Search Results (4)

The effects of meteorological conditions on asthma in Haikou, a tropical city in China, are still unclear. This study aimed to determine the relationships between meteorological factors and the number of asthma hospital visits in Haikou. A Poisson generalized additive model combined with a distributed lag nonlinear model is used to model the nonlinear exposure–response relationship between the daily mean temperature and asthma hospital visits. The daily mean pressure and air quality are used as covariates and simultaneously control the mixed effects of holiday effects, weekend effects, and long-term trends. The results indicate that there is a significant statistical relationship between the daily mean temperature and asthma hospital visits, which shows an inverted J-shaped relationship. When the daily mean temperature is below the reference value (29.3 °C), the number of asthma patients increases considerably, and there is a marked lag in the prevalence of asthma. The longest lag is 9 days, and the most pronounced impact of the daily mean temperature on the number of asthma hospital visits can be found when the lag time is 1–4 days. When the daily mean temperature is 10 °C, the cumulative effect of the relative risk of asthma is 2.204, an increase of 120.4% (95% CI 1.294–3.755). If the daily mean temperature is below the 2.5th percentile value (14.8 °C), the relative risk significantly increases by more than 5.3% (95% CI 1.000–1.110), and the longest lasting impact time is 5 days. This indicates that increases in asthma hospital visits in Haikou, China, are significantly correlated with low-temperature weather. We suggest that preventive measures for asthma should take low-temperature weather into account. Additionally, we also found that extremely high temperatures have a certain impact on the increase in asthma hospital visits, but that the correlation is not significant. Full article

Despite the vast annual number of international visitors to the tropics, surprisingly little data are available on the psychological well-being associated with the travels or with travelers’ diarrhoea (TD). We herein recruited participants of a vaccination trial, OEV-123, before their 12-day holiday in Benin, West Africa. We assessed the travelers’ psychological distress with a general health questionnaire (GHQ-12) and retrieved data on TD from the trial database. The GHQ-12 was completed before (wave 0), at return (wave 1), and 1-month after (wave 2) the trip. Of the 174 participants, 73% were women, with a mean age 40 years. Moreover, 24% reported psychological distress before traveling, 10% immediately after, and 16% 1-month after the trip (GHQ-12, 3 or more; 0–12 scoring). The findings showed that psychological well-being increased after the tropical holiday. The GHQ-12 middle wave sum score differed from the wave 0 (p < 0.001) and wave 2 (p = 0.008) sum scores, with travelers reporting highest levels of well-being on their return, with evidence of a lasting improvement. TD was experienced by 71%, and it had a negative impact on psychological well-being only if experienced after travel. Full article

The South China Sea (SCS) is one of the most important fishery resource bases in the world. Marine fisheries, as a crucial component of regional food security and national revenue, raise wide concern about marine ecology, social-economic and political consequences at regional, national and local scales. The large-scale dynamic detection and analysis of fishing activity in the SCS is still unclear because of the accessibility of in-site data, finite automatic identification system (AIS) usage, complex geopolitics and poor additional data coverage. Nighttime light imagery (NTL) derived from low light imaging sensors and the popularity of light fishing in the SCS offers a unique way to unveil fishing activities and its dynamics. In this study, we proposed a set of algorithms for automatic detection of nighttime fishing activity and provided the first large-scale dynamic analysis of nighttime fishing activity in the SCS using monthly Visible Infrared Imaging Radiometer Suite (VIIRS) images between 2012 and 2019. The proposed method effectively minimized the spatio-temporal fluctuations in radiance values of background and their implications to ship detection by integrating high radiance gradient detection and local adaptive thresholding. Further, nighttime fishing activity trajectories were decomposed into trend and seasonal components by using Hilbert-Huang transformation (HHT) to accurately access general trends and the seasonality of nighttime fishing activity in the SCS. The typical subregions analysis, environmental driver analysis, correlation coefficient analysis and hot spot analysis were integrated to characterize the nighttime fishing activity. It appears that the nighttime fishing activity in the SCS exhibited spatio-temporal variability and heterogeneity and was shaped by policy and natural factors such as holidays, annual Chinese fishery moratoria in the Chinese Exclusive Economic Zone (EEZ) and seasonal tropical storm activity. Full article

Historically, seasonal variations in suicide rates were thought to be associated with changes in weather. Most of this evidence however, is based on studies that were conducted in developed countries that are located outside the tropics. As such, it is necessary to examine this association in developing countries, such as Colombia, which do not experience marked seasons. In addition, it is important to adjust for the effect of holidays when analyzing this association as they have been reported to be a relevant confounding factor. Our objective was to estimate the association between daily suicide incidence among men and women in five major Colombian cities (Bogotá, Medellin, Cali, Barranquilla, and Bucaramanga) and daily temperature and rainfall. For this purpose, we conducted a multi-city, multi-temporal ecological study from 2005 to 2015, using data from the suicide mortality registries (provided by the National Administrative Department of Statistics). Daily measurements of the two weather variables were obtained from the official historical registry of the meteorological station at each city airport. We used these data to estimate conditional Poisson models for daily suicide counts, stratifying by sex and adjusting for holidays. Although we found that none of the weather variable estimators could reject the null hypothesis, we uncovered an association between suicide incidence and long weekends in the total suicide model (Incidence Rate Ratio (IRR): 1.19, 95% confidence interval (CI): 1.04–1.23). We found no evidence of association between weather variables and suicide in Colombia. Our study is based on daily observations and it provides evidence of absence of this association in a tropical country that does not experience marked seasons. Full article