@article {7263, title = {Measurement differences in depression: chronic health-related and sociodemographic effects in older Americans.}, journal = {Psychosom Med}, volume = {70}, year = {2008}, month = {2008 Nov}, pages = {993-1004}, publisher = {70}, abstract = {

OBJECTIVE: To evaluate the influence of five chronic health conditions (high blood pressure, heart conditions, stroke, diabetes, and lung diseases) and four sociodemographic characteristics (age, gender, education, and race/ethnicity) on the endorsement patterns of depressive symptoms in a sample of community-dwelling older adults.

METHOD: Participants were adults aged >or=65 years from the 2004 Health and Retirement Study (n = 9448). Depressive symptoms were measured with a nine-item Center for Epidemiologic Studies-Depression scale. Measurement differences attributable to health and sociodemographic factors were assessed with a multidimensional model based on item response theory.

RESULTS: Evidence for unidimensionality was equivocal. We used a bifactor model to express symptom endorsement patterns as resulting from a general factor and three specific factors ("dysphoria," "psychosomatic," and "lack of positive affect"). Even after controlling for the effects of health on the psychosomatic factor, heart conditions, stroke, diabetes, and lung diseases had significant positive effects on the general factor. Significant effects due to gender and educational levels were observed on the "lack of positive affect" factor. Older adults self-identifying as Latinos had higher levels of general depression. On the symptom level, meaningful measurement noninvariance due to race/ethnic differences were found in the following five items: depressed, effort, energy, happy, and enjoy life.

CONCLUSIONS: The increased tendency to endorse depressive symptoms among persons with specific health conditions is, in part, explained by specific associations among symptoms belonging to the psychosomatic domain. Differences attributable to the effects of health conditions may reflect distinct phenomenological features of depression. The bifactor model serves as a vehicle for testing such hypotheses.

}, keywords = {Aged, Aged, 80 and over, Chronic disease, Cohort Studies, Comorbidity, Confounding Factors, Epidemiologic, Culture, depression, Diabetes Mellitus, Educational Status, ethnicity, Factor Analysis, Statistical, Female, Heart Diseases, Humans, Hypertension, Interviews as Topic, Lung Diseases, Male, Self-Assessment, Sex Factors, Stroke, United States}, issn = {1534-7796}, doi = {10.1097/PSY.0b013e31818ce4fa}, author = {Frances Margaret Yang and Richard N Jones} }