OBJECTIVE To update state-specific estimates of diabetes-attributable costs in the U.S. and assess changes in spending from 2013 to 2021.RESEARCH DESIGN AND METHODS We used an attributable fraction approach to estimate direct medical costs of diagnosed diabetes using the 2021 State Health Expenditure Accounts, the 2021 Behavioral Risk Factor Surveillance System, and the Centers for Medicare and Medicaid Services 2018-2019 Minimum Data Set. We estimated diabetes-attributable productivity losses from morbidity and mortality using the 2016-2021 National Health Interview Survey and the 2021 mortality data from the Centers for Disease Control and Prevention. Costs were adjusted to 2021 U.S. dollars.RESULTS Total diabetes-attributable cost in 2021 was $640 billion ($335 billion in direct medical costs and $305 billion in indirect costs). The median state-level total diabetes-attributable cost was $8.2 billion (range $842 million to $81 billion). The median state-level per-person cost was $21,082, ranging from $17,452 to $37,090. Total diabetes-attributable cost increased by a median of 33% between 2013 and 2021, ranging from 16% to 68% across states. Medical costs increased by 50% overall (range 33-79%) and by 27% (range 15-41%) for per person with diabetes. Costs paid by Medicaid experienced the highest increase between 2013 and 2021 (median 153%; range 41-483%).CONCLUSIONS State economic costs of diagnosed diabetes are substantial and increased over the last decade. These costs and their growth vary considerably across states. These findings may help state policymakers in developing evidenced-based public health interventions in their respective states to prevent and control the prevalence of diabetes.

Introduction We assessed state-level disparities in diabetes prevalence among adults in rural and urban areas in the United States. Methods We estimated state-specific diabetes prevalence in rural and urban areas in 41 states with applicable data from the 2021 Behavioral Risk Factor Surveillance System. Rural areas were defined based on the 2013 National Center for Health Statistics Urban-Rural Classification Scheme. We estimated diabetes odds ratios (ORs) in rural versus urban areas in each state by using logistic regressions adjusted for sociodemographic characteristics and obesity status. Analyses were conducted in 2023. Results In rural areas, diabetes prevalence was 14.3%, ranging from 8.4% in Colorado to 21.3% in North Carolina. In urban areas, the prevalence was 11.2%, ranging from 6.9% in Colorado to 15.5% in West Virginia. Unadjusted diabetes ORs in rural versus urban areas were significant (P < .05) and greater than 1 for 19 states. After adjusting for age, sex, race, and ethnicity, the ORs were significant and greater than 1 for 7 states (Florida, Illinois, Kentucky, Maryland, North Carolina, Oregon, and Virginia). With additional adjustment for education, income, and obesity status, diabetes ORs in rural versus urban areas remained significant and greater than 1 for 2 states (North Carolina and Oregon). Conclusion Our findings reveal significant geographic disparities in diabetes prevalence between rural and urban areas in 19 states. The differences in most states may have been explained by rural-urban differences in sociodemographic characteristics and obesity rates. Our findings could inform decision makers to identify effective ways to reduce rural-urban disparities within states.

INTRODUCTION:In 2019 among US adults, 1 in 9 had diagnosed diabetes and 1 in 5 had diagnosed depression. Since these conditions frequently coexist, compounding their health and economic burden, we examined state-specific trends in depression prevalence among US adults with and without diagnosed diabetes.METHODS:We used data from the 2011 through 2019 Behavioral Risk Factor Surveillance System to evaluate self-reported diabetes and depression prevalence. Joinpoint regression estimated state-level trends in depression prevalence by diabetes status.RESULTS:In 2019, the overall prevalence of depression in US adults with and without diabetes was 29.2% (95% CI, 27.8%-30.6%) and 17.9% (95% CI, 17.6%-18.1%), respectively. From 2011 to 2019, the depression prevalence was relatively stable for adults with diabetes (28.6% versus 29.2%) but increased for those without diabetes from 15.5% to 17.9% (average annual percent change [APC] over the 9-year period = 1.6%, P = .015). The prevalence of depression was consistently more than 10 percentage points higher among adults with diabetes than those without diabetes. The APC showed a significant increase in some states (Illinois: 5.9%, Kansas: 3.5%) and a significant decrease in others (Arizona: -5.1%, Florida: -4.0%, Colorado: -3.4%, Washington: -0.9%). In 2019, although it varied by state, the depression prevalence among adults with diabetes was highest in states with a higher diabetes burden such as Kentucky (47.9%), West Virginia (47.0%), and Maine (41.5%).CONCLUSION:US adults with diabetes are more likely to report prevalent depression compared with adults without diabetes. These findings highlight the importance of screening and monitoring for depression as a potential complication among adults with diabetes.

