Lambert Kelly G, Nelson Randy J, Jovanovic Tanja, Cerdá Magdalena
Department of Psychology, Randolph-Macon College, Ashland, VA 23005, USA.
Department of Neuroscience, The Ohio State University Wexner Medical Center, Columbus, OH 43210, USA.
Neurosci Biobehav Rev. 2015 Nov;58:107-22. doi: 10.1016/j.neubiorev.2015.04.007. Epub 2015 May 1.
With a majority of humans now living in cities, strategic research is necessary to elucidate the impact of this evolutionarily unfamiliar habitat on neural functions and well-being. In this review, both rodent and human models are considered in the evaluation of the changing physical and social landscapes associated with urban dwellings. Animal models assessing increased exposure to artificial physical elements characteristic of urban settings, as well as exposure to unnatural sources of light for extended durations, are reviewed. In both cases, increased biomarkers of mental illnesses such as major depression have been observed. Additionally, applied human research emphasizing the emotional impact of environmental threats associated with urban habitats is considered. Subjects evaluated in an inner-city hospital reveal the impact of combined specific genetic vulnerabilities and heightened stress responses in the expression of posttraumatic stress disorder. Finally, algorithm-based models of cities have been developed utilizing population-level analyses to identify risk factors for psychiatric illness. Although complex, the use of multiple research approaches, as described herein, results in an enhanced understanding of urbanization and its far-reaching effects--confirming the importance of continued research directed toward the identification of putative risk factors associated with psychiatric illness in urban settings.
如今，大多数人生活在城市中，因此开展战略性研究以阐明这种在进化意义上并不熟悉的栖息地对神经功能和幸福感的影响很有必要。在这篇综述中，我们在评估与城市居住相关的不断变化的自然和社会环境时，考虑了啮齿动物模型和人类模型。本文回顾了评估城市环境中人造自然元素暴露增加以及长时间暴露于非自然光源影响的动物模型。在这两种情况下，均观察到了诸如重度抑郁症等精神疾病的生物标志物增加。此外，还考虑了强调与城市栖息地相关的环境威胁对情绪影响的应用人类研究。在内城医院接受评估的受试者揭示了特定基因易感性与创伤后应激障碍表达中应激反应增强的综合影响。最后，利用人口水平分析开发了基于算法的城市模型，以识别精神疾病的风险因素。尽管很复杂，但如本文所述，使用多种研究方法能够增强我们对城市化及其深远影响的理解——这证实了持续开展研究以识别城市环境中与精神疾病相关的潜在风险因素的重要性。
