Changes in Sales of Tobacco and Nicotine Replacement Therapy Products Before and During the COVID-19 Pandemic.

INTRODUCTION: The COVID-19 pandemic and its associated social distancing policies such as lockdowns and quarantine influenced people's lives and health behaviors. We comprehensively assessed national trends in sales of cigarettes, cigars, e-cigarettes, and over-the-counter nicotine replacement therapy (NRT) products before and during the pandemic, allowing for cross-product comparisons. Stockpiling behavior was also assessed. METHODS: We used US national tobacco and over-the-counter NRT retail store scanner data (excluding internet, specialty/vape store, and prescription sales) collected at 4-week intervals by NielsenIQ from December 2018 to June 2021. We applied an interrupted time-series model to assess differences in tobacco product and NRT unit sales before and during the pandemic. We defined the prepandemic period as December 16, 2018, through April 4, 2020, pandemic as starting on April 5, 2020, through June 26, 2021, and the stockpiling period as one 4-week period before the pandemic started. RESULTS: Four-week cigarette, e-cigarette, and cigar unit sales on average increased by 11.5% (P = .006), 37.1% (P < .001), and 26.1% (P < .001) respectively, while 4-week NRT unit sales decreased on average by 13.1% (P < .001), during the pandemic compared with the prepandemic period. Stockpiling was associated with increases in sales of all tobacco products and NRT products. CONCLUSION: Unit sales of assessed tobacco products increased while NRT unit sales decreased during the COVID-19 pandemic, compared with the prepandemic period. These changes may suggest an increase in the intensity of tobacco product use or stockpiling of tobacco products among people who use tobacco.

Trends in Nicotine Strength in Electronic Cigarettes Sold in the United States by Flavor, Product Type, and Manufacturer, 2017-2022.

INTRODUCTION: Most e-cigarettes contain highly addictive nicotine. This study assessed trends in nicotine strength in e-cigarettes sold in the United States during January 2017-March 2022. AIMS AND METHODS: We obtained January 2017-March 2022 national retail e-cigarette sales data from NielsenIQ. We assessed monthly average nicotine strength overall, by e-cigarette product and flavor type, and manufacturer. A Joinpoint regression model assessed the magnitude and significance of changes in nicotine strength. RESULTS: During January 2017-March 2022, monthly average nicotine strength of e-cigarette products increased from 2.5% to 4.4%, an average of 0.8% per month (p < .001). Monthly average nicotine strength of disposable e-cigarettes increased the most (average monthly percentage change [AMPC] = 1.26%, p < .001) as compared to prefilled pods (AMPC = 0.6%, p < .001) and e-liquids (AMPC = 0.5%, p = .218). Monthly average nicotine strength for all flavors of e-cigarette products increased except for mint-flavored products. Increases were greatest for beverage-flavored products (AMPC = 2.1%, p < .001), followed by menthol-flavored products (AMPC = 1.2%, p < .001). Among the top 10 e-cigarette manufacturers assessed, monthly average nicotine strength decreased for Juul Labs products from 5% to 4.7% (AMPC = -0.1%, p < .001) but increased significantly for five manufacturers' products and remained unchanged at 5%-6% for four manufacturers' products. CONCLUSIONS: Monthly average nicotine strength of e-cigarette products increased overall, for most product and flavor types, and for some manufacturers in the United States during the study period. Imposing maximum limits on nicotine strength of e-cigarettes together with other evidence-based tobacco control strategies can help reduce the use of e-cigarettes among youth and increase tobacco product cessation among adults. IMPLICATIONS: From January 2017 to March 2022, the monthly average nicotine strength of disposable e-cigarettes increased substantially and exceeded prefilled pods since May 2020. E-cigarettes with menthol flavor and youth-appealing flavors, like fruit, also had sharp increases in monthly average nicotine strength. Among the top 10 e-cigarette manufacturers, monthly average nicotine strength increased or remained unchanged at a high nicotine level for all manufacturers' products, except Juul Lab's products. Comprehensive strategies including restricting sales of all flavored e-cigarettes, restricting youth tobacco product access, and imposing maximum limits on nicotine strength may help reduce youth e-cigarette use and increase tobacco cessation.

Changes in Sales of E-Cigarettes, Cigarettes, and Nicotine Replacement Therapy Products Before, During, and After the EVALI Outbreak.

