Objective To study the relationship between environment selenium distribution characteristic and Kaschin-Beck disease (KBD) in the Yarlung Zangbo River banks and to provide some measures for prevention and control of KBD in the north side of the river bank.Methods Considering the geography and KBD distribution,we made a survey in Xietongmen (KBD area),Lazi and Sajia (non-KBD area) counties in 2013 and 2015.Water,soil,herbage,grain food and children hair samples were collected.Selenium of the samples was measured by hydride generation-atomic fluorescence spectrometry.Results A total of 246 samples of natural soil,cultivated soil,drinking water,food and forage,and 103 samples of children hair were collected.The selenium in natural soil,cultivated soil,herbage,barley,tsampa,self-produced wheat in non-KBD area in the south side of Yarlung Zangbo River bank were significantly higher than those in KBD areas in the north side [mean (μg/kg):288.62 vs 134.90,228.26 vs 160.28,41.85 vs 5.10,13.99 vs 4.02,12.64 vs 8.07,27.44 vs 13.56,U =7,23,0,19,62,0,P ＜ 0.05].Hair selenium in school children in KBD area in the north side was higher than that previously reported,but still significantly lower than that in non-KBD areas in the south side of the river bank [mg/kg:0.221 vs 0.306,U =650,P ＜ 0.01],and about 65.45％ (36/55)of school children in KBD area were at a risk of selenium deficiency in the north of the Yarlung Zangbo River bank.Conclusions The selenium contem in the food chain of soilplants-animals (human being) is significantly lower in KBD area in the north side of Yarlung Zangbo River bank than that in non-KBD areas in the south side.It's still a key factor for the occurrence and prevalence of KBD that low selenium in environment in KBD areas in the north side.

Objective:To investigate the levels of urinary arsenic metabolites in arsenic-exposed people with different degrees of skin lesions.Methods:A cluster sampling method was used to select people with different degrees of skin lesions in the drinking water arsenic poisoning area of Bayannaoer City, Inner Mongolia Autonomous Region. According to the "Standard of Diagnosis for Endemic Arsenism" (WS/T 211-2001), the research subjects were divided into four clinical grading: normal, suspicious, mild, moderate and above on the basis of the degrees of skin lesions. Urine samples from any 1 middle section were collected, and the levels of urinary arsenic metabolites of different forms in different clinically graded people were detected by inductively coupled plasma mass spectrometry (ICP-MS).Results:A total of 522 people were included, including 309 males and 213 females; the age was (39.11 ± 12.38) years old, ranging from 11 to 65 years old. There were 337, 80, 31, 74 people in normal, suspicious, mild, moderate and above clinical grading, the levels of inorganic arsenic (iAs, medians: 15.46, 37.16, 104.46, 163.06 μg/L), monomethylarsonic acid (MMA, medians: 15.95, 33.27, 82.80, 123.84 μg/L), dimethylarsenic acid (DMA, medians: 78.16, 147.86, 301.28, 371.30 μg/L), total arsenic (tAs, medians: 113.90, 220.94, 501.25, 684.46 μg/L), iAs percentage (iAs%, medians: 15.66%, 15.53%, 21.67%, 21.65%), MMA percentage (MMA%, medians: 13.51%, 15.40%, 17.14%, 16.43%), DMA percentage (DMA%, medians: 70.37%, 67.98%, 63.25%, 61.23%), monomethylation rate (PMI, medians: 0.84, 0.84, 0.78, 0.78), dimethylation rate (SMI, medians: 0.84, 0.81, 0.79, 0.79), and ratio of MMA to DMA (MMA/DMA, medians: 0.20, 0.23, 0.27, 0.27) were compared in different clinically graded people, the differences were statistically significant ( H = 97.98, 96.44, 85.50, 95.08, 38.58, 29.94, 51.98, 38.58, 43.20, 43.20, P < 0.01). Compared with normal people, iAs, MMA, DMA, tAs, MMA%, and MMA/DMA levels significantly increased, and SMI level significantly decreased in suspicious, mild, moderate and above people ( P < 0.017); compared with normal people, iAs% level significantly increased, and DMA% and PMI levels significantly decreased in mild, moderate and above people ( P < 0.017). Conclusion:The levels of urinary arsenic metabolites in arsenic-exposed people with different degrees of skin lesions are different, showing a dose-response relationship.