To reduce the risk of gum disease, the American Diabetes Association recommends that people with diabetes brush twice and floss once daily and see the dentist twice a year. But only about two-thirds of all US adults seek dental care within a year. Regular dental checkups are more important for those with diabetes. Thus, we studied the current oral health status (visiting a dentist or a dental clinic in the past year and the number with permanent tooth loss) in US adults aged ≥ 18 years with and without diagnosed diabetes using data from the 2020 Behavioral Risk Factor Surveillance System. Both diabetes and oral health-related information were self-reported. We computed overall and state-specific age-adjusted estimates by diabetes status. In 2020, 64.4% (95% CI 64.0%-64.8%) of US adults had a dental visit within the past year. Annual dental checkups were more common among women, older people, non-Hispanic White persons, and those having higher education, better income, and health insurance. The proportion of US adults with diabetes seeing a dentist in the past year was significantly lower compared to those without diabetes (56.7% [95% CI 54.8%-58.5%] vs. 65.4% [95% CI 65.0%-65.8%]) . Both men (56.3% [95% CI 53.6%-58.9%] vs. 62.4% [95% CI 61.9%-63.0%]) and women (57.1% [95% CI 54.6%-59.6%] vs. 68.2% [95% CI 67.7%-68.8%]) with diabetes were also significantly less likely to get dental care than their counterparts. The frequency of annual dental visits among adults with diabetes also varied by state; Texas had the lowest percentage (39.8% [95% CI 32.5%-47.6%]) while Alaska had the highest (77.1% [95% CI 68.8%-83.7%]) . Adults with diabetes (34.1% [95% CI 32.4%-35.9%]) were also more likely to have a history of one or more permanent teeth removed due to tooth decay or gum disease than those without diabetes (26.5% [95% CI 26.1%-26.8%]) . Without having regular dental checkup and adequate oral hygiene, adults with diabetes are at increased risk for gum disease. These findings highlight a gap in preventive oral care among adults with diabetes. Disclosure P. Cho: None. I.A. Hora: None. K.M. Bullard: None.

In 2019, about 1 in 10 U.S. adults had diagnosed diabetes, and 1 in 5 had diagnosed depression. Since depression and diabetes frequently coexist, we examined the trend in the prevalence of depression among U.S. adults with and without diagnosed diabetes using data from the 2011-2019 Behavioral Risk Factor Surveillance System. Both diabetes and depression information were self-reported. We also estimated state level depression trends by diabetes status. We used Joinpoint to assess trends. In 2019, the overall prevalence of depression in U.S. adults with and without diabetes was 24.7% (95% CI 23.9%-25.4%) and 17.9% (95% CI 17.6%-18.1%), respectively. From 2011 to 2019, the prevalence of depression was relatively stable for adults with diabetes (from 28.6% to 29.2%), but it increased for those without diabetes from 15.5% to 17.9% (annual percent change = 1.59, p = 0.015) (Figure). The prevalence of depression was consistently more than 10 percentage points higher among adults with diabetes than in those without the disease. The trend increased in some states while it went down in others. Although it varied by state, the depression prevalence among adults with diabetes was higher in states with a larger diabetes burden such as Kentucky (47.9%) and West Virginia (47.0%). Adults with diabetes are at increased risk for depression; these findings highlight the importance of screening for depression, especially among persons with diabetes.View largeDownload slideView largeDownload slide DisclosureP. Cho: None. I. A. Hora: None. K. M. Bullard: None. S. R. Benoit: None.

