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Background Systemic corticosteroids (SCS) are commonly used but are associated with adverse effects. Given their prevalent use, the potential impact of SCS use on health-related quality of life (HRQoL) is important to characterize. Objective To assess the HRQoL of patients taking SCS. Methods The 2000-2003 Medical Expenditure Panel Survey was used to examine EQ-5D and SF-6D scores associated with SCS use in adults. The study sample was restricted to those with a condition for which SCS are prescribed. SCS use was categorized into three levels: none; 1-3; and ≥4 prescriptions per year. HRQoL scores were regressed on SCS use (1-3 or ≥4 annual prescriptions) controlling for age, gender, race, ethnicity, education, income category, geographic region, number of ER visits, number of outpatient visits, total number of chronic conditions (for which SCS are not used) and conditions for which SCS are clinically indicated. Results There were 54,856 individuals with no SCS exposure, 2245 with 1-3 and 624 with ≥4 annual SCS prescriptions. In adjusted analyses, use of ≥4 annual SCS prescriptions appeared to be associated with significantly lower EQ-5D (US), EQ-5D (UK), SF-6D and EQ-5D VAS scores compared to no exposure: –0.032, –0.047, –0.036, and –7.58. Conclusion While SCS are efficacious and widely used for numerous conditions, results suggest that their use may be associated with a substantial deleterious impact on HRQoL. This potential negative effect should be considered in balance with the cost and efficacy of comparable treatments.

OBJECTIVE:--Given the risk of obesity and diabetes in the U.S., and clear benefit of exercise in disease prevention and management, this study aimed to determine the prevalence of physical activity among adults with and at risk for diabetes. RESEARCH DESIGN AND METHODS--The Medical Expenditure Panel Survey is a nationally representative survey of the U.S. population. In the 2003 survey, 23,283 adults responded when asked about whether they were physically active (moderate or vigorous activity, >=30 min, three times per week). Information on sociodemographic characteristics and health conditions were self-reported. Additional type 2 diabetes risk factors examined were age >=45 years, non-Caucasian ethnicity, BMI >=25 kg/m², hypertension, and cardiovascular disease. RESULTS:--A total of 39% of adults with diabetes were physically active versus 58% of adults without diabetes. The proportion of active adults without diabetes declined as the number of risk factors increased until dropping to similar rates as people with diabetes. After adjustment for sociodemographic and clinical factors, the strongest correlates of being physically active were income level, limitations in physical function, depression, and severe obesity (BMI >=40 kg/m²). Several traditional predictors of activity (sex, education level, and having received past advice from a health professional to exercise more) were not evident among respondents with diabetes. CONCLUSIONS:--The majority of patients with diabetes or at highest risk for developing type 2 diabetes do not engage in regular physical activity, with a rate significantly below national norms. There is a great need for efforts to target interventions to increase physical activity in these individuals.

Background: The variability in preferences used in quality-adjusted life-years estimation jeopardizes the comparability of cost-effectiveness analyses and has led the Panel on Cost-Effectiveness in Health and Medicine (the PCEHM) to call for a catalog of \"off-the-shelf\" preference weights associated with conditions that can be used by health researchers without the burden of collecting primary data. Objective: The current research responds to the call by developing a nationally representative catalog of preference-based scores for chronic conditions and associated sociodemographic characteristics. Methods: The authors report the ${\\rm EQ}\\text{-}5{\\rm D}_{\\text{index}}$ scores of chronic conditions and associated sociodemographic characteristics in the nationally representative Medical Expenditure Panel Survey (MEPS). Chronic conditions were coded using \"quality priority conditions\" (QPC) and clinical classification categories (CCC). OLS, Tobit, and censored least absolute deviations (CLAD) regression models were used to provide condition estimates adjusted for age, comorbidity, gender, race, ethnicity, income, and education. Results: Unadjusted and adjusted ${\\rm EQ}\\text{-}5{\\rm D}_{\\text{index}}$ scores for each QPC and CCC code are presented. ${\\rm EQ}\\text{-}5{\\rm D}_{\\text{index}}$ scores for older age categories were lower than younger categories, female scores were lower than males, certain racial groups had lower scores than others, and ${\\rm EQ}\\text{-}5{\\rm D}_{\\text{index}}$ scores were higher for individuals with higher education and income levels. Conclusion: The preference-based chronic condition scores reported in this research are nationally representative and may be useful to researchers to calculate quality-adjusted life-years for cost-effectiveness analyses and population-based burden of illness studies without the difficulty of primary data collection. Further research is necessary to validate these scores in condition-specific studies.