INTRODUCTION: In 2019, an outbreak of e-cigarette, or vaping, product use-associated lung injury (EVALI) occurred in the US. We used Nielsen retail sales data to assess trends in sales of e-cigarettes, cigarettes, and nicotine replacement therapy (NRT) products before, during, and after the EVALI outbreak. METHODS: Monthly unit sales of e-cigarettes, cigarettes, and NRT products overall and by product type were assessed during January 2019 through June 2020 by using an interrupted time series model. Two time points were specified at the period ending July 13, 2019, and the period ending February 22, 2020, to partition before, during, and after the outbreak period. Sales trends by aggregated state-level EVALI case prevalence (low, medium, and high) were assessed to investigate interstate variations in changes of sales coinciding with the EVALI outbreak. RESULTS: Monthly e-cigarette sales increased 3.5% (P < .001) before the outbreak and decreased 3.1% (P < .001) during the outbreak, with no significant changes after the outbreak. Monthly cigarette sales increased 1.6% (P < .001) before the outbreak, decreased 1.8% (P < .001) during the outbreak, and increased 2.7% (P < .001) after the outbreak. NRT sales did not change significantly before or during the outbreak but decreased (2.8%, P = .01) after the outbreak. Sales trends by state-level EVALI case prevalence were similar to national-level sales trends. CONCLUSION: Cigarette and e-cigarette sales decreased during the EVALI outbreak, but no changes in overall NRT sales were observed until after the outbreak. Continued monitoring of tobacco sales data can provide insight into potential changes in use patterns and inform tobacco prevention and control efforts.

Cost of Cigarette Smoking‒Attributable Productivity Losses, U.S., 2018.

INTRODUCTION: Information on morbidity-related productivity losses attributable to cigarette smoking, an important component of the economic burden of cigarette smoking, is limited. This study fills this gap by estimating these costs in the U.S. and by state. METHODS: A human capital approach was used to estimate the cost of the morbidity-related productivity losses (absenteeism, presenteeism, household productivity, and inability to work) attributable to cigarette smoking among adults aged ≥18 years in the U.S. and by state. A combination of data, including the 2014-2018 National Health Interview Survey, 2018 Current Population Survey Annual Social and Economic Supplement, 2018 Behavioral Risk Factor Surveillance System, 2018 value of daily housework, and literature-based estimate of lost productivity while at work (presenteeism), was used. Costs were estimated for 2018, and all analyses were conducted in 2021. RESULTS: Estimated total cost of morbidity-related productivity losses attributable to cigarette smoking in the U.S. in 2018 was $184.9 billion. Absenteeism, presenteeism, home productivity, and the inability to work accounted for $9.4 billion, $46.8 billion, $12.8 billion, and $116.0 billion, respectively. State-level total costs ranged from $291 million to $16.9 billion with a median cost of $2.7 billion. CONCLUSIONS: The cost of morbidity-related productivity losses attributable to cigarette smoking in the U.S. and in each state was substantial in 2018 and varied across the states. These estimates can guide public health policymakers and practitioners planning and evaluating interventions designed to alleviate the burden of cigarette smoking at the state and national levels.

Inpatient care cost, duration, and acute complications associated with BMI in children and adults hospitalized for COVID-19.

OBJECTIVE: This study aimed to assess the association of BMI with inpatient care cost, duration, and acute complications among patients hospitalized for COVID-19 at 273 US hospitals. METHODS: Children (aged 2-17 years) and adults (aged ≥18 years) hospitalized for COVID-19 during March 2020-July 2021 and with measured BMI in a large electronic administrative health care database were included. Generalized linear models were used to assess the association of BMI categories with the cost and duration of inpatient care. RESULTS: Among 108,986 adults and 409 children hospitalized for COVID-19, obesity prevalence was 53.4% and 45.0%, respectively. Among adults, overweight and obesity were associated with higher cost of care, and obesity was associated with longer hospital stays. Children with severe obesity had higher cost of care but not significantly longer hospital stays, compared with those with healthy weight. Children with severe obesity were 3.7 times (95% CI: 1.4-9.5) as likely to have invasive mechanical ventilation and 62% more likely to have an acute complication (95% CI: 39%-90%), compared with children with healthy weight. CONCLUSIONS: These findings show that patients with a high BMI experience significant health care burden during inpatient COVID-19 care.

Estimation of Coronavirus Disease 2019 Hospitalization Costs From a Large Electronic Administrative Discharge Database, March 2020-July 2021.

