Non-fatal injury data: characteristics to consider for surveillance and research.

BACKGROUND: All data systems used for non-fatal injury surveillance and research have strengths and limitations that influence their utility in understanding non-fatal injury burden. The objective of this paper was to compare characteristics of major data systems that capture non-fatal injuries in the USA. METHODS: By applying specific inclusion criteria (eg, non-fatal and non-occupational) to well-referenced injury data systems, we created a list of commonly used non-fatal injury data systems for this study. Data system characteristics were compiled for 2018: institutional support, years of data available, access, format, sample, sampling method, injury definition/coding, geographical representation, demographic variables, timeliness (lag) and further considerations for analysis. RESULTS: Eighteen data systems ultimately fit the inclusion criteria. Most data systems were supported by a federal institution, produced national estimates and were available starting in 1999 or earlier. Data source and injury case coding varied between the data systems. Redesigns of sampling frameworks and the use of International Classification of Diseases, 9th Revision, Clinical Modification/International Classification of Diseases, 10th Revision, Clinical Modification coding for some data systems can make longitudinal analyses complicated for injury surveillance and research. Few data systems could produce state-level estimates. CONCLUSION: Thoughtful consideration of strengths and limitations should be exercised when selecting a data system to answer injury-related research questions. Comparisons between estimates of various data systems should be interpreted with caution, given fundamental system differences in purpose and population capture. This research provides the scientific community with an updated starting point to assist in matching the data system to surveillance and research questions and can improve the efficiency and quality of injury analyses.

COVID-19 Vaccine Acceptability Among Clients and Staff of Homeless Shelters in Detroit, Michigan, February 2021.

Understanding COVID-19 vaccine acceptability among clients and staff of homeless shelters can inform public health efforts focused on communicating with and educating this population about COVID-19 vaccines and thus improve vaccine uptake. The objective of this study was to assess COVID-19 vaccine acceptability and uptake among people in homeless shelters in Detroit, Michigan. A cross-sectional study was conducted from February 9 to 23, 2021. Seventeen homeless shelters were surveyed: seven male-only, three male/female, and seven women and family shelters. All clients and staff aged ≥18 years and able to complete a verbal survey in English or with a translator were eligible to participate; of the 168 individuals approached, 26 declined, leaving a total sample of 106 clients and 36 staff participating in the study. The median client and staff ages were 44 and 54 years, respectively. Most participants (>80%) identified as non-Hispanic Black or African American. Sixty-one (57.5%) clients and 27 (75.5%) staff had already received or planned to receive a COVID-19 vaccination. Twelve (11.3%) clients and four (11.1%) staff were unsure, and 33 (31.1%) clients and five (13.9%) staff did not plan to get vaccinated. Reasons for hesitancy were concerns over side effects (29 clients [64.4%] and seven staff [77.8%]) and unknown long-term health impacts (26 clients [57.8%] and six staff [66.7%]). More than half of the clients had already received or planned to receive the vaccine. Continuing efforts such as vaccine education for hesitant clients and staff and having accessible vaccine events for this population may improve acceptability and uptake.

Analysis of social determinants of health and individual factors found in health equity frameworks: Applications to injury research.

INTRODUCTION: This research evaluated existing health equity frameworks as they relate to social determinants of health (SDOHs) and individual factors that may impact injury outcomes and identify gaps in coverage using the Healthy People (HP) 2030 key domains. METHODS: The study used a list of health equity frameworks sourced from previous literature. SDOHs and individual factors from each framework were identified and categorized into the Healthy People 2030 domains. Five injury topic areas were used as examples for how SDOHs and individual factors can be compared to injury topic-specific health disparities to identify health equity frameworks to apply to injury research. RESULTS: The study identified 59 SDOHs and individual factors from the list of 33 health equity frameworks. The number of SDOHs and individual factors identified varied by Healthy People 2030 domain: Neighborhood and Built Environment contained 16 (27.1%) SDOHs and individual actors, Social and Community Context contained 22 (37.3%), Economic Stability contained 10 (16.9%), Healthcare Access and Quality contained 10 (16.9%), and Education Access and Quality contained one (1.7%). Twenty-three (39.0%) SDOHs/individual factors related to traumatic brain injury, thirteen (22.0%) related to motor vehicle crashes and suicide, 11 (18.6%) related to drowning and older adult falls. Eight frameworks (24.2%) covered all HP 2030 key domains and may be applicable to injury topics. CONCLUSIONS: Incorporating health equity into research is critical. Health equity frameworks can provide a way to systematically incorporate health equity into research. The findings from this study may be useful to health equity research by providing a resource to injury and other public health fields. PRACTICAL APPLICATIONS: Health equity frameworks are a practical tool to guide injury research, translation, evaluation, and program implementation. The findings from this study can be used to guide the application of health equity frameworks in injury research for specific topic areas.

