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.

Linking nighttime outdoor lighting attributes to pedestrians' feeling of safety: An interactive survey approach.

Public space lighting (PSL) contributes to pedestrians' feeling of safety (FoS) in urban areas after natural dark. However, little is known how different PSL attributes, such as illuminance, light temperature, uniformity and glare, affect people's FoS in different contextual settings. The present study aims to bridge this knowledge gap by developing a model linking different PSL attributes with FoS, while controlling for individual, locational, environmental and temporal factors. To develop such model, the study employs a novel interactive user-oriented method, based on a specially-designed mobile phone application-CityLightsTM. Using this app, a representative sample of observers reported their impressions of PSL attributes and FoS in three cities in Israel, following a set of predetermined routes and points. As the study shows, higher levels of illumination and uniformity positively affect FoS, while lights perceived as warm tend to generate higher FoS than lights perceived as cold. These findings may guide future illumination polices aimed at promoting energy efficiency while ensuring urban sustainability.

Characterization of Localities with a High Likelihood of Illicit Connections between Runoff and Sewage Systems.

Flooding of the sewage system is an environmental hazard often caused by illegal connections between drainage and sewage systems. The timely detection of such illicit connections, often done by property owners in an attempt to remove rainwater promptly from their private courtyards, is a complex task due to the high cost of field surveying and limited manpower of environmental law-enforcement authorities. This paper suggests an empirical approach to the identification and characterization of localities with an elevated likelihood of illegal connections between runoff and sewage systems. The proposed approach is implemented in three stages. First, the association between rainfall and the amount of wastewater arriving to sewage treatment facilities from different localities is analyzed. Next, regression residuals are investigated, to identify localities with an especially strong association between the amount of rainfall and sewage surplus. The identified localities are then analyzed, to determine their geographic location, physical and socioeconomic attributes. In the present study, the proposed approach is tested using data for 623 urban and rural localities in Israel. As the study shows, the probability of association between the amount of rainfall and sewage surplus, which we consider as an indicator of pirate connections between drainage and sewage systems, tends to increase as a function of socioeconomic welfare of the local residents, surface slope, and the level of urbanization. The proposed approach can help law-enforcement authorities to focus their efforts on specific locations and to reduce economic and environmental damages associated with illegal connections between drainage and sewage systems.

Forecasting health effects potentially associated with the relocation of a major air pollution source.

Epidemiological studies often focus on risk assessments associated with exposures to specific air pollutants or proximity to different air pollution sources. Although this information is essential for devising informed health policies, it is not always helpful when it comes to the estimation of potential health effects associated with the introduction or relocation of local health hazards. In this paper, we suggest a novel approach to forecasting the morbidity-reduction impact of hypothetical removal of a major air pollution source from a densely populated urban area. The proposed approach is implemented in three stages. First, we identify and measure the strength of association of individual environmental factors with local morbidity patterns. Next, we use the estimated models to simulate the impact of removal of the pollution source under analysis and its replacement by green areas. Using this assessment, we then estimate potential changes in the local morbidity rates by mutually comparing the observed risk surface of disease with the risk surface simulated by modelling. To validate the proposed approach empirically, we use childhood asthma morbidity data available for a major metropolitan area in Israel, which hosts a large petrochemical complex. According to our estimates, relocation of the petrochemical complex in question is expected to result in about 70% drop in the childhood asthma morbidity rate area-wide. To the best of our knowledge, the present study is the first that suggests an operational approach to incorporating epidemiological assessments as an input for urban development plans related to local sources of air pollution.

Estimating the effectiveness of different environmental law enforcement policies on illegal C&D waste dumping in Israel.

