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Pronk NP, Woodard C, Zimmerman FJ, Arena R. An ecological framework for population health and well-being. Prog Cardiovasc Dis 2025:S0033-0620(25)00042-8. [PMID: 40154649 DOI: 10.1016/j.pcad.2025.03.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/25/2025] [Accepted: 03/25/2025] [Indexed: 04/01/2025]
Abstract
Social structures have become focal points in considering how to address the circumstances and conditions under which people live their lives. Yet, the many interactions among multiple factors that make up social and structural determinants are complex, interdependent, interactive, dynamic, and multilevel. This paper introduces an evidence-informed ecological framework that organizes drivers and feedback mechanisms collectively representing a generative force towards population health and well-being. The proposed ecological framework supports explanatory and exploratory considerations for prevention and management of population health and well-being issues. The framework explicitly includes a recognition that successful health and well-being outcomes are often dependent on the presence of social capital and healthy power dynamics. Dominant cultural norm is positioned as an overarching driver in this framework because it shapes the political realities and power dynamics responsible for infrastructure as well as the habits and behaviors of people at both the individual and social levels.
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Affiliation(s)
- Nicolaas P Pronk
- HealthPartners Institute, Minneapolis, MN, USA; Department of Health Policy and Management, University of Minnesota, Minneapolis, MN, USA; Healthy Living for Pandemic Event Protection (HL - PIVOT) Network, Chicago, IL, USA.
| | - Colin Woodard
- Nationhood Lab, Pell Center for International Relations and Public Policy, Salve Regina University, Newport, RI, USA.
| | - Frederick J Zimmerman
- Department of Health Policy and Management, Center for Health Advancement, UCLA, Los Angeles, CA, USA.
| | - Ross Arena
- Healthy Living for Pandemic Event Protection (HL - PIVOT) Network, Chicago, IL, USA; Department of Physical Therapy, College of Applied Science, University of Illinois, Chicago, IL, USA.
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2
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Zimmerman FJ, Pronk NP. Socioeconomic milieu and culture: Forcing factors and the Most fundamental determinant of health. Prog Cardiovasc Dis 2025:S0033-0620(25)00036-2. [PMID: 40118198 DOI: 10.1016/j.pcad.2025.03.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/16/2025] [Accepted: 03/16/2025] [Indexed: 03/23/2025]
Abstract
We introduce the concept of forcing factors, analogous to risk factors for population-wide health outcomes, that are attributes of the physical, social, legal, economic, or cultural environment that are common to all people in an identified population and that promote or inhibit particular outcomes of health, wellness, and well-being. Examples include laws governing food or tobacco marketing, the built environment, and climate change. Culture also functions as a forcing factor of health outcomes. In contrast to past explanations of adverse health outcomes that have relied on cultural attributes of a specific sub-population, we draw on work of John McKinlay to make the point that it is the shared culture of a country or a region that influences health outcomes. Culture itself operates in a particular cultural context.
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Affiliation(s)
- Frederick J Zimmerman
- Department of Health Policy and Management, Center for Health Advancement, University of California, Los Angeles, USA.
| | - Nicolaas P Pronk
- HealthPartners Institute, Bloomington, MN, USA; Department of Health Policy and Management, School of Public Health, University of Minnesota, Minneapolis, MN, USA; Healthy Living for Pandemic Event Protection (HL-PIVOT), University of Illinois Chicago, Chicago, IL, USA.
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3
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Donovan SM, Abrahams M, Anthony JC, Bao Y, Barragan M, Bermingham KM, Blander G, Keck AS, Lee BY, Nieman KM, Ordovas JM, Penev V, Reinders MJ, Sollid K, Thosar S, Winters BL. Personalized nutrition: perspectives on challenges, opportunities, and guiding principles for data use and fusion. Crit Rev Food Sci Nutr 2025:1-18. [PMID: 39907017 DOI: 10.1080/10408398.2025.2461237] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2025]
Abstract
Personalized nutrition (PN) delivers tailored dietary guidance by integrating health, lifestyle, and behavioral data to improve individual health outcomes. Recent technological advances have enhanced access to diverse data sources, yet challenges remain in collecting, integrating, and analyzing complex datasets. To address these, the Personalized Nutrition Initiative at Illinois organized a workshop titled "Personalized Nutrition Data: Challenges & Opportunities," which gathered experts to explore three essential data domains in PN: 1) health and biological, 2) social, behavioral, and environmental, and 3) consumer purchasing data. Discussions underscored the importance of cross-disciplinary collaboration to standardize data collection, enable secure data sharing, and develop data fusion techniques that respect privacy and build trust. Participants emphasized the need for representative datasets that include underserved populations, ensuring that PN services are accessible and equitable. Key principles for responsible data integration were proposed, alongside strategies to overcome barriers to effective data use. By addressing these challenges, PN can enhance health outcomes through precise, personalized recommendations tailored to diverse population needs.