Objective To study the relationship between hair selenium content and arsenism among population from endemic arsenism area caused by coal combustion in the southern of Shaanxi Province.Methods Four high-arsenic-exposed villages in southern Shaanxi Province were selected as the study area,and the nonarsenic-exposed villages nearby were selected as the control area,90 hair samples of residents exposed to high arsenic in the study area and 14 hair samples of residents in the control area were collected.Inductively Coupled Plasma Mass Spectrometry (ICP-MS) was used to determine the contents of arsenic and selenium in hair samples.Selenium/hair arsenic (Se/As) value was calculated,and the relationship between selenium content in hair samples and arsenicosis was analyzed.Results The geometric mean of selenium concentration in hair from the study area was 8.72 mg/kg,which was significandy higher than that from the control area (0.54 mg/kg,t =9.811,P ＜ 0.05).However,selenosis case was not found in the study area.Selenium content in hair was not obviously correlated with arsenism (r =0.075,P ＞ 0.05),while the Se/As value was negatively associated with the grade of arsenism (P ＞ 0.05).The geometric mean of selenium content in hair of female from the study area was 12.79 mg/kg,which was higher than that in hair of male (6.5 mg/kg,t =1.738,P ＜ 0.01).Meanwhile,the Se/As value in hair of female from the study area (1.15) was significantly higher than that in hair of male (0.65,t =3.218,P ＜ 0.05).Conclusions The environment of the study area is polluted by arsenic and selenium derived from stone-coal burning.Antagonism between arsenic and selenium might reduce the toxicity of selenium.Therefore,selenosis is not found in the study area.In addition,antagonism between arsenic and selenium might also induce lower prevalence of arsenism for female in the studly area.

Objective To understand the changes of arsenic poisoning in drinking water arsenic poisoning areas in Inner Mongolia Autonomous Region,to provide a scientific basis for timely adjustment of local arsenic poisoning prevention and control measures.Methods In accordance with the requirements of the national "Surveillance Scheme of Drinking-Water-Borne Endemic Arsenism",38 villages were selected from 8 cities as monitoring sites in Inner Mongolia Autonomous Region in 2015.The situation of the villages in improving water quality and operation of the arsenic reducing projects was investigated,water samples were collected to detect water arsenic content of all the monitoring villages exposed or previously exposed to high arsenic water in the resident population,and 30 adult patients with arsenic poisoning were tested urine arsenic level.Results Thirty-eight monitored villages had changed the water sources;the change rate was 100.00％ (38/38).Water arsenic content qualified projects were 17,covering 36 villages.The project with water arsenic content exceeded the national standard was 1,the rate of exceeded standard was 5.56％ (1/18),covering 2 monitored villages.In the 36 water arsenic content qualified natural villages,4 163 people were examined,and arsenic poisoning patients detection rate was 10.21％ (425/4 163).The incidence of mild,moderate,severe and skin cancer cases was 7.59％ (316/4 163),1.68％ (70/4 163),0.86％ (36/4 163) and 0.07％ (3/4 163),respectively,no new cases and new skin cancer cases.In the natural villages where the content of arsenic in water exceeded the standard,461 resident people who were drinking high arsenic water were examined.The detection rate of arsenic poisoning patients was 3.69％ (17/461),no moderate,severe,new and skin cancer cases.A total of 1 107 patients with arsenic poisoning were tested for urinary arsenic levels in the 36 villages with normal water available and water arsenic levels in the range of 0.000-0.441 mg/L with a median of 0.011 mg/L.The content of urinary arsenic in 60 patients with arsenic poisoning was detected in the 2 natural villages with the arsenic content exceeded the standard.The range was 0.030-0.268 mg/L and the median was 0.155 mg/L.Conclusions The projects of anti-arsenic water have effects in Inner Mongolia Autonomous Region.But there are still water projects with water arsenic content exceeded the standard,which seriously affects the health of residents,and the water management and maintenance of water projects needs to be strengthened.