Illegal dumping of construction and demolition (C&D) waste is a major concern for environmental policy-makers. Three different environmental law enforcement policies, aimed at the reduction of illegal C&D waste dumping, are enforced in Israel. These policies include fines (F), vehicle impoundment (V), and criminal indictment (I) by the court. Although, the scope of illegal C&D waste dumping in Israel appears to decline, little is known which of the above policies has been effective in combating the phenomenon. In an attempt to answer this question, we use data on F-V-I instances, recorded between July 2007 and December 2016, and compare them with monthly changes in the ratio between the amount of waste brought to authorized waste dumping sites and the estimated amount of C&D waste generated in the country each month. As the study shows, only the V-sanction was found to be significantly affecting the ratio (t = 3.083; p < 0.01), while the effect of other policy was found insignificant. We explain low efficiency of other law enforcement policies by relatively small fines imposed on the offenders, long court proceedings, combined with a relatively low chance of being caught. By contrast, the V-sanction may be more effective because it results in immediate and severe economic losses to the offenders, causing C&D waste transporters to haul their load to authorized sites. As we argue, for an environmental enforcement policy to be effective, it should be adequate to the severity of the offense and applied swiftly.

Prevalence of Asthma among Young Men Residing in Urban Areas with Different Sources of Air Pollution.

BACKGROUND: Asthma is a common respiratory disease, which is linked to air pollution. However, little is known about the effect of specific air pollution sources on asthma occurrence. OBJECTIVES: To assess individual asthma risk in three urban areas in Israel characterized by different primary sources of air pollution: predominantly traffic-related air pollution (Tel Aviv) or predominantly industrial air pollution (Haifa bay area and Hadera). METHODS: The medical records of 13,875, 16- 19-year-old males, who lived in the affected urban areas prior to their army recruitment and who underwent standard pre-military health examinations during 2012-2014, were examined. Nonparametric tests were applied to compare asthma prevalence, and binary logistic regressions were used to assess the asthma risk attributed to the residential locations of the subjects, controlling for confounders, such as socio-demographic status, body mass index, cognitive abilities, and education. RESULTS: The asthma rate among young males residing in Tel Aviv was 8.76%, compared to 6.96% in the Haifa bay area and 6.09% in Hadera. However, no statistically significant differences in asthma risk among the three urban areas was found in controlled logistic regressions (P > 0.20). This finding indicates that exposure to both industrial- and traffic-related air pollution is associated with asthma prevalence. CONCLUSIONS: Both industrial- and traffic-related air pollution have a negative effect on asthma risk in young males. Studies evaluating the association between asthma risk and specific air pollutants (e.g., sulfur dioxide, particulate matter, and nitrogen dioxide) are needed to ascertain the effects of individual air pollutants on asthma occurrence.

Spatial identification of environmental health hazards potentially associated with adverse birth outcomes.

Reduced birth weight (RBW) and reduced head circumference (RHC) are adverse birth outcomes (ABOs), often linked to environmental exposures. However, spatial identification of specific health hazards, associated with these ABOs, is not always straightforward due to presence of multiple health hazards and sources of air pollution in urban areas. In this study, we test a novel empirical approach to the spatial identification of environmental health hazards potentially associated with the observed RHC and RBW patterns. The proposed approach is implemented as a systematic search, according to which alternative candidate locations are ranked based on the strength of association with the observed birth outcome patterns. For empirical validation, we apply this approach to the Haifa Bay Area (HBA) in Israel, which is characterized by multiple health hazards and numerous sources of air pollution. We identified a spot in the local industrial zone as the main risk source associated with the observed RHC and RBW patterns. Multivariate regressions, controlling for personal, neighborhood, and geographic factors, revealed that the relative risks of RHC and RBW tend to decline, other things being equal, as a function of distance from the identified industrial spot. We recommend the proposed identification approach as a preliminary risk assessment tool for environmental health studies, in which detailed information on specific sources of air pollution and air pollution dispersion patterns is unavailable due to limited reporting or insufficient monitoring.

Kernel density analysis reveals a halo pattern of breast cancer incidence in Connecticut.

Breast cancer (BC) incidence rates in Connecticut are among the highest in the United States, and are unevenly distributed within the state. Our goal was to determine whether artificial light at night (ALAN) played a role. Using BC records obtained from the Connecticut Tumor Registry, we applied the double kernel density (DKD) estimator to produce a continuous relative risk surface of a disease throughout the State. A multi-variate analysis compared DKD and census track estimates with population density, fertility rate, percent of non-white population, population below poverty level, and ALAN levels. The analysis identified a "halo" geographic pattern of BC incidence, with the highest rates of the disease observed at distances 5-15 km from the state's major cities. The "halo" was of high-income communities, with high ALAN, located in suburban fringes of the state's main cities.

