Disaggregating the effects of daytime and nighttime light exposures on obesity, overweight, prostate and breast cancer morbidity worldwide.

Hormone-dependent cancers and overweight/obesity are not necessarily linked but might have similar underlying causes, such as circadian disruption, lack of physical activity, and unhealthy nutrition. Several empirical studies also attribute the rise in these types of morbidity to vitamin D deficiency, linked in turn to insufficient sunlight exposure. Other studies place an emphasis on melatonin (MLT) hormone suppression, associated with artificial light at night (ALAN) exposure. Yet no studies, carried out to date, have attempted to determine which of these environmental risk factors is associated stronger with the morbidity types in question. In this study, we aim to narrow this knowledge gap by analyzing data available for 100+ countries worldwide, while controlling ALAN and solar radiation exposure estimates by several potential confounders, such as GDPpc, GINI inequality index and unhealthy food consumption. As the study reveals, all the morbidity types under analysis are significantly and positively associated with ALAN exposure estimates (p < 0.05), while solar radiation appears to be significantly associated with prostate cancer rates only (p < 0.05), but not with breast cancer or overweight/obesity rates (p > 0.1). To the best of our knowledge, this study is the first that separates the effects of ALAN and daylight exposures on the abovementioned types of morbidity.

Investigating the combined effect of ALAN and noise on sleep by simultaneous real-time monitoring using low-cost smartphone devices.

The association between artificial light at night (ALAN) and noise, on the one hand, and sleep, on the other, is well established. Yet studies investigating these associations have been infrequent and mostly conducted in controlled laboratory conditions. As a result, little is known about the applicability of their results to real-world settings. In this paper, we attempt to bridge this knowledge gap by carrying out an individual-level real-world study, involving 72 volunteers from different urban localities in Israel. The survey participants were asked to use their personal smartphones and smartwatches to monitor sleep patterns for 30 consecutive days, while ALAN and noise exposures were monitored in parallel, with inputs reported each second. The volunteers were also asked to fill in a questionnaire about their individual attributes, daily habits, room settings, and personal health, to serve as individual-level controls. Upon cointegration, the assembled data were co-analyzed using bivariate and multivariate statistical tools. As the study reveals, the effect of ALAN and noise on sleep largely depends on when the exposure occurred, that is, before sleep or during sleep. In particular, the effect of ALAN exposure was found to be most pronounced if it occurred before sleep, while exposure to noise mattered most if it occurred during the sleep phase. As the study also reveals, the effects of ALAN and noise appear to amplify each other, with a 14-15.3% reduction in sleep duration and an 8-9% reduction in sleep efficiency observed at high levels of ALAN-noise exposures. The study helped to assemble a massive amount of real-time observations, enabling a robust individual-level analysis.

Using mobile phones as light at night and noise measurement instruments: a validation test in real world conditions.

Exposure to noise from road traffic and industries is known to be linked to various health dysfunctions, including hypertension, cardiovascular diseases and hearing loss. Exposure to artificial light at night (ALAN) is also increasingly recognized as being associated with ecosystem damage and various illnesses, including cancers, excessive weight gain and sleep disorders. However, measuring and monitoring these environmental risk factors by professional equipment are laborious and expensive, which impede large-scale research and various citizen science initiatives. In this study, we test a possibility that reliable noise and ALAN exposure estimates can be gathered using smartphones (SPs) sensors. To verify this assumption, we develop a standardized testing protocol, and use Andro-Sensor app, installed on three different Samsung Galaxy SPs - S7, S20FE5G, and SM520F, - to perform measurements of ALAN and noise in real-world conditions while comparing these measurements with measurements performed by professional (type 2) equipment - SL814 for noise and LX-1330B for illumination. The analysis of 3450 measurements, performed in two different locations in Israel, reveals that the SPs measurements and measurements performed by control instruments correlate strongly for noise (r = 0.76-0.94) and are nearly identical for ALAN (r = 0.998-0.999). The association between the two types of measurements is also found to be close to linear, with the slope of the trend line being close to 45° for ALAN and varying between 30° and 45° for noise, depending on the SPs used. Our conclusion is that the level of accuracy of ALAN measurements by SPs is greater for ALAN than for noise, which can make SPs a useful tool for large-scale ALAN studies that do not require the accuracy of professional instruments.

Assessing the impacts of ALAN and noise proxies on sleep duration and quality: evidence from a nation-wide survey in Israel.

Sleep is a reversible state that sustains physiological and psychological processes in humans. As well established, individual-level factors, such as stress, smoking, drugs, and caffeine intake, reduce sleep duration and quality. However, studies of the effect of environmental risk factors, such as artificial light at night (ALAN) and noise, on sleep have been infrequent. Using records obtained from the 2017 Social Survey of Israel and combined with ALAN satellite data and various proxies for traffic noise, the present study aimed to determine how the combination of ALAN and traffic noise impact sleep duration and quality in urban areas. The increase of road density at the place of residence reduces average sleep duration by ~4.5% (~18 min.) and increases the frequency of reported sleep difficulties by ~3.5%, all other factors held equal. Similarly, an increase in ALAN exposure reduces average sleep duration by ~3% (~12 min) and increases the frequency of reported sleep difficulties by ~11%. The study also reveals a significant interaction between the two environmental risk factors in question, with the adverse impact of ALAN on sleep quality especially pronounced in high noise exposure areas.