Type 2 Diabetes Prevention Programs-From Proof-of-Concept Trials to National Intervention and Beyond.

The prevention of type 2 diabetes (T2D) in high-risk people with lifestyle interventions has been demonstrated by several randomized controlled trials. The intervention effect has sustained up to 20 years in post-trial monitoring of T2D incidence. In 2000, Finland launched the national T2D prevention plan. For screening for high T2D risk, the non-laboratory Finnish Diabetes Risk Score was developed and widely used, also in other countries. The incidence of drug-treated T2D has decreased steadily since 2010. The US congress authorized public funding for a national diabetes prevention program (NDPP) in 2010. It was built around a 16-visit program that relies on referral from primary care and self-referral of persons with either prediabetes or by a diabetes risk test. The program uses a train-the-trainer program. In 2015 the program started the inclusion of online programs. There has been limited implementation of nationwide T2D prevention programs in other countries. Despite the convincing results from RCTs in China and India, no translation to the national level was introduced there. T2D prevention efforts in low-and middle-income countries are still limited, but results have been promising. Barriers to efficient interventions are greater in these countries than in high-income countries, where many barriers also exist. Health disparities by socioeconomic status exist for T2D and its risk factors and form a challenge for preventive interventions. It seems that a stronger commitment to T2D prevention is needed, such as the successful WHO Framework Convention on Tobacco Control, which legally binds the countries to act.

Trends in Total and Out-of-pocket Payments for Noninsulin Glucose-Lowering Drugs Among U.S. Adults With Large-Employer Private Health Insurance From 2005 to 2018.

OBJECTIVE: To estimate trends in total payment and patients' out-of-pocket (OOP) payments of noninsulin glucose-lowering drugs by class from 2005 to 2018. RESEARCH DESIGN AND METHODS: We analyzed data for 53 million prescriptions from adults aged >18 years with type 2 diabetes under fee-for-service plans from the 2005-2018 IBM MarketScan Commercial Databases. The total payment was measured as the amount that the pharmacy received, and the OOP payment was the sum of copay, coinsurance, and deductible paid by the beneficiaries. We applied a joinpoint regression to evaluate nonlinear trends in cost between 2005 and 2018. We further conducted a decomposition analysis to explore the drivers for total payment change. RESULTS: Total annual payments for older drug classes, including metformin, sulfonylurea, meglitinide, α-glucosidase inhibitors, and thiazolidinedione, declined during 2005-2018, ranging from -$271 (-53.8%) for metformin to -$2,406 (-92.2%) for thiazolidinedione. OOP payments for these drug classes also reduced. In the same period, the total annual payments for the newer drug classes, including dipeptidyl peptidase-4 inhibitors, glucagon-like peptide 1 receptor agonists, and sodium-glucose cotransporter 2 inhibitors, increased by $2,181 (88.4%), $3,721 (77.6%), and $1,374 (37.0%), respectively. OOP payment for these newer classes remained relatively unchanged. Our study findings indicate that switching toward the newer classes for noninsulin glucose-lowering drugs was the main driver that explained the total payment increase. CONCLUSIONS: Average annual payments and OOP payment for noninsulin glucose-lowering drugs increased significantly from 2005 to 2018. The uptake of newer drug classes was the main driver.

Cost-Effectiveness of the New 2018 American College of Physicians Glycemic Control Guidance Statements Among US Adults With Type 2 Diabetes.

OBJECTIVES: This study aims to estimate the national impact and cost-effectiveness of the 2018 American College of Physicians (ACP) guidance statements compared to the status quo. METHODS: Survey data from the 2011-2016 National Health and Nutrition Examination were used to generate a national representative sample of individuals with diagnosed type 2 diabetes in the United States. Individuals with A1c <6.5% on antidiabetic medications are recommended to deintensify their A1c level to 7.0% to 8.0% (group 1); individuals with A1c 6.5% to 8.0% and a life expectancy of <10 years are recommended to deintensify their A1c level >8.0% (group 2); and individuals with A1c >8.0% and a life expectancy of >10 years are recommended to intensify their A1c level to 7.0% to 8.0% (group 3). We used a Markov-based simulation model to evaluate the lifetime cost-effectiveness of following the ACP recommended A1c level. RESULTS: 14.41 million (58.1%) persons with diagnosed type 2 diabetes would be affected by the new guidance statements. Treatment deintensification would lead to a saving of $363 600 per quality-adjusted life-year (QALY) lost for group 1 and a saving of $118 300 per QALY lost for group 2. Intensifying treatment for group 3 would lead to an additional cost of $44 600 per QALY gain. Nationally, the implementation of the guidance would add 3.2 million life-years and 1.1 million QALYs and reduce healthcare costs by $47.7 billion compared to the status quo. CONCLUSIONS: Implementing the new ACP guidance statements would affect a large number of persons with type 2 diabetes nationally. The new guidance is cost-effective.