Diabetes mellitus (DM) is a leading contributor to morbidity and mortality in the United States (US). Prior DM prevalence estimates in Asian Americans are predominantly from Asians aggregated into a single group, but the Asian American population is heterogenous. To evaluate self-reported DM prevalence in disaggregated Asian American subgroups to inform targeted management and prevention. Serial cross-sectional analysis. Respondents to the US Behavioral Risk Factor Surveillance System surveys who self-identify as non-Hispanic Asian American (NHA, N=57,001), comprising Asian Indian (N=11,089), Chinese (N=9458), Filipino (N=9339), Japanese (N=10,387), and Korean Americans (N=2843), compared to non-Hispanic White (NHW, N=2,143,729) and non-Hispanic Black (NHB, N=215,957) Americans. Prevalence of self-reported DM. Univariate Satterthwaite-adjusted chi-square tests compared the differences in weighted DM prevalence by sociodemographic and health status. Self-reported fully adjusted DM prevalence was 8.7% (95% confidence interval 8.2–9.3) in NHA, compared to 14.3% (14.0–14.6) in NHB and 10.0% (10.0–10.1) in NHW (p<0.01 for difference). In NHA subgroups overall, DM prevalence was 14.4% (12.6–16.3) in Filipino, 13.4% (10.9–16.2) in Japanese, 10.7% (9.6–11.8) in Asian Indian, 5.1% (4.2–6.2) in Chinese, and 4.7% (3.4–6.3) in Korean Americans (p<0.01). Among those aged ≥65 years, DM prevalence was highest in Filipino (35.0% (29.4–41.2)) and Asian Indian (31.5% (25.9–37.8)) Americans. Adjusted for sex, education, and race/ethnicity-specific obesity category, NHA overall had a 21% higher DM prevalence compared to NHW (prevalence ratio 1.21 [1.14–1.27]), while prevalence ratios were 1.42 (1.24–1.63) in Filipinos and 1.29 (1.14–1.46) in Asian Indians. Adjusted self-reported DM prevalence is higher in NHA compared with NHW. Disaggregating NHA reveals heterogeneity in self-reported DM prevalence, highest in Filipino and Asian Indian Americans.

Social determinants of health (SDoH), the conditions in which we live, learn, work, and play, have a profound impact on health and lead to health disparities in our communities. The Centers for Disease Control and Prevention (CDC) created an interactive SDoH module within the US Diabetes Surveillance System to explore these disparities in the context of diabetes burden and risk factors (Figure). The module was launched with the CDC Social Vulnerability Index (SVI), which was created to identify communities needing support during hazardous events. The index is composed of Census Bureau data on 15 variables, grouped into 4 themes: socioeconomic status, household composition and disability, minority status and language, and housing and transportation. Percentile ranks are used to score areas from 0-1 on social vulnerability with 1 being the most vulnerable. SVI is available at the national level to compare counties across states and at the state level to compare counties within a state. In addition to SVI, CDC will scale this module to include other SDoH such as food insecurity, community walkability, and crime. Local, state, and federal public health practitioners may find this application useful for identifying disparities in SDoH and chronic disease and designing targeted interventions to reduce these disparities in the communities of greatest need.View largeDownload slideView largeDownload slide DisclosureS. R. Benoit: None. D. C. Shelton: None. Y. Wang: None. K. Batchu: None. K. M. Bullard: None. P. Cho: None. I. A. Hora: None. D. King: None. J. W. Reynolds: None. H. Xie: None. Y. Zhang: None. M. Aboneaaj: None.

