Although violent crime has declined in recent decades, it remains a recurring feature of daily life in some neighborhoods. Mounting evidence indicates that such violence has a long reach, which goes beyond family and friends of the victim and undermines the health of people in the surrounding community. However, like all forms of adversity, community violence elicits a heterogeneous response: Some remain healthy, but others deteriorate. Despite much scientific attention, the neural circuitries that contribute to differential adaptation remain poorly understood. Drawing on knowledge of the brain's intrinsic functional architecture, we predicted that individual differences in resting-state connectivity would explain variability in the strength of the association between neighborhood violence and cardiometabolic health. We enrolled 218 urban youth (age 12-14 years, 66% female; 65% black or Latino) and used geocoding to characterize their exposure to neighborhood murder over the past five years. Multiple aspects of cardiometabolic health were assessed, including obesity, insulin resistance, and metabolic syndrome. Functional MRI was used to quantify the connectivity of major intrinsic networks. Consistent with predictions, resting-state connectivity within the central executive network (CEN) emerged as a moderator of adaptation. Across six distinct outcomes, a higher neighborhood murder rate was associated with greater cardiometabolic risk, but this relationship was apparent only among youth who displayed lower CEN resting-state connectivity. By contrast, there was little evidence of moderation by the anterior salience and default mode networks. These findings advance basic and applied knowledge about adaptation by highlighting intrinsic CEN connectivity as a potential neurobiological contributor to resilience. resilience | stress | children | neuroscience | cardiovascular
Background: Nutritional status influences immunity but its specific association with susceptibility to COVID-19 remains unclear. We examined the association of specific dietary data and incident COVID-19 in the UK Biobank (UKB). Methods: We considered UKB participants in England with self-reported baseline (2006–2010) data and linked them to Public Health England COVID-19 test results—performed on samples from combined nose/throat swabs, using real time polymerase chain reaction (RT-PCR)—between March and November 2020. Baseline diet factors included breastfed as baby and specific consumption of coffee, tea, oily fish, processed meat, red meat, fruit, and vegetables. Individual COVID-19 exposure was estimated using the UK’s average monthly positive case rate per specific geo-populations. Logistic regression estimated the odds of COVID-19 positivity by diet status adjusting for baseline socio-demographic factors, medical history, and other lifestyle factors. Another model was further adjusted for COVID-19 exposure. Results: Eligible UKB participants (n = 37,988) were 40 to 70 years of age at baseline; 17% tested positive for COVID-19 by SAR-CoV-2 PCR. After multivariable adjustment, the odds (95% CI) of COVID-19 positivity was 0.90 (0.83, 0.96) when consuming 2–3 cups of coffee/day (vs. <1 cup/day), 0.88 (0.80, 0.98) when consuming vegetables in the third quartile of servings/day (vs. lowest quartile), 1.14 (1.01, 1.29) when consuming fourth quartile servings of processed meats (vs. lowest quartile), and 0.91 (0.85, 0.98) when having been breastfed (vs. not breastfed). Associations were attenuated when further adjusted for COVID-19 exposure, but patterns of associations remained. Conclusions: In the UK Biobank, consumption of coffee, vegetables, and being breastfed as a baby were favorably associated with incident COVID-19; intake of processed meat was adversely associated. Although these findings warrant independent confirmation, adherence to certain dietary behaviors may be an additional tool to existing COVID-19 protection guidelines to limit the spread of this virus.