Within-Trial Cost-Effectiveness of a Structured Lifestyle Intervention in Adults With Overweight/Obesity and Type 2 Diabetes: Results From the Action for Health in Diabetes (Look AHEAD) Study.

OBJECTIVE: To assess the cost-effectiveness (CE) of an intensive lifestyle intervention (ILI) compared with standard diabetes support and education (DSE) in adults with overweight/obesity and type 2 diabetes, as implemented in the Action for Health in Diabetes study. RESEARCH DESIGN AND METHODS: Data were from 4,827 participants during their first 9 years of study participation from 2001 to 2012. Information on Health Utilities Index Mark 2 (HUI-2) and HUI-3, Short-Form 6D (SF-6D), and Feeling Thermometer (FT), cost of delivering the interventions, and health expenditures was collected during the study. CE was measured by incremental CE ratios (ICERs) in costs per quality-adjusted life year (QALY). Future costs and QALYs were discounted at 3% annually. Costs were in 2012 U.S. dollars. RESULTS: Over the 9 years studied, the mean cumulative intervention costs and mean cumulative health care expenditures were $11,275 and $64,453 per person for ILI and $887 and $68,174 for DSE. Thus, ILI cost $6,666 more per person than DSE. Additional QALYs gained by ILI were not statistically significant measured by the HUIs and were 0.07 and 0.15, respectively, measured by SF-6D and FT. The ICERs ranged from no health benefit with a higher cost based on HUIs to $96,458/QALY and $43,169/QALY, respectively, based on SF-6D and FT. CONCLUSIONS: Whether ILI was cost-effective over the 9-year period is unclear because different health utility measures led to different conclusions.

The Longitudinal Epidemiologic Assessment of Diabetes Risk (LEADR): Unique 1.4 M patient Electronic Health Record cohort.

BACKGROUND: The Longitudinal Epidemiologic Assessment of Diabetes Risk (LEADR) study uses a novel Electronic Health Record (EHR) data approach as a tool to assess the epidemiology of known and new risk factors for type 2 diabetes mellitus (T2DM) and study how prevention interventions affect progression to and onset of T2DM. We created an electronic cohort of 1.4 million patients having had at least 4 encounters with a healthcare organization for at least 24-months; were aged ≥18 years in 2010; and had no diabetes (i.e., T1DM or T2DM) at cohort entry or in the 12 months following entry. EHR data came from patients at nine healthcare organizations across the U.S. between January 1, 2010-December 31, 2016. RESULTS: Approximately 5.9% of the LEADR cohort (82,922 patients) developed T2DM, providing opportunities to explore longitudinal clinical care, medication use, risk factor trajectories, and diagnoses for these patients, compared with patients similarly matched prior to disease onset. CONCLUSIONS: LEADR represents one of the largest EHR databases to have repurposed EHR data to examine patients' T2DM risk. This paper is first in a series demonstrating this novel approach to studying T2DM. IMPLICATIONS: Chronic conditions that often take years to develop can be studied efficiently using EHR data in a retrospective design. LEVEL OF EVIDENCE: While much is already known about T2DM risk, this EHR's cohort's 160 M data points for 1.4 M people over six years, provides opportunities to investigate new unique risk factors and evaluate research hypotheses where results could modify public health practice for preventing T2DM.

The contribution of specific non-communicable diseases to the achievement of the Sustainable Development Goal 3.4 in Peru.