OBJECTIVE:To assess the prevalence of diagnosed diabetes among employed US adults from 36 states by occupation group using data from 2014 to 2018 Behavioral Risk Factor Surveillance System.METHODS:Prevalence of diabetes was calculated by 22 broad and 93 detailed occupation groups among a sample of 366,633 employed respondents. Wald chi-square values were used to determine the significance of associations between diabetes and occupation groups after adjusting for sex, age, and race/ethnicity.RESULTS:The prevalence of diabetes was 6.4% among employed US adults. The three broad occupation groups with the highest adjusted prevalence of diabetes were protective services (8.9%), farming, fishing, and forestry (8.8%), and community and social services (8.4%).CONCLUSIONS:Prevalence of diabetes differed by occupation. Work-related factors (eg, shift work, job stress) should be further examined in relation to risk of developing diabetes.

We examined changes in the prevalence of chronic health conditions among US-bound refugees originating from Burma resettling over 8 years by the type of living arrangement before resettlement, either in camps (Thailand) or in urban areas (Malaysia). Using data from the required overseas medical exam for 73,251 adult (≥ 18 years) refugees originating from Burma resettling to the United States during 2009–2016, we assessed average annual percent change (AAPC) in proportion ≥ 45 years and age- and sex-standardized prevalence of obesity, diabetes, hypertension, chronic obstructive pulmonary disease (COPD), and musculoskeletal disease, by camps versus urban areas. Compared with refugees resettling from camps, those coming from urban settings had higher prevalence of obesity (mean 18.0 vs. 5.9%), diabetes (mean 6.5 vs. 0.8%), and hypertension (mean 12.7 vs. 8.1%). Compared with those resettling from camps, those from urban areas saw greater increases in the proportion with COPD (AAPC: 109.4 vs. 9.9) and musculoskeletal disease (AAPC: 34.6 vs. 1.6). Chronic conditions and their related risk factors increased among refugees originating from Burma resettling to the United States whether they had lived in camps or in urban areas, though the prevalence of such conditions was higher among refugees who had lived in urban settings.

CDC, the Food and Drug Administration (FDA), state and local health departments, and public health and clinical stakeholders are investigating a nationwide outbreak of e-cigarette, or vaping, product use-associated lung injury (EVALI) (1). As of November 13, 2019, 49 states, the District of Columbia, and two U.S. territories (Puerto Rico and U.S. Virgin Islands) have reported 2,172 EVALI cases to CDC, including 42 (1.9%) EVALI-associated deaths. To inform EVALI surveillance, including during the 2019-20 influenza season, case report information supplied by states for hospitalized and nonhospitalized patients with EVALI were analyzed using data collected as of November 5, 2019. Among 2,016 EVALI patients with available data on hospitalization status, 1,906 (95%) were hospitalized, and 110 (5%) were not hospitalized. Demographic characteristics of hospitalized and nonhospitalized patients were similar; most were male (68% of hospitalized versus 65% of nonhospitalized patients), and most were aged <35 years (78% of hospitalized versus 74% of nonhospitalized patients). These patients also reported similar use of tetrahydrocannabinol (THC)-containing products (83% of hospitalized versus 84% of nonhospitalized patients). Given the similarity between hospitalized and nonhospitalized EVALI patients, the potential for large numbers of respiratory infections during the emerging 2019-20 influenza season, and the potential difficulty in distinguishing EVALI from respiratory infections, CDC will no longer collect national data on nonhospitalized EVALI patients. Further collection of data on nonhospitalized patients will be at the discretion of individual state, local, and territorial health departments. Candidates for outpatient management of EVALI should have normal oxygen saturation (≥95% while breathing room air), no respiratory distress, no comorbidities that might compromise pulmonary reserve, reliable access to care, strong social support systems, and should be able to ensure follow-up within 24-48 hours of initial evaluation and to seek medical care promptly if respiratory symptoms worsen. Health care providers should emphasize the importance of annual influenza vaccination for all persons aged ≥6 months, including persons who use e-cigarette, or vaping, products (2,3).

