Erica I. Lubetkin

Gender and the Burden of Disease Attributable to Obesity

OBJECTIVES We estimated the burden of disease in the United States attributable to obesity by gender, with life expectancy, quality-adjusted life expectancy, years of life lost annually, and quality-adjusted life years lost annually as outcome measures. METHODS We obtained burden of disease estimates for adults falling into the following body-mass index categories: normal weight (23 to <25), overweight (25 to <30), and obese (> or = 30). We analyzed the 2000 Medical Expenditure Panel Survey to obtain health-related quality-of-life scores and the 1990-1992 National Health Interview Survey linked to National Death Index data through the end of 1995 for mortality. RESULTS Overweight men and women lost 270,000 and 1.8 million quality-adjusted life years, respectively, relative to their normal-weight counterparts. Obese men and women lost 1.9 million and 3.4 million quality-adjusted life years, respectively, per year. Much of the burden of disease among overweight and obese women arose from lower health-related quality of life and late life mortality. CONCLUSIONS Relative to men, women suffer a disproportionate burden of disease attributable to overweight and obesity, mostly because of differences in health-related quality of life.

Relationship among sociodemographic factors, clinical conditions, and health-related quality of life: Examining the EQ-5D in the U.S. general population

Introduction: Health-related quality of life (HRQL) measures are used increasingly in evaluations of clinical and population-based outcomes and in economic analyses. We investigate the influence of demographic, socioeconomic, and chronic disease factors on the HRQL of a representative U.S. sample. Methods: We examined data from 13,646 adults in the 2000 Medical Expenditure Panel Survey, a nationally representative sample of the U.S. general population, who completed a self-administered questionnaire containing the EQ-5D, a preference-based measure. We assessed the relationships between EQ-5D scores and sociodemographic variables, including age, sex, race/ethnicity, income and education, and six common chronic conditions. Results: In fully adjusted models, EQ-5D scores decreased with increasing category of age and were lower for persons with a lower income and educational attainment as well as each of the six conditions. Although the EQ-5D scores were lower for females and Whites compared with Blacks such differences were not of a magnitude considered to be clinically important. Conclusions: In the U.S., sociodemographic factors and clinical conditions are strongly associated with scores on the EQ-5D. Population health studies and risk-adjustment models should account and adjust for these factors when assessing the performance of health programs and clinical care.

Trends in Quality-Adjusted Life-Years Lost Contributed by Smoking and Obesity

BACKGROUND Quality-adjusted life-years (QALYs) use preference-based measurements of health-related quality-of-life (HRQOL) to provide an assessment of the overall burden of disease using a single number. PURPOSE This study estimated QALYs lost contributed by smoking and obesity for U.S. adults from 1993 to 2008. METHODS Population HRQOL data were from the 1993-2008 Behavioral Risk Factor Surveillance System. The QALYs lost contributed by a risk factor is the sum of QALYs lost due to morbidity in the current year and future QALYs lost in expected life-years due to premature deaths (mortality). Premature deaths were estimated from the National Health Interview Survey Linked Mortality Files and mortality statistics. RESULTS From 1993 to 2008, the proportion of smokers among U.S. adults declined 18.5% whereas the proportion of obese people increased 85%. The smoking-related QALYs lost were relatively stable at 0.0438 QALYs lost per population. In 1993 the QALYs lost were much smaller for obesity compared to smoking, with obesity contributing about 0.0204 QALYs lost. However, as a result of the increasing prevalence of obesity, the contribution of obesity-related QALYs lost increased consistently and had increased by 127% in 2008 when obesity resulted in 0.0464 QALYs lost, slightly more than smoking did. Smoking had a bigger impact on mortality than morbidity, whereas obesity had a bigger impact on morbidity than mortality. CONCLUSIONS This study estimated the overall burden of smoking and obesity over time and results indicate that because of the marked increase in the proportion of obese people, obesity has become an equal, if not greater, contributor to the burden of disease than smoking. Such data are essential in setting targets for reducing modifiable health risks and eliminating health disparities.

Mapping the SF-12 to the EuroQol EQ-5D Index in a national US sample.

Background . Preference scores for the Medical Outcomes Study (MOS) SF-12 would enable its use in cost-effectiveness analyses. Previous mapping studies of MOS instruments to preference-based instruments have not examined performance in national samples. Participants . 15,000 adults in the 2000 Medical Expenditure Panel Survey annual survey including the SF-12 and EQ-5D Index. Methods . Regression of the EQ-5D Index scores onto the physical and mental component summary scores of the SF-12, testing 2nd-4th degree polynomial and spline models, including and excluding sociodemographics. Results . A 2nd degree polynomial model explained 63% of the variance in EQ-5D scores, with robust internal and external validation. More complex models explained minimally additional variance. Compared with EQ-5D valuations, prediction models overestimated the lowest health states (6% of the population). Conclusions . The mapped SF-12 yields usable preference-scaled scores, with some caution for the lowest health states.

I think therefore I am: perceived ideal weight as a determinant of health.

OBJECTIVES We examined whether stress related to negative body image perception and the desire to lose weight explained some of the body mass index-health gradient. METHODS We used 2003 Behavioral Risk Factor Surveillance System data to examine the impact of desired body weight, independent of actual body mass index, on the amount of physically and mentally unhealthy days by race, ethnicity, and gender. RESULTS The difference between actual and desired body weight was a stronger predictor than was body mass index (BMI) of mental and physical health. When we controlled for BMI and age, men who wished to lose 1%, 10%, and 20% of their body weight respectively suffered a net increase of 0.1, 0.9, and 2.7 unhealthy days per month relative to those who were happy with their weight. For women, the corresponding numbers were 0.1, 1.6, and 4.3 unhealthy days per month. The desire to lose weight was more predictive of unhealthy days among women than among men and among Whites than among Blacks or Hispanics. CONCLUSIONS Our results raise the possibility that some of the health effects of the obesity epidemic are related to the way we see our bodies.

