Objective:To study the relationship between urinary arsenic methylation metabolism patterns and skin keratinization and pigmentation abnormalities in population exposed to arsenic through drinking water.Methods:Using a cross-sectional study method, a survey on endemic arsenic poisoning was conducted among permanent residents of drinking water endemic arsenic poisoning areas in Bayannur City, Inner Mongolia Autonomous Region in 2004 (before water improvement). In 2017 (after water improvement), 71 arsenic exposed individuals were followed up as survey subjects. According to the "Diagnosis of Endemic Arsenism" (WS/T 211-2015), the clinical grading of skin injuries (skin keratinization, pigmentation abnormalities) in the survey subjects was evaluated. Urine samples were collected for detection of arsenic methylation metabolite levels by high-performance liquid chromatography inductively coupled plasma mass spectrometry and calibrated with urinary creatinine. The changes and amplitudes of urinary arsenic methylation indicators before and after water improvement were calculated and analyzed according to the outcome of skin keratinization and pigmentation abnormalities which were divided into reduced, unchanged, and added groups.Results:(1) The changes in urinary total arsenic (TAs), inorganic arsenic (iAs), monomethyl arsenic (MMA), and dimethyl arsenic (DMA) levels in different outcome groups of skin keratinization were compared, and the differences were statistically significant ( H = 9.08, 8.77, 9.28, 8.57, P < 0.05). The changes in urinary TAs, iAs, MMA, DMA levels, iAs percentage (iAs%), DMA percentage (DMA%), and primary methylation index (PMI) in different outcome groups of skin pigmentation abnormalities were compared, and the differences were statistically significant ( H = 8.04, 10.67, 8.29, 9.14, 6.30, 9.10, 7.20, P < 0.05). (2) The comparison of amplitudes in urinary TAs, iAs, MMA, and DMA levels in different outcome groups of skin keratinization showed statistically significant differences ( H = 6.92, 7.34, 6.66, 6.16, P < 0.05). The amplitudes in urinary iAs level, iAs%, DMA%, and PMI in different outcome groups of skin pigmentation abnormalities were compared, and the differences were statistically significant ( H = 7.94, 7.61, 9.95, 7.22, P < 0.05). Conclusion:The changes pattern of urinary TAs, iAs, MMA, DMA, iAs%, DMA%, and PMI in population exposed to arsenic through drinking water is related to the transformation of skin keratinization and pigmentation abnormalities.

Objective:To study the relationship between the levels of multiple elements in urine and the risk of arsenic poisoning in populations exposed to drinking water arsenic in Inner Mongolia Autonomous Region (Inner Mongolia).Methods:From April 2023 to January 2024, a case-control study method was used to select 128 individuals with a residence time of ≥10 years in drinking water arsenic exposed areas in Inner Mongolia as study subjects. Eighty-one individuals diagnosed with arsenic poisoning were selected as the case group, and 47 healthy individuals were selected as the control group for urine sample collection and questionnaire survey. Inductively coupled plasma mass spectrometry was employed to determine the levels of 10 elements (chromium, manganese, cobalt, nickel, copper, zinc, arsenic, molybdenum, cadmium and lead) in urine. The levels of each element in urine were divided into four groups ( Q1, Q2, Q3, and Q4 groups) based on quartiles. The associations between the levels of various elements in urine and the risk of arsenic poisoning were studied using binary logistic regression model and restricted cubic spline (RCS). Results:The age of the control group and the case group [ M ( Q1, Q3)] were 61 (53, 69) and 61 (56, 67) years old, respectively. There were 19 and 43 males, and 28 and 38 females, respectively. There was no statistically significant differences in age and and gender composition between the two groups ( Z = - 0.39, P = 0.700; χ 2 = 1.91, P = 0.167). The levels of urinary copper and cadmium of the case group were higher than those of the control group, and the differences were statistically significant ( Z = - 2.66, - 2.16, P < 0.05). The results of univariate logistic regression analysis showed that urinary copper was an influencing factor for arsenic poisoning ( P = 0.017). The results of multivariate logistic regression analysis revealed that after adjusting for covariates, urinary copper and arsenic were independent influencing factors of arsenic poisoning ( P < 0.05). Taking Q1 group as a reference, urinary copper in Q3 group [ OR (95% CI) = 8.23 (1.81, 37.39), P = 0.006] increased the risk of arsenic poisoning, while urinary arsenic in Q2, Q3, and Q4 groups [ OR (95% CI) = 0.24 (0.06, 0.92), 0.12 (0.03, 0.53), 0.15 (0.04, 0.63), P < 0.05] decreased the risk of arsenic poisoning. After adjusting for covariates, RCS did not show a dose-response relationship between urinary copper, urinary arsenic, and arsenic poisoning ( P > 0.05). Conclusion:Urinary arsenic and copper are associated with the risk of arsenic poisoning in the drinking water arsenic exposed areas of Inner Mongolia, copper exposure may contribute significantly to arsenic poisoning.

