Active school transport and fast food intake: are there racial and ethnic differences?

Objectives To investigate whether active school transport was associated with fast food consumption, and to examine differences across racial/ethnic groups. Methods Adolescent data (n = 3194) from the 2009 California Health Interview Survey were analyzed with logistic regression models to examine the association between active school transport (AST) and fast food intake across racial/ethnic groups. Results In the overall sample, AST during 1–2 days in the past week was associated with greater likelihood of fast food intake (OR: 1.58; 95% CI: 1.03–2.43), compared with zero days of AST, controlling for demographic and other factors. The association between AST and fast food intake differed significantly by race/ethnicity (p < 0.01). Among Latino adolescents, greater frequency of AST was significantly associated with greater likelihood of fast food intake (1–2 days OR, 2.37, 95%CI: 1.05–5.35; 3–4 days OR, 2.78, 95% CI: 1.04–7.43; 5 days OR, 2.20, 95%CI: 1.23–3.93). Among White and Asian adolescents, there was a curvilinear pattern: relative to adolescents who reported zero days of AST, those who did AST 1–2 days/week had greater likelihood of fast food intake, but AST of 3–4 days and 5 days/week was associated respectively, with higher and lower likelihood of fast food intake among both groups. Conclusions AST appears to be a risk factor for fast food intake, and may expose some ethnic groups more than others to increased opportunity to purchase and consume fast food. Programs and policies to promote AST among adolescents should incorporate efforts to encourage healthy eating and discourage concentration of fast food outlets near schools

Computationally accelerating protein-ligand docking for neglected tropical diseases : a case study on drug repurposing for Leishmaniasis

While computational Deep Learning methods substantially reduce the screening burden for molecular docking, they can not be reliably trusted to find the top ligands binding to a given target. This suggests that current Deep Learning methods can be used to come up with a short list of most promising ligands (and drug candidates) but the final predictions should rely on molecular docking. The study proposes a method blending representation learning and molecular docking to predict protein ligand interaction, a key building block of drug repurposing and discovery, using Leishmaniasis as a case study. Molecular docking is a computational procedure that attempts to predict non-covalent binding of macromolecules.Swedish International Development Cooperation Agency (SIDA)Knowledge 4 All Foundation (K4A)International Research Centre on Artificial Intelligence under the auspices of UNESC

Separate and unequal: The influence of neighborhood and school characteristics on spatial proximity between fast food and schools

Objective. Social science and health literature have identified residential segregation as a critical factor in exposure to health-related resources, including food environments. Differential spatial patterning of food environments surrounding schools has significant import for youth. We examined whether fast food restaurants clustered around schools in New York City, and whether any observed clustering varied as a function of school type, school racial demographics, and area racial and socioeconomic demographics. Results. A minimum of 25% of schools had a fast food restaurant within 400 m. High schools had higher fast food clustering than elementary schools. Public elementary and high schools with large proportions of Black students or in block groups with large proportions of Black residents had higher clustering than White counterparts. Finally, public high schools had higher clustering than private counterparts, with 1.25 to 2 times as many restaurants than expected by chance. Conclusion. The results suggest that the geography of opportunity as it relates to school food environments is unequal in New York City

Computationally accelerating protein-ligand matching for neglected tropical disease : a case in Leishmaniasis

The presentation provides the structure for the study and statistical analysis of the results. The aim was to apply drug repurposing with computational methods towards finding medications to cure Leishmaniasis. The analysis includes correlations between Deep Learning and molecular locking tools. Deep learning is a subset of machine learning in artificial intelligence that has networks capable of learning, unsupervised from data that is unstructured or unlabeled. (Also known as deep neural learning or deep neural network)

Advancing Research on Racial–Ethnic Health Disparities: Improving Measurement Equivalence in Studies with Diverse Samples

To conduct meaningful, epidemiologic research on racial–ethnic health disparities, racial–ethnic samples must be rendered equivalent on other social status and contextual variables via statistical controls of those extraneous factors. The racial–ethnic groups must also be equally familiar with and have similar responses to the methods and measures used to collect health data, must have equal opportunity to participate in the research, and must be equally representative of their respective populations. In the absence of such measurement equivalence, studies of racial–ethnic health disparities are confounded by a plethora of unmeasured, uncontrolled correlates of race–ethnicity. Those correlates render the samples, methods, and measures incomparable across racial–ethnic groups, and diminish the ability to attribute health differences discovered to race–ethnicity vs. to its correlates. This paper reviews the non-equivalent yet normative samples, methodologies and measures used in epidemiologic studies of racial–ethnic health disparities, and provides concrete suggestions for improving sample, method, and scalar measurement equivalence

Measurement methodologies for reducing errors in the assessment of EMF by exposimeter