BACKGROUND: Non-communicable diseases (NCDs) have received political attention and commitment, yet surveillance is needed to measure progress and set priorities. Building on global estimates suggesting that Peru is not on target to meet the Sustainable Development Goal 3.4, we estimated the contribution of various NCDs to the change in unconditional probability of dying from NCDs in 25 regions in Peru. METHODS: Using national death registries and census data, we estimated the unconditional probability of dying between ages 30 and 69 from any and from each of the following NCDs: cardiovascular, cancer, diabetes, chronic respiratory diseases and chronic kidney disease. We estimated the contribution of each NCD to the change in the unconditional probability of dying from any of these NCDs between 2006 and 2016. RESULTS: The overall unconditional probability of dying improved for men (21.4%) and women (23.3%). Cancer accounted for 10.9% in men and 13.7% in women of the overall reduction; cardiovascular diseases also contributed substantially: 11.3% in men) and 9.8% in women. Consistently in men and women and across regions, diabetes moved in the opposite direction of the overall reduction in the unconditional probability of dying from any selected NCD. Diabetes contributed a rise in the unconditional probability of 3.6% in men and 2.1% in women. CONCLUSIONS: Although the unconditional probability of dying from any selected NCD has decreased, diabetes would prevent Peru from meeting international targets. Policies are needed to prevent diabetes and to strengthen healthcare to avoid diabetes-related complications and delay mortality.

Implementing Lifestyle Change Interventions to Prevent Type 2 Diabetes in US Medicaid Programs: Cost Effectiveness, and Cost, Health, and Health Equity Impact.

BACKGROUND: Lifestyle change interventions (LCI) for prevention of type 2 diabetes are covered by Medicare, but rarely by US Medicaid programs that constitute the largest public payer system in the USA. We estimate the long-term health and economic implications of implementing LCIs in state Medicaid programs. METHODS: We compared LCIs modeled after the intervention of the Diabetes Prevention Program versus routine care advice using a decision analytic simulation model and best available data from representative surveys, cohort studies, Medicaid claims data, and the published literature. Target population were non-disability-based adult Medicaid beneficiaries aged 19-64 years at high risk for type 2 diabetes (BMI ≥25 kg/m2 and HbA1c ≥ 5.7% or fasting plasma glucose ≥ 110 mg/dl) from eight study states (Alabama, California, Connecticut, Florida, Iowa, Illinois, New York, Oklahoma) that represent around 50% of the US Medicaid population. Incremental cost-effectiveness ratios (ICERs) measured in cost per quality-adjusted life years (QALYs) gained, and population cost and health impact were modeled from a healthcare system perspective and a narrow Medicaid perspective. RESULTS: In the eight selected study states, 1.9 million or 18% of non-disability-based adult Medicaid beneficiaries would belong to the eligible high-risk target population - 66% of them Hispanics or non-Hispanic black. In the base-case analysis, the aggregated 5- and 10-year ICERs are US$226 k/QALY and US$34 k/QALY; over 25 years, the intervention dominates routine care. The 5-, 10-, and 25-year probabilities that the ICERs are below US$50 k (US$100 k)/QALY are 6% (15%), 59% (82%) and 96% (100%). From a healthcare system perspective, initial program investments of US$800 per person would be offset after 13 years and translate to US$548 of savings after 25 years. With a 20% LCI uptake in eligible beneficiaries, this would translate to upfront costs of US$300 million, prevent 260 thousand years of diabetes and save US$205 million over a 25-year time horizon. Cost savings from a narrow Medicaid perspective would be much smaller. Minorities and low-income groups would over-proportionally benefit from LCIs in Medicaid, but the impact on population health and health equity would be marginal. CONCLUSIONS: In the long-term, investments in LCIs for Medicaid beneficiaries are likely to improve health and to decrease healthcare expenditures. However, population health and health equity impact would be low and healthcare expenditure savings from a narrow Medicaid perspective would be much smaller than from a healthcare system perspective.

National and State-Level Trends in Nontraumatic Lower-Extremity Amputation Among U.S. Medicare Beneficiaries With Diabetes, 2000-2017.