Drugs and Drug Classes Involved in Overdose Deaths Among Females, United States: 1999-2017.

Background: Drug overdose deaths among U.S. women have risen steadily from 1999 to 2017, especially among certain ages. Various studies report involvement of drugs and drug classes in overdose deaths. Less is known, however, regarding the combinations that are most often indicated on death certificates, particularly among females. Analyzing mutually, exclusive drug/drug class combinations listed on death certificates of females are the objective of this study. Materials and Methods: Mortality data for U.S. female residents were obtained from the 1999 to 2017 National Vital Statistics System (n = 260,782). Analyses included deaths with an underlying cause of death based on International Classification of Diseases, 10th Revision (ICD-10) codes for drug overdoses. The drug/drug class involved included individual 4-digit ICD-10 codes in the range T36.0-T50.9, including poisoning deaths due to all drugs, excluding alcohol. Years from 1999 to 2017 were grouped in six 3-year categories with the most recent year (2017) left separate for analysis. All drug overdose deaths were analyzed in mutually exclusive categories. Results: From 1999 to 2017, the top-listed drug/drug class overall and by year grouping was solely "other and unspecified drugs, medicaments and biological substances"; however, that listing dropped from 25.8% from the 1999 to 2001 period to 14.1% in 2017. Overall, the next most frequent single drug/drug class mentions were "natural and semisynthetic opioids" (20,951; 8.0%) and "cocaine" (10,882; 4.2%). Two of the top five drug/drug class combinations included benzodiazepines ("natural and semisynthetic opioids"/"benzodiazepines" and "methadone"/"benzodiazepines"). Conclusions: Analyzing trends in drugs and drug classes involved in female drug overdose deaths is a critical foundation for developing gender-responsive public health interventions. Reducing high-risk drug use by improving prescribing practices, preventing drug use initiation, and addressing use of multiple drugs can help prevent overdose deaths.

Health equity guiding frameworks and indices in injury: A review of the literature.

BACKGROUND: In early 2021, CDC released the CORE Health Equity Strategy, which resolves to integrate a comprehensive health equity approach to the work of the Agency. One priority of the Injury Center's Division of Injury Prevention is to move health equity research in injury forward. The purpose of this research is to perform an initial exploration of health equity guiding frameworks and indices to better understand which of these has been applied to injury research topics. METHODS: A PubMed and CINAHL search of meta-analysis and systematic review articles was conducted from January 1998 through April 2022. Articles of any type and additional frameworks/indices were also identified from staff knowledge of the literature. Books were also considered, where accessible. The following areas were reviewed for each resource: population addressed, guiding framework/index, other health equity variables, gaps identified, and whether the articles addressed an injury topic. FINDINGS: The PubMed/CINAHL search produced 230 articles, and an additional 29 articles and 8 books were added from previous knowledge of the literature, resulting in a total of 267 resources for review. There were 60 frameworks/indices compiled that were relevant to health equity. Out of all the resources, three reported on an injury topic and used the PROGRESS-Plus framework, the WHO Social Determinants of Health Conceptual Framework, and a social-ecological framework. CONCLUSIONS: This study found there were many frameworks/indices for measuring health equity; however, there were few injury-related meta-analysis and systematic review articles. Some frameworks/indices may be more appropriate than others for measuring health equity in injury topic areas, depending on which social determinants of health (SDOHs) they address. PRACTICAL APPLICATIONS: Measuring health equity in injury and other public health research areas can help build a foundation of evidence. Moving forward, injury researchers can consider the frameworks/indices identified through this study in their health equity injury research.

Incidence of COVID-19 Among Persons Experiencing Homelessness in the US From January 2020 to November 2021.

