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Keshet-Sitton, A., Or-Chen, K., Yitzhak, S., Tzabary, I., & Haim, A. (2016). Light and the City: Breast Cancer Risk Factors Differ Between Urban and Rural Women in Israel. Integr Cancer Ther, 16(2), 176–187.
Abstract: Women are exposed to indoor and outdoor artificial light at night (ALAN) in urban and rural environments. Excessive exposure to hazardous ALAN containing short wavelength light may suppress pineal melatonin production and lead to an increased breast cancer (BC) risk. Our objective was to address the differences in BC risks related to light exposure in urban and rural communities. We examined indoor and outdoor light habits of BC patients and controls that had lived in urban and rural areas in a 5-year period, 10 to 15 years before the time of the study. Individual data, night time sleeping habits and individual exposure to ALAN habits were collected using a questionnaire. A total of 252 women (110 BC patients and 142 controls) participated in this study. The sample was divided to subgroups according to dwelling area and disease status. Age matching was completed between all subgroups. Odds ratios (ORs) with 95% confidence intervals (CIs) were estimated for urban and rural women separately, using binary logistic regression. OR results of urban population (92 BC patients and 72 control) revealed that BC risk increases with daily use of cellphone (OR = 2.13, 95% CI = 1.01-4.49, P < .05) and residence near strong ALAN sources (OR = 1.51, 95% CI = 0.99-2.30, P < .06). Nevertheless, BC risk decreases if a woman was born in Israel (OR = 0.44, 95% CI = 0.21-0.93, P < .03), longer sleep duration (OR = 0.75, 95% CI = 0.53-1.05, P < .1), and reading with bed light illumination before retiring to sleep (OR = 0.77, 95% CI = 0.61-0.96, P < .02). Furthermore, in the rural population (18 BC patients and 66 control) BC risk increases with the number of years past since the last menstruation (OR = 1.12, 95% CI = 1.03-1.22, P < .01). However, BC risk decreases with longer sleep duration (OR = 0.53, 95% CI = 0.24-1.14, P < .1), reading with room light illumination before retiring to sleep (OR = 0.55, 95% CI = 0.29-1.06, P < .07), and sleeping with closed shutters during the night (OR = 0.66, 95% CI = 0.41-1.04, P < .08). These data support the idea that indoor and outdoor nighttime light exposures differ between urban and rural women. Therefore, we suggest that women can influence BC risk and incidence by applying protective personal lighting habits. Further studies with larger sample sizes are needed to strengthen the results.
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Keshet-Sitton, A., Or-Chen, K., Huber, E., & Haim, A. (2016). Illuminating a Risk for Breast Cancer: A Preliminary Ecological Study on the Association Between Streetlight and Breast Cancer. Integr Cancer Ther, .
Abstract: Artificial light at night (ALAN) for elongating photophase is a new source of pollution. We examined the association between measured ALAN levels and breast cancer (BC) standard morbidity ratio (SMR) at a statistical area (SA) level in an urban environment. Sample size consisted of 266 new BC cases ages 35-74. Light measurements (lux) were performed in 11 SAs. A new calculated variable of morbidity per SA size (SMR35-74/km2) was correlated with the light variables per road length, using Pearson correlations (P < .05, 1-tailed). Looking for a light threshold, we correlated percentage of light points above SA light intensity median with SMR35-74/km2 SMR35-74/km2 was significantly and positively strongly correlated with mean, median, and standard-deviation (SD) light intensity per road length (r = .79, P < .01, R2 = .63; r = .77, P < .01, R2 = .59; and r = .79, P < .01, R2 = .63). Light threshold results demonstrate a marginally significant positive moderate correlation between percentage of points above 16.3 lux and SMR35-74/km2 (r = .48, P < .07; R2 = .23). In situ results support the hypothesis that outdoor ALAN illumination is associated with a higher BC-SMR in a specific area and age group. Moreover, we suggest an outdoor light threshold of approximately 16 lux as the minimal intensity to affect melatonin levels and BC morbidity. To the best of our knowledge, our attempt is the first to use this method and show such association between streetlight intensity and BC morbidity and therefore should be further developed.