Objective The prevalence of obesity and associated cardiometabolic risk factors such as diabetes, hyperlipidemia and hypertension is increasing significantly for all demographic groups. Research design and methods The 2000 and 2002 Medical Expenditure Panel Survey (MEPS), a nationally representative survey of the U.S. population, was used to estimate the marginal impact of obesity on health function, perception, and preferences for individuals with diabetes, hyperlipidemia, and hypertension using multivariate regression methods controlling for age, sex, race, ethnicity, education, income, insurance, smoking status, comorbidity, and proxy response. Three different instruments were used: SF-12 physical component scale (PCS-12) and mental component scale (MCS-12); EQ-5D index and visual analogue scale (VAS). Censored least absolute deviation was used for the EQ-5D and VAS (due to censoring) and ordinary least squares (OLS) was used for the PCS-12 and MCS-12. Results After controlling for sociodemographic characteristics, diabetes, hyperlipidemia, and hypertension were associated with significantly lower scores compared to normal weight individuals without the condition for all four instruments. Obesity significantly exacerbated this association. Controlling for comorbidity attenuated the negative association of obesity and cardiometabolic risk factors on instrument scores. In addition, scores decreased for increasing weight and number of risk factors. Conclusions Obesity significantly exacerbates the deleterious association between diabetes, hyperlipidemia, and hypertension, and health function, health perception, and preference-based scores in the United States.

Background Accurate assessment of preference-based health-related quality of life is important in determining the value of asthma interventions. Objective To examine the sensitivity and responsiveness of the EQ-5D and the AQL-5D to differences in asthma control measured by the Asthma Control Questionnaire (ACQ-5). Methods The Observational Study of Asthma Control and Outcomes was a prospective survey of persistent asthma patients ≥12 years old in Kaiser Colorado. Patients received a survey three times in 1 year, including the ACQ-5, AQL-5D and EQ-5D-3L (including VAS). Censored Least Absolute Deviations (CLAD) and logistic regression were used, controlling for sociodemographics and smoking. Results There were 6666 completed surveys (1799 individuals completed all three survey waves). After controlling for covariates, each one-point increase in ACQ-5 was associated with a decrease of 0.066, 0.058, 0.074 and 6.12 in EQ-5D(US), EQ-5D(UK), AQL-5D and VAS scores. Uncontrolled asthma (ACQ-5 > 1.5) was associated with a decrease of 0.15, 0.17, 0.11 and 10, respectively (vs. ACQ ≤ 1.5). AQL-5D scores were statistically significantly different across categories of ACQ-5 scores of 0.5 (the minimum clinically important difference [MCID]), while EQ-5D scores were not significant across most categories. The AQL-5D appeared more robust to changes in control over time (responsiveness) compared to EQ-5D-3L. Conclusion The AQL-5D appears more responsive to changes in asthma control over time and more sensitive to detecting differences corresponding to the ACQ-5 MCID than the EQ-5D-3L. Using the EQ-5D-3L without an asthma-specific measure such as the AQL-5D may miss clinically important changes in asthma control.

