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Persad-Clem R, Hoerster KD, Romano EFT, Huizar N, Maier KJ. Climate to COVID, global to local, policies to people: a biopsychosocial ecological framework for syndemic prevention and response in behavioral medicine. Transl Behav Med 2022; 12:516-525. [PMID: 35613005 DOI: 10.1093/tbm/ibac021] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
Land development, pollution, and waste have affected natural environments, contributing to hurricanes, wildfires, and pandemic infectious diseases like COVID-19. Globalized corporate food systems that produce ultra-refined foods with low nutritional value contribute to both environmental conditions and health conditions like obesity and undernutrition. This has the greatest impact on communities already suffering from elevated health risks driven by economic inequities rooted in racism. These interacting environmental, health, and social conditions represent a syndemic. We outline practical suggestions to address this syndemic of environmental degradation, pandemic infectious disease, chronic disease, undernutrition, and inequity through research and practice at many levels, including individual behavior, local communities, and regional, national and global policy. Collaboration with communities is central to simultaneously tackling interconnected human and environmental health threats. For example, community-led groups have increased access to healthy food in response to pandemic conditions. Building on behavioral medicine's rich foundation of ecological models, communities have partnered with local researchers to address the needs of equitable public transport and reduction of greenhouse gas emissions through multilevel research and practice. Policymakers, researchers, practitioners, and community members should collaborate with each other and across disciplines to find lasting, multiduty solutions to improve physical, psychosocial, and planetary health.
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Affiliation(s)
- Reema Persad-Clem
- Geisinger Commonwealth School of Medicine, School of Graduate Education, Scranton, PA 18509, USA
| | - Katherine D Hoerster
- VA Puget Sound Healthcare System, Seattle Division, Mental Health Service, Seattle, WA 98108, USA.,Department of Psychiatry and Behavioral Sciences, School of Medicine, University of Washington, Seattle, WA 98195, USA.,Department of Health Systems and Population Health, School of Public Health, University of Washington, Seattle, WA 98195, USA
| | - Evalynn Fae T Romano
- Department of Health Systems and Population Health, School of Public Health, University of Washington, Seattle, WA 98195, USA
| | - Nancy Huizar
- Got Green Seattle, Seattle, WA 98108, USA.,NHuizar Consulting LLC, Seattle, WA 98108, USA
| | - Karl J Maier
- Department of Psychology, Salisbury University, Salisbury, MD 21801, USA
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Tang C, Liu X, He Y, Gao J, Xu Z, Duan J, Yi W, Wei Q, Pan R, Song S, Su H. Association between extreme precipitation and ischemic stroke in Hefei, China: Hospitalization risk and disease burden. THE SCIENCE OF THE TOTAL ENVIRONMENT 2020; 732:139272. [PMID: 32428771 DOI: 10.1016/j.scitotenv.2020.139272] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/14/2020] [Revised: 03/27/2020] [Accepted: 05/05/2020] [Indexed: 06/11/2023]
Abstract
BACKGROUND Ischemic stroke is an acute cardiovascular disease with high disability and mortality. Extreme precipitation has been reported to increase the risk of some cardiovascular diseases and further increase the burden of disease. At present, no studies have evaluated the relationship between extreme precipitation and ischemic stroke. OBJECTIVE The aim of this study was to quantitatively analyze the association between extreme precipitation and ischemic stroke hospitalizations and further explore disease burden and its associated susceptible population. METHODS In this study, we used Poisson generalized linear model combined with distributed lag nonlinear model to investigate the relationship between extreme precipitation (≥95th percentile) and ischemic stroke and further explored the lag effect of extreme precipitation for population with different individual characteristics. RESULTS Ischemic stroke hospitalizations were significantly associated with extreme precipitation. The single-day effect occurred on lag 3 (RR = 1.040, 95% CI: 1.058-1.073) lasted until lag 8 (RR = 1.036, 95% CI: 1.004-1.068). The cumulative lag effects of extreme precipitation on ischemic stroke lasted six days (lag 6-lag 11). Male and people aged ≥65 years were more sensitive to extreme precipitation. The attributable fraction (AF) and numbers (AN) of extreme precipitation on hospitalizations for ischemic stroke were 1.38% and 236.4, respectively. CONCLUSION Our study suggested that extreme precipitation may increase the risk of hospital admissions for ischemic stroke, emphasizing the need for society and families to pay more attention to male and people aged ≥65 years.
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Affiliation(s)
- Chao Tang
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui 230032, China
| | - Xiangguo Liu
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui 230032, China
| | - Yangyang He
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui 230032, China
| | - Jiaojiao Gao
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui 230032, China
| | - Zihan Xu
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui 230032, China
| | - Jun Duan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui 230032, China
| | - Weizhuo Yi
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui 230032, China
| | - Qiannan Wei
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui 230032, China
| | - Rubing Pan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui 230032, China
| | - Shasha Song
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui 230032, China
| | - Hong Su
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui 230032, China.
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