Impact of county and state immigration policies on immigrant household enrollment in the supplemental nutrition assistance program.

Introduction: Low-income immigrants who are eligible to participate in the Supplemental Nutrition Assistance Program (SNAP) participate at lower rates compared to non-immigrants. Immigrant households may be more likely to participate in SNAP if they live in areas with policies that integrate them into society and protect them from deportation. Methods: Data on low-income immigrant households came from the 2019 American Community Survey (N = 87,678). The outcome was whether any household member received SNAP in the previous 12 months. Immigrant policy exposures came from two sources: the State Immigration Policy Resource, which includes 18 immigrant criminalizing and integrating policies, and a database that identified 'sanctuary policies' (SP), which we summarized at the county level. Multivariable logistic regression adjusted for person/household-level and area-level confounders. Results: Living in a jurisdiction with a SP was associated with 21% higher odds of enrolling in SNAP compared to living in a jurisdiction without a SP (adjusted odds ratio [aOR] 1.21, 95% CI=1.11,1.31). Relative to the least immigrant friendly states, living in the most immigrant-friendly states was associated with 16% higher odds of SNAP enrollment (aOR=1.16, 95%CI=1.06-1.28). When SP and state-level immigrant friendly policy environment were cross-classified, SNAP participation was 23% and 26% higher for those living in jurisdictions with one- and both- exposures, respectively, relative to those with neither (aOR 1.23; CI 1.12,1.36; aOR 1.26; CI 1.15,1.37). Conclusions: Many at high risk of food insecurity - including immigrants and citizens in households with immigrants - are eligible for SNAP but under-enroll. Policies that welcome and safeguard immigrants could reduce under enrollment.

Spatial scale effects on associations between built environment and cognitive function: Multi-Ethnic Study of Atherosclerosis.

Built environments have the potential to favorably support cognitive function. Despite growing work on this topic, most of the work has ignored variation in the spatial scale of the effect. The issue with spatial scale effects is that the size and shape of the areal unit within which built environment characteristics are measured naturally influence the built environment exposure metric and thus the estimated associations with health. We used spatial distributed lag modeling (DLM) to estimate how associations between built environment exposures (walkable destinations [WD], social destinations [SD]) and change in cognition varied across distance of these destinations from participants' residences. Cognition was assessed as maintained/improved processing speed (PS) and global cognition (GC). Person-level data from Exam 5 (2010-2012) and Exam 6 (2016-2018) of the Multi-Ethnic Study of Atherosclerosis was used (N = 1380, mean age 67). Built environment data were derived from the National Establishment Time Series. Higher availability of walkable and social destinations at closer distance from participants' residence was associated with maintained/improved PS. The adjusted associations between maintained/improved PS and destinations waned with increasing distance from the residence; associations were evident until approximately 1.9-km for WD and 1.5-km for SD. Associations were most apparent for participants living in areas with high population density. We found little evidence for associations between change in GC and built environment at any distance. These results highlight the importance of identifying appropriate spatial scale to understand the mechanisms for built environment-cognition associations.

Adolescent mental distress in the wake of climate disasters.

Objective: Retrospective exposure to a higher number and prolonged duration of climate-related disasters could be positively associated with adolescent mental distress. Methods: Person-level data came from 38,616 high-school students residing in 22 urban public-school districts in 14 states (U.S. Youth Risk Behavior Survey, 2019). Each district's federally declared climate-related catastrophes (severe storms, floods, wildfire, etc.) came from the Federal Emergency Management Agency. Logistic regression models estimated the adjusted odds ratios (aOR) of adolescent mental distress (MD, using survey responses feeling prolonged sadness/ hopelessness and short sleep duration) according to disaster events and days during three exposure periods (past 2-, 5-, 10-years); adjusted for age, gender, race/ethnicity, socio-economic disadvantage, feeling unsafe at school, district area size, district poverty, and region. Results: Over 10 years, the median number of disaster events was 3 and total disaster days was 64. Adolescents experiencing the highest number of disaster days (top quartile vs. less) had 25% higher odds of MD when exposed within the past 2-years (aOR 1.25 [95% CI 1.14, 1.38]), and 20% higher odds of MD when exposed within the past 5-years (aOR 1.20 95% CI 1.07, 1.35). The odds of MD were not statistically associated with exposure periods that extended to 10 years, nor disaster events (instead of disaster days, all p-values > 0.1). Conclusions: Severe weather will become more frequent and last longer with human-induced climate warming. More studies like this are needed to understand the broad range of adverse effects and enhance planning and preparedness including preparing for worsening mental health among adolescents.