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Affiliation(s)
- Sharon M Donovan
- Personalized Nutrition Initiative, Carl R. Woese Institute for Genomic Biology, and the Department of Food Science and Human Nutrition, University of Illinois Urbana-Champaign, Urbana, IL, USA
| | | | | | - Ying Bao
- Gies College of Business, University of Illinois Urbana-Champaign, Urbana, IL, USA
| | - Maribel Barragan
- Personalized Nutrition Initiative, Carl R. Woese Institute for Genomic Biology, University of Illinois Urbana-Champaign, Urbana, IL, USA
| | - Kate M Bermingham
- Zoe Ltd, London, UK, Department of Nutritional Sciences, King's College London, London, UK
| | - Gil Blander
- Segterra (InsideTracker), Cambridge, MA, USA
| | - Anna-Sigrid Keck
- Personalized Nutrition Initiative, Carl R. Woese Institute for Genomic Biology, University of Illinois Urbana-Champaign, Urbana, IL, USA
| | - Bruce Y Lee
- Artificial Intelligence, Modeling, and Informatics for Nutrition Guidance and Systems (AIMINGS) Center, PHICOR, and the Center for Advanced Technology and Communication in Health (CATCH), at the City University of New York (CUNY), Graduate School of Public Health and Health Policy, New York City, NY, USA
| | | | - Jose M Ordovas
- Nutrition and Genomics Laboratory, JM-USDA-Human Nutrition Research Center on Aging, Tufts University, Boston, MA, USA
| | | | - Machiel J Reinders
- Wageningen University & Research, Wageningen Social & Economic Research, the Hague, the Netherlands
| | - Kris Sollid
- International Food Information Council, Washington, DC, USA
| | - Sumeet Thosar
- Personalized Nutrition Initiative, Carl R. Woese Institute for Genomic Biology, University of Illinois Urbana-Champaign, Urbana, IL, USA
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4
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Khiari H, Arfaoui E, Mahjoub N, Henchiri S, Sliti A, Hsairi M. Estimated Cancer Incidence in Northern Tunisia in 2023: Northern Tunisia Cancer Registry. Asian Pac J Cancer Prev 2024; 25:4359-4369. [PMID: 39733429 PMCID: PMC12008349 DOI: 10.31557/apjcp.2024.25.12.4359] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2024] [Indexed: 12/31/2024] Open
Abstract
BACKGROUND Cancer is a major cause of morbidity and mortality in Tunisia. The objectives of our study were to estimate the incidence level of the main cancer sites in Northern Tunisia in 2023 and to dress projections till 2040. METHODS The population based cancer registry database of northern Tunisia was the source of cases of this study. This registry uses the active method to collect data from all health services that cover cancer patients of both public and private sectors. Incidence rate projections were established using the age-period-cohort model. RESULTS In 2023, according to our estimations, age standardized incidence rate (ASR) including skin cancers other than melanoma was of 165.9 /100,000 in males and 141.4/100,000 in females. In men, the five most common cancer locations (apart from the skin) were: lung with an ASR of 37.6/100,000 habitant, colorectal (29.4/100,000), bladder (24.1/100,000), prostate (15.2/100,000) and stomach (6.0/100,000). Concerning females, the top five locations (apart from the skin) were: breast (55.4/100,000), colorectal (23.0/100,000), corpus uteri (9.3/100,000), thyroid (9.0/100,000) and lung (5.8/100,000). By 2040, the incidence rates of colorectal cancer would reach more than the double in both genders. The ASR of lung and bladder cancers in males would be increasing; however, that of stomach cancer would be stable next decades. In females, while incidence rates of breast, thyroid and corpus uteri cancers would reach more than the double in 2040, cervical cancer incidence is expected to be stable next decades. CONCLUSION Cancer incidence level in Northern Tunisia place the country in an intermediate level and projections seem to be worrying. Strengthening prevention, screening and early diagnosis are strongly recommended.
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Affiliation(s)
- Houyem Khiari
- Department of Epidemiology and Biostatistics, Salah Azaiz Institute of Cancer, Tunis, Tunisia.
| | - Emna Arfaoui
- Department of Epidemiology and Biostatistics, Salah Azaiz Institute of Cancer, Tunis, Tunisia.
| | | | | | - Alyssa Sliti
- Department of Epidemiology and Biostatistics, Salah Azaiz Institute of Cancer, Tunis, Tunisia.
| | - Mohamed Hsairi
- Department of Epidemiology and Biostatistics, Salah Azaiz Institute of Cancer, Tunis, Tunisia.
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Tylden ES, Delgado AB, Lukic M, Moi L, Busund LTR, Pedersen MI, Lombardi AP, Olsen KS. Roles of miR-20a-5p in breast cancer based on the clinical and multi-omic (CAMO) cohort and in vitro studies. Sci Rep 2024; 14:25022. [PMID: 39443510 PMCID: PMC11499649 DOI: 10.1038/s41598-024-75557-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Accepted: 10/07/2024] [Indexed: 10/25/2024] Open
Abstract
MicroRNAs are involved in breast cancer development and progression, holding potential as biomarkers and therapeutic targets or tools. The roles of miR-20a-5p, a member of the oncogenic miR-17-92 cluster, remain poorly understood in the context of breast cancer. In this study, we elucidate the role of miR-20a-5p in breast cancer by examining its associations with breast cancer risk factors and clinicopathological features, and its functional roles in vitro. Tissue microarrays from 313 CAMO cohort breast cancer surgical specimens were constructed, in situ hybridization was performed and miR-20a-5p expression was semiquantitatively scored in tumor stromal fibroblasts, and in the cytoplasm and nuclei of cancer cells. In vitro analysis of the effect of miR-20a-5p transfection on proliferation, migration and invasion was performed in three breast cancer cell lines. High stromal miR-20a-5p was associated with higher Ki67 expression, and higher odds of relapse, compared to low expression. Compared to postmenopausal women, women who were premenopausal at diagnosis had higher odds of high stromal and cytoplasmic miR-20a-5p expression. Cytoplasmic miR-20a-5p was significantly associated with tumor grade. In tumors with high cytoplasmic miR-20a-5p expression compared to low expression, there was a tendency towards having a basal-like subtype and high Ki67. In contrast, high nuclear miR-20a-5p in cancer cells was associated with smaller tumor size and lower odds of lymph node metastasis, compared to low nuclear expression. Transfection with miR-20a-5p in breast cancer cell lines led to increased migration and invasion in vitro. While the majority of our results point towards an oncogenic role, some of our findings indicate that the associations of miR-20a-5p with breast cancer related risk factors and outcomes may vary based on tissue- and subcellular location. Larger studies are needed to validate our findings and further investigate the clinical utility of miR-20a-5p.
