简介：AbstractBackground:China has experienced rapid urbanization in the past 30 years. We aimed to report blood cadmium level (BCL) in the rapidly urbanized Yangtze Plain of China, and explore the association between BCL and 25-hydroxyvitamin D (25(OH)D).Methods:Our data source was the Survey on Prevalence in East China for Metabolic Diseases and Risk Factors (SPECT-China) cross-sectional study (ChiCTR-ECS-14005052, www.chictr.org). We enrolled 3234 subjects from 12 villages in the Yangtze Plain. BCLs were measured by atomic absorption spectrometry. 25(OH)D was measured with a chemiluminescence assay.Results:A total of 2560 (79.2%) subjects were diagnosed with vitamin D deficiency. The median (interquartile range) BCL was 1.80 μg/L (0.60-3.42) for men and 1.40 μg/L (0.52-3.10) for women. In women, mean 25(OH)D concentrations were inversely associated with BCL (0.401, 95% confidence interval: -0.697 to -0.105 nmol/L lower with each doubling of the BCL) after adjustment for age, educational status, current smoking, body mass index, diabetes, and season. However, there was no significant difference in 25(OH)D across the BCL tertiles for men.Conclusions:BCL in Chinese residents in the Yangtze Plain were much higher than that in developed countries. An inverse association between BCL and 25(OH)D was found in general Chinese women after multivariable adjustment. Future prospective cohort and animal studies are warranted to resolve the direction and temporality of these relationships, and to elucidate the exact mechanisms involved.

简介：AbstractBackground:Oncomelania hupensis is only intermediate snail host of Schistosoma japonicum, and distribution of O. hupensis is an important indicator for the surveillance of schistosomiasis. This study explored the feasibility of a random forest algorithm weighted by spatial distance for risk prediction of schistosomiasis distribution in the Yangtze River Basin in China, with the aim to produce an improved precision reference for the national schistosomiasis control programme by reducing the number of snail survey sites without losing predictive accuracy.Methods:The snail presence and absence records were collected from Anhui, Hunan, Hubei, Jiangxi and Jiangsu provinces in 2018. A machine learning of random forest algorithm based on a set of environmental and climatic variables was developed to predict the breeding sites of the O. hupensis intermediated snail host of S. japonicum. Different spatial sizes of a hexagonal grid system were compared to estimate the need for required snail sampling sites. The predictive accuracy related to geographic distances between snail sampling sites was estimated by calculating Kappa and the area under the curve (AUC).Results:The highest accuracy (AUC = 0.889 and Kappa = 0.618) was achieved at the 5 km distance weight. The five factors with the strongest correlation to O. hupensis infestation probability were: (1) distance to lake (48.9%), (2) distance to river (36.6%), (3) isothermality (29.5%), (4) mean daily difference in temperature (28.1%), and (5) altitude (26.0%). The risk map showed that areas characterized by snail infestation were mainly located along the Yangtze River, with the highest probability in the dividing, slow-flowing river arms in the middle and lower reaches of the Yangtze River in Anhui, followed by areas near the shores of China’s two main lakes, the Dongting Lake in Hunan and Hubei and the Poyang Lake in Jiangxi.Conclusions:Applying the machine learning of random forest algorithm made it feasible to precisely predict snail infestation probability, an approach that could improve the sensitivity of the Chinese schistosome surveillance system. Redesign of the snail surveillance system by spatial bias correction of O. hupensis infestation in the Yangtze River Basin to reduce the number of sites required to investigate from 2369 to 1747.