Identifying an acceptable number of ambulatory blood pressure measurements for accuracy of average blood pressure and nocturnal dipping status.

We aimed to identify the minimum number of ambulatory blood pressure (ABP) measures to accurately determine daytime and nighttime systolic blood pressure (BP) averages and nocturnal dipping status (i.e., relative daytime:nighttime change). A total of 43 midlife participants wore an ABP monitor for 24 h with measurements every 20/30 min during the daytime/nighttime, as identified by a sleep diary. We calculated daytime/nighttime systolic BP average and dipping status from all available measurements per participant (i.e., normative data). We then calculated daytime and nighttime BP per participant based on a random selection of 8-20 and 4-10 measurements and replicated random selections 1,000 times. We calculated accuracy by checking the proportion from 1,000 different randomly selected samples for a particular number of measurements that systolic BP was ±5 mmHg of normative data, and dipping status remained unchanged for each participant compared with the normative value. The best fit for the regression model estimated the minimal number of measurements for an accuracy of 95% in BP averages. For a 95% accuracy in estimating daytime and nighttime systolic BP, 11 daytime and 8 nighttime measurements were required. The highest accuracy for dipping status was 91.6 ± 13.4% using 20 daytime and 10 nighttime measures, while the lowest was (83.4 ± 15.1%) using 8 daytime and 4 nighttime measures. In midlife adults, 11 daytime and 8 nighttime measurements are likely enough to calculate average systolic BPs accurately. However, no minimum number is suggested to accurately calculate dipping status.NEW & NOTEWORTHY We found that a minimum of 11 blood pressure (BP) measures are necessary to calculate an accurate average daytime BP, and 8 nighttime measures are necessary to calculate an accurate nighttime average if 95% accuracy is acceptable. Regarding BP dipping status, the current recommendations (20 daytime/7 nighttime) inaccurately classified the dipping status 10.5% of the time, suggesting that guidelines may need to be updated to classify patients as nocturnal dippers or nondippers correctly.

Belonging, endurance, and resistance: Black placemaking theory in primary care.

Black-Americans continue to experience pervasive health disparities. Factors contributing to increased disease risk include a general mistrust of biomedical institutions among Black Americans. The purpose of this focus group study was to identify, among Black patients who regularly seek care from a primary provider, salient themes regarding barriers to 1) receiving quality primary care; and 2) adhering to medical recommendations. We examined transcripts of eight focus groups held remotely with 29 Black patients (aged 30-60 years) who had established primary care providers. Using grounded theory and an inductive thematic analysis of the transcripts, we identified three themes (belonging, endurance, and resistance) consistent with Black placemaking theory. Our findings suggest that reducing health disparities for Black Americans will require clinical initiatives that emphasize: 1) attention to social influences on health behavior and to features of medical institutions that mark them as White spaces (belonging); 2) recognition of, as well as sensitivity to, community awareness of the systemic and interpersonal barriers to health and safety that many Black adults endure; and 3) reframing avoidant (resistant) behaviors as protective strategies among Black patients. Examining primary care in this way-through the lens of Black placemaking theory-reveals how culturally meaningful approaches to harnessing the specialized knowledge and resilience that clearly exists among many Black communities can improve health care delivery.

Cardiovascular disease risk: it is complicated, but race and ethnicity are key, a Bayesian network analysis.

Background: Cardiovascular diseases are the leading cause of morbidity and mortality in the United States. Despite the complexity of cardiovascular disease etiology, we do not fully comprehend the interactions between non-modifiable factors (e.g., age, sex, and race) and modifiable risk factors (e.g., health behaviors and occupational exposures). Objective: We examined proximal and distal drivers of cardiovascular disease and elucidated the interactions between modifiable and non-modifiable risk factors. Methods: We used a machine learning approach on four cohorts (2005-2012) of the National Health and Nutrition Examination Survey data to examine the effects of risk factors on cardiovascular risk quantified by the Framingham Risk Score (FRS) and the Pooled Cohort Equations (PCE). We estimated a network of risk factors, computed their strength centrality, closeness, and betweenness centrality, and computed a Bayesian network embodied in a directed acyclic graph. Results: In addition to traditional factors such as body mass index and physical activity, race and ethnicity and exposure to heavy metals are the most adjacent drivers of PCE. In addition to the factors directly affecting PCE, sleep complaints had an immediate adverse effect on FRS. Exposure to heavy metals is the link between race and ethnicity and FRS. Conclusion: Heavy metal exposures and race/ethnicity have similar proximal effects on cardiovascular disease risk as traditional clinical and lifestyle risk factors, such as physical activity and body mass. Our findings support the inclusion of diverse racial and ethnic groups in all cardiovascular research and the consideration of the social environment in clinical decision-making.