Objective:To investigate epidemiological characteristics of arsenic poisoning-related skin lesions in an arsenic tailing area in Hunan Province.Methods:A cross-sectional study was conducted. From October 2016 to January 2017, all residents aged over 18 years (except pregnant women) were enrolled from 3 villages in Baiyun Town, Shimen County, Hunan Province by using a cluster-sampling method. Demographic information was collected through a face-to-face questionnaire interview. All residents received skin examination performed by professional dermatologists, and blood, urine, and hair samples were collected for the measurement of arsenic levels. Non-conditional logistic regression analysis was performed to analyze factors associated with arsenic poisoning-related skin lesions.Results:A total of 1 092 eligible residents in the arsenic tailing area were recruited in this study, and 756 (69.2%, 95% CI: 66.5%, 72.0%) presented with arsenic poisoning-related skin lesions, including hyperkeratosis, hypo- or hyper-pigmentation. The median ( Q1, Q3) arsenic levels were 0.31 (0.14, 0.74) μg/g in hair samples ( n = 1 079), 0.84 (0.67, 1.10) μg/L in blood samples ( n =1 091), and 60.31 (41.71, 91.52) μg/L in urine samples ( n =1 092). Multivariable analysis showed that the occurrence of arsenic poisoning-related skin lesions was associated with age, residential location, and occupational arsenic exposure history, but was not associated with gender, ethnicity, education levels, migration history, arsenic levels in hair, blood, or urine. Compared with the group aged 18 - 39 years, the group aged 40 - 59 years and the group aged over 60 years showed significantly higher risks of arsenic poisoning-related skin lesions (adjusted OR = 11.34, 95% CI: 5.98, 21.50, P < 0.001; adjusted OR = 71.82, 95% CI: 35.81, 144.05, P < 0.001, respectively). Compared with the residents in the Wangyangqiao village, residents in the Heshan village and Huangchang village showed significantly higher risks of arsenic poisoning-related skin lesions (adjusted OR = 2.89, 95% CI: 2.05, 4.08, P < 0.001; adjusted OR = 4.13, 95% CI: 1.94, 8.78, P < 0.001, respectively). The risk of arsenic poisoning-related skin lesions was significantly higher in residents with occupational exposure history than in those without (adjusted OR = 1.99, 95% CI: 1.04, 3.83, P = 0.039) . Conclusion:Nearly 70% of the residents presented with arsenic poisoning-related skin lesions in an arsenic tailing area in Hunan Province, and the duration and previous degree of arsenic exposure were associated with the risk of arsenic poisoning-related skin lesions.

Objective:To analyze the relationship between plasma uranium concentration and renal injury.Methods:A case-control study was conducted in Hunan province, involving 102 renal injury cases and 102 matched controls. The association between plasma uranium concentration and renal injury was analyzed using conditional logistic regression models, and the dose-response relationship was analyzed through restricted cubic spline regression. The linear regression model and Spearman correlation were used to analyze the association between plasma uranium concentration and renal injury indicators.Results:The median of plasma uranium concentration was 8.94 ng/L in all subjects and 10.19 ng/L in the case group. The plasma uranium may be a risk factor for renal injury, with a dose-response relationship between the both representing nonlinear association ( χ2=5.15, P<0.05). The risk of renal injury was 4.21 times higher in the group exposed to highest uranium concentration than that in the group exposed to lowest uranium concentration. Plasma uranium concentration was closely related to glomerular filtration rate, serum creatinine and β 2-microglobulin ( r=0.211, -0.142, 0.195, P<0.05). Conclusions:The plasma uranium concentration is significantly associated with the renal injury, which may provide epidemiology evidence for the prevention of renal injury.

Chronic kidney disease (CKD) is suffered progressive loss of kidney function lasting more than 3 months and is classified according to the degree of kidney damage (level of proteinuria) and the decreased glomerular filtration rate (GFR). The most severe form of CKD is end-stage renal disease. The prevalence of CKD is high with fast growth rate and the disease burden has become increasingly serious. CKD has become an important public health problem threatening human health. The etiology of CKD is complex. In addition to genetic factors, environmental factors are an important cause of CKD. With the development of industrialization, environmental metal pollution has become increasingly severe, and its impact on human health has received widespread attention. A large number of studies have shown that metals such as lead, cadmium, and arsenic can accumulate in the kidney, which can cause damage to the structure and function of the kidney, and play an important role in the development of CKD. Therefore, summarizing the epidemiological research progress in the relationship between arsenic, cadmium, lead, and other metal exposures and kidney diseases can provide new ideas for the prevention and control of kidney diseases caused by metal exposure.
Humans ; Cadmium/toxicity* ; Arsenic/toxicity* ; Kidney ; Renal Insufficiency, Chronic/epidemiology* ; Kidney Failure, Chronic