Objective:To study the effect of water improvement on urinary arsenic methylation metabolism in population exposed to arsenic through drinking water.Methods:A cluster sampling method was used to select drinking water type arsenism areas in Bayannur City, Inner Mongolia Autonomous Region. Permanent residents lived in the arsenism areas for more than 10 years were selected as the survey subjects. Urine samples ( n = 874, 111, 145) were collected in 2004 (before water improvement), 2014 (4 years after water improvement) and 2017 (7 years after water improvement), respectively, and some subjects were followed up in 2014 and 2017. High performance liquid chromatography-inductively coupled plasma mass spectrometry (HPLC-ICP-MS) was used to detect different forms of arsenic metabolites in urine [inorganic arsenic (iAs), monomethylarsonic acid (MMA), dimethylarsenic acid (DMA)], and total arsenic (tAs), the iAs percentage (iAs%), MMA percentage (MMA%), DMA percentage (DMA%), monomethylation rate (PMI), dimethylation rate (SMI), and the ratio of MMA to DMA (MMA/DMA) were calculated. The content and distribution of urinary arsenic metabolites in people exposed to arsenic before and after water improvement were compared and analyzed. Results:Compared with 2004, the levels of iAs, MMA, DMA, tAs and iAs% in urine of arsenic exposed population in 2014 were lower ( Z =-14.12,-12.79,-14.27,-14.21,-6.90, P < 0.001), the levels of MMA%, DMA% and PMI were higher ( Z =-3.22,-2.91,-6.90, P < 0.05); in the same drinking water arsenic exposed population, compared with 2004, the levels of iAs, MMA, DMA, tAs and iAs% in urine ( n = 48) were lower ( Z =-5.57,-5.53,-5.54,-5.55,-2.86, P < 0.05) in 2014, and PMI level was higher ( Z =-2.86, P = 0.004). Compared with 2014, the levels of iAs% and MMA/DMA in urine of arsenic exposed population in 2017 were lower ( Z =-4.97,-2.25, P < 0.05), the levels of MMA, DMA, tAs, DMA%, PMI and SMI were higher ( Z =-4.01,-5.39,-4.77,-4.61,-4.97,-2.25, P < 0.05); in the same drinking water arsenic exposed population, compared with 2014, the level of iAs% in urine ( n = 28) was lower ( Z =-2.87, P = 0.004) in 2017, the levels of DMA% and PMI were higher ( Z =-2.32,-2.87, P < 0.05). Conclusion:Water improvement could significantly reduce the levels of urinary arsenic metabolites iAs, MMA, DMA and tAs and increase the level of DMA% in arsenic exposed population.

Objective:To investigate the arsenic metabolism pattern and possible influencing factors in the population in drinking-water-borne endemic arsenic poisoning (drinking-water-borne arsenic poisoning for short) areas.Methods:In December 2004, a cluster sampling method was used to select arsenic poisoning population (arsenic poisoning group) and healthy population (control group) in drinking-water-borne arsenic poisoning area of Bayannur City, Inner Mongolia Autonomous Region as the survey subjects. A questionnaire survey was conducted. Arsenic content in drinking water at home of survey subjects, the levels of urinary arsenic and its metabolites, including [trivalent arsenic (As Ⅲ), inorganic arsenic (iAs), monomethylarsenic acid (pentavalent, MMA V), dimethylarsenic acid (pentavalent, DMA V), total arsenic (tAs), percentage of inorganic arsenic (iAs%), percentage of monomethylarsenic acid (MMA%), percentage of dimethylarsenic acid (DMA%), primary methylation index (PMI), secondary methylation index (SMI)] were tested using high performance liquid chromatography-inductively coupled plasma mass spectrometry; nail arsenic and nail selenium levels were tested using atomic fluorescence spectrometer. The influencing factors of arsenic metabolism pattern were analyzed by multiple linear regression. Results:A total of 536 survey subjects were included, including 155 individuals in the arsenic poisoning group and 381 in the control group. The water arsenic level ranged from 0.0 to 825.7 μg/L. Compared with the control group, there was no significant difference in the distribution of gender, education level and dental fluorosis in the arsenic poisoning group ( P > 0.05), but there were significant differences in the distribution of age, marital status, smoking, drinking and water arsenic ( P < 0.05). Compared with the control group, the levels of urinary As Ⅲ, iAs, MMA V, DMA V, tAs, MMA%, MMA/DMA and nail arsenic in the arsenic poisoning group were higher ( P < 0.05), while the levels of urinary DMA%, SMI and nail selenium were lower ( P < 0.05); but there was no statistically significant difference in the levels of urinary iAs% and PMI ( P > 0.05). Gender, education level, depth of wells, water arsenic, total number of wells and nail arsenic were the influencing factors of urinary As Ⅲ (β = - 19.82, - 23.83, 0.61, 0.21, 7.26, 2.98, P < 0.05). Age, depth of wells, water arsenic and nail arsenic were the influencing factors of urinary tAs (β = 3.18, 3.25, 1.31, 15.59, P < 0.05). Gender, education level, depth of wells, water arsenic, total number of wells and nail arsenic were the influencing factors of urinary iAs (β = - 20.47, - 25.90, 0.64, 0.25, 7.87, 3.11, P < 0.05). Age, gender, education level, water arsenic and nail arsenic were the influencing factors of urinary MMA V (β = 0.52, - 17.07, - 21.84, 0.22, 2.77, P < 0.05). Age, depth of wells, water arsenic and nail arsenic were the influencing factors of urinary DMA V (β = 2.35, 2.47, 0.85, 9.22, P < 0.05). Conclusions:Compared with healthy individuals, there are differences in arsenic metabolism pattern among individuals with drinking-water-borne arsenic poisoning. Age, gender, education level, depth of wells, water arsenic, total number of wells and nail arsenic may be influencing factors of different arsenic metabolism patterns.