Community Conditions and Cardiovascular Health: Neighborhood Socioeconomic Status and Perceptions as Predictors of Nocturnal Blood Pressure Dipping in African American Young Adults

Background: Literature has shown that the African American community disproportionately experiences certain health outcomes and poverty-stricken neighborhoods where myriad circumstances might raise their acute and chronic stress levels. Given that stress is associated with heightened cardiovascular activity, neighborhood socioeconomic status (SES) and stressful neighborhood conditions may be associated with adverse blood pressure (BP) parameters and associated negative health outcomes in African Americans. Objective: We explored the associations between neighborhood factors assessed at baseline and in daily life moments with nocturnal BP dipping in African American young adults. Methods: Healthy African American young adults (N=105) completed 2 or 4 days of hourly ambulatory BP monitoring and ecological momentary assessment surveys and a baseline survey. Neighborhood SES was assessed as the percentage of families living under the poverty threshold. Neighborhood stress and neighborhood cohesion were assessed using subscales of a neighborhood collective socialization scale (Sampson et al., 1997) and a community disorder scale (Cutrona et al., 2000). Neighborhood factors were assessed at the baseline level and, in a subsample, the momentary level. Nocturnal BP dipping was assessed as a percentage [i.e., (daytime BP - nighttime BP) / daytime BP]. Results: An interaction between neighborhood SES and community disorder was associated with less systolic BP dipping, p = .025, η2 = .06. Specifically, among those with high levels of community disorder, higher levels of neighborhood SES were more strongly associated with less dipping. Further, higher neighborhood cohesion was associated with greater diastolic BP dipping, b = .09, p = .049, η2 = .04. Results regarding momentary level neighborhood stressors will be presented. Conclusions: The absence of nocturnal BP dipping has been associated with hypertension and cardiovascular disease (CVD). Because diminished dipping was associated with neighborhood SES and community disorder while greater dipping was associated with neighborhood cohesion, we can infer that neighborhood factors may be risk factors for future CVD. Further research should investigate the compounding effects of additional characteristics of neighborhoods on cardiovascular health, such as the quality of healthcare or food insecurity

Gotcha-I: a multiview human videos dataset

The growing need of security in large open spaces led to the need to use video capture of people in different context and illumination and with multiple biometric traits as head pose, body gait, eyes, nose, mouth, and further more. All these traits are useful for a multibiometric identification or a person re-identification in a video surveillance context. Body Worn Cameras (BWCs) are used by the police of different countries all around the word and their use is growing significantly. This raises the need to develop new recognition methods that consider multibiometric traits on person re-identification. The purpose of this work is to present a new video dataset called Gotcha-I. This dataset has been obtained using more mobile cameras to adhere to the data of BWCs. The dataset includes videos from 62 subjects in indoor and outdoor environments to address both security and surveillance problem. During these videos, subjects may have a different behavior in videos such as freely, path, upstairs, avoid the camera. The dataset is composed by 493 videos including a set of 180° videos for each face of the subjects in the dataset. Furthermore, there are already processed data, such as: the 3D model of the face of each subject with all the poses of the head in pitch, yaw and roll; and the body keypoint coordinates of the gait for each video frame. It’s also shown an application of gender recognition performed on Gotcha-I, confirming the usefulness and innovativeness of the proposed dataset.2242130,16Q