Background Heavy metal emissions from mining and smelting areas are a global problem, and health risks associated with heavy metal contamination of soils are of great concern. The long-term mining of the largest realgar mine in Asia has caused severe arsenic and other metal pollution to the surrounding rivers and soils. Objective To understand the levels of metal contamination and health risks in agricultural soils of villages surrounding the largest realgar mine in Asia, and to lay a good foundation for further necessary pollution control actions and decisions. Methods A field survey was conducted to collect soil samples according to the Technical rules for monitoring of environmental quality of farmland soil (NY/T 395-2012), and then inductively coupled plasma mass spectrometry was used to determine the contents of 28 heavy metals [cadmium (Cd), arsenic (As), lead (Pb), mercury (Hg), chromium (Cr), nickel (Ni), copper (Cu), zinc (Zn), beryllium (Be), selenium (Se), cobalt (Co), antimony (Sb), molybdenum (Mo), vanadium (V), barium (Ba), thallium (Tl), boron (B) , bismuth (Bi), lithium (Li), manganese (Mn), strontium (Sr), calcium (Ca), rubidium (Rb), iron (Fe), magnesium (Mg), aluminum (Al), kalium (K), and titanium (Ti)]. Geoaccumulation index, single factor pollution index, and Nemerow comprehensive index were used to evaluate the degree and characteristics of single metal pollution and combined pollution in soil, respectively. A health risk assessment model was used to evaluate the risks of metals in soil to human health. Results The results of geoaccumulation index calculation revealed that 22 heavy metals were enriched in the soil, and the indexes of target heavy metals from high to low were Cd > Se > Pb >Hg > As > Co> Ni > Cu > Zn > Bi > Sb > Mo > Be> Cr > Ba >V > Li > Sr> Mn> Rb > Ca> Tl . The single factor pollution indexes of 17 heavy metals from high to low were Be > Cd > B > Mo > V > As > Ni > Cu > Pb > Zn > Co > Se > Tl > Ba > Cr > Hg > Sb. The Nemerow comprehensive index indicated all sampling points were graded as severe pollution. The mean of total non-carcinogenic health risk values and the mean of carcinogenic health risk values for the target heavy metals in the area were higher than the threshold (1) and the maximum acceptable risk (1.0×10^–4), respectively. The total carcinogenic health risks for adults and children reached 1.1×10^–3 and 1.67×10^–3, respectively. The mean non-carcinogenic health risk values of As, Co, Cr, and Pb pollution were greater than 1, and the maximum non-cancer risk value of Sb for children was greater than 1. The mean carcinogenic risk values of Ni, As, and Cu exceeded 1.0×10^–4 for both adults and children, and the maximum carcinogenic risk values of Be and Cr for children were more than 1.0×10^–4. Conclusion The farmland soil around the hugest realgar mine in Asia is contaminated by multiple metals. The study soil is seriously polluted by Cd, Se, Pb, As, Hg, Be, B, Mo, V, Ni, Cu, Pb, Zn, Co, and Ba. The pollution of Ni, As, Cu, Cr, and Be is considered as carcinogenic hazards to health, while the pollution of As, Co, Cr, Pb, and Sb poses non-carcinogenic health risks. Our study findings show that the soil is polluted by Co and Group 1 carcinogen Be, which could cause health risks; although Cr and Sb have not reached severe pollution levels, there are certain health risks and also need attention.

