Dataset Information

Public Health Approaches to Type 2 Diabetes Prevention: the US National Diabetes Prevention Program and Beyond.

ABSTRACT:

Purpose of review

This article highlights foundational evidence, translation studies, and current research behind type 2 diabetes prevention efforts worldwide, with focus on high-risk populations, and whole-population approaches as catalysts to global prevention.

Recent findings

Continued focus on the goals of foundational lifestyle change program trials and their global translations, and the targeting of those at highest risk through both in-person and virtual modes of program delivery, is critical. Whole-population approaches (e.g., socioeconomic policies, healthy food promotion, environmental/systems changes) and awareness raising are essential complements to efforts aimed at high-risk populations. Successful type 2 diabetes prevention strategies are being realized in the USA through the National Diabetes Prevention Program and elsewhere in the world. A multi-tiered approach involving appropriate risk targeting and whole-population efforts is essential to curb the global diabetes epidemic.

SUBMITTER: Gruss SM

PROVIDER: S-EPMC6682852 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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Publications

Public Health Approaches to Type 2 Diabetes Prevention: the US National Diabetes Prevention Program and Beyond.

Gruss Stephanie M SM Nhim Kunthea K Gregg Edward E Bell Miriam M Luman Elizabeth E Albright Ann A

Current diabetes reports 20190805 9

<h4>Purpose of review</h4>This article highlights foundational evidence, translation studies, and current research behind type 2 diabetes prevention efforts worldwide, with focus on high-risk populations, and whole-population approaches as catalysts to global prevention.<h4>Recent findings</h4>Continued focus on the goals of foundational lifestyle change program trials and their global translations, and the targeting of those at highest risk through both in-person and virtual modes of program de ...[more]

PMID: 31385061

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Project description:BackgroundAntipsychotics contribute to the development of type 2 diabetes mellitus (T2DM) in individuals with schizophrenia. However, the extent of the relationship between antipsychotic use and T2DM varies in different settings, and the magnitude of the drug-specific effects fluctuates widely. This study aimed to explore the association of T2DM with antipsychotic use among enrollees with schizophrenia in China's National Basic Public Health Service Program (NBPHSP) and the drug-specific relationship with T2DM among patients receiving antipsychotic monotherapy.MethodsWe recruited diabetes-free patients with schizophrenia who were enrolled in the NBPHSP of Hunan Province from October 2009 to December 2018. The participants were classified into the following three groups: regular antipsychotic use, intermittent antipsychotic use, and antipsychotic-free groups. The patients were followed up until they received a T2DM diagnosis or until April 2019. Cox regression models were constructed to calculate the overall and drug-specific hazard ratios (HRs) to determine the antipsychotic-T2DM relationship. Interactive and subgroup analyses were performed to assess the heterogeneity of the effects across subgroups.ResultsA total of 122,064 NBPHSP enrollees with schizophrenia were followed up for 1,507,829 cumulative person-years, and 2,313 (1.89%) patients developed T2DM. Patients who regularly and intermittently used antipsychotics had 117% (HR: 2.17, 95% CI: 1.83-2.57) and 53% (HR: 1.53, 95% CI: 1.23-1.90) higher risks of developing T2DM than antipsychotic-free patients, respectively. Regarding monotherapy, the T2DM risk increased by 66, 80, 62, and 64% after the regular use of clozapine, risperidone, chlorpromazine, and perphenazine, respectively. In addition, the antipsychotic-related risk of T2DM decreased as the patient's baseline body mass index, and baseline fasting plasma glucose level, as well as the dietary proportion of animal products, increased.ConclusionAntipsychotics, especially clozapine, risperidone, chlorpromazine, and perphenazine, increased the T2DM risk among NBPHSP enrollees with schizophrenia. Mental health officers should accurately identify enrollees at a high risk of T2DM and take appropriate preventive measures to reduce the incidence of T2DM among patients with schizophrenia.

Project description:IntroductionThis clinical demonstration trial compared the effectiveness of the Veterans Affairs Diabetes Prevention Program (VA-DPP) with an evidence-based usual care weight management program (MOVE!®) in the Veterans Health Administration health system.DesignProspective, pragmatic, non-randomized comparative effectiveness study of two behavioral weight management interventions.Setting/participantsObese/overweight Veterans with prediabetes were recruited from three geographically diverse VA sites between 2012 and 2014.InterventionVA-DPP included 22 group-based intensive lifestyle change sessions.Main outcome measuresWeight change at 6 and 12 months, hemoglobin A1c (HbA1c) at 12 months, and VA health expenditure changes at 15 months were assessed using VA electronic health record and claims data. Between- and within-group comparisons for weight and HbA1c were done using linear mixed-effects models controlling for age, gender, race/ethnicity, baseline outcome values, and site. Analyses were conducted in 2015-2016.ResultsA total of 387 participants enrolled (273 VA-DPP, 114 MOVE!). More VA-DPP participants completed at least one (73.3% VA-DPP vs 57.5% MOVE! p=0.002); four (57.5% VA-DPP vs 42.5% MOVE!, p=0.007); and eight or more sessions (42.5% VA-DPP vs 31% MOVE!, p=0.035). Weight loss from baseline was significant at both 6 (p<0.001) and 12 months (p<0.001) for VA-DPP participants, but only significant at 6 months for MOVE! participants (p=0.004). Between groups, there were significant differences in 6-month weight loss (-4.1 kg VA-DPP vs -1.9 kg MOVE!, p<0.001), but not 12-month weight loss (-3.4 kg VA-DPP vs -2.0 kg MOVE!, p=0.16). There were no significant differences in HbA1c change or outpatient, inpatient, and total VA expenditures.ConclusionsVA-DPP participants had higher participation rates and weight loss at 6 months, but similar weight, HbA1c, and health expenditures at 12 months compared to MOVE!ParticipantsFeatures of VA-DPP may help enhance the capability of MOVE! to reach a larger proportion of the served population and promote individual-level weight maintenance.