OBJECTIVE: Diabetes is a leading cause of nontraumatic lower-extremity amputation (NLEA) in the U.S. After a period of decline, some national U.S. data have shown that diabetes-related NLEAs have recently increased, particularly among young and middle-aged adults. However, the trend for older adults is less clear. RESEARCH DESIGN AND METHODS: To examine NLEA trends among older adults with diabetes (≥67 years), we used 100% Medicare claims for beneficiaries enrolled in Parts A and B, also known as fee for service (FFS). NLEA was defined as the highest-level amputation per patient per calendar year. Annual NLEA rates were estimated from 2000 to 2017 and stratified by age-group, sex, race/ethnicity, NLEA level (toe, foot, below-the-knee amputation [BKA], or above-the-knee amputation [AKA]), and state. All rates were age and sex standardized to the 2000 Medicare population. Trends over time were assessed using Joinpoint regression and annual percent change (APC) reported. RESULTS: NLEA rates (per 1,000 people with diabetes) decreased by half from 8.5 in 2000 to 4.4 in 2009 (APC -7.9, P < 0.001). However, from 2009 onward, NLEA rates increased to 4.8 (APC 1.2, P < 0.01). Trends were similar across most age, sex, and race/ethnic groups, but absolute rates were highest in the oldest age-groups, Blacks, and men. By NLEA type, overall increases were driven by increases in rates of toe and foot NLEAs, while BKA and AKA continued to decline. The majority of U.S. states showed recent increases in NLEA, similar to national estimates. CONCLUSIONS: This study of the U.S. Medicare FFS population shows that recent increases in diabetes-related NLEAs are also occurring in older populations but at a less severe rate than among younger adults (<65 years) in the general population. Preventive foot care has been shown to reduce rates of NLEA among adults with diabetes, and the findings of the study suggest that those with diabetes-across the age spectrum-could benefit from increased attention to this strategy.

Cost-effectiveness of Interventions to Manage Diabetes: Has the Evidence Changed Since 2008?

OBJECTIVE: To synthesize updated evidence on the cost-effectiveness (CE) of interventions to manage diabetes, its complications, and comorbidities. RESEARCH DESIGN AND METHODS: We conducted a systematic literature review of studies from high-income countries evaluating the CE of diabetes management interventions recommended by the American Diabetes Association (ADA) and published in English between June 2008 and July 2017. We also incorporated studies from a previous CE review from the period 1985-2008. We classified the interventions based on their strength of evidence (strong, supportive, or uncertain) and levels of CE: cost-saving (more health benefit at a lower cost), very cost-effective (≤$25,000 per life year gained [LYG] or quality-adjusted life year [QALY]), cost-effective ($25,001-$50,000 per LYG or QALY), marginally cost-effective ($50,001-$100,000 per LYG or QALY), or not cost-effective (>$100,000 per LYG or QALY). Costs were measured in 2017 U.S. dollars. RESULTS: Seventy-three new studies met our inclusion criteria. These were combined with 49 studies from the previous review to yield 122 studies over the period 1985-2017. A large majority of the ADA-recommended interventions remain cost-effective. Specifically, we found strong evidence that the following ADA-recommended interventions are cost-saving or very cost-effective: In the cost-saving category are 1) ACE inhibitor (ACEI)/angiotensin receptor blocker (ARB) therapy for intensive hypertension management compared with standard hypertension management, 2) ACEI/ARB therapy to prevent chronic kidney disease and/or end-stage renal disease in people with albuminuria compared with no ACEI/ARB therapy, 3) comprehensive foot care and patient education to prevent and treat foot ulcers among those at moderate/high risk of developing foot ulcers, 4) telemedicine for diabetic retinopathy screening compared with office screening, and 5) bariatric surgery compared with no surgery for individuals with type 2 diabetes (T2D) and obesity (BMI ≥30 kg/m2). In the very cost-effective category are 1) intensive glycemic management (targeting A1C <7%) compared with conventional glycemic management (targeting an A1C level of 8-10%) for individuals with newly diagnosed T2D, 2) multicomponent interventions (involving behavior change/education and pharmacological therapy targeting hyperglycemia, hypertension, dyslipidemia, microalbuminuria, nephropathy/retinopathy, secondary prevention of cardiovascular disease with aspirin) compared with usual care, 3) statin therapy compared with no statin therapy for individuals with T2D and history of cardiovascular disease, 4) diabetes self-management education and support compared with usual care, 5) T2D screening every 3 years starting at age 45 years compared with no screening, 6) integrated, patient-centered care compared with usual care, 7) smoking cessation compared with no smoking cessation, 8) daily aspirin use as primary prevention for cardiovascular complications compared with usual care, 9) self-monitoring of blood glucose three times per day compared with once per day among those using insulin, 10) intensive glycemic management compared with conventional insulin therapy for T2D among adults aged ≥50 years, and 11) collaborative care for depression compared with usual care. CONCLUSIONS: Complementing professional treatment recommendations, our systematic review provides an updated understanding of the potential value of interventions to manage diabetes and its complications and can assist clinicians and payers in prioritizing interventions and health care resources.