Background Exposure to uranium can result in multi-organ toxicity in humans. Some experimental studies have shown that uranium presents a damaging effect on liver, but no relevant population studies have been reported. Objective To investigate a potential association of plasma uranium exposure with liver injury. Methods The inhabitants of two representative areas of heavy metal pollution in northern and southern Hunan were selected as the research subjects. A total of 740 participants were recruited through 1∶1 paired case-control design based on a pre-determined diagnostic criterion for liver injury (defined as two or more anomalies among alanine aminotransferase, aspartate aminotransferase, and total bilirubin in the health examination) and the principle of case-control comparability. Information such as general demographic characteristics and medical history were collected through questionnaires and physical examination. Plasma uranium and liver function were determined by laboratory tests. Spearman correlation was applied to assess the association between plasma uranium concentration and liver injury indexes, and restricted cubic spline model was used to evaluate the dose-response relationship between plasma uranium concentration and liver injury. The participants were divided into four groups from Q1 to Q4 according to the quartile values of plasma uranium concentration of the control group after natural logarithmic transformation (with the Q1 group as the reference group), and the association between plasma uranium concentration and liver injury was evaluated by conditional logistic regression. Results The plasma uranium level in M (P₂₅, P₇₅) of the case group was 10.89 (6.78-18.53) ng·L⁻¹, higher than that in the control group, 9.26 (5.01-14.38) ng·L⁻¹ (P<0.001). The results of Spearman correlation analysis showed that alanine aminotransferase and aspartate aminotransferase were positively correlated with plasma uranium level (r_s=0.138, r_s=0.167; P<0.001). The restricted cubic spline model showed that the risk of liver injury increased with the increase of plasma uranium concentration (overall effect P<0.001). After adjusting for confounding factors such as gender, age, smoking, alcohol consumption, and prevalence of hypertension and hyperlipidemia, the results of conditional logistic regression analysis showed that the risks of liver injury in the Q2 group, the Q3 group, and the Q4 group were 2.043 (95%CI: 1.135-3.680), 2.246 (95%CI: 1.238-4.075), and 3.536 (95%CI: 1.955-6.397) times higher than that of the Q1 group respectively. Conclusion Plasma uranium exposure is associated with liver injury. This study is the first to provide population-level evidence of such an association.

OBJECTIVES: To evaluate residents' knowledge, attitude and behavior towards coronavirus disease 2019 (COVID-19) in Hunan Province, and to explore the factors influencing behaviors. METHODS: A self-designed questionnaire was used to conduct an online survey for 4 139 Hunan residents. The contents included general population information, residents' knowledge, attitude and practice to COVID-19. RESULTS: Mean scores of knowledge, attitude, and behavior were 29.82±3.16, 6.71±1.12, and 14.93±1.45, respectively. Residents had the highest score of major symptoms of COVID-19 (3.96±0.39), but the lowest was the main transmission routes (3.47±0.89). A total of 22.68% of the residents were very or relatively afraid of the outbreak, but 95.22% of the residents had confidence in defeating COVID-19. In behavior dimension, "handling of suspicious symptoms" had the lowest score (3.58±0.75). The behavior implementation rate of "keep the surfaces of household items clean" (80.50%), "doing more exercise, reasonable diet, working and resting regularly" (84.59%), and "avoid hand contacting with eyes, mouth or nose" (89.51%) were relatively low. Pearson correlation coefficient showed that the knowledge, attitude, and practices score were correlated with each other (knowledge vs behavior: =0.366; knowledge vs attitude: =0.041; attitude vs behavior: =0.100; all <0.05). Multiple linear regression analysis showed that the knowledge, attitude and behavior on COVID-19 were mostly influenced by education background (all <0.05), and the independent factors affecting behavior included knowledge and attitude, gender, permanent residence, education background (all <0.05). CONCLUSIONS Residents in Hunan Province have a good knowledge, attitude, and behavior to COVID-19. Nevertheless there are still weak links to be improved in all dimensions. It is necessary to strengthen knowledge and behavior of family protection, and care for residents' psychological health, especially persons with low education degree, male and rural residents.
Betacoronavirus ; China ; Coronavirus Infections ; psychology ; Health Knowledge, Attitudes, Practice ; Humans ; Pandemics ; Pneumonia, Viral ; psychology ; Surveys and Questionnaires

By searching the database of CNKI, Wanfang and PubMed, the prevalence and risk factors of atopic dermatitis, psoriasis, acne, and urticaria were relatively more investigated, which were the skin diseases of more concern in the current epidemiological study of skin diseases. Three national epidemiologic surveys reported that the prevalence of atopic dermatitis increased from 0.69% in 1998, to 3.07% in 2002, and 12.94% in 2014, respectively. The prevalence of psoriasis increased from 0.123% in 1984 to 0.47% in 2009 according to 2 national surveys. The prevalence of acne was 8.1% in a national investigation in 2008. Representative national prevalence data of urticaria is not available. Risk factors for these skin diseases are distinct. Atopic dermatitis, psoriasis, and urticaria are more related to environment and mental stress, while acne is more related to skin type and dietary factors. Owing to the heterogeneities in diagnostic methods used in the dermatoepidemiologic surveys (some of the diagnoses were self-reported) and a lack of follow ups, the reliability of data remained questionable, and the comparability across the surveys was difficult. As a result, it is necessary to conduct population-based cohort studies on skin diseases in China.
Acne Vulgaris ; epidemiology ; China ; epidemiology ; Dermatitis, Atopic ; Humans ; Prevalence ; Psoriasis ; epidemiology ; Reproducibility of Results ; Risk Factors ; Urticaria