Objective:To analyze the influence factors behind the effective prevention and control of Kashin-Beck disease (KBD) in Tibet Autonomous Region (Tibet).Methods:Based on the data of KBD in Tibet in 2010 and 2015 provided by the Tibet Center for Disease Control and Prevention, the contribution of different prevention and control measures for KBD in Tibet was analyzed from the natural environment and socio-economic aspects (including vegetation coverage, economic level, industrial structure, dietary nutrition, planting structure, land use, aid to Tibet policy and medical care) by using the method of optimal parameters-based geographical detector.Results:There were differences in the explanatory power of various influencing factors on the prevention and control effect of KBD in different periods. In 2010, the proportion of forest area and per capita food consumption of farmers and herdsmen were the dominant factors ( q = 0.482, 0.366, P < 0.05). In 2015, the normalized vegetation index, the proportion of sown area of grain and oil crops, and the proportion of forest area were dominant ( q = 0.378, 0.334, 0.323, P < 0.05). The interaction between various influencing factors was stronger than that of single factor. In 2010, the explanatory power of the interaction between the proportion of forest area and grassland area was the highest ( q = 0.737), followed by the interaction between the proportion of agricultural and animal husbandry output value and the proportion of forest area ( q = 0.688). In 2015, the explanatory power of the interaction between per capita disposable income of farmers and herdsmen and the proportion of agricultural and animal husbandry output value was the highest ( q = 0.844), followed by the interaction between per capita disposable income of farmers and herdsmen and the proportion of arable land area ( q = 0.808). Conclusion:The key to the prevention and control of KBD in Tibet is to improve the economic level, improve the dietary nutrition of residents, adjust the structure of agriculture and animal husbandry and agricultural planting, and change the land use mode.

Objective:To analyze the influence factors behind the effective prevention and control of Kashin-Beck disease (KBD) in Tibet Autonomous Region (Tibet).Methods:Based on the data of KBD in Tibet in 2010 and 2015 provided by the Tibet Center for Disease Control and Prevention, the contribution of different prevention and control measures for KBD in Tibet was analyzed from the natural environment and socio-economic aspects (including vegetation coverage, economic level, industrial structure, dietary nutrition, planting structure, land use, aid to Tibet policy and medical care) by using the method of optimal parameters-based geographical detector.Results:There were differences in the explanatory power of various influencing factors on the prevention and control effect of KBD in different periods. In 2010, the proportion of forest area and per capita food consumption of farmers and herdsmen were the dominant factors ( q = 0.482, 0.366, P < 0.05). In 2015, the normalized vegetation index, the proportion of sown area of grain and oil crops, and the proportion of forest area were dominant ( q = 0.378, 0.334, 0.323, P < 0.05). The interaction between various influencing factors was stronger than that of single factor. In 2010, the explanatory power of the interaction between the proportion of forest area and grassland area was the highest ( q = 0.737), followed by the interaction between the proportion of agricultural and animal husbandry output value and the proportion of forest area ( q = 0.688). In 2015, the explanatory power of the interaction between per capita disposable income of farmers and herdsmen and the proportion of agricultural and animal husbandry output value was the highest ( q = 0.844), followed by the interaction between per capita disposable income of farmers and herdsmen and the proportion of arable land area ( q = 0.808). Conclusion:The key to the prevention and control of KBD in Tibet is to improve the economic level, improve the dietary nutrition of residents, adjust the structure of agriculture and animal husbandry and agricultural planting, and change the land use mode.