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Affiliation(s)
- Eline Sol Tylden
- Department of Medical Biology, Faculty of Health Sciences, UiT The Arctic University of Norway, Tromso, Norway
| | - André Berli Delgado
- Department of Medical Biology, Faculty of Health Sciences, UiT The Arctic University of Norway, Tromso, Norway
| | - Marko Lukic
- Department of Community Medicine, Faculty of Health Sciences, UiT The Arctic University of Norway, Tromso, Norway
| | - Line Moi
- Department of Clinical Pathology, University Hospital of North Norway, Tromso, Norway
| | - Lill-Tove Rasmussen Busund
- Department of Medical Biology, Faculty of Health Sciences, UiT The Arctic University of Norway, Tromso, Norway
- Department of Clinical Pathology, University Hospital of North Norway, Tromso, Norway
| | - Mona Irene Pedersen
- Department of Clinical Medicine, Faculty of Health Sciences, UiT The Arctic University of Norway, Tromso, Norway
| | - Ana Paola Lombardi
- Department of Medical Biology, Faculty of Health Sciences, UiT The Arctic University of Norway, Tromso, Norway
| | - Karina Standahl Olsen
- Department of Community Medicine, Faculty of Health Sciences, UiT The Arctic University of Norway, Tromso, Norway.
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6
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Bartsch SM, Weatherwax C, Leff B, Wasserman MR, Singh RD, Velmurugan K, John DC, Chin KL, O’Shea KJ, Gussin GM, Martinez MF, Heneghan JL, Scannell SA, Shah TD, Huang SS, Lee BY. Modeling Nursing Home Harms From COVID-19 Staff Furlough Policies. JAMA Netw Open 2024; 7:e2429613. [PMID: 39158906 PMCID: PMC11333984 DOI: 10.1001/jamanetworkopen.2024.29613] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/30/2024] [Accepted: 06/28/2024] [Indexed: 08/20/2024] Open
Abstract
Importance Current guidance to furlough health care staff with mild COVID-19 illness may prevent the spread of COVID-19 but may worsen nursing home staffing shortages as well as health outcomes that are unrelated to COVID-19. Objective To compare COVID-19-related with non-COVID-19-related harms associated with allowing staff who are mildly ill with COVID-19 to work while masked. Design, Setting, and Participants This modeling study, conducted from November 2023 to June 2024, used an agent-based model representing a 100-bed nursing home and its residents, staff, and their interactions; care tasks; and resident and staff health outcomes to simulate the impact of different COVID-19 furlough policies over 1 postpandemic year. Exposures Simulating increasing proportions of staff who are mildly ill and are allowed to work while wearing N95 respirators under various vaccination coverage, SARS-CoV-2 transmissibility and severity, and masking adherence. Main Outcomes and Measures The main outcomes were staff and resident COVID-19 cases, staff furlough days, missed care tasks, nursing home resident hospitalizations (related and unrelated to COVID-19), deaths, and costs. Results In the absence of SARS-CoV-2 infection in the study's 100-bed agent-based model, nursing home understaffing resulted in an annual mean (SD) 93.7 (0.7) missed care tasks daily (22.1%), 38.0 (7.6) resident hospitalizations (5.2%), 4.6 (2.2) deaths (0.6%), and 39.7 (19.8) quality-adjusted life years lost from non-COVID-19-related harms, costing $1 071 950 ($217 200) from the Centers for Medicare & Medicaid Services (CMS) perspective and $1 112 800 ($225 450) from the societal perspective. Under the SARS-CoV-2 Omicron variant conditions from 2023 to 2024, furloughing all staff who tested positive for SARS-CoV-2 was associated with a mean (SD) 326.5 (69.1) annual furlough days and 649.5 (95% CI, 593.4-705.6) additional missed care tasks, resulting in 4.3 (95% CI, 2.9-5.9) non-COVID-19-related resident hospitalizations and 0.7 (95% CI, 0.2-1.1) deaths, costing an additional $247 090 (95% CI, $203 160-$291 020) from the CMS perspective and $405 250 (95% CI, $358 550-$451 950) from the societal perspective. Allowing 75% of staff who were mildly ill to work while masked was associated with 5 additional staff and 5 additional resident COVID-19 cases without added COVID-19-related hospitalizations but mitigated staffing shortages, with 475.9 additional care tasks being performed annually, 3.5 fewer non-COVID-19-related hospitalizations, and 0.4 fewer non-COVID-19-related deaths. Allowing staff who were mildly ill to work ultimately saved an annual mean $85 470 (95% CI, $41 210-$129 730) from the CMS perspective and $134 450 (95% CI, $86 370-$182 540) from the societal perspective. These results were robust to increased vaccination coverage, increased nursing home transmission, increased importation of COVID-19 from the community, and failure to mask while working ill. Conclusion and Relevance In this modeling study of staff COVID-19 furlough policies, allowing nursing home staff to work with mild COVID-19 illness was associated with fewer resident harms from staffing shortages and missed care tasks than harms from increased COVID-19 transmission, ultimately saving substantial direct medical and societal costs.
