The Diabetes Prevention Gap And Opportunities To Increase Participation In Effective Interventions.

To understand the current state of prediabetes burden and treatment in the US, we examined recent trends in prediabetes prevalence, testing, and access to preventive resources. We estimated 13.5 percent prevalence of diagnosed prediabetes in the overall US adult population, using national survey data. Although prediabetes prevalence increased by 4.8 percentage points from 2010 to 2020, access to preventive resources remained low. The most effective intervention for diabetes prevention, known as the National Diabetes Prevention Program, remained woefully undersupplied and underused. There are only 2,098 National Diabetes Prevention Program-recognized providers nationally, and only 3 percent of adults with prediabetes have participated in the program. We suggest three actions to augment prevention efforts: increase payment for prevention interventions to avoid supply distortions, improve data integration and patient follow-up, and extend coverage and broaden access for preventive interventions. These actions, which would require policy-level changes, could lower the barriers to prevention.

Co-occurrence of diabetes and depression in the U.S.

Evidence exists that depression interacts with physical illness to amplify the impact of chronic conditions like diabetes. The co-occurrence of these two conditions leads to worse health outcomes and higher healthcare costs. This study seeks to understand what demographic and socio-economic indicators can be used to predict co-occurrence at both the state and the individual level. Diabetes and depression are modeled as a bivariate normal distribution using data from the Behavioral Risk Factor Surveillance System 2016-2017 cohorts. The tetrachoric (latent) correlation between diabetes and depression is 17.2% and statistically significant, however the likelihood of any person being diagnosed with both conditions is small-as high as 4.3% (Arizona) and as low as 2.3% (Utah). We find that demographic characteristics (sex, age, and race) operate in opposite directions in predicting diabetes and depression diagnosis. Behavioral indicators (BMI≥30, smoking, and exercise); and life outcomes, (schooling attainment, marital and veteran status) work in the same direction to produce co-occurrence and as such are more powerful predictors of co-occurrence than demographic characteristics. It is important to have a rapid and efficient instrument to diagnoses co-occurrence. Simple questions about lifestyle choices, educational attainment and family life could help bridge the gap between primary care and psychological services with beneficial spillovers for patient-doctor communication.

How Much Does Attendance Impact Weight Loss and Health Care Spending in a Diabetes Prevention Program Serving Older Adults?

PURPOSE: Measure attendance to the Young Men's Christian Association (YMCA) of the USA (Y-USA) diabetes prevention program (DPP) and show how attendance impacts weight loss and medical spending in a population of Medicare beneficiaries. DESIGN: Observational study using a pre- and post-specification. SETTING: A total of 17 participating YMCAs nationwide. PARTICIPANTS: 3317 Medicare beneficiaries with prediabetes. INTERVENTION: Community-based trainings of lifestyle intervention (National DPP). MEASURES: We used weight measurements from the Y-USA DPP participants, and Medicare fee-for-service part A and B claims data (January 2011-December 2016) from Chronic Conditions Data Warehouse. ANALYSIS: We used multivariate regression models to test the impact of class attendance on weight loss and Medicare expenditures. RESULTS: From a maximum of 24 classes, participants on average attended 14 (standard deviation: 6). The relationship between attendance and both weight loss and savings were approximately linear. During each weekly class, participants lost an average of 0.72 (confidence interval [CI]: 0.67-0.77) pounds and saved on average $58 (CI: $38-78) in medical expenses per class attended. CONCLUSIONS: Attendance to diabetes prevention programs is often challenging. To obtain both clinically relevant changes (weight loss greater than 5% of one's initial body weight) and economically relevant savings, completing at least 14 core sessions is essential. Steps to increase attendance and motivation across vulnerable groups may be an essential consideration for policymakers.

Impact of Financial Incentives on Diabetes Prevention Class Attendance and Program Completion: Evidence From Minnesota, Montana, and New York.

PURPOSE: To test the role of financial incentives to motivate engagement in diabetes prevention programs (DPPs). DESIGN: Minnesota, Montana, and New York randomized 3 different approaches to providing incentives: incentivizing class attendance and weight loss (all states), class attendance only (NY), and weight loss only (NY). We used New York to test how different approaches to providing incentives influence DPP completion and attendance. SETTING: Health-care facilities and local young men's Christian association. PARTICIPANTS: Eight hundred thirty one Medicaid enrollees in Minnesota, 204 in Montana, and 560 in New York. INTERVENTION MEASURE: Impact of the financial incentives on DPP program completion rates. We measured completion of DPP classes in 2 ways: completing 9 or more or 16 or more DPP classes. ANALYSIS: Multivariate logistic model to compare completion of DPP classes between participants randomized into receiving financial incentives and controls. RESULTS: Receipt of incentives was associated with higher odds at attending 9 or more classes (odds ratio [OR]: 2.2; P < .01) in Minnesota, Montana (OR: 2.2; P < .05), and New York (OR: 1.9; P < .01) as well as attending 16 or more classes in Minnesota (OR: 3.1; P < .01), Montana (OR: 2.1; P < .01), and New York (OR: 2.9; P < .01). In New York, individuals paid to attend classes attended more classes than individuals paid based on results only. CONCLUSION: Among Medicaid beneficiaries, financial incentives improve DPP class attendance.