Selecting the optimal risk threshold of diabetes risk scores to identify high-risk individuals for diabetes prevention: a cost-effectiveness analysis.

AIMS: Although risk scores to predict type 2 diabetes exist, cost-effectiveness of risk thresholds to target prevention interventions are unknown. We applied cost-effectiveness analysis to identify optimal thresholds of predicted risk to target a low-cost community-based intervention in the USA. METHODS: We used a validated Markov-based type 2 diabetes simulation model to evaluate the lifetime cost-effectiveness of alternative thresholds of diabetes risk. Population characteristics for the model were obtained from NHANES 2001-2004 and incidence rates and performance of two noninvasive diabetes risk scores (German diabetes risk score, GDRS, and ARIC 2009 score) were determined in the ARIC and Cardiovascular Health Study (CHS). Incremental cost-effectiveness ratios (ICERs) were calculated for increasing risk score thresholds. Two scenarios were assumed: 1-stage (risk score only) and 2-stage (risk score plus fasting plasma glucose (FPG) test (threshold 100 mg/dl) in the high-risk group). RESULTS: In ARIC and CHS combined, the area under the receiver operating characteristic curve for the GDRS and the ARIC 2009 score were 0.691 (0.677-0.704) and 0.720 (0.707-0.732), respectively. The optimal threshold of predicted diabetes risk (ICER < $50,000/QALY gained in case of intervention in those above the threshold) was 7% for the GDRS and 9% for the ARIC 2009 score. In the 2-stage scenario, ICERs for all cutoffs ≥ 5% were below $50,000/QALY gained. CONCLUSIONS: Intervening in those with ≥ 7% diabetes risk based on the GDRS or ≥ 9% on the ARIC 2009 score would be cost-effective. A risk score threshold ≥ 5% together with elevated FPG would also allow targeting interventions cost-effectively.

Using natural experimental studies to guide public health action: turning the evidence-based medicine paradigm on its head.

Despite smaller effect sizes, interventions delivered at population level to prevent non-communicable diseases generally have greater reach, impact and equity than those delivered to high-risk groups. Nevertheless, how to shift population behaviour patterns in this way remains one of the greatest uncertainties for research and policy. Evidence about behaviour change interventions that are easier to evaluate tends to overshadow that for population-wide and system-wide approaches that generate and sustain healthier behaviours. Population health interventions are often implemented as natural experiments, which makes their evaluation more complex and unpredictable than a typical randomised controlled trial (RCT). We discuss the growing importance of evaluating natural experiments and their distinctive contribution to the evidence for public health policy. We contrast the established evidence-based practice pathway, in which RCTs generate 'definitive' evidence for particular interventions, with a practice-based evidence pathway in which evaluation can help adjust the compass bearing of existing policy. We propose that intervention studies should focus on reducing critical uncertainties, that non-randomised study designs should be embraced rather than tolerated and that a more nuanced approach to appraising the utility of diverse types of evidence is required. The complex evidence needed to guide public health action is not necessarily the same as that which is needed to provide an unbiased effect size estimate. The practice-based evidence pathway is neither inferior nor merely the best available when all else fails. It is often the only way to generate meaningful evidence to address critical questions about investing in population health interventions.

The Andean Latin-American burden of diabetes attributable to high body mass index: A comparative risk assessment.

BACKGROUND: Body mass index (BMI) has increased in Latin-America, but the implications for the diabetes burden have not been quantified. We estimated the proportion and absolute number of diabetes cases attributable to high BMI in Bolivia, Ecuador and Peru (Andean Latin-America), with estimation of region-level indicators in Peru. METHODS: We estimated the population attributable fraction (PAF) of BMI on diabetes (regardless of type 1 or 2) from 1980 to 2014, including the number of cases attributable to overweight (BMI 25-<30), class I (30-<35), class II (BMI 35-<40) and class III (BMI ≥ 40) obesity. We used age- and sex-specific prevalence estimates of diabetes and BMI categories (NCD-RisC and Peru's DHS survey) combined with relative risks from population-based cohorts in Peru. FINDINGS: Across Andean Latin-America in 2014, there were 1,258,313 diabetes cases attributable to high BMI: 209,855 in Bolivia, 367,440 in Ecuador and 681,018 in Peru. Between 1980 and 2010, the absolute proportion of diabetes cases attributable to class I obesity increased the most (from 12.9% to 27.2%) across the region. The second greatest increase was for class II obesity (from 3.6% to 16.5%). There was heterogeneity in the fraction of diabetes cases attributable to high BMI by region in Peru, as coastal regions had the largest fractions, and so did high-income regions. INTERPRETATION: Over one million diabetes cases are attributable to high BMI in Andean Latin-America. Public health efforts should focus on implementing population-based interventions to reduce high BMI and to develop focused interventions targeted at those at highest risk of diabetes.

