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The objective of the study was to investigate, using academic-community epidemiologic co-analysis, the odds of reported heat-related illness for people with (1) central air conditioning (AC) or window unit AC versus no AC, and (2) fair/poor vs. good/excellent reported health. From 2016 to 2017, 101 Detroit residents were surveyed once regarding extreme heat, housing and neighborhood features, and heat-related illness in the prior 5 years. Academic partners selected initial confounders and, after instruction on directed acyclic graphs, community partners proposed alternate directed acyclic graphs with additional confounders. Heat-related illness was regressed on AC type or health and co-selected confounders. The study found that heat-related illness was associated with no-AC (n = 96, odds ratio (OR) = 4.66, 95% confidence interval (CI) = 1.22, 17.72), living &le, 5 years in present home (n = 57, OR = 10.39, 95% CI = 1.13, 95.88), and fair/poor vs. good/excellent health (n = 97, OR = 3.15, 95% CI = 1.33, 7.48). Co-analysis suggested multiple built-environment confounders. We conclude that Detroit residents with poorer health and no AC are at greater risk during extreme heat. Academic-community co-analysis using directed acyclic graphs enhances research on community-specific social and health vulnerabilities by identifying key confounders and future research directions for rigorous and impactful research.

Extreme summertime heat is a significant public health threat that disproportionately impacts vulnerable urban populations. Research on health impacts of climate change (including increasing intensity, duration, and frequency of hot weather) is sometimes designed and implemented without the involvement of the communities being studied, i.e., &ldquo, community-placed&rdquo, not &ldquo, community-based.&rdquo, We describe how the Heatwaves, Housing, and Health: Increasing Climate Resiliency in Detroit (HHH) partnership engaged relevant communities by integrating a community-based participatory research (CBPR) approach into an existing, academic-designed research project through a steering committee of community and academic partners. Using a case study approach, we analyze program documentation, partnership evaluation questionnaires, and HHH steering committee meeting notes. We describe the CBPR process by which we successfully collected research data in Detroit during summer 2016, engaged in collaborative analysis of data, and shared results with Detroit residents. Evaluations of the partnership over 2 years show community involvement in research, enhanced capacities, success in securing new grant funding, and ways that CBPR strengthened the validity, relevance, and translation of research. Engaging communities as equal partners using CBPR, even after a study is underway, can strengthen research to understand and address the impacts of extreme heat on health and equity in urban communities.

Breeding programs aim to improve crop yield and environmental stability for enhanced food security. The principal methodology in breeding for stable yield gain relies on the indirect selection of beneficial genetics by yield evaluation across diverse environmental conditions. This methodology requires substantial resources while delivering a slow pace of yield gain and environmental adaptation. Alternative methods are required to accelerate gain and adaptation, becoming even more imperative in a changing climate. New molecular tools and approaches can enable accelerated creation and deployment of multiple alleles of genes identified to control key traits. With the advent of tools that enable breeding by targeted allelic selection, identifying gene targets associated with an improved crop performance ideotype will become crucial. Previous studies have shown that altered photoperiod regimes increase yield in wheat (