BACKGROUND: Information on the costs of inpatient care for patients with coronavirus disease 2019 (COVID-19) is very limited. This study estimates the per-patient cost of inpatient care for adult COVID-19 patients seen at >800 US hospitals. METHODS: Patients aged ≥18 years with ≥1 hospitalization during March 2020-July 2021 with a COVID-19 diagnosis code in a large electronic administrative discharge database were included. We used validated costs when reported; otherwise, costs were calculated using charges multiplied by cost-to-charge ratios. We estimated costs of inpatient care per patient overall and by severity indicator, age, sex, underlying medical conditions, and acute complications of COVID-19 using a generalized linear model with log link function and gamma distribution. RESULTS: The overall cost among 654673 patients hospitalized with COVID-19 was $16.2 billion. Estimated per-patient hospitalization cost was $24 826. Among surviving patients, estimated per-patient cost was $13 090 without intensive care unit (ICU) admission or invasive mechanical ventilation (IMV), $21 222 with ICU admission alone, and $59 742 with IMV. Estimated per-patient cost among patients who died was $27 017. Adjusted cost differential was higher among patients with certain underlying conditions (eg, chronic kidney disease [$12 391], liver disease [$8878], cerebrovascular disease [$7267], and obesity [$5933]) and acute complications (eg, acute respiratory distress syndrome [$43 912], pneumothorax [$25 240], and intracranial hemorrhage [$22 280]). CONCLUSIONS: The cost of inpatient care for COVID-19 patients was substantial through the first 17 months of the pandemic. These estimates can be used to inform policy makers and planners and cost-effectiveness analysis of public health interventions to alleviate the burden of COVID-19.

U.S. healthcare spending attributable to cigarette smoking in 2014.

INTRODUCTION: Cigarette smoking continues to be the leading cause of preventable disease and death in the U.S. Smoking also carries an economic burden, including smoking-attributable healthcare spending. This study assessed smoking-attributable fractions in healthcare spending between 2010 and 2014, overall and by insurance type (Medicaid, Medicare, private, out-of-pocket, other federal, other) and by medical service (inpatient, non-inpatient, prescriptions). METHODS: Data were obtained from the 2010-2014 Medical Expenditure Panel Survey linked to the 2008-2013 National Health Interview Survey. The final sample (n = 49,540) was restricted to non-pregnant adults aged 18 years or older. Estimates from two-part models (multivariable logistic regression and generalized linear models) and data from 2014 national health expenditures were combined to estimate the share of and total (in 2014 dollars) annual healthcare spending attributable to cigarette smoking among U.S. adults. All models controlled for socio-demographic characteristics, health-related behaviors, and attitudes. RESULTS: During 2010-2014, an estimated 11.7% (95% CI = 11.6%, 11.8%) of U.S. annual healthcare spending could be attributed to adult cigarette smoking, translating to annual healthcare spending of more than $225 billion dollars based on total personal healthcare expenditures reported in 2014. More than 50% of this smoking-attributable spending was funded by Medicare or Medicaid. For Medicaid, the estimated healthcare spending attributable fraction increased more than 30% between 2010 and 2014. CONCLUSIONS: Cigarette smoking exacts a substantial economic burden in the U.S. Continuing efforts to implement proven population-based interventions have been shown to reduce the health and economic burden of cigarette smoking nationally.

Receipt of and Spending on Cessation Medication Among US Adults With Employer-Sponsored Health Insurance, 2010 and 2017.

OBJECTIVE: Studies examining the use of smoking cessation treatment and related spending among enrollees with employer-sponsored health insurance are dated and limited in scope. We assessed changes in annual receipt of and spending on cessation medications approved by the US Food and Drug Administration (FDA) among tobacco users with employer-sponsored health insurance from 2010 to 2017. METHODS: We analyzed data on 439 865 adult tobacco users in 2010 and 344 567 adult tobacco users in 2017 from the IBM MarketScan Commercial Database. We used a negative binomial regression to estimate changes in receipt of cessation medication (number of fills and refills and days of supply). We used a generalized linear model to estimate spending (total, employers', and out of pocket). In both models, covariates included year, age, sex, residence, and type of health insurance plan. RESULTS: From 2010 to 2017, the percentage of adult tobacco users with employer-sponsored health insurance who received any cessation medication increased by 2.4%, from 15.7% to 16.1% (P < .001). Annual average number of fills and refills per user increased by 15.1%, from 2.5 to 2.9 (P < .001) and days of supply increased by 26.4%, from 81.9 to 103.5 (P < .001). The total annual average spending per user increased by 53.6%, from $286.40 to $440.00 (P < .001). Annual average out-of-pocket spending per user decreased by 70.9%, from $70.80 to $20.60 (P < .001). CONCLUSIONS: Use of smoking cessation medications is low among smokers covered by employer-sponsored health insurance. Opportunities exist to further increase the use of cessation medications by promoting the use of evidence-based cessation treatments and reducing barriers to coverage, including out-of-pocket costs.