Objective:To study the relationship between urinary arsenic methylation metabolism patterns and skin keratinization and pigmentation abnormalities in population exposed to arsenic through drinking water.Methods:Using a cross-sectional study method, a survey on endemic arsenic poisoning was conducted among permanent residents of drinking water endemic arsenic poisoning areas in Bayannur City, Inner Mongolia Autonomous Region in 2004 (before water improvement). In 2017 (after water improvement), 71 arsenic exposed individuals were followed up as survey subjects. According to the "Diagnosis of Endemic Arsenism" (WS/T 211-2015), the clinical grading of skin injuries (skin keratinization, pigmentation abnormalities) in the survey subjects was evaluated. Urine samples were collected for detection of arsenic methylation metabolite levels by high-performance liquid chromatography inductively coupled plasma mass spectrometry and calibrated with urinary creatinine. The changes and amplitudes of urinary arsenic methylation indicators before and after water improvement were calculated and analyzed according to the outcome of skin keratinization and pigmentation abnormalities which were divided into reduced, unchanged, and added groups.Results:(1) The changes in urinary total arsenic (TAs), inorganic arsenic (iAs), monomethyl arsenic (MMA), and dimethyl arsenic (DMA) levels in different outcome groups of skin keratinization were compared, and the differences were statistically significant ( H = 9.08, 8.77, 9.28, 8.57, P < 0.05). The changes in urinary TAs, iAs, MMA, DMA levels, iAs percentage (iAs%), DMA percentage (DMA%), and primary methylation index (PMI) in different outcome groups of skin pigmentation abnormalities were compared, and the differences were statistically significant ( H = 8.04, 10.67, 8.29, 9.14, 6.30, 9.10, 7.20, P < 0.05). (2) The comparison of amplitudes in urinary TAs, iAs, MMA, and DMA levels in different outcome groups of skin keratinization showed statistically significant differences ( H = 6.92, 7.34, 6.66, 6.16, P < 0.05). The amplitudes in urinary iAs level, iAs%, DMA%, and PMI in different outcome groups of skin pigmentation abnormalities were compared, and the differences were statistically significant ( H = 7.94, 7.61, 9.95, 7.22, P < 0.05). Conclusion:The changes pattern of urinary TAs, iAs, MMA, DMA, iAs%, DMA%, and PMI in population exposed to arsenic through drinking water is related to the transformation of skin keratinization and pigmentation abnormalities.

