Very little information exists on racial differences in quality of life among older adults. In this paper, we examine black-white differences in health-related quality of life (HRQOL) and identify factors that may account for these differences. The participants were 5,986 community-dwelling persons age 65+ (62% black at baseline) from the Chicago Health and Aging Project. Poor HRQOL was defined as having 14 or more self-reported physically or mentally unhealthy days over the past 30 days. A higher proportion of blacks (11.0%) than whites (9.7%) reported poor HRQOL. After adjusting for age and sex, blacks had increased odds of reporting poor HRQOL compared with whites (odds ratio [OR] = 1.72; 95% CI: 1.50-1.98). The black-white differences in HRQOL tended to increase with age (p < 0.05) and were greater among females (p < 0.05). Lifetime socioeconomic status, summary measures of medical conditions, and cognitive function accounted for most of the black-white difference (OR = 1.06; 95% CI: 0.89-1.27). Our results suggest that racial differences in HRQOL are associated with the combined effects of social disadvantage, poor physical health, and lower cognitive function.
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http://dx.doi.org/10.1007/s11136-006-9115-y | DOI Listing |
Objective: To identify and characterize how race and ethnicity influence the relationship between autism and weight status, across all categories of weight from underweight to severe obesity.
Study Design: We developed a propensity score-matched cross-sectional dataset of children with and without parent-reported autism in the National Survey of Children Health (NSCH, 2016-2022) and Adolescent Brain and Cognition Development Study (ABCD, 2016-2018). We included non-Hispanic Asian, non-Hispanic Black, non-Hispanic White, and Hispanic children aged 6 to 17 years.
Sensors (Basel)
January 2025
Sensor Science Division, National Institute of Standards and Technology, Gaithersburg, MD 20878, USA.
Terrestrial laser scanners (TLS) are portable dimensional measurement instruments used to obtain 3D point clouds of objects in a scene. While TLSs do not require the use of cooperative targets, they are sometimes placed in a scene to fuse or compare data from different instruments or data from the same instrument but from different positions. A contrast target is an example of such a target; it consists of alternating black/white squares that can be printed using a laser printer.
View Article and Find Full Text PDFCancers (Basel)
January 2025
Program in Public Health, Stony Brook Medicine, Stony Brook, NY 11794, USA.
Introduction: Colorectal cancer (CRC) is the third most commonly diagnosed cancer in the United States (U.S.).
View Article and Find Full Text PDFFoods
January 2025
Shandong Key Laboratory of Healthy Food Resources Exploration and Creation, School of Food Sciences and Engineering, Qilu University of Technology, Shandong Academy of Sciences, Daxue Road, Changqing District, Jinan 250353, China.
Herein, -glucan (BG) was extracted from different colored varieties of highland barley (HB, ), defined as BBG, WBG, and LBG depending on the colors of black, white, and blue and their molecular structure and physicochemical properties were investigated through a series of technical methods. The high-performance anion-exchange chromatography (HPAEC) results indicated the extracted BBG, LBG, and WBG mainly comprised glucose regardless of color. The molecular weight (M) of BBG, LBG, and WBG were 55.
View Article and Find Full Text PDFSoc Sci Med
January 2025
University of California - Berkeley, School of Public Health, Division of Epidemiology, United States; University of California - Berkeley, School of Public Health, Division of Biostatistics, United States.
Structural racism is a fundamental cause of racial health inequities; however, it is a complex construct that is difficult to quantitatively analyze due to its multi-dimensionality. We classified fifty US states into three typologies of structural racism using a latent profile analysis. Five domains of structural racism were included in the analysis: Black-White inequities in educational attainment, employment, homeownership, incarceration, and income.
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