A new arbutin derivative from the leaves of Vaccinium dunalianum wight.

A new arbutin derivative, namely dunalianosides J (1), along with six known compounds, arbutin (2), robustaside A (3), 6'-O-caffeoylarbutin (4), dunalianoside D (5), kaempferol 3-O-ß-D-glucopyranoside (6) and kaempferol 3-O-ß-D-sambubioside (7) were isolated from the leaves of Vaccinium dunalianum Wight (Ericaceae). The structure of 1 was elucidated by extensive 1D and 2D NMR, HR-MS and CD spectroscopic analyses. In which, kaempferol 3-O-ß-D-sambubioside (7) was isolated from the genus Vaccinium for the first time.

Characterizing a large outbreak of dengue fever in Guangdong Province, China.

BACKGROUND: Dengue cases have been reported each year for the past 25 years in Guangdong Province, China with a recorded historical peak in 2014. This study aims to describe the epidemiological characteristics of this large outbreak in order to better understand its epidemic factors and to inform control strategies. METHODS: Data for clinically diagnosed and laboratory-confirmed dengue fever cases in 2014 were extracted from the China Notifiable Infectious Disease Reporting System. We analyzed the incidence and characteristics of imported and indigenous cases in terms of population, temporal and spatial distributions. RESULTS: A total of 45 224 dengue fever cases and 6 deaths were notified in Guangdong Province in 2014, with an incidence of 47.3 per 100 000 people. The elderly (65+ years) represented 11.7 % of total indigenous cases with the highest incidence (72.3 per 100 000). Household workers and the unemployed accounted for 23.1 % of indigenous cases. The majority of indigenous cases occurred in the 37(th) to 44(th) week of 2014 (September and October) and almost all (20 of 21) prefecture-level cities in Guangdong were affected. Compared to the non-Pearl River Delta Region, the Pearl River Delta Region accounted for the majority of dengue cases and reported cases earlier in 2014. Dengue virus serotypes 1 (DENV-1), 2 (DENV-2) and 3 (DENV-3) were detected and DENV-1 was predominant (88.4 %). CONCLUSIONS: Dengue fever is a serious public health problem and is emerging as a continuous threat in Guangdong Province. There is an urgent need to enhance dengue surveillance and control, especially for the high-risk populations in high-risk areas.

Health impact of the 2008 cold spell on mortality in subtropical China: the climate and health impact national assessment study (CHINAs).

BACKGROUND: Many studies have investigated heat wave related mortality, but less attention has been given to the health effects of cold spells in the context of global warming. The 2008 cold spell in China provided a unique opportunity to estimate the effects of the 2008 cold spell on mortality in subtropical regions, spatial heterogeneity of the effects, stratification effect and added effects caused by sustained cold days. METHODS: Thirty-six study communities were selected from 15 provinces in subtropical China. Daily mortality and meteorological data were collected for each community from 2006 to 2010. A distributed lag linear non-linear model (DLNM) with a lag structure of up to 27 days was used to analyze the association between the 2008 cold spell and mortality. Multivariate meta-analyses were used to combine the cold effects across each community. RESULTS: The 2008 cold spell increased mortality by 43.8% (95% CI: 34.8% ~ 53.4%) compared to non-cold spell days with the highest effects in southern and central China. The effects were more pronounced for respiratory mortality (RESP) than for cardiovascular (CVD) or cerebrovascular mortality (CBD), for females more than for males, and for the elderly aged ≥75 years old more than for younger people. Overall, 148,279 excess deaths were attributable to the 2008 cold spell. The cold effect was mainly from extreme low temperatures rather than sustained cold days during this 2008 cold spell. CONCLUSIONS: The 2008 cold spell increased mortality in subtropical China, which was mainly attributable to the low temperature rather than the sustained duration of the cold spell. The cold effects were spatially heterogeneous and modified by individual-specific characteristics such as gender and age.

The effects of dust-haze on mortality are modified by seasons and individual characteristics in Guangzhou, China.

This study aimed to investigate the effects of dust-haze on mortality and to estimate the seasonal and individual-specific modification effects in Guangzhou, China. Mortality, air pollution and meteorological data were collected for 2006-2011. A dust-haze day was defined as daily visibility <10 km with relative humidity <90%. This definition was further divided into light (8-10 km), medium (5-8 km) and heavy dust-haze (<5 km). A distributed lag linear model (DLM) was employed. Light, medium and heavy dust-haze days were associated with increased mortality of 3.4%, 6.8% and 10.4% respectively, at a lag of 0-6 days. This effect was more pronounced during the cold season, for cardiovascular mortality (CVD), respiratory mortality (RESP), in males and people ≥60years. These effects became insignificant after adjustment for PM10. We concluded that dust-haze significantly increased mortality risk in Guangzhou, China, and this effect appears to be dominated by particulate mass and modified by season and individual-specific factors.

[The impact of temperature on cardiovascular disease deaths in 4 cities, China: a time-series study].