Objective:To study the relationship between the levels of multiple elements in urine and the risk of arsenic poisoning in populations exposed to drinking water arsenic in Inner Mongolia Autonomous Region (Inner Mongolia).Methods:From April 2023 to January 2024, a case-control study method was used to select 128 individuals with a residence time of ≥10 years in drinking water arsenic exposed areas in Inner Mongolia as study subjects. Eighty-one individuals diagnosed with arsenic poisoning were selected as the case group, and 47 healthy individuals were selected as the control group for urine sample collection and questionnaire survey. Inductively coupled plasma mass spectrometry was employed to determine the levels of 10 elements (chromium, manganese, cobalt, nickel, copper, zinc, arsenic, molybdenum, cadmium and lead) in urine. The levels of each element in urine were divided into four groups ( Q1, Q2, Q3, and Q4 groups) based on quartiles. The associations between the levels of various elements in urine and the risk of arsenic poisoning were studied using binary logistic regression model and restricted cubic spline (RCS). Results:The age of the control group and the case group [ M ( Q1, Q3)] were 61 (53, 69) and 61 (56, 67) years old, respectively. There were 19 and 43 males, and 28 and 38 females, respectively. There was no statistically significant differences in age and and gender composition between the two groups ( Z = - 0.39, P = 0.700; χ 2 = 1.91, P = 0.167). The levels of urinary copper and cadmium of the case group were higher than those of the control group, and the differences were statistically significant ( Z = - 2.66, - 2.16, P < 0.05). The results of univariate logistic regression analysis showed that urinary copper was an influencing factor for arsenic poisoning ( P = 0.017). The results of multivariate logistic regression analysis revealed that after adjusting for covariates, urinary copper and arsenic were independent influencing factors of arsenic poisoning ( P < 0.05). Taking Q1 group as a reference, urinary copper in Q3 group [ OR (95% CI) = 8.23 (1.81, 37.39), P = 0.006] increased the risk of arsenic poisoning, while urinary arsenic in Q2, Q3, and Q4 groups [ OR (95% CI) = 0.24 (0.06, 0.92), 0.12 (0.03, 0.53), 0.15 (0.04, 0.63), P < 0.05] decreased the risk of arsenic poisoning. After adjusting for covariates, RCS did not show a dose-response relationship between urinary copper, urinary arsenic, and arsenic poisoning ( P > 0.05). Conclusion:Urinary arsenic and copper are associated with the risk of arsenic poisoning in the drinking water arsenic exposed areas of Inner Mongolia, copper exposure may contribute significantly to arsenic poisoning.

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.

Objective:To investigate the relationship between the outcome of skin injury and urinary arsenic methylation metabolism levels in people exposed to arsenic through drinking water.Methods:Using cluster sampling method, permanent residents from drinking-water-borne endemic arsenic poisoning areas in Bayannur City, Inner Mongolia Autonomous Region were selected as survey subjects in 2004 (before water improvement). In 2017 (after water improvement), 74 survey subjects from 2004 were tracked and followed up. Urine samples were collected from survey subjects and high-performance liquid chromatography inductively coupled plasma mass spectrometry was used to detect the levels of arsenic methylation metabolites in urine. According to the "Diagnosis of Endemic Arsenic Poisoning" (WS/T 211-2015), the clinical grading (normal, suspicious, mild, moderate and severe) of skin injury of the survey subjects and the outcome of 2017 (improved, unchanged, aggravated) were assessed. A database was established and SPSS 25.0 software was used for statistical analysis.Results:The clinical grading ratios of skin injuries among survey subjects in 2004 and 2017 were compared, the differences were statistically significant (normal, suspicious, mild, moderate and severe: 38, 18, 4, 14 cases in 2004 and 27, 31, 3, 13 cases in 2017, χ 2 = 53.02, P < 0.001). Compared with 2004, in 2017, the levels of total arsenic (tAs), inorganic arsenic (iAs), monomethylarsenic (MMA), dimethylarsenic (DMA), percentage of inorganic arsenic (iAs%), and ratio of monomethylarsenic to dimethylarsenic (MMA/DMA) in the urine of survey subjects were low, and the differences were statistically significant ( Z = - 8.24, - 9.07, - 7.81, - 8.04, - 8.24, - 3.56, P < 0.001). The levels of dimethylarsenic percentage (DMA%), monomethylation rate (PMI) and dimethylation rate (SMI) were higher, and the differences were statistically significant ( Z = - 6.39, - 8.24, - 3.52, P < 0.001). In 2004, patients with different clinical grading of skin injuries had different outcomes in 2017 (χ 2 = 30.80, P < 0.001). There were statistically significant differences in tAs, iAs, MMA and DMA variation in urine among skin injury patients with different outcomes ( H = 10.62, 9.35, 8.80, 9.13, P < 0.05). Conclusions:Improving water can significantly reduce the levels of tAs, iAs, MMA, and DMA in the urine of arsenic exposed individuals. The outcome of skin injury in individuals exposed to arsenic through drinking water is related to the variation of urinary arsenic methylation metabolites tAs, iAs, MMA, and DMA.

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 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.