Adverse Childhood Experiences and Adult Smoking, Nebraska, 2011

Introduction Smoking is a public health risk; the prevalence of smoking among adults in Nebraska is 18-4%. Studies indicate that maltreatment of children alters their brain development, possibly increasing risk for tobacco use. Previous studies have documented associations between childhood maltreatment and adult health behaviors, demonstrating the influence of adverse experiences on tobacco use. We examined prevalence and associations between adverse childhood experiences and smoking among Nebraskans. Methods We analyzed 2011 Nebraska Behavioral Risk Factor Surveillance System (Adverse Childhood Experience module) data, defining adverse childhood experience exposures as physical, sexual, and verbal abuse (ie, direct exposures), and household dysfunction associated with mental illness, substance abuse, divorce, domestic violence, and living with persons with incarceration histories (ie, environmental exposures). We estimated prevalence of exposures, taking into account the complex survey design. We used logistic regression with predicted margins to estimate adjusted relative risk for smoking by direct or environmental exposure. Results Approximately 51% of Nebraskans experienced 1 or more adverse childhood events; 7% experienced 5 or more. Prevalence of environmental exposures (42%) was significantly higher than that of direct exposures (31%). Prevalence of individual exposures ranged from 6% (incarceration of a household member) to 25% (verbal abuse). Adjusted relative risks of smoking for direct and environmental exposures were 1.5 and 1.8, respectively. Conclusion We present a new method of evaluating adverse childhood experience data. Prevalence of adverse childhood experiences is high among Nebraskans, and these exposures are associated with smoking. State-specific strategies to monitor adverse events among children and provide interventions might help to decrease the smoking rate in this population

Adverse Childhood Experiences and Adult Smoking, Nebraska, 2011

Introduction Smoking is a public health risk; the prevalence of smoking among adults in Nebraska is 18-4%. Studies indicate that maltreatment of children alters their brain development, possibly increasing risk for tobacco use. Previous studies have documented associations between childhood maltreatment and adult health behaviors, demonstrating the influence of adverse experiences on tobacco use. We examined prevalence and associations between adverse childhood experiences and smoking among Nebraskans. Methods We analyzed 2011 Nebraska Behavioral Risk Factor Surveillance System (Adverse Childhood Experience module) data, defining adverse childhood experience exposures as physical, sexual, and verbal abuse (ie, direct exposures), and household dysfunction associated with mental illness, substance abuse, divorce, domestic violence, and living with persons with incarceration histories (ie, environmental exposures). We estimated prevalence of exposures, taking into account the complex survey design. We used logistic regression with predicted margins to estimate adjusted relative risk for smoking by direct or environmental exposure. Results Approximately 51% of Nebraskans experienced 1 or more adverse childhood events; 7% experienced 5 or more. Prevalence of environmental exposures (42%) was significantly higher than that of direct exposures (31%). Prevalence of individual exposures ranged from 6% (incarceration of a household member) to 25% (verbal abuse). Adjusted relative risks of smoking for direct and environmental exposures were 1.5 and 1.8, respectively. Conclusion We present a new method of evaluating adverse childhood experience data. Prevalence of adverse childhood experiences is high among Nebraskans, and these exposures are associated with smoking. State-specific strategies to monitor adverse events among children and provide interventions might help to decrease the smoking rate in this population

Previously Undiagnosed HIV Infections Identified Through Cluster Investigation, North Carolina, 2002–2007

During cluster investigation, index patients name social contacts that are not sex or drug-sharing partners. The likelihood of identifying new HIV infections among social contacts is unknown. We hypothesized greater odds of identifying new infections among social contacts identified by men who report sex with men (MSM). We reviewed North Carolina HIV diagnoses during 2002–2005 and used logistic regression to compare testing results among social contacts of MSM, men who report sex with women only (MSW) and women. HIV was newly diagnosed among 54/601 (9.0%) social contacts tested named by MSM, 16/522 (3.1%) named by MSW, and 23/639 (3.6%) named by women. Compared with those named by MSW, odds of new HIV diagnosis were greater among MSM social contacts (adjusted odds ratio: 2.5; 95% confidence interval: 1.3–4.7). Testing social contacts identified previously undiagnosed HIV infections and could provide an opportunity to interrupt transmission

Statistical methods used in the public health literature and implications for training of public health professionals

<div><p>Statistical literacy and knowledge is needed to read and understand the public health literature. The purpose of this study was to quantify basic and advanced statistical methods used in public health research. We randomly sampled 216 published articles from seven top tier general public health journals. Studies were reviewed by two readers and a standardized data collection form completed for each article. Data were analyzed with descriptive statistics and frequency distributions. Results were summarized for statistical methods used in the literature, including descriptive and inferential statistics, modeling, advanced statistical techniques, and statistical software used. Approximately 81.9% of articles reported an observational study design and 93.1% of articles were substantively focused. Descriptive statistics in table or graphical form were reported in more than 95% of the articles, and statistical inference reported in more than 76% of the studies reviewed. These results reveal the types of statistical methods currently used in the public health literature. Although this study did not obtain information on what should be taught, information on statistical methods being used is useful for curriculum development in graduate health sciences education, as well as making informed decisions about continuing education for public health professionals.</p></div

Frequency of use reported for statistical modeling and related advanced statistical techniques (n = 216).

<p>Frequency of use reported for statistical modeling and related advanced statistical techniques (n = 216).</p

Public health journals reviewed and number of articles from 2013 included in the study sample.

<p>Public health journals reviewed and number of articles from 2013 included in the study sample.</p

Frequency of use reported for statistical software packages (n = 216).

<p>Frequency of use reported for statistical software packages (n = 216).</p

Public health impact of the U.S. Scenario Modeling Hub

Beginning in December 2020, the COVID-19 Scenario Modeling Hub has provided quantitative scenario-based projections for cases, hospitalizations, and deaths, aggregated across up to nine modeling groups. Projections spanned multiple months into the future and provided timely information on potential impacts of epidemiological uncertainties and interventions. Projections results were shared with the public, public health partners, and the Centers for Disease Control COVID-19 Response Team. The projections provided insights on situational awareness and informed decision-making to mitigate COVID-19 disease burden (e.g., vaccination strategies). By aggregating projections from multiple modeling teams, the Scenario Modeling Hub provided rapidly synthesized information in times of great uncertainty and conveyed possible trajectories in the presence of emerging variants. Here we detail several use cases of these projections in public health practice and communication, including assessments of whether modeling results directly or indirectly informed public health communication or guidance. These include multiple examples where comparisons of projected COVID-19 disease outcomes under different vaccination scenarios were used to inform Advisory Committee for Immunization Practices recommendations. We also describe challenges and lessons learned during this highly beneficial collaboration