OBJECTIVE:--Obesity and physical inactivity are established risk factors for type 2 diabetes and cardiovascular comorbidities. Whether adiposity or fitness level is more important to health is controversial. The objective of this research is to determine the relative associations of physical activity and BMI with the prevalence of diabetes and diabetes-related cardiovascular comorbidities in the U.S. RESEARCH DESIGN AND METHODS--The Medical Expenditure Panel Survey (MEPS) is a nationally representative survey of the U.S. population. From 2000 to 2002, detailed information on sociodemographic characteristics and health conditions were collected for 68,500 adults. Normal weight was defined as BMI 18.5 to <25 kg/m², overweight 25 to /=]40 kg/m². Physical activity was defined as moderate/vigorous activity [>/=]30 min [>/=]3 days per week. RESULTS:--The likelihood of having diabetes and diabetes-related cardiovascular comorbidities increased with BMI regardless of physical activity and increased with physical inactivity regardless of BMI. Compared with normal-weight active adults, the multivariate-adjusted odds ratio (OR) for diabetes was 1.52 (95% CI 1.25-1.86) for normal-weight inactive adults and 1.65 (1.40-1.96) for overweight inactive adults; the OR for diabetes and comorbid hypertension was 1.71 (1.32-2.19) for normal-weight inactive adults and 1.84 (1.47-2.32) for overweight inactive adults. CONCLUSIONS:--Both physical inactivity and obesity seem to be strongly and independently associated with diabetes and diabetes-related comorbidities. These results support continued research investigating the independent causal nature of these factors.

Background : Many statistical analyses, clinical trials and cost-utility analyses designed to measure the impact of a particular disease on utility scores often overlook the important influence of co-morbidity burden. Objectives : This study aims to examine the impact of co-morbidity burden on EQ-5D index scores in a nationally representative sample of the US. Methods : The pooled 2001 and 2003 Medical Expenditure Panel Survey was used. The total number of chronic conditions for each individual was calculated based on Clinical Classification Categories codes. Spline regression was used to identify nonlinear age effects: individuals were separated into four quartiles based on age. Censored least absolute deviation was used to regress EQ-5D index scores on age and chronic co-morbidity, controlling for income, gender, race, ethnicity, education, physical activity and smoking status. Interactions between age and chronic conditions were also explored. Results : The coefficients for chronic co-morbidities were highly statistically significant with large magnitudes for those with two or more chronic conditions (coefficient two chronic conditions=-0.16; coefficient nine chronic conditions=-0.28). After controlling for chronic co-morbidities and other confounders, age was not statistically significant except for those aged >58 years and the magnitude of this coefficient was very small (coefficient aged >58 years=-0.0006). The interactions between age and chronic comorbidity were significant, but the deleterious impact of their interaction was largely dominated by the existence and number of chronic conditions. Conclusions : Chronic conditions have a significant deleterious impact on EQ-5D index scores that is much more pronounced than age and other sociodemographic and behavioural characteristics. Future analyses and costutility models should incorporate the impact of multiple morbidity.

Comparative studies evaluating traditional versus newer antianginal (AA) medications in chronic stable angina pectoris (CSA) on cardiovascular (CV) outcomes and utilization are limited, particularly in patients with diabetes mellitus (DM). Claims data (2008 to 2012) were analyzed using a commercial database. Patients with CSA receiving a β blocker (BB), calcium channel blocker (CCB), long-acting nitrate (LAN), or ranolazine were identified and followed for 12 months after a change in AA therapy. Patients on traditional AA medications were required to have concurrent sublingual nitroglycerin. Therapy change was defined as adding or switching to another traditional AA medication or ranolazine to identify patients whose angina was inadequately controlled with previous therapy. Four groups were identified (BB, CCB, LAN, or ranolazine users) and matched on relevant characteristics. A DM subset was identified. Logistic regression compared revascularization at 30, 60, 90, 180, and 360 days. Negative binomial regression compared all-cause, CV-, and DM-related (in the DM cohort) health care utilization. A total of 8,008 patients were identified with 2,002 patients in each matched group. Majority were men (mean age 66 years). A subset of 3,724 patients with DM (BB, n = 933; CCB, n = 940; LAN, n = 937; and ranolazine, n = 914) resulted from this cohort. Compared to ranolazine in the overall cohort, traditional AA medication exhibited greater odds for revascularization and higher rates in all-cause outpatient, emergency room visits, inpatient length of stay, and CV-related emergency room visits. In the DM cohort, ranolazine demonstrated similar benefits over traditional AA medication. In conclusion, ranolazine use in patients with inadequately controlled chronic angina is associated with less revascularization and all-cause and CV-related health care utilization compared to traditional AA medication.