IntroductionThis study analyzes changes in hospital emergency department (ED) visit rates before and after the 2014 Affordable Care Act (ACA) insurance expansions in Illinois. We compare the association between population insurance status change and ED visit rate change between a 24-month (2012–2013) pre-ACA period and a 24-month post-ACA (2014–2015) period across 88 socioeconomically diverse areas of Illinois.MethodsWe used annual American Community Survey estimates for 2012–2015 to obtain insurance status changes for uninsured, private, Medicaid, and Medicare (disability) populations of 88 Illinois Public Use Micro Areas (PUMAs), areas with a mean of about 90,000 age 18–64 residents. Over 12 million ED visits to 201 non-federal Illinois hospitals were used to calculate visit rates by residents of each PUMA, using population-based mapping weights to allocate visits from zip codes to PUMAs. We then estimated n=88 correlations between population insurance-status changes and changes in ED visit rates per 1,000 residents comparing the two years before and after ACA implementation.ResultsThe baseline PUMA uninsurance rate ranged from 6.7% to 41.1% and there was 4.6-fold variation in baseline PUMA ED visit rates. The top quartile of PUMAs had >21,000 reductions in uninsured residents; 16 PUMAs had at least a 15,000 person increase in Medicaid enrollment. Compared to 2012–2013, 2014–2015 average monthly ED visits by the uninsured dropped 42%, but increased 42% for Medicaid and 10% for the privately insured. Areas with the largest increases in Medicaid enrollment experienced the largest growth in ED use; change in Medicaid enrollment was the only significant correlate of area change in total ED visits and explained a third of variation across the 88 PUMAs.ConclusionACA implementation in Illinois accelerated existing trends towards greater use of hospital ED care. It remains to be seen whether providing better access to primary and preventive care to the formerly uninsured will reduce ED use over time, or whether ACA insurance expansion is a part of continued, long-term growth. Monitoring ED use at the local level is critical to the success of new home- and community-based care coordination initiatives.
INTRODUCTION-Contextual factors representing chronic stressors, such as neighborhood crime characteristics, have been repeatedly linked to compromised mental and physical health, and may contribute to the pathologizing of normative/non-clinical experiences. However, the impact of such structural factors has seldom been incorporated in Clinical High Risk (CHR) for psychosis research. Understanding how context can influence the presence or severity of symptoms such as suspiciousness/paranoia may have important relevance for promoting valid and reliable assessment, as well as for understanding ways in which environment may be related to illness development and expression. METHODS-A total of 126 adolescents and young adults (n CHR = 63, n control = 63) underwent clinical interviews for Clinical High-Risk syndromes. Neighborhood crime indices and socioeconomic status were calculated through geocoding and extracting of publicly available Census and Federal Bureau of Investigation (FBI) data. Analyses examined presence of
Objective To better understand approaches to reducing mortality from the opioid epidemic, we analyzed in-hospital versus community opioid-related overdose deaths in Illinois. Methods We used data from the Statewide Unintentional Drug Overdose Reporting System (July 2017 through December 2018) to identify deaths that occurred in hospitals and communities (ie, homes or public spaces). We used census tract–level data for 34 Illinois counties to create bivariate mapping by overdose death rates. We used logistic regression to analyze the association of demographic and overdose characteristics with the likelihood of death in a hospital versus a community. Results During the study period, 2833 opioid-related overdose deaths occurred in 24 Illinois counties, 655 (23.1%) of which occurred in the hospital; of 2178 community deaths, 1888 (86.7%) occurred in the same census tract as the decedent’s recorded residence and 1285 (59.0%) occurred in the decedent’s home. Non-Hispanic Black people were 1.63 (95% CI, 1.27-2.10) times more likely than non-Hispanic White people to die in a hospital. Decedents from suburban Cook County and other Chicago suburban counties were significantly more likely to die in the hospital than decedents from Chicago or other Illinois counties. Documentation of a previous overdose, history of opioid use, and having bystanders present were significantly associated with hospital deaths. Evidence of a rapid overdose, fentanyl present, or prescription opioids were significantly associated with deaths in a community. Conclusions The high number of opioid-related overdose deaths in the community illustrates the need to decriminalize illicit drug use and facilitate treatment seeking. Establishing supervised safe consumption sites may have the biggest effect in reducing the number of opioid-related overdose deaths.