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Affiliation(s)
- Sarah M. Bartsch
- Center for Advanced Technology and Communication in Health, City University of New York Graduate School of Public Health and Health Policy, New York
- Public Health Informatics, Computational, and Operations Research, City University of New York Graduate School of Public Health and Health Policy, New York
- Artificial Intelligence, Modeling, and Informatics for Nutrition Guidance and Systems Center, City University of New York Graduate School of Public Health and Health Policy, New York
| | - Colleen Weatherwax
- Center for Advanced Technology and Communication in Health, City University of New York Graduate School of Public Health and Health Policy, New York
- Public Health Informatics, Computational, and Operations Research, City University of New York Graduate School of Public Health and Health Policy, New York
- Artificial Intelligence, Modeling, and Informatics for Nutrition Guidance and Systems Center, City University of New York Graduate School of Public Health and Health Policy, New York
| | - Bruce Leff
- Division of Geriatric Medicine and Gerontology, The Center for Transformative Geriatric Research, Johns Hopkins School of Medicine, Baltimore, Maryland
| | | | - Raveena D. Singh
- Division of Infectious Diseases, Department of Medicine, University of California Irvine School of Medicine, Irvine
| | - Kavya Velmurugan
- Center for Advanced Technology and Communication in Health, City University of New York Graduate School of Public Health and Health Policy, New York
- Public Health Informatics, Computational, and Operations Research, City University of New York Graduate School of Public Health and Health Policy, New York
- Artificial Intelligence, Modeling, and Informatics for Nutrition Guidance and Systems Center, City University of New York Graduate School of Public Health and Health Policy, New York
| | - Danielle C. John
- Center for Advanced Technology and Communication in Health, City University of New York Graduate School of Public Health and Health Policy, New York
- Public Health Informatics, Computational, and Operations Research, City University of New York Graduate School of Public Health and Health Policy, New York
- New York City Pandemic Response Institute, New York
| | - Kevin L. Chin
- Center for Advanced Technology and Communication in Health, City University of New York Graduate School of Public Health and Health Policy, New York
- Public Health Informatics, Computational, and Operations Research, City University of New York Graduate School of Public Health and Health Policy, New York
- Artificial Intelligence, Modeling, and Informatics for Nutrition Guidance and Systems Center, City University of New York Graduate School of Public Health and Health Policy, New York
| | - Kelly J. O’Shea
- Center for Advanced Technology and Communication in Health, City University of New York Graduate School of Public Health and Health Policy, New York
- Public Health Informatics, Computational, and Operations Research, City University of New York Graduate School of Public Health and Health Policy, New York
- Artificial Intelligence, Modeling, and Informatics for Nutrition Guidance and Systems Center, City University of New York Graduate School of Public Health and Health Policy, New York
| | - Gabrielle M. Gussin
- Division of Infectious Diseases, Department of Medicine, University of California Irvine School of Medicine, Irvine
| | - Marie F. Martinez
- Center for Advanced Technology and Communication in Health, City University of New York Graduate School of Public Health and Health Policy, New York
- Public Health Informatics, Computational, and Operations Research, City University of New York Graduate School of Public Health and Health Policy, New York
- Artificial Intelligence, Modeling, and Informatics for Nutrition Guidance and Systems Center, City University of New York Graduate School of Public Health and Health Policy, New York
| | - Jessie L. Heneghan
- Center for Advanced Technology and Communication in Health, City University of New York Graduate School of Public Health and Health Policy, New York
- Public Health Informatics, Computational, and Operations Research, City University of New York Graduate School of Public Health and Health Policy, New York
- Artificial Intelligence, Modeling, and Informatics for Nutrition Guidance and Systems Center, City University of New York Graduate School of Public Health and Health Policy, New York
| | - Sheryl A. Scannell
- Center for Advanced Technology and Communication in Health, City University of New York Graduate School of Public Health and Health Policy, New York
- Public Health Informatics, Computational, and Operations Research, City University of New York Graduate School of Public Health and Health Policy, New York
- Artificial Intelligence, Modeling, and Informatics for Nutrition Guidance and Systems Center, City University of New York Graduate School of Public Health and Health Policy, New York
| | - Tej D. Shah
- Center for Advanced Technology and Communication in Health, City University of New York Graduate School of Public Health and Health Policy, New York
- Public Health Informatics, Computational, and Operations Research, City University of New York Graduate School of Public Health and Health Policy, New York
- Artificial Intelligence, Modeling, and Informatics for Nutrition Guidance and Systems Center, City University of New York Graduate School of Public Health and Health Policy, New York
| | - Susan S. Huang
- Division of Infectious Diseases, Department of Medicine, University of California Irvine School of Medicine, Irvine
| | - Bruce Y. Lee
- Center for Advanced Technology and Communication in Health, City University of New York Graduate School of Public Health and Health Policy, New York
- Public Health Informatics, Computational, and Operations Research, City University of New York Graduate School of Public Health and Health Policy, New York
- Artificial Intelligence, Modeling, and Informatics for Nutrition Guidance and Systems Center, City University of New York Graduate School of Public Health and Health Policy, New York
- New York City Pandemic Response Institute, New York
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7
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Lee BY, Pavilonis B, John DC, Heneghan J, Bartsch SM, Kavouras I. The Need to Focus More on Climate Change Communication and Incorporate More Systems Approaches. JOURNAL OF HEALTH COMMUNICATION 2024; 29:1-10. [PMID: 38831666 DOI: 10.1080/10810730.2024.2361566] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/05/2024]
Abstract
Society is at an inflection point-both in terms of climate change and the amount of data and computational resources currently available. Climate change has been a catastrophe in slow motion with relationships between human activity, climate change, and the resulting effects forming a complex system. However, to date, there has been a general lack of urgent responses from leaders and the general public, despite urgent warnings from the scientific community about the consequences of climate change and what can be done to mitigate it. Further, misinformation and disinformation about climate change abound. A major problem is that there has not been enough focus on communication in the climate change field. Since communication itself involves complex systems (e.g. information users, information itself, communications channels), there is a need for more systems approaches to communication about climate change. Utilizing systems approaches to really understand and anticipate how information may be distributed and received before communication has even occurred and adjust accordingly can lead to more proactive precision climate change communication. The time has come to identify and develop more effective, tailored, and precise communication for climate change.