Cost Effectiveness of the Tips From Former Smokers® Campaign-U.S., 2012-2018.

INTRODUCTION: Since 2012, the Centers for Disease Control and Prevention has conducted the national Tips From Former Smokers® public education campaign, which motivates smokers to quit by featuring people living with the real-life health consequences of smoking. Cost effectiveness, from the healthcare sector perspective, of the Tips From Former Smokers® campaign was compared over 2012-2018 with that of no campaign. METHODS: A combination of survey data from a nationally representative sample of U.S. adults that includes cigarette smokers and literature-based lifetime relapse rates were used to calculate the cumulative number of Tips From Former Smokers® campaign‒associated lifetime quits during 2012-2018. Then, lifetime health benefits (premature deaths averted, life years saved, and quality-adjusted life years gained) and healthcare sector cost savings associated with these quits were assessed. All the costs were adjusted for inflation in 2018 U.S. dollars. The Tips From Former Smokers® campaign was conducted and the survey data were collected during 2012-2018. Analyses were conducted in 2019. RESULTS: During 2012-2018, the Tips From Former Smokers® campaign was associated with an estimated 129,100 premature deaths avoided, 803,800 life years gained, 1.38 million quality-adjusted life years gained, and $7.3 billion in healthcare sector cost savings on the basis of an estimated 642,200 campaign-associated lifetime quits. The Tips From Former Smokers® campaign was associated with cost savings per lifetime quit of $11,400, per life year gained of $9,100, per premature deaths avoided of $56,800, and per quality-adjusted life year gained of $5,300. CONCLUSIONS: Mass-reach health education campaigns, such as Tips From Former Smokers®, can help smokers quit, improve health outcomes, and potentially reduce healthcare sector costs.

Medical expenditures for hypertensive disorders during pregnancy that resulted in a live birth among privately insured women.

OBJECTIVE: To estimate the excess maternal health services utilization and direct maternal medical expenditures associated with hypertensive disorders during pregnancy and one year postpartum among women with private insurance in the United States. STUDY DESIGN: We used 2008-2014 IBM MarketScan® Commercial Databases to identify women aged 15-44 who had a pregnancy resulting in live birth during 1/1/09-12/31/13 and were continuously enrolled with non-capitated or partially capitated coverage from 12 months before pregnancy through 12 months after delivery. Hypertensive disorders identified by diagnosis codes were categorized into three mutually exclusive types: preeclampsia and eclampsia, chronic hypertension, and gestational hypertension. Multivariate negative binomial and generalized linear models were used to estimate service utilization and expenditures, respectively. MAIN OUTCOME MEASURES: Per person excess health services utilization and medical expenditures during pregnancy and one year postpartum associated with hypertensive disorders (in 2014 US dollars). RESULTS: Women with preeclampsia and eclampsia, chronic hypertension, and gestational hypertension had $9,389, $6,041, and $2,237 higher mean medical expenditures compared to women without hypertensive disorders ($20,252), respectively (ps < 0.001). One-third (36%) of excess expenditure associated with hypertensive disorders during pregnancy was attributable to outpatient services. CONCLUSIONS: Hypertensive disorders during pregnancy were associated with significantly higher health services utilization and medical expenditures among privately insured women with hypertensive disorders. Medical expenditures varied by types of hypertensive disorders. Stakeholders can use this information to assess the potential economic benefits of interventions that prevent these conditions or their complications.

Prevalence and medical expenditures of diabetes-related complications among adult Medicaid enrollees with diabetes in eight U.S. states.

