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Climate-sensitive hazards, including extreme heat, wildfire smoke, flooding, and rising sea levels, can jeopardize the health of all populations. However, certain population groups are more vulnerable to harm from these hazards. While youth–particularly those from historically marginalized groups and communities–are among those at the highest risk, their abilities may be underutilized in local climate adaptation efforts. This exploratory research aimed to identify opportunities for youth involvement in climate and environmental solutions in their historically marginalized communities. Specifically, this study (1) investigated youth risk perceptions and impacts of various climate-sensitive hazards (e.g. extreme heat, wildfire smoke, flooding, and sea level rise); (2) examined current barriers, resource needs, and opportunities for youth to engage in climate and environmental solution work; and (3) explored current methods and spaces where youth and community leaders can support youth-led climate-related initiatives. Through focus group discussions with youth and in-depth interviews with community leaders who are directly with youth, this study identified opportunities to leverage youth experiences, perceptions, and assets to promote a healthy and resilient community in the face of various compounding climate-related threats. Results showed that while youth recognize the changing climate and associated health impacts, they require more financial resources and support from local decision-makers to maintain their engagement and promote community resilience. Engaging youth in climate action and community resilience involves more than just centering youth voices and perspectives–it requires intentional collaboration, capacity-building, organizing, granting decision-making power, and other strategies to produce inclusive, intersectional, and sustainable solutions. 

Abstract Research conducted in the context of a disaster or public health emergency is essential to improve knowledge about its short- and long-term health consequences, as well as the implementation and effectiveness of response and recovery strategies. Integrated approaches to conducting Disaster Research Response (DR2) can answer scientific questions, while also providing attendant value for operational response and recovery. Here, we propose a Concept of Operations (CONOPS) template to guide the collaborative development and implementation of DR2 among academic public health and public health agencies, informed by previous literature, semi-structured interviews with disaster researchers from academic public health across the United States, and discussion groups with public health practitioners. The proposed CONOPS outlines actionable strategies to address DR2 issues before, during, and after disasters for public health scholars and practitioners who seek to operationalize or enhance their DR2 programs. Additional financial and human resources will be necessary to promote widespread implementation of collaborative DR2 programs. 

Brain age (BA), distinct from chronological age (CA), can be estimated from MRIs to evaluate neuroanatomic aging in cognitively normal (CN) individuals. BA, however, is a cross-sectional measure that summarizes cumulative neuroanatomic aging since birth. Thus, it conveys poorly recent or contemporaneous aging trends, which can be better quantified by the (temporal) pace P of brain aging. Many approaches to map P, however, rely on quantifying DNA methylation in whole-blood cells, which the blood–brain barrier separates from neural brain cells. We introduce a three-dimensional convolutional neural network (3D-CNN) to estimate P noninvasively from longitudinal MRI. Our longitudinal model (LM) is trained on MRIs from 2,055 CN adults, validated in 1,304 CN adults, and further applied to an independent cohort of 104 CN adults and 140 patients with Alzheimer’s disease (AD). In its test set, the LM computes P with a mean absolute error (MAE) of 0.16 y (7% mean error). This significantly outperforms the most accurate cross-sectional model, whose MAE of 1.85 y has 83% error. By synergizing the LM with an interpretable CNN saliency approach, we map anatomic variations in regional brain aging rates that differ according to sex, decade of life, and neurocognitive status. LM estimates of P are significantly associated with changes in cognitive functioning across domains. This underscores the LM’s ability to estimate P in a way that captures the relationship between neuroanatomic and neurocognitive aging. This research complements existing strategies for AD risk assessment that estimate individuals’ rates of adverse cognitive change with age.