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Affiliation(s)
- Bruce Y Lee
- New York City Pandemic Response Institute (PRI), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Artificial Intelligence, Modeling, and Informatics, for Nutrition Guidance and Systems (AIMINGS) Center, CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
| | - Brian Pavilonis
- New York City Pandemic Response Institute (PRI), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
| | - Danielle C John
- New York City Pandemic Response Institute (PRI), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
| | - Jessie Heneghan
- Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Artificial Intelligence, Modeling, and Informatics, for Nutrition Guidance and Systems (AIMINGS) Center, CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
| | - Sarah M Bartsch
- Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Artificial Intelligence, Modeling, and Informatics, for Nutrition Guidance and Systems (AIMINGS) Center, CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
| | - Ilias Kavouras
- New York City Pandemic Response Institute (PRI), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
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8
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Heneghan J, John DC, Bartsch SM, Piltch-Loeb R, Gilbert C, Kass D, Chin KL, Dibbs A, Shah TD, O'Shea KJ, Scannell SA, Martinez MF, Lee BY. A Systems Map of the Challenges of Climate Communication. JOURNAL OF HEALTH COMMUNICATION 2024; 29:77-88. [PMID: 38845202 PMCID: PMC11414781 DOI: 10.1080/10810730.2024.2361842] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2024]
Abstract
Over the past sixty years, scientists have been warning about climate change and its impacts on human health, but evidence suggests that many may not be heeding these concerns. This raises the question of whether new communication approaches are needed to overcome the unique challenges of communicating what people can do to slow or reverse climate change. To better elucidate the challenges of communicating about the links between human activity, climate change and its effects, and identify potential solutions, we developed a systems map of the factors and processes involved based on systems mapping sessions with climate change and communication experts. The systems map revealed 27 communication challenges such as "Limited information on how individual actions contribute to collective human activity," "Limited information on how present activity leads to long-term effects," and "Difficult to represent and communicate complex relationships." The systems map also revealed several themes among the identified challenges that exist in communicating about climate change, including a lack of available data and integrated databases, climate change disciplines working in silos, a need for a lexicon that is easily understood by the public, and the need for new communication strategies to describe processes that take time to manifest.
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Affiliation(s)
- Jessie Heneghan
- Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Artificial Intelligence, Modeling, and Informatics, for Nutrition Guidance and Systems (AIMINGS) Center, CUNY Graduate School of Public Health and Health Policy, New York City, USA
| | - Danielle C John
- Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Pandemic Response Institute, New York City, New York, USA
| | - Sarah M Bartsch
- Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Artificial Intelligence, Modeling, and Informatics, for Nutrition Guidance and Systems (AIMINGS) Center, CUNY Graduate School of Public Health and Health Policy, New York City, USA
| | - Rachael Piltch-Loeb
- Environmental, Occupational, and Geospatial Health Sciences, City University of New York Graduate School of Public Health and Health Policy, New York City, New York, USA
| | - Christine Gilbert
- School of Communication & Journalism, Stony Brook University, Stony Brook, New York, USA
- Alan Alda Center for Communicating Science, Stony Brook University, Stony Brook, New York, USA
- School of Marine and Atmospheric Sciences, Stony Brook University, Stony Brook, New York, USA
| | - Dan Kass
- Vital Strategies, New York, New York, USA
| | - Kevin L Chin
- Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Artificial Intelligence, Modeling, and Informatics, for Nutrition Guidance and Systems (AIMINGS) Center, CUNY Graduate School of Public Health and Health Policy, New York City, USA
| | - Alexis Dibbs
- Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Artificial Intelligence, Modeling, and Informatics, for Nutrition Guidance and Systems (AIMINGS) Center, CUNY Graduate School of Public Health and Health Policy, New York City, USA
| | - Tej D Shah
- Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Artificial Intelligence, Modeling, and Informatics, for Nutrition Guidance and Systems (AIMINGS) Center, CUNY Graduate School of Public Health and Health Policy, New York City, USA
| | - Kelly J O'Shea
- Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Artificial Intelligence, Modeling, and Informatics, for Nutrition Guidance and Systems (AIMINGS) Center, CUNY Graduate School of Public Health and Health Policy, New York City, USA
| | - Sheryl A Scannell
- Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Artificial Intelligence, Modeling, and Informatics, for Nutrition Guidance and Systems (AIMINGS) Center, CUNY Graduate School of Public Health and Health Policy, New York City, USA
| | - Marie F Martinez
- Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Artificial Intelligence, Modeling, and Informatics, for Nutrition Guidance and Systems (AIMINGS) Center, CUNY Graduate School of Public Health and Health Policy, New York City, USA
| | - Bruce Y Lee
- Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Artificial Intelligence, Modeling, and Informatics, for Nutrition Guidance and Systems (AIMINGS) Center, CUNY Graduate School of Public Health and Health Policy, New York City, USA
- Pandemic Response Institute, New York City, New York, USA
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9
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Pronk NP, Lee BY. Qualitative systems mapping in promoting physical activity and cardiorespiratory fitness: Perspectives and recommendations. Prog Cardiovasc Dis 2024; 83:43-48. [PMID: 38431224 DOI: 10.1016/j.pcad.2024.02.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/25/2024] [Accepted: 02/25/2024] [Indexed: 03/05/2024]
Abstract
The purpose of this report is to provide a perspective on the use of qualitative systems mapping, provide examples of physical activity (PA) systems maps, discuss the role of PA systems mapping in the context of iterative learning to derive breakthrough interventions, and provide actionable recommendations for future work. Systems mapping methods and applications for PA are emerging in the scientific literature in the study of complex health issues and can be used as a prelude to mathematical/computational modeling where important factors and relationships can be elucidated, data needs can be prioritized and guided, interventions can be tested and (co)designed, and metrics and evaluations can be developed. Examples are discussed that describe systems mapping based on Group Model Building or literature reviews. Systems maps are highly informative, illustrate multiple components to address PA and physical inactivity issues, and make compelling arguments against single intervention action. No studies were identified in the literature scan that considered cardiorespiratory fitness the focal point of a systems maps. Recommendations for future research and education are presented and it is concluded that systems mapping represents a valuable yet underutilized tool for visualizing the complexity of PA promotion.