AIMS: To estimate the prevalence and medical expenditures of diabetes-related complications (DRCs) among adult Medicaid enrollees with diabetes. METHODS: We estimated the prevalence and medical expenditures for 12 diabetes-related complications by Medicaid eligibility category (disability-based vs. non-disability-based) in eight states. We used generalized linear models with log link and gamma distribution to estimate the total per-person annual medical expenditures for DRCs, controlling for demographics, and other comorbidities. RESULTS: Among non-disability-based enrollees (NDBEs), 40.1% (in California) to 47.5% (in Oklahoma) had one or more DRCs, compared to 53.6% (in Alabama) to 64.8% (in Florida) among disability-based enrollees (DBEs). The most prevalent complication was neuropathy (16.1%-27.1% for NDBEs; 20.2%-30.4% for DBEs). Lower extremity amputation (<1% for both eligibilities) was the least prevalent complication. The costliest per-person complication was dialysis (per-person excess annual expenditure of $22,481-$41,298 for NDBEs; $23,569-$51,470 for DBEs in 2012 USD). Combining prevalence and per-person excess expenditures, the three costliest complications were nephropathy, heart failure, and ischemic heart disease (IHD) for DBEs, compared to neuropathy, nephropathy, and IHD for NDBEs. CONCLUSIONS: Our study provides data that can be used for assessing the health care resources needed for managing DRCs and evaluating cost-effectiveness of interventions to prevent and management DRCs.

Factors Contributing to the Rising National Cost of Glucose-Lowering Medicines for Diabetes During 2005-2007 and 2015-2017.

OBJECTIVE: We examined changes in glucose-lowering medication spending and quantified the magnitude of factors that are contributing to these changes. RESEARCH DESIGN AND METHODS: Using the Medical Expenditure Panel Survey, we estimated the change in spending on glucose-lowering medications during 2005-2007 and 2015-2017 among adults aged ≥18 years with diabetes. We decomposed the increase in total spending by medication groups: for insulin, by human and analog; and for noninsulin, by metformin, older, newer, and combination medications. For each group, we quantified the contributions by the number of users and cost-per-user. Costs were in 2017 U.S. dollars. RESULTS: National spending on glucose-lowering medications increased by $40.6 billion (240%), of which insulin and noninsulin medications contributed $28.6 billion (169%) and $12.0 billion (71%), respectively. For insulin, the increase was mainly associated with higher expenditures from analogs (156%). For noninsulin, the increase was a net effect of higher cost for newer medications (+88%) and decreased cost for older medications (-34%). Most of the increase in insulin spending came from the increase in cost-per-user. However, the increase in the number of users contributed more than cost-per-user in the rise of most noninsulin groups. CONCLUSIONS: The increase in national spending on glucose-lowering medications during the past decade was mostly associated with the increased costs for insulin, analogs in particular, and newer noninsulin medicines, and cost-per-user had a larger effect than the number of users. Understanding the factors contributing to the increase helps identify ways to curb the growth in costs.

Medical Costs Among Youth Younger Than 20 Years of Age With and Without Diabetic Ketoacidosis at the Time of Diabetes Diagnosis.

OBJECTIVE: While diabetic ketoacidosis (DKA) is common in youth at the onset of the diabetes, the excess costs associated with DKA are unknown. We aimed to quantify the health care services use and medical care costs related to the presence of DKA at diagnosis of diabetes. RESEARCH DESIGN AND METHODS: We analyzed data from the U.S. MarketScan claims database for 4,988 enrollees aged 3-19 years insured in private fee-for-service plans and newly diagnosed with diabetes during 2010-2016. Youth with and without DKA at diabetes diagnosis were compared for mean health care service use (outpatient, office, emergency room, and inpatient visits) and medical costs (outpatient, inpatient, prescription drugs, and total) for 60 days prior to and 60 days after diabetes diagnosis. A two-part model using generalized linear regression and logistic regression was used to estimate medical costs, controlling for age, sex, rurality, health plan, year, presence of hypoglycemia, and chronic pulmonary condition. All costs were adjusted to 2016 dollars. RESULTS: At diabetes diagnosis, 42% of youth had DKA. In the 60 days prior to diabetes diagnosis, youth with DKA at diagnosis had less health services usage (e.g., number of outpatient visits: -1.17; P < 0.001) and lower total medical costs (-$635; P < 0.001) compared with youth without DKA at diagnosis. In the 60 days after diagnosis, youth with DKA had significantly greater health care services use and health care costs ($6,522) compared with those without DKA. CONCLUSIONS: Among youth with newly diagnosed diabetes, DKA at diagnosis is associated with significantly higher use of health care services and medical costs.

