Abstract: BACKGROUND: Literature has identified detrimental health effects from the indiscriminate use of artificial nighttime light. We examined the co-distribution of light at night (LAN) and breast cancer (BC) incidence in Georgia, with the goal to contribute to the accumulating evidence that exposure to LAN increases risk of BC. METHODS: Using Georgia Comprehensive Cancer Registry data (2000-2007), we conducted a case-referent study among 34,053 BC cases and 14,458 lung cancer referents. Individuals with lung cancer were used as referents to control for other cancer risk factors that may be associated with elevated LAN, such as air pollution, and since this cancer type was not previously associated with LAN or circadian rhythm disruption. DMSP-OLS Nighttime Light Time Series satellite images (1992-2007) were used to estimate LAN levels; low (0-20 watts per sterradian cm(2)), medium (21-41 watts per sterradian cm(2)), high (>41 watts per sterradian cm(2)). LAN levels were extracted for each year of exposure prior to case/referent diagnosis in ArcGIS. RESULTS: Odds ratios (OR) and 95% confidence intervals (CI) were estimated using logistic regression models controlling for individual-level year of diagnosis, race, age at diagnosis, tumor grade, stage; and population-level determinants including metropolitan statistical area (MSA) status, births per 1,000 women aged 15-50, percentage of female smokers, MSA population mobility, and percentage of population over 16 in the labor force. We found that overall BC incidence was associated with high LAN exposure (OR = 1.12, 95% CI [1.04, 1.20]). When stratified by race, LAN exposure was associated with increased BC risk among whites (OR = 1.13, 95% CI [1.05, 1.22]), but not among blacks (OR = 1.02, 95% CI [0.82, 1.28]). CONCLUSIONS: Our results suggest positive associations between LAN and BC incidence, especially among whites. The consistency of our findings with previous studies suggests that there could be fundamental biological links between exposure to artificial LAN and increased BC incidence, although additional research using exposure metrics at the individual level is required to confirm or refute these findings.

Abstract: The successful bidding of the 2022 Winter Olympics (Beijing 2022, officially known as the XXIV Olympic Winter Games) has greatly stimulated Chinese enthusiasm to participate in winter sports. Consequently, the Chinese ski industry is rapidly booming driven by enormous market demand and government support. However, investing in ski area at an unreasonable location will cause problems both from economic perspective (in terms of operation and management) as well as geographical concerns (such as environmental degradation). To evaluate the suitability of a ski area based on scientific 20 metrics has since become a prerequisite to the sustainable development of ski industry. In this study, we evaluate the locational suitability of ski areas in China by integrating their natural and socioeconomic conditions using linear weighted method based on geographic information systems (GIS) spatial analysis combined with remote sensing, online and field survey data. Key indexes for evaluating the natural suitability include snow cover, air temperature, topographic conditions, groundwater, and vegetation, whereas socioeconomic suitability is evaluated based on economic conditions, accessibility of transportation, 25 distance to tourist attractions, and distance to cities. As such, an integrated metrics considering both natural and socioeconomic suitability is defined to be a threshold and used to identify the suitability of a candidate region for ski area development. The results show that 92% of existing ski areas are located in areas with an integrated index greater than 0.5. In contrary, a ski area is considered to be a dismal prospect when the locational integrated index is less than 0.5. Finally, corresponding development strategies for decision-makers are proposed based on the multi-criteria metrics, which will be extended to incorporate potential influences from future climate change and socioeconomic development.

Abstract: OBJECTIVES: Growing but limited evidence suggests that night shift work is associated with breast cancer. The authors conducted a nationwide case-control study nested within a cohort of 18,551 female military employees born in 1929-1968 to investigate the risk for breast cancer after night shift work and to explore the role of leisure time sun exposure and diurnal preference. METHODS: The authors documented 218 cases of breast cancer (1990-2003) and selected 899 age-matched controls from the cohort by incidence density sampling. Information on shift work, sun exposure habits, diurnal preference and other potential confounders was obtained from a structured questionnaire. ORs were estimated by multivariate conditional logistic regression. RESULTS: Overall, the authors observed an adjusted OR of 1.4 (95% CI 0.9 to 2.1) among women with ever compared with never night shifts. The RR for breast cancer tended to increase with increasing number of years of night shift work (p=0.03) and with cumulative number of shifts (p=0.02),with a neutral risk for fewer than three night shifts per week. The OR for the group with the highest tertile of cumulative exposure was 2.3 (95% CI 1.2 to 4.6). The most pronounced effect of night shift work on breast cancer risk was observed in women with morning chronotype preference and intense night shifts (OR=3.9, 95% CI 1.6 to 9.5). Night shift workers tended to sunbathe more frequently than day workers. CONCLUSIONS: The results indicate that frequent night shift work increases the risk for breast cancer and suggest a higher risk with longer duration of intense night shifts. Women with morning preference who worked on night shifts tended to have a higher risk than those with evening preference.