Diabetes Care Editors' Expert Forum 2018: Managing Big Data for Diabetes Research and Care.

Technological progress in the past half century has greatly increased our ability to collect, store, and transmit vast quantities of information, giving rise to the term "big data." This term refers to very large data sets that can be analyzed to identify patterns, trends, and associations. In medicine-including diabetes care and research-big data come from three main sources: electronic medical records (EMRs), surveys and registries, and randomized controlled trials (RCTs). These systems have evolved in different ways, each with strengths and limitations. EMRs continuously accumulate information about patients and make it readily accessible but are limited by missing data or data that are not quality assured. Because EMRs vary in structure and management, comparisons of data between health systems may be difficult. Registries and surveys provide data that are consistently collected and representative of broad populations but are limited in scope and may be updated only intermittently. RCT databases excel in the specificity, completeness, and accuracy of their data, but rarely include a fully representative sample of the general population. Also, they are costly to build and seldom maintained after a trial's end. To consider these issues, and the challenges and opportunities they present, the editors of Diabetes Care convened a group of experts in management of diabetes-related data on 21 June 2018, in conjunction with the American Diabetes Association's 78th Scientific Sessions in Orlando, FL. This article summarizes the discussion and conclusions of that forum, offering a vision of benefits that might be realized from prospectively designed and unified data-management systems to support the collective needs of clinical, surveillance, and research activities related to diabetes.

Influence of Diabetes Complications on HbA1c Treatment Goals Among Older U.S. Adults: A Cost-effectiveness Analysis.

OBJECTIVE: Guidelines on the standard care of diabetes recommend that glycemic treatment goals for older adults consider the patient's complications and life expectancy. In this study, we examined the influence of diabetes complications and associated life expectancies on the cost-effectiveness (CE) of HbA1c treatment goals. RESEARCH DESIGN AND METHODS: We used data from the 2011-2016 National Health and Nutrition Examination Survey (NHANES) to generate nationally representative subgroups of older individuals with diabetes with various health states. We used the Centers for Disease Control and Prevention-RTI International diabetes CE model to estimate the long-term consequences of two treatment goals-a stringent control goal (HbA1c <7.5%) and a moderate control goal (HbA1c <8.5%)-on health and cost. Our simulation population represented typical patients, and all individuals in each health subgroup had average characteristics, which did not account for person-level variations. The CE study was conducted from a health system perspective and followed the study samples over a lifetime. We used $50,000 per quality-adjusted life year (QALY) as the incremental CE threshold. RESULTS: A stringent goal was, on average, cost-effective for individuals with no complications ($10,007 per QALY) or only microvascular complications (excluding renal failure; $19,621 per QALY), but it was not cost-effective for individuals with one or more macrovascular complications (all >$82,413 per QALY). Further, a stringent goal was not cost-effective when an individual had less than 7 years of life remaining. CONCLUSIONS: Our findings support the guideline recommendation that glycemic goals for older adults should consider the complexity of their complications and their life expectancy from a CE perspective.

Trends in incidence of total or type 2 diabetes: systematic review.

