Testing the Duke Population Health Profile (Duke-PH) in a Sample of Community Health Center Patients.

Introduction: Our purpose was to develop and test a brief, self-report, and scorable survey instrument for measuring population health profiles from the individual respondent's perspective. We defined population health as the state of physical, mental, and social well-being of a group of individuals, including determinants of their well-being. Materials and Methods: Respondents were adult patients in a community health center. Instrument items, an overall scale, and two subscales were developed and evaluated. Reliability was tested by Cronbach's alphas and test-retest correlations; construct validity was tested by correlations between scores and economic and clinical factors; criterion validity was tested by regression analyses for prediction of morbidity and health care utilization by baseline scores; and feasibility was tested by length of administration time. Results: This was a 2-years prospective study of 450 patients, mostly black non-Hispanics (54%) and Hispanics (29%), many with no health insurance (45%), and poor enough to meet the federal poverty level (73%). The Duke Population Health Profile (Duke-PH) was developed with a 14-item PH scale for overall population health profile and two 7-item subscales, one for social determinants and the other for health determinants. Validity of item selection was indicated by item convergent and item discriminant correlations. Scale and subscale reliability were supported for internal consistency by Cronbach's alphas of 0.63-0.73, and for temporal stability by test-retest correlations of 0.65-0.78. Support for construct validity was shown by the more favorable baseline subscale and scale mean scores for patients able to buy private insurance than for patients unable to afford it. Criterion validity was supported by regression analyses showing that baseline scale and subscale scores predicted both baseline morbidity and 6-months utilization. Feasibility was shown by the mean self-administration time of 3.9 min and mean interviewer-administration time of 5.8 min. Discussion: The strength of this study is support for Duke-PH reliability, validity, and feasibility in a community health center patient population. The new instrument is unique because it measures both social and health determinants of population health from the perspective of individuals in the population.

Does binge eating disorder impact weight-related quality of life?

OBJECTIVES: To determine whether binge eating disorder (BED) impacts weight-related quality of life in obese individuals seeking weight loss treatment and to investigate the role of psychological symptoms, BMI, and demographic variables in the relationship between BED and weight-related quality of life. RESEARCH METHODS AND PROCEDURES: Three hundred seventeen women (BMI = 37.6) and 213 men (BMI = 41.3) completed questionnaires on admission into an intensive residential lifestyle modification program. Weight-related quality of life was assessed using the Impact of Weight on Quality of Life-Lite (IWQOL-Lite). The presence of BED was determined using the Questionnaire on Eating and Weight Patterns-Revised. Psychological symptoms were assessed using the Beck Depression Inventory and the global severity index of the Symptom Checklist 90-R. RESULTS: BED prevalence in this sample was 17.9%. Participants with BED, in comparison with those without BED, were more likely to be women (75.8% vs. 56.3%, p < 0.001), younger (45.0 vs. 49.7 years, p = 0.003), white (98.9% vs. 91.7%), heavier (BMI = 42.0 vs. 38.5, p = 0.002), psychologically distressed, and more impaired on total IWQOL-Lite (51.5 vs. 65.3, p < 0.001) and all IWQOL-Lite subscales. However, after controlling for demographic variables, BMI, and psychological symptoms, BED was not independently associated with weight-related quality of life. DISCUSSION: The association between BED and impairment in quality of life that has been previously reported in the literature may largely be accounted for by differences between those with and without BED on demographic variables, BMI, and psychological symptoms. BED does not seem to independently impact weight-related quality of life.