Population-level study links short-wavelength nighttime illumination with breast cancer incidence in a major metropolitan area.

Several population-level studies revealed a positive association between breast cancer (BC) incidence and artificial light at night (ALAN) exposure. However, the effect of short-wavelength illumination, implicated by laboratory research and small-scale cohort studies as the main driving force behind BC-ALAN association, has not been supported by any population-level study carried out to date. We investigated a possible link between BC and ALAN of different subspectra using a multi-spectral year-2011 satellite image, taken from the International Space Station, and superimposing it with year-2013 BC incidence data available for the Great Haifa Metropolitan Area in Israel. The analysis was performed using both ordinary least square (OLS) and spatial dependency models, controlling for socioeconomic and locational attributes of the study area. The study revealed strong associations between BC and blue and green light subspectra (B = 0.336 ± 0.001 and B = 0.335 ± 0.002, respectively; p < 0.01), compared to a somewhat weaker effect for the red subspectrum (B = 0.056 ± 0.001; p < 0.01). However, spatial dependency models, controlling for spatial autocorrelation of regression residuals, confirmed only a positive association between BC incidence and short-wavelength (blue) ALAN subspectrum (z = 2.462, p < 0.05) while reporting insignificant associations between BC and either green (z = 1.425, p > 0.1) or red (z = -0.604, p > 0.1) subspectra. The obtained result is in line with the results of laboratory- and small-scale cohort studies linking short-wavelength nighttime illumination with circadian disruption and melatonin suppression. The detected effect of blue lights on BC incidence may help to develop informed illumination policies aimed at minimizing the adverse health effects of ALAN exposure on human health.

Environmental risk factors associated with low birth weight: The case study of the Haifa Bay Area in Israel.

BACKGROUND: Low birth weight (LBW) is known to be associated with infant mortality and postnatal health complications. Previous studies revealed strong relationships between LBW rate and several socio-demographic factors, including ethnicity, maternal age, and family income. However, studies of association between LBW rate and environmental risk factors remain infrequent. STUDY METHODS: We retrieved a geo-referenced data set, containing 7216 individual records of children born in 2015 in the Haifa Bay Area in Israel. Using this dataset, we analysed factors affecting LBW prevalence by applying two alternative techniques: analysis of LBW rates in small census area (SCAs) and more recently developed double kernel density (DKD) relative risk (RR) estimates. RESULTS: In the SCA models, LBW rate was found to be associated with proximity to petrochemical industries (B=-0.26, 95%CI=-0.30, -0.22), road density (B=0.05, 95%CI=0.02, 0.08), distance to the seashore (B=0.17, 95%CI=0.14, 0.22), PM2.5 (B=0.06, 95%CI=0.04, 0.09) and NOx (B=0.10, 95%CI=0.06, 0.13) exposure estimates. Although similar factors emerged in the DKD models as well, in most cases, the effects of these factors in the latter models were found to be stronger: proximity to petrochemical industries (B=-0.48, 95%CI= -0.51, -0.30), road density (B=0.05, 95%CI=0.02, 0.08), distance to the seashore (B=0.24, 95%CI=0.21, 0.27), PM2.5 (B=0.08, 95%CI=0.05, 0.10) and NOx (B=0.20, 95%CI=0.17, 0.23) exposure estimates. In addition, elevation above the sea level was found to be statistically significant in spatial dependence models estimated for both DKD and SCA rates (P < 0.01). CONCLUSION: The analysis revealed an excess LBW rate in residential areas located close to petrochemical industries and a protective effect of seashore proximity and elevation above the sea level on the LBW rate. We attribute the latter finding to the moderating effect of elevated seashore locations on outdoor temperatures during the hot summer season.

Identifying areas under potential risk of illegal construction and demolition waste dumping using GIS tools.