According to the new biopsychosocial medical model,status and burden of diseases should be evaluated comprehensively,and health-related quality of life can be an important measurement index of the burden of diseases.Conventional assessment methods for health-related quality of life include interval-based assessment methods and preference-based assessment methods (health utilities and willingness-to-pay).This review introduces willingness-to-pay,and summarizes its applications in skin diseases.However,at present,only a small quantity of small-scale studies are available on willingness-to-pay,with only a few kinds of skin diseases involved.In the application of health-economic assessment of skin diseases,willingness-to-pay can serve as an approximate index of benefit gains,and be more valuable in practice than health utilities (the index of utility gains).With the increase in health-economic researches on skin diseases,more attention is paid to the willingness-to-pay for skin diseases and other health-economic assessment methods,and large-scale health-economic assessment-related researches are expected to be conducted on more kinds of skin diseases.

To construct an intelligent assistant diagnosis model based on the clinical images of basal cell carcinoma (BCC) and pigmented nevi in Chinese by using the advanced convolutional neural network (CNN).
 Methods: Based on the Xiangya Medical Big Data Platform, we constructed a large-scale clinical image dataset of skin diseases according to Chinese ethnicity and the Xiangya Skin Disease Dataset. We evaluated the performance of 5 mainstream CNN models (ResNet50, InceptionV3, InceptionResNetV2, DenseNet121, and Xception) on a subset of BCC and pigmented nevi of this dataset. We also analyzed the basis of the diagnosis results in the form of heatmaps. We compared the optimal CNN classification model with 30 professional dermatologists.
 Results: The Xiangya Skin Disease Dataset contains 150 223 clinical images with lesion annotations, covering 543 skin diseases, and each image in the dataset contains support for pathological gold standards and the patient's overall medical history. On the test set of 349 BCC and 497 pigmented nevi, the optimal CNN model was Xception, and its classification accuracy can reach 93.5%, of which the area under curve (AUC) values were 0.974 and 0.969, respectively. The results of the heatmap showed that the CNN model can indeed learn the characteristics associated with disease identification. The ability of the Xception model to identify clinical images of BCC and Nevi was basically comparable to that of professional dermatologists.
 Conclusion: This study is the first assistant diagnosis study for skin tumor based on Chinese ethnic clinical dataset. It proves that CNN model has the ability to distinguish between Chinese ethnicity's BCC and Nevi, and lays a solid foundation for the following application of artificial intelligence in the diagnosis and treatment for skin tumors.
Area Under Curve ; Carcinoma, Basal Cell ; diagnostic imaging ; Humans ; Neural Networks, Computer ; Nevus, Pigmented ; diagnostic imaging ; Skin Neoplasms ; diagnostic imaging

Objective To understand health literacy levels in elderly people aged 60 years and above in Hunan, and explore factors related to health literacy.Methods Hunan residents aged 60 years and above were randomly recruited by the multistage stratified cluster sampling method.A total of 611 elderly people from 13 counties of Hunan were included in the study, which was conducted through questionnaires.Results The median health literacy score for elderly people aged 60 years and above was 51.00 (4-90), and it was lower than that for people under 60 years old, which was 56.00.Single factor analysis found that education level, occupation, number of family members, and household income each had an influence on health literacy scores (H=59.526, 20.609, 17.214, and 50.749, respectively;P=0.000, 0.002, 0.001 and 0.000, respectively).The number of people with basic health literacy accounted for 10.6％ (65/611) of the total.Multiple logistic regression analysis found that chronic disease was a factor affecting basic health literacy.Compared with elderly people without chronic diseases, a higher percentage of people with basic health literacy was among elderly people with chronic diseases (OR =1.870, 95％ CI: 1.037-3.373).Conclusions The health literacy level is lower in elderly people aged 60 years and above than those under 60 years old in Hunan.Only 10.6％ (65/611) of them show basic health literacy.Education level, occupation, number of family members, and household income are the factors related to health literacy.Health education about healthy lifestyle and behavior as well as chronic disease prevention and control should be increased in order to improve the health literacy level in elderly people.