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Despite a substantial economic burden of type 2 diabetes (T2D) on the working population, the costs of T2D for employers are not well characterized. We estimated productivity losses and medical costs due to T2D among employees aged 18-64 years using 2018-20MarketScan® databases. We estimated missed days due to absences, short-term disability (STD) , and long-term disability (LTD) attributable to T2D, overall and by age and sex. We converted these losses into costs by multiplying them by an average hourly wage. We used two-part and generalized linear models (controlling for age, sex, state of residence, employer industry type, and Charlson Comorbidity Index score) to estimate the productivity costs and medical costs in total and by service type. All costs were in 20USD. Overall, employees with T2D had 68% higher costs measured in productivity losses and medical services than those without diabetes (Table) , yielding a total cost attributable to T2D of $6,933. Most of the extra cost (90%) was from medical costs, followed by productivity costs due to STD (7%) , absences (2%) , and LTD (1%) . The youngest group had higher STD days and outpatient costs. Females had more absences and STD days and higher outpatient costs than males. Our estimates may assist employers in assessing potential financial gains from improved efforts to prevent and manage T2D in the workplace. Disclosure J.Park: None. E.Luman: None. P.Zhang: None.

Despite a high prevalence of DM and CVD in older adults in the US, relatively little is known about how CVD prevalence varies by sociodemographic factors in older adults with DM. Using the 2017-20Medicare Current Beneficiaries Survey, we examined the prevalence of self-reported myocardial infarction (MI) , heart failure (HF) , and stroke by race/ethnicity (non-Hispanic White, non-Hispanic Black, Hispanic, and others) , poverty (income-to-poverty ratio: ≤100%, 200%) , educational level (high school) , and urbanicity of residence among Medicare beneficiaries with DM aged ≥65 years. We estimated weighted adjusted prevalence of CVDs using multivariable logistic regression, controlling for age and sex. Compared to non-Hispanic White persons, non-Hispanic Black persons had a higher prevalence of HF and Hispanic persons had a lower prevalence (Figure) ; rural residents had a higher prevalence of MI, HF, and stroke than urban residents; the lowest income group (≤100%) had a higher prevalence of MI, HF, and stroke than the highest income group (>200%) ; and those with high school education (P Disclosure J.Park: None. X.Zhou: None. P.Zhang: None.

Cost-effectiveness (CE) of LPT2DP is influenced by the type 2 diabetes (T2D) risk of the intervention population. Current LPT2DPs can be grouped into three types: delivered in-person individually or in group and delivered virtually. We identified the T2D risk thresholds that were cost-effective for each type of the LPT2DPs. Using the CDC-RTI diabetes CE simulation model, we estimated CEs of the three LPT2DPs types in 11 population groups with an annual incidence of developing T2D ranging from 1% to 11%. We used $50K and $20K per quality-adjusted life year (QALY) gained in 25-years to measure the CEs of the LPT2DPs. We generated a nationally representative simulation sample using data from the 2011-2016 National Health and Nutrition Examination Survey. Data on program’s cost and effectiveness were from published literature. We took a health care system perspective, and costs were expressed in 2018 USD. Using $50K/QALY, the annual T2D incidence of the target population needs to be ≥ 5% for the in-person individual program, 4% for the digitally delivered program, and 3% for the in-person group program (Figure). The T2D risk thresholds were higher for each program when using $20K/QALY. Besides considering the availability of the programs and participants’ preferences, our findings can assist decision-makers in selecting the most appropriate population for their LPT2DPs. Disclosure J. Park: None. P. Zhang: None. H. Shao: Research Support; Self; Sanofi. M. Laxy: None. G. Imperatore: None.

Diabetes (DM) is among the most common chronic diseases diagnosed in youth in the United States. In adults, a bi-directional relationship has been demonstrated between DM and mental, behavioral, and developmental disorders (MBDD). Such comorbidities may significantly impact the quality of life of patients with DM and disease management. However, little is known about the association of DM and MBDD in youth. To examine the magnitude of overlap between these chronic conditions, we calculated prevalence estimates using the 2016-2019 National Survey of Children’s Health, an annual, cross-sectional survey of non-institutionalized US children aged 0-17 years (N = 131,774). Parents were asked if their child was ever diagnosed with DM or with any of the following MBDDs: attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder, learning disability, intellectual disability, developmental delay, anxiety, depression, behavioral or conduct problems, Tourette syndrome, or speech disorder. We present crude prevalence estimates and predictive margins adjusted for age, sex, and race/ethnicity, both weighted to be representative of the US youth population. Among US youth, prevalence estimates were 0.45% (95%CI: 0.36-0.55) for DM and 22.7% (22.2-23.2) for any MBDD. Crude prevalence of any MBDD varied by DM status (DM: 43.7% [34.5-53.4]; no DM: 22.6% [22.1-23.1]). Compared with youth without DM, those with DM had a higher adjusted prevalence of any MBDD (prevalence ratio: 1.55 [1.20-2.00]) and individual MBDDs (p Disclosure C. E. Barrett: None. K. M. Bullard: None. J. Park: None. A. Koyama: None. C. Mercado: None. A. H. Claussen: None. K. Newsome: None. M. E. Pavkov: None.

People with diabetes face higher out-of-pocket (OOP) health care costs than those without diabetes. This burden can lead to low adherence to treatments and adverse health outcomes, particularly among older adults. The OOP burden in older adults with diabetes has not been studied in the U.S. We estimated the OOP burden from 1999-2015 in Medicare beneficiaries with diabetes aged ≥65 using the Medicare Current Beneficiary Survey. OOP costs included premiums, deductibles, copays, coinsurance, and payments not covered by insurance. High OOP burden was defined as a person’s OOP costs ≥ 10% of their income. We estimated the prevalence of high OOP burden in all beneficiaries, by income quartile, and by race/ethnicity. Average OOP costs ranged from $2,864 to $4,212 (2015 $) and the percentage of those with high OOP burden varied from 38% to 46%, with slight increases over time. By income quartile, the average OOP costs were $2,292, $3,661, $4,032, and $4,430 for 75% groups, with decreases only in Disclosure J. Park: None. Y. Wang: None. K.A. Look: None. E. Luman: None. P. Zhang: None.

Recent changes in health coverage benefits and increases in diabetes medication prices may have affected out-of-pocket (OOP) expenditures for people with diabetes. High OOP expenditures is a barrier to get adequate medical care. We assessed national trends in OOP expenditures overall and by OOP-component among adults aged 18-64 years with diabetes from 2001 to 2017 using data from the U.S. Medical Expenditure Panel Survey. OOP expenditures were defined as the amount paid by a family with one or more members with diabetes, including insurance premiums, deductions, copays, coinsurance and payments not covered by insurance. High OOP burden was defined as spending >10% of the family’s pretax income on OOP expenditures. We examined trends overall as well as by insurance type, income (as a ratio of federal poverty level, FPL), type of service, and whether patients used insulin. We tested for changes in trends using joinpoint analysis. OOP expenditures were adjusted to 2017 U.S. dollars. From 2001 to 2017, OOP expenditures decreased 4.3%, from $4328 to $4139, and the percentage of persons with high OOP burden fell 32%, from 28% to 19% (P Disclosure Y. Wang: None. J. Park: None. R. Li: None. E. Luman: None. P. Zhang: None.