerstein
HC
,
Yusuf
S
,
Bosch
J
, et al.;
DREAM (Diabetes REduction Assessment with ramipril and rosiglitazone Medication) Trial Investigators
.
Effect of rosiglitazone on the frequency of diabetes in patients with impaired glucose tolerance or impaired fasting glucose: a randomised controlled trial
.
Lancet
2006
;
368
:
1096
1105
65
DeFronzo
RA
,
Tripathy
D
,
Schwenke
DC
, et al.;
ACT NOW Study
.
Pioglitazone for diabetes prevention in impaired glucose tolerance
.
N Engl J Med
2011
;
364
:
1104
1115
66
Kawamori
R
,
Tajima
N
,
Iwamoto
Y
,
Kashiwagi
A
,
Shimamoto
K
;
Voglibose Ph-3 Study Group
.
Voglibose for prevention of type 2 diabetes mellitus: a randomised, double-blind trial in Japanese individuals with impaired glucose tolerance
.
Lancet
2009
;
373
:
1607
1614
67
Gerstein
HC
,
Bosch
J
,
Dagenais
GR
, et al.;
ORIGIN Trial Investigators
.
Basal insulin and cardiovascular and other outcomes in dysglycemia
.
N Engl J Med
2012
;
367
:
319
328
68
Holman
RR
,
Haffner
SM
,
McMurray
JJ
, et al.;
NAVIGATOR Study Group
.
Effect of nateglinide on the incidence of diabetes and cardiovascular events
.
N Engl J Med
2010
;
362
:
1463
1476
69
Torgerson
JS
,
Hauptman
J
,
Boldrin
MN
,
Sjöström
L
.
XENical in the prevention of diabetes in obese subjects (XENDOS) study: a randomized study of orlistat as an adjunct to lifestyle changes for the prevention of type 2 diabetes in obese patients
.
Diabetes Care
2004
;
27
:
155
161
70
Garvey
WT
,
Ryan
DH
,
Henry
R
, et al
.
Prevention of type 2 diabetes in subjects with prediabetes and metabolic syndrome treated with phentermine and topiramate extended release
.
Diabetes Care
2014
;
37
:
912
921
71
McMurray
JJ
,
Holman
RR
,
Haffner
SM
, et al.;
NAVIGATOR Study Group
.
Effect of valsartan on the incidence of diabetes and cardiovascular events
.
N Engl J Med
2010
;
362
:
1477
1490
72
Bosch
J
,
Yusuf
S
,
Gerstein
HC
, et al.;
DREAM Trial Investigators
.
Effect of ramipril on the incidence of diabetes
.
N Engl J Med
2006
;
355
:
1551
1562
73
Everett
BM
,
Donath
MY
,
Pradhan
AD
, et al
.
Anti-inflammatory therapy with canakinumab for the prevention and management of diabetes
.
J Am Coll Cardiol
2018
;
71
:
2392
2401
74
Ray
KK
,
Colhoun
HM
,
Szarek
M
, et al.;
ODYSSEY OUTCOMES Committees and Investigators
.
Effects of alirocumab on cardiovascular and metabolic outcomes after acute coronary syndrome in patients with or without diabetes: a prespecified analysis of the ODYSSEY OUTCOMES randomised controlled trial
.
Lancet Diabetes Endocrinol
2019
;
7
:
618
628
75
Pittas
AG
,
Dawson-Hughes
B
,
Sheehan
P
, et al.;
D2d Research Group
.
Vitamin D supplementation and prevention of type 2 diabetes
.
N Engl J Med
2019
;
381
:
520
530
76
Dawson-Hughes
B
,
Staten
MA
,
Knowler
WC
, et al.;
D2d Research Group
.
Intratrial exposure to vitamin D and new-onset diabetes among adults with prediabetes: a secondary analysis from the Vitamin D and Type 2 Diabetes (D2d) study
.
Diabetes Care
2020
;
43
:
2916
2922
77
Zhang
Y
,
Tan
H
,
Tang
J
, et al
.
Effects of vitamin D supplementation on prevention of type 2 diabetes in patients with prediabetes: a systematic review and meta-analysis
.
Diabetes Care
2020
;
43
:
1650
1658
78
Barbarawi
M
,
Zayed
Y
,
Barbarawi
O
, et al
.
Effect of vitamin D supplementation on the incidence of diabetes mellitus
.
J Clin Endocrinol Metab
2020
;
105
:
dgaa335
79
Diabetes Prevention Program Research Group
.
Long-term safety, tolerability, and weight loss associated with metformin in the Diabetes Prevention Program Outcomes Study
.
Diabetes Care
2012
;
35
:
731
737
80
Ratner
RE
,
Christophi
CA
,
Metzger
BE
, et al.;
Diabetes Prevention Program Research Group
.
Prevention of diabetes in women with a history of gestational diabetes: effects of metformin and lifestyle interventions
.
J Clin Endocrinol Metab
2008
;
93
:
4774
4779
81
Aroda
VR
,
Christophi
CA
,
Edelstein
SL
, et al.;
Diabetes Prevention Program Research Group
.
The effect of lifestyle intervention and metformin on preventing or delaying diabetes among women with and without gestational diabetes: the Diabetes Prevention Program outcomes study 10-year follow-up
.
J Clin Endocrinol Metab
2015
;
100
:
1646
1653
82
Diabetes Prevention Program Research Group
.
Long-term effects of metformin on diabetes prevention: identification of subgroups that benefited most in the Diabetes Prevention Program and Diabetes Prevention Program Outcomes Study
.