CDC, the Food and Drug Administration, state and local health departments, and other public health and clinical stakeholders are investigating a national outbreak of electronic-cigarette (e-cigarette), or vaping, product use-associated lung injury (EVALI) (1). As of October 22, 2019, 49 states, the District of Columbia (DC), and the U.S. Virgin Islands have reported 1,604 cases of EVALI to CDC, including 34 (2.1%) EVALI-associated deaths in 24 states. Based on data collected as of October 15, 2019, this report updates data on patient characteristics and substances used in e-cigarette, or vaping, products (2) and describes characteristics of EVALI-associated deaths. The median age of EVALI patients who survived was 23 years, and the median age of EVALI patients who died was 45 years. Among 867 (54%) EVALI patients with available data on use of specific e-cigarette, or vaping, products in the 3 months preceding symptom onset, 86% reported any use of tetrahydrocannabinol (THC)-containing products, 64% reported any use of nicotine-containing products, and 52% reported use of both. Exclusive use of THC-containing products was reported by 34% of patients and exclusive use of nicotine-containing products by 11%, and for 2% of patients, no use of either THC- or nicotine-containing products was reported. Among 19 EVALI patients who died and for whom substance use data were available, 84% reported any use of THC-containing products, including 63% who reported exclusive use of THC-containing products; 37% reported any use of nicotine-containing products, including 16% who reported exclusive use of nicotine-containing products. To date, no single compound or ingredient used in e-cigarette, or vaping, products has emerged as the cause of EVALI, and there might be more than one cause. Because most patients reported using THC-containing products before symptom onset, CDC recommends that persons should not use e-cigarette, or vaping, products that contain THC. In addition, because the specific compound or ingredient causing lung injury is not yet known, and while the investigation continues, persons should consider refraining from the use of all e-cigarette, or vaping, products.

Older adults are at increased risk of unintentional falls and fall-related injuries. Chronic diseases like diabetes are also common among older adults. Older diabetic adults are at increased risk for falls partly due to diabetes-related complications and medication side effects. We analyzed 2016 Behavioral Risk Factor Surveillance System survey data from 50 states, District of Columbia, and three U.S. territories to assess the risk of falling (percentage of older adults with self-reported falls and injurious falls) among 34,462 older adults aged ≥65 years with diabetes. We also examined the risk of falling by selected self-reported fall risk factors—sex, bodyweight, general health status, and comorbid conditions (history of stroke, visual impairment, arthritis, depression, difficulty walking or climbing stairs). Among older diabetic adults, 35.5% reported falling one or more times in the past 12 months; of those, 38.7% suffered injuries from falls. Compared to their counterparts without salient risk factors stated above, older diabetic adults with selected characteristics were significantly more likely to fall (all p values Disclosure P. Cho: None. I.A. Hora: None.

Structured lifestyle interventions can reduce diabetes incidence and cardiovascular disease (CVD) risk among persons with impaired glucose tolerance (IGT), but it is unclear whether they should be implemented among persons without IGT. We conducted a systematic review and meta-analyses to assess the effectiveness of lifestyle interventions on CVD risk among adults without IGT or diabetes. We systematically searched MEDLINE, EMBASE, CINAHL, Web of Science, the Cochrane Library, and PsychInfo databases, from inception to May 4, 2016. We selected randomized controlled trials of lifestyle interventions, involving physical activity (PA), dietary (D), or combined strategies (PA+D) with follow-up duration ≥12 months. We excluded all studies that included individuals with IGT, confirmed by 2-hours oral glucose tolerance test (75g), but included all other studies recruiting populations with different glycemic levels. We stratified studies by baseline glycemic levels: (1) low-range group with mean fasting plasma glucose (FPG) <5.5mmol/L or glycated hemoglobin (A1C) <5.5%, and (2) high-range group with FPG ≥5.5mmol/L or A1C ≥5.5%, and synthesized data using random-effects models. Primary outcomes in this review included systolic blood pressure (SBP), diastolic blood pressure (DBP), total cholesterol (TC), low density lipoprotein cholesterol (LDL-C), high density lipoprotein cholesterol (HDL-C), and triglycerides (TG). Totally 79 studies met inclusion criteria. Compared to usual care (UC), lifestyle interventions achieved significant improvements in SBP (-2.16mmHg[95%CI, -2.93, -1.39]), DBP (-1.83mmHg[-2.34, -1.31]), TC (-0.10mmol/L[-0.15, -0.05]), LDL-C (-0.09mmol/L[-0.13, -0.04]), HDL-C (0.03mmol/L[0.01, 0.04]), and TG (-0.08mmol/L[-0.14, -0.03]). Similar effects were observed among both low-and high-range study groups except for TC and TG. Similar effects also appeared in SBP and DBP categories regardless of follow-up duration. PA+D interventions had larger improvement effects on CVD risk factors than PA alone interventions. In adults without IGT or diabetes, lifestyle interventions resulted in significant improvements in SBP, DBP, TC, LDL-C, HDL-C, and TG, and might further reduce CVD risk.

