Associations of Abdominal Muscle Density and Area and Incident Cardiovascular Disease, Coronary Heart Disease, and Stroke: The Multi-Ethnic Study of Atherosclerosis.

BACKGROUND: Muscle density is inversely associated with all-cause mortality, but associations with cardiovascular disease (CVD) risk are not well understood. This study evaluated the association between muscle density and muscle area and incident total CVD, coronary heart disease (CHD), and stroke in diverse men and women. METHODS AND RESULTS: Adult participants (N=1869) in the Multi-Ethnic Study of Atherosclerosis Ancillary Body Composition Study underwent computer tomography scans of the L2-L4 region of the abdomen. Muscle was quantified by density (Hounsfield units) and area in cm2. Sex-stratified Cox proportional hazard models assessed associations between incident total CVD, incident CHD, and incident stroke across sex-specific percentiles of muscle area and density, which were entered simultaneously into the model. Mean age for men and women at baseline were 64.1 and 65.1 years, respectively, and median follow-up time was 10.3 years. For men, associations between muscle density and incident CVD were inverse but not significant in fully adjusted models (P trend=0.15). However, there was an inverse association between density and CHD (P trend=0.02; HR, 0.26 for 95th versus 10th percentile), and no association with stroke (P trend=0.78). Conversely, for men, there was a strong positive association between muscle area and incident CVD (HR, 4.19 for 95th versus 10th percentile; P trend<0.001). Associations were stronger for CHD (HR, 6.18 for 95th versus 10th percentile; P trend<0.001), and null for stroke (P trend=0.67). Associations for women were mostly null. CONCLUSIONS: For men, abdominal muscle density is associated with lower CHD risk, whereas greater muscle area is associated with markedly increased risk of CHD.

Early Ascertainment of Breast Cancer Diagnoses Comparing Self-Reported Questionnaires and Electronic Health Record Data Warehouse: The WISDOM Study.

PURPOSE: The goal of this study was to use real-world data sources that may be faster and more complete than self-reported data alone, and timelier than cancer registries, to ascertain breast cancer cases in the ongoing screening trial, the WISDOM Study. METHODS: We developed a data warehouse procedural process (DWPP) to identify breast cancer cases from a subgroup of WISDOM participants (n = 11,314) who received breast-related care from a University of California Health Center in the period 2012-2021 by searching electronic health records (EHRs) in the University of California Data Warehouse (UCDW). Incident breast cancer diagnoses identified by the DWPP were compared with those identified by self-report via annual follow-up online questionnaires. RESULTS: Our study identified 172 participants with confirmed breast cancer diagnoses in the period 2016-2021 by the following sources: 129 (75%) by both self-report and DWPP, 23 (13%) by DWPP alone, and 20 (12%) by self-report only. Among those with International Classification of Diseases 10th revision cancer diagnostic codes, no diagnosis was confirmed in 18% of participants. CONCLUSION: For diagnoses that occurred ≥20 months before the January 1, 2022, UCDW data pull, WISDOM self-reported data via annual questionnaire achieved high accuracy (96%), as confirmed by the cancer registry. More rapid cancer ascertainment can be achieved by combining self-reported data with EHR data from a health system data warehouse registry, particularly to address self-reported questionnaire issues such as timing delays (ie, time lag between participant diagnoses and the submission of their self-reported questionnaire typically ranges from a month to a year) and lack of response. Although cancer registry reporting often is not as timely, it does not require verification as does the DWPP or self-report from annual questionnaires.

Psychometric Analysis of the Modified Differential Emotions Scale and the Six-Item Life Orientation Test-Revised in a Cohort of Older Women from the Women's Health Initiative.

Background: Positive affect and emotional resources, such as optimism, may play a major role in women's health and promote healthy well-being later in life. However, positive affect and optimism measures have not been psychometrically assessed in older women, despite relations to health. Therefore, the objective of this study was to psychometrically assess measures of positive affect and optimism and test their association with other measures of well-being. Methods: In a Women's Health Initiative subcohort of 58,810 women (mean age [standard deviation] 79.0 [6.1]; 89% White), positive affect and optimism were measured using the modified Differential Emotions Scale (mDES) and Life Orientation Test-Revised (LOT-R), respectively. Reliability was tested using Cronbach's alpha and McDonald's omega. Performance was assessed using item response theory. Factor analysis was used to explore the construct validity of the LOT-R. Convergent and divergent validity with other well-being measures was tested. Results: Results suggest good reliability (mDES: Cronbach's alpha = 0.90 and omega total = 0.92; LOT-R: Cronbach's alpha = 0.79, omega hierarchical = 0.61, and omega total = 0.83). Item response analyses indicate mDES's ability to discriminate across positive affect; LOT-R was skewed toward lower optimism levels. Exploratory factor analyses suggest a two-factor solution for the LOT-R. Significant, but small correlations in expected directions to well-being measures confirmed validity hypotheses. Conclusions: The mDES and LOT-R measured positive affect and optimism with good reliability, item performance, and validity in a large sample of older postmenopausal women, supporting use of these measures to quantify effects of positive affect and optimism-promoting interventions.