Work-related factors of mental health among Chicago residents two years into the COVID-19 pandemic.

The COVID-19 pandemic led to widespread consequences for economic, social, and general wellbeing with rates of anxiety and depression increasing across the population and disproportionately for some workers. This study explored which factors were the most salient contributors to mental health through a cross-sectional 68-item questionnaire that addressed topics related to the pandemic. Data were collected through an address-based sampling frame over the two months from April 2022 to June 2022.

The Relation of Neighborhood Racial and Income Polarity to Preterm Birth Rates in Chicago.

Objectives: To investigate the extent to which spatial social polarization is associated with preterm birth among urban African-American and non-Latinx white women, and whether prenatal care modifies this relationship.

Methods: We performed multilevel logistic regression analyses on a 2013-2017 dataset of Chicago vital records (N = 29,179) with appended Index of Concentration at the Extremes (ICE) values for race and income.

Results: Women who resided in the bottom ICE quintile neighborhoods had a preterm birth rate of 11.

Transitioning the Healthy Chicago Survey From a Telephone Mode to Self-administered by Mail Mode.

Context: As response rates to health surveys conducted by telephone continue to decline and costs continue to increase, practitioners are increasingly considering a transition to self-administered mail contact modes.

Objective: To compare empirical differences observed across adjacent administrations of the Healthy Chicago Survey (HCS) conducted by telephone versus self-administered via mail contact.

Design: Data from the 2016, 2018, and 2020 administrations of the HCS are contrasted, and demographic distributions are benchmarked against the American Community Survey to investigate differences that may be linked to the HCS' transition from a telephone to self-administered mail mode between 2018 and 2020.

Validation of a Machine Learning Model to Predict Childhood Lead Poisoning.

Importance: Childhood lead poisoning causes irreversible neurobehavioral deficits, but current practice is secondary prevention.

Objective: To validate a machine learning (random forest) prediction model of elevated blood lead levels (EBLLs) by comparison with a parsimonious logistic regression.

Design, Setting, And Participants: This prognostic study for temporal validation of multivariable prediction models used data from the Women, Infants, and Children (WIC) program of the Chicago Department of Public Health.

Expanded HIV Testing and Linkage to Care: Conventional vs. Point-of-Care Testing and Assignment of Patient Notification and Linkage to Care to an HIV Care Program.

Objective: The University of Chicago Medicine (UCM) led the Expanded Testing and Linkage to Care (X-TLC) program for disproportionately affected populations on the South Side of Chicago. The X-TLC program aimed to expand routine HIV testing to high-prevalence communities with disproportionately affected populations (i.e.

Willingness of US men who have sex with men (MSM) to participate in Couples HIV Voluntary Counseling and Testing (CVCT).

Background: We evaluated willingness to participate in CVCT and associated factors among MSM in the United States.

Methods: 5,980 MSM in the US, recruited through MySpace.com, completed an online survey March-April, 2009.

Exposure to HIV partner counseling and referral services and notification of sexual partners among persons recently diagnosed with HIV.

Objective: Among HIV-infected persons, we evaluated use of client partner notification (CPN) and health-department partner notification strategies to inform sex partners of possible HIV exposure, and prior exposure to partner counseling and referral services.

Methods: We conducted a cross-sectional, observational study of 590 persons diagnosed with HIV in the prior 6 months at 51 HIV test, medical, and research providers in Chicago and Los Angeles in 2003 and 2004. Logistic regression was used to identify independent correlates of using CPN to notify all locatable partners.