The use of the EQ-5D preference-based health status measure in adults with Type 2 diabetes mellitus

Diabet. Med. 28, 395–413 (2011)

Levels and Correlates of Patient Activation in Health Center Settings: Building Strategies for Improving Health Outcomes

Patient activation refers to people’s ability to engage in self-management of their health and health care. We assessed the performance of the Patient Activation Measure (PAM) for patients attending three inner-city health centers and compared resultant scores with those of the general U.S. adult population. We approached 801 patients and 527 (65.8%) participated; the majority were Latino(a) or African American/Black. No differences in activation were seen according to age. Males and more educated patients were more activated (p<.05) and patients with better self-rated health and adequate health literacy were more activated than their counterparts (p<.001). Patterns of scores resembled those of the U.S. general population for educational attainment and self-rated health but not for gender and age. Compared with the general population, more patients were characterized as level 1 (least activated). Developing strategies that enhance patient activation is critical to improving health outcomes, particularly in less advantaged populations.

Mapping the SF-12 to preference-based instruments: convergent validity in a low-income, minority population.

Background. The profile-based SF-12 has a low respondent burden and is used widely in clinical settings to monitor health and evaluate programs. Deriving preference scores for the SF-12 health profile would permit its use in cost-effectiveness analyses. Previous mapping studies of SF family instruments to preference-based instruments have not examined convergent validity or performance in low-income, minority populations. Objectives. To map the SF-12 to the EuroQol (EQ-5D Index) and the Health Utilities Index Mark 3 (HUI3) in a low-income, predominantly minority sample. Research Design. We used a cross-sectional survey data. Subjects. We studied a convenience sample of 240 low-income, predominantly Latino and black patients attending a community health center in New York. Measures. We used separate regressions of the EQ-5D Index and HUI3 onto the physical (PCS-12) and mental (MCS-12) components of the SF-12 scores as measures. Results. For the EQ-5D Index regression, the adjusted variance explained was 58% (bootstrap validation 95% confidence interval [CI], 46–66). For the HUI3 regression, the adjusted variance explained was 51% (bootstrap 95% CI, 39–59). The correlation coefficient between the 2 predicted measures was 0.96. The correlation of the predicted HUI3 with the EQ-5D Index (0.73) and the predicted EQ-5D Index with the HUI3 (0.70) exceeded that between the 2 original preference-based measures themselves (0.69). Conclusions. These pilot results suggest that the SF-12 could be successfully mapped to both the EQ-5D Index and HUI3, yielding preference-based scores that demonstrate convergent validity in a low-income, minority sample.

Factors Associated with Obesity and Coronary Heart Disease in People with Intellectual Disabilities

Advances in health care for people with intellectual disabilities (ID) that have resulted in increased longevity also force health care providers, researchers, and policymakers to question the adequacy of chronic disease management for the growing number of middle aged and elderly persons in this population. We report on sociodemographic and clinical factors associated with obesity, hypertension, hypercholesterolemia, and diabetes mellitus in an ethnically/racially diverse sample of people with ID in New York City. Administrative and chart review data were collected from a community-based specialty medical practice for people with intellectual disabilities. Adult subjects were included if they had an intellectual disability, lived in the community either independently or with relatives, received all of their planned, outpatient health care services though this practice, and had a primary care visit within the study period. One hundred twenty-six (43.0%) persons were obese, 58 (19.9%) had hypertension, 77 (26.5%) had hypercholesterolemia, and 13 (4.5%) had diabetes mellitus. Age, gender, and BMI (for the latter three conditions) were the most consistent risk factors. Intellectual functioning and behavioral problems were not associated with greater odds of these conditions. This study provides crucial information for improving community-based primary care for people with intellectual disabilities. Specifically, these findings highlight the importance of constructing innovative strategies to mitigate chronic disease risk factors in this population that involve community-based case management service providers who can help adults with ID and their families adopt needed lifestyle and behavior changes.

Obesity-related quality-adjusted life years lost in the U.S. from 1993 to 2008.

BACKGROUND Although trends in the prevalence of obesity and obesity-attributable deaths have been examined, little is known about the resultant burden of disease associated with obesity. PURPOSE This study examined trends in the burden of obesity by estimating the obesity-related quality-adjusted life years (QALYs) lost-defined as the sum of QALYs lost due to morbidity and future QALYs lost in expected life years due to premature deaths-among U.S. adults along with differences by gender, race/ethnicity, and state. METHODS Health-related quality-of-life data were taken from the 1993-2008 Behavioral Risk Factor Surveillance System to calculate QALYs lost due to morbidity. Age-specific mortality data were used to calculate QALYs lost due to mortality. RESULTS QALYs lost due to obesity in U.S. adults have more than doubled from 1993 to 2008. Black women had the most QALYs lost due to obesity, at 0.0676 per person in 2008. This number was 31% higher than the QALYs lost in black men and about 50% higher than the QALYs lost in white women and white men. A strong and positive relationship between obesity-related QALYs lost and the percentage of the population reporting no leisure-time physical activity at the state level (r=0.71) also was found. CONCLUSIONS This analysis enables the overall impact of obesity on both morbidity and mortality to be examined using a single value. The overall health burden of obesity has increased since 1993 and such increases were observed in all gender-by-race subgroups and in all 50 states and the District of Columbia.