Impact of Financial Incentives on Service Use, Spending, and Health in Medicaid.

INTRODUCTION: The Centers for Medicare and Medicaid Services provided grants to Medicaid programs through the Medicaid Incentives for Prevention of Chronic Diseases program to test whether financial incentives changed the use of healthcare services, Medicaid spending, and health outcomes. Six states implemented programs related to diabetes prevention, weight management, diabetes management, and hypertension management. The purpose of this study is to examine whether receipt of financial incentives increased use of services incentivized by the program; reduced expenditures, inpatient admissions, emergency department visits; and improved health outcomes. METHODS: State data on program participation and incentives (between 2011 and 2015) and 2 years of Medicaid claims data pre-Medicaid Incentives for Prevention of Chronic Diseases enrollment and >2 years of claims data after enrollment were analyzed using covariate-adjusted regression analyses. Negative binomial, logistic, and linear regressions were used, depending on the outcome variable of interest (services, inpatient admissions and emergency department visits, and total expenditures). Analyses were conducted in 2015 and 2016. RESULTS: Incentive recipients attended, on average, one to two more diabetes prevention classes than control participants, but incentives did not significantly improve uptake of other types of services, such as meetings with a health coach or doctor, gym visits, or attendance at Weight Watchers meetings. Modest improvements in health outcomes, such as weight loss, were observed, yet there were very few significant changes in inpatient admissions, emergency department visits, and Medicaid expenditures. CONCLUSIONS: Financial incentives are useful for engaging Medicaid enrollees in disease prevention programs, but program engagement may not necessarily lead to changing patterns of healthcare utilization and expenditures in the short run.

State-level diabetes-attributable mortality and years of life lost in the United States.

PURPOSE: To estimate state-level diabetes-attributable deaths and years of life lost (YLL) in the Unites States. METHODS: We estimated diabetes-attributable all-cause and cardiovascular disease (CVD) deaths by age, sex, and state, using the attributable fraction approach. Data on diabetes prevalence were collected from Behavioral Risk Factor Surveillance System. Relative risks for people with and without diabetes were estimated using the National Health Interview Survey. State-sex-age-specific deaths were obtained from CDC WONDER. YLL were calculated by multiplying the number of people with diabetes by the difference in life expectancy between people with and without diabetes using the life table approach. RESULTS: Nationally, estimated diabetes-attributable all-cause deaths and CVD deaths were 293,224 and 90,953, respectively. Diabetes resulted in a total of 109,707,000 YLL with an average 4.4 years of life lost per person with diabetes. Most state variation in total deaths was explained by state population size and diabetes prevalence. All-cause deaths ranged from 415 in Alaska to 28,538 in California, and CVD deaths ranged from 113 in Alaska to 8908 in California. Across all states, the average diabetes-attributable death rate per 100,000 was 125 for males and 105 for females for all-cause deaths and 40 for males and 31 for females for CVD deaths. CONCLUSIONS: Mortality attributable to diabetes is greatly underestimated when looking only at diabetes listed as an underlying cause of death. These results can be used to track state differences in deaths due to diabetes and to monitor the success of public health activities.

A Review of the Impacts of Different Approaches for Diabetes Prevention and a Framework for Making Investment Decisions.

This paper selectively reviews the economic research on individual (i.e., diabetes prevention programs and financial rewards for weight loss) and population-wide based diabetes prevention interventions (such as food taxes, nutritional labeling, and worksite wellness programs) that demonstrate a direct reduction in diabetes incidence or improvements in diabetes risk factors such as weight, glucose or glycated hemoglobin. The paper suggests a framework to guide decision makers on how to use the available evidence to determine the optimal allocation of resources across population-wide and individual-based interventions. This framework should also assist in the discussion of what parameters are needed from research to inform decision-making on what might be the optimal mix of strategies to reduce diabetes prevalence.

Identifying risk for type 2 diabetes in different age cohorts: does one size fit all?

