Background-A number of indexes measuring self-reported generic health-related quality-of-life (HRQoL) using preference-weighted scoring are used widely in population surveys and clinical studies in the U.S.

PurposeThe purpose of this study was to describe gender differences in self-reported health-related quality-of-life (HRQoL) and to examine whether differences are explained by sociodemographic and socioeconomic status (SES) differentials between men and women.MethodsData were from four US nationally representative surveys: US Valuation of the EuroQol EQ-5D Health States Survey (USVEQ), Medical Expenditure Panel Survey (MEPS), National Health Measurement Study (NHMS) and Joint Canada/US Survey of Health (JCUSH). Gender differences were estimated with and without adjustment for sociodemographic and SES indicators using regression within and across data sets with SF-6D, EQ-5D, HUI2, HUI3 and QWB-SA scores as outcomes.ResultsWomen have lower HRQoL scores than men on all indexes prior to adjustment. Adjusting for age, race, marital status, education and income reduced but did not remove the gender differences, except with HUI3. Adjusting for marital status or income had the largest impact on estimated gender differences.ConclusionsThere are clear gender differences in HRQoL in the United States. These differences are partly explained by sociodemographic and SES differentials.

Significant improvements in HRQoL at the population level will only be possible if we improve the HRQoL of people at the lowest end of the socioeconomic distribution.

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Background-Five health-related quality-of-life (HRQoL) indexes-EQ-5D, HUI2, HUI3, QWB-SA, and SF-6D-are each used to assign community-based utility scores to health states, although these scores differ.

Children with uncontrolled epilepsy use significantly more healthcare resources and have a greater economic burden than children with stable epilepsy. However, epilepsy accounted for only half of overall costs, indicating that comorbid conditions may add substantially to the disease burden.

The economic burden of acromegaly in the US has been largely unknown. We describe the prevalence of treatment patterns, complication rates, and associated healthcare utilization and costs of acromegaly in the US. Patients were identified between 1/1/2002 and 12/31/2009 in claims databases. During 1-year after each continuously-enrolled patient's first acromegaly claim, pharmacy and medical claims were used to estimate outcomes. Regression models were used to adjust outcomes. There were 2,171 acromegaly patients (mean age: 45.3 years; 49.7% female); 77.8% received the majority of their care from non-endocrinologists. Pharmacologic treatment was used by 30.8% of patients: octreotide-LAR in 18.6%, dopamine agonists in 9.8%, short-acting octreotide in 4.7%, pegvisomant in 4.1%, and lanreotide in 1.2%; 56% had biochemical monitoring. Comorbidities were common, ranging from 6.6% (colon neoplasms) to 25.6% (musculoskeletal abnormalities). Mean healthcare costs were $24,900. Adjusted analyses indicated comorbidities increased the odds of hospitalization: by 76% for musculoskeletal abnormalities; 193% for cardiovascular abnormalities; and 56% for sleep apnea (p< 0.05). Odds of emergency department visits increased by 87% (musculoskeletal) and 132% (cardiovascular abnormalities) (p < 0.01). After adjustments, colon neoplasms were associated with $8,401 mean increase in costs; musculoskeletal abnormalities with $7,502, cardiovascular abnormalities with $13,331, sleep apnea with $10,453, and hypopituitarism with $6,742 (p < 0.01). Complications are common and increase utilization and cost in acromegaly patients. Cardiovascular complications nearly tripled the odds of hospitalization (OR 2.93) and increased annual mean cost by $13,331. Adequate management of this disease may be able to reduce health care utilization and cost associated with these complications and with acromegaly in general.

Six commonly used HRQoL indexes and two of three health status summary measures indicated lower HRQoL with obesity and overweight than with normal BMI, but the degree of decrement varied by index. The association appeared driven primarily by physical health, although mental health also played a role among women. Counter to hypotheses, blacks may have highest HRQoL when overweight.