Do respiratory virus infections modify associations of asthma exacerbation with aeroallergens or fine particulate matter? A time series study in Philadelphia PA.

Respiratory virus infections are related to over 80% of childhood asthma exacerbations. They enhance pro-inflammatory mediator release, especially for sensitized individuals exposed to pollens/molds. Using a time-series study design, we investigated possible effect modification by respiratory virus infections of the associations between aeroallergens/PM2.5 and asthma exacerbation rates. Outpatient, emergency department (ED), and inpatient visits for asthma exacerbation among children with asthma (28,540/24,444 [warm/cold season]), as well as viral infection counts were obtained from electronic health records of the Children's Hospital of Philadelphia from 2011 to 2016. Rate ratios (RRs, 90th percentile vs. 0) for late-season grass pollen were 1.00 (0.85-1.17), 1.04 (0.95-1.15), and 1.12 (0.96-1.32), respectively, for respiratory syncytial virus (RSV) counts within each tertile. However, similar trends were not observed for weed pollens/molds or PM2.5. Overall, our study provides little evidence supporting effect modification by respiratory viral infections.

Brief introductory guide to agent-based modeling and an illustration from urban health research / Breve guia introdutório de modelagem baseada em agentes e uma ilustração a partir da pesquisa em saúde urbana / Breve guía introductoria de modelación basada en agentes y una ilustración a partir de la investigación en salud urbana

Abstract There is growing interest among urban health researchers in addressing complex problems using conceptual and computation models from the field of complex systems. Agent-based modeling (ABM) is one computational modeling tool that has received a lot of interest. However, many researchers remain unfamiliar with developing and carrying out an ABM, hindering the understanding and application of it. This paper first presents a brief introductory guide to carrying out a simple agent-based model. Then, the method is illustrated by discussing a previously developed agent-based model, which explored inequalities in diet in the context of urban residential segregation.

Resumo Há um interesse crescente entre os pesquisadores de saúde urbana em trabalhar com problemas complexos utilizando modelos conceituais e computacionais do campo de sistemas complexos. A modelagem baseada em agentes (MBA) é uma ferramenta computacional de modelagem que tem recebido crescente interesse. No entanto, vários pesquisadores ainda não se sentem familiarizados com o desenvolvimento e a execução de uma MBA, dificultando a sua aplicação e compreensão. Este artigo primeiramente apresenta um breve guia introdutório para executar um simples modelo baseado em agentes. Em seguida, o método é ilustrado discutindo um modelo baseado em agente previamente desenvolvido, que explora as desigualdades na dieta no contexto da segregação residencial urbana.

Resumen Existe un interés creciente entre los estudiosos de la salud urbana en trabajar con problemas complejos, utilizando modelos conceptuales y computacionales del campo de sistemas complejos. La modelación basada en agentes (MBA) es una herramienta de modelación computacional que suscita cada vez más interés. Sin embargo, varios estudiosos todavía no se encuentran familiarizados con el desarrollo e implementación de un MBA, lo que dificulta su aplicación y comprensión. En este artículo se ofrece inicialmente una breve guía introductoria para llevar a cabo un simple modelo basado en agentes. De esta manera el método se ilustra discutiendo un modelo basado en agentes, desarrollado previamente, que explora las desigualdades en la dieta en un contexto de segregación residencial urbana.