Background: Based on our recently reported associations between specific dietary behaviors and the risk of COVID-19 infection in the UK Biobank (UKB) cohort, we further investigate whether these associations are specific to COVID-19 or extend to other respiratory infections. Methods: Pneumonia and influenza diagnoses were retrieved from hospital and death record data linked to the UKB. Baseline, self-reported (2006–2010) dietary behaviors included being breastfed as a baby and intakes of coffee, tea, oily fish, processed meat, red meat (unprocessed), fruit, and vegetables. Logistic regression estimated the odds of pneumonia/influenza from baseline to 31 December 2019 with each dietary component, adjusting for baseline socio-demographic factors, medical history, and other lifestyle behaviors. We considered effect modification by sex and genetic factors related to pneumonia, COVID-19, and caffeine metabolism. Results: Of 470,853 UKB participants, 4.0% had pneumonia and 0.2% had influenza during follow up. Increased consumption of coffee, tea, oily fish, and fruit at baseline were significantly and independently associated with a lower risk of future pneumonia events. Increased consumption of red meat was associated with a significantly higher risk. After multivariable adjustment, the odds of pneumonia (p ≤ 0.001 for all) were lower by 6–9% when consuming 1–3 cups of coffee/day (vs. <1 cup/day), 8–11% when consuming 1+ cups of tea/day (vs. <1 cup/day), 10–12% when consuming oily fish in higher quartiles (vs. the lowest quartile—Q1), and 9–14% when consuming fruit in higher quartiles (vs. Q1); it was 9% higher when consuming red meat in the fourth quartile (vs. Q1). Similar patterns of associations were observed for influenza but only associations with tea and oily fish met statistical significance. The association between fruit and pneumonia risk was stronger in women than in men (p = 0.001 for interaction). Conclusions: In the UKB, consumption of coffee, tea, oily fish, and fruit were favorably associated with incident pneumonia/influenza and red meat was adversely associated. Findings for coffee parallel those we reported previously for COVID-19 infection, while other findings are specific to these more common respiratory infections.
Objectives. To examine gun violence with respect to hospital visits for treatment of intentional assault gunshot wounds (IGWs). Methods. IGW-coded visits among residents of Cook County, Illinois, were matched to census zip code tabulation areas (ZCTAs) to map changes in IGW visit frequencies between 2018 and 2020. Patient characteristics were compared across years, and Poisson regression models for the likelihood of an inpatient admission or in-hospital death were estimated. Results. Over the study period, Cook County residents made 7122 IGW-coded hospital visits to 89 Illinois hospitals, resulting in $342 million in charges and 24 894 hospital days. The number of visits almost doubled between 2018 and 2020, from 1553 to 3031; 6 ZCTAs had increases of more than 60 visits. Approximately one third of patients with a visit were admitted, and 6.5% died. Conclusions. Hospital statistics do not include the full toll of nonfatal gun injuries or the costs of related community-level trauma. The health care system remains crucial in implementing epidemiological approaches to violence prevention. Addressing the national spike in shootings will require large investments in community economic development and a professional public safety workforce. (Am J Public Health. Published online ahead of print March 24, 2022: e1–e8. https://doi.org/10.2105/AJPH.2022.306747 )
Objectives: This study was designed to evaluate a patient navigation program undertaken with our community partners in Chicago’s Chinatown. Inadvertently, the study collected data on two biannual mammography screening cycles that coincided almost exactly with implementation of the Affordable Care Act (ACA) in Illinois. Methods: The study uses claims data to profile mammography screening rates for residents of an 18 zip code, 398 census tract area on Chicago’s near south and southwest side. Patient addresses were geocoded from biannual (August 2011 to July 2103 and August 2103 to July 2015) Illinois Medicaid and Illinois Breast and Cervical Cancer Program (IBCCP) claims. Screening rates are presented separately for low-income women ages 40 to 49 and 50 to 64 years. We compare change between 16 tracts with greater than 20% Chinese ancestry, 85 tracts with 1% to 20% Chinese ancestry, and 297 tracts with less than 1% Chinese ancestry. Results: There were more than 65,000 low-income women age 40 to 64 in the study area (mammogram patients were 63% Black, 23% Hispanic, 10% White, 2.5% Asian, and 2.5% other/unknown race and ethnicity). The increase in screening was greatest in Chinatown, although mean rates were not significantly different across the three areas (p = .07). Discussion: Our results demonstrate large increases in mammography screening after ACA implementation in 2013–2014. The greatest increase occurred in the Chinatown patient navigation program area. The study provides a template for programs aimed at using public community-area data to evaluate programs for improving access to care and health equity.
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