OBJECTIVE: To estimate age-specific risk equations for type 2 diabetes onset in young, middle-aged, and older US adults, and to compare the performance of simple equations based on readily available demographic information alone, against enhanced equations that require both demographic and clinical information (fasting plasma glucose, high-density lipoprotein, and triglyceride levels). RESEARCH DESIGN AND METHODS: We estimated the probability of developing diabetes by age group using data from the Coronary Artery Risk Development in Young Adults (for ages 18-40 years), Atherosclerosis Risk in Communities (for ages 45-64 years), and the Cardiovascular Health Study (for ages 65 years and older). Simple and enhanced equations were estimated using logistic regression models, and performance was compared by age group. Thresholds based on these risk equations were evaluated using split-sample bootstraps and calibrating the constant of one age cohort to others. RESULTS: Simple risk equations had an area under the receiver-operating curve (AUROC) of 0.72, 0.79, 0.75, and 0.69 for age groups 18-30, 28-40, 45-64, and 65 and older, respectively. The corresponding AUROCs for enhanced equations were 0.75, 0.85, 0.85, and 0.81. Risk equations based on younger populations, when applied to older cohorts, underpredict diabetes incidence and risk. Conversely, risk equations based on older populations overpredict the likelihood of diabetes in younger cohorts. CONCLUSIONS: In general, risk equations are more successful in middle-aged adults than in young and old populations. The results demonstrate the importance of applying age-specific risk equations to identify target populations for intervention. While the predictive capacity of equations that include biomarkers is better than of those based solely on self-reported variables, biomarkers are more important in older populations than in younger ones.

Health selection into neighborhoods among patients enrolled in a clinical trial.

Health selection into neighborhoods may contribute to geographic health disparities. We demonstrate the potential for clinical trial data to help clarify the causal role of health on locational attainment. We used data from the 20-year United Kingdom Prospective Diabetes Study (UKPDS) to explore whether random assignment to intensive blood-glucose control therapy, which improved long-term health outcomes after median 10 years follow-up, subsequently affected what neighborhoods patients lived in. We extracted postcode-level deprivation indices for the 2710 surviving participants of UKPDS living in England at study end in 1996/1997. We observed small neighborhood advantages in the intensive versus conventional therapy group, although these differences were not statistically significant. This analysis failed to show conclusive evidence of health selection into neighborhoods, but data suggest the hypothesis may be worthy of exploration in other clinical trials or in a meta-analysis.

A Feasibility Study of Supply and Demand for Diabetes Prevention Programs in North Carolina.

INTRODUCTION: Diabetes Prevention Programs (DPPs) have shown that healthy eating and moderate physical activity are effective ways of delaying and preventing type 2 diabetes in people with impaired glucose tolerance. We assessed willingness to pay for DPPs from the perspective of potential recipients and the cost of providing these programs from the perspective of community health centers and local health departments in North Carolina. METHODS: We used contingent valuation to determine how much potential recipients would be willing to pay to participate in DPPs under 3 different models: delivered by registered professionals (traditional model), by community health workers, or online. By using information on the minimum reimbursement rate at which public health agencies would be prepared to provide the 3 models, we estimated the marginal costs per person of supplying the programs. Matching supply and demand, we estimated the degree of cost sharing between recipients and providers. RESULTS: Potential program recipients (n = 99) were willing to pay more for programs led by registered professionals than by community health workers, and they preferred face-to-face contact to an online format. Socioeconomic status (measured by education and employment) and age played the biggest roles in determining willingness to pay. Leaders of public health agencies (n = 27) reported up to a 40% difference in the cost of providing the DPP, depending on the delivery model. CONCLUSION: By using willingness to pay to understand demand for DPPs and computing the provider's marginal cost of providing these services, we can estimate cost sharing and market coverage of these services and thus compare the viability of alternate approaches to scaling up and sustaining DPPs with available resources.

Impact Of The YMCA Of The USA Diabetes Prevention Program On Medicare Spending And Utilization.

The YMCA of the USA received a Health Care Innovation Award from the Centers for Medicare and Medicaid Services to provide a diabetes prevention program to Medicare beneficiaries with prediabetes in seventeen regional networks of participating YMCAs nationwide. The goal of the program is to help participants lose weight and increase physical activity. We tested whether the program reduced medical spending and utilization in the Medicare population. Using claims data to compute total medical costs for fee-for-service Medicare participants and a matched comparison group of nonparticipants, we found that the overall weighted average savings per member per quarter during the first three years of the intervention period was $278. Total decreases in inpatient admissions and emergency department (ED) visits were significant, with nine fewer inpatient stays and nine fewer ED visits per 1,000 participants per quarter. These results justify continued support of the model.