Objective: As well known, using a single body worn sensor exposimeter introduces systematic errors on the measurement of the incident free space electric field strength. This is because the body creates around it high, intermediate and low level field zones, which depend on the direction of arrival of the incident field. The goal of this work is to propose an efficient method for the reduction of these errors. Methods: After classifying the perturbations induced by the body on the measured electric and magnetic fields thanks to realistic numerical simulations, we then propose a two-sensor setup in conjunction with simple semi-empirical correction formulas, in order to compensate these perturbations. Results: At 942 MHz, when the two sensors are placed in any opposite sides of the body at chest height, the worst case, maximum and average errors respectively decrease to 12% and 3% compared to 83% and 22% for measurement techniques using a single sensor, or 32% and 11% when using the average value of the measurements. Conclusion: The error related to the measurement in the presence of the body was significantly reduced by the proposed method making use of two opposite sensors, E-field and H-field at the chest. Significance: The conformity of exposure to EMF in terms of reference values according to the ICNIRP is given in the abscence of the human body. The interest of this work lies in the reduction of the errors made when measuring the field in the presence of the body

Havens of Risks or Resources? A Study of Two Latino Neighborhoods in New York City

Research has been mixed on the potential risks and resources that ethnic enclaves may confer upon residents: whereas some authors characterize racial and ethnic minority neighborhoods through the lens of segregation and risk, others argue that these minority neighborhoods are ethnic enclaves that can improve the availability of resources to residents. In this study, we sought to assess two predominantly Latino New York City neighborhoods (one enclave neighborhood and one comparison) in the areas of structural resources (e.g., grocers, parks), cultural resources (e.g., botanicas, hair salons), and risks (e.g., empty lots, bars) by street-level coding in 20 census tracts (streets N = 202). We used Poisson generalized linear models to assess whether enclave status of a neighborhood predicted the numbers of risks and resources on streets within those neighborhoods. Enclave status did not predict the number of risks (Rate ratio = 1.08(0.83, 1.42), χ (2)(1, N = 202) = 0.35, p = n. s.) or cultural resources (Rate ratio = 0.87(0.54, 1.40), χ (2)(1, N = 202) = 0.34, p = n. s.), yet it was associated with a higher number of structural resources (Rate ratio = 1.90(1.48, 2.43), χ (2)(1, N = 202) = 25.74, p < 0.001). The results suggest that while living in an ethnic enclave may not reduce risks, it may help residents cope with those risks through an increased number of structural resources. These findings support theories that conceptualize ethnic enclaves as neighborhoods where greater resources are available to residents. The focus on resources within this work was instrumental, as no difference would have been found if a solely risk-focused approach had been employed.VoRSUNY DownstateSTAR ProgramN/

A Framework for Examining Social Stress and Susceptibility to Air Pollution in Respiratory Health

Objective: There is growing interest in disentangling the health effects of spatially clustered social and physical environmental exposures and in exploring potential synergies among them, with particular attention directed to the combined effects of psychosocial stress and air pollution. Both exposures may be elevated in lower-income urban communities, and it has been hypothesized that stress, which can influence immune function and susceptibility, may potentiate the effects of air pollution in respiratory disease onset and exacerbation. In this paper, we attempt to synthesize the relevant research from social and environmental epidemiology, toxicology, immunology, and exposure assessment to provide a useful framework for environmental health researchers aiming to investigate the health effects of environmental pollution in combination with social or psychological factors. Data synthesis: We review the existing epidemiologic and toxicologic evidence on synergistic effects of stress and pollution, and then describe the physiologic effects of stress and key issues related to measuring and evaluating stress as it relates to physical environmental exposures and susceptibility. Finally, we identify some of the major methodologic challenges ahead as we work toward disentangling the health effects of clustered social and physical exposures and accurately describing the interplay among these exposures. Conclusions: There is still tremendous work to be done toward understanding the combined and potentially synergistic health effects of stress and pollution. As this research proceeds, we recommend careful attention to the relative temporalities of stress and pollution exposures, to nonlinearities in their independent and combined effects, to physiologic pathways not elucidated by epidemiologic methods, and to the relative spatial distributions of social and physical exposures at multiple geographic scales

The Geography of Fast Food Outlets: A Review

The availability of food high in fat, salt and sugar through Fast Food (FF) or takeaway outlets, is implicated in the causal pathway for the obesity epidemic. This review aims to summarise this body of research and highlight areas for future work. Thirty three studies were found that had assessed the geography of these outlets. Fourteen studies showed a positive association between availability of FF outlets and increasing deprivation. Another 13 studies also included overweight or obesity data and showed conflicting results between obesity/overweight and FF outlet availability. There is some evidence that FF availability is associated with lower fruit and vegetable intake. There is potential for land use policies to have an influence on the location of new FF outlets. Further research should incorporate good quality data on FF consumption, weight and physical activity