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Affiliation(s)
- Nicolaas P Pronk
- HealthPartners Institute, 8170 33(rd) Avenue South, Bloomington, MN 55425, USA; Department of Health Policy and Management, University of Minnesota, 420 Delaware St SE, Minneapolis, MN 55455, USA.
| | - Bruce Y Lee
- Center for Advanced Technology and Communication in Health (CATCH) and PIHCOR, Graduate School of Public Health and Health Policy, City University of New York (CUNY), New York, NY, USA
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10
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Fotie J, Matherne CM, Wroblewski JE. Silicon switch: Carbon-silicon Bioisosteric replacement as a strategy to modulate the selectivity, physicochemical, and drug-like properties in anticancer pharmacophores. Chem Biol Drug Des 2023; 102:235-254. [PMID: 37029092 DOI: 10.1111/cbdd.14239] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Revised: 03/19/2023] [Accepted: 03/21/2023] [Indexed: 04/09/2023]
Abstract
Bioisosterism is one of the leading strategies in medicinal chemistry for the design and modification of drugs, consisting in replacing an atom or a substituent with a different atom or a group with similar chemical properties and an inherent biocompatibility. The objective of such an exercise is to produce a diversity of molecules with similar behavior while enhancing the desire biological and pharmacological properties, without inducing significant changes to the chemical framework. In drug discovery and development, the optimization of the absorption, distribution, metabolism, elimination, and toxicity (ADMETox) profile is of paramount importance. Silicon appears to be the right choice as a carbon isostere because they possess very similar intrinsic properties. However, the replacement of a carbon by a silicon atom in pharmaceuticals has proven to result in improved efficacy and selectivity, while enhancing physicochemical properties and bioavailability. The current review discusses how silicon has been strategically introduced to modulate drug-like properties of anticancer agents, from a molecular design strategy, biological activity, computational modeling, and structure-activity relationships perspectives.
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Affiliation(s)
- Jean Fotie
- Department of Chemistry and Physics, Southeastern Louisiana University, Hammond, Louisiana, USA
| | - Caitlyn M Matherne
- Department of Chemistry and Physics, Southeastern Louisiana University, Hammond, Louisiana, USA
| | - Jordan E Wroblewski
- Department of Chemistry and Physics, Southeastern Louisiana University, Hammond, Louisiana, USA
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11
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Lee BY, Greene D, Scannell SA, McLaughlin C, Martinez MF, Heneghan JL, Chin KL, Zheng X, Li R, Lindenfeld L, Bartsch SM. The Need for Systems Approaches for Precision Communications in Public Health. JOURNAL OF HEALTH COMMUNICATION 2023; 28:13-24. [PMID: 37390012 PMCID: PMC10373800 DOI: 10.1080/10810730.2023.2220668] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/02/2023]
Abstract
A major challenge in communicating health-related information is the involvement of multiple complex systems from the creation of the information to the sources and channels of dispersion to the information users themselves. To date, public health communications approaches have often not adequately accounted for the complexities of these systems to the degree necessary to have maximum impact. The virality of COVID-19 misinformation and disinformation has brought to light the need to consider these system complexities more extensively. Unaided, it is difficult for humans to see and fully understand complex systems. Luckily, there are a range of systems approaches and methods, such as systems mapping and systems modeling, that can help better elucidate complex systems. Using these methods to better characterize the various systems involved in communicating public health-related information can lead to the development of more tailored, precise, and proactive communications. Proceeding in an iterative manner to help design, implement, and adjust such communications strategies can increase impact and leave less opportunity for misinformation and disinformation to spread.
