Adam Paulsen

University of Wisconsin, Madison, Mississippi, United States

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Publications (3)2.86 Total impact

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    ABSTRACT: To assess how health-related quality of life (HRQoL) varies by body mass index (BMI) category among gender and racial subgroups using nine HRQoL measures. Among 3,710 US adults, we evaluated self-reported height, weight, and HRQoL that was measured by six indexes (EQ-5D; HUI2; HUI3; SF-6D; QWB-SA; HALex) and three summary measures (theta; PCS; MCS). Mean HRQoL was estimated by weighted regression for normal, overweight, and obese subgroups (BMI: 18.5-24.9 kg/m(2); 25-29.9; and 30-50). HRQoL was significantly lower (P < 0.0001) with increasing BMI category except for MCS. Obese individuals were 5.3 units lower on PCS (1-100 scale) and 0.05-0.11 lower on the HRQoL indexes (0-1 scale) than those with normal weight. MCS scores were significantly lower for obese than normal-weight among women (P = 0.04) but not men (P = 0.11). Overweight blacks had higher HRQoL than blacks in other BMI categories (P = 0.033). 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.
    Quality of Life Research 06/2011; 20(5):665-74. · 2.86 Impact Factor
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    ABSTRACT: Purpose: Assessing the impact of health conditions in national surveys is important for policy-relevant cost-effectiveness analyses. We compare estimates of the impacts of eleven chronic health conditions in the same survey respondents using six commonly used indexes of health-related quality of life (HRQoL). Method: The National Health Measurement Study is a cross-sectional telephone survey of 3844 US adults aged 35-89 that includes the items required to calculate the EQ-5D, HALex, HUI2, HUI3, SF-6D, and QWB-SA. Respondents were also asked whether they had ever been diagnosed with each of eleven different health conditions: sleep disorder, stroke, depression, back pain due to herniated disk, coronary heart disease (CHD), respiratory disease (COPD), ulcer, arthritis, diabetes, thyroid condition, and eye disease. Data were stratified into ages 35-64 and 65-89 years. Within each age stratum, we performed survey-weighted regression analyses for each index using indicator variables for all eleven health conditions, with age and gender as independent variables in the equation. Coefficients and associated standard errors for each condition represent condition impacts adjusted for other conditions, age, and gender. Result: Condition impacts for the conditions vary by age strata and index. In the younger age stratum, the largest impacts were for herniated disk (mean impact = -0.11) and depression (-0.10); in the older age stratum, the largest impacts were for stroke (-0.10) and depression (-0.10). Smallest impact was for thyroid disorder (-0.01) in younger, and ulcer (-0.004) in older respondents. Within the conditions with large impacts, the ratio of maximum impact to minimum impact across the indexes ranged from 1.4 (arthritis) to 5.3 (COPD). Impacts measured by the HUI3 are generally largest and those for SF-6D smallest. For example, the estimated loss in undiscounted QALYs over 10 years for depression in those aged 65-89 ranges from 0.68 QALYs using the QWB-SA to 1.73 QALYs using the HUI3. Results are limited by lack of information on the severity of the self-reported conditions. Conclusion: Health condition impact estimates can vary substantially across commonly used HRQoL indexes. This probably is due to both different scaling and differential sensitivity to dimensions of health across the indexes. Therefore, computed QALYs in reference case cost-effectiveness analyses may differ substantially by the HRQoL index used to measure outcomes.
    The 31th Annual Meeting of the Society for Medical Decision Making; 10/2009
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    ABSTRACT: Purpose: We assessed the relationship between health-related quality of life (HRQoL) and self-reported body mass index (BMI) using nine distinct measures of health status and HRQoL. Methods: Data were from the National Health Measurement Study (NHMS), a cross-sectional telephone survey of 3,844 non-institutionalized U.S. adults aged 35-89 years, administering all HRQoL measures to each participant. BMI was calculated from self-reported height and weight. We estimated mean HRQoL scores using weighted least squares for normal, overweight, and obese categories of BMI (18.5-24.9 kg/m2; 25-29.9; and ≥30, respectively) with respect to age, race, education and smoking for six standard indices of HRQoL (EQ-5D; SF-6D; HUI3; HUI2; QWB-SA; and HALex) and three summary measures of health status (Theta – an item response theory-derived composite measure – and SF-36 physical and mental component scores (PCS and MCS)). Results: Among 3,712 U.S. adults with complete BMI data, eight of out nine measures captured significantly lower unadjusted mean HRQoL (p<0.0001) with increasing BMI category, with differences between obese and normal weight 5.2 for PCS, 0.36 for Theta and ranging from 0.10 for HALex to 0.04 for SF-6D. Differences between overweight and normal individuals were 1.9 for PCS, 0.11 for Theta, and ranged from 0.0 on SF-6D to 0.03 on both QWB and HALex. There was no significant difference in mean MCS scores between BMI groups (p=0.46), except that obese women had worse MCS than normal weight women (difference=1.2, p=0.0134). While other race and gender patterns appeared different based on effect sizes, these differences were not statistically significant with a few exceptions. There was an indication that blacks were less affected by overweight than other races (p=0.034), particularly on the HUI2, HUI3, and EQ-5D (normal-overweight differences of 0.04 on each). Adjustments did not change results. Conclusions: Among U.S. adults, six commonly-used HRQoL indices and two summary measures – excluding the MCS – of health status detected significantly lower HRQoL associated with obesity and overweight as compared with normal BMI, although preference score indexes did differ in their sensitivity to BMI. The association appeared to be primarily driven by physical but not mental health status for all groups except for women.
    The 31th Annual Meeting of the Society for Medical Decision Making; 10/2009