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.

Factors Contributing to Increases in Diabetes-Related Preventable Hospitalization Costs Among U.S. Adults During 2001-2014.

OBJECTIVE: To examine changes in diabetes-related preventable hospitalization costs and to determine the contribution of each underlying factor to these changes. RESEARCH DESIGN AND METHODS: We used data from the 2001-2014 U.S. National (Nationwide) Inpatient Sample (NIS) for adults (≥18 years old) to estimate the trends in hospitalization costs (2014 USD) in total and by condition (short-term complications, long-term complications, uncontrolled diabetes, and lower-extremity amputation). Using regression and growth models, we estimated the relative contribution of following underlying factors: total number of hospitalizations, rate of hospitalization, the number of people with diabetes, mean cost per admission, length of stay, and cost per day. RESULTS: During 2001-2014, the estimated total cost of diabetes-related preventable hospitalizations increased annually by 1.6% (92.9 million USD; P < 0.001). Of this 1.6% increase, 75% (1.2%) was due to the increase in the number of hospitalizations, which is a result of a 3.8% increase in diabetes population and a 2.6% decrease in the hospitalization rate, and 25% (0.4%) was due to the increase in cost per admission, for a net result of a 1.6% increase in cost per day and a 1.3% decline in mean length of stay. By component, the cost of short-term complications, lower-extremity amputations, and long-term complications increased annually by 4.2, 1.9, and 1.5%, respectively, while the cost of uncontrolled diabetes declined annually by 2.6%. CONCLUSIONS: The total cost of diabetes-related preventable hospitalizations had been increasing during 2001-2014, mainly resulting from increases in number of people with diabetes and cost per hospitalization day. The underlying factors identified in our study could lead to efforts that may lower future hospitalization costs.

Modeling the impact of obesity on the lifetime risk of chronic kidney disease in the United States using updated estimates of GFR progression from the CRIC study.

RATIONALE & OBJECTIVE: As the prevalence of obesity continues to rise in the United States, it is important to understand its impact on the lifetime risk of chronic kidney disease (CKD). STUDY DESIGN: The CKD Health Policy Model was used to simulate the lifetime risk of CKD for those with and without obesity at baseline. Model structure was updated for glomerular filtration rate (GFR) decline to incorporate new longitudinal data from the Chronic Renal Insufficiency Cohort (CRIC) study. SETTING AND POPULATION: The updated model was populated with a nationally representative cohort from National Health and Nutrition Examination Survey (NHANES). OUTCOMES: Lifetime risk of CKD, highest stage and any stage. MODEL, PERSPECTIVE, & TIMEFRAME: Simulation model following up individuals from current age through death or age 90 years. RESULTS: Lifetime risk of any CKD stage was 32.5% (95% CI 28.6%-36.3%) for persons with normal weight, 37.6% (95% CI 33.5%-41.7%) for persons who were overweight, and 41.0% (95% CI 36.7%-45.3%) for persons with obesity at baseline. The difference between persons with normal weight and persons with obesity at baseline was statistically significant (p<0.01). Lifetime risk of CKD stages 4 and 5 was higher for persons with obesity at baseline (Stage 4: 2.1%, 95% CI 0.9%-3.3%; stage 5: 0.6%, 95% CI 0.0%-1.1%), but the differences were not statistically significant (stage 4: p = 0.08; stage 5: p = 0.23). LIMITATIONS: Due to limited data, our simulation model estimates are based on assumptions about the causal pathways from obesity to CKD, diabetes, and hypertension. CONCLUSIONS: The results of this study indicate that obesity may have a large impact on the lifetime risk of CKD. This is important information for policymakers seeking to set priorities and targets for CKD prevention and treatment.

Economic Costs Attributable to Diabetes in Each U.S. State.