OBJECTIVE: To estimate the effects of temperature on cardiovascular disease (CVD) deaths in 4 cities-Kunming, Changsha, Guangzhou and Zhuhai, from southern part of China. METHODS: Daily CVD deaths, meteorological and air pollution data were used to explore the association between temperature and mortality. Distributed lag non-linear model was fitted for each city to access the delayed and cumulative effects of low, median and high temperature on CVD deaths. Cold and hot effects of temperature on CVD deaths were then accessed, based on the linear threshold model. RESULTS: The city-specific exposure-response functions appeared to be non-linear. Temperatures that associated with the lowest mortality for Changsha, Kunming, Guangzhou and Zhuhai were 22.0°C, 20.0°C, 26.0°C, and 25.5°C. The greatest cumulative RRs (95%CI) for CVD deaths of low temperature during the delayed period of the study in the 4 cities were 1.858 (1.089 - 3.170), 1.537 (1.306 - 1.809), 2.121 (1.771 - 2.540) and 1.934 (1.469 - 2.548), while 1.100 (0.816 - 1.483), 1.061 (0.956 - 1.177), 1.134 (1.047 - 1.230) and 1.259 (1.104 - 1.436) for high temperatures in Changsha, Kunming, Guangzhou and Zhuhai respectively. The hot effect was greater than the cold effect on the current days. The hot effect was restricted to the first week, whereas the cold effect increased over the lag days, and then last for 3 - 4 weeks. CONCLUSION: The city-specific exposure-response functions appeared to be non-linear. Both high and cold temperatures were associated with increased CVD deaths, but the impact of low temperature was more notable. Cold effect was delayed by several days but last for a longer period than the hot effect did.

[Time-series analysis on the malaria morbidity affected by meteorological factors in Guangdong province].

OBJECTIVE: To evaluate the associations between malaria risk and meteorological factors. METHODS: A negative binomial distribution regression analysis was built between the temperature, relative humidity, rainfall capacity and the monthly incidence of malaria, based on the temperature information provided by Guangdong Meteorological Department and the malaria incidence information provided by Guangdong Center of Disease Prevention and Control during year 1980 to 2004, adopting the time-series analysis method and by distributed lag non-linear model, in order to analyze the immediate factors. RESULTS: The number of monthly malaria cases in Guangdong province reached 4010 between year 1984 and 2004, while the monthly maximal temperature, minimal temperature, average temperature, relative humidity and average rainfall capacity was separately 26.3°C, 18.8°C, 21.9°C, 88.0% and 5.6 mm. The immediate effect of monthly maximal temperature on malaria incidence showed non-linear relationships. When the temperature reached 32.3°C, the risk was highest, the relative risk (RR) was 2.51 (95%CI: 1.99 - 3.16); when the relative humidity was 60.0%, the relative risk of malaria was highest as 1.19 (95%CI: 0.66 - 2.11) and then decreased gradually; and when the relative humidity was 86.6%, the risk of malaria was lowest at 0.51 (95%CI: 0.34 - 0.76). The risk of malaria increased while the rainfall capacity was 14.5 mm, the risk of malaria was the highest at 1.29 (95%CI: 0.87 - 1.93). Strongest delayed effects on malaria incidence was observed when the monthly maximal temperature reached 31.5°C at lagged 2 months, with the value of RR at 1.81 (95%CI: 1.02 - 3.22). When the monthly rainfall capacity was over 15.2 mm, the delayed effects was strong but short. When the monthly maximal temperature of 33.7°C, the excess risk of malaria was comparatively high, the excess risk was 92.2% (95%CI: 30.5% - 183.2%) when lagging one month. When the relative humidity was low, the delayed effect of malaria lasted for a long time, and the cumulative effect was huge. When the relative humidity reached 87.0%, the excess risk lagging 3 months was only -66.6% (95%CI: -86.4% - -17.7%). When the rainfall capacity was 15.5 mm, the cumulative effect on malaria reached the peak after 3 months, while the excess risk was 40.7% (95%CI: -30.0% - -182.6%); afterwards the cumulative effect gradually weakened. Positive and negative interaction effects were significant between malaria risk and maximal temperature and monthly rainfall capacity, and monthly rainfall capacity and relative humidity at lagged 2 months, respectively. CONCLUSION: High temperature and large rainfall capacity might be the risk factors of malaria in Guangdong province, and there was an obvious interaction between the two factors.

[What temperature index is the best predictor for the impact of temperature on mortality].

OBJECTIVE: To explore the suitable temperature index to establish temperature-mortality model. METHODS: The mortality and meteorological information of Guangzhou between year 2006 and 2010 were collected to explore the association between sendible temperature, heat index and deaths by adopting distributed lag non-linear model to fit the daily maximum, mean and minimum temperature with and without humidity. Q-Q plots based on the standardized residuals of each model were used to qualitatively access the goodness of fitting. The minimum Akaike information criterion (AIC) and residual sum of squares (RSS) value were used to explore the most suitable temperature index for model establishment, and to further analyze the fittest temperature index for different diseases, ages and cold and hot effect. RESULTS: Guangzhou features a subtropical monsoon climate, with an annual average temperature at 22.9°C and daily average relative humidity of 71%. The standardized residuals of all models followed normal distribution. For all death, death from circulation system diseases, the 65-84 years old aging groups and cold effect models, the daily average temperature fit better, whose AIC (RSS) values were the smallest as 11 537 (1897), 9527 (1928), 10 595 (2018) and 11 523 (1899), respectively. However, for death from respiratory system disease, groups aging under 65 years old or over 85 years old and hot effect models, the daily average sendible temperature fit better, whose AIC (RSS) values were the smallest as 8265(1854), 675 (1739), 8550 (1871) and 11 687 (1938), respectively. In comparison with the model controlling both temperature and relative humidity, different diseases, aging groups and cold and hot effect models fitted by sendible temperature index showed smaller AIC (RSS) values. The relative risk (RR) value of the cold effect lagging 0 - 3 days fitting by daily maximal temperature was < 1, and the RR value of it fitting by daily minimum temperature was > 1.04. The RR value of the hot effect lagging 0 - 1 days fitting by daily maximal temperature was < 1.16, and the RR values of it fitting by daily minimum temperature and daily average temperature were > 1.16. CONCLUSION: There were no best temperature indicators for different diseases, ages and cold and hot effect. The model using sendible temperature index better fit the model including relative humidity as a covariable.