The objective of this study was to determine the direct and indirect costs of acute coronary syndromes (ACS) alone and with common cardiovascular comorbidities. A retrospective analysis was conducted using the Medical Expenditure Panel Survey from 1998 to 2009. Four mutually exclusive cohorts were evaluated: ACS only, ACS with atrial fibrillation (AF), ACS with heart failure (HF), and ACS with both conditions. Direct costs were calculated for all-cause and cardiovascular-related health care resource utilization. Indirect costs were determined from productivity losses from missed days of work. Regression analysis was developed for each outcome controlling for age, US census region, insurance coverage, sex, race, ethnicity, education attainment, family income, and comorbidity burden. A negative binomial regression model was used for health care utilization variables. A Tobit model was utilized for health care costs and productivity loss variables. Total health care costs were greatest for those with ACS and both AF and HF ($38,484±5,191) followed by ACS with HF ($32,871±2,853), ACS with AF ($25,192±2,253), and ACS only ($17,954±563). Compared with the ACS only cohort, the mean all-cause adjusted health care costs associated with ACS with AF, ACS with HF, and ACS with AF and HF were $5,073 (95% confidence interval [CI] 719-9,427), $11,297 (95% CI 5,610-16,985), and $15,761 (95% CI 4,784-26,738) higher, respectively. Average wage losses associated with ACS with and without AF and/or HF amounted to $5,266 (95% CI -7,765, -2,767), when compared with patients without these conditions. ACS imposes a significant economic burden at both the individual and society level, particularly when with comorbid AF and HF.

Estimate the economic burden associated with incremental increases in the number of cardiometabolic risk factors (CMRFs) in the US. We used the nationally representative Medical Expenditure Panel Survey from 2010 to 2012 to create a retrospective cohort of people based on the number of CMRFs (one, two, and three or four), and a comparison cohort of people with zero CMRFs. CMRFs included abdominal obesity, elevated blood pressure, elevated triglycerides, and elevated glucose and were defined using diagnostic codes, prescribed medications, and survey responses. Adjusted regression analysis was developed to compare health expenditures, utilization, and lost-productivity differences between the cohorts. Generalized linear regression was used for health care expenditures, and negative binomial regression was used for utilization and productivity, controlling for individual characteristics. The number of CMRFs was associated with significantly more annual utilization, health care expenditures, and reduced productivity. As compared with people with zero CMRFs, people with one, two, and three or four CMRFs had 1.15 (95% confidence interval [CI]: 1.06, 1.24), 1.37 (95% CI: 1.25, 1.51), and 1.39 (95% CI: 1.22, 1.57) times higher expected rate of emergency room visits, respectively. Compared with people with zero CMRFs, people with one, two, and three or four CMRFs had increased incremental health care expenditures of US$417 (95% CI: $70, $763), US$2,326 (95% CI: $1,864, $2,788), and US$4,117 (95% CI: $3,428, $4,807), respectively. Those with three or four CMRFs reported employment of 60%, compared with 80% in patients with zero CMRFs. People with three or four CMFRs had 1.75 (95% CI: 1.42, 2.17) times higher expected rate of days missed at work due to illness, compared with people with zero CMRFs. Our findings demonstrate a direct association between economic burden and number of CMRFs. Although this was expected, the increase in burden that was independent from the cost of cardiovascular disease was surprising.