OBJECTIVE: To estimate direct medical and indirect costs attributable to diabetes in each U.S. state in total and per person with diabetes. RESEARCH DESIGN AND METHODS: We used an attributable fraction approach to estimate direct medical costs using data from the 2013 State Health Expenditure Accounts, 2013 Behavioral Risk Factor Surveillance System, and the Centers for Medicare & Medicaid Services' 2013-2014 Minimum Data Set. We used a human capital approach to estimate indirect costs measured by lost productivity from morbidity (absenteeism, presenteeism, lost household productivity, and inability to work) and premature mortality, using the 2008-2013 National Health Interview Survey, 2013 daily housework value data, 2013 mortality data from the Centers for Disease Control and Prevention Wide-ranging Online Data for Epidemiologic Research, and mean wages from the 2014 Bureau of Labor Statistics. Costs were adjusted to 2017 U.S. dollars. RESULTS: The estimated median state economic cost was $5.9 billion, ranging from $694 million to $55.5 billion, in total and $18,248, ranging from $15,418 to $30,915, per person with diabetes. The corresponding estimates for direct medical costs were $2.8 billion (range $0.3-22.9) and $8,544 (range $6,591-12,953) and for indirect costs were $3.0 billion (range $0.4-32.6) and $9,672 (range $7,133-17,962). In general, the estimated state median indirect costs resulting from morbidity were larger than costs from mortality both in total and per person with diabetes. CONCLUSIONS: Economic costs attributable to diabetes were large and varied widely across states. Our comprehensive state-specific estimates provide essential information needed by state policymakers to monitor the economic burden of the disease and to better plan and evaluate interventions for preventing type 2 diabetes and managing diabetes in their states.

Medical Expenditures Associated With Diabetes Among Adult Medicaid Enrollees in Eight States.

INTRODUCTION: Little information is available on state-specific financial burdens of diabetes in the Medicaid population, yet such information is essential for state Medicaid programs to plan diabetes care and evaluate the benefits of diabetes prevention. We estimated medical expenditures associated with diabetes among adult Medicaid enrollees in 8 states. METHODS: We analyzed the latest available 2012 CMS Medicaid claims data for 1,193,811 adult enrollees aged 19-64 years in 8 states: Alabama, California, Connecticut, Florida, Illinois, Iowa, New York, and Oklahoma. For each state, we stratified the study population by Medicaid eligibility criteria: disability and nondisability. For each group, we estimated per capita annual medical expenditures on outpatient care, inpatient care, and prescription drugs by using a 2-part model, adjusted for age, sex, race/ethnicity, and comorbidities. We calculated the expenditures associated with diabetes as the difference in predicted expenditures for enrollees with and without diabetes. Analyses were done in 2017. RESULTS: For disability-based enrollees, the estimated total per capita annual diabetes expenditures ranged from $6,183 in Alabama to $15,319 in New York (all P < .001). For nondisability-based enrollees, the corresponding estimates ranged from $4,985 in Alabama to $15,366 in New York (all P < .001). The proportion of individual components varied by state and eligibility criteria. CONCLUSION: Medical expenditures associated with diabetes among adults on Medicaid were substantial and varied across studied states. Our estimates can be used by the 8 state Medicaid programs to prepare health care resources needed for diabetes care and assess the financial benefits of diabetes prevention programs.

Diabetes-Attributable Nursing Home Costs for Each U.S. State.

OBJECTIVE: To estimate the diabetes-attributable nursing home costs for each state. RESEARCH DESIGN AND METHODS: We used a diabetes-attributable fraction (AF) approach to estimate nursing home costs attributable to diabetes (in 2013 dollars) in aggregate and per person with diabetes in each state. We calculated the AFs as the difference in diabetes prevalence between nursing homes and the community. We used the Centers for Medicare & Medicaid Services 2013-2015 Minimum Data Set to estimate the prevalence of diabetes in nursing homes and to adjust for the intensity of care among people with diabetes in nursing homes. Community prevalence was estimated using the Behavioral Risk Factor Surveillance System (BRFSS). State nursing home expenditures were from the 2013 State Health Expenditure Accounts. RESULTS: The fraction of total nursing home expenditures attributable to diabetes ranged from 12.3% (Illinois) to 22.5% (Washington, DC; median AF of 15.6%, New Jersey). The median AF was highest in the 19-64 years age-group and lowest in the 85 years or older age-group. Nationally, diabetes-attributable nursing home costs were $18.6 billion. State-level diabetes-attributable costs ranged from $21 million in Alaska to $2.0 billion in California. Diabetes-attributable nursing home costs per person ranged from $374 in New Mexico to $1,610 in Washington, DC (median of $799 in Maine). CONCLUSIONS: Our estimates provide state policymakers with an improved understanding of the economic burden of diabetes in each state's nursing homes. These estimates could serve as critical inputs for planning and evaluating diabetes prevention and management interventions that can keep people healthier and living longer in their communities.