Investigation on spatial variability and influencing factors of drinking water iodine in Xinjiang, China.
<h4>Background and objectives</h4>Xinjiang is one of the areas in China with extremely severe iodine deficiency. The health of Xinjiang residents has been endangered for a long time. In order to provide reasonable suggestions for scientific iodine supplementation and improve the health a...
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Public Library of Science (PLoS)
2021-01-01
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| Online Access: | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0261015&type=printable |
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| author | Zhen Yang Chenchen Wang Yanwu Nie Yahong Sun Maozai Tian Yuhua Ma Yuxia Zhang Yimu Yuan Liping Zhang |
| author_facet | Zhen Yang Chenchen Wang Yanwu Nie Yahong Sun Maozai Tian Yuhua Ma Yuxia Zhang Yimu Yuan Liping Zhang |
| author_sort | Zhen Yang |
| collection | DOAJ |
| description | <h4>Background and objectives</h4>Xinjiang is one of the areas in China with extremely severe iodine deficiency. The health of Xinjiang residents has been endangered for a long time. In order to provide reasonable suggestions for scientific iodine supplementation and improve the health and living standards of the people in Xinjiang, it is necessary to understand the spatial distribution of iodine content in drinking water and explore the influencing factors of spatial heterogeneity of water iodine content distribution.<h4>Methods</h4>The data of iodine in drinking water arrived from the annual water iodine survey in Xinjiang in 2017. The distribution of iodine content in drinking water in Xinjiang is described from three perspectives: sampling points, districts/counties, and townships/streets. ArcGIS was used for spatial auto-correlation analysis, mapping the distribution of iodine content in drinking water and visualizing the distribution of Geographically Weighted Regression (GWR) model parameter. Kriging method is used to predict the iodine content in water at non-sampling points. GWR software was used to build GWR model in order to find the factors affecting the distribution of iodine content in drinking water.<h4>Results</h4>There are 3293 sampling points in Xinjiang. The iodine content of drinking water ranges from 0 to 128 μg/L, the median is 4.15 μg/L. The iodine content in 78.6% of total sampling points are less than 10 μg/L, and only that in the 3.4% are more than 40 μg/L. Among 1054 towns' water samples in Xinjiang, 88.9% of the samples' water iodine content is less than 10 μg/L. Among the 94 studied areas, the median iodine content in drinking water in 87 areas was less than 10 μg/L, those values in 7 areas were between 10-40 μg/L, and the distribution of water iodine content in Xinjiang shows clustered. The GWR model established had found that the effects of soil type and precipitation on the distribution of iodine content in drinking water were statistically significant.<h4>Conclusions</h4>The iodine content of drinking water in Xinjiang is generally low, but there are also some areas which their drinking water has high iodine content. Soil type and precipitation are the factors affecting the distribution of drinking water iodine content, and are statistically significant (P<0.05). |
| format | Article |
| id | doaj-art-dc7ba2127aad432fa2bbb4d822131600 |
| institution | DOAJ |
| issn | 1932-6203 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj-art-dc7ba2127aad432fa2bbb4d8221316002025-08-20T03:15:44ZengPublic Library of Science (PLoS)PLoS ONE1932-62032021-01-011612e026101510.1371/journal.pone.0261015Investigation on spatial variability and influencing factors of drinking water iodine in Xinjiang, China.Zhen YangChenchen WangYanwu NieYahong SunMaozai TianYuhua MaYuxia ZhangYimu YuanLiping Zhang<h4>Background and objectives</h4>Xinjiang is one of the areas in China with extremely severe iodine deficiency. The health of Xinjiang residents has been endangered for a long time. In order to provide reasonable suggestions for scientific iodine supplementation and improve the health and living standards of the people in Xinjiang, it is necessary to understand the spatial distribution of iodine content in drinking water and explore the influencing factors of spatial heterogeneity of water iodine content distribution.<h4>Methods</h4>The data of iodine in drinking water arrived from the annual water iodine survey in Xinjiang in 2017. The distribution of iodine content in drinking water in Xinjiang is described from three perspectives: sampling points, districts/counties, and townships/streets. ArcGIS was used for spatial auto-correlation analysis, mapping the distribution of iodine content in drinking water and visualizing the distribution of Geographically Weighted Regression (GWR) model parameter. Kriging method is used to predict the iodine content in water at non-sampling points. GWR software was used to build GWR model in order to find the factors affecting the distribution of iodine content in drinking water.<h4>Results</h4>There are 3293 sampling points in Xinjiang. The iodine content of drinking water ranges from 0 to 128 μg/L, the median is 4.15 μg/L. The iodine content in 78.6% of total sampling points are less than 10 μg/L, and only that in the 3.4% are more than 40 μg/L. Among 1054 towns' water samples in Xinjiang, 88.9% of the samples' water iodine content is less than 10 μg/L. Among the 94 studied areas, the median iodine content in drinking water in 87 areas was less than 10 μg/L, those values in 7 areas were between 10-40 μg/L, and the distribution of water iodine content in Xinjiang shows clustered. The GWR model established had found that the effects of soil type and precipitation on the distribution of iodine content in drinking water were statistically significant.<h4>Conclusions</h4>The iodine content of drinking water in Xinjiang is generally low, but there are also some areas which their drinking water has high iodine content. Soil type and precipitation are the factors affecting the distribution of drinking water iodine content, and are statistically significant (P<0.05).https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0261015&type=printable |
| spellingShingle | Zhen Yang Chenchen Wang Yanwu Nie Yahong Sun Maozai Tian Yuhua Ma Yuxia Zhang Yimu Yuan Liping Zhang Investigation on spatial variability and influencing factors of drinking water iodine in Xinjiang, China. PLoS ONE |
| title | Investigation on spatial variability and influencing factors of drinking water iodine in Xinjiang, China. |
| title_full | Investigation on spatial variability and influencing factors of drinking water iodine in Xinjiang, China. |
| title_fullStr | Investigation on spatial variability and influencing factors of drinking water iodine in Xinjiang, China. |
| title_full_unstemmed | Investigation on spatial variability and influencing factors of drinking water iodine in Xinjiang, China. |
| title_short | Investigation on spatial variability and influencing factors of drinking water iodine in Xinjiang, China. |
| title_sort | investigation on spatial variability and influencing factors of drinking water iodine in xinjiang china |
| url | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0261015&type=printable |
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