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Background A petroleum leak into the Joint Base Pearl Harbor-Hickam water system on Oahu, Hawaii in November 2021 contaminated the drinking water of approximately 93,000 users, causing many to relocate for months. Perceptions of health and wellbeing were captured using the Centers for Disease Control/Agency for Toxic Substances and Disease Registry (CDC/ATSDR) Assessment of Chemical Exposures (ACE) cross-sectional survey in collaboration with the Hawaii Department of Health (HDOH). Methods Responses from the ACE online survey of community members, businesses, schools, health care and veterinary care organizations during the contamination event, containing quantitative questions and qualitative information from an open text field, were analyzed. Separately, a qualitative key informant questionnaire was administered to community establishments. Thematic content analysis was used to analyze and identify prominent themes from the ACE open text field and the key informant responses that were triangulated by the quantitative data when the themes aligned. Results Six major themes of disruption, communication, trust, stress, support, and ongoing needs were identified. Burdensome logistics from obtaining alternate water, negative financial impacts from relocation or losing business, distrust of information, perceived lack of support from response entities and uncertainty of long-term health impact caused significant disruption, stress and mental health. Individuals reported needing water, shelter, and mental health care while establishments wanted financial reimbursement and a resolution. Conclusions The findings show that environmental disasters have significant disruptive and mental health impacts from stress. Identified themes can inform and improve emergency response and communication strategies and increase trust with community members during and after large chemical exposure events.

Background: In 2021, a large petroleum leak contaminated a water source that supplied drinking water to military and civilians in Oahu, Hawaii. Methods: We conducted an Assessment of Chemical Exposures (ACE) survey and supplemented that information with complementary data sources: (1) poison center caller records; (2) emergency department visit data; and (3) a key informant questionnaire. Results: Among 2,289 survey participants, 86% reported ≥1 new or worsening symptom, 75% of which lasted ≥30 days, and 37% sought medical care. Most (n = 1,653, 72%) reported new mental health symptoms. Among equally observable symptoms across age groups, proportions of children ≤2 years experiencing vomiting, runny nose, skin rashes, and coughing (33, 46, 56, and 35%, respectively) were higher than other age groups. Poison center calls increased the first 2 weeks after the contamination, while emergency department visits increased in early December 2021. Key informant interviews revealed themes of lack of support, mental health symptoms, and long-term health impact concerns. Discussion: This event led to widespread exposure to petroleum products and negatively affected thousands of people. Follow-up health surveys or interventions should give special consideration to longer-term physical and mental health, especially children due to their unique sensitivity to environmental exposures.

A better understanding of whether and how economic factors impact mental health can inform policy and program decisions to improve mental health. This study looked at the association between county-level economic factors and the prevalence of self-reported poor mental health among adults in United States counties in 2019, overall and disaggregated for urban and rural counties. General dominance analyses were completed to rank-order the relative influence of the selected variables in explaining county prevalence of adults reporting > 14 poor mental health days in the last 30 days (“poor mental health”). The highest weighted variables were assessed for the statistical significance of their relationships with county-level poor mental health through multiple linear regression. Across all models, the four highest-ranked economic factors were household income, receipt of Supplemental Security Income, population with a college degree, and receipt of Supplemental Nutrition Assistance Program benefits. The overall, rural, and urban models explained over 68% of the variation in poor mental health prevalence between counties. Urban and rural models showed notable differences in the top factors associated with poor mental health and opposite associations between poor mental health and population with public insurance. The findings from this study indicate a significant association between several economic factors and poor mental health, which may inform decision makers in addressing mental health in the United States.

IntroductionWe investigated 2018 gestational diabetes mellitus (GDM) prevalence estimates in three surveillance systems (National Vital Statistics System, State Inpatient Database, and Pregnancy Risk Assessment Monitoring Survey).MethodsWe calculated GDM prevalence for jurisdictions represented in each system; a subset of data was analyzed for people 18–39 years old in 22 jurisdictions present in all three systems to observe dataset-specific demographics and GDM prevalence using comparable categories.ResultsGDM prevalence estimates varied widely by data system and within the data subset despite comparable demographics.DiscussionUnderstanding the differences between GDM surveillance data systems can help researchers better identify people and places at higher risk of GDM.SignificanceWhat is Already Known on this Subject?Gestational diabetes mellitus (GDM) prevalence varies by data system and population. Estimates of GDM prevalence are essential to inform prevention, identification, and management programs.What this Report Adds?GDM prevalence estimates varied widely by data system (NVSS, SID, PRAMS) and participant demographics varied only slightly when a subset of comparable data were evaluated using jurisdictions available in all three systems (21 states and the District of Columbia). Understanding the differences between surveillance data systems can help researchers better identify people and places at higher risk of GDM.