From co-design to co-production: Approaches, enablers, and constraints in developing a public health, capacity-building solution.

INTRODUCTION: Investigating how co-designed knowledge can be translated to co-produce a public health capacity-building solution for difficult-to-engage population groups drawing on the co-production experience of a prevention-focused, capacity-building mental health solution targeting primary producers. DESIGN: A qualitative study undertaken in rural and regional Victoria involving members of the design working group including project team (7px), digital design team (5px), marketing team (3px), and funding partner representatives. The study design involved reflective practice to collect data to identify the phases of co-production and assess the design working group members' experiences. The analysis involved inductive coding using Braun and Clarke's thematic analysis. OBJECTIVE: Identifying major points of divergence and/or convergence; enablers and/or constraints; and ways to better navigate and strengthen the co-production process. FINDING: Given members of the design working group, diverse skills sets divergence was experienced in all co-production phases. Divergence was also experienced between the project team and the funding partner given the uniqueness of working conditions and requirements of workers in the primary production industry. The project team applied an iterative development process to project management; encouraging iterative cycles to create/test/revise among the teams, and with the funding partner, until each was satisfied with the end result (convergence). DISCUSSION & CONCLUSION: When developing a co-created public health prevention campaign it is critical that the project team focuses on relationship building among the members of the design working group and ensures adequate resourcing, development of shared understanding of project goals and target audience, ongoing communication, and a commitment to working iteratively.

Decreased activation of placental mTOR family members is associated with the induction of intrauterine growth restriction by secondhand smoke in the mouse.

Cigarette smoke is known to be a risk for the development of intrauterine growth restriction (IUGR). Our objective was to assess the effects of secondhand smoke (SHS) during pregnancy and to what extent it regulates the activation of mTOR family members and murine trophoblast invasion. Mice were treated to SHS for 4 days. Placental and fetal weights were recorded at the time of necropsy. Immunohistochemistry was used to determine the level of placental trophoblast invasion. Western blots were utilized to assess the activation of caspase 3, XIAP, mTOR, p70 and 4EBP1 in treated and control placental lysates. As compared to controls, treated animals showed: (1) decreased placental (1.4-fold) and fetal (2.3-fold) weights (p < 0.05); (2) decreased trophoblast invasion; (3) significantly decreased active caspase 3 (1.3-fold; p < 0.02) and increased active XIAP (3.6-fold; p < 0.05) in the placenta; and (4) a significant decrease in the activation of placental mTOR (2.1-fold; p < 0.05), p70 (1.9-fold; p < 0.05) and 4EBP1 (1.3-fold; p < 0.05). Confirmatory in vitro experiments revealed decreased trophoblast invasion when SW71 cells were treated with 0.5 or 1.0 % cigarette smoke extract (CSE). Similar to primary smoking, SHS may induce IUGR via decreased activation of the mTOR family of proteins in the placenta. Increased activation of the placental XIAP protein could be a survival mechanism for abnormal trophoblast cells during SHS exposure. Further, CSE reduced trophoblast invasion, suggesting a direct causative effect of smoke on susceptible trophoblast cells involved in IUGR progression. These results provide important insight into the physiological consequences of SHS exposure and smoke-mediated placental disease.

Cigarette smoke and decreased oxygen tension inhibit pulmonary claudin-6 expression.

PURPOSE: Chronic obstructive pulmonary disease is a condition involving perturbed barrier integrity coincident with both emphysema and inflammation of the airways, and smoking is considered a major risk factor. Claudins (Cldns) stabilize barriers and contribute to tight junctions by preventing paracellular transport of extracellular fluid constituents. METHODS: To determine Cldn6 was differentially influenced by tobacco smoke, Cldn6 was evaluated in cells and tissues by q-PCR, immunoblotting, and immunohistochemistry following exposure. Cldn6 transcriptional regulation was also assessed using luciferase reporter constructs. RESULTS: Q-PCR and immunoblotting revealed that Cldn6 was decreased in alveolar type II-like epithelial cells (A549) and primary small airway epithelial cells when exposed to cigarette smoke extract (CSE). Cldn6 was also markedly decreased in the lungs of mice exposed to acute tobacco smoke delivered by a nose-only automated smoke machine compared to controls. Luciferase reporter assays incorporating 0.5-kb, 1.0-kb, or 2.0-kb of the Cldn6 promoter revealed decreased transcription of Cldn6 following exposure to CSE. Cldn6 transcriptional regulation was also assessed in hypoxic conditions due to low oxygen tension observed during smoking. Hypoxia and hypoxia inducible factor-1 alpha caused decreased transcription of the Cldn6 gene via interactions with putative response elements in the proximal promoter sequence. CONCLUSIONS: These data reveal that tight junctional proteins such as Cldn6 are differentially regulated by tobacco-smoke exposure and that Cldns are potentially targeted when epithelial cells respond to tobacco smoke. Further research may show that Cldns expressed in tight junctions between parenchymal cells contribute to impaired structural integrity of the lung coincident with smoking.

Development of a Synthetic Population Model for Assessing Excess Risk for Cardiovascular Disease Death.

Importance: Evaluating the association of social determinants of health with chronic diseases at the population level requires access to individual-level factors associated with disease, which are rarely available for large populations. Synthetic populations are a possible alternative for this purpose. Objective: To construct and validate a synthetic population that statistically mimics the characteristics and spatial disease distribution of a real population, using real and synthetic data. Design, Setting, and Participants: This population-based decision analytical model used data for Allegheny County, Pennsylvania, collected from January 2015 to December 2016, to build a semisynthetic population based on the synthetic population used by the modeling and simulation platform FRED (A Framework for Reconstructing Epidemiological Dynamics). Disease status was assigned to this population using health insurer claims data from the 3 major insurance providers in the county or from the National Health and Nutrition Examination Survey. Biological, social, and other variables were also obtained from the National Health Interview Survey, Allegheny County, and public databases. Data analysis was performed from November 2016 to February 2020. Exposures: Risk of cardiovascular disease (CVD) death. Main Outcomes and Measures: Difference between expected and observed CVD death risk. A validated risk equation was used to estimate CVD death risk. Results: The synthetic population comprised 1 188 112 individuals with demographic characteristics similar to those of the 2010 census population in the same county. In the synthetic population, the mean (SD) age was 40.6 (23.3) years, and 622 997 were female individuals (52.4%). Mean (SD) observed 4-year rate of excess CVD death risk at the census tract level was -40 (523) per 100 000 persons. The correlation of social determinant data with difference between expected and observed CVD death risk indicated that income- and education-based social determinants were associated with risk. Estimating improved social determinants of health and biological factors associated with disease did not entirely remove the excess in CVD death rates. That is, a 20% improvement in the most significant determinants still resulted in 105 census tracts with excess CVD death risk, which represented 24% of the county population. Conclusions and Relevance: The results of this study suggest that creating a geographically explicit synthetic population from real and synthetic data is feasible and that synthetic populations are useful for modeling disease in large populations and for estimating the outcome of interventions.