Project description:The largest and longest clinical trial of metformin for the prevention of diabetes is the Diabetes Prevention Program/Diabetes Prevention Program Outcomes Study (DPP/DPPOS). In this review, we summarise data from the DPP/DPPOS, focusing on metformin for diabetes prevention, as well as its long-term glycaemic and cardiometabolic effects and safety in people at high-risk of developing diabetes. The DPP (1996-2001) was a RCT of 3234 adults who, at baseline, were at high-risk of developing diabetes. Participants were assigned to masked placebo (n = 1082) or metformin (n = 1073) 850 mg twice daily, or intensive lifestyle intervention (n = 1079). The masked metformin/placebo intervention phase ended approximately 1 year ahead of schedule because of demonstrated efficacy. Primary outcome was reported at 2.8 years. At the end of the DPP, all participants were offered lifestyle education and 88% (n = 2776) of the surviving DPP cohort continued follow-up in the DPPOS. Participants originally assigned to metformin continued to receive metformin, unmasked. The DPP/DPPOS cohort has now been followed for over 15 years with prospective assessment of glycaemic, cardiometabolic, health economic and safety outcomes. After an average follow-up of 2.8 years, metformin reduced the incidence of diabetes by 31% compared with placebo, with a greater effect in those who were more obese, had a higher fasting glucose or a history of gestational diabetes. The DPPOS addressed the longer-term effects of metformin, showing a risk reduction of 18% over 10 and 15 years post-randomisation. Metformin treatment for diabetes prevention was estimated to be cost-saving. At 15 years, lack of progression to diabetes was associated with a 28% lower risk of microvascular complications across treatment arms, a reduction that was no different among treatment groups. Recent findings suggest metformin may reduce atherosclerosis development in men. Originally used for the treatment of type 2 diabetes, metformin, now proven to prevent or delay diabetes, may serve as an important tool in battling the growing diabetes epidemic. Long-term follow-up, currently underway in the DPP/DPPOS, is now evaluating metformin's potential role, when started early in the spectrum of dysglycaemia, on later-stage comorbidities, including cardiovascular disease and cancer.Trial registrationClinicalTrials.gov NCT00038727 and NCT00004992.

Project description:BackgroundThe National Health Service (NHS) Diabetes Prevention Program is a behavior change intervention for adults in England who are identified as being at high risk of developing type 2 diabetes. The face-to-face service was launched in 2016, followed by a digital service (NHS Digital Diabetes Prevention Program [NHS-DDPP]) in 2019. A total of 4 service providers were commissioned to deliver the NHS-DDPP and were required to deliver the digital service in line with a program specification detailing the key intervention content. The fidelity of the behavior change content in the digital service (ie, the extent to which the program is delivered as intended) is currently unknown. Digital interventions may allow higher fidelity as staff do not have to be trained to deliver all intervention content. Assessing fidelity of the intervention design is particularly important to establish the planned behavior change content in the NHS-DDPP and the extent to which this adheres to the program specification. This is the first known independent assessment of design fidelity in a large-scale digital behavior change intervention.ObjectiveThis study aims to assess the fidelity of the behavior change content in each of the 4 NHS-DDPP providers' intervention designs to the full program specification.MethodsWe conducted a document review of each provider's NHS-DDPP intervention design, along with interviews with program developers employed by the 4 digital providers (n=6). Providers' intervention design documents and interview transcripts were coded for behavior change techniques (BCTs; ie, the active ingredients of the intervention) using the Behavior Change Technique Taxonomy version 1 and underpinning theory using the Theory Coding Scheme framework. The BCTs identified in each digital provider's intervention design were compared with the 19 BCTs included in the program specification.ResultsOf the 19 BCTs specified in the program specification, the 4 providers planned to deliver 16 (84%), 17 (89%), 16 (84%), and 16 (84%) BCTs, respectively. An additional 41 unspecified BCTs were included in at least one of the 4 digital providers' intervention designs. By contrast, inconsistent use of the underpinning theory was apparent across providers, and none of the providers had produced a logic model to explain how their programs were expected to work. All providers linked some of their planned BCTs to theoretical constructs; however, justification for the inclusion of other BCTs was not described.ConclusionsThe fidelity of BCT content in the NHS-DDPP was higher than that previously documented for the face-to-face service. Thus, if service users engage with the NHS-DDPP, this should increase the effectiveness of the program. However, given that a clear theoretical underpinning supports the translation of BCTs in intervention designs to intervention delivery, the absence of a logic model describing the constructs to be targeted by specific BCTs is potentially problematic.

Dataset Information

Public Health Approaches to Type 2 Diabetes Prevention: the US National Diabetes Prevention Program and Beyond.

Purpose of review

Recent findings

Publications

Public Health Approaches to Type 2 Diabetes Prevention: the US National Diabetes Prevention Program and Beyond.

Similar Datasets

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