This study systematically assessed the effectiveness of lifestyle interventions on glycemic indicators among adults (⩾18years) without IGT or diabetes. Randomized controlled trials using physical activity (PA), diet (D), or their combined strategies (PA+D) with follow-up ⩾12months were systematically searched from multiple electronic-databases between inception and May 4, 2016. Outcome measures included fasting plasma glucose (FPG), glycated hemoglobin (HbA1c), fasting insulin (FI), homeostasis model assessment-estimated insulin resistance (HOMA-IR), and bodyweight. Included studies were divided into low-range (FPG <5.5mmol/L or HbA1c <5.5%) and high-range (FPG ⩾5.5mmol/L or HbA1c ⩾5.5%) groups according to baseline glycemic levels. Seventy-nine studies met inclusion criteria. Random-effect models demonstrated that compared with usual care, lifestyle interventions achieved significant reductions in FPG (-0.14mmol/L [95%CI, -0.19, -0.10]), HbA1c (-0.06% [-0.09, -0.03]), FI (%change: -15.18% [-20.01, -10.35]), HOMA-IR (%change: -22.82% [-29.14, -16.51]), and bodyweight (%change: -3.99% [-4.69, -3.29]). The same effect sizes in FPG reduction (0.07) appeared among both low-range and high-range groups. Similar effects were observed among all groups regardless of lengths of follow-up. D and PA+D interventions had larger effects on glucose reduction than PA alone. Lifestyle interventions significantly improved FPG, HbA1c, FI, HOMA-IR, and bodyweight among adults without IGT or diabetes, and might reduce progression of hyperglycemia to type 2 diabetes mellitus.

Background: Trends in state-level prevalence of pre-pregnancy diabetes mellitus (PDM; i.e., type 1 or type 2 diabetes diagnosed before pregnancy) among delivery hospitalizations are needed to inform healthcare delivery planning and prevention programs.Purpose: To examine PDM trends overall, by age group, race/ethnicity, primary payer, and with comorbidities such as pre-eclampsia and pre-pregnancy hypertension, and to report changes in prevalence over 11 years.Methods: In 2014, State Inpatient Databases from the Agency for Healthcare Research and Quality were analyzed to identify deliveries with PDM and comorbidities using diagnosis-related group codes and ICD-9-CM codes. General linear regression with a log-link and binomial distribution was used to assess the annual change.Results: Between 2000 and 2010, PDM deliveries increased significantly in all age groups, all race/ethnicity groups, and in all states examined (p < 0.01). The age-standardized prevalence of PDM increased from 0.65 per 100 deliveries in 2000 to 0.89 per 100 deliveries in 2010, with a relative change of 37% (p < 0.01). Although PDM rates were highest in the South, some of the largest relative increases occurred in five Western states ( >= 69%). Non-Hispanic blacks had the highest PDM rates and the highest absolute increase (0.26 per 100 deliveries). From 2000 to 2010, the proportion of PDM deliveries with pre-pregnancy hypertension increased significantly (p < 0.01) from 7.4% to 14.1%.Conclusions: PDM deliveries are increasing overall and particularly among those with PDM who have hypertension. Effective diabetes prevention and control strategies for women of childbearing age may help protect their health and that of their newborns. Published by Elsevier Inc. on behalf of American Journal of Preventive Medicine