Construction and demolition (C&D) waste, dumped illegally in ravines and open areas, contaminates soil and can cause underground water pollution and forests fires. Yet, effective monitoring of illegal C&D waste dumping and enforcing legislation against the offenders are often a difficult task due to the large size of geographic areas that need to be monitored, and limited human and financial resources available to environmental law enforcement agencies. In this study, we use Geographic Information System (GIS) tools and geo-statistical modelling to identify the areas under potentially elevated risk of illegal C&D waste dumping in the Haifa district of Israel. As our analysis shows, locational factors, significantly associated with the accumulated amount of waste in the existing illegal C&D waste sites, include: distance to the nearest main road, depth of the ravine present at the site (p<0.01), and forest proximity (p<0.05). Using the model incorporating these locational parameters, we mapped the areas under the elevated risk of illegal C&D waste dumping for future monitoring. As we suggest, the proposed approach may be useful for environmental law enforcement authorities, by helping them to focus on specific sites for inspection, save resources, and act against the offenders more efficiently.

A new approach to spatial identification of potential health hazards associated with childhood asthma.

RESEARCH BACKGROUND: Childhood asthma is a chronic disease, known to be linked to prolonged exposure to air pollution. However, the identification of specific health hazards, associated with childhood asthma is not always straightforward, due to the presence of multiple sources of air pollution in urban areas. In this study, we test a novel approach to the spatial identification of environmental hazards that have the highest probability of association with the observed asthma morbidity patterns. METHODS: The effect of a particular health hazard on population morbidity is expected to weaken with distance. To account for this effect, we rank potential health hazards based on the strength of association between the observed morbidity patterns and wind-direction weighted proximities to these locations. We validate this approach by applying it to a study of spatial patterns of childhood asthma in the Greater Haifa Metropolitan Area (GHMA) in Israel, characterised by multiple health hazards. RESULTS: We identified a spot in the local industrial zone as the primary risk source for the observed asthma morbidity patterns. Multivariate regressions, controlling for socio-economic and geographic variables, revealed that the observed incidence rates of asthma tend to decline as a function of distance from the identified industrial location. CONCLUSION: The proposed identification approach uses disease patterns as its main input, and can be used by researches as a preliminary risk assessment tool, in cases in which specific sources of locally elevated morbidity are unclear or cannot be identified by traditional methods.

Spatial identification of potential health hazards: a systematic areal search approach.

BACKGROUND AND AIMS: Large metropolitan areas often exhibit multiple morbidity hotspots. However, the identification of specific health hazards, associated with the observed morbidity patterns, is not always straightforward. In this study, we suggest an empirical approach to the identification of specific health hazards, which have the highest probability of association with the observed morbidity patterns. METHODS: The morbidity effect of a particular health hazard is expected to weaken with distance. To account for this effect, we estimate distance decay gradients for alternative locations and then rank these locations based on the strength of association between the observed morbidity and wind-direction weighted proximities to these locations. To validate this approach, we use both theoretical examples and a case study of the Greater Haifa Metropolitan Area (GHMA) in Israel, which is characterized by multiple health hazards. RESULTS: In our theoretical examples, the proposed approach helped to identify correctly the predefined locations of health hazards, while in the real-world case study, the main health hazard was identified as a spot in the industrial zone, which hosts several petrochemical facilities. CONCLUSION: The proposed approach does not require extensive input information and can be used as a preliminary risk assessment tool in a wide range of environmental settings, helping to identify potential environmental risk factors behind the observed population morbidity patterns.

Is prostate cancer incidence worldwide linked to artificial light at night exposures? Review of earlier findings and analysis of current trends.

Widespread use of artificial light at night (ALAN) might contribute to the global burden of hormone-dependent cancers. Previous attempts to verify this association in population-level studies have been sparse. Using GLOBOCAN, US-DMSP, and World Bank 2010-2012 databases, we studied the association between ALAN and prostate cancer (PC) incidence in 180 countries worldwide, controlling for several country-level confounders. The PC-ALAN association emerged marginally significant when year-2012 PC age-standardized rate data were compared with ALAN levels (t = 1.886, p < .1); this association was more significant (t > 2.7; p < .01) when only 110 countries with well-maintained cancer registries were analyzed. Along with other variables, ALAN explains up to 79% of PC ASR variability. PC-ALAN association appears to vary regionally, with the greatest deviations in Central Africa, Small Island Developing States, Southeast Asia, and Gulf States.