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Affiliation(s)
- Bruce Y. Lee
- Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA
- New York City Pandemic Response Institute (PRI), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA
| | - Danielle Greene
- New York City Pandemic Response Institute (PRI), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA
| | - Sheryl A. Scannell
- Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA
- New York City Pandemic Response Institute (PRI), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA
| | - Christopher McLaughlin
- New York City Pandemic Response Institute (PRI), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA
| | - Marie F. Martinez
- Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA
- New York City Pandemic Response Institute (PRI), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA
| | - Jessie L. Heneghan
- Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA
- New York City Pandemic Response Institute (PRI), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA
| | - Kevin L. Chin
- Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA
- New York City Pandemic Response Institute (PRI), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA
| | - Xia Zheng
- School of Communication & Journalism, Stony Brook University, Stony Brook, NY, USA
- Alan Alda Center for Communicating Science, Stony Brook University, Stony Brook, NY, USA
| | - Ruobing Li
- School of Communication & Journalism, Stony Brook University, Stony Brook, NY, USA
- Alan Alda Center for Communicating Science, Stony Brook University, Stony Brook, NY, USA
| | - Laura Lindenfeld
- School of Communication & Journalism, Stony Brook University, Stony Brook, NY, USA
- Alan Alda Center for Communicating Science, Stony Brook University, Stony Brook, NY, USA
| | - Sarah M. Bartsch
- Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA
- New York City Pandemic Response Institute (PRI), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA
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12
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Pronk NP, Mabry PL, Bond S, Arena R, Faghy MA. Systems science approaches to cardiovascular disease prevention and management in the era of COVID-19: A Humpty-Dumpty dilemma? Prog Cardiovasc Dis 2023; 76:69-75. [PMID: 36563922 PMCID: PMC9764826 DOI: 10.1016/j.pcad.2022.12.003] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/11/2022] [Accepted: 12/11/2022] [Indexed: 12/24/2022]
Abstract
The coronavirus disease 2019 (COVID-19) pandemic necessitated the implementation and prioritizing of strict public health strategies to mitigate COVID-19 transmission and infection over all else. As we enter a 'recovery' phase in which the impact of the virus recedes (but does not relent), we ask, "How do we develop a game plan that considers prevention over management of public health threats of a more chronic nature, including cardiovascular disease?" We frame this choice point as a "Humpty-Dumpty" moment for public health with enduring and potentially irreversible consequences. Citing clear examples of other public health successes and failures, we outline in detail how sustaining cardiovascular population health under complex post-pandemic conditions will necessitate decision-making to be informed with a systems science approach, in which interventions, goals, outcomes and features of complex systems are carefully aligned.
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Affiliation(s)
- Nicolaas P Pronk
- HealthPartners Institute, Minneapolis, MN, USA; Department of Health Policy and Management, University of Minnesota, Minneapolis, MN, USA; Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Healthy Living for Pandemic Event Protection (HL-PIVOT) Network, Chicago, IL, USA.
| | | | - Sam Bond
- Department of Biomedical and Health Information Sciences, University of Illinois at Chicago, Chicago, USA; Healthy Living for Pandemic Event Protection (HL-PIVOT) Network, Chicago, IL, USA
| | - Ross Arena
- Healthy Living for Pandemic Event Protection (HL-PIVOT) Network, Chicago, IL, USA; Department of Physical Therapy, College of Applied Health Sciences, University of Illinois at Chicago, USA
| | - Mark A Faghy
- Healthy Living for Pandemic Event Protection (HL-PIVOT) Network, Chicago, IL, USA; Department of Physical Therapy, College of Applied Health Sciences, University of Illinois at Chicago, USA; Biomedical Research Theme, School of Human Sciences, University of Derby, UK
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13
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Lee BY, Ordovás JM, Parks EJ, Anderson CAM, Barabási AL, Clinton SK, de la Haye K, Duffy VB, Franks PW, Ginexi EM, Hammond KJ, Hanlon EC, Hittle M, Ho E, Horn AL, Isaacson RS, Mabry PL, Malone S, Martin CK, Mattei J, Meydani SN, Nelson LM, Neuhouser ML, Parent B, Pronk NP, Roche HM, Saria S, Scheer FAJL, Segal E, Sevick MA, Spector TD, Van Horn L, Varady KA, Voruganti VS, Martinez MF. Research gaps and opportunities in precision nutrition: an NIH workshop report. Am J Clin Nutr 2022; 116:1877-1900. [PMID: 36055772 PMCID: PMC9761773 DOI: 10.1093/ajcn/nqac237] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2021] [Revised: 04/06/2022] [Accepted: 08/30/2022] [Indexed: 02/01/2023] Open
Abstract
Precision nutrition is an emerging concept that aims to develop nutrition recommendations tailored to different people's circumstances and biological characteristics. Responses to dietary change and the resulting health outcomes from consuming different diets may vary significantly between people based on interactions between their genetic backgrounds, physiology, microbiome, underlying health status, behaviors, social influences, and environmental exposures. On 11-12 January 2021, the National Institutes of Health convened a workshop entitled "Precision Nutrition: Research Gaps and Opportunities" to bring together experts to discuss the issues involved in better understanding and addressing precision nutrition. The workshop proceeded in 3 parts: part I covered many aspects of genetics and physiology that mediate the links between nutrient intake and health conditions such as cardiovascular disease, Alzheimer disease, and cancer; part II reviewed potential contributors to interindividual variability in dietary exposures and responses such as baseline nutritional status, circadian rhythm/sleep, environmental exposures, sensory properties of food, stress, inflammation, and the social determinants of health; part III presented the need for systems approaches, with new methods and technologies that can facilitate the study and implementation of precision nutrition, and workforce development needed to create a new generation of researchers. The workshop concluded that much research will be needed before more precise nutrition recommendations can be achieved. This includes better understanding and accounting for variables such as age, sex, ethnicity, medical history, genetics, and social and environmental factors. The advent of new methods and technologies and the availability of considerably more data bring tremendous opportunity. However, the field must proceed with appropriate levels of caution and make sure the factors listed above are all considered, and systems approaches and methods are incorporated. It will be important to develop and train an expanded workforce with the goal of reducing health disparities and improving precision nutritional advice for all Americans.