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DuBose, J. R., & Hadi, K. (2016). Improving inpatient environments to support patient sleep. Int J Qual Health Care, 28(5), 540–553.
Abstract: PURPOSE: Although sleep is important for healing, sleep deprivation is a major concern for patients in hospitals. The purpose of this review is to consolidate the observational and interventional studies that have been done to understand exogenous, non-pharmacological strategies for improving sleep in hospitals. DATA SOURCES: We searched Medline, CINAHL, PsycINFO and the Web of Science databases for peer-reviewed articles published between 1970 and 2015 in English. STUDY SELECTION: A title review of 13,113 articles from four databases resulted in 783 articles that were further culled to 277 based on a review of the abstracts. The net result after reading the articles and a hand search was 42 articles. DATA EXTRACTION: From each article we recorded the independent variables, methods used for measuring sleep and specific sleep outcomes reported. RESULTS OF DATA SYNTHESIS: Noise is a modifiable cause of some sleep disruptions in hospitals, and when reduced can lead to more sleep. Earplugs and eye masks may help, but changing the sound and light environment is more effective. Calming music in the evening has been shown to be effective as well as daytime bright light exposure. Nursing care activities cause sleep disruption, but efforts at limiting interventions have not been demonstrated to improve sleep conditions. CONCLUSION: The research is hard to consolidate due to the multitude of independent variables and outcome metrics, but overall points to the potential for making meaningful improvements in the quality of patient sleep.
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Sharma, R. C., Tateishi, R., Hara, K., Gharechelou, S., & Iizuka, K. (2016). Global mapping of urban built-up areas of year 2014 by combining MODIS multispectral data with VIIRS nighttime light data. International Journal of Digital Earth, , 1–17.
Abstract: An improved methodology for the extraction and mapping of urban built-up areas at a global scale is presented in this study. The Moderate Resolution Imaging Spectroradiometer (MODIS)-based multispectral data were combined with the Visible Infrared Imager Radiometer Suite (VIIRS)-based nighttime light (NTL) data for robust extraction and mapping of urban built-up areas. The MODIS-based newly proposed Urban Built-up Index (UBI) was combined with NTL data, and the resulting Enhanced UBI (EUBI) was used as a single master image for global extraction of urban built-up areas. Due to higher variation of the EUBI with respect to geographical regions, a region-specific threshold approach was used to extract urban built-up areas. This research provided 500-m-resolution global urban built-up map of year 2014. The resulted map was compared with three existing moderate-resolution global maps and one high-resolution map in the United States. The comparative analysis demonstrated finer details of the urban built-up cover estimated by the resultant map.
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Rybnikova, N. A., Haim, A., & Portnov, B. A. (2016). Does artificial light-at-night exposure contribute to the worldwide obesity pandemic? Int J Obes (Lond), 40(5), 815–824.
Abstract: BACKGROUND: Worldwide overweight and obesity rates are on the rise, with about 1 900 billion adults being defined as overweight and about 600 million adults being defined as obese by the World Health Organization (WHO). Increasing exposure to artificial light-at-night (ALAN) may influence body mass, by suppression of melatonin production and disruption of daily rhythms, resulting in physiological or behavioral changes in the human body, and may thus become a driving force behind worldwide overweight and obesity pandemic. METHODS: We analyzed most recent satellite images of night time illumination, available from the US Defense Meteorological Satellite Program (DMSP), combining them with country-level data on female and male overweight and obesity prevalence rates, reported by the WHO. The study aims to identify and measure the strength of association between ALAN and country-wide overweight and obesity rates, controlling for per capita GDP, level of urbanization, birth rate, food consumption and regional differences. RESULTS: ALAN emerged as a statistically significant and positive predictor of overweight and obesity (t>1.97; P<0.05), helping to explain, together with other factors, about 70% of the observed variation of overweight and obesity prevalence rates among females and males in more than 80 countries worldwide. Regional differences in the strength of association between ALAN and excessive body mass are also noted. CONCLUSIONS: This study is the first population-level study that confirms the results of laboratory research and cohort studies in which ALAN was found to be a contributing factor to excessive body mass in humans.International Journal of Obesity advance online publication, 23 February 2016; doi:10.1038/ijo.2015.255.
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