OBJECTIVE: To assess what proportions of studies reported increasing, stable, or declining trends in the incidence of diagnosed diabetes. DESIGN: Systematic review of studies reporting trends of diabetes incidence in adults from 1980 to 2017 according to PRISMA guidelines. DATA SOURCES: Medline, Embase, CINAHL, and reference lists of relevant publications. ELIGIBILITY CRITERIA: Studies of open population based cohorts, diabetes registries, and administrative and health insurance databases on secular trends in the incidence of total diabetes or type 2 diabetes in adults were included. Poisson regression was used to model data by age group and year. RESULTS: Among the 22 833 screened abstracts, 47 studies were included, providing data on 121 separate sex specific or ethnicity specific populations; 42 (89%) of the included studies reported on diagnosed diabetes. In 1960-89, 36% (8/22) of the populations studied had increasing trends in incidence of diabetes, 55% (12/22) had stable trends, and 9% (2/22) had decreasing trends. In 1990-2005, diabetes incidence increased in 66% (33/50) of populations, was stable in 32% (16/50), and decreased in 2% (1/50). In 2006-14, increasing trends were reported in only 33% (11/33) of populations, whereas 30% (10/33) and 36% (12/33) had stable or declining incidence, respectively. CONCLUSIONS: The incidence of clinically diagnosed diabetes has continued to rise in only a minority of populations studied since 2006, with over a third of populations having a fall in incidence in this time period. Preventive strategies could have contributed to the fall in diabetes incidence in recent years. Data are limited in low and middle income countries, where trends in diabetes incidence could be different. SYSTEMATIC REVIEW REGISTRATION: Prospero CRD42018092287.

Reach and Use of Diabetes Prevention Services in the United States, 2016-2017.

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.

Eye Care Utilization Among Insured People With Diabetes in the U.S., 2010-2014.

OBJECTIVE: Diabetic retinopathy (DR) is the leading cause of blindness among working-age adults, and although screening with eye exams is effective, screening rates are low. We evaluated eye exam visits over a 5-year period in a large population of insured patients 10-64 years of age with diabetes. RESEARCH DESIGN AND METHODS: We used claims data from IBM Watson Health to identify patients with diabetes and continuous insurance coverage from 2010 to 2014. Diabetes and DR were defined using ICD-9 Clinical Modification codes. We calculated eye exam visit frequency by diabetes type over a 5-year period and estimated period prevalence and cumulative incidence of DR among those receiving an eye exam. RESULTS: Among the 298,383 insured patients with type 2 diabetes and no diagnosed DR, almost half had no eye exam visits over the 5-year period and only 15.3% met the American Diabetes Association (ADA) recommendations for annual or biennial eye exams. For the 2,949 patients with type 1 diabetes, one-third had no eye exam visits and 26.3% met ADA recommendations. The 5-year period prevalence and cumulative incidence of DR were 24.4% and 15.8%, respectively, for patients with type 2 diabetes and 54.0% and 33.4% for patients with type 1 diabetes. CONCLUSIONS: The frequency of eye exams was alarmingly low, adding to the abundant literature that systemic changes in health care may be needed to detect and prevent vision-threatening eye disease among people with diabetes.

Trajectory of Excess Medical Expenditures 10 Years Before and After Diabetes Diagnosis Among U.S. Adults Aged 25-64 Years, 2001-2013.

OBJECTIVE: We assessed the excess medical expenditures for adults newly diagnosed with diabetes, for up to 10 years before and after diabetes diagnosis. RESEARCH DESIGN AND METHODS: Using the 2001-2013 MarketScan data, we identified people with newly diagnosed diabetes among adults aged 25-64 years (diabetes cohort) and matched them with people who did not have diagnosed diabetes (control cohort) using 1:1 propensity score matching. We followed these two cohorts up to ±10 years from the index date, with annual matched cohort sizes ranging from 3,922 to 39,726 individuals. We estimated the yearly and cumulative excess medical expenditures of the diabetes cohorts before and after the diagnosis of diabetes. RESULTS: The per capita annual total excess medical expenditure for the diabetes cohort was higher for the entire 10 years prior to their index date, ranging between $1,043 in year -10 and $4,492 in year -1. Excess expenditure spiked in year 1 ($8,109), declined in year 2, and then increased steadily, ranging from $4,261 to $6,162 in years 2-10. The cumulative excess expenditure for the diabetes cohort during the entire 20 years of follow-up was $69,177 ($18,732 before and $50,445 after diagnosis). CONCLUSIONS: People diagnosed with diabetes had higher medical expenditures compared with their counterparts, not only after diagnosis but also up to 10 years prior to diagnosis. Managing risk factors for type 2 diabetes and cardiovascular disease before diagnosis, and for diabetes-related complications after diagnosis, could alleviate medical expenditure in people with diabetes.