Importance: A lack of timely and high-quality data is an ongoing challenge for public health responses to COVID-19 among people experiencing homelessness (PEH). Little is known about the total number of cases of COVID-19 among PEH. Objective: To estimate the number of COVID-19 cases among PEH and compare the incidence rate among PEH with that in the general population. Design, Setting, and Participants: This cross-sectional study used data from a survey distributed by the Centers for Disease Control and Prevention to all US state, district, and territorial health departments that requested aggregated COVID-19 data among PEH from January 1, 2020, to September 30, 2021. Jurisdictions were encouraged to share the survey with local health departments. Main Outcomes and Measures: The primary study outcome was the number of cases of COVID-19 identified among PEH. COVID-19 cases and incidence rates among PEH were compared with those in the general population in the same geographic areas. Results: Participants included a population-based sample of all 64 US jurisdictional health departments. Overall, 25 states, districts, and territories completed the survey, among which 18 states (72.0%) and 27 localities reported COVID-19 data among PEH. A total of 26 349 cases of COVID-19 among PEH were reported at the state level and 20 487 at the local level. The annual incidence rate of COVID-19 among PEH at the state level was 567.9 per 10 000 person-years (95% CI, 560.5-575.4 per 10 000 person-years) compared with 715.0 per 10 000 person-years (95% CI, 714.5-715.5 per 10 000 person-years) in the general population. At the local level, the incidence rate of COVID-19 among PEH was 799.2 per 10 000 person-years (95% CI, 765.5-834.0 per 10 000 person-years) vs 812.5 per 10 000 person-years (95% CI, 810.7-814.3 per 10 000 person-years) in the general population. Conclusions and Relevance: These results provide an estimate of COVID-19 incidence rates among PEH in multiple US jurisdictions; however, a national estimate and the extent of under- or overestimation remain unknown. The findings suggest that opportunities exist for incorporating housing and homelessness status in infectious disease reporting to inform public health decision-making.

Exposure to bisphenol A, chlorophenols, benzophenones, and parabens in relation to reproductive hormones in healthy women: A chemical mixture approach.

BACKGROUND: Little is known about the associations of bisphenol A, chlorophenols, benzophenones, and parabens with reproductive hormone levels in women. Our goal was to evaluate the associations between repeated measures of these chemicals and their mixtures with reproductive hormones in women. METHODS: Longitudinal urine samples from healthy, premenopausal women (n = 143 with 3-5 urine samples each) were measured for bisphenol A, five chlorophenols (2,4-dichlorophenol (2,4-DCP), 2,5-dichlorophenol, 2,4,5-trichlorophenol, 2,4,6-trichlorophenol, triclosan), two ultraviolet (UV) filters (benzophenone-1, benzophenone-3), and eight parabens and their metabolites (benzyl, butyl, ethyl, heptyl, methyl, propyl, 4-hydroxybenzoic acid (4-HB), 3,4-dihydroxybenzoic acid (3,4-DHB)) over two menstrual cycles. Estradiol, progesterone, luteinizing hormone (LH), and follicle stimulating hormone (FSH) were measured in blood up to 8 times each menstrual cycle. Linear mixed models were used for both single and multi-chemical exposures estimated using principal component analysis. Four factors were identified including: paraben; paraben metabolites and BPA, phenols, and UV filters. Models were adjusted for creatinine, age, race, and body mass index and weighted with inverse probability of exposure weights to account for time varying confounding. RESULTS: In single-chemical models, 3,4-DHB was associated with estradiol (0.06 (95% confidence interval (CI): 0.001, 0.12)), 2-4-DCP with increased progesterone 0.14 (0.06, 0.21) and decreased FSH -0.08 (-0.11, -0.04), and 4-HB was associated with increased FSH 0.07 (0.01, 0.13). In multi-chemical models, all factors were associated with increased progesterone (beta coefficient range: 0.15 for UV filter factor to 0.32 for paraben factor). The paraben factor and the paraben metabolite and BPA factor were associated with increased estradiol [0.21 (0.15, 0.28); 0.12 (0.07, 0.18)]. The phenol and UV filter factors were associated with decreased estradiol, FSH, and LH. The UV filter factor showed the strongest inverse association with estradiol -0.16 (-0.22, -0.10), FSH -0.12 (-0.17, -0.07), and LH -0.17 (-0.23, -0.10). CONCLUSION: Mixtures of phenols were associated with changes in reproductive hormones. Such changes could contribute to adverse health in women but additional research is necessary.