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Affiliation(s)
- Bruce Y Lee
- Health Policy and Management, City University of New York Graduate School of Public Health and Health Policy, New York, NY, USA
| | - José M Ordovás
- USDA-Human Nutrition Research Center on Aging at Tufts University, Boston, MA, USA
| | - Elizabeth J Parks
- Nutrition and Exercise Physiology, University of Missouri School of Medicine, MO, USA
| | | | - Albert-László Barabási
- Network Science Institute and Department of Physics, Northeastern University, Boston, MA, USA
| | | | - Kayla de la Haye
- Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Valerie B Duffy
- Allied Health Sciences, University of Connecticut, Storrs, CT, USA
| | - Paul W Franks
- Novo Nordisk Foundation, Hellerup, Denmark, Copenhagen, Denmark, and Lund University Diabetes Center, Sweden
- The Lund University Diabetes Center, Malmo, SwedenInsert Affiliation Text Here
| | - Elizabeth M Ginexi
- National Institutes of Health, Office of Behavioral and Social Sciences Research, Bethesda, MD, USA
| | - Kristian J Hammond
- Computer Science, Northwestern University McCormick School of Engineering, IL, USA
| | - Erin C Hanlon
- Department of Medicine, The University of Chicago, Chicago, IL, USA
| | - Michael Hittle
- Epidemiology and Clinical Research, Stanford University, Stanford, CA, USA
| | - Emily Ho
- Public Health and Human Sciences, Linus Pauling Institute, Oregon State University, Corvallis, OR, USA
| | - Abigail L Horn
- Information Sciences Institute, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA
| | | | | | - Susan Malone
- Rory Meyers College of Nursing, New York University, New York, NY, USA
| | - Corby K Martin
- Ingestive Behavior Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA, USA
| | - Josiemer Mattei
- Nutrition, Harvard TH Chan School of Public Health, Boston, MA, USA
| | - Simin Nikbin Meydani
- USDA-Human Nutrition Research Center on Aging at Tufts University, Boston, MA, USA
| | - Lorene M Nelson
- Epidemiology and Population Health, Stanford University, Stanford, CA, USA
| | | | - Brendan Parent
- Grossman School of Medicine, New York University, New York, NY, USA
| | | | - Helen M Roche
- UCD Conway Institute, School of Public Health, Physiotherapy, and Sports Science, University College Dublin, Dublin, Ireland
| | - Suchi Saria
- Johns Hopkins University, Baltimore, MD, USA
| | - Frank A J L Scheer
- Brigham and Women's Hospital, Boston, MA, USA
- Medicine and Neurology, Harvard Medical School, Boston, MA, USA
| | - Eran Segal
- Computer Science and Applied Math, Weizmann Institute of Science, Rehovot, Israel
| | - Mary Ann Sevick
- Grossman School of Medicine, New York University, New York, NY, USA
| | - Tim D Spector
- Twin Research and Genetic Epidemiology, King's College London, London, United Kingdom
| | - Linda Van Horn
- Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Krista A Varady
- Kinesiology and Nutrition, University of Illinois at Chicago, Chicago, IL, USA
| | - Venkata Saroja Voruganti
- Nutrition and Nutrition Research Institute, Gillings School of Public Health, The University of North Carolina, Chapel Hill, NC, USA
| | - Marie F Martinez
- Health Policy and Management, City University of New York Graduate School of Public Health and Health Policy, New York, NY, USA
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14
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Bright K. Understanding system barriers and facilitators in transnational clinical cancer research: The value of rapid and multimodal ethnographic inquiry. FRONTIERS IN SOCIOLOGY 2022; 7:991183. [PMID: 36530449 PMCID: PMC9751659 DOI: 10.3389/fsoc.2022.991183] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Accepted: 11/16/2022] [Indexed: 06/17/2023]
Abstract
INTRODUCTION In middle and low resource countries worldwide, up to 70% of breast cancer cases are diagnosed as locally advanced (stages IIB-IIIC). Delays in referral from primary to specialty care have been shown to prolong routes to diagnosis and may be associated with higher burdens of advanced disease, but specific clinical and organizational barriers are not well understood. METHODS This article reports on the use of rapid ethnographic research (RER) within a largescale clinical trial for locally advanced breast cancer (LABC) in India, Mexico, South Africa, and the US. Our purpose is twofold. First, we demonstrate the value of ethnography as a mode of evaluative listening: appraising the perspectives of diverse patients and clinicians regarding prolonged routes to LABC diagnosis and treatment. Second, we show the value of ethnography as a compass for navigating among discrepant clinical research styles, IRB protocols, and institutional norms and practices. We discuss advantages and limits involved in each use of RER. RESULTS On the one hand, ethnographic interviews carried out before and during the clinical trial enabled more regular communication among investigators and research sites. On the other hand, the logistics of doing the trial placed limits on the extent and duration of inductive, immersive inquiry characteristic of traditional fieldwork. As a partial solution to this problem, we developed a multimodal ethnographic research (MER) approach, an augmentation of video-chat, phone, text, and email carried out with, and built upon the initial connections established in, the in-person fieldwork. This style has its limits; but it did allow us to materially improve the ways in which the medical research proceeded. DISCUSSION In conclusion, we highlight the value of not deferring to a presumed incommensurability of ethnographic fieldwork and clinical trialwork while still being appropriately responsive to moments when the two approaches should be kept apart.
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Affiliation(s)
- Kristin Bright
- Department of Anthropology, Middlebury College, Middlebury, VT, United States
- Department of Anthropology, University of Toronto, Toronto, ON, Canada
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