Diabetes Care
2019
;
42
:
601
608
83
Ramachandran
A
,
Snehalatha
C
,
Mary
S
,
Mukesh
B
,
Bhaskar
AD
;
Indian Diabetes Prevention Programme (IDPP)
.
The Indian Diabetes Prevention Programme shows that lifestyle modification and metformin prevent type 2 diabetes in Asian Indian subjects with impaired glucose tolerance (IDPP-1)
.
Diabetologia
2006
;
49
:
289
297
84
Griffin
SJ
,
Bethel
MA
,
Holman
RR
, et al
.
Metformin in non-diabetic hyperglycaemia: the GLINT feasibility RCT
.
Health Technol Assess
2018
;
22
:
1
64
85
Aroda
VR
,
Edelstein
SL
,
Goldberg
RB
, et al.;
Diabetes Prevention Program Research Group
.
Long-term metformin use and vitamin B12 deficiency in the Diabetes Prevention Program Outcomes Study
.
J Clin Endocrinol Metab
2016
;
101
:
1754
1761
86
Ali
MK
,
Bullard
KM
,
Saydah
S
,
Imperatore
G
,
Gregg
EW
.
Cardiovascular and renal burdens of prediabetes in the USA: analysis of data from serial cross-sectional surveys, 1988-2014
.
Lancet Diabetes Endocrinol
2018
;
6
:
392
403
87
Pan
Y
,
Chen
W
,
Wang
Y
.
Prediabetes and outcome of ischemic stroke or transient ischemic attack: a systematic review and meta-analysis
.
J Stroke Cerebrovasc Dis
2019
;
28
:
683
692
88
Huang
Y
,
Cai
X
,
Mai
W
,
Li
M
,
Hu
Y
.
Association between prediabetes and risk of cardiovascular disease and all cause mortality: systematic review and meta-analysis
.
BMJ
2016
;
355
:
i5953
89
Yeh
H-C
,
Duncan
BB
,
Schmidt
MI
,
Wang
N-Y
,
Brancati
FL
.
Smoking, smoking cessation, and risk for type 2 diabetes mellitus: a cohort study
.
Ann Intern Med
2010
;
152
:
10
17
90
Oba
S
,
Noda
M
,
Waki
K
, et al.;
Japan Public Health Center-Based Prospective Study Group
.
Smoking cessation increases short-term risk of type 2 diabetes irrespective of weight gain: the Japan Public Health Center-Based Prospective Study [published correction appears in PLoS One 2013;8:10.1371/annotation/23aa7c42-9a4d-42a7-8f50-9d0ac4b85396]
PLoS One
2012
;
7
:
e17061
91
Hu
Y
,
Zong
G
,
Liu
G
, et al
.
Smoking cessation, weight change, type 2 diabetes, and mortality
.
N Engl J Med
2018
;
379
:
623
632
92
Orchard
TJ
,
Temprosa
M
,
Barrett-Connor
E
, et al.;
Diabetes Prevention Program Outcomes Study Research Group
.
Long-term effects of the Diabetes Prevention Program interventions on cardiovascular risk factors: a report from the DPP Outcomes Study
.
Diabet Med
2013
;
30
:
46
55
93
Salas-Salvadó
J
,
Díaz-López
A
,
Ruiz-Canela
M
, et al.;
PREDIMED-Plus investigators
.
Effect of a lifestyle intervention program with energy-restricted Mediterranean diet and exercise on weight loss and cardiovascular risk factors: one-year results of the PREDIMED-Plus trial
.
Diabetes Care
2019
;
42
:
777
788
94
Gong
Q
,
Gregg
EW
,
Wang
J
, et al
.
Long-term effects of a randomised trial of a 6-year lifestyle intervention in impaired glucose tolerance on diabetes-related microvascular complications: the China Da Qing Diabetes Prevention Outcome Study
.
Diabetologia
2011
;
54
:
300
307
95
Arnett
DK
,
Blumenthal
RS
,
Albert
MA
, et al
.
2019 ACC/AHA Guideline on the Primary Prevention of Cardiovascular Disease: a report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines
.
Circulation
2019
;
140
:
e596
e646
96
Nadeau
KJ
,
Anderson
BJ
,
Berg
EG
, et al
.
Youth-onset type 2 diabetes consensus report: current status, challenges, and priorities
.
Diabetes Care
2016
;
39
:
1635
1642
97
Rooney
MR
,
Rawlings
AM
,
Pankow
JS
, et al
.
Risk of progression to diabetes among older adults with prediabetes
.
JAMA Intern Med
2021
;
181
:
511
519
98
Lachin
JM
,
Christophi
CA
,
Edelstein
SL
, et al.;
DDK Research Group
.
Factors associated with diabetes onset during metformin versus placebo therapy in the diabetes prevention program
.
Diabetes
2007
;
56
:
1153
1159
99
Perreault
L
,
Pan
Q
,
Schroeder
EB
, et al.;
Diabetes Prevention Program Research Group
.
Regression From prediabetes to normal glucose regulation and prevalence of microvascular disease in the Diabetes Prevention Program Outcomes Study (DPPOS)
.
Diabetes Care
2019
;
42
:
1809
1815
100
Chen
Y
,
Zhang
P
,
Wang
J
, et al
.
Associations of progression to diabetes and regression to normal glucose tolerance with development of cardiovascular and microvascular disease among people with impaired glucose tolerance: a secondary analysis of the 30 year Da Qing Diabetes Prevention Outcome Study
.
Diabetologia
2021
;
64
:
1279
1287
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