Zhong et al. Respond to "There's No Place Like Home".
Zhong et al. Respond to "There's No Place Like Home".
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钟等人。
DOI：
10.1093/aje/kwac085
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发表时间：
2022
影响因子：
5
通讯作者：
Longcore,Travis
中科院分区：
文献类型：
--
作者：
Zhong,Charlie;Franklin,Meredith;Wang,SophiaS;Longcore,Travis
我们赞赏Hauptman等人的评论(1)，强调了在理解环境暴露及其不平等如何导致睡眠中断方面的挑战。最近，人们对睡眠及其缺乏如何影响人类健康的兴趣，导致了几项大型队列研究，如加州教师研究，将这些问题纳入了后续调查问卷。我们同意Hauptman等人的观点。种族平等问题确实需要比我们研究中的更深入的询问(2)；即使在我们的队列中，非西班牙裔白人参与者体验到的夜间人造光(艾伦)、噪音和空气污染水平较低，而绿地水平高于其他人群(表1)。需要不同的人群进一步了解社会和种族差异如何影响光线、绿地、噪音和空气污染水平以及随后的健康影响。卫星图像在评估夜间人造光方面的局限性是众所周知的(3，4)，尽管新的技术和努力，如由亚历杭德罗·S博士(https://citiesatnight.)领导的城市夜间项目正在进行的那些Org/)有助于提高我们在居民层面更准确地估计暴露的能力。重要的是，正如Hauptman等人指出的那样，这些新措施包括评估被认为对昼夜节律最具破坏性的短波长蓝光的能力(4，5)。虽然我们无法评估艾伦在室内的暴露情况，但我们认识到这一问题越来越令人担忧，因为估计85%的美国人现在拥有智能手机(6)。许多智能手机现在包括某种形式的内置、依赖时间的蓝光过滤来解决这些问题，这种过滤似乎确实是一种有效的手段，至少可以部分减少对昼夜节律的干扰。所有种族、民族和社会经济背景的智能手机拥有量的增加，以及最近包括睡眠跟踪功能的智能手表，为在未来的研究中经济高效地包括室内艾伦和睡眠模式的衡量提供了机会。测量室外光线和室内照射之间的相关性，以及室外光线对室内照射的相对贡献，仍然是今后工作的重要重点。这种对基于卫星的暴露指标的验证，特别是在城市形态与农村和郊区环境有很大不同的城市，可能会产生进一步的见解。此外，智能手机应用程序可能会
We appreciate the comments by Hauptman et al.(1) highlighting the challenges in understanding how environmental exposures and their inequities contribute to sleep disruptions. The recent interest in how sleep, and the lack thereof, affects human health has led several large cohort studies, such as the California Teachers Study, to include such questions in follow-up questionnaires. We agree with Hauptman et al. that racial equity issues indeed require further interrogation than present in our study (2); even in in our cohort, non-Hispanic White participants experienced lower levels of artificial light at night (ALAN), noise, and air pollution and higher levels of green space compared with the rest of the cohort (Table 1). Diverse populations are required to further understand how the role that social and racial disparities affect levels of light, green space, noise, and air pollution and subsequent health effects. The limitations of satellite imagery in assessing artificial light at night (ALAN) are well known (3, 4), although new technologies and efforts such as those being undertaken by the Cities at Night project led by Dr. Alejandro Sánchez (https://citiesatnight. org/) are helping to improve our ability to estimate exposure more accurately at the residential level. Importantly, as noted by Hauptman et al., these new measures include the ability to assess short-wavelength blue light, believed to be most disruptive to circadian rhythm (4, 5). While we were unable to assess indoor exposure to ALAN, we recognize that it is of increasing concern, as an estimated 85% of Americans now own a smartphone (6). Many smartphones now include some form of built-in, time-dependent blue light filtering to address these concerns, and such filtering does appear to be an effective means of at least partially reducing disruptions to circadian rhythm (7, 8). The increased prevalence of smartphone ownership across all racial, ethnic, and socioeconomic backgrounds, and more recently smartwatches that include sleep tracking features, provides opportunities to cost effectively include measures of indoor ALAN and sleep patterns in future studies. Measurement of the correlation between outdoor light and indoor exposure, as well as the relative contribution of outdoor light to indoor exposure, remains an important focus for future efforts. Such validation of satellite-based exposure metrics, especially in cities where urban morphology differs substantially from rural and suburban contexts, is likely to yield further insights. In addition, smartphone apps may be