November is National Diabetes Month.In the United States, approximately 29 million persons have diabetes, and an additional 86 million adults have prediabetes, putting them at risk for developing type 2 diabetes, heart disease, and stroke (1).Persons with diabetes can take steps to control the disease and prevent complications, and those with prediabetes can prevent or delay the onset of type 2 diabetes through weight loss, healthy eating, and physical activity (1,2).After decades of continued increases, the prevalence of diabetes changed little from 2007-2008 to 2011-2012 (3).CDC and the American Medical Association has launched Prevent Diabetes STAT: Screen, Test, Act Today (http://www.preventdiabetesstat.org).This multiyear initiative includes a toolkit (http://www.cdc.gov/diabetes/prevention/pdf/STAT_toolkit.pdf ) to help persons determine their risk for type 2 diabetes and to guide health care providers on the best methods to screen patients for prediabetes and refer patients at high risk to prevention programs.The CDC-led National Diabetes Prevention Program promotes diabetes prevention programs that focus on lifestyle changes in communities throughout the United States (4).More information about CDCrecognized diabetes prevention programs is available at https://nccd.cdc.gov/DDT_DPRP/Registry.aspx.

November is National Diabetes Month.In the United States, approximately 29 million persons have diabetes, and an additional 86 million adults have prediabetes, putting them at risk for developing type 2 diabetes, heart disease, and stroke (1).Persons with diabetes can take steps to control the disease and prevent complications, and those with prediabetes can prevent or delay the onset of type 2 diabetes through weight loss, healthy eating, and physical activity (1,2).After decades of continued increases, the prevalence of diabetes changed little from 2007-2008 to 2011-2012 (3).CDC and the American Medical Association has launched Prevent Diabetes STAT: Screen, Test, Act Today (http://www.preventdiabetesstat.org).This multiyear initiative includes a toolkit (http://www.cdc.gov/diabetes/prevention/pdf/STAT_toolkit.pdf ) to help persons determine their risk for type 2 diabetes and to guide health care providers on the best methods to screen patients for prediabetes and refer patients at high risk to prevention programs.The CDC-led National Diabetes Prevention Program promotes diabetes prevention programs that focus on lifestyle changes in communities throughout the United States (4).More information about CDCrecognized diabetes prevention programs is available at https://nccd.cdc.gov/DDT_DPRP/Registry.aspx.

Asians and Native Hawaiians or other Pacific Islanders (NHPIs) are fast-growing U.S. minority populations at high risk for type 2 diabetes. Although national studies have described diabetes prevalence, incidence, and risk factors among Asians and NHPIs compared with non-Hispanic whites, little is known about state-level diabetes prevalence among these two racial groups, or about how they differ from one another with respect to diabetes risk factors. To examine state-level prevalence of self-reported, physician-diagnosed (diagnosed) diabetes and risk factors among Asians and NHPIs aged ≥18 years, CDC analyzed data from the 2011-2014 Behavioral Risk Factor Surveillance System (BRFSS). Among five states and Guam with sufficient data about NHPIs for analysis, the age-adjusted diabetes prevalence estimate for NHPIs ranged from 13.4% (New York) to 19.1% (California). Among 32 states, the District of Columbia (DC), and Guam that had sufficient data about Asians for analysis, diabetes prevalence estimates for Asians ranged from 4.9% (Arizona) to 15.3% (New York). In the five states and Guam with sufficient NHPI data, NHPIs had a higher age-adjusted prevalence of diabetes than did Asians, and a higher proportion of NHPIs were overweight or obese and had less than a high school education compared with Asians. Effective interventions and policies might reduce the prevalence of diabetes in these growing, high-risk minority populations.