Lower Cancer Rates Among Druze Compared to Arab and Jewish Populations in Israel, 1999-2009.

The Druze are a small ethnic minority in Israel amounting to about 130,000 residents (or 1.7 % of the total population of the country). Unlike other population groups, the Druze strive to keep their own traditions and marry mainly inside their own community. During the last decade, cancer morbidity among both Jews and Arabs in Israel has been increasing, while data on the Druze are little known and have not been analyzed and compared to other population groups to date. To compare cancer morbidity rates among Druze, Arabs and Jews in Israel during 1999-2009, gender-specific and age-standardized incidence rates of all site cancers and specific cancers of three population groups (Jews, Arabs and Druze) were received from the Israel National Cancer Registry for the period 1999-2009. Based on these rates, periodical incidence rates were calculated and mutually compared across the groups stratified by gender. As the analysis shows, the Druze had significantly lower cancer rates compared to both Arabs and Jews. Thus, for all site cancers, there were significantly higher cancer rates in Jewish males versus Druze males (RR = 1.39, 95 % CI = 1.16-1.65) and in Jewish females versus Druze females (RR = 1.53, 95 % CI = 1.27-1.85), but not statistically significant for Arab males versus Druze males (RR = 1.12 95 % CI = 0.93-1.35). Lung cancer rates in Arab males were also higher compared to Druze males (RR = 1.84, 95 % CI = 1.13-3.00). Jewish males had statistically significant higher rates of prostate cancer compared to Druze males (RR = 2.47, 95 % CI = 1.55-3.91). For thyroid and colon cancers, risks were not significantly different at the 95 % CI level; however, the risks were significantly different at the 90 % CI level (RR = 3.62, 90 % CI 1.20-11.02 and RR = 1.69, 90 % CI = 1.03-2.77, respectively). Jewish females had significantly higher rates of invasive breast cancer (RR = 2.25, 95 % CI = 1.55-3.25), in situ cervical cancer (RR = 4.01, 95 % CI = 1.27-12.66) and lung cancer (RR = 3.22, 95 % CI = 1.12-9.24) compared to Druze females. We thus observed lower cancer rates among Druze versus Arab and Jewish populations in Israel. A reason for these differences may be due to different nutritional habits. Druze still keep a less processed nutritional lifestyle, than is common in industrial society. There may also be other reasons that have not been identified yet.

Light at night and breast cancer incidence in Connecticut: An ecological study of age group effects.

The aim of this study was to test the prediction that within the state of Connecticut, USA, communities with high nighttime outdoor light level would have higher breast cancer incidence rates. Breast cancer cases were identified from the Connecticut Tumor Registry, the oldest within the United States, for years 2005 and 2009 and geocoded to the 829 census tracts in the state. Nighttime light level (LAN) was obtained from the Defense Meteorological Satellite Program (DMSP), 1996/97 satellite image, providing a 10-year lag. Regression models were used incorporating the LAN levels and census level data on potential confounders for the whole female population of the state, and for separate age groups. Light level emerged as a significant predictor of breast cancer incidence. After taking account of several potential confounders, the excess risk in the highest LAN level census tracts compared to the lowest was about 63% (RR=1.63; 95% CI=1.41, 1.89). The association of LAN with breast cancer incidence weakened with age; the association was strongest among premenopausal women.

The new world atlas of artificial night sky brightness.

Artificial lights raise night sky luminance, creating the most visible effect of light pollution-artificial skyglow. Despite the increasing interest among scientists in fields such as ecology, astronomy, health care, and land-use planning, light pollution lacks a current quantification of its magnitude on a global scale. To overcome this, we present the world atlas of artificial sky luminance, computed with our light pollution propagation software using new high-resolution satellite data and new precision sky brightness measurements. This atlas shows that more than 80% of the world and more than 99% of the U.S. and European populations live under light-polluted skies. The Milky Way is hidden from more than one-third of humanity, including 60% of Europeans and nearly 80% of North Americans. Moreover, 23% of the world's land surfaces between 75°N and 60°S, 88